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THE UCLA ANDERSON FORECAST
FOR THE NATION AND CALIFORNIA
December 2011 Report
FORECASTS:
2011 4th Quarter
2013 4th Quarter
60th Year
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Copyright 2011 by the Regents of the University of California.
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THE UCLA ANDERSON FORECAST
FOR THE NATION AND CALIFORNIA
December 2011 Report
Nation California
The Long Slump 11 California: Recovery Part Deux? 79
David Shulman Jerry Nickelsburg
Understanding the Risks to 19 Charts 89
China's Economy Recent Evidence
William Yu
Charts 94
Charts 45 Forecast
Recent Evidence
Tables 101
Charts 53 Summary
Forecast
Tables 105
Tables 61 Detailed
Summary
Tables 67
Detailed
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THE UCLA ANDERSON FORECAST
FOR THE NATION
December 2011 Report
The Long Slump
Understanding the Risks to China's Economy
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The Long Slump
The Long Slump
David Shulman
Senior Economist
UCLA Anderson Forecast
December 2011
“But for a lot of people, I know it doesn’t feel like the recession ever ended. The unemployment rate remains
painfully high, and more than two-fifths of the unemployed have been out of work for longer than six months,
by far the highest ratio since World War II.”1
Ben S. Bernanke
Let’s face it, despite a modestly growing GDP, Figure 1 Unemployment Rate, 2005Q1-2013Q4F
the labor market remains mired in a long slump. Next
year will mark the fourth year in a row with an unem- (Percent)
ployment rate exceeding 9%, the worst performance 10%
of the postwar era. (See Figure 1) Indeed, the broader
U-6 series, which takes into account part-time work- 9%
ers seeking full time employment and discouraged
workers, has consistently been above 16%. Put sim- 8%
ply, there are currently 25 million Americans look-
7%
ing for full-time work. Moreover the employment-
population ratio remains below the level reached
6%
at the official bottom of the recession in 2009. (See
Figure 2) Unfortunately, although we are forecast- 5%
ing modest job growth on the order of 150,000 jobs
a month, total payroll employment will still be about 4%
three million jobs below the late 2007 peak. (See 2005 2006 2007 2008 2009 2010 2011 2012 2013
Figure 3) Given the decidedly weak labor market, it
is not a coincidence that real personal income is still
Source: Bureau of Labor Statistics and UCLA Anderson Forecast
below the level reached in 2008. (See Figure 4)
UCLA Anderson Forecast, December 2011 Nation–11
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The Long Slump
Figure 2 Employment/Population Ratio, 1948 – October 2011, Monthly Data
Source: Federal Reserve Bank of St. Louis
Figure 3 Payroll Employment 2005Q1-2013Q4F Although recent data has improved and the no-
tion of a double-dip recession now appears to be off
(Millions, SAAR) the table, we continue to forecast real GDP growth at
138 a below trend rate over the next five quarters. Spe-
cifically we are forecasting a 2% growth rate for the
136 current quarter and a sub-2% growth rate for most of
2012. (See Figure 5) However, for 2013 we envision
growth to exceed 3% as several of the contractionary
134
forces discussed below abate.
132
Policy in a Trap: The Ghost of David Ricardo
130 Pimco’s Bill Gross asked the following question
in his latest missive to investors, “Can you solve a
128
debt crisis with more debt?”2 The answer is usu-
2005 2006 2007 2008 2009 2010 2011 2012 2013 ally you can, except when sovereign debt in excess
of 80-90% of GDP becomes a barrier to growth.3 In
that case, the concept of Ricardian Equivalence may
Source: Bureau of Labor Statistics and UCLA Anderson Forecast
come into play.4 David Ricardo, the great early 19th
12–Nation UCLA Anderson Forecast, December 2011
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The Long Slump
Figure 4 Real Personal Income, 2000 – September 2011, In $Billions, Monthly Data
Sources: Federal Reserve Bank of St. Louis
Figure 5 Real GDP Growth, 2005Q1 – 2013Q4 century English political economist offered up the
theory that the issuance of government debt is essen-
(Percent Change, SAAR)
tially equivalent to a promise to increase taxation in
6%
the future. Realizing that, taxpayers save more today
4% to meet their projected tax obligations. When debt
2%
is low, taxpayers do not worry about the prospect of
future taxation because they rightly believe that it will
0% remain outstanding forever and hence never be paid
- 2%
off. As a historical matter, most folks have not had
kitchen table conversations about how high deficits
- 4% will increase their taxes in the future.
- 6%
However, when debt is high, there is a very
- 8%
real prospect that it will have to be paid off in the
- 10% future and the funds to make the required pay-
2005 2006 2007 2008 2009 2010 2011 2012 2013
ments will come from increased taxation and re-
duced government spending. All of a sudden, the
Source: U.S. Department of Commerce and UCLA Anderson Forecast deficit becomes real! (E.g. Greece) A similar process
UCLA Anderson Forecast, December 2011 Nation–13
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The Long Slump
occurs in corporate finance where a modest increase a result of the high-deficit fiscal policy of the past
in leverage will actually lower the cost of capital. decade and the projection of mega-deficits as far as
However, once leverage is deemed to be excessive by the eye can see, Super Committee or not. (See Figure
the financial markets, the cost of capital skyrockets. 6) In fact, the high deficits will occur against a back-
drop of declining real federal purchases, but rapidly
Closer to home, the Obama Administration’s increasing transfer (entitlement) payments.
proposals to stimulate the economy with social
security tax cuts and infrastructure spending today Similarly, the Fed has been following a full
to be financed by tax increases in the future is an throttle expansionary monetary policy since 2008.
example of Ricardian Equivalence. In this case, the The Federal Funds rate has been set at zero since
government is explicitly promising taxpayers that early 2009 and will remain there through 2013. (See
their taxes will go up in the future; no guesswork is Figure 7) With the policy rate set at zero the Fed has
required. For the American consumer already reeling engaged in two massive quantitative easing programs
from home and stock price declines, the prospect of and recently put in place an “operation twist” to lower
future tax increases would weigh on current spending. long-term interest rates.
Similarly, the Ricardian result holds true, to a lesser
extent, with financing the stimulus with future cuts in Another quantitative easing program looms on
long-term reductions in entitlement programs. the horizon. However, it remains to be seen whether
further policy measures will stimulate the economy.
Thus, it is unlikely the economy would receive To be sure the earlier policies likely put a floor under
the stimulative effects of the fiscal policy that nor- the 2007-09 recession and planted the seeds for
mally would be predicted by the standard economet- recovery; it is not clear whether or not the policy has
ric models. In other words, fiscal policy as we have been all that efficacious of late. Remember the imple-
known has come to a dead end. This eventuality is mentation of the second round of quantitative easing
Figure 6 Federal Surplus/Deficit, Figure 7 Federal Funds vs. 10 Year U.S. Treasury
FY 2000 – FY 2021F Yields, 2005Q1- 2013Q4F
(Annual Data, Billions $) (Rates)
$500 6%
5%
$0
4%
$ - 500
3%
2%
$ - 1000
1%
0%
$ - 1500
-1%
2005 2006 2007 2008 2009 2010 2011 2012 2013
$ - 2000 Fed Funds 10-Yr. T -bonds
2001 2005 2009 2013 2017 2021
Sources: Office of Management and Budget and UCLA Anderson Forecast Sources: Federal Reserve Board and UCLA Anderson Forecast
14–Nation UCLA Anderson Forecast, December 2011
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The Long Slump
in September 2010 triggered inflationary fears with With that, U.S exports to the Euro region will
a run-up in commodity prices that worked to depress slow and similarly for Asian and Latin American
consumer spending. It appears that the Fed might be exports thereby depressing activity world-wide. Thus,
pushing on a string, the bane of monetary policy. the global economy will grow more slowly in 2012
than 2011. And this assumes that we avoid a full
Another factor inhibiting monetary policy is the blown banking crisis in Europe that could bring with
notion that very low interest rates can be contraction- it a world-wide restriction in credit analogous to the
ary. I know this goes against the grain of Keynesian Lehman Brothers collapse of 2008.
theory, but there may be a new kind of paradox
of thrift at work. A year ago we wrote about the Therefore, it is not an accident that most of the
phenomenon of how low interest rates actually can world’s stock markets have suffered declines this
encourage savings and reduce consumption.5 How year. In fact, even with the August and November
so? With very low interest rates, pension plans require swoons in U.S. share prices, the U.S. stock market
increased contributions to meet their actuarial ob- has held up far better than its counterparts around the
ligations. The same principle holds true for defined world. For example, as of late-November, the U.S.
contribution plans where a target level of savings has market was down 8% year-to-date, while Germany
to be reached in order to fund the desired amount of was down 21%, France down 25%, Japan down 20%,
retirement income. Because the retirement planning China down 16%, and Brazil down 21%. (See Figure
for most Americans never contemplated a 2% 10-Year 8)
U.S. Treasury bond, the average American facing re-
tirement over the next 10-15 years is between a rock
Figure 8 Global Stock Market Performance,
and a hard place. Indeed, for those already retired,
2011 through Nov. 25
low interest rates act as a depressant on consumption.
Thus, while low interest rates work to stimulate
purchases of homes, consumer durables and busi-
-8%
ness equipment, there is a very real drag coming
-15%
from reduced everyday consumption for current and
prospective retirees. Because we are in a whole new
world with respect to interest rates, it is still too early -21%
to tell how powerful in suppressing demand the new -25%
paradox of thrift is. -31%
-13%
The Crisis in Europe
-16%
The economic situation in Europe continues -20%
to deteriorate with the Eurozone placing its mem- -24%
ber countries in straight jacket similar to the gold South Korea -13%
standard rules of a century ago. Without the ability
to devalue their respective currencies, the troubled
countries of Portugal, Italy, Ireland, Greece, Spain -10%
-21%
and perhaps France are forced to deflate their domes-
tic economies. Austerity is the rule of the day and it is
Sources: The Wall Street journal
likely that the continent will be in recession next year.
UCLA Anderson Forecast, December 2011 Nation–15
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The Long Slump
Figure 9 Real Exports, 2000 – 2013F, construction as the backlog of excess supply is eaten
Percent Change into. (See Figure 12)
(Percent Change, Annual Data) Although investment in equipment and software
15%
will continue to grow in 2013, it will come off of its
10% heady double-digit pace of the past two years. (See
Figure 13) We are forecasting growth of 6.7% and
5% 7.1% in 2012 and 2013, respectively. Nevertheless,
this sector will be growing three times faster than the
0% overall economy.
-5%
Of course as we have noted for many years, the
state and local sector is undergoing a fundamental
-10%
restructuring as real spending continues to decline.
-15% (See figure 14) Because of the prevalence of defined
2001 2003 2005 2007 2009 2011 2013 benefit plans, this sector is being especially harmed
by the very low interest rates we are experiencing.
Sources: U.S. Department of Commerce and UCLA Anderson Forecast
Last month, Rhode Island, under the weight of a huge
unfunded liability, radically reformed its pension
As a result, we forecast that after increasing plans that included cuts for existing beneficiaries.
11.3% in 2010 and an estimated 6.6% this year, we Put bluntly, the laws of arithmetic are overcoming
forecast that real exports will increase by only 3.4%
in 2012 and rebound to a healthy 7.7% in 2013.(See Figure 10 Real Consumer Spending,
Figure 9) The recently announced $40 billion airplane 2005Q1 – 2013Q4F
orders announced by Boeing certainly augers well for
export growth later in the decade. (Percent Change)
6%
The Domestic Economy
4%
Despite the scare coming from the recent de-
2%
cline in stock prices, consumer spending, especially
on automobiles is continuing to grow. (See Figures 0%
10 and 11) To be sure, the recent gains in consumer
spending might not be maintained, but, unlike the - 2%
sluggishness earlier in the year, it will remain a
source of modest strength. Moreover, automobile - 4%
sales are being buoyed by pure replacement demand
as the fleet is reaching the limits of aging. Further- - 6%
more, housing starts have bottomed and while this 2005 2006 2007 2008 2009 2010 2011 2012 2013
sector won’t be a major source of growth in 2012
Sources: U.S. Cepartment of Commerce and UCLA Anderson Forecast
we suspect that 2013 will bring with it a rebound in
16–Nation UCLA Anderson Forecast, December 2011
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The Long Slump
Figure 11 Automobile Sales, 2005Q1 – 2013Q4 Figure 13 Real Investment in Equipment and
Software, 2000 -2013F
(Millions, SAAR)
18 (Percent Change, Annual Data)
15%
16 10%
5%
14
0%
12 -5%
-10%
10
-15%
8
-20%
2001 2003 2005 2007 2009 2011 2013
2005 2006 2007 2008 2009 2010 2011 2012 2013
Sources: UCLA Anderson Forecast Sources: U.S. Department of Commerce and UCLA Anderson Forecast
Figure 12 Housing Starts, 2005Q1 – 2013Q4F, Figure 14 Real State and Local Government
in thousands, SAAR Spending, 2005 – 2013F, Percent Change
(Thousands, SAAR)
2500
(Percent Change, Annual Data)
2%
2000
1%
1500
0%
1000
-1%
500 -2%
0 -3%
2005 2006 2007 2008 2009 2010 2011 2012 2013 2005 2006 2007 2008 2009 2010 2011 2012 2013
Sources: U.S. Department of Commerce and UCLA Anderson Forecast Sources: U.S. Department of Commerce and UCLA Anderson Forecast
UCLA Anderson Forecast, December 2011 Nation–17
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The Long Slump
the laws of politics, even in the very unionized and to lower the unemployment rate much below 9%
very Democratic state of Rhode Island. through 2013. Furthermore, government policy seems
to be incapable of noticeably improving the situa-
Conclusion tion. Indeed the Federal government will be reducing
purchases during the forecast period. The economy
The United States is facing an unemployment will be sustained by modest increases in consumption
crisis in a slow growth economy. A modestly grow- and business investment along with the beginnings of
ing GDP on the order of 2% will not be sufficient a housing recovery in 2013.
Endnotes
1. Bernanke, Ben S., Remarks, At the Town Hall Meeting with Soldiers and Their Families, Fort Bliss, Texas, November 10, 2011, Board of
Governors of the Federal Reserve System.
2. Gross, William H., “Pennies from Heaven,” Pimco Investment Outlook, November 2011.
3. See Reinhart, Carmen M., and Kenneth S. Rogoff, “This Time is Different,” Princeton, Princeton University Press, 2009.
4. See Ricardo, David (1820), “Essay on the Funding System,” in “The Works of David Ricardo on the Life and Writings of the Author, J.R.
McColloch, London, John Murray, 1888. For the modern version of Ricardian Equivalence see, Barro, Robert J., “Are Government
Bonds Net Wealth,” Journal of Political Economy, 82:6, 1095-1117 and “On the Determination of the Public Debt,” Journal of Political
Economy, 87:5, 940-971.
5. See Shulman, David, “Risky Business,” UCLA Anderson Forecast, December 2010.
18–Nation UCLA Anderson Forecast, December 2011
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Understanding the Risks to China's Economy
Understanding the Risks to
China's Economy
William Yu
Economist
UCLA Anderson Forecast
December 2011
“It was the best of times, it was the worst of times, it was the age of wisdom, it was the age of foolishness, it was
the epoch of belief, it was the epoch of incredulity, it was the season of Light, it was the season of Darkness, it
was the spring of hope, it was the winter of despair,…”
Charles Dickens, A Tale of Two Cities, 18591
Over the past three decades, China has experi- with which a developed country strives to accurately
enced a period of persistent and remarkable economic collect and measure real-time economic variables, the
growth. However, recent evidence suggests that strain of this task for an emerging country with a rap-
China is likely to face an economic slowdown. The idly changing society and a population of 1.3 billion
question is: Will China’s economy encounter a soft is substantial. Second, before 1992 China’s GDP mea-
landing or a hard landing? In light of our research, surement was based on the Soviet material product
we suggest that both scenarios are equally likely. This system (MPS). In 1992, China officially adopted the
article will present our reasons for the likelihood of worldwide system of national accounts (SNA), yet it
a hard landing and will illustrate how the result of still does not fully follow the SNA standard. There-
China’s landing affects the U.S. economy. fore, inconsistencies are inherent in China’s data.
Our analysis begins with the ten risks facing Third, and most importantly, as an authoritarian
Chinese economic development and growth. It is regime controlled by the Chinese Communist Party,
important to note the interconnectivity of several of China intends—and is able—to adjust their data re-
these risks. leases so as to display government control in a favor-
able light. In addition to this skewing of data to the
government’s liking, as economic growth becomes
1. Data Risk the foremost political goal of the government, those
who achieve this end are rewarded politically. With-
It should not be surprising to find the quality
out an alternative way to climb up the political ladder,
and reliability of Chinese economic data challenged
e.g. by election, Chinese officials have an incentive
for three reasons. First, considering the difficulty
to boost economic performance, either in reality or by
UCLA Anderson Forecast, December 2011 Nation–19
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Understanding the Risks to China's Economy
paper, under their jurisdiction. This could potentially Table 1 The Mean and Standard Deviation of GDP
lead to compromised data. Growth Rates from 1980 to 2009 for the 25
Largest Economies
For instance, let’s look at the most important Standard Ratio of
economic data, real GDP growth, to decipher the Mean D eviation Mean/S.D.
possible moderation/manipulation of China’s eco- US 1.62 2.27 0.71
nomic data. Table 1 and Figure 1 show the mean and China 8.60 3.29 2.62
standard deviation (SD) of annual real GDP per capita Japan 1.61 2.27 0.71
growth rates adjusted for purchasing power parity Germany 1.44 1.80 0.80
from 1980 to 2009 for the current largest 25 econo- France 1.33 1.48 0.90
mies in the world.
UK 1.84 2.17 0.85
Brazil 0.77 3.62 0.21
The first column of Table 1 is the mean of real
Italy 1.28 2.05 0.63
GDP growths for these 25 countries. The highest
India 4.08 3.28 1.25
average growth rate is China’s at 8.6% per year over
Canada 1.46 2.20 0.67
the past 30 years, which reflects the breathtaking
Russia 1.47 6.67 0.22
economic growth and rising standard of living in
Spain 2.02 2.16 0.93
China. Number two is Korea’s 5.16% growth rate;
number three is Taiwan’s 4.88%; and number four is Australia 2.20 1.69 1.30
India’s 4.08%. The major developed country's aver- Mexico 1.03 4.66 0.22
age growth rates all lie between 1% and 2%. Korea 5.16 4.83 1.07
Netherlands 1.77 1.73 1.03
The second column of Table 1 presents the SD Turkey 2.05 4.28 0.48
of GDP growth, which represents the volatility of Indonesia 3.43 4.29 0.80
GDP growth for these countries. The larger the value, Switzerland 1.12 1.83 0.62
the more volatile the economy. The largest SD is Rus- Poland 2.02 4.98 0.40
sia’s 6.67%, indicative of the colossal collapse of the Belgium 1.71 1.96 0.88
Soviet Union in the 1990s. The third column of Table Sweden 1.59 2.23 0.71
1 is the ratio of GDP mean to SD. A high ratio implies Saudi Arabia 1.51 5.65 0.27
that either the economy’s mean growth is high or its Taiwan 4.88 3.51 1.39
volatility is low, or both. Therefore, a higher ratio Norway 2.37 1.92 1.24
is desirable because it suggests that the economy is
growing at a stable rate. In contrast, a lower ratio is Japan (1951 -79) 6.62 3.46 1.91
undesirable because it suggests that the economy is Taiwan (1960 -89) 6.92 3.10 2.23
either growing slowly or in an unsteady variation.
Korea (1960 -89) 5.99 4.17 1.44
Figure 1 illustrates the ratio of growth to volatil- Source: Penn World Table Version 7.0
ity with the SD along the x-axis and the mean growth
along the y-axis. The middle oval encircles the major-
ity of the countries. The ratios range from the U.S.’s ing Asian economies—India, Indonesia, Taiwan, and
0.71 to Taiwan’s 1.39. Developed countries with Korea—with higher growths and volatilities in the
lower growths and smaller volatilities are located in center. The bottom-right oval including Russia, Saudi
the bottom-left corner of the oval. We see four emerg- Arabia, Mexico, Brazil, Poland, and Turkey shows
20–Nation UCLA Anderson Forecast, December 2011
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Understanding the Risks to China's Economy
countries encountering higher volatilities but lower pan from 1951 to 1979 is 1.91; and Taiwan from 1960
growths. Therefore, they have a relatively smaller to 1989 is 2.33. Even so, China’s ratio is much higher.
ratio of mean to SD ranging from 0.21 to 0.48.
It is possible that the ratio reveals a reality of
China is located above and beyond all the other unprecedented economic growth in China. We believe
countries with a stunning ratio of 2.62. One might it is more likely that the GDP data has been modified
presume that China’s pro-growth and fine-tuning poli- in either of two ways: (1) GDP growths have been
cies do indeed contribute to the size of this number. overstated, or (2) the fluctuations of GDP growth
If history is any guide, we can go back to look at the have been smoothed out. If we use Taiwan’s 2.33
previous economic miracles of Asian economies: ratio as a more realistic indicator, Chinese GDP mean
Japan, Korea, and Taiwan. We see that these highly and S.D. combination should be either (8.6, 3.69) or
growing economies did experience higher mean to (7.67, 3.29) instead of the currently reported (8.6,
volatility ratios. Korea from 1960 to 1989 is 1.44; Ja- 3.29).
Figure 1 The Mean and Standard Deviation of GDP Growth Rates from 1980 to 2009
9
China,2.62
8
7
Japan, 1.91
Taiwan, 2.33
1951-79 Korea, 1.44
1960-89 1960-89
6
Korea, 1.07
GDP 5 Taiwan, 1.39
Growth
Mean
4
India, 1.25 Indonesia, 0.8
3
AUS, 1.3 Norway, 1.24
2 Poland , 0.4
Germany, 0.8 US, 0.71 Turkey, 0.48
Japan, 0.71
Saudi Arabia, 0.27 Russia, 0.22
1 France, 0.9 Brazil, 0.21
Mexico, 0.22
0
1 2 3 4 5 6 7
GDP Growth Standard Deviation (Volatility)
Source: Penn World Table Version 7.0
UCLA Anderson Forecast, December 2011 Nation–21
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Understanding the Risks to China's Economy
Maddison and Wu (2008)2 provide a detailed It is also worth noting that when our analysis
analysis of China’s GDP measuring problem. Figure uses China’s official data, the focus should be more
2 displays their estimates and those from the official on average levels than on short-term dynamics.
source, the National Bureau of Statistics of China Moreover, China eventually will have to pay the price
(NBS). They argue that China’s official GDP data for its resource misallocation based consistently on
between 1992 and 2003 has been overstated and misinformed data.
smoothed out; the official data has mean: 10.2 and
SD: 2.34 with mean/SD ratio: 4.36 compared to their
estimates of mean: 8.83, SD: 4.61, and ratio: 1.92.
2. Overinvestment Risk
In other words, they suggest that China’s real GDP
The most imminent risk China faces right now
growth rate was overstated by at least 1%. Their
is its overinvestment, including both private and
conclusion reconciles our suspicions as detailed in
public investment. Figure 3 presents the annual real
this report.
and nominal GDP growth rates of China. Figure 4
shows the percentage of nominal GDP components
Make no mistake, without government window
in China from 1980 to 2010 by the expenditure ap-
dressing, the record of China’s economic growth is
proach. It is clear to see that the percentage of invest-
still phenomenal. In terms of economic fluctuations,
ment over GDP, including private and public, was
it is ironic to see that governments and economists
over 40% from 1993 to 1995, hovered from 35% to
all over the world work hard to stabilize the business
39% between 1996 to 2002, and rose to over 40%
cycle while China can simply achieve it by this “data
again in 2003 and to 49% in 2010. If we calculate the
moderation.” However, in summary of this section,
contribution of investment growth to GDP growth,
one should be careful when interpreting not only GDP
the investment growth contributes 56% of China’s
but all Chinese economic data in which there might
GDP growth on average from 2001 to 2010 (private
be systematic biases given the unusual nature of insti-
consumption growth contributes 27%, government
tution in China.
consumption contributes 12%, and net export contrib-
utes 5%). Despite measurement bias and error in the
Figure 2 The Chinese GDP Growth Rates from data, the large and widening investment percentage of
Different Estimates GDP in China is unusual.
16
%
14 According to the Penn World Table 7, from
12
1950 to 2009 only a few dozen countries had a record
of investment to GDP ratio over 40% in addition to
10
China. Most of these countries are either former So-
8 viet Union allies, Middle East countries, or small and
6 poor African countries. Over the past two decades, we
4
do see more recognizable country names in this 40%
investment boom club: Singapore (1960 to 1997),
2
Thailand (1989 to1997), South Korea (1989 to 1997),
0 and Malaysia (1993 to 1997). All of these Asian in-
92 93 94 95 96 97 98 99 00 01 02 03
vestment booms ended in the Asian financial crisis of
China's Offical Number (Mean: 10.2, SD: 2.34, Mean/SD Ratio: 4.36)
Maddison and Wu's Estimate (Mean: 8.83, SD: 4.61, Mean/SD Ratio: 1.92)
1997. The more recent countries are Vietnam (2007-
2009) and the United Arab Emirates (2007-2009).
Sources: National Bureau of Statistics of China and Maddison and Wu The latter has suffered a serious real estate slump
(2008)
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in the past two years. The only western developed Next, let’s look at the annual real investment
country to have had a record of an over 40% invest- growth rates of China, Japan, and the U.S., the largest
ment ratio is Iceland in 2006, and we all know what three economies in the world, from 1980 to 2010.
happened to Iceland after 2006. (Figure 5) The bars represent China’s real invest-
ment growth. Since 2001, investment has grown
above 10% most of the time with an annual average
Figure 3 The Annual Nominal and Real GDP
Growth Rates of China of 14.1% from 2001 to 2010. Two investment booms
in the U.S.—(1) 1996 to 2000 with an average 8.5%
35
%
growth and (2) 2003 to 2006 with an average 4.9%—
30 are no comparison to China’s runaway investment
bubble. It is worth noting that Japan experienced a
25
similar investment craze from 1984 to 1990 with an
20 average annual growth rate of 8.5% followed by its
anemic “lost decade.” All these bubbles end up burst-
15
ing. Will China’s be different?
10
Isn’t investment beneficial to economic growth?
5
Yes, adequate investment is not only healthy but
0 also crucial to economic growth. However, persis-
1980 1985 1990 1995 2000 2005 2010 tent overinvestment will lead to failure in repaying
Real GDP Growth
Nominal GDP Growth
Figure 5 The Annual Real Investment Growth Rates
Source: National Bureau of Statistics of China of China, Japan, and the U.S.
%
Figure 4 Components of Nominal GDP of China 30
100 1 0 0 .0
1 0 0 .4
1 0 0 .0
9 9 .7
3
19080. . 0
2
19090. . 0
1 0 0 .0
1 0 0 .0
1 0 0 .0
1 0 4 .0
1 0 0 .0
1 0 2 .5
1 0 0 .0
9 9 .9
1 0 0 .0
1 0 0 .9
1 0 0 .0
1 0 1 .1 1 0 0 .0
9 7 .3
1 0 0 .0
9 7 .2
0
19090. . 0
1 0 0 .0
1 0 1 .8 19080. . 0
7 4
19080. . 0 19080. . 0
0 1 0 0 .0 1 0 0 .0 1 0 0 .0
9 7 .2
19070. . 0
5 19070. . 0
8 1 0 0 .0
9 7 .4
19070. . 0
8 1 0 0 .0
9 7 .5 1 0 0 .0 1 0 0 .0 1 0 0 .0 1 0 0 .0 1 0 0 .0 1 0 0 .0
9 5 .6 9 5 .8 9 5 .6 9 6 .0
9 4 .5
% 20
9 2 .5 9 2 .3
9 1 .2
8 9 .7
8 8 .0 8 8 .1
8 7 .5
8 6 .9
8 6 .2
8 5 .6 8 5 .2
8 5 .0 8 4 .8 8 5 .0 8 4 .6
8 3 .8 8 3 .7 8 3 .8 8 4 .0 8 3 .6
8 3 .2 8 2 .8
8 2 .3 8 2 .4
80
8 1 .9 8 2 .2 8 1 .8 8 1 .8
8 1 .5 8 1 .7
8 0 .4
7 8 .7 7 9 .0
7 7 .7
10
60
0
4 8 .6
4 7 .7
4 3 .9
4 3 .0
4 2 .5
40
4 1 .6 4 1 .8 4 1 .7
-10
4 0 .5 4 1 .0
4 0 .3
3 8 .8
3 8 .1 3 7 .8
3 7 .5
3 7 .0 3 6 .6 3 6 .6 3 6 .7
3 6 .3 3 6 .2 3 6 .2 3 6 .5
3 4 .8 3 4 .9 3 4 .9 3 5 .3
3 4 .2
3 2 .5 3 2 .8
3 1 .9
20 -20
1980 1985 1990 1995 2000 2005 2010
China US Japan
0
1980 1985 1990 1995 2000 2005 2010
Sources: National Bureau of Statistics of China; Economic and Social
Investment (Private & Gov't) Private Consumption
Government Consumption Net Export Research Institute of Japan; Bureau of Economic Analysis of the U.S.
Note: The investments are from both private and public (government) sec-
Sources: National Bureau of Statistics of China, CEIC Data for 2010 tors; shaded periods are U.S. recessions
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that which was borrowed and an eventual collapse investment is from SOEs. 64.4% of investment is for
because the return and marginal product of invest- structure while 20.4% is for purchasing equipment
ment will diminish as the investment and the capital- and instruments. Note that the nominal transportation
labor ratio increase. For example, from Figure 5 we infrastructure investment increased by a sharp 47% in
can see that China had an investment boom in the 2009 with a total of 2,498 billion yuan ($886 billion).
early 1990s, most of which was conducted by state- This reflects the colossal size of China’s stimulus into
owned enterprises (SOEs), resulting in an almost airports, highways, high-speed railroads, etc. amid the
0% return on assets for SOEs in 1998. The aver- global financial crisis.
age non-performing bank loan ratio was probably
around 30 – 50% in the late 1990s. This triggered the One might wonder how China could invest so
privatization/consolidations of SOEs and banking much for so long. Some controversial evidence, i.e.
restructures. Later the total number of SOEs declined Bai et al. (2006)3, shows that the exceptionally per-
from 300,000 to less than 100,000. And as shown by sistent and high investment return is the main driver;
Maddison and Wu (2008) in Figure 2, China had a therefore they conclude that China does not invest
significantly hard landing in 1998 in contrast to the too much. Knight and Ding (2011)4 provide three
soft landing portrayed by the official report. assumptions to explain Chinese exceptionalism. First,
the economic reform starting in 1978 began with an
Figure 6 exhibits the percentage of China’s exceptionally low level of capital, so there has been
total investment in fixed assets in September of 2011. much more room for China’s investment to grow
The biggest sector of investment is the manufactur- before reaching its steady state.
ing sector with 34% of total investment. The second
largest sector is real estate with 25%, and the third Second, two sources supply the abundant labor
largest sector is transportation with 9%. 34.6% of the that accommodates the rapid capital accumulations
and contain a relatively stable capital-labor ratio: (1)
since the dismantling of inefficient SOEs in the late
Figure 6 The Percentage of China’s Total 1990s, tremendous underemployed labor from former
Investment in Fixed Assets, SOEs were released into more productive private
September 2011 sectors; (2) the land reform of 1975 to 1985 drove a
massive relocation of rural peasants into urban indus-
trial sectors. Both sources have prevented China from
Others being subject to diminishing returns to capital in the
Mining 15%
past. Even if this hypothesis is true, we know that the
4%
Electricity, Gas windfall gain of labor supply from urbanization and
and Water
Facilities
Manufacturing sector restructure is not indefinitely sustainable.
34%
5%
Environment Third, central and local governments have been
and Public
Facilities subsidizing production factors such as capital, energy,
8% land, etc.; as well as repressing their costs below ap-
Transportation
9%
Real Estate
25%
propriate market prices. Huang (2011)5 calculated all
of these value distortions of factor markets, e.g. labor
market: 411 billion yuan, capital market: 607 billion
yuan, land market: 120 billion yuan, energy market:
Source: National Bureau of Statistics of China
204 billion yuan, and environment cost: 591 billion
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yuan for 2008. The total cost distortions sum up to growth and production: the Great Leap Forward from
2,138 billion yuan, or 7.2% of GDP. Distorted factor 1958 to 1961.
markets created incentives for massive investment for
accumulating physical capital.
3. Real Estate Bubble Risk
Knight and Ding (2011) provide another expla-
As mentioned in the previous section, next to
nation for the Chinese investment mania, in particular
manufacturing, real estate is the second largest com-
for SOEs. Similar to our argument of Chinese data
ponent of investment, accounting for 25.5% of the
moderation/manipulation, the main goal of SOEs is
total with 5.4 trillion yuan for the first three quarters
not profit maximization but investment and output
of 2011 at a nominal 32.6% growth rate compared to
maximization. The reward to managers in SOEs
the same period in 2010. Is this a property bubble?
takes the form of prestige, commanding power, and
the perks of managing SOEs, in which the larger the
According to Wu, Gyourko, and Deng (2011)6,
SOE, the greater the reward. Moreover, state-owned
real housing prices in Beijing, Chengdu, Hangzhou,
banks provide easier and cheaper credit to SOEs than
Shanghai, and Shenzhen have appreciated by at least
to small and medium-sized private enterprises. For
10% per year between 2003 and 2010, with Beijing’s
example, SOEs stand for one-third of the national
growth rate appreciating closer to 20%. The real
output but account for two-thirds of bank loans. The
housing prices in Tianjin, Wuhan and Xian have risen
misplaced incentive of SOEs has led to overinvesting
between 5.9% and 8.7% per year. The real housing
and SOE size expansion.
price index for newly-built private homes in 35 major
cities has risen 118% from 2003 to 2010, with an
Japan Déjà Vu? annual 9.7% compounded growth for eight years. To
get a better picture of how the Chinese property price
Looking back at Figures 3 and 5, China needs to appreciation compares to other real estate bubbles in
rethink its potential GDP growth rate. A GDP growth the past, let’s take a look at the following list:
rate above 10% is not sustainable. In the aftermath of
Japan’s burst bubble, Japanese scholars and officials • U.S.: According to the Case-Shiller Home Com-
pondered what went wrong in the 1980s. Their con- posite 10 city price index, the real housing price
fessions sum up in two points: (1) Japanese preferred in the U.S. rose 137% for nine consecutive years
high growth rather than low growth amid a stable from 1997 to 2005, with an average 9.6% com-
inflation environment. What is wrong with this? pounded growth annually. The housing bubble
There was no concern for a bubble economy then. began to burst in 2006. Since then, the real hous-
(2) Japanese cannot resist the temptation of a flood of ing price has declined 39%. The real housing
cheap money from lax lending policies. The distorted price is back to 2001’s level.
demand for investment is accommodated by the dis-
torted supply for investment: low costs of funds. We • Japan: According to the Japan Real Estate In-
will discuss this risk in the following section. stitute, the real residential housing price rapidly
increased 146% over a five-year period from
Currently, China is walking down the same 1985 to 1990, with an average 18% compounded
bubble path as Japan, but hopes for a better ending. appreciation per year during the bubble period.
The Chinese should know better than others after The bubble exploded in 1991. Since then the real
having experienced in its own history the catastrophic residential property price has declined 67% over
consequence of a blind and distorted pursuit of high 20 years.
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• Hong Kong: The average real private domestic raising real estate transaction taxes, introducing new
housing price7 in Hong Kong increased 156% for property taxes in some major cities, and increasing
seven years from 1990 to 1997, with an average mortgage rates.
13% compounded appreciation annually. The
bubble burst with the Asian financial crisis in This tightening policy has been effective. Hous-
1997. Since then, the real housing price declined ing sales and price appreciation have slowed down in
54% over the following 6 years. 2011. In recent months, the price has actually stag-
nated. Now, like many other countries have asked
If we can call these property price churn-ups in after their governments began popping the bubbles,
the U.S., Japan, and Hong Kong housing bubbles in the Chinese may wonder—Will the property market
hindsight, what has been happening in China’s real in China stabilize or will it collapse? We suggest that
estate market is not far away from a bubble. To access China is more likely to face a real estate hard landing
the housing affordability in China, the International than soft landing. Even if China can avoid a housing
Monetary Fund (IMF) computes the housing price- crash in the near future, this does not guarantee that
to-income ratio for various Chinese cities and other China’s economy will be off the hook. Neverthe-
countries. The higher the ratio, the less likely housing less, we will not see massive mortgage defaults and
is affordable. In 2010, at the whole-nation level the foreclosures occurring in China like we did in the
U.S. ratio was around 2.5 while China was near 5. At U.S. because Chinese homebuyers have much higher
the city level, Singapore was around 6.5, and Tokyo down payments and home equity to buffer the declin-
was about 9 while Hangzhou and Shanghai were ing housing price. The deleveraging crisis will come
about 13, and Beijing was near 20. The ratios show from other players in this bubble game: real estate
that the current high housing prices are not sustain- developers.
able in major Chinese cities.
4. Credit Risk
An asset bubble, by definition, will always
burst. The relevant question is how quickly it will One might wonder this: Where does the money
burst, and how deep and fast the price adjustment will to support China’s investment boom come from? We
be. Based on the history record, we find that, by and suggest that the money is from four separate chan-
large, the bigger the bubble, the deeper the crash will nels.
be in the aftermath. Nevertheless, whenever the asset
bubble is concerned, we hear the following counterar- 1) High Domestic Savings: China is a country with
gument: “No, this time is different. The ABC market a very high savings rate. In 2010, China’s gross
is different because of XYZ. Therefore, we should not domestic savings as a percentage of GDP was
worry about the bubble.” 52%, much higher than 11.5% in the U.S. and
20.8% in Japan. Three components of domestic
Despite some denial of the possibility of Chi- savings—government savings, enterprise savings
na’s property bubble, the Chinese government has (including SOEs) and household savings—have
imposed a number of policies in an attempt to con- all increased in the past decade. High savings in
tain the runaway housing prices all over the nation. the government and banks allow for the funding
Cooling measures include raising down payments of various public and private investments. High
for second homes (from 50% to 60%), increasing the household savings are accompanied with low
number of areas where home purchases are limited, household consumption. We will discuss why
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Chinese households are so frugal in the following sides of the PBC’s balance sheet are equal to
section. $207 billion, $208 billion, $249 billion, $466 bil-
lion, $420 billion, $487 billion, and $461 billion
2) Currency Intervention: To keep China’s ex- from 2004 to 2010, respectively.
ports competitive, China’s central bank (People’s
Bank of China, PBC) intervenes in the foreign To prevent this money supply and inflation explo-
currency market to keep the value of Chinese sion, the Chinese government issues government
currency—Renminbi or yuan—lower than the bonds to take money away from the market. This
foreign exchange market’s equilibrium price, in is called “sterilization.” Moreover, the PBC can
particular against the U.S. dollar. To achieve this press state-controlled banks to keep their extra
goal, the PBC prints yuan to buy into outstand- reserves in the PBC from lending out. But the
ing U.S. dollars gained from Chinese exporters or sterilization policy does not work in the long run.
from foreign investors (both from foreign direct We have seen that the increased money supply
investment and speculators’ hot money). Figure eventually fuels investment projects all over
7 displays the rapid accumulation of Chinese for- China and causes rising inflation, as experienced
eign reserves’ value in terms of the U.S. dollar. It in 2007 and 2008.
increases exponentially from $623 billion in 2004
to $2,914 billion in 2010 to $3,202 billion by the 3) Credit Boom: Figure 8 shows the growth rate of
end of the third quarter of 2011. domestic credit in China and other selected coun-
tries that have encountered overinvestment and
In other words, the PBC needs to issue the same bubble burst problems. The dashed lines in Figure
amount of yuan as the foreign reserve increment 8 represent the eruptions of either the financial
each year. These ballooned components on both crisis or bubble burst in these countries. Most
countries have elevated credit growth before the
crisis, e.g. Korea, Singapore, Hong Kong, Thai-
Figure 7 Foreign Exchange Reserve of China land, Malaysia, and in particular the UAE (over
$billion
40% growths from 2005 to 2008). Excepting
3500 Korea, all countries saw their credit growth slump
3000
in the aftermath of the bubble burst.
2500
On average, China had the highest credit growth
2000
among these countries with a 20% annual rate
1500 over the past three decades. Similar to the real
1000
investment cycle shown in Figure 5, China
experienced several credit spikes in four peri-
500
ods: (1) 1984-1986, (2) 1993, (3) 2002, and (4)
0
2009. The latest one in 2009 came in the midst
of the global financial crisis. To bolster a teeter-
Reserve Increase Foreign reserve
ing economy, China launched a stimulus program
Source: World Development Indicators that unleashed the massive state-controlled bank
reserves and expanded bank lending to local gov-
ernments and SOEs by more than 30%.
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Figure 8 Growth Rate of Net Domestic Credit for Various Countries
CHINA JAPAN US
50 50 50
(%)
40 40 40
30 30 30
20 20 20
10 10 10
0 0 0
-10 -10 -10
-20 -20 -20
1980 1985 1990 1995 2000 2005 2010 1980 1985 1990 1995 2000 2005 2010 1980 1985 1990 1995 2000 2005 2010
KOREA SINGAPORE HK
50 50 50
40 40 40
30 30 30
20 20 20
10 10 10
0 0 0
-10 -10 -10
-20 -20 -20
1980 1985 1990 1995 2000 2005 2010 1980 1985 1990 1995 2000 2005 2010 1980 1985 1990 1995 2000 2005 2010
THAILAND MALAYSIA UAE
50 50 50
40 40 40
30 30 30
20 20 20
10 10 10
0 0 0
-10 -10 -10
-20 -20 -20
1980 1985 1990 1995 2000 2005 2010 1980 1985 1990 1995 2000 2005 2010 1980 1985 1990 1995 2000 2005 2010
Source: World Development Indicators
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According to the PBC, total official outstand- lenders in the 1980s and American lenders in the
ing loans in China have increased 23 trillion 2000s -- hope the collateral will help recover their
yuan ($3.6 trillion) from 30 trillion yuan (97% losses if defaults happen. If defaults come with
of GDP) in the end of 2008 to 53 trillion yuan property price corrections, the lenders would bear
(124% of GDP) in the third quarter of 2011. Most more loss, which could further trigger a wide-
of the lending went to the construction binges of spread domestic panic and financial crisis.
China’s local government’s infrastructure and real
estate companies’ developments. China’s Na- 4) Local Land Sales Revenue: Land sales, often in
tional Audit Office reported that local government the form of farmlands owned by the state being
had amassed 10.7 trillion yuan ($1.65 trillion) turned over to real estate developers, are a major
of debt by the end of 2010, about 27% of GDP. source of funding for Chinese local government
The debt defaults are expected to range from an public infrastructure projects. With the occur-
optimistic 2.5 trillion yuan to a pessimistic 8 tril- rence of property price correction in major cities
lion yuan. and accumulating inventory, local governments
will find it harder and harder to sell new lands
Making matters worse, like the U.S.’s shadow to SOEs and other private developers. If the real
banking system, China has undergone an explo- estate market cannot recover, we will see two
sion of off-balance-sheet lending activities over problems on the horizon as a result.
the past two years in order to avoid government
scrutiny or to circumvent new regulations. These First, local cities will default on their debts to
informal lending activities—such as letters of state banks. Given the unified nature of China’s
credit, securitizing acceptance bills, entrusted political system, China’s central government will
loans, and trust loans, which are repackaged as then bail out the battered banks suffering from a
so-called wealth-management products—became spike of nonperforming loans. A decade ago, the
popular for wealthy individuals and cash-rich Beijing government transferred tens of billions of
institutions because of their more attractive yields dollars to help recapitalize state banks. Second,
than a normal deposit interest. local governments will have to cut back their
infrastructure investment spree, which could lead
UBS AG estimate that the size of China’s infor- to an investment slump. To postpone the outbreak
mal shadow banking stands at about 12 trillion of local government defaults, the central govern-
yuan (about 23% of formal lending). Fitch Rat- ment recently began allowing the local govern-
ings estimates that the total new financing for ments to issue bonds. It remains to be seen how
2011, consisting of official banking (45%) and this kick-the-can-down-the-road policy could
shadow banking with additional loans from Hong affect the timing of the default.
Kong banks (55%), will amount to 18 trillion
yuan. Credit is to a bubble economy what alcohol is
to a party gone wild. When the alcohol is gone,
In summary, China’s credit boom could explode the party is over. And what remains is nothing
like a time bomb at any moment if borrowers more than an unpleasant hangover. The end of the
fail to repay. Most of the collateral for loans is in credit boom is the end of the investment bubble.
real estate. Chinese lenders -- just like Japanese
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5. Inflation Risk Unfortunately, we must point out that this is another
example of China’s “data moderation.” Why? Like
An easy way to tell whether or not an economy other countries, China’s CPI tracks the general goods
is overheating is to look at the country’s inflation rate. and services of a typical Chinese consumer, including
Figure 9 exhibits the year-over-year monthly Con- food, residence, recreation, education, transporta-
sumer Price Index (CPI) inflation rate and food infla- tion, communication, healthcare, clothing, household
tion rate in China. From 1987 to date, we have seen facilities, etc.
four sharp rises of inflation in 1988, 1994, 2008, and
2011. These inflation peaks are highly-correlated with Unlike most other countries, however, the NBS
investment and credit growths as shown in Figures 5 does not publish the weights assigned to these CPI
and 8. This suggests that the inflation cycle is driven components. We cannot know how the headline CPI
mostly by the accelerating investment boom and esca- is calculated. It is well believed by the public in
lating money supply in China. China that the official number understates the true
change in cost of living. For instance, if we compare
Looking at Figure 9, it seems that China has the difference of food inflation and CPI inflation in
contained CPI inflation better over the past decade Figure 9, we find it hard to understand why the gap
than in the 1980s and the 1990s. According to the is so large. Food inflation is mostly twice as much as
most recent official report, the CPI inflation in Octo- CPI inflation. The only explanation is that the weight
ber 2011 is 5.5%, down from 6%-plus over the past of food in the consumption basket is too low to
few months. The inflation number seems not be too impact the headline CPI. But this is inconsistent with
bad when compared to other developing countries’. the fact that, given the standard of living in China,
food consumption should be a major proportion of
household spending. Therefore, we suggest that food
Figure 9 Year-over-Year Inflation Rates in China inflation rates might reflect true inflation rates more
30
closely than the currently released CPI inflation rate.
%
25 Figure 10 displays the one-year benchmark
deposit and lending interest rates, one of the main
20
monetary policy instruments of the PBC. To cool
15 down the overheating economy and property bubble,
over the past year the PBC has raised the lending
10 interest rate from 5.31% to 6.56%. If high inflation
5
in China persists, it could complicate China’s future
government stabilization policy. The contractionary
0 policy is targeting both the rising inflation and the
asset bubble. If the inflation does not come down,
-5
88 90 92 94 96 98 00 02 04 06 08 10 China will not be able to easily loosen its tightening
policy to mitigate the growing stress in the real estate
Consumer Price Index Food Price
market.
Sources: National Bureau of Statistics of China, CEIC Data
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Figure 10 One-Year Benchmark Deposit and Lending In contrast, China has seen its trade share increasing
Interest Rates in China from about 20% in the early 1980s to above 40% in
2000, and accelerating to 70% in 2006 after enter-
ing the World Trade Organization (WTO). It is this
12
% upward trend of international trade and openness that
10 has partly driven the investment boom in China over
the past two decades because investors expect that
8 the growing global market will be able to absorb their
increasing manufacturing capacity and products.
6
4
Figure 11 Trade as a Percentage of GDP
2 70
%
0 60
1980 1985 1990 1995 2000 2005 2010
50
Deposit Rate Lending Rate
40
Sources: People’s Bank of China, CEIC Data
30
20
6. Export-Oriented Risk
10
Like Japan and other East Asian economies, the 0
export sector has been the engine of economic growth 1980 1985 1990 1995 2000 2005 2010
and employment creation for China over the past two CHINA US JAPAN
decades. The net export, export minus import, as a
percentage of GDP has been above 4% since 2005 Source: World Development Indicators
as shown in Figure 4. The current account surplus
results in a mounting foreign reserve in China as pre-
sented in Figure 7. Although the net export consists of According to China’s official data, in 2010
only 4% of China’s GDP in 2010, international trade China’s export value to the world was $1.58 trillion
has a far more important role for China’s economy and the import value from the rest of the world was
than it appears in terms of its employment impact and $1.39 trillion, resulting in a $186 billion trade surplus.
its derived demand on manufacturing investment. Among China’s export markets, advanced economies
count for 70%. Figure 12 presents major trading part-
Figure 11 indicates trade, or the sum of export ners with China in 2010. The European Union is the
and import of goods and services, as a percentage of largest export market for China with $311 billion. The
GDP for China, the U.S., and Japan. Over the past second largest market and the single largest coun-
three decades, we have seen the trade share in the try for China’s export is the U.S. with $284 billion.
U.S. and Japan fluctuating between 15% and 30%. For the past five years, on average, China’s export
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value to Europe has been growing 18% annually and appetite for Chinese export goods in the near future.
growing 13% annually to the U.S. China’s growth A lukewarm export market will directly hamper
dependence on export received quite the blow in 2009 China’s GDP growth. When the expectation of a
when the global financial crisis spread around the weak export market materializes, it could hinder
world. China’s real net export stumbled by more than long-lasting manufacturing investment sprees because
37% and had a -2.9% contribution to its GDP growth. of a concern of overcapacity. Therefore, the external
China swiftly initiated real estate and infrastructure shock to export-oriented nature of Chinese economy
investment to diminish this loss for the export sec- will be another blow to China’s economic growth.
tor. But this question remains: Will China be able to
engineer another investment boost when exports fall Is Chinese Currency Undervalued?
in the future?
One of the most controversial political economy
With the ongoing European debt crisis and the questions over the past several years has been wheth-
bleak U.S. employment market, it is hard to predict er or not Chinese currency, yuan or Renminbi, is
that these two major markets will have a favorable undervalued. Before answering this question, we need
to clearify the definition of “value.” There are two
Figure 12 Major Trading Partners with China kinds of value: (1) fundamental value and (2) equilib-
in 2010 rium value. The fundamental value will be uncovered
in the long run by rational market forces with perfect
300 information, while the equilibrium value will be
250 decided by day-to-day demand and supply driven by
Export
200 available and imperfect information, expectation, or
$Billion 150 noises. By and large, equilibrium value will convert
100 to the long-term fundametal value.
50
0 If the question is whether or not Chinese cur-
rency is under its fundamental value, it is not an easy
one to answer because many factors that determine
the fundamental value of Chinese currency and prod-
ucts in the international trade and finance markets,
300 e.g. productivity and prices in tradable goods, are
neither stable nor observable in real time. However,
250
Import if the question is whether or not Chinese currency is
200
under its equilibrium value, the answer is yes. China
$Billion 150
heavily intervenes in the foreign exchange market to
100 prevent Renminbi from appreciating in order to main-
50
tain its export sector’s competitiveness. According to
economic theory, if a country manages to undervalue
0
its currency—or nominal exchange rate—for a long
time, the country’s inflation rates will eventually rise.
Indeed, we have seen surging inflation in China in
2008 and 2011.
Source: CEIC Data
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Figure 13 presents the nominal exchange rates Chinese consumers have seen income growth, they do
between the Chinese yuan and the U.S. dollar and not want to spend too much for four reasons:
the euro from 1987 to date. China pegged the dollar
to yuan exchange at $0.12 from 1995 to 2005. From 1) Since the SOE reform in the late 1990s, declin-
2005 to 2008, Renminbi appreciated from $0.12 to ing public employment leads to a reduction in
$0.146 (about 22%) and then remained at the same benefit coverage for public education, health care,
rate through the financial crisis. In 2010, it started ap- and housing services, which Chinese employees
preciating again, going from $0.146 to $0.157 (about previously received. Without a comprehensive
7.5%). Since the dollar has been depreciating much social safety net, such as unemployment insur-
more against the euro than against the yuan, the yuan ance, social security or pension funds, Medicare,
has not appreciated much against the euro over the etc., you are on your own if you lose your job, get
past decade. sick, or retire. The government will not provide
the necessary help for you. As a result, Chinese
households need to save a portion of their income
Figure 13. Nominal Exchange Rate USD/Yuan and to prepare for rainy days. Furthermore, rising
Euro/Yuan
education and health care expenditures have
.28
beefed up the need for more savings in the past
USD per yuan
or Going up means few years8.
Euro per yuan .24 yuan appreication
2) Facing soaring housing prices, those Chinese who
want to buy a house have to save more in order
.20 to afford one. On the other hand, in contrast to
American consumers who increased their spend-
.16 ing after watching their home equity and housing
wealth balloon, Chinese homeowners do not have
.12
the same propensity to spend with rising housing
wealth. Putting this together, a real estate bubble
.08
88 90 92 94 96 98 00 02 04 06 08 10 restrains household consumption and propels
USD/CNY EUR/CNY savings.
3) China’s financial market is underdeveloped, so
Sources: CEIC Data, Federal Reserve credit and consumer loans are not easily acces-
sible to normal households. To buy big-ticket
items, one needs to save a sufficient amount of
7. Consumption Imbalance Risk money ahead of time. In addition, there are few
choices for reliable financial investment in China.
If China’s investment boom is not sustainable
Bank deposits are the most common household fi-
and if foreigners’ appetites for Chinese exports are
nance. As seen in Figure 10, the current one-year
reducing, the only savior for China’s economic mo-
deposit interest rate is 3.5%, which is below the
mentum is domestic private consumption. However,
official CPI inflation rate. Facing a declining real
this hope is not easily realized. As shown in Figure
interest rate, Chinese households have to save
4, it is stunning to see that the percentage of private
more to cover their purchasing power loss amid a
consumption over GDP has been shrinking over the
surging inflation environment.
past decade from 46% in 2000 to 34% in 2010. Mean-
4) Consumers are frugal because of several invisible
while, the domestic saving rates over GDP have in-
factors. For example, facing overall macroeco-
creased from 38% in 2000 to 50% in 2010. Although
nomic uncertainty, Chinese consumers need to
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prepare additional precautionary savings. More- As the Chinese economy is getting bigger, foreign
over, in Chinese culture, thrift is acknowledged as consumers will not be able to digest China’s products.
a virtue, which explains relatively higher savings Looking forward, China has no choice but to boost its
in other East Asian countries as well. domestic consumption demand by improving those
factors that repress private consumption.
In the aftermath of the Great Recession, by
looking at painfully deleveraging American consum- All Good Things Come to an End
ers, we all agree that living beyond our means is not
desirable. But it is also distorted to live way below Examining the history of fast-growing econo-
our means like Chinese consumers. Depressed con- mies in the world over the past five decades, Eichen-
sumption and overinvestment is not a sustainable way green et al. (2011)10 suggest that rapidly growing
to grow an economy. Niall Ferguson (2011)9 suggests economies will slow down by at least 2% in GDP
six elements to make the West a source of economic growth rates as the country’s per capita incomes reach
dynamism and political stability: (1) Competition, (2) certain levels (they suggest $15,000 on average).
Science, (3) Rule of Law, (4) Medicine, (5) Consum- They propose the following reasons:
erism, and (6) Work Ethic.
• Eventually the pool of underemployed rural labor
Consumerism is one contributing element to will be drained;
an economy that continually dominates and prospers • The share of employment in manufacturing will
in this capitalism world. Why? Because household peak;
consumption is the ultimate goal of economy growth.
It is the fundamental driver of government spending, • Growth will come to depend on the difficult pro-
private and public investment, export, import, grow- cess of raising productivity in the service sector;
ing income, enhancing technology and innovation. • A larger capital stock will bring more depricia-
In 2010, China, the second largest economy in the tion; and
world, had a GDP of $5.88 trillion, about 40% of the • When the economy approaches the technology
U.S. GDP of $14.58 trillion, while China’s household froniter, it will transit from relying on imported
consumption—$2.26 trillion—is only about 22% of technology to indigenous innovation.
U.S. consumption—$10.42 trillion.
China will face these challenge points one by
When a country has a larger proportion of
one. Their empirical evidence also reveals three
consumption, the economy will grow steadily due to
predictors of economy slowdown, all fitting China’s
a stable consumption growth. It is rather difficult for
current status.
a nation’s consumption to decline sharply because
the nature of consumption (nondurable goods and
1) When the consumption share of GDP increases,
services) is smoothing. But investment is different. It
the probability of economic slowdown will
is very volatile, and it will reduce substantially from
decrease. But when the consumption share
time to time. After all, we cannot expand factories,
becomes too large, e.g. the consumption spree
skyscrapers, highways, and high-speed rails every
in the U.S. from 2000 to 2006, the probability of
day. In sum, China’s current high-investment-low-
GDP growth slowdown will increase, as shown in
consumption model is fragile and risky. It worked for
Figure 14.
China over the past decade because developed econo-
2) When the investment share of GDP increases, the
mies, especially American consumers, were absorbing
probablity of economic slowdown will decrease.
rapid capacity build-up in China through its exports.
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Figure 14 Probability of Growth Slowdown
Probability
China China
of Growth
Slowdown
0% 62-64% 80% 0% 30% 60%
Consumption Share of GDP Investment Share of GDP
This is absolutely correct because investment will 8. Rule of Law Risk
accumulate physical capital, which will bolster
producitivity. But when the investment share be- The above risks are either short term or medium
comes too big, e.g. the investment spree in China term, which would trigger a hard landing and a down-
from 2003 to 2011, the probability of economic turn for China’s business cycle. The Chinese econ-
slowdown will increase. omy is also exposed to some long-term risks, which
3) Countries with more dramatically undervalued will undermine its economic growth in the long
currencies are more likely to experience growth run. The most serious risk is its lack of rule of law.
slowdowns. The possible reason for this is that Although China’s rule of law is better than in some
these countries, which are more dependent on third-world countries, it is still far behind a developed
exports, are more vulnerable to external shocks. country’s standard. For instance, the World Bank
Table 2 The World Bank’s Worldwide Governance Indicators for 2010
Rank 1 2 3 4 5 6 7 8 9
Voice and US Japan Taiwan Korea Brazil India Mexico Singapore China
Accountability 1.16 1.05 0.9 0.71 0.5 0.42 0.08 - 0.29 - 1.65
Political Singapore Japan Taiwan US Korea Brazil China Mexico India
Stability and
Absence of
Violence 1.12 0.87 0.79 0.31 0.1 0.05 - 0.77 - 0.79 - 1.31
Government Singapore US Japan Taiwan Korea Mexico China Brazil India
Effectiveness 2.25 1.44 1.4 1.21 1.19 0.17 0.12 0.07 0
Regulatory Singapore US Taiwan Japan Korea Mexico Brazil China India
Quality 1.8 1.42 1.18 0.98 0.91 0.28 0.1 9 - 0.23 - 0.39
Singapore US Japan Taiwan Korea Brazil India China Mexico
Rule of Law 1.69 1.58 1.31 1.01 0.99 0 - 0.06 - 0.35 - 0.56
Control of Singapore Japan US Taiwan Korea Brazil Mexico India China
Corruption 2.18 1.54 1.23 0.75 0.42 0.06 - 0.37 - 0.52 - 0.6
Source: World Bank Worldwide Governance Indicators, 2011.
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developed an indicator to grasp a country’s institution the polluters. To have a sustainable economic growth,
quality and its rule of law. Table 2 displays China and China needs to pay more attention to the externalities
eight other economies with ratings ranging from 2.5 created by its economic development and growth.
(the best) to -2.5 (the worst). China is located near the
bottom in all categories. The upper panel of Figure 15 provides the
energy use efficiency of major economies in 2008.
If China cannot improve their rule of law, The higher the value is, the more energy a country
China’s economic growth will eventually stumble and consumes to generate the same GDP. China uses
fall behind other countries in the future. A nation with 279.7 kg per $1000 GDP, which is much higher than
a stable rule of law guaranteed by the government other countries. This could partly explain the global
that enforces contracts and protect property rights will
more likely promote technology progress and innova-
tion. Without technology progress, when the labor Figure 15 Energy Use Efficiency and CO2 Intensity
migration and the capital accumulation reach their
Energy Use Efficiency, 2008
tipping points, China will lose its growth traction. kg of oil equivalent per $1000 GDP (PPP
adjusted)
Additionally, China has to improve, at least, 300
two rules of law: (1) constitution and (2) intellectual
250
property right, which are not currently followed or
implemented. Without fair practice and protection 200
of human rights and civil rights written into China’s 150
constitution, two unwanted outcomes could occur.
100
First, social unrest could explode and stymie invest-
ment and economic growth because there is no impar- 50
tial institution, e.g. court, to settle growing disputes. 0
Second, an uncertain and unfair environment will
drive away the best talents of the nation, resulting
in brain drain and human capital loss. Without the
protection of intellectual property rights, China will
CO2 Intensity, 2007
not create indigenous innovations because there is no kg per kg of oil equivalent energy use
incentive to induce significant research and develop-
4
ment, which require long-term and expensive invest-
3.5
ment.
3
2.5
9. Environmental Risk 2
1.5
GDP is not a perfect barometer of a country’s 1
standard of living because, for example, it does not 0.5
measure the forgone value of leisure activities or
0
long-term costs of pollution and environmental dam-
age that accompany GDP growth. As China continues
its breakneck GDP growth, the environmental cost is
usually either ignored or not appropriately shared by Source: World Development Indicators
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commodity price run-up over the past decade not only Figure 16 Dependence Ratio History and Forecast
because China has stellar economy growth but also 100
because it has such an energy-intensive method of %
economic growth. Figure 15’s lower panel presents 90
the Carbon emission intensity for each unit of energy 80
used by major economies in 2007. Again, China is the 70
highest one, emitting $3.5 kg of CO2 for each kg of
energy use. China should improve its energy efficien- 60
cy as well as reduce its pollution output in order to 50
foster the health, welfare, and prosperity of its nation. 40
10. Demographic Risk
30
Over the past three decades, China has had a China US Japan
demographic advantage for economic growth. Figure Source: United Nations Population Division, World Population Prospects,
16 depicts the dependence ratio, which is the ratio of 2010 Revision
population of young (below age 15) and old (above
age 65) over the working group (age 15 to 64) for Figure 17 Population Growth Rate History and
China, the U.S., and Japan. The higher the ratio is, the Forecast
bigger the burden for the working age adult to support 2
the children and the retired. For China, its depen- %
1.5
dence ratio has been declining from 69% in 1980 to
38% in 2010. The growing working population trend 1
will be reverted in 2015. Starting then, China will 0.5
see a climbing dependence ratio, just as Japan did in
1995. 0
-0.5
Moreover, the total population growth rate,
as shown in Figure 17, does not look promising -1
for China. In 2010, China’s population growth rate
declined below 0.5%, similar to Japan’s level in 1986. China US Japan
And China’s population growth is projected to decline
Source: United Nations Population Division, World Population Prospects,
rapidly to zero growth in 2028 and continue to drop 2010 Revision
to -0.5% in 2046. In contrast, U.S. population growth,
although declining, is expected to remain above 0.5%
for the next four decades. The good news is that Leading Economic Indicators
China still has a relatively higher urban population
growth (migrating from rural areas) projected for the Currently, the Conference Board and the Orga-
future. In 2010, China’s urban population growth rate nization for Economic Cooperation and Development
was 2.5%, which is higher than 1% in the U.S. and (OECD) produce China’s economic leading indicators
0.2% in Japan. including the following components: (1) Conference
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Board: consumer expectation index, China Federa- Treasury bill yield, is a relatively simple and usefully
tion of Logistics and Purchasing (CFLP) Purchas- leading indicator of the recession (when the spread
ing Managers Index (PMI): export orders subindex, closes to zero or turns to negative). Therefore, let’s
CFLP PMI: supplier deliveries subindex, total loans look at the Chinese government bond’s yield curves
issued by financial institutions, 5,000 industrial and spread though the Chinese bond market might
enterprises diffusion index (raw materials), and total not be liquid and efficient enough because of insuf-
floor space started. (2) OECD: M2, chemical fertilizer ficient trading volume and market participants. Figure
production, production of crude steel, 5,000 indus-
trial enterprises (overseas order level), real estate
under construction, production of motor vehicles, and Figure 18 The Market Prices of Copper and Iron Ore
Shanghai stock exchange turnover. Since these lead-
ing indicators are newly born, their forecasting ability US cent
480 320
US cent
Iron Ore
remains to be examined. Copper 440
280
400
240
360
At this point, we suggest three simple indexes 320 200
to get a hold of the current state of China’s economy: 280
(1) HSBC China PMI, (2) the market price of iron
160
240
ore and copper, which shed light on China’s heavily 200
120
dependent sector—manufacturing and construction 160 80
investment, and (3) China’s export growth to the 120
2005 2006 2007 2008 2009 2010 2011
European Union and the U.S. The HSBC flash China
Copper Iron Ore
PMI in November, 2011 is 48, a 32-month low, de-
clining from 51 in October. Figure 18 shows that two
Sources: Global Finance Data; copper is the high-grade copper price
commodities, of which China is the main buyer in the from New York Mercantile Exchange, and iron ore is from Brazil’s market.
global market, had prices that plunged in the out-
break of the global financial crisis and that rebounded Figure 19 Monthly Year-over-year Growth Rates
sharply in the deepest chaos of late 2008 as China of China’s Nominal Export Values to the
launched a massive construction boom. Now we can European Union and the U.S., January
see both prices are heading downwards. The global 2006 to September 2011
price of these raw materials may reflect Chinese con- %
50
struction investment.
40
Moreover, as shown in Figure 19, year-over- 30
year monthly Chinese export values to the E.U. and
20
the U.S. have dwindled to below 10%. In particular,
China’s export growth to the E.U. has gone negative 10
as of late. Over the past five years, China’s export to 0
the E.U. contributed one-fifth of total Chinese export
-10
growth. With a likely E.U. recession approaching, the
languid export engine foretells an ominous future for -20
China’s growth. 2006 2007 2008 2009 2010 2011
EU US
In the U.S., the yields spread, say the difference
between 10-year Treasury bond yield and 3-month Sources: Eurostat, U.S. Census Bureau
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Figure 20 Chinese Government Bond Yields and Spreads, 5/18/2009 to 11/24/2011
Source: Global Finance Data
20 displays the Chinese government bond yields in 1 the looming risks mentioned above, we suggest that
year, 5 year, and 10 year as well as the yield spread it is possible to see China’s hard landing, especially
between 1-year and 10-year bonds. Since December if China still keeps its pursuit of high growth in the
2010, the yield spread has declined below than 1%. future. However, given the currently available market
Not that in September 2011, the yield spread has been indicators and limited data, we cannot make a specific
dropped below 0.2%. forecast regarding the probability, the timing, and the
depth of China’s hard landing.
Hard Landing or Soft Landing?
Medium-Term Growth
When the economy slows down smoothly and
orderly without causing a significant decline of output Another question is: Will China return to its
growth and employment, we call this a soft landing. splendid economic growth after its short-term land-
In contrast, if the economy slows down abruptly with ing? We suggest that it is very unlikely. Here we list
a painful and significant reduction of output growth several studies that present China’s medium- or long-
and employment, it is called a hard landing. Based on term forecast:
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• Lee and Hong (2010)11 project that China will China’s GDP per capita will pass the U.S.’s by 2035
grow 6.1% to 7.0% per annum in the 2010s and and become not only the largest but also the richest
5.0% to 6.2% in the 2020s. economy in the world. Is it possible? Now, let’s look
• Maddison (2009)12 predicts that China will grow at other country’s catch-up stories.16
5% per annum on average between 2004 and
2030. From 1950 to 1970, Japan had spectacular
growth. If we were in 1970 assuming that the past
• Buiter and Rahbari (2011)13 anticipate that China
growth rate in Japan would continue, we would
will grow 5% per annum between 2010 and 2050.
expect to see Japan surpass the U.S. in 1975. This did
• Fogel (2007)14 conjectures that China will grow not happen, however, because Japan’s growth rate
7.9% per annum between 2011 to 2040. started to slow down in 1970. Despite slowing down,
• The Conference Board (2011)15 forecasts that Japan had decent growth in the 1970s and 1980s.
China will grow according to three scenarios: Again, if we were in 1989, we would not be able to
o Optimistic: 9.7% per annum in 2012 to 2016; help but predict that Japan would overpass the U.S.
4.9% in 2017 to 2025. to become the richest major economy in 1990. Yet
again, this did not occur because Japan had another
o Base: 7% per annum in 2012 to 2016; 3.5% growth slowdown starting in 1990. Germany is simi-
in 2017 to 2025. lar to Japan in that it seems to have had a hard time
o Pessimistic: 3.8% per annum in 2012 to breaking through the U.S.’s “glass ceiling.”
2016; 3% in 2017 to 2025.
Similarly, Taiwan and Korea have shown splen-
Given the analysis we present above, we agree did growth over the past several decades, especially
more with the first three forecasts as well as the base in the 1970s, 1980s, and 1990s. If we were in 1996,
or pessimistic view from the Conference Board about assuming no change in the past growth trajectory, we
China’s trajectory rather than with Fogel or the Con- would be tempted to predict that the standard of liv-
ference Board’s optimistic view. We predict that on ing in Taiwan and Korea would surpass Japan before
average China will grow 5.5% in the medium term. In 2005. Again, this did not happen. The Asian Tigers
the long run, it is likely that China will face another did not break through Japan’s glass ceiling. Taiwan
slowdown because long-term factors will kick in, and Korea, however, did successully break through
such as an aging population and maturing urbaniza- Mexico’s and Brazil’s in the 1980s. How? Taiwan and
tion. Korea both had an impressive institution transforma-
tion while Mexico and Brazil did not.
It may be hard to convince some of the slow-
down in China’s growth forecast. Figure 21 may China’s economic growth will soon face a glass
make this easier by showing that the high growths in ceiling imposed by Mexico, Brazil and Russia, which
late-developing economies do not last forever. Figure are global competitors with China, in particular
21 shows the GDP per capita, an indicator of a na- for labor wages and production costs. If China can
tion’s standard of living, for the U.S. and nine other conduct the necessary reforms for its rule of law and
major catching-up economies from 1950 to 2010. institution quality and establish a healthy and steady
The U.S. remains on top with the highest standard consumer market, it will have a chance to surpass
of living among these economies. China grew rap- Mexico and Brazil in terms of standard of living.
idly over the past three decades; it surpassed India in Failing these two changes, China’s economic wonder
1992. If China continues this stunning growth rate, will stop and stagnate in the middle-income area like
many other countries.
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Figure 21 Per Capita GDP for 10 Economies, PPP Figure 22. U.S. Exports to China and Trade Deficit
Adjusted, at 2005 $ Price with China
400
60,000
$ Billion
40,000 350
($)
20,000 US Taiwan
Germany Russia 300
14,000
10,000 Japan
Mexico
250
6,000
Korea 200
4,000
Brazil
2,000 150
1,400
1,000 India
100
600
China 50
400
200 0
50 55 60 65 70 75 80 85 90 95 00 05 10 99 00 01 02 03 04 05 06 07 08 09 10
Export to China
China Brazil Germany
Trade Deficit with China
India Japan Korea
Mexico Russia Taiwan
US Source: US Bureau of Economic Analysis
Source: Penn World Table 7.0
Figure 23. U.S. Exports to China Growth, U.S.
Exports to China and European Union as
Percentage of Total Exports, U.S. Deficit
Impacts of China’s Slowdown on the U.S. with China as Percentage of the Whole
Deficit
We believe that the interaction between the 60
economies of the U.S. and China favors one country %
over the other. Via international trade, changes in the 50
U.S. economy will affect and spill over more to China
than Chinese economic changes will influence the 40
U.S. Figure 22 presents U.S. exports to China (the
blue shaded bar) and the U.S. trade deficit with China 30
(the red bar). The combined value of the two bars
are U.S. imports from China. It is apparent that the 20
U.S. imports much more from China than it exports
10
to China. In 2010, the U.S. export to China was $114
billion while the import from China was $376 billion,
0
resulting in a trade deficit of $262 billion. 99 00 01 02 03 04 05 06 07 08 09 10
Export to China Growth Rate
In Figure 23, the bars represent the U.S. exports Export to China / Total Export
to China annual growth rate. Over the past decade, Export to EU / Total Export
Deficit with China / Total Deficit
the growth rate average has been around 15%.
Despite U.S. export growth to China, the share of Source: US Bureau of Economic Analysis
exports to China over total exports of the U.S. is only
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about 6%. Because its share is not substantial yet, we Conclusions
believe that the possible slowdown or hard landing of
the Chinese economy will not have much of an affect In summary, the take-away points from our
on the U.S. economy. report on China are as follows:
By contrast, U.S. exports to the European Union • We should take heed when reading China’s data.
have been above 20% over the past decade, meaning There is a high tendency for window dressing
Europe’s economy will have more influence on U.S. through “data moderation.”
exports if it is worsened. Moreover, the black dashed • The overinvestment in manufacturing capacity,
line is the share of trade deficit with China over the real estate market, and infrastructure are not sus-
whole U.S. trade deficit. It rose sharply and went tainable. The bubble is going to burst.
above 50% in 2009 and 2010. That said, trading with
China alone constitutes about half of our trade deficit. • Amid the looming risks, it is possible to see a
hard landing of China’s economy in the future
although its probability, timing, and depth remain
It is therefore reasonable for the U.S. and China
unclear at this point.
to settle this unbalanced and unsustainable trade
relationship. If, unfortunately, a trade war happens,
it is clear that China will lose much more than the For better or for worse, China will be sitting as
U.S. Moreover, we suggest that U.S. exports to China the second largest economy for some time. If China
will see more growth on consumption goods than on can face and resolve ten risks in the future, China will
capital goods. grow to be an advanced economy sooner than later.
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Endnotes
1. In Modern Chinese history, one could say that two hundred years before 1842, it was the best of times for China. From 1842 to 1978, it
was the worst of times. Since 1978, it has been the best of times as well as the worst of times.
2. Maddison, Angus, and Harry X. Wu, 2008. “Measuring China’s Economic Performance,” World Economics, 9(2): 13-44.
3. Bai, Chong-en, Chang-Tai Hsieh, and Yingyi Qian, 2006. “The Return to Capital in China,” Brookings Papers on Economic Activity,
2(2): 61-88.
4. Knight, John, and Sai Ding, 2010. “Why Does China Invest So Much?” Asian Economic Papers, 9(3): 87-117.
5. Huang, Yiping, 2010. “China’s Great Ascendancy and Structural Risks: Consequences of Asymmetric market Liberalization,” Asian-
Pacific Economic Literature, 24(1): 65-85.
6. Wu, Jing, Joseph Gyourko, and Yongheng Deng, 2011. “Evaluating Conditions in Major Chinese Housing Markets,” Regional Science
and Urban Economics, doi: 10.1016/j.
7. The data is from Rating and Valuation Department of Hong Kong SAR.
8. Chamon, Marcos, and Eswar Prasad, 2010. “Why Are Saving Rates of Urban Households in China Rising?” American Economic
Journal: Macroeconomics, 2(1): 93-130.
9. In his book, 2011, Civilization: The West and the Rest.
10. Eichengreen, Barry, Donghyun Park, and Kwanho Shin, 2011. “When Fast Growing Economies Slow Down: International Evidence
and Implications for China,” NBER Working Paper 16919.
11. Lee, Jong-Wha, and Kiseok Hong, 2010, “Economic Growth in Asia: Determinants and Prospects,” Asian Development Bank Working
Paper 220.
12. Maddison, Angus, 2009, Chinese Economic Performance in the Long Run, 960-2030 AD, Paris: OECD.
13. Buiter, William and Ebrahim Rehbari, 2011. “Global Growth Generators: Moving Beyond Emerging Markets and BRICs,” Citigroup
Global Markets.
14. Fogel, Robert, 2007. “Capitalism and Democracy in 2040: Forecasts and Speculations,” NBER Working Paper 13184.
15. Conference Board, 2011, Global Economic Outlook, New York: Conference Board.
16. Economic growth theory calls this “unconditional convergence.”
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THE UCLA ANDERSON FORECAST
FOR THE NATION
December 2011 Report
Charts
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Charts – Recent Evidence
Price Inflation Interest Rates
Consumer vs. Producers' Price Index 3-Mo. T-Bills vs. Long Gov't Bond Yields
Jan. 1999 to Oct. 2011 Jan. 1999 to Oct. 2011
(% Change Year Ago) (Percent)
10 7
3-Month
6 Long Gov'ts
5 5
4
0
3
-5 2
1
-10 0
99 00 01 02 03 04 05 06 07 08 09 10 11
Consumer Prices Producer Prices-Fin. Goods -1
99 00 01 02 03 04 05 06 07 08 09 10 11
Automobile Sales
Jan. 2000 to Oct. 2011 Industrial Production
(Mil. Units) Jan. 1999 to Oct. 2011
14 (Index 2002 = 100)
105
Cars
12 Trucks
100
10
95
8
6 90
4 85
2
00 01 02 03 04 05 06 07 08 09 10 11 80
99 00 01 02 03 04 05 06 07 08 09 10 11
UCLA Anderson Forecast, December 2011 Nation–47
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Charts – Recent Evidence
Total Nonfarm Employment Employment in Manufacturing
Jan. 1999 to Oct. 2011 Jan. 1999 to Oct. 2011
(Thous.) (Thous.)
138000 18000
136000 17000
16000
134000
15000
132000
14000
130000
13000
128000 12000
126000 11000
99 00 01 02 03 04 05 06 07 08 09 10 11 99 00 01 02 03 04 05 06 07 08 09 10 11
Employment in Services Employment in Construction
Jan. 1999 to Oct. 2011 Jan. 1999 to Oct. 2011
(Thous.) (Thous.)
118000 8000
116000
7500
114000
7000
112000
110000 6500
108000
6000
106000
5500
104000
102000 5000
99 00 01 02 03 04 05 06 07 08 09 10 11 99 00 01 02 03 04 05 06 07 08 09 10 11
48–Nation UCLA Anderson Forecast, December 2011
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Charts – Recent Evidence
Crude Oil Price Core Consumer Price Index
West Texas Intermediate Jan. 1999 to Oct. 2011
Jan. 2000 to Oct. 2011 (% Change Year Ago)
($/Barrel) 3.0
140 2.7
120 2.4
100 2.1
80 1.8
1.5
60
1.2
40 0.9
20 0.6
0 0.3
00 01 02 03 04 05 06 07 08 09 10 11 99 00 01 02 03 04 05 06 07 08 09 10 11
Composite Indexes of Economic Indicators Ceridian-UCLA Pulse of Commerce Index
Jan. 1999 to Oct. 2011 Jan. 1999 to Oct. 2011
(Index 2004=100) (Index 2007=100)
120 105
100
Leading
110 Coincident 95
90
100
85
90 80
75
80 70
99 00 01 02 03 04 05 06 07 08 09 10 11 99 00 01 02 03 04 05 06 07 08 09 10 11
UCLA Anderson Forecast, December 2011 Nation–49
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Charts – Recent Evidence
Total Business Inventory-to-Sales Ratio Real Disposable Personal Income
Jan. 1997 to Sept. 2011 Jan. 1999 to Oct. 2011
1.50 (Bil. 2005$)
11000
1.45
10500
1.40 10000
1.35 9500
9000
1.30
8500
1.25 8000
1.20 7500
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 99 00 01 02 03 04 05 06 07 08 09 10 11
Retail Sales Real Personal Consumption
Jan. 1999 to Oct. 2011 Jan. 1999 to Oct. 2011
(Bil. $) (Bil. 2005$)
400 9600
9300
350
9000
300 8700
8400
250
8100
200 7800
7500
150
7200
100 6900
99 00 01 02 03 04 05 06 07 08 09 10 11 99 00 01 02 03 04 05 06 07 08 09 10 11
50–Nation UCLA Anderson Forecast, December 2011
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Charts – Recent Evidence
Single-Family New Home Sales Housing Starts
Jan. 1999 to Sept. 2011 Jan. 1999 to Oct. 2011
(Thous.) (Mil. Units)
1400 2.5
1200 2.0
1000
1.5
800
1.0
600
400 0.5
200 0.0
99 00 01 02 03 04 05 06 07 08 09 10 11 99 00 01 02 03 04 05 06 07 08 09 10 11
Rate of Unemployment Unemployment Insurance Claims
Jan. 1999 to Oct. 2011 Jan. 1, 2000 to Nov. 19, 2011
(Percent) (Thous.)
11.0 700
10.1
600
9.1
8.2 500
7.3
400
6.3
5.4 300
4.4
3.5 200
99 00 01 02 03 04 05 06 07 08 09 10 11 00 01 02 03 04 05 06 07 08 09 10 11
UCLA Anderson Forecast, December 2011 Nation–51
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Charts – Recent Evidence
Japanese and European U.S., Japanese and German
Exchange Rates Stock Markets
Jan. 2000 to Oct. 2011 Jan. 1999 to Oct. 2011
(Deutschmark/$) (Yen/$) (Index Jan.'90 = 1.00)
1.20 140 6
1.10 130 5
1.00 120 4
110 3
0.90
100 2
0.80 90 1
0.70 80 0
0.60 70 -1
00 01 02 03 04 05 06 07 08 09 10 11 99 00 01 02 03 04 05 06 07 08 09 10 11
Euro/U.S. $ (Left) Yen/U.S. $ (Right) U.S. Japan Germany
U.S. and Japanese U.S., Japanese and German
Long Term Gov't Bond Yields Consumer Price Index
Jan. 1999 to Oct. 2011 Jan. 2000 to Oct. 2011
(Percent) (% Change Year Ago)
8 6
6 4
2
4
0
2 -2
0 -4
99 00 01 02 03 04 05 06 07 08 09 10 11 00 01 02 03 04 05 06 07 08 09 10 11
U.S. Japan U.S. Japan Germany
52–Nation UCLA Anderson Forecast, December 2011
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Charts – Forecast
Real Disposable Income and Consumption Consumer Expenditures on Medical Services:
(4-Qtr. % Ch.) Quantity % + Price % = Expenditure %
8 (3-Yr. % Ch.)
10
6
8
4
6
2
0 4
-2 2
-4 0
1992 1995 1998 2001 2004 2007 2010 2013 1999 2001 2003 2005 2007 2009 2011 2013
Consumption Disposable Income Quantity Price
Real Export and Import Growth Real GDP Growth
(4-Qtr. % Ch.) Developed World vs. U.S.
20 (5-Yr. % Ch.)
6
10
5
0 4
3
-10
2
-20
1
-30 0
1992 1995 1998 2001 2004 2007 2010 2013 1993 1997 2001 2005 2009 2013
Exports Imports U.S. Developed World
UCLA Anderson Forecast, December 2011 Nation–53
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Charts – Forecast
Real GDP Growth Actual Real GDP
(4-Qtr. % Ch.) Vs. Potential Real GDP
6 (Bil. 2005 $)
16000
4
14000
2
12000
0
10000
-2
8000
-4
6000
1992 1995 1998 2001 2004 2007 2010 2013
-6 Actual Real GDP Potential Real GDP
1992 1995 1998 2001 2004 2007 2010 2013
Defense Spending Real Purchases of Goods and Services
As A Share of GDP by the Federal Government
(Percent) (% Ch. 12-Qtr. Mov. Avg.)
10 8
7
8
5
6 4
2
4 1
-1
2
-3
0 -4
1978 1983 1988 1993 1998 2003 2008 2013 1997 1999 2001 2003 2005 2007 2009 2011 2013
54–Nation UCLA Anderson Forecast, December 2011
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Charts – Forecast
Change in Real Business Inventories Real Investment-Producers Durable Equip.
(3-yr. Moving Average) Info. Processing Equip. vs. Other Equip.
(% of Real GDP) (3-yr. % Ch.)
0.8 30
0.6 20
0.4
10
0.2
0
0.0
-0.2 -10
-0.4 -20
1992 1995 1998 2001 2004 2007 2010 2013
-0.6 Total Less Info. Equip. Information Processing Equip.
1995 1997 1999 2001 2003 2005 2007 2009 2011 2013
Business Fixed Investment Share of Real GDP Vs. Real Investment in Nonresidential Structures
Producers Durable Equip. Share of Bus. Fixed Invest. Total vs. Commercial Bldgs.
(Percent) (Percent) (3-Yr. % Ch.)
12 80 10
11 75
0
10 70
9 65 -10
8 60
7 55 -20
6 50
1992 1995 1998 2001 2004 2007 2010 2013 -30
Bus. Fixed Investment Share 1995 1998 2001 2004 2007 2010 2013
Prod. Dur. Share/Bus. Fixed Total Commercial Bldgs.
UCLA Anderson Forecast, December 2011 Nation–55
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Charts – Forecast
Business Fixed Investment Share of Real GDP Real Investment in Residential Structures
Vs. Capital Stock Growth Vs. New Housing Starts
(Invest. Share %) (4-Qtr. % Ch.) (Bil. 2005 $) (Mil. Units)
12 8 800 2.5
11 6 700 2.0
10 600
4 1.5
9 500
2 1.0
8 400
7 0 300 0.5
6 -2 200 0.0
1992 1995 1998 2001 2004 2007 2010 2013 1989 1993 1997 2001 2005 2009 2013
Bus. Fixed Investment Share Capital Stock Growth Real Investment (Left) Housing Starts (Rt.)
Real Hourly Wage Compensation Federal Surplus or Deficit
Vs. Productivity in Nonfarm Sector (Percent of GDP)
(10-Yr. % Ch.) 2
3.0
2.5 0
2.0 -2
1.5
-4
1.0
0.5 -6
0.0
-8
-0.5
1973 1978 1983 1988 1993 1998 2003 2008 2013
Real Wage Productivity -10
1989 1993 1997 2001 2005 2009 2013
56–Nation UCLA Anderson Forecast, December 2011
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Charts – Forecast
Consumer Price Index Inflation Real Refiner's Cost of Crude Oil
(Percent of GDP) (2005$/barrel)
6 90
5 80
4 70
60
3
50
2
40
1 30
0 20
-1 10
1989 1993 1997 2001 2005 2009 2013 1978 1983 1988 1993 1998 2003 2008 2013
Real and Nominal Exchange Rate Treasury Yields Vs. CPI Inflation
Industrial Countries Trade Weighted Average (Percent)
(Indexed: 2000 = 1.00) 15
1.4
1.2 11
1.0
0.8 7
0.6
0.4 2
0.2
0.0 -2
1989 1993 1997 2001 2005 2009 2013 1964 1971 1978 1985 1992 1999 2006 2013
Nominal Exchange Rate Real Exchange Rate Inflation 30-Year Bonds 90-Day Bills
UCLA Anderson Forecast, December 2011 Nation–57
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Charts – Forecast
Unemployment and Capacity Utilization Mfg. Federal Transfers to Persons
Postwar Business Cycles (Percent of GDP)
(%) (100% - Capacity Util.) 12
10 95
9 90 11
8 85
7 80 10
6 75
9
5 70
4 65 8
3 60
1964 1971 1978 1985 1992 1999 2006 2013
Unemployment Rate Capacity Util. Mfg. Rate 7
1989 1992 1995 1998 2001 2004 2007 2010 2013
Federal Transfers to Persons U.S. Housing Starts
For Health Insurance Vs. Mortgage Rate
(Percent of GDP) (Mil. Units) (Percent)
4.0 2.5 18
16
3.5 2.0
14
1.5 12
3.0 10
1.0 8
2.5
6
0.5
2.0 4
0.0 2
1981 1985 1989 1993 1997 2001 2005 2009 2013
1.5 Housing Starts Mortgage Rate
1989 1993 1997 2001 2005 2009 2013
58–Nation UCLA Anderson Forecast, December 2011
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Charts – Forecast
U.S. Retail Sales of Federal Net Interest Payments on
Automobiles and Light Trucks National Debt
(Mil. Units) (Percent of National Income)
20 4.5
4.0
15
3.5
10 3.0
2.5
5
2.0
0 1.5
1989 1993 1997 2001 2005 2009 2013
Automobiles Light Trucks 1.0
1989 1993 1997 2001 2005 2009 2013
UCLA Anderson Forecast, December 2011 Nation–59
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THE UCLA ANDERSON FORECAST
FOR THE NATION
December 2011 Report
Tables
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Forecast Tables - Summary
Table 1. Summary of the UCLA Anderson Forecast for the Nation
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Monetary Aggregates and GDP (% Ch.)
Money Supply (M1) 4.9 6.5 5.5 2.0 0.2 -0.1 4.4 14.2 6.3 15.8 11.6 5.7
Money Supply (M2) 7.5 6.9 4.7 4.3 5.3 6.3 7.1 7.9 2.3 7.4 6.2 4.2
GDP Price Index 1.6 2.1 2.8 3.3 3.2 2.9 2.2 1.1 1.2 2.1 1.4 1.3
Real GDP 1.8 2.5 3.5 3.1 2.7 1.9 -0.3 -3.5 3.0 1.8 1.7 2.5
Interest Rates (%) on:
Federal Funds 1.7 1.1 1.3 3.2 5.0 5.0 1.9 0.2 0.2 0.1 0.1 0.2
90-day Treasury Bills 1.6 1.0 1.4 3.1 4.7 4.4 1.4 0.2 0.1 0.1 0.1 0.2
10-year Treasury Bonds 4.6 4.0 4.3 4.3 4.8 4.6 3.7 3.3 3.2 2.8 2.4 3.4
30-year Treasury Bonds 5.4 5.1 5.1 4.6 4.9 4.8 4.3 4.1 4.3 3.9 3.3 4.2
Moody’s Corporate Aaa Bonds 6.5 5.7 5.6 5.2 5.6 5.6 5.6 5.3 4.9 4.6 4.3 5.1
30-yr Bond Less Inflation 4.1 3.0 2.5 1.6 2.2 2.1 1.0 3.9 2.5 1.4 2.0 2.6
Federal Fiscal Policy
Defense Purchases (% Ch.)
Current $ 11.4 13.8 10.6 6.9 6.1 6.0 11.4 5.0 5.7 1.3 -1.8 -2.6
Constant $ 7.4 8.7 5.7 1.5 1.6 2.2 7.5 5.8 3.3 -1.9 -3.3 -4.1
Other Expenditures (% Ch.)
Transfers to Persons 9.8 7.0 4.9 6.1 6.4 6.5 9.0 16.9 7.4 -0.1 1.3 2.9
Grants to S&L Gov’t 10.2 11.1 3.3 3.5 -0.6 6.0 3.9 22.0 10.2 -7.3 -7.2 1.3
Billions of Current Dollars, Unified Budget Basis, Fiscal Year
Receipts 1853.2 1782.1 1879.8 2153.4 2406.7 2567.7 2523.6 2104.4 2161.7 2302.5 2535.1 2823.3
Outlays 2011.0 2159.2 2292.6 2472.1 2654.9 2729.2 2978.4 3520.1 3455.9 3601.1 3594.7 3629.3
Surplus or Deficit (-) -157.8 -377.1 -412.8 -318.7 -248.2 -161.5 -454.8 -1415.7 -1294.2 -1298.6 -1059.7 -806.0
As Shares of GDP (%), NIPA Basis
Revenues 17.5 16.9 17.0 18.1 18.9 18.9 17.5 16.0 16.7 17.0 17.6 18.8
Expenditures 19.8 20.3 20.2 20.4 20.4 20.7 21.8 24.8 25.5 25.0 24.2 23.7
Defense Purchases 4.1 4.5 4.6 4.7 4.7 4.7 5.2 5.6 5.6 5.5 5.2 4.9
Transfers to Persons 11.8 12.0 11.9 11.8 11.9 12.0 12.9 15.5 15.9 15.3 15.0 14.9
Surplus or Deficit (-) -2.4 -3.4 -3.2 -2.2 -1.5 -1.7 -4.3 -8.7 -8.8 -7.9 -6.6 -4.8
Details of Real GDP (% Ch.)
Real GDP 1.8 2.5 3.5 3.1 2.7 1.9 -0.3 -3.5 3.0 1.8 1.7 2.5
Final Sales 1.3 2.5 3.1 3.2 2.6 2.2 0.1 -2.7 1.4 2.0 1.6 2.4
Consumption 2.7 2.8 3.3 3.4 2.9 2.3 -0.6 -1.9 2.0 2.3 2.0 1.8
Business Fixed Investment -7.9 1.4 6.2 6.7 8.0 6.5 -0.8 -17.9 4.4 9.0 5.8 6.1
Equipment and Software -4.2 3.1 7.9 8.5 7.6 3.3 -4.3 -16.0 14.6 10.6 6.7 7.1
Structures -17.7 -3.8 1.1 1.4 9.2 14.1 6.4 -21.2 -15.8 4.9 3.4 3.3
Residential Construction 5.3 8.2 9.8 6.3 -7.5 -18.9 -24.3 -22.5 -4.6 -2.3 2.9 18.5
Exports -2.0 1.6 9.5 6.8 9.0 9.3 6.1 -9.4 11.3 6.6 3.4 7.7
Imports 3.4 4.4 11.1 6.1 6.1 2.4 -2.7 -13.6 12.5 4.8 2.4 3.2
Federal Purchases 7.3 6.6 4.1 1.3 2.1 1.2 7.2 6.0 4.5 -1.7 -2.9 -3.6
State & Local Purchases 3.3 -0.1 -0.2 -0.2 0.9 1.4 -0.0 -0.9 -1.8 -2.3 -2.6 -0.9
Billions of 2005 Dollars
Real GDP 11543.1 11836.4 12246.9 12622.9 12958.5 13206.4 13161.9 12703.1 13088.0 13317.5 13540.9 13874.5
Final Sales 11530.4 11819.1 12180.6 12573.0 12899.1 13178.7 13198.2 12848.1 13029.2 13291.6 13505.3 13830.8
Inventory Change 12.8 17.3 66.4 49.9 59.4 27.7 -36.3 -145.0 58.8 26.0 35.5 43.6
UCLA Anderson Forecast, December 2011 Nation–63
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Forecast Tables - Summary
Table 2. Summary of the UCLA Anderson Forecast for the Nation
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Industrial Production and Resource Utilization
Industrial Prod. (% Ch.) 0.2 1.3 2.3 3.2 2.2 2.7 -3.7 -11.2 5.3 3.8 2.2 3.6
Capacity Util. Manuf. (%) 72.9 73.9 76.1 78.2 78.6 79.2 74.9 66.2 71.7 74.7 75.8 77.4
Real Bus. Investment
as % of Real GDP 15.5 15.7 16.3 16.8 16.8 16.1 15.0 12.6 12.6 13.2 13.7 14.5
Nonfarm Employment (mil.) 130.3 130.0 131.4 133.7 136.1 137.6 136.8 130.8 129.8 131.1 132.2 134.1
Unemployment Rate (%) 5.8 6.0 5.5 5.1 4.6 4.6 5.8 9.3 9.6 9.1 9.2 9.0
Inflation (% Ch.)
Consumer Price Index 1.6 2.3 2.7 3.4 3.2 2.9 3.8 -0.3 1.6 3.2 1.6 1.9
Total less Food & Energy 2.3 1.5 1.8 2.1 2.5 2.3 2.3 1.7 1.0 1.7 1.7 1.9
Consumption Chain Index 1.4 2.0 2.6 3.0 2.7 2.7 3.3 0.2 1.8 2.5 1.4 1.7
GDP Chain Index 1.6 2.1 2.8 3.3 3.2 2.9 2.2 1.1 1.2 2.1 1.4 1.3
Producers Price Index -2.3 5.3 6.2 7.3 4.7 4.8 9.8 -8.7 6.9 8.5 -0.4 1.9
Factors Related to Inflation (% Ch.)
Nonfarm Business Sector
Wage Compensation 3.2 4.7 3.3 3.9 3.8 4.0 3.4 1.6 2.0 2.7 2.6 3.1
Productivity 4.5 3.7 2.6 1.6 0.9 1.5 0.6 2.3 4.1 1.0 1.2 1.0
Unit Labor Costs -1.3 1.0 0.7 2.3 2.9 2.4 2.8 -0.7 -2.0 1.7 1.3 2.0
Farm Price Index -4.6 12.6 10.5 -3.8 -1.2 22.5 12.4 -16.5 12.2 22.9 -2.6 -4.3
Crude Oil Price ($/bbl) 26.1 31.1 41.5 56.5 66.1 72.3 99.6 61.7 79.4 93.3 96.3 108.7
New Home Price ($1000) 185.0 191.4 217.8 234.2 243.1 243.7 230.4 214.5 221.2 220.9 225.6 229.0
Income, Consumption and Saving (% Ch.)
Disposable Income 4.7 4.6 6.1 4.4 6.9 5.1 5.8 -2.1 3.6 3.7 2.7 2.8
Real Disposable Income 3.3 2.5 3.4 1.4 4.0 2.4 2.4 -2.3 1.8 1.2 1.4 1.1
Real Consumption 2.7 2.8 3.3 3.4 2.9 2.3 -0.6 -1.9 2.0 2.3 2.0 1.8
Savings Rate (%) 3.6 3.5 3.6 1.6 2.6 2.4 5.4 5.2 5.3 4.5 3.9 3.2
Housing and Automobiles--millions of units
Housing Starts 1.710 1.854 1.949 2.073 1.812 1.342 0.900 0.554 0.585 0.597 0.664 0.958
Auto & Light Truck Sales 16.8 16.6 16.9 16.9 16.5 16.1 13.2 10.4 11.6 12.6 13.2 14.5
Corporate Profits
Billions of Dollars
Before Taxes 765.3 903.5 1229.4 1640.2 1822.7 1738.4 1359.9 1455.7 1819.5 1929.6 2042.7 2287.0
After Taxes 573.0 659.7 923.3 1227.8 1349.5 1292.9 1050.9 1183.3 1408.4 1503.5 1569.3 1729.7
Percent Change
Before Taxes 7.4 18.1 36.1 33.4 11.1 -4.6 -21.8 7.0 25.0 6.1 5.9 12.0
After Taxes 12.5 15.1 40.0 33.0 9.9 -4.2 -18.7 12.6 19.0 6.8 4.4 10.2
International Trade Factors
Nominal
U.S. Dollar--% change
Industrial Countries -1.5 -12.3 -8.2 -1.9 -1.5 -5.6 -4.5 4.3 -3.0 -6.1 3.7 -2.3
Developing Countries 3.3 2.3 -0.1 -3.1 -2.5 -3.8 -2.6 7.2 -4.1 -3.6 1.1 -5.2
Exports -2.4 3.8 13.4 10.6 12.7 13.0 11.1 -14.3 16.2 13.6 4.3 8.8
Imports 2.3 8.0 16.4 12.7 10.5 6.0 7.7 -22.8 19.4 13.3 2.6 5.9
Net Exports (bil. $) -427 -504 -619 -723 -769 -713 -710 -392 -517 -579 -559 -529
Real
U.S. Dollar--% change
Industrial Countries -0.4 -12.4 -8.0 -2.4 -2.5 -6.3 -5.1 7.7 -0.7 -7.4 3.4 -2.1
Developing Countries 2.5 -1.6 -4.5 -6.1 -5.1 -7.4 -9.5 6.2 -5.1 -8.1 -4.3 -9.8
Exports -2.0 1.6 9.5 6.8 9.0 9.3 6.1 -9.4 11.3 6.6 3.4 7.7
Imports 3.4 4.4 11.1 6.1 6.1 2.4 -2.7 -13.6 12.5 4.8 2.4 3.2
Net Exports (bil. ‘05$) -548 -604 -688 -723 -729 -649 -495 -359 -422 -412 -405 -337
64–Nation UCLA Anderson Forecast, December 2011
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Forecast Tables - Summary
Table 3. Quarterly Summary of the UCLA National Anderson Forecast for the Nation
2011:2 2011:3 2011:4 2012:1 2012:2 2012:3 2012:4 2013:1 2013:2 2013:3 2013:4
Monetary Aggregates and GDP (% Ch.)
Money Supply (M1) 12.1 37.0 22.2 4.5 3.5 5.4 6.2 6.3 5.9 5.3 4.0
Money Supply (M2) 6.2 21.4 8.0 3.2 2.6 3.1 3.7 4.5 4.8 4.9 4.9
GDP Price Index 2.5 2.5 1.0 1.7 1.0 0.9 1.0 1.7 1.4 1.5 1.6
Real GDP 1.3 2.5 2.0 1.5 1.2 1.5 2.2 2.4 3.1 3.3 3.3
Interest Rates (%) on:
Federal Funds 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.3
90-day Treasury Bills 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.3
10-year Treasury Bonds 3.2 2.4 2.1 2.1 2.3 2.5 2.8 3.0 3.2 3.5 3.8
30-year Treasury Bonds 4.3 3.7 3.0 3.1 3.3 3.4 3.7 3.9 4.1 4.3 4.6
Moody’s Corporate Aaa Bonds 5.0 4.5 3.9 4.1 4.2 4.3 4.6 4.8 5.0 5.2 5.5
30-yr Bond Less Inflation 1.0 1.3 1.9 2.2 2.3 2.1 2.4 1.9 2.2 2.4 2.8
Federal Fiscal Policy
Defense Purchases (% Ch.)
Current $ 11.1 6.6 -3.7 -3.7 -4.6 -3.9 -3.7 -1.5 -2.1 -2.0 -2.0
Constant $ 7.0 4.8 -5.3 -5.5 -5.5 -4.8 -4.8 -4.2 -3.4 -3.3 -3.3
Other Expenditures (% Ch.)
Transfers to Persons 6.0 -9.2 0.4 4.3 2.5 3.0 2.4 4.2 1.9 3.0 3.0
Grants to S&L Gov’t 10.7 -36.8 -11.0 -2.5 1.3 2.9 0.1 0.4 0.2 3.6 3.7
Billions of Current Dollars, Unified Budget Basis, NSA
Receipts 714.1 568.5 561.9 534.9 803.3 635.0 614.9 609.0 884.3 715.0 686.2
Outlays 855.2 896.6 895.6 933.5 880.2 885.5 903.9 935.1 891.0 899.2 919.6
Surplus or Deficit (-) -141.1 -328.1 -333.7 -398.6 -76.9 -250.4 -289.0 -326.1 -6.7 -184.2 -233.3
As Shares of GDP (%), NIPA Basis
Revenues 17.1 17.1 17.0 17.4 17.5 17.6 17.8 18.8 18.9 18.9 18.8
Expenditures 25.5 24.6 24.6 24.4 24.3 24.2 24.0 23.9 23.8 23.6 23.4
Defense Purchases 5.5 5.6 5.5 5.4 5.3 5.2 5.1 5.0 5.0 4.9 4.8
Transfers to Persons 15.6 15.1 15.0 15.0 15.0 15.1 15.0 15.0 14.9 14.9 14.8
Surplus or Deficit (-) -8.4 -7.6 -7.6 -7.0 -6.8 -6.6 -6.2 -5.2 -4.9 -4.7 -4.6
Details of Real GDP (% Ch.)
Real GDP 1.3 2.5 2.0 1.5 1.2 1.5 2.2 2.4 3.1 3.3 3.3
Final Sales 1.6 3.5 1.8 0.9 1.0 1.4 2.2 2.5 3.0 3.1 3.1
Consumption 0.7 2.4 2.1 2.0 2.2 2.1 2.1 1.6 1.5 1.6 1.3
Business Fixed Investment 10.3 16.3 7.3 2.8 3.3 1.4 6.5 3.8 9.4 9.4 9.3
Equipment and Software 6.2 17.4 7.7 2.4 5.3 5.5 8.9 4.0 9.3 9.2 8.0
Structures 22.6 13.3 6.4 3.9 -2.2 -9.0 0.1 3.3 9.6 10.0 13.2
Residential Construction 4.2 2.5 -4.7 1.1 5.0 11.7 9.4 15.8 27.4 32.9 29.1
Exports 3.6 4.0 2.9 2.5 2.6 4.8 6.9 9.3 8.9 8.2 9.3
Imports 1.4 1.9 0.3 2.8 3.9 3.2 3.7 1.9 3.8 4.1 3.6
Federal Purchases 1.9 2.0 -3.1 -4.4 -4.4 -3.9 -3.9 -3.7 -3.2 -3.1 -3.1
State & Local Purchases -2.8 -1.3 -3.4 -2.8 -3.0 -1.8 -1.6 -0.8 0.1 -0.1 0.3
Billions of 2005 Dollars
Real GDP 13271.8 13352.8 13417.6 13467.5 13507.3 13557.8 13630.9 13711.1 13815.7 13928.6 14042.5
Final Sales 13232.7 13347.4 13407.4 13437.9 13471.2 13519.7 13592.5 13675.4 13776.6 13882.3 13989.0
Inventory Change 39.1 5.4 10.3 29.6 36.1 38.1 38.4 35.7 39.1 46.2 53.5
UCLA Anderson Forecast, December 2011 Nation–65
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Forecast Tables - Summary
Table 4. Quarterly Summary of The UCLA National Anderson Forecast for the Nation
2011:2 2011:3 2011:4 2012:1 2012:2 2012:3 2012:4 2013:1 2013:2 2013:3 2013:4
Industrial Production and Resource Utilization
Production--% change 0.5 5.1 1.1 1.5 2.1 3.3 2.5 3.8 4.4 4.6 4.2
Capacity Util. Manuf. (%) 74.3 74.9 75.1 75.3 75.6 75.9 76.3 76.5 77.1 77.7 78.3
Real Bus. Investment
as % of Real GDP 13.1 13.4 13.5 13.6 13.6 13.7 13.9 14.0 14.3 14.6 15.0
Nonfarm Employment (mil.) 131.0 131.2 131.5 131.7 132.0 132.4 132.7 133.2 133.7 134.4 135.0
Unemployment Rate (%) 9.1 9.1 9.1 9.2 9.2 9.2 9.2 9.2 9.1 8.9 8.8
Inflation--% change
Consumer Price Index 4.1 3.1 1.8 0.8 1.1 1.5 1.4 2.3 2.1 2.1 2.0
Total less Food & Energy 2.5 2.7 1.6 1.4 1.5 1.6 1.7 2.0 2.1 2.2 2.2
Consumption Deflator 3.3 2.4 1.2 0.8 1.0 1.3 1.2 2.0 1.9 1.9 1.9
GDP Deflator 2.5 2.5 1.0 1.7 1.0 0.9 1.0 1.7 1.4 1.5 1.6
Producers Price Index 6.7 -2.5 -0.4 -2.5 0.4 0.3 1.8 3.9 1.5 1.0 2.3
Factors Related to Inflation--%change
Nonfarm Business Sector
Wage Compensation 2.7 2.1 1.2 3.4 2.7 2.8 2.9 3.3 3.2 3.1 3.3
Productivity -0.7 3.7 1.6 1.2 0.5 0.5 1.2 0.9 1.4 1.4 1.3
Unit Labor Costs 3.3 -1.5 -0.4 2.2 2.3 2.3 1.7 2.4 1.8 1.7 2.0
Farm Price Index 7.8 7.7 -13.0 -0.8 -2.1 -4.2 -4.4 -4.5 -4.5 -4.5 -4.5
Crude Oil Price ($/bbl) 102.6 89.7 87.1 90.4 98.1 97.7 99.0 109.3 110.3 110.4 104.8
New Home Price ($1000) 229.0 215.4 212.3 231.5 229.1 225.5 216.5 232.5 229.5 227.2 226.7
Income, Consumption and Saving--%change
Disposable Income 3.9 0.6 2.5 3.7 3.1 2.5 2.6 1.4 3.5 4.1 5.0
Real Disposable Income 0.6 -1.7 1.3 2.8 2.0 1.2 1.4 -0.6 1.6 2.2 3.1
Real Consumption 0.7 2.4 2.1 2.0 2.2 2.1 2.1 1.6 1.5 1.6 1.3
Savings Rate (%) 5.1 4.1 3.9 4.1 4.0 3.8 3.6 3.1 3.1 3.2 3.6
Housing and Automobiles--millions of units
Housing Starts 0.572 0.615 0.618 0.617 0.640 0.676 0.721 0.795 0.911 1.017 1.108
Auto and Light Truck Sales 12.1 12.4 13.0 12.8 13.0 13.2 13.6 14.1 14.5 14.7 14.7
Corporate Profits
Billions of Dollars
Before Taxes 1890.6 1992.8 1957.9 2048.4 2029.2 2030.5 2062.7 2261.1 2279.1 2292.0 2315.9
After Taxes 1470.1 1558.0 1531.0 1570.2 1557.1 1561.2 1588.7 1708.3 1724.7 1733.4 1752.4
Percent Change
Before Taxes 2.9 23.4 -6.8 19.8 -3.7 0.2 6.5 44.4 3.2 2.3 4.2
After Taxes 4.3 26.1 -6.8 10.6 -3.3 1.1 7.2 33.7 3.9 2.0 4.5
International Trade
Nominal
U.S. Dollar--% change
Industrial Countries -12.2 1.0 12.0 8.2 4.6 -3.1 -3.1 -3.0 -2.9 -2.0 -0.8
Developing Countries -7.9 3.8 16.5 2.3 -4.4 -8.4 -5.6 -4.2 -5.3 -4.3 -3.0
Exports--% change 12.7 6.2 3.7 1.7 2.7 5.1 7.8 11.0 10.2 9.5 10.6
Imports--% change 14.1 1.1 3.1 -2.2 3.3 5.0 6.2 4.8 7.5 7.5 6.4
Net Exports (bil. $) -597.1 -572.8 -574.0 -549.8 -557.5 -563.7 -563.9 -537.6 -532.5 -531.1 -515.5
Real
U.S. Dollar--% change
Industrial Countries -14.0 -0.4 11.4 8.5 5.2 -3.5 -3.3 -2.9 -2.5 -1.3 -0.1
Developing Countries -12.6 -2.4 9.8 -2.8 -9.4 -13.2 -10.4 -9.0 -9.7 -8.4 -7.0
Exports--% change 3.6 4.0 2.9 2.5 2.6 4.8 6.9 9.3 8.9 8.2 9.3
Imports--% change 1.4 1.9 0.3 2.8 3.9 3.2 3.7 1.9 3.8 4.1 3.6
Net Exports (bil. ‘05$) -416.4 -409.4 -398.3 -402.3 -411.7 -408.0 -397.5 -366.1 -346.3 -330.4 -306.3
66–Nation UCLA Anderson Forecast, December 2011
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Forecast Tables - Detailed
Table 5. Part A. Gross Domestic Product
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Billions of Current Dollars
Gross Domestic Product 10642.3 11142.2 11853.3 12623.0 13377.2 14028.7 14291.6 13938.9 14526.6 15096.8 15568.3 16164.6
Personal Consumption
Expenditures 7439.2 7804.1 8270.6 8803.5 9301.0 9772.3 10035.5 9866.1 10245.5 10735.5 11100.9 11481.8
Durable Goods 992.1 1019.9 1072.9 1123.4 1155.0 1188.4 1108.9 1029.6 1085.5 1156.3 1198.4 1253.3
Autos and Parts 401.3 401.0 403.9 408.2 394.8 399.9 339.3 316.5 340.1 371.9 388.8 419.5
Nondurable Goods 1617.9 1708.1 1819.3 1953.4 2069.8 2175.5 2272.8 2167.8 2301.5 2487.3 2563.5 2645.7
Services 4829.2 5076.1 5378.5 5726.8 6076.3 6408.3 6653.8 6668.7 6858.5 7091.9 7339.0 7582.8
Gross Private Domestic
Investment 1647.0 1729.7 1968.6 2172.3 2327.2 2295.2 2087.6 1546.8 1795.1 1905.2 2022.2 2215.0
Residential 509.5 577.6 680.6 775.0 761.9 628.7 472.4 354.6 338.1 334.4 348.4 421.9
Nonres. Structures 282.8 281.9 306.7 351.8 433.7 524.9 586.3 449.9 374.4 409.9 429.5 448.5
Producers Dur. Equip. 842.7 853.8 916.4 995.6 1071.7 1112.6 1070.0 903.0 1015.7 1125.6 1201.9 1293.3
Change In Inv. 12.0 16.4 64.9 50.0 60.0 29.1 -41.1 -160.8 67.0 35.2 42.4 51.2
Net Exports -427.2 -504.1 -618.7 -722.7 -769.3 -713.1 -709.8 -391.5 -516.9 -578.8 -558.7 -529.2
Exports 1003.0 1041.0 1180.2 1305.1 1471.1 1661.7 1846.8 1583.1 1839.8 2090.6 2179.8 2371.2
Imports 1430.2 1545.2 1798.9 2027.8 2240.4 2374.8 2556.5 1974.6 2356.7 2669.4 2738.5 2900.4
Government Purchases 1983.4 2112.6 2232.8 2369.9 2518.4 2674.3 2878.1 2917.5 3002.8 3034.9 3003.9 2997.0
Federal 680.7 756.5 824.7 876.3 931.7 976.4 1080.1 1142.7 1222.9 1237.3 1220.4 1194.5
Defense 437.7 498.0 550.8 589.1 624.9 662.3 737.8 774.9 819.2 829.9 815.0 793.6
Other 243.0 258.6 273.9 287.3 306.9 314.1 342.3 367.8 403.7 407.5 405.4 400.9
State and Local 1302.7 1356.1 1408.2 1493.6 1586.7 1697.9 1798.0 1774.8 1780.0 1797.6 1783.6 1802.5
Billions of 2005 Dollars
Gross Domestic Product 11543.1 11836.4 12246.9 12622.9 12958.5 13206.4 13161.9 12703.1 13088.0 13317.5 13540.9 13874.5
Personal Consumption
Expenditures 8018.3 8244.5 8515.8 8803.5 9054.5 9262.9 9211.7 9037.5 9220.9 9429.2 9619.5 9788.0
Durable Goods 927.9 989.1 1060.9 1123.4 1174.2 1232.4 1171.8 1108.3 1188.3 1278.0 1340.8 1406.3
Autos & Parts 394.0 404.8 410.4 408.2 394.4 401.4 346.8 322.5 330.1 350.2 362.8 387.3
Nondurable Goods 1780.1 1840.7 1892.8 1953.4 2005.0 2042.9 2019.1 1983.4 2041.3 2078.8 2115.7 2148.2
Services 5318.5 5418.2 5562.7 5726.8 5875.6 5990.1 6017.0 5935.5 5991.8 6086.4 6186.4 6267.9
Gross Private Domestic
Investment 1800.4 1870.1 2058.2 2172.3 2231.8 2159.5 1939.8 1454.2 1714.9 1787.8 1893.1 2054.3
Residential 613.9 664.3 729.5 775.0 718.2 584.2 444.4 345.6 330.8 323.6 333.3 393.7
Nonres. Structures 356.6 343.0 346.7 351.8 384.0 438.2 466.4 367.3 309.1 324.3 335.2 346.3
Equipment & Software 824.2 850.0 917.3 995.6 1071.1 1106.8 1059.4 889.7 1019.4 1127.3 1203.0 1287.9
Change In Inv. 12.8 17.3 66.4 49.9 59.4 27.7 -36.3 -145.0 58.8 26.0 35.5 43.6
Net Exports -548.5 -603.7 -687.9 -722.7 -729.4 -648.8 -494.8 -358.8 -421.8 -412.1 -404.9 -337.3
Exports 1098.3 1116.0 1222.6 1305.1 1422.1 1554.4 1649.3 1494.0 1663.2 1773.0 1833.5 1973.9
Imports 1646.8 1719.7 1910.4 2027.8 2151.5 2203.3 2144.0 1852.9 2085.0 2185.1 2238.4 2311.2
Government Purchases 2279.6 2330.4 2362.0 2369.9 2402.1 2434.2 2497.4 2539.6 2556.8 2504.5 2437.2 2388.7
Federal 779.5 831.1 865.0 876.3 894.9 906.1 971.1 1029.5 1075.9 1057.6 1027.1 990.0
Defense 505.3 549.3 580.4 589.1 598.4 611.8 657.7 695.6 718.3 704.7 681.3 653.0
Other 274.0 281.7 284.6 287.3 296.6 294.2 313.4 333.8 357.7 352.8 345.9 337.2
State and Local 1500.7 1499.7 1497.1 1493.6 1507.2 1528.1 1528.1 1514.2 1487.0 1453.1 1416.1 1403.5
UCLA Anderson Forecast, December 2011 Nation–67
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Forecast Tables - Detailed
Table 5. Part B. Gross Domestic Product
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Annual Rates of Change of Current Dollar GDP Components (%)
Gross Domestic Product 3.5 4.7 6.4 6.5 6.0 4.9 1.9 -2.5 4.2 3.9 3.1 3.8
Personal Consumption
Expenditures 4.1 4.9 6.0 6.4 5.7 5.1 2.7 -1.7 3.8 4.8 3.4 3.4
Durable Goods 4.8 2.8 5.2 4.7 2.8 2.9 -6.7 -7.1 5.4 6.5 3.6 4.6
Autos and Parts 4.7 -0.1 0.7 1.1 -3.3 1.3 -15.2 -6.7 7.4 9.3 4.5 7.9
Nondurable Goods 1.9 5.6 6.5 7.4 6.0 5.1 4.5 -4.6 6.2 8.1 3.1 3.2
Services 4.6 5.1 6.0 6.5 6.1 5.5 3.8 0.2 2.8 3.4 3.5 3.3
Gross Private Domestic
Investment -0.9 5.0 13.8 10.3 7.1 -1.4 -9.0 -25.9 16.1 6.1 6.1 9.5
Residential 7.9 13.4 17.8 13.9 -1.7 -17.5 -24.9 -24.9 -4.7 -1.1 4.2 21.1
Nonres. Structures -14.2 -0.3 8.8 14.7 23.3 21.0 11.7 -23.3 -16.8 9.5 4.8 4.4
Producers Dur. Equip. -6.2 1.3 7.3 8.6 7.6 3.8 -3.8 -15.6 12.5 10.8 6.8 7.6
Exports -2.4 3.8 13.4 10.6 12.7 13.0 11.1 -14.3 16.2 13.6 4.3 8.8
Imports 2.3 8.0 16.4 12.7 10.5 6.0 7.7 -22.8 19.4 13.3 2.6 5.9
Government Purchases 7.4 6.5 5.7 6.1 6.3 6.2 7.6 1.4 2.9 1.1 -1.0 -0.2
Federal 11.3 11.1 9.0 6.3 6.3 4.8 10.6 5.8 7.0 1.2 -1.4 -2.1
Defense 11.4 13.8 10.6 6.9 6.1 6.0 11.4 5.0 5.7 1.3 -1.8 -2.6
Other 11.1 6.4 5.9 4.9 6.8 2.3 9.0 7.5 9.7 0.9 -0.5 -1.1
State and Local 5.5 4.1 3.8 6.1 6.2 7.0 5.9 -1.3 0.3 1.0 -0.8 1.1
Annual Rates of Change of Constant Dollar GDP Components (%)
Gross Domestic Product 1.8 2.5 3.5 3.1 2.7 1.9 -0.3 -3.5 3.0 1.8 1.7 2.5
Personal Consumption
Expenditures 2.7 2.8 3.3 3.4 2.9 2.3 -0.6 -1.9 2.0 2.3 2.0 1.8
Durable Goods 7.6 6.6 7.3 5.9 4.5 5.0 -4.9 -5.4 7.2 7.5 4.9 4.9
Autos & Parts 5.3 2.7 1.4 -0.5 -3.4 1.8 -13.6 -7.0 2.3 6.1 3.6 6.8
Nondurable Goods 2.0 3.4 2.8 3.2 2.6 1.9 -1.2 -1.8 2.9 1.8 1.8 1.5
Services 1.9 1.9 2.7 3.0 2.6 1.9 0.4 -1.4 0.9 1.6 1.6 1.3
Gross Private Domestic
Investment -1.4 3.9 10.1 5.5 2.7 -3.2 -10.2 -25.0 17.9 4.2 5.9 8.5
Residential 5.3 8.2 9.8 6.2 -7.3 -18.7 -23.9 -22.2 -4.3 -2.2 3.0 18.1
Nonres. Structures -17.7 -3.8 1.1 1.4 9.2 14.1 6.4 -21.2 -15.8 4.9 3.4 3.3
Equipment & Software -4.2 3.1 7.9 8.5 7.6 3.3 -4.3 -16.0 14.6 10.6 6.7 7.1
Exports -2.0 1.6 9.5 6.8 9.0 9.3 6.1 -9.4 11.3 6.6 3.4 7.7
Imports 3.4 4.4 11.1 6.1 6.1 2.4 -2.7 -13.6 12.5 4.8 2.4 3.2
Government Purchases 4.7 2.2 1.4 0.3 1.4 1.3 2.6 1.7 0.7 -2.0 -2.7 -2.0
Federal 7.3 6.6 4.1 1.3 2.1 1.2 7.2 6.0 4.5 -1.7 -2.9 -3.6
Defense 7.4 8.7 5.7 1.5 1.6 2.2 7.5 5.8 3.3 -1.9 -3.3 -4.1
Other 7.2 2.8 1.0 0.9 3.2 -0.8 6.5 6.5 7.1 -1.3 -2.0 -2.5
State and Local 3.3 -0.1 -0.2 -0.2 0.9 1.4 -0.0 -0.9 -1.8 -2.3 -2.6 -0.9
68–Nation UCLA Anderson Forecast, December 2011
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Forecast Tables - Detailed
Table 6. Employment
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Employment (Millions)
Total 136.5 137.7 139.2 141.7 144.4 146.0 145.4 139.9 139.1 139.7 140.0 141.3
Nonagricultural 130.3 130.0 131.4 133.7 136.1 137.6 136.8 130.8 129.8 131.1 132.2 134.1
Natural Res. & Mining 0.6 0.6 0.6 0.6 0.7 0.7 0.8 0.7 0.7 0.8 0.8 0.8
Construction 6.7 6.7 7.0 7.3 7.7 7.6 7.2 6.0 5.5 5.5 5.4 5.4
Manufacturing 15.3 14.5 14.3 14.2 14.2 13.9 13.4 11.8 11.5 11.7 11.9 12.0
Trans. Warehous. Util 4.8 4.8 4.8 4.9 5.0 5.1 5.1 4.8 4.7 4.8 4.9 5.1
Trade 20.7 20.5 20.7 21.0 21.3 21.5 21.2 20.1 19.9 20.1 20.4 20.7
Financial Activities 7.8 8.0 8.0 8.2 8.3 8.3 8.1 7.8 7.6 7.6 7.6 7.7
Information 3.4 3.2 3.1 3.1 3.0 3.0 3.0 2.8 2.7 2.7 2.6 2.7
Professional & Busi. 16.0 16.0 16.4 17.0 17.6 17.9 17.7 16.6 16.7 17.2 17.5 18.2
Education & Health 16.2 16.6 16.9 17.4 17.8 18.3 18.8 19.2 19.6 20.0 20.4 20.7
Leisure & Hospitality 12.0 12.2 12.5 12.8 13.1 13.4 13.4 13.1 13.0 13.2 13.5 13.6
Other Services 5.4 5.4 5.4 5.4 5.4 5.5 5.5 5.4 5.4 5.4 5.5 5.5
Government 21.5 21.6 21.6 21.8 22.0 22.2 22.5 22.6 22.5 22.1 21.8 21.7
Federal 2.8 2.8 2.7 2.7 2.7 2.7 2.8 2.8 3.0 2.8 2.8 2.7
State & Local 18.7 18.8 18.9 19.1 19.2 19.5 19.7 19.7 19.5 19.2 19.0 19.0
Population and Labor Force (Millions)
Population aged 16+ 223.6 226.1 228.6 231.2 234.0 236.8 239.4 241.8 244.3 246.8 249.3 251.7
Labor Force 145.1 146.5 147.4 149.3 151.4 153.1 154.3 154.2 153.9 153.6 154.2 155.2
Unemployment (%) 5.8 6.0 5.5 5.1 4.6 4.6 5.8 9.3 9.6 9.1 9.2 9.0
Table 7. Personal Income and Its Disposition
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Billions of Current Dollars
Personal Income 9060.1 9378.2 9937.3 10485.9 11268.1 11912.3 12460.2 11930.2 12373.5 12989.0 13402.6 13898.9
Wages & Salaries 4997.3 5139.6 5425.7 5701.0 6068.9 6421.7 6550.9 6270.4 6408.2 6663.7 6861.9 7140.5
Other Labor Income 747.4 845.6 874.6 931.6 960.2 980.5 1052.4 1073.1 1090.0 1110.7 1148.3 1205.3
Nonfarm Income 871.9 894.1 984.1 1025.9 1103.6 1052.6 1046.1 902.1 984.2 1045.5 1091.3 1147.3
Farm Income 18.5 36.5 49.7 43.9 29.4 37.8 51.8 39.2 52.2 66.5 70.2 69.4
Rental Income 218.8 204.2 198.4 178.2 146.5 143.7 231.6 305.9 350.2 402.6 411.4 369.9
Dividends 397.7 423.1 548.3 555.0 702.2 791.9 783.4 598.8 717.7 791.4 868.1 923.8
Interest Income 911.9 889.8 860.2 987.0 1127.5 1265.1 1382.0 1108.9 1003.4 995.2 984.0 1030.8
Transfer Payments 1282.2 1341.8 1415.5 1508.6 1605.0 1718.5 1879.2 2138.1 2281.2 2340.1 2418.9 2513.8
Personal Contributions
For Social Insurance 385.3 396.5 419.2 445.2 475.1 499.6 517.2 506.1 513.6 426.7 451.6 501.9
Personal Tax and Nontax
Payments 1050.4 1000.3 1047.8 1208.6 1352.4 1488.7 1435.7 1141.4 1193.9 1398.9 1494.9 1656.1
Disposable Income 8009.7 8377.8 8889.4 9277.3 9915.7 10423.6 11024.5 10788.8 11179.7 11590.1 11907.7 12242.8
Consumption 7439.2 7804.1 8270.6 8803.5 9301.0 9772.3 10035.5 9866.1 10245.5 10735.5 11100.9 11481.8
Interest 191.3 182.7 190.3 210.8 230.1 260.9 245.6 213.7 173.4 159.3 162.3 170.6
Transfers To Foreigners 40.6 41.2 43.6 48.4 51.6 59.4 66.2 67.4 72.9 73.9 76.2 80.2
Personal Saving 282.2 289.7 318.3 143.2 256.6 248.7 592.3 552.5 592.8 523.6 464.2 397.7
Personal Saving Rate(%) 3.6 3.5 3.6 1.6 2.6 2.4 5.4 5.2 5.3 4.5 3.9 3.2
UCLA Anderson Forecast, December 2011 Nation–69
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Forecast Tables - Detailed
Table 8. Personal Consumption Expenditures By Major Types
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Billions of Current Dollars
Personal Consumption 7439.2 7804.1 8270.6 8803.5 9301.0 9772.3 10035.5 9866.1 10245.5 10735.5 11100.9 11481.8
Durable Goods 992.1 1019.9 1072.9 1123.4 1155.0 1188.4 1108.9 1029.6 1085.5 1156.3 1198.4 1253.3
Autos and Parts 401.3 401.0 403.9 408.2 394.8 399.9 339.3 316.5 340.1 371.9 388.8 419.5
Nondurable Goods 1617.9 1708.1 1819.3 1953.4 2069.8 2175.5 2272.8 2167.8 2301.5 2487.3 2563.5 2645.7
Services 4829.2 5076.1 5378.5 5726.8 6076.3 6408.3 6653.8 6668.7 6858.5 7091.9 7339.0 7582.8
Billions of 2005 Dollars
Personal Consumption 8018.3 8244.5 8515.8 8803.5 9054.5 9262.9 9211.7 9037.5 9220.9 9429.2 9619.5 9788.0
Durable Goods 927.9 989.1 1060.9 1123.4 1174.2 1232.4 1171.8 1108.3 1188.3 1278.0 1340.8 1406.3
Autos and Parts 394.0 404.8 410.4 408.2 394.4 401.4 346.8 322.5 330.1 350.2 362.8 387.3
Nondurable Goods 1780.1 1840.7 1892.8 1953.4 2005.0 2042.9 2019.1 1983.4 2041.3 2078.8 2115.7 2148.2
Services 5318.5 5418.2 5562.7 5726.8 5875.6 5990.1 6017.0 5935.5 5991.8 6086.4 6186.4 6267.9
Annual Rates of Real Growth
Personal Consumption 2.7 2.8 3.3 3.4 2.9 2.3 -0.6 -1.9 2.0 2.3 2.0 1.8
Durable Goods 7.6 6.6 7.3 5.9 4.5 5.0 -4.9 -5.4 7.2 7.5 4.9 4.9
Autos and Parts 5.3 2.7 1.4 -0.5 -3.4 1.8 -13.6 -7.0 2.3 6.1 3.6 6.8
Furniture 7.3 5.6 7.9 5.7 4.3 0.7 -4.2 -8.4 8.1 5.0 3.0 2.9
Other Durables 6.6 8.9 8.7 8.9 7.7 4.7 -3.3 -5.0 6.1 6.3 3.5 1.4
Nondurable Goods 2.0 3.4 2.8 3.2 2.6 1.9 -1.2 -1.8 2.9 1.8 1.8 1.5
Food and Beverages 0.2 1.2 1.2 3.3 2.9 1.5 -1.1 -1.3 2.4 1.5 1.5 2.6
Gasoline and Oil 1.5 3.3 2.1 0.6 -1.7 -0.7 -4.1 -0.8 0.4 -2.9 2.9 1.2
Fuel
Clothing and Shoes 3.1 5.2 4.7 6.1 4.7 3.5 -0.6 -4.7 5.8 3.0 1.9 0.3
Other Nondurables 3.3 4.9 4.1 3.4 3.8 2.8 0.3 -1.9 3.4 4.1 1.5 1.3
Services 1.9 1.9 2.7 3.0 2.6 1.9 0.4 -1.4 0.9 1.6 1.6 1.3
Housing 0.5 1.1 2.5 5.1 2.9 0.4 1.1 1.1 0.5 0.3 0.4 0.3
Transportation Serv. -2.7 0.4 2.5 0.8 -0.2 0.9 -5.5 -8.8 0.8 0.5 2.5 2.4
Health Care 5.9 2.2 3.2 3.3 1.8 2.3 2.4 1.9 1.4 2.9 2.4 1.6
Recreational Service 0.6 3.2 5.2 1.9 3.6 3.9 -1.3 -3.9 2.0 2.7 3.3 0.6
Food Svcs. Accom. 1.6 3.7 4.1 3.7 3.3 1.3 -0.9 -3.5 3.1 3.8 1.8 0.8
Financial Services -0.4 0.0 2.5 3.4 2.6 3.3 -1.0 -7.7 -1.2 1.7 2.2 2.9
Other Services 0.5 2.7 1.5 0.8 2.1 2.3 -1.8 -1.3 -0.0 0.3 1.5 1.7
Table 9. Residential Construction and Housing Starts
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Housing Starts (Millions of Units)
Housing Starts 1.710 1.854 1.949 2.073 1.812 1.342 0.900 0.554 0.585 0.597 0.664 0.958
Single-family 1.363 1.505 1.604 1.719 1.474 1.036 0.616 0.442 0.471 0.422 0.431 0.655
Multi-family 0.347 0.349 0.345 0.354 0.338 0.306 0.284 0.112 0.114 0.175 0.233 0.303
Residential Construction Expenditures (Billions of Dollars)
Current Dollars 509.5 577.6 680.6 775.0 761.9 628.7 472.4 354.6 338.1 334.4 348.4 421.9
2005 Dollars 613.9 664.3 729.5 775.0 718.2 584.2 444.4 345.6 330.8 323.6 333.3 393.7
% Change 5.3 8.2 9.8 6.2 -7.3 -18.7 -23.9 -22.2 -4.3 -2.2 3.0 18.1
Related Concepts
Treas. Bill Rate 1.60 1.01 1.37 3.15 4.73 4.35 1.37 0.15 0.14 0.06 0.06 0.16
Conventional 30-year
Mortgage Rate 6.54 5.82 5.84 5.87 6.41 6.34 6.04 5.04 4.69 4.44 4.09 4.87
Median Sales Price of
New Homes (Thous $) 185.0 191.4 217.8 234.2 243.1 243.7 230.4 214.5 221.2 220.9 225.6 229.0
Real Disp. Income 8009.7 8377.8 8889.4 9277.3 9915.7 10423.6 11024.5 10788.8 11179.7 11590.1 11907.7 12242.8
% Change 3.3 2.5 3.4 1.4 4.0 2.4 2.4 -2.3 1.8 1.2 1.4 1.1
70–Nation UCLA Anderson Forecast, December 2011
EMBARGOED: DO NOT RELEASE UNTIL 1AM, DECEMBER 7, 2011 PST
Forecast Tables - Detailed
Table 10. Business Fixed Investment and Inventories
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Billions of Current Dollars
Business Fixed Investment 1125.4 1135.7 1223.0 1347.3 1505.3 1637.5 1656.3 1353.0 1390.1 1535.6 1631.4 1741.9
Equipment & Software 842.7 853.8 916.4 995.6 1071.7 1112.6 1070.0 903.0 1015.7 1125.6 1201.9 1293.3
Nonresidential Structures 282.8 281.9 306.7 351.8 433.7 524.9 586.3 449.9 374.4 409.9 429.5 448.5
Buildings 188.1 182.1 196.7 212.9 247.6 297.3 322.0 253.9 174.8 165.1 179.2 203.3
Commercial 99.8 94.6 104.3 112.9 128.4 150.8 149.1 95.5 64.5 64.7 72.4 82.2
Industrial 22.7 21.4 23.7 29.9 35.1 43.7 57.4 61.2 40.8 37.0 40.7 46.3
Other Buildings 65.6 66.0 68.7 70.2 84.1 102.8 115.6 97.1 69.5 63.4 66.1 74.7
Utilities 56.3 53.5 48.6 51.4 61.1 85.6 99.5 98.6 89.4 98.4 93.7 89.7
Mining Exploration 30.2 38.4 51.9 77.1 114.2 130.9 151.7 87.9 100.9 136.5 146.6 146.0
Other 8.1 7.8 9.4 10.4 10.7 11.0 13.1 9.5 9.4 9.9 9.9 9.5
Billions of 2005 Dollars
Business Fixed Investment 1173.7 1189.6 1263.0 1347.3 1455.5 1549.9 1537.7 1263.2 1319.2 1438.3 1521.9 1614.3
Equipment & Software 824.2 850.0 917.3 995.6 1071.1 1106.8 1059.4 889.7 1019.4 1127.3 1203.0 1287.9
Nonresidential Structures 356.6 343.0 346.7 351.8 384.0 438.2 466.4 367.3 309.1 324.3 335.2 346.3
Buildings 222.3 210.0 213.9 212.9 229.2 260.5 272.0 214.1 151.8 141.0 148.1 160.9
Commercial 119.5 110.3 114.4 112.9 118.4 131.2 124.5 78.4 54.4 53.5 57.9 63.0
Industrial 26.2 24.3 25.5 29.9 33.0 39.0 48.6 50.8 34.6 30.8 32.8 35.7
Other Buildings 76.6 75.4 74.1 70.2 77.9 90.3 99.3 85.7 63.5 57.1 57.8 62.6
Utilities 66.0 61.3 52.1 51.4 56.2 75.6 82.5 82.4 71.9 75.4 71.3 67.5
Mining Exploration 52.6 60.0 69.9 77.1 88.3 93.6 101.5 65.8 76.7 95.9 103.5 106.4
Other 9.3 8.7 10.1 10.4 10.1 9.9 11.6 8.7 9.0 9.5 9.3 8.6
Percent Change in Real Business Fixed Investment
Business Fixed Investment -7.9 1.4 6.2 6.7 8.0 6.5 -0.8 -17.9 4.4 9.0 5.8 6.1
Equipment & Software -4.2 3.1 7.9 8.5 7.6 3.3 -4.3 -16.0 14.6 10.6 6.7 7.1
Nonresidential Structures -17.7 -3.8 1.1 1.4 9.2 14.1 6.4 -21.2 -15.8 4.9 3.4 3.3
Buildings -19.0 -5.5 1.9 -0.5 7.7 13.6 4.4 -21.3 -29.1 -7.2 5.1 8.7
Commercial -19.5 -7.7 3.7 -1.3 4.9 10.8 -5.2 -37.0 -30.6 -1.6 8.1 8.9
Industrial -41.6 -7.3 4.9 17.3 10.3 18.2 24.8 4.5 -31.8 -10.9 6.3 8.9
Other Buildings -5.4 -1.6 -1.7 -5.4 11.0 15.9 9.9 -13.7 -25.8 -10.1 1.2 8.3
Utilities -1.6 -7.2 -15.0 -1.4 9.5 34.4 9.1 -0.0 -12.8 4.9 -5.4 -5.3
Mining Exploration -26.9 14.1 16.4 10.3 14.5 6.1 8.4 -35.2 16.6 25.0 7.9 2.8
Other -35.3 -5.9 15.5 3.4 -2.9 -1.8 17.1 -24.7 2.6 6.0 -1.7 -7.6
Related Concepts
Annual Growth-Price Deflator For:
Producers Dur. Equip. -2.0 -1.8 -0.5 0.1 0.0 0.5 0.5 0.5 -1.8 0.2 0.1 0.5
Structures 4.2 3.6 7.6 13.1 12.9 6.1 4.9 -2.6 -1.1 4.3 1.4 1.1
Moody’s AAA Rate(%) 6.5 5.7 5.6 5.2 5.6 5.6 5.6 5.3 4.9 4.6 4.3 5.1
Capacity Utilization in
Manufacturing(%) 72.9 73.9 76.1 78.2 78.6 79.2 74.9 66.2 71.7 74.7 75.8 77.4
Final Sales(Bil. 2005 $) 11530.4 11819.1 12180.6 12573.0 12899.1 13178.7 13198.2 12848.1 13029.2 13291.6 13505.3 13830.8
Change in Business Inventories
Current Dollars 12.0 16.4 64.9 50.0 60.0 29.1 -41.1 -160.8 67.0 35.2 42.4 51.2
2005 Dollars 12.8 17.3 66.4 49.9 59.4 27.7 -36.3 -145.0 58.8 26.0 35.5 43.6
UCLA Anderson Forecast, December 2011 Nation–71
EMBARGOED: DO NOT RELEASE UNTIL 1AM, DECEMBER 7, 2011 PST
Forecast Tables - Detailed
Table 11. Federal Government Receipts and Expenditures
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Billions of Current Dollars
Unified Budget Basis, Fiscal Year
Receipts 1853.2 1782.1 1879.8 2153.4 2406.7 2567.7 2523.6 2104.4 2161.7 2302.5 2535.1 2823.3
Outlays 2011.0 2159.2 2292.6 2472.1 2654.9 2729.2 2978.4 3520.1 3455.9 3601.1 3594.7 3629.3
Surplus or Deficit (-) -157.8 -377.1 -412.8 -318.7 -248.2 -161.5 -454.8 -1415.7 -1294.2 -1298.6 -1059.7 -806.0
National Income & Products Accounts Basis, Calendar Year
Current Receipts 1859.3 1885.1 2014.0 2290.1 2524.5 2654.7 2502.3 2232.5 2429.6 2571.7 2740.4 3041.5
Current Tax Receipts 1073.5 1070.3 1153.8 1383.7 1558.3 1637.6 1447.7 1170.2 1340.7 1544.4 1675.4 1907.9
Personal Current Taxes 828.6 774.2 799.2 931.9 1049.9 1165.6 1101.3 856.6 896.4 1071.9 1157.6 1308.2
Taxes - Corporate Income 150.5 197.8 250.3 341.0 395.0 362.8 233.6 201.7 329.6 346.4 388.6 462.4
Taxes - Production/Imports 86.8 89.3 94.3 98.8 99.4 94.5 94.0 97.3 101.5 110.4 112.2 119.3
Contributions for Soc. Ins. 739.3 762.8 807.6 852.6 904.6 945.3 973.1 948.9 970.9 906.7 950.5 1022.6
Income Receipts on Assets 20.3 22.8 23.2 23.7 26.1 29.8 30.7 48.1 53.1 54.9 48.7 42.1
Current Transfer Receipts 26.1 25.6 29.0 33.6 38.3 44.8 54.4 69.8 69.8 67.2 66.8 69.4
Surplus of Gov’t. Enterprises 0.2 3.7 0.3 -3.5 -2.9 -2.7 -3.7 -4.4 -4.8 -1.5 -0.9 -0.5
Current Expenditures 2112.1 2261.5 2393.4 2573.1 2728.3 2900.0 3115.7 3450.4 3703.3 3766.9 3774.7 3825.2
Consumption Expenditures 590.5 660.3 721.4 765.8 811.0 848.9 931.8 986.7 1054.1 1077.1 1067.7 1046.3
Defense 380.7 435.2 481.2 514.8 543.9 575.4 633.3 664.1 702.1 722.0 712.3 693.9
Nondefense 209.9 225.1 240.2 251.0 267.1 273.6 298.5 322.5 352.0 355.1 355.3 352.4
Transfer Payments 1252.1 1339.4 1405.1 1491.3 1587.1 1690.5 1841.9 2153.6 2313.6 2310.9 2340.2 2409.1
Government Social Benefits 914.9 962.6 1014.3 1078.0 1180.7 1254.2 1385.7 1601.8 1708.3 1742.6 1807.0 1867.9
To the Rest of the World 9.7 10.1 10.7 11.2 12.5 13.3 15.4 16.1 16.6 16.8 17.4 17.8
Grants-in-Aid
To S&L Governments 304.2 338.0 349.2 361.2 359.0 380.8 395.5 482.4 531.5 492.5 457.0 462.9
To the Rest of the World 23.3 28.6 30.9 40.9 35.0 42.2 45.3 53.3 57.3 59.0 58.9 60.6
Interest Payments 229.1 212.9 221.0 255.4 279.2 313.2 292.1 252.0 279.9 317.9 314.2 321.8
Subsidies 40.5 49.0 46.0 60.5 51.0 47.4 49.9 58.3 55.8 60.9 52.6 47.9
Surplus or Deficit (-) -252.8 -376.4 -379.5 -283.0 -203.8 -245.2 -613.5 -1217.9 -1273.7 -1195.2 -1034.2 -783.7
Table 12. State and Local Government Receipts and Expenditures
2002 2003 2004 2006
2005 2007 2008 2009 2010 2011 2012 2013
Billions of Current Dollars
Receipts 928.7 977.7 1059.4 1163.1 1249.1 1313.6 1326.4 1252.8 1307.9 1367.6 1408.2 1464.3
As Share of GDP 8.7 8.8 8.9 9.2 9.3 9.4 9.3 9.0 9.0 9.1 9.0 9.1
Personal Tax and Nontax
Receipts 221.8 226.2 248.6 276.7 302.5 323.1 334.4 284.8 297.5 327.0 337.3 347.9
Corporate Profits 30.9 34.0 41.7 55.0 59.1 57.8 47.4 47.4 57.9 53.4 56.8 65.5
Indirect Business Tax and
Nontax Accruals 676.0 717.5 769.1 831.4 887.4 932.7 944.6 920.6 952.6 987.2 1014.0 1051.0
Contributions For Social
Insurance 15.9 20.1 24.1 24.8 21.8 18.9 19.0 20.2 20.8 21.6 22.3 23.3
Federal Grants-In-Aid 304.2 338.0 349.2 361.2 359.0 380.8 395.5 482.4 531.5 492.5 457.0 462.9
Expenditures 1466.8 1535.1 1609.3 1704.5 1778.6 1910.8 2017.1 2031.7 2090.0 2149.8 2157.6 2210.0
As Share of GDP 13.8 13.8 13.6 13.5 13.3 13.6 14.1 14.6 14.4 14.2 13.9 13.7
Purchases 1302.7 1356.1 1408.2 1493.6 1586.7 1697.9 1798.0 1774.8 1780.0 1797.6 1783.6 1802.5
Transfer Payments 333.0 353.4 384.3 404.8 402.9 433.7 456.7 498.1 534.6 557.7 572.5 606.4
Interest Received 12.0 20.6 19.0 10.9 2.1 0.5 16.2 28.0 35.4 42.9 43.1 43.4
Net Subsidies -5.2 -3.2 -0.6 0.3 1.7 16.2 15.3 11.9 12.4 13.7 11.9 9.9
Dividends Received 1.6 1.7 2.0 2.1 2.3 2.4 2.9 2.5 2.6 3.1 3.3 3.4
Net Wage Accruals 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Surplus Or Deficit -54.1 -38.8 -8.4 26.0 51.0 12.2 -72.3 -78.1 -25.3 -61.9 -52.3 -28.1
72–Nation UCLA Anderson Forecast, December 2011
EMBARGOED: DO NOT RELEASE UNTIL 1AM, DECEMBER 7, 2011 PST
Forecast Tables - Detailed
Table 13. U.S. Exports and Imports of Goods and Services
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Billions of Current Dollars
Net Exports-Goods & Serv. -427.2 -504.1 -618.7 -722.7 -769.3 -713.1 -709.8 -391.5 -516.9 -578.8 -558.7 -529.2
Current Account Balance -457.2 -519.1 -628.5 -745.8 -800.6 -710.3 -677.1 -376.6 -470.9 -461.3 -467.6 -449.5
Merchandise Balance -493.6 -562.4 -684.7 -801.9 -860.5 -838.7 -848.9 -522.6 -669.5 -765.2 -742.1 -726.8
Exports-Goods & Services 1003.0 1041.0 1180.2 1305.1 1471.1 1661.7 1846.8 1583.1 1839.8 2090.6 2179.8 2371.2
Merchandise 700.3 726.8 817.0 906.1 1024.4 1162.0 1297.5 1064.7 1277.8 1477.9 1544.2 1692.9
Food, Feeds & Beverages 49.6 55.0 56.6 59.0 66.0 84.3 108.3 93.9 107.7 126.8 123.8 125.6
Industrial Supplies 153.5 168.3 199.5 227.5 267.3 316.2 386.9 293.8 388.7 489.9 503.8 538.9
Motor Vehicles & Parts 78.9 80.7 89.2 98.4 107.3 121.3 121.5 81.7 112.0 132.7 139.5 153.3
Capital Goods, Ex. MVP 240.0 247.0 281.5 302.5 339.5 360.0 383.7 315.7 374.6 413.0 440.0 498.3
Computer Equipment 38.6 39.9 42.8 45.5 47.6 45.6 43.9 37.7 43.9 49.7 55.2 65.0
Other 201.5 207.1 238.7 257.0 291.9 314.5 339.8 278.0 330.8 363.2 384.8 433.3
Consumer Goods, Ex. MVP 84.4 89.9 103.3 115.3 129.1 146.0 161.3 150.0 165.9 174.4 186.2 209.7
Other 43.5 39.4 41.0 47.5 50.8 61.3 61.8 54.8 56.9 61.6 60.4 65.3
Services 302.7 314.2 363.2 399.0 446.6 499.7 549.3 518.4 562.0 612.7 635.6 678.4
Imports-Goods & Services 1430.2 1545.2 1798.9 2027.8 2240.4 2374.8 2556.5 1974.6 2356.7 2669.4 2738.5 2900.4
Merchandise 1193.9 1289.3 1501.7 1708.0 1884.9 2000.7 2146.3 1587.3 1947.3 2243.1 2286.3 2419.6
Foods, Feeds & Beverage 49.7 55.8 62.1 68.1 75.0 81.7 90.4 82.9 92.5 108.0 109.8 114.3
Petroleum & Products 103.5 133.1 180.5 251.9 302.5 346.7 476.1 267.7 353.7 463.3 436.3 423.1
Indus Supplies Ex. Petr 159.6 175.7 226.4 266.0 291.4 295.7 318.9 197.1 250.4 298.8 299.7 329.7
Motor Vehicles & Parts 203.8 210.1 228.2 239.5 256.6 256.6 233.2 159.2 225.6 257.8 274.0 299.2
Capital Goods, Ex. MVP 258.5 272.4 320.2 355.0 391.6 411.6 423.2 342.0 418.7 479.8 498.8 533.0
Computer Equipment 75.2 76.5 88.6 93.3 101.4 105.2 101.2 94.2 117.3 121.1 128.1 136.7
Other 183.3 195.8 231.6 261.7 290.2 306.5 322.0 247.8 301.5 358.6 370.7 396.3
Consumer Goods, Ex. MVP 310.7 337.7 377.2 411.5 446.1 478.2 486.7 432.5 486.6 518.6 547.3 593.9
Other 82.7 80.5 82.9 90.3 93.5 95.9 82.3 75.4 88.6 83.3 83.9 86.8
Services 236.3 255.9 297.3 319.8 355.4 374.0 410.1 387.3 409.4 426.3 452.2 480.8
Billions of 2005 Dollars
Net Exports-Goods & Serv. -548.5 -603.7 -687.9 -722.7 -729.4 -648.8 -494.8 -358.8 -421.8 -412.1 -404.9 -337.3
Exports-Goods & Services 1098.3 1116.0 1222.6 1305.1 1422.1 1554.4 1649.3 1494.0 1663.2 1773.0 1833.5 1973.9
Imports-Goods & Services 1646.8 1719.7 1910.4 2027.8 2151.5 2203.3 2144.0 1852.9 2085.0 2185.1 2238.4 2311.2
Exports and Imports -- % Change
Current Dollars
Exports -2.4 3.8 13.4 10.6 12.7 13.0 11.1 -14.3 16.2 13.6 4.3 8.8
Imports 2.3 8.0 16.4 12.7 10.5 6.0 7.7 -22.8 19.4 13.3 2.6 5.9
Constant Dollars
Exports -2.0 1.6 9.5 6.8 9.0 9.3 6.1 -9.4 11.3 6.6 3.4 7.7
Imports 3.4 4.4 11.1 6.1 6.1 2.4 -2.7 -13.6 12.5 4.8 2.4 3.2
Production Indicators - % Change
U.S. Industrial Production 0.2 1.3 2.3 3.2 2.2 2.7 -3.7 -11.2 5.3 3.8 2.2 3.6
Real GDP -- Industrial Countries 2.0 1.7 2.8 2.5 2.8 2.7 0.4 -3.5 2.8 1.7 1.4 2.2
Real GDP -- Developing Countries 2.9 3.7 6.3 5.4 6.7 6.5 3.8 -0.6 7.3 5.2 4.3 5.2
Price Indicators
Price Deflators (% Ch)
Exports -0.4 2.1 3.5 3.6 3.4 3.3 4.7 -5.4 4.4 6.6 0.8 1.0
Imports -1.1 3.5 4.8 6.2 4.1 3.5 10.6 -10.6 6.1 8.1 0.2 2.6
Crude Oil Prices ($/barrel) 26.1 31.1 41.5 56.5 66.1 72.3 99.6 61.7 79.4 93.3 96.3 108.7
Real U.S. Dollar
Ex. Rate-Indust. Countries 1.27 1.11 1.02 1.00 0.97 0.91 0.87 0.93 0.93 0.86 0.89 0.87
%Change -0.4 -12.4 -8.0 -2.4 -2.5 -6.3 -5.1 7.7 -0.7 -7.4 3.4 -2.1
Ex. Rate-Dev. Countries 1.13 1.11 1.06 1.00 0.95 0.88 0.80 0.84 0.80 0.74 0.71 0.64
%Change 2.5 -1.6 -4.5 -6.1 -5.1 -7.4 -9.5 6.2 -5.1 -8.1 -4.3 -9.8
UCLA Anderson Forecast, December 2011 Nation–73
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Forecast Tables - Detailed
Table 14. Implicit Price Deflators and Other Inflation Indicators (Percent Change)
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Implicit Price Deflators
GDP 1.6 2.1 2.8 3.3 3.2 2.9 2.2 1.1 1.2 2.1 1.4 1.3
Consumption 1.4 2.0 2.6 3.0 2.7 2.7 3.3 0.2 1.8 2.5 1.4 1.7
Durables -2.6 -3.6 -1.9 -1.1 -1.6 -2.0 -1.9 -1.8 -1.7 -1.0 -1.2 -0.3
Motor Vehicles -0.5 -2.7 -0.7 1.6 0.1 -0.5 -1.8 0.3 5.0 3.1 0.9 1.1
Furniture -2.1 -2.8 -1.2 0.1 -0.4 -0.7 -0.8 -0.3 -4.2 -1.4 -0.5 0.0
Other Durables -1.8 -1.6 -0.4 -1.5 1.8 3.7 3.4 1.2 0.5 2.9 1.4 2.4
Nondurables -0.1 2.1 3.6 4.0 3.2 3.2 5.7 -2.9 3.2 6.1 1.3 1.6
Food 1.5 1.9 3.1 1.8 1.7 3.9 6.1 1.3 0.3 4.1 2.8 0.7
Clothing & Shoes -2.6 -2.5 -0.3 -0.9 -0.4 -1.0 -0.8 0.9 -0.7 1.3 0.7 1.1
Gasoline -6.5 16.8 17.5 22.6 12.9 9.7 18.1 -27.2 18.2 26.6 -2.5 1.2
Fuel -10.8 21.0 16.4 34.1 14.2 8.1 36.3 -32.2 17.3 27.3 -3.0 1.8
Motor Vehicle Fuel -6.1 16.5 17.6 21.8 12.8 9.8 17.0 -26.8 18.3 26.5 -2.5 1.2
Services 2.7 3.2 3.2 3.4 3.4 3.4 3.4 1.6 1.9 1.8 1.8 2.0
Housing 4.0 2.5 2.3 2.5 3.6 3.5 2.8 1.8 0.1 1.2 1.9 2.1
Utilities -3.0 6.7 4.4 8.9 8.0 3.5 7.7 -2.0 1.4 2.2 2.5 3.9
Electricity -1.0 2.4 1.9 6.1 12.1 4.1 6.5 3.0 0.2 1.8 1.9 2.7
Natural Gas -14.6 22.9 8.4 19.8 2.4 -0.2 13.2 -22.0 -2.0 -1.3 1.4 8.7
Water & Sanit. 3.2 3.7 6.0 5.3 4.9 5.1 5.8 6.2 6.4 5.3 4.2 3.3
Health Care 2.6 3.8 3.7 3.2 3.1 3.7 2.7 2.7 2.5 1.7 2.2 2.3
Transportation 0.5 2.1 1.5 3.7 4.2 2.3 5.5 2.9 2.1 2.7 1.5 1.6
Recreation 2.9 3.1 2.6 2.8 3.4 2.8 3.1 1.2 1.1 1.7 1.2 1.3
Food & Accomm. 2.4 2.1 3.3 3.2 3.4 3.9 3.9 2.3 1.4 2.6 2.3 1.5
Financial & Insura 2.8 4.5 5.6 3.7 2.3 4.5 3.2 0.4 5.6 1.4 1.2 2.0
Other Services 4.8 4.8 4.6 4.9 4.1 3.2 4.8 2.6 3.2 2.7 2.1 2.1
Investment Deflators:
Nonresidential -0.4 -0.4 1.4 3.3 3.4 2.1 2.0 -0.6 -1.6 1.3 0.4 0.6
Structures 4.2 3.6 7.6 13.1 12.9 6.1 4.9 -2.6 -1.1 4.3 1.4 1.1
Equip. & Software -2.0 -1.8 -0.5 0.1 0.0 0.5 0.5 0.5 -1.8 0.2 0.1 0.5
Residential 2.5 4.8 7.3 7.2 6.1 1.4 -1.2 -3.4 -0.4 1.1 1.1 2.5
Government Purchases 2.6 4.2 4.3 5.8 4.8 4.8 4.9 -0.3 2.2 3.2 1.7 1.8
Federal 3.7 4.2 4.7 4.9 4.1 3.5 3.2 -0.2 2.4 2.9 1.6 1.5
State & Local 2.1 4.2 4.0 6.3 5.3 5.5 5.9 -0.4 2.1 3.3 1.8 2.0
Exports -0.4 2.1 3.5 3.6 3.4 3.3 4.7 -5.4 4.4 6.6 0.8 1.0
Imports -1.1 3.5 4.8 6.2 4.1 3.5 10.6 -10.6 6.1 8.1 0.2 2.6
Other Inflation Related Indicators
Consumer Price Index
All Urban 1.6 2.3 2.7 3.4 3.2 2.9 3.8 -0.3 1.6 3.2 1.6 1.9
Producers Price Index -2.3 5.3 6.2 7.3 4.7 4.8 9.8 -8.7 6.9 8.5 -0.4 1.9
Nonfarm Sector Indicators
Wage Compensation 3.2 4.7 3.3 3.9 3.8 4.0 3.4 1.6 2.0 2.7 2.6 3.1
Productivity 4.5 3.7 2.6 1.6 0.9 1.5 0.6 2.3 4.1 1.0 1.2 1.0
Unit Labor Costs -1.3 1.0 0.7 2.3 2.9 2.4 2.8 -0.7 -2.0 1.7 1.3 2.0
Crude Oil Prices (dollars/barrel)
West Texas Intermediate 26.10 31.14 41.45 56.46 66.10 72.28 99.61 61.69 79.41 93.35 96.29 108.68
74–Nation UCLA Anderson Forecast, December 2011
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Forecast Tables - Detailed
Table 15. Producers Price Indexes
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Annual Percent Change
All Commodities -2.3 5.3 6.2 7.3 4.7 4.8 9.8 -8.7 6.9 8.5 -0.4 1.9
Industrial Commodities -2.4 5.0 6.0 8.6 5.4 3.8 9.7 -9.0 7.0 7.7 -0.5 2.6
Textiles & Apparel -1.2 -0.1 1.0 1.5 1.4 1.0 2.4 0.5 1.7 7.5 -0.0 0.2
Fuels -11.5 21.1 12.4 23.2 6.6 6.6 20.5 -25.7 17.3 15.4 -1.6 4.5
Chemicals 0.0 6.6 7.8 10.1 7.2 4.4 14.2 -6.5 7.5 11.4 -1.2 1.9
Rubber & Plastics -0.3 2.6 2.8 7.5 6.9 0.8 7.0 -0.4 3.3 7.2 1.1 1.4
Lumber & Wood -0.6 2.4 10.2 0.4 -1.1 -1.0 -0.6 -4.4 5.4 0.3 -0.9 5.0
Pulp & Paper 0.6 2.2 3.0 3.5 3.6 3.4 4.6 -0.5 5.0 3.8 0.9 2.1
Metals & Products 0.4 2.6 15.8 7.5 12.9 6.5 10.0 -12.2 11.1 8.0 -3.5 3.7
Equipment -0.6 -0.8 0.1 1.3 2.0 0.9 1.9 1.2 -0.1 1.3 0.2 0.7
Trans. Equipment -0.4 0.8 2.0 1.6 1.1 1.6 2.3 2.3 0.7 1.7 2.8 2.3
Farm -4.6 12.6 10.5 -3.8 -1.2 22.5 12.4 -16.5 12.2 22.9 -2.6 -4.3
Processed Foods & Feeds -0.8 5.3 5.5 1.3 0.4 7.3 9.3 -2.3 3.4 8.4 1.4 -1.5
By Stage of Processing
Crude Materials -10.6 25.1 17.6 14.6 1.4 12.2 21.5 -30.3 21.5 16.7 -0.9 3.5
Intermediate Materials -1.5 4.6 6.6 8.0 6.4 3.9 10.3 -8.4 6.4 9.2 -0.6 1.9
Finished Goods -1.3 3.2 3.6 4.9 2.9 3.9 6.4 -2.5 4.2 6.0 0.6 1.3
Consumers -1.5 4.2 4.4 5.8 3.4 4.5 7.4 -3.8 5.6 7.6 0.4 1.2
Producers -0.4 0.3 1.4 2.3 1.5 1.9 2.9 2.0 0.4 1.6 1.2 1.6
Table 16. Money, Interest Rates and Corporate Profits
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Billions of Dollars
Money Supply (M1) 1196.3 1273.5 1344.2 1371.6 1374.2 1372.2 1433.1 1636.8 1740.7 2016.2 2250.8 2378.1
Money Supply (M2) 5587.0 5971.9 6254.7 6521.9 6865.0 7297.6 7816.4 8432.3 8623.2 9258.1 9835.4 10247.9
Percent Change
Money Supply (M1) 4.9 6.5 5.5 2.0 0.2 -0.1 4.4 14.2 6.3 15.8 11.6 5.7
Money Supply (M2) 7.5 6.9 4.7 4.3 5.3 6.3 7.1 7.9 2.3 7.4 6.2 4.2
Interest Rates (Percent)
Short-term Rates
3-Month Treas. Bills 1.60 1.01 1.37 3.15 4.73 4.35 1.37 0.15 0.14 0.06 0.06 0.16
Prime Bank Loans 4.68 4.12 4.34 6.19 7.96 8.05 5.09 3.25 3.25 3.25 3.25 3.32
U.S. Government Bond Yields
5 Year Maturity 3.82 2.97 3.43 4.05 4.75 4.43 2.80 2.19 1.93 1.54 1.38 2.07
10 Year Maturity 4.61 4.02 4.27 4.29 4.79 4.63 3.67 3.26 3.21 2.79 2.41 3.38
30 Year Maturity 5.43 5.05 5.11 4.56 4.88 4.84 4.27 4.07 4.25 3.91 3.35 4.21
State and Local Governments Bond Yields
Domestic Municipal Bonds 5.03 4.74 4.68 4.40 4.40 4.39 4.86 4.62 4.29 4.50 4.19 4.87
Corporate Bond Yields
Moodys AAA Corp. Bonds 6.49 5.67 5.63 5.23 5.59 5.56 5.63 5.31 4.94 4.64 4.29 5.10
Conventional Mortgage Rate 6.54 5.82 5.84 5.87 6.41 6.34 6.04 5.04 4.69 4.44 4.09 4.87
Corporate Profits (Billions of Dollars)
Profits Before Taxes 765.33 903.48 1229.43 1640.15 1822.73 1738.38 1359.93 1455.68 1819.45 1929.59 2042.69 2287.02
Inventory Valuation Adj. -2.58 -11.30 -34.28 -30.70 -38.03 -47.25 -44.45 0.60 -39.08 -52.92 17.22 -10.48
Profits After Taxes 573.00 659.73 923.30 1227.78 1349.45 1292.90 1050.90 1183.28 1408.38 1503.47 1569.31 1729.69
UCLA Anderson Forecast, December 2011 Nation–75
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THE UCLA ANDERSON FORECAST
FOR CALIFORNIA
December 2011 Report
California: Recovery Part Deux?
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California: Recovery Part Deux?
California: Recovery Part Deux?
Jerry Nickelsburg
Senior Economist
UCLA Anderson Forecast
December 2011
The dog days of summer certainly were that for but it will not reach, that of the U.S over the forecast
the California economy as unemployment and income period. The preliminary indication of a new recovery
growth slowed substantially. As autumn arrived there having begun in September yields a slightly more
were indications of more of the same. The California optimistic forecast than that of last September. For
economy seemed to be poised for a continuation of the most part, our increased optimism, such as it
somewhat tepid job growth along the coast and an is, represents a sliding forward to 2011 some of the
erosion of labor markets in the inland region. This recovery we were predicting in 2012. In reality the
led to our September forecast of a net gain of zero numbers have not changed much.
jobs in the state for the balance of the 2011, followed
by a return to growth in the first or second quarter of In this California report we will continue our
20121. ongoing examination of the bifurcated recovery. What
is different this time is that Inland California has
But the September employment numbers, finally begun to grow. By examining the employment
released in late October, turned out to be a pleasant numbers in some detail together with trade and
surprise2. Although other indicators did not predict housing data we find that while the news for Inland
stronger growth in payroll employment, there it was. California is good, there remains a long road ahead.
October has now followed course yielding the first
signs of a nascent new recovery. Have we turned the In some sense the employment numbers
corner in the Golden State? Perhaps we have. But for Inland California may not be surprising.
a weak national and international outlook does not Unemployment rates above 15% lead to falling wages
argue for the return of the recovery to be a robust on the one hand, and entrepreneurship on the other.
return. What is important, however, is that the last Eventually a bottom is reached and the economy
two months have yielded both job growth in excess turns around. In the past, the engines of growth
of the U.S. rate and job growth which is widespread for Inland California have been migration-induced
throughout the state. construction and government. In the September and
October job numbers we find that neither of these
Looking forward to the next six months we is driving hiring, and unlike the past three decades,
expect net new additions to employment to be about there are no clear engines of job growth throughout
at the same rate as the U.S. Thereafter, the December Inland California.
California forecast calls for growth at a rate slightly
faster than that of the U.S. Consequently, California’s These encouraging employment numbers for
unemployment rate will begin to converge towards, payroll employment come from the Establishment
UCLA Anderson Forecast, December 2011 California–79
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California: Recovery Part Deux?
Survey3 and they are confirmed by the Current represent an end to the growth hiatus in the private
Population Survey (Household Survey). The sector. By the numbers, the last two months have seen
Household Survey is generally considered less a return to recovery levels (at least 2010 recovery
reliable during times when the economy is changing level) in private sector job growth.
direction but it does include self employed
entrepreneurs and non-payroll family members With respect to the public sector, the latest
working in a family business, groups not counted in California tax revenues are a good indication that
the Establishment Survey. The Household Survey contraction in public sector employment will continue
reports that California has added 176,000 jobs in for at least another fiscal year4. However, total
the last two months. If job creation were to continue (private and public sector) job growth in September
at this rate, the losses in the recession would be and October was much faster than the U.S.; so much
recouped by the end of 2012. All of this good news so that the gains in the total number of payroll jobs
might be cause for celebration except for the fact from October 2010 to October 2011 give the state
that neither the state nor the nation is forecast to bragging rights for the largest number of new payroll
be growing fast enough to support that kind of job jobs created in the U.S. To be fair, California remains
creation over the coming year. second to Texas with respect to private sector payroll
jobs, but not a distant second (Texas lost more public
Employment Retrospective sector jobs than California).
Private sector job growth in California stalled These recent gains in payroll and non-payroll
out in March and has been basically non-existent jobs have pushed California’s unemployment
since then. The gains in September and October rate down from 12.1% to 11.7% while the U.S.
Change in Private Non-Farm Payroll Employment
(000 jobs, SA)
100
50
Thousands
0
-50
-100
-150
Jan -08 Jul -08 Jan -09 Jul -09 Jan -10 Jul -10 Jan -11 Jul -11
80–California UCLA Anderson Forecast, December 2011
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California: Recovery Part Deux?
unemployment rate has only fallen by 0.1%. To mean “recovered from a recession.” It only means
put this in perspective, the U.S. unemployment the contraction has ended. The pain remains real
rate remains 2.7% below that of California, an and persistent until solid and sustained gains occur.
improvement over July, but the gap remains wide. Throughout the counties of Inland California, with
a few exceptions such as Tulare and Kern Counties,
Looking behind the numbers we find more employment after the gains of the last two months
good news. The employment gains over the last four remains 8% to 12% below 2006-2007 levels. There
months were widespread throughout California. The is clearly a long way to go and these trends in
Inland Empire, San Joaquin Valley and Sacramento Inland California, if they were to prove to be trends,
Delta areas shared in the employment growth and are only the beginning of the process. In the last
virtually all regions in California experienced California report we presented some analysis that
employment growth at a faster rate than the U.S. suggested that “a long way to go” is about five more
These data present the first solid indication that years. Though gains in agriculture, food processing,
Inland California has bottomed out and a recovery in energy, and education have begun this process
the hardest hit regions of California has begun. the question remains, “what will be the engine of
economic growth in Inland California over the next
But, before we start shooting off fireworks, we decade in the absence of growth in construction and
must temper all of these very encouraging results government?”
with a dose of reality. The end of a recession does not
Percent of Pre-Recession Peak
Non-Farm Employment
100%
98%
Inland Empire
96%
Stanislaus
94% Fresno
San Joaquin
92%
Solano
90% Sacramento
East Bay
88%
86%
2008 2009 2010 2011
UCLA Anderson Forecast, December 2011 California–81
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California: Recovery Part Deux?
Employment Gain July to Oct. 2011
6.0%
5.0%
4.0%
3.0%
2.0%
1.0%
0.0%
SJ Valley Inland Bay Area Mid Coast Sac. Delta OC, SD, VC Los Angeles U.S.
Empire
Goods Movement Retrospective particularly in Los Angeles, The Inland Empire and
the East Bay, and therefore, the loss in volume is a
The movement of goods across California’s down note in an otherwise encouraging set of data.
ports and highways is as much as anything a good The large inventory drawdown in the U.S. during the
indicator of current and future economic activity. third quarter of 2011 ought to generate an increase
Unfortunately the growth we are seeing in California of orders for goods from Asia and therefore create
employment is not reflected in the trade data. more traffic through California’s seaports. Were this
While no decline in activity is depicted in the data, to happen another recovery period in the logistics
no real recovery is either. It is for this reason that industry could indeed begin, but there as yet are no
our forecast, in spite of encouraging employment ports data indicating this will happen in the current
numbers, has strengthened only slightly from the quarter5.
forecast released last September.
International Air Cargo shows the same pattern
At the seaports we find that seaborne exports as seaborne imports and exports. Exports through
are showing a small amount of growth over the LAX and SFO have grown the last three months, but
last three months. This increase brings the level of are not yet above the 2010 expansion peaks. Imports
exports (measured in TEUs or twenty foot equivalent have fallen back in the last few months and given up
container units) back to where it was in 2010. It a little less than half of the 2010 gains. Domestic air
may indicate a trend, but it is entirely too early to cargo, as evidenced by traffic through Ontario and
tell. As for seaborne imports, the past three months Oakland airports show the same going nowhere blues.
have given back about half of the recovery gains At both airports total freight traffic remains stuck at
from late 2009 and 2010. Imports generate a demand recession levels6.
for California’s beleaguered logistics industry
82–California UCLA Anderson Forecast, December 2011
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California: Recovery Part Deux?
California Seaport Traffic
(000 TEU's, SA)
900
800
700
600
Thousands
500
400
300
200
100
0
2006 2007 2008 2009 2010 2011
Import By Sea Exports By Sea
California International Air Cargo
Title (Tons Loaded)
80
70
60
50
Thousands
40
30
20
10
0
2006 2007 2008 2009 2010 2011
Outbound Inbound
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California: Recovery Part Deux?
California Regional Airport Freight Traffic (Monthly, S.A.,
Tons of cargo)
70
60
50
Thousands
40
30
20
10
0
Jan Jul Jan Jul Jan Jul Jan Jul
2008 2009 2010 2011
Oakland Ontario
Ceridian-UCLA Pulse of Commerce Index, Jan 1999 to 2011
Workday and Seasonally Adj., 2007=100
110
100
90
80
70
60
50
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
84–California UCLA Anderson Forecast, December 2011
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California: Recovery Part Deux?
A third measure of goods movement is the the inland parts of the state7. Even though economic
Ceridian-UCLA Pulse of CommerceTM. This is an contraction has ended and there are even signs of a
index of diesel fuel purchases by long haul truckers corner being turned, housing markets inland look
as collected real time by Ceridian and analyzed very much as they did three months ago.
by the UCLA Anderson Forecast. The index for
diesel fuel purchases in California showed a strong The foreclosure rate in San Francisco and Santa
upward trend during the 2010 recovery, but fell back Clara Counties is about a third of that of nearby
as the economy stalled earlier this year. The last Solano and San Joaquin Counties and that of Orange
month’s Ceridian-UCLA Pulse of CommerceTM and San Diego Counties a little more than half of
for California was higher than the previous month, nearby Riverside and San Bernardino Counties. One
however one month does not a trend make. Over would then expect new construction in these lower
the last three months the Ceridian-UCLA Pulse of stressed coastal counties before it comes to the inland
CommerceTM for California has moved sideways, counties. That is exactly what the permit data reveal.
consistent with the other indicators on the movement The shift to multi-family housing in the more densely
of goods, but not consistent with a rapid recovery in populated coastal cities continues while single-family
the current quarter. housing has not begun to recover.
Housing Retrospective Home sales volumes have not moved in the past
20 months. Throughout the state, but particularly in
One of the important differentiators between the inland counties, we find stagnant sales. With a
Inland and Coastal California is the importance of significant proportion of today’s home sales coming
residential construction in sustaining job growth in from short sales and foreclosures there is continued
Foreclosures per 1,000 homes, September 2011
8
7
6
5
4
3
2
1
0
San Francisco
Riverside
Contra Costa
Fresno
Ventura
Orange County
Sacramento
Merced
Alameda
San Bernardino
Santa Clara
Tulare
Stanislaus
Kern
Placer
San Joaquin
Solano
Yolo
El Dorado
San Mateo
San Diego
Los Angeles
UCLA Anderson Forecast, December 2011 California–85
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California: Recovery Part Deux?
New Building Permits -- California (SA, 3 Mo. Average)
9,000
8,000
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
2007 2008 2009 2010 2011
Single Family Permits Multi-Family Permits
Home Sales 2010-2011
5,000
4,500
4,000
3,500
3,000
2,500
2,000
1,500
1,000
500
0
Jan May Sep Jan May Sep
2010 2010 2010 2011 2011 2011
Riverside San Bernardino Solano Contra Costa
86–California UCLA Anderson Forecast, December 2011
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California: Recovery Part Deux?
FHFA Home Price Index
190
180
Solano
170
Riverside/SB
160 Stockton
Fresno
150
Bakersfield
140 Sacramento
Visalia
130
120
2010 Q1 2010 Q3 2011 Q1
downward pressure on prices. The FHFA price index economy is right now. Inland California has begun to
for metropolitan areas in Inland California confirms grow with the rest of the state, but the two transitional
this weakening of home prices, and we expect it to sectors, government and housing, are far from
continue until such time as owner occupied home turning a corner. Good news, but not fantastic news.
sales once again dominate the market. In coastal California export and technology growth
has been the key to recovery and a resurgence of
Distressed housing sales, either REOs or short investment and exports in 2012 will continue to drive
sales are still half or more of all home sales. What the coastal economies.
this means is both normal home trading activity and
normal building activity is on hold until the ultimate The employment numbers continue to be
price and appreciation properties of the post-crash encouraging, but the trade numbers do not reflect a
housing markets are evident. Basically, developers robust recovery. In the broader picture there is slow
won’t build until the price of housing is such that growth in consumption in the U.S., there is a slowing
they are able to sell the homes at a profit. Unstable of growth to the point of double dip recessions for
and uncertain markets keep them on the sidelines and some of California’s trading partners abroad, and
prevent new hiring in the construction trades. there is an economic policy in Washington, which is
now, for all intents and purposes, played out8.
The California Forecast
We might be witnessing the return of the
One of the signs of a turning point is turbulence recovery, indeed the indications are strong enough
in the data. Some data will show recovery while other to slightly boost our forecast, but the headwinds are
data will not. That seems to be where the California substantial and the resumption of employment growth
UCLA Anderson Forecast, December 2011 California–87
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California: Recovery Part Deux?
we are seeing shifts our view of the recovery forward, Our forecast for 2012 is similar to last quarter’s
but it does not change our general view of how the forecast. Employment growth of 1.4% and 2.1% is
recovery will play out in the coming years. expected in 2012 and 2013 respectively. Payrolls
will grow less rapidly, at 1.4%, 1.2% and 2.0% for
The current forecast is for the surge in the last two forecast years. Real personal income
employment to abate and slow growth to persist on growth is forecast to be 3.9% in 2011 followed by
average through 2012. The U.S., California’s trading 2.6% and 2.1% in 2012 and 2013 respectively. The
partners and consumer’s purchases will all pitch in unemployment rate will hover around 11.6% through
to generate faster growth in 2013 and though it is 2012.
beyond the forecast horizon, even more robust growth
the following year. What this means is a steady Unemployment will fall through 2013, the last
decrease in the unemployment rate in California over year of our forecast, and will average approximately
the next two quarters followed by a slow trajectory 10.5%. Employment growth in 2011 and 2012 will
towards, but not reaching, single digit unemployment push unemployment down marginally, and therefore,
the following four quarters. we do not expect it to reach single digits until 2014.
Endnotes
1. Jerry Nickelsburg, “Bifurcated and Buffeted,” UCLA Anderson Forecast, September 2011
2. http://www.labormarketinfo.edd.ca.gov
3. Payroll employment estimates are derived from the Establishment Survey which measures employment by the domicile of the firm. Total
employment and unemployment estimates are derived from the Household Survey which measures employment by the domicile of the
employee.
4. http://www.dof.ca.gov/finance_bulletins/
5. Data Sources: Port of Long Beach, Port of Los Angeles, Port of Oakland.
6. Data Sources: LAWA, San Francisco Airport, Oakland Airport
7. Jerry Nickelsburg, “Buffeting and Bifurcation,” UCLA Anderson Forecast, September 2011.
8. David Shulman, “Stalled,” UCLA Anderson Forecast, September 2011.
88–California UCLA Anderson Forecast, December 2011
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THE UCLA ANDERSON FORECAST
FOR CALIFORNIA
December 2011 Report
Charts
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Charts – Recent Evidence
California Employment (6-mo. moving avg.) California Unemployment Rate
Jan. 1997 to Oct. 2011 (Thous.) Jan. 1993 to Oct. 2011
15500 17500 (Percent)
14
15000 17000
16500 12
14500
16000
14000 10
15500
13500
15000 8
13000 14500
6
12500 14000
97 98 99 00 01 02 03 04 05 06 07 08 09 10 11
Wage & Salary Emp. (Left) HH Survey Emp. (Right) 4
93 95 97 99 01 03 05 07 09 11
Taxable Sales in California Ceridian-UCLA Pulse of Commerce Index
1998:1Q to 2010:Q2 Jan. 1999 to Oct. 2011
(Bil. $) (Index 2007=100)
600 110
550 100
500 90
80
450
70
400
60
350
50
99 00 01 02 03 04 05 06 07 08 09 10 11
300 US, Overall Pacific Region California
98 99 00 01 02 03 04 05 06 07 08 09 10
UCLA Anderson Forecast, December 2011 California–91
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Charts – Recent Evidence
California New Car Registrations California Existing-Home Prices
Jan. 1999 to Aug. 2011 1987:1Q to 2011:3Q
(Mil.) (Thous. $)
1.8 600
1.6 (3-mo. moving avg.) 500
1.4
400
1.2
1.0 300
0.8 200
0.6
100
0.4 87 89 91 93 95 97 99 01 03 05 07 09 11
99 00 01 02 03 04 05 06 07 08 09 10 11 Source: California Association of Realtors
California Existing-Home Sales New One-Family Houses Sold
Jan. 2000 to Oct. 2011 Western Region
(Thous.) Jan. 2000 to Sept. 2011
700 (Thous.)
400
600 (3-mo. moving average)
300
500
400 200
300 100
200
00 01 02 03 04 05 06 07 08 09 10 11 0
Source: California Association of Realtors 00 01 02 03 04 05 06 07 08 09 10 11
92–California UCLA Anderson Forecast, December 2011
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Charts – Recent Evidence
New Residential Units Through Building Permit Valuations
California Building Permits Total Nonresidential
Jan. 2000 to Sept. 2011 Jan. 1999 to Sept. 2011
(Thous.) (Mil. $)
300 24000
3-mo. moving avg.
250 22000
200 20000
18000
150
16000
100
14000
50 12000
0 10000
00 01 02 03 04 05 06 07 08 09 10 11
Single-Unit Multi-Unit 8000
99 00 01 02 03 04 05 06 07 08 09 10 11
California Construction Employment California Employment by Sector
Jan. 1998 to Oct. 2011 Jan. 1998 to Oct. 2011
(Thous.) (Thous.) (Thous.)
1000 2800 13000
2600 12500
900
2400
12000
800 2200
11500
700 2000
1800 11000
600
1600 10500
98 99 00 01 02 03 04 05 06 07 08 09 10 11
500 Goods Producing (Left) Services (Right)
98 99 00 01 02 03 04 05 06 07 08 09 10 11
UCLA Anderson Forecast, December 2011 California–93
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Charts – Forecast
Real Personal Income Nonfarm Employment
California versus U.S. California versus U.S.
(% Change Year Ago) (% Change Year Ago)
10 8
6
5 4
2
0 0
-2
-5 -4 California Usually Snaps Back With U.S. Recovery
-6
-10 -8
1965 1971 1977 1983 1989 1995 2001 2007 2013 1965 1971 1977 1983 1989 1995 2001 2007 2013
California U.S. California U.S.
Rates of Unemployment California Employment versus
California versus U.S. Real Personal Income
(Percent) (3-Yr. % Ch.)
14 10
12
5
10
8 0
6
-5
4
2 -10
1965 1971 1977 1983 1989 1995 2001 2007 2013 1965 1971 1977 1983 1989 1995 2001 2007 2013
California U.S. Nonfarm Emp. Real Personal Income
94–California UCLA Anderson Forecast, December 2011
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Charts – Forecast
Real California Taxable Sales California Consumer Price Inflation
(% Change Year Ago) (4-Qtr Percent Change)
20 20
10 15
10
0
5
-10
0
-20
-5
1965 1971 1977 1983 1989 1995 2001 2007 2013
-30 California U.S.
1965 1971 1977 1983 1989 1995 2001 2007 2013
California Share of U.S. California Nonfarm Employment
Employment and Population History & Forecast
(Percent) Vs. 2.3% Trend from 1990:3
13 (Thous)
22000
12 20000
6.5 Million Jobs Below Trend
18000 by Year 2013
11
16000
10 14000
12000
9
10000
8 8000
1965 1971 1977 1983 1989 1995 2001 2007 2013 1985 1989 1993 1997 2001 2005 2009 2013
Emp Population History & Forecast 2.3% Trend Line
UCLA Anderson Forecast, December 2011 California–95
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Charts – Forecast
Growth in Population California Net Natural Increase and
(4-Qtr Percent Change) Net Inmigration
4.0 (Thous.)
500
400
3.0 300
200
2.0 100
0
-100
1.0
-200
-300
1965 1971 1977 1983 1989 1995 2001 2007 2013
0.0 Immigration Natural Increase
1965 1971 1977 1983 1989 1995 2001 2007 2013
Population of California vs. U.S. Gross Labor Force Participation Rate
(Ca. Mil.; U.S. 10 Mil.) Labor Force/Total Population
40 (Percent)
52
35 50
48
30 46
44
25
42
20 40
38
15 36
1965 1971 1977 1983 1989 1995 2001 2007 2013 1965 1971 1977 1983 1989 1995 2001 2007 2013
California U.S. California U.S.
96–California UCLA Anderson Forecast, December 2011
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Charts – Forecast
U.S. Median Price of Single-Family Homes New Residential Units Through
(Thous. $) California Building Permits
300 (Thous. Units)
400
250
300
200
150 200
100 100
50
0
1983 1989 1995 2001 2007 2013
0 Single-Unit Multi-Unit
1965 1971 1977 1983 1989 1995 2001 2007 2013
Real Value of Nonresidential California Employment
Construction in California in Construction
(Bil. 2005 $) (Thous.)
35 1000
30 900
800
25
700
20
600
15
500
10 400
5 300
1985 1989 1993 1997 2001 2005 2009 2013 1983 1988 1993 1998 2003 2008 2013
UCLA Anderson Forecast, December 2011 California–97
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Charts – Forecast
California Employment California Employment
in Education and Health Services in Manufacturing
(Thous.) (Thous.)
2000 2200
1800 2000
1600
1800
1400
1600
1200
1400
1000
800 1200
600 1000
1983 1988 1993 1998 2003 2008 2013 1983 1988 1993 1998 2003 2008 2013
California Employment California Employment
in Information in Trade
(Thous.) (Thous.)
600 2600
550 2400
2200
500
2000
450
1800
400 1600
350 1400
1983 1988 1993 1998 2003 2008 2013 1983 1988 1993 1998 2003 2008 2013
98–California UCLA Anderson Forecast, December 2011
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Charts – Forecast
California Employment California Employment
in Financial Activities in State and Local Government
(Thous.) (Thous.)
950 2400
900 2200
850
2000
800
1800
750
1600
700
650 1400
600 1200
1983 1988 1993 1998 2003 2008 2013 1983 1988 1993 1998 2003 2008 2013
California Employment California Employment
in Professional & Business Services in Federal Government
(Thous.) (Thous.)
2400 380
2200 360
2000 340
1800 320
1600 300
1400 280
1200 260
1000 240
800 220
1983 1988 1993 1998 2003 2008 2013 1983 1988 1993 1998 2003 2008 2013
UCLA Anderson Forecast, December 2011 California–99
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THE UCLA ANDERSON FORECAST
FOR CALIFORNIA
December 2011 Report
Tables
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Forecast Tables - Summary
Table 1. Summary of the UCLA Forecast for California
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Personal Income, Taxable Sales, and Price Inflation (%Change)
Personal Income (Bil.$) 1233.0 1312.2 1387.7 1495.5 1566.4 1610.3 1528.5 1590.3 1683.8 1747.2 1821.8
Calif. (% Ch) 3.8 6.4 5.7 7.8 4.7 2.8 -5.1 4.0 5.9 3.8 4.3
U.S.(% Ch) 3.5 6.0 5.5 7.5 5.7 4.6 -4.3 3.7 5.0 3.2 3.7
Pers. Income (Bil. 2005$) 1305.9 1354.2 1387.0 1445.4 1468.2 1467.7 1390.2 1426.3 1482.2 1521.1 1553.6
Calif. (% Ch) 1.7 3.7 2.4 4.2 1.6 -0.0 -5.3 2.6 3.9 2.6 2.1
U.S. (% Ch) 1.4 3.3 2.5 4.6 2.9 1.3 -4.4 1.9 2.4 1.8 2.0
Taxable Sales (Bil.$) 459.9 499.8 536.3 559.5 561.3 532.3 456.6 471.1 488.8 505.2 525.0
(% Ch) 4.3 8.7 7.3 4.3 0.3 -5.2 -14.2 3.2 3.8 3.4 3.9
(Bil. 2005$) 487.1 515.8 536.0 540.8 526.2 485.2 415.2 422.5 430.3 439.8 447.8
(% Ch) 2.2 5.9 3.9 0.9 -2.7 -7.8 -14.4 1.7 1.8 2.2 1.8
Consumer Prices (% Ch) 2.3 2.6 3.6 3.9 3.3 3.4 -0.3 1.3 2.5 1.3 2.2
Employment and Labor Force (Household Survey, % Change)
Employment 0.0 1.1 1.9 1.4 0.9 -0.5 -4.3 -1.4 0.1 1.4 2.1
Labor Force 0.2 0.5 1.0 0.8 1.4 1.5 0.1 -0.2 -0.5 1.0 1.0
Unemployment Rate (%) 6.9 6.2 5.4 4.9 5.3 7.2 11.3 12.4 11.9 11.6 10.5
U.S. 6.0 5.5 5.1 4.6 4.6 5.8 9.3 9.6 9.1 9.2 9.0
Total Nonfarm Nonfarm Employment (Payroll Survey, % Change)
Calif. -0.5 1.0 1.8 1.8 0.8 -1.2 -6.0 -1.3 1.4 1.2 2.0
U.S. -0.3 1.1 1.7 1.8 1.1 -0.6 -4.4 -0.7 1.0 0.9 1.4
Construction 2.9 6.7 6.4 3.2 -4.4 -11.7 -20.9 -10.3 1.4 0.2 0.7
Manufacturing -5.5 -1.4 -1.2 -1.0 -1.6 -2.7 -10.1 -3.1 0.9 1.3 2.4
Nondurable Goods -3.2 -1.5 -2.1 -0.6 -1.1 -2.0 -8.1 -2.2 0.1 1.2 1.6
Durable Goods -6.7 -1.3 -0.7 -1.2 -1.8 -3.0 -11.2 -3.6 1.4 1.4 2.9
Trans. Warehousing & Util -2.1 0.4 0.9 1.8 2.3 -0.6 -6.1 -1.9 0.8 0.2 2.2
Trade 0.2 1.6 2.7 2.0 1.0 -2.5 -7.5 -0.7 1.3 0.5 1.7
Information -4.3 1.3 -1.8 -1.6 1.0 1.0 -7.4 -2.6 5.7 3.1 3.4
Financial Activities 3.8 1.9 2.8 0.8 -3.4 -6.1 -7.0 -3.0 -0.6 -0.4 1.4
Professional Busi. Serv. -1.6 0.6 3.0 3.8 1.0 -1.2 -8.0 0.5 3.3 2.6 3.8
Edu. & Health Serv. 2.5 1.5 1.7 1.8 3.5 3.3 1.5 1.5 2.7 2.2 1.5
Leisure & Hospitality 1.3 2.8 2.5 3.0 2.7 0.8 -4.4 -0.6 2.2 1.7 1.7
Other Services -0.3 -0.1 0.3 0.3 1.0 -0.2 -4.9 -0.3 -0.3 1.7 3.1
Federal Gov’t 0.6 -1.7 -0.2 -0.7 -0.6 0.5 1.1 6.6 -5.6 1.4 1.6
State & Local Gov’t -1.0 -1.1 1.1 1.6 2.0 1.0 -1.9 -3.1 -0.8 -0.3 0.9
Nonfarm Employment (Payroll Survey, Thous.)
Total Nonfarm 14394 14533 14801 15061 15175 14985 14085 13896 14085 14254 14542
Construction 797 850 905 934 893 788 624 560 568 569 573
Manufacturing 1542 1521 1503 1488 1464 1425 1282 1242 1254 1271 1302
Nondurable Goods 566 557 546 543 536 526 483 472 473 478 486
Durable Goods 976 964 957 945 928 900 799 770 781 792 815
Trans. Warehousing & Util 481 483 487 496 508 505 474 465 469 470 480
Trade 2238 2273 2335 2382 2405 2345 2168 2152 2180 2191 2228
Information 476 482 473 466 471 475 440 429 453 467 483
Financial Activities 879 895 920 928 897 842 783 760 756 752 762
Professional Busi. Serv. 2085 2098 2160 2242 2265 2239 2059 2069 2138 2195 2279
Edu. & Health Serv. 1543 1567 1593 1621 1678 1733 1760 1787 1834 1875 1903
Leisure & Hospitality 1400 1439 1475 1519 1560 1573 1503 1494 1527 1552 1579
Other Services 504.3 503.8 505.4 507.0 512.1 511.3 486.1 484.7 483.0 491.1 506.4
Federal Gov’t 255.4 251.0 250.4 248.7 247.1 248.4 251.3 267.8 252.8 256.2 260.3
State & Local Gov’t 2170.6 2146.7 2169.9 2203.9 2247.9 2271.0 2227.9 2159.0 2141.7 2134.7 2153.7
Population and Migration
Net Inmigration(Thous) 71 7 -79 -130 -83 26 83 88 72 67 85
Population (Thous) 35252 35560 35797 35982 36229 36584 36965 37351 37713 38059 38417
(% Ch) 1.1 0.9 0.7 0.5 0.7 1.0 1.0 1.0 1.0 0.9 0.9
Construction Activity
Residential Building
Permits (Thous. Un.) 197.2 213.0 208.8 163.5 113.1 65.4 36.3 44.5 45.1 52.7 109.2
Nonres.Permits (Mil.’05$) 16986 17699 18236 18728 18886 15309 8893 9222 10000 10006 11801
UCLA Anderson Forecast, December 2011 California–103
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Forecast Tables - Summary
Table 2. Quarterly Summary of the UCLA Forecast for California
2011:1 2011:2 2011:3 2011:4 2012:1 2012:2 2012:3 2012:4 2013:1 2013:2 2013:3 2013:4
Personal Income, Taxable Sales, and Price Inflation (%Change)
Personal Income (Bil.$) 1664.9 1682.2 1685.5 1702.5 1721.5 1738.5 1755.2 1773.6 1788.8 1810.1 1832.5 1855.7
Calif.(% Ch) 9.9 4.2 0.8 4.1 4.5 4.0 3.9 4.3 3.5 4.8 5.1 5.2
U.S. (% Ch) 8.8 4.6 0.9 2.2 4.3 3.5 3.4 3.5 3.0 4.3 4.4 4.5
Pers. Income (Bil. 2005$) 1470.2 1479.2 1485.8 1493.7 1507.5 1518.2 1525.2 1533.3 1538.0 1547.9 1558.7 1569.9
Calif.(% Ch) 5.6 2.5 1.8 2.1 3.7 2.9 1.9 2.2 1.2 2.6 2.8 2.9
U.S. (% Ch) 4.8 1.3 -1.4 1.0 3.4 2.5 2.1 2.3 1.0 2.4 2.5 2.6
Taxable Sales (Bil. $) 482.7 487.6 490.3 494.6 499.0 502.9 507.2 511.7 516.5 521.9 527.7 533.9
(% Ch) 5.7 4.1 2.3 3.5 3.6 3.2 3.5 3.6 3.8 4.3 4.5 4.8
(Bil. 2005$) 426.3 428.8 432.2 433.9 436.9 439.2 440.8 442.4 444.1 446.4 448.9 451.7
(%Ch) 1.5 2.4 3.2 1.6 2.8 2.1 1.5 1.5 1.5 2.1 2.3 2.5
Consumer Prices (% Ch) 5.4 2.5 -0.6 2.1 0.9 1.2 2.2 2.2 2.4 2.3 2.4 2.2
Employment and Labor Force (Household Survey, % Change)
Employment 0.7 0.6 -1.7 4.0 0.9 1.3 1.7 2.1 2.1 2.4 2.6 2.6
Labor Force -0.7 -1.2 -0.7 2.4 1.3 1.0 1.0 1.1 0.9 1.1 0.8 0.7
Unemployment Rate (%) 12.2 11.8 12.0 11.7 11.8 11.7 11.5 11.3 11.1 10.8 10.4 10.0
U.S. 8.9 9.1 9.1 9.1 9.2 9.2 9.2 9.2 9.2 9.1 8.9 8.8
Total Nonfarm Nonfarm Employment (Payroll Survey, % Change)
Calif. 3.4 0.2 1.8 1.0 0.9 1.2 1.6 1.9 2.0 2.2 2.4 2.5
U.S. 1.3 1.4 0.7 0.7 0.7 1.0 1.1 0.9 1.4 1.7 1.8 1.9
Construction 9.5 -0.2 2.5 0.9 -0.1 -0.6 -0.5 -0.3 1.4 1.3 1.3 1.3
Manufacturing 1.8 0.8 0.8 0.7 1.2 1.8 1.9 2.6 2.7 2.6 2.5 2.2
Nondurable Goods -2.8 0.4 1.4 0.3 1.2 1.8 1.6 1.4 1.7 1.7 1.7 1.6
Durable Goods 4.6 1.0 0.4 0.9 1.2 1.8 2.0 3.4 3.3 3.1 2.9 2.5
Trans. Warehousing & Util. 1.1 3.1 -1.6 -0.7 -0.5 0.7 1.8 1.8 2.1 3.3 1.8 2.9
Trade 4.7 0.5 0.9 0.4 0.2 0.2 0.6 1.5 2.0 2.3 2.2 2.5
Information 10.6 5.6 0.8 5.1 1.4 2.9 4.2 3.9 3.1 2.7 3.5 3.9
Financial Activities -0.7 -0.8 -1.4 -0.4 -0.6 -0.3 0.4 0.3 1.6 2.1 2.9 2.0
Professional Busi. Serv. 7.8 0.3 1.8 2.1 2.6 3.4 3.9 3.5 3.5 3.8 4.7 4.8
Edu. & Health Serv. 3.8 0.6 3.0 2.2 2.5 2.8 1.4 1.2 1.2 1.6 1.7 2.0
Leisure & Hospitality 4.5 1.9 0.5 1.5 1.8 2.0 1.9 1.8 1.4 1.6 1.8 2.0
Other Services -0.9 0.8 -1.1 1.4 2.2 2.5 2.7 2.4 2.9 3.8 3.8 4.0
Federal Gov’t -5.1 -8.4 6.0 1.6 1.0 1.1 2.2 2.2 1.4 1.2 1.7 0.9
State and Local Gov’t -1.4 -2.3 5.2 -1.2 -1.6 -1.8 0.4 1.7 1.1 0.9 1.1 1.0
Nonfarm Employment (Payroll Survey, Thous.)
Total Nonfarm 14039 14047 14109 14143 14176 14218 14276 14345 14417 14496 14582 14672
Construction 566 566 569 570 570 569 569 568 570 572 574 576
Manufacturing 1250 1253 1255 1258 1261 1267 1273 1281 1290 1298 1306 1313
Nondurable Goods 472 472 474 474 475 478 479 481 483 485 487 489
Durable Goods 779 781 782 784 786 789 793 800 807 813 819 824
Trans. Warehousing & Util. 467 471 469 468 467 468 470 473 475 479 481 484
Trade 2175 2178 2183 2185 2186 2187 2190 2199 2209 2222 2234 2248
Information 447 453 454 460 461 465 469 474 477 481 485 489
Financial Activities 758 757 754 753 752 752 752 753 756 760 765 769
Professional Busi. Serv. 2130 2131 2141 2152 2166 2184 2205 2224 2244 2265 2291 2318
Edu. & Health Serv. 1822.9 1825.7 1839.4 1849.7 1861.3 1874.1 1880.4 1886.1 1891.5 1899.0 1907.1 1916.3
Leisure & Hospitality 1519.1 1526.2 1528.2 1533.9 1540.9 1548.6 1556.0 1562.9 1568.4 1574.7 1581.6 1589.6
Other Services 482.6 483.6 482.2 483.8 486.4 489.4 492.8 495.7 499.3 504.0 508.7 513.7
Federal Gov’t 255 249 253 254 255 255 257 258 259 260 261 261
State and Local Gov’t 2139 2127 2154 2147 2139 2129 2131 2140 2146 2151 2156 2162
Population and Migration
Net Inmigration(Thous) 75.1 76.8 70.0 64.6 61.3 63.5 68.4 72.9 79.2 82.5 85.7 91.7
Population (Thous) 37579 37670 37758 37845 37930 38015 38102 38190 38279 38370 38462 38556
(% Ch) 1.0 1.0 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 1.0 1.0
Construction Activity
Residential Building
Permits (Thous. Un.) 42.6 48.9 45.0 43.8 45.1 45.5 54.8 65.2 73.5 89.1 123.0 151.1
Nonres.Permits (Mil. ‘05$) 9891.7 10192.7 10075.4 9840.9 9860.7 9863.8 9997.5 10301.4 10631.2 11353.3 12531.3 12688.5
104–California UCLA Anderson Forecast, December 2011
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Forecast Tables - Detailed
Table 3. Personal Income, Taxable Sales, Construction and Population in California
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Aggregates
(Bil $)
Personal Income 1233.0 1312.2 1387.7 1495.5 1566.4 1610.3 1528.5 1590.3 1683.8 1747.2 1821.8
Disposable Income 1090.7 1157.6 1211.4 1298.3 1351.0 1409.4 1368.4 1417.3 1492.6 1542.0 1588.9
(Bil 2005$)
Personal Income 1305.9 1354.2 1387.0 1445.4 1468.2 1467.7 1390.2 1426.3 1482.2 1521.1 1553.6
Disposable Income 1155.2 1194.7 1210.9 1254.7 1266.3 1284.5 1244.6 1271.2 1313.9 1342.4 1355.1
(Nominal %Ch)
Personal Income 3.8 6.4 5.7 7.8 4.7 2.8 -5.1 4.0 5.9 3.8 4.3
Disposable Income 5.1 6.1 4.6 7.2 4.1 4.3 -2.9 3.6 5.3 3.3 3.0
(Real %Ch)
Personal Income 1.7 3.7 2.4 4.2 1.6 -0.0 -5.3 2.6 3.9 2.6 2.1
Disposable Income 2.9 3.4 1.4 3.6 0.9 1.4 -3.1 2.1 3.4 2.2 0.9
Components of Personal Income (Bil $)
Personal Income 1233.0 1312.2 1387.7 1495.5 1566.4 1610.3 1528.5 1590.3 1683.8 1747.2 1821.8
Wages & Salaries 666.2 706.2 743.5 792.9 837.4 845.3 801.5 818.6 860.8 889.2 924.9
Other Labor Income 158.2 171.7 181.6 183.6 184.6 191.6 189.7 192.2 199.8 214.6 233.8
Farm 5.2 6.8 4.8 4.8 7.5 5.3 6.0 7.2 8.1 8.9 10.0
Other Income 353.4 378.9 407.1 454.1 467.8 484.0 413.8 434.7 463.6 485.8 509.5
Transfer Payments 152.5 160.2 167.9 181.0 191.6 208.9 238.3 260.0 268.5 278.4 287.3
Social Insurance 102.3 111.2 117.1 120.6 122.4 124.7 120.8 122.3 116.6 128.4 141.7
Taxable Sales
Nominal
Level (Bil $) 459.9 499.8 536.3 559.5 561.3 532.3 456.6 471.1 488.8 505.2 525.0
%Ch 4.3 8.7 7.3 4.3 0.3 -5.2 -14.2 3.2 3.8 3.4 3.9
Real
Level (Bil. 2005$) 487.1 515.8 536.0 540.8 526.2 485.2 415.2 422.5 430.3 439.8 447.8
%Ch 2.2 5.9 3.9 0.9 -2.7 -7.8 -14.4 1.7 1.8 2.2 1.8
New Automobile Sales (Mil Un.)
New Registrations 1.46 1.48 1.36 1.22 1.02 0.76 0.51 0.52 0.55 0.85 1.18
U.S. Sales 16.64 16.87 16.95 16.50 16.09 13.19 10.40 11.55 12.63 13.17 14.51
Construction Activity
Residential Building Permits (Thous.)
Total 197.2 213.0 208.8 163.5 113.1 65.4 36.3 44.5 45.1 52.7 109.2
Single-Family 140.1 151.9 154.6 107.3 68.4 32.8 25.3 25.6 20.5 24.3 50.9
Multi-family 57.1 61.1 54.3 56.3 44.8 32.7 11.0 19.0 24.5 28.3 58.3
Nonresidential Permit Valuation
Nominal (Mil. $) 13956.8 15651.2 18263.1 21139.8 22622.8 19187.8 10897.0 11169.8 12630.6 12818.6 15288.9
%Ch -4.2 12.1 16.7 15.8 7.0 -15.2 -43.2 2.5 13.1 1.5 19.3
Real (Mil. 2005$) 16985.8 17699.3 18236.4 18728.2 18885.6 15309.0 8892.7 9222.4 10000.2 10005.9 11801.1
%Ch -7.5 4.2 3.0 2.7 0.8 -18.9 -41.9 3.7 8.4 0.1 17.9
Population (Thous.)
Net Inmigration 71.3 6.7 -78.8 -129.6 -82.7 25.7 82.7 87.7 71.6 66.6 84.8
Net Natural Increase 304.0 301.0 316.0 314.0 330.0 329.0 299.0 298.0 286.6 278.1 281.0
Population 35252.3 35560.0 35797.2 35981.6 36228.9 36583.6 36965.3 37351.0 37713.0 38059.5 38416.7
UCLA Anderson Forecast, December 2011 California–105
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Regional Modeling Group
The Los Angeles Department of Water and Power
(DWP), established at the beginning of the century is
the largest municipally-owned utility in the nation. It
exists under and by virtue of the Charter of the City
of Los Angeles enacted in 1925.
With a work force in excess of 9,000, the DWP
provides water and electricity to some 3.5 million
residents and businesses in a 464-square-mile area.
DWP’s operations are financed solely by the sale of
water and electric services. Capital funds are raised
through the sale of bonds. No tax support is received.
A five-member Board of Water and Power Commis-
sioners establishes policy for the DWP. The Board
members are appointed by the Mayor and confirmed
by the City Council for five-year terms.
UCLA Anderson Forecast, December 2011 Regional Modeling Group–107
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Regional Modeling Group
The Los Angeles County Metropolitan Transporta- Metro’s Mission is to insure the continuous improve-
tion Authority (Metro) is unique among the nation’s ment of an efficient and effective transportation
transportation agencies. It serves as transportation system for Los Angeles County. In support of this
planner and coordinator, designer, builder and opera- mission, our team members provide expertise and
tor for one of the country’s largest, most populous leadership based on their distinct roles: operating
counties. More than 9 million people – one-third of transit system elements for which the agency has de-
California’s residents – live, work, and play within its livery responsibility, planning the countywide trans-
1,433-square-mile service area. portation system in cooperation with other agencies,
Besides operating over 2,000 coaches in the Metro managing the construction and engineering of trans-
Bus fleet, Metro also designed, built and now operates portation system components and delivering timely
over 73 miles of Metro Rail service. The Metro Rail support services to the Metro organization.
system currently consists of 62 stations and several Metro was created in the state legislature by As-
more are in the planning and/or design stage. sembly Bill 152 in May 1992. This bill merged the
In addition to operating its own services Metro funds Los Angeles County Transportation Commission
16 municipal bus operators and funds a wide array (LACTC) and the Southern California Rapid Transit
of transportation projects including bikeways and District (RTD) to become the Los Angeles County
pedestrian facilities, local road and highway improve- Metropolitan Transportation Authority. The merger
ments, goods movement, and the popular Freeway became effective on April 1, 1993.
Patrol and Call Boxes. Metro is governed by a 13-member Board of Direc-
Recognizing that no one form of transit can solve tors comprised of: the five Los Angeles County Super-
urban congestion problems, Metro’s multimodal ap- visors, the Mayor of Los Angeles, three Los Angeles
proach uses a variety of transportation alternatives to mayor-appointed members, four city council members
meet the needs of the highly diverse population in the representing the other 87 cities in Los Angeles County
region. and one non-voting member is appointed by the Gov-
ernor of California.
108–Regional Modeling Group UCLA Anderson Forecast, December 2011
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Seminar Members
The nonpartisan Legislative Analyst's Office (LAO) The Legislature and Governor created the California
has been providing fiscal and policy advice to the Research Bureau (CRB) within the California State
California Legislature for more than 65 years. It is Library in the 1991 Budget Act. The bureau pro-
particularly well known for its fiscal and program- vides objective, nonpartisan, timely, and confidential
matic expertise and nonpartisan analyses relating to research to the Governor’s Office, members of both
the state budget, including making recommendations houses of the Legislature, and other state constitu-
for operating programs in the most effective and tional officers. The Bureau provides these clients with
cost-efficient manner possible. Its responsibilities also research, policy assistance through written reports
include making economic and demographic forecasts and other documents, consultations, seminars, and
for California, and fiscal forecasts for state govern- other training and assistance in preparing legislative
ment revenues and expenditures. It also prepares proposals. The Bureau has five branches: Environ-
fiscal analyses for all propositions that appear on the mental and Natural Resources; Education and Hu-
California statewide ballot, including bond measures. man Services; Economics; General Law and Govern-
ment; and Information Services. It maintains a small
For more information about the LAO, office at the State Capitol in Room 5210 to make
please visit our website at www.lao.ca.gov or call us reference services conveniently available.
at 916-445-4656.
UCLA Anderson Forecast, December 2011 Seminar Members–109
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Seminar Members
City of El Segundo City of Hermosa Beach
El Segundo is a small coastline community equally re- The Los Angeles Magazine has named Hermosa an
nowned for its quaint, small town atmosphere as well "outstanding coastal town" praising many of our
as a thriving business environment that caters to some businesses and shops. From traditional Surf and Turf
of the region's most prestigious corporations. to more exotic cuisines, from Comedy to Jazz, Her-
mosa Beach has many fine dining and entertainment
Conveniently located just south of Los Angeles Inter- places from which to choose. Our hotel and lodging
national Airport, adjacent to the Pacific Ocean, and facilities offer breath taking ocean views and all the
quickly accessible to the 105 and 405 freeways, El comforts of home which are surrounded by a Mecca
Segundo is ideally situated between Los Angeles and of restaurants, upscale shops and tourist delights.
the South Bay beach communities. Come to Hermosa Beach, relax and enjoy the warmth
of our hospitality.
El Segundo prides itself on its excellent schools,
quality recreation programs, safe neighborhoods and
unparalleled city services.
It is also a haven for business, with 13 Fortune 500
companies and a diverse mix of aerospace firms,
high-tech businesses, professional service outfits, fine
restaurants and retailers.
Whether you are looking to relocate or start up, El
Segundo offers the ultimate combination of location,
amenities, and incentives for your business.
110–Seminar Members UCLA Anderson Forecast, December 2011
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Seminar Members
The State of California’s Department of Finance is Health Net, Inc. is among the nation’s largest publicly
responsible for submitting to the State’s fiscal year traded managed health care companies. Its mission
budget to the Governor in January of each year. The is to help people be healthy, secure and comfortable.
Department is part of the State’s Executive Branch The company’s health plans and government con-
and part of the Governor’s Administration. The Di- tracts subsidiaries provide health benefits to approxi-
rector of Finance is appointed by the Governor and is mately 6.7 million individuals across the country
his chief fiscal advisor. The Director sits as a member through group, individual, Medicare, Medicaid and
of the Governor’s cabinet and senior staff. Principal TRICARE and Veterans Affairs programs. Health
functions include: Net’s behavioral health subsidiary, MHN, provides
mental health benefits to approximately 7.0 million
Establish appropriate fiscal policies to carry out the individuals in all 50 states. The company’s subsidiar-
Administration’s Programs. ies also offer managed health care products related
Prepare, enact and administer the State’s Annual to prescription drugs, and offer managed health care
Financial Plan. product coordination for multi-region employers and
Analyze legislation which has a fiscal impact. administrative services for medical groups and self-
Develop and maintain the California State Account- funded benefits programs.
ing and Reporting System (CALSTARS).
Monitor/audit expenditures by State departments to
ensure compliance with approved standards and poli-
cies.
Develop economic forecasts and revenue estimates.
Develop population and enrollment estimates and
projections.
Review expenditures on data processing activities of
departments.
In addition, the Department of Finance interacts with
the Legislature through various reporting require-
ments, by presenting and defending the Governor’s
Budget and in the legislature.
The Department interacts with other State depart-
ments on a daily basis on terms of administering
the budget, reviewing fiscal proposals, establishing
accounting systems, auditing department expenditures
and communicating the Governor’s fiscal policy to
departments.
UCLA Anderson Forecast, December 2011 Seminar Members–111
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Seminar Members
The Employment Development Department’s La- The energy industry is changing rapidly and dramati-
bor Market Information Division (LMID) regularly cally. As global competition transforms the way com-
collects, analyzes, and publishes information about panies do business, energy issues are no longer simply
California’s labor market, which has approximately local, or even national. At the same time, its clear that
1,068,000 employers covered by Unemployment the importance of providing reliable local service has
Insurance and a civilian labor force of approximately never been more important.
16.6 million. In addition to employment and unem-
ployment data, LMID provides economic develop- Our heritage at Southern California Edison is based
ment and planning information; industry and occupa- on reliability. For more than 100 years we have
tional characteristics, trends, and wage information; provided high-quality, reliable electric service to more
and social and demographic information. Most of than 4.2 million business and residential customers
these data are available for the state and counties. over a 50,000 square mile service area in coastal,
Some data are available for other geographic regions central, and southern California.
a well.
Of course, recent changes in the California’s electric
In addition to basic labor market information, the industry have affected us as well. In 1997, as part
LMID provides technical assistance, training seminars of the restructuring of the electric industry in our
for data users, and standard and customized reports state, SCE sold its 12 fossil fuel generating stations
for state and sub-state geographic areas. Labor and overhauled nearly every aspect of its business to
market information is available electronically and in prepare for the changing environment. While we still
print. own and operate hydro and nuclear power facilities
that serve our area, our main role is that of power
For more information, visit our website at www. transmission and distribution. The power needed for
calmis.ca.gov or call 916-262-2162. our customers is largely purchased from the Cali-
fornia Power Exchange and provided by SCE to our
customers without a price markup.
At SCE we want you to know that even in times of
change, we retain our proven commitment to service,
reliability, innovation, and the community.
112–Seminar Members UCLA Anderson Forecast, December 2011
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Seminar Members
The Irvine Company is a nearly 150-year-old, privately
held best-of-class real estate investment company with
operations throughout California. Its management
structure is concentrated in two main operating groups:
Community Development, an affiliate responsible for the
planning and development of all for-sale residential hous-
ing communities and other land sales; and the Investment
Properties Group, which plans and guides the develop-
ment, marketing and management of the company’s large
and diverse statewide portfolio of retail, office, apartment
and resort properties.
•The Irvine Company is one of America’s most respected
and diversified private real estate companies.
•It owns and manages a high-quality investment portfolio
of nearly 95 million square feet that includes 116 apart-
ment communities, 484 office buildings, 41 retail centers,
and five yacht marinas.
•The portfolio also contains world-class resort proper-
ties including Pelican Hill®, which features 204 rooms
and suites, 128 villas and two 18-hole championship golf
courses overlooking the Pacific Ocean.
•Guided by an unwavering pursuit of excellence, the
company is highly respected for its stewardship and
master planning of The Irvine Ranch® in Orange County,
California.
•Donald Bren is Chairman of the Irvine Company. He
oversees a Board of Directors that includes some of the
nation’s most accomplished and respected business lead-
ers and former public officials.
UCLA Anderson Forecast, December 2011 Seminar Members–113
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114-Sponsors UCLA Anderson Forecast, December 2011
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Members
Corporate 6 Individual Member
California Energy Commission Alston & Bird, LLP
RPA American Beauty Development
The California Endowment Austrian Trade Commission
Bank Leumi USA
Corporate 4 BRE Properties, INC
ADP Broadway Federal Bank
City of Los Angeles Business First Books
IBIS World, Inc. Cal Recycle
Irvine Company California Air Resources Board
Southern California Assoc of Governments California Association of Realtors
California Department of Transportation
Corporate 3 California Housing Finance Agency
Ameron International California Public Utilities Commission
Center Bank California State Board of Equalization
City National Bank California State Polytechnic University, Pomona
City of Santa Monica California State University, Fullerton
Hanmi Bank California State University, Long Beach
Kia Motors America, Inc. California State University, Sacramento
Kilroy Realty Corporation California Steel Industries, Inc
Los Angeles Police Federal Credit Union Cathay Bank
McMaster-Carr Supply Company CB Richard Ellis
Mitsubishi Cement Corp. Chartwell Capital Solutions
Nara Bank Chicago Title
Pepperdine University Chu & Waters, LLP
Shelly Automotive Group City of Beverly Hills
State Compensation Insurance Fund City of Carlsbad
State Farm Insurance Co. City of Garden Grove
The Newhall Land and Farming Company City of New Orleans
Unified Western Grocers, Inc. City Of Sacramento
WCIRB City of San Diego
City of San Diego - Office of the IBA
City of Santa Clara
City of Torrance
CompWest Insurance Company
Consulate General of Japan
Cornerstone Real Estate Advisers LLC
UCLA Anderson Forecast, December 2011 Members - 115
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Members
County of San Diego Orange County Transportation Authority
Cox Communications, Inc. Pacific Western Bank
Crystal Cruises Parsons Brinckerhoff
CSU, Chico Pasadena Public Library
Desmond, Marcello & Amster Pepperdine University - Office of Instit
DMC Investment Group, Inc. PG&E
Far East National Bank Philip Durden
FDIC Preferred Employers Insurance Company
Fidelity Investments Money Management Inc. RBC Capital Markets
First California Bank Rio Tinto Minerals
Gilmore Bank San Diego Gas & Electric Co.
Golden Security Bank School Services of California Inc.
Goodwin Procter LLP SEIU Local 721
Granite Rock Company Stanford University
Harold Davidson & Associates Inc. State of Hawaii
Heritage Bank of Commerce Sully-Miller Contracting Co
Howard Hsieh Teichert Aggregates
HR&A Advisors, Inc. The Aerospace Corporation
JETRO, Los Angeles The Olson Company
Keefe, Bryette & Woods U.S. Court of Appeals
Kinecta Federal Credit Union United Methodist F.C.U.
KPMG University of California Library, Berkeley
Lehigh Southwest Cement Company University of California San Diego
Lloyd Management Corporation University of Cincinnati
Londre Marketing Consultants, LLC University of Hawaii Library
Los Angeles Public Library University of Richmond
Los Angeles Times USS-POSCO Industries
Mack 5 Visterra Credit Union
Massmann International Booksellers Vulcan Materials
Maynard Consulting Services Warland Investments
Merritt Santa Monica Wells Fargo & Co
Metals USA Wells Fargo Bank - West Covina
Metropolitan Water Dist Winreal Operating Co.
Monterey County Administrative Office Winzler & Kelly
Northern California Power Agency York University Libraries
Northwood Investors
Orange County Resources & Development
116 - Members UCLA Anderson Forecast, December 2011
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Speakers
Edward E. Leamer David Shulman
Director Senior Economist
Edward E. Leamer is the Chauncey J. Medberry Professor of David Shulman is currently managing member of his own
Management, Professor of Economics and Professor of Sta- LLC and engages in educational and charitable activi-
tistics at UCLA. He received a B.A. degree in mathematics ties, including being a Distinguished Visiting Professor at
from Princeton University and a Ph.D. degree in economics Baruch College and a Visiting Professor at the Univer-
and an M.A. degree in mathematics from the University of sity of Wisconsin. Dr. Shulman is currently a member of
Michigan. After serving as Assistant and Associate Professor NAREIT’s Real Estate Investment Advisory Council. He
at Harvard University he joined the University of California blogs at Shulmaven.blogspot.com. Shulman received a
at Los Angeles in 1975 as Professor of Economics and served bachelor’s degree from Baruch College in 1965, an MBA in
as Chair from 1983 to 1987. 1966 from the Graduate School of Management at UCLA;
and his Ph.D. in 1975 with a specialization in Finance.
In 1990 he moved to the Anderson Graduate School of
Management and was appointed to the Chauncey J. Med- From 1986 to 1997, Dr. Shulman was employed by Salomon
berry Chair. Professor Leamer is a Fellow of the American Brothers Inc. in various capacities. He was their director of
Academy of Arts and Sciences, and a Fellow of the Econo- real estate research from 1987 to 1991 and became Chief
metric Society. He is a Research Associate of the National Equity Strategist from 1992 to 1997. As Chief Equity
Bureau of Economic Research and a visiting scholar at the Strategist, he was responsible for developing the firms
International Monetary Fund and the Board of Governors of overall equity market view and maintaining their list of
the Federal Reserve System. Dr. Leamer has published over recommended stocks. Dr. Shulman was widely quoted in
100 articles and 4 books . This research has been supported print and electronic media and he coined the terms “Gold-
by continuous grants for over 25 years from the National ilocks Economy” and “New Paradigm Economy.” In 1991,
Science Foundation, the Sloan Foundation and the Russell he was named a Managing Director; and in 1990, he won
Sage Foundation. His research papers in econometrics have the First Annual Graaskamp Award for Excellence in real
been collected in Sturdy Econometrics, published in the estate research from the Pension Real Estate Association.
Edward Elgar Series of Economists of the 20th Century.
In March 2005, Dr. Shulman retired from Lehman
His research in international economics and econometric
Brothers, where he was Managing Director and head
methodology has been discussed in a chapter written by
Real Estate Investment Trust Analyst. Before joining
Herman Leonard and Keith Maskus in New Horizons in
Lehman Brothers in 2000, he was a member and Senior
Economic Thought: Appraisals of Leading Economists.
Vice President at Ulysses Management LLC from 1998-
Recent research interests of Professor Leamer include the
1999, an Investment Manager of a private investment
North American Free Trade Agreement, the dismantling
partnership and an offshore corporation, whose invest-
of the Swedish welfare state, the economic integration of
ment capital approximated $1 billion at the end of 1999.
Eastern Europe, Taiwan and the Mainland, and the impact
of globalization on the U.S. economy.
UCLA Anderson Forecast, December 2011 Speakers–117
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Speakers
Jerry Nickelsburg William Yu
Senior Economist Economist
Jerry Nickelsburg joined the UCLA Anderson Forecast in William Yu joined the UCLA Anderson Forecast in 2011
2006 as an economist. At the Anderson Forecast he plays a as an economist. At Forecast he focuses on the economic
key role in the economic modeling and forecasting of the Los modeling and forecasting of Los Angeles and other re-
Angeles, Southern California and California economies. He gional economies in California. He also conducts research
has conducted special studies into the future of manufactur- and forecast on Asian emerging economies, especially
ing in Los Angeles, the distribution of income, the economic China, and their impacts on the US economy. His research
impact of the writer’s strike, the aerospace industry, the interests include a wide range of economic and financial
undocumented construction and manufacturing labor force, issues, such as time series econometrics, stock, bond and
the ports of Los Angeles and Long Beach and the garment commodity price dynamics, public health, human capital,
industry, focusing on the development of new data and the higher education, and economic sustainability. He has
application of economic theory and statistical methods to published over a dozen research articles in Journal of
sectoral issues. He is a regular presenter at the Los Angeles Forecasting, International Journal of Forecasting, Journal
Mayor’s Economic Conference and has been cited in the of International Money and Finance, Journal of Health
national and local media including the Financial Times, New Care Finance, Journal of Education Finance, Economic
York Times, Los Angeles Times, Reuters, Variety, CNBC, Affairs, and Global Economic Review, etc. He has also
NBC, PBS, and L.A. Business Journal. served as a reviewer for various journals, such as Jour-
nal of Money, Credit, and Banking, Journal of Banking
He received his Ph.D. in economics from the University of
and Finance, Japan and the World Economy, and Energy
Minnesota in 1980 specializing in monetary economics and
Journal, etc.
econometrics. He was formerly a professor of Economics at
the University of Southern California and has held executive He received his bachelor’s degree in finance from Na-
positions with McDonnell Douglas, Flight Safety Interna- tional Taiwan University in 1995 and was an analyst in
tional, and Flight Safety Boeing during a fifteen year span Fubon Financial Holding in Taipei from 1997 to 2000. In
in the aviation business. 2006, he received his Ph.D. degree in economics from the
University of Washington where he was also an econom-
From 2000 to 2006, he was the Managing Principal of Deep
ics instructor and won two distinguished teaching awards.
Blue Economics, a consulting firm he founded. He held
In 2006, he worked for the Frank Russell Investment
a position with the Federal Reserve Board of Governors
Group for Treasury and corporate yields modeling and
developing forecasting tools, and has advised banks, in-
forecasting. From 2006 to 2011, he served as an assistant
vestors and financial institutions. He has been the recipient
and an associate professor of economics at Winona State
of the Korda Fellowship, USC Outstanding Teacher, India
University where he taught courses including interna-
Chamber of Commerce Jubilee Lecturer and is a Fulbright
tional economics, forecasting methods, intermediate
Scholar. He has published over 40 articles on monetary
macroeconomics, introductory macroeconomics, money
economics, econometrics, aviation economics, and industrial
and banking, and Asian economies.
organization.
118–Speakers UCLA Anderson Forecast, December 2011
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