# Autocorrelation-Example-with-Price-level-as-a-function-of-Money-Supply

Document Sample

```					Intro to CPIMZM.xls
This workbook uses money supply and price level data to practice with autocorrelation concepts. The data sources are contained in the three data sheets, then grouped in the Analysis sheet. The example was created in 2000, so the numbers are a bit dated.

A bigger concern is the extremely simple theory applied. We stress that this example is simply a teaching device that gives students practice in applying the introductory methods on autocorrelation Obviously, much more sophisticated handling of trend and the DGP is required than we are using here. That said, the example enables the student to put into play tests for autocorrelation (including using the P Value Calculator add-in to run the The Analysis sheet has a series of questions for you to walk through. Answers are available in the Answers folder of this CD ROM.

troductory methods on autocorrelation reviewed in the text.

he P Value Calculator add-in to run the DW test) and transformation of data to run FGLS.

Current Business Cycle (since Trough) Per Business Cycle Dating Committee of the NBER (see BusCycleData sheet) 3/91 to latest Data as of Jun-2000 available up to Apr-2000 Do the 10 Steps to see an application of autocorrelation analysis. 1) Quantity Theory (MV = PY) implies P = b0 + b1M + e. Price Level measured by CPI (see CPIData sheet); M measured by MZM (see MoneyData sheet).
SCROLL RIGHT TO CONTINUE

2) Data collected and organized
DATE Excel Date MZMNS CPI 1991.03 Mar-91 2326.52 1991.04 Apr-91 2357.26 1991.05 May-91 2349.91 1991.06 Jun-91 2377.69 1991.07 Jul-91 2390.79 1991.08 Aug-91 2401.74 1991.09 Sep-91 2407.94 1991.1 Oct-91 2434.12 1991.11 Nov-91 2478.97 1991.12 Dec-91 2519.93 1992.01 2543.91 This example is used asJan-92 a teaching device, giving the 1992.02 Feb-92 2583.8 student an opportunity to put in practice the 1992.03 Mar-92 Handling trend and 2615.01 procedures described in the text. 1992.04 Apr-92 2647.85 other complications implicit in this example require May-92 2642.89 methods1992.05 the scope of this book. beyond 1992.06 Jun-92 2658.34 1992.07 Jul-92 2680.63 1992.08 Aug-92 2710.47 1992.09 Sep-92 2724.77 1992.1 Oct-92 2746.67 1992.11 Nov-92 2780.66 1992.12 Dec-92 2796.4 1993.01 Jan-93 2787.83 1993.02 Feb-93 2780.71 1993.03 Mar-93 2792.54 1993.04 Apr-93 2816.65 1993.05 May-93 2824.14 1993.06 Jun-93 2837.96 1993.07 Jul-93 2846.74 1993.08 Aug-93 2856.1 1993.09 Sep-93 2862.9 1993.1 Oct-93 2879.75 1993.11 Nov-93 2914.02 1993.12 Dec-93 2942.23 1994.01 Jan-94 2935.18 1994.02 Feb-94 2912.78 1994.03 Mar-94 2929.64 1994.04 Apr-94 2956.48 1994.05 May-94 2921.92 1994.06 Jun-94 2915.76 1994.07 Jul-94 2925.58 1994.08 Aug-94 2913.9 1994.09 Sep-94 2900.53

3) Run OLS regression of CPI on MZM. Make a chart o
You may use LINEST or execute Tools: Data Analysis: Regression 135 135.2 135.6 136 136.2 136.6 137.2 137.4 137.8 137.9 138.1 138.6 139.3 139.5 139.7 140.2 140.5 140.9 141.3 141.8 142 141.9 142.6 143.1 143.6 144 144.2 144.4 144.4 144.8 145.1 145.7 145.8 145.8 146.2 146.7 147.2 147.4 147.5 148 148.4 149 149.4

1994.1 1994.11 1994.12 1995.01 1995.02 1995.03 1995.04 1995.05 1995.06 1995.07 1995.08 1995.09 1995.1 1995.11 1995.12 1996.01 1996.02 1996.03 1996.04 1996.05 1996.06 1996.07 1996.08 1996.09 1996.1 1996.11 1996.12 1997.01 1997.02 1997.03 1997.04 1997.05 1997.06 1997.07 1997.08 1997.09 1997.1 1997.11 1997.12 1998.01 1998.02 1998.03 1998.04 1998.05 1998.06 1998.07 1998.08 1998.09 1998.1 1998.11 1998.12 1999.01 1999.02 1999.03 1999.04 1999.05 1999.06

Oct-94 Nov-94 Dec-94 Jan-95 Feb-95 Mar-95 Apr-95 May-95 Jun-95 Jul-95 Aug-95 Sep-95 Oct-95 Nov-95 Dec-95 Jan-96 Feb-96 Mar-96 Apr-96 May-96 Jun-96 Jul-96 Aug-96 Sep-96 Oct-96 Nov-96 Dec-96 Jan-97 Feb-97 Mar-97 Apr-97 May-97 Jun-97 Jul-97 Aug-97 Sep-97 Oct-97 Nov-97 Dec-97 Jan-98 Feb-98 Mar-98 Apr-98 May-98 Jun-98 Jul-98 Aug-98 Sep-98 Oct-98 Nov-98 Dec-98 Jan-99 Feb-99 Mar-99 Apr-99 May-99 Jun-99

2898.67 2907.77 2915.55 2895.83 2853.51 2850.34 2866.06 2842.94 2882.68 2908.97 2925.61 2932.99 2942.42 2967.58 3000.4 3005.15 3009.82 3058.51 3080.69 3049.95 3086.35 3105.96 3118.99 3121.63 3129.62 3169.23 3214.71 3213.83 3218.89 3259.28 3284.85 3247.43 3282.26 3305.2 3347.65 3362.36 3384.03 3429.29 3482.64 3499.29 3525.61 3581.55 3631.92 3613.19 3657.89 3680.87 3729.72 3776.19 3838.41 3919.2 3997.81 4018.67 4050.98 4085.63 4136.55 4103.1 4136.02

149.5 149.7 149.7 150.3 150.9 151.4 151.9 152.2 152.5 152.5 152.9 153.2 153.7 153.6 153.5 154.4 154.9 155.7 156.3 156.6 156.7 157 157.3 157.8 158.3 158.6 158.6 159.1 159.6 160 160.2 160.1 160.3 160.5 160.8 161.2 161.6 161.5 161.3 161.6 161.9 162.2 162.5 162.8 163 163.2 163.4 163.6 164 164 163.9 164.3 164.5 165 166.2 166.2 166.2

1999.07 1999.08 1999.09 1999.1 1999.11 1999.12 2000.01 2000.02 2000.03 2000.04

Jul-99 Aug-99 Sep-99 Oct-99 Nov-99 Dec-99 Jan-00 Feb-00 Mar-00 Apr-00

4150.18 4183.93 4189.25 4217.69 4270.26 4342.12 4358.89 4352.83 4416.24 4463.73

166.7 167.1 167.9 168.2 168.3 168.3 168.7 169.7 171.1 171.2

neyData sheet).
SCROLL RIGHT TO CONTINUE

n MZM. Make a chart of observed values and fitted OLS line.

4) Use the OLS coefficients t

ta Analysis: Regression

Or get the residuals from Tools: Data A

SCROLL RIGHT TO CONTINUE

4) Use the OLS coefficients to find residuals

THREE DIAGNOSTIC TESTS 5) Create a residuals on lagged residuals graph

Or get the residuals from Tools: Data Analysis: Regression

SCROLL RIGHT TO CONTINUE

residuals graph

6) Run an estimated rho test

Use the P Value Calculator add-in

7) Run the Durbin Watson test

8) Correct for first-order autocorrelation Transform the original data. Run OLS on the transformed data.

9) Compare the OLS and FGLS estimates Find Predicted Y using OLS and FGLS coefficients. Make a chart with CPI and MZM observed values with OLS and GLS Predicted CPI lines.

10) Testing for AR1 autocorrelated errors in transformed model Run the three diagnostic tests on the transformed model. What do you conclude?

http://www.nber.org/cycles.html

Reformatted and organized in Excel.

US Business Cycle Expansions and Contractions
Contractions (recessions) start at the peak of a business cycle and end at the trough. BUSINESS CYCLE REFERENCE DATES DURATION IN MONTHS Contraction Expansion Cycle Trough from Trough from Previous Trough to Previous Peak from Peak Next Peak Trough Previous Peak Trough Peak December 1854 June 1857 30 December 1858 October 1860 18 22 48 40 June 1861 April 1865 8 46 30 54 December 1867 June 1869 32 18 78 50 December 1870 October 1873 18 34 36 52 March May April May June June December August June January December March July July November March June October October May April February November March July November March 1879 1885 1888 1891 1894 1897 1900 1904 1908 1912 1914 1919 1921 1924 1927 1933 1938 1945 1949 1954 1958 1961 1970 1975 1980 March March July January December June September May January January August January May October August May February November July August April December November January July 1882 1887 1890 1893 1895 1899 1902 1907 1910 1913 1918 1920 1923 1926 1929 1937 1945 1948 1953 1957 1960 1969 1973 1980 1981 1990 65 38 13 10 17 18 18 23 13 24 23 7 18 14 13 43 13 8 11 10 8 10 11 16 6 16 8 36 22 27 20 18 24 21 33 19 12 44 10 22 27 21 50 80 37 45 39 24 106 36 58 12 92 99 74 35 37 37 36 42 44 46 43 35 51 28 36 40 64 63 88 48 55 47 34 117 52 64 28 100 101 60 40 30 35 42 39 56 32 36 67 17 40 41 34 93 93 45 56 49 32 116 47 74 18 108

The determination that the last recession ended in March 1991 is the most recent decision of the Business Cycle Dating Committee of the N

1982 July 1991

Average, all cycles: 1854-1991 (31 cycles) 1854-1919 (16 cycles) 1919-1945 (6 cycles) 1945-1991 (9 cycles)

18 22 18 11

35 27 35 50

53 48 53 61

53* 49** 53 61

Average, peacetime cycles: 1854-1991 (26 cycles) 1854-1919 (14 cycles) 1919-1945 (5 cycles) 1945-1991 (7 cycles) * 30 cycles. ** 15 cycles. *** 25 cycles. **** 13 cycles.

19 22 20 11

29 24 26 43

48 46 46 53

48*** 47**** 45 53

7/81

11/82 Contraction Expansion 16 months 92 months

Figures printed in bold italic are the wartime expansions (Civil War, World Wars I and II, Korean War, and Vietnam War); the postwar contra From the U.S. Department of Commerce, Survey of Current Business, October 1994, Table C-51. -----------------------------------------------------------------------Announcement dates: The March 1991 trough was announced December 22, 1992. The July 1990 peak was announced April 25, 1991. The November 1982 trough was announced July 8, 1983. The July 1981 peak was announced January 6, 1982. The July 1980 trough was announced July 8, 1981. The January 1980 peak was announced June 3, 1980.

The NBER does not define a recession in terms of two consecutive quarters of decline in real GNP. Rather, a recession is a recurring period A growth recession is a recurring period of slow growth in total output, income, employment, and trade, usually lasting a year or more. A gro A depression is a recession that is major in both scale and duration. Further discussion of these concepts can be found in the NBER book, Source: Public Information Office National Bureau of Economic Research, Inc. 1050 Massachusetts Avenue Cambridge MA 02138 USA 617-868-3900

Cycle Dating Committee of the National Bureau of Economic Research.

7/90

3/91

Expansion months

Contraction 8 months

Expansion 100 months (so far)

Vietnam War); the postwar contractions, and the full cycles that include the wartime expansions.

r, a recession is a recurring period of decline in total output, income, employment, and trade, usually lasting from six months to a year, and marked by wide ually lasting a year or more. A growth recession may encompass a recession, in which case the slowdown usually begins before the recession starts, but e can be found in the NBER book, Business Cycles, Inflation and Forecasting, 2nd edition, by Geoffrey H. Moore, 1983, Ballinger Publishing Co., Cambridge

months to a year, and marked by widespread contractions in many sectors of the economy. egins before the recession starts, but ends at about the same time. Slowdowns also may occur without recession, in which case the economy continues to 83, Ballinger Publishing Co., Cambridge, MA.

n which case the economy continues to grow, but at a pace significantly below its long-run growth

http://146.142.4.24/cgi-bin/surveymost?cu All Items (first choice)

Data extracted on: June 12, 2000 (01:56 PM)

-----------------------------------------------------------------------Consumer Price Index-All Urban Consumers

Series Catalog: Series ID : CUUR0000SA0 Not Seasonally Adjusted Area : U.S. city average Item : All items Base Period : 1982-84=100

Data: Year 1913 1914 1915 1916 1917 1918 1919 1920 1921 1922 1923 1924 1925 1926 1927 1928 1929 1930 1931 1932 1933 1934 1935 1936 1937 1938 1939 1940 1941 1942 1943 Jan 9.8 10 10.1 10.4 11.7 14 16.5 19.3 19 16.9 16.8 17.3 17.3 17.9 17.5 17.3 17.1 17.1 15.9 14.3 12.9 13.2 13.6 13.8 14.1 14.2 14 13.9 14.1 15.7 16.9 Feb 9.8 9.9 10 10.4 12 14.1 16.2 19.5 18.4 16.9 16.8 17.2 17.2 17.9 17.4 17.1 17.1 17 15.7 14.1 12.7 13.3 13.7 13.8 14.1 14.1 13.9 14 14.1 15.8 16.9 Mar 9.8 9.9 9.9 10.5 12 14 16.4 19.7 18.3 16.7 16.8 17.1 17.3 17.8 17.3 17.1 17 16.9 15.6 14 12.6 13.3 13.7 13.7 14.2 14.1 13.9 14 14.2 16 17.2 Apr 9.8 9.8 10 10.6 12.6 14.2 16.7 20.3 18.1 16.7 16.9 17 17.2 17.9 17.3 17.1 16.9 17 15.5 13.9 12.6 13.3 13.8 13.7 14.3 14.2 13.8 14 14.3 16.1 17.4 May 9.7 9.9 10.1 10.7 12.8 14.5 16.9 20.6 17.7 16.7 16.9 17 17.3 17.8 17.4 17.2 17 16.9 15.3 13.7 12.6 13.3 13.8 13.7 14.4 14.1 13.8 14 14.4 16.3 17.5 Jun 9.8 9.9 10.1 10.8 13 14.7 16.9 20.9 17.6 16.7 17 17 17.5 17.7 17.6 17.1 17.1 16.8 15.1 13.6 12.7 13.4 13.7 13.8 14.4 14.1 13.8 14.1 14.7 16.3 17.5 Jul 9.9 10 10.1 10.8 12.8 15.1 17.4 20.8 17.7 16.8 17.2 17.1 17.7 17.5 17.3 17.1 17.3 16.6 15.1 13.6 13.1 13.4 13.7 13.9 14.5 14.1 13.8 14 14.7 16.4 17.4

1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000

17.4 17.8 18.2 21.5 23.7 24 23.5 25.4 26.5 26.6 26.9 26.7 26.8 27.6 28.6 29 29.3 29.8 30 30.4 30.9 31.2 31.8 32.9 34.1 35.6 37.8 39.8 41.1 42.6 46.6 52.1 55.6 58.5 62.5 68.3 77.8 87 94.3 97.8 101.9 105.5 109.6 111.2 115.7 121.1 127.4 134.6 138.1 142.6 146.2 150.3 154.4 159.1 161.6 164.3 168.7

17.4 17.8 18.1 21.5 23.5 23.8 23.5 25.7 26.3 26.5 26.9 26.7 26.8 27.7 28.6 28.9 29.4 29.8 30.1 30.4 30.9 31.2 32 32.9 34.2 35.8 38 39.9 41.3 42.9 47.2 52.5 55.8 59.1 62.9 69.1 78.9 87.9 94.6 97.9 102.4 106 109.3 111.6 116 121.6 128 134.8 138.6 143.1 146.7 150.9 154.9 159.6 161.9 164.5 169.7

17.4 17.8 18.3 21.9 23.4 23.8 23.6 25.8 26.3 26.6 26.9 26.7 26.8 27.8 28.8 28.9 29.4 29.8 30.1 30.5 30.9 31.3 32.1 33 34.3 36.1 38.2 40 41.4 43.3 47.8 52.7 55.9 59.5 63.4 69.8 80.1 88.5 94.5 97.9 102.6 106.4 108.8 112.1 116.5 122.3 128.7 135 139.3 143.6 147.2 151.4 155.7 160 162.2 165 171.1

17.5 17.8 18.4 21.9 23.8 23.9 23.6 25.8 26.4 26.6 26.8 26.7 26.9 27.9 28.9 29 29.5 29.8 30.2 30.5 30.9 31.4 32.3 33.1 34.4 36.3 38.5 40.1 41.5 43.6 48 52.9 56.1 60 63.9 70.6 81 89.1 94.9 98.6 103.1 106.9 108.6 112.7 117.1 123.1 128.9 135.2 139.5 144 147.4 151.9 156.3 160.2 162.5 166.2 171.2

17.5 17.9 18.5 21.9 23.9 23.8 23.7 25.9 26.4 26.7 26.9 26.7 27 28 28.9 29 29.5 29.8 30.2 30.5 30.9 31.4 32.3 33.2 34.5 36.4 38.6 40.3 41.6 43.9 48.6 53.2 56.5 60.3 64.5 71.5 81.8 89.8 95.8 99.2 103.4 107.3 108.9 113.1 117.5 123.8 129.2 135.6 139.7 144.2 147.5 152.2 156.6 160.1 162.8 166.2

17.6 18.1 18.7 22 24.1 23.9 23.8 25.9 26.5 26.8 26.9 26.7 27.2 28.1 28.9 29.1 29.6 29.8 30.2 30.6 31 31.6 32.4 33.3 34.7 36.6 38.8 40.6 41.7 44.2 49 53.6 56.8 60.7 65.2 72.3 82.7 90.6 97 99.5 103.7 107.6 109.5 113.5 118 124.1 129.9 136 140.2 144.4 148 152.5 156.7 160.3 163 166.2

17.7 18.1 19.8 22.2 24.4 23.7 24.1 25.9 26.7 26.8 26.9 26.8 27.4 28.3 29 29.2 29.6 30 30.3 30.7 31.1 31.6 32.5 33.4 34.9 36.8 39 40.7 41.9 44.3 49.4 54.2 57.1 61 65.7 73.1 82.7 91.6 97.5 99.9 104.1 107.8 109.5 113.8 118.5 124.4 130.4 136.2 140.5 144.4 148.4 152.5 157 160.5 163.2 166.7

Aug 9.9 10.2 10.1 10.9 13 15.4 17.7 20.3 17.7 16.6 17.1 17 17.7 17.4 17.2 17.1 17.3 16.5 15.1 13.5 13.2 13.4 13.7 14 14.5 14.1 13.8 14 14.9 16.5 17.3

Sep 10 10.2 10.1 11.1 13.3 15.7 17.8 20 17.5 16.6 17.2 17.1 17.7 17.5 17.3 17.3 17.3 16.6 15 13.4 13.2 13.6 13.7 14 14.6 14.1 14.1 14 15.1 16.5 17.4

Oct 10 10.1 10.2 11.3 13.5 16 18.1 19.9 17.5 16.7 17.3 17.2 17.7 17.6 17.4 17.2 17.3 16.5 14.9 13.3 13.2 13.5 13.7 14 14.6 14 14 14 15.3 16.7 17.4

Nov 10.1 10.2 10.3 11.5 13.5 16.3 18.5 19.8 17.4 16.8 17.3 17.2 18 17.7 17.3 17.2 17.3 16.4 14.7 13.2 13.2 13.5 13.8 14 14.5 14 14 14 15.4 16.8 17.4

Dec 10 10.1 10.3 11.6 13.7 16.5 18.9 19.4 17.3 16.9 17.3 17.3 17.9 17.7 17.3 17.1 17.2 16.1 14.6 13.1 13.2 13.4 13.8 14 14.4 14 14 14.1 15.5 16.9 17.4

Ann 9.9 10 10.1 10.9 12.8 15.1 17.3 20 17.9 16.8 17.1 17.1 17.5 17.7 17.4 17.1 17.1 16.7 15.2 13.7 13 13.4 13.7 13.9 14.4 14.1 13.9 14 14.7 16.3 17.3

17.7 18.1 20.2 22.5 24.5 23.8 24.3 25.9 26.7 26.9 26.9 26.8 27.3 28.3 28.9 29.2 29.6 29.9 30.3 30.7 31 31.6 32.7 33.5 35 37 39 40.8 42 45.1 50 54.3 57.4 61.2 66 73.8 83.3 92.3 97.7 100.2 104.5 108 109.7 114.4 119 124.6 131.6 136.6 140.9 144.8 149 152.9 157.3 160.8 163.4 167.1

17.7 18.1 20.4 23 24.5 23.9 24.4 26.1 26.7 26.9 26.8 26.9 27.4 28.3 28.9 29.3 29.6 30 30.4 30.7 31.1 31.6 32.7 33.6 35.1 37.1 39.2 40.8 42.1 45.2 50.6 54.6 57.6 61.4 66.5 74.6 84 93.2 97.9 100.7 105 108.3 110.2 115 119.8 125 132.7 137.2 141.3 145.1 149.4 153.2 157.8 161.2 163.6 167.9

17.7 18.1 20.8 23 24.4 23.7 24.6 26.2 26.7 27 26.8 26.9 27.5 28.3 28.9 29.4 29.8 30 30.4 30.8 31.1 31.7 32.9 33.7 35.3 37.3 39.4 40.9 42.3 45.6 51.1 54.9 57.9 61.6 67.1 75.2 84.8 93.4 98.2 101 105.3 108.7 110.3 115.3 120.2 125.6 133.5 137.4 141.8 145.7 149.5 153.7 158.3 161.6 164 168.2

17.7 18.1 21.3 23.1 24.2 23.8 24.7 26.4 26.7 26.9 26.8 26.9 27.5 28.4 29 29.4 29.8 30 30.4 30.8 31.2 31.7 32.9 33.8 35.4 37.5 39.6 40.9 42.4 45.9 51.5 55.3 58 61.9 67.4 75.9 85.5 93.7 98 101.2 105.3 109 110.4 115.4 120.3 125.9 133.8 137.8 142 145.8 149.7 153.6 158.6 161.5 164 168.3

17.8 18.2 21.5 23.4 24.1 23.6 25 26.5 26.7 26.9 26.7 26.8 27.6 28.4 28.9 29.4 29.8 30 30.4 30.9 31.2 31.8 32.9 33.9 35.5 37.7 39.8 41.1 42.5 46.2 51.9 55.5 58.2 62.1 67.7 76.7 86.3 94 97.6 101.3 105.3 109.3 110.5 115.4 120.5 126.1 133.8 137.9 141.9 145.8 149.7 153.5 158.6 161.3 163.9 168.3

17.6 18 19.5 22.3 24.1 23.8 24.1 26 26.5 26.7 26.9 26.8 27.2 28.1 28.9 29.1 29.6 29.9 30.2 30.6 31 31.5 32.4 33.4 34.8 36.7 38.8 40.5 41.8 44.4 49.3 53.8 56.9 60.6 65.2 72.6 82.4 90.9 96.5 99.6 103.9 107.6 109.6 113.6 118.3 124 130.7 136.2 140.3 144.5 148.2 152.4 156.9 160.5 163 166.6

http://www.stls.frb.org/fred/data/monetary/mzmns

Money Zero Maturity Money Stock (MZM) Not Seasonally Adjusted Billions of Dollars Source: Federal Reserve Bank of St. Louis Downloaded 2000. DATE MZMNS 1991.03 2326.52 1991.04 2357.26 1991.05 2349.91 1991.06 2377.69 1991.07 2390.79 1991.08 2401.74 1991.09 2407.94 1991.1 2434.12 1991.11 2478.97 1991.12 2519.93 1992.01 2543.91 1992.02 2583.8 1992.03 2615.01 1992.04 2647.85 1992.05 2642.89 1992.06 2658.34 1992.07 2680.63 1992.08 2710.47 1992.09 2724.77 1992.1 2746.67 1992.11 2780.66 1992.12 2796.4 1993.01 2787.83 1993.02 2780.71 1993.03 2792.54 1993.04 2816.65 1993.05 2824.14 1993.06 2837.96 1993.07 2846.74 1993.08 2856.1 1993.09 2862.9 1993.1 2879.75 1993.11 2914.02 1993.12 2942.23 1994.01 2935.18 1994.02 2912.78 1994.03 2929.64 1994.04 2956.48 1994.05 2921.92 1994.06 2915.76 1994.07 2925.58 1994.08 2913.9 1994.09 2900.53 1994.1 2898.67 1994.11 2907.77 1994.12 2915.55 1995.01 2895.83 1995.02 2853.51

Why MZM as a measure of money stock? Why not M1? "Readers are cautioned that since early 1994 the level and growth of M1 have bee For analytical purposes, MZM largely replaces M1." Notes section of Monetary Trends, p. 19.

1995.03 1995.04 1995.05 1995.06 1995.07 1995.08 1995.09 1995.1 1995.11 1995.12 1996.01 1996.02 1996.03 1996.04 1996.05 1996.06 1996.07 1996.08 1996.09 1996.1 1996.11 1996.12 1997.01 1997.02 1997.03 1997.04 1997.05 1997.06 1997.07 1997.08 1997.09 1997.1 1997.11 1997.12 1998.01 1998.02 1998.03 1998.04 1998.05 1998.06 1998.07 1998.08 1998.09 1998.1 1998.11 1998.12 1999.01 1999.02 1999.03 1999.04 1999.05 1999.06 1999.07 1999.08 1999.09 1999.1 1999.11

2850.34 2866.06 2842.94 2882.68 2908.97 2925.61 2932.99 2942.42 2967.58 3000.4 3005.15 3009.82 3058.51 3080.69 3049.95 3086.35 3105.96 3118.99 3121.63 3129.62 3169.23 3214.71 3213.83 3218.89 3259.28 3284.85 3247.43 3282.26 3305.2 3347.65 3362.36 3384.03 3429.29 3482.64 3499.29 3525.61 3581.55 3631.92 3613.19 3657.89 3680.87 3729.72 3776.19 3838.41 3919.2 3997.81 4018.67 4050.98 4085.63 4136.55 4103.1 4136.02 4150.18 4183.93 4189.25 4217.69 4270.26

1999.12 2000.01 2000.02 2000.03 2000.04

4342.12 4358.89 4352.83 4416.24 4463.73

94 the level and growth of M1 have been depressed by retail sweep programs . . .

```
DOCUMENT INFO
Shared By:
Categories:
Tags:
Stats:
 views: 91 posted: 11/28/2009 language: English pages: 40
Description: Autocorrelation-Example-with-Price-level-as-a-function-of-Money-Supply