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Micro Based Exchange Rate Forecasting

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Micro Based Exchange Rate Forecasting Powered By Docstoc
					Dynamic Effects of Government Spending on
Foreign Trade




                    Master Thesis Presentation




 Professor Moisa Altar, PhD                   Student: Florea Adina Maria




                               Bucharest
                              July 13, 2008
       TABLE OF CONTENT



• Introduction
• Literature review
• Testing Strateg
      Preliminary Analysis
      Removing seasonability
      Measuring correlation
      Testing Co Integration
      Testing for Causality
      A VaR Model
• Theoretical Model
      • About DSGE models
      • The model
      • Solving an RBC model
• Conclusions
• Bibliography
                                                                                        Introduction




                                                                  Introduction


   The present paper studies the dynamic effects of a temporary increase in government
    spending on foreign trade.

    First, it seeks to establish empirically how the exchange rate, the terms of trade and the
    trade balance (net exports) respond to an exogenous increase in government spending.

   Second, it rationalizes these responses within a stochastic general equilibrium model
    which features price rigidities and thus allows for a potentially important role of monetary
    policy
       TABLE OF CONTENT



• Introduction
• Literature review
• Testing Strategy
                    Preliminary Analysis
     Removing seasonability
     Measuring correlation
     Testing Co Integration
     Testing for Causality
     A VaR Model
• Theoretical Model
     • About DSGE models
     • The model
     • Solving an RBC model
• Conclusions
• Bibliography
                                                                                   Literature Review




    Literature Review



   Based on Vector Autoregressions (VAR), empirical investigations of the dynamic effects of
    fiscal policy in a closed economy context was numerous.

   Attempts have a been made to account for this evidence using different versions of
    stochastic general equilibrium models, e.g. Fata´s and Mihov (2001), Burnside et al.
    (2004) and Galı´ et al.(2005).

   Little evidence, has been put forward regarding the dynamic effects of
    government spending on foreign trade. Exceptions are Kim and Roubini (2003) and
    Giuliodori and Beetsma (2004), who do not, explore their empirical findings within a
    formal theoretical framework.

    Canzoneri et al. (2003) provide a VAR analysis of the effects of fiscal policy on foreign
    trade and, although they analyze their findings within a general equilibrium model, they
    make the restrictive assumption that trade is always balanced.
       TABLE OF CONTENT



• Introduction
• Literature review
• Testing Strategy
                    Preliminary Analysis
     Removing seasonability
     Measuring correlation
     Testing Co Integration
     Testing for Causality
     A VaR Model
• Theoretical Model
     • About DSGE models
     • The model
     • Solving an RBC model
• Conclusions
• Bibliography
                                                                              Testing Strategy




                                                           Testing Strategy




Preliminary Removig       Measuring     Testing         Testing       VaR
 Analysis   seasonability Correlation   CoIntegration   Causality     Model
                                                                                                       VaR Model




                                                       Prelimi   Removi    Measu    Testing   Testin     Va
                                                        nary     g         ring               g          R
    Preliminary Analysis                               Analysi   season    Correl
                                                                                    CoInteg
                                                                                    ration    Causa      Mo
                                                         s       ability   ation              lity       del




   By assessing the time series conclusions can be made, both individual and related to each
    other, about the characteristics of the time series. Future conclusions can also be
    compared to test the plausibility of the findings .
   When working with statistical data it is important to assess the data by doing a
    graphical analysis . By doing this we can find out the characteristics of the series.
    When working with time series it could be important if the series is stationary or
    non-stationary. A stationary time series is having a constant mean and a constant
    variance. A non-stationary time series have booth a varying mean and variance
                                                                                               VaR Model




Preliminary Analysis

               Mean       Media    Maximu      Minimu     St.Deviatio   Skewnes     Kurtosi
                          n        m           m          n             s           s
  Exhange      0.471655   0.4714   0.664696    0.351431   0.073939      0.652313    3.263714
  rate                    09
  GDP          4.542360   4.5512   4.662212    4.386703   0.077326      -0.205011   2.021476
                          58
  Governmen    6.723044   6.8163   7.023225    6.287115   0.229315      -0.472499   1.762508
  t Spending              23
  Private      8.866546   8.8547   9.127926    8.620724   0.165382      -0.012440   1.545872
  Spending                66
  Terms of     -0.03017   -        0.023209    -0.07283   0.019904      -0.071568   3.305647
  Trade                   0.0295
                          6
  Exports      -2.26755   -        -2.150777   -2.36398   0.065956      0.106906    1.610720
                          2.2781
                          5
  Private      7.134391   7.1637   7.489188    6.688977   0.258951      -0.303227   1.603231
  Investment              94
  Private      8.670441   8.6514   9.923671    8.463391   0.147886      0.144053    1.646388
  Consumptio              21
  n




 Conclusions: private spending, government spending, terms of trade and exchange series
                     has a leptokurtosis distribution as the Kurtosis >3
              the other series has a platy kurtosis distribution( Kurtosis <3 )
                                                                                               Removing seasonability




                                                        Prelimi   Removi    Measu    Testing        Testin    Va
                                                         nary     g         ring                    g         R
    Removing seasonability                              Analysi   season    Correl
                                                                                     CoInteg
                                                                                     ration         Causa     Mo
                                                          s       ability   ation                   lity      del




    Time series that are based on monthly or quarterly data often follow a cyclical behavior,
     which repeats itself; this is called seasonality (Quantitative Micro Software, 2005).
     Granger say that such time series “have an observable
     component consisting of a fairly constant shape repeated every 12 months

    The underlying component causing this behavior can be extracted relieving the time
     series from these cyclical repetitions.

    There is a concern of autocorrelation that one time series are automatically adjusting to
     the other, between the two time series that would generate spurious results if no
     adjustment for seasonality would be done.

    When removing the seasonality in the data we are using a moving average additive
     method as we have also negative data.(Census X12)
                                                                                                Measuring Correlation




                                                         Prelimi   Removi    Measu    Testing      Testin     Va
                                                          nary     g         ring                  g          R
    Measuring Correlation                                Analysi   season    Correl
                                                                                      CoInteg
                                                                                      ration       Causa      Mo
                                                           s       ability   ation                 lity       del




    Next step is to investigate the correlation. If there would to be no correlation there would
     be no causality.
    The correlation answers to if the strength and direction of two variables is similar. A
     value is received when doing a correlation test, which ranges from 1.0 to -1.0. A number
     more separated from 0 means that there is a strong positive or negative correlation e.g.
     1.0 or -1.0.
                                                                                                Testing CoIntegration




                                                         Prelimi   Removi    Measu    Testing      Testin    Va
                                                          nary     g         ring                  g         R
    Testing CoIntegration                                Analysi   season    Correl
                                                                                      CoInteg
                                                                                      ration       Causa     Mo
                                                           s       ability   ation                 lity      del




   According to Nelson and Plosser (1982) and Engle & Granger (1987) there exist unit roots
    in most macroeconomic time-series. Further they state that time series exhibit stochastic
    non-stationarity due to this unit root. Engle & Granger (1987) state that a linear
    combination of two or more non-stationary time series can be said to be stationary. If a
    stationary linear combination exists is the non-stationary time series co-integrated. “The
    stationary linear combination is called the co-integrating vector and may be interpreted as
    a long-run equilibrium relationship among the variables”
   The hypothesis behind is that random shocks in the economy have long lasting effects
    (Engle & Granger, 1987).
   This is important before doing a causality test, as it must be decided whether there exists
    a common unit root. “If variables follow a unit root process, it can lead to spurious results
    when the levels of the variables are used for estimation purposes because the variance of
    the process becomes infinite. In that case, least squares estimation with levels variables is

    clearly inappropriate”. (Jung and Seldon, 1995, pp. 580)


   First I estimate the auto correlation function (ACF) which generates a diagram
                                                                              Testing CoIntegration




Testing CoIntegration




As the geometrical shape of the bars in figures show a falloff to zero in AC and
values near 1.000 in lag 0, and close to zero in the other lags in Partial Correlation
(PAC)), it indicates non-stationarity.
The diagram shows us that is valid to perform a pretest for integration using
Augmented Dickey Fuller test.
After doing the ADF test : exchange rate series is non stationary, exports is non
stationary and terms of trade is non stationary
                                                                                                Testing Causality




                                                        Prelimi   Removi    Measu    Testing   Testin    Va
                                                         nary     g         ring               g         R
    Testing Causality                                  Analysi    season    Correl
                                                                                     CoInteg
                                                                                     ration    Causa     Mo
                                                         s        ability   ation              lity      del




   The Granger test was conducted on seasonal adjusted data, as the results from the
    augmented Dickey Fuller test and Co-integration test suggests..
   From the test we can see all the probabilities are within the 5%(and 10% ) significant
    level, hence it can be rejected.
   These results indicate that there is a two-way causal relationship
       TABLE OF CONTENT



• Introduction
• Literature review
• Testing Strategy
                    Preliminary Analysis
     Removing seasonability
     Measuring correlation
     Testing Co Integration
     Testing for Causality
     A VaR Model
• Theoretical Model
     • About DSGE models
     • The model
     • Solving an RBC model
• Conclusions
• Bibliography
                                                                                                                       VaR Model




                                                                       Prelimi   Removi    Measu    Testing   Testin    VaR
                                                                        nary     g         ring               g
    VaR Model                                                          Analysi   season    Correl
                                                                                                    CoInteg
                                                                                                    ration    Causa
                                                                                                                        Model
                                                                         s       ability   ation              lity




   VAR includes six variables:
       the   log   of   real government spending per capita,
       the   log   of   real private spending per capita (private consumption plus investment),
       the   log   of   the GDP deflator,
       the   log   of   the nominal exchange rate,
       the   log   of   the terms of trade .


   For the latter were considered
       net exports (scaled by GDP),
       the log of real private investment per capita
       the log of real private consumption per capita.
       The baseline specification includes four lags of each
   The VAR model includes 4 lags of each endogenous variable, a constant and a linear time
    trend.
   For the estimation, U.S. quarterly data period (1990:1 -2003:4)
                                                                                  VaR Model




VaR Model:

In order to identify an exogenous shock to government spending, it is assumed that
government spending does not respond contemporaneously to changes in the other variables
included in the VAR.

While the solid line gives the point estimates, the shaded area gives the 95% confidence
Interval

 VAR includes six variables:
                      the log of real government spending per capita,
     the log of real private spending per capita (private consumption plus investment),
     the log of the GDP deflator,
     the log of the nominal exchange rate,
     the log of the terms of trade .

 For the latter were considered
      net exports (scaled by GDP),
      the log of real private investment per capita
      the log of real private consumption per capita.
     The VAR model includes 4 lags of each endogenous variable.
For the estimation, U.S. quarterly data period (1990:1 -2003:4)
                                                                                       VaR model




VaR Model – Impulse Functions:


 In order to trace out the responviness of the dependent variables in VaR
 To shock to the error term we have made the impulse functions:



Government Spending:
                                                           Government spending (panel a) rises
                                                           significantly and persistently




Private Spending:
                                                           Private spending increases mildly, but
                                                           not significantly and starts to decline
                                                           after a few quarters
                                                  VaR Model




VaR Model:


Terms of trade:    The terms of trade appreciate sharply on
                   impact




Nominal Exchange   The nominal exchange rate depreciates on
Rate                impact and this effect becomes stronger
                   and significant after six- seven quarters
                                                      VaR Model




VaR Model:


Net Exports:
               Net exports increase significantly on impact and
               remain above trend for an extended period.




Investment
               Private investment is depressed
                                                 VaR Model




VaR Model:


Consumption:   Consumption increases gradually
       TABLE OF CONTENT



• Introduction
• Literature review
• Testing Strategy
                    Preliminary Analysis
     Removing seasonability
     Measuring correlation
     Testing Co Integration
     Testing for Causality
     A VaR Model
• Theoretical Model
     • The model
     • Solving an RBC model
• Conclusions
• Bibliography
                                                                                                  The model




Theoretical Model:

To rationalize the evidence obtained from the VAR a two-country general equilibrium model
is proposed.(The origin of DSGE comes from Real Business Cycle model which was developed by
Kydland and Prescott (1982), to capture the output fluctuations )
Hypothesis:
             1. both countries supply distinct goods to the world market thereby giving an important
role to the allocation of private spending
             2. Fiscal policy is characterized by an exogenous process for government spending
financed entirely through sum taxes
             3. Private spending is biased towards domestically produced goods, while
government spending falls entirely on domestic goods
             4. Monetary policy is characterized by an interest rate feedback rule
             5. Regarding the structure of international financial markets, is
distinguished the case where financial markets are complete at the international level from
a set up where only non-state-contingent bonds are traded across countries.

Since the countries are symmetric, the exposition is focused on the home country using the following
notation:
            - foreign variables within the home economy are indexed by the subscript ‘F’, while
foreign variables in the foreign economy are indexed by a star.
       TABLE OF CONTENT



• Introduction
• Literature review
• Testing Strategy
                    Preliminary Analysis
     Removing seasonability
     Measuring correlation
     Testing Co Integration
     Testing for Causality
     A VaR Model
• Theoretical Model
     • The model
     • Solving an RBC model
• Conclusions
• Bibliography
                                                                      Solving an RBC Modell




Solving an RBC Model:




 The model introduced here is a basic RBC model with monopolistic competition
 The model was solved with Matlab using Dynare;
 The model equations can be found in the document attached :


 Results :
                                                Solving an RBC Modell




Solving an RBC Model – Impulse Functions:

                                            C- consumption
                                            l – labour
                                            R – interest rate(cost
                                            Of capital)
                                            K – capital stock
                                            I – investmenr
                                            W – wage
                                            Y – production
                                            Z - technology
       TABLE OF CONTENT



• Introduction
• Literature review
• Testing Strategy
                    Preliminary Analysis
     Removing seasonability
     Measuring correlation
     Testing Co Integration
     Testing for Causality
     A VaR Model
• Theoretical Model
     • The model
     • Solving an RBC model
• Conclusions
• Bibliography
                                                                              Solving an RBC Modell




   Conclusions



This paper has tried to empirically establish the dynamic effects of an exogenous increase in
government spending on the nominal exchange rate, the terms of trade and the trade balance.
The main finding proves to be robust across various VAR specifications: the exchange rate
depreciates, the terms of trade appreciate and the trade balance moves into surplus after an
exogenous increase in government spending.
The strong and significant response of the terms of trade provides a guideline for the theoretical
exploration of the empirical findings. Specifically, It was investigated whether a two-country
two-good general equilibrium model with price rigidities can account for the evidence, and if so
under what conditions and as an example of solving a DSGE model with Dynare , the solution
Of an RBC model was presented.
       TABLE OF CONTENT



• Introduction
• Literature review
• Testing Strategy
                    Preliminary Analysis
     Removing seasonability
     Measuring correlation
     Testing Co Integration
     Testing for Causality
     A VaR Model
• Theoretical Model
     • The model
     • Solving an RBC model
• Conclusions
• Bibliography
                                                                                                       Solving an RBC Modell




Conclusions

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Calvo, G.A., 1983. Staggered prices in utility-maximizing framework.
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Chinn, M.D., Prasad, E.S., 2003. Medium-term determinants of current accounts in industrial
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Cole, H.L., Obstfeld, M., 1991. Commodity trade and international risk sharing:
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Cooley, T.F., Dwyer, M., 1998. Business cycle analysis without much theory e a look at structural VARs.
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Klein, P., 2000. Using the generalized schur form to solve a multivariate linear rational expectations model.
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Kollmann, R., 1998. US trade balance dynamics: the role of fiscal policy and productivity shocks
               and of financial market linkages. Journal of International Money and Finance 17 (4), 637e669.
Lane, P., Perotti, R., 2003. The importance of composition of fiscal policy: evidence from different exchange
               rate regimes. Journal of Public Economics 87 (9e10), 2253e2279.
Schmitt-Grohe´, S., Uribe, M., 2003. Closing small open economy models.
               Journal of International Economics 61 (1), 163e185.
Tille, C., 2001. The role of consumption substitutability in the international transmission of monetary shocks.
                Journal of International Economics 53 (2), 421e444.
Van der Ploeg, F., 1993. Channels of international policy transmission.
                Journal of International Economics 34 (3e4), 245e267.

				
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