Economic and Financial Modelling with EViews: A Guide for Students and Professionals

293 Pages·2018·19.11 MB·English

by  Abdulkader Aljandali, Motasam Tatahi

Statistics and Econometrics for Finance
Abdulkader Aljandali · Motasam Tatahi
Economic
and Financial
Modelling
with EViews
A Guide for Students and Professionals
Statistics and Econometrics for Finance
Series Editors
David Ruppert, Cornell University, Ithaca, New York
Jianqing Fan, Princeton University, Princeton, New Jersey
Eric Renault, Brown University, Providence, Rhode Island
Eric Zivot, University of Washington, Seattle, Washington
More information about this series at http://www.springer.com/series/10377
Abdulkader Aljandali • Motasam Tatahi
Economic and Financial
Modelling with EViews
A Guide for Students and Professionals
Abdulkader Aljandali Motasam Tatahi
Department of Accounting, Finance Department of Economics, Finance
and Economics and Accounting
Coventry University London Regent’s University London-European
London, UK Business School London
London, UK
ISSN 2199-093X ISSN 2199-0948 (electronic)
Statistics and Econometrics for Finance
ISBN 978-3-319-92984-2 ISBN 978-3-319-92985-9 (eBook)
https://doi.org/10.1007/978-3-319-92985-9
Library of Congress Control Number: 2018944692
© Springer International Publishing AG, part of Springer Nature 2018
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Contents
1 Introduction to EViews . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Importing Data into EViews . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2.1 Reading Excel/IBM SPSS Data Variables . . . . . . . . . . . 5
1.2.2 Saving and Opening an EViews Data File . . . . . . . . . . . 7
2 A Guideline for Running Regression . . . . . . . . . . . . . . . . . . . . . . . . 11
2.1 EViews Regression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.1.1 Saving the Regression Equation . . . . . . . . . . . . . . . . . . 15
2.1.2 Editing and Saving Regression Graphics . . . . . . . . . . . . 16
2.2 The Cobb-Douglas Function . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.2.1 Estimation of the Cobb-Douglas Model . . . . . . . . . . . . . 21
2.2.2 Interpret the Regression Equation . . . . . . . . . . . . . . . . . 22
2.2.3 Testing the Coefficients . . . . . . . . . . . . . . . . . . . . . . . . 24
2 2
2.2.4 Comment on the Value of the R and Testing the R . . . 25
2.2.5 Multicollinearity and Residual Analysis . . . . . . . . . . . . . 25
3 Time Series Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
3.1 Time Series One: The Real Money Demand (RMD) . . . . . . . . . . 38
3.1.1 Informal Method: Plot the Time Series
and Generate a Correlogram . . . . . . . . . . . . . . . . . . . . . 38
3.1.2 Formal Method: Run the Augmented
Dickey-Fuller (ADF) Test . . . . . . . . . . . . . . . . . . . . . . . 40
3.2 Time Series Two: The Real GDP (RGDP) . . . . . . . . . . . . . . . . . 42
3.2.1 Informal Method: Plot the Time Series
and Generate a Correlogram . . . . . . . . . . . . . . . . . . . . . 42
3.2.2 Formal Method: Run the Augmented
Dickey-Fuller (ADF) Test . . . . . . . . . . . . . . . . . . . . . . . 43
3.3 Time Series Three: Interest Rates (INT) . . . . . . . . . . . . . . . . . . . 44
3.3.1 Informal Method: Plot the Time Series
and Generate a Correlogram . . . . . . . . . . . . . . . . . . . . . 44
v
vi Contents
3.3.2 Formal Method: Run the Augmented
Dickey-Fuller (ADF) Test . . . . . . . . . . . . . . . . . . . . . . . 46
3.4 Time Series Four: The First Difference
of the RMD-DRMD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.4.1 Informal Method: Plot the Time Series
and Generate a Correlogram . . . . . . . . . . . . . . . . . . . . . 47
3.4.2 Formal Method: Run the Augmented
Dickey-Fuller (ADF) Test . . . . . . . . . . . . . . . . . . . . . . . 49
3.5 Time Series Five: The First Difference
of the RGDP-DRGDP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
3.5.1 Informal Method: Plot the Time Series
and Generate a Correlogram . . . . . . . . . . . . . . . . . . . . . 50
3.5.2 Formal Method: Run the Augmented
Dickey-Fuller (ADF) Test . . . . . . . . . . . . . . . . . . . . . . . 51
3.6 Time Series Six: The First Difference of INT-DINT . . . . . . . . . . 52
3.6.1 Informal Method: Plot the Time Series
and Generate a Correlogram . . . . . . . . . . . . . . . . . . . . . 52
3.6.2 Formal Method: Run the Augmented
Dickey-Fuller (ADF) Test . . . . . . . . . . . . . . . . . . . . . . . 54
4 Time Series Modelling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
4.1 The Property of Stationarity . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
4.1.1 Trend Differencing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
4.1.2 Seasonal Differencing . . . . . . . . . . . . . . . . . . . . . . . . . 60
4.1.3 Homoscedasticity of the Data . . . . . . . . . . . . . . . . . . . . 60
4.2 Time Series in Practice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
5 Further Properties of Time Series . . . . . . . . . . . . . . . . . . . . . . . . . . 73
5.1 Stochastic and Deterministic Trends . . . . . . . . . . . . . . . . . . . . . . 73
5.2 The Lag Operator and Invertibility . . . . . . . . . . . . . . . . . . . . . . . 75
5.3 The Characteristic Equation and Stationarity . . . . . . . . . . . . . . . . 78
5.4 Unit Root Tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
Appendix 5.1: The Binomial Theorem . . . . . . . . . . . . . . . . . . . . . . . . 84
Appendix 5.2: The Quadratic Equation . . . . . . . . . . . . . . . . . . . . . . . . 85
6 Economic Forecasting Using Regression . . . . . . . . . . . . . . . . . . . . . 89
6.1 Forecasting with Regression Models . . . . . . . . . . . . . . . . . . . . . 90
6.2 Step One: Checking the Stationarity of the Series . . . . . . . . . . . . 90
6.3 Step Two: Making Series Stationary . . . . . . . . . . . . . . . . . . . . . 94
6.4 Step Three: The Cointegration Test . . . . . . . . . . . . . . . . . . . . . . 99
6.5 Step Four: Model Forecasting . . . . . . . . . . . . . . . . . . . . . . . . . . 101
6.6 Step Five: Making a Joint Graph of the Dependent Variable
and Its Forecast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
6.7 Step Six: Adding Autocorrelation of the Error Term . . . . . . . . . . 108
Contents vii
7 Economic Forecasting using ARIMA Modelling . . . . . . . . . . . . . . . 111
7.1 The Box-Jenkins Methodology . . . . . . . . . . . . . . . . . . . . . . . . . 111
7.2 The ARIMA Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
7.3 Autocorrelations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
7.3.1 Autocorrelation Functions . . . . . . . . . . . . . . . . . . . . . . 114
7.3.2 Partial Autocorrelation Functions (PACF) . . . . . . . . . . . 116
7.3.3 Patterns of the ACF and PACF . . . . . . . . . . . . . . . . . . . 117
8 Modelling Volatility in Finance and Economics: ARCH,
GARCH and EGARCH Models . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
8.1 The ARCH Class of Models . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
8.2 Testing for ARCH Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
8.3 Problems with ARCH Models in Practice . . . . . . . . . . . . . . . . . . 154
8.4 GARCH Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
8.5 Application: Modelling Volatility & Estimating
a GARCH (1, 1) Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
8.6 Cointegration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168
8.7 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192
9 Limited Dependent Variable Models . . . . . . . . . . . . . . . . . . . . . . . . 197
9.1 The Linear Probability Model . . . . . . . . . . . . . . . . . . . . . . . . . . 198
9.2 The Logit Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201
9.3 Applying the Logit Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202
9.4 The Logit Model in EViews . . . . . . . . . . . . . . . . . . . . . . . . . . . 203
10 Vector Autoregression (VAR) Model . . . . . . . . . . . . . . . . . . . . . . . . 211
10.1 The VAR Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212
10.2 The Estimation Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213
Appendix 10.1: The Wald Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234
11 Panel Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237
11.1 Panel Stationary Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . 238
11.1.1 The LGDP Panel Data . . . . . . . . . . . . . . . . . . . . . . . . 239
11.1.2 The LGEX Panel Data . . . . . . . . . . . . . . . . . . . . . . . . 240
11.1.3 The First Difference of the Data . . . . . . . . . . . . . . . . . 241
11.1.4 The DLGDP Panel Data . . . . . . . . . . . . . . . . . . . . . . . 242
11.1.5 The DLGEX Panel Data . . . . . . . . . . . . . . . . . . . . . . . 243
11.2 The Panel ECM Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 246
11.2.1 Pooled OLS regression . . . . . . . . . . . . . . . . . . . . . . . . 248
11.2.2 The Fixed Effects Least Squares Dummy
Variable (LSDV) Model . . . . . . . . . . . . . . . . . . . . . . . 249
11.2.3 Model Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253
11.2.4 Limitations of the Fixed Effects LSDV Model . . . . . . . 254
11.3 The Random Effects Model (REM) or Error Components
Model (ECM) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255
11.4 Fixed Effects Model vs. Random Effects Model . . . . . . . . . . . . 257
11.5 The Final Result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 259
viii Contents
12 Capital Asset Pricing Model (CAPM) . . . . . . . . . . . . . . . . . . . . . . . 261
12.1 The CAPM Equation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261
12.2 Residual Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 275
Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 277
List of Figures
Fig. 1.1 The EViews opening window . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
Fig. 1.2 Table read specification dialogue box . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Fig. 1.3 HARMON data imported into EViews . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Fig. 1.4 The Workfile structure dialogue box . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
Fig. 1.5 Appropriate set up for the Workfile Structure dialogue box . . . . . 6
Fig. 1.6 The correctly dated data file . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
Fig. 1.7 Selecting variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
Fig. 1.8 The Show dialogue box . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
Fig. 1.9 EViews output showing models variables . . . . . . . . . . . . . . . . . . . . . . . . . 9
Fig. 1.10 Descriptive Statistics in EViews . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
Fig. 2.1 The Equation Estimation dialogue box . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Fig. 2.2 The EViews regression equation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
Fig. 2.3 The Jarque-Bera test of normality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Fig. 2.4 The Breusch-Godfrey test of serial autocorrelation . . . . . . . . . . . . . . . 14
Fig. 2.5 White’s heteroscedasticity test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
Fig. 2.6 The observed, fitted values and the residuals . . . . . . . . . . . . . . . . . . . . . 16
Fig. 2.7 The Graph Options dialogue box . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Fig. 2.8 An edited plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Fig. 2.9 The Generate Series by Equation dialogue box . . . . . . . . . . . . . . . . . . . 19
Fig. 2.10 A monthly listing of the standardised residuals . . . . . . . . . . . . . . . . . . . 19
Fig. 2.11 A plot of the standardised residuals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
Fig. 2.12 Scatter plot of Log (Y) Log (K) data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Fig. 2.13 Scatter plot of Log (Y) and Log (L) data . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Fig. 2.14 Estimate a regression equation dialogue box . . . . . . . . . . . . . . . . . . . . . . 24
Fig. 2.15 Regression equation residuals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Fig. 2.16 Graph Options dialogue box . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
Fig. 2.17 Plot of the E residuals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
Fig. 2.18 Actual, fitted and residuals data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
Fig. 2.19 Testing for Multicollinerarity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
Fig. 2.20 Testing for Normality of the residuals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
ix
x List of Figures
Fig. 2.21 The White test statistic in EViews . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
Fig. 2.22 Correlogram of residuals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
Fig. 2.23 Serial correlation LM test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
Fig. 3.1 Plot of the RMD series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
Fig. 3.2 Correlogram of RMD series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
Fig. 3.3 RMD unit root test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
Fig. 3.4 RGDP plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
Fig. 3.5 Corrlogram of RGDP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
Fig. 3.6 RGDP unit root test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
Fig. 3.7 INT plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Fig. 3.8 Correlogram of INT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
Fig. 3.9 INT unit root test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
Fig. 3.10 DRMD plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
Fig. 3.11 Correlogram of DRMD .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
Fig. 3.12 DRMD unit root test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
Fig. 3.13 DRGDP plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
Fig. 3.14 Correlogram of DRGDP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
Fig. 3.15 DRGDP unit root test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
Fig. 3.16 DINT plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
Fig. 3.17 Correlogram of DINT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
Fig. 3.18 DINT unit root test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
Fig. 4.1 Stock levels over time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Fig. 4.2 Regression model using the RMD, RGDP and INT
variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
Fig. 4.3 Plot of U residuals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
Fig. 4.4 Correlogram test for U residuals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
Fig. 4.5 U residuals unit root test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
Fig. 4.6 Regression output using RMD, RGDP and INT . . . . . . . . . . . . . . . . . . 68
Fig. 4.7 DRMD’s ECM model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
Fig. 4.8 Breusch-Godfrey serial correlation LM test . . . . . . . . . . . . . . . . . . . . . . . 71
Fig. 5.1 A time series with a deterministic trend . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
Fig. 5.2 An Argand plot of the complex number 2 + 3i . . . . . . . . . . . . . . . . . . . 86
Fig. 6.1 Data plot of PCE and PDI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
Fig. 6.2 Plot of the Natural Log of PCE (LPCE) . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
Fig. 6.3 Correlogram of LPCE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
Fig. 6.4 LPCE Unit root test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
Fig. 6.5 Plot of the Natural Log PDI-LPI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
Fig. 6.6 Correlogram of LPDI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
Fig. 6.7 LPDI unit root test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
Fig. 6.8 Plot of the first difference (DLPCE) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
Fig. 6.9 Correlogram of DLPCE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
Fig. 6.10 DLPCE unit root test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
Fig. 6.11 Plot of the first difference (DLPDI) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97