Econometric Methods and Applications

Econometric Methods and Applications

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Einband

Gebundene Ausgabe

Erscheinungsdatum

06.01.2023

Verlag

Springer India

Seitenzahl

200

Details

Einband

Gebundene Ausgabe

Erscheinungsdatum

06.01.2023

Verlag

Springer India

Seitenzahl

200

Maße (L/B)

23.5/15.5 cm

Auflage

2022 edition

Sprache

Englisch

ISBN

978-81-322-3692-4

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  • Econometric Methods and Applications
  • Part I Basic Regression Analysis.- 1. Introduction.- 1.1 About the book.- 1.2 Steps in empirical project.- 1.3 Overview of chapters.- 1.4 List of empirical exercises in the book.- 2. Getting acquainted with data.- 2.1 Structure of data and types of measurements.- 2.2 Data analysis.- 2.2.1 Concepts underlying data analysis.- 2.2.2 Data analysis through graphical techniques.- 2.2.3 Data analysis through descriptive statistics.- 3. Classical Linear Regression Model.- 3.1 The simple and multiple regression models: Overview.- 3.1.1 Estimation using ordinary least squares.- 3.1.2 Properties of the ordinary least squares estimators.- 3.1.3 Goodness-of-fit .- 3.1.4 Hypothesis testing.- 3.2 Empirical Illustration: Housing price model.- 3.2.1 Literature review.- 3.2.2 Estimation of the model as simple regression model.- 3.2.3 Presentation and interpretation of regression results.- 3.2.4 Estimation of the model as a multiple regression model.- 3.2.5 Presentation and interpretation of regression results.- 3.2.6 Estimation of the model using GRETL.- 3.3 Empirical Illustration: Exchange rate and relative price ratio.- 3.3.1 Literature review.- 3.3.2 Estimation of the model as simple regression model.- 3.3.3 Presentation and interpretation of regression results.- 4. Dummy Variable Regression Models.- 4.1 Qualitative data and dummy variable regression model: Overview.- 4.1.1 Intercept, slope and multiplicative dummies.- 4.2 Empirical Illustration: Wage earnings as a function of education, age, experience, gender.- 4.2.1 Literature review.- 4.2.2 Estimation of the model with dummy variables.- 4.2.3 Interpreting intercept and slope dummies.- 4.2.4 Estimation of the model using GRETL.- 4.3 Empirical Illustration: Expenditure on running a school.- 4.3.1 Literature review.- 4.3.2 Estimation of the model with dummy variables.- 4.3.3 Interpreting intercept and slope dummies.- 4.4 Detecting seasonal trends in data – Empirical Illustration using efficient market hypothesis.- 4.4.1 Literature review.- 4.4.2 Estimation of the model.- 4.4.3 Presentation and interpretation of regression results.- Part II Diagnostics and Model Selection.- 5. Violations of the Classical Assumptions I: Multicollinearity.- 5.1 Detection, consequences, remedies: an overview.- 5.2 Empirical Illustration: Housing starts relations.- 5.2.1 Brief note on housing starts relations and literature review.- 5.2.2 Detection of multicollinearity.- 5.2.3 Consequences of multicollinearty.- 5.2.4 Remedies for multicollinearity.- 5.2.5 Estimation of the model using GRETL.- 6. Violations of the Classical Assumptions II: Heteroscedasticity.- 6.1 Detection, consequences, remedies: an overview.- 6.2 Empirical Illustration: Size of the Firm and Profit Ratios.- 6.2.1 Literature review.- 6.2.2 Detection of heteroscedasticity .- 6.2.3 Consequences of heteroscedasticity.- 6.2.4 Remedies for heteroscedasticity.- 6.2.5 Estimation of the model using GRETL.- 7. Violations of the Classical Assumptions III: Serial correlation.- 7.1 Detection, consequences, remedies: an overview.- 7.2 Empirical Illustration: Cobb Douglas Production Function.- 7.2.1 Brief note on Cobb Douglas function and literature review.- 7.2.2 Detection of serial correlation.- 7.2.3 Consequences of serial correlation .- 7.2.4 Treatment of serial correlation.- 7.2.5 Estimation of the model using GRETL.- 8. Functional Forms and Model Specification.- 8.1 Choice of functional forms.- 8.1.1 Linear log functional form: Engel expenditure function.- 8.1.2 Log linear functional form: GDP growth rate model.- 8.1.3 Double log functional form: Cobb Douglas production function.- 8.1.4 Polynomial functional form: Cost function.- 8.1.5 Reciprocal functional form: Philips curve.- 8.1.6 Functional form with interaction term: Consumption function.- 8.1.7 Regression through the origin: Capital asset pricing model.- 8.2 Model specification.- 8.2.1 Omission and inclusion of regressors.- 8.2.2 Measurement errors in variables.- 8.2.3 Test for misspecification.- 8.3 Approaches to choice of models.- 8.3.1 Traditional approach.- 8.3.2 Hendry’s approach.- 8.3.3 Empirical application on model selection: Economic growth models.- 8.3.4 Empirical application on model selection: Housing price model.- 9. Guide to Doing an Empirical Project using Ordinary Least Squares.- 9.1 Steps in empirical project.- 9.2 Empirical Illustration: Consumption function.- 9.3 Empirical Illustration: Deficit and interest rates.- Part III Advanced Topics in Econometrics.- 10. Dynamic Econometrics Models.- 10.1Distributed lag models: an overview.- 10.1.1Kyock transformation.- 10.1.2Almon transformation.- 10.1.3Autoregressive models.- 10.1.4 Partial adjustment model.- 10.1.5Adaptive expectations model .- 10.2 Empirical Illustration: Demand for money.- 10.2.1 Brief note on money demand function and literature review.- 10.2.2 Estimation and interpretation of results.- 10.2.3 Estimation of the model using GRETL.- 11. Instrument Variable Estimation and Two Stage Least Squares Estimation.- 11.1 Instrument variable estimation of the regression model: an overview.- 11.2 Two stage least squares: overview .- 11.2.1 Single endogenous explanatory variable.- 11.2.2 Multiple endogenous explanatory variables.- 11.3 Empirical Illustration: Demand and supply for loans.- 11.3.1 Literature review.- 11.3.2 Instrument variable estimation and two stage least squares estimation of the model using GRETL.- 12. Simultaneous Equation Models.- 12.1 Simultaneous equation model: an overview.- 12.1.1 Problem of simultaneity.- 12.1.2 Problem of identification.- 12.1.3 Estimation procedure using method of indirect least squares.- 12.1.4 Estimation procedure using method of two stage least squares.- 12.2 Empirical Illustration: Macroeconomic Model.- 12.2.1 Brief note on macroeconomic model and literature review.- 12.2.2 Estimation of the model using GRETL.- 13. Topics in Time Series Econometrics.- 13.1 Stochastic processes: an overview.- 13.1.1 Stationary and non-stationary time series.- 13.1.2 Testing for unit roots.- 13.1.3 Cointegration estimation for unit root time series.- 13.2 Empirical Illustration: Closing stock prices of IBM.- 13.2.1 Literature review.- 13.2.2 Estimation of the model and interpretation of results.- 13.2.3 Estimation of the model using GRETL.- 13.3 Empirical Illustration: Term structure of interest rates.- 13.3.1 Literature review.- 13.3.2 Estimation of the model and interpretation of results.- 14. Panel Data Estimation.- 14.1 Panel Data: an overview.- 14.1.1 Fixed effects model.- 14.1.2 Random effects model.- 14.2 Empirical Illustration: Investment data of companies.- 14.2.1 Literature review.- 14.2.2 Estimation of the model and interpretation of results.- 14.2.3 Estimation of the model using GRET.- L 14.3 Empirical Illustration: Wage earnings model.- 14.3.1 Literature review.- 14.3.2 Estimation of the model and interpretation of results.- 15. Qualitative Response Models .- 15.1 Introduction to qualitative response model.- 15.2 Linear probability model.- 15.3 Logit model.- 15.4 Probit model.- 15.5 Empirical Illustration: Predicting bank failure.- 15.6 Empirical Illustration: Applications for mortgages.