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2018-06-07

Applied econometrics

An Introduction


Pages: 396

Trade Paper: ISBN 9788885486508; $ 64,95

Pdf: ISBN 9788885486515; $ 45,95

Author: Massimiliano Marcellino

 

Table of Contents

 

Applied Econometrics. An Introduction


1. Introduction
1.1 What is econometrics?
1.2 Elements of an econometric study
1.3 Data
1.4 The descriptive analysis
1.5 Some examples
The main concepts of this chapter

 

2. The Linear Regression Model
2.1 Definitions and notation
2.2 The assumptions of the linear regression model
2.3 The role of the error term
2.4 OLS estimators of the regression function parameters
2.5 The linear model and the OLS estimators in vector notation
2.6 Properties of OLS estimators
2.6.1. Unbiasedness
2.6.2 The variance of the OLS estimators
2.6.3 Consistency
2.6.4 Efficiency of OLS estimators
2.6.5 The distribution of the OLS estimators
2.6.6. Orthogonality between OLS fitted values and residuals
2.7 An estimator of the error variance
2.8 Maximum Likelihood Estimators for the linear model
2.9 The coefficient of determination
2.10 Linear transformations of variables and their effects
2.11 The multiple regression model
2.12 Multicollinearity
2.13 An empirical analysis with simulated data
2.14 An empirical analysis of aggregate consumption
2.15 An empirical analysis of aggregate investment
2.16 An empirical analysis of labor productivity
The main concepts of this chapter
Exercises

 

3. Inference in the Linear Regression Model
3.1 Interval estimators
3.2 Testing hypothesis on the parameters of the linear regression model
3.3 Type I and type II errors
3.4 The concept of p-value
3.5 Significance testing
3.6 The relationship between confidence intervals and hypothesis testing
3.7 One-way tests
3.8 The F-test
3.9 Restricted OLS estimators
3.10 Omitted variables and irrelevant variables
3.11 An empirical analysis with artificial data
3.12 An empirical analysis of the determinants of aggregate consumption
3.13 An empirical analysis of the determinants of aggregate investment
3.14 An empirical analysis of the determinants of labor productivity
3.15 An empirical analysis of the CAPM
The main concepts of this chapter
Exercises

 

4. The Generalized Linear Regression Model
4.1 Heteroscedasticity and serial correlation of the errors
4.2 The Generalized Least Squares estimators (GLS and FGLS)
4.3 Tests for homoscedasticity
4.4 Tests for no correlation
4.5 The assumptions of Normality of the errors
4.6 The hypothesis of linearity in the parameters
4.7 Nonlinear transformations of the variables
4.8 An empirical analysis with simulated data
4.9 An empirical analysis of the determinants of aggregate consumption
The main concepts of this chapter
Exercises

 

5. Parameter Instability in the Linear Regression Model
5.1 Structural breaks and tests for parameter stability
5.2 Recursive estimation methods
5.3 Remedies for parameter instability
5.4 Forecasting with the linear regression model
5.5 Forecasting with unknown parameters
5.6 Multi-step ahead forecasting
5.7 An empirical analysis with simulated data
5.8 An empirical analysis of the determinants of aggregate consumption
The main concepts of this Chapter
Exercises

 

6. Stochastic Regressors
6.1 Stochastic regressors, independent of the error term
6.2 Stochastic regressors, asymptotically uncorrelated with the error term
6.3 Stochastic regressors, correlated with the error term
6.4 Instrumental Variables (IV) and IV estimator
6.5 Two-Stage Least Squares (TSLS) estimator and the over-identification test
6.6 The Hausman Test
6.7 An empirical analysis based on simulated data
6.8 An empirical analysis of aggregate consumption
The main concepts of this chapter
Exercises

 

7. Dynamic Models
7.1 Dynamic models: a classification
7.2 Dynamic models: specification, estimation, inference and diagnostic control
7.3 An empirical analysis with stationary simulated data
7.4 An empirical analysis of the determinants of the FED decisions
7.5 Unit roots and stochastic trends
7.6 Implications for estimation and inference
7.7 Cointegration: basics
7.8 An empirical analysis with integrated simulated data
7.9 An empirical analysis of the determinants of aggregate consumption
7.10 An empirical analysis of short-term interest rates
The main concepts of this chapter
Exercises

 

8. Models for Panel Data
8.1 The Seemingly Unrelated Regression (SUR) model
8.2 The Fixed Effects model
8.3 The Random Effects (RE) model
8.4 Some additional considerations on fixed and random effects
8.5 An empirical analysis with simulated data
8.6 An empirical analysis with simulated data on the use of fixed and random effects methods
8.7 An empirical analysis with simulated data when N>T
8.8 An empirical analysis of the effects of public capital in the Italian regions
The main concepts of this chapter
Exercises

 

9. Models for Qualitative Data
9.1 The linear regression model with a binary dependent variable
9.2 The LOGIT and PROBIT models: specification
9.3 The LOGIT and PROBIT models: estimation and interpretation of estimated coefficients
9.4 Model evaluation
9.5 An empirical analysis with simulated data
9.6 Leading indicators for GDP growth
9.7 An empirical analysis of the sign of stock returns
The main concepts of this chapter
Exercises

Applied-econometrics