Solution Manuals For Real Econometrics The Right Tools to Answer Important Questions Second Edition Michael Bailey

Name: Solution Manuals For Real Econometrics The Right Tools to Answer Important Questions Second Edition Michael Bailey
SKU: 9541
Price: 50.00 USD
Availability: InStock

$50.00

Publication Date – January 2019

ISBN: 9780190857462

656 pages

Category: Economics

Description

Table of Contents

List of Figures

List of Tables

Useful Commands for Stata

Useful Commands for R

Preface for Students: How This Book Can Help You Learn Econometrics

Preface for Instructors: How to Help Your Students Learn Econometrics

Acknowledgments

1 The Quest for Causality

The Core Model

Two Challenges: Randomness and Endogeneity

CASE STUDY: Flu Shots

CASE STUDY: Country Music and Suicides

Randomized Experiments as the Gold Standard

2 Stats in the Wild: Good Data Practices

2.1 Know Our Data

2.2 Replication

CASE STUDY: Violent Crime in the United States

2.3 Statistical Software

I The OLS FRAMEWORK

3 Bivariate OLS: The Foundation of Econometric Analysis

3.1 Bivariate Regression Model

3.2 Random Variation in Coefficient Estimates

3.3 Exogeneity and Unbiasedness

3.4 Precision of Estimates

3.5 Probability Limits and Consistency

3.6 Solvable Problems: Heteroscedasticity and Correlated Errors

3.7 Goodness of Fit

CASE STUDY: Height and Wages

3.8 Outliers

4 Hypothesis Testing and Interval Estimation: Answering Research Questions

4.1 Hypothesis Testing

4.2 t Tests

4.3 p Values

4.4 Power

4.5 Straight Talk about Hypothesis Testing

4.6 Confidence Intervals

5 Multivariate OLS: Where the Action Is

5.1 Using Multivariate OLS to Fight Endogeneity

5.2 Omitted Variable Bias

CASE STUDY: Does Education Support Economic Growth?

5.3 Measurement Error

5.4 Precision and Goodness of Fit

CASE STUDY: Institutions and Human Rights

5.5 Model Specification

6 Dummy Variables: Smarter Than You Think

6.1 Using Bivariate OLS to Assess Difference of Means

CASE STUDY: Sex Differences in Heights

6.2 Dummy Independent Variables in Multivariate OLS

6.3 Transforming Categorical Variables to Multiple Dummy Variables

CASE STUDY: When Do Countries Tax Wealth?

6.4 Interaction Variables

CASE STUDY: Energy Efficiency

7 Specifying Models

7.1 Quadratic and Polynomial Models

CASE STUDY: Global Warming

7.2 Logged Variables

7.3 Standardized Coefficients

7.4 Hypothesis Testing about Multiple Coefficients

CASE STUDY: Comparing Effects of Height Measures

II THE CONTEMPORARY ECONOMETRIC TOOLKIT

8 Using Fixed Effects to Fight Endogeneity in Panel Data and Difference-in-Difference Models

8.1 The Problem with Pooling

8.2 Fixed Effects Models

8.3 Working with Fixed Effects Models

8.4 Two-Way Fixed Effects Model

CASE STUDY: Trade and Alliances

8.5 Difference-in-Difference

9 Instrumental Variables: Using Exogenous Variation to Fight Endogeneity

9.1 2SLS Example

9.2 Two-Stage Least Squares (2SLS)

CASE STUDY: Emergency Care for Newborns

9.3 Multiple Instruments

9.4 Quasi and Weak Instruments

9.5 Precision of 2SLS

9.6 Simultaneous Equation Models

CASE STUDY: Supply and Demand Curves for the Chicken Market

10 Experiments: Dealing with Real-World Challenges

10.1 Randomization and Balance

CASE STUDY: Development Aid and Balancing

10.2 Compliance and Intention-to-Treat Models

10.3 Using 2SLS to Deal with Non-compliance

CASE STUDY: Minneapolis Domestic Violence Experiment

10.4 Attrition

CASE STUDY: Health Insurance and Attrition

10.5 Natural Experiments

CASE STUDY: Crime and Terror Alerts 354

11 Regression Discontinuity: Looking for Jumps in Data

11.1 Basic RD Model

11.2 More Flexible RD Models

11.3 Windows and Bins

CASE STUDY: Universal Prekindergarten

11.4 Limitations and Diagnostics

CASE STUDY: Alcohol and Grades

III LIMITED DEPENDENT VARIABLES

12 Dummy Dependent Variables

12.1 Linear Probability Model

12.2 Using Latent Variables to Explain Observed Variables

12.3 Probit and Logit Models

12.4 Estimation

12.5 Interpreting Probit and Logit Coefficients

CASE STUDY: Econometrics in the Grocery Store

12.6 Hypothesis Testing about Multiple Coefficients

CASE STUDY: Civil Wars

IV ADVANCED MATERIAL

13 Time Series: Dealing with Stickiness over Time

13.1 Modeling Autocorrelation

13.2 Detecting Autocorrelation

13.3 Fixing Autocorrelation

CASE STUDY: Using an AR(1) Model to Study Global Temperature Changes

13.4 Dynamic Models

13.5 Stationarity

CASE STUDY: Dynamic Model of Global Temperature

14 Advanced OLS

14.1 How to Derive the OLS Estimator and Prove Unbiasedness

14.2 How to Derive the Equation for the Variance of O?1

14.3 How to Derive the Omitted Variable Bias Conditions

14.4 Anticipating the Sign of Omitted Variable Bias

14.5 Omitted Variable Bias with Multiple Variables

14.6 Omitted Variable Bias due to Measurement Error

15 Advanced Panel Data

15.1 Panel Data Models with Serially Correlated Errors

15.2 Temporal Dependence with a Lagged Dependent Variable

15.3 Random Effects Models

16 Conclusion: How to Be an Econometric Realist

APPENDICES

Math and Probability Background

A. Summation

B. Expectation

C. Variance

D. Covariance

E. Correlation

F. Probability Density Functions

G. Normal Distributions

H. Other Useful Distributions

I. Sampling

Citations and Additional Notes

Guide to Review Questions

Bibliography

Photo Credits

Glossary

Index

Solution Manuals For Real Econometrics The Right Tools to Answer Important Questions Second Edition Michael Bailey

Related

Related products

Login

Register