Econometrics II (2235.YR.015777.1)
General information
Type: |
OBL |
Curs: |
1 |
Period: |
S semester |
ECTS Credits: |
3 ECTS |
Teaching Staff:
Prerequisites
There are no prerequisites, but basic concepts of statistics and linear algebra will be a helpful background for this course.
Workload distribution
Practical Lessons
COURSE CONTRIBUTION TO PROGRAM
The course provides a discussion of basic techniques for empirical analysis in economics and management. It starts by describing the nature of social science data and the way to conceptualize it in order to facilitate statistical analysis. It then moves to the study of specific statistical models and the interpretation of their computer output. Finally, the course presents a selection of topics in regression analysis, dealing with the most common problems found in empirical applications.
Course Learning Objectives
The objective of this course is to prepare students for basic empirical work in social science. In particular, topics will include basic data analysis, regression analysis, testing, as well as more advanced topics like panel data, difference in difference estimation, or instrumental variables. The course provides hands-on experience in econometric analysis designed to help students to acquire the skills necessary to carry out their own empirical research.
CONTENT
1. INTRODUCTION 1. Uncertainty and Data Analysis
2. The Concept of Stochastic Process
3. Data as Realizations of Stochastic Process
4. The Linear Regression Model
5. The OLS Estimation of the Model
6. The Properties of the OLS Estimators
- Small Sample Properties
- Asymptotic Properties
7. Hypothesis Testing in the Linear Regression Model
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2. BASIC ECONOMETRIC ANALYSIS |
3. REGRESSION WITH PANEL DATA THEORY
1. Panel Data: What and Why
2. Panel Data with Two Time Periods
3. Fixed Effects Regression
4. Regression with Time Fixed Effects
5. Standard Errors for Fixed Effects Regression
6. Fixed Effects versus Lagged Dependent Variables
PRACTICE
1. Panel Data in Stata
2. Application to "Why Do Management Practices Differ Across Firms and Countries" 2010, Bloom and Van Reenen, Journal of Economic Perspectives.
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4. INSTRUMENTAL VARIABLES REGRESSION (IV) THEORY
1. IV Regression: Why and What; Two Stage Least Squares
2. The General IV Regression Model
3. Checking INstrument Validity
a) Weal and Strong Instruments
b) Instrument exogeneity
c)Overidentifying Restrictions
PRACTICE
1. IV in Stata
2. Empirical paper: "Inside the Family Firm: The Role of Families in Succession Decisions and Performance", 2007, Quarterly Journal of Economics, Bennedsen, Nielsen, Perez-Gonzalez and Wolfenzon.
3. Application to "Why Do Management Practices Differ across Firms and Countries?", 2010, Bloom and Van Reenen, Journal of Economic Perspectives.
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5. DIFFERENCE-IN-DIFFERENCE ESTIMATOR THEORY
1. Identificattion
2. Key Assumptions
3. Dif-in-Dif in Regression Form
PRACTICE
1. Empirical paper: "Inside the Family Firm: The Role of Families in Succession Decisions and Performance", 2007, Quarterly Journal of Economics, Bennedsen, Nielsen, Perez-Gonzalez and Wolfenzon.
2. Empirical paper: "Tracing the Impact of Bank Liquidity Shocks: Evidence from an Emerging Market", 2008, American Economic Review, Khwaja and Mian.
3. Dif-in-Dif implementation in Stata
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Relation between Activities and Contents
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| Individual paper |
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Methodology
The course intends to provide the student with an overview of different state of the art econometric techniques. These tools will help the student design his/her own quantitative research question according to the nature of the data available to the student. The course includes practical lessons during which students will learn the basics of the statistical package Stata and how to implement the theoretical concepts developed in class using this program.
ASSESSMENT
ASSESSMENT BREAKDOWN
| Description |
% |
| Individual paper |
100 |
Assessment criteria
The grade will be based on an empirical exercise. You will be provided with a data set and a research question. You will have to do the following:
1. Short literature review on the topic
2. Propose estimation method
3. Estimate the model using Stata
4. Analyze your results paying particular attention to potential pitfalls (i.e., selection bias, measurement error, reverse causality and omitted variable bias)
5. Propose potential solutions
You will have to hand in a 10-15 page report with this analysis. Handing in the report is a necessary condition to pass the course. Class attendance is a necessary condition to pass the course. Failing to attend classes or submit the project will result in failure of the course.
Bibliography
Stock and Watson (2012), Introduction to Econometrics, Pearson, 3rd Edition.
Verbeek M. (2004), A Guide to Modern Econometrics, Wiley, 2nd Edition.
