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KINT 4070 - INTRODUCTION TO ECONOMETRICS USING STATA : APPLICATION TO POLICY EVALUATION

Type d'enseignement : Seminar

Semester : Spring 2017-2018

Number of hours : 24

Language of tuition : English

Voir les plans de cours et bibliographies

Pre-requisite

Content will be accessible to a broad audience, but the discipline is based on mathematics and statistics. Hence, students will be expected to have taken a college-level statistics course. Knowledge of differential calculus is also recommended. In addition, approximately half of the course will be spent on problems using Stata. Students should be accustomed to using a computer and be enthusiastic about learning a new programming language. Finally, most examples and exercises will be about public policy evaluation in developed and developing countries. Students should preferably have some interest in this field.

Course Description

The objective of the course is to introduce the fundamental concepts of econometrics to students with little quantitative background, but interested in the field of public policy and impact evaluation. The course will be divided into two sections: 1) Introduction to basic skills and knowledge needed to understand quantitative analysis (descriptive stats, inferential stats, OLS). 2) Application to experimental and non experimental evaluation techniques (before and after, simple comparison, difference-in-differences, multivariate regression, instrumental variable and randomized evaluation). Each 2 hours course will be divided as follow: 1) Lecture 2) homework corrections/work in Stata.

Teachers

GLOVER, Dylan (PhD candidate, Teaching Assistant)

Pedagogical format

For each course, I will present using lecture slides and give out weekly homework.

Course validation

Participation (15%). Mid-term exam (35%). Final exam (50%).

Workload

2-3 hour/week.

Additional required reading

  • Introductory Econometrics (Wooldridge)
  • Mostly Harmless Econometrics (Angrist and Pischke)

Plans de cours et bibliographies

Session 1: Descriptive Statistics

Assignment for this session

  • Application to stata 1

Session 2: Inferential Statistics

Assignment for this session

  • Application to stata 2

Session 3: Comparing means and simple regression

Assignment for this session

  • Application to stata 3

Session 4: Variance of an estimator 

Assignment for this session

  • Application to stata 4

Session 5: Multivariate Regression

Assignment for this session

  • Application to stata 5

Session 6: Midterm/Naive impact estimation: Before and after/Simple Comparison and Omitted Variable Bias

Assignment for this session

  • Application to stata 6

Session 7: Non linearities and interactions

Assignment for this session

  • Application to stata 7

Session 8: Difference in differences

Assignment for this session

  • Application to stata 8

Session 9: Fixed effects

Assignment for this session

  • Application to stata 9

Session 10: Instrumental variables

Assignment for this session

  • Application to stata 10

Session 11: Randomized Evaluation

Assignment for this session

  • Application to stata 11

Session 12: Final

biographical information

Dylan holds a PhD in Economics from SciencesPo. He is currently a Post Doctoral researcher at INSEAD focusing on the topics of labor, discrimination and inequality. He previsouly received a BA in Political Economy from UC Berkeley and Masters degrees in Economics and Economics and Public Policy from SciencesPo and Ecole Polytechnique. He started working at the Paris School of Economics in 2007 as part of J-PAL Europe, a research lab specialized in policy analysis using randomized controlled trials (RCT) before becoming a Research Manager on an RCT in Morocco which aimed to evaluate the impact of an entrepreneurial support program provided to small businesses and rural cooperatives. He is currently studying the effects of discrimination on job search, the impacts of changing firm recruiting behavior, the relationship between geographic mobility and unemployment and perceptions of inequality among the rich.