This course will provide participants an extensive range of up-to-date statistical and econometric techniques to analyze microeconomic data. In particular, a wide variety of microeconometric methods available in Stata will be covered, including linear regression, instrumental-variables estimation, nonlinear models for binary, multinomial, and censored models, estimation of average treatment effects, simulation and bootstrapping, and duration analysis. Special emphasis will be placed on the rationale of the models, the implementation of the methods and the interpretation of the results using multiple examples. Overall, the course aims to help participants analyze microeconomic data by applying different econometric techniques using a popular specialized software.
Applications for this course must be submitted by July 24, 2014.
Course materials available to AGRODEP members only
Chapter 0: Preliminaries & Review
- Introduction and general discussion on microeconometric methods
- Basic data analysis in Stata
Chapter 1: Linear models
- OLS and GLS regressions
- Robust and clustered standard errors
- Regression analysis, prediction and specification tests
Chapter 2: Instrumental-variables estimation
- IV estimators: IV, 2SLS and GMM
- Testing for endogeneity and overindentifying restrictions
- Weak instruments
Chapter 3: Nonlinear models
- Binary response models: Linear Probability Model, Probit and Logit
- Multinomial response models: Multinomial Logit
- Censored models: Tobit and Selection models
Chapter 4: Estimation of average treatment effects
- Regression methods
- Propensity score matching
Chapter 5: Simulation and bootstrapping
- Simulation applications
- Bootstrap methods
Chapter 6: Duration Analysis
- Hazard Functions
The course level is appropriate for participants with a background in economics or related fields, statistics, mathematics, and/or public policy. A strong background in quantitative analysis is preferable. Basic knowledge of Stata is required.
In order to apply for this course, AGRODEP members must complete the following by July 24, 2014:
You do not need to retake the Stata test if you have already successfully passed it.
If you would like to practice using Stata before taking the proficiency test, please review the modules below. Information included covers Stata use for beginners, linear regressions, bivariate regressions, and panel data. You will need to know this information to successfully complete the test.
- Training Module 1: Introduction to Stata
- Training Module 2: Basic Data Management, Graphs, and Log-Files
- Training Module 3: Linear Regressions
- Training Module 4: Bivariate Regressions
- Training Module 5: Panel Data Regressions
Manuel A. Hernandez is a Research Fellow at IFPRI. He received his PhD in Economics from Texas A&M University. He also holds a Bachelor’s degree in Economics from the Universidad del Pacifico in Lima, Peru. Prior to starting his graduate studies, he worked for more than four years in different research institutes in Peru, including the Research Center of the Universidad del Pacifico (CIUP) and the Group of Analysis for Development (GRADE). He has been involved in several research projects on labor markets, small and medium enterprises, informal economy, impact evaluation and industrial organization and regulation. His current research interests lie in the areas of oligopoly markets, risk scoring, price volatility and impact evaluation.