Event: Micro Econometrics Course
Venue: Indepth Research Services, Nairobi, Kenya.
Event Date: 30th October -10th November, 2017
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INTRODUCTION
This course consists of lectures and computer sessions which focus upon a number of models and estimators that figure prominently in what is referred as Microeconometrics. The course provides a review and practical guide to a number of microeconometric models and estimators. The focus is on panel data models as well as on a broad class of models of discrete choice behavior.
This course will teach topics from an applied perspective and demonstrate the techniques using Stata.
Duration
10 Days
Who should attend?
The course 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.
Objectives
• Introduce participants to a number of estimators and concepts that represent central aspects of micro econometrics.
• To help participants analyze microeconomic data by applying different econometric techniques using a popular specialized software (Stata).
• To broaden the knowledge of participants on estimation techniques.
Topics to be covered
Overview
• Introduction and general discussion on micro econometric methods
• Basic data analysis in Stata
Policy evaluation
• Causality and Inference
• Economic Policy Evaluation
o Treatment Effects
o The Self-Selection Problem
o Matching
Estimation
• OLS and the Method of Moments
• Gauss Markov Assumptions
Endogeneity and instrumental variable estimation
• Conditional and Unconditional Moments
• The OLS and the IV Estimator
• Instruments
o The Validity of Instruments
o The Relevance of instruments
Linear unobserved effects panel data models
• Introduction to Panel Data Models
• Fixed Effects Models
• Random Effects
• Hausman Tests
Generalized method of moments
• Introduction
• Optimal Weight Matrices: Some Intuition
• The Method of Moments
• OLS and IV Moment Estimators
• Introduction
• Over identification Tests: The Validity of Moment Restrictions
• Identification Tests: The Relevance of Moments
• Weak Identification
• IV/2SLS or GMM
Dynamic panel data models
• Weak versus Strict Exogeneity
• LSDV Bias in Dynamic Models
• The Difference GMM Estimator
• The System GMM Estimator
• Pooled Mean Group Estimators
Discrete choice
• Binary Choice Models
• The Probit and Logit Models
• Partial Effects and Average Partial Effects
• Endogeneity in Binary Choice: control functions, bivariate probit, and the linear probability model
• Theoretical Underpinnings of Discrete Choice Models
• The Specification of a Random Utility Model
• Identification
• The Logit Model
• Endogeneity and Discrete Choice
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