Policy Evaluation and Structural Equation Models Using Stata

  • Location: CEMAPRE (ISEG), Lisbon
  • Duration: 4 days (12th September 2017 - 15th September 2017)
  • Software: Stata
  • Level: Various
  • Delivered By: Pierre Hoonhout, Lisbon School of Economics & Management - Universidade de Lisboa
  • Topic: Econometrics, Microeconomics, Policy analysis
Policy Evaluation and Structural Equation Models Using Stata

Course Overview

Most questions of interest are fundamentally questions of causality, for example, what is the effect of some variable x on some other variable y. This course introduces the statistical methods that are currently available for studying such questions. Modern causal analyses are based on either the potential outcomes framework or the structural equation framework. Advantages and disadvantages of both frameworks will be discussed.

Rubin developed the potential outcome approach into a powerful formal framework, the Rubin Causal Model (RCM), for assessing causation in observational data. The resulting methods make only few assumptions, which adds credibility to the results obtained.

Structural Equation Models (SEM) make more assumptions, and have been a dominant influence in management science and marketing for decades. More recently, it has captured the interest of the other social sciences.

A Structural equation model is a causal framework that provides elegant and relatively easy-to-use methods to deal with many important issues that applied empirical researchers have to face. These include multi-level random effects, endogeneity, sample selection and missing data.

Recent versions of Stata include implementations of these methods. This course aims to introduce the theory of the RCM and SEM and show how to apply the theory using Stata.

Course Agenda

Day 1 - The Rubin Causal Model Under Unconfoundedness

  • The Potential Outcomes Framework
  • Regression Methods and Weighting
  • Matching, Regression Discontinuity Design

Day 2 - The Rubin Causal Model With Unobserved Confounders

  • Panel Data and Diff-in-Diff
  • The Control Function Approach
  • GMM estimation and Instrumental Variables
  • Local Average Treatment Effects

Day 3 - Structural Equation Models

  • Maximum Likelihood Estimation
  • Confirmatory Factor Analysis
  • Path Analysis and Structural Equation Models
  • Latent Growth and Group Comparisons

Day 4 - Generalized Structural Equation Models

  • Generalized Linear Models
  • Categorical Responses
  • Models for Counts and Survival/Duration Data
  • Nested and Crossed Random Effects

Preequisites

This course is aimed at students, professionals and researchers in the social sciences that have a basic understanding of the most commonly used econometric models.

Terms & Conditions

  • Student registrations: Attendees must provide proof of full time student status at the time of booking to qualify for student registration rate (valid student ID card or authorised letter of enrolment).
  • Additional discounts are available for multiple registrations.
  • Cost includes course materials, lunch and refreshments.
  • Attendees are provided with temporary licences for the software(s) used in the course and will be instructed to download and install the software prior to the start of the course. Alternatively, we can also provide laptops for an additional cost of £12.00 per day.
  • If you need assistance in locating hotel accommodation in the region, please notify us at the time of booking.
  • Payment of course fees required prior to the course start date.
  • Registration closes 5-calendar days prior to the start of the course.
    • 100% fee returned for cancellations made over 28-calendar days prior to start of the course.
    • 50% fee returned for cancellations made 14-calendar days prior to the start of the course.
    • No fee returned for cancellations made less than 14-calendar days prior to the start of the course.

The number of seats available is restricted. Please register early to guarantee your place.

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    1-day pass (12/09/2017 - 15/09/2017)
    2-day pass (12/09/2017 - 15/09/2017)
    3-day pass (12/09/2017 - 15/09/2017)
    4-day pass (12/09/2017 - 15/09/2017)

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