2165-Microeconometrics-2425_S2

Topic outline

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  General

  The course covers a range of advanced econometric techniques frequently employed in the analysis of micro data (at the household, individual or firm level). The course intends to make the student familiar with basic statistical and econometric techniques that are used in the analysis of microeconomic data. Lectures combine theory and empirical applications and will include examples and discussions of empirical papers that employ the different techniques.

  Instructor: Alex Armand (alex.armand@novasbe.pt)
  Office Hours: By appointment (e-mail the instructor)
  Teaching: Mondays 11:00–14:00 | Room B010
  
  Grader: Galina Vysotskaya (galina.vysotskaya@novasbe.pt)
  
  Tentative schedule (evolving during the course): 
  
  

  • General microeconometrics approach: 3 Feb
  • Identification in linear models (cross-section data): 10 Feb - 17 Feb
  • Counterfactuals - from ATE to LATE: 24 Feb - 10 Mar
    
  • Identification in linear models (panel data): 31 Mar - 7 Apr
    
  • Non-linear models and the maximum likelihood: 14 Apr
  • Latent variable models: 21 Apr
  • Censored data: 28 Apr
  • Sample selection: 5 May
  • Revision: 9 May
    

  
  Assignments (see deadline on item below)
  
  PS1 + PS2 + PS3 + Group assignment
  
  FINAL EXAM
  

  • Course Syllabus File
  • Announcements Forum
  • To Self-enroll in this course, click the Gear icon on the right and after that the “Enrol me in this course” - Enrolment key is: metrics25

  • SAMPLE exam File
  • Sample questions File
  • Last year final exam (with solutions) File
  • Final Grades File
  • Final Exam - Solution File
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  Problem sets

  For the submission of problem sets, please use the format that is more convenient for you, the important thing is that the content is readable for the grader. Preferred file format is pdf.
  
  

  • Q&A for Problem Sets - Add here questions or doubts you have about the problem sets Forum
  • Problem set 1 - due March 3rd by 11am Assignment
  • Problem set 1 - Datasets File
  • Problem set 1 - Solution File
  • Problem set 2 - due Apr 7th by 11am Assignment
  • Problem set 2 - Datasets File
  • Problem set 2 - Solution File
  • Problem set 3 - due May 5h by 11am Assignment
  • Problem set 3 - Datasets File
  • Problem set 3 - Solution File
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  Group assignment

  • Group assignment submission - due May 11th (one submission per group is enough - indicate all names in the submitted file)
  • Group assignment File
  • Submit group members - max 4 students per group URL
  • Groups for group assignment File
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  General microeconometrics approach

  • The general microeconometrics approach File
  • VOLUNTARY READING Identification Problems in the Social Sciences and Everyday Life (Manski) File
  • DATA: Dataset for replication of empirical part (STATA format) File
  • DATA: Dataset for replication of empirical part (text delimited format) File
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  Identification in linear models (cross-section data)

  • Linear model with cross section data (updated) File
  • APPLICATION: The Colonial Origins of Comparative Development: An Empirical Investigation (Acemoglu et al.) File
  • APPLICATION: Children and Their Parents' Labor Supply: Evidence from Exogenous Variation in Family Size (Angrist and Evans) File
  • APPLICATION: Does compulsory school attendance affect schooling and earnings (Angrist and Krueger) File
  • DATA: Dataset for replication of empirical part on OLS (Stata format) File
  • DATA: Dataset for replication of empirical part on OLS (text delimited format) File
  • DATA: Dataset for replication of empirical part on IV (STATA format) File
  • DATA: Dataset for replication of empirical part on IV (text delimited format) File
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  Counterfactuals: from ATE to LATE

  • Counterfactuals File
  • DATA: Dataset for replication of empirical part (STATA format) File
  • DATA: Dataset for replication of empirical part (text format) File
  • CODE: STATA code for replicating empirical part File
  • APPLICATION: Evaluating the econometric evaluations of training programs with experimental data (Lalonde) File
  • APPLICATION: Incentive effects of social assistance: A regression discontinuity approach (Lemieux and Milligan) File
  • ADDITIONAL READING ON LATE: Identification and Estimation of Local Average Treatment Effects (Imbens and Angrist) File
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  Identification in linear models with panel data

  • Panel data models File
  • APPLICATION: The costs of low birth weight (Almond et al.) File
  • APPLICATION: Minimum wages and employment - A case study of the fast-food industry in New Jersey and Pennsylvania (Card and Krueger) File
  • DATA: Dataset for replication of empirical part (STATA format) File
  • DATA: Dataset for replication of empirical part (text delimited format) File
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  Non-linear models and MLE

  • Introduction to non-linear models File
  • PROOF FOR VOLUNTARY EXERCISE: estimation of parameters of a normal distribution using MLE URL
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  Binary and discrete outcomes

  • Binary and discrete outcomes File
  • APPLICATION: The sensitivity of an empirical model of married women's hours of work to economic and statistical assumptions (Mroz) File
  • DATA: Dataset for replication of empirical part (text delimited format) File
  • DATA: Dataset for replication of empirical part (STATA format) File
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  Data censoring and corner solution outcomes

  • Data censoring and corner solution outcomes File
  • DATA: Dataset for replication of empirical part (STATA format) File
  • DATA: Dataset for replication of empirical part (text delimited format) File
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  Missing data and selection models

  • Missing data and selection models File
  • DATA: Dataset for replication of empirical part (STATA format) File
  • DATA: Dataset for replication of empirical part (text delimited format) File
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  Generalized Method of Moments

  Not available