教學大綱 Syllabus

科目名稱：勞動經濟學（三）：勞動經濟實證專題

Course Name: Labor Economics (III): Empirical Methods and Applications
  • 學年學期：112-1 Fall Semester, 2023
  • 科目代碼：258704001 Course No.258704001

修別：選

Type of Credit: Elective

3.0

學分數

Credit(s)

30

預收人數

Number of Students

課程資料Course Details
  • 開課單位：經濟碩一、經濟博一、經濟碩二、經濟博二 Course Department:Economics/G/1&2
  • 授課老師：黃柏鈞 Instructor: HUANG PO-CHUN
  • 先修科目：無Prerequisite(N/A)
  • 上課時間：五D56 Session: fri13-16

課程簡介Course Description

The purpose of this course is to help students understand modern empirical techniques used in labor and public economics. We will focus on two topics:

(1) econometric identification issues in empirical microeconomics--how economists estimate causal effects using observational data

(2) sufficient statistics approach to welfare analysis--how integration of reduced-form estimates and economic theories can help inform the welfare analysis.

Participants are expected to write a high-quality research proposal that will hopefully lead to thesis research.

 

核心能力分析圖 Core Competence Analysis Chart

能力項目說明

    課程目標與學習成效Course Objectives & Learning Outcomes

    1. Understand threats to uncovering causal effects from observational data

    2. Be able to apply a range of econometric tools and interpret estimates

    3. Write a high quality paper proposal that will hopefully lead to your thesis

     

    每周課程進度與作業要求 Course Schedule & Requirements

    教學週次Course Week 彈性補充教學週次Flexible Supplemental Instruction Week 彈性補充教學類別Flexible Supplemental Instruction Type

    Lecture 1: Introduction

    •     Meanings of Identification
    •     Reduced Form vs. Structural Model Identification

    Lecture 2: Counterfactual Framework and Randomized Controlled Trials 

    •     Potential Outcomes
    •     Selection Bias
    •     RAND HIE and OHP

    Lecture 3: Estimating Causal Effects Using Regression Adjustment 

    •     Omitted Variable Bias
    •     Practical Regression Hints  
    •     Technological Change: Krueger (1993) + DiNardo and Pischke (1997) 

    Lecture 4: Machine Learning for Applied Econometrics 

    •     Prediction v.s. Causation
    •     LASSO and Ridge Estimators
    •     Double LASSO

    Lecture 5: Topics on Labor Supply

    •     Substitution and Income Effects of Labor Supply
    •     Labor Supply Effect of Unemployment Insurance (UI)
    •     Elderly Labor Supply and Retirement Benefits

    Mid-Term Presentations 

    Lecture 6: Panel Data and Difference-in-Differences 

    •     Fixed Effect Estimation
    •     Difference-in-Differences
    •     DD with Variations in Treatment Timing: Andrew Goodman-Bacon (2021)

    Lecture 7: Synthetic Control Method

    •     Abadie (2021)
    •     Peri and Yasenov (2019) and Bohn et. al (2014)

    Lecture 8: Topics on Labor Demand: Minimum Wage

    •     Substitution and Scale Effects of Labor Demand 
    •     Recent Advances in Minimum Wage Research
    •     Aaronson, French, Sorkin, and To (2018); Meer and West (2015)

    Lecture 9: Instrumental Variables 

    •     IV and Simultaneous Equations           
    •     IV and LATE
    •     Angrist and Evans (1998): Labor Supply and Fertility

    Group Prsentations: present a paper from the Reading List (announced in class)

    Lecture 10: Topics on Labor Demand: Bartik Instruments

    •     The China Syndrome: Autor et. al (2013)
    •     Bartik Instrument 
    •     Sorkin (2019)

    Lecture 11: Regression Discontinuity (Kink) Designs 

    •     Identifying Assumptions and Estimation
    •     IV and RD
    •     Regression Kink Design
    •     Unemployment Insurance

    Lecture 12: Sufficient Statistic Approach for Welfare Analysis 

    •     Basic Search Model
    •     Optimal Unemployment Insurance: Baily-Chetty Formula
    •     Consumption Based Approach: Gruber (1997)

    Lecture 13: Decomposition Methods in Economics (Optional)

    •     Oaxaca-Blinder Decomposition
    •     DFL Reweighting Method
    •     Chidren and Gender Inequality: Klevens et. al (2020) and Cortes et. al (2020)

    Final Presentations

     

     

    授課方式Teaching Approach

    70%

    講述 Lecture

    30%

    討論 Discussion

    0%

    小組活動 Group activity

    0%

    數位學習 E-learning

    0%

    其他： Others:

    評量工具與策略、評分標準成效Evaluation Criteria

    1. 50% Problem Sets 

    We will do four problem sets during the course of semester. The problem set questions will include both theoretical questions and statistical analysis of data, which will involve the software package STATA.

    2. 50% Presentations and Paper Proposal:

    Each student is required to write a paper proposal. You are encouraged to meet with me to talk about a topic for your paper before midterm presentations. Final proposals are due on January 20.

     

    指定/參考書目Textbook & References

    Recommended Text for Labor Economics

    George Borjas, Labor Economics (6th edition)

    Recommended Text for Econometrics:

    Joshua D. Angrist and JÖrn-Steffen Pischke (2009), Mostly Harmless Econometrics, Princeton University Press 

    Joshua D. Angrist and JÖrn-Steffen Pischke (2016), Mastering 'Metrics, Princeton University Press 

    Jeffrey Wooldridge (2015), Introductory Econometrics: A Modern Approach (6th edition), Cengage 

    Scott Cunningham (2021), Causal Inferences: The Mixtape, Yale University Press

     

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    課程相關連結Course Related Links

    You can download course materials at 

https://wm5.nccu.edu.tw/mooc/index.php

    課程附件Course Attachments

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