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Human capital accumulation increases productivity and employment opportunities.


1 Overview

Human capital accumulation increases productivity and employment opportunities. One approach to quan- tifying the returns to human capital is to estimate the effect of a year of schooling on an individual’s wage. While economics has developed sound theoretical foundations, empirical work on the return to human cap- ital has been at the center of considerable debate.


For our term project, we will explore a part of that debate by estimating the returns to education replicating (approximately, I have simplified the analysis to a degree) the results of Angrist and Krueger (1990). I chose this approach to foster critical thinking and deepen econometric knowledge. Our analysis will also draw upon the Bound, Jaeger, and Baker’s (1995) critique of the instrumental variables approach used in Angrist and Kreuger (1990).


Throughout the term, you will complete parts of the analysis and submit each component as a homework assignment. In doing so, I can assist with your learning of econometrics in practice. Additionally, the home- work assignments enable me to address issues with coding or analysis.


For each assignment, you need only to submit what is requested. You will save the project components completed as homework and compile each one into single document that you will submit at the end of the term. The compiled document, described below, is your term paper for ECON 4400.


We will use the 2021 American Community Survey (ACS) to estimate the returns to education and the probability of participating in the labor force. Per the U.S. Census Bureau:

“The American Community Survey (ACS) is an ongoing survey that provides vital information on a yearly basis about our nation and its people.”

You will conduct your analysis of the returns to education and labor force participation using a sample of individuals residing in a U.S. state. Table 1 lists the state assigned to each student. To download your assigned datafile, log on Carmen, go to Modules, scroll toward the bottom of the page, and download the state datafile assigned to you.


2 Paper Requirements and Expectations

You will write, at most, a three-page analysis (not including tables and can be longer if needed) of the returns to education (and of labor force participation) and submit it at the beginning of class on Friday, 04/21. The paper will also include three tables: a table of summary statistics, labor force participation estimates, and returns to education estimates (see Sections 3.1, 3.2, 3.3, and 3.4). You need to attach your do-file with the


paper. If you do not submit a working do-file, you will receive, at most, half credit for this assessment.


Your do-file needs to be cleaned of any incorrect commands, i.e., commands that do not produce output, generate an error, and any redundant or unneeded commands. The entire do-file needs to be executable. In other words, if you click the execute icon, Stata executes every command without error.


Your write-up of the analysis should follow the below general outline–the sub-items do not need to follow the stated order. At a minimum, you must address each enumerated item. Your writing needs to flow (does not read as an itemized list). Each paragraph must consist of one key idea and includes supportive statements (evidence, results, etc.) of that key idea. Additionally, you need to ensure your writing includes transitions between key ideas (paragraphs).

1. Introduction

(a) Discuss the importance and benefit of education in the context of earnings.

(b) For background, read

“Economic returns to education: What We Know, What We Don’t Know, and Where We Are Going–Some Brief Pointers” by Dickson and Harmon (2011)

“Does Compulsory School Attendance Affect Schooling and Earnings” by Angrist and Krueger (1990)

“Educational Attainment and Quarter of Birth: A Cautionary Tale of LATE” by Barua and Lang (2008)

“Problems With Instrumental Variables Estimation When the Correlation Between the In- struments and the Endogenous Explanatory Variable is Weak” by Bound, Jaeger, and Baker (1995)

You can access the papers on Carmen Modules, Articles for Term Project–bottom of the Modules page

2. Data and Methodology

(a) Discuss the data used for analysis

(b) Discuss the subsamples used for analysis, referencing the summary statistics

3. Labor Force Participation

(a) State the objective of using regression analysis to explain labor force participation

(b) Include the labor force participation model (see Section 3.4)

(c) Discuss the OLS and Logistic results

4. Returns to Education

(a) Introduce and discuss the wage equation (see Section 3.2)

(b) Discuss OLS return to education

(c) Discuss how robust the estimated return to education is to the inclusion of occupational dummy variables

(d) Discuss Why OLS estimate for the return to education is biased

(e) Discuss Two Stage Least Squares (2SLS) estimator–how does it address the endogeneity prob- lem?


(f) Discuss the instrumental variables (see Section 3.3), including the relevancy and validity re- quirements

(g) Discuss the 2SLS return to education

(h) Discuss the local average treatment effect (LATE)

(i) Discuss how robust the estimated return to education is to the inclusion of occupational dummy variables

(j) Compare and discuss OLS versus 2SLS estimates. Do the result meet expectations? Explain (Hint: why is OLS biased?) Discuss the F-statistic from the test for weak instruments. What insights does the test provide regarding the results?

5. Discussion and Conclusion



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