Current Teaching
Fall 2017, ECON 4531, Labor Economics
Office: Hanson Hall 3-107
Office Hours: Thursday 2:30-4:30 pm or by appointment
Email: fazil001 at umn dot edu
Please use the moodle site for updates about the course. Main textbook (required) is Labor Economics, 7th Edition by George Borjas. The Natural Survival of Work, by Pierre Cahuc and Andre Zylberberg, is a supplementary book to learn the policies to deal with unemployment. Mastering Metrics, by Joshua D. Angrist and Jörn-Steffen Pischke, covers the empirical methods discussed in the class.
Some Important Topics:
  • Selection bias in estimating labor supply curve, compensating wage differentials, return to schooling, etc.
  • Simultaneity bias in estimating supply or demand
  • Time, cohort and age effects; cross-sectional vs. panel data
  • How to overcome biases in estimation; instrumental variable, difference-in-difference estimation, experimental design, treatment and control groups
References:
Labor Supply Estimation:​
  • Heckman, James J. "Sample Selection Bias as a Specification Error." Econometrica 47.1 (1979): 153-161.​
⇨ If one wants to estimate the labor supply elasticity, there may be a sample selection bias in the results for mainly two reasons: i) Individuals self-select whether to enter the labor market or not, ii) Analysts mostly trim the data in a non-random way. Different from the omitted variable bias, this bias is due to having missing observations and a nonrandom sample.

Labor Demand Estimation:
  • Hamermesh, Daniel S., and Stephen J. Trejo. "The demand for hours of labor: Direct evidence from California." Review of economics and statistics 82.1 (2000): 38-47.
⇨ According to regulations in California, employees must be paid 1.5 times the employee's regular rate of pay for all hours worked in excess of eight hours. This regulation started to cover men after 1980. Exploiting this policy change, a difference in difference estimator is used to estimate price elasticity of demand for overtime hours.
  • Card, David, and Alan B. Krueger. "Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania." American Economic Review 84 (1994): 772-793. ​
 ​⇨ In 1992, minimum wage increased in New Jersey while it stayed constant in Pennsylvania. Difference in difference estimator is used to assess the effect of minimum wages on employment. 
  • Acemoglu, Daron, David H. Autor, and David Lyle. "Women, war, and wages: The effect of female labor supply on the wage structure at midcentury." Journal of political Economy 112.3 (2004): 497-551.
​⇨ Military mobilization of men during WW2 was not uniform across states and was highly correlated with change in female employment. To get rid of simultaneity bias, mobilization rates is used as an instrumental variable and female labor demand elasticity is estimated.

Equilibrium
  • Card, David. "The Impact Of The Mariel Boatlift on the Miami Labor Market." Industrial and Labor Relations Review 43.2 (1990): 245-257.
⇨ The Mariel Boatlift is a mass immigration of Cubans from Cuba's Mariel Harbor to Miami in 1980 for a short period of time. This natural experiment provides an opportunity to analyze the effects of immigration on the labor market.
  • Angrist, Joshua D., and Alan B. Krueger. "Empirical strategies in labor economics." Handbook of labor economics 3 (1999): 1277-1366.
⇨ This paper includes a difference in difference estimation for a boatlift that was anticipated but did not happen. Results cast doubt on Card's paper.
  • Donald, Stephen G., and Kevin Lang. "Inference with difference-in-differences and other panel data." The review of Economics and Statistics 89.2 (2007): 221-233.
⇨ Inference with difference in difference is discussed when the number of groups is small. Based on findings about confidence intervals, they explain seemingly opposite results in the Mariel Boatlift that did and did not happen.

Compensating Wage Differentials
  • Villanueva, Ernesto. "Estimating Compensating Wage Differentials Using Voluntary Job Changes: Evidence from Germany." ILR Review 60.4 (2007): 544-561.
⇨ More skilled workers have higher wage rates and better job amenities, so raw data implies a positive correlation between wage rates and job amenities contrary to the theory about compensating wage differentials. To get rid of the ability bias, one needs to keep track of individuals through time by using panel data.

​Returns to Education
  • Chetty, Raj, et al. "How does your kindergarten classroom affect your earnings? Evidence from Project STAR." The Quarterly Journal of Economics 126.4 (2011): 1593-1660.
  • Duflo, Esther. "Schooling and Labor Market Consequences of School Construction in Indonesia: Evidence from an Unusual Policy Experiment." American Economic Review 91.4 (2001): 795-813.
  • Angrist, Joshua D., and Alan B. Krueger. "Does compulsory school attendance affect schooling and earnings?." The Quarterly Journal of Economics 106.4 (1991): 979-1014.
⇨ More able students choose to get an education for longer periods. Since students self-select their education level, a raw estimate of return to schooling is going to capture the effect of schooling together with an ability bias. To estimate returns to education, Chetty et al. uses data from a randomized (controlled) experiment while Duflo uses data from a natural experiment, a school construction program in Indonesia. Lastly, Angrist and Krueger use birth quarters as instrumental variable to estimate the effect of schooling since birth quarters are related with educational attainment due to school start age and compulsory school attendance policies.

Income Inequality
  • Song, Jae, et al. Firming up inequality. No. w21199. National Bureau of Economic Research, 2015.
⇨ Increase in income inequality in 1980s and 1990s is well documented while the reasons are not clear. Computing between and within group inequality is a way to understand the effect of observables on inequality. This paper investigates the effects of firms on wage inequality by measuring between and within firm inequality using a massive data set.

Labor Mobility
  • Lubotsky, Darren. "Chutes or ladders? A longitudinal analysis of immigrant earnings." Journal of Political Economy 115.5 (2007): 820-867.
⇨ If age-earnings profile of immigrants are drawn by using cross-sectional data, two biases will arise: cohort bias since different cohorts of immigrants can have different characteristics and a selection bias since immigrants self-select to stay or return back. So, a longitudinal data is required to analyze the income of immigrants.

​Labor Market Discrimination
  • Holzer, Harry J., and Keith R. Ihlanfeldt. "Customer discrimination and employment outcomes for minority workers." The Quarterly Journal of Economics 113.3 (1998): 835-867.
⇨ One type of discrimination in the labor market is customer discrimination. This paper use difference in difference method to analyze the effect of customers' racial composition on the employment decisions of the firms. 
Past Teaching
University Of Minnesota
Labor Economics, ECON 4531, Instructor: Fall 2014 (Evaluation Score: 4.31/6), Spring 2015(5.35/6), Fall 2015 (5.57/6), Spring 2016 (5.63/6), Fall 2016.
Introduction to Econometrics, ECON 4261: TA, Summer 2015(5.71/6). Topics covered:
  • Finite sample properties of OLS and large sample theory
  • GMM
  • Panel data econometrics
  • Time-series econometrics
Introduction to Macroeconomics, ECON 1102, Instructor: Fall 2013, Spring 2014.
Introduction to Macroeconomics, ECON 1102, TA: Fall 2012, Spring 2013.
Bilkent University
Introduction to Economics, ECON 101, TA: Spring 2018.
Introduction to Probability and Statistics, ECON 221, TA: Fall 2007.

Some Graphs from Labor Economics Class:
Picture
At first glance, it looks like immigrants' age-earning curve is steeper than the natives. Is this the case in reality? In this graph, there is a cohort bias due to cross-sectional data and also a selection bias since immigrants self-select to stay or return back. So, the truth can be the opposite of what you see.
Picture
If one wants to estimate return to schooling, she is going to face a problem. Data shows the realization of the wage rates but not the counterfactuals. In the context of the left graph, Ace goes to school for 11 years and Bob for 12 years due to difference in the rate of return to education. Then, one can not know what would be the  wage rate of Ace if he went to school for 12 years or the wage rate of Bob if he went to school for 11 years. This is ability bias due to self-selection. There are ways to eliminate this bias. Angrist and Krueger (1991) is a well-known example of using instrumental variable estimation to measure the return to schooling.