Joshua Angrist is a Professor in the MIT Economics Department and a Research Associate at the National Bureau of Economic Research in Cambridge, Massachusetts. Previously, he was on the faculties of The Hebrew University of Jerusalem, and Harvard University. His Bachelor's degree is from Oberlin College. Professor Angrist is a fellow of the Econometric Society and has published widely on the economic returns to schooling, the determinants of school quality, the relationship between military service and the civilian labor market, and econometric methodology. He has worked as a consultant to the U.S. and Israeli governments on labor market issues and data, and teaches courses on program and policy evaluation methods for government officials in a number of countries. Professor Angrist is currently working on projects related to education policy, achievement incentives, immigration, and econometric methods.
Joshua Angrist started off by underlining the three key criteria any applied work should meet, being quality, clarity and credibility. Capturing relationships is the core of a regression, which was discussed within the broader setting of the conditional expectation function (CEF). Thinking deeper about capturing relationships brought the issue of causality to the floor and the notion that a discussion on causality is only sensible when there is room to manipulate the explanatory variable. This observation was followed by a detailed look at some empirical work on human capital earnings functions and the effect on earnings of serving in the military. The next day the lecture expanded on the examples of the previous day and discussed the evaluation of (training) programs in general. Using the observation that even when it is difficult to experiment there might be so called natural experiments to exploit, the last lecture closed the circle returning to the regression approach by including Instrumental Variables. All this was supported by well known published empirical work.
2. Gerard Pfann (IZA and Maastricht University)
Gerard Pfann (1959) is IZA's Research Director since September 2001. He is also Full Professor of Econometrics and Management Sciences at Maastricht University (The Netherlands) since 1996. In 1996 Gerard Pfann received the prestigious PIONIER Research Award from the Netherlands Science Foundation that he used to create the Business Investment Research Center (BIRC) at Maastricht University. He continues to hold his position as Director of BIRC. During the period 1993 to 1998 he acted as Founding Editor of the Journal of Empirical Finance.
Gerard holds a Master's degree in Econometrics (1985) from the University of Amsterdam, and received his Ph.D. in Economics (1989) from Maastricht University. In 1990 he was appointed Fellow of the Royal Netherlands Academy of Arts and Sciences (KNAW). He held visiting positions at the Irving B. Harris Graduate School of Public Policy Studies at the University of Chicago (2000-2001) and at the Graduate School of Business (1993-1994). He held Research Fellowships from the Center of Operations Research and Econometrics (CORE) and the Department of Economics at the Université Catholique de Louvain-la-Neuve (1989-1990), as well as from the European Commission (1990), and was Visiting Scholar at the Institute of Empirical Macroeconomics in Minneapolis (1991) and at the Institute of Economics and Statistics at Oxford University (1988-1989).
Gerard's research interests are empirical econometrics applied to labor economics, investment decision making, human resource management, and industrial organization.
Gerard Pfann started off by carefully describing the origin of the concept of adjustment costs within the field of labor economics. Whereas in the long run the economy will be in equilibrium, adjustment costs play an important role in the short run. Different specifications were discussed and it was shown how time series estimates could reveal the underlying parameters of structural models of adjustment costs. A brief discussion on the lumpiness of adjustment costs introduced the notion of (firing) costs under uncertainty. The role of uncertainty was illuminated using an option value model. The flip side of the coin, quits, were discussed in a similar framework under no uncertainty, uncertainty and uncertainty with the possibility of an extremely severe negative shock. In the last lecture, all these notions came together in the detailed case study of a large Dutch aircraft manufacturer that experienced a substantial amount of adjustments (downsizing) and eventually ended in a bankruptcy of the firm.
Outline of the Lectures and Reading List
EMPIRICAL STRATEGIES IN APPLIED ECONOMETRICS (download complete outline in PDF format)
I. AGNOSTIC REGRESSION
G. Chamberlain, "Panel Data," Chapter 22 in The Handbook of Econometrics, Volume II, Amsterdam:
II. CAUSAL REGRESSION AND REGRESSION VS. MATCHING
J. Angrist and A. Krueger, "Empirical Strategies in Labor Economics," Chapter 23 in O. Ashenfelter and
D. Card, eds., The Handbook of Labor Economics, Volume III, North Holland, 1999.
J. Angrist, "Estimating the Labor Market Impact of Voluntary Military Service Using Social Security
Data on Military Applicants," Econometrica, March 1998.
III. ESTIMATING THE EFFECT OF TRAINING PROGRAMS
R. Lalonde, "The Promise of Public Sector-Sponsored Training Programs," The Journal of Economic
Perspectives 9 (Spring 1995), 149-168.
O. Ashenfelter and D. Card, "Using the Longitudinal Structure of Earnings to Estimate the Effect of
Training Programs on Earnings," The Review of Economics and Statistics 67 (1985):
R. LaLonde, "Evaluating the Econometric Evaluations of Training Programs with Experimental Data,"
American Economic Review 76 (September 1986): 604-620.
J. Heckman and J. Hotz, "Choosing Among Alternative Nonexperimental Methods for Estimating
the Impact of Social programs: The Case of Manpower Training," JASA 84 (1989): 862-8.
R. Dehejia and S. Wahba, "Causal Effects in Nonexperimental Studies: Re-evaluating the Evaluation of
Training Programs," JASA 94 (Sept. 1999).
IV. INSTRUMENTAL VARIABLES
A. Models with constant effects; Wald, grouping, and two-sample IV
J. Angrist and A. Krueger, "Instrumental Variables and the Search for Identification," Journal of
Economic Perspectives, Fall 2001.
W. Newey, "Generalized Method of Moments Specification Testing," Journal of Econometrics 29
J. Angrist, "Grouped Data Estimation and Testing in Simple Labor Supply Models," Journal of
Econometrics, February/March 1991.
J. Angrist and A. Krueger, "The Effect of Age at School Entry on Educational Attainment: An
Application of Instrumental Variables with Moments from Two Samples," JASA 87 (June 1992),
J. Angrist and A. Krueger, "Split-Sample Instrumental Variables Estimates of the Returns to Schooling,"
JBES, April 1995.
J. Angrist, "Lifetime Earnings and the Vietnam Era Draft Lottery: Evidence from Social Security
Administrative Records," American Economic Review, June 1990.
B. IV with heterogeneous potential outcomes
G. Imbens and J. Angrist, "Identification and Estimation of Local Average Treatment Effects,"
Econometrica, March 1994.
J. Angrist, G. Imbens, and D. Rubin, "Identification of Causal effects Using Instrumental Variables,"
with comments and rejoinder, JASA, 1996.
J. Angrist and G. Imbens, "Two-Stage Least Squares Estimation of Average Causal Effects in Models
with Variable Treatment Intensity," JASA, June 1995.
J. Angrist and A. Krueger, "Does Compulsory Schooling Attendance Affect Schooling and Earnings?,"
Quarterly Journal of Economics 106, November 1991, 979-1014.
V. MISCELLANEOUS TOPICS
A. Limited dependent variables and quantile treatment effects
A. Abadie, "Semi-Parametric Estimation of Instrumental Variable Models for Causal Effects," NBER
Technical Working Paper No. 261, September 2000.
J. Angrist, "Estimation of Limited-Dependent Variable Models with Binary Endogenous Regressors:
Simple Strategies for Empirical Practice," The Journal of Business and Economic
Statistics, January 2001.
A. Abadie, J. Angrist, and G. Imbens, "Instrumental Variables Estimation of the Effect of Subsidized
Training on the Quantiles of Trainee Earnings," Econometrica, November, 2001.
J. Angrist and W. Evans, "Children and their Parents' Labor Supply: Evidence from Exogenous Variation
in Family Size," American Economic Review, June 1998, 450-477.
B. Clustering and the Moulton problem
B. Moulton, "Random Group Effects and the Precision of Regression Estimates," Journal of
Econometrics 32 (1986), pp. 385-97.
K. Liang, and Scott L. Zeger, "Longitudinal Data Analysis Using Generalized Linear Models,"
Biometrika 73 (1986), 13-22.
C.M. Schmidt, Rob Baltussen, and Rainer Sauerborn, "The Evaluation of Community-Based
Interventions: Group-Randomization, Limits and Alternatives," IZA DP No. 206, October 2000.
Z. Feng, P. Diehr, A. Peterson, and D. McLerran, "Selected Statistical issues in Group Randomized
Trials," Annual Review of Public Health 22 (2001), 167-87.
C. The propensity score paradox
J. Hahn, "On the Role of the Propensity Score in Efficient Estimation of Average Treatment
Effects," Econometrica 66, March 1998.
J. Angrist and J. Hahn, "When to Control for Covariates? Panel-Asymptotic Results for Estimates of
Treatment Effects," NBER Technical Working Paper, May 1999.
THE LABOR ECONOMICS OF ADJUSTMENT COSTS
The first lecture will give an overview of the prevailing dynamic adjustment models of labor as a productive input. The second lecture is dedicated to deriving optimal decision rules for employment adjustment under uncertainty when a firm faces fixed and irreversible adjustment costs. An empirical application of downsizing illustrates the importance of these rules to understand how heterogeneous firing costs affect optimal firm behavior. The third lecture will present a new model of two-sided learning when both workers and the employer face irreversible costs to separate.
Walter Oi (1962): "Labor as a Quasi-Fixed Factor." JPE 70, p538-55.
Steve Nickell (1978): "Fixed Costs, Employment, and Labour Demand over the Cycle." Economica 45, p329-45.
Tom Sargent (1978): "Estimation of Dynamic Labor Demand Schedules under Rational Expectations." JPE 86, p1009-44.
Dan Hamermesh (1989): "Labor Demand and the Structure of Adjustment Costs." AER 79, p674-89.
Dan Hamermesh and Gerard Pfann (1996): "Adjustment Costs in Factor Demand." JEL 34, p1264-92.
Avinash Dixit (1989): "Entry and Exit Decisions under Uncertainty." JPE 97, p620-638.
Samuel Bentolila and Guiseppe Bertola (1990): "Firing Costs and Labour Demand: How Bad is Eurosclerosis?" REStud 57, p381-402.
Gerard Pfann (2001): "Options to Quit." EL 70, p259-65.
Gerard Pfann (2001): "Downsizing." IZA DP 307.
Roy Radner (1981): "Monitoring Cooperative Agreements in a Repeated Principal-Agent Relationship." Econometrica 49, p1127-48.
Leonardo Felli and Chris Harris (1996): "Learning, Wage Dynamics, and Firm-Specific Human Capital." JPE 104, p838-68.
Gerard Pfann and Dan Hamermesh (2001): "Two-Sided Learning, Labor Turnover, and Worker Displacement." NBER WP-8273.