NBER Publications by James Powell
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| November 2008 | Identification and Estimation of 'Irregular' Correlated Random Coefficient Models
with Bryan S. Graham: w14469
In this paper we study identification and estimation of a correlated random coefficients (CRC) panel data model. The outcome of interest varies linearly with a vector of endogenous regressors. The coefficients on these regressors are heterogenous across units and may covary with them. We consider the average partial effect (APE) of a small change in the regressor vector on the outcome (cf., Chamberlain, 1984; Wooldridge, 2005a). Chamberlain (1992) calculates the semiparametric efficiency bound for the APE in our model and proposes a √N consistent estimator. Nonsingularity of the APE’s information bound, and hence the appropriateness of Chamberlain’s (1992) estimator, requires (i) the time dimension of the panel (T) to stric... |
| 1986 | The Cyclical Behavior of Industrial Labor Markets: A Comparison of the Prewar and Postwar Eras
with Ben S. Bernanke
in The American Business Cycle: Continuity and Change, Robert J. Gordon, ed.
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| June 1984 | The Cyclical Behavior of Industrial Labor Markets: A Comparison of the Pre-War and Post-War Eras
with Ben S. Bernanke: w1376
This paper studies the cyclical behavior of a number of industrial labor markets of the pre-war (1923-1939) and post-war (1954-1982) eras. In the spirit of Burns and Mitchell we do not test a specific structural model of the labor market but instead concentrate on describing the qualitative features of the (monthly, industry-level) data.The two principal questions we ask are: First, how is labor input (as measured by the number of workers, the hours of work, and the intensity of utilization) varied over the cycle ? Second, what is the cyclical behaviorof labor compensation (as measured by real wages, product wages, and real weekly earnings) ? We study these questions in both the frequency domain and the time domain. Many of our findings simply reinforce, or perhaps refine, existing percept... |
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