Daniel Henderson is a professor of economics and the J. Weldon and Delores Cole Faculty Fellow at the University of Alabama and an associate expert at FWO (Research Foundation - Flanders) in Brussels, Belgium. He was formerly an associate and assistant professor of economics at the State University of New York at Binghamton. He has held visiting appointments at the Université catholique de Louvain, in Louvain-la-Neuve, Belgium (Institute of Statistics), Xiamen University (Wang Yanan Institute for Studies in Economics) in Xiamen, China and at Southern Methodist University, in Dallas, Texas (Department of Economics). He received his Ph.D. in economics from the University of California, Riverside in 2003 and his B.A. in economics from the University of California, Davis in 1998.

His research focus is in applied nonparametric microeconometrics with an emphasis in the economics of education, and economic growth and development. He has also written papers examining the determinants of child health, environmental economics, and international trade. His work has been published in journals such as Computational Statistics and Data Analysis, Economic Journal, Economics of Education Review, European Economic Review, International Economic Review, Journal of Applied Econometrics, Journal of Business and Economic Statistics, Journal of Econometrics, Journal of Human Resources, Journal of the Royal Statistical Society, Oxford Bulletin of Economics and Statistics, and Review of Economics and Statistics.

In addition to many subfields of economics, his work has been cited in the fields of Accounting, Archeology, Engineering, Environment, Management, Operations Research, Physical and Life Sciences, Production and Manufacturing, Regional Science and Statistics.

His research has been featured in local, national and international newspapers, magazines and blogs, including: (1) Newspapers -- Boston Globe, Chronicle of Higher Education and Sunday Telegraph (AU) (2) Magazines -- Atlantic Monthly, Business Week Online and U.S. News and World Report (3) Blogs -- Hechinger Report, Inside Higher Education and New York Times.

He joined IZA as a Research Fellow in October 2008.

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Publications

IZA Discussion Paper No. 10747
Published in: Journal of Labor Research, 2017, 38(3), 261–282 |

This note takes a first look at the distribution of returns to education for people with disabilities, a particularly disadvantaged group whose labor market performances have not been well studied or documented. Using a nonparametric approach, we uncover significant heterogeneity in the returns to education for these workers, which is...

IZA Discussion Paper No. 10076
published in: Applied Economics, 2017, 49(12), 1164-1184

We examine the educational production function and efficiency of public school districts in Illinois. Using nonparametric kernel methods, we find that most traditional schooling inputs are irrelevant in determining test scores (even in a very general setting). Property tax caps are the only relevant factor that is related to districts'...

IZA Discussion Paper No. 8771
published in: Economics Letters, 2015, 128, 17-20

We examine the (potentially nonlinear) relationship between inequality and growth using a method which does not require an a priori assumption on the underlying functional form. This approach reveals a plateau completely missed by commonly used (nonlinear) parametric approaches - the economy first expands rapidly with a large decline in...

IZA Discussion Paper No. 8736
published in: Empirical Economics, 2015, 48, 227-251

In this paper, we employ a partially linear nonparametric additive regression estimator, with recent U.S. Current Population Survey data, to analyze returns to schooling. Similar to previous research, we find that blacks and Hispanics have higher rates of return on average. However, for married males, while non-Hispanic whites have lower...

IZA Discussion Paper No. 8144
published in: Journal of Business and Economic Statistics, 2014, 32, 555-575

In this paper we consider nonparametric estimation of a structural equation model under full additivity constraint. We propose estimators for both the conditional mean and gradient which are consistent, asymptotically normal, oracle efficient and free from the curse of dimensionality. Monte Carlo simulations support the asymptotic developments. We employ a...

IZA Discussion Paper No. 7089
published in: Oxford Bulletin of Economics and Statistics, 2014, 76 (3), 334-359

Empirical growth regressions typically include mean years of schooling as a proxy for human capital. However, empirical research often finds that the sign and significance of schooling depends on the sample of observations or the specification of the model. We use a nonparametric local-linear regression estimator and a nonparametric variable...

IZA Discussion Paper No. 6874
published in: Jeffrey Racine, Liangjun Su and Aman Ullah (eds.), Oxford Handbook of Nonparametric and Semiparametric Econometrics and Statistics, Oxford: OUP, 2014

This paper offers some new directions in the analysis of nonparamertric models with exogenous treatment assignment. The nonparametric approach opens the door to the examination of potentially different distributed outcomes. When combined with cross-validation, it also identifies potentially irrelevant variables and linear versus nonlinear effects. Examination of the distribution of...

IZA Discussion Paper No. 6781
published in: Economics Letters, 2012, 117 (3), 578-581

A simple graphical approach to presenting results from nonlinear regression models is described. In the face of multiple covariates, 'partial mean' plots may be unattractive. The approach here is portable to a variety of settings and can be tailored to the specific application at hand. A simple four variable nonparametric...

IZA Discussion Paper No. 5997
published in: Journal of the Royal Statistical Society, Series A (Statistics in Society), 2012, 175 (4), 863-892

In this paper we compare two flexible estimators of technical efficiency in a cross-sectional setting: the nonparametric kernel SFA estimator of Fan, Li and Weersink (1996) to the nonparametric bias corrected DEA estimator of Kneip, Simar and Wilson (2008). We assess the finite sample performance of each estimator via Monte...

IZA Discussion Paper No. 5662
published in: Economics of Education Review, 2011, 30 (6), 1202-1214

This paper relaxes the assumption of homogeneous rates of return to schooling by employing nonparametric kernel regression. This approach allows us to examine the differences in rates of return to education both across and within groups. Similar to previous studies we find that on average blacks have higher returns to...

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