Daniel J. Henderson

Growth Empirics Without Parameters

Recent research on growth empirics has focused on resolving model and variable uncertainty. The conventional approach has been to assume a linear growth process and then to proceed with investigating the relevant variables that determine cross‐country growth. This article questions the linearity assumption underlying the vast majority of such research and uses recently developed non‐parametric techniques to handle non‐linearities as well as select relevant variables. We show that inclusion of non‐linearities is necessary for determining the empirically relevant variables and uncovering key mechanisms of the growth process.

Technological Change and Transition: Relative Contributions to Worldwide Growth During the 1990s

In this paper we used the procedures developed in the Kumar and Russell (2002) growth-accounting study to examine cross-country growth during the 1990s. Using a data set comprising developed, newly industrialized, developing and transitional economies, we decomposed the growth of output per worker into components attributable to technological catch-up, technological change and capital accumulation. In contrast to the study by Kumar and Russell (2002), which concluded that capital deepening was the major force of growth and change in the world income per worker distribution over the 1965-1990 period, our analysis showed that, during the 1990s, the major force in the further divergence of the rich and the poor was due to technological change, whereas capital accumulation played a lesser and opposite role. In further contrast, we found that efficiency changes (insignificantly) led (on average) to regress rather than progress. Finally, although on average we found that transitional economies performed similar to the rest of the world, the procedure was able to discover some interesting patterns within the set of transitional countries.

Public and Private Capital Productivity Puzzle: A Nonparametric Approach ∗

Is public expenditure productive? Is there a shortfall or excess in public capital investment? We address these old issues in the light of new econometric tools. It is argued that the Cobb-Douglas specification that ignores nonlinearity inherent in the functional relationship of the production technology causes incorrect estimates of input elasticities. To avoid possible model misspecification, we use Li-Racine generalized kernel estimation. This procedure is used to estimate the returns to private capital, employment, and public capital in gross state product from a panel of 48 states for 17 years. In contrast to previous studies, we find that the return to public capital is positive and significantly different from zero.

Do Former College Athletes Earn More at Work? A Nonparametric Assessment

This paper investigates how students’ collegiate athletic participation affects their subsequent labor market success. By using newly developed techniques in nonparametric regression, it shows that on average former college athletes earn a wage premium. However, the premium is not uniform, but skewed so that more than half the athletes actually earn less than nonathletes. Further, the premium is not uniform across occupations. Athletes earn more in the fields of business, military, and manual labor, but surprisingly, athletes are more likely to become high school teachers, jobs that pay relatively lower wages to athletes.

Does Education Matter for Economic Growth

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 relevance test to conduct a rigorous and systematic search for significance of mean years of schooling by examining five of the most comprehensive schooling databases. Contrary to a few recent papers that have identified significant nonlinearities between education and growth, our results suggest that mean years of schooling is not a statistically relevant variable in growth regressions. However, we do find evidence (within a cross-sectional framework), that educational achievement, measured by mean test scores, may provide a more reliable measure of human capital than mean years of schooling.

Pollution Abatement Costs and Foreign Direct Investment Inflows to U.S. States: A Nonparametric Reassessment

Keller and Levinson (2002) utilize state-level panel data on inflows of foreign direct investment along with an innovative measure of relative pollution abatement costs to assess the impact of environmental stringency on capital flows. Using standard parametric panel data models, the authors find moderate evidence that capital flows are sensitive to abatement costs. Using recently developed nonparametric methods, we assess the robustness of this conclusion. The nonparametric approach reveals that (a) some of the parametric results are not robust, and (b) the impact of relative abatement costs is heterogeneous across states and generally of smaller magnitude than previously suggested.

Imposing Economic Constraints in Nonparametric Regression: Survey, Implementation and Extension

Economic conditions such as convexity, homogeneity, homotheticity, and monotonicity are all important assumptions or consequences of assumptions of economic functionals to be estimated. Recent research has seen a renewed interest in imposing constraints in nonparametric regression. We survey the available methods in the literature, discuss the challenges that present themselves when empirically implementing these methods and extend an existing method to handle general nonlinear constraints. A heuristic discussion on the empirical implementation for methods that use sequential quadratic programming is provided for the reader and simulated and empirical evidence on the distinction between constrained and unconstrained nonparametric regression surfaces is covered.

A Nonparametric Examination of Capital-Skill Complementarity

This paper uses nonparametric kernel methods to construct observation-specific elasticities of substitution for a balanced panel of 73 developed and developing countries to examine the capital-skill complementarity hypothesis. The exercise shows some support for capital-skill complementarity, but the strength of the evidence depends upon the definition of skilled labor and the elasticity of substitution measure being used. The added flexibility of the nonparametric procedure is also able to uncover that the elasticities of substitution vary across countries, groups of countries and time periods.

Fixed vs Random: The Hausman Test Four Decades Later

Hausman (1978) represented a tectonic shift in inference related to the specification of econometric models. The seminal insight that one could compare two models which were both consistent under the null spawned a test which was both simple and powerful. The so-called ‘Hausman test’ has been applied and extended theoretically in a variety of econometric domains. This paper discusses the basic Hausman test and its development within econometric panel data settings since its publication. We focus on the construction of the Hausman test in a variety of panel data settings, and in particular, the recent adaptation of the Hausman test to semiparametric and nonparametric panel data models. We present simulation experiments which show the value of the Hausman test in a nonparametric setting, focusing primarily on the consequences of parametric model misspecification for the Hausman test procedure. A formal application of the Hausman test is also given focusing on testing between fixed and random effects within a panel data model of gasoline demand.

Explaining African Growth Performance: A Production-Frontier Approach

This paper employs a production frontier approach that allows distinguishing technologic progress from efficiency development. Data on 35 African countries in 1970-2007 show that efficiency losses have constrained growth in Africa while technology progress has played a marginal growth enhancing role in the region. Moreover, physical and human capital accumulation are the main factors that drive productivity growth at the country level. Examining the outcomes of successful countries suggests that good governance, institutional quality and good policies are key factors for improving economic development in Africa. These factors are even more required in Sub-Saharan Africa given the natural constraints of geography in the region.