1) David H. Bernstein, Bent Nielsen. "Asymptotic theory for cointegration analysis when the cointegration rank is deficient," Econometrics, 2019, 7(1), 6.
Abstract: We consider cointegration tests in the situation where the cointegration rank is deficient. This situation is of interest in finite sample analysis and in relation to recent work on identification robust cointegration inference. We derive asymptotic theory for tests for cointegration rank and for hypotheses on the cointegrating vectors. The limiting distributions are tabulated. An application to US treasury yields series is given. working-paper-version
2) David H. Bernstein, Christopher F. Parmeter. "Returns to Scale in Electricity Generation: Replicated and Revisited," Energy Economics, 2017. (forthcoming)
Abstract: We replicate the findings of two influential studies on returns to scale in the United States electricity generation market. The main results are contrasted using both local-linear nonparametric regression, a technique robust to parametric functional form assumptions, as well as an updated data set. While the quantitative findings across all of the estimators deployed differ somewhat regarding the magnitude of returns to scale, we document a decrease in returns to scale within the electricity generation market from 1955 to 1996. working-paper-version
1) Subal Kumbhakar, David H. Bernstein. "Does xistence of inefficiency matter to a neoclassical xorcist? Some econometric issues in panel stochastic frontier models," Springer Proceedings in Business and Economics, 2019. (forthcoming)
Abstract: Does the presence of inefficiency affect estimation of the production function? This paper shows that one cannot ignore inefficiency in estimating the production function simply because standard neoclassical production theory does not recognize its existence. Exclusion of inefficiency can cause inconsistency in the estimates of the technology parameters due to omitted variables which are determinants of inefficiency. We show how one can avoid this inconsistency in estimating the production technology irrespective of whether one is interested in estimating inefficiency or not. Our proposed estimation methods use two state-of-the-art stochastic frontier (SF) panel models. Since distributional assumptions are often a bone of contention even among the followers of the SF approach, we focus on estimation methods that do not rely on distributional assumptions for the inefficiency and noise components.
1) David H. Bernstein. "What moves the labor force participation rate?," Preprints, 2018. (Under review)
Abstract: The seasonally adjusted civilian labor force participation rate, the sum of employed and unemployed persons as a percentage of the civilian non-institutional population, is analysed in the general to specific modelling framework with a saturating set of step indicators from January 1977 through June 2018. The results indicate that, ceteris paribus, the rise in the ratio of women to men in the labor force in addition to positive demographic movements can largely account for the rise in the labor force participation rate up to January 2000. Subsequently, the aging population helps to explain the decline. Recessions play a transitory role.
Work in Progress
1) An updated assessment of efficiency and returns to scale for U.S. electric power plants (job market paper)
2) Robust estimation of the stochastic frontier model (with Christopher F. Parmeter and Ian A. Wright)
3) Modelling and understanding volume (with Eileen Tipoe)
The 2018 North American Productivity Workshop at Miami Business School