Abstracts of Published Papers
Adjustment of Inputs and Measurement of Technical Efficiency:
A Dynamic Panel Data Analysis of the Egyptian Manufacturing Sectors
The purpose of this paper is to construct a dynamic stochastic production frontier incorporating the sluggish adjustment of inputs, to measure the speed of adjustment of output, and to compare the technical efficiency estimates from this dynamic model to those from a static model. By assuming instantaneous adjustment of all inputs, a static model may underestimate technical efficiency of a production unit in the short-run. However, in this paper I show that under the assumption of similar adjustment speed for all inputs, a linear partial adjustment scheme for output characterizes the dynamic production frontier. The dynamic frontier with time-invariant technical efficiency is estimated using the system GMM (generalized method of moments) estimator. Applying the model and estimation method on a panel dataset spanning nine years of data on private manufacturing establishments in Egypt, I find that 1) the speed of adjustment of output is significantly lower than unity, 2) the static model underestimates technical efficiency by 4.5 percentage points on average, and 3) the ranking of production units based on their technical efficiency measures changes when the lagged adjustment process of inputs is taken into account.
Choice, Internal Consistency and Rationality
with Prasanta K. Pattanaik and Yongsheng Xu
(Economics and Philosophy)
Classical rational choice theory is built on several important internal consistency conditions. In recent years, the reasonableness of those internal consistency conditions has been questioned and criticized, and several responses to accommodate such criticisms have been proposed in the literature. This paper develops a general framework to accommodate the issues raised by criticisms of classical rational choice theory, and examines the broad impact of these criticisms on rational choice theory from both a normative and positive point of view.
Abstracts of Completed Papers
Financial Reforms and Technical Efficiency in Indian Commercial Banking:
A Generalized Stochastic Frontier Analysis
(With Sudeshna Pal, Submitted to Review of Financial Economics)
In this study we estimate technical efficiency of Indian commercial banks from 1989 - 2009 using a multiple-output generalized stochastic production frontier, and analyze the effects of financial sector reforms on measured efficiency. This generalized technique estimates technical efficiency in the presence of multiple outputs, filling a gap in the existing literature. Our results show that Indian commercial banks were operating with 64% efficiency on average during the sample period and that efficiency declined in both public and private banks during most parts of the post-reform period. The capital adequacy ratios negatively influenced efficiency while the number of branches had no significant effect on bank efficiency. Financial sector reforms, however, have had mixed results on technical efficiency. The initial phase of reform had positive impact on technical efficiency while the later phases adversely affected technical efficiency of commercial banks. Throughout the sample period, public sector banks show higher efficiency levels compared to private sector and foreign banks.
Adjustment of Inputs and Measurement of Time-varying Technical Efficiency: A Dynamic Panel Data Analysis
(Submitted to Journal of Productivity Analysis)
This paper provides estimation method to measure technical efficiency of production units and the speed of adjustment of output, both varying with time, from a dynamic stochastic production frontier that incorporates the sluggish adjustment of inputs. Using a panel dataset on private manufacturing establishments in Egypt I find that the speed of adjustment of output is lower than unity in every period and slowly increases over time. When compared to the results from the static model, the dynamic model is found to produce higher estimates of technical efficiency on average, captures more variation in the time pattern of technical efficiency, and provides a different ranking of production units.
Median-based Rules for Decision Making under Complete Ignorance
(To be revised and resubmitted to Mathematical Social Sciences)
This paper characterizes a class of rules for decision-making when an agent knows the possible states of the world and the outcome of each of her actions for each state, but does not have any information about the probabilities with which each state occurs. The existing literature in this framework has mainly considered ‘max’-based or ‘min’-based rules and their variants that reflect rather extreme forms of optimism or pessimism on the part of an agent. In contrast, this paper focuses on the median outcome(s) and characterizes a class of decision-making rules that reflects a more ‘balanced’ attitude of the agent.
Abstracts of Research Papers in Progress
Effect of Elections on Government Expenditure in Elementary, Secondary, and Higher Education Sectors in India:
A Semiparametric Panel Data Analysis
This study focuses on political and non-political determinants of government expenditure in education in India. Motivated by the idea that elections can serve as disciplining devices that enable the electorate to extract greater effort from politicians in an election year, we analyze the impact of elections, controlling for other non-political variables, on the elementary, secondary, and higher education sector in India. We use semiparametric econometric techniques for panel data models using data from thirteen major Indian states over the period 1990-91 to 1998-99.
Nonparametric Random Effects Estimator:
A Panel Data Model with Time-varying Individual Effects
(With Deniz Baglan)
This paper extends a linear panel data model with time-varying individual effects to a nonparametric model in which the functional form of the relationship between the dependent and the independent variables is unspecified. We derive the kernel estimator for such a panel data model in the random effects framework and implement Monte Carlo simulations to investigate finite sample performances of our estimator. We also discuss possible applications of the estimator proposed in this paper.
Stochastic Frontier Models with Time-Varying Individual Effects: A Nonparametric Investigation
(With Deniz Baglan)
This paper extends a linear stochastic production frontier model with time-varying individual effects to a nonparametric model in which the functional form of the production frontier is unspecified. We derive the kernel estimator for such a frontier in fixed effects framework and implement Monte Carlo simulations to investigate finite sample performances of our estimator. Lastly, we apply the estimator proposed in this paper to estimate the production function and time-varying technical efficiency of private manufacturing establishments in Egypt over the period 1988 to 1996.
Technical Efficiency of the U.S. Food Manufacturing Industries and Influence of the Foreign Direct Investments:
A Stochastic Production Frontier Approach
This paper examines the technical efficiency of the U.S. food manufacturing industries using a panel data from the National Bureau of Economic Research (NBER) at the 3 digit industry level over the period from 1980 to 2005. The food manufacturing sector being one of the largest manufacturing sectors in the U.S., we estimate the time-varying technical efficiency and the internal ranking of the industries within this sector. Further, since the Foreign Direct Investments (FDI) are likely to foster growth and improvement in performance of these industries, we study the influence of the FDI in the U.S. on efficiency of these industries using data from the Bureau of Economic Analysis (BEA).