We investigate conditions sufficient for identification of average treatment effects using instrumental variables. First we show that the existence of valid instruments is not sufficient to identify any meaningful average treatment effect. We then establish that the combination of an instrument and a condition on the relation between the instrument and the participation status is sufficient for identification of a local average treatment effect for those who can be induced to change their participation status by changing the value of the instrument. Finally we derive the probability limit of the standard IV estimator under these conditions. It is seen to be a weighted average of local average treatment effects.

Evolution and Rationality Some Recent Game-Theoretic Results. Identification and Estimation of Local Average Treatment Effects

http://people.stern.nyu.edu/wgreene/FrontierModeling/Reference-Papers/Greene-JE2005-Heterogeneity.pdf

Reconsidering heterogeneity in panel data estimators of the stochastic frontier model

This paper uses the concept of a metafrontier to compare the technical efficiencies of firms that may be classified into different groups. The paper presents the basic analytical framework necessary for the definition of a metafrontier, shows how a metafrontier can be estimated using non-parametric and parametric methods, and presents an empirical application using cross-country agricultural sector data. The paper also explores the issues of technological change, time-varying technical inefficiency, multiple outputs, different efficiency orientations, and firm heterogeneity.

/pdf/metafrontier-frameworks-for-the-study-of-firm-level-59ca3drmoy.pdf

Metafrontier frameworks for the study of firm-level efficiencies and technology ratios

The Econometrics of Panel DataSpringer Handbook of Science and Technology IndicatorsPanel Data EconometricsThe Econometrics of Panel DataA Practitioner's Guide to Stochastic Frontier Analysis Using StataBenchmarking for Performance EvaluationEssays on Microeconomics and Industrial OrganisationHealth System EfficiencyInternational Journal of Production EconomicsEconometric Analysis of Model Selection and Model TestingInternational Applications of Productivity and Efficiency AnalysisAdvanced Robust and Nonparametric Methods in Efficiency AnalysisEconometrics and the Philosophy of EconomicsThe Measurement of Productive EfficiencyMeasuring Efficiency in Health CareFinancial, Macro and Micro Econometrics Using REconometric Analysis of Cross Section and Panel DataApplied EconometricsProductivity and Efficiency AnalysisEconometric Model SelectionProductivity and Efficiency AnalysisStochastic Frontier AnalysisThe Oxford Handbook of Health EconomicsThe Measurement of Productive Efficiency and Productivity GrowthNew Directions in Productivity Measurement and Efficiency AnalysisA Primer on Efficiency Measurement for Utilities and Transport RegulatorsPanel Data EconometricsProduction and Efficiency Analysis with RApplications of Modern Production TheoryThe Measurement of Productive EfficiencyNonparametric Econometric Methods and ApplicationAn Introduction to Efficiency and Productivity AnalysisHealth, the Medical Profession, and RegulationThe Analysis of Household SurveysData Envelopment AnalysisProgramming Collective IntelligenceEfficiency AnalysisProductivity and Efficiency AnalysisMeasurement of Productivity and EfficiencyProduction Frontiers

The Econometric Approach to Efficiency Analysis

A DEA-based stochastic frontier estimation framework is presented to evaluate contextual variables affecting productivity that allows for both one-sided inefficiency deviations as well as two-sided random noise. Conditions are identified under which a two-stage procedure consisting of DEA followed by ordinary least squares (OLS) regression analysis yields consistent estimators of the impact of contextual variables. Conditions are also identified under which DEA in the first stage followed by maximum likelihood estimation (MLE) in the second stage yields consistent estimators of the impact of contextual variables. This requires the contextual variables to be independent of the input variables, but the contextual variables may be correlated with each other. Monte Carlo simulations are carried out to compare the performance of our two-stage approach with one-stage and two-stage parametric approaches. Simulation results indicate that DEA-based procedures with OLS, maximum likelihood, or even Tobit estimation in the second stage perform as well as the best of the parametric methods in the estimation of the impact of contextual variables on productivity. Simulation results also indicate that DEA-based procedures perform better than parametric methods in the estimation of individual decision-making unit (DMU) productivity. Overall, the results establish DEA as a nonparametric stochastic frontier estimation (SFE) methodology.

Evaluating Contextual Variables Affecting Productivity Using Data Envelopment Analysis

How do firms smooth production when facing financing uncertainty? By using a model incorporating financing constraints, this paper shows that firms may adjust capacity utilization rates to buffer against financing disturbances. In particular, it emphasizes that variable capacity utilization plays the roles of both inter- and intra-temporal substitution of capital in this context. The paper presents results from the comparative statics and numerical calibrations of the model. These results show that the implied short-run dynamics are consistent with business cycle phenomena. The results also indicate that the long-run average of the capital stock is not likely to be affected by financing uncertainty, so that stabilization policy in the banking sector may only have a second-order welfare gain.

Production Smoothing When Bank Loan Supply Shifts: The Role of Variable Capacity Utilization

Government policies are frequently used to promote productivity. Some policies are designed to enhance production technology, while others are meant to improve production efficiency. An important i...

A Stochastic Frontier Model with Endogenous Treatment Status and Mediator

In this paper, we discuss the specification and estimation of technical efficiency in a variety of stochastic frontier production models. The focus is on cross-sectional models. We start from the basic neoclassical production theory and introduce technical inefficiency in there. Various model specifications with several distributional assumptions on the inefficiency component are explored in detail. Theoretical and empirical issues are illustrated with empirical examples using STATA.

Estimation of Technical Inefficiency in Production Frontier Models Using Cross-Sectional Data

We propose a method of moment estimator for a stochastic frontier model in which one of the independent variables is measured with errors. The estimator corrects for the measurement errors, and it requires only minimal assumption on the error distribution, has no need for additional data, and is computationally inexpensive. A Monte Carlo study shows favorable statistical properties of this estimator. We apply this estimator to an investment model with financing constraint, where a major explanatory variable, Tobin's Q, is known to prone to measurement problems. We find that the Q's explanatory powers increase substantially upon correcting for the measurement errors.

A Method of Moments Estimator for a Stochastic Frontier Model with Errors in Variables

We investigate government-subsidised credit effects on participating financial institutions’ performance in terms of cost efficiency. Using farmers’ credit unions in Taiwan as an example, we find that credit unions’ cost inefficiency is positively correlated with the extent of involvement in subsidy programmes. The results are robust to the control of local competition and labour quality. In addition to the stochastic frontier models from which we obtain the main results, we also propose a new distribution-free estimation method based on quantile regressions. Results of this study point out that, when evaluating the social costs of the credit programmes, it is important to take into account the efficiency loss generated among financial intermediaries by credit subsidy programmes.

Hung-Jen Wang

Papers

Production Smoothing When Bank Loan Supply Shifts: The Role of Variable Capacity Utilization

A Stochastic Frontier Model with Endogenous Treatment Status and Mediator

Estimation of Technical Inefficiency in Production Frontier Models Using Cross-Sectional Data

A Method of Moments Estimator for a Stochastic Frontier Model with Errors in Variables

The Cost Effects of Government‐Subsidised Credit: Evidence from Farmers’ Credit Unions in Taiwan