Privatization, Soft Budget Constraint, and Social Burdens: A Random-Effects Stochastic Frontier Analysis on Chinese Manufacturing Technical Efficiency

Traditional panel stochastic frontier studies on privatization of Chinese State-owned firms face a major challenge, namely, the endogeneity problem. The endogeneity problem is present because decision-making process of privatization in China is very likely influenced by some unobserved characteristics of a firm. In particular, better-performing SOEs are more likely to be chosen for privatization because the local governments may have incentives to attract private investors or to retain momentum for future reform. To deal with this challenge, this paper proposes a two-step stochastic frontier model. The first step addresses the endogeneity issue by estimating the probability of privatization with a random effects probit model. The second step estimation investigates the causes of Chinese manufacturing’s inefficiency with a random-effects stochastic frontier model. The estimation results suggest that privatization, hardening budget constraint and reducing firms’ social obligations have significantly contributed to the improvements of firms’ efficiency. However, no evidence is found that more autonomy for managers and lower debt asset ratio may help improve firms’ efficiency.Panel data, random effects, technical efficiency, stochastic frontier, privatization, soft-budget constraint, managerial incentives, social burdens

Parametric Estimation Of Technical And Scale Efficiencies In Italian Citrus Farming

Ray (1998) has proposed a model for estimating scale efficiency using a parametric approach. Following this methodology, a scale efficiency measure is obtained from the estimated parameters of the production frontier function and from the estimated scale elasticities. This study aims to estimate technical and scale efficiencies achieved by the Italian citrus fruit-growing farms. A stochastic frontier production model is considered in order to estimate technical and scale efficiencies. The analysis is expected to estimate the role of both technical and scale efficiencies in conditioning productivity. Particular attention is put on determining the (technical and scale) inefficiency effects associated with a set of structural and environmental variables that should affect efficiency and on the relationship between technical and scale efficiency scores. Empirical findings suggest that the greater portion of overall inefficiency in the sample might depend on producing below the production frontier than on operating under an inefficient scale. Indeed, room for improving technical efficiency is, on average, larger (29%) than the margin due to scale inefficiency (18.2%). Results also indicate a weak relationship between the two efficiency measures.Technical efficiency Scale efficiency Stochastic Frontier Analysis Citrus farming Italy

Spatial Competition and Cooperation Effects on European Airports' Efficiency

This paper is devoted to statistical analysis of spatial competition and cooperation between European airports. We propose a new multi-tier modification of spatial models, which allow estimating of spatial influence varying with the distance. Competition and cooperation effects don't diminish steadily with moving from a given airport, their structure is more complex. The suggested model is based on a set of distance tiers, with different possible effects inside each tier. We apply the proposed modification to the standard spatial stochastic frontier model and use it to estimation of competition and cooperation effects for European airport and airport's efficiency levels. We identify three tiers of spatial influence with different completion-cooperation ratio in each one. In the first, closest to an airport, tier we note significant advantage of cooperation effects over competition ones. In the second, more distant, tier we discover the opposite situation – significant advantage of completion effects. The last tier's airports doesn't influence significantly. In this paper we also consider some other possible applications of the proposed spatial multi-tier model.spatial stochastic frontier, airport efficiency, competition, cooperation

Estimation of a panel stochastic frontier model with unobserved common shocks

This paper develops panel stochastic frontier models with unobserved common correlated effects. The common correlated effects provide a way of modeling cross-sectional dependence and represent heterogeneous impacts on individuals resulting from unobserved common shocks. Traditional panel stochastic frontier models do not distinguish between common correlated effects and technical inefficiency. In this paper, we propose a modified maximum likelihood estimator (MLE) that does not require estimating unobserved common correlated effects. We show that the proposed method can control the common correlated effects and obtain consistent estimates of parameters and technical efficiency for the panel stochastic frontier model. Our Monte Carlo simulations show that the modified MLE has satisfactory finite sample properties under a significant degree of cross-sectional dependence for relatively small T. The proposed method is also illustrated in applications based on a cross country comparison of the efficiency of banking industries

Essays on Stochastic Frontier Models

This thesis consists of three independent chapters. The first chapter “Bayesian Inference in Dynamic Panel Stochastic Frontier Models” proposes a new stochastic frontier model which accounts for the intertemporal production behaviour. The conceptualization is based on the notion that firms face production adjustment costs in the short run due to the presence of quasi-fixed inputs. Consequently, this sluggish adjustment of the entire production process will create a dependency between the current and past production state. To capture this dynamic process, this chapter utilizes the traditional partial adjustment mechanism. The mechanism delivers a dynamic specification and allows factor inputs and inefficiency shocks to have an intertemporal effect on the production process. Moreover, the model allows heterogeneous adjustment speeds and input elasticities across the production units. Model inference is based on Bayesian MCMC techniques with data-augmentation. We illustrate the new model in an empirical application where we estimate the productivity and efficiency growth of the Egyptian private manufacturing sector during the early 90’s. In a similar vein, the second chapter, “Dynamic Panel Stochastic Frontier Models with Inefficiency Effects”, deals with dynamic panel frontier models where inefficiency effects can be a function of exogenous environmental variables. This chapter builds upon advancements in the field and utilizes parametric cumulative distribution functions to specify technical efficiency. The proposed model allows the presence of fixed effects and time-varying inefficiencies. Model estimation is based on the Generalized Method of Moments (GMM) approach, where various forms of input endogeneity can be effectively addressed. Last, the third chapter “A simple method for modelling the energy efficiency rebound effects with an application to energy demand frontiers” proposes a new simple method for estimating the energy inefficiency rebound effects. Model estimation is based on a two-stage approach. In the first stage, we argue in estimating a reduced form stochastic frontier model with country-specific inefficiency heteroscedastic effects. In the second stage, the energy efficiency rebound effects can be obtained effectively using moment-matching methods such as the GMM approach. We apply the proposed model on aggregate energy frontiers where we estimate the energy efficiency and the corresponding rebound effects for a balanced panel of OECD economies. The empirical results suggest an overall upward trend of energy efficiency scores. The energy rebound effects range from 28% to 92%, indicating that energy efficiency actions could have a limited impact on achieving environmental objectives

Economies of scale and efficiency measurement in Switzerland's Nursing homes

This paper examines the cost efficiency in the nursing home industry, an issue of concern to Swiss policy makers because of the explosive growth of national expenditure on elderly care and the aging of the population. A stochastic cost frontier model with a translog function has been applied to a balanced panel data of 1780 observations from 356 nursing homes operating over five years (1998-2002) in Switzerland. We compare the estimation results from different panel data econometric techniques focusing on the various methods of specification of unobserved heterogeneity across firms. In particular, the potential effects of such unobserved factors on the estimation results and their interpretation have been discussed. The paper eventually addresses three empirical issues: (1) the measurement of economies of scale in the nursing home sector, (2) the assessment of the economic performance of the firms by estimating their cost efficiency scores, and (3) the role of unobserved heterogeneity in the estimation process. The findings suggest that the economies of scale are an important potential source of cost reduction in a majority of Swiss nursing homes. Taking the size as given the efficiency performance of most individual units is practically very close to the estimated best practice. Nevertheless, the efficiency estimates suggest that some of the nursing homes can significantly reduce their costs by improving their operations.COST EFFICIENCY, ECONOMIES OF SCALE, NURSING HOMES, STOCHASTIC FRONTIER, PANEL DATA

Privatization, Soft Budget Constraint, and Social Burdens: A Random-Effects Stochastic Frontier Analysis on Chinese Manufacturing Technical Efficiency

Traditional panel stochastic frontier studies on privatization of Chinese State-owned firms face a major challenge, namely, the endogeneity problem. The endogeneity problem is present because decision-making process of privatization in China is very likely influenced by some unobserved characteristics of a firm. In particular, better-performing SOEs are more likely to be chosen for privatization because the local governments may have incentives to attract private investors or to retain momentum for future reform. To deal with this challenge, this paper proposes a two-step stochastic frontier model. The first step addresses the endogeneity issue by estimating the probability of privatization with a random effects probit model. The second step estimation investigates the causes of Chinese manufacturing’s inefficiency with a random-effects stochastic frontier model. The estimation results suggest that privatization, hardening budget constraint and reducing firms’ social obligations have significantly contributed to the improvements of firms’ efficiency. However, no evidence is found that more autonomy for managers and lower debt asset ratio may help improve firms’ efficiency

Parametric Estimation Of Technical And Scale Efficiencies In Italian Citrus Farming

Ray (1998) has proposed a model for estimating scale efficiency using a parametric approach. Following this methodology, a scale efficiency measure is obtained from the estimated parameters of the production frontier function and from the estimated scale elasticities. This study aims to estimate technical and scale efficiencies achieved by the Italian citrus fruit-growing farms. A stochastic frontier production model is considered in order to estimate technical and scale efficiencies. The analysis is expected to estimate the role of both technical and scale efficiencies in conditioning productivity. Particular attention is put on determining the (technical and scale) inefficiency effects associated with a set of structural and environmental variables that should affect efficiency and on the relationship between technical and scale efficiency scores. Empirical findings suggest that the greater portion of overall inefficiency in the sample might depend on producing below the production frontier than on operating under an inefficient scale. Indeed, room for improving technical efficiency is, on average, larger (29%) than the margin due to scale inefficiency (18.2%). Results also indicate a weak relationship between the two efficiency measures

Profit Efficiency of Groundnut Production: Evidence from Eastern Province of Zambia

The study analysed profit efficiency and its determinants in smallholder groundnut production in the context of profit maximization as an incentive for optimum production in Eastern Province of Zambia. The stochastic frontier approach with the application of the flexible translog profit function and inefficiency model was used in estimating the profit efficiency. Secondary data for the 2012 Rural Agricultural Livelihoods Survey from Central Statistical Office of Zambia, which used a multi-stage sampling method, was utilized. Cross sectional data for 1,232 farm households was used in this analysis. Results showed existence of high level of inefficiency in groundnut farming because the gamma ratio (γ = 0.6445) was comparatively large. Seed price and value of fixed capital are key variables highly significant in the profit function. The result further revealed that the profit efficiencies of the farmers varied widely between 9.5% and 92.38%. The groundnut farmers were able to realize 72.5% of their frontier profit on the average suggesting that an estimated 27.5% of the profit is lost due to a combination of technical and allocative inefficiencies. Education level, credit access, land tenure, distance to market, storage facility and weeding were significant factors found to influence profit efficiency. Technologies that enhance fixed capital, improving availability and access to improved seed varieties and credit, and land reform measures aimed at promoting titled land ownership are required to achieve significant positive effects on profit efficiency. Also, policy measures that will improve weed control mechanisms, reduce transportation cost and encourage education advancement and ownership of proper storage facilities among smallholder farmers are advocated. Keywords: Groundnut, Profit Efficiency, Stochastic Frontier, Zambi

Comparing efficiency of health systems across industrialized countries: a panel analysis.

BackgroundRankings from the World Health Organization (WHO) place the US health care system as one of the least efficient among Organization for Economic Cooperation and Development (OECD) countries. Researchers have questioned this, noting simplistic or inappropriate methodologies, poor measurement choice, and poor control variables. Our objective is to re-visit this question by using newer modeling techniques and a large panel of OECD data.MethodsWe primarily use the OECD Health Data for 25 OECD countries. We compare results from stochastic frontier analysis (SFA) and fixed effects models. We estimate total life expectancy as well as life expectancy at age 60. We explore a combination of control variables reflecting health care resources, health behaviors, and economic and environmental factors.ResultsThe US never ranks higher than fifth out of all 36 models, but is also never the very last ranked country though it was close in several models. The SFA estimation approach produces the most consistent lead country, but the remaining countries did not maintain a steady rank.DiscussionOur study sheds light on the fragility of health system rankings by using a large panel and applying the latest efficiency modeling techniques. The rankings are not robust to different statistical approaches, nor to variable inclusion decisions.ConclusionsFuture international comparisons should employ a range of methodologies to generate a more nuanced portrait of health care system efficiency