Bus transit technical efficiency using latent class stochastic indirect production frontier

Using an Indirect Production Frontier (IPF), this article examines technical inefficiency within a latent class framework while simultaneously accounting for allocative distortions from operating and capital subsidies. It identifies two latent classes of US public transit systems, one characterized by economies of scale with 16.61% technical inefficiency and the other by diseconomies of scale with 14.16% technical inefficiency. It decomposes technical inefficiency among some of its sources and finds that the incentive tier of federal operating subsidies, regulations regarding years of vehicle use, subsidy-induced allocative distortion from labour overuse relative to capital negatively influence technical inefficiency in all transit systems. For the Latent Class 1 transit systems, the sources of lower technical inefficiency are operating speed, purchased transportation and years-of-vehicle-use regulation. For the Latent Class 2 transit systems, these sources are subsidy-induced capital-labour allocative distortion and the incentive tier component of the federal formula grant.     

Endogeneity in panel stochastic frontier models: an application to the Japanese cotton spinning industry

We present a panel stochastic frontier model that handles the endogeneity problem. This model can treat the endogeneity of both frontier and inefficiency variables. We apply our method to examine the technical efficiency of Japanese cotton spinning industry. Our results indicate that market concentration is endogenous, and when its endogeneity is properly handled, it has a larger negative impact on the technical efficiency of cotton spinning plants. We find that the exogenous model substantially overestimates efficiency in concentrated markets.     

Pseudolikelihood estimation of the stochastic frontier model

Stochastic frontier analysis is a popular tool to assess firm performance. Almost universally it has been applied using maximum likelihood (ML) estimation. An alternative approach, pseudolikelihood (PL) estimation, which decouples estimation of the error component structure and the production frontier, has been adopted in both the non-parametric and panel data settings. To date, no formal comparison has yet to be conducted comparing these methods in a standard, parametric cross-sectional framework. We produce a comparison of these two competing methods using Monte Carlo simulations. Our results indicate that PL estimation enjoys almost identical performance to ML estimation across a range of scenarios and performance metrics, and for certain metrics, outperforms ML estimation when the distribution of inefficiency is incorrectly specified.     

An explanation of the changes in the proportion of temporary workers in Spain

In this paper a theoretical model is developed to identify the main determinants of the proportion of temporary workers at firms. The outcomes show that the proportion of temporary workers has a counter-cyclical behaviour: it grows during the slump period up to 1995 and falls during the subsequent recovery. However, given the effect of the general economic cycle, firms that raise their sales or improve their market dynamism index tend to increase their proportion of temporary workers. This proportion also rises when the average labour cost decreases, firm size increases, and the knowledge capital stock diminishes.     

A performance assessment of Mozambique banks: a Bayesian stochastic frontier

This article analyses the technical efficiency of Mozambican banks from 2005 to 2014 with a Bayesian stochastic frontier model. The intermediate approach is adopted and the results reveal that efficiency varies amongst the banks analysed. Foreign ownership of Mozambican banks is also analysed, as is public ownership, the role of mergers and acquisitions, big banks and active dividend policy within the context of bank costs. Policy implications are then derived.     

Estimating a mixture of stochastic frontier regression models via the em algorithm: A multiproduct cost function application

Researchers have become increasingly interested in estimating mixtures of stochastic frontiers. Mester (1993), Caudill (1993), and Polachek and Yoon (1987), for example, estimate stochastic frontier models for different regimes, assuming sample separation information is given. Building on earlier work by Lee and Porter (1984), Douglas, Conway, and Ferrier (1995) estimate a stochastic frontier switching regression model in the presence of noisy sample separation information. The purpose of this paper is to extend earlier work by estimating a mixture of stochastic frontiers assuming no sample separation information. This case is more likely to occur in practice than even noisy sample separation information. In order to estimate a mixture of stochastic frontiers with no sample separation information, an EM algorithm to obtain maximum likelihood estimates is developed. The algorithm is used to estimate a mixture of stochastic (cost) frontiers using data on U.S. savings and loans for the years 1986, 1987, and 1988. Statistical evidence is found supporting the existence of a mixture of stochastic frontiers. First version received: 3/13/01/Final version received: 6/17/02 RID="*" ID="*"  I am grateful to Ram Acharya, Janice Caudill, and especially James R. Barth for several helpful comments on an earlier version of the paper. During the revision process I benefitted greatly from the suggestions of the Associate Editor and three anonymous referees.     

Efficiency measurement of the English football Premier League with a random frontier model

Using the random stochastic frontier model, this paper examines the technical efficiency of the English football Premier League from 1998/99 to 2003/04. The model disentangles homogenous and heterogeneous variables in the cost function, which leads us to advise the implementation of common policies as well as policies by clusters.     

The impact of incentive regulation on productivity in the US telecommunications industry: A stochastic frontier approach

This paper investigates whether the substitution of price cap regulation (PCR) and other forms of incentive regulation for traditional rate of return regulation (RRR) has had a measurable effect on productivity growth in the US telecommunications industry. A stochastic frontier approach is employed to compute the efficiency change, technological progress, and productivity growth for 25 LECs over the 1988-1998 time periods. By examining the relationship between the change in productivity growth and regulatory regime variables and other control variables, we find that PCR has a significant and positive effect, both in contemporaneous and lagged specifications.     

Valuing improvements in urban water security: evidence of heterogeneity derived from a latent class model for eastern Australia

In many Australian cities the response to drought has included the imposition of mandatory constraints over how water is used by households, often termed ‘water restrictions’. A similar rationing approach has been witnessed in California’s recent drought. The aim of water restrictions is to slow the depletion of water storage but restrictions have also been criticized for the costs they impose on specific water users. In order to gain insight into the potential magnitude of the cost of water restrictions, this study uses a choice experiment to investigate the non-market values for specific attributes associated with the outcomes of drought restrictions. This information was sought to understand the community’s willingness to pay for attributes related to the extent, frequency and duration of water restrictions. The article reports a latent class choice model for a major city in eastern Australia and investigates heterogeneity in preferences towards increasing water availability during drought. This study departs from the existing literature by conducting the choice experiment in a context where water supply is relatively abundant. This unique framing of the choice experiment allows for a useful comparison with existing studies and also raises challenges about the interpretation of the data for planning purposes.     

The transient and persistent efficiency of Italian and German universities: a stochastic frontier analysis

Despite measures on the European level to increase the compatibility between the higher education sectors, the recent literature exposes variations in their efficiencies. To gain insights into these differences, we split the efficiency term according to the two management levels each university is confronted with. We separate short-term and long-term efficiency while controlling for unobserved institution-specific heterogeneity. We argue that the first term reflects the efficiency of the individual universities working within the country, while the second term echoes the influence of the overall country-specific higher education structure. The cross-country comparison displays whether efficiency differences between countries are related to the individual performance of their universities or their higher education structure. This allows more purposeful policy recommendations and expands the literature regarding the efficiency of universities in a fundamental way. Choosing Italy and Germany as two important illustrative examples, we show that the Italian higher education sector exhibits a higher overall efficiency value. With the individual universities working at the upper bound of efficiency in both countries, the remaining inefficiency and the gap between the countries are caused by persistent, structural inefficiency. Future measures should hence aim at the country-specific structure and not solely at the activities of single universities.     

Patterns of poverty among elderly Americans: a latent class Markov model

This article studies poverty persistence and the role of social security programmes on poverty among elderly in the US. We use a Latent Markov model to disentangle unobserved heterogeneity and state dependence. Because of its dynamic nature, unobserved heterogeneity is modelled to vary over time. This allows to capture different latent states of poverty that change over time. Result indicates the existence of three unobserved types evolving over time according to their propensity to be poor. Moreover, a strong persistence in poverty especially for women, individuals living alone and ethnic minorities is found. Finally, the estimates indicate that giving social assistance tends to reduce poverty.     

FDI performance: a stochastic frontier analysis of location and variance determinants

The opening up process of the eastern European countries was marked by greater integration of FDI with their western neighbouring countries. Using the single-step ML approach to stochastic frontier analysis, the location and variance determinants of FDI are estimated using the knowledge capital (KK) model framework. The findings, based on a panel of bilateral FDI stocks from 10 western to 10 eastern European countries over the 1996–2007 period, suggest FDI is determined by both horizontal and vertical motives while the process of liberalization and infrastructural developments significantly reduces the variance of FDI. In using a stochastic frontier specification of the KK model, the efficiency of FDI performance is identified relative to maximum levels. The bilateral efficiency scores suggest a mixed performance, indicating scope to improve the efficiency of FDI.     

Measuring China's innovative capacity: a stochastic frontier exercise

We adopt a stochastic frontier analysis of innovative activity to disentangle countries’ patenting capacity from patenting efficiency. We analyse the determinants of innovative capacity of a set of 26 OECD countries plus China, over the period 1992–2007, to show if and how China's technological activity is growing faster than commonly held as compared to the most innovative countries of the world. Our results highlight that both internal and external elements jointly contribute to enhance countries’ innovative capacity and efficiency. In particular, while government-funded R&D is more important for innovative capacity, privately funded R&D as well as foreign direct investments (FDIs) affects technical efficiency (TE). Moreover, as for the whole set of countries, FDIs seem to exert a resource-seeking role (as they negatively affect TE), this does not happen for China, where FDIs exert a positive effect. Results are robust to the use of alternative measures of innovative inputs (such as higher education expenditure in R&D and R&D personnel, but also FDI flows rather than stocks). Finally, human capital measures are generally not very effective in enhancing patenting efficiency, apart from tertiary education.     

A latent class model for obesity

We extend the discrete data latent class literature by explicitly defining a latent variable for class membership as a function of both observables and unobservables, thereby allowing the equations defining the class membership and observed outcomes to be correlated. The procedure is then applied to modelling observed obesity outcomes, based upon an underlying ordered probit equation.     

Food environment and weight outcomes: a stochastic frontier approach

Food environment includes supermarkets, restaurants, warehouse clubs and supercentres and other food outlets. As such, it can affect weight outcomes through healthy food-access cost and availability, which in turn shape eating styles and habits. This article evaluates the impact of food environment on weight outcomes through a stochastic frontier approach (SFA) that comprehensively includes various components of the food environment. The model is estimated using body mass indexes (BMIs) as the dependent variable and demographics and food environment data from New England counties as explanatory variables. Empirical results indicate that supercentres and limited service restaurants are positively associated with weight gain, while full service restaurants are negatively associated with BMIs. In metropolitan counties, the presence of full and limited service restaurants has a significant impact on BMIs; in non-metropolitan counties, these establishments do not, except in those adjacent to metropolitan areas. Empirical results also validate SFA is a more appropriate specification than the standard linear model. In addition, SFA allows us to rank counties and identify targets for effective policy interventions. An ordered logit model of weight status is estimated with the same explanatory variables, confirming that the directions of the effects of the food environment components are similar.     

Estimation of technical inefficiency effects using panel data and doubly heteroscedastic stochastic production frontiers

In previous studies, measures of technical inefficiency effects derived from stochastic production frontiers have been estimated from residuals which are sensitive to specification errors. This study corrects for this inaccuracy by extending the doubly heteroscedastic stochastic cost frontier suggested by Hadri (1999) to the model for technical inefficiency effects. This model is a stochastic frontier production function for panel data as proposed by Battese and Coelli (1995). The study uses, for illustration of the techniques, data on 101 mainly cereal farms in England. We find that the correction for heteroscedasticity is supported by the data. Both point estimates and confidence intervals for technical efficiencies are provided. The confidence intervals are constructed by extending the “Battese-Coelli” method reported by Horrace and Schmidt (1996) by allowing the technical inefficiency to be time varying and the disturbance terms to be heteroscedastic. The confidence intervals reveal the precision of technical efficiency estimates and show the deficiencies of making inferences based exclusively on point estimates. First version received: March 2000/Final version received: Oct. 2001 RID="*" ID="*"  The authors are grateful to the Economic and Social Research Council for access to their Data Archive which has provided the data for this research. We are indebted to Badi Baltagi and two anonymous referees for their helpful comments and suggestions. The usual caveat applies.     

Efficiency and Equity in School Funding: A Case Study for Kansas

This study measures cost inefficiency of Kansas public school districts and applied both mathematical programming and stochastic frontier approach. The empirical study uses two-stage data envelopment analysis model and the cost inefficiency effects model proposed by Battese and Coelli (Empirical Economics 24:325–332, 1995) and applied to a panel data. The results found mean inefficiencies from these two models are very close. The results indicate that Kansas school districts, on average, exhibit cost inefficiency in their operations, however, there is a tendency for inefficiencies to decline over time. The study does not find any strong evidence for lower efficiency due to lower expenditure per-pupil. Instead, we found inconclusive evidences where lower efficiency for certain school districts could be assigned to unfavorable environmental cost conditions.

Quantile estimation of frontier production function

The purpose of the paper is to provide new information on the performance of frontier estimation methods, using data from Italian hotel industry. Quantile regression is also suggested as solution to frontier production function estimation. It is shown that, while the choice of estimation methods among conventional techniques significantly affects the economic analysis, quantile regression provides valuable new information by estimating the whole spectrum of production functions corresponding to different efficiency levels. In addition, the method makes available a coherent framework to analyze the performance of the conventional techiniques. Jel classification: C14, C16, D24We would like to thank the Co-Editor, the Associate Editor and an anonymous referee for comments and suggestions. The research was supported by the University Research Council and the National Research Council. The usual disclaimer applies.The estimates were computed using the Roger Koenker and StatLibS-Plus routine of quantile regression and the Tim Coelli and CEPA Web site FRONTIER 4.1 Program. The data set is provided by the Ho.Re.Ca. survey conducted by ISTAT in 1992.First version received: June 2001/Final version received: December 2002     

Credits and non-interest rate determinants of loan demand: a Spanish case study

This article uses bivariate probit analysis to model the potential relationship between the condition of being credit-unconstrained and holding loans as well as to ascertain determinants of a household being credit-unconstrained and likely holding consumer and real-estate loans. It documents that family size, education, permanent and transitory incomes, among others, affect Spanish households’ desire and capacity to hold loans. Furthermore, these factors were found to affect demands for real-estate and consumer loans differently. In general, the above and other results from this research provide insights that would interest credit consumers, credit suppliers, and policy makers in Spain.