Public and Private Capital Productivity Puzzle: A Nonparametric Approach

Is public expenditure productive? Is there a shortfall or excess in public capital investment? We address these old issues in the light of new econometric tools. It is argued that the Cobb-Douglas specification that ignores nonlinearity inherent in the functional relationship of the production technology causes incorrect estimates of input elasticities. To avoid possible model misspecification, we use Li-Racine generalized kernel estimation. This procedure is used to estimate the returns to private capital, employment, and public capital in gross state product from a panel of 48 states for 17 years. In contrast to previous studies, we find that the return to public capital is positive and significantly different from zero.     

Stochastic error specification in primal and dual production systems

In this paper we derive both primal and dual‐cost systems in which the stochastic specifications arise from the model (random environment or measurement errors and optimization errors)—not tacked on at the end after the deterministic system is worked out. Derivation of the error structures is based on cost‐minimizing behavior on the firms. The primal systems constitute the production function and the first‐order conditions of cost minimization. We consider two dual‐cost systems. The first dual system is based on the cost function and cost share equations. The second dual system is based on a multiplicative general error production model that is an alternative to McElroy's additive general error production model. Our multiplicative general error model gives a clear and intuitive economic meaning to the error components. The resulting cost system is easy to estimate compared to the alternative cost systems. The error components in the multiplicative general error model can capture heterogeneity in the technology parameters even in a cross‐sectional model. Panel data are not necessary to estimate either the primal or dual systems. The models are estimated using data on 72 fossil fuel‐fired steam electric power generation plants (observed for the period 1986–1999) in the USA. Copyright © 2009 John Wiley & Sons, Ltd.     

Is the post-reform growth of the Indian manufacturing sector efficiency driven? Empirical evidence from plant-level data

It is generally believed that the structural reforms that were introduced in India following the macro-economic crisis of 1991 ushered in competition and forced companies to become more efficient. However, whether the post-1991 growth is an outcome of more efficient use of resources or greater use of factor inputs remains an open empirical question. In this paper, we use plant-level data from 1989–1990 and 2000–2001 to address this question. Our results indicate that while there was an increase in the productivity of factor inputs during the 1990s, most of the growth in value added is explained by growth in the use of factor inputs. We also find that median technical efficiency declined in all but one of the industries between 1989–1990 and 2000–2001, and that change in technical efficiency explains a very small proportion of the change in gross value added.     

中国制造业增长方式和结构变迁的再检验——基于行业和时期异质性的半参数平滑系数模型

本文采用了基于充分灵活的生产函数形式的半参数平滑系数模型（SPSCM），对1999-2008年中国制造业的要素产出弹性、全要素生产率以及生产率主要影响因子的作用进行了估计和测算。主要研究结论包括：研究期内制造业全要素生产率年均增长141%， 显示中国制造业进入集约增长模式。在2002-2003年期间，中国制造业结构发生较大变化。伴随劳动密集型产业和产业环节快速扩张，资本产出弹性大幅下降，劳动力产出弹性攀升。企业规模和技术进步对生产率都有显著的积极影响，自主研发对生产率的影响在时间和行业之间具有广泛的异质性，但2004年以后出现了趋同的积极影响。     

Heterogeneity of technological regimes and banking efficiency in former socialist economies

Cost efficiency of banks in 20 former socialist emerging economies is analyzed using a latent class stochastic efficiency frontier model that explicitly accounts for unobserved differences in technological regimes due to the heterogeneity of economic environments in which the banks are operating. We find that banking systems in former socialist emerging economies are characterized by three distinct technological regimes. Based on the estimated efficiency scores we group the countries into three categories and provide an intuitive interpretation of these three regimes.     

A stochastic frontier approach to modelling financial constraints in firms: An application to India

We propose the use of stochastic frontier approach to modelling financial constraints of firms. The main advantage of the stochastic frontier approach over the stylised approaches that use pooled OLS or fixed effects panel regression models is that we can not only decide whether or not the average firm is financially constrained, but also estimate a measure of the degree of the constraint for each firm and for each time period, and also the marginal impact of firm characteristics on this measure. We then apply the stochastic frontier approach to a panel of Indian manufacturing firms, for the 1997–2006 period. In our application, we highlight and discuss the aforementioned advantages, while also demonstrating that the stochastic frontier approach generates regression estimates that are consistent with the stylised intuition found in the literature on financial constraint and the wider literature on the Indian credit/capital market.     

A hedonic-output-index-based approach to modeling polluting technologies

Despite some recent criticisms, the conventional radial distance function, which treats undesirable by-products as either frontier shifters or inputs, remains a popular go-to formulation of polluting production processes among practitioners. This unfading popularity is arguably driven by the ability of radial distance functions, unlike alternative directional distance functions, to allow for unit-free multiplicative changes in arguments as well as, by implicitly postulating the radial direction, to free researchers from the dilemma of having to explicitly choose the directional vector. In this paper, we offer a generalization of the standard radial distance function to polluting technologies that can accommodate undesirable by-products in a more economically meaningful way. Specifically, we propose modeling undesirable outputs via a hedonic output index, which is meant to ensure that pollutants are treated as outputs, as opposed to inputs or theoretically unregulated frontier shifters, while also recognizing their undesirable nature. By using a radial input distance function generalized to encompass an (unobservable) hedonic output index of desirable and undesirable outputs, we are able to meaningfully describe relationships between different products (including the complementarity of desirable and undesirable outputs) within producible output sets as well as to represent technically feasible polluting production possibilities given inputs. An empirical application of our methodology to the case of Dutch dairy farms in 2001–2009 demonstrates the complexity of interactions between outputs, thereby attesting to the value of more elaborate representations of production possibilities.     

A dynamic profit function with adjustment costs for outputs

It is well known that there are adjustment costs associated with many input factors, which delays firms response to changes in relative prices. Although adjustment costs are implicitly acknowledged when a cost rather than profit function is used, little attention has been given to adjustment costs for outputs. However, in many cases there will also be adjustment costs associated with changes in the product mix for multioutput firms. In this paper we formulate a firm’s optimization problem in a profit maximizing set up that allows adjustment costs for all netputs from which it follows that adjustment cost for some factors affect the adjustment of both inputs and outputs. We also show that one can test whether a factor is quasi-fixed or fully fixed.      

DEA, DFA and SFA: A comparison

The nonparametric data envelopment analysis (DEA) model has become increasingly popular in the analysis of productive efficiency, and the number of empirical applications is now very large. Recent theoretical and mathematical research has also contributed to a deeper understanding of the seemingly simple but inherently complex DEA model. Less effort has, however, been directed toward comparisons between DEA and other competing efficiency analysis models. This paper undertakes a comparison of the DEA, the deterministic parametric (DFA), and the stochastic frontier (SFA) models. Efficiency comparisons across models in the above categories are done based on 15 Colombian cement plants observed during 1968–1988.     

Do we estimate an input or an output distance function? An application of the mixture approach to European railways

In this paper, we estimate parametric input and output distance functions and discuss how to estimate a mixture/latent class model (LCM) involving the output and input distance functions in the context of multi-input and multi-output production technology. The proposed technique is applied to a panel data on European Railways (1971–1994). This model allows us to identify determinants of the efficiency orientation, thereby providing useful information that can help researchers to choose between the input and the output-oriented approaches. In addition, we develop cross-indices that can be used to compute input (output) technical inefficiency from the estimates of output (input) distance function.