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A Parametric Distance Function Approach for Malmquist ProductivityIndex Estimation
... We employ translog multi-input multi-output specification to estimate the productivity index (and its components of technological change and efficiency change) following Fuentes et al. (2001). ...
... 8 In the productivity analysis literature, the Stochastic Frontier Analysis (SFA) is preferred to Data Envelopment Analysis (DEA) when either random error needs to be considered or production is subject to uncontrollable factors including uncertainties in the prices of input and output, and other market situations. Recent development of the DEA, however, incorporates stochastic characteristics of the production frontier in the DEA framework (or distance function estimation) and we utilize this advantage following Fuentes et al. (2001). ...
... We adopt the following translog function to estimate a parametric distance function for the transformation function corresponding to a multi-output/multi-input technology with technological progress defined in the usual form as a trend variable following Grosskopf et al (1997) and Fuentes et al. (2001): ...
China's economic growth has been extremely rapid in the past two decades, with an annual growth rate of about 10% in the last two decades. Subsequently, environmental problems are threatening China's sustainable future. Pollution damage is estimated to be around $54 billion annually and closed to 8 % of Chinese GDP. Policy makers in China are facing the tradeoffs between economic growth and environmental protection. Growth of total factor productivity plays an important role in GDP growth in Chin. The costs of alternative production and pollution abatement technologies, which are influenced by TFP, are important determinants of the environmental compliance cost. Thus, it is important to understand the interaction between environmental regulation and technological/productivity change. In the long run, the most important single criterion on which to judge environmental policies might be the extent to which they spur new technology toward the efficient conservation of environmental quality. Most of the empirical studies in the literature, however, are focused on the analysis in developed countries, especially in US. To our knowledge, there are no existing studies that have estimated the efficiency of environmental technology and management, systematically analyzed its determinants, and assessed empirically the impact of environmental regulations on productivity in China. We employ economic techniques and find that efficiency in Chinese environmental management is deteriorating. Our results show that Chinese environmental efficiency (or productivity) is decreasing while market productivity is improving. Main determinant of market productivity change is R&D while main determinant of environmental productivity is pollution abatement expenditure instead of pollution tax.
... For this purpose, we use a translog multi-input, multi-output, specification to estimate a Malmquist productivity index, applying parametric-stochastic frontier approaches (Fuentes et al., 2001) and deriving an environmental productivity index (Kaneko and Managi, 2004;Managi and Karemera, 2005). In this analysis, we exploit the econometric approach (in the second step of the procedure) to understand the determinants of environmental productivity in greater depth. ...
... To estimate a parametric distance function, the translog function is chosen (as opposed to the Cobb-Douglas function, for example, which is more restrictive) because, among other advantages, it offers flexibility, is easy to derive and permits the imposition of homogeneity Grosskopf et al., 1997). Following Grosskopf et al. (1997) and Fuentes et al. (2001), the translog function to estimate a parametric distance function corresponds to a multioutput/multi-input technology with technological progress defined in the usual way as a trend variable. This function for firm i ...
... where h is a vector of estimated parameters (a, b, d, c, g, l). Following Lovell et al. (1994) and Fuentes et al. (2001), we obtain the following stochastic frontier model by choosing one of the outputs arbitrarily (e.g. ...
The paper analyses the productivity of marketing cooperatives incorporating environmental inputs/outputs. In the European agriculture, expectations for attaining sustainable and competitive agriculture rely to a great extent on the cooperative sector's ability to adapt to new market conditions. These challenges have led marketing cooperatives in the fruit and vegetables sector to consider improvements in productivity and sound environmental performance. The study analyses the total factor productivity related to environmental variables in this sector using a parametric-stochastic approach and panel data on Spanish cooperatives over the period 1994-2002. Additionally, the determinants of environmental productivity are examined econometrically. The estimates obtained show an increase in efficiency for the period under study and a relationship between productivity changes and management factors, such as labour quality, capital intensity and environmental spillover. Copyright 2006 Blackwell Publishing Ltd.
... Ferrier and Porter, 1991;Kondo and Yamamoto, 2002) considering different aspects of TFP and its components in terms of efficiency and technology, but without taking into account aspects related to environmental factors. We use a translog multi-input multi-output specification to estimate the Malmquist productivity index applying parametricstochastic frontier approaches (Fuentes et al., 2001) and deriving a productivity environmental index (Kaneko and Managi, 2004;Managi and Karemera, 2005). We also analyze the determinants of productivity environmental changes and highlight the main conclusions and policy implications. ...
... In order to estimate a parametric distance function, the translog function is chosen because, among other advantages, it offers flexibility, is easy to derive and permits the imposition of homogeneity Grosskopf et al., 1997). This function to estimate a parametric distance function corresponds to a multi-output/multi-input technology with technological progress defined in the usual way as a trend variable (Grosskopf et al., 1997;Fuentes et al., 2001) and can be expressed (for firm i at time t) as: ln D 0 t (x i,t , y i,t ) = α 0 + Σ k α k ln x k i,t + 1/2 Σ k Σ l α kl ln x k i,t ln x l i,t + Σ k Σ m δ km ln x k i,t ln y m i,t + Σ m β m ln y m i,t +1/2 Σ m Σ n β mn ln y m i,t ln y n i,t + γ 1 t + 1/2 γ 2 t 2 + Σ k η k ln x k i,t t + Σ m µ m ln y m i,t t The usual restrictions for symmetry and linear homogeneity of degree +1 are applied: α kl = α lk and β mn = β nm ∀ k, l, m, n ...
... We obtain the following frontier model stochastic by choosing one of the outputs arbitrarily (e.g. y M i,t ; see Lovell et al., 1994;Fuentes et al., 2001) -ln y M ...
The object of the present paper is to analyze the productivity of marketing cooperatives incorporating environmental inputs/outputs. In the European agricultural policy, expectations for attaining sustainable and competitive agriculture lie to a great extent on the cooperative sector’s ability to adapt to the new market conditions. These challenges have led marketing cooperatives in the fruit and vegetables sector to consider improvement in productivity and sound environmental performance. In this sector environmental management was intensified by the Common Agrarian Policy (CAP) through incentives on the so-called Operative Programs (OP). The present study analyses the total factor productivity (TFP) related to environmental variables in this sector using a parametric-stochastic approach and taking as reference a panel data of Spanish cooperatives for the period 1994-2002. Additionally, the determinants of productivity environmental indices are examined econ ometrically. The estimates obtained show a relevant increase in the efficiency component for the period under study and a relatively low impact of incentive schemes. However, they also show a relationship between productivity changes and several management factors in cooperatives, such as labor quality, capital intensity and environmental spillover.
... Interpreted in terms of distances defined in Figure 1 Malmquist indices are also estimated using SFA. We follow CCD (1982) and, further, Perelman (1998 and, in their use of parametric distance functions to derive the SFA efficiency scores. The basic input distance function models the efficiency score assuming the translog form as an appropriate approximation for the distance function: ...
... As in Fuentes et al (1998Fuentes et al ( , 2001, we apply SFA to equation (13) and the results are then employed to estimate the total factor productivity change and to decompose this magnitude in its technical and efficiency change components. As a result efficiency changes are modelled as follows: 11 ...
Twenty-five train operating companies (TOCs) were created between 1994-1997, as part of the restructuring process of the railway industry in Great Britain. The TOCs operate monopoly franchises for the provision of passenger rail services over certain routes - some of which continue to receive government subsidies. This paper investigates how the efficiency of these train operating companies evolved prior to the October 2000 Hatfield crash (which caused significant disruption to the network) using data envelopment analysis and stochastic frontier analysis. Our data allows us to look at the relative efficiency and productivity through the privatisation, to control the efficiency scores for environmental data and to correlate these results with safety and quality indicators. The analysis sheds some light on the successes and failures of the UK’s most controversial privatisation to date.
... An input-based Malmquist index of productivity growth (Caves et al. 1982) is derived from the input distance function. This Malmquist index can be decomposed into technical efficiency (TE) and technical change (TC) components (Fuentes et al. 2001). In terms of input-conservation, technical change is defined as the rate at which inputs can be proportionally decreased over time without change in output levels. ...
... The first term in square brackets measures the rate of improvement in technical efficiency between period t and t + 1. The second term represents the estimated rate of technical change over that period obtained by averaging the technical change growth rates for periods t and t + 1. See Fuentes et al. (2001) and Grifell- Tatje and Lovell (1995) for more on the links between the Malmquist TFP growth index and the productivity measures used here. The translog functional form (Christensen et al. 1973) was chosen for the input distance function. ...
The performance of pulp and paper industries in four Canadian regions is compared based on the estimation of an input distance function, with and without pollutant outputs. Distance functions are techniques for the representation and estimation of multiple-output and multiple-input production technologies. They are quantity-based techniques. Non-marketed outputs such as pollutants can be easily incorporated into productivity analysis with the help of distance functions. This environmentally sensitive approach provides higher productivity growth estimates for all regions, indicating the need for adjusting conventional measures that ignore the non-marketed benefits of pollution abatement activities. The results also consistently indicate the presence of substantial differences in the regional levels of technical efficiency. Regional industries have not enjoyed similar rates of technological progress due to differences in their underlying structures. Productivity growth estimates for most regional industries remain weak or negative even after the recognition of pollution abatement efforts. Estimates of regional level costs of abatement for biological oxygen demand (BOD) and suspended solids (TSS) are provided.
... In their study, productivity index is decomposed into three components: technical efficiency change, technical change and scale efficiency change. The application of explicit distance measures was later adopted in parametric stochastic frontier approach by FUENTES et al. (2001) andOREA (2002). ...
The main aim of this study is to measure the technical efficiency and decompose total factor productivity (TFP) growth of Polish crop farms. The novelty of our contribution is threefold. First of all, our work contributes to research on agricultural performance of Central and Eastern European countries in the post-European Union accession period. Secondly, compared to previous studies, our study expands them by decomposition of total factor productivity growth for a specific sector based on a very extensive dataset, thus providing a more in-depth analysis of factors driving productivity growth. Thirdly, we have thoroughly explored the same data set by several different models, showing consequences of choosing a particular model. The empirical analysis is based on a balanced panel of farms, from 2004 to 2011, taken from the Farm Accountancy Data Network. Findings show that the average technical efficiency was only 63%. The elasticity of production was highest with respect to materials and lowest with respect to area. The capital elasticity was statistically non-significant. We point out that this sector is characterized by increasing returns to scale, with estimates ranging from 1.05 to 1.3 for the majority of observations. Furthermore, the results show that TFP was slightly decreasing (on average by 0.067% per annum) over the entire period.
... Output or average production has been obtained from the accountable value added (value of sales minus purchases) 5 . The labor factor has been obtained from labour expenses (Fuentes et al., 2001; Kondo and Yamamoto, 2002), and the capital factor from the depreciation expenditures (accountable replacement value of fixed assets) 6 . All variables have been corrected for inflation (base year 1995) and are expressed in real terms (converted to thousands of euros). ...
Development of the horticultural sector in the Mediterranean agricultural areas of Spain is closely linked to the activity of co-operative organisations for the production and marketing of produce. These entities are especially important in finding answers to current demand requirements in the food market, bearing in mind the small family-scale nature of many of the farm enterprises in this sector. The present paper explores the ability of horticultural co-operatives in adapting to the new challenges in this sector from a productivity analysis viewpoint. Total factor productivity and efficiency are considered indicative measurements of the response of these organisations to the current market environment. In this study, Malmquist productivity indices are estimated using non-parametric techniques and taking as reference panel data of Andalusian horticultural co-operatives for the period 1995-2004. For a more in-depth analysis, productivity indices are broken down into technological change and efficiency change indicators, also considering the impact of other variables of co-operatives. The indicators obtained showed a relevant increase in efficiency for the period under study and a positive relationship between the results and quality investment. On the whole this research work adds to studies in the adaptation process of co-operatives in the current competitive scenario, offering insight into the improvement in total productivity and its correlation with several management variables in the fruit and vegetables sector.
... By utilising the property of homogeneity of degree one in outputs δ (x, λ y) = λ δ (x, y) ∀ λ > 0 and setting λ to y −1 M (e.g. Coelli and Perelman 1996;Fuentes et al 2001), one yields δ (x, y/y M ) = y −1 M · δ (x, y) which leads to δ (x, y) = y M · δ (x, y/y M ). By inserting the last equation into equation (1) and dividing by y M the final estimation equation is denoted by ...
In the estimation of multiple output technologies in a primal approach, the main question is how to handle the multiple outputs. Often, an output distance function is used, where the classical approach is to exploit its homogeneity property by selecting one output quantity as the dependent variable, dividing all other output quantities by the selected output quantity, and using these ratios as regressors (OD). Another approach is the stochastic ray production frontier (SR), which transforms the output quantities into their Euclidean distance as the dependent variable and their polar coordinates as directional components as regressors. A number of studies have compared these specifications using real world data and have found significant differences in the inefficiency estimates. However, in order to get to the bottom of these differences, we apply a Monte-Carlo simulation. We test the robustness of both specifications for the case of a Translog output distance function with respect to different common statistical problems as well as problems arising as a consequence of zero values in the output quantities. Although our results show clear reactions to some statistical misspecifications, on average none of the approaches is clearly superior. However, considerable differences are found between the estimates at single replications. Taking average efficiencies from both approaches gives clearly better efficiency estimates than taking just the OD or the SR. In the case of zero values in the output quantities, the SR clearly outperforms the OD with observations with zero output quantities omitted and the OD with zero values replaced by a small positive number.
... They also present some potential shortcomings, especially if the translog specification is used. In this case, regular conditions on the production function are not guaranteed and must be checked, especially convexity on outputs and concavity on inputs (Fuentes et al., 1998). The Malmquist index construction allows us to decompose the secular productivity into frontier shifts effects and catching up effects. ...
In this paper we use a stochastic frontier approach to analyse the technical change in the post-privatisation period in the gas distribution sector in Argentina. We found that there is both a catching up effect and a shift in the frontier, which shows that the sector as a whole improved its efficiency in the reviewed period. Moreover, this phenomenon holds not only for the average but also for every firm in the sample.
... Cummins et al. (CWZ) (1999) provide evidence consistent with both the efficient structure and expense preference hypotheses. The Spanish insurance industry has been studied previously by Fuentes et al. (2001) and Cummins and Rubio-Misas (2003). The former study analyzes productivity change in the period 1987–1994 and finds low rates of productivity growth in spite of deregulation. ...
This paper provides new information on the effects of organizational structure on efficiency by analyzing Spanish stock and mutual insurers over the period 1989–1997. We test the efficient structure hypothesis, which predicts that the market will sort organizational forms into market segments where they have comparative advantages, and the expense preference hypothesis, which predicts that mutuals will be less efficient than stocks. Technical, cost, and revenue frontiers are estimated using data envelopment analysis. The results indicate that stocks and mutuals are operating on separate production, cost, and revenue frontiers and thus represent distinct technologies. In cost and revenue efficiency, stocks of all sizes dominate mutuals in the production of stock output vectors, and smaller mutuals dominate stocks in the production of mutual output vectors. Larger mutuals are neither dominated by nor dominant over stocks in the cost and revenue comparisons. Thus, large mutuals appear to be vulnerable to competition from stock insurers in Spain. Overall, the results are consistent with the efficient structure hypothesis but are generally not consistent with the expense preference hypothesis.
Poverty is pervasive in rural Ethiopia. The Growth and Transformation Plan stipulated that
increasing the agricultural productivity of farmers is one entry point for poverty reduction. In this regard, studying the sources of productivity growth and its implication for poverty
reduction is very important for policymaking. So far, studies in Ethiopia focused on
productivity per se. Other studies on household poverty also paid more attention to the
impact of productivity-enhancing factors such as roads and improved agricultural water
management technologies on household poverty. However, studies on the impact of
productivity growth on poverty reduction are limited. In an attempt to fill this gap, this
study analyzed sources of agricultural productivity and their impact on household poverty.
Stochastic Frontier Analysis (SFA) was employed to decompose the Malmquist Total Factor Productivity Index using the Ethiopian Rural Household Survey data. The results showed that agricultural TFP grew for the sample households. The analysis further showed that the main source of TFP growth was an improvement in technical efficiency. The results also revealed that there is no growth in technology (the state of knowledge) of the farmers that significantly shifts the production frontier upward. Results of Two Stages Least Squares (2SLS) fixed-effects regression also indicated that growth in technical efficiency reduces household poverty. Other productivity indicators, land and labor productivity, also reduce household poverty, albeit not as responsive as technical efficiency.
This chapter reviews the modern frontier efficiency and productivity methodologies that have been developed to analyze firm performance, emphasizing applications to the insurance industry. The focus is on the two most prominent methodologies-stochastic frontier analysis using econometrics and non-parametric frontier analysis using mathematical programming. The chapter considers the underlying theory of the methodologies as well as estimation techniques and the definition of inputs, outputs, and prices. Seventy-four insurance efficiency studies are identified from 1983 to 2011, and 37 chapters published in upper tier journals from 2000 to 2011 are reviewed in detail. Of the 74 total studies, 59.5% utilize data envelopment analysis as the primary methodology. There is growing consensus among researches on the definitions of inputs, outputs, and prices. © Springer Science+Business Media New York 2013. All rights reserved.
Different processes in Decision Making Unit (DMU) are the same as subprocesses in that DMU when it is not considered as blackbox. Most of the time these subprocesses are mooted in a series structure and frequently used in real world applications. When it is aimed to evaluate the performance of a unit with its subprocesses and what it did in the past, those techniques which show progress and regress can be used. One of these famous techniques is Malmquisr Productivity Index (MPI). Here MPI is developed and used for series structural DMUs, with two components, in which intermediate inputs and outputs exist.
The aim of this paper is to examine the correlation between CO2 emissions and technical efficiency of logistics sector. In doing so, a one-step Stochastic Frontier Analysis (SFA) approach is employed based on panel data from 25 provincial logistics sector in China. Besides CO2 emissions, rail mileage, highway mileage, inland waterway mileage and the progress degree of provincial marketization in China are also assumed as inefficient factors to technical efficiency. The result of empirical research shows that the coefficients of four assumed inefficient factors pass significant test except the inland waterway mileage. The most important insight is that this research measures the coefficient of CO2 emissions to technical efficiency of logistics sector, i.e. reducing 1% CO2 emissions leads to 0.231% enhancement of technical efficiency of logistics sector. Meantime, facilitating the progress of marketization and expanding mileage of rail and highway system can also improve technical efficiency of logistics sector.
In this paper, we measure the productivity changes of 30 airports in Greater China during 2000–2006 by computing their Malmquist productivity indices using parametric output distance functions. On average, the productivity of airports grew at 10.3% annually over our period. In addition, decomposing the Malmquist index did not provide evidence supporting any “catching-up” in technical efficiency between regional airports and major hubs.
As integrated supply chains, ubiquitous computing, and mobile applications have become the backbone for conducting business nowadays, the economic significance of information technology (IT) is self-evident. In this paper, we study IT value from an unconventional perspective: the production of IT capital goods. Using the true fixed-effects model of translog stochastic production frontier, we evaluate the performance of IT industries for 19 Organization of Economic Cooperation and Development (OECD) countries over the period of 2000 to 2009. We examine the productivity growth of these IT industries based on the Malmquist index and further analyze these productivity patterns through technological change and efficiency change. Overall, these IT industries are found to enjoy greater productivity growth than other industries when compared with previous findings. Our results show that technological progress is the main driver of productivity growth for the IT industry, efficiency change has a negligible effect, and each country's IT industry exhibits a distinctive performance profile. Policy implications are drawn from our results and related issues are identified for future research. We also highlight the advance of research methodology used in the study that can account for measurement errors, random fluctuations, and unobserved heterogeneity commonly encountered in empirical information systems research.
The Korean government has driven the venture capital market since KTB Network was created in 1981 to provide capital to the high tech firms. Due to the venture policy, the venture capital market has undergone a compressed growth in a short period of time. In 1986, the government enacted the “Small and Medium Business Start-up Support Act” and “Finance Act to Support New Technology Businesses” to provide legal bases to establish venture capital (VC) firms. The government pushed the VC firms to carry out equity investments on small and medium businesses within the age of 7 years. Hence, the Korea Development Bank Capital and TG Venture, the archetypes of today’s VC firms, have been established to finance high tech firms such as Medison, Mirae, and Sambo Computer (Lee 2003). In spite of the efforts made by the government, until the mid-1990s, there were problems in constructing the venture capital market, due to poor system to finance technology and lack of policy measures to support the high tech firms. There was no exit system to liquidize the equity investments, and most of the investment targets were from mature industries which brought low returns. Further debt financing was preferred to equity investment because of the low risk and high interest rate.
This paper is organized as follows. Chapter 2 presents the literature reviewed and the hypotheses proposed. In Chap. 3, methodologies are presented while in Chap. 4, the data and the variables are presented. In Chap. 5, the effect of asset composition strategies on operating efficiency is estimated and analyzed. In Chap. 6, the estimation results are reviewed and policy implications addressed.
The objective is to examine sources of productivity change on Finnish dairy farms in the 1990s. The decomposition of productivity change into technical and technical efficiency change is widely recognized but it neglects the scale effect. Generalized decompositions incorporating all three components are calculated for a sample of Finnish dairy farms from 1989-2000. This period is of interest because of the drastic change in agricultural policy when Finland joined the European Union (EU) in 1995. The results indicate that productivity growth was on average low, approximately 0.15% per year. Neutral technical change was identified as the most important source of productivity growth (1.1%). Technical efficiency decreased by almost 0.5% annually. The contribution of the scale effect in productivity change increased towards the end of study period.
In this paper we apply Stochastic Frontier Analysis through a distance function to investigate the impact of firm size on productivity development in electricity distribution. We use a sample of seventeen Brazilian firms from 1998 to 2005 and decompose productivity into technical efficiency, scale efficiency and technical change. Moreover, a further step is to decompose the technical change measurement into several components. The results indicate that firm size is important for industry's productivity, and therefore a key aspect to consider when making decisions that affect the market structure in the electricity distribution industry.
Malmquistindexes of productivity are generally estimated using index numbertechniques or non-parametric frontier approaches. The aim ofthis paper is to show that Malmquist indexes can be estimatedin a similar way using parametric-deterministic or parametric-stochasticfrontier approaches. To allow a multi-output multi-input technologyand for technical change in production, we adopt an output distancefunction which is specified in a translog form. We then showthat using the estimated parameters, several radial distancefunctions can be calculated and combined in order to estimateand decompose the productivity index. Finally, this approachis applied to a panel of Spanish insurance companies. The mainresults confirm those generally obtained for financial services:very low rates of growth and technical change in spite of a rapidderegulation process and expansion of activity.
Growth in the neoclassical framework stems from two sources: factor accumulation and productivity growth. The growth driven
by increased factor accumulation cannot be sustained because of the non-availability of factor inputs in future as well as
diminishing returns to factors. Hence, economists have emphasized on productivity growth. Total factor productivity (TFP)
growth is important even for developing countries like India with relatively abundant labour, as these economies face an acute
shortage of some other productive resources. Many studies have been undertaken to examine the trends in productivity in India.
Most of the empirical studies on productivity in India have focused on the TFP growth (TFPG) of the manufacturing sector in
the post reform period. Some of these studies include Brahmananda (1982), Ahluwalia (1991), Golder (1986,1990, 2004), Srivastava
(1996, 2001), Chand and Sen (2002), Unel (2003), Das (2003), and Topalova (2003). Evidence on TFPG in India as brought out
by these studies vary considerably. This is due to the use of different estimation methods of TFPG, as well as the use of
different data sets. None of the above studies has considered variation in input utilization rates over business cycles to
compute TFP or Solow residual. In this paper, I have considered variable input utilization — variable capital utilization
and variable labour efforts derived explicitly from a partial equilibrium model on Indian data. Variability of factor inputs
can occur over a business cycle when firms are not able to disinvest capital or lay off workers in a downturn. It is particularly
important for Indian industries which have operated till 1991 under a rigid license, permit and quota regime. During an expansion
period, capital is fully utilized while in recession period, there is under utilization of capital stocks. Firms were known
to hoard capital above their optimal level as they could claim a lower capital requirement for later expansion, and hence
strengthen their claim for production license. On the labour front, labour protection laws have made it virtually impossible
for the firms to lay off workers even when they have stopped producing. Also, training new workers is costly and firms encourage
workers to work harder in the expansion period. In the typical TFP calculation, labor/capital inputs are measured as higher
than ‘real’ in recessions, and as lower than ‘real’ in expansions. Accounting for factor hoarding or surplus can thus have
a significant impact on TFPG estimation since the standard computation of the Solow residual fails to filter out cyclical
variation in input utilization rate, assigning it to fluctuations in technology.
Since the deregulation of the Australian financial system in early 1980s, the banking industry has undergone sweeping changes.
As of December 2005, there were 53 authorised banks in Australia, including eleven foreign subsidiary banks and 29 branches
of foreign banks (APRA 2005). With the entry of foreign banks and former domestic building societies into the market, domestic
banks have reacted to the intensified competition by performing more efficiently and engaging more actively in mergers and
acquisitions. However, the four major banks generally hold the view that the consolidation of the financial services industry
and the competitiveness of the industry in the international market have been hindered by a restrictive political and regulatory
environment, such as the four pillars policy prohibiting mergers among the four major banks (Guy and Whyte 2002). Therefore,
it is important to analyse the performance of the Australian banking industry, with particular reference to the Wallis Inquiry
into the Australian Financial System (hereafter the Inquiry) in 1996, to which the Australian Federal Government responded
by adopting the four pillars policy.
Non-Bank Financial Institutions (NBFIs) play an important dual role in a financial system. Traditionally, NBFIs comprise of a mixed bag of institutions that includes all financial institutions not classified as commercial banks. They complement the role of commercial banks, filling in financial intermediation gaps by offering a range of products and services that they offered. Nevertheless, they also compete with commercial banks, forcing the latter to be more efficient and responsive to their customers needs. Most NBFIs are also actively involved in the securities markets and in the mobilization and allocation of long-term financial resources. The state of development of NBFIs is usually a good indicator to the state of development of a country’s financial system as a whole.
Given the substantial task of the NBFIs, it is worth raising the issue of its role. In particular, since Gerschenkron (1962) classic study emphasizing the role of the banking systems in the economic development of Germany, France and Italy in the nineteenth century, it may appear that the need for NBFIs is largely redundant in the specific circumstances of the developing economies. There are two main reasons why the existence of NBFIs is important; one reason concerns the economic development and the other reason relates to financial stability. As NBFIs are established to avoid tight prudential controls applicable to banks, they play a prominent role in financial system failures. Increased competition from NBFIs could also result in banks increasing their lending volumes, by lowering their lending standards to maintain market shares. This may result in a rapid lending growth, which could indirectly result in a financial crisis.
It is a very strategic and efficient policy for Korea, a small country with few natural resources, to develop information
and communication technology (ICT) as an alternative source of development. The surprisingly rapid development of the ICT
industry is a result of long term and optimal R&D investment and also due to the national uniqueness of this industry field.
Specially, the fast diffusion of super-highway internet has enabled the advanced foundation for this industry. With the development
of ICT, a new type of industry has emerged. The digital content industry has enjoyed the benefits of the ICT industry development
and has the distinct characteristics compared to traditional industries. Economic scholars are forecasting the various future
possibilities and the next generation of ICT. They emphasize the necessity of moving the axis from communication network-based
services to content-based services.
Despite the emergence of industrialisation, the agricultural sector still plays a prominent role both in the Thai economy and social development. As indicated by the National Statistical Office (2006), around 57% of the total population relies on the agricultural sector in Thailand, while the contribution of the agricultural sector to gross domestic product has gradually decreased (Office of the National Economic and Social Development Board 2005). This implies that the more the Thai economy progresses, the more the productivity inequality between the conventional and modern sectors increases. It has long been a critical question for policy makers to choose the appropriate direction of development planning to improve the above situations through many measures and interventions on the sector in Thailand.
The primary purpose of this study is to measure and investigate factors influencing Thai agricultural cooperatives’ technical efficiency including its pure technical and scale efficiencies in 2004. The study was an application of a data envelopment analysis approach in order to estimate technical efficiency, based on the financial statements of agricultural cooperatives in Thailand, and also to investigate the determinants of the efficiencies among different management policies and operation environments. The empirical results of technical efficiency and influencing factors are necessary for policy makers and cooperatives’ stakeholders to enable them to choose the appropriate direction of development planning to improve the performance of agricultural cooperatives and the Thai economy.
This paper is organized into five sections. Following this introduction, the analytical framework is explained. Next, data are described. The last two sections cover the empirical findings of this study, and conclusions and policy implications.
Empirical analysis of the efficiency of higher education institutions has commonly involved the use of data envelopment analysis
(DEA). Leading studies in this area include those that measure efficiency at the school level, such as Ahn et al. (1988) on
US universities in 1981–1985, Glass et al. (1998) on UK universities in 1989–1992, and Avkiran (2001), Abbott and Doucouliagos
(2003) and Carrington et al. (2004) on Australian universities. There are also a few studies that measure efficiency at the
departmental level. For example, Madden et al. (1997) assessed the efficiency of economics departments in Australian universities,
Johnes and Johnes (1993) assessed the efficiencies of economics departments in the UK in 1984–1988, Haksever and Muragishi
(1998) and Colbert et al. (2000) studied the efficiency performance of MBA programs in the US, and Ray and Jeon (2003) employed
a production model and DEA to examine the reputation and production efficiency of MBA programs in general.
The Indian industrial sector has gone through various phases since independence. During the late 1970s and 1980s, there was a stagnation in the Indian industrial production. The slowdown in industrial production observed during the 1980s was primarily on account of low productivity. There was persistence of high costs on account of adoption of obsolete technology and low quality of production. However, progress in the process of deregulation was initiated during the 1980s.
The major reforms in Indian Industrial sector were witnessed during the 1990s. For instance, in 1991, there was a gradual dismantling of industrial licensing, removal of import licensing from nearly all manufactured intermediate and capital goods, tariff reduction and relaxation of rules for foreign investment. The reforms in respect of the industrial sector were intended to free the sector from barriers to entry and from other restrictions to expansion, diversification and modification so as to improve the efficiency, productivity, and international competitiveness of the Indian industry. Against this backdrop, the paper makes an attempt to examine the impact of reforms on Industrial sector (both organized and unorganized sector) in India during the reforms period by adopting both partial factor productivity and total factor productivity approach. Further, to identify the role of technical efficiency and technical change, attempt has been made to decompose total factor productivity growth (henceforth, TFPG) into technical change and efficiency change by using Malmquist index.
The paper is organized as follows: Sect. 4.2 deals with data base and methodology adopted while in Sect. 4.3, the growth performance of the Indian manufacturing sector has been discussed. In Sect. 4.4 an attempt is made to examine the productivity performance of the organized and unorganized manufacturing sectors while Sect. 4.5 deals with policy issues followed by summary and conclusion in Sect. 4.6.
National financial systems, and banking sectors in particular, assume increasing importance and fluidity with the progress of economic development and the increase in economic openness. This notwithstanding, attempts to measure and formally monitor the performance of the banking sector have largely been confined to western developed economies. As a result, little concrete empirical information and evidence is available about banking productivity and efficiency in non-western countries. Accordingly, the aim of the present investigation is to start filling the gap left by non-industrialized countries in the empirical literature of efficiency studies of banking.
This paper is an extension of the metafrontier Malmquist productivity index, which takes into account the effect of scale
efficiency change in its decomposition for both the non-parametric and parametric frameworks. Meanwhile, the ‘catch-up’ in
the index is also disintegrated as two components: pure technological catch-up and frontier catch-up. An empirical application
that uses unbalanced panel data of the Taiwanese and Chinese commercial banking industry is also conducted under a parametric
framework. The results reveal that the adverse scale efficiency change is the key factor to inducing the inferior productivity
growth seen in Chinese banks compared with Taiwanese banks, which spotlights the importance of the scale efficiency change
term on productivity measures. It also provides one possible explanation for the recent hot issue about the motives for the
two shores of the Taiwan Straits advancing financial openness to each other and mutually signing a banking Memorandum of Understanding.
KeywordsMalmquist productivity index–Productivity growth–Metafrontier
The defense market, which is composed of a sole demander and few suppliers, is generally regarded as a monopolistic market. In this sense, it has its own characteristics that are different from other common competitive markets. High precision technology and a huge amount of capital investment in the initial stage of production are essential in the defense industry, and this necessitates subsidy policy of the government. Most of the supplies are produced in an order-based manner due to the special specification requirements and this hampers the market-driven pricing mechanism. The price is determined based on negotiations between the two parties, considering the cost of production, retrieval of the investment, and efficient allocation of the government budget.
This study is organized as follows. The history of the Korean defense industry and policies are summarized in Sect. 10.2. The data is described in Sect 10.3. In Sect 10.4, this study sets out the stochastic frontier production function for the analysis of efficiency and the model for decomposition of TFP. The results of the estimation of the stochastic frontier model are presented in Sect 10.5, where technical efficiency, testing results on factors affecting efficiency and decomposition of TFP are discussed. Lastly, Sect 10.6 presents the conclusions of this study.
Rice is the major crop in Thailand and it will remain so as long as it continues to be the major export crop and the staple food of the Thai population. However, the fact is that, although Thailand is the main rice-exporting country in the world, its rice yields are among the lowest in Asia (Office of Agricultural Economics, 2004a, b). This might imply low productivity and high technical inefficiency in major rice production. In an attempt to resolve this problem, the Thai government has promoted the use of inputs in rice production, such as chemical fertiliser, highyielding varieties and chemicals, to increase the yields. The total amount of chemical fertiliser that was imported increased from about 1.3 million tonnes in 1985 to 3.9 million tonnes in 2004, with an annual growth rate of 4.6%. The value of imported chemical fertiliser also increased with a higher annual growth rate of 8.7%. The increasing use of chemical fertiliser and chemicals whose prices have been rising continuously has resulted in substantial increases in production costs.
This paper aims to answer two questions: how has rural credit contributed to the production of rice? and how do agricultural loans from the rural financial institutions affect the technical efficiency of rice farmers? This study is based on data from farmers in Chiang Mai and Chiang Rai provinces which are the main areas for major rice production in the Upper North sub-region. The results from this study will be useful for determining the government policies on rural financial institutions.
This paper is set out as follows: Sect. 2 provides an overview of the rural financial institutions. Section 3 presents survey data on rice farmers and model specifications. Section 4 discusses the results from the translog stochastic frontier production function. The last section provides policy implications and conclusions.
In this paper we introduce a method for conducting a Hyper Sensitivity Analysis (HSA) of productivity and efficiency measurement
problems. HSA is an intuitive generalization of conventional sensitivity analysis where the term “hyper” indicates that the
sensitivity analysis is conducted with respect to functions rather than numeric values. The concept of HSA is suited for situations
where several candidates for the function quantifying the utility of (input, output) pairs are available. Both methodological
and technical issues arising in the area of multiple criteria productivity measurement in the context of such an analysis
are examined.
Keywordshyper sensitivity analysis–productivity–efficiency–DEA–multiple objective programming–composite concave programming.
In this paper, the issue of whether it is possible to design an objective impartial system of analysis of the Olympic results, which the majority of participating countries would agree upon, is analyzed by discussing different ways of ranking the performance of participating countries at Sydney 2000 Olympic Games. It is demonstrated that key measures frequently reported in the media lack the necessary descriptive power. The productivity measurement approach is used for modelling the multiple objective nature of the underlying situation. The unsupervised data mining technique of self-organizing maps is used to group the participating countries into homogenous clusters. The Data Envelopment Analysis (DEA)-based model is then used for producing a new ranking of participating teams acceptable as “fair” by the majority of participants.
This paper estimates the productivity evolution of the Brazilian electricity distribution industry decomposing it in terms of technical efficiency, scale-efficiency and technical change. This exercise aims to understand one important issue that has not been analyzed in previous papers, that is the impact of firm’s size in efficiency and productivity evolution. It employs stochastic frontier analysis on a panel of 18 Brazilian firms from 1998-2005. The results allow us to conclude that company size is an important issue in the evolution of the industry’s productivity and, therefore, a key aspect to consider when making decisions affecting the organization and composition of electricity distribution.
The environmental Kuznets curve (EKC) has been extensively criticized on econometric and theoretical grounds. Recent econometric results and case studies show that national emissions of important pollutants are monotonic in income but changes in technology can lead over time to reductions in pollution - a lowering of the EKC - and that pollution reducing innovations and standards may be adopted with relatively short time lags in some developing countries. This study combines the recent literature on measuring environmental efficiency and technological change using production frontier methods with the use of the Kalman filter - a time series method for signal extraction - to model the state of abatement technology in a panel of countries over time. The EKC is reformulated as the best practice technology frontier - countries' position relative to the frontier reflects the degree to which they have adopted best practice. The results are used to determine whether countries are converging to best practice over time and how many years it will take each country to achieve current best practice. The model is applied to sulfur dioxide emissions from sixteen mainly developed countries.
This article proposes a tractable approach for analyzing the sources of TFP changes (i.e., technical change, changes in technical
and allocative inefficiency, and the scale effect) in a multi-output setting, while retaining the single-equation nature of
the econometric procedure used to estimate the parameters of the underlying technology. The proposed approach relies on Bauer's
cost function-based decomposition of TFP changes and the duality between input distance and cost functions. The empirical
results are based on a sample of 121 UK livestock farms observed over the period 1983–92 and a translog input distance function.
The published empirical literature on frontier production functions is dominated by two broadly defined estimation approaches - parametric and non-parametric. Using panel data on Korean rice production, parametric and non-parametric production frontiers are estimated and compared with estimated productivity. The non-parametric approach employs two alternative measures based on the Malmquist index and the Luenberger indicator, while the parametric approach is closely related to the time-variant efficiency model. Productivity measures differ considerably between these approaches. It is discovered that measures of efficiency change are more sensitive to the choice of the model than are measures of technical change. Both approaches reveal that the main sources of growth in Korean rice farming have been technical change and productivity improvements in regions of the country that have been associated with low efficiency. Copyright 2004 Australian Agricultural and Resource Economics Society Inc. and Blackwell Publishing Asia Pty Ltd..
Regional differences in total factor productivity, efficiency, and technological change in the Philippine rice sector are examined for the post-Green Revolution era. Malmquist productivity indices were constructed for 1971-90 and were decomposed into efficiency and technological change. The average annual Malmquist productivity growth was only slightly positive. Productivity growth was negative during the early 1970s, and was followed by a period of positive growth. Growth was negative again in the late 1980s. The period of positive growth coincided with the introduction of new rice varieties while the declines are likely to have been caused by intensification of rice production in lowland farming systems. Certain regions such as Central Luzon, Western Visayas, and Southern and Northern Mindanao had higher rates of technological change than others. This may be due to higher investments in infrastructure and education, increased adoption of tractors, and a better agroclimatic environment. Copyright 2003 American Agricultural Economics Association.
The degree of inequality in the levels of well-being of its citizens tells us a great deal about a society. It enables us to judge its social and economic system, to identify those citizens with a claim on community compassion, to identify the sources of hardship, and to devise strategies for reducing levels of hardship. The value of such information is undoubted. But we confront a severe practical problem in first defining, and then measuring, what we mean by well-being. It is surely multi-dimensional, and difficult to reduce to a scalar-valued index.
DEA is typically applied to cross-section data to analyze productive efficiency. DEA is infrequently applied to panel data
to analyze the variation of productive efficiency over time, but when it is, the technique of choice has been window analysis.
Here, we adopt a different approach to the use of DEA with panel data. Following the lead of Färe and others, we use DEA to
construct a Malmquist index of productivity change, and we provide a new decomposition of the Malmquist productivity index.
Our new decomposition allocates productivity change to change in productive efficiency, the magnitude of technical change,
and the bias of technical change. We then propose an evaluation of managerial performance, not on the usual basis of static
efficiency, but on the intertemporal basis of change in efficiency and adaptation to the bias of technical change. We illustrate
our approach with an examination of the recent productivity change experience in Spanish savings banks.
Deterministic frontier analysis (DFA), stochastic frontier analysis (SFA), and data envelopment analysis (DEA) are alternative analytical techniques designed to measure the efficiency of producers. All three techniques were originally developed within a cross-sectional context, in which the objective is to compare the efficiencies of producers. More recently all three techniques have been extended for use in a panel data context. In the latter context it is possible to measure productivity change, and to decompose measured productivity change into its sources, one of which is efficiency change. However when efficiency measurement techniques, particularly SFA, have been applied to panel data, it has infrequently been made clear what the objective of the analysis is: the measurement of efficiency, which may vary through time as well as across producers, or the measurement and decomposition of productivity change. In this paper I explore the use of each technique in a panel data context. I find DFA and DEA to have achieved a more satisfactory reorientation toward productivity measurement than SFA has.
The relationship between Malmquist productivity change and profitability is developed in this paper. Our theoretical construct is applied to Swedish pharmacies.
Thefirst objective of this paper is to develop a generic measureof scale efficiency for a multiple-input multiple-output firm,using basic principles of modern production theory. The secondobjective is to combine measures of technological change, technicalefficiency change, and scale efficiency change into an encompassing(primal) measure of productivity change. This measure and itsdecomposition is compared to a number of recent proposals inorder to shed light on what seems to have become a controversialissue. The paper proceeds by developing an encompassing dualmeasure of productivity change. This dual measure is then appliedto panel data of a set of Dutch firms, continuing the empiricalwork of Balk (1998). It turns out that extending the Malmquistproductivity index with factors measuring scale efficiency changeand input mix change leads to appreciably different outcomes.
In recent years the Malmquist index has gained in popularity as a measure of productivity change. We demonstrate that, in the presence of non-constant returns to scale, the Malmquist productivity index does not accurately measure productivity change. The bias is systematic, and depends on the magnitude of scale economies.
A stochastic frontier production function is defined for panel data on sample firms, such that the disturbances associated with observations for a given firm involve the differences between traditional symmetric random errors and a non-negative random variable, which is associated with the technical efficiency of the firm. Given that the non-negative firm effects are time-invariant and have a general truncated normal distribution, we obtain the best predictor for the firm-effect random variable and the appropriate technical efficiency of an individual firm, given the values of the disturbances in the model. The results obtained are a generalization of those presented by Jondrow et al. (1982) for a cross-sectional model in which the firm effects have half-normal distribution. The model is applied in the analysis of three years of data for dairy farms in Australia.
The error term in the stochastic frontier model is of the form (v–u), where v is a normal error term representing pure randomness, and u is a non-negative error term representing technical inefficiency. The entire (v–u) is easily estimated for each observation, but a previously unsolved problem is how to separate it into its two components, v and u. This paper suggests a solution to this problem, by considering the expected value of u, conditional on (v–u). An explicit formula is given for the half-normal and exponential cases.
In 1953 Sten Malmquist, a Swedish economist and statistician, published
inTrabajos de Estad{\'i}stica the foundations of a productivity index
which now bears his name. In this paper we generalize the Malmquist
productivity index. We show that (i) the generalized Malmquist productivity
index can be expressed as the product of a Malmquist productivity
index and a Malmquist scale index; (ii) the generalized Malmquist
productivity index can also be expressed as the ratio of a Malmquist
output quantity index to a Malmquist input quantity index; (iii)
the geometric mean of a pair of Malmquist scale indexes is equal
to the reciprocal of the T\"{o}rnqvist scale index, which implies
that (iv) the geometric mean of a pair of generalized Malmquist productivity
indexes is equal to a T\"{o}rnqvist productivity index.
Collateral impacts of LULUCF projects, especially those concerning social and environmental aspects, have been recognised as important by the Marrakech Accords. The same applies to the necessity of assessing and, if possible, of quantifying the magnitude of these impacts. This article aims to define, clarify and structure the relevant social, economic and environmental issues to be addressed and to give examples of indicators that ought to be included in the planning, design, implementation, monitoring, and ex post evaluation of LULUCF projects. This is being done by providing a conceptual framework for the assessment of the sustainability of such projects that can be used as a checklist when dealing with concrete projects, and that in principle is applicable to both Annex I and non-Annex I countries. Finally, a set of recommendations is provided to further develop and promote the proposed framework.
This paper is an empirical study of the uncertainty associated with estimates from stochastic frontier models. We show how to construct confidence intervals for estimates of technical efficiency levels under different sets of assumptions ranging from the very strong to the relatively weak. We demonstrate empirically how the degree of uncertainty associated with these estimates relates to the strength of the assumptions made and to various features of the data.
Previous studies of the so-called frontier production function have not utilized an adequate characterization of the disturbance term for such a model. In this paper we provide an appropriate specification, by defining the disturbance term as the sum of symmetric normal and (negative) half-normal random variables. Various aspects of maximum-likelihood estimation for the coefficients of a production function with an additive disturbance term of this sort are then considered.
This paper develops index number procedures for making comparisons under very general circumstances. Malmquist input, output, and productivity comparisons are defined for structures of production with arbitrary returns to scale, substitution possibilities and biases in productivity change. For translog production structures, Törnqvist output and input indexes are shown to equal the mean of two Malmquist indexes. The Törnqvist productivity index, corrected by a scale factor, is shown to equal the mean of two Malmquist productivity indexes. Similar results are given for making cost of living comparisons under general structures of consumer preferences.
In this paper we consider the specification and estimation of the Cobb-Douglas production function model. After reviewing the "traditional" specifying assumptions for the model which are based on deterministic profit maximization, we develop a model in which profits are stochastic and in which maximization of the mathematical expectation of profits is posited. "Sampling theory" and Bayesian estimation techniques for this model are presented.
The purpose of this chapter is to study productivity change in Swedish hospitals during the time period from 1970 to 1985. By comparing annual changes in the productivity of individual hospitals, it is possible both to identify general trends in the productivity of the hospital industry as a whole and to identify individual hospitals exhibiting patterns of change in productivity that differ from the rest of the industry. A careful analysis of the results of this exercise should add to our knowledge about the factors determining the pattern of hospital productivity in Sweden.
В статье производится анализ агрегированной производственной функции, вводится аппарат, позволяющий различать движение вдоль такой функции от ее сдвигов. На основании сделанных в статье предположений делаются выводы о характере технического прогресса и технологических изменений. Существенное внимание уделяется вариантам применения концепции агрегированной производственной функции.
A sequel to his frequently cited Cost and Production Functions (1953), this book offers a unified, comprehensive treatment of these functions which underlie the economic theory of production. The approach is axiomatic for a definition of technology, by mappings of input vectors into subsets of output vectors that represent the unconstrained technical possibilities of production. To provide a completely general means of characterizing a technology, an alternative to the production function, called the Distance Function, is introduced. The duality between cost function and production function is developed by introducing a cost correspondence, showing that these two functions are given in terms of each other by dual minimum problems. The special class of production structures called Homothetic is given more general definition and extended to technologies with multiple outputs.
Malmquistindexes of productivity are generally estimated using index numbertechniques or non-parametric frontier approaches. The aim ofthis paper is to show that Malmquist indexes can be estimatedin a similar way using parametric-deterministic or parametric-stochasticfrontier approaches. To allow a multi-output multi-input technologyand for technical change in production, we adopt an output distancefunction which is specified in a translog form. We then showthat using the estimated parameters, several radial distancefunctions can be calculated and combined in order to estimateand decompose the productivity index. Finally, this approachis applied to a panel of Spanish insurance companies. The mainresults confirm those generally obtained for financial services:very low rates of growth and technical change in spite of a rapidderegulation process and expansion of activity.
In this paper we use multi-output distance functions to investigate technical inefficiency in European railways. The principle aim of the paper is to compare the results obtained from the three alternative methods of estimating multi-output distance functions. Namely, the construction of a parametric frontier using linear programming; data envelopment analysis (DEA) and corrected ordinary least squares (COLS). Input-orientated, output-orientated and constant returns to scale (CRS) distance functions are estimated and compared. The results indicate a strong degree of correlation between the input- and output-orientated results for each of the three methods. There are also significant correlations observed between the results obtained using the alternative estimation methods. The strongest correlations being between the parametric linear programming and the COLS methods. Finally, the paper concludes with the suggestion that a combination of the technical efficiency scores, obtained from the three different methods, be used as the preferred set of scores. This idea is borrowed from the time-series forecasting literature.
The second edition of An Introduction to Efficiency and Productivity Analysis is designed to be a general introduction for those who wish to study efficiency and productivity analysis. The book provides an accessible, well-written introduction to the four principal methods involved: econometric estimation of average response models; index numbers, data envelopment analysis (DEA); and stochastic frontier analysis (SFA). For each method, a detailed introduction to the basic concepts is presented, numerical examples are provided, and some of the more important extensions to the basic methods are discussed. Of special interest is the systematic use of detailed empirical applications using real-world data throughout the book. In recent years, there have been a number of excellent advance-level books published on performance measurement. This book, however, is the first systematic survey of performance measurement with the express purpose of introducing the field to a wide audience of students, researchers, and practitioners. Indeed, the 2nd Edition maintains its uniqueness: (1) It is a well-written introduction to the field. (2) It outlines, discusses and compares the four principal methods for efficiency and productivity analysis in a well-motivated presentation. (3) It provides detailed advice on computer programs that can be used to implement these performance measurement methods. The book contains computer instructions and output listings for the SHAZAM, LIMDEP, TFPIP, DEAP and FRONTIER computer programs. More extensive listings of data and computer instruction files are available on the book's website: (www.uq.edu.au/economics/cepa/crob2005).
Extra t.p. with thesis statement and English abstract inserted. Thesis (doctoral)--Göteborgs universitet, 1994. Includes bibliographical references (p. 135-137).
This paper outlines a procedure for estimating a general index of technical change within the context of a qui te general production technology. Specifically, when panel data are a vailable for firms in an industry, time-specific dummies can be combi ned in a nonlinear estimation procedure to yield a general index of t echnical change that may be both nonneutral and scale augmenting. The general index can serve as the basis for analysis of the determinant s of technical change. Results for a sample of thirty electric utilit ies over the period 1951-78 show that the productivity decline of the 1970s can be attributed primarily to sulphur oxide restrictions and secularly declining capacity utilization due to rapidly increasing pe ak-load demands. Copyright 1988 by University of Chicago Press.
Equality and efficiency are key issues in educational reform. Here the authors analyze the efficiency and equality consequences of various school finance reforms using a cost-indirect output distance function. This function readily models multiple-output production under conditions of budgetary constraint, and provides a natural measure of performance that is closely related to Farrell-type measures of efficiency. The analysis suggests that despite school district inefficiency, finance reforms can affect student achievement. However, any potential gains in output from redistribution are dwarfed by the potential gains from increased efficiency. More strikingly, the analysis demonstrates that budgetary reforms designed to equalize expenditures could actually increase the inequality of student achievement. © 2000 by the President and Fellows of Harvard College and the Massachusetts Institute of Technolog
Econometric estimation of allocative and technical efficiency has frequently been carried out using a shadow cost function and its associated share or demand equations. Since the problem is formulated in terms of shadow prices, the effect of allocative inefficiency on input usage must be computed indirectly from input share or demand equations. As an alternative approach, we derive and estimate an input shadow distance system comprising the dual shadow input distance function and the price equations derived from the shadow cost minimization problem. Estimated shadow quantities provide direct estimates of the effect of allocative inefficiency on input usage. One can also easily calculate firm- and time-varying technical inefficiency by decomposing the residuals. We also compute returns to scale and the cost savings obtained by eliminating both types of inefficiency. Our approach is illustrated using a panel of U.S. railroads.
The purpose of this paper is to provide for both life and non-life insurance an assessment of the relative productive performance of French companies. We use parametric and nonparametric approaches to construct a frontier to be used as a yardstick of productive efficiency. Our data basis covers 84 life and 243 non-life companies for the period 1984–1989. The main findings show a high correlation between parametric and nonparametric results and a wide dispersion in the rates of inefficiency across companies. This dispersion can be reduced when controlling for variations in scale, ownership, distribution, reinsurance, and claims ratios.
Proposes a method for the decomposition of total factor productivity change into two distinct elements, technical progress and changes in technical efficiency. The analysis indicates that the slow-down in total factor productivity growth in Yugoslavia in the 1970s was a consequence of both a reduction in the rate of technological progress and of a deterioration in technical efficiency with the latter clearly predominating over deteriorating technological progress. -V.S.Mead
Recent developments in the econometric estimation of multi-output, multi-input distance functions have provided a promising new solution to the single-output restriction implicit in the standard production function. However, a suspicion that regressor endogeneit ma introduce possible simultaneous equations bias has concerned some econometricians. In this paper we show that, under profit maximising behaviour, distance functions face no greater danger from such bias than their production function cousins. Furthermore, we prove that ordinar least squares (OLS) provides consistent estimates of an input distance function under an assumption of cost minimising behaviour. We also prove that OLS provides consistent estimates of an output distance function under an assumption of revenue maximising behaviour. These results are established for the Cobb-Douglas and translog functional forms, which are the two most commonl used functional forms in applied anal ses. Our results provide strong suppor...
Generalized Moments Estimation of a Spatially Correlated Panel Data Model
- V Druska
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Druska, V., and W. C. Horrace. (1999). "Generalized Moments Estimation of a Spatially Correlated Panel Data
Model." University of Arizona, mimeo.
Efficiency and Productivity
- S Grosskopf
Grosskopf, S. (1993). "Efficiency and Productivity." In H. Fried, C. A. K. Lovell, and S. Schmidt (eds.), The
Measurement of Productive Efficiency: Techniques and Applications. New York: Oxford University Press.