Technical Efficiency Model Research Articles

DEKOMPOSISI PERTUMBUHAN PRODUKTIVITAS INDUSTRI MANUFAKTUR INDONESIA: PENDEKATAN STOCHASTIC FRONTIER

Productivity growth can be decomposed into its sources, namely technical changes, technical efficiency changes, and business scale changes. The role of each of these sources is important to be studied because Indonesia experienced a decline in total factor productivity (TFP) growth in 1990-2015 which indicates a productivity issue. The results of previous studies by Margono Sharma (2006) and Ikhsan (2007) regarding the decomposition of productivity growth in the manufacturing industry sector in Indonesia using a stochastic frontier approach, there are still disagreement about the contribution of technical changes and technical efficiency changes to TFP growth. This is thought to be caused by differences in the specifications of the technical efficiency models used, namely Battese Coelli (1992) and Lee Schmidt (1993). The two models have different estimation methods, Battese Coelli (1992) use maximum likelihood estimate, while Lee Schmidt (1993) use non-linear least squares. Hence the scalar parameters that determine the pattern of technical efficiency over time (η in Battese Coelli (1992) and θ in Lee Schmidt (1993)) are different.This study uses data for the period of 2003-2014 in the manufacturing industry sector. The results of this study indicate that different technical efficiency model specifications produce a different relative contribution of TFP growth sources. Therefore, choosing a technical efficiency model to decompose TFP growth should be thorough if the results will be used in important policy making.

Data envelopment analysis for scale elasticity measurement in the stochastic case: with an application to Indian banking

In the nonparametric data envelopment analysis literature, scale elasticity is evaluated in two alternative ways: using either the technical efficiency model or the cost efficiency model. This evaluation becomes problematic in several situations, for example (a) when input proportions change in the long run, (b) when inputs are heterogeneous, and (c) when firms face ex-ante price uncertainty in making their production decisions. To address these situations, a scale elasticity evaluation was performed using a value-based cost efficiency model. However, this alternative value-based scale elasticity evaluation is sensitive to the uncertainty and variability underlying input and output data. Therefore, in this study, we introduce a stochastic cost-efficiency model based on chance-constrained programming to develop a value-based measure of the scale elasticity of firms facing data uncertainty. An illustrative empirical application to the Indian banking industry comprising 71 banks for eight years (1998–2005) was made to compare inferences about their efficiency and scale properties. The key findings are as follows: First, both the deterministic model and our proposed stochastic model yield distinctly different results concerning the efficiency and scale elasticity scores at various tolerance levels of chance constraints. However, both models yield the same results at a tolerance level of 0.5, implying that the deterministic model is a special case of the stochastic model in that it reveals the same efficiency and returns to scale characterizations of banks. Second, the stochastic model generates higher efficiency scores for inefficient banks than its deterministic counterpart. Third, public banks exhibit higher efficiency than private and foreign banks. Finally, public and old private banks mostly exhibit either decreasing or constant returns to scale, whereas foreign and new private banks experience either increasing or decreasing returns to scale. Although the application of our proposed stochastic model is illustrative, it can be potentially applied to all firms in the information and distribution-intensive industry with high fixed costs, which have ample potential for reaping scale and scope benefits.

DEKOMPOSISI PERTUMBUHAN PRODUKTIVITAS INDUSTRI MANUFAKTUR INDONESIA: PENDEKATAN STOCHASTIC FRONTIER

Productivity growth can be decomposed into its sources, namely technical changes, technical efficiency changes, and business scale changes. The role of each of these sources is important to be studied because Indonesia experienced a decline in total factor productivity (TFP) growth in 1990-2015 which indicates a productivity issue. The results of previous studies by Margono Sharma (2006) and Ikhsan (2007) regarding the decomposition of productivity growth in the manufacturing industry sector in Indonesia using a stochastic frontier approach, there are still disagreement about the contribution of technical changes and technical efficiency changes to TFP growth. This is thought to be caused by differences in the specifications of the technical efficiency models used, namely Battese Coelli (1992) and Lee Schmidt (1993). The two models have different estimation methods, Battese Coelli (1992) use maximum likelihood estimate, while Lee Schmidt (1993) use non-linear least squares. Hence the scalar parameters that determine the pattern of technical efficiency over time (η in Battese Coelli (1992) and θ in Lee Schmidt (1993)) are different.This study uses data for the period of 2003-2014 in the manufacturing industry sector. The results of this study indicate that different technical efficiency model specifications produce a different relative contribution of TFP growth sources. Therefore, choosing a technical efficiency model to decompose TFP growth should be thorough if the results will be used in important policy making.

Does Charco-Dam Technology Affect Production Efficiencies? Evidence from Small-Scale Vegetable Farmers in Nzega District, Tanzania

Abstract Water for irrigation is an essential and primary factor influencing crop productivity. However, there is limited information on how availability of irrigation water guarantees efficient use of inputs in farm production, especially for the rainwater harvesting technologies managed at household level. This study employed survey method to collect data from 528 small scale vegetable farmers, randomly selected from 5 wards and 5 villages, among the farmers 220 were adopters of Charco-Dam Technology (CDT) and 308 were non-adopters. Technical Efficiency Model was used to estimate production efficiencies of 528 small-scale vegetable producers, and Propensity Score Matching (PSM) Approach employed to evaluate the influence of adopting charco-dam technology on the production efficiencies of these farmers located in Nzega district, Tanzania. Results from the analysis present the essential intuitions about adoption of CDT and its effects on production efficiencies. It was observed that there was inefficient use of inputs (land-size, labour, quantity of improved seeds, amount of chemical used and amount of fertilizer used) among small-scale vegetable producers in the study area. The inefficiency was basically observed to be caused by household-size, cost of farm labour as well as growing cabbages and scarlet-eggplants. It is further observed that, farming experience, number of farm workers and radio listening behaviour reduced technical inefficiency (i.e., improve technical efficiency). Further analysis using PSM method, found that the adopters of charco-dam technology in the study area significantly increased the efficient use of inputs as compared to non-adopters, and hence realised high yields. This study recommends that, technologies like charco-dam should be encouraged, especially to small-scale farmers in arid and semi-arid areas. Furthermore, experienced farmers should share expertise on the use of inputs, with other less experienced farmers. In line with this, the role of agricultural information on improvement of production efficiency should not be undermined in improving efficient use of inputs. Hence, programmes and intervention that focus on encouraging farmers to listen to radio programmes related to agriculture, particularly those covering specific crop and location, are recommended.

A Novel Hybrid Parametric and Non-Parametric Optimisation Model for Average Technical Efficiency Assessment in Public Hospitals during and Post-COVID-19 Pandemic.

The COVID-19 pandemic has had a significant impact on hospitals and healthcare systems around the world. The cost of business disruption combined with lingering COVID-19 costs has placed many public hospitals on a course to insolvency. To quickly return to financial stability, hospitals should implement efficiency measure. An average technical efficiency (ATE) model made up of data envelopment analysis (DEA) and stochastic frontier analysis (SFA) for assessing efficiency in public hospitals during and after the COVID-19 pandemic is offered. The DEA method is a non-parametric method that requires no information other than the input and output quantities. SFA is a parametric method that considers stochastic noise in data and allows statistical testing of hypotheses about production structure and degree of inefficiency. The rationale for using these two competing approaches is to balance each method’s strengths, weaknesses and introduce a novel integrated approach. To show the applicability and efficacy of the proposed hybrid VRS-CRS-SFA (VCS) model, a case study is presented.

Determinants of Technical Efficiency in Smallholder Corn Crop Farming: Application of Stochastic Frontier Production Function

Agricultural expansion such as corn expansion is often associated with extensification and resulting land acreage loss. Best input practices could increase production and yields and thus potentially reduce land expansion. This study aims to investigate the ability of input, such as land and other factors to affect production in terms of technical efficiency, and investigate the best input practices on corn technical efficiency. Primary and secondary data are used to answer the research objectives. In this study, corn data were used in the 2019 Planting Season. A sample of 120 farmers was taken randomly by applying stratified random sampling that based on land area. Appropriate qualitative and quantitative data analysis methods are used which are distinguished based on their research objectives using the empirical model of production functions, and the technical efficiency model. The results show that all input has an effect to increase corn yield, and support technical efficiency increasing the effect of input using. However, the effect of input using on yields appears to operate through other methods but technical efficiency increases.
 

FOOD CROP PRODUCTIVITY IN NIGERIA: AN ESTIMATION OF TECHNICAL EFFICIENCY AND TECHNOLOGICAL GAP RATIO

<p><strong>Background: </strong>This study analyzed the determinants of food crop productivity in Nigeria. <strong>Objectives: </strong>To describe the socio-economic characteristics of the food crop farmers, estimate the meta-frontier production and compare the technological gap ratio of the various food crop farmers, and then analyzed the determinants of productivity of food crop farmers in the six geopolitical zones of Nigeria. <strong>Methodology: </strong>General Household Survey –Panel Wave 2 from National Bureau of Statistics Abuja, Nigeria was used for this study, and a total of 1,678 food crop farmers were randomly selected from the six geo-political zones in Nigeria. The study employed the use of descriptive statistics, Data Envelopment Analysis (DEA), and Multiple linear regression. <strong>Results: </strong>Most (34.3%) of the farmers were aged between 41-50 years with modal family size of 6 - 10 members. The illiteracy level was high (62.2%) among the various food crop farmers as they had no formal education. The mean technical efficiency and mean Technological Gap Ratios (TGRs) of the food crop farmers were 0.563 and 0.716 respectively. The difference in the mean technical efficiency and meta-production model of food crop farmers showed a huge productivity potential ratio in the various zones of the country. Age (t = 2.99, P= 0.06), plot size square (t = 4.40, P= 0.00), plot ownership (t =2.59, P= 0.01) and access to credit (t = -2.13, P= 0.033) do significantly influence the productivity of the food crop farmers, and were the determinants of food crop productivity in Nigeria. <strong>Implications: </strong>There is the need to enhance capacity of the food crop enterprises to promote food security and economic growth in Nigeria. <strong>Conclusion:</strong> Given the level of technology available, food crop farmers produce lower than the country potential output.</p>

The DEA Method and Its Application Possibilities for Measuring Efficiency in the Public Sector—The Case of Local Public Employment Services

Public Employment Services (PES) are identified as important institutions in the process of improving the match between supply and demand in the labor market, which, despite their importance, still do not achieve the desired efficiency. The indicated problem is partly due to the lack of appropriate evaluation methods for the applied labor market policy instruments. This paper aims to verify the possibility of using the two-stage Data Envelopment Analysis (DEA) method in measuring the efficiency of public sector entities. The authors focused on 39 PES operating in Mazovia province, Poland in 2019. In the first stage, the model of technical efficiency of local PES included six variables (four inputs and two outputs). Only seven PES obtained full efficiency. The inefficiency of analyzed PES varied from about 1% to 80%. In the second stage, the attention focuses on the relationship between true unknown efficiency and its determinants (five environmental variables, both demand and supply oriented). Then, the regression coefficients and confidence intervals showed that three out of five variables influence the efficiency results, the share of the long-term unemployed, the share of the unemployed under 30, and the share of the unemployed over 50 in the total number of unemployed.

Airport Technical Efficiency and Business Model Innovations: A Case of Local and Regional Airports in Thailand

The growth in demand for air transport and budget constraints put the pressure on airport development. Therefore, airports worldwide need to finance themselves and look for better managerial tools to improve airport efficiency. Business models and business model innovations as a means of strategic management are proved to have positive impacts on performance. However, the studies relating to airport business models are scarce and lack scholarly attention, especially in the contexts of small airports. Consequently, to bridge the gap in the literature, the dissertation’s goal is to design business models and propose business model innovations using a case study of local and regional airports in Thailand.

Technical efficiency, intellectual capital efficiency and bank performance in emerging markets: the case of India

PurposeThis paper examines the impacts of technical efficiency and intellectual capital efficiency (ICE) on bank performance in India after controlling other bank-, industry-specific and macroeconomic variables.Design/methodology/approachThe authors use secondary data on listed Indian commercial banks for the period 2005–2018. The authors use data envelopment analysis (DEA) technique-based Malmquist index (MI) to obtain technical efficiency and value-added intellectual coefficient (VAIC) model for computing ICE. System generalized method of moments (GMM) (SGMM) model in a dynamic framework is used to estimate the parameters, which takes into consideration issues of endogeneity, heterogeneity and persistence of bank performance. Further, the authors use quantile regression model to examine whether the impacts of covariates are homogeneous at different locations of the conditional distribution of bank performance.FindingsThe authors find positive impact of technical efficiency and negative influence of market concentration on bank performance. The results of the study support the efficient structure (ES) hypothesis (ESH). The authors observe positive influence of intellectual capital (IC) on bank performance, which indicates the relevance of intellectual resources in enhancing banks' value. Further, the results of quantile regression indicate that the impacts of technical efficiency and ICE are more pronounced at higher quantiles of the conditional distribution of bank performance.Originality/valueThis paper in the Indian context examines the influences of technical efficiency and ICE after controlling bank-, industry-specific and macroeconomic factors.

Stochastic Model of Technical and Economic Efficiency of the Organization of Construction of Housing Facilities

Stochastic Model of Technical and Economic Efficiency of the Organization of Construction of Housing Facilities

A new inverse DEA cost efficiency model for estimating potential merger gains: a case of Canadian banks

Estimating potential gains from mergers is an important strategic decision-making problem. This paper introduces a new inverse data envelopment analysis (DEA) based on a cost efficiency model for estimating potential gains from mergers. There are restructuring scenarios for firms that want to minimize cost. The existing inverse DEA technical efficiency models are not appropriate for estimating merger gains in these situations. It is also shown that the proposed inverse DEA cost efficiency model can reveal more merger gains than the inverse DEA technical efficiency model. The applicability of the proposed method is shown through an application in Canada’s banking sector to determine the required level of inputs and outputs for a merged bank to achieve target levels of cost and technical efficiencies. The results highlight the potential financial gains to improving both technical and cost efficiencies as efficiency-seeking banks increasingly become large and complex institutions through growth, mergers and acquisitions in a financial environment that is being shaped by reforms and technological innovation.

A Novel MIMIC-Style Model of European Bank Technical Efficiency and Productivity Growth

Using Bayesian Monte Carlo methods, we augment a stochastic distance function measure of bank efficiency and productivity growth with indicators of capitalization, return and risk. Our novel Multiple Indicator-Multiple Cause (MIMIC) style model generates more precise estimates of policy relevant parameters such as returns to scale, technical inefficiency, and productivity growth. We find considerable variation in the performance of EU-15 banks over the period 2008-2015. For the vast majority of banks, productivity growth – the sum of efficiency and technical changes - is negative, implying that the industry would benefit from innovation. We show that greater technical efficiency is associated with higher profitability, higher capital, a lower probability of default and lower return volatility.

Do the coupling effects of environmental regulation and R&D subsidies work in the development of green innovation? Empirical evidence from China

Global environmental problems will require the development of new technologies. How will green technology-related public policy affect this process? By exploiting an economic assessing model of green technical innovation efficiency, this paper examines the impact of two different environmental policies (environmental regulation and government subsidy) and their interaction on green technical innovation. The analysis was conducted by collecting innovation-related data on 30 provinces in China over the period 2006–2016. It was found that there are dramatic regional differences in green innovation efficiency in China. The average efficiency in the eastern region is about 0.8, followed by the western region, the central region and the north-eastern region, with 0.4, 0.2 and 0.2, respectively. During the sample period, there was a statistically significant effect of the coupling of the two policy instruments on the innovative efficiency of green technology of China, which is − 0.01. Regulatory policies have a remarkable incentive influence on the performance of green innovation in the central region (0.5) but a restraining effect on the eastern region (− 0.9). R&D subsidies play an essential role in inducing green technology only in the central region (0.2). The paper concludes that both regulative policy and governmental subsidies have failed to achieve the goal of promoting green innovation development in China. These two figures show the average regional efficiency of the two types of innovation with or without environment-related factors using innovation-related data on a panel of 30 provinces in China over the period 2006–2016.

English

In Ethiopia, technical efficiency studies started about three decades ago. These studies have reached different conclusions regarding agriculture efficiency based on technical efficiency scores. This study represents the first attempt to use meta-analysis to examine the mean technical efficiency estimates in agriculture in Ethiopia. The current study employed 45 frontier studies published from 1993 to 2014 for the meta-analysis. The study employed fractional regression to model for the meta-regression analysis. The result of the study shows that there is no publication bias in technical efficiency studies in Ethiopia. The meta-analysis result shows the overall mean technical efficiencies are 68 and 71% based on fixed effect model and random effect model, respectively, suggesting that there are still opportunities for improvement in the efficiency of Ethiopian agriculture. The result also shows that technical efficiency was found to be decreasing over years for studies carried out in all the four regions together (Tigray, Amhara, Oromia, and South). Overall, the study obtained moderator variables (that is, wheat, maize, sample size, food crop, number of inputs) significantly affecting the estimation of the reported mean technical efficiencies in primary studies across the four meta-regression model specifications. The finding of the decline in technical efficiency over years implies that even though there is a scope of improving efficiency in the country, government should also consider side by side introduction and dissemination of new agricultural technologies to reverse the decreasing technical efficiency. This will ultimately boost the country’s agricultural and food production. Besides, the results call upon researchers and academicians to be curious in identifying study-specific attributes, which are essential for modeling farm-level efficiency. Key words: Meta-analysis, technical efficiency, fixed effect and random effect models. &nbsp

How Does the Public Spending Affect Technical Efficiency? Some Evidence from 15 European Countries

The relationship between government size and economic growth has been widely debated. Departing from this issue, we provide an empirical analysis of the impact of government size on technical efficiency. The aim of this paper is to estimate by using a True Random Effect model the impact of public sector’s size and of public expenditure components on 15 European countries’ technical efficiency from 1996 to 2011. Using the total public expenditure as a proxy for the government size we estimate simultaneously national optimal production function and technical efficiency model by controlling for income distribution and institutional quality. Our main findings show that the effect of public sector’s size on efficiency is positive while the type of public expenditures may have both positive and negative impact. In more details, results suggest that social protection, cultural, and health expenditures have a positive effect on technical efficiency, while others have a negative impact. More controversial is the impact of education expenditure, even if a positive effect on efficiency prevails when controlling for heteroscedasticity.

Эволюция Технической Эффективности Российских Регионов в 2011-2016 Годы: Метод Стохастического Анализа Sfa С Пространственными Эффектами (The Evolution of Technical Efficiency of Russian Regions in 2011-2016: SFA Stochastic Analysis Method with Spatial Effects)

Russian Abstract: В препринте на основе стохастического анализа SFA предложены оценки технической эффективности 78 регионов России в 2011-2016 годы, учитывающие пространственные эффекты. Предложена пространственная спецификация модели технической эффективности для регионов. Выявлено общее снижение технической эффективности в регионах. Выделены устойчивые во времени пространственные группы регионов, отличающиеся гомогенностью технической эффективности. Получены выводы о силе влияния инновационных факторов на техническую эффективность. English Abstract: The research of dynamics technical efficiency of the Russian regions in 2011-2016 is conducted in the preprint. The spatial specification of SFA - model of technical efficiency for regions is offered. The General decrease of technical efficiency in the regions was revealed. The spatial groups of regions, stable in time, differing in homogeneity of technical efficiency are allocated. The conclusions about the influence of innovative factors on technical efficiency.

A novel model of costly technical efficiency

This paper presents a novel model of measuring technical inefficiency based on the notion that higher efficiency requires a certain cost. First, we apply the “rational inefficiency hypothesis” of Bogetoft and Hougaard (2003) but we fail to find that it rationalizes our data set of large U.S banks with multiple inputs and outputs. In consequence, we adopt a novel model of profit maximization which explicitly incorporates the cost of technical inefficiency. The cost of inefficiency is treated as unknown and is parametrized as a function of inputs, outputs and decision-making-unit specific fixed effects. More importantly, by showing the model to be equivalent to one in which inefficiency is an arbitrary function of inputs, outputs and the inefficiency cost, we are able to determine optimal directions in the input-output space that would reduce inefficiency. Bayesian techniques organized around Markov Chain Monte Carlo are used to perform the computations and provide statistical inferences as well as useful policy measures to reduce inefficiencies in the U.S banking sector through an examination of different realistic scenarios.

Assessment of Neighborhood and Spillover Effects on Technical Efficiency of Irrigated Rice Farmers

Neighborhood and spillover effects on technical efficiency were investigated among 270 randomly drawn farming households from 18 irrigated villages in Guimba, Nueva Ecija, Philippines, using a two-step procedure. In the first stage, stochastic frontier production function was used to estimate farmer’s technical efficiency; in the second stage, appropriate spatial econometric models of technical efficiency were estimated. Spatial econometric models adopted in this study detected spatial dependency on technical efficiency in the error term of the spatial model across seasons and locations, which can be associated with unobserved factors that similarly influence farmers’ technical efficiencies at the same time. Farm size, income, and regular contact and consultation with agricultural technicians were found to significantly affect technical efficiency. Results of the spatial regression show that owner-cultivator status and loamy soil are associated with increased technical efficiency. The local government of Guimba can use findings of this study in formulating agricultural policies and implementing essential interventions to improve the technical efficiency of rice farmers.

Endogeneity in panel data stochastic frontier model with determinants of persistent and transient inefficiency

In this paper we consider a stochastic frontier panel data model in which the random firm-effects are introduced along with the persistent and transient technical inefficiency. Moreover, we allow determinants of both persistent and transient inefficiency, and allow both firm-effects and persistent inefficiency to be correlated with the regressors. We discuss a two-step procedure, which applies the MLE and the system NLS approach, to estimate parameters of the model and prediction of persistent and transient technical efficiency. Finally, we demonstrate our approach by applying it to the U.S. power generating plant data.