Analysis of productivity in the Health Care Centers of the Community of Madrid (Spain) 2015-2017

The main objective of this work has focused on extending the existing literature on the analysis of total factor productivity of the Health Care Centers (HCC) of the Community of Madrid (Spain) in the period 2015-2017, with two important contributions; the application and comparison of the Malmquist indices with two robust methodologies such as the Hicks-Moorsteen and Färe Primont indices which, except for error, have not been previously used in this sector and the regional scope, which has been scarcely analyzed. The main results reveal decreases in HC productivity due to the three proposed methodologies. These decreases range between 4.90% and 0.25% for the Färe-Primont and Hicks-Moorsteen indices respectively between 2015/17 in average terms. Convergence analyses confirm that this takes place in the case of the Malmquist and Hicks-Moorsteen proposals.

INFERENCE IN DYNAMIC, NONPARAMETRIC MODELS OF PRODUCTION: CENTRAL LIMIT THEOREMS FOR MALMQUIST INDICES

The Malmquist index gives a measure of productivity in dynamic settings and has been widely applied in empirical work. The index is typically estimated using envelopment estimators, particularly data envelopment analysis (DEA) estimators. Until now, inference about productivity change measured by Malmquist indices has been problematic, including both inference regarding productivity change experienced by particular firms as well as mean productivity change. This paper establishes properties of a DEA-type estimator of distance to the conical hull of a variable returns to scale production frontier. In addition, properties of DEA estimators of Malmquist indices for individual producers are derived as well as properties of geometric means of these estimators. The latter requires new central limit theorem results, extending the work of Kneip, Simar, and Wilson (2015, Econometric Theory 31, 394–422). Simulation results are provided to give applied researchers an idea of how well inference may work in practice in finite samples. Our results extend easily to other productivity indices, including the Luenberger and Hicks–Moorsteen indices.

Analyzing Africa's Total Factor Productivity Trends

Using data envelopment analysis (DEA), the authors investigate the productivity changes of 42 African countries by computing the Malmquist productivity indices. Subsequently, the measured Malmquist productivity indices become the dependent variables of a pooled truncated regression. The point estimates of the Malmquist indices indicate that TFP improved at an annual rate of 1.97% over the period 1992-2007. The decomposition of TFP shows that the major contribution of TFP growth is technological progress. Nevertheless, technical efficiency also appears to be trending upwards. Therefore, these results suggest that contrary to the dominant view in previous studies, Africa's TFP since the early 1990s has been accompanied by positive technological change rather than stagnation. The second stage results suggest that improving the quality of human capital and FDI not only augments the quality of labor, but also indirectly improves TFP. Regression results also show that an increase in openness positively affects TFP growth as this facilitates adoption of more efficient techniques of production.

Efficiency analysis of Indian banking industry over the period 2008–2017 using data envelopment analysis

Purpose The purpose of this paper is to estimate the relative efficiencies of banks of the Indian domestic banking sector by employing various models of data envelopment analysis (DEA) using the panel data of the recent decade (2008–2017). The paper provides a comparative analysis of these models based on the efficiency outputs. It compares the performance of banks based on their ownership and sizes and studies the decade-long trend of productivity using Malmquist indices. Design/methodology/approach This paper estimates overall technical, pure technical and scale efficiencies of 21 public sector banks and 17 private banks. It compares the descriptive statistics of efficiency estimates found out through 18 different DEA models and compares them using two non-parametric statistical tests. It studies the difference in efficiencies based on ownership and size by applying the same statistical tests. It employs the Malmquist index method to study the technological and technical progress in the banks’ productivity over the decade of FY 2008–FY 2017. Findings During FY 2016–2017, only 9 out of 38 banks were overall technically efficient with the whole sample having a mean overall technical inefficiency of 5 percent with scale inefficiency contributing more than pure technical inefficiency. The comparative study ascertains that private sector and public sector banks (PSBs) possess efficiencies that are similar based on super-efficiency slack-based model – variable returns to scale and non-oriented, a model that the authors argue to be the most suitable for the real-life business banking scenarios whereas the private sector banks possess better efficiency than the PSBs. The Malmquist indices prove that private sector banks have a higher increase in productivity based on both technological progress and efficiency improvements whereas PSBs had a loss of efficiency and comparatively less improvement in technology. Research limitations/implications This study has a limitation of choosing a single model of inputs and outputs. Improved insights can be drawn by employing more models based on different inputs and outputs. Further, relevance of each input and output can be examined using a regression-based feedback mechanism (Ouenniche and Carrales, 2018). The influence of environmental factors on the efficiencies can be studied using second-stage regression models and the relationship between efficiency scores and financial ratios can be examined. Originality/value This study is based on the panel data of the recent decade (2008–2017) and provides insights into the efficiency scenario of the Indian banking industry and how it changed over the past decade, to the leadership of banks, the banking regulators and the policy makers. The comparative analysis of DEA models based on a sample of Indian banks is first of its kind in the Indian context and helps the researchers to select an appropriate model and delve into further research on the same.

TECHNICAL CHANGE DIRECTIONS OF CHINA’S GRAIN PRODUCTION: APPLICATION OF THE BIAS-CORRECTED MALMQUIST INDICES

This paper aims at measuring productivity and efficiency of China’s three most important grain crops–rice, wheat and maize–as well as identifying the main directions of technical change prevailing in their production. The bias-corrected Malmquist production indices are employed to measure the technical changes (TCs) in terms of input-saving or input-using in China’s grain production, by using provincial aggregate data obtained from the National Farm Production Costs and Returns Survey. The research covers the period of 2003–2013. Application of the bias-corrected Malmquist index showed a labor-saving technical change against all the remaining inputs for the three crops under analysis. The highest frequencies of fertilizer- and machinery-using, labor-saving technical changes were observed for wheat farming. Therefore, a reduction in labor intensity should be the most promising for wheat if compared with rice and maize.

Analyzing Africa's Total Factor Productivity Trends

Using data envelopment analysis (DEA), the authors investigate the productivity changes of 42 African countries by computing the Malmquist productivity indices. Subsequently, the measured Malmquist productivity indices become the dependent variables of a pooled truncated regression. The point estimates of the Malmquist indices indicate that TFP improved at an annual rate of 1.97% over the period 1992-2007. The decomposition of TFP shows that the major contribution of TFP growth is technological progress. Nevertheless, technical efficiency also appears to be trending upwards. Therefore, these results suggest that contrary to the dominant view in previous studies, Africa's TFP since the early 1990s has been accompanied by positive technological change rather than stagnation. The second stage results suggest that improving the quality of human capital and FDI not only augments the quality of labor, but also indirectly improves TFP. Regression results also show that an increase in openness positively affects TFP growth as this facilitates adoption of more efficient techniques of production.

EFFICIENCY AND PRODUCTIVITY CHANGE IN FIELD CROP AND MILK FARMS IN LUBLIN PROVINCE IN 2014-2016

The aim of the study was assessment of efficiency and productivity of farms in the Lublin province in the years 2014-2016. The analysis was based on the Data Envelopment Analysis (DEA) model oriented on inputs and Malmquist indices with its components. The calculations were made for medium-sized field and dairy farms that continuously collected data for the FADN system during the period under consideration. In our research all efficiency indicators for dairy farms were larger than for field crop farms. In the years 2014-2016, the average technical efficiency of dairy farms was 0.752, which means that in those farms it is possible to reduce inputs on average by 25% and the value of production will remain at the same level. In the case of field crop farms, inputs should be limited by 33%. The applied decomposition of calculated Malmquist indices allowed to define what factors influenced changes in productivity.

Determinants of the Productivity Change for the Banking Sector in Egypt

This study aims to undertake an evaluation and examination of the productivity change of the Egyptian banking sector, using a novel data set which covers 14 banks operating in the Egyptian market from 1997 to 2013. We use a non-parametric approach Data Envelopment Analysis (DEA) based analysis to investigate the productivity change in the Egyptian banking sector. Input-oriented Malmquist indices of productivity change are estimated with DEA to measure total factor productivity (TFP) change. The TFP changes are decomposed into the product of technological change and technical efficiency change (catch up). In the second stage, potential determinants of productivity change are studied using a regression model. We find that the Egyptian banking sector as a whole shows a productivity regress of 0.9 per cent per year, which is mainly due to the technological improvements. The estimated regression model identifies some variables which significantly influence the productivity of banks in Egypt. The banks with higher loans to deposit ratio and higher returns on equity have higher productivity growth reflecting on their strong strategic and managerial skills. The size of bank seems to be associated with an increase in productivity. The maturity of a bank (measured by age) is associated with higher productivity. The net interest margin (NIM) and non-interest expense over total assets (NIETA) variables do not seem to be affecting the productivity of banks. Surprisingly, our results reveal that the financial crisis is negatively and statistically insignificant which means there are no effects on the Egyptian banks.

Efficiency of Microfinance Institutions in India: Evidence from Malmquist Indices

The current study constructs a balanced panel data set on microfinance institutions in India during 2008-2012 and employs a data envelopment analysis to examine the efficiency of the institutions. The results show a decrease of 0.3 per cent in productivity during the study period. In addition, the technical efficiency change, pure efficiency change and scale efficiency attributes to the overall inefficiency of the institutions. Also, profit institutions are more efficient than non-profit institutions. Results from Tobit regressions indicate that the impact of population and GDP on the efficiency of the institutions is significant, but that of the number of microfinance institutions is not.