The Use of Bootstrapped Malmquist Indices to Reassess Productivity Change Findings: An Application to a Sample of Polish Farms

The paper assesses the extent to which sampling variation affects findings about Malmquist productivity change derived using Data Envelopment Analysis (DEA), in the first stage calculating productivity indices and in the second stage investigating the farm-specific change in productivity. Confidence intervals for Malmquist indices are constructed using Simar and Wilson's (1999) bootstrapping procedure. The main contribution of the paper is to account in the second stage for the information provided by the bootstrap in the first stage. The DEA standard errors of the Malmquist indices given by bootstrapping are employed in an innovative heteroscedastic panel regression, using a maximum likelihood procedure. The application is to a sample of 250 Polish farms over the period 1996-2000. The confidence interval's results suggest that contrary to what was reported by previous studies, the second half of 1990s for Polish farms was characterised not so much by productivity regress but rather by stagnation. As for the determinants of farm productivity change, we find that the integration of the DEA standard errors in the second-stage regression is significant in explaining a proportion of the variance in the error term. Although our heteroscedastic regression results differ with those from the standard Ordinary Least Squares, in terms of significance (fewer parameters are significant in our heteroscedastic regression) and sign (of the parameter of the share of other income in total income), they are consistent with theory and previous research. Family farms concentrating on farming experienced larger productivity progress than farms with hired labour and income diversification.productivity, Malmquist, bootstrapping, second-stage regression, Poland, Productivity Analysis,

Productivity growth in electric energy retail in Colombia. A bootstrapped malmquist indices approach

This paper offers a productivity growth estimate for electric energy commercialization firms in Colombia, using a non-parametric Malmquist bootstrap methodology. The estimation and methodology serve two main purposes. First, in Colombia commercialization firms are subject to a price-cap regulation scheme, a non-common arrangement in the international experience for this part of the industry. Therefore the paper’s result suggest an estimate of the productivity factor to be used by the regulator, not only in Colombia but in other countries where commercialization is a growing part of the industry (renewable energy, for instance). Second, because of poor data collection from regulators and firms themselves, regulation based on a single estimation of productivity seems inappropriate and error-prone. The nonparametric Malmquist bootstrap estimation allows an assessment of the result in contrast to a single one estimation. This would open an opportunity for the regulator to adopt a narrower and more accurate productivity estimation or override an implausible result and impose a productivity factor in the price-cap to foster the development of the industry.DEA, Malmquist, Productivity growth, Bootstrap, Electricity commercialization,Colombia

The Role of Environmental Factors in Growth Accounting: A Nonparametric Analysis

This paper explores a relatively new methodology, the directional distance function method, to analyze productivity growth. The method explicitly evaluates the role undesirable outputs of the economy, such as carbon dioxide and other green-house gases, have on the frontier production process which we specify as a piece-wise linear and convex boundary function. We decompose productivity growth into efficiency change (catching up) and technology change (innovation). We test the statistical significance of the estimates using recently developed bootstrap methods. We also explore implications for growth of total factor productivity in the OECD and Asian economies.

A two-stage productivity analysis using bootstrapped Malmquist index and quantile regression

This paper examines the effects of farm characteristics and government policies in enhancing productivity growth for a sample of Greek farms, using a two-stage procedure. In the 1st-stage, non-parametric estimates of Malmquist index and its decompositions are computed, while a bootstrapping procedure is applied to provide their statistical precision. In the 2nd-stage, the productivity growth estimates are regressed on various covariates using a bootstrapped quantile regression approach. The effect that the covariates exert on productivity growth of the average producer is analyzed, as well as the marginal effect of a given covariate for individuals at different points in the conditional productivity distribution. The results indicate that there exists large disparity of the covariates effect on productivity growth at different quantiles. Thus, policy suggestions should take into account the productivity distribution involved, as well as the selected policy objectives.Malmquist productivity index, quantile regression, bootstrap, Research Methods/ Statistical Methods, C14, C21, D24,

Productivity, Technical and Efficiency Change in Singapore's Services Sector, 2005 to 2008

The current study was motivated by statements made by the Economic Strategies Committee that Singapore's recent productivity levels in services were well below countries such as the US, Japan and Hong Kong. Massive employment of foreign workers was cited as the reason for poor productivity levels. To shed more light on Singapore's falling productivity, a nonparametric Malmquist productivity index was employed which provides measures of productivity change, technical change and efficiency change. The findings reveal that growth in total factor productivity was attributed to technical change with no improvement in efficiency change. Such results suggest that gains from TFP were input-driven rather than from a 'best-practice' approach such as improvements in operations or better resource allocation.Efficiency, productivity; Malmquist indices; Singapore services

Productivity Growth, Technical Efficiency and Technical Change on Minnesota Farms

Changes and trends in farm productivity have been of intense interest to many involved with agriculture. This study used data envelopment analysis (DEA) to estimate the output-oriented Malmquist total factor productivity (TFP) index from panel data for 1993-2006 for farms in Southern Minnesota. Bootstrap methods were used to estimate confidence intervals for the productivity, efficiency change and technical change indices. The model included three inputs (labor, land and immediate expenditures) and six outputs (corn, soybean, milk, hog, beef, and nonfarm income). Productivity growth was found to be positive during the period, with an average annual productivity growth of 6.6 percent. However, TFP growth has been slowing down in recent years and indeed negative in 2000/01, 2002/03 and 2005/06. In the second stage of the analysis, the significance of various factors that might affect farm performance was estimated. Farm size (as measured by the log of farm income) was correlated with higher productivity which may help explain the increase in farm size in Minnesota farms in recent years. Government subsidies were found to have a negative impact on farm performance supporting the argument that agricultural subsidies may create disincentives for farmers to improve their productivity and efficiency. A higher nonfarm income ratio was positively related with higher productivity growth. A higher proportion of hired labor has a negative effect implying family labor is more crucial than hired labor in improving productivity.total factor productivity, farms, Malmquist index, data envelopment analysis, DEA, bootstrap, government subsidies, Farm Management, Productivity Analysis, Q12, C14,

Forecasting the Malmquist Productivity Index

The Malmquist Productivity Index (MPI) suggests a convenient way of measuring the productivity change of a given unit between two consequent time periods. Until now, only a static approach for analyzing the MPI was available in the literature. However, this hides a potentially valuable information given by the evolution of productivity over time. In this paper, we introduce a dynamic procedure for forecasting the MPI. We compare several approaches and give credit to a method based on the assumption of circularity. Because the MPI is not circular, we present a new decomposition of the MPI, in which the time-varying indices are circular. Based on that decomposition, a new working dynamic forecasting procedure is proposed and illustrated. To construct prediction intervals of the MPI, we extend the bootstrap method in order to take into account potential serial correlation in the data. We illustrate all the new techniques described above by forecasting the productivityt index of 17 OCDE countries, constructed from their GDP, labor and capital stock.Malmquist Productivity Index, circularity efficiency, smooth bootstrap

Productivity and Quality-Environmental Changes in Marketing Co-operatives: An Analysis on the Horticultural Sector

The object of the present paper is to analyse productivity incorporating quality-environmental changes in marketing co-operatives. Firstly, it reviews competitiveness factors in the current European agri-food market, especially in relation to the fruit and vegetables sector. Secondly, the productivity trend is studied empirically using nonparametric methods (Malmquist indices) and taking as reference panel data of Andalusian horticultural co-operatives for the period 1994-2001. For this purpose productivity is decomposed into technological change, efficiency and quality-environmental change. Additionally, the correlation of these results with other economic variables is analysed. The indicators obtained show a relevant increase in efficiency for the period under study and a high relationship between the results and product quality-environmental improvement.productivity, quality-environment, efficiency, marketing co-operative, horticultural sector, Agribusiness, Productivity Analysis, D24, Q13, Q21, L15,

SENSITIVITY ANALYSIS OF EFFICIENCY AND MALMQUIST PRODUCTIVITY INDICES: AN APPLICATION TO SPANISH SAVINGS BANKS

Hypothesis testing and statistical precision in the context of nonparametric efficiency and productivity measurement have been investigated since the early 1990s. Recent contributions focus on this matter through the use of resampling methods?i.e., bootstrapping techniques. However, empirical evidence is still practically non-existent. This gap is more noticeable in the case of banking efficiency studies, where the literature is immense. In this paper, we explore productivity growth and productive efficiency for Spanish savings banks over the (initial) post-deregulation period 1992?1998 using Data Envelopment Analysis (DEA) and bootstrapping techniques. Results show that productivity growth has occurred, mainly due to improvement in production possibilities, and that mean efficiency has remained fairly constant over time. The bootstrap analysis yields further evidence, as for many firms productivity growth, or decline, is not statistically significant. With regard to efficiency measurement, the bootstrap reveals that the disparities in the original efficiency scores of some firms are lessened to a great extent. Desde principios de los años noventa ha habido avances notables en el contraste de hipótesis dentro del contexto de la medición de la eficiencia y la productividad mediante técnicas paramétricas. Las contribuciones más recientes han enfocado el tema a través de métodos de remuestreo -conocidos en la literatura como técnicas bootstrap-. Sin embargo, prácticamente no ha habido aplicaciones, algo también patente en el estudio de la eficiencia de la empresa bancaria. En este artículo, analizamos la eficiencia productiva y el crecimiento de la productividad de las cajas de ahorro españolas durante el periodo 1992-1998 a través de técnicas no paramétricas (DEA) y de técnicas bootstrap, con el fin de poder realizar inferencia estadística. Los resultados indican que la productividad ha aumentado, principalmente debido a una mejora en las posibilidades de producción, mientras que la eficiencia promedio no ha variado sustancialmente. El análisis bootstrap revela que, en el caso de la productividad, para muchas empresas su aumento o disminución no es estadísticamente significativo. En cuanto a la eficiencia, muestra que las diferencias entre empresas individuales se reducen de manera notable cuando consideramos intervalos de confianza.bootstrap, data envelopment analysis, efficiency, productivity, savings bank bootstrap, técnicas no paramétricas, eficiencia, productividad, cajas de ahorro.

Efficiency and productivity of Singapore’s manufacturing sector 2001-2010: An analysis using Simar and Wilson’s (2007) bootstrapped truncated approach

This paper seeks to explain the lagging productivity in Singapore’s manufacturing noted in the statements of the Economic Strategies Committee Report 2010. Two methods are employed: the Malmquist productivity to measure total factor productivity change and Simar and Wilson’s (J Econ, 136:31–64, 2007) bootstrapped truncated regression approach. In the first stage, the nonparametric data envelopment analysis is used to measure technical efficiency. To quantify the economic drivers underlying inefficiencies, the second stage employs a bootstrapped truncated regression whereby bias-corrected efficiency estimates are regressed against explanatory variables. The findings reveal that growth in total factor productivity was attributed to efficiency change with no technical progress. Most industries were technically inefficient throughout the period except for ‘Pharmaceutical Products’. Sources of efficiency were attributed to quality of worker and flexible work arrangements while incessant use of foreign workers lowered efficiency