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.
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Paper provided by Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie) in its series Working Papers. Serie EC with number
2002-30.
Find related papers by JEL classification: C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General C61 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Optimization Techniques; Programming Models; Dynamic Analysis G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Mortgages L5 - Industrial Organization - - Regulation and Industrial Policy
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