since the difference in productivity growth rates in different provinces is a result of regional inequality, efficiency criteria in the development of regional-scale agricultural activities is beneficial. therefore it is important that long-term movements in the provinces to identify differences in productivity levels to take effective measures such as investment more in infrastructure, researc...

This paper analyses the productivity growth of the SUMA tax offices located in Spain evolved between 2004 and 2006 by using Malmquist Index based on Data Envelopment Analysis (DEA) models. It goes a step forward by smoothed bootstrap procedure which improves the quality of the results by generalising the samples, so that the conclusions obtained from them can be applied in order to increase pro...

We propose a dynamic DEA model involving network structure in each period within the framework of a slacks-based measure approach. We have previously published the network SBM (NSBM) and the dynamic SBM (DSBM) models separately. Hence, this article is a composite of these two models. Vertically, we deal with multiple divisions connected by links of network structure within each period and, hori...

Recent literature has started to explore the use of nonparametric methods to estimate alphas and betas in the conditional CAPM and conditional multifactor models. This paper explores two of the most recent contributions and proposes a third method. Nonparametric estimation of factor modeling involves choosing techniques which are different both technically and in application, but common in the ...

This research analyses the relationship between efficiency, innovation and seasonality of Spanish coasts for a five-year period (2015–2019). First all, nexus level efficiency changes in productivity, driven by improvements and/or is determined using Data Envelopment Analysis Malmquist Index. Second, this paper proposes synthetic index to measure assess its connection with innovation, cross appr...

The problem of system identification from a time series of measurements is solved by using nonparametric additive models. Having only few structural information about the system, a nonparametric approach may be more appropriate than a parametric one for which detailed prior knowledge is needed. Based on nonparametric regression, the functions in the additive models are estimated by a penalized ...