showing 6 related works from this author
Disentangling Tax Evasion from Inefficiency in Firms Tax Declaration: An Integrated Approach
2019
In this article we present a new methodology to support fiscal monitoring by the Italian Revenue Agency (IRA) with the aim of improving current taxpayers fiscal compliance and fighting tax evasion within small and medium enterprises. In fact, given the methodology behind the Sector Studies (Studi di Settore - SdS) system, there is room for firms to implement tax evasion strategies by simply adjusting revenues (and costs) toward an estimated average threshold (known ex-ante), the so called "presumptive" revenues, and achieving the fiscal "congruity" status. By estimating a production function through stochastic frontier analysis we avoid estimating the average threshold know ex-ante and can …
Fitting generalized linear models with unspecified link function: A P-spline approach
2008
Generalized linear models (GLMs) outline a wide class of regression models where the effect of the explanatory variables on the mean of the response variable is modelled throughout the link function. The choice of the link function is typically overlooked in applications and the canonical link is commonly used. The estimation of GLMs with unspecified link function is discussed, where the linearity assumption between the link and the linear predictor is relaxed and the unspecified relationship is modelled flexibly by means of P-splines. An estimating algorithm is presented, alternating estimation of two working GLMs up to convergence. The method is applied to the analysis of quit behavior of…
Semiparametric stochastic frontier models: A generalized additive model approach
2017
Abstract The choice of the functional form of the frontier into a stochastic frontier model is typically neglected in applications and canonical functions are usually considered. This paper introduces a semiparametric approach for stochastic frontier estimation that extends previous works based on pseudo-likelihood estimators allowing flexibility in model selection and capability of imposing monotonicity and concavity constraints. For these purposes the present work introduces a generalized additive framework that moreover permits to model the influence of contextual/environmental factors to the hypothesized production process by the relative extension given by generalized additive models f…
Stochastic frontier models using R
2020
Abstract The production function is usually assumed to specify the maximum output obtainable, from a given set of inputs, describing the boundary or frontier of the obtainable output from each feasible combination of input; it relates the production process of individual units to the efficient border of the production possibilities. The measure of the distance of each unit from the border is the most immediate way to assess its (in)efficiency. However, the production function is not generally known, but it has only a set of information on each production unit and it is therefore essential to develop techniques to estimate the production frontier. Starting from the packages already developed…
How efficient is maize production among smallholder farmers in Zimbabwe? A comparison of semiparametric and parametric frontier efficiency analyses
2018
The controversial Fast Track Land Reform Programme in Zimbabwe that redistributes commercially-owned farmland to smallholder households has caused concerns about the efficiency of agricultural prod...
Flexible Estimation of Heteroskedastic Stochastic Frontier Models via Two-step Iterative Nonlinear Least Squares
2019
Despite its importance, the monotonicity condition is typically overlooked in stochastic frontier analysis. This article illustrates a straightforward and useful method for the estimation of semiparametric stochastic frontier models imposing such constraint and incorporating exogenous inefficiency effects exploiting the scaling property. An iterative estimation algorithm based on nonlinear least squares is developed and the behavior of the proposed procedure is investigated through a set of Monte Carlo experiments comparing its finite sample properties with those of available alternatives. The simulation results highlight very good performance of the new algorithm which outperforms the comp…