Tax breaks for incentive pay,productivity and wages: Evidence from a reform in Italy

This paper analyses the impact of a tax break on incentive pay (introduced in Law n. 208/2015) on labour productivity and average wages in Italian firms. We use a unique source of firm-level information drawn from a large representative survey of Italian firms merged with the ORBIS archive. By applying difference-in-differences methods, we obtain the following results. First, the tax break has a positive effect on both labour productivity and average wages, although the positive effect on average wages is not confirmed by robustness tests. Second, productivity impacts are mainly driven by family firms in northern regions, where firms benefit from the more dynamic business environment in which they operate. These results take into account unobserved heterogeneity and endogeneity issues.     

Special issue: Qualitative and quantitative methods in tourism research

Quality & Quantity -     

Disciplinary homogeneity in university departments following the Gelmini law: an exploratory analysis through social networks

Quality & Quantity - The aim of this work is to evaluate the implementation of the Gelmini law; a law that has reorganized the universities into departments in order to create homogeneous...     

Comparing predictive accuracy in small samples using fixed-smoothing asymptotics

We consider fixed-smoothing asymptotics for the Diebold and Mariano (Journal of Business and Economic Statistics, 1995, 13(3), 253–263) test of predictive accuracy. We show that this approach delivers predictive accuracy tests that are correctly sized even when only a small number of out-of-sample observations is available. We apply the fixed-smoothing asymptotics to the Diebold and Mariano test to evaluate the predictive accuracy of the Survey of Professional Forecasters (SPF) and of the European Central Bank Survey of Professional Forecasters (ECB SPF) against a simple random walk. Our results show that the predictive abilities of the SPF and of the ECB SPF were partially spurious.     

Reliable Robust Regression Diagnostics

Motivated by the requirement of controlling the number of false discoveries that arises in several application fields, we study the behaviour of diagnostic procedures obtained from popular high‐breakdown regression estimators when no outlier is present in the data. We find that the empirical error rates for many of the available techniques are surprisingly far from the prescribed nominal level. Therefore, we propose a simulation‐based approach to correct the liberal diagnostics and reach reliable inferences. We provide evidence that our approach performs well in a wide range of settings of practical interest and for a variety of robust regression techniques, thus showing general appeal. We also evaluate the loss of power that can be expected from our corrections under different contamination schemes and show that this loss is often not dramatic. Finally, we detail some possible extensions that may further enhance the applicability of the method.     

Trade policy, biotechnology and grain self-sufficiency in China

Over the past 20 years the growth of China's agricultural economy has been extraordinary. However, it seems unlikely that China will maintain self‐sufficiency in grains by 2005 without substantial intervention. We develop a CGE model to assess the options available to Chinese policy makers. We compare the welfare effects of import tariffs and domestic support, and explore the potential of biotechnology as a means to achieve self‐sufficiency through improvements in agricultural productivity. Our results indicate that the price interventions that would be required to maintain China's desired self‐sufficiency ratios are considerable, and are unlikely to be compatible with WTO accession. The productivity improvements required are also significant, and likely beyond the current potential of biotechnology.