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排序方式: 共有191条查询结果,搜索用时 171 毫秒
121.
Information Accumulation in Development 总被引:1,自引:0,他引:1
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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. 相似文献
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Simonetti Biagio Antolini Fabrizio Castellano Rosella Gallo Michele González-Rodríguez María Rosario Giusti Antonio Sarnacchiaro Pasquale 《Quality and Quantity》2020,54(5-6):1385-1386
Quality & Quantity - 相似文献
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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... 相似文献
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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. 相似文献
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Silvia Salini Andrea Cerioli Fabrizio Laurini Marco Riani 《Revue internationale de statistique》2016,84(1):99-127
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. 相似文献