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摘要翻译：
我们对来自意大利的反事实方案评估进行了广泛的元回归分析，考虑了关于企业和创新政策的出版和灰色文献。我们指定了一个多水平的模型，用于发现正效应估计的概率，也评估了由合著网络可能引起的相关性。我们发现，积极效应的可能性是相当大的，尤其是对较弱的公司和公共项目直接针对的结果。然而，从长远来看，这些政策不太可能引发变革。
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英文标题：
《Evaluating Public Supports to the Investment Activities of Business
Firms: A Multilevel Meta-Regression Analysis of Italian Studies》
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作者：
Chiara Bocci, Annalisa Caloffi, Marco Mariani, Alessandro Sterlacchini
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最新提交年份：
2020
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分类信息：
一级分类：Statistics 统计学
二级分类：Applications 应用程序
分类描述：Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学，教育学，流行病学，工程学，环境科学，医学，物理科学，质量控制，社会科学
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一级分类：Economics 经济学
二级分类：Econometrics 计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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英文摘要：
We conduct an extensive meta-regression analysis of counterfactual programme evaluations from Italy, considering both published and grey literature on enterprise and innovation policies. We specify a multilevel model for the probability of finding positive effect estimates, also assessing correlation possibly induced by co-authorship networks. We find that the probability of positive effects is considerable, especially for weaker firms and outcomes that are directly targeted by public programmes. However, these policies are less likely to trigger change in the long run.
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PDF链接：
https://arxiv.org/pdf/2006.01880
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