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The Impact of Model Choice on Estimates of Regional TFP
International Regional Science Review ( IF 1.8 ) Pub Date : 2018-02-01 , DOI: 10.1177/0160017618754311
Thomas Schatzer 1, 2 , Matthias Siller 1, 2 , Janette Walde 3 , Gottfried Tappeiner 1
Affiliation  

A large range of different approaches to determine a region’s total factor productivity (TFP) is currently used in the literature. As there is no generally recognized method, it is an important issue whether different approaches produce comparable results or whether results depend heavily on the chosen method. By employing a data set of 220 European regions over the period from 1990 to 2007, the present work compares a set of TFP estimation approaches and examines whether regional TFP levels and TFP growth rates obtained from the various approaches differ considerably from each other. More specifically, the neoclassical accounting approach, the cross-section approach, the pooled panel approach, and the fixed-effects approach are investigated. Furthermore, this article proposes an extension of the fixed-effects approach that allows estimation of both regional TFP levels and region-specific, long-term TFP growth rates in a single estimation procedure. The results clearly demonstrate that the choice between the examined approaches has an essential impact on estimation results for both TFP levels and TFP growth rates. From the apparent differences between the obtained results, it is reasonable to expect that follow-up analyses based on TFP estimates, for example, studies investigating the determinants of regional TFP, are affected by the model choice to a considerable extent. Therefore, it is important to examine whether one model is superior to others or whether it is only up to the scholar to choose a model.

中文翻译:

模式选择对区域全要素生产率估算的影响

当前,文献中使用了各种各样的方法来确定一个地区的全要素生产率(TFP)。由于没有公认的方法,因此重要的问题是,不同的方法是否产生可比较的结果,或者结果是否严重取决于所选的方法。通过使用1990年至2007年期间220个欧洲地区的数据集,本工作比较了一组TFP估算方法,并检验了通过各种方法获得的区域TFP水平和TFP增长率是否存在显着差异。更具体地说,研究了新古典会计方法,横截面方法,合并面板方法和固定效应方法。此外,本文提出了固定效应方法的扩展,该方法允许在单个估计过程中估计区域TFP水平和特定区域的长期TFP增长率。结果清楚地表明,在所考察的方法之间进行选择对TFP水平和TFP增长率的估计结果均具有重要影响。从获得的结果之间的明显差异,可以合理地预期基于TFP估计值的后续分析(例如,研究区域TFP决定因素的研究)会在很大程度上受到模型选择的影响。因此,重要的是要检查一种模型是否优于其他模型,还是仅由学者来选择模型。单一估算程序中的长期TFP增长率。结果清楚地表明,在所考察的方法之间进行选择对TFP水平和TFP增长率的估计结果均具有重要影响。从获得的结果之间的明显差异,可以合理地预期基于TFP估计的后续分析(例如,调查区域TFP决定因素的研究)会在很大程度上受到模型选择的影响。因此,重要的是要检查一种模型是否优于其他模型,还是仅由学者来选择模型。单一估算程序中的长期TFP增长率。结果清楚地表明,在所考察的方法之间进行选择对TFP水平和TFP增长率的估计结果都具有重要影响。从获得的结果之间的明显差异,可以合理地预期基于TFP估计值的后续分析(例如,研究区域TFP决定因素的研究)会在很大程度上受到模型选择的影响。因此,重要的是要检查一种模型是否优于其他模型,还是仅由学者来选择模型。从获得的结果之间的明显差异,可以合理地预期基于TFP估计值的后续分析(例如,研究区域TFP决定因素的研究)会在很大程度上受到模型选择的影响。因此,重要的是要检查一种模型是否优于其他模型,还是仅由学者来选择模型。从获得的结果之间的明显差异,可以合理地预期基于TFP估计值的后续分析(例如,研究区域TFP决定因素的研究)会在很大程度上受到模型选择的影响。因此,重要的是要检查一种模型是否优于其他模型,还是仅由学者来选择模型。
更新日期:2018-02-01
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