Productivity Races I: Are Some Productivuty Measures Better Than Others?
Productivity Races I: Are Some Productivuty Measures Better Than Others?
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生产力竞赛一：某些生产力衡量标准是否优于其他衡量标准？
DOI：
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发表时间：
1997
期刊：
影响因子：
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通讯作者：
Douglas W. Dwyer
中科院分区：
文献类型：
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作者：
Douglas W. Dwyer
在这项研究中，我们在工厂层面构建了12种不同的生产率衡量标准，并测试了哪些生产率衡量标准与直接经济绩效衡量标准最密切相关。我们首先考察这些指标与各种利润指标的关联度有多高。然后，我们评估每项生产率指标与较低的工厂关闭率和较快的工厂生长(就业、产出和资本增长)之间的关联程度。所有被考虑的生产率衡量标准都是可信的，因为无论以什么标准衡量，生产率高的工厂显然更有利可图，关闭的可能性更小，增长更快。然而，劳动生产率和基于生产函数回归估计的全要素生产率指标比基于要素份额的全要素生产率指标(TFP)更能预测植物的生长和存活。基于数年数据的生产率衡量标准似乎优于仅基于最近一年数据的生产率衡量标准。
In this study we construct twelve different measures of productivity at the plant level and test which measures of productivity are most closely associated with direct measures of economic performance. We first examine how closely correlated these measures are with various measures of profits. We then evaluate the extent to which each productivity measure is associated with lower rates of plant closure and faster plant growth (growth in employment, output, and capital). All measures of productivity considered are credible in the sense that highly productive plants, regardless of measure, are clearly more profitable, less likely to close, and grow faster. Nevertheless, labor productivity and measures of total factor productivity that are based on regression estimates of production functions are better predictors of plant growth and survival than factor share-based measures of total factor productivity (TFP). Measures of productivity that are based on several years of data appear to outperform measures of productivity that are based solely on data from the most recent year.