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A new look at the decomposition of agricultural productivity growth incorporating weather effects

机译:新看看农业生产力增长的分解融合了天气效应

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摘要

Random fluctuations in temperature and precipitation have substantial impacts on agricultural output. However, the contribution of these changing configurations in weather to total factor productivity (TFP) growth has not been addressed explicitly in econometric analyses. Thus, the key objective of this study is to quantify and to investigate the role of changing weather patterns in explaining yearly fluctuations in TFP. For this purpose, we define TFP to be a measure of total output divided by a measure of total input. We estimate a stochastic production frontier model using U.S. state-level agricultural data incorporating growing season temperature and precipitation, and intra-annual standard deviations of temperature and precipitation for the period 1960-2004. We use the estimated parameters of the model to compute a TFP index that has good axiomatic properties. We then decompose TFP growth in each state into weather effects, technological progress, technical efficiency, and scale-mix efficiency changes. This approach improves our understanding of the role of different components of TFP in agricultural productivity growth. We find that annual TFP growth averaged 1.56% between 1960 and 2004. Moreover, we observe substantial heterogeneity in weather effects across states and over time.
机译:在气温和降水的随机波动对农业生产产生重大影响。然而,这些改变配置的天气全要素生产率(TFP)增长的贡献一直没有计量分析明确处理。因此,本研究的主要目的是量化,并探讨在TFP每年解释波动变化的天气模式的作用。为了这个目的,我们定义TFP是总输出由总输入的度量划分的量度。我们采用美国国家级农业数据结合生长季节温度和降水,温度和降水的内部年度标准偏差期间2060至04年估计随机生产前沿模型。我们用模型估计的参数来计算具有良好公理性质的TFP指标。然后,我们分解TFP增长在每个州到天气的影响,技术进步,技术效率,规模和混合效率的变化。这种方法提高我们的农业生产率TFP增长的不同组成部分的作用的认识。我们发现,每年的全要素生产率增长1960年至2004年间平均为1.56%。此外,我们在天气的影响各州和随着时间的推移观察实质性的异质性。

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