英文文献：U.S. Crop Yields Redux: Weather Effects versus Human Inputs-美国作物产量回归:气候影响与人类投入
英文文献作者：Trindade, Federico J.
英文文献摘要：
Over the 40-year period from 1960 to 2000 the dramatic increase in world crop production was the result of land expansion, but also the result from increasing yields through the use of chemicals, fertilizers, pesticides and water from irrigation systems (Tilman et al., 2002, PNAS). An additional 50 percent increase in world population and higher incomes are expected to double food demand by 2050. Studies show that agriculture production in certain regions like the cereal production areas of the United States, are operating near maximum yield potential (Grassini et. al, 2011, FCP). All this seems to indicate that the food production increases needed to satisfy future demand will put great pressure on existing cropland and natural resources. Climate change, a final source of concern, is likely to aggravate the situation (Schlenker and Roberts, 2009, PNAS). An important step towards understanding the evolution of agricultural production under different climate scenarios is to carefully estimate the effect that different temperatures have on agricultural productivity. This is the goal of this research. Most agronomic studies on the effects of weather on crop yields are based on field experiments. These studies account for the biological effect of different temperatures on specific crops (Ritchie and Nesmith, 1991, MP&SS.) Schlenker and Roberts (2009) consider the effect of weather on aggregate farm yields. They regress corn, wheat and cotton yields in counties east of the 100? meridian on weather variables during the years 1950-2005 and found that there is an increasing positive relation between temperatures and crop yield up to 29-32?C (depending on the crop.) Temperatures above these thresholds are found to reduce yields significantly. Their regressions included precipitation, time trend, soils, and county effects for location-specific unobserved factors. There are two important omissions in this study. First, they only consider rain-fed counties, those east of the 100? meridian, while production increases have been directly related to irrigation developments mostly west of the 100?. Second, their study controls for natural characteristics like precipitation but does not allow for purchased inputs. These inputs have had a pivotal role on increased yields and are under the control of the farmer. It is important then to understand the degree of substitution and the contribution of these versus other inputs to the time trends they estimated. This research develops a county level biomass production function for an 800-mile climatic gradient from the Rocky Mountains to the Mississippi River (41o N latitude). A panel data set that includes 101 counties for the 1960-2008 period is developed. The quantity of biomass produced per hectare (from all crops) is hypothesized to result from the use of traditional inputs under farmers’ control such as land, fertilizer, chemicals, and irrigation and from environmental variables such as soil organic matter, precipitation and temperatures. Indexes are constructed for all variables at the county level. Given interest on climate effects, particular emphasis is placed in the development of county precipitation and degree-days indexes. A semi transcendental logarithmic production specification is jointly estimated with share equations for purchased inputs using a seemingly unrelated estimation approach with panel data corrections. The authors do not know of any other study for this region that provides this information. Results quantify the critical effects that high temperatures have on agricultural productivity in the region, after controlling for irrigation, other managed inputs, soil characteristics, precipitation, and technological change. We found a negative and substantially increasing (nonlinear) effect of temperatures over 30 ?C on crop yields. While a full day of temperatures between 30?C and 35?C decreases expected yield by 0.5%, a day of temperatures over 35?C decreases yields by 36.5%. Our results are qualitatively similar to the findings in Schlenker and Roberts but provide additional information. First, the inclusion of irrigated land seems to diminish greatly the negative effect of higher temperatures. We estimate that in irrigated areas the harmful effect of temperatures above 35?C is reduced by 62%. Second, it is also clear that semi-arid areas like western Nebraska and eastern Colorado and Wyoming, for example, compensate the lack of precipitation with high values of irrigation. Finally, the contribution of fertilizer and chemicals to yield changes is significant, substantially reducing the residual time trend due to unspecified factors. Technological change has been irrigation, fertilizer, and chemicals using.

作物产量回归:天气影响与人类投入。从1960年到2000年的40年间，世界作物产量的急剧增长是土地扩张的结果，但也是通过使用化学药品、化肥、杀虫剂和灌溉系统的水增加产量的结果(Tilman et al.， 2002, PNAS)。预计到2050年，世界人口再增加50%，收入增加，粮食需求将增加一倍。研究表明，某些地区的农业生产，如美国的谷物生产区，正在接近最大产量潜力(Grassini等人，2011,FCP)。所有这一切似乎表明，满足未来需求所需的粮食产量增加将对现有耕地和自然资源造成巨大压力。最后一个令人担忧的问题是气候变化，它可能会使情况恶化(Schlenker and Roberts, 2009, PNAS)。要理解不同气候情景下农业生产的演变，一个重要的步骤是仔细估计不同温度对农业生产率的影响。这就是本研究的目的。大多数关于天气对作物产量影响的农艺研究都是基于大田试验。这些研究解释了不同温度对特定作物的生物学效应(Ritchie和Nesmith, 1991, MP&SS)。Schlenker和Roberts(2009)考虑了天气对农业总产量的影响。他们回归玉米、小麦和棉花产量县东部的100?子午线天气变量在1950年- 2005年,发现越来越积极的温度和作物产量之间的关系29-32?C(取决于作物)。温度超过这些阈值会显著降低产量。他们的回归包括降水、时间趋势、土壤和针对特定位置未观测因素的县域效应。本研究有两个重要的遗漏。首先,他们只考虑雨养县,东100?的子午线,虽然产量增加灌溉发展直接相关的主要是西方的100?。其次，他们的研究控制了自然特征，如降水，但不考虑购买投入。这些投入物对提高产量起了关键作用，并在农民的控制之下。重要的是要了解替代的程度和这些相对于其他投入对他们估计的时间趋势的贡献。这项研究开发了从落基山脉到密西西比河(北纬41度)800英里气候梯度的县级生物量生产函数。建立了涵盖1960-2008年期间101个县的面板数据集。假设每公顷(所有作物)产生的生物量是由农民控制下的传统投入的使用，如土地、化肥、化学品和灌溉，以及土壤有机质、降水和温度等环境变量造成的。在县级层面上为所有变量构建指标。考虑到气候效应，重点编制县域降水和度日指数。一个半超越对数生产规范是联合估计与共享方程购买的投入使用一个看似无关的估计方法与面板数据更正。作者不知道该地区的任何其他研究提供了这方面的信息。在控制了灌溉、其他管理投入、土壤特性、降水和技术变革之后，结果量化了高温对该地区农业生产力的关键影响。我们发现负面和大幅增加(非线性)温度超过30?C对作物产量的影响。虽然一天30?C和35?C之间的温度降低预期收益率0.5%,