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Abstract

It is estimated that world population will increase by 30 percent to reach more than 9 billion people by 2050. Given expected higher income, per capita consumption of protein will induce an increase in cereal production of at least 70% over current levels; quantity attainable without incorporating new land if the yield growth rates increase at least 1.3% per year (Fulginiti and Perrin, 2010). The dramatic increase in world crop production observed in the second half of the nineteenth century was the result from increasing yields through the use of chemicals, fertilizers, pesticides and water from irrigation systems (Tilman et al., 2002). During the last years it was observed by several authors a decrease in global yields growth rates for the major crops (corn, wheat, rice and soybeans) when comparing the period 1990-2010 with 1960-1990 (Alston et al. 2010, Fuglie 2010, World Bank Development Report 2007). If this observed decline in agricultural productivity growth continues, average global yields growth rate for the main crops could fall below 1.3% increase per year, lower than the needed amount to reach the production goal of 2050. Thus, the food production increases needed to satisfy future demand will put greater stress on existing cropland and natural resources, if the prices rise there will be also greater pressure to convert natural ecosystems to cropland. Climate change, a final source of concern, is likely to aggravate the situation. Considering different scenarios of future trends in climate, several authors have found that the impact that climate change will have over agriculture production will most likely be negative (Schlenker and Roberts, 2009). Schlenker and Roberts consider the effect of weather on aggregate farm yields. They regressed corn, wheat and cotton yields in counties east of the 100º 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 29-32ºC (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 100º meridian, while production increases have been directly related to irrigation developments mostly west of the 100º. 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. An important step towards understanding the evolution of agricultural production under different climate scenarios is to carefully estimate the effect that different temperatures and precipitation have on agricultural productivity considering also inputs under farmers’ control and the farmers’ profit maximizing behavior. Another issue of importance, given the developments of the last 60 years, is the study of rain-fed as well as irrigated agriculture. These are the objectives of our analysis; we do not know of any other study with these objectives that considers this set of variables and assumptions. 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 percent of irrigated land 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 different intervals of degree-days indexes. A semi transcendental logarithmic production specification is jointly estimated with share equations for purchased inputs using a seemingly unrelated estimation approach. Additionally, to avoid simultaneity issues, price indexes are used as instruments for fertilizer and chemicals used. Out results are able to 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. Confirming Schlenker and Roberts (2009) results, we find a negative and increasing (nonlinear) effect of temperatures over 30ºC on crop yields; a full day of temperatures between 30ºC and 35ºC decreases expected yield by 1.0%, a day of temperatures over 35ºC decreases yields by 27.1%. Our results provide additional information than the findings of Schlenker and Roberts. The inclusion of irrigated land seems to diminish greatly the negative effect of higher temperatures; converting rain fed crops to irrigated crop will produce a sharp decrease in the negative impact of the higher temperature interval. Results also show that the 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. Technological change has been fertilizer and chemicals using.

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