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Presentation ID 16258

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Agriculture is a resource-intensive activity. It currently uses a substantial portion of the Earth’s natural resources: crop production, pasture and livestock grazing systems occupy around 40% of total land area, nitrogen fertilizer applied to agricultural land comprises more than half of the global reactive nitrogen attributable to human activity and agricultural production consumes more fresh water than any other human activity since it accounts for 80% of all freshwater consumption (Cassman 2003). Water is one of the key determinants of agricultural land productivity, adequate water supply to crops is essential to achieve maximum yield and greater stability, enabling also greater scope for diversification. The success of irrigation in improving food security and fostering rural welfare during the last decades has been extremely important but an inappropriate management of it can contribute to a series of environmental problems. The achievement of the required sustained (and sustainable) growth in agricultural production over the next 40 years calls for understanding the current and future enhancers and constraints of agricultural productivity. As water becomes scarcer it is important to estimate the real contribution that water has for agricultural productivity given the whole set of variables that are present in the farming production process, including also the amount of fertilizer and chemicals used, the environment where the process is held (such as temperature, precipitation and soil organic matter) and the farmers profit maximizing behavior. The objective of this study is to measure the contribution that the amount of water irrigated has on agricultural productivity in addition to the effect of weather and the traditional inputs. The data set used in this study consists on data from a survey done to farmers in three different Natural Resources Districts (NRDs) in the state of Nebraska during the period 2004 to 2011. The chosen NRDs are spread over the 41st parallel along East, Center and West Nebraska accounting for important weather (temperatures and precipitation) and soil variability. The data set consists of more than 30,000 observations with information on actual yield, type of crop, inches of water employed, nitrogen applied and manure rates. Additionally we include estimations on temperature (measured in intervals of degree days), precipitation and soil organic matter. Using these variables, this research develops an econometric production function that assumes a semi transcendental logarithmic technology. Particular interest is given to the amount of water used and its interactions with the remaining variables. We do not know of any other similar study done at this level of aggregation and with this great amount of observations. The hypothesized production function follows the form: Where for each field Yi represents the log of the biomass produced at year t for all the crops, Xit is a vector of the log of the amount of water used, amount of fertilizer used, amount of manure used and the time trend at year t, Kit is soil organic matter for year t and rit is a vector of rainfall an 2 degree days intervals (dd30-35 and dd35-40) for year t. By estimating the production elasticities from this translog specification we are able to obtain the effect of water and the other inputs in our hypothesized biomass yield function at each data point. Initial results quantify the critical importance that the amount of irrigated water has on agricultural productivity. As expected the amount of water used has a positive effect on the expected yield, for every extra inch of water pumped the yield is expected to increase by 6.74 percent. Results also highlight the significant negative effect of higher temperatures, a full day of temperatures over 35ºC is expected to decrease the yield in 33.1 percent but this harmful negative effect can be decreased by the use of irrigation. Results also highlight and quantify the importance of the use of Nitrogen as fertilizer. As a next step in this analysis, we plan to use the already available information on nitrogen and electricity prices to improve our estimation; by incorporating share equations we will be able to account for the economic behavior of the producer (as well as the physical relations between the inputs) and additionally to study the effect that price changes due to market or policy modifications can have on factor allocation (in the short run) or in technical change (induced by price changes in the long run).

Agriculture is a resource-intensive activity. It currently uses a substantial portion of the Earth’s natural resources: crop production, pasture and livestock grazing systems occupy around 40% of total land area, nitrogen fertilizer applied to agricultural land comprises more than half of the global reactive nitrogen attributable to human activity and agricultural production consumes more fresh water than any other human activity since it accounts for 80% of all freshwater consumption (Cassman 2003). Water is one of the key determinants of agricultural land productivity, adequate water supply to crops is essential to achieve maximum yield and greater stability, enabling also greater scope for diversification. The success of irrigation in improving food security and fostering rural welfare during the last decades has been extremely important but an inappropriate management of it can contribute to a series of environmental problems. The achievement of the required sustained (and sustainable) growth in agricultural production over the next 40 years calls for understanding the current and future enhancers and constraints of agricultural productivity. As water becomes scarcer it is important to estimate the real contribution that water has for agricultural productivity given the whole set of variables that are present in the farming production process, including also the amount of fertilizer and chemicals used, the environment where the process is held (such as temperature, precipitation and soil organic matter) and the farmers profit maximizing behavior. The objective of this study is to measure the contribution that the amount of water irrigated has on agricultural productivity in addition to the effect of weather and the traditional inputs. The data set used in this study consists on data from a survey done to farmers in three different Natural Resources Districts (NRDs) in the state of Nebraska during the period 2004 to 2011. The chosen NRDs are spread over the 41st parallel along East, Center and West Nebraska accounting for important weather (temperatures and precipitation) and soil variability. The data set consists of more than 30,000 observations with information on actual yield, type of crop, inches of water employed, nitrogen applied and manure rates. Additionally we include estimations on temperature (measured in intervals of degree days), precipitation and soil organic matter. Using these variables, this research develops an econometric production function that assumes a semi transcendental logarithmic technology. Particular interest is given to the amount of water used and its interactions with the remaining variables. We do not know of any other similar study done at this level of aggregation and with this great amount of observations. The hypothesized production function follows the form: Where for each field Yi represents the log of the biomass produced at year t for all the crops, Xit is a vector of the log of the amount of water used, amount of fertilizer used, amount of manure used and the time trend at year t, Kit is soil organic matter for year t and rit is a vector of rainfall an 2 degree days intervals (dd30-35 and dd35-40) for year t. By estimating the production elasticities from this translog specification we are able to obtain the effect of water and the other inputs in our hypothesized biomass yield function at each data point. Initial results quantify the critical importance that the amount of irrigated water has on agricultural productivity. As expected the amount of water used has a positive effect on the expected yield, for every extra inch of water pumped the yield is expected to increase by 6.74 percent. Results also highlight the significant negative effect of higher temperatures, a full day of temperatures over 35ºC is expected to decrease the yield in 33.1 percent but this harmful negative effect can be decreased by the use of irrigation. Results also highlight and quantify the importance of the use of Nitrogen as fertilizer. As a next step in this analysis, we plan to use the already available information on nitrogen and electricity prices to improve our estimation; by incorporating share equations we will be able to account for the economic behavior of the producer (as well as the physical relations between the inputs) and additionally to study the effect that price changes due to market or policy modifications can have on factor allocation (in the short run) or in technical change (induced by price changes in the long run).

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.

Using linear programming data envelope analysis (DEA) I studied the impact that high temperatures have over the agricultural performance of counties in Nebraska. I have found that the incidence of high temperatures is no uniform for all the counties. There is an important negative incidence of temperatures over 32° Celsius during the growing season over agricultural performance on most counties, but for some counties this incidence is not significant.

Using linear programming data envelope analysis (DEA) I studied the impact that high temperatures have over the agricultural performance of counties in Nebraska. I have found that the incidence of high temperatures is no uniform for all the counties. There is an important negative incidence of temperatures over 32° Celsius during the growing season over agricultural performance on most counties, but for some counties this incidence is not significant.

I studied the impact that high temperatures have over the agricultural performance for countries in Nebraska.

I studied the impact that high temperatures have over the agricultural performance for countries in Nebraska.

This article uses parametric and nonparametric methods to update estimates of agricultural productivity growth in 10 South American countries in 1969-2009 with the objective of checking if the slowdown being measured in other countries is present in the region. Results show that the increase in agricultural output during the period analyzed is explained by factor accumulation, but also by higher Total Factor Productivity (TFP) and that the slowdown present in the U.S. and some European economies does not seem to be present in South America. The region yearly average TFP growth went from 1.23 percent during the 1970s to 1.79 percent in the 1980s, 2.04 percent in the 1990s and 2.59 during the 2000s. This growth is not uniform across countries; the different performances can be associated to different environmental and institutional conditions.