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Many studies have done econometric estimates of how climate alters crop yields and or land rents in an effort to gain information on potential effects of climate change. However, an important related factor, the atmospheric carbon dioxide (CO2) concentration, and in fact a driver of climate change is ignored. This means the prior econometric estimates are biased as they infer what will happen under climate change from observations in the recent past, but without consideration of CO2 effects. Furthermore although CO2 has been varying, it has proceeded at a very linear pace and cannot be disentangled from technological progress using historical crop yield data. This paper is designed to overcome this issue and estimate the consequences that CO2 has and will have in conjunction with climate change. The paper also partitions yield growth into temporal CO2 and climate change affected components and begins to address an issue of how climate change and its drivers will affect rates of technological progress. Moreover, we also factor in a number of conditions regarding to extreme events. This allows us 1) to estimate the consequences of such factors on yields; 2) to project given forecasts of climate change induced shifts in those factors what the implications are for yield distributions; and 3) carry this into welfare and technological change analyses. First, we use a stochastic production function approach of the type suggested by Just and Pope (1978, 1979) estimated with a three-step feasible generalized least squares approach to estimate the effect of climate change and CO2 fertilization on crop yields. The observational data of crop yields and planted acreage are collected from the USDA-National Agricultural Statistics Service. State-level climate data used in this study are obtained from the National Oceanic and Atmospheric Administration. The free-air CO2 enrichment (FACE) experimental data are obtained from the USDA Agricultural Research Service and SOYFACE, University of Illinois. Next, to investigate the implication of future climate change on crop yield and its variability, we employ our estimated coefficients together with future climate change projected by standard GCMs used in the IPCC (2007) with the IPCC SRES scenario A1B. Finally, to explore the market outcomes and welfare implications of economic units given climate-induced shifts in yields across US regions, we plug in our projected percentage changes of mean crop yields into the agricultural sector model (ASM), a price endogenous, spatial equilibrium mathematical programming of the agricultural sector in the US. Our initial results find that yields of C-3 crops, soybeans, cotton, and wheat, positively respond to the elevated CO2, while yields of C-4 crops, corn and sorghum do not. However, we find that C-4 crops indirectly benefit from elevated CO2 in times and places of drought stress. We find the effect of crop technological progress to mean yields is non-linear with inverted-U shape in all crops, except cotton. Our study also reveals that ignoring the atmospheric CO2 in econometric model of crop yield studies is likely to overestimate the pure effect of climate change on crop yields as CO2 enhances those yields. For climate change impact, the average climate conditions and their variability appear to contribute in a statistically significant way to both average crop yields and their variability. Moreover, generally we find that the effect of CO2 fertilization generally outweighs the effect of climate change on mean crop yields in many regions. In terms of market outcomes and welfare distribution, we find the yield growth under the combined climate change and CO2 effect tends to decrease price in 2050. Planted acreage of all crops in North Plains, except wheat winter, is projected to increase, while it tends to decrease in South Plains, Lake States, Delta States, Southeast, and Mountains for almost all crops. Overall consumers’ surplus is projected to increase, while producers’ surplus is heterogeneously affected across US regions, but in total decreases by about $ 4.72 billion. Overall the total US welfare is increased about $ 2.27 billion compared to the base scenario. There are several clear implications of above findings. For example, 1) returns to agricultural research should be reevaluated in the light of climate change influences as for example aggressive CO2 mitigation will decrease returns; 2) models using econometric methods to predict future crop yields should be aware that ignoring CO2 fertilization may overestimate the real effect of climate change on crop yields; and 3) welfare losses for producers under climate change are likely with consumers gaining.

Many studies have done econometric estimates of how climate alters crop yields and or land rents in an effort to gain information on potential effects of climate change. However, an important related factor, the atmospheric carbon dioxide (CO2) concentration, and in fact a driver of climate change is ignored. This means the prior econometric estimates are biased as they infer what will happen under climate change from observations in the recent past, but without consideration of CO2 effects. Furthermore although CO2 has been varying, it has proceeded at a very linear pace and cannot be disentangled from technological progress using historical crop yield data. This paper is designed to overcome this issue and estimate the consequences that CO2 has and will have in conjunction with climate change. The paper also partitions yield growth into temporal CO2 and climate change affected components and begins to address an issue of how climate change and its drivers will affect rates of technological progress. Moreover, we also factor in a number of conditions regarding to extreme events. This allows us 1) to estimate the consequences of such factors on yields; 2) to project given forecasts of climate change induced shifts in those factors what the implications are for yield distributions; and 3) carry this into welfare and technological change analyses. First, we use a stochastic production function approach of the type suggested by Just and Pope (1978, 1979) estimated with a three-step feasible generalized least squares approach to estimate the effect of climate change and CO2 fertilization on crop yields. The observational data of crop yields and planted acreage are collected from the USDA-National Agricultural Statistics Service. State-level climate data used in this study are obtained from the National Oceanic and Atmospheric Administration. The free-air CO2 enrichment (FACE) experimental data are obtained from the USDA Agricultural Research Service and SOYFACE, University of Illinois. Next, to investigate the implication of future climate change on crop yield and its variability, we employ our estimated coefficients together with future climate change projected by standard GCMs used in the IPCC (2007) with the IPCC SRES scenario A1B. Finally, to explore the market outcomes and welfare implications of economic units given climate-induced shifts in yields across US regions, we plug in our projected percentage changes of mean crop yields into the agricultural sector model (ASM), a price endogenous, spatial equilibrium mathematical programming of the agricultural sector in the US. Our initial results find that yields of C-3 crops, soybeans, cotton, and wheat, positively respond to the elevated CO2, while yields of C-4 crops, corn and sorghum do not. However, we find that C-4 crops indirectly benefit from elevated CO2 in times and places of drought stress. We find the effect of crop technological progress to mean yields is non-linear with inverted-U shape in all crops, except cotton. Our study also reveals that ignoring the atmospheric CO2 in econometric model of crop yield studies is likely to overestimate the pure effect of climate change on crop yields as CO2 enhances those yields. For climate change impact, the average climate conditions and their variability appear to contribute in a statistically significant way to both average crop yields and their variability. Moreover, generally we find that the effect of CO2 fertilization generally outweighs the effect of climate change on mean crop yields in many regions. In terms of market outcomes and welfare distribution, we find the yield growth under the combined climate change and CO2 effect tends to decrease price in 2050. Planted acreage of all crops in North Plains, except wheat winter, is projected to increase, while it tends to decrease in South Plains, Lake States, Delta States, Southeast, and Mountains for almost all crops. Overall consumers’ surplus is projected to increase, while producers’ surplus is heterogeneously affected across US regions, but in total decreases by about $ 4.72 billion. Overall the total US welfare is increased about $ 2.27 billion compared to the base scenario. There are several clear implications of above findings. For example, 1) returns to agricultural research should be reevaluated in the light of climate change influences as for example aggressive CO2 mitigation will decrease returns; 2) models using econometric methods to predict future crop yields should be aware that ignoring CO2 fertilization may overestimate the real effect of climate change on crop yields; and 3) welfare losses for producers under climate change are likely with consumers gaining.

This study aims to investigate the effect of climate change on transportation flows and inland waterways in the Mississippi River Basin due to climate-induced shifts in crop production patterns in 2050 using two large scale modeling systems, an Agricultural Sector Model (ASM) and an International Grain Transportation Model (IGTM), with technical approach developed to link the two models. Simulated results from ASM show that 1) US and total social welfare rises; 2) crop producer welfare varies across US regions; 3) production and prices of all crops including corn and soybeans also varies; 4) National total cropland use increases with the expansion of irrigated land and contraction of dryland. After breaking down crop acreage results of ASM to the county level and reaggregating to the crop reporting district (CRD) level, which is the spatial scale employed in IGTM. Our study finds that overall supply of corn and soybeans likely increases in the Northern part, while it tends to decline in some areas from Central to Southern parts of the US. By subtracting demand for grains assumed to constant overtime with simulated supply of grains, we obtain the amount of excess supply and demand for grains, which are used as inputs in IGTM. Various interested findings from IGTM are revealed. For example, Corn Belt, the largest producer of corn in the US, is anticipated to ship less corn supply to Pacific, Northeast, Rocky Mountains, Southeast, and Mississippi Lower ports, while the Great Lakes ports, Lake States, and the Great Plains are expected to receive higher corn shipments from Corn Belt. For the aspect of export, the importance of Lower Mississippi ports, the largest destination for grain export from the US to the rest of the world, is going to diminish, where as the role of Pacific Northwest ports are simulated to increase. Considering overall demand for modes of transportation for total grain shipments, demand for rail and truck is expected to rise, while demand for barge mode is projected to drop., This study was funded by the the University Transportation Center for Mobility, Texas Transportation Institute

This study was funded by the the University Transportation Center for Mobility, Texas Transportation Institute

The impacts of agritourism on farm profitability are poorly understood. Using Census of Agriculture records, we employ propensity score matching to estimate the effects of agritourism on the net cash income per acre of New Jersey farms. We find that agritourism has statistically significant and positive effects on farm profitability. Profit impacts are highest among small farms operated by individuals primarily engaged in farming. Positive but smaller effects are observed for lifestyle farms. Profit effects among larger farms are not statistically significant.