This study provides an analysis of producers' crop planting decision behavior in response to econometric factors, the biophysical environment, and biofuel policy mandates. Specifically, we measure the effects due to economic impacts on an area planted with corn from 1990 to 2015. We develop a crop supply response model and estimate that acres planted with corn in the state of North Dakota have increased by 1.2 million over the last twelve years. Also, the value of crop price elasticities indicates a significant impact on corn planted acreage decisions due to change in crop prices. Corn future price and ethanol price elasticities are positively impacted by corn planted acreage whereas corn planted acreage negatively impacts competitive crop price elasticities. We find that impact of climate variables on corn acreage decision is evident. We show that the inclusion of county interaction effect variables significantly improves the model parameters. Key findings also indicate that a 1% increase in soil moisture in month of May led to a 0.1486% increase in corn acreage expansion. Similarly, as maximum temperature increased during the planting season, corn planted acreage expanded significantly. Also, the total rainfall is positively correlated with corn planted acreage as expected. For example, a 1% increase in total rainfall led to a 0.2143% increase in total corn planted acreage.

This research is primarily designed to examine crop yield variation due to change in weather pattern and crop management activities by exploring a comprehensive list of factors (e.g. environmental, economic etc.). Given that existing literature indicates significant effects when farmland value is regressed on weather variables, a natural question is to ask whether major agricultural crop yields responds to change in historical weather pattern. To answer this question, this study relies on a state level panel dataset including agricultural and high-resolution weather data covering the period 1997-2018. Using a Seemingly Unrelated Regression (SUR) approach, this study estimates how crop spatial distribution patterns have impacted crop yield variation in response to weather in United States Greater Midwest region. Key findings indicate that changes in crop management activities correspond closely to estimate of both crop price and weather effects. Additionally, corn yield response to weather change varies with crop spatial distribution pattern, with distinct impacts on the magnitude and even the direction at the state level. Further, revenue of corn, soybeans, wheat and their respective lagged yields have positive and significant effect to respective crop yields. Finally, a major crop yield does vary across region due to variation of crop prices, precipitation and temperature. These findings have useful implications for agriculture sector on how historical weather trends have affected crop yield and distribution pattern.

No abstract

No abstract

No abstract