Crop Acreage Response Modeling in North Dakota and Greater Midwest

Abstract

Our research consists of two papers. First paper focus on the trend of North Dakota (ND) crop acreage changes and include economic factors (expected prices of crops, input price, crop yield, revenue of crops) and climate factors (precipitation, minimum and maximum temperature, growing degree days, and palmer drought severity index). We are using Geographic Information System (GIS) database for cropland areas throughout ND for the years 1998 through 2013. But we are using five crops for our analysis. We use Seemingly Unrelated Tobit Left Censored Regression and Monte Carlo Simulation techniques for our analysis. We also include renewable fuel standard dummy (year 2005 and 2007). Findings suggest that prices of crop, yield, revenue, input price significant impact on crop acreage. Marginal effects of crop price increase by $1 to own acreage of barley, corn, soybean, wheat, and oilseeds ranges between 50 to 295 acres, 28 to 572 acres, -24 to 45 acres, -198 to -39 acres, and 7 to 48 acres throughout ND and statistically significant except soybean. Elasticity of own-price to acreage of barley, corn, soybean, wheat, and oilseeds are 1.16%, 1.23%, 0.17%, -0.16%, and 0.53%, respectively, and statistically significant except soybean. Second paper mainly focus on three states ND, South Dakota (SD), and Minnesota (MN) causes of crop acres planted changes due to economic factors as well as weather factors. We are using Seemingly unrelated regression and Monte Carlo Simulation technique for that paper. We produce a balanced panel dataset with annual observations of the planted acreages of each of the five crops in each of the three states, along with the relevant price and yield variables for each crop and pertinent precipitation and temperature variables for each year in each state. Monte Carlo Simulation technique used to calculate own-price elasticity of MN state barley, corn, soybean, wheat, and sunflower to their own acreage are -0.506%, 0.197%, 0.116%, 0.566 %, and 11.34%, respectively; in SD state are -0.739%, 0.312%, 0.290%, 0.309%, and 1.72%, respectively and statistically significant except barley crop elasticity. This research findings will help forecast future agricultural land use trends & crop area response.