Five hypotheses were put forth to explain the dominance of farm-expansion buyers in the farmland market. Those hypotheses were: economies of size, excess machinery, wealth, excess labor and quality of management. It was hypothesized that among farmland buyers, farm-expansion buyers are most likely to consider such factors in their bid price for land;Those five hypotheses have been suggested in the literature, but not all of them have been theoretically evaluated or empirically tested. Those hypotheses that have been tested, were tested by models using aggregate land value data, whereas a micro-land-price-data set of Iowa farmland sales was used in this study. From this data set, 128 observations were selected from the years 1975 to 1979 and were grouped by the six Iowa price-reporting districts;A linear regression model was constructed and estimated by using ordinary least squares to explain the variation in real sale price. Independent variables used to test the hypotheses were the inverse of total acres farmed, a dummy variable indicating excess machinery, acres owned times the real-average-county land value, a dummy variable indicating excess labor and the number of years of education and farm experience. Other independent variables were included to capture the effect of expected returns, location, land contracts, size of purchase and building value. The intercept was allowed to shift by year and price-reporting district. A second model replaced the inverse of total acres farmed, the economies of size variable, with horsepower per acre. A number of the variables had missing observations, which were replaced by the sample mean;The results indicate that approximately 54 percent of the variation in real sale price was explained by the two different versions of the model. All of the estimates had the hypothesized sign with the exception of years of experience. Of the variables used to capture the effect of the farm-expansion hypotheses, only the estimate for the horsepower per acre specification of the economies of size hypothesis was significant at the 5 percent level. Estimates for other variables that were significant were expected returns, size of purchase and distance to marketing center.