We examine the relationship credit access has had with the U.S. agricultural productivity and residual returns to resources. Our theoretical analysis suggests that limited credit access can be sufficient to prevent a representative farmer from maximizing both short- and long-run profits. Empirical results show that increased credit access is positively associated with both productivity and residual returns to resources. Our findings imply that one way to stimulate the U.S. agricultural productivity growth is to increase credit access. They also provide strong empirical support for the productivity-stimulating value of programs such as the Farm Service Agency’s Farm Loan Program.

Prior tests of Hicks’ Induced Innovation Hypothesis (IIH) have been greatly hampered because the lack of supply-side data implicitly requires the untenable assumption that the marginal research cost is the same for different inputs. We document that, with appropriate model specification and panel data, a two-way fixed-effects estimator can account for much of the non-neutrality of the innovation function. Using a test procedure that is robust to a time-variant and non-neutral innovation function, we test the IIH in U.S. agriculture for the period 1960–2004. We use only readily available data for innovation demand and total public research expenditures.

Problems of instability and disequilibrium in U.S. agriculture are synthesized within a single conceptual framework. Agricultural and non-agricultural sector offer curves are used to illustrate why it may not be feasible to achieve and maintain equilibrium and price stability in U.S. agriculture. Empirical evidence on resource disequilibrium and instability in the ratio of prices paid and received by farmers is presented.

Energy prices increased significantly following the first energy price shock of 1973. Agricultural producers found few short run substitution possibilities as relative factor prices changed. Inelastic demands resulted in total expenditures on energy inputs that have closely followed energy price changes over time. A dynamic cost function model is estimated to derive short and long run adjustments within U.S. agriculture between 1948 and 2002 to changes in relative input prices. The objective is to measure the degree of farm responsiveness to energy price changes and if this responsiveness has changed over time. Findings support inelastic demands for all farm inputs. Statistical results support moderate increases in responses to energy and other input price changes in the 1980s. However, demands for all inputs remain inelastic in both the short and long run. Estimation of share equations associated with a dynamic cost function indicates that factor adjustment to input price changes are essentially complete within 1 year.