The paper presents an econometric model of dynamic agricultural input demand functions that includes research based technical change and autoregressive disturbances and fits the model to data for a set of state aggregates pooled over 1950-82. The methodological approach is one of developing a theoretical foundation for a dynamic input demand system and accepting state aggregate behavior as approximated by nonlinear adjustment costs and long-term profit maximization. Although other studies have largely ignored autocorrelation in dynamic input demand systems, the results show shorter adjustment lags with autocorrelation than without autocorrelation. Dynamic input demand own-price elasticities for six input groups are inelastic, and the demand functions poses significant cross-price and research stock effects.