Nonparametric measures of the impact of public research expenditures on Australian broadacre agriculture

Abstract

Nonparametric methods are used to measure the impact of public research expenditures on Australian broadacre agriculture over the 1953^94 period. Results using both unrestricted and 30-year lagged speci¢cations of the research impacts on productivity suggest that while certain aspects of the nonparametric multiinput/output technologies are quite robust to alternative speci¢cations (in particular, the associated Malmquist total factor productivity indexes), other aspects are less stable (in particular, the indexes on input and, to a lesser extent, output biased technical change). Internal rates of return to research expenditures on Australian broadacre agriculture are estimated to be in the 12 per cent to 20 per cent range.

Issues in benefit‐cost analysis of agricultural research projects

“…Usually it is reasonable to expect that the knowledge increment responsible for an agricultural innovation will be used for some years subsequently to help develop innovations that replace it. This is consistent with the ¢ndings by Pardey and Craig (1989), Chavas and Cox (1992) and Cox et al (1997) that the e¡ects of research expenditures on agricultural output seem to persist for at least 30 years, given that adoption of agricultural innovations rarely continues for this long. Hence the position of Page et al (1991), as outlined above, is likely to be reasonable for only few innovations of concern to this article.…”

“…The bene¢ts from an advance do not accrue until producers begin to adopt the innovations resulting from it. Some idea of the typical lag between initiating an agricultural research project and the adoption of innovations therefrom has been provided by Cox et al (1997). Their study suggested that productivity gains from Australian crop and livestock research lagged behind research expenditure by at least ten years.…”

Measuring Productivity Growth in Australian Broadacre Agriculture

“…Both primal and dual approaches to representing technology nonparametrically have been developed and provide nonparametric bounds on the underlying production technology (Banker and Maindiratta, 1988). The derivation of primal and dual nonparametric measures under profit maximization is detailed in Chavas and Cox (1994) and in Cox, Mullen and Hu (1996). We have restricted our attention to the dual measures.…”

Forecasting technological change in agriculture—An endogenous implementation in a global land use model

“…The reason for taking the R&D investment data of the year 1981 is the typical time lag between investment in R&D and its impact. The literature offers quite a wide range of various delays and lag-structures proposed for agriculture, ranging from a few years to several decades [18,[29][30][31]. Chavas [32] summarises results from empirical studies suggesting a time lag of 8-15 years for private investments and 15-25 years for public investments.…”