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This paper revisits claims about implications of production function specification for pesticide productivity measurement and presents two extensions of the popular damage control specification, along with an empirical application. One extension eliminates bias caused by relying solely on economic data and shows how to include variables that represent the pest population when they are necessary to avoid bias. The second extension allows for the possibility of phytotoxicity. These extensions generalize the damage control specification by eliminating bias and allowing for a range over which the first and third stages of production may occur. The main contributions of the analysis are to clarify existing misconceptions about pesticide productivity modeling and to provide extensions to the damage control specification that permit greater realism for empirical analysis.

The concept of geoeconomic time, introduced here, is based on the interface among economic activity, technology, and geophysical processes. Geoeconomic time is what should frame economic analysis of global warming policy. Otherwise, the analysis will be flawed. Application of geoeconomic time to global warming has two parts. The first is the future time frame for projecting impacts on the earth. The second is the historic time frame for delineating our bounds of ignorance regarding the possible consequences of global warming. Many economic analyses conclude against policies to reduce emissions of warming gases, and instead conclude in favour of the “optimal” policy of adapting to global warming. The concept of geoeconomic time reveals that the magnitude of our ignorance is of such a scale that we can never reduce uncertainty sufficiently to design “optimal” policies. Concludes in favour of risk‐reducing policies for research, development and commercialization of energy efficiency technologies and renewable energy. Successful examples can be found at the state and local levels of government action.

As CO2 equivalent gases increase beyond a doubling, there will likely be unavoidable damage to U.S. agriculture. In equatorial regions of the world, damage from global warming will occur earlier than in the U.S. Biogeophysical lags, including deep-ocean mixing with warmer surface waters, can delay the warming caused by CO2 emissions. In this chapter, comparative dynamics trace the path of damage to U.S. agriculture from climate change, after considering adaptation to climate change, technological change that will occur both with and without climate change, and ocean thermal lag.

This chapter demonstrates that results from climate change models using the OLG approach can depend significantly on various economic and social conditions. Thereby, policy recommendations derived from OLG models can prove rather different from those resulting from conventional ILA models. This chapter presents the integrated assessment OLG model for the analysis of global warming ALICE 1.2, which allows for modeling a flexible interest rate and for incorporating various assumptions on demographic change and public institutions designed for the protection of the environment. Thus, ALICE 1.2 is particularly appropriate for providing policy makers with quantitative figures about the desirable and feasible reduction levels of carbon dioxide emissions.

We present direct econometric tests of the induced innovation hypothesis. We test whether the price of herbicides relative to labor, machinery, and land, as well as research stocks, affects the direction of technological change and long-run substitution of herbicides for labor, machinery, and land, in U.S. agriculture. In the long run, a decrease in the price of herbicides relative to labor induces a strong labor-saving and herbicide-using bias in technological change. Public research induces labor-saving, machinery-saving, land-saving, and herbicide-using biases. Exogenous changes in scientific knowledge and/or spillovers from other sectors are labor and machinery saving and herbicide using.