Modeling endogenous technological change for climate policy analysis

The approach used to model technological change in a climate policy model is a critical determinant of its results in terms of the time path of CO2 prices and costs required to achieve various emission reduction goals. We provide an overview of the different approaches used in the literature, with an emphasis on recent developments regarding endogenous technological change, research and development, and learning. Detailed examination sheds light on the salient features of each approach, including strengths, limitations, and policy implications. Key issues include proper accounting for the opportunity costs of climate-related knowledge generation, treatment of knowledge spillovers and appropriability, and the empirical basis for parameterizing technological relationships. No single approach appears to dominate on all these dimensions, and different approaches may be preferred depending on the purpose of the analysis, be it positive or normative. © 2008 Elsevier B.V. All rights reserved.

The induced innovation hypothesis and energy-saving technological change

We develop a methodology for testing Hicks's induced innovation hypothesis by estimating a product-characteristics model of energy-using consumer durables, augmenting the hypothesis to allow for the influence of government regulations. For the products we explored, the evidence suggests that (i) the rate of overall innovation was independent of energy prices and regulations; (ii) the direction of innovation was responsive to energy price changes for some products but not for others; (iii) energy price changes induced changes in the subset of technically feasible models that were offered for sale; (iv) this responsiveness increased substantially during the period after energy-efficiency product labeling was required; and (v) nonetheless, a sizable portion of efficiency improvements were autonomous.

Environmental policy and technological change

The relationship between technological change and environmental policy has received increasing attention from scholars and policy makers alike over the past ten years. This is partly because the environmental impacts of social activity are significantly affected by technological change, and partly because environmental policy interventions themselves create new constraints and incentives that affect the process of technological developments. Our central purpose in this article is to provide environmental economists with a useful guide to research on technological change and the analytical tools that can be used to explore further the interaction between technology and the environment. In Part 1 of the article, we provide an overview of analytical frameworks for investigating the economics of technological change, highlighting key issues for the researcher. In Part 2, we turn our attention to theoretical analysis of the effects of environmental policy on technological change, and in Part 3, we focus on issues related to the empirical analysis of technology innovation and diffusion. Finally, we conclude in Part 4 with some additional suggestions for research.

Where does energy R&D come from? Examining crowding out from energy R&D

Recent efforts to endogenize technological change in climate policy models demonstrate the importance of accounting for the opportunity cost of climate R&D investments. Because the social returns to R&D investments are typically higher than the social returns to other types of investment, any new climate mitigation R&D that comes at the expense of other R&D investment may dampen the overall gains from induced technological change. Unfortunately, there has been little empirical work to guide modelers as to the potential magnitude of such crowding out effects. This paper considers both the private and social opportunity costs of climate R&D. Addressing private costs, we ask whether an increase in climate R&D represents new R&D spending, or whether some (or all) of the additional climate R&D comes at the expense of other R&D. Addressing social costs, we use patent citations to compare the social value of alternative energy research to other types of R&D that may be crowded out. Beginning at the industry level, we find no evidence of crowding out across sectors-that is, increases in energy R&D do not draw R&D resources away from sectors that do not perform R&D. Given this, we proceed with a detailed look at alternative energy R&D. Linking patent data and financial data by firm, we ask whether an increase in alternative energy patents leads to a decrease in other types of patenting activity. While we find that increases in alternative energy patents do result in fewer patents of other types, the evidence suggests that this is due to profit-maximizing changes in research effort, rather than financial constraints that limit the total amount of R&D possible. Finally, we use patent citation data to compare the social value of alternative energy patents to other patents by these firms. Alternative energy patents are cited more frequently, and by a wider range of other technologies, than other patents by these firms, suggesting that their social value is higher. © 2011 Elsevier B.V.

Behavioral Perspectives on Organizational Change: Practice Adoption, Product Culling, and Technological Search

This dissertation explores the complex process of organizational change, applying a behavioral lens to understand change in processes, products, and search behaviors. Chapter 1 examines new practice adoption, exploring factors that predict the extent to which routines are adopted “as designed” within the organization. Using medical record data obtained from the hospital’s Electronic Health Record (EHR) system I develop a novel measure of the “gap” between routine “as designed” and routine “as realized.” I link this to a survey administered to the hospital’s professional staff following the adoption of a new EHR system and find that beliefs about the expected impact of the change shape fidelity of the adopted practice to its design. This relationship is more pronounced in care units with experienced professionals and less pronounced when the care unit includes departmental leadership. This research offers new insights into the determinants of routine change in organizations, in particular suggesting the beliefs held by rank-and-file members of an organization are critical in new routine adoption. Chapter 2 explores changes to products, specifically examining culling behaviors in the mobile device industry. Using a panel of quarterly mobile device sales in Germany from 2004-2009, this chapter suggests that the organization’s response to performance feedback is conditional upon the degree to which decisions are centralized. While much of the research on product exit has pointed to economic drivers or prior experience, these central finding of this chapter—that performance below aspirations decreases the rate of phase-out—suggests that firms seek local solutions when doing poorly, which is consistent with behavioral explanations of organizational action. Chapter 3 uses a novel text analysis approach to examine how the allocation of attention within organizational subunits shapes adaptation in the form of search behaviors in Motorola from 1974-1997. It develops a theory that links organizational attention to search, and the results suggest a trade-off between both attentional specialization and coupling on search scope and depth. Specifically, specialized unit attention to a more narrow set of problems increases search scope but reduces search depth; increased attentional coupling also increases search scope at the cost of depth. This novel approach and these findings help clarify extant research on the behavioral outcomes of attention allocation, which have offered mixed results.