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.

The Toronto Word Pool: Norms for imagery, concreteness, orthographic variables, and grammatical usage for 1,080 words

Imagery and concreteness norms and percentage noun usage were obtained on the 1,080 verbal items from the Toronto Word Pool. Imagery was defined as the rated ease with which a word aroused a mental image, and concreteness was defined in relation to level of abstraction. The degree to which a word was functionally a noun was estimated in a sentence generation task. The mean and standard deviation of the imagery and concreteness ratings for each item are reported together with letter and printed frequency counts for the words and indications of sex differences in the ratings. Additional data in the norms include a grammatical function code derived from dictionary definitions, a percent noun judgment, indexes of statistical approximation to English, and an orthographic neighbor ratio. Validity estimates for the imagery and concreteness ratings are derived from comparisons with scale values drawn from the Paivio, Yuille, and Madigan (1968) noun pool and the Toglia and Battig (1978) norms. © 1982 Psychonomic Society, Inc.

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.

Component-wise gradient boosting and false discovery control in survival analysis with high-dimensional covariates.

MOTIVATION: Technological advances that allow routine identification of high-dimensional risk factors have led to high demand for statistical techniques that enable full utilization of these rich sources of information for genetics studies. Variable selection for censored outcome data as well as control of false discoveries (i.e. inclusion of irrelevant variables) in the presence of high-dimensional predictors present serious challenges. This article develops a computationally feasible method based on boosting and stability selection. Specifically, we modified the component-wise gradient boosting to improve the computational feasibility and introduced random permutation in stability selection for controlling false discoveries. RESULTS: We have proposed a high-dimensional variable selection method by incorporating stability selection to control false discovery. Comparisons between the proposed method and the commonly used univariate and Lasso approaches for variable selection reveal that the proposed method yields fewer false discoveries. The proposed method is applied to study the associations of 2339 common single-nucleotide polymorphisms (SNPs) with overall survival among cutaneous melanoma (CM) patients. The results have confirmed that BRCA2 pathway SNPs are likely to be associated with overall survival, as reported by previous literature. Moreover, we have identified several new Fanconi anemia (FA) pathway SNPs that are likely to modulate survival of CM patients. AVAILABILITY AND IMPLEMENTATION: The related source code and documents are freely available at https://sites.google.com/site/bestumich/issues. CONTACT: yili@umich.edu.

Dust in the wind: How climate variables and volcanic dust affect rates of tooth wear in Central American howling monkeys.

OBJECTIVES: Two factors have been considered important contributors to tooth wear: dietary abrasives in plant foods themselves and mineral particles adhering to ingested food. Each factor limits the functional life of teeth. Cross-population studies of wear rates in a single species living in different habitats may point to the relative contributions of each factor. MATERIALS AND METHODS: We examine macroscopic dental wear in populations of Alouatta palliata (Gray, 1849) from Costa Rica (115 specimens), Panama (19), and Nicaragua (56). The sites differ in mean annual precipitation, with the Panamanian sites receiving more than twice the precipitation of those in Costa Rica or Nicaragua (∼3,500 mm vs. ∼1,500 mm). Additionally, many of the Nicaraguan specimens were collected downwind of active plinian volcanoes. Molar wear is expressed as the ratio of exposed dentin area to tooth area; premolar wear was scored using a ranking system. RESULTS: Despite substantial variation in environmental variables and the added presence of ash in some environments, molar wear rates do not differ significantly among the populations. Premolar wear, however, is greater in individuals collected downwind from active volcanoes compared with those living in environments that did not experience ash-fall. DISCUSSION: Volcanic ash seems to be an important contributor to anterior tooth wear but less so in molar wear. That wear is not found uniformly across the tooth row may be related to malformation in the premolars due to fluorosis. A surge of fluoride accompanying the volcanic ash may differentially affect the premolars as the molars fully mineralize early in the life of Alouatta.