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Very little. A plethora of integrated assessment models (IAMs) have been constructed and used to estimate the social cost of carbon (SCC) and evaluate alternative abatement policies. These models have crucial flaws that make them close to useless as tools for policy analysis: certain inputs (e.g., the discount rate) are arbitrary, but have huge effects on the SCC estimates the models produce; the models' descriptions of the impact of climate change are completely ad hoc, with no theoretical or empirical foundation; and the models can tell us nothing about the most important driver of the SCC, the possibility of a catastrophic climate outcome. IAM-based analyses of climate policy create a perception of knowledge and precision, but that perception is illusory and misleading.

This paper estimates a structural dynamic equilibrium model of the Brazilian labor market in order to study trade-induced transitional dynamics. The model features a multi-sector economy with overlapping generations, heterogeneous workers, endogenous accumulation of sector-specific experience, and costly switching of sectors. The model's estimates yield median costs of mobility ranging from 1.4 to 2.7 times annual average wages, but a high dispersion of these costs across the population. In addition, sector-specific experience is imperfectly transferable across sectors, leading to additional barriers to mobility. Using the estimated model for counterfactual trade liberalization experiments, the main findings are: (1) there is a large labor market response following trade liberalization but the transition may take several years; (2) potential aggregate welfare gains are significantly reduced due to the delayed adjustment; (3) trade-induced welfare effects depend on initial sector of employment and on worker demographics such as age and education. The experiments also highlight the sensitivity of the transitional dynamics with respect to assumptions regarding the mobility of capital.

World governments have committed to halting human-induced extinctions and safeguarding important sites for biodiversity by 2020, but the financial costs of meeting these targets are largely unknown. We estimate the cost of reducing the extinction risk of all globally threatened bird species (by > 1 International Union for Conservation of Nature Red List category) to be U.S. $0.875 to $1.23 billion annually over the next decade, of which 12% is currently funded. Incorporating threatened nonavian species increases this total to U.S. $3.41 to $4.76 billion annually. We estimate that protecting and effectively managing all terrestrial sites of global avian conservation significance (11,731 Important Bird Areas) would cost U.S. $ 65.1 billion annually. Adding sites for other taxa increases this to U.S. $76.1 billion annually. Meeting these targets will require conservation funding to increase by at least an order of magnitude.

This paper models the optimal search strategies of the unemployed across space to characterize local labor markets. Our methodology allows for linkages between numerous areas, while preserving tractability. We estimate that labor markets are quite local, as the attractiveness of jobs to applicants sharply decays with distance. Also, workers are discouraged from searching in areas with strong competition from other job-seekers. However, as labor markets overlap, a local stimulus or transport improvements have modest effects on local outcomes, because ripple effects in job applications dilute their impact across a series of overlapping markets.

We investigate the role of dynamic production inputs and their associated adjustment costs in shaping the dispersion of static measures of capital misallocation within industries (and countries). Across nine data sets spanning 40 countries, we find that industries exhibiting greater time-series volatility of productivity have greater cross-sectional dispersion of the marginal revenue product of capital. We use a standard investment model with adjustment costs to show that variation in the volatility of productivity across these industries and economies can explain a large share (80–90 percent) of the cross-industry (and cross-country) variation in the dispersion of the marginal revenue product of capital.

We examine the fit between a firm's product market strategy and its business model. We develop a formal model in order to analyze the contingent effects of product market strategy and business model choices on firm performance. We investigate a unique, manually collected dataset, and find that novelty-centered business models--coupled with product market strategies that emphasize differentiation, cost leadership, or early market entry--can enhance firm performance. Our data suggest that business model and product market strategy are complements, not substitutes.

With the recent evolution of additive manufacturing (AM), accurate cost prediction models are of increasing importance to assist decision-making during product development tasks. Estimating the cost is a challenging task in that it requires a vast amount of manufacturing knowledge that has to be synchronised with many aspects from design to production. As a result, various AM cost models have been developed. This review is performed with the aim of providing an overview of the costing models being developed and utilised associated with the additive manufacturing product development phases. For a better understanding in this field, it is required to become familiar with the various terminologies, perspectives, concepts, techniques, and approaches used in developing these models. It was observed that the contexts and views described during the development of the models were often targeted at specific applications as well as technologies and were classified in many ways. Accordingly, the paper compiles different aspects of the cost estimation classification technique and provides definitions of some of the key terminologies. The main motivation is to provide broad and in-depth reviews of the estimation models developed over the past three decades using a systematic classification approach. From the review, a visualisation of future insights into the AM cost-oriented estimation framework from the perspective of various AM users can be better understood.

Which agency problems affect corporate cash policy? To answer this question, we estimate a dynamic model of finance and investment with three mechanisms that misalign managerial and shareholder incentives: limited managerial ownership of the firm, compensation based on firm size, and managerial perquisite consumption. We find that perquisite consumption critically impacts cash policy. Size-based compensation also matters, but less. Firms with lower blockholder and institutional ownership have higher managerial perquisite consumption, low managerial ownership is a key factor in the secular upward trend in cash holdings, and agency plays little role in small firms' substantial cash holdings.

Procurement contracts are often renegotiated because of changes that are required after their execution. Using highway paving contracts we show that renegotiation imposes significant adaptation costs. Reduced form regressions suggest that bidders respond strategically to contractual incompleteness and that adaptation costs are an important determinant of their bids. A structural empirical model compares adaptation costs to bidder markups and shows that adaptation costs account for 7.5-14 percent of the winning bid. Markups from private information and market power, the focus of much of the auctions literature, are much smaller by comparison. Implications for government procurement are discussed.

We examine the role of individual discount rates in energy efficiency decisions using evidence from an extensive survey of US homeowners to elicit preferences for energy efficiency and cash flows over time. We find considerable heterogeneity in individual discount rates. We also find that individual time preferences systematically influence willingness to invest in energy efficiency, as measured through product choices, required payback periods, and energy efficiency tax credit claims. Education is a key driver of individual discount rates. Our findings highlight the importance of individual discount rates to understanding energy efficiency investments, the energy-efficiency gap, and policy evaluation.