Environmental and Energy Economics
January 23 and 24, 2014
Solomon Hsiang, University of California at Berkeley and NBER, and Amir Jina, Columbia University
Do natural disasters have a causal effect on economic development? Reconstructing every country's physical exposure to the universe of tropical cyclones during 1950 to 2008, Hsiang and Jina exploit year-to-year variation in cyclone strikes to identify the effect of disasters on long-run growth. The data reject long-standing hypotheses that disasters stimulate growth via "creative destruction" or that short-run losses disappear following migrations or transfers of wealth. Instead, the authors find robust evidence that national incomes decline relative to their pre-disaster trend and do not recover within 20 years. This result is globally valid, holding for countries of all types, and is supported by non-income variables as well as global patterns of climate-based adaptation. National income loss arises from a small but persistent suppression of annual growth rates spread across the 15 years following disaster, generating large and significant cumulative effects: a 90th percentile event reduces per capita incomes by 7.4 percent two decades later, effectively undoing 3.7 years of average development. The gradual nature of these losses renders them inconspicuous to a casual observer, but simulations indicate that they have dramatic influence over the long-run development of countries with regular or continuous exposure to disaster. Linking these results to projections of future cyclone activity, the authors estimate that under conservative discounting assumptions the present discounted cost of "business as usual" climate change is roughly $9.7 trillion larger than previously thought.
Joseph Shapiro, Yale University and NBER
Shapiro puts trade's benefits and environmental costs on the same theoretical and empirical footing in order to provide a more complete measure of trade's welfare effects. He describes a model of trade and the environment, compiles new data on the CO2 emissions from shipping, and estimates key parameters using instrumental variables. Results show that international trade's benefits exceed international trade's environmental costs by two orders of magnitude. While proposed regional or global carbon taxes on the CO2 emissions from transporting goods would increase global welfare and increase the implementing region's GDP, they would also harm poor countries.
Severin Borenstein, University of California at Berkeley and NBER; James Bushnell, University of California at Davis and NBER; Frank Wolak, Stanford University and NBER; and Matthew Zaragoza-Watkins, University of California at Berkeley
Borenstein, Bushnell, Wolak, and Zaragoza-Watkins analyze the demand for emissions allowances and the supply of allowances and abatement opportunities in California's 2013–2020 cap and trade market for greenhouse gases (GHG). They estimate a cointegrated vector autoregression for the main drivers of greenhouse gas emissions using annual data from 1990 to 2011 and use it to forecast business-as-usual (BAU) emissions during California's program and the impact of the state's other GHG reduction programs. They then consider additional price-responsive and price-inelastic activities that will affect the supply/demand balance in the allowance market. The authors show that there is significant uncertainty in the BAU emissions levels because of uncertainty in economic growth and other factors. The authors' analysis also suggests that while many GHG abatement programs are in place, most of the planned abatement will not be very sensitive to the price of allowances, creating a steep abatement supply curve. The combination of BAU uncertainty and inelastic abatement supply implies a high probability that the price in California will either be at the price floor, or high enough to trigger a safety valve mechanism called the Allowance Price Containment Reserve (APCR). The authors estimate a low probability that the price would end up in an intermediate range between the price floor and the APCR. The analysis suggests that cap and trade markets, as they have been established in California, the EU, and elsewhere, may be more likely to experience price volatility and extreme low or high prices than is generally recognized.
Anderson, Kellogg, and Salant show that crude oil production from existing wells in Texas does not respond to current or expected future oil prices, contradicting a basic prediction of Hotelling's (1931) canonical model of exhaustible resource extraction. In contrast, the drilling of new wells exhibits a strong price response, as does the rental rate on drilling rigs. To explain these observations, the authors reformulate Hotelling's model as a drilling problem, in which firms choose when to drill new wells, but flow from existing wells is limited by a capacity constraint that decays toward zero as reservoir pressure declines. This drilling problem implies a modified Hotelling rule for discounted revenue flows net of drilling costs. The model rationalizes the empirical findings from Texas and can replicate several other well-known features of the oil industry: local production peaks, backwardated price expectations following unanticipated positive demand shocks, and expectations that prices will rise faster than the interest rate following large, unanticipated negative demand shocks.
Louis Kaplow, Harvard University and NBER
Regulation produces enormous benefits and costs, both of which are greatly influenced by myriad exemptions and preferences for small firms that contribute a significant minority of output in many sectors. These firms may generate a disproportionate share of harm because they are exempt and because exemption induces additional harmful activity to be channeled their way. Kaplow analyzes optimal regulatory exemptions where firms have different productivities that are unobservable to the regulator, regulated and unregulated output each cause harm although at different levels, and regulation and the exemption level affect entry and the output choices of regulated and unregulated firms. He also analyzes the optimal use of output taxation alongside regulation — that is, optimal regulation with taxation, in contrast to the traditional comparison of regulation versus taxation. In many settings, optimal schemes involve subtle effects and have counterintuitive features: for example, incentives of firms to drop output to become exempt can be too weak as well as too strong, and optimal output taxes may equal zero despite the presence of externalities. When all instruments under examination are admitted, a planner can achieve the first best, and in this regime optimal regulation is voluntary.
Koichiro Ito, Boston University and NBER, and James Sallee, University of Chicago and NBER
In many countries, fuel economy standards mandate that vehicles meet a certain level of fuel economy, but heavier or larger vehicles are allowed to meet a lower standard. This has the perverse implication of allowing automakers to meet standards either by improving fuel economy or by increasing weight, which lowers fuel economy and increases externalities related to accidents. This is but one example of an attribute-based regulation in which the subsidy, tax, or regulation imposed on a product is a function not just of the amount of the externality the product generates, but also how each product's externality compares to that of other products deemed to be similar by virtue of a commonality in some other attribute. Such policies are ubiquitous, but the core logic and welfare consequences of their deployment have not been studied by academic economists. Ito and Sallee develop an analytical framework that captures the central implications of attribute-based policies, characterizes the deadweight loss caused by attribute-basing, and establishes situations in which attribute-basing may be efficient. The authors empirically examine the consequences of attribute-based fuel economy standards in Japan, where fuel economy standards are an attribute-based function of vehicle weight. They use cross-sectional and panel techniques to demonstrate that attribute-based regulation has significantly altered the distribution of vehicle weight in Japan. For cars whose weight is altered in response to the policy, the authors estimate that the alteration generates a welfare loss from the exacerbation of weight-related externalities of $1,441 per unit sold, which translates into a $648 million annual loss across the Japanese auto market.
Christopher Costello and Corbett Grainger, University of Wisconsin, Madison
The literature on the impact of property rights on resource exploitation has examined individual harvester's incentives, but in many instances it is a regulator, not the individual firms, who determines the aggregate exploitation rate. Costello and Grainger study how the strength of property rights to individual firms affects a regulator's choice over aggregate exploitation rates for a natural resource when the regulator is captured by the industry. The regulator is modeled as an intermediary between current and future resource harvesters, rather than between producers and consumers as in the traditional regulatory capture paradigm. When incumbent resource users have weak property rights, they have an incentive to pressure the regulator to extract resources at an inefficiently rapid rate. In contrast, when property rights are strong, this incentive is minimized or eliminated. The authors build a theoretical model in which different property rights institutions can be compared by their incentives for exerting influence on the regulator. The main theoretical prediction — that stronger individual property rights will lead the regulator to mandate more economically efficient extraction paths — is tested empirically and robustly confirmed with a novel panel dataset from global fisheries. These changes in extraction paths are expected to lead to dramatically different environmental outcomes.
Samuel Bell, Cornell University; Kelsey Jack, Tufts University and NBER; Paulina Oliva, University of California at Santa Barbara and NBER; Christopher Severen, University of California at Santa Barbara; and Elizabeth Walker, Harvard University
Many technology adoption decisions are made under uncertainty about the costs or benefits of adoption. As shocks to the net benefits are realized, agents may prefer to abandon a technology that appeared profitable at the time of take up. Thus, uncertainty breaks the link between the decision to take up and to follow through with a technology. Bell, Jack, Oliva, Severen, and Walker use a field experiment to study the performance of two common incentive tools to promote adoption in a context characterized by uncertainty about the costs of follow through. Farmers in rural Zambia are offered input subsidies for tree seedlings and performance rewards for tree survival, both of which are effective at increasing the total number of trees. The incentive treatments identify a structural model of intertemporal decision-making under uncertainty. Estimation results indicate that the farmers experience idiosyncratic shocks to net profits after take up, which increase participation but lower average per farmer tree survival. While input subsidies have a relatively small (positive) effect on social welfare, the level of performance reward that maximizes welfare is high because of its combined effect on: 1, the social value of increased tree survival; 2, direct farmer profits conditional on performance; and 3, the farmer's unconditional option value of postponing the decision to follow through.
Michael Greenstone, MIT and NBER; Stephen Ryan, University of Texas at Austin and NBER; and Michael Yankovich, U.S. Military Academy at West Point
Hunt Allcott and Allan Collard-Wexler, New York University and NBER, and Stephen O'Connell, City University of New York
Allcott, Collard-Wexler, and O'Connell develop a hybrid Leontief/Cobb-Douglas production function model that characterizes how input shortages affect firms. As a case study, they analyze how "power holidays" affect daily production at large Indian textile plants using data from Bloom et al. (2013). The authors then study the short-run effects of electricity shortages on all Indian manufacturing plants between 1992 and 2010 using archival data on shortages, previously unavailable panel data, and an instrument for shortages based on variation in hydro reservoir inflows. They estimate that electricity shortages are a substantial drag on Indian manufacturing, reducing output by about 5 percent. However, productivity effects are smaller: because electricity is a small share of costs, higher-cost self-generation increases energy costs by only about 0.15 to 0.5 percent of revenues, and because most inputs can be stored during outages the productivity loss is only a fraction of the output loss. The authors also show that because of economies of scale in self-generation, shortages impose much larger losses on small plants, suggesting an additional distortion to the firm size distribution in developing economies.