The social cost of carbon revisited

An estimate of the social cost of carbon (SCC) is crucial to climate policy. But how should we estimate the SCC? A common approach uses an integrated assessment model (IAM) to simulate time paths for the atmospheric CO₂ concentration, its impact on temperature, and resulting reductions in GDP. I have argued that IAMs have deficiencies that make them poorly suited for this job, but what is the alternative? I present an approach to estimating an average SCC, which I argue can be a useful guide for policy. I rely on a survey of experts to elicit opinions regarding (1) probabilities of alternative economic outcomes of climate change, but not the causes of those outcomes; and (2) the reduction in emissions required to avert an extreme outcome, i.e., a large climate-induced reduction in GDP. The average SCC is the ratio of the present value of lost GDP from an extreme outcome to the total emission reduction needed to avert that outcome. I discuss the survey instrument, explain how experts were identified, and present results. I obtain SCC estimates of $200/mt or higher, but the variation across experts is large. Trimming outliers and focusing on experts who expressed a high degree of confidence in their answers yields lower SCCs, $80 to $100/mt, but still well above the IAM-based estimates used by the U.S. government.     

Willingness to pay for clean air in China

We use a residential sorting model incorporating migration disutility to recover the implicit value of clean air in China. The model is estimated using China Population Census Data along with PM2.5 satellite data. Our study provides new evidence on the willingness to pay for air quality improvements in developing countries and is the first application of an equilibrium sorting model to the valuation of non-market amenities in China. We employ two instrumental variables based on coal-fired electricity generation and wind direction to address the endogeneity of local air pollution. Results suggest important differences between the residential sorting model and a conventional hedonic model, highlighting the role of moving costs and the discreteness of the choice set. Our sorting results indicate that the economic value of air quality improvement associated with a one-unit decline in PM2.5 concentration is up to $8.83 billion for all Chinese households in 2005.     

Cheap talk efficacy under potential and actual Hypothetical Bias: A meta-analysis

Cheap Talk (CT) is a common technique employed in stated preference methods of nonmarket valuation to reduce Hypothetical Bias (HB). However, multiple studies have documented its mixed usefulness. Using meta-analysis of 67 studies identified after reviewing over 400 articles, we first show the efficacy of CT while controlling for publication bias. We then investigate when CT is likely to be effective. Our results indicate that on average CT is significant in reducing estimated economic values by about 20% compared to the baseline treatment without implementing CT. Further analysis demonstrates that using CT in the context of public goods, using a budget/substitute reminder, and using CT in conjunction with other HB mitigation strategies improves its efficacy. In addition, we show that CT works better when the actual HB is larger thus one potential reason for previous studies failing to identify positive reduction in potential HB through CT may be because actual HB is small instead of CT being ineffective.     

Non-cooperative and cooperative climate policies with anticipated breakthrough technology

Global warming can be curbed by pricing carbon emissions and thus substituting fossil fuel with renewable energy consumption. Breakthrough technologies (e.g., fusion energy) can reduce the cost of such policies. However, the chance of such a technology coming to market depends on investment. We model breakthroughs as an irreversible tipping point in a multi-country world, with different degrees of international cooperation. We show that international spill-over effects of R&D in carbon-free technologies lead to double free-riding, strategic over-pollution and underinvestment in green R&D, thus making climate change mitigation more difficult. We also show how the demand structure determines whether carbon pricing and R&D policies are substitutes or complements.     

Environmental disaster,pollution and infant health: Evidence from the Deepwater Horizon oil spill

In 2010 the Gulf Coast experienced the largest oil spill affecting U.S. waters in history. Evaporating crude oil and dispersant chemicals can cause major health problems. This paper examines the impact of the Deepwater Horizon oil spill on air quality and infant health outcomes. Using U.S. Environmental Protection Agency (EPA) AirData, vital statistics data from National Center for Health Statistics (NCHS), and a difference-in-difference methodology, we find that the oil spill of 2010 increased concentrations of PM2.5, NO2, SO2, and CO in affected coastal counties, increased incidence of low birth weight (<2500 g) and premature born infants (<37 weeks of gestation). Heterogeneity effects reveal more pronounced adverse infant health outcomes for black, Hispanic, less educated, unmarried, and younger mothers. Results are robust to a wide range of controls and robustness checks.     

Carbon taxation,OPEC and the end of oil

I develop a differential game between an oil cartel and an importer investing in research and development (R&D) to reduce the cost of a green substitute to oil. In equilibrium, the cartel is forced to deter the substitute, which thus imposes a price ceiling falling over time. Credible carbon taxes are below the Pigovian level, implying the importer cannot internalise the full pollution externality, much less capture resource rents. Without carbon pricing, the importer curtails long-run pollution using a costly R&D programme. Normatively, climate policy will be more expensive if relying on green R&D programmes only.     

Environmental regulation as a double-edged sword for housing markets: Evidence from the NOx Budget Trading Program

We investigate the effects of environmental regulations on housing markets using a quasi-experimental setting—the NO_x Budget Trading Program (NBP). Hedonic theory predicts that house prices should rise as pollution levels decrease. However, environmental regulations may also affect labor markets, and thus housing demand. Employing a difference-in-differences framework, we find that house prices shifted up in the regulated areas with low manufacturing intensity, whereas in the areas with high manufacturing intensity, housing markets were weakened. We also find that in high-manufacturing-intensity areas, loan application volume declined, rejection rate augmented, and the probability of loan default increased.     

Energy performance certification and time on the market

This paper analyzes whether energy performance certificates (EPCs) serve as means to reduce the information asymmetry among market participants during the sale of homes. Using a sample of 876,000 single-family homes in the Netherlands, we examine the impact of EPC adoption on the speed of sale. Our results indicate that energy-rated homes sell faster than non-energy-rated homes, an effect that varies by 7–12 percent depending on model specifications and increases when positive (green) ratings are granted. The information conveyed by these certificates reduces the information asymmetry between buyers and sellers, which helps to reduce the uncertainty of quality.     

Spatial aggregation and the value of natural capital

Location matters for the value of capital assets. The value of changes in natural capital wealth can depend on whether natural capital asset prices are measured locally and then aggregated or whether average values are applied over aggregate representative areas. Spatial heterogeneity of resource characteristics and institutions impact approximations of the intertemporal welfare function and accounting price function because when spatial aggregation precedes valuation it implies greater arbitrage opportunities leading to more inelastic shadow (accounting) price functions than when valuation is done locally and then aggregated. Aggregation of observed values across varying resource and institutional characteristics can lead to omitted variables bias. We illustrate these results in the context of groundwater in the Kansas High Plains Aquifer and demonstrate that the accounting price function is less elastic when the accounting price is measured locally. Failure to measure locally and then aggregate could lead to undervaluing scarce resources and overvaluing plentiful ones, which biases wealth accounts in favor of passing the non-declining wealth sustainability test.     

Effects of stricter environmental regulations on resource development

This analysis seeks to understand whether changes in oil regulation brought about by the shale revolution have restricted the pace of drilling and production. This hypothesis is tested using data on North Dakota and Montana both before and after North Dakota increased regulations that raise fixed costs. Results generally find that the new regulations had no statistical impact on the pace of drilling and production, however it is found that smaller operators reduced their production and exited. These results are instructive for policymakers who weigh the loss of economic welfare against improved environmental quality when deciding on new regulations.