Robert S. Pindyck, MIT and NBER,
Uncertainty, Extreme Outcomes, and Climate Change Policy
Focusing on tail effects -- low probability but very adverse outcomes -- Pindyck incorporates distributions for temperature change and its economic impact in an analysis of climate change policy. He estimates the fraction of consumption w(tau) that society would be willing to sacrifice to ensure that any increase in temperature at a future point is limited to tau . Using information on the distributions for temperature change and economic impact from studies assembled by the IPCC and from "integrated assessment models" (IAMs), he fits displaced gamma distributions for these variables. Unlike existing IAMs, he models economic impact as a relationship between temperature change and the growth rate of GDP, as opposed to the level of GDP. This allows warming to have a permanent impact on future GDP. Pindyck finds that the fitted distributions for temperature change and economic impact yield values of w(tau) above 2 or 3 percent for small values of tau only for extreme parameter values and/or substantial shifts in the temperature distribution -- which does not support the immediate adoption of a stringent abatement policy.
Mireille Jacobson, UC, Irvine and NBER; and Heather N. Royer, University of California, Santa Barbara and NBER,
Aftershocks: The Impact of Clinic Violence on Abortion Services
Between 1973 and 2003, abortion providers in the United States were the targets of over 300 acts of extreme violence, including arson, bombings, murders, and acid attacks. Jacobson and Royer use unique data on these acts and on abortions, abortion providers, and births to examine the extent to which anti-abortion attacks have affected health care providers' decisions to offer abortion services and women's decisions about whether and where to terminate a pregnancy. The authors find that clinic violence reduces both the number of abortion providers and abortion rates in the areas where the violence occurs. Once travel is taken into account, though, the overall effect of the violence is much smaller. On net, the researchers find that women living near a targeted clinic bring 1 percent more births to term shortly following the attack. Births return to trend thereafter. Thus, far from preventing abortions per se, the main effect of violence is to raise the time, money, and psychic cost of obtaining an abortion.
Soren Anderson, Michigan State University,
Using Loopholes to Reveal the Marginal Cost of Regulation: The Case of Fuel-Economy Standards
Government policies increasingly promote ethanol for security, air quality, and climate benefits. Anderson develops a model that links household preferences for ethanol as a substitute for gasoline to aggregate price responses. He estimates the model using data from many retail fueling stations. Ethanol demand is sensitive to relative fuel prices, with a mean elasticity of 2.5-3.0. Fuel-switching behavior extends over a wide range of prices, implying that preferences are heterogeneous. Accounting for this heterogeneity
cuts the cost of an ethanol standard in half, because households with strong preferences
choose ethanol without large subsidies. Costs still exceed benefits by a wide margin.
Lucas W. Davis, University of Michigan and NBER; and Matthew E. Kahn, UC, Los Angeles and NBER,
International Trade in Used Vehicles: The Environmental Consequences of NAFTA
Over the last two decades an unprecedented increase in private vehicle
ownership has taken place in the developing world. This growth is due, in part,
to increased international trade in used vehicles. Davis and Kahn use theory and
empirical evidence to evaluate the environmental implications of free trade in
vehicles and other used durable goods. With non-homothetic preferences, used
vehicles are relatively inexpensive in high-income countries, and free trade causes
these goods to be exported to low-income countries. The researchers apply this framework to
the North American Free Trade Agreement. Since trade restrictions were
eliminated in 2005, over 2.5 million used cars have been exported from the
United States to Mexico. Using a unique, vehicle-level dataset, the researchers find that
traded vehicles are dirtier than the stock of vehicles in the United States and
cleaner than the stock in Mexico, so trade leads average vehicle emissions to
decrease in both countries. Total greenhouse gas emissions increase, primarily
because trade gives new life to vehicles that otherwise would have been
Arik Levinson, Georgetown University and NBER,
Valuing Public Goods Using Happiness Data: The Case of Air Quality
Levinson describes and implements a method for estimating the average marginal value of a time-varying local public good: air quality. He uses the General Social Survey (GSS) and the National Survey of Families and Households (NSFH), which ask thousands of people in various U.S. locations how happy they are, along with other demographic and attitude questions. These data are matched with the Environmental Protection Agency's Air Quality System (AQS) to find the level of pollution in those locations on the dates the survey questions were asked. People with higher incomes in any given year and location report higher levels of happiness, and people interviewed on days when air pollution was worse than the local seasonal average report lower levels of happiness. Combining these two concepts, he derives the average marginal rate of substitution between income and air quality - a compensating variation for air pollution.
Avraham Ebenstein, Harvard University,
Water Pollution and Digestive Cancers in China
Following China's economic reforms of the late 1970s, rapid industrialization has led to a deterioration of water quality in the country's lakes and rivers. China's cancer rate also has increased in recent years, and digestive cancers (that is, stomach, liver, esophageal) now account for 11 percent of fatalities (WHO 2002) and nearly one million deaths annually. Ebenstein examines a potential causal link between surface water quality and digestive cancers by exploiting variation in water quality across China's river basins. Using a sample of 145 mortality registration points in China, he finds that a deterioration of the water quality by a single grade (on a six-grade scale) is associated with a 9.3 percent increase in the death rate attributable to digestive cancer, controlling for observable characteristics of the Disease Surveillance Points (DSP). The analysis rules out other potential explanations for the observed correlation, such as smoking rates, dietary patterns, and air pollution. This link is also robust to estimation using 2SLS with rainfall and upstream manufacturing as instruments. As a consequence of the large observed relationship between digestive cancer rates and water pollution, he examines the benefits and costs of increasing China's levy rates for rm dumping of untreated waste water. His estimates indicate that doubling China's current levies would save roughly 29,000 lives per year, but require an additional 500 million dollars in annual spending on waste water treatment by firms, implying a cost of roughly 18,000 dollars per averted death.
Robin Burgess, London School of Economics and NBER; Olivier Deschenes, UC, Santa Barbara and NBER; Dave Donaldson, London School of Economics; and Michael Greenstone, MIT,
Weather and Death in India: Mechanisms and Implications of Climate Change
Burgess and his co-authors estimate the impact of inter-annual variation in weather on mortality and well being in India, using data from 1957-2000. Their main results indicate a highly nonlinear relationship between daily temperatures and annual mortality rates. For example, one additional day with a mean temperature above 32 degrees C, relative to a day with a mean temperature in the 22 degrees - 24 degrees C range, increases the annual mortality rate by roughly 0.8 percent. This effect is almost entirely concentrated in the rural regions of India where even now more than two thirds of the population lives. The authors then set out to understand the mechanisms behind this result. They analyze the impact of temperature shocks on agricultural outcomes and find support for the existence of excess rural mortality: Exposure to extreme temperatures causes stark declines in the agricultural wage rate and has no effect on labor supply, causing large declines in rural workers' real income. In addition, the authors analyze the response of the formal banking sector to the temperature shocks. They estimate models that relate credit disbursements per capita to their measure of exposure to extreme temperatures. They find that credit disbursements are negatively affected in rural areas in periods of unexpected exposure to high temperatures. Based on this evidence, it appears that the availability of smoothing mechanisms in response to temperature shocks in the formal sector varies across rural and urban areas; this may explain part of the differential mortality response. Finally, the paper takes the estimated response functions between temperatures, precipitations, and mortality to provide some predictions on the impacts of climate change on mortality in India. It is important to bear in mind that this paper relies on inter-annual variation in temperature and thus will produce an overestimate of the costs of climate change, because individuals can engage in a limited set of adaptation in response to inter-annual variation. With this caveat in mind, the predictions based on "business as usual" scenarios suggest an increase in the overall Indian annual mortality rate of approximately 8 percent - 56 percent by the end of the century. The estimated increase in rural areas ranges between 16 percent and 71 percent. As a reference point, a similar exercise suggests that climate change will lead to a roughly 2 percent increase in the United States by the end of the century (Deschenes and Greenstone 2008). These mortality impacts are large. This is true regardless of whether one views them as the current impact of weather shocks on mortality in India or as informative about the costs of climate change.
David Autor, MIT and NBER; Alan Manning, London School of Economics; and Christopher Smith, MIT,
The Role of the Minimum Wage in the Evolution of U.S. Wage Inequality over Three Decades: A Modest Re-Assessment
Autor, Manning, and Smith offer a fresh analysis of the effect of state and federal minimum wages on earnings inequality over 1979 to 2007, exploiting substantially longer state-level wage panels than were available to earlier analyses, as well as a proliferation of recent state minimum wage laws. They obtain identification using cross-state and over-time variation in the "bite" of federal and applicable state minimum wages, as per influential studies by Lee (1999) and Teulings (2000, 2003). Distinct from this work, they use statutory minimum wages as instrumental variables for the bite of the minimum wage, thereby purging simultaneity bias stemming from errors-invariables, which they hypothesize causes upward bias in prior OLS estimates. As with previous analyses, they find that the minimum wage reduces inequality in the lower tail of the wage distribution, but by a smaller amount than was suggested by earlier OLS models. Models purged of simultaneity bias indicate that the minimum wage explains at most half of the rapid rise in female inequality during the 1980s, one-quarter of the rise in male inequality, and a 30 to 40 percent of the more modest rise in subsequent years. These impacts are still larger than would be implied by a simple mechanical application of the minimum to the distribution, suggesting spillovers onto percentiles above those directly affected by the minimum. The researchers identify these spillovers by structurally estimating the latent wage distribution, calculating the mechanical effect of the minimum wage through truncation, and inferring spillovers by comparison of the mechanical and observed distributions. Spillovers account for a substantial amount of the minimum's modest impact on percentiles in the lower tail of the wage distribution, though the contribution of spillovers depends on the year that is considered.
Till von Wachter, Columbia University and NBER,
Long-Term Earnings Losses due to Mass Layoffs During the 1982 Recession: An Analysis Using U.S. Administrative Data from 1974 to 2004
Von Wachter and his co-authors use Social Security records covering up to 30 years of earnings to present the first national estimates of the long-term cost of job displacements during the 1982 recession. They use a new longitudinal dataset that includes firm size to isolate workers who separate from their stable job during a sudden mass-layoff. When they compare the workers displaced from their jobs to similar non-displaced workers, they find large immediate losses in annual earnings of around 30 percent. After 15 to 20 years, these losses are still 20 percent and thus represent a significant setback in workers' life-time resources. These estimates are robust to alternative specifications including industry-year or firm-year effects, they also hold for workers with weak prior job attachment, and they are strong and long-lasting for all age- and industry-groups studied. They are still large and permanent, albeit somewhat smaller, for workers displaced at the peak of the late 1980s recovery. These estimates confirm the larger range of estimates from previous studies based on single U.S. states and selected samples of workers.
James B. Bushnell, UC, Berkeley and NBER; and Yihsu Chen, UC, Merced,
Regulation, Allocation, and Leakage in Cap-and-Trade Markets for CO2
Among the most contentious elements of the design of cap-and-trade systems for emissions trading is the allocation or assignment of the emissions credits themselves. Policymakers usually try to satisfy a range of goals through the allocation process, including easing the transition costs for high-emissions firms, reducing leakage to unregulated regions, and mitigating the impact of the regulations on product prices such as electricity. Bushnell and Chu develop a detailed representation of the U.S. western electricity market to assess the potential impacts of various allocation proposals. Several proposals involve the "updating" of permit allocation, where the allocation is tied to the ongoing output, or input use, of plants. These allocation proposals are designed with the goals of limiting the pass-through of carbon costs to product prices, mitigating leakage, and of mitigating the costs to high-emissions firms. However, allocation updating can greatly inflate permit prices, thereby limiting the benefits of such schemes to high emissions firms. Rather than mitigating the impact on high carbon producers, the net operating profit of such firms actually can be lower under input-based updating than under auctioning. This is because product prices (and therefore revenues) are lower under input-based updating, but overall compliance costs are relatively comparable between auctioning and input-based updating. Thus, the anticipated benefits from allocation updating are greatly reduced and further distortions are introduced into the trading system.
Justin McCrary, UC, Berkeley and NBER; John DiNardo, University of Michigan and NBER; and Matias Busso, University of Michigan,
New Evidence on the the Finite Sample Properties of Propensity Score Matching and Reweighting Estimates
Currently available asymptotic results in the literature suggest that matching estimators have higher variance than reweighting estimators. The extant literature comparing the finite sample properties of matching to specific reweighting estimators, however, has concluded that reweighting performs far worse than even the simplest matching estimator. Busso, DiNardo, and McCrary resolve this puzzle. They show that the findings from the finite sample analyses are not inconsistent with asymptotic analysis -- but are very specific to particular choices regarding the implementation of reweighting -- and fail to generalize to settings likely to be encountered in actual empirical practice. In the DGPs studied here, reweighting typically outperforms propensity score matching.