Title Coming Soon
Abstract Coming Soon
[joint with IO and ARE]
Abstract Coming Soon
[joint with IO and ARE]
Abstract: We study the impact of learning-by-doing and product innovation on the path of technical progress in wind turbine manufacturing. To measure changes in wind turbine cost over time, we leverage a simple but physically realistic model of how observable wind turbine characteristics, like rotor size, relate to power production and manufacturing material needs. We embed this into a model of wind turbine demand, and estimate it using 20 years of global data on wind farm characteristics, including wind speeds, power prices, and the turbines they installed. Our cost estimates negatively correlate both with manufacturer experience, and with measures of manufacturing innovation, like the delivery of newer and larger turbines. These results are consistent with a theory that LBD and innovation explain much of the observed decline in wind turbine prices over the last 20 years.
University of California, Santa Cruz
“Product Quality Disclosure with Uninformed Sellers”
(Joint with Erica Myers and Steve Puller)
Abstract: This study examines markets in which both buyers and sellers may not fully observe transacted product quality. Using a behavioral model, we illustrate how ignorance can influence sellers’ quality disclosure decisions. Empirically, we leverage a natural policy experiment that encourages homeowners to provide potential buyers with certified measurements of energy efficiency. Using similar nearby homes to form a counterfactual, we find that credible disclosure significantly increases price capitalization of and investments in energy efficiency. Despite very heterogeneous price benefits from disclosure, we show that properties’ relative energy efficiency only weakly predicts disclosure propensities. Connecting our empirical findings to the model, we demonstrate using a computational simulation that a substantial share of homeowners are apparently uninformed about the relative energy efficiency of their own properties. Our findings yield insights about the energy efficiency gap and hold implications for disclosure policies in real estate markets and in other settings.
University of California, Berkeley – Ciriacy-Wantrup Post-Doc
Abstract: I propose a framework to estimate demand and analyze welfare in water markets using transactions data. To infer preferences from observed choices in an existing market, this framework overcomes two key empirical challenges. First, it can recover marginal valuations in the presence of unobserved transaction costs, which lead observed prices to be distributed less widely than true marginal valuations. Second, it can correctly estimate price elasticities in settings where total quantity is fixed and agents may choose to either buy or sell, including water markets and other cap-and-trade systems. I apply this framework to estimate the gains available from an efficient statewide surface water market in California, where conveyance infrastructure is well-developed yet transaction volume remains low. Full Paper
Arizona State University
Abstract: We study whether long-term exposure to air pollution impairs cognition among the US Medicare population. We link fifteen years of administrative records for 7.4 million adults age 65 and older to the Environmental Protection Agency’s air-quality monitoring network to track the evolution of individuals’ health, onset of Alzheimer’s disease and related forms of dementia, financial decisions, and cumulative exposure to fine-particulate air pollution (PM2.5) based on their precise residential locations. We see evidence of Tiebout’s mechanism at work: movers tend to move to less polluted neighborhoods but, among movers, those who are older and those with dementia tend to move to more polluted neighborhoods. We address residential sorting and measurement error in assigning pollution to people by utilizing quasi-random variation in PM2.5 exposures stemming from the EPA’s initial (2005) designation of nonattainment counties for PM2.5. We find robust evidence that a 1 microgram per cubic meter (μg/m3) increase in decadal exposure to PM2.5 (8.5% of the mean) increases the probability of an dementia diagnosis by the end of the decade by 0.5 to 1.2 percentage points (4% to 6%). Our estimates are slightly larger at exposure levels below the EPA’s current regulatory threshold. We also find that higher cumulative exposures to PM2.5 impair financial decision making among those not diagnosed with dementia, where the magnitudes of the effects are 3% to 6% of the negative effect of dementia on decision making. Finally, we find no evidence that exposure to PM2.5 affects the diagnosis rates for morbidities thought to be unrelated to air-pollution and no evidence that pollutants other than PM2.5 impair cognition, providing evidence against confounding.
U.S. Census Bureau
Abstract: How do parental endowments shape the economic prospects of their children? Using a newly constructed dataset from the U.S. Census Bureau linking survey, Census and administrative records, we evaluate the effect of early childhood pollution exposure on the long-run effects of the individuals directly affected, as well as the persistence of these effects across generations – exploring the effects of in-utero pollution exposure on the children of those that were in utero exposed. We exploit variation in particulate matter, which sharply dropped following the enactment of the 1970 Clean Air Act Amendments, which we argue allows us to identify these effects as causal. We find that increased early life exposure to particulate matter is associated with significant reductions in the later life earnings of affected individuals, as well as changes in family structure, through an increased likelihood of divorce. In addition, we find evidence that the consequences of this exposure are transmitted across generations. The children of those affected by increased in-utero pollution exposure are less likely to attend college and experience lower earnings. Preliminary evidence on the drivers of the second generation effects point to the importance of economic, as opposed to genetic, channels, highlighting the role that policy could play in equalizing opportunities.
University of Minnesota
Abstract: China is developing and pilot-testing a new measure of ecological performance, Gross Ecosystem Product (GEP), as a guide in securing the well-being of people and nature. The aim of GEP accounting is to help reveal the contribution of ecosystems to society; show the ecological connections among regions (e.g., between suppliers and beneficiaries of ecosystem services such as flood control or water purification); inform appropriate compensation from beneficiaries to suppliers; serve as a performance metric for government officials; and otherwise inform government policy and investment. GEP will be reported alongside Gross Domestic Product (GDP). Around the world, there is widespread recognition of the need to move beyond GDP for more complete performance measures of the ecological, economic, and social systems supporting human wellbeing (e.g., Stiglitz et al. 2010, UN Sustainable Development Goals 2015). There are ongoing efforts to provide more complete metrics, including the System of Environmental-Economic Accounting (UN 2012, 2013), Wealth Accounting and Valuation of Ecosystem Services (WAVES 2017), Inclusive Wealth (e.g., Arrow et al. 2012, World Bank 2011, UNU 2014), and the Human Development Index (UNDP 1990). But to date these efforts receive far less attention than GDP. China’s adoption of GEP could put ecological information on a par with economic information in one of the world’s most influential countries.
University of Chicago
Joint with the Economics Department
[Note Time & Location: 648 Evans Hall, 4:10-5:30pm]
Abstract: Climate science documents uncertainty induced by different emission scenarios, alternative models, and ambiguous physical interactions. Moreover, for some purposes, it constructs tractable approximations to initially complex models. To engage in credible policy analysis requires that we acknowledge and confront the limits to our understanding of dynamic mechanisms by which human inputs impact the climate. Our research stresses limits to our understanding, with particular focus on the channel from emissions to atmospheric concentration and the channel from concentration to temperature. Even in the most recently developed Atmospheric Ocean General Circulation Models, there is wide variation across models in key policy parameters produced by such models for the same amount of anthropogenic forcing. This variation persists when considering impacts for a wide range of time scales, including shorter time scales that are more typical in economic investigations. We find it productive to pose hypothetical social planning problems and embrace recent advances in decision theory designed to confront uncertainty. The decision problems allow us to assess more formally the consequences of uncertainty. Especially for problems of this nature, we find it important to think of uncertainty as broadly conceived to include risk within a given model, ambiguity across models and potential model misspecification. We draw on asset pricing insights to understand better the consequences of climate impacts that depend on the horizon to the adverse outcomes might be realized. We show the potential importance of both state dependence and horizon dependence in marginal valuations of uncertainty. Because our analysis acknowledges the limits to our knowledge, it implies specific forms of caution but not inaction.
Tel Aviv University