Erich Muehlegger’s research while affiliated with University of California, Davis and other places

Land use regulations are one of the primary ways in which state and local governments influence the urban landscape, affecting where people live, how much they commute and the impact they have on the environment. Using a new, novel data on the stringency of land use regulation in the U.S. over the past decades, we study the effect of local regulation on the individual commuting times. Paired with demographic data from the U.S. Census, we examine whether land use policies disproportionately affect particular socioeconomic or demographic groups and find a positive relationship between land use regulation and commuting time. In addition, we show that this relationship increases disproportionately for workers with a Bachelor's degree or more, and that these impacts could be mitigated by the establishment of a public transit system.

Can data from mobile phones be used to observe economic shocks and their consequences at multiple scales? Here we present novel methods to detect mass layoffs, identify individuals affected by them and predict changes in aggregate unemployment rates using call detail records (CDRs) from mobile phones. Using the closure of a large manufacturing plant as a case study, we first describe a structural break model to correctly detect the date of a mass layoff and estimate its size. We then use a Bayesian classification model to identify affected individuals by observing changes in calling behaviour following the plant's closure. For these affected individuals, we observe significant declines in social behaviour and mobility following job loss. Using the features identified at the micro level, we show that the same changes in these calling behaviours, aggregated at the regional level, can improve forecasts of macro unemployment rates. These methods and results highlight promise of new data resources to measure microeconomic behaviour and improve estimates of critical economic indicators. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

We examine real-world data on 6,700 motor vehicle crashes and data on cell phone usage in a mid-sized European country. In a non-experimental context, we document a positive correlation at the cell-tower level between call volumes and the likelihood of a nearby motor vehicle accident leading to a serious injury. We demonstrate that these correlations are robust to a series of controls. Scaling our estimates by the number of crashes in our data, we estimate that a 100% increase in call volumes is associated with a 15% to 43% increase in the likelihood of a serious crash.

Climate change is a complex long-run phenomenon. The speed and severity with which it is occurring is difficult to observe, complicating the formation of beliefs for individuals. We use Google search intensity data as a proxy for the salience of climate change and examine how search patterns vary with unusual local weather. We find that searches for “climate change” and “global warming” increase with extreme temperatures and unusual lack of snow. Furthermore, we demonstrate that effects of abnormal weather extend beyond search behavior to observable action on environmental issues. We examine the voting records of members of the U.S. Congress from 2004 to 2011 and find that members are more likely to take a pro-environment stance on votes when their home state experiences unusual weather.

We study the diffusion of hybrid vehicles among consumers. Using data on sales of 11 different models over seven years, we identify the effect of the penetration rate – total cumulative hybrid sales per capita – on new hybrid purchases. The penetration rate significantly affects new purchases, and the effect differs by hybrid model. In particular, we find a positive diffusion effect from the Toyota Prius and a negative diffusion effect from the Honda Insight, with elasticities of 0.23 to 0.85 for the Prius and –0.08 to –0.32 for the Insight. This finding is consistent with our model of model–specific learning along with anecdotal evidence that early Insight models were perceived to be of lower quality than Prius models. Higher Insight penetration rates gave a negative signal about hybrid quality and inhibited rather than promoted hybrid adoption. The findings are relevant for policy designed to promote new technologies.

Climate change is a complex long-run phenomenon. The speed and severity with which it is occurring is difficult to observe, complicating the formation of beliefs for individuals. We use Google Insights search intensity data as a proxy for the salience of climate change and examine how search patterns vary with unusual local weather. We find that searches for "climate change" and "global warming" increase with extreme temperatures and unusual lack of snow. The responsiveness to weather shocks is greater in states that are more reliant on climate-sensitive industries and that elect more environmentally-favorable congressional delegations. Furthermore, we demonstrate that effects of abnormal weather extend beyond search behavior to observable action on environmental issues. We examine the voting records of members of the U.S. Congress from 2004 to 2011 and that members are more likely to take a pro-environment stance on votes when their home-state experiences unusual weather.

Firms often lack knowledge of the nature of the uncertainty they or their opponents face and use heuristics or approximations to determine their strategy. We define and analyze one type of “heuristic strategy”, in which firms choose strategies based on the expectation of their opponents’ private information rather than the full information about the distribution of that private information. We find that, in equilibrium, the degree to which the heuristic strategy differs from the Bayesian strategy depends on: (1) the convexity of a firm's marginal profits with respect to their opponents’ private information and (2) whether firm strategies are complementary or substitutable. Under certain conditions, firms’ equilibrium profits are greater when all firms use heuristics than when all firms use the full information. Our results provide insight into incentives firms may have to either facilitate or impede access to industry information.

Gasoline taxes can be employed to correct externalities associated with automobile use, to reduce dependency on foreign oil, and to raise government revenue. Our understanding of the optimal gasoline tax and the ecacy of existing taxes is largely based on empirical analysis of consumer responses to gasoline price changes. In this paper, we directly examine how gasoline taxes affect gasoline consumption as distinct from tax-inclusive retail gasoline prices. Across a variety of specifications and estimation methods, we find that consumers respond more strongly to gasoline tax changes. Our main specification shows that a 5-cent tax increase would reduce gasoline consumption by 0.86 percent, compared with 0.29 percent from an equivalent change in tax-inclusive gasoline prices. This difference suggests that traditional analysis could significantly underestimate policy impacts of tax changes. We further investigate the differential effect from gasoline taxes and gasoline prices on both the intensive and extensive margins of gasoline consumption. We discuss implications of our findings for the estimation of the implicit discount rate for vehicle purchases and for the fiscal benefits of raising taxes.

In this paper, we provide new evidence regarding the pass-through of diesel and gasoline taxes to prices, and how the estimated pass-through depends on a variety of supply conditions including a measure of state residual supply elasticity, and refinery and inventory constraints. In addition, we estimate the response of tax incidence to gasoline content regulations, which complicate the supply chain by increasing product heterogeneity. We find that state gasoline and diesel taxes are on average fully passed on to consumers. We also find that the pass-through of diesel taxes is greater in settings where untaxed uses of diesel are more important, which corresponds to times when residual supply is more elastic. We find that only half of the state diesel tax is passed on to consumers when U.S. refinery capacity utilization is above 95 percent. Gasoline taxes, on the other hand, are fully passed through regardless of season or capacity utilization, indicating that a gas tax holiday would provide price relief to consumers. We find that regional gasoline content regulations affect pass-through – we estimate tax pass-through is 22 percentage points lower in a state using two blends of gasoline than a state using one blend of gasoline.

This paper measures the extent to which prices exceed marginal costs in the U.S. natural gas distribution market during the period 1991-2007. We find large departures from marginal cost pricing in all 50 states, with residential and commercial customers facing average markups of over 40%. Based on conservative estimates of the price elasticity of demand these distortions impose hundreds of millions of dollars of annual welfare loss. Moreover, current price schedules are an important pre-existing distortion which should be taken into account when evaluating carbon taxes and other policies aimed at addressing external costs.