In Progress:

  • The Effectiveness of Air Quality Warnings and Temporary Driving Bans: Evidence from Air Pollution and Urban Transit Flows in Santiago. (dissertation chapter)

Driving restrictions are common strategies to curb mobile source emissions in many cities of the world. In this study, I use high frequency data on air pollution and urban transit flows to evaluate the effectiveness of temporary license plate-based driving bans, triggered with 24-hour air quality warnings, in curbing local air pollution in Santiago, Chile. Taking advantage of the discontinuities in the air quality index used to announce these episodes, I estimate the effect of these incidences, and their driving bans, in reducing ambient concentrations of major pollutants from car emissions. As effective driving bans lessen mobile source pollution by getting cars off the roads and pushing their drivers towards cleaner forms of transportation, I also evaluate this policy using data on vehicle trips, and on the use of Santiago’s mass-transit systems. For identification, I employ a fuzzy regression discontinuity design that uses the thresholds in Santiago’s air quality index as instruments for the episodes’ announcement. Results show that on average, temporary driving restrictions push around 4-6% of cars off the roads during peak hours, and around 7-10% during off-peak hours of days with air quality warnings. This is consistent with reductions in PM, CO, and NOconcentrations mostly during peak hours. Evidence on alternative transportation modes indicates that drivers substitute primarily towards the metro and during hours at which the system is not running at full capacity. Days with exacerbated levels of air pollution, however, show lower increases in mass-transit system ridership, which suggests that air quality warnings may induce an avoidance behavior on affected drivers who stay at home avoiding outdoor exposure to pollution. Results in this study represent suggestive evidence that air quality warnings informing on the risks of outdoor exposure to pollution are an efficient mechanism to secure the effectiveness of driving restrictions.

Resource extractive industries are often challenged by nearby communities due to the environmental impacts of the activity. If proximity to mining represents a disamenity to households, the opening of new mines should lead to a decrease in housing prices. Due to the high pollution potential of this activity, mine openings could also affect households’ willingness to pay (WTP) for environmental quality improvements. This study addresses whether the high-pollution potential of mining outweighs its economic benefits in emerging economies using Chile as a case study. To empirically measure this difference, repeated cross-sectional data on resource extraction site openings is combined with households’ information for over 20,000 rental housing units in Chile. Implicit prices for both air and water quality are elicited using a hedonic price function where rental prices are defined as a function of unit and city-level characteristics. The identification strategy relies on a spatial difference-in-difference (DID) design, where houses in cities hosting site openings are compared with houses in cities without mining, before and after the new sitings. A spatial DID nearest-neighborhood matching estimator strengths this strategy. Results show that mining represents an environmental disamenity to households. Renters who live near mining get compensated with rental prices that are around 14-25% lower. This represents an average willingness to pay of USD52-94 a month to avoid proximity to mines in Chile. Further distinction among types of residents suggest that this market capitalization is higher among long-term residents, which constitutes evidence of a taste-based sorting of households across space.

  • The U.S. Coal-To-Gas Plant Conversion Process: Evidence from Housing Market Capitalizations (dissertation chapter; with Scott Loveridge)

The power sector is currently the largest source of greenhouse gas emissions in the U.S., with coal-fired power plants representing 71% of these emissions. Fewer emissions per Mwh of generation, however, could be released if fuels cleaner than coal were burned. That is the case of natural gas, whose prices over the last decade led to a rise in gas-fired electricity generation in the U.S. in lieu of coal-fired generation, reducing all CO2, SO2, and NOx emissions released by this sector. As the likelihood of adverse responses to pollution depends on the degree of exposure to this contamination, the use of natural gas as a coal substitute raises questions on the economic impacts that a reduced local pollution generates on households living nearby. Switching power plants are expected to represent less of a nuisance for households, in which case compensations required by these individuals for dealing with power plants’ unpleasant effects are expected to decrease. This paper evaluates this claim by looking at the effects that this coal-to-gas plant conversion process generate on the market value of houses located near these switching facilities. Using an extensive dataset on housing market transactions in the U.S., we evaluate whether this conversion affects households’ marginal willingness to pay to avoid proximity to power plant facilities. To identify this effect, we estimate a hedonic price equation in two different spatial difference-in-difference designs. We first compare houses near switching-power plants to houses located near coal-fired power plants before and after the switching. We also compare houses near and far switching plans before and after the conversion date. Finally, we estimate a difference-in-difference-in-difference estimation where houses near and far switching and coal-fired power plants are compared before and after the conversion date.

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CU Environmental and Resource Economics Workshop. Colorado, 2017 – Photo Credits: Sarah Jacobson