Research
Research Interests:
Applied Microeconomics
Urban and Transportation Economics
Public Economics
Environmental Economics
Health Economics
This paper examines the impact of a number of fundamental determinants of commute mode choice on transit use, and explores the role of social influence. The determinants explored cover socioeconomic characteristics, built environment and neighborhood characteristics, transit accessibility, and trip characteristics. Social interactions have been found to affect many of the decisions of economic agents, and are likely to play a role in the decision to use transit. A unique dataset is built to conduct this analysis across a number of major US cities, and examine the effects in both the residence and workplace neighborhoods, where a neighborhood is defined as a census tract. Social influence is explored across 3 different dimensions: space (neighborhood), income, and race. A novel instrumental variable is constructed to identify spatial social influence, and an alternative identification strategy is devised to identify the income-group and racial social influence. The evidence suggests that spatial social influence exists among both coworkers and residential neighbors, and that peer effects among coworkers are larger than those among residential neighbors. Moreover, income-group social influence, among both coworkers and residential neighbors, plays a significant role in the rich commuter's decision to use transit. However, racial social influence does not affect a commuter's decision to use transit, regardless of race.
Khordagui, N., 2019. Parking prices and the decision to drive to work: Evidence from California. Transportation Research Part A: Policy and Practice, 130, pp.479-495.
This paper explores the impact of parking prices on the decision to drive to work using a California household travel survey dataset and a discrete choice model. The paper tackles estimation challenges posed by insufficient parking information. The first challenge is the estimation of parking prices for those who do not drive, which is addressed by using a sample selection model. The second challenge is to understand the effect of the extent of the prevalence of Employer-Paid parking coupled with incentive programs offered in-lieu of parking. To address this challenge, two extreme scenarios are examined, and a range for the marginal effects of parking prices is estimated; one scenario assumes everyone receives Employer-Paid parking coupled with in-lieu of parking incentives, and the second assumes that no one is offered such incentives. The results suggest that higher parking prices reduce driving, regardless of the followed approach. It is estimated that a 10% increase in parking prices leads to a 1 - 2 percentage point decline in the probability of driving to work. This range varies with initial parking prices, where the lower end of the range increases at a decreasing rate, and the higher end peaks at $2.5 and decreases with higher prices. Moreover, there seems to be no evidence of sample selection bias. The evidence confirms that parking pricing can indeed be an effective transportation demand management tool.
Commute Mode Choices and the Role of Parking Prices, Parking Availability and Urban Form: Evidence from Los Angeles County
(In collaboration with Sofia Franco)
We examine the joint role of parking prices, parking availability, and urban form, in commute mode choice in Los Angeles county using a travel survey and two unique parking datasets. We explore how these factors affect the decision to drive and then expand the analysis to a multinomial context. The results indicate that a 10% increase in parking prices is associated with a 1.1% drop in the probability of driving to work. Residential on-street and off-street parking, and workplace urban form, significantly affect commute mode choices. These findings have important implications for parking pricing, minimum parking requirements, and employer-paid parking.
Pollution and Child Mortality: Evidence from Egypt
The paper investigates whether air pollution in Egypt has negative impacts on the health of children in general, and on infant mortality in particular. Several air pollutants are included in the analysis: Carbon Monoxide, Nitrogen Dioxide, Ozone, and Particulate Matter under 2.5 micrometers. A unique dataset is constructed by combining data from two different sources. Microdata for Egypt are obtained from the Demographic and Health Survey (DHS), and pollution data are obtained from satellite imagery. The data from the two different sources are combined using Geographic Information System tools, and relying on the GPS data of the household locations also obtained from the DHS. The relationship is estimated using discrete analysis, on a sample of over 30,000 births over the years 2004-2014. The results indicate that air pollution raises the probability of a newborn dying within the first month of life. In particular, the findings suggest that Nitrogen Dioxide and Particulate Matter are particularly harmful, although there is some evidence on Carbon Monoxide as well. The evidence has several policy implications, aiding in the assessment of air pollution impact of policies and projects, and evaluating the damage of air polluting activities.