Job Market Paper:

Demand and Supply for Rooftop Solar Panels: Evidence from California Solar Initiatives

Solar energy has become the most important renewable energy source in California --- around one third of the state's solar capacity comes from rooftop solar panels. My work estimates the demand and supply functions of rooftop solar panels in California using a rebate program called California Solar Initiatives (CSI). Accurately estimating demand and supply is crucial for evaluating previous incentive programs and guiding future ones. I estimate the demand elasticity in California to be -3.824 and the supply elasticity to be 5.572. These estimates further imply that for each dollar of rebate rate increase, sellers receive $0.29 and households get $0.71. CSI contributed to 46% of new adoptions and a 29% increase in solar generation capacity between 2007 and 2014. It generated a $525 million increase in consumer surplus and producer surplus. However, $663 million spent did not go to either households or sellers. Of the surplus generated, more than 40% went to the top 25% wealthiest Zipcodes. My estimation also shows that as prices of solar panels decrease, households and sellers get more inelastic. This implies that rebates are no longer an efficient way to achieve higher adoption of solar panels in the future, as prices will likely continue to decrease. My contribution to the literature is a new method of using rebates as a source of exogeneous change to estimate both demand and supply functions simultaneously. I analyze disaggregated data at the Zipcode-month level and I use a two-part model to incorporate large amounts of Zipcode-months with no solar panel installations

Other Working Papers:

Chinese Environmental Regulation, Its Effect on Economic Activities and Industry Composition

I study the effect of Chinese environmental regulation on air pollution and industry emissions, economic activity, and industry composition.  My identification comes from a 1998 policy that imposed more stringent environmental regulations on cities designated as “Two Control Zone” (TCZ).   Because the TCZ is not randomly assigned, I use propensity-score matching to match TCZ cities with non-TCZ cities.  Comparing the matched cities and using ambient aerosol optical thickness data from NASA as a proxy for ambient air pollution, I find that ambient air pollution fell by 5% in TCZ cities compared to non-TCZ cities between 2000 and 2012.  However, the TCZ cities have 8% lower GDP growth and almost 30% less new foreign direct investment.

​Pollution and City Development: Evidence from China

I examine the impact of pollution on city development, focusing on employment growth, in China from 2003 to 2013. I derived the regression specification from a structure model that implies that change in employment in an industry in a city is affected by the national growth rate of the industry, by a city-level congestion force, and by city amenity (pollution). For each city-industry, I use the growth rate in other cities in that industry as an exogeneous variable and estimate the national growth rate and predict city-level population growth. I use NASA satellite data as a proxy for the city pollution level. To solve the endogenous issue of pollution, I use coal intensity for each industry multiplied by exogeneous national growth of that industry to predict coal use increase in a city. I use this variable as an IV for pollution level. I find that a 1% increase in city pollution level decreases employment growth by 1.43%. I further interact this effect with the local government’s transparency with environmental information by using the Pollution Information Transparency Index (PITI), a 100-point system in which a higher number means greater transparency. I show that a one-point increase in PITI decreases the negative impact of pollution by 0.05%. 

Consulting Research:

​Economic Impact Evaluation of the City of Pasadena’s Minimum Wage Ordinance
co-authored with Professor Edward E. Leamer and Jonathan Gu

We analyze the impact of the minimum-wage change in Pasadena, California, in a three-phase project. First, we compare Pasadena with surrounding cities, using the characteristics of the nearby cities to help design the geographic structure of a data set ideally organized for studying local competition. Second, we focus on the effect of California’s minimum-wage increases on Pasadena and neighboring communities from 2006 to July 1, 2016. Finally, we studied the effect of minimum-wage differences between Pasadena and surrounding neighborhoods. Solid evidence was hard to identify, due to the small difference between the Pasadena minimum wage and those of the neighboring cities.
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