Jason Huang

Stanford University
Department of Economics
579 Serra Mall
Stanford, CA 94305
530-848-8003

Email: jhuang99@stanford.edu


Curriculum Vitae
Linkedin

Fields:
Public Economics
Microeconomic Theory

Expected Graduation Date:
December, 2017

Thesis Committee:

Caroline Hoxby (Primary):
choxby@stanford.edu

Florian Scheuer:
scheuer@stanford.edu

Petra Persson:
perssonp@stanford.edu

Publications

Optimal Tax Mix with Income Tax Non-compliance (with Juan Rios)
Journal of Public Economics (December 2016).

Although developing countries face high levels of income inequality, they rely more on consumption taxes, which tend to be linear and are less effective for redistribution than a non-linear income tax. One explanation for this pattern is that the consumption taxes are generally more enforceable in these economies. This paper studies the optimal combination of a linear consumption tax with a non-linear income tax for redistributive purposes. In our model, households might not comply with the income tax code by reporting income levels that differ from their true income. However, the consumption tax is fully enforceable. We derive a formula for the optimal income tax schedule as a function of the consumption tax rate, the recoverable elasticities, and the moments of the taxable income distribution. Our equation differs from those of Mirrlees (1971) and Saez (2001) because households face a consumption tax and they respond to income tax not only through labor supply but also through mis-reporting their incomes. Both aspects are empirically relevant to our calibration of the optimal top rate in the Russian economy. We then characterize the optimal mix between a linear consumption tax rate and a non-linear income tax schedule. Finally, we find that the optimal consumption tax rate is non-increasing in the redistributive motives of the social planner.


Working Papers

Measuring Consumer Sensitivity to Audio Advertising: A Field Experiment on Pandora Internet Radio (with David Reiley and Nickolai M. Riabov)

A randomized experiment with almost 35 million Pandora listeners enables us to measure the sensitivity of consumers to advertising, an important topic of study in the era of ad-supported digital content provision. The experiment randomized listeners into nine treatment groups, each of which received a different level of audio advertising interrupting their music listening, with the highest treatment group receiving more than twice as many ads as the lowest treatment group. By keeping consistent treatment assignment for 21 months, we can see that the long-term effects of a change in “ad load,” or number of ads per hour, take over a year to be fully realized. We estimate a demand curve that is strikingly linear, with the number of hours listened decreasing linearly in the number of ads per hour (also known as the price of ad-supported listening). We also show the negative impact on the number of days listened and on the probability of listening at all in the final month. Using an experimental design that separately varies the number of commercial interruptions per hour and the number of ads per commercial interruption, we find that neither makes much difference to listeners above and beyond their impact on the total number of ads per hour. Lastly, we find increased ad load causes a significant increase in the number of paid ad-free subscriptions to Pandora, particularly among older listeners.


Research in Progress

Impact of Food Inspection Grades on Restaurant Business and Customer Composition

In many markets, consumers cannot observe certain important product attributes, and this asymmetry of information leads to market inefficiencies. In the case of retail food establishments, customer cannot monitor the food hygiene in the back of the kitchens. Since 2010, New York City's Department of Health and Mental Hygiene began making the results from their inspections publicly available. Inspectors have been handing out letter grades summarizing the inspection results that the restaurants must post visibly on their entrance windows. By combining the food inspection data with proprietary debit and credit transactions data from 2014 to 2015, I study how consumer choices and customer composition react to changes in food inspection grades. I test not only whether the new information revealed by the changes in grades affects overall business but also whether repeat customers respond differently from transient ones. I find that getting a letter grade lower than A is associated with an economically small but statistically significant dip in daily revenue and foot traffic. In addition, I find that customers who had frequented an establishment in the past two months were less responsive to the grade changes. The findings from this paper both measure the efficacy of a public policy and serve as evidence for hypothesis on consumer behaviors that data from previous studies have unable to provide.


Can Monitoring and Citations Make Food Safer?

Customers cannot easily monitor a restaurant's food preparation process to ensure that it follows proper hygiene standards. In response to this information asymmetry, local governments send out trained public servants to conduct regular health inspections. In this paper, I estimate the impact of citations given out during these inspections on restaurant cleanliness, measured by subsequent inspection results and 311 complaint calls. To address the endogeneity of the inspection outcomes, which conflates the detection of the inspectors and the compliance by the restaurants, I exploit the random assignments of inspectors and construct inspector-specific measures of stringency as an instrumental variable. I find that this variable is highly predictive of not only the overall results but also the specific violations that are cited, despite the random assignment process. I find that more citations leads to better subsequent inspection outcomes, and the effects are larger for chain affiliates. Given that cleanliness is a multi-dimensional task, I document how citations in one dimension affect results in other dimensions during subsequent inspections. While I find that the restaurants respond the most in areas in which they received citations, I also find that citations in one area improve other areas as well. These cross-dimension estimates shed light on the production function of the retail food industry and can guide the optimal design of the grading rubric or the violation fine schedules. Lastly, I find that consumers respond to these improved sanitation conditions by making 311 complaint calls less frequently.