Working samples
I am an Applied Microeconomist. My research interests include Urban and Transportation Economics, with empirical applications of choice models usually employed in Applied Industrial Organization. Recently, I've picked up some interest in Environment and Education Economics. Below are the abstracts to some of my recent research.
It's getting bitter! The effects of climate change on the Coffee market
Abstract:​
Coffee is the second most popular beverage behind water, with an estimated four hundred billion cups consumed per year. Coffee provides livelihoods for approximately sixty million people across the globe. Yet, as climate change looms near, coffee is experiencing a sustainability crisis. Climate change is expected to decrease coffee bean quality, increase the risk of coffee diseases, change the coffee growing techniques, and overall shrink the growing areas. This will not only affect the coffee quality for the consumers, but also entail devastating implications to the coffee farmers. This paper aims to provide structured predictions to the outcomes for the coffee market, including prices, quantities, market shares, and farmer employment. It also proposes policies that may change the trajectory of the market. The paper provides an analytical model for coffee production in coffee-exporting countries and coffee demands in coffee-importing countries. Parameters in the models are quantified using the data from the Food and Agriculture Organization for coffee-growing regions and coffee-importing regions. Using the quantified model, the paper predicts the future of coffee production and consumption, given the projected climate change. Preliminary results show that prices will keep increasing, robusta coffee will dominate the market, and farmers face high layoffs as climate change becomes more severe. This baseline business-as-usual outcome is then used to compare with simulated policy interventions (net zero, minimum farm-gate price, etc.) that may alleviate the adverse effects of climate change on the coffee market.
​
JEL Classification: Q1, Q5
​
The Invisible cost of competition: insights from the airline industry
​
Abstract
Ever since the Airline Deregulation Act in 1978, the airline industry drastically transitioned from the most condensed and regulated industry to one of the most competitive one. Severe competition makes airline industry's product margin among the lowest at 8.2% in 2018, only slightly more than half of U.S. average (15.2%). The introduction of electronic booking and budget airlines increased the competition in this market to an unparalleled degree. This section begins a two-part, in-depth analysis that explores the effects of airline industry competition on the firms' financial and operational behavior. It provides an estimate for the degree of competition by employing the discrete choice techniques with differentiated product to estimate the demand for air travel in the U.S. domestic markets. A substitution matrix and a vector of preferences for observable characteristics are obtained for each quarter from 1993Q1 to 2018Q4. A measure for competition in the industry is formulated for each airline during the period. The result shows an increasing degree of competition in the airline industry across the years. Airlines' average absolute value of own-price elasticity went from 2.59 at the beginning of 1993 to 5.24 by the end of 2018. Firms' absolute own price elasticity of demand almost uniformly increase over the time period, indicating that the airlines industry has become an increasingly competitive and price sensitive market. The paper then focuses on the effects of competition on the airlines' Financial and operational behavior. Specifically, the effects of competition on airline's safety expense, 1 product-differentiation expense, route choices and fleet composition. This uses the index of competition derived previously and the difference in differences method with instrumental variable for the independent variable. Simultaneity raises endogeneity concern in the OLS regression: Firms' Financial and operational behavior can be affected by the degree of competition, but conversely, rm behavior can also affect the degree of competition. Causal inference can be extracted using an instrumental variable. I choose the percentage of markets for each airline to face direct flight, budget major competitor (namely, Southwest airlines) as an instrument for competition. First stage result shows that the absolute price elasticity of an airline raises by 1.37 percentage points per 10% increase of their market shares facing nonstop budget rival. Second stage result shows that, the expense for safety does not change signicantly, but the expenses for product differentiation decreases as the markets become more competitive. Airlines fly longer routes on average, and air fleets gravitates towards homogeneously narrow-body, long-distance airplanes as airlines face more competition
​
JEL Classification:
The effects of information on parking behavior: simulations from demand estimation
With Alex Anas
​
Abstract
This paper is funded by the National Science Foundation, to solve the increasing parking traffic faced on multiple university campuses and generally in major urban settings. In the project, we investigate the issue based on the context of the SUNY Buffalo campus because of the availability of quality data. The statistics suggest that there are enough parking spaces supply for any given time on campus, but the problem is that parkers are not aware of available lots, leading to a significant market failure and parking traffic due to the lack of information. This leads to a huge inefficiency regarding time and fuel resources dedicated to find available parking spots. An obvious and cost-efficient remedy is to let parkers have access to accurate information on the availability of parking spaces through a mobile phone application. However, some questions must be answered: how much user usage is required for the application to optimally operate, and how effective this is compared to other possible remedies such as strategic pricing of parking lots and relocating classes. The paper first estimates the demand for each parking lot at different hours throughout the day. The necessary data that depict the market are available in the form of class schedule (demand of parking), the map of parking lots and their capacity (supply of parking), and the occupancy of these lots at different hours (market clearance). The parameters for the demand function for parking are estimated using both OLS and discrete-choice methods (Logit and discrete choice with capacity constraints). The parameters obtained from demand estimation are then used to build simulation models that probabilistically generate individual parking behavior using the class schedule. This simulation takes into account the percentage of parkers with and without information from the mobile phone application. The information only needs to reach about twenty percent of all parkers to achieve optimal gain in welfare. The increased information not only benefits app users, but also non-users, or in other words, there exists a positive externality from access to information. The gain in welfare from the optimal app usage is compared to the gain in welfare using strategic pricing and strategic relocation of classes.