"Capital Controls and International Trade: An Industry Financial Vulnerability Perspective" with Tao Wang and David Xu.
Journal of International Money and Finance, Vol. 116, September 2021
Paper Link: [PIIE WP] [Elsevier]
Capital control policies have consequences on economic growth and international trade. In recent decades, some countries have liberalized their capital accounts, while others have used capital control policies in response to financial crises. Using data on 99 countries from 1995-2014, we find evidence that the effect of capital controls on trade vary across industries that have differing levels of external financing and asset tangibility. For exporter countries that tighten capital controls, industries that rely more heavily on external financing experience a larger decline in exports, while industries that possess more tangible assets experience a smaller decline in exports. For importer countries, tighter capital controls imply a decrease in trade, and this effect is uniform across all industries. The pattern with respect to external financing persists after accounting for availability of domestic credit and the differences in industry shares, and are predominantly found in countries with low levels of financial development. On the other hand, the varying effect related to asset tangibility is mostly absorbed by domestic credit market.
Have the Risk Profiles of Large U.S. Bank Holding Companies Changed? with Ricardo Correa and Linda Goldberg. Federal Reserve Bank of New York: Liberty Street Economics Blog. 2020.
Press Coverage: [Bloomberg]
Analysis of Pre-Doctoral Work: Evidence from the Federal Reserve Bank of New York Research Analyst Job (Discontinued)
Paper Link: Available upon request
Using unique survey data from the Federal Reserve Bank of New York (New York Fed) RA Program across 2000-2019 (roughly 20 cohorts), this paper aims to further explore the RA environment and pipeline features through two main areas: (1) the popularity of pursuing an Economics or Finance PhD after the RA job and (2) the gender composition of RAs. I find that roughly 80% of RAs go on to pursue higher education at some point in their career, but only 60-70% of RAs go on to do PhDs. Among those that pursue PhDs, 78% choose to pursue an Economics or Financial Economics PhD, and many do so at prestigious Economics PhD Programs. On the dimension of gender, I find that the share of female RAs remain below 50% across almost all years, and the share of female RAs are typically lower in finance and macroeconomic functions compared to the microeconomics function. Across all subject areas, there is a lower share of females that go on to pursue an Economics PhD.
The Big Mac Index
Paper Link: [PDF]
In this International Economics seminar paper, I explore the Big Mac Index that was first introduced by the Economist. Furthermore, I explain how the Big Mac Index fits in with in international economics theory, such as purchasing power parity (absolute vs. relative) and non-traded goods. Then, I discuss the surrounding literature that uses the Big Mac Index in the purchasing power parity and exchange rate literature.
Policy-making in an Open Economy
Paper Link: [PDF]
This seminar paper covers the basics of two key international macroeconomic models: the Mundell (1963) and Fleming (1962) model and Dornbusch (1976) model. I first build the framework and intuition of the Mundell-Fleming Model, then cover monetary and fiscal policy outcomes under flexible and fixed exchange rate regimes. Then, I go through the intuition and mechanics of the Dornbusch model. As an extension, I examine the Frenkel and Rodriguez (1982) model that incorporates capital mobility and balance of payment identities into the Dornbusch model.
A Bayesian Approach to Model Goal Scoring: Using the Poisson Distribution and Markov Chain Monte Carlo
Paper Link: [PDF]
In this expository essay, I explore Markov Chain Monte Carlo (MCMC) in goal-scoring using the Poisson distribution, proposed by Everson and Goldsmith-Pinkham (2008). First, I explain the mathematical and intuitive aspects of the Gibbs Sampler, which uses a Gamma prior and Poisson likelihood along with a home-field advantage parameter, proposed in Everson and Goldsmith-Pinkham (2008), and discuss the results of their algorithm based on English Premier League soccer data. Then, I use a simplified version of the MCMC, which takes away the home-field advantage parameter, and apply it to 2017 Professional Ultimate Frisbee data (AUDL), a relatively newer sports scene which has a similar environment to soccer. I implement the MCMC for teams within a division, for 5 divisions. I find that this method is acceptable, but not all divisions are predicted properly. I suggest future steps of research, which include home-field advantage, star power, and other aspects of the sport.