Ph.D. candidate in economics with good knowledge in developing statistical/machine learning models to address real-life issues.
Demonstrated leadership and collaboration skills through lab management and teaching undergraduates. EDUCATION
University of Illinois at Urbana-Champaign (UIUC) Urbana-Champaign, IL Ph.D. Economics Expected May 2020
Relevant Coursework: Empirical Corporate Finance, Empirical Industrial Organization, Computational Economics.
Department Summer Research Grant, Cleo Fitzsimmons Best Core Performance Award. Joint Program at Kyushu University and Renmin University Japan/China M.S. Economics 2012
Scholarship for Best Academic Performance
Renmin University China
B.S. Economics and Mathematics, Renmin University 2009
University scholarships each year for four years. RESEARCH EXPERIENCE
Prediction of House Prices
Constructed machine learning models to predict house prices based on the Ames Housing Dataset.
Tested Lasso, XGBoost, and Random Forest regression models and tuned their hyper-parameters to optimize the model predicting power in Python.
Found that Lasso and XGBoost had similar performance, though Lasso regression generated 10% smaller mean square errors for testing data.
Causal Analysis of the E ects of Markdowns on Store Sales
Built models to estimate the e ects of markdowns on retail sales with panel data of forty- ve stores.
Estimated multilinear regression models with Python pandas PanelOLS package, controlling for store xed e ects, time xed e ects, and holiday xed e ects.
Checked the robustness of the results by controlling for lagged store sales instead of store xed e ects. Causal Analysis of Dividends and Free Cash Flow Problem
Investigated the empirical implication of the theory that rms increase dividends to mitigate the free cash ow agency problem.
Applied the theory to a numerically testable hypothesis that the stock market should respond more positively to dividend increase announcements of rms with fewer investment opportunities.
Used multilinear regression to test the hypothesis in Stata, controlling for rm characteristics and time xed e ects.
Rejected the hypothesis based on P value and concluded that the free cash
ow theory could not explain dividend increase.
The Market for Ideas and Economic Growth (PhD Thesis)
Modeled the dynamic interactions of incumbent rms and independent inventors in product markets and the market for ideas in a continuous-time, in nite-horizon economy using optimal control theory.
Investigated the e ects of intellectual property rights and antitrust policies on research e orts of hetero- geneous innovators and aggregate innovation.
Identi ed optimal policies to foster faster aggregate innovation.
Modeled rms’ product market entry, exit, and expansion, and identi ed impacts of technology transac- tions on those dynamics.
Adverse Selection and Financing of Entrepreneurship
Modeled the capital market to nance innovations as a random search, match, and negotiation process with adverse selection.
Modeled the contracting problem between entrepreneurs and corporate venture capitalists with incomplete contract theory.
Characterized optimal nancing strategies of start-ups under di erent research and development costs and product market competition conditions.
Empirical Industrial Organization Demand and Entry Models Estimation
Used the discrete-choice model to estimate the demand function for di erentiated products with product- level data on the ready-to-eat cereal industry.
Research Assistant, UIUC 01/2015-05/2017
Designed and programmed large-scale parallel simulations to study the e ects of monetary policies.
Wrote programs to generate 10,000 sample paths of 5,000 time periods using MATLAB and GNU Octave to run on the computer cluster of UIUC.
Fitted those programs with real-world data to compute parameter values and then generated results under di erent hypotheses.
Teaching Assistant, UIUC 08/2014-present
Courses taught: Economic Statistics, Microeconomic Principles, Macroeconomic Principles.
Taught students statistic theories from descriptive statistics to hypothesis testing.
Coached students to use data analysis software.
Led multiple discussion sessions each week for 40 undergraduates.
Guided students in using macroeconomic theories in the writing of policy analyses. INTERNSHIP
Hollyhigh Finance (Beijing) 07/2010-09/2010
Performed industry analyses and company valuation for mergers and acquisitions business. TECHNICAL STRENGTHS
Programming Languages Python, MATLAB, R, Stata, SQL, Mathematica Professional Certi cate CFA Level II, IBM Data Science Professional Certi cate