Economist · Leader · Scholar · Data Science Advocate

Le Wang

Le Wang

David M. Kohl Chair and Professor at Virginia Tech. Director of the Kohl Centre and the Data Science for the Public Good Program. Endowed chair, center director, and institution-builder with twenty years of research, teaching, and academic leadership at R1 universities.

PositionEndowed Chair & Professor
InstitutionVirginia Tech

At a Glance

20+
Years at R1 Institutions
2
Endowed Chair Positions
7
Research & Teaching Awards
44+
Peer-Reviewed Publications
30+
Ph.D. & M.A. Students Advised
Data science with impact and with purpose — economics operating at the intersection of technical innovation and human systems.
— Le Wang's guiding research and teaching philosophy
01

Biography

Le Wang is the David M. Kohl Chair and Professor at Virginia Tech, where he directs the Kohl Centre — an interdisciplinary hub he revitalized from the ground up — and the Data Science for the Public Good Program. His guiding vision, "data science with impact and with purpose," brings together rigorous economic analysis, modern machine learning methods, and experiential student learning, all oriented toward real-world impact.

His research spans labor economics, education, health, inequality, and intergenerational mobility, with particular methodological depth in distributional analysis, causal inference, and causal machine learning. He has published 44 peer-reviewed articles in leading outlets including the Journal of Political Economy, Journal of Econometrics, Journal of Business & Economic Statistics, and Journal of Applied Econometrics, alongside interdisciplinary work in natural language processing and early childhood development. His scholarship has been recognized with the Kuznets Prize, the Emerald Liberati Award for Outstanding Author Contribution, and the VPR Award for Excellence in Transdisciplinary Research.

A dedicated educator, Professor Wang has won multiple Outstanding Professor Awards and a Presidential Professorship. He designed one of the nation's early 4+1 programs integrating machine learning and causal inference into applied economics at the University of Oklahoma and has built award-nominated experiential learning ecosystems at Virginia Tech. He currently teaches Ph.D.-level causal inference and has mentored more than 30 doctoral and master's students placed across academia, government, and industry.

Beyond research and teaching, he serves as Co-Editor of the China Economic Review and the Journal of Labor Research, Associate Editor of Econometric Reviews, and a member of the Board of Trustees of the Southern Economic Association. He is a Research Fellow of the IZA Institute, the Global Labor Organization, and the HCEO Global Working Group at the University of Chicago.

2012
Women and Public Policy Fellow
Harvard University
2025
Inaugural IREI Fellow
Virginia Tech — identified by peers as an outstanding researcher
2023
Emerald Liberati Award
Outstanding Author Contribution, Advances in Econometrics
2023
VPR Transdisciplinary Research Award
University of Oklahoma — research with broad societal benefits
2018
Kuznets Prize
Best paper, Journal of Population Economics
2018
Presidential Professorship
University of Oklahoma
02

Research

Dr. Wang's research spans applied microeconomics and econometrics, with substantive focus on income distribution, intergenerational mobility, labor markets, education, health, and public policy. Methodologically, he works at the intersection of distributional analysis, causal inference, and modern machine learning. Dr. Wang has published 44 peer-reviewed articles in outlets including the Journal of Political Economy, Journal of Econometrics, Journal of Business & Economic Statistics, and Journal of Applied Econometrics.

Featured Work

SMRGeneralized Intergenerational Mobility Regressions (with E. Maasoumi & D. Zhang), Sociological Methods & Research, 2025
JPEThe Gender Gap Between Earnings Distributions (with E. Maasoumi), Journal of Political Economy, 2019
J EconomWhat Can We Learn About the Racial Gap in the Presence of Sample Selection? (with E. Maasoumi), Journal of Econometrics, 2017
J EconomEstimating Semiparametric Panel Data Models by Marginal Integration (with J. Qian), Journal of Econometrics, 2012
JBESA Nonparametric Non-classical Measurement Error Approach to Estimating Intergenerational Mobility Elasticities (with Y. An & R. Xiao), Journal of Business & Economic Statistics, 2022

Explore by Topic

Income Distribution, Inequality, & Mobility
15 papers
Econometrics
19 papers
Education
9 papers
Labor
24 papers
Demography
11 papers
Health
9 papers
Public Policy
12 papers
Interdisciplinary
4 papers
AI
3 papers
Other Topics
4 papers
Showing all 60 items
[1]Generalized Intergenerational Mobility Regression (with E. Maasoumi & D. Zhang), Sociological Methods & Research, 54(4), 2025
[2]The Growth of Hispanic Entrepreneurship and Undocumented Immigrants (with C. Wang), Small Business Economics, 65(1), 163–189, 2025
[3]Geography and the European Marriage Pattern (with K. de Beurs & K. Harper), Research in Economic History, 38, 2025
[4]Baby Steps to Success: The Impact of Paid Maternity Leave on Children's Long-Term Outcomes in U.S. (with K. Regmi), Journal of Population Economics, 38(37), 2025
[5]BTW: A Non-Parametric Variance Stabilization Framework for Multimodal Model Integration (with J. Hou & X. Wang), Proc. on Findings of EMNLP'25, 2025
[6]Head Start Staff Well-being: Early Impact Results from a Cluster Randomized Controlled Trial (RCT) of a Holistic Wellness Intervention (with K.A. Kwon, T. Ford, D. Horm, H. Wang & others), Early Childhood Research Quarterly, 2025
[7]How Policies Can Support and Sustain Early Childhood Educator Well-Being (with K.C. Gallagher, R. Ssentuuwa, A. Daro & D. Horm), Educating Young Children, Summer 2025
[8]Politician's Childhood Experience and Government Policies: Evidence from the Chinese Great Famine (with C. Li & J. Zhang), Journal of Comparative Economics, 76–92, 2024
[9]Maternity Leave (with K. Regmi), Handbook of Labor, Human Resources and Population Economics, 2023
[10]A Nonparametric Non-classical Measurement Error Approach to Estimating Intergenerational Mobility Elasticities (with Y. An & R. Xiao), Journal of Business & Economic Statistics, 40(1), 169–185, 2022
[11]Women's Potential Earnings Distributions (with E. Maasoumi), Advances in Econometrics, 229–252, 2022
[12]SNAP Participation, Diet Quality, and Obesity: Robust Evidence with Estimation Techniques without External Instrumental Variables (with S. Chen), Empirical Economics, 61, 1641–1667, 2021
[13]Higher-order Risk-Returns to Education (with D. Henderson & A.-C. Souto), Journal of Risk Analysis and Management, 13(11), 253, 2020
[14]The Politics of Environmental Enforcement: The Case of the Resource and Conservation Recovery Act (with P.G. Fredriksson), Empirical Economics, 58, 2020
[15]The Gender Gap Between Earnings Distributions (with E. Maasoumi), Journal of Political Economy, 127(5), 2019
[16]Hidden Group Patterns in Democracy Developments: Bayesian Inference for Grouped Heterogeneity (with J. Kim), Journal of Applied Econometrics, 34(6), 1016–1028, 2019
[17]Crime on the Field (with C. Kitchens & M. Makofske), Southern Economic Journal, 85(3), 821–864, 2019
[18]Informal Search, Bad Search?: The Effects of Job Search Method on Wages among Rural Migrants in China (with Y. Chen & M. Zhang), Journal of Population Economics, 31(3), 837–876, 2018
[19]What Can We Learn About the Racial Gap in the Presence of Sample Selection? (with E. Maasoumi), Journal of Econometrics, 199(2), 117–130, 2017
[20]The Robust Relationship Between US Food Aid and Civil Conflict (with C.-Y. Chu & D.J. Henderson), Journal of Applied Econometrics, 32(5), 1027–1032, 2017
[21]The Distribution of Returns to Education for People with Disabilities (with D.J. Henderson & A. Houtenville), Journal of Labor Research, 38(3), 261–282, 2017
[22]The Three Is of Public Schools: Irrelevant Inputs, Insufficient Resources and Inefficiency (with D.J. Henderson & L. Simar), Applied Economics, 49(12), 1164–1184, 2017
[23]Knot Yet: Minimum Marriage Age Law, Marriage Delay, and Earnings (with C. Wang), Journal of Population Economics, 30, 771–804, 2017
[24]The Inequality-Growth Plateau (with D.J. Henderson & J. Qian), Economics Letters, 128, 17–20, 2015
[25]How Does Education Affect the Earnings Distribution in China, Oxford Bulletin of Economics and Statistics, 75(3), 435–454, 2013
[26]Estimating Returns to Education when the IV Sample is Selective, Labour Economics, 21, 74–85, 2013
[27]Party Politics, Governors and Economic Policy (with P.G. Fredriksson & P.L. Warren), Southern Economic Journal, 80(1), 106–126, 2013
[28]Estimating Semiparametric Panel Data Models by Marginal Integration (with J. Qian), Journal of Econometrics, 167(2), 483–493, 2012
[29]Economic Transition and College Premium in Urban China, China Economic Review, 23(2), 238–252, 2012
[30]The Effects of 9/11 on Intermarriage between Natives and Immigrants to the U.S. (with C. Wang), Review of Economics of the Household, 10(2), 171–192, 2012
[31]The Oh-So Straight and Narrow Path: Can the Health Care Expenditure Curve Be Bent? (with B. Woodward), Health Economics, 21(8), 1023–1029, 2012
[32]Debts on Debts (with J.R. Faria & Z. Wu), North American Journal of Economics & Finance, 23(2), 203–219, 2012
[33]Do Central Banks Affect Tobin's q? (with J.R. Faria, A.V. Mollick & A. Sachsida), International Review of Economics & Finance, 22(1), 1–15, 2012
[34]Language Skills and the Earnings Distribution Among Immigrants (with C. Wang), Industrial Relations, 50(2), 297–322, 2011
[35]Heterogeneity in Schooling Rates of Return (with D.J. Henderson & S. Polachek), Economics of Education Review, 30(6), 1202–1214, 2011
[36]Is the Quantity-Quality Trade-off a Trade-off for All, None, or Some? (with D.L. Millimet), Economic Development and Cultural Change, 60(1), 155–195, 2011
[37]Sex and Environmental Policy in the U.S. House of Representatives (with P.G. Fredriksson), Economics Letters, 113(3), 228–230, 2011
[38]Are Politicians Office or Policy Motivated? The Case of U.S. Governors' Environmental Policies (with P.G. Fredriksson & K.A. Mamun), Journal of Environmental Economics and Management, 62(2), 241–253, 2011
[39]Time Series Analysis of Income Convergence in China (with H. Liu), Applied Economics Letters, 17(1), 2010
[40]Economic Reform, Growth and Convergence in China (with E. Maasoumi), Econometrics Journal, 11(1), 128–154, 2008
[41]Fertility and the Health of Children: A Nonparametric Investigation (with D.J. Henderson, D.L. Millimet & C. Parmeter), Advances in Econometrics, 21, 167–195, 2008
[42]Is there a risk-return trade-off? Evidences from Chinese stock markets (with H. Liu & D. Kong), Frontiers of Economics in China, 3(1), 1–23, 2008
[43]Fertility and Employment Choice: A Differential Game Approach (with J. Faria), Economics Bulletin, 10(8), 1–8, 2007
[44]A Distributional Analysis of the Gender Earnings Gap in Urban China (with D.L. Millimet), B.E. Journal of Economic Analysis & Policy, 5(1), 2006
[60]R&RBeyond Common Support: An Iterative Approach to Identification and Estimation of Nonseparable Models with Endogeneity (with J. Zeng), Journal of Business & Economic Statistics
[45]WIPSufficient Statistical Measures of Intergenerational Mobility: The Case of Denmark (with S. Eshaghnia, J. Heckman & E. Maasoumi)
[46]WIPLove Has No Boundaries: Racial Assortative Mating and Intergenerational Mobility (with D. Xie)
[47]WIPEnvironmental Roots of Intergenerational Mobility (with D. Xie)
[48]WIPMaternity Leave and Child Health in India (with E. Asker & S. Dhongde)
[49]WIPThe Impact of Immigration on Natives' Labor Market Outcomes: A Causal Machine Learning Approach (with C. Wang)
[50]WIPBorn to Lose: Daughters and Divorce (with D. Xie)
[51]WIPA Functional Quantile Approach to Estimating Intergenerational Mobility (with P. Du & P. Sang)
[52]WIPSufficient Statistical Measures of Intergenerational Mobility (with E. Maasoumi)
[53]WIPEstimation and Testing in the Presence of an Invalid Instrumental Variable (with R. Fan)
[54]WIPPartially Linear Varying-Coefficient Fixed Effects Panel Data Models with Sample Selections (with K. Yan & S. Dhongde)
[55]WIPBreaking Parallel: A Nonparametric Difference-in-Differences Approach (with X. Xing)
[56]WIPA L-infinity Norm Counterfactual and Synthetic Control Approach (with Y. Ye & X. Xing)
[57]WIPTree-based Difference-in-Differences Approach
[58]WIPSIMAGENT: Towards Multi-Agent LLM for Real-World Stakeholder Debate Simulations without Ground Truth (with P. Pitre, L. Zhang, N. Ramakrishnan & X. Wang)
03

Leadership & Institution-Building

Virginia Tech · 2023–Present

Kohl Centre — From Vision to Reality

Transformed the Kohl Centre from a defunct entity into a comprehensive interdisciplinary hub integrating research, teaching, and external partnerships. Launched, led, and coordinated interdisciplinary research initiatives that elevate academic excellence across campus. Launched multiple experiential learning programs. Manages multiple foundation accounts, and sponsored research funding. Built strategic partnerships with government agencies, industry, and community stakeholders.

Virginia Tech · 2025–Present

Data Science for the Public Good Program

Directs a USDA funded flagship experiential learning program that has supported 30 student fellowships, connecting students with public agencies, nonprofits, and industry partners for project-based learning. Programs nominated for the University Exemplary Program Award and Diggs Teaching Scholar Program.

U of Oklahoma · 2016–2023

4+1 BA/MA in Managerial Economics with Big Data

Designed and launched one of the nation's early programs integrating machine learning and causal inference into applied economics. Oversaw all aspects from curriculum development and admissions to research advising and job placement.

Philosophy

Leadership Through Trust & Shared Governance

Grounded in transparency, shared governance, and careful stewardship. Views academic leadership as relying on persuasion rather than command, trust rather than hierarchy.

2022–Present
Board of Trustees
Southern Economic Association
2018–Present
Director, Young Scholars Program
Global Labor Organization
04

Teaching & Mentorship

Professor Wang teaches at every level — from undergraduate principles to Ph.D. econometrics — with a consistent emphasis on integrating rigorous theory with modern quantitative and data analytical tools and real-world application. His teaching evaluations include perfect scores at both undergraduate and graduate levels.

As an advisor, he has chaired or co-chaired more than 30 Ph.D dissertations and theses. His former students hold positions at institutions including the Federal Housing Finance Agency, the World Bank, Amazon, TransUnion, and numerous universities across the U.S. and abroad.

🏆

3× Outstanding Professor Award

Chosen by graduating MA class at UNH (2009, 2011, 2013)

🎓

Presidential Professorship

University of Oklahoma — pedagogy & curriculum innovation

📐

Curriculum Innovator

Pioneered 4+1 ML + causal inference economics program

Courses

Ph.D.
Econometrics II: Causal Inference
Virginia Tech · 2023–Present

Advanced treatment of causal inference methods for doctoral students, covering potential outcomes, instrumental variables, regression discontinuity, difference-in-differences, synthetic control, and modern causal machine learning approaches.

Masters
Statistics for Data Science (with R)
University of Oklahoma · 2016–2023

Applied statistics course using R for data science, covering data wrangling, visualization, statistical modeling, and decision-making frameworks for management and policy contexts.

Masters
Machine Learning & Causal Inference (with R)
University of Oklahoma · 2016–2023

Integrated course combining predictive analytics, machine learning algorithms, and modern causal inference methods with hands-on R programming for applied economists.

Ph.D.
Econometrics I
University of Oklahoma · 2016–2023

Core Ph.D. econometrics sequence covering probability, statistical inference, and the linear and nonlinear regression models with applications.

Teaching Evaluations

Consistently outstanding evaluations including perfect scores at both undergraduate and graduate levels across four institutions.

View Evaluations
05

Tutorials & Resources

Applied tutorials in R and Quarto covering econometric methods, data science tools, and reproducible research workflows — built from coursework and research practice.

06

Editorial & Professional Service

Co-Editor
China Economic Review
2020 – Present
Co-Editor
Journal of Labor Research
2019 – Present
Associate Editor
Econometric Reviews
2014 – Present

Get in Touch

I welcome inquiries about research collaboration, speaking engagements, and academic leadership opportunities.

Curriculum Vitae

Full academic CV with complete publication list, grants, advising record, and service.

Download CV (PDF)