جست‌وجوی استاد و پژوهشگر

• Econometrics
• Microeconometrics
• Partial Identification
• +۳ مورد دیگر

Adam M. Rosen is a Professor of Economics at Duke University's Department of Economics, where he has served since 2019. Previously, he held academic roles at University College London (UCL), including Associate Professor (2013–2016) and Assistant Professor (2006–2013). He is an affiliated researcher with the Centre for Microdata Methods and Practice (CeMMAP) and the Institute for Fiscal Studies (IFS). His research focuses on econometric theory and applications, particularly in instrumental variable methods, partial identification, and structural models. Rosen earned his Ph.D. in Economics from Northwestern University (2006) and a B.A. in Economics and Mathematics with Computer Science from Cornell University (1999). His work has been published in top journals such as the Review of Economic Studies, Econometrica, and the Journal of Econometrics. He has received numerous awards, including Fellow of the Journal of Econometrics (2024) and the Best Associate Editor Award (2024). Rosen's research interests span econometric theory, partial identification, instrumental variables, and applied microeconometrics. His recent work includes advancements in IV methods for Tobit models, discrete choice models, and counterfactual analysis. He has advised over a dozen PhD students and contributes actively to professional service, including editorial roles at the Journal of Econometrics and Econometrics Journal. He has held grants from the European Research Council and ESRC, among others, and his teaching spans advanced econometrics courses at both UCL and Duke. His affiliations with CeMMAP and IFS reflect his commitment to advancing microdata methods and policy analysis.

• Econometrics
• Econometric and statistical methods
• Economics
• +۳ مورد دیگر

Andrew Chesher is the William Stanley Jevons Professor of Economics and Economic Measurement at University College London (UCL) and holds Honorary Professor status at Beihang University. He previously served as Professor of Econometrics at the University of Bristol (1984–1999) and Lecturer in Econometrics at the University of Birmingham (1971–1983). He earned a Bachelor of Social Science from the University of Birmingham (1970) and a Doctor of Science, Honoris Causa from the University of Birmingham (2017). His research focuses on econometric methods, structural modeling, measurement error analysis, and applied microeconometrics. Key contributions include work on instrumental variable methods, panel data analysis, and applications in transportation economics, population policy, and market structure. Chesher has advised international agencies like the World Bank and UNDP, contributing to real-world policy solutions. He is a Fellow of the British Academy, Econometric Society, and Academy of Social Sciences. Chesher founded UCL’s Centre for Microdata Methods and Practice (2000), a global leader in econometric methodology. His awards include the 2017 Doctor of Science (honoris causa) and leadership roles such as President of the Royal Economic Society (2016–2018). Research highlights include modeling highway maintenance costs in Brazil/India (World Bank), Malaysia’s marriage/fertility policies (UNDP), and private-sector efficiency studies with firms like EDF Energy and regulators like Ofcom. His work bridges theory and practice, emphasizing robust methods for endogeneity, discrete choice models, and incomplete data scenarios.

João Santos Silvaمشاهده پروفایل

استاد

• Econometrics
• Applied Economics
• Quantile Regression
• +۴ مورد دیگر

Professor João Santos Silva is a Professor in Economics at the University of Surrey, Department of Economics. His academic journey includes a PhD in Economics from the University of Bristol (1992), a Master's in Applied Mathematics from the Technical University of Lisbon (1988), and a Bachelor's in Economics from the same institution (1985). Prior to Surrey, he taught at the Technical University of Lisbon and the University of Essex. His research focuses on theoretical and applied microeconometrics, with notable contributions in quantile regression, count data models, gravity equations in trade, and mode regression. He co-authored the seminal paper "The Log of Gravity" , recognized as a Classic in Economics. Silva has developed several Stata modules, including fqreg and ppml , advancing econometric software tools. He teaches courses such as ECOM042: Econometrics I and ECOM066: Advanced Econometrics 2. His work has been published in top journals like the Review of Economics and Statistics and Journal of Econometrics . Notable contributions include addressing endogeneity in count data models, machine learning applications in trade research, and analysis of price stickiness in firms. Silva’s research emphasizes methodological rigor and practical relevance in economic analysis.

• Discrete Choice Econometrics
• Transportation Economics
• Urban Economics
• +۲ مورد دیگر

Mogens Fosgerau is a Professor at the Department of Economics, University of Copenhagen, with a research focus on discrete choice theory, rational inattention, transportation and urban economics, congestion modeling, and entropy-based frameworks. He has held an ERC Advanced Grant (2017-2023) and completed a Grand Solutions project for the Innovation Fund Denmark (2016-20). Education: Mathematical Economics (Aarhus University, 1990), PhD in Mathematics (University College London, 1992). Current affiliations: Department of Economics (University of Copenhagen), Faculty of Social Sciences. Former roles: Guest Professor at DTU (2022-2023), member of the Commission for Green Transition of Passenger Cars (2019-2021). His research explores the intersection of information theory and discrete choice models, addressing complex substitution patterns and endogeneity issues through generalized entropy frameworks. He applies these models to transportation planning, urban economics, and climate policy analysis. Recent publications focus on perturbed utility models, inverse product differentiation logit, and rational inattention in spatial choice contexts. His work bridges theoretical econometrics with practical transport and environmental policy challenges. Awards: Recipient of the 2021 Transportation Science Meritorious Service Award. Former Editor-in-Chief of Economics of Transportation (2012-2020). Advising and Grants: Leads research projects funded by the European Research Council and Innovation Fund Denmark. Has participated in policy committees including the Danish Environmental Economic Council (2019-2025) and the Committee on Public Transport Mobility (2023-24).

Bryan S. Grahamمشاهده پروفایل

استاد

• Econometrics
• Social Networks
• Inequality Measurement
• +۴ مورد دیگر

Bryan S. Graham is a Professor in the Department of Economics at the University of California, Berkeley, where he has held faculty positions since 2005, progressing from Assistant Professor to his current full Professor rank in 2017. His research focuses on the econometrics of social interactions and networks, with particular expertise in measuring the effects of stratification on inequality. He is an active member of the Inequality: Measurement, Interpretation, and Policy (MIP) Network and contributes significantly to the field of network econometrics. Professor Graham's educational background reflects exceptional academic achievement: B.A. in Quantitative Economics from Tufts University (1997), Summa Cum Laude, Phi Beta Kappa M.Phil. in Economics from Oxford University (2000) as a Rhodes Scholar Ph.D. in Economics from Harvard University (2005) His research program bridges theoretical econometric advances with practical applications to economic policy questions. Graham has pioneered methods for analyzing network data, identifying social interactions, and measuring segregation effects. His work appears in top journals including Econometrica, Review of Economic Studies, and Journal of Econometrics. He has authored the influential Handbook of Social Economics chapter on network econometrics and co-edited the comprehensive volume 'The Econometric Analysis of Network Data' (2020). Professor Graham's publications reveal a consistent focus on developing methodological tools for analyzing social networks and peer effects, with increasing sophistication in handling complex network structures and addressing identification challenges. His recent work has expanded into practical applications in education policy and spatial inequality while maintaining theoretical rigor in econometric methodology. His scientific contributions have been recognized through prestigious awards including election as Fellow of the International Association of Applied Econometrics (2023) and multiple competitive National Science Foundation grants totaling over $1 million. Early career recognition included the Rhodes Scholarship, Fulbright Scholarship, and National Science Foundation Graduate Fellowship. As an educator, Graham teaches undergraduate and graduate econometrics courses at UC Berkeley and has developed specialized short courses internationally on econometric methods for social spillovers and network data. He has served on numerous editorial boards including as Co-Editor of the Review of Economics and Statistics (2014-2019) and has organized major conferences including the Berkeley-Stanford Econometrics Jamborees. Beyond academia, he maintains active research affiliations with the National Bureau of Economic Research, Center for Evaluation and Development at the University of Mannheim, and the Human Capital and Economic Opportunity Working Group at INET.

Mark Robertsمشاهده پروفایل

استاد

• Industrial Organization
• International Trade
• Firm Dynamics
• +۴ مورد دیگر

Mark Roberts serves as Professor of Economics at Pennsylvania State University and Director of the Federal Statistical Research Data Centers (RDC), overseeing critical infrastructure for confidential federal data access. His academic affiliation centers within the Department of Economics, where he conducts research on industrial dynamics and international trade. Roberts' research focuses on micro-level firm behavior , examining how R&D investment, export exposure, and market structure interact to influence productivity. Key themes include developing economy industrial evolution (particularly China), Swedish manufacturing dynamics , and long-term innovation impacts . His methodology emphasizes granular data analysis to uncover patterns in firm entry/exit and productivity spillovers. Analysis of his 15 most recent publications (2013-2025) reveals dominant economic research trajectories, with 14 articles concentrated in industrial organization and international trade. The sole outlier—a 2023 pediatric medicine paper—contrasts sharply with his core economic scholarship, suggesting possible co-authorship with another researcher sharing his name. His work consistently bridges theoretical economic models with empirical micro-data validation. As RDC Director, Roberts manages secure data facilities enabling high-impact social science research. His leadership connects academic inquiry with federal statistical resources, facilitating studies on business dynamics through integrated data systems as highlighted in his 2014 publication.

Ralf Wilkeمشاهده پروفایل

استاد

• Applied Econometrics
• Microeconometrics
• Labour Economics
• +۳ مورد دیگر

Ralf Wilke is a Professor in Applied Econometrics and Microeconometrics at the Copenhagen Business School , with affiliations to ZEW as a research associate. His career spans multiple institutions including the University of Leicester, University of Nottingham, and University of York. Education: Diplom-Volkswirt (Bonn University), DEA (University of Toulouse I), Dr. rer. pol. (Dortmund University) Current Roles: Professor at CBS, Research Associate at ZEW Prior Roles: Lecturer/Associate Professor at Leicester/Nottingham, Readership at York Research Focus: Specializing in econometric methods for analyzing duration data, competing risks, panel models with group structures, and applications in industrial life modeling. His work addresses complex censoring mechanisms and spatial diffusion patterns in historical economic contexts. Recent Publication Trends: Recent articles emphasize duration modeling with dependent censoring, copula-based competing risks frameworks, and structural econometric approaches to panel data. Key disciplines include computational statistics, quality engineering, and cliometrics.

Sorawoot Srisumaمشاهده پروفایل

دانشیار

• Econometrics
• Empirical Industrial Organizations
• Dynamic Discrete Choice Models
• +۳ مورد دیگر

Sorawoot Srisuma is an Associate Professor in the Department of Economics at the National University of Singapore (NUS). His research focuses on econometrics and empirical industrial organization, with particular emphasis on structural estimation, dynamic discrete choice models, and market structure analysis. He holds a PhD from the London School of Economics. Key research areas include the analysis of subjective well-being data, nonparametric identification in economic models, and the welfare effects of market frictions. His work often combines advanced econometric techniques with applications in industrial organization and development economics. Recent publications explore topics such as search models with heterogeneous agents, spatial autoregressions with varying coefficients, and the impacts of mental health policies. He is affiliated with the Institute of Operations Research and Analytics (IORA), part of NUS’s Smart Nation Research Cluster. His teaching areas include advanced econometrics, and he has contributed to methodological advancements in structural estimation, particularly in dynamic games and Markov decision processes.

• Health Economics
• Applied Microeconometrics
• Reproductive Health
• +۴ مورد دیگر

Matilde P. Machado is an Associate Professor in the Department of Economics at Universidad Carlos III de Madrid and Director of the Master in Health Assessment and Market Access. She holds a PhD in Economics from Boston University. Her research focuses on Health Economics, Applied Microeconometrics, and the intersection of Education, Labor, and Gender from an Economic History perspective. She led a CAF-funded project on 'Intergenerational Mobility in Latin America' with Ricardo Mora and Karen Olivo. Teaching includes undergraduate courses in Health Economics (taught in both Spanish and English) and postgraduate courses in Industrial Economics (in English). Recent work explores historical parish records to analyze female labor force participation and maternal influences. Her research spans topics such as hospital quality measurement, moral hazard in health services, and healthcare efficiency.

Danny McGowanمشاهده پروفایل

استاد

• Finance
• Financial Intermediation
• Banking
• +۱۰ مورد دیگر

Danny McGowan is Professor of Finance and Head of the Department of Finance at Birmingham Business School, University of Birmingham . He holds a PhD in Economics from the University of Nottingham and has a strong academic background in economics and finance. Education: PhD in Economics, University of Nottingham, 2010 MSc in Economics, University of Bristol, 2007 BSc in Economics, University of Bristol, 2003 His research centers on applied microeconomics with a focus on financial intermediation, banking, mortgage markets, and household finance . He frequently employs quasi-experimental methods to study the impact of regulation, competition, and institutional frameworks on financial institutions and markets. His recent work explores the societal determinants of wealth inequality, lending, and entrepreneurship, as well as the effects of deposit market competition and mortgage default. His publication record is impressive, with articles in leading journals such as the Review of Financial Studies , Journal of Financial and Quantitative Analysis , and Journal of Financial Intermediation . The recent articles show a consistent trend in analyzing bank conduct, risk management, regulation, and the real effects of financial markets , often using natural experiments and policy changes as identification strategies. Research Funding and Recognition: Principal Investigator on a ~£400,000 Leverhulme Research Project Grant Over £500,000 in research funding from ESRC, British Academy, and Leverhulme Trust Research cited in House of Commons inquiries and by media outlets Advising and Grants: He has successfully advised four PhD students to completion, all of whom have secured academic positions. His research is supported by major grants from UK research councils, demonstrating the significance and impact of his work in the field of finance. Professional Engagement: He is an active member of leading professional associations including the American Finance Association, American Economic Association, European Finance Association, and Royal Economic Society, and regularly presents his work at international conferences.

Marc Henryمشاهده پروفایل

استاد

• Microeconometrics
• Optimal Transport
• Inequality Measurement
• +۳ مورد دیگر

Marc Henry is a Liberal Arts Professor of Economics at Pennsylvania State University, serving as the Graduate Program Director in the Department of Economics. He holds a Ph.D. from the London School of Economics (1999). His research focuses on microeconometrics, optimal transport, inequality measurement, and environmental engineering applications in pollution control. Key research interests include the application of the Roy model to analyze occupational segregation and STEM participation, optimal transport theory for inequality measurement, and experimental design for nanoparticle removal in waste incineration systems. His work bridges econometric theory with practical policy analysis, particularly in gender economics and environmental technology. Recent publications highlight themes such as multidimensional inequality indices, hedonic equilibrium identification, and the design of scrubbers for particulate matter control. His contributions span both theoretical advancements (e.g., vector copulas, Sklar theorem extensions) and applied environmental engineering solutions. Dr. Henry’s research has been disseminated through venues like Google Scholar, with a focus on combining rigorous statistical methods with real-world policy implications. His academic activities include advising on graduate programs and maintaining a research website: https://sites.google.com/site/mabhenry/ .

Gauthier Lanotمشاهده پروفایل

استاد

• Empirical Micro-economics
• Econometrics
• Labour Economics
• +۳ مورد دیگر

Gauthier Lanot is a Professor at the Umeå School of Business, Economics and Statistics (USBE), Department of Economics, Umeå University. His research focuses on empirical micro-economics, econometrics, labour economics, public economics, and public finance. He holds a PhD from Université Louis Pasteur (1993) and has held positions at Keele University (UK), Laval University (Canada), and Queen's University Belfast (UK). He served as an associate editor for the Journal of the Royal Statistical Society Series A (2010-2013) and on the Danish National Centre for Social Research Advisory Board (2013-2016). His research explores topics such as tax incidence, minimum wage effects, pension policies, and labour market dynamics. Current projects include studies on electricity demand flexibility, military deployment impacts, and taxation responses. Lanot has taught courses like Industrial Economics and Microeconomics Analysis at both undergraduate and graduate levels. He secured grants from Forte and Handelsbanken in 2021, and is affiliated with the Economic Policy Network. Key contributions include analyses of retirement decisions in Denmark, lottery demand modeling, and evaluation of UK economic research performance. His work bridges theoretical econometric methods with applied policy analysis, emphasizing empirical rigor in public finance and labour market studies.

Hyungsik Roger Moonمشاهده پروفایل

استاد

• Econometrics Theory
• Applied Econometrics
• Labor Economics
• +۵ مورد دیگر

Hyungsik Roger Moon is Professor of Economics in the Department of Economics at the University of Southern California's Dornsife College of Letters, Arts and Sciences, where he has served since 2000 after beginning his career at UC Santa Barbara. His academic trajectory progressed from Assistant Professor (2000) to Associate Professor (2004) and full Professor (2008), reflecting sustained contributions to econometric methodology. His educational foundation includes: Ph.D. in Economics, Yale University, 1998 M.A. in Economics, Yale University, 1995 B.A. in Economics, Seoul National University, 1989 Moon's research centers on econometric theory development and applied methodology, with particular expertise in panel data analysis, dynamic modeling, and high-dimensional estimation. His theoretical innovations address complex challenges in interactive fixed effects, unit root testing, and heterogeneity modeling, while applied work spans labor economics (income dynamics), health economics (pancreatic cancer trials), and macroeconomics (Covid-19 forecasting). This dual focus bridges rigorous mathematical frameworks with real-world policy applications across multiple economic subfields. Analysis of recent publications reveals an intensifying focus on robust estimation techniques for dyadic data, Bayesian approaches to sparse heterogeneity, and methodological innovations in forecasting with censored panel data. His work increasingly integrates machine learning concepts with traditional econometrics, particularly in high-dimensional seemingly unrelated regression systems and network-based peer effect modeling. His distinguished scientific contributions have been recognized through: Fellow of the Econometric Society (2023) Fellow of the Journal of Econometrics (2019) RK Cho Economics Award (2018) Maekyung/KAEA Economist Award (2012) Econometric Theory Multa Scripsit Award (2006-2007) Korea-America Economic Association Young Scholar Award (2005) Moon has secured significant research funding including an NSF grant of $180,675 for 'Forecasting with Dynamic Panel Data Models' (2016-2020) and $68,000 for 'Asymptotic Analysis of Panel Regression Models' (2009-2010). His academic leadership extends to editorial roles at the Journal of Business and Economic Statistics, Econometric Theory, and Journal of Econometrics, plus administrative service as Director of Graduate Studies for USC's Economics Ph.D. program (2018-2021) and Associate Director of USC Dornsife INET (2015-2017). Through his position at USC Dornsife INET and graduate program leadership, Moon actively shapes research directions in new economic thinking while mentoring future econometricians through advanced courses like Big Data Econometrics.

• Labor Economics
• Unemployment
• Wages
• +۴ مورد دیگر

Pedro Portugal is an Adjunct Professor of Economics at Nova School of Business and Economics and a Senior Researcher at the Bank of Portugal. He holds a PhD in Economics from the University of South Carolina (1991) and an Agregação from Universidade do Porto (1999). His research focuses on applied labor economics, including unemployment dynamics, wage bargaining, microeconometric methods, and drug policy. He has published extensively in top journals like the American Economic Review and the Journal of Labor Economics. His work often explores worker displacement, firm survival, and labor market institutions. Portugal’s contributions include analyzing wage disparities, unemployment compensation systems, and the impact of drug decriminalization policies. He collaborates closely with institutions like the Bank of Portugal and international partners, contributing to policy-relevant economic analysis. Education: PhD in Economics, University of South Carolina, 1991 Agregação in Economics, Universidade do Porto, 1999 Master’s equivalent in Economics, Universidade do Porto, 1982 Research Interests: Portugal’s work spans microeconomic foundations of unemployment, wage determination mechanisms, and survival dynamics of firms. He employs advanced econometric techniques to analyze labor market structures, including the effects of collective bargaining, unemployment insurance systems, and labor contract types. His recent studies address wage persistence, gender wage gaps, and the socio-economic impacts of drug policy reforms. Grants and Collaborations: His research has been supported by international collaborations, including projects with the European Union and the Bank of Portugal. He frequently participates in policy forums addressing labor market challenges and economic recovery strategies post-recession. Labs/Teams: Leads research initiatives at the Bank of Portugal’s Economic Analysis Department, focusing on macroeconomic and labor market modeling. Collaborates with global institutions like IZA Institute of Labor Economics and the European Economic Association.

Whitney Neweyمشاهده پروفایل

استاد

• Econometrics
• Machine Learning
• Causal Inference
• +۷ مورد دیگر

Whitney Newey is the Ford Professor of Economics at the Massachusetts Institute of Technology (MIT) and a Research Associate at the National Bureau of Economic Research (NBER). He holds affiliations with multiple prestigious institutions, including fellowships with the American Academy of Arts and Sciences, the Econometric Society, and the International Association of Applied Econometrics. His research focuses on advanced econometric methodologies, particularly in structural and causal parameter estimation, machine learning integration, and high-dimensional regression analysis. Dr. Newey’s academic career includes roles as co-editor of Econometrica and program co-chair for the 2005 World Congress of the Econometric Society. His work bridges theoretical econometrics and applied policy analysis, addressing topics such as taxable income elasticity, demand modeling, and semiparametric estimation techniques. Notable achievements include the 2020 American Economic Association Distinguished Fellow award and the Sloan Foundation Research Fellowship. His publications span leading journals such as Quantitative Economics , Econometrica , and Journal of Political Economy , reflecting contributions to both foundational econometric theory and practical policy evaluation. His advisory roles include mentoring through MIT’s Department of Economics, though specific advisee names are not listed in available materials. Current research emphasizes debiased machine learning applications and inference methods in complex economic models.