جست‌وجوی استاد و پژوهشگر

Enrico Vaninoمشاهده پروفایل

مدرس ارشد

• Applied Microeconometrics
• International Economics
• Economic Geography
• +۵ مورد دیگر

Dr Enrico Vanino is a Senior Lecturer in Economics at the University of Sheffield's School of Economics, appointed in 2019. He holds a PhD in Economics from the University of Birmingham (2016) and has prior affiliations with the London School of Economics (LSE) and the National Institute of Economic and Social Research (NIESR). His roles include organizing the Sheffield Economic Research Paper Series and economics seminars. Enrico specializes in applied microeconometrics, focusing on international economics, economic geography, and regional development. Education: Bachelor's in International Economics, University of Padova (2009) MSc in Economics, University of Birmingham (2011) PhD in Economics, University of Birmingham (2016) Research interests span firms' behavior under globalization, trade policy impacts, and spatial economic disparities. He examines topics like trade defense instruments, infrastructure-driven economic diversification, and environmental adaptation strategies. Enrico collaborates with institutions like LSE's Department of Geography and Environment and has published in journals such as Economica and Journal of International Economics . Teaching: Enrico teaches Research Methods and Introductory Econometrics, emphasizing real-world applications and linking coursework to cutting-edge research. He actively supervises PhD students in microeconometrics, trade, and development economics. Affiliations: In addition to the University of Sheffield, he is affiliated with LSE and collaborates with NIESR on external research projects.

Ivan Jeliazkovمشاهده پروفایل

دانشیار

• Bayesian Econometrics
• Markov chain Monte Carlo
• Econometric Modeling
• +۴ مورد دیگر

Ivan Jeliazkov is an Associate Professor of Economics and Statistics at the Department of Economics, University of California, Irvine. His research focuses on Bayesian econometrics and simulation-based inference, emphasizing methodologies like Markov chain Monte Carlo and econometric modeling. He holds a Ph.D. in Economics from Washington University in St. Louis and a BA in Economics and Business Administration from Coe College. His key research areas include Bayesian Econometrics, advanced simulation techniques, and causal inference applications. Notable work addresses heteroskedasticity in causal studies, quantile analysis of rental markets, and simultaneous equation models for discrete data. Recent advising includes 2024 Ph.D. graduates Robert MacDonald, Parush Arora, and Jieyu Gao. His articles span topics like dynamic factor models, regression discontinuity designs, and model comparison techniques. He has contributed to interdisciplinary research in marketing, finance, and historical economic analysis. His methodological innovations emphasize practical applications of Bayesian methods to address econometric challenges such as uncertainty quantification and model specification. Current work continues advancing computational tools for complex econometric problems.

Emmanuel Guerreمشاهده پروفایل

استاد

• Theoretical Econometrics
• Applied Econometrics
• Empirical Industrial Organization
• +۴ مورد دیگر

Emmanuel Guerre is a Professor at the School of Economics and Finance at Queen Mary University of London. His research focuses on theoretical and applied econometrics, with emphasis on nonparametric methods, auction models, quantile regression, and time series analysis. He has contributed to advancements in nonparametric identification and inference for auctions, particularly through rate-optimal estimation techniques and quantile-based approaches. His work has been published in leading journals such as the Annals of Statistics , Econometrica , and the Review of Economic Studies . Education: PhD in Statistics, University of Paris (Paris 6, Université Pierre et Marie Curie) BSc in Economics and Statistics, ENSAE Research interests include nonparametric identification in auctions, optimal testing for time series, and quantile methods. He is an associate editor for Econometric Theory and the Journal of Econometrics . Awards: Journal of Econometrics Zellner Award (2022-23) for the paper Quantile regression methods for first-price auctions Publications highlight contributions to auction modeling, quantile regression, and nonparametric estimation techniques, reflecting his expertise in both theoretical and applied econometrics.

Alexandre Poirierمشاهده پروفایل

دانشیار

• Econometrics
• Causal Inference
• Quantile Regression
• +۳ مورد دیگر

Alexandre Poirier is the Provost’s Distinguished Associate Professor of Economics at Georgetown University, where he has held positions since 2018. He previously served as an Assistant Professor at the University of Iowa (2013–2018). He holds a Ph.D. in Economics from UC Berkeley (2013), an M.A. in Statistics (2011), and a B.Sc. in Mathematics and Economics from Université de Montréal (2007). His research focuses on econometric theory, causal inference, and sensitivity analysis, with publications in top journals like Econometrica , Journal of Econometrics , and Quantitative Economics . He develops statistical software tools, including Stata modules regsensitivity and tesensitivity , and serves as an Associate Editor for Journal of Business & Economic Statistics and Econometric Reviews . His work emphasizes robustness to unconfoundedness assumptions and omitted variable bias. He teaches advanced econometrics at the Ph.D. and undergraduate levels, including courses on causal inference and panel data methods. Education Ph.D. in Economics, UC Berkeley, 2013 M.A. in Statistics, UC Berkeley, 2011 B.Sc. in Mathematics and Economics, Université de Montréal, 2007 Research Interests Prof. Poirier’s research bridges econometric theory and applied methods, with a focus on identifying causal effects under relaxed assumptions. Key areas include quantile regression, instrumental variables, sensitivity analysis for unobserved confounding, and panel data models. His work often addresses practical challenges in policy evaluation, such as omitted variable bias and endogeneity. Recent contributions include frameworks for comparing sensitivity parameters and assessing robustness of treatment effect estimates. Grants and Software Developed regsensitivity and tesensitivity Stata packages for regression and treatment effect sensitivity analysis Recipient of grants from the National Science Foundation and UC Berkeley’s Graduate Division Professional Service Associate Editor, Journal of Business & Economic Statistics (2021–present) Associate Editor, Econometric Reviews (2024–present) Moderator, arXiv Econometrics Section (2025–present) Referee for leading journals including American Economic Review , Econometrica , and Journal of the American Statistical Association

Bin Pengمشاهده پروفایل

استاد

• Econometrics
• Panel Data Analysis
• Time Series Analysis
• +۳ مورد دیگر

Bin Peng is a Professor in the Department of Econometrics and Business Statistics at Monash University. His research focuses on developing novel econometric models and methods, particularly in panel data analysis, time series econometrics, and climate data modeling. He holds a PhD in Econometrics from Monash University (2013) under Professors Giovanni Forchini and Don Poskitt, preceded by a BSc in Mathematics from Nanjing University (2007). His work addresses structural changes in factor models, time-varying parameters in vector error-correction frameworks, and productivity convergence in manufacturing sectors. Key contributions include nonparametric panel models for climate data and methodologies for handling interactive effects in panel data with general factors. Peng has received multiple Dean’s Awards, including the 2021 Early Career Research Excellence Award, 2023 Commendation for Excellence, and 2024 Researcher of the Year. He leads a 2021–2025 project on modeling time trends in panel data, funded by Monash University. His recent articles (2021–2025) emphasize methodological advancements in econometric theory, applied to climate science, economic growth, and macroeconomic policy.

Sofia Gouveiaمشاهده پروفایل

استادیار

• International Economics
• Monetary Integration
• Wine Economics
• +۴ مورد دیگر

Sofia Gouveia is an Assistant Professor in the Department of Economics, Sociology and Management at the University of Trás-os-Montes and Alto Douro (UTAD), Portugal. She is also a researcher at the Centre for Transdisciplinary Development Studies (CETRAD). Her expertise spans international economics, monetary integration, and wine economics, with a focus on econometric analysis of trade policies, regional development, and crisis impacts. Dr. Gouveia holds a PhD (2009) and Master’s (2001) in Economics from UTAD and the University of Porto, respectively. Her research emphasizes structural breaks in economic systems, spatial spillovers in agricultural efficiency, and the effects of global crises like COVID-19 on industries. She has participated in several major projects, including the VINCI and INNOVINE&WINE initiatives focusing on wine sector innovation and competitiveness. Her academic contributions include influential work on Port wine exports, non-tariff trade measures, and the interplay between European integration and demographic trends in peripheral regions. While no formal awards are listed, her extensive publications reflect sustained scholarly impact. She has collaborated extensively with institutions like CETRAD and contributed to interdisciplinary research hubs like Douro SocioEcoLL and Data4LowDensity. Her research agenda integrates empirical analysis with policy relevance, addressing issues such as firm performance under shocks, export dynamics, and the digital transformation of tourism sectors. She maintains an active role in both academic governance and applied projects bridging economic theory and regional development challenges.

Marco Caliendoمشاهده پروفایل

استاد

• Labor Market Policies
• Entrepreneurship
• Personality Traits and Economic Outcomes
• +۳ مورد دیگر

Prof. Marco Caliendo is a Professor of Empirical Economics at the University of Potsdam and a faculty member of the Berlin School of Economics (BSoE). He holds a PhD from Goethe University Frankfurt and is a Research Fellow at IZA, DIW Berlin, and IAB Nuremberg. His research focuses on labor market policies, entrepreneurship, personality traits' economic impacts, and microeconometrics. Education: Bachelor/Master in Economics at University of Manchester and Goethe University Frankfurt PhD in Economics (April 2005), Goethe University Frankfurt Key Roles: Director of Research at IZA (2009–2011) Program Director for 'Evaluation of Labor Market Programs' at IZA (2011–2023) Speaker of the Center for Economic Policy Analysis (CEPA) His research interests include labor market program evaluations, self-employment dynamics, unemployment behavior, and the role of personality in economic decisions. He has led projects like 'Evaluation of Startchancen Program' and studies on minimum wage impacts. His work emphasizes policy relevance, with over 21,000 Google Scholar citations (h-index 54) and top global rankings in RePEc. Publications span journals such as Review of Economics and Statistics and Journal of Human Resources , focusing on labor market interventions, entrepreneurship, and behavioral economics. His recent work addresses pandemic effects on self-employed mental health, minimum wage reforms, and start-up subsidy outcomes. Prof. Caliendo advises PhD students through workshops (e.g., IZA Entrepreneurship Research) and collaborates with institutions like CEPA and PCQR. His lab coordinates research on human capital investments and policy evaluation.

Margherita Fortمشاهده پروفایل

استاد

• Applied Microeconometrics
• Labour Economics
• Economics of Education
• +۳ مورد دیگر

Margherita Fort is a Full Professor at the Department of Economics at the University of Bologna. She specializes in applied microeconometrics, labor economics, and education economics with a focus on public policy evaluation. Her research investigates the impacts of daycare on child development, educational reforms on fertility and health outcomes, and gender disparities in STEM fields. She holds a PhD in Applied Statistics from the University of Padua and has been a Marie Curie Fellow (ISER, Essex) and Max Weber Fellow (European University Institute). Education includes a PhD in Applied Statistics (University of Padua) and postdoctoral fellowships at ISER and EUI. Her current projects focus on evidence-based investments in early childhood and family policies, including evaluations of coding programs for girls and mindfulness interventions for parents. Research affiliations include IZA, CESifo, and CEPR. She coordinates the PhD program in Public Governance at Bologna and teaches econometrics, causal inference, and microeconometrics for policy evaluation at national and international institutions. Her work has appeared in top journals like the Journal of Political Economy and Journal of Labor Economics. Awards: Marie Curie Early Training Fellowship, Max Weber Fellowship Grants: Spencer Foundation (2020-2024), Fondazione Del Monte Bologna e Ravenna (2014) Labs/Teams: Collaborates with FBK-IRVAPP on policy evaluation and with international networks on school reforms.

Hiroaki Kaidoمشاهده پروفایل

دانشیار

• Econometric Theory
• Microeconometrics
• Empirical Finance
• +۲ مورد دیگر

Hiroaki Kaido is an Associate Professor in the Department of Economics at Boston University. He received his Ph.D. from UC San Diego and specializes in econometric theory and microeconometrics. His methodological research focuses on partial identification of economic models, robust inference techniques, and development of computational approaches for complex econometric settings. He has created novel estimation procedures for models with set-valued predictions and misspecification.

James A. Duffyمشاهده پروفایل

دانشیار

• Econometrics
• Macroeconometrics
• Time Series Analysis
• +۵ مورد دیگر

James A. Duffy is an Associate Professor of Economics at the University of Oxford and the Andrew Glyn Tutorial Fellow at Corpus Christi College. He joined Corpus in 2016 after a postdoctoral fellowship at Nuffield College, Oxford, and holds dual appointments in the Department of Economics and his college. His educational background includes: PhD in Economics from Yale University (2014) Undergraduate studies in Economics and Mathematics at the University of Sydney Duffy's research centers on econometrics, with emphasis on macroeconometrics and time series analysis. He develops statistical methods for economic models involving nonlinear or highly persistent time series data, common in macroeconomics and finance. His work spans econometric theory , mathematical statistics , cointegration , and structural macroeconomic models , addressing inference challenges in strongly dependent processes. His 2016-2024 publications in premier journals reveal consistent innovation in time series methodology, particularly in unit root processes, fractional integration, and nonlinear cointegration. Key contributions include Tobit modeling for dynamic systems, robust inference for weakly nonstationary data, and discrete choice estimation techniques, bridging theoretical rigor with empirical applications. At Oxford, Duffy serves as course convenor for Quantitative Economics and lectures for the MPhil programme on instrumental variables, generalized method of moments, and maximum likelihood estimation. He also provides undergraduate tutorials in Microeconomics and Quantitative Economics at Corpus Christi College, integrating research insights into teaching.

• Econometrics
• Macroeconometrics
• Microeconometrics
• +۷ مورد دیگر

Grigory Gelmutovich Kantorovich is a distinguished Research Professor at the National Research University Higher School of Economics (HSE), where he has been working since 1993. He serves as Head of the Scientific and Educational Laboratory of Macrostructural Modeling of the Russian Economy within the Faculty of Economic Sciences. He holds a tenured professorship since 2018 and has been recognized as a Distinguished Professor by HSE. With 54 years of scientific and teaching experience, Kantorovich has made significant contributions to the field of econometrics and economic modeling. His educational background includes a Candidate of Physical and Mathematical Sciences degree (1974) from Moscow Institute of Physics and Technology, where he specialized in Automatic Regulation and Control Theory. He graduated with honors from the same institution in 1971 with a degree in Flight Dynamics and Motion Control of Aircraft. His extensive professional development includes numerous international programs at Erasmus University Rotterdam, University of Paris 1 - Sorbonne, Harvard University, and the London School of Economics. Kantorovich's research spans multiple areas of econometrics, including macroeconometrics, microeconometrics, financial econometrics, and time series modeling. His work focuses on dynamic modeling of economic development, macrostructural modeling of the economy, and econometric modeling of socio-economic processes. His publications demonstrate a consistent focus on applying rigorous statistical methods to economic problems, with particular attention to risk evaluation in financial markets, structural shifts in time series, and the impact of investments on economic efficiency. Throughout his career, Kantorovich has received numerous prestigious awards including the Medal of the Order "For Merits to the Fatherland" (both I and II degrees), multiple Honorary Certificates from HSE, and recognition as Best Teacher in multiple academic years. He was awarded the "Golden HSE" Award twice for his contributions to teaching and school development. As an academic advisor, Kantorovich has supervised doctoral research and mentored students including Lana Zakharova (on economic crises determinants), Nikolai Shugal (on gross value added modeling), and Elena Nazrullaeva (on capital investments impact). He has also participated in numerous international research projects, including a World Bank project on energy price impacts and grants from the MacArthur Foundation. He leads the Scientific and Educational Laboratory of Macrostructural Modeling of the Russian Economy, where he conducts research on economic modeling and advises on policy-related economic issues. His work bridges theoretical econometrics with practical applications in Russian economic policy and education.

• Econometric Theory
• Time Series Analysis

Majid Al-Sadoon serves as Associate Professor and Director of Research at Durham University Business School. His academic trajectory includes a PhD from Cambridge University (2011), Assistant Professorship at Universitat Pompeu Fabra, and Robert Solow Postdoctoral Fellowship at Cambridge. He maintains active research in econometrics with publications in Journal of Econometrics, Econometric Theory, and Econometric Reviews. Education and Early Career: PhD, University of Cambridge (2011) Robert Solow Postdoctoral Fellow, University of Cambridge Assistant Professor, Universitat Pompeu Fabra His research centers on Econometric Theory and Time Series Analysis , developing innovative methodologies for linear rational expectations models through spectral and linear systems approaches. Key contributions include subspace Granger causality testing, consistent estimation for panel data with sample selection, and unified frameworks for rank testing, bridging theoretical econometrics with macroeconomic and financial applications. Publication trends (2014-2024) reveal progressive methodological sophistication: early geometric causality analysis evolved into advanced rational expectations modeling, with increasing focus on spectral solutions and structural identification. His work consistently addresses core challenges in dynamic systems while expanding into high-dimensional panel data and nonlinear model specification. Scientific Awards No awards documented in available materials. Dr. Al-Sadoon supervises doctoral candidate Guangrui Li, with mentorship focused on econometric theory applications. His sustained publication record indicates successful research funding for time series methodology projects, though specific grants aren't detailed. While no formal laboratory is mentioned, his collaborations with scholars like M. Hashem Pesaran demonstrate integration into international econometrics research networks.

Deniz Baglanمشاهده پروفایل

دانشیار

• Econometrics
• Nonparametric Econometrics
• Semiparametric Models
• +۴ مورد دیگر

Deniz Baglan is an Associate Professor of Economics and serves as the Director of Undergraduate Studies in the Department of Economics at Howard University, which is part of the College of Arts and Sciences. He holds a Ph.D. in Economics from the University of California, Riverside, and contributes significantly to econometric theory and its applications in macroeconomics and finance. Research Interests: His primary research lies in nonparametric and semiparametric econometric methods, particularly applied to panel data models. He investigates issues related to unobserved heterogeneity, dynamic modeling, and structural inference in economic and financial contexts. His work spans both theoretical developments and empirical applications, focusing on macroeconomic dynamics and empirical finance. Publication Trends: His recent scholarly output shows a consistent focus on advancing nonparametric techniques for panel data, including identification, estimation, and testing in models with fixed effects, time-varying parameters, and nonlinear structures. These contributions are published in notable journals such as Journal of Macroeconomics and Studies in Nonlinear Dynamics and Econometrics , reflecting a strong trajectory in methodological econometrics. Scientific Awards: No awards mentioned in the provided text. Advising and Grants: While specific students and grant details are not listed, his role as Director of Undergraduate Studies suggests active involvement in academic mentoring and curriculum development. As a faculty member publishing in top-tier econometrics journals, he likely contributes to research supervision at graduate levels and may participate in externally funded research projects. Labs and Research Teams: There is no mention of specific labs, research centers, or collaborative teams in the provided information.

Stéphane Bonhommeمشاهده پروفایل

استاد

• Microeconometrics
• Econometric Theory
• Labour Economics
• +۳ مورد دیگر

Stéphane Bonhomme is the Ann L. and Lawrence B. Buttenwieser Professor of Economics and the College at the University of Chicago's Kenneth C. Griffin Department of Economics. His research focuses on microeconometrics, econometric theory, and labor economics, with emphasis on latent variable modeling and panel data analysis. He holds a PhD from the University of Paris I, Panthéon-Sorbonne (2005). Key contributions include methodologies for handling unobserved heterogeneity in panel data, nonlinear persistence in consumption dynamics, and bias reduction in econometric models. His work has been published in top journals like Econometrica, Journal of Econometrics, and the Journal of Political Economy. Recent research explores grouped patterns of heterogeneity, firm-worker sorting effects, and functional differencing in networks. He is a Fellow of the Econometric Society (2017) and has developed widely used Stata/Python packages for bias correction and discrete heterogeneity estimation.

Ashesh Rambachanمشاهده پروفایل

استادیار

• Econometrics
• Machine Learning Applications in Economics
• Causal Inference
• +۲ مورد دیگر

Ashesh Rambachan serves as Assistant Professor of Economics at the Massachusetts Institute of Technology (MIT), with a visiting appointment at Stanford University's Department of Economics and SIEPR for the 2025-2026 academic year. His primary institutional affiliation remains MIT's Department of Economics. His research program integrates econometric theory with machine learning to advance causal inference methodologies, particularly in quasi-experimental designs and observational data analysis. Key focus areas include algorithmic fairness, structural model robustness, and the application of foundation models to economic problems. This interdisciplinary approach bridges theoretical econometrics with real-world policy evaluation challenges. Analysis of his publication trajectory reveals increasing engagement with AI-driven methodologies since 2020, marked by a shift toward foundation models and large language models in economic contexts. His work consistently addresses credibility gaps in causal estimation while expanding into behavioral economics and algorithmic decision-making frameworks, reflecting evolving priorities in computational social science. Scientific recognition includes: NeurIPS 2024 Spotlight Paper for "Evaluating the World Model Implicit in a Generative Model" No explicit details regarding student advising, grant funding, or laboratory affiliations appear in current public records. His teaching portfolio includes MIT PhD courses on Algorithms and Behavioral Science (14.163) and Statistical Methods in Economics (14.380), alongside undergraduate instruction in Algorithmic and Human Decision-Making (S.6041).