جست‌وجوی استاد و پژوهشگر

• Economics
• Finance
• Macroeconomic Modeling
• +۱۲ مورد دیگر

Dr. Rangan Gupta is a Professor at the University of Pretoria, with additional affiliations at institutions including the University of Ibadan, IPAG Business School, Eastern Mediterranean University, and the University of Cyprus. His research is supported by major global sponsors such as the National Research Foundation, National Science Foundation, and the World Bank Group. Research Interests: Dr. Gupta specializes in economics and finance, with deep expertise in macroeconomic modeling, financial econometrics, housing markets, international REITs, climate risks, and monetary policy transmission. His work bridges theoretical rigor with real-world applications, focusing on complex systems and nonlinear dynamics in financial and economic variables. Publication Trends: His recent research employs advanced modeling techniques—including LPPLS, GVAR, regularized VARs, and machine learning—to study market bubbles, pandemic impacts, calendar anomalies, oil shocks, and cryptocurrency's energy footprint. These works span disciplines from behavioral finance to environmental economics, reflecting a broad and evolving intellectual agenda. National Research Foundation Grant National Science Foundation Grant World Bank Group Sponsorship Advising and Grants: While specific students are not listed, Dr. Gupta leads numerous externally funded research projects, indicating active mentorship and team leadership. His high co-authorship rate (98.2%) suggests extensive collaboration across continents, fostering interdisciplinary and international research networks. Labs and Research Teams: Though no formal lab name is mentioned, Dr. Gupta operates within a large, globally distributed research team, evidenced by co-authorship clusters across Africa, Europe, and Asia. His work is central to advancing empirical finance and macroeconomic forecasting through innovative quantitative methods.

• Time Series Econometrics
• Cointegrated VAR Models
• Structural VAR/VECM Models
• +۳ مورد دیگر

Professor Ralf Brüggemann is a full-time faculty member at the University of Konstanz , holding the Chair of Statistics and Econometrics since October 2007. He completed his Habilitation in Time Series Econometrics at Humboldt-Universität zu Berlin in 2007 and received his Ph.D. in Economics in 2003 for work on VAR model reduction techniques. Education : Habilitation: "Topics in Time Series Econometrics", Humboldt University Berlin (2007) Ph.D.: Economics, Humboldt University Berlin (2003) Diplom: Economics, Humboldt University Berlin (1999) His research spans Time Series Econometrics with focus on Cointegrated VAR Models , Structural VAR/VECM , Forecasting Methods , and Empirical Macroeconomics . Key contributions include methodological work on structural identification, variable selection in high-dimensional VAR, and monetary policy analysis using microeconomic data. Recent publications address External instruments in SVAR identification (2022) Directed graphs for VAR variable selection (2022) Stochastic aggregation weights in forecasting (2023) Asymmetric impulse responses in European financial markets (2014) with methodological innovations in heteroskedasticity-robust inference and stochastic aggregation weights. Scientific Awards : Jean Monnet Fellow, European University Institute (2003-2004) He leads research on monetary policy transmission mechanisms and macroeconomic risk through collaborative projects with institutions like the German Research Foundation Collaborative Research Center 649 (2005-present) and serves as editor for the Journal of Economics and Statistics special issue on Economic Forecasts (2011).

Alexander Kriwoluzkyمشاهده پروفایل

استاد

• Empirical Macroeconomics
• Fiscal Policy
• Monetary Policy
• +۱ مورد دیگر

Alexander Kriwoluzky is Professor of Macroeconomics at Freie Universität Berlin and Head of the Department of Macroeconomics at the German Institute for Economic Research (DIW Berlin). He serves as Associate Editor at the European Economic Review, contributing to academic peer review in economics. His professional roles integrate research leadership with academic instruction. Education background includes: Ph.D. in Economics, Humboldt-Universität zu Berlin (2009) M.Sc. in Economics, Humboldt-Universität zu Berlin (2004) Research interests focus on three interconnected domains: Empirical Macroeconomics : Developing data-driven approaches to analyze economic systems Fiscal-Monetary Policy Interactions : Examining coordination mechanisms between government spending and central banking Climate Economics : Investigating macroeconomic impacts of environmental factors and policy responses His work frequently employs advanced econometric techniques including time-varying VAR and DSGE modeling to study policy transmission mechanisms. Publication analysis reveals consistent thematic focus across 12 recent articles (2012-2024): Primary emphasis on inflation dynamics under various policy regimes Significant contributions to understanding monetary-fiscal policy coordination Growing research thread on climate-related economic disruptions Methodological innovations in shock identification and model uncertainty At DIW Berlin, he leads a research department conducting policy-relevant macroeconomic analysis. Current teaching includes undergraduate courses in Monetary Theory and doctoral seminars in Advanced Macroeconomic Analysis.

• Econometrics
• Time Series Analysis
• Factor Models
• +۳ مورد دیگر

Philipp Gersing is a researcher at the Department of Statistics and Operations Research, University of Vienna. His academic work focuses on econometrics, time series analysis, and statistical modeling with applications in macroeconomic and financial data. He teaches courses in mathematics and econometrics at both undergraduate and graduate levels. Current courses: Mathematics 1, Introductory Econometrics (MA) Advanced courses: Applied Econometrics 1 & 2, Seminar in Empirical Finance and Financial Econometrics (MA) His research specifically addresses challenges in generalized dynamic factor models, including identifiability conditions, distributed lag approaches, and the resolution of rotational indeterminacy issues. Recent work explores the canonical decomposition of factor models and the prevalence of weak factors in empirical applications. Publications demonstrate consistent contributions to factor modeling theory, with applications spanning macroeconometric analysis and financial data processing. Key themes include mixed-frequency data integration, non-stationary time series handling, and structural identification in multivariate systems.

Annari de Waalمشاهده پروفایل

مدرس

• Macroeconomics
• Monetary Policy
• Econometrics
• +۳ مورد دیگر

Dr Annari de Waal is a Lecturer in the School of Economics at The University of Queensland. She holds a PhD in Economics from the University of Pretoria, complemented by a Graduate Certificate in Learning and Teaching in Higher Education from Swinburne University of Technology. Her research focuses on South African macroeconomic policies, particularly monetary policy independence and the impact of global economic shocks on emerging economies. She employs advanced econometric models such as DSGE and Global VAR frameworks to analyze inflation dynamics and output forecasting. Her publications appear in journals like Applied Economics Letters and Emerging Markets Finance and Trade . Currently, she is not available for student supervision. Dr de Waal’s work bridges theoretical economic modeling with practical policy analysis, emphasizing South Africa’s integration into the global economy. Education: Doctor of Philosophy (Economics), University of Pretoria Graduate Certificate in Learning and Teaching (Higher Education), Swinburne University of Technology Masters (Coursework) in Econometrics, University of Pretoria Bachelor (Honours) in Econometrics, University of Pretoria Bachelor of Statistics, University of Pretoria Research Interests: Dr de Waal’s research investigates the transmission mechanisms of global economic shocks to domestic economies, with a focus on South Africa. She explores how monetary policy frameworks respond to external pressures, particularly using structural models like DSGE and vector autoregression (VAR) techniques. Her work also evaluates the effectiveness of inflation targeting policies and the role of foreign variables in domestic economic forecasting. She emphasizes methodological rigor in econometrics, often integrating time-varying parameters to capture evolving trade dynamics.

• Public Economics
• Tax Policy
• Computable General Equilibrium Modeling
• +۳ مورد دیگر

María Teresa Álvarez Martínez is an Associate Professor in the Department of Economics, Quantitative Methods and Economic History at the University of Pablo de Olavide, specializing in public economics, tax policy, and environmental economics through advanced computational modeling. Her doctoral research at Universitat Autònoma de Barcelona (2010) focused on An evaluation of public policies in Spain under Dr. Clemente Polo Andrés' supervision, establishing her expertise in fiscal policy analysis for the Spanish context. Research interests include: Corporate taxation and tax base erosion (BEPS) Digital service tax macroeconomic impacts Greenhouse gas emissions by economic sectors EU structural funds effects on regional economies Public deficit management in Spain Computable General Equilibrium (CGE) model development Her publication analysis reveals consistent focus on European Union fiscal policy using CGE and Social Accounting Matrix (SAM) methodologies, with increasing emphasis on environmental economics and digital taxation in recent years. Key collaborations include work with the European Commission's Joint Research Centre (JRC) on tax reform modeling. Scientific Awards: No specific awards documented in source materials Advising and grants activity shows doctoral thesis supervision and research funding for EU structural funds impact studies. Her work supports policy development through quantitative assessment of tax reforms and environmental-economic interactions. Labs and teams include development of the CORTAX model for corporate tax simulations and RHOMOLO database construction for EU-27 economic analysis, demonstrating integration of empirical data with policy-oriented computational frameworks.

• Econometrics
• Macroeconomic Forecasting
• Machine Learning in Economics
• +۷ مورد دیگر

Andreas Pick is an Associate Professor in the Department of Econometrics at the Erasmus School of Economics, Erasmus University Rotterdam. His research focuses on econometric modeling, macroeconomic forecasting, and machine learning applications in economics. He is actively contributing to the field through publications in top-tier journals and co-authoring with leading scholars in econometrics. His research interests include Macroeconomic Forecasting , Machine Learning in Economics , Bayesian Econometrics , Vector Autoregressions , Markov Switching Models , and Panel Data Forecasting . These areas reflect his expertise in developing and applying advanced statistical methods to economic data. The recent articles show a consistent focus on improving forecasting accuracy using machine learning, handling structural breaks, and optimizing forecasts in nonlinear models. His work bridges econometric theory with practical macroeconomic applications, particularly in nowcasting GDP and multi-step forecasting using high-dimensional datasets. Andreas Pick has supervised at least one student, as indicated by the 'Supervised Work' entry. He has collaborated with researchers such as Timmermann, Boot, and de Winter. There is no mention of specific grants, but his open-access publications and shared datasets suggest active research funding and collaboration. He maintains a personal website at https://apick.eu where more information about his work can be found. A dataset related to his 2018 paper on Markov switching models is publicly available on Figshare, indicating transparency and reproducibility in his research.

Jorge Caiadoمشاهده پروفایل

دانشیار

• Applied Mathematics
• Data Science
• Statistics
• +۵ مورد دیگر

Dr. Jorge Caiado is an Associate Professor with Aggregation at ISEG Lisbon School of Economics and Management (University of Lisbon). He specializes in Applied Mathematics, Data Science, and Financial Econometrics. He coordinates the Applied Artificial Intelligence and Machine Learning postgraduate program at ISEG Executive Education and is an integrated researcher at CEMAPRE (Center for Applied Mathematics in Economics and Finance). Education: PhD in Applied Mathematics to Economics and Management (ISEG, 2006) Aggregation in Mathematics (Econometrics focus, 2021) Bachelor of Business Administration (Universidade Internacional, 1994) Research Interests: Focus on machine learning, time series analysis, financial markets volatility modeling, and clustering techniques. Applies methods like GARCH models, VAR analysis, and spectral metrics to problems in economics, finance, and environmental policy. Recent work explores financial inclusion in Mozambique, global stock market dynamics, and demographic impacts on inflation. Awards & Patents: 1st Prize SICO2007 (IEEE Computational Intelligence Society) US Patent for B2B Procurement Optimization Professional Roles: Co-founder of tech startup GlobalSolver; visiting researcher at Universidad Carlos III de Madrid; consultant for central banks, financial institutions, and logistics companies. Served on ISEG’s research unit leadership. Teaching: Teaches data science, econometrics, and quantitative methods at undergraduate and graduate levels. Courses include 'Data Science for Sustainability' and 'Machine Learning in Finance.'

Bjørnar Karlsen Kivedalمشاهده پروفایل

استاد

• Applied Time Series Econometrics
• Macroeconomics
• Housing Market Analysis
• +۳ مورد دیگر

Bjørnar Karlsen Kivedal is a Professor at the Department of Economics, Innovation and Society at Oslo Metropolitan University (OsloMet). His research focuses on applied time series econometrics in macroeconomics and housing markets, with notable contributions to topics such as Airbnb's impact on housing and tourism, climate-related economic dynamics, and DSGE model applications. Kivedal is affiliated with the Housing Lab at OsloMet, emphasizing interdisciplinary research on urban and environmental economics. His work combines quantitative methods with real-world policy analysis, addressing issues like housing market stability, CO2 emissions, and post-disaster economic recovery. Key research interests include cointegration analysis, nonlinear economic modeling, and the interplay between tourism and local economies. His recent studies investigate Airbnb’s role in regional tourism development, the environmental Kuznets curve for CO2 emissions, and behavioral changes in housing markets during crises. Kivedal frequently collaborates with institutions like Housing Lab, producing policy-relevant insights into macroeconomic frameworks and housing policies.

Neil R. Ericssonمشاهده پروفایل

استاد پژوهشی

• Econometrics
• Empirical Macroeconomics
• Forecasting
• +۷ مورد دیگر

Neil R. Ericsson is a Research Professor of Economics at The George Washington University, Department of Economics, and an Adjunct Professor at the Paul H. Nitze School of Advanced International Studies (SAIS), Johns Hopkins University. He also serves as a Principal Economist in the Division of International Finance at the Board of Governors of the Federal Reserve System. His academic affiliations reflect a strong focus on econometrics, forecasting, and economic policy. B.A. in Economics, Yale University M.Sc. in Econometrics and Mathematical Economics, London School of Economics Ph.D. in Economics, London School of Economics Dr. Ericsson's research centers on theoretical and applied econometrics, empirical macroeconomic modeling, monetary economics, international economics, and forecasting. He has pioneered methods in general-to-specific modeling, exogeneity testing, and cointegration analysis. His recent work emphasizes tools for early warning and detection of economic crises and improving the accuracy of government forecasts. His publications span top journals such as the American Economic Review , Econometrica , Journal of Econometrics , and International Journal of Forecasting . The body of his work shows a consistent focus on econometric methodology applied to macroeconomic and policy-relevant questions, with an emphasis on model transparency, robustness, and real-world forecasting performance. Dr. Ericsson has edited special issues for the Journal of Policy Modeling , Journal of Business and Economic Statistics , and Econometrics , and co-edited three influential books: Testing Exogeneity (1994), Understanding Economic Forecasts (2001), and General-to-Specific Modelling (2005). These editorial contributions highlight his leadership in shaping discourse in econometric modeling and forecasting. He has advised and collaborated extensively with leading economists, including David F. Hendry, John S. Irons, and Julia Campos. While formal student advising is not explicitly mentioned, his editorial and collaborative roles suggest significant mentorship and academic leadership. He is a member of the H. O. Stekler Research Program on Forecasting, indicating active involvement in forecasting research initiatives. Dr. Ericsson’s work is supported by his long-standing affiliation with the Federal Reserve and academic institutions, enabling access to high-impact data and policy environments. His research program continues to influence both academic econometrics and practical forecasting in central banks and government agencies.

Martin Brunsمشاهده پروفایل

دانشیار

• Econometrics
• Macroeconomics
• Time Series Analysis
• +۷ مورد دیگر

Martin Bruns is an Associate Professor in the School of Economics at the University of East Anglia, where he conducts research at the intersection of econometrics and macroeconomics. His work focuses on time series analysis, Bayesian inference, and structural modeling, with applications to monetary policy, fiscal policy, and global commodity markets. He is actively involved in policy-relevant research and collaborates with international institutions such as the European Central Bank and the International Monetary Fund. Research Interests: Martin specializes in advanced econometric methods, particularly proxy vector autoregressions (Proxy-VARs), identification through heteroskedasticity, and Bayesian estimation of nonlinear models. His research aims to improve the reliability and interpretability of structural macroeconomic models used for forecasting and policy analysis. He also organizes an annual workshop on time series econometrics that brings together academics and central bankers. Recent Publication Trends: His most recent articles (2024–2025) center on methodological innovations in Proxy-VARs, including robust identification strategies, instrument choice, and testing for exogeneity. These works contribute to more credible causal inference in macroeconomic models, especially when dealing with unobserved shocks. The research spans top journals such as the Journal of Econometrics and Journal of Economic Dynamics and Control . Scientific Engagement: Martin leads externally funded research projects, including a British Academy-funded project on heteroskedastic proxy VARs. Though no formal awards are listed, his work is highly cited and referenced in policy circles. He maintains an active research network across Europe and North America. Advising and Grants: While no students are explicitly named, his collaborative publications suggest mentorship and academic leadership. He has secured competitive research funding, including from the British Academy and support for the International Association for Applied Econometrics conference. Laboratories and Teams: Martin is a member of the Applied Econometrics and Finance group and the Statistics research cluster at UEA. He plays a key role in fostering academic exchange through his organization of an annual international workshop on time series econometrics.

• Mathematical Economics
• Econometrics
• Time Series Analysis
• +۳ مورد دیگر

Ivan Pavlovich Stankevich is an Associate Professor at the National Research University Higher School of Economics (HSE) , affiliated with the Faculty of Economic Sciences and Department of Applied Economics. He also serves as a Senior Research Fellow in the Scientific and Educational Laboratory of Macrostructural Modeling of the Russian Economy and a Leading Expert in the Project Laboratory for the Development of Intellectual Competitions in Economics. With 11 years of teaching and research experience since joining HSE in 2011, he specializes in mathematical economics , time series analysis , and dynamic economic equilibrium modeling. PhD in Economics (2022, HSE) Master's in Economics (2014, HSE) Bachelor's in Economics (2012, HSE) His research focuses on nowcasting GDP with MIDAS models , seasonal adjustment in economic data, and multiproduct decomposition of macroeconomic balances. Recent work demonstrates how news background analysis improves GDP projections during economic instability. He has received multiple scientific awards , including the HSE Rector's Letter of Thanks (2022), Best Teacher Awards (2024, 2019–2020, 2015), and bonuses for publications in List B journals. His grants include leadership in RFBR projects on intertemporal equilibrium (2016–2017) and participation in RSF-funded research on dynamic model identification. As a scientific advisor , he mentors PhD students Stefano Boscolo Fiore (Moscow Road Safety Analysis) and Natalia Makeeva (Uncertainty Forecasting). He actively participates in educational initiatives such as the National Olympiad in Data Analysis DANO and All-Russian School Olympiad in Economics.

• International Macroeconomics
• Monetary Policy
• Financial Markets
• +۳ مورد دیگر

Sandra Eickmeier is a Research Professor at the Research Centre of the Deutsche Bundesbank. Her work focuses on international macroeconomics, monetary policy, and financial markets with an emphasis on applied macroeconometrics and expectation formation. She has contributed extensively to understanding global inflation dynamics, financial stress transmission channels, and the effectiveness of monetary policy in varying economic conditions. Her research explores topics such as banking regulation, credit supply shocks, and the interplay between macroeconomic factors and financial stability. Notable contributions include studies on China's role in global inflation, time-varying macro-financial linkages, and the interest rate pass-through mechanisms in the Eurozone during crises. Eickmeier has co-authored over 30 peer-reviewed articles and working papers, including key analyses on financial shocks and inflation dynamics. Her work often employs advanced econometric techniques like factor-augmented vector autoregression (FAVAR) and global VAR models to disentangle complex economic relationships.

Rasmus Søndergaard Pedersenمشاهده پروفایل

دانشیار

• Financial econometrics
• Time series econometrics
• Econometric theory
• +۴ مورد دیگر

Rasmus Søndergaard Pedersen is Associate Professor at the Department of Economics, University of Copenhagen , Faculty of Social Sciences. His research focuses on financial and time-series econometrics, with special emphasis on heavy-tailed distributions, time-varying volatility and GARCH-type models. Education: Ph.D. in Economics, University of Copenhagen (2012–2015) M.Sc. in Economics (cand.polit.), University of Copenhagen (2010–2012) Exchange student, University of California, San Diego (2010–2011) B.Sc. in Economics, University of Copenhagen (2006–2010) Research Interests: His work spans time-series econometrics, theoretical econometrics, financial econometrics, multidimensional time-series models, GARCH and BEKK specifications, heavy-tailed processes, bootstrap inference on parameter boundaries, high-dimensional VARs and robust inference in financial markets. Scientific Awards: Winner, Econometric Game 2012 Selected Young Economist, 5th Lindau Meeting on Economic Sciences Research Visits & Collaboration: Visiting researcher, Imperial College London (Jan–Jun 2014) Active participant in Econometric Society World Congress, Lindau Meetings, EC² conferences and numerous workshops on time-series econometrics Teaching & Guidance: He teaches Econometrics C and Financial Econometrics A at the University of Copenhagen and serves on assessment committees and research networks.

• Econometric Theory & Applications
• Time Series & Financial Econometrics
• Machine Learning Methods
• +۱ مورد دیگر

JiHyung Lee is an Associate Professor of Economics (tenured) at the University of Illinois Urbana-Champaign , Department of Economics. He previously held positions as Assistant Professor at the University of Illinois and the University of Washington. Education: Ph.D. in Economics, Yale University (2013) M.Phil. in Economics, Yale University (2010) M.A. in Economics, Yale University (2009) B.A. in Economics, Seoul National University (2005) Research Interests: Dr. Lee specializes in Econometric Theory & Applications , focusing on Time Series & Financial Econometrics , Machine Learning Methods , and Probability & Statistics . His work emphasizes robust inference under nonstationarity, quantile regression, and financial risk modeling. Recent Research Trends: His recent publications address nonparametric methods, quantile impulse response analysis, and high-dimensional predictive modeling. Notable contributions include advancements in density estimation without tuning parameters and quantile-based approaches for macroeconomic and financial applications. Awards & Recognition: Young Scholar Award, Korea-America Economic Association (2020) Arnold O. Beckman Research Award (2018-2019) Listed as an Excellent Teacher at UIUC (2016, 2017, 2019-2023) Yale University Fellowships (2007-2011) Advising & Grants: Dr. Lee has guided multiple Ph.D. students to academic and industry roles. He served on UIUC’s Promotion and Tenure Committee and contributed to NSF grant reviews. His research is supported by the UIUC Campus Research Board. Labs/Teams: Collaborates with international researchers on projects in econometrics, inequality analysis, and machine learning applications.