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Christian WolfView profile

Assistant Professor

• Macroeconomics
• Monetary Economics
• Time Series Econometrics
• +3 more

Christian Wolf is an Assistant Professor at the Massachusetts Institute of Technology (MIT) Department of Economics and a Faculty Research Fellow at the National Bureau of Economic Research (NBER). His work bridges macroeconomics, monetary economics, and econometric methodology. Research Interests: Wolf specializes in macroeconomics and monetary policy , with a focus on econometric techniques like structural vector autoregressions (VARs) and local projections . His research explores policy counterfactuals, heterogeneous-agent models, and fiscal-monetary interactions. Recent Publications: His work spans topics such as equivalence between fiscal and monetary tools in HANK models, robust identification in VARs, and the interplay between inequality and macroeconomic dynamics. Articles appear in journals like Econometrica , Journal of Political Economy , and American Economic Review . Awards: Faculty Research Fellow, NBER Contact: ckwolf@mit.edu | Office: E52-554, MIT

• Productivity Analysis
• Macroeconomic Policy
• Energy Economics
• +4 more

Dr. IKM Mokhtarul Wadud is a Senior Lecturer in the Department of Economics at The University of Sydney, Australia. Previously, he held roles as Senior Lecturer at Deakin University, Lecturer at Monash University Malaysia, and Assistant Professor at the University of Rajshahi, Bangladesh. He earned his PhD in Economics from the University of Wollongong in 2001. His research focuses on productivity analysis, macroeconomic policy, energy economics, and applied econometric modeling. Notable contributions include co-authoring the Asia Pacific edition of Introductory Econometrics (Cengage Learning) and publishing in journals like Economic Modelling and Energy Policy . His recent work addresses financial sustainability strategies in higher education during the pandemic and the impact of economic policy uncertainty on property prices in Australia. Dr. Wadud has presented at international conferences and served as a reviewer for multiple journals. His research spans diverse regions, including Australia, Thailand, Malaysia, and Bangladesh, with analyses of oil price volatility, monetary policy effects, and industrial competitiveness.

Fabio MilaniView profile

Professor

• Macroeconomics
• Monetary Economics
• International Macroeconomics
• +3 more

Professor Fabio Milani is a faculty member in the Department of Economics at the University of California, Irvine (UCI), where he also serves as Director of Graduate Studies for the Economics Ph.D. Program. He holds a Laurea in Economics from Bocconi University (2000) and a Ph.D. in Economics from Princeton University (2006). His research focuses on Macroeconomics, Monetary Economics, International Macroeconomics, and Time Series Econometrics, with an emphasis on deviations from rational expectations and the impact of learning behavior on macroeconomic fluctuations. Professor Milani’s work explores how psychological factors and heterogeneous expectations drive economic outcomes, including business cycles and inflation dynamics. He has extensively analyzed the role of sentiment, news shocks, and adaptive learning in macroeconomic models. His teaching spans Ph.D. courses like Macroeconomic Theory and Advanced Macroeconomics, as well as undergraduate courses on Financial Markets and the Macroeconomy. He advises numerous Ph.D. students, many of whom hold academic and policy roles globally. His publications span over 30 articles in top journals, including the Economic Journal , Journal of Economic Dynamics and Control , and Journal of Monetary Economics . Recent research includes studies on inflation tolerance, heterogeneous expectations, and the implications of learning models for monetary policy design. While no scientific awards are explicitly listed, his contributions reflect significant scholarly impact in macroeconomic theory and policy analysis.

• Econometrics
• Applied Econometrics
• Financial Econometrics
• +6 more

Professor Yongcheol Shin is a faculty member in the Department of Economics at the University of York. His academic background includes a BA (Hanyang University), MA (Hanyang University), and PhD (Michigan State University). He specializes in applied and theoretical econometrics, focusing on financial and macroeconomic modeling. Education: BA (Hanyang University), MA (Hanyang University), PhD (Michigan State University) His research spans econometric theory and applications in finance and macroeconomics. Key areas include nonlinear panel data modeling, cointegrating VAR models, regime-switching models, and statistical hypothesis testing for time series. Recent work addresses interactive effects in panel data and multilevel factor models. Recent publications (2023) focus on panel data analysis, canonical correlation, and unit root testing. These studies reflect his expertise in econometric methodology and its application to financial economics, macroeconomics, and trade dynamics. Scientific awards include: 2018 Maekyung-KAEA Economist Award He leads the ESRC-funded project 'New Cross-Sectionally Dependent Panel Data Methods for the Analysis of Macroeconomic and Financial Networks' (2020-2024), collaborating with researchers like J. Chen and W. Wang.

Hafiz HoqueView profile

Professor

• Corporate Finance
• Corporate Boards
• Director’s Network
• +6 more

Professor Hafiz Hoque is a faculty member in the Accounting and Finance Department at Swansea University's School of Management. He holds a PhD from Bayes Business School and serves as Director of the Hawkes Centre for Empirical Finance. His research focuses on corporate finance, bank regulations, green innovation, climate change, and ESG. With over 20 publications in top journals and £100k+ in grants, his work explores topics like corporate boards, IPO markets, and Islamic finance. He has supervised 8 PhD students to completion and welcomes new applications. Key areas include climate finance and regulatory impacts on banking sectors. Education: PhD from Bayes Business School (formerly Cass Business School). Research Interests: Corporate finance dynamics, director networks, banking regulations, green innovation, and climate finance. His work bridges theoretical frameworks with empirical analysis, addressing global financial challenges such as pandemic governance and ESG integration. Grants & Funding: Over £100,000 in grants secured in the past decade, supporting research on financial markets and regulatory policies. Labs/Teams: Director of the Hawkes Centre for Empirical Finance, fostering interdisciplinary research in finance and empirical methods.

• Numerical Analysis
• Applied Mathematics
• Computational Fluid Dynamics
• +5 more

Stefan Vandewalle is a full professor at the Department of Computer Science, Faculty of Engineering Sciences, KU Leuven. His research focuses on numerical analysis, applied mathematics, and computational methods for stochastic differential equations, wind energy modeling, and uncertainty quantification. Department Chair, KU Leuven Member, Subdivision Numerical Analysis and Applied Mathematics Member, iSi Health Institute Observer, Faculty Council of Sciences Chair, Department Council for Computer Science His recent work explores multiscale modeling, Monte Carlo methods, and data assimilation techniques. Projects include micro-macro Parareal algorithms, wind turbine aeroelasticity, and turbulent flow reconstruction for wind farms. He supervises PhD candidates and collaborates on interdisciplinary studies involving structural mechanics and renewable energy systems. Publications highlight advancements in parallel-in-time methods, stochastic optimization for tokamak reactors, and DNS-based control of turbulent flows. Key keywords: Multiscale numerical methods Uncertainty quantification Wind energy simulation Monte Carlo algorithms PDE-constrained optimization Stochastic differential equations He contributes to academic governance as a member of extended faculty boards and evaluation committees.

Leland BybeeView profile

Assistant Professor

• Machine Learning
• Natural Language Processing
• Econometrics
• +2 more

Leland Bybee is an Assistant Professor of Finance at the University of Chicago Booth School of Business . He leverages machine learning and natural language processing to address economic and financial questions, particularly focusing on belief measurement with applications to asset pricing and behavioral economics. Ph.D. in Financial Economics, Yale School of Management (2024) M.S. in Statistics, University of Michigan (2017) B.A. in Economics, University of Chicago (2013) His research integrates computational methods with economic theory to analyze: Textual analysis of business news for macroeconomic tracking Narrative-driven asset pricing models Memory-based belief formation using kernel methods Macroeconomic determinants of currency returns He has received multiple awards including: Dimension Fund Advisors Distinguished Paper Award BlackRock Applied Research Award HEC Top Finance Graduate Award The Brattle Group PhD Candidates Award EFA Engelbert Dockner Memorial Prize Bybee teaches Machine Learning in Finance and participates in finance seminars, contributing computational tools like regIPCA (Python) and changepointsHD (R) to the research community.

Michele PifferView profile

Senior Lecturer

• Bayesian Econometrics
• Time Series Analysis
• Macroeconomics
• +3 more

Dr. Michele Piffer is a Senior Lecturer in Economics at King’s Business School, King’s College London, and a Senior Researcher in the Modelling Team at the Bank of England. He holds a PhD in Economics from the London School of Economics (2014), an MSc in Economics (distinction) from LSE (2008), and a Laurea Triennale + Specialistica in Economics (cum laude) from Università Cattolica, Milano (2007). His research focuses on Bayesian Econometrics, Time Series Analysis, Macroeconomics, and Monetary Policy. Key areas include uncertainty shocks, structural VAR models, and unconventional monetary policy impacts on fiscal balances. He has organized academic events such as the 'QuickTalks: Macroeconometrics and Applied Macro' (2022) and the 'Workshop in Structural VAR Models' (2020). Recent work emphasizes methodological advancements in Bayesian estimation and applied macroeconomic analysis, with contributions to journals like Quantitative Economics , The Econometrics Journal , and Journal of the European Economic Association . His research aids central banks and statistical agencies in understanding market trends through quantitative analysis.

• Economic Growth
• International Economics
• Business Cycles
• +8 more

Miguel Leon-Ledesma is a Professor of Economics at the Department of Economics , University of Exeter Business School , joining in September 2024. Previously, he held a Professorship at the University of Kent . A macroeconomist, he specializes in Economic Growth , International Economics , and Business Cycles , with affiliations as Research Fellow at the Centre for Economic Policy Research (CEPR) and Fellow at the National Institute for Economic and Social Research (NIESR). He has advised international organizations like the European Central Bank and Asian Development Bank and serves as a committee member and trustee for the UK's Money Macro and Finance Society (MMF) . Research Interests : His work bridges macroeconomic theory and empirical analysis , focusing on growth volatility, trade dynamics, labor share trends, and structural transformation. He explores how monetary policy interacts with labor markets, the role of technology frontiers in productivity, and the impact of import elasticities and network effects on development. Article Trends : His recent publications and working papers emphasize growth convergence , DSGE model innovations , factor substitution in production, and trade-policy linkages , reflecting a thematic focus on macroeconomic stability, structural change, and globalization's economic implications. Scientific Awards : Research Fellow, Centre for Economic Policy Research (CEPR) Fellow, National Institute for Economic and Social Research (NIESR) Grants & Projects : Funded by the Leverhulme Trust , Nuffield Foundation , and ESRC , his work includes projects on pensions and health economics, oil shocks' network amplification, and UK firm creation during the pandemic. Labs & Teams : Collaborates with international researchers (e.g., Mathan Satchi, Laura Puzzello) and contributes to policy-oriented networks like the Money Macro and Finance Society , integrating academic research with institutional policy advice.

Gaël KermarrecView profile

Researcher

• Boundary Layer Meteorology
• Atmospheric Turbulence
• GNSS Applications
• +3 more

Dr. Gaël Kermarrec is a researcher at the Boundary Layer Meteorology Group , part of the Institute of Meteorology and Climatology within the Faculty of Mathematics and Physics at Leibniz University Hannover . His work focuses on atmospheric turbulence, GNSS applications, and remote sensing for environmental monitoring. Boundary layer meteorology Turbulence theory GNSS signal processing Terrestrial laser scanning Climate change impacts Geodetic time series analysis His research integrates advanced mathematical models like LR B-splines and Matérn covariance with large eddy simulations to study: Atmospheric turbulence effects on optical/GNSS signals Hydrospheric mass loading Deformation analysis of terrain/port infrastructure Climatic sea-level changes Machine learning for remote sensing The 15 most recent articles (2025-2023) demonstrate his focus on: GNSS-based turbulence detection AI-enhanced climate mapping Advanced surface approximation techniques Multi-sensor data fusion Stochastic modeling of geodetic observations Environmental impacts on optical measurements He has developed tools like the Klimascanner QGIS plugin for urban climate resilience and contributes to: Understanding atmospheric scale lengths Improving TLS/GNSS deformation monitoring Analyzing hydrospheric changes Wavefront modeling Ionospheric corrections

Mawuli Kouami SegnonView profile

Researcher

• Econometrics
• Time Series Analysis
• Financial Forecasting
• +5 more

Dr. Mawuli Kouami Segnon is a researcher at the Chair of Empirical Economics, School of Business and Economics, University of Münster. His work focuses on econometric modeling, financial time series analysis, and volatility forecasting across various domains including cryptocurrencies, energy markets, and macroeconomic indicators. Research interests include: Development of advanced volatility models (GARCH, multifractal, regime-switching) Applications to financial markets, energy economics, and macroeconomic policy High-frequency data analysis and mixed-frequency forecasting Count data modeling with conditional heteroscedasticity Portfolio risk management using copula and multifractal approaches Recent publications demonstrate expertise in: Geopolitical risk impacts on stock volatility Comparative analysis of realized variance measures Inflation uncertainty modeling in G7 countries Electricity price volatility in Australian markets Bitcoin market forecasting Historical economic data analysis Current projects (since 2020) involve: Innovative economic/financial time series forecasting Financial market volatility modeling Applications of multifractal structures in econometrics

Mohsen PourahmadiView profile

Professor

• Time Series Analysis
• Multivariate Statistics
• Covariance Estimation
• +7 more

Mohsen Pourahmadi is a Professor in the Department of Statistics at Texas A&M University, part of the College of Arts & Sciences. His research focuses on developing methodologies for modeling covariance matrices in multivariate and time series data, with applications to financial analysis, longitudinal studies, neuroeconomics, and high-dimensional data. Key tools include graphical lasso algorithms, Cholesky decomposition, and Bayesian approaches. He emphasizes extending generalized linear models (GLM) to covariance matrix estimation, leveraging prediction theory and stochastic processes. Education details are not explicitly provided in the text. His work spans theoretical advancements in covariance estimation, such as sparse VAR models, nonstationary process analysis, and regularized multivariate regression. He has contributed to applications like detecting cyber attacks on infrastructure systems and analyzing breast cancer data through Bayesian networks. Research interests include time series graphical models, antedependence models for longitudinal data, and regularization techniques for high-dimensional covariance matrices. His recent work explores fused-lasso penalties, Bayesian correlation matrix estimation, and stationary subspace analysis. Pourahmadi has authored numerous articles on topics ranging from multivariate volatility modeling to nonparametric covariance estimation, emphasizing both computational efficiency and theoretical rigor.

Seojeong LeeView profile

Associate Professor

• Econometrics
• Statistical Inference
• Generalized Method of Moments (GMM)
• +8 more

Associate Professor Seojeong Lee is a faculty member at the University of New South Wales (UNSW) Business School, School of Economics, specializing in advanced econometric theory. She joined UNSW in 2012 after completing her PhD at the University of Wisconsin-Madison and has established herself as a leading researcher in robust inference methods under complex data conditions. Her educational background includes: Ph.D. in Economics, University of Wisconsin-Madison (2008-2012) M.A. in Economics, Seoul National University (2006-2008) B.A. in Economics and Political Science (dual major), Seoul National University, summa cum laude (2000-2006, with military service 2002-2004) Professor Lee's research centers on developing theoretically rigorous methods for econometric inference, with primary focus on generalized method of moments (GMM), instrumental variables (IV), and two-stage least squares (2SLS) under model misspecification. Her work addresses critical challenges including invalid/many/weak instruments, heterogeneous treatment effects, and clustered sampling, contributing foundational advances to statistical inference in economics. Analysis of her recent publications reveals a strong trajectory in refining methods for many-instrument settings and misspecified models, with increasing emphasis on computational implementations (e.g., Stata packages) and applications to causal inference. Her work bridges theoretical econometrics with practical policy-relevant analysis. Her scientific achievements include: Australian Research Council DECRA Fellowship (2017-2019) UNSW Dean's Research Fellowship (2020-2022) Zellner Thesis Award Honorable Mention from American Statistical Association (2014) Multiple competitive UNSW research awards Professor Lee actively supervises PhD candidates Wei Tian and Fangzhou Yu, and has secured over AUD 700,000 in research funding including ARC Discovery Projects. She teaches undergraduate and postgraduate econometrics courses, integrating her research into pedagogy. Her ongoing work continues to push boundaries in robust econometric methodology for modern data challenges.

• Applied Econometrics
• Time Series Modelling
• Tourism Economics
• +6 more

Professor Selva Selvanathan is a Professor of Econometrics at Griffith University, affiliated with the Department of Accounting, Finance, and Economics at the Griffith Business School. He serves as Director of the Economics Policy Analysis Program (EPAP) and a member of the Griffith Asia Institute. His research focuses on applied econometrics, time series modeling, tourism and energy economics, and consumer demand analysis. He has authored/co-authored over 100 articles and multiple monographs, contributing to leading journals such as the Review of Economic Studies and Journal of Econometrics . Education: PhD in Economics (University of WA and Murdoch University, Australia), MSc (University of Bucharest, Romania), BSc (University of Jaffna, Sri Lanka). Research Interests: Professor Selvanathan’s work spans econometric methodologies, tourism economics, energy policy, and consumer behavior. His recent studies include modeling financial asset demand in Sri Lanka, analyzing alcohol consumption patterns in Australia, and exploring the gender dimensions of cleaner energy transitions. Awards and Honors: Pro-Vice Chancellor’s Research Excellence Award 2014 (Research Supervision) University of Western Australia Distinguished Teaching Award (1988) Griffith Awards for Excellence in Teaching 2005 – Innovation Across the Institution Grants and Collaborations: Leading projects funded by the Department of Foreign Affairs and Trade, Australian Research Council, and Griffith University. Notable grants include policy capacity-building initiatives in Vietnam and Sri Lanka, and studies on alcohol control measures. Advising and Mentorship: Supervised over 20 doctoral students, including works on foreign aid impacts, renewable energy transitions, and rural livelihoods. Current research includes market integration dynamics and energy policy effectiveness. Labs/Teams: Active in Griffith Asia Institute and EPAP, fostering interdisciplinary research on Asian economies and policy analysis.

José António Ferreira MachadoView profile

Professor

• Econometrics
• Quantile Regression
• Wage Distributions
• +3 more

José António Ferreira Machado is a Full Professor at the Nova School of Business and Economics, Universidade Nova de Lisboa. He currently serves as Vice-Rector of the university and previously held director roles at the Nova School of Business and Economics (2005-2015) and Angola Business School (2010-2015). His academic career includes consultancy at the Bank of Portugal (1992-2015) and teaching Econometrics, Statistics, and Macroeconomics. Research Interests: Machado's work focuses on Econometrics, Quantile Regression, Wage Distributions, Firm Size Analysis, and Macroeconomic Modeling. His most cited paper (2005) introduced counterfactual decomposition methods for wage distribution analysis. Recent publications examine quantile regression extensions, trade margins, and moment-based statistical inference. His research spans both theoretical and applied economics, with collaborations including J. M.C. Santos Silva and Roger Koenker.