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Econometrics

Tablet and papers with graphs and numbers presented in report style

Econometrics

In economics, the field of econometrics helps quantify cause-and-effect relationships by using graphical representations that correlate the involved factors.

It combines statistical and mathematical methods that let users figure out possible outcomes and determine their further plan of action accordingly.

Researchers

Paul Contoyannis | Head of the Health Research Unit (Athens Institute for Education and Research [ATINER]) Learn More

Associate Professor

My research focuses on health economics and microeconometrics. Recent work has looked at the dynamics of depression in adolescence in the United States and the effects of the delisting of high strength opioids on the prescription of opioids in Ontario, and changes to the insurance coverage of under 25’s on the prescription of antidepressants in Ontario.  Other work is focused on the effects of recent changes to the benefit system on opioid and antidepressant prescribing in the United Kingdom.

Irene Botosaru Learn More

Canada Research Chair, Tier 2, Associate Professor

My research interest is in econometrics. My work focuses on accommodating and quantifying the role of heterogeneity in micro-econometric models. For example, I am interested in methods that introduce richer dynamics, such as individual heterogeneity that changes over time, and in methods that modify commonly used statistical methods to overcome data limitations typically faced by economists.

Learn more about Irene’s research.

Stephen Jones Learn More

Professor

My current research addresses changing labour market dynamics in Canada, the US and beyond using econometric techniques applied to (mostly) confidential data.  I study transition behaviour between traditional labour market states (Employment, Unemployment, Out of the Labour Force) as well as exploring heterogeneities within these traditional categories.

Recent foci include a detailed comparison of individuals on the margins of the labour force in Canada and the US, part of a larger comparative study sponsored by the NBER, and work on how labour market dynamics were changed by the economic upheaval associated with the COVID-19 pandemic.

Surprisingly, this latter project found relatively modest heterogeneity in the overall impact of the pandemic by gender and even by age, and noted the resilience of the Canadian labour market in the face of an unprecedented downturn.

Chris Muris Learn More

Associate Professor

My primary research interest is in theoretical econometrics. I develop new procedures that economists can apply to data to estimate key parameters in models that they frequently use. For example, some of my research proposes and analyzes new methods for working with panel data sets: data sets in which individuals, households, or firms are observed for at least two time periods. Some of my other research explores issues related to missing data and the evaluation of programs.

Learn more about Chris’ research.

Jeffery S. Racine Learn More

Professor, Department of Economics, Professor, Graduate Program in Statistics, Department of Mathematics and Statistics, Senator William McMaster Chair in Econometrics, Fellow of Journal of Econometrics, Associate Editor, Econometric Reviews

In 1989, I graduated with a PhD degree from the University of Western Ontario (Supervisor: Aman Ullah). I am a professor at McMaster University, teaching in the Economics Department as well as the Graduate Program in Statistics, within the Department of Mathematics and Statistics. I am a Fellow of the Journal of Econometrics and hold the Senator William McMaster Chair in Econometrics. I have previously held appointments at Syracuse University, the University of South Florida, the University of California San Diego (two-year visiting appointment), and York University.

My research interests include nonparametric estimation and inference, shape constrained estimation, cross-validatory model selection, frequentist model averaging, nonparametric instrumental methods, and entropy-based measures of dependence and their statistical underpinnings. My interests are in parallel distributed computing paradigms and their application to computationally intensive nonparametric estimators. The journal Econometric Reviews has appointed me as Associate Editor.

I have co-authored the textbook Nonparametric Econometrics: Theory and Practice (joint with Qi Li, published by Princeton University Press, 2007, with a Chinese translation published in 2015), the monograph Nonparametric Econometrics: A Primer (published by Foundations and Trends in Econometrics, 2008, with a Russian translation published in the journal Quantile in 2008), the textbook Reproducible Econometrics Using R (published by Oxford University Press, 2018), and the textbook An Introduction to the Advanced Theory and Practice of Nonparametric Econometrics: A Replicable Approach Using R (published by Cambridge University Press, 2019). I have co-authored the R packages np and crs on the Comprehensive R Archive Network (CRAN).

Michael Veall Learn More

Academic Director, Statistics Canada Research Data Centre, Professor

I am Principal Investigator of the Canadian Research Data Centre Network (CRDCN), a network of 33 sites across Canada with funding from the Social Sciences and Humanities Research Council of Canada, the Canadian Institutes of Health Research, and the Canadian Foundation of Innovation (as a Major Science Initiative). At each site, confidential, anonymized Statistics Canada data can be used while protecting individual privacy.

I am also the Academic Director of the Statistics Canada Research Data Centre at McMaster, a CRDCN member. My personal research in the past emphasized evaluating econometric simulation methods; more recently it has involved applied econometric applications as a member of teams studying issues in population health, taxation and inequality, and the labour market.

Sergei Filiasov

PhD Student

My interests include the development and application of optimal statistical decision rules based on the minimax-regret criterion. Specifically, I focus on the development of optimal statistical decision rules for multiple treatment arms and non-linear welfare functions, as well as state-space constrained rules. I also study the performance and behaviour of minimax-regret rules in finite samples.

Sara Kamali-Anaraki

PhD Student