The goal of the course is to provide an understanding of selected topics of current academic research in the areas of international macroeconomics and international finance. Topics covered include: the intertemporal approach to the current account; international business cycle models, international risk sharing and capital flows; monetary exchange rate models; and macroeconomic policy in open economies.

This is a continuation of ECO2400H and ECO2401H, and is designed for specialists in Econometrics. A number of topics not covered in the other courses are considered, and the content varies from year to year depending on the interests of the students and the instructor.

This course will present the factor models in both a static and a dynamic framework.This includes the Singular Value Decomposition (SVD) in the static case as well as the state space modelling of dynamic factor models,and their extensions for large number of observed variables or individuals.Among the applications, the granularity adjustment required in the new Basel 2 regulation for credit risk will be completely derived.

This course is directed at graduate students conducting research in the applied micro fields, especially (but not exclusively) labour, development, and public economics. This is not purely a labour economics course: it is a course in empirical and applied econometrics. The tools covered in the course, however, are central to those used in empirical labour economics, as well as other applied microeconomics fields like development and public economics. The focus will be on the identification of casual relationships using regression-based analysis. Empirical examples will be drawn from recent work in labour economics.

This is a core course in labour economics. The course is pitched at the PhD level. Qualified MA students are also welcomed. MA students who are interested in a more public policy oriented labour course should take ECO3801H. ECO3800H is not a prerequisite for ECO3801H. Both courses are required for PhD students who want to write the field examination in labour economics.

The objective of this course is to use microeconomics and econometrics to study the labour market. Special attention will be paid to the interaction between economic theory and empirical research. The topics covered will include labour supply, educational attainment, on-the-job training, on-the-job matching, hedonic markets, internal labour markets, and economics of the family.

The objective of this course is to present the most recent research in labour economics with a focus on empirical methods, and to discuss how the resulting insights can inform the evaluation of public policy. The topics covered will include job loss and search at the micro and macro level, labour market power and monopsony, firms and peers impact on wage determination, selection, equalizing wage differentials and gender disparities in the labour market. Applications will include public policies addressing pay equity, management practices, immigrant selection mechanisms, and the rise in alternative working arrangements.

ECO3900H and ECO3901H explore the factors influencing firms' behaviour, market outcomes, and welfare within oligopoly industries. These courses emphasize the integration of economic models, data analysis, and skillful identification strategies to address empirical questions in economics. The first half focuses on models and empirical applications concerning firms' productivity, consumer demand, price and quantity competition, collusion, advertising, and market entry. In the second half, topics include industry dynamics such as investment, innovation, product design, vertical contracts, networks, and mergers.

ECO3900H and ECO3901H explore the factors influencing firms' behaviour, market outcomes, and welfare within oligopoly industries. These courses emphasize the integration of economic models, data analysis, and skillful identification strategies to address empirical questions in economics. The first half focuses on models and empirical applications concerning firms' productivity, consumer demand, price and quantity competition, collusion, advertising, and market entry. In the second half, topics include industry dynamics such as investment, innovation, product design, vertical contracts, networks, and mergers.

Directed reading and research course.

Directed reading and research course.

The broad objective of the course it to foster the transition from coursework to independent research. Students will identify research topics and be matched with a faculty member. Each student is required to write an original research paper under the supervision of a faculty member. By the time this course is completed, students will have learned presentation skills, completed the second year paper requirement, identified a thesis topic, and struck a thesis committee.

Biologists need to use statistical methods to test their hypotheses. Given the increasing complexity of experiments, they need to understand the limitations of these statistics, how to select the appropriate tests for their needs, and how to interpret their results both statistically and biologically. The goal of this advanced course in statistics is to teach biologists how to choose and use statistics so that they can address relevant biological questions and test them with the appropriate methods. On overview of advanced regression models and ANOVA methods will be presented. Assignments include two computer labs and a term paper.

An introduction to multivariate statistical methods commonly used by researchers in ecology and evolutionary biology. Topics range from methods focused on single datasets (e.g., principal component analysis, principal coordinates analysis, cluster analysis) to methods involving groups of observations (e.g., discriminant analysis) to methods relating sets of variables to one another (e.g., canonical correspondence analysis, redundancy analysis, procrustes analysis). An emphasis on the graphical geometry of the methods will be provided. The course is oriented more towards the underlying application and understanding of the methods rather than the underlying mathematical derivations or theory.

Ecological processes are inherently spatially distributed due to spatial dependence of environmental conditions and spatial autocorrelation of species behaviors and dispersal abilities. A broad overview of spatial analytical methods that quantify (geostatistics, network theory, boundary detection), test (restricted randomization) and model (spatial regressions), and model spatially autocorrelated ecological data will be presented. Students will be introduced to the concept of spatial scales and how multiscale analysis can be performed with census and sampled data. Spatial methods to deal with point pattern data and surface pattern data will be reviewed. Assignments include two computer labs and a term paper.

This graduate course intended for new MSc and PhD students provides a forum for students to enhance their current skills and understanding of how to do 'good' science and issues encountered as scientists by involving a combination of (i) student-led discussions, (ii) lectures/discussions led by faculty, and (iii) short presentations by students.

The class will read and discuss papers on topics that include: human subjectivity and its role in science; semi-philosophical controversies about approaches to science and research tactics; common pitfalls/errors in experimental design and statistical analysis; brief overviews of emerging statistical approaches; and a variety other issues important to researchers (e.g., ethics). Faculty from the department will lecture to provide background on some statistical topics (e.g., power analysis, control of false discoveries).

The major course assignment includes an essay that aims to facilitate students' progress in their thesis research by: a) defining the broad, scientific objectives for their research, b) evaluating possible approaches for their research objectives, and c) describing and justifying a set of strategic approaches to employ to achieve their objectives. The essay is not a thesis proposal, but is designed to empower students in the broad thinking required before writing a thesis proposal.

A short graduate course module focused on developing the academic and professional skills required to succeed during and beyond graduate education in life sciences, with an emphasis on ecology and evolution. Employers from government, NGOs, public school systems, private sectors, etc. emphasize that they look for employee skill sets that include critical thinking, problem-solving, communication, creativity, teamwork, interpersonal relationships, administration, and leadership. This course will provide graduate students with: 1) opportunities to think, learn and communicate in a broad integrative manner and experience working in small interdisciplinary groups; 2) access to material for networking and non-laboratory skill assessment tools needed for success in academic and non-academic life science careers; and 3) opportunities to strengthen communication skills, including face-to-face networking with professionals who have careers outside the academic environment (e.g., government scientists, environmental consultants, NGOs, biotech companies). Topics for interactive lectures by faculty and invited lecturers, and classroom discussions, may include: the practical aspects of succeeding in graduate school; enhancing research skills; problem-solving techniques; leadership; finding successful collaborations; developing strong written and oral communication skills; opportunities to enhance imaginative, creative, and innovative thinking; further training as a postdoctoral fellow; effective networking; integrating family commitments; career transitions; CVs and resumés; career options in and out of academia; best methods of searching for and landing the job; staff management; global scientific issues; social implications; and maintaining career development.

A graduate course that examines foundational principles in ecology and their relationship to currently active questions and fields of research. With strong reliance on primary literature, it aims to prepare students for more methodological graduate courses and for independent dissertation-level research in ecology and evolutionary biology. Within a broad survey of the field, particular stress is placed on quantitative approaches to areas of ecology important to evolutionary biology, such as population and metapopulation dynamics, community ecology, and species interactions.

This graduate course introduces students to major areas of research in evolutionary biology at a graduate level. The goal of the course is to teach students core concepts underlying these areas and to train students to apply these concepts to a variety of problems in evolutionary biology. The course will include a mix of lectures on fundamental concepts as well as student-driven discussions of primary literature related to those concepts. The course will cover concepts in evolutionary ecology, evolutionary genetics, and comparative methods.

This graduate course considers topical subjects in ecology and/or evolution. The specific course focus in a given course offering will cover specific aspects of one or more of the following areas: population ecology, community ecology, landscape ecology, conservation ecology, microevolution, macroevolution, genomics, quantitative genetics, sexual selection, ethology, behaviour genetics, neurophysiology, and related topics. The emphasis in a given course offering may prioritize current ideas in the field, classic papers, or a combination of the two. The topic(s) and emphasis may change from year to year depending on the instructor(s).

Modelling is a critical tool for describing the complex dynamics of ecosystems and for addressing urgent management questions in ecology, epidemiology and conservation. In this practical introduction, students learn how to formulate ecological and epidemiological models, link them to data, and implement/analyze them using computer simulations. The course includes approaches for modelling individuals, populations, and communities, with applications in population viability assessments, natural resource management and food security, invasive species and pest control, disease eradication, and climate change mitigation. While not a requirement, some experience with computer programming will be beneficial for this course.

This graduate course considers topical subjects in ecology and/or evolution. The specific course focus in a given course offering will cover specific aspects of one or more of the following areas: population ecology, community ecology, landscape ecology, conservation ecology, microevolution, macroevolution, genomics, quantitative genetics, sexual selection, ethology, behaviour genetics, neurophysiology, and related topics. The emphasis in a given course offering may prioritize current ideas in the field, classic papers, or a combination of the two. The topic(s) and emphasis may change from year to year depending on the instructor(s).

This graduate course considers topical subjects in ecology and/or evolution. The specific course focus in a given course offering will cover specific aspects of one or more of the following areas: population ecology, community ecology, landscape ecology, conservation ecology, microevolution, macroevolution, genomics, quantitative genetics, sexual selection, ethology, behaviour genetics, neurophysiology, and related topics. The emphasis in a given course offering may prioritize current ideas in the field, classic papers, or a combination of the two. The topic(s) and emphasis may change from year to year depending on the instructor(s).

Mathematics is central to science because it provides a rigorous way to go from a set of assumptions to their logical consequences. In ecology and evolution this might be how we think a virus will spread and evolve, how climate change will impact a threatened population, or how much genetic diversity we expect to see in a randomly mating population. In this course you'll learn how to build, analyze, and interpret mathematical models of increasing complexity through readings, lectures, tutorials, assignments, computer labs, and a final project. The focus is on deterministic dynamical models (recursions and differential equations) but we also touch on probability theory and stochastic simulations.

Major concepts in ecology and evolution from the perspective of plant-animal interactions. The richness of interactions between plants and animals is explored including antagonistic interactions (e.g., herbivory), mutualistic interactions (e.g., pollination, seed dispersal, ant-plant associations), and interactions involving multiple species across trophic levels.

Lectures will provide an in-depth coverage of modern methods of phylogenetic reconstruction, including molecular systematics based on DNA sequences. The principles and philosophy of classification will be taught with an emphasis on 'tree-thinking,' one of the most important conceptual advances in evolutionary biology. Tutorials will focus on recent developments in the study of evolutionary patterns while gaining proficiency in reading, presenting, and critiquing scientific papers.

This graduate course considers topical subjects in ecology and/or evolution. The specific course focus in a given course offering will cover specific aspects of one or more of the following areas: population ecology, community ecology, landscape ecology, conservation ecology, microevolution, macroevolution, genomics, quantitative genetics, sexual selection, ethology, behaviour genetics, neurophysiology, and related topics. The emphasis in a given course offering may prioritize current ideas in the field, classic papers, or a combination of the two. The topic(s) and emphasis may change from year to year depending on the instructor(s).

This graduate course considers topical subjects in ecology and/or evolution. The specific course focus in a given course offering will cover specific aspects of one or more of the following areas: population ecology, community ecology, landscape ecology, conservation ecology, microevolution, macroevolution, genomics, quantitative genetics, sexual selection, ethology, behaviour genetics, neurophysiology, and related topics. The emphasis in a given course offering may prioritize current ideas in the field, classic papers, or a combination of the two. The topic(s) and emphasis may change from year to year depending on the instructor(s).

This short graduate course considers topical subjects in ecology and evolution. The specific course focus in a given course offering will cover specific aspects of one or more of the following areas: population ecology, community ecology, landscape ecology, conservation ecology, evolutionary ecology, microevolution, macroevolution, genomics, quantitative genetics, and related topics. The emphasis in a given course offering may prioritize current ideas in the field, classic papers, or a combination of the two. The topic(s) and emphasis may change from year to year depending on the instructor(s).

This short graduate course considers topical subjects in ecology and evolution. The specific course focus in a given course offering will cover specific aspects of one or more of the following areas: population ecology, community ecology, landscape ecology, conservation ecology, evolutionary ecology, microevolution, macroevolution, genomics, quantitative genetics, and related topics. The emphasis in a given course offering may prioritize current ideas in the field, classic papers, or a combination of the two. The topic(s) and emphasis may change from year to year depending on the instructor(s).

This short graduate course considers topical subjects in ecology and evolution. The specific course focus in a given course offering will cover specific aspects of one or more of the following areas: population ecology, community ecology, landscape ecology, conservation ecology, evolutionary ecology, microevolution, macroevolution, genomics, quantitative genetics, and related topics. The emphasis in a given course offering may prioritize current ideas in the field, classic papers, or a combination of the two. The topic(s) and emphasis may change from year to year depending on the instructor(s).