I mostly teach applied econometrics and the economics of natural resources and the environment. If you want access to my course material, don't hesitate to contact me at julien.salanie@univ-st-etienne.fr

Econometrics 1 (The linear model) - Bachelor [website]

This course is a first presentation of the econometrics of the linear model. It focuses on the ordinary least square estimator and its properties (unbiasedness, efficiency and consistancy) under mild assumptions. The course also sets the basics of inference. Several practice sessions are proposed to get familiar with the estimation of linear model making all the calculations by hand or with a basic spreadsheet software (excel or openoffice).

Econometrics 2 (Applied econometrics) - Bachelor [website]

This course is a follow-up of Econometrics 1. We keep going with OLS and the linear model but we go further on model selection and we look further into the assumptions made so far (non-multicolinearity, homoskedaticity and non-autocorrelation) and we learn what to do when we fail on these assumptions. We also go more into the exogeneity assumption. We introduce multilevel modelling to see how fixed effects and random effects can help us. We also dig into the role of control variables using directed acyclic graphs (DAGs). Practice sessions in R help to operationalize the concepts and methods.

Economics of natural resources - Bachelor [website]

In this course, we introduce time into economic analysis. We learn how to handle dynamic optimization problems (free and constrained) using calculus of variations and the Maximum Principle. We illustrate this approach looking at the exploitation of natural (renewable or renewable) resources (mining, forestry, fishing). We also broader illustrations in industrial organization and macroeconomic growth. Practice sessions using exercises help to get into concrete problems.

Econometrics 3 (Program evaluation) - Master [website]

Causality is an important empirical issue. In this course we discuss the endogeneity issue and how to make causal claims using regressions. We look at several approaches: controls, experiments, instrumental variables, matching, difference-in-differences, regression discontinuity and synthetic controls. All methods are applied to real data examples by replicating published papers in R.

Environmental economics - Master [website]

This course is a first dive into the economics of environmental issues. The core of the course deals with designing environmental policy using taxes, norms and standards, permits and subsidies. Environmental policy is first presented in a simplified framework (perfect competition, full information, separability). The next sessions of the course deals with relaxing these assumption. We first deal with environmental policy under uncertainty and asymetric information. Then we present environmental policy when it affects production. Finally, we set some elements of environmental policy under imperfect competition.