... introductory course to microeconmetrics
Throughout the course we will make heavy use of Python and its SciPy ecosystem.
We heavily rely on Jupyter Notebooks throughout the course and so we provide some useful resources below. For further information, please do not hesitate to contact us.
- Winship, C., and Morgan, S. L. (2014). Counterfactuals and causal inference: Methods and principles for social research (Analytical methods for social research) (2nd ed.). Cambridge, England: Cambridge University Press.
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Heckman, J. J., and Vytlacil, E. J. (2007a). Econometric evaluation of social programs, part I: Causal effects, structural models and econometric policy evaluation. In J. J. Heckman, and E. E. Leamer (Eds.), Handbook of Econometrics (Vol. 6B, pp. 4779–4874). Amsterdam, Netherlands: Elsevier Science.
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Imbens G. W., and Rubin D. B. (2010). Rubin Causal Model. In S. N. Durlauf, and L. E. Blume (Eds.), Microeconometrics (pp. 229-241). London, England: Palgrave Macmillan.
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Pearl, J. (2014). Causality (2nd ed.). Cambridge, England: Cambridge University Press.
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Peters, J., Janzig, D., and Schölkopf, B. (2018) Elements of causal inference: Foundations and learning algorithms. Cambridge, MA: The MIT Press.
Please use the table of content to navigate the rest of the material.
We collect a list of additional, more general, reading recommendations here.
We provide the lectures in the form of a Jupyter notebook.
We briefly introduce the course and discuss some basic ideas about counterfactuals and causal inference.
We introduce the basic tools used throughout the class.
We provide some additional resources that are useful for our course work.
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Wooldridge, J. M. (2009). Econometric analysis of cross section and panel data (2nd ed.). Cambridge, MA: The MIT Press.
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Angrist, J. D., and Pischke, J. (2009). Mostly harmless econometrics: An empiricists companion. Princeton, NJ: Princeton University Press.
The two textbooks above provide an impressive amount of data from research articles. We provide them in a central place here.
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Rossant, C. (2018). IPython interactive computing and visualization cookbook (2nd ed.). Birmingham, England: Packt Publishing.
- Summer Quarter 2019, Graduate Program at the University of Bonn, please see here for details.
