Micro data analysis 1600-SZD-WM-MDA
The aim of this course is to familiarize students with the methods used in modern, applied empirical research involving microeconomic data. Topics such as model specification, estimation and inference will be covered for each data type. If possible all lectures will take place in a computer lab, and will involve description of the given method and analysis of the case studies to gain a better understanding. This course we will use an open source statistical software, R. Grades will be based on home assignments and the final test.
The course will cover following topics:
Introduction and Ordinary Least Squares:
• Course outline, grading. Introduction to R software.
• Ordinary Least Squares – advantages and disadvantages, limiting conditions
Generalization of the linear model:
• Heteroskedasticity and quantile regression.
• Endogeneity and two stage least square methods.
• Generalized linear models.
Maximum likelihood estimation (MLE):
• Binary models.
• Inference with MLE: testing hypothesis, marginal effects, elasticities.
• Random utility model and models for multinomial variables (multinomial logit model, mixed logit model).
• Models for ordinal variables and count data.
Type of course
Course coordinators
Learning outcomes
Participants of the course will be familiarized with methods and tools of microeconometrics – both theoretical (rationale, assumptions, theory) and practical (building a model, data analysis, estimation, interpretation of the results).
Assessment criteria
1. Completing the course is based on the results of written paper (60%) and 2 home assignments (30%).
2. To pass the course requires collecting at least 50% of the total number of points.
The final result is calculated using the following formula:
Result = 0.6*(percentage paper score) + 0.4* (Home assignment percentage score).
Home assignments consist of solving data analysis problems (individually or in groups, depending on the assignment). Solutions are verified and the most common mistakes are reviewed in class.
Attendance is not a requirement for completing the course.
All students are subject to the same rules. There are no other possibilities to complete the course.
Bibliography
− Greene, W. H., 2011. Econometric Analysis. 7 Ed., Prentice Hall.
− Cameron, A. C., and Trivedi, P. K., 2005. Microeconometrics: Methods and Applications. Cambridge University Press.
Textbooks – selected topics
− Train, K. E., 2009. Discrete Choice Methods with Simulation. 2 Ed., Cambridge University Press, New York.
− Hensher, D. A., Rose, J. M., and Greene, W. H., 2015. Applied Choice Analysis. 2 Ed., Cambridge University Press, Cambridge.
− Greene, W. H., and Hensher, D. A., 2010. Modeling Ordered Choices: A Primer. Cambridge University Press.
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: