Department of Applied Economics

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Regular version of the site

Events

Apr 25 – Apr 26

7th Conference "Applied Econometrics"

All events

Publications

Book

Academic Star Wars: Excellence Initiatives in Global Perspective
In press

Yudkevich Maria, Altbach P. G., Salmi J.

Cambridge: MIT Press, 2023.

Article

The Impact of Carbon Tax and Research Subsidies on Economic Growth in Japan

Besstremyannaya G., Dasher R., Golovan S.

HSE Economic Journal. 2025. Vol. 29. No. 1. P. 72-102.

Book chapter

Science or industry: Improving the quality of the Russian higher education system

Panova A., Slepyh V.

In bk.: Vocation, Technology & Education. Vol. 1. Iss. 4. Shenzhen Polytechnic University, 2024.

Working paper

Living Standards in the USSR during the Interwar Period

Voskoboynikov I.

Economics/EC. WP BRP. Высшая школа экономики, 2023. No. 264.

All publications

109028, Moscow
Pokrovsky blvd. 11,
Room S-527
Phone: (495) 772-95-99 ext.27502, 27503, 27498

Administration

Department Head – Svetlana B. Avdasheva

Deputy Department Head – Liudmila S. Zasimova

Manager – Maxim Shevelev

Faculty of Economic Sciences

Department of Applied Economics

Delivered by:: Department of Applied Economics

Type:: Mago-Lego

When:: 4 module

Instructor

Sheluntcova, Maria

Full Syllabus Ask Question

Abstract

This course is devoted to binary choice models that are central in applied econometrics. We deal with the situation when the potential outcomes are discrete, i.e. the presence or absence of some quality of the object in question. It might also be the decision of an individual to perform or not to perform any action. The scope of application of these models is very wide. Classical examples are the problems of forecasting companies' defaults, employment equations, modeling the level of education, and many other problems of identifying the determinants of a certain choice and predicting its probability. In addition, we consider models with truncated dependent variable. The course includes Tobin and Heckman models that enables us to deal with truncated samples and selection bias. The course is applied in nature. Analysis of course’s topics is based on numerical examples. At the seminars, students use statistical software, i.e. STATA.