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Forecasting Output Growth of Russian Manufacturing Industries Using Panel Data Models

Andrey V. Polbin – Head of Department of Mathematical Modeling of Economic Processes, Russian Presidential Academy of National Economy and Public Administration; Deputy Head of International Department of Mathematical Modeling of Economic Processes, Gaidar Institute for Economic Policy, Candidate of Economic Sciences (Moscow, Russia). Е-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Andrey V. Shumilov – Senior Researcher of the Russian Presidential Academy of National Economy and Public Administration, Candidate of Physical and Mathematical Sciences, Associate Professor (Moscow, Russia). E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

In this paper, we utilize panel data models for forecasting output growth rates of Russian manufacturing industries. Using monthly data for 2015–2021, we find that one-month-ahead forecasts of panel models are superior to corresponding naive forecasts based on averaging past growth rates. Compared to individual industry models, panel data models yield better forecasts at 1–6 months horizons for a number of industries, but the overall forecasting accuracy improves only slightly.

The article was written on the basis of the RANEPA state assignment research programme.

Key words: forecasting, dynamic panel data model, output growth, Russian manufacturing industries.

JEL-codes: C22, C23, C53.