Macro-indicators of Russian Economy and World Economy Indices. Cointegration Analysis

In this paper we do a research on relationships between macro-indicators of Russian economy and world economy indices. To this end, we construct and estimate models within time series econometrics. In this case, if ordinary least squares is used, so-called spurious regression is possible, as shown in this paper. But if the indicators have a common stochastic trend, that is, there is a cointegration relationship between them, ordinary least squares may be used, and derived estimators converge to real values faster than in the classic case. Much of the work is focused on the cointegration analysis. Using cointegrating regression method, we search for cointegration relationships, and construct an error-correction model for them. We make conclusions based on the research, such as, the world steel production is the most optimal predictor of Russia's GDP (compared to oil prices, Kilian Index, and Agricultural Raw Material Index). This claim is noticeable, because Russia's economy is traditionally considered to be highly dependent on oil prices.