We study the role of oil prices in forecasting Russian recession periods with probit models. Our findings suggest that fluctuations in nominal oil prices are useful predictors of the Russian business cycle, even when controlling for a number of classic recession predictors. However, in line with international findings, the term spread turns out to be the most powerful predictor of future recessions. Overall, the best in-sample fit is found using a model including the term spread and the oil price variable as predictors. The pseudo out-of-sample forecasts confirm the findings.
Fields of Science
- 511 Economics