Composite leading indicators of economic activity: An application to the upstream oil and gas industry in Rio de Janeiro

This paper proposes a monthly composite leading indicator to anticipate turning points in the economic activity of the upstream oil and gas industry in Rio de Janeiro, from January 2002 to May 2019. Firstly, we build a database with 61 series, and categorize each of them into i) rapidly responsive to economic activities; ii) expectation-sensitive; or iii) prime movers indicators. Afterward, we remove the seasonality of the series through the X-13 ARIMA-SEATS method and use the Bry-Boschan algorithm to identify the cycles. Then, we evaluate the components’ fit to integrate the composite leading indicator through four statistical tests: cross-correlation, quadratic probability score, Granger causality, and probit. The assessment of the composite leading indicator demonstrates that it leads 67% of the peaks and 100% of the troughs in the target series (5/6 of the turning points). Furthermore, the average leading period is 8.4 months, while the median is 9 and the standard error is 2.8 months. We contribute to the literature by creating, to our knowledge, the first leading indicator for the oil and gas industry in Brazil.