Clive Granger

Cointegration, developed by Clive Granger and Robert Engle, identifies when two or more non-stationary time series move together in the long run despite short-term fluctuations. If two series are cointegrated, there exists a linear combination of them that is stationary, indicating a meaningful equilibrium relationship.

Granger shared the 2003 Nobel Memorial Prize in Economic Sciences with Robert Engle for methods of analyzing economic time series. Granger was specifically cited for his work on cointegration and methods for modeling long-run relationships among economic variables that individually exhibit trends.

The Granger causality test examines whether past values of one time series help predict another series, beyond what is possible using only the past values of the second series itself. While not true causation in the philosophical sense, Granger causality indicates predictive content useful for forecasting and understanding temporal relationships.

Granger's contributions to time-series analysis—including cointegration, causality testing, and spurious regression detection—are fundamental tools for economists building forecasting models. These methods help analysts identify genuine relationships between economic variables and avoid false conclusions from analyzing trending data.