Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
The existence of a serial correlation common feature among the first differences of a set of 1(1) variables implies the existence of a common cycle in the Beveridge–Nelson–Stock–Watson decomposition of those variables. A test for the existence of common cycles among cointegrated variables is developed. The test is used to examine the validity of the common trend‐common cycle structure implied by Flavin's excess sensitivity hypothesis and Campbell and Mankiw's mixture of rational expectations and rule‐of‐thumb hypothesis for consumption and income. Linear independence between the cointegration and the cofeature vectors is exploited to decompose consumption and income into their trend and cycle components.