Evaluating the Information Value for Measures of Systemic Conditions

Timely identification of coincident systemic conditions and forward-looking capacity to anticipate adverse developments are critical for macroprudential policy. Despite clear recognition of these factors in literature, an evaluation methodology and empirical tests for the information value of coincident measures are lacking. This paper provides a twofold contribution to the literature: (i) a general-purpose evaluation framework for assessing information value for measures of systemic conditions, and (ii) an empirical assessment of the information value for several alternative measures of US systemic conditions. We find substantial differences among the measures, of which the Cleveland Financial Stress Index shows best-in-class identification performance. In terms of forecasting performance, Kamakura's Troubled Company Index, Cleveland Financial Stress Index, and Goldman Sachs Financial Conditions Index show moderately stable usefulness metrics over time