We show that political booms, measured by the rise in governments' popularity, predict financial crises above and beyond other better-known early warning indicators, such as credit booms. This predictive power, however, only holds in emerging economies. We show that governments in emerging...

This paper investigates whether leading indicators can help explain the cross-country incidence of the 2008-09 financial crisis. Rather than looking for indicators with specific relevance to the current crisis, the selection of variables is driven by an extensive review of more than eighty...

This paper applies the Least Absolute Shrinkage and Selection Operator (LASSO) to make rolling 1-minute-ahead return forecasts using the entire cross section of lagged returns as candidate predictors. The LASSO increases both out-of-sample fit and forecast-implied Sharpe ratios. And, this...

A representative investor does not know which member of a set of well-defined parametric "structured models'' is best. The investor also suspects that all of the structured models are misspecified. These uncertainties about probability distributions of risks give rise to components of...

We provide an overview of the data required to monitor repo and securities lending markets for the purposes of informing policymakers and researchers about firm-level and systemic risk. We start by explaining the functioning of these markets and argue that it is crucial to understand the...

This paper implements a liquidity measure, “Liquidity Mismatch Index (LMI),” to gauge the mismatch between the market liquidity of assets and the funding liquidity of liabilities. We construct the LMIs for 2882 bank holding companies during 2002-2014 and investigate the time-series and...

In this paper we discuss the properties of confidence intervals for regression parameters based on robust standard errors. We discuss the motivation for a modification suggested by Bell and McCaffrey (2002) to improve the finite sample properties of the confidence intervals based on the...

In this paper we propose a new variance estimator for OLS as well as for nonlinear estimators such as logit, probit and GMM, that provcides cluster-robust inference when there is two-way or multi-way clustering that is non-nested. The variance estimator extends the standard cluster-robust...

A consensus has recently emerged that variables beyond the level, slope, and curvature of the yield curve can help predict bond returns. This paper shows that the statistical tests underlying this evidence are subject to serious small-sample distortions. We propose more robust tests, including a...

Recent work on robust estimation has led to many procedures, which are easy to formulate and straightforward to program but difficult to study analytically. In such circumstances experimental sampling is quite attractive, but the variety and complexity of both estimators and sampling situations...