A major policy challenge posed by derivatives clearinghouses is that their collateral requirements can rise sharply in times of stress, reducing market liquidity and further exacerbating downturns.
In this paper, the authors develop a new tool to improve the short-term forecasting of real GDP growth in the euro area and Japan. This new tool, which uses unrestricted mixed-data sampling (U-MIDAS) regressions, allows an evaluation of the usefulness of a wide range of indicators in predicting short-term real GDP growth.
This paper studies the formation of consumers’ inflation expectations using micro-level data from the Michigan Survey. It shows that beyond the well-established socio-economic determinants of inflation expectations such as gender, income or education, other characteristics such as the households’ financial situation and their purchasing attitudes also matter.
We exploit the panel dimension of the Canadian Financial Monitor (CFM) data to estimate the impact of retail payment innovations on cash usage. We estimate a semiparametric panel data model that accounts for unobserved heterogeneity and allows for general forms of non-random attrition.
The network pattern of financial linkages is important in many areas of banking and finance. Yet bilateral linkages are often unobserved, and maximum entropy serves as the leading method for estimating counterparty exposures.
Information on the allocation and pricing of over-the-counter (OTC) markets is scarce. Furfine (1999) pioneered an algorithm that provides transaction-level data on the OTC interbank lending market.
Estimation of the quantile model, especially with a large data set, can be computationally burdensome. This paper proposes using the Gaussian approximation, also known as quantile coupling, to estimate a quantile model.