Using novel data and machine learning techniques, we develop an early warning system for bank distress. The main input variables come from confidential regulatory returns, and our measure of distress is derived from supervisory assessments of bank riskiness from 2006 through to 2012. We...

This paper provides an analysis of the competitive process in the market for personal current accounts in the United Kingdom. Using survey data, we first describe some stylised developments in this market over our sample period (1996-2001). We find a gradual change in the distribution of market...

Recent studies illustrate that under some conditions dynamic stochastic general equilibrium models can be expressed as structural vector autoregressive models of infinite order. Based on this mapping and the theoretical results about vector autoregressive models of infinite order this paper...

This paper develops a tractable capitalist-worker New Keynesian model to study the interaction of fiscal policy and household heterogeneity. Workers can save in bonds subject to portfolio adjustment costs; firm ownership is concentrated among capitalists who do not supply labor. The model...

In a world of interconnected financial markets it is plausible that risk appetite — an important factor in asset pricing — is determined globally. By constructing an estimate of variance risk premia (VRP) for UK, US and euro-area equity markets, we are able to estimate international variance...

Tail interdependence is defined as the situation where extreme outcomes for some variables are informative about such outcomes for other variables. We extend the concept of multi-information to quantify tail interdependence at different levels of extremity, decompose it into systemic and...

Universal function approximators, such as artificial neural networks, can learn a large variety of target functions arbitrarily well given sufficient training data. This flexibility comes at the cost of the ability to perform parametric inference. We address this gap by proposing a generic...

This paper uses a vector autoregression model estimated with Bayesian methods to identify the effect of productivity news shocks on labour market variables by imposing that they are orthogonal to current technology but they explain future observed technology. In the aftermath of a positive news...

In this paper, we provide evidence that fat tails and stochastic volatility can be important in improving in-sample fit and out-of-sample forecasting performance. Specifically, we construct a VAR model where the orthogonalised shocks feature Student's t distribution and time-varying variance. We...

This paper proposes a method for detecting the sources of misspecification in a dynamic stochastic general equilibrium (DSGE) model based on testing, in a data-rich environment, the exogeneity of the variables of the DSGE with respect to some auxiliary variables. Finding evidence of...