This paper proposes a methodology to nowcast and forecast inflation using data with sampling frequency higher than monthly. The nowcasting literature has been focused on GDP, typically using monthly indicators in order to produce an accurate estimate for the current and next quarter. This paper...

We use a novel disaggregate sectoral euro area data set with a regional breakdown to investigate price changes and suggest a new method to extract factors from over-lapping data blocks. This allows us to separately estimate aggregate, sectoral, country-specific and regional components of price...

This paper makes a significant contribution on both conceptual and methodological fronts, in the analysis of the effect of maternal autonomy on school enrolment age of children in India. The school entry age is modelled using a discrete time duration model where maternal autonomy is entered as a...

This study investigates the systematic risk factors driving emerging market (EM) credit risk by jointly modelling sovereign and corporate credit spreads at a global level. We use a multi-regional Bayesian panel VAR model, with time-varying betas and multivariate stochastic volatility. This model...

The authors evaluate the out-of-sample forecasting performance of six competing models at horizons of up to three quarters ahead in a pseudo-real time setup. All the models use information in monthly indicators released ahead of quarterly GDP. The authors estimate two models – averaged vector...

The misevaluation of risk in securitized …financial products is central to understand- ing the Financial Crisis of 2007-2008. This paper characterizes the evolution of factors affecting collateralized debt obligations (CDOs) based on subprime mortgages. A key feature of subprime-mortgage backed...

We exploit the richness of a large data set of daily and monthly business cycle indicators by pooling them to produce Nowcast of contemporaneous real GDP growth. We conduct predictions based on a pooling of bivariate forecasts which uses these indicators as predictors of GDP (Nowcast with...

A new method is proposed for estimating linear triangular models, where identification results from the structural errors following a bivariate and diagonal GARCH(1,1) process. The associated estimator is a GMM estimator shown to have the usual √T-asymptotics. A Monte Carlo study of the...

This paper makes a significant contribution on both conceptual and methodological fronts, in the analysis of the effect of maternal autonomy on school enrolment age of children in India. The school entry age is modelled using a discrete time duration model where maternal autonomy is entered as a...