We propose a new no-change benchmark to evaluate forecasts of series that are temporally aggregated. The new benchmark is the last high-frequency observation and reflects the null hypothesis that the underlying series, rather than the aggregated series, is unpredictable. Under the random walk...

We investigate the causal structure of financial systems by accounting for contemporaneous relationships. To identify structural parameters, we introduce a novel non-parametric approach that exploits the fact that most financial data empirically exhibit heteroskedasticity. The identification...

We distinguish between the goods and services sectors in an otherwise standard unobserved components model of US inflation. Our main finding is that, while both sectors used to contribute to the overall variation in aggregate trend inflation, since the 1990s this variation has been driven almost...

This paper develops and estimates a two-factor model of intergenerational skill transmission when earnings inequality reflects differences in individual skills and other non-skill shocks. We consider heterogeneity in both initial skills and skill growth rates, allowing variation in skill growth...

We propose and estimate a dynamic and individual model of expectations formation that links individual consumers' inflation expectations to their own lagged forecasts as well as proxies for the rational expectation forecasts. The model builds on the existing rational inattention literature and...

I investigate the impact of contactless credit cards (CTCs) on cash use in Canada, using panel data between 2010 and 2017. I show that ignoring unobserved heterogeneity would lead to overstating the impact of CTCs on cash usage in a linear model. Using finite mixture modelling, I provide...

In this paper, we present new evidence from unobserved components time-series models on the cyclical behavior of the demand for education relative to economic cycles. We investigate the cyclical properties of schooling decisions, the time-varying exposure of these decisions to changes in the...

We propose a new no-change benchmark to evaluate forecasts of series that are temporally aggregated. The new benchmark is the last high-frequency observation and reflects the null hypothesis that the underlying series, rather than the aggregated series, is unpredictable. Under the random walk...

We document that the term structures of risk-neutral expected loss and gain uncertainty on S&P 500 returns are upward sloping on average. These shapes mainly reflect the higher premium required by investors to hedge downside risk and the belief that potential gains will increase in the long run....

We introduce a new class of time-varying parameter vector autoregressions (TVP-VARs) where the identified structural innovations are allowed to influence - contemporaneously and with a lag - the dynamics of the intercept and autoregressive coefficients in these models. An estimation algorithm...