We identify the temporary and permanent components of US stock prices through appropriate restrictions on a vector autoregression of real stock returns and changes in interest rates, employing alternative robust estimation procedures designed to allow for non-Gaussian innovations.  2000 Elsevier Science S.A. All rights reserved.

Comovement is more than correlation. This paper estimates the contributions of intermediate production linkages, trade patterns, and financial holdings on the directed graph of linkages that describe the international propagation of macroeconomic shocks at the business cycle frequency. The empirical methodology is a novel generalization of the panel vector autoregression (VAR) which nests both ...

This study examines the time-varying connectedness among realized volatilities of seven major cryptocurrencies between January 2020 and May 2022. To this end, we implement time frequency parameter vector autoregression (TVP-VAR) approaches. Our findings propose that (i) COVID-19 pandemic significantly affected dynamic connectedness; (ii) total index hits its apex around official announcement pa...

A large empirical literature has examined the transmission mechanism of structural shocks in great detail. The possible role played by changes in the volatility of shocks has largely been overlooked in vector autoregression based applications. This paper proposes an extended vector autoregression where the volatility of structural shocks is allowed to be time-varying and to have a direct impact...

The subway is one of the major passenger transport systems in Seoul, Korea. Over the last 30 years, the subway system has interacted with urban land use. This study aims to describe the subway system evolution and reveal the causal relations with land rent and population distributions in conjunction with the evolution of the subway system. Extensive and rapid expansion of subway networks have i...

We model the conditional mean and volatility of stock returns as a latent vector autoregressive (VAR) process to study the contemporaneous and intertemporal relationship between expected returns and risk in a flexible statistical framework and without relying on exogenous predictors. We find a strong and robust negative correlation between the innovations to the conditional moments that leads t...

This paper suggests a term structure model which parsimoniously exploits a broad macroeconomic information set. The model uses the short rate and the common components of a large number of macroeconomic variables as factors. Precisely, the dynamics of the short rate are modeled with a FactorAugmented Vector Autoregression and the term structure is derived using parameter restrictions implied by...