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...

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...

Based on a broad set of regional aggregated and disaggregated consumer price index (CPI) data from major industrialized countries in Asia, North America and Europe we are examining the role that national borders play for goods market integration. In line with the existing literature we find that...

We use consumer price data for 81 European cities (in Germany, Austria, Finland, Italy, Spain, Portugal and Switzerland) to study the impact of the introduction of the euro on goods market integration. Employing both aggregated and disaggregated consumer price index (CPI) data we confirm...

We use consumer price data for 205 cities/regions in 21 countries to study PPP deviations before, during and after the major currency crises of the 1990s. We combine data from industrialized nations in North America (Unites States, Canada and Mexico), Europe (Germany, Italy, Spain and Portugal),...

Global developments play an important role in domestic inflation rates. Previous literature has found that a substantial amount of the variation in a large set of national inflation rates can be explained by a single global factor. However, inflation volatility has been typically neglected,...

The COVID-19 pandemic has led to enormous movements in economic data that strongly affect parameters and forecasts obtained from standard VARs. One way to address these issues is to model extreme observations as random shifts in the stochastic volatility (SV) of VAR residuals. Specifically, we...

The estimation of large vector autoregressions with stochastic volatility using standard methods is computationally very demanding. In this paper we propose to model conditional volatilities as driven by a single common unobserved factor. This is justified by the observation that the pattern of...