- Common Factor Models (1)
- Disaggregated Prices (1)
- Euro Area Regional and Sectoral Inflation (1)
- common factor models (1)
- disaggregated prices (1)
- euro area regional and sectoral inflation (1)
- goods market integration (1)
- nominal exchange rate regime neutrality (1)
- real and nominal border effect (1)
- real exchange rate dispersion (1)
- Nominal exchange rate regimes and relative price dispersion : on the importance of nominal exchange rate volatility for the width of the border (2003)
- 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 intra-national markets are better integrated than international market. Additionally, our results show that there is a large "ocean" effect, i.e., inter-continental markets are significantly more segmented than intra-continental markets. To examine the impact of the establishment of the European Monetary Union (EMU) on integration, we split our sample into a pre-EMU and EMU sample. We find that border effects across EMU countries have declined by about 80% to 90% after 1999 whereas border estimates across non-EMU countries have remained basically unchanged. Since global factors have affected all countries in our sample similarly and major integration efforts across EMU countries were made before 1999, we suggest that most of the reduction in EMU border estimates has been "nominal". Panel unit root evidence shows that the observed large differences in integration across intra- and inter-continental markets remain valid in the long-run. This finding implies that real factors are responsible for the documented segmentations across our sample countries.
- On the importance of sectoral and regional shocks for price setting : [Version Juli 2012] (2012)
- 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 changes. We thereby provide an improved estimate of the sectoral factor in comparison with previous literature, which decomposes price changes into an aggregate and idiosyncratic component only, and interprets the latter as sectoral. We find that the sectoral component explains much less of the variation in sectoral regional inflation rates and exhibits much less volatility than previous findings for the US indicate. We further contribute to the literature on price setting by providing evidence that country- and region-specific factors play an important role in addition to the sector-specific factors, emphasising heterogeneity of inflation dynamics along different dimensions. We also conclude that sectoral price changes have a “geographical” dimension, that leads to new insights regarding the properties of sectoral price changes.
- On the importance of sectoral shocks for price-setting (2009)
- We use a novel disaggregate sectoral euro area dataset with a regional breakdown that allows explicit estimation of the sectoral component of price changes (rather than interpreting the idiosyncratic component as sectoral as done in other papers). Employing a new method to extract factors from over-lapping data blocks, we find for our euro area data set that the sectoral component explains much less of the variation in sectoral regional inflation rates and exhibits much less volatility than previous findings for the US indicate. Country- and region-specific factors play an important role in addition to the sector-specific factors. We conclude that sectoral price changes have a “geographical” dimension, as yet unexplored in the literature, that might lead to new insights regarding the properties of sectoral price changes. JEL-Classifications: E31, E4, E5, C3 Keywords: Disaggregated Prices, Euro Area Regional and Sectoral Inflation, Common Factor Models.