The conduct of time series analysis on the Euro Area currently presents problems in terms of availability of sufficiently long data sets. The ECB has provided a dataset of quarterly data from 1970 covering many data series in its Area Wide Model (AWM), but not for a number of important financial market series. This paper discusses methods for producing such backdata and in the resulting difficulties in selecting aggregation methods. Simple applicaiton of the AWM weights results in orders of magnitude difference in financial series. The use of different aggregation methods across series induces relationships. The effects of different possible methods of constructing data are shown through estimation of simple Taylor rules, which result in different weights on output gaps and inflation deviation for what are purportedly the same data
Euro area, data aggregation, Taylor rule
Time series analysis for the Euro Area requires the availability of sufficiently long historical data series, but the appropriate construction methodology has received little attention. The benchmark dataset, developed by the European Central Bank for use in its Area Wide Model (AWM), is based on fixed-weight aggregation across countries with historically distinct monetary policies and financial markets of varying international importance. This paper proposes a new methodology, based on the historical distance from monetary integration between core and periphery countries, for producing back-dated monetary and financial series for the Euro Area. The impact of using the new methodology versus the AWM data is illustrated through a structural VAR analysis and estimates of an international DSGE model. An important advantage of the new methodology is that it can be applied to develop appropriate series as new member countries join the Euro Area.
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