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Extra info for Bloomberg Business Week (2013.06.17 - 2013.06.23)
4 Beffy et al. (2006) explain the PFA procedure used by the OECD in detail. 2 3 Descriptive Analysis Methods for Measuring Synchronicity Contemporaneous unconditional Pearson correlations computed either between the business cycles of individual countries and a reference country or computed as unconditional bilateral correlations are the most commonly employed measures for synchronicity (cf. table 1 in section 2). The first alternative allows one to examine whether a single country converges to a reference series – the euro area aggregate, in our case – while the second alternative allow one to examine the dispersion of business cycle similarities over a group of countries.
1 A Statistical Test of Convergence The test is based on the sign and significance of the coefficient TU in the regression ȡt c ȡ ș ȡ t İtȡ , in which t is a linear time trend. A positive and significant coefficient indicates that synchronicity has risen over time and that convergence has taken place. In the exact same manner, the test is run by replacing Ut with the comovement measures Ȗt in order to test if convergence with respect to decreasing output gap distances can be detected. Table 5 and table 6 present results of the convergence tests for three sample periods: (i) the complete observation period from 1973Q1 to 2006Q1, (ii) the period 46 3 Descriptive Analysis from 1980Q1 to 1998Q4 prior to the introduction of the euro which covers important developments towards European integration (completion of the Single Market Program, Treaty of Maastricht), (iii) the period from 1999Q1 to 2006Q1, which marks the introduction of the euro.
In our calculations we use these standard parameters. Also considered is a symmetric moving average (MA) for estimating a smooth trend component of the underlying series. The estimate of the cycle is the difference between the observations and the MA, which in our study is also set to 12 quarters and 36 months, for quarterly and monthly data, respectively. The MA has the distinct advantage of being simple to compute and highly transparent. A similar property holds for the first order difference (D1) of seasonally adjusted series and for the year-on-year difference (DIF4) of time series.