CES VŠEM o aktuálních ekonomických problémech

compare results for all main pURTs (the LLC, the IPS, the M-W,
and the Pesaran’s test); however, the main emphasis will be
placed on results of the Pesaran’s CADF test. 52
The latest versions of both tests (LLC and IPS) offer tools to solve
some practical problems, such as cross-sectional correlation (as
cross-sectional independence of innovations is assumed).
Regarding the cross-sectional dependence, Bussiére al. (2010)
summarise findings of the study of Pesaran and Tosetti (2007)
that tries to shed some light on this issue. They distinguish
between two types of correlation – 'strong' and 'weak'. While the
first one cannot be solved by demeaning time series, the other
can. The potential impacts also depend on the country size and
time dimensions. In the case of medium and large panels, weak
cross-sectional correlation does not pose a serious problem;
strong correlation for non-stationary panel has not been
addressed yet (an attempt is presented in the study by Bussiére
al., 2010).
2. DATA
Empirical studies have used different sorts of data as there is no
prior information. While some have worked with monthly data
(Telatar and Hasanov, 2009), others used quarterly (Matei, 2009)
or even yearly data (Solakoglu, 2006). We have decided to rely
on quarterly data as they are sufficiently long and allow us to
perform robustness tests. This is also connected with some
advantages and disadvantages. The time span is longer for
quarterly data than it would have been for monthly data and it is
a reasonable way of solving problem of low number of yearly
observations for our set of countries. On the other hand,
52 The LLC and IPS tests are due to their construction with the assumption of
cross section independence, not perfectly adequate for our analysis.
86