The research was supported by the Hungarian National Research, Development and Innovation Office, project No. K-124808. The authors acknowledge the helpful comments of László Halpern, István Kónya, Róbert Lieli, Gábor Pintér and Károly Attila Soós on earlier drafts. Any remaining errors are those of the authors.
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Appendix can be accessed online at: https://www.mtakti.hu/wp-content/uploads/2020/06/Complementary.docx.
The article draws on an extensive study by the authors (Krekó – Oblath 2018), which addresses several issues belonging to our topic, but not discussed in this article, in particular, convergence in income and price levels within the EU. Due to limitations of space, Section 5 of the article, Table 1, most of the figures, as well as the Appendix are omitted from the printed version, but they are accessible online as “Complementary text, figures, tables and appendices to the article” at https://www.mtakti.hu/wp-content/uploads/2020/06/Complementary.docx.
The term “comparative” refers to the fact that spatial price levels/structures can be interpreted only in comparison to a reference country or a group of countries, e.g., the average of the EU.
The PPP reflects the purchasing power of the domestic currency relative to a reference region. Our empirical work relies on the PPP database of the Eurostat, which expresses the purchasing power of currencies as compared to an artificial currency unit, called purchasing power standard (PPS). The PPS is defined so that 1 PPS has the same purchasing power as 1 euro with respect to an average of the EU member-states. In other words, the PPS shows the cost of a basket in country i, which costs 1 euro in the average of (a group of) the EU countries. Since the time series for certain items, in particular, goods and services, expressed in PPS-EU28 are relatively short, our analyses rely on data measured in PPS-EU15.
It should be stressed that the internal relative price indicator is also interpreted to a reference group: it shows how the price level of services is related to the price level of goods in the home country, as compared to the EU15.
Samuelson referred to the results of international comparisons performed in the framework of the ICP project in which the University of Pennsylvania had a major role. The PWT constitutes a major statistical source for worldwide comparisons of real GDP and its components. The data indicate a close positive association between the level of real incomes and relative price levels of GDP.
It should be noted that while the Penn-effect works among countries at considerably different levels of economic development, it does not appear to be significant within the most and the least developed group of countries; see Rogoff (1996) and Hassan (2016) on this point.
A thorough review of the related literature is provided by Devereux (2014). For a recent contribution, challenging the notion that higher productivity growth is accompanied by the RER-appreciation, see Gubler – Sax (2019).
It should be noted that while several endeavours had been made to explain the underperformance of particular developed economies by RER-overvaluations (see in particular Kaldor (1966, 1971) on the UK and Corden (1984) on the “Dutch disease”), these interpretations did not refer to misalignments of RERs from the levels implied by the level of development.
Similarly to Berg – Miao (2010), we use the term “symmetric effect” of misalignments in the above sense, though we are aware that “symmetry” is sometimes considered to imply that both under- and overvaluations are harmful for growth. This, however, would involve an asymmetry in the sense that misalignments with a negative and a positive sign would both have a negative effect on growth.
We use the term “stylized facts” more broadly than as introduced by Kaldor (1961). We refer to statistical observations underlying and motivating, rather than to observations meant to be actually explained by, our analysis. See Skidelsky (2017) on Kaldor's original interpretation of the term.
Luxembourg, an extreme outlier, is not included in our sample.
This is similar to the much earlier results of Kravis – Lipsey (1983). Berka – Devereux (2013) also documented the close association between relative price and income levels within the EU for the period of 1995–2009. They quantified the aggregate internal RER as the relative price of non-tradables to tradables, based on a selection of items at the lowest level of aggregation. Their results are similar to ours, suggesting that at the aggregate level there is a rather close correspondence between the relative price of non-tradables to tradables on the one hand, and services to goods, on the other.
The actual regressions estimated in Section 3 differ from the ones illustrated in Fig. 2, as our estimates contain year dummies and we apply the DOLS method by adding short term dynamic terms to the regression.
Since the population of Cyprus and Malta is below 1 million, they are not included in our sample.
For reasons discussed earlier, Luxembourg is not included in our sample.
The sample period is short and the number of a cross-sections is large so the power of unit root and cointegration tests is low and sensitive to the number of lags, but the majority of the tests confirmed cointegration between the variables in the long-term equation.
The role of leading and lagged dynamic terms is to give an asymptotically efficient estimation for the long-term parameter by eliminating the feedback in the cointegrating system.
This specification is similar to Rodrik (2008), however, he adds country fixed effect instead of lagged dependent variable to the equation.
In addition to the lagged dependent variable, the specification also includes the second lag of the dependent variable and the Arellano–Bond test statistic for the AR(2) in the first differences is not rejected in any specification.
If the data generating process is the lagged dependent variable but modelled with fixed effect, the model might overestimate the effect of misalignment, and the estimated parameter could be biased downward if a fixed effect model is incorrectly estimated by the lagged dependent variable.
The effect of inflation, government deficit and investment/GDP is similar in the fixed effect specifications, that is, when only the within variation is used for identification. However, economic freedom usually loses significance in the fixed effect models, as the within variation is much less important at this variable.
We also investigated whether the ER regime influences the long-term RER, but the dummy for fixed ER proved to be insignificant in all specifications for the long-term relationship.
If only the absolute size of misalignments was considered, it would not be possible to differentiate between the effects of over- and undervaluations.
First we tested the sign asymmetry by adding the dummy variable
Since 1995, the following CEEU countries operated under the fixed ER regime: BU, EE, LT, LV; since 2007: SI; since 2009: SK. Table A16 in the Appendix includes the classification of the EU member-states by the ER regimes.
References include studies referred to Section 5, accessible online.