EIB Papers Volume 13. n°1/2008 - European Investment Bank

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Productivity of public capital increased in countries where the public capital stock grew. 76 Volume13 N°1 2008 EIB PAPERS Figure 5. Public capital ratios for three groups of countries, 1960-2001 (a) Public-capital-to-GDP ratio (b) Public-capital-to-private-capital ratio 0.6 0.4 0.2 0.0 (c) Change in public-capital-to-GDP ratio (d) Variability of the public-capital-to-GDP ratio 0.2 0.1 0.0 -0.1 -0.2 N O P mean median mean median N O P mean median mean median Note: The figure shows the differences in the mean (blue bars) and median (red bars) for three groups of countries. In the “P” group public capital has become more productive over time. In the “N” group public capital has become less productive. In the “O” group the productivity of public capital did not change during the 1990s. See the last column of Table 5 for the countries in the various groups. In Figure 5 we analyse whether there is any difference across the three groups with respect to the • Average of the public-capital-to-GDP ratio; • Public-capital-to-private-capital ratio • Change in the public-capital-to-GDP ratio; and • Variability in the public-capital-to-GDP ratio. The blue bar denotes the mean for the group, while the gray bar shows the median. Figure (5a) suggests that the public capital stock is not systematically different across countries where the impact of public capital on output increased during the 1990s (“P”) and those countries where this impact decreased (“N”) or remained the same (“O”). The F-statistic of an ANOVA analysis to the test whether the capital stock ratio differs between the three groups is 0.15 (p = 0.86). 0.25 0.20 0.15 0.10 0.05 0,00 0.10 0.08 0.06 0.04 0.02 0.00 N O P N O P
Figures (5b) and (5d) show that there is also hardly any systematic difference across the three groups of countries with respect to the ratio of public and private capital and the variability of the public capital stock. The F-statistics are 0.14 (p = 0.87) and 1.83 (p = 0.19), respectively. However, Figure (5c) shows that countries in the “P” group have an increasing capital-stock-to-GDP ratio, while countries in the “N” group saw this ratio decline. Indeed, the test that the change in the capital stock is equal for the three groups can be rejected; the F-statistic is 4.63 (p = 0.02). 4.2 Panel VARs As an alternative to the time-series models reported in Section 3, we also estimate VARs for our panel of countries. We first examine the order of integration of the variables. Recent literature suggests that panel-based unit root tests have higher power than unit root tests based on individual time series. Using Eviews, we have computed five panel unit root tests, namely tests proposed by Levin, Lin and Chu (LLC) (2002), Breitung (BR) (2000), Im, Pesaran and Shin (IPS) (2003), ADF and PP tests (Maddala and Wu 1999 and Choi 2001), and a test suggested by Hadri (2000). While these tests are commonly termed ‘panel unit root’ tests, they are simply multiple-series unit root tests that have been applied to panel data structures. The tests suggested by Levin, Lin and Chu (2002), Breitung (2000), and Hadri (2000) assume that there is a common unit root process that is identical across cross-sections. The first two tests employ a null hypothesis of a unit root, while the Hadri panel unit root test is similar to the KPSS unit root test and has a null hypothesis of no unit root in any of the series in the panel. The Im, Pesaran, and Shin, and the ADF and PP tests allow for individual unit root processes that may vary across cross-sections. Table 6 shows the outcomes of the panel unit root tests. YES (NO) indicates (no) evidence for a unit root. It becomes clear that the results vary widely across the various tests. While the Hadri test suggests that all series are I(1), the other tests suggest that one or more series may be trend stationary. We proceed under the assumption that all series contain a unit root. This choice can be justified as we also find that the series are cointegrated and that there are two cointegrating vectors (indicated by both the trace test and the maximum eigenvalue test). The number of lags selected is two. Table 6. Panel unit root tests Government capital Private capital Output Hours worked LLC NO NO NO YES BR NO NO NO YES IPS NO YES YES YES ADF NO YES YES YES PP YES YES YES YES Hadri YES YES YES YES Notes: YES = evidence for unit root; NO = No evidence for unit root. The acronyms in the first column refer to the following tests: Levin, Lin and Chu (LLC), Breitung (BR), Im, Pesaran and Shin (IPS), Augmented Dickey-Fuller (ADF), and Phillips-Perron (PP). Figure 6 shows the long-run generalized impulse response for output for a one-standard-deviation shock to public capital. The impact of public capital on output is positive but we do not provide confidence intervals. To examine whether the impact of public capital on output has changed over time, we have estimated ‘recursive’ and ‘rolling-window’ VARs. Figure 7 shows the results for the latter; the results for the ‘recursive’ VARs are similar and are therefore not shown. The moving window for the ‘rolling’ VAR is 20 years. So the first VAR that we estimate covers the period 1960-1979 In the panel of countries the impact of public capital on output is positive. EIB PAPERS Volume13 N°1 2008 77
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Preface This year the European Inve
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Infrastructure investment, growth a
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Government investment is not the sa
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Despite progress, infrastructure de
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Table 7. Infrastructure indicators
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EU funds provide additional resourc
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Various empirical studies confirm t
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In some new member states there is
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PPPs offer new opportunities to fin
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Strong legal and institutional fram
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Additional fiscal reporting - even
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