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The stationarity of inflation in Croatia: anti-inflation stabilization program and the change in persistence

Economic Change and Restructuring volume 50, pages 45–58 (2017)Cite this article

Abstract

This study examines the impact of the anti-inflation stabilization policies on the behavior of inflation in Croatia in the early 1990s and through the subsequent post-stabilization period using fractional integration techniques. Indeed, the implementation of the stabilization program in October 1993 brought immediate deflation with a relative high degree of inflation stability in the post-stabilization period. With allowance for a structural break corresponding to the stabilization program in October 1993, the degree of persistence was substantially reduced with the fractional differencing parameter being positive but close to zero in the post-stabilization period.

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Notes

  1. Sticky price models of Taylor (1979) implies stationarity of the price level whereas the Phillips curve models of Calvo (1983) and Ball (1993) allow a unit root in prices, but require inflation to be stationary.

  2. For the Fisher effect to hold the inflation rate should contain a unit root and be cointegrated with the nominal interest rate for the real interest rate to be I(0). See Nelson and Schwert (1977), Barsky (1987), Rose (1988), Chapman and Ogaki (1993), Wallace and Warner (1993), Evans and Lewis (1995), Crowder and Hoffman (1996), among others, for discussion of the Fisher effect. As noted by Garcia and Perron (1996), the nonstationarity of real interest rates is problematic for the pricing of options in the Black–Scholes model along with consumption capital asset pricing models as well.

  3. As noted by Yellen and Akerloff (2006), to keep the unemployment rate below the natural rate requires an ever-increasing rate of inflation which implies the non-stationarity of inflation.

  4. Note that stationarity and integration of order zero, I(0), are not the same concept. In the context of fractional integration or I(d) processes, covariance stationarity is satisfied as long as d is smaller than 0.5.

  5. See as examples Taylor (1985), Clarida et al. (1999), Orphanides and Wieland (2000), and Martin and Milas (2004) for discussion with respect to the importance of the stationarity of inflation for monetary policy.

  6. Studies by Culver and Papell (1997), Lee and Wu (2001), Osterholm (2004), Lee et al. (2007), Basher and Westerlund (2008), Cook (2009), Ho (2009), Romero-Avila and Usabiaga (2009), Narayan and Narayan (2010), and Tsong et al. (2012) utilize a variety of panel unit root tests. Henry and Shields (2004), Gregoriou and Kontonikas (2006; 2009), Nobay et al. (2010), and Zhou (2013) employ nonlinear unit root tests. Lee and Tsong (2009) and Tsong and Lee (2010) use bootstrap covariate stationarity tests while Lai (1997) and Cook (2005) employ modified Dickey-Fuller tests; Charemza et al. (2005) use a symmetric stable Paretian distribution with infinite variables in unit root tests; and Chang et al. (2013) utilize flexible Fourier stationarity tests. Hassler and Wolters (1995), Baillie et al. (1996), Baum et al. (1999), Bos et al. (1999), Lee (2005), Gadea and Mayoral (2006), and Meller and Nautz (2012) apply fractional integration techniques to examine the long memory and persistence behavior of inflation.

  7. See Begg (1996), Burton and Fischer (1998), Brada and Kutan (1999), Kutan and Brada (1999), and Ross (2000) regarding the experience of several transition economies in addressing post-stabilization inflation. Due to price liberalization and disruption in trade linkages, all transition economies suffered high inflation and major recessions in the early 1990s. Following initial stabilization programs of the early 1990 s, most transition economies succeeded in lowering inflation but only to moderate levels. According to Roaf et al. (2014), in some cases, such as Romania and Bulgaria, initial attempts at stabilization were unsuccessful. During the early stages of transition, stabilization programs were largely based on nominal anchors, primarily the exchange rate, but in some cases the wage rate, relying on direct controls and quantitative restrictions to implement monetary policy. As transition economies stabilized by the end of the 1990s, many countries began to face a number of additional challenges. For instance, increased capital flows placed pressure on domestic demand making it difficult to maintain a low inflation rate. For those countries with more developed financial institutions, the pegging of nominal exchange rates was abandoned in favor of indirect methods of monetary control. Several transition economies (Poland, Hungary, the Czech Republic, and Slovakia) adopted inflation targeting as a result.

  8. Much of the discussion regarding the anti-inflation stabilization program is drawn from Payne (2002).

  9. See Egert and Lang (2006) on the effectiveness of foreign exchange intervention with respect to the Croatian economy.

  10. In the years up to 2002, Deutche mark was the primary currency and afterwards the euro.

  11. For an overview, see Scheiber and Stixt (2009).

  12. For more on Maastricht criteria, see http://ec.europa.eu/economy_finance/euro/adoption/who_can_join/index_en.htm.

  13. Broz (2010) investigates whether the introduction of the euro is justifiable in the case of Central an Eastern European countries with a special focus on Croatia. Moreover, new European Union members that entered after the euro was launched in 2002 are not eligible for an opt-out clause.

  14. Source for the data is Croatian Bureau of Statistics.

  15. Similar results were obtained with other “local” Whittle semiparametric approaches (Robinson, 1995; Abadir et al. 2007).

  16. We also examined inflation in the post-stabilization period using the ADF, Phillips-Perron, and KPSS unit root and stationarity tests with an intercept and trend in which the ADF and Phillips-Perron unit root tests reject the null hypothesis of a unit root with test statistics of −77.27 and −64.94, respectively, each statistically significant at the 1 percent level. The KPSS stationarity test fails to reject the null hypothesis of stationarity with a test statistic of 0.112.

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Authors and Affiliations

  1. University of Navarra, Pamplona, Spain

    Luis A. Gil-Alana

  2. The Institute of Economics, Zagreb, Croatia

    Andrea Mervar

  3. J. Whitney Bunting College of Business, Georgia College & State University, Milledgeville, GA, 31061, USA

    James E. Payne

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  1. Luis A. Gil-Alana
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  2. Andrea Mervar
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  3. James E. Payne
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Correspondence to James E. Payne.

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Gil-Alana, L.A., Mervar, A. & Payne, J.E. The stationarity of inflation in Croatia: anti-inflation stabilization program and the change in persistence. Econ Change Restruct 50, 45–58 (2017). https://doi.org/10.1007/s10644-016-9181-2

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