Globalisation effect on inflation in the Great Moderation era: New evidence from G10 countries

Qin, Duo; He, Xinhua Article Globalisation effect on inflation in the Great Moderation era: New evidence from G10 countries Economics: The Open-Access, Open-Assessment E-Journal Provided in Cooperation with: Kiel Institute for the World Economy – Leibniz Center for Research on Global Economic Challenges Suggested Citation: Qin, Duo; He, Xinhua (2013) : Globalisation effect on inflation in the Great Moderation era: New evidence from G10 countries, Economics: The Open-Access, Open-Assessment E-Journal, ISSN 1864-6042, Kiel Institute for the World Economy (IfW), Kiel, Vol. 7, Iss. 2013-25, pp. 1-32, https://doi.org/10.5018/economics-ejournal.ja.2013-25 This Version is available at: https://hdl.handle.net/10419/75207 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. http://creativecommons.org/licenses/by/3.0/ Received August 31, 2012 Published as Economics Discussion Paper October 31, 2012 Revised April 1, 2013 Accepted May 29, 2013 Published June 5, 2013 © Author(s) 2013. Licensed under the Creative Commons License - Attribution 3.0 Vol. 7, 2013-25 | June 05, 2013 | http://dx.doi.org/10.5018/economics-ejournal.ja.2013-25 Globalisation Effect on Inflation in the Great Moderation Era: New Evidence from G10 Countries Duo Qin and Xinhua He Abstract Dynamic econometric models are built individually for ten countries from G10 during the Great Moderation period, with the aim of analysing counterfactually the globalisation effect on inflation. The main findings are (i) the effect is highly heterogeneous from country to country; (ii) increases in trade openness could be either inflationary or deflationary whereas increased imports from low-cost emerging-market economies are mostly deflationary; and (iii) there is almost no direct globalisation impact as far as inflation persistence is concerned while the impact on inflation variability can be positive as well as negative. Overall, globalisation is found to have contributed positively to lowering rather than stabilising inflation during the Great Moderation era. JEL C52 E31 E37 F41 Keywords Inflation dynamics; globalisation Authors Duo Qin, Department of Economics, School of Oriental & African Studies, University of London, Thornhaugh Street, Russell Square, London WC1H 0XG, London, UK, [email protected] Xinhua He, Institute of World Economics and Politics, Chinese Academy of Social Sciences, Beijing, China Citation Duo Qin and Xinhua He (2013). Globalisation Effect on Inflation in the Great Moderation Era: New Evidence from G10 Countries. Economics: The Open-Access, Open-Assessment E-Journal, Vol. 7, 2013-25. http:// dx.doi.org/10.5018/economics-ejournal.ja.2013-25 www.economics-ejournal.org 1 1 Introduction The effect of globalisation on inflation of the last two decades constitutes one of the unsettled issues in the recent debate over the state of macroeconomics in the wake of the latest global recession triggered by the 2008 financial crisis. It relates particularly to the discussion of whether the state of low and stable inflation in many developed economies of the West since the early 1990s, a period referred to as the ‘Great Moderation’ (see Bernanke, 2004), should be credited to the success of domestic macroeconomic policies or simply to the rising global supply of cheap manufactured goods from those rapidly developing economies such as China (see, e.g., McCarthy, 2007; White, 2008; Bean, 2010; Clarida, 2012). Should globalisation be a major factor in driving domestic inflation, standard monetary theories of inflation could be invalidated, e.g., see Wang and Wen (2007).0F1 It is a well-known fact that there exists a considerable degree of correlation in the inflationary processes among many developed countries, as shown from Table 1 of the Western countries of G10. When it comes to econometric model results, however, the evidence is inconclusive concerning the hypothesis of whether globalisation has indeed significantly contributed to the inflation dynamics of Table 1. Correlation coefficients of CPI inflation 1998Q1–2010Q3 Note: The coefficients in bold in the upper triangle indicate those which are larger than their corresponding coefficients in the lower triangle. _________________________ 1 See also White (2009) for a more general critique. BEL CAN CHE DEU FRA UK ITA NLD SWE US BEL 1 0.37 0.65 0.62 0.64 0.50 0.41 0.42 0.48 0.70 CAN 0.41 1 0.61 0.08 0.77 0.68 0.67 -0.20 0.78 0.69 CHE 0.60 0.32 1 0.72 0.71 0.65 0.75 0.29 0.82 0.72 DEU 0.57 0.06 0.85 1 0.40 0.28 0.42 0.60 0.41 0.44 FRA 0.79 0.50 0.67 0.62 1 0.71 0.81 -0.09 0.78 0.78 UK 0.43 0.32 0.31 0.27 0.47 1 0.63 -0.11 0.75 0.75 ITA 0.42 0.12 0.74 0.69 0.62 0.22 1 -0.02 0.82 0.63 NLD 0.40 0.20 0.37 0.47 0.32 -0.09 0.44 1 0.05 0.05 SWE 0.57 0.31 0.66 0.69 0.64 0.19 0.62 0.50 1 0.67 US 0.73 0.60 0.61 0.48 0.71 0.55 0.46 0.20 0.42 1 1992Q1 – 2010Q3 www.economics-ejournal.org 2 these economies. For example, while supportive evidence are presented in Pain et al. (2006, 2008), Borio and Filardo (2007), Pehnelt (2007), Wang and Wen (2007), Milani (2010) and also partially in Ciccarelli and Mojon (2010), negative results are reported by Ball (2006) and Ihrig et al. (2010). It is thus not surprising that such studies are questioned not only on theoretical grounds but also on empirical procedures.1F2 The present investigation seeks to improve the commonly used empirical procedure in modelling the globalisation effects on inflation in order to produce more robust and precise evidence for future theoretical development. With respect to the previous studies, we choose the G10 economies except Japan as the objects of our investigation. Our improvement lies mainly in two aspects. First, domestic inflation is modelled at a country-by-country level with a careful choice of the variables representing globalisation. The LSE general-to-specific dynamic specification approach is adopted to ensure empirical robustness of the end model choice. Second, model simulations are carefully designed to enable more realistic counterfactual analyses of the globalisation effects. In particular, a novel simulation is designed to evaluate the disaggregate import effects from the lowcost emerging-market economies. The design overcomes a key weakness in the existing practice of macro model simulations – the lack of cross-country price level differences from the aggregate price indices. In short, our modelling experiment has resulted in relatively robust inflation models for the most of ten economies during the Great Moderation period. In all the ten cases, the responsiveness of inflation to import prices has been statistically significant; and in eight out of the ten cases, foreign trade openness has been also found significant. Moreover, the model simulation results show that both the trade openness and rising imports from the emerging-market economies have exerted sizeable effects on the level and variability of inflation, but that globalisation has impacted little as far as inflation persistence is concerned. On the whole, the evidence that we have produced is sufficiently strong to support the globalisation hypothesis. The rest of the paper is organised as follows. The next section describes our modelling method and the related data issues; the subsequent section discusses our model simulation designs and the related data measurement issues; the empirical _________________________ 2 For example, see NBER Digest at http://www.nber.org/digest/jun07/w12687.html . www.economics-ejournal.org 3 results concerning globalisation are discussed in Section 4, which is followed by a short section summarising the main findings. 2 Modelling strategy and data issues Most of the existing empirical studies are based on extended Phillips curve models, e.g., Ball (2006), Borio and Filardo (2007), Pehnelt (2007), Ihrig et al. (2010), Guerrieri et al. (2010) and Mihailov et al. (2011). One theoretical weakness of the type of Phillips curve models is the absence of explicitly specified long-run disequilibrium effect on the inflation dynamics. The long-run effect is included in the form of an error-correction (EC) term in the models by Pain et al. (2006, 2008). We shall follow their step. Analyses based on common factor models have also become popular, e.g., see Ciccarelli and Mojon (2010). While the common factor model approach is expedient for summarising a relatively large set of inflation series, the approach becomes awkward when the indicator set is made up of many highly trended price indices, an aggregate of which is needed for the long-run components in the EC modelling. The issue of how to represent globalisation in models is arguably the most crucial here. Various channels of globalisation has been discussed in the empirical literature, such as import price path-through, global output slacks, global competition via labour and capital markets. However, it is evident from numerous empirical studies that the globalisation effect on domestic inflation is mainly through overseas goods market imbalance or disequilibrium. Four variables are usually used to capture such imbalance – foreign output gaps, trade openness indicators, import price and common factors from cross-country inflation series. We shall adopt only two here – import price and trade openness indicators. Foreign output gaps are disregarded on both theoretical and empirical considerations. Theoretically, our aim is to model how much inflation of a specific country is affected by foreign markets, rather than how much global inflation is affected by global market supply and demanding conditions. Therefore, prices from abroad should contain adequate and timely information on the global market conditions. Empirically, data on foreign output gaps are not directly collected but indirectly derived. The derivation lacks a unanimously accepted formula; and the available modelling evidence using the data is disappointing, e.g., see Calza www.economics-ejournal.org 4 (2009) and Ihrig et al. (2010), owing possibly to rather high degrees of measurement errors involved in the derivation. Global inflation is derived from common factor models in Mumtaz and Surico (2008), and also Ciccarelli and Mojon (2010). The latter study further uses the common factor as a leading indicator to predict inflation of each country in a panel of twenty-two developed economies. While latent common factors do capture certain amount of the global inflationary effect, the method suffers from two shortcomings – limited sample representation of global inflation through exclusion of mainly the majority of developing economies in panels from which the factors are derived, and failure to exclude the inflation data of each economy to be modelled from the common factor, making it difficult to identify the factor as purely a foreign price variable. We thus start the modelling experiment with import price since it is the least controversial and the most commonly used variable to capture the foreign trade effect.2F3 Denoting it P as the aggregate price index, it p its logarithm and it p as inflation for country i under study, we take the following general form of an errorcorrection model: (1) M itiitiittititi n j Mjitij n j Gjitij n jjitij n jjitij n jjitijiit pwpececp yuwpp 211 0 1101 0 ,                  where it w is the logarithm of wage index, it W, M it p the logarithm of the import price index, M it P, G it y the domestic output gap, and it u the unemployment rate. The wage index is used as a proxy of domestic costs, e.g., see Pain et al. (2006, 2008). Obviously, it is impossible to rule out any foreign impact on wages, as pointed out by Ihrig et al (2010). However, simple correlation analyses show that the degree of correlation in crosscountry wage rates is notably smaller than that of inflation on average, e.g., see Table 2 versus Table 1. It should be noted that (1) resembles an _________________________ 3 In fact, Pain et al (2008) conclude that the indirect effect through import prices seems to be the only channel through which foreign economic conditions affect consumer price inflation. www.economics-ejournal.org 5 Table 2. Correlation coefficients of wage rates 1998Q1 – 2009Q4 1992Q1  2009Q4 Note: The coefficients in bold in the upper triangle indicate those which are larger than their corresponding coefficients in the lower triangle. extension of typical augmented Phillips curve models by an 1it ec term. Here, model (1) also generalises model [A1.1] in Pain et al. (2006) in three aspects: (a) It does not impose static homogeneity in the 1it ec term; (b) it allows for more than one lag of G it y; and (c) it considers it u since it was a key variable in the original Phillips’ curve prior to the invention of G it y and since empirical evidence of the role of G it y has not been unquestionably strong. However, model (1) excludes certain variables, such as energy and food price inflation, which have been considered in the literature, e.g., see Borio and Filardo (2007) and Ihrig et al. (2010). The exclusion is based on the observation that inflation series of these prices tend to be considerably correlated with those of import prices, as shown in Table 3. The correlation makes it incoherent not to interpret the significance of the food and energy price inflation variables as evidence of globalisation. Obviously, ij  and 2i  in (1) form our parameters of interest here and evidence of 0 ij  and/or 0 2 i  is confirmatory of the globalisation hypothesis. However, a more interesting and specific facet of the hypothesis is that the impact of M it p could increase with the growth of trade while the roles of those domestic factors decrease. Many existing studies test the facet by comparison of sub-sample estimation results, which basically follows the time-varying parameter BEL CAN CHE DEU FRA UK ITA NLD SWE US BEL 1 -0.44 0.33 0.26 -0.01 0.03 0.02 0.36 0.39 -0.04 CAN -0.20 1 -0.37 -0.27 0.22 0.33 0.52 -0.05 -0.08 0.53 CHE -0.04 -0.33 1 0.39 0.25 -0.06 -0.04 0.27 0.51 0.15 DEU 0.47 0.07 -0.11 1 0.14 0.06 0.02 0.18 0.57 0.04 FRA 0.19 0.28 0.03 0.42 1 0.02 0.47 0.50 0.30 0.61 UK 0.23 0.25 -0.18 0.01 -0.01 1 0.19 -0.08 0.46 0.25 ITA 0.21 0.49 -0.23 0.16 0.45 0.26 1 0.44 0.29 0.55 NLD 0.46 0.07 -0.14 0.47 0.54 -0.04 0.48 1 0.21 0.37 SWE 0.50 -0.01 -0.03 0.42 0.32 0.56 0.38 0.27 1 0.35 US -0.07 0.40 -0.01 0.33 0.49 -0.18 0.29 0.34 0.01 1 www.economics-ejournal.org 6 approach. Unfortunately, the approach suffers from the drawback of neglecting the possibility of time-varying parameter estimates being the result of model misspecification. It also makes it difficult to further apply models for simulation or projection purposes. Hence, we intend to try and obtain constant-parameter models by isolating the effect of trade intensification through appropriate variable choice. Besides, the limit of our attention to the Great Moderation era should help reduce the risk of significant parameter shifts. Specifically, we postulate an alternative model to (1) by introducing a trade-ratio based openness index, O it r, as a measure of increasing import penetration, similar to what Pain et al. (2006, 2008) and Ihrig et al. (2010) have done: (2) M itiitiittititi n j Mjitij n j Gjitij n jjitij n jjitij n jjitijiit pwpececp yuwpp ~~ , ~ ~~~ 211 0 1101 0                  where weighted variables are denoted by circumflex. For example,   O it G it G it ryy  1 ~ . Noticeably, it W and M it P can be weighted by either arithmetic weight or geometric weight. The former is adopted here, i.e.   O it M it M it rPp ln ~  and     O ititit rWw  1ln ~ , after experimenting with both.3F4 Other variations of (2) should also be possible depending on which parameters in (1) are potentially most susceptible to trade-induced shifts. For example, Pain et al. (2006, 2008) only consider the case of weighted long-run parameters, i.e.: (2a) M itiitiittititi n j Mjitij n j Gjitij n jjitij n jjitij n jjitijiit pwpececp yuwpp ~~ ,211 0 1101 0                  _________________________ 4 We find models with geometric weighted variables usually result in larger residuals and much worse simulation results than models with arithmetic weighted variables. www.economics-ejournal.org 7 Ihrig et al. (2010) experiment with adding weighted G it y ~ and M it p ~ to an augmented Phillips curve models rather than replace the relevant un-weighted variables (their model does not have the error-correction term). We shall experiment with several variations of model (2) with different mixture of weighted explanatory variables, for example, one with only the short-run variables weighted and another with only the long-run variables weighted. Many existing studies adopt simply the a priori dynamically specified inflation models, for example those which follow the New Keynesian theoretical approach. We believe it mainly an a posteriori matter to appropriately specify the dynamic structure of a model, especially its short-run structural part, see Hendry and Richard (1982, 1983), Hendry et al. (1984). In order to search for empirically robust model specifications, especially in the present case where we face multiple possible model variations, it is essential to put in place a set of criteria for model choice. The criteria that we adopt are based on the LSE general-to-specific model specification approach, see Hendry (1995). Specifically, model reduction via ‘testimation’ by the general-to-specific approach is carried out for (1) and several variations of (2). The resulting simplified models are assessed especially for having (a) correct signs of the long-run parameters and the negative feedback parameter of the 1it ec term, and (b) relatively constant parameter estimates, in addition of passing all the commonly used diagnostic tests. When more than one such data-coherent model is found for one country, encompassing tests are performed to assist the end model selection.4F5 The OLS method is used for simplicity throughout of the testimation. Although the estimator is known to be ‘biased’ when the regressors may contain ‘endogenous’ variables, such kind of simultaneity bias has been repeatedly shown to be statistically insignificant in numerous empirical studies over more than a half century, e.g. see Gilbert and Qin (2006). The above modelling strategy is applied to ten countries of the G10: Belgium (BEL), Canada (CAN), France (FRA), Germany (DEU), Italy (ITA), Netherlands (NLD), Sweden (SWE), Switzerland (CHE), the UK and the US. Japan is left out here because of its post-1990 idiosyncratic experience of deflationary recession, e.g., see McKinnon and Ohno (2001). Quarterly data is collected for the period _________________________ 5 The software, PcGets, has been used to assist the testimation but the end model selection is not made mechanically from models produced by PcGets. www.economics-ejournal.org 14 currency, approximate well of M it P, i.e., M it M it PP  ˆ. Next, we exploit (3) to decompose the set of trading partners into two groups: one for the emergingmarket economies, E, and the rest the developed countries, D, with 0;    EDNED : (4)       EtEtDtEt Ej X jt Ej jt jt Ej jt Dj X jt Dj jt jt Dj jt M it P PP              1 ln lnln       The decomposition will enable us to carry out counterfactual simulations through fixing the values of Et  and Et  respectively to evaluate the direct impact of imports from the emerging-market economies. Thirty-two economies are included in the trade set for the calculated import prices by equation (3) (see the appendix for the list and data sources). In addition to the eleven countries of the G10, the rest economies are selected because of their relatively high ranks in import shares of the ten G10 countries to be modelled according to the Direction of Trade data released by the IMF. These include Algeria, Austria, Brazil, Belgium, the Czech Republic, China, France, Finland, Germany, Hungary, Ireland, Italy, Libya, Malaysia, Mexico, the Netherlands, Poland, Portugal, Russia, Saudi Arabia, Spain, Turkey, Canada, Hong Kong, Denmark, Japan, Norway, Sweden, Switzerland, United Kingdom, United States and Taiwan. The trade set covers about 80% of the total imports for each of the G10 country on average. The closeness of these calculated import price series to the published import prices are shown in Figure 2. To further decompose the calculated prices by (4), the trade set is divided into two subsets, with the developed economy set comprising the G10 plus Austria, Denmark, Finland, Ireland, Luxembourg, Norway, Portugal and Spain, and the rest forming the emerging-market set. Now, a major problem arises when it comes to the decomposition equation (4): all the individual country export price indices are based on 2005=100, which www.economics-ejournal.org 15 Figure 2. Actual import price, M it P (solid line) and Calculated import price, M it P ˆ (dotted line) Belgium 70 90 110 130 150 1994 1996 1998 2000 2002 2004 2006 2008 2010 Canada 70 90 110 130 150 1994 1996 1998 2000 2002 2004 2006 2008 2010 France 60 80 100 120 140 1994 1996 1998 2000 2002 2004 2006 2008 2010 Germany 60 80 100 120 140 1994 1996 1998 2000 2002 2004 2006 2008 2010 Italy 60 80 100 120 140 160 1994 1996 1998 2000 2002 2004 2006 2008 2010 Netherlands 60 80 100 120 140 160 1994 1996 1998 2000 2002 2004 2006 2008 2010 Sweden 60 80 100 120 140 160 1994 1996 1998 2000 2002 2004 2006 2008 2010 Switzerland 60 80 100 120 140 1994 1996 1998 2000 2002 2004 2006 2008 2010 UK 60 80 100 120 140 1994 1996 1998 2000 2002 2004 2006 2008 2010 US 60 80 100 120 140 1994 1996 1998 2000 2002 2004 2006 2008 2010 www.economics-ejournal.org 16 effectively removes the differences in the aggregate price levels between the developed economies and the emerging-market economies. In other words, aggregate price indices reflect no information on the purchasing power parity (PPP) between countries by definition. To circumvent the problem, we make use of the PPP conversion factors for the year 2005 estimated by the World Bank (2008, Table 1.a) for around 150 countries. We are aware of the imprecise nature of using the World Bank factors here as these factors are estimated on the basis of both the service and goods prices of the domestic economies concerned while the price indices that we intend to convert are export prices only. But these factors are the best available aggregate ones and it is not unrealistic to assume that the export price level of an economy should be at par with its domestic price level in general. From a cross-section sample perspective, the World Bank estimates can be regarded as providing a set of PPP-based weights on the cross section of year 2005, whereas the panel of aggregate price indices which have been used in the calculated price series assume equal weights for all economies in 2005. Provided that the sample of 32 economies in our panel is adequately representative of the World Bank sample, recalculation of the price series by reweighting the individual price series using the World Bank PPP-based factors should not generate substantial differences from the result using the un-weighted ones.7F8 Figure 3 illustrates the decomposed series of Et  and Dt  calculated by using the World Bank PPP-based factors to reweight all the export price series of the emergingmarket economies in our trade subset. Noticeably, the gaps between the two sets of series are as wide as 50 on average. Since for a few emerging market economies, the earliest available trade data start in 1994. Our counterfactual simulations are run for the period of 1994Q1 to 2008Q3, i.e. the main part of the Great Moderation era prior to the latest global recession. We begin by running a baseline simulation in which we substitute the actual series of the import price indices by those series constructed by (3).8F9 This is _________________________ 8 The recalculation is tried for several of the G10 countries and the results show that the un-weighted and the weighted series are indeed very close. 9 Our baseline simulation is in fact very close to the actual CPI series because of both the small residuals in our estimated equations and the relatively good fit of our calculated import price series to the actual ones (see Figure 2). www.economics-ejournal.org 17 Figure 3. PPP based import price calculated for developed countries, Dt  (solid line) and emerging market economies, Et  (dotted line) Belgium 0 20 40 60 80 100 120 140 160 1994 1996 1998 2000 2002 2004 2006 2008 Canada 0 20 40 60 80 100 120 140 160 1994 1996 1998 2000 2002 2004 2006 2008 France 0 50 100 150 200 1994 1996 1998 2000 2002 2004 2006 2008 Germany 0 50 100 150 200 1994 1996 1998 2000 2002 2004 2006 2008 Italy 0 50 100 150 200 1994 1996 1998 2000 2002 2004 2006 2008 Netherlands 0 50 100 150 200 1994 1996 1998 2000 2002 2004 2006 2008 Sweden 0 20 40 60 80 100 120 140 160 180 1994 1996 1998 2000 2002 2004 2006 2008 Switzerland 0 20 40 60 80 100 120 140 160 1994 1996 1998 2000 2002 2004 2006 2008 UK 0 50 100 150 200 1994 1996 1998 2000 2002 2004 2006 2008 US 0 50 100 150 200 250 300 1994 1996 1998 2000 2002 2004 2006 2008 www.economics-ejournal.org 18 Figure 4. Simulated impact of the openness indices (solid line: baseline inflation; dotted line: simulated inflation with O it r fixed at the 1994Q1 value) Note: No effect for Sweden and the US as the selected model version is without the indices; the UK result is based on the model version with the index. Belgium 1.0% 1.5% 2.0% 2.5% 3.0% 1995 1997 1999 2001 2003 2005 2007 Canada 1.0% 1.5% 2.0% 2.5% 3.0% 1995 1997 1999 2001 2003 2005 2007 France 0.0% 0.5% 1.0% 1.5% 2.0% 2.5% 3.0% 3.5% 1995 1997 1999 2001 2003 2005 2007 Germany 0.0% 0.5% 1.0% 1.5% 2.0% 2.5% 3.0% 1995 1997 1999 2001 2003 2005 2007 Italy -1.0% 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 1995 1997 1999 2001 2003 2005 2007 Netherlands -1.0% 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 1995 1997 1999 2001 2003 2005 2007 Switzerland -1.5% -1.0% -0.5% 0.0% 0.5% 1.0% 1.5% 2.0% 2.5% 3.0% 1995 1997 1999 2001 2003 2005 2007 UK 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 7.0% 1995 1997 1999 2001 2003 2005 2007 www.economics-ejournal.org 19 Figure 5. Simulated impact of the shares of imports from the developed countries versus the emerging market economies (solid line: baseline inflation; dotted line: simulated inflation with Et fixed to its 1994Q1 value) (completed on the next page) Belgium 1.0% 1.5% 2.0% 2.5% 3.0% 1995 1997 1999 2001 2003 2005 2007 Canada 1.0% 1.5% 2.0% 2.5% 3.0% 1995 1997 1999 2001 2003 2005 2007 France 0.0% 0.5% 1.0% 1.5% 2.0% 2.5% 3.0% 3.5% 1995 1997 1999 2001 2003 2005 2007 Germany 0.0% 0.5% 1.0% 1.5% 2.0% 2.5% 3.0% 1995 1997 1999 2001 2003 2005 2007 Italy -1.0% 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 1995 1997 1999 2001 2003 2005 2007 Netherlands 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 1995 1997 1999 2001 2003 2005 2007 Sweden -4.0% -2.0% 0.0% 2.0% 4.0% 6.0% 8.0% 10.0% 1995 1997 1999 2001 2003 2005 2007 Switzerland -1.5% -1.0% -0.5% 0.0% 0.5% 1.0% 1.5% 2.0% 2.5% 3.0% 1995 1997 1999 2001 2003 2005 2007 UK 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 7.0% 1995 1997 1999 2001 2003 2005 2007 US 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 1995 1997 1999 2001 2003 2005 2007 www.economics-ejournal.org 20 Figure 6. Simulated impact of the import prices from the emerging market economies (solid line: baseline inflation; dotted line: simulated inflation with DtEt   ) Belgium 1.0% 1.5% 2.0% 2.5% 3.0% 1995 1997 1999 2001 2003 2005 2007 Canada 1.0% 1.5% 2.0% 2.5% 3.0% 1995 1997 1999 2001 2003 2005 2007 France 0.0% 0.5% 1.0% 1.5% 2.0% 2.5% 3.0% 3.5% 1995 1997 1999 2001 2003 2005 2007 Germany 0.0% 0.5% 1.0% 1.5% 2.0% 2.5% 3.0% 3.5% 1995 1997 1999 2001 2003 2005 2007 Italy -1.0% 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 1995 1997 1999 2001 2003 2005 2007 Netherlands 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 7.0% 1995 1997 1999 2001 2003 2005 2007 Sweden -4.0% -2.0% 0.0% 2.0% 4.0% 6.0% 8.0% 10.0% 1995 1997 1999 2001 2003 2005 2007 Switzerland -1.5% -1.0% -0.5% 0.0% 0.5% 1.0% 1.5% 2.0% 2.5% 3.0% 1995 1997 1999 2001 2003 2005 2007 UK 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 7.0% 1995 1997 1999 2001 2003 2005 2007 US 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% 7.0% 1995 1997 1999 2001 2003 2005 2007 www.economics-ejournal.org 21 to separate the errors owing to the deviations of the calculated indices from the actual indices out of the subsequent simulations. Next, three scenarios are designed to illustrate the globalisation impacts of three factors respectively: (i) the openness index by setting O it rfixed to its initial value at the beginning of the simulation, (ii) the trade shares by setting Et  to its initial value at the beginning of the simulation and (iii) the disaggregate import prices by setting Et =Dt . Figures 4–6 and Table 5 summarises the simulated results. A word of caution is necessary here before we move on to the next section. Simulations are limited by the models on which they are based. Here, the formulation of models (1) and (2) restricts our simulations at least in two respects. First, the indirect impact of import prices via labour costs, productivity gains through competition and other channels is beyond our simulations; second, the aggregate and dynamic features of the models make it impossible to separate out the individual contributions of Et  versus Dt  entirely. 4 Empirical results of globalisation effects We are now in the position of discussing the globalisation effects found from the econometric exercise. First, let us examine the relevant parameter estimates in Table 4. It is remarkable that all the countries except Sweden and the US fit in with model (2). Of the import price variable, the effects are of the globalisationintensified type, i.e., the openness-index weighted type for six out of the ten countries in terms of the short-run variable and for six to seven of them in terms of the long-run variable. Moreover, unemployment variable is found to be the openness-index weighted type in the cases of Belgium, Italy and the Netherlands; the domestic output gap variable is found to be the openness-index weighted type in the cases of Italy and the UK; and the short-run wage rate variable falls also into the type in the cases of Canada, France, the Netherlands and Switzerland. If we focus ourselves on the import price variable irrespective of the openness index specification, we find that the long-run import price effect is present in all but the Italian models, and that the effect is stronger than that of the wage variable in Germany, the Netherlands, Sweden and Switzerland. A closer examination reveals that these four countries share the common features of both having their openness www.economics-ejournal.org 22 Table 5. Summary impact on inflation from model simulations Average inflation (sample mean in %) Inflation variability (standard deviation) Inflation persistence (Marques’s r) 1995-2008 2000-2008 1995-2008 2000-2008 1995-2008 2000-2008 Belgium 1.79 1.85 0.28 0.31 0.56 0.60 Scenario 1 -4.2% -2.1% -4.2% -6.3% 0.56 0.54 Scenario 2 +0.7% +0.9% -0.1% -1.0% 0.56 0.60 Scenario 3 +1.5% +1.8% +0.1% -1.0% 0.55 0.60 Canada 2.03 2.19 0.36 0.32 0.51 0.49 Scenario 1 +5.5% -1.9% -7.7% +22.0% 0.53 0.54 Scenario 2 +4.5% +6.0% +8.2% -2.6% 0.49 0.49 Scenario 3 +8.6% +9.3% +5.4% -2.0% 0.49 0.49 France 1.65 1.98 0.63 0.47 0.44 0.51 Scenario 1 -2.4% +0.3% +29.7% +57.8% 0.55 0.51 Scenario 2 +2.5% +2.9% +3.0% -1.3% 0.42 0.54 Scenario 3 +6.2% +2.0% -10.0% -2.9% 0.42 0.51 Germany 1.45 1.67 0.49 0.43 0.55 0.51 Scenario 1 -62.2% -60.9% -34.9% -44.1% 0.51 0.46 Scenario 2 +12.2% +14.4% +8.2% -9.9% 0.47 0.54 Scenario 3 +31.6% +21.3% -8.6% +12.8% 0.60 0.60 Italy 2.37 3.24 1.41 0.66 0.36** 0.46 Scenario 1 +23.7% +20.7% +15.7% +48.3% 0.53 0.46 Scenario 2 -1.3% -1.5% -1.0% +2.1% 0.38* 0.46 Scenario 3 -0.1% +1.5% +2.9% +4.1% 0.42 0.46 Netherlands 2.21 2.56 1.16 1.27 0.64** 0.60 Scenario 1 -42.7% -34.9% +10.0% +11.0% 0.62* 0.54 Scenario 2 +24.1% +28.7% +3.7% -15.3% 0.60 0.57 Scenario 3 +51.3% +47.5% -2.4% -10.0% 0.64** 0.60 Sweden 1.09 1.31 2.35 1.52 0.56 0.49 Scenario 2 +17.5% +21.7% -3.1% -4.9% 0.55 0.46 Scenario 3 +27.8% +23.9% -2.1% -8.9% 0.55 0.49 Switzerland 0.47 0.67 0.71 0.72 0.51 0.51 Scenario 1 -46.3% -35.7% -16.3% -16.4% 0.49 0.51 Scenario 2 +5.7% +4.5% +5.0% +6.6% 0.51 0.51 Scenario 3 +3.1% +3.6% +7.1% +7.6% 0.53 0.51 www.economics-ejournal.org 23 Table 5 continued UK 1.94 2.14 1.10 0.95 0.58 0.60 Scenario 1 -2.3% -2.2% +2.5% +5.2% 0.58 0.57 Scenario 2 +9.2% +11.1% +0.7% -1.4% 0.56 0.60 Scenario 3 +15.8% +14.6% -0.7% -0.3% 0.64** 0.60 US 2.68 3.03 1.01 0.86 0.49 0.40 Scenario 2 +12.7% +13.5% +7.4% +5.6% 0.49 0.34* Scenario 3 +25.0% +19.8% +29.2% +26.0% 0.47 0.40 Note: See the penultimate paragraph of Section 3 for the design of the three scenarios. Marques’s (2004) measure of inflation persistence, r, is defined as T n r1, where n stands for the number of times the series crosses the mean during a time interval with T+1 observations. r is normally distributed with mean 0.5 and variance of T 5.0 . The superscripts ** and * in the last two columns indicate the corresponding r exceeding the significance levels of 95% and 90% respectively. Of the first four columns, The summary statistics in the first rows of each country are calculated from the baseline simulation. The statistics in the rows of three scenarios are calculated as percentage differences of the scenarios against the baseline. indices well above 30% and their shares of import from the emerging-market economies greater than 15% (see Figure 1). To a certain extent, the short-run import price effect is more striking. It is not only present in all the ten cases but also dominantly positive, with virtually an accelerative effect for more than half of the cases (i.e., close to the specification of jt M p  with a positive coefficient). Hence on grounds of model (1), the evidence constitutes an overwhelming case for the globalisation hypothesis. Even if on grounds of (2), the case is adequately strong. Our results on the role of import price are in broad agreement with those reported in Pain et al. (2006, 2008), although our long-run parameter estimates show too distinct heterogeneity to support their grouped estimates or assumed homogeneity. Nevertheless, it is clear from Table 4 that omission of the long-run effect is a model specification error in those studies which only consider short-run Phillips curve inflation models. 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World Development Indicators 2008. Washington DC: World Bank. http://data.worldbank.org/products/data-books/WDI-2008 Please note: You are most sincerely encouraged to participate in the open assessment of this article. You can do so by either recommending the article or by posting your comments. Please go to: http://dx.doi.org/10.5018/economics-ejournal.ja.2013-25 The Editor © Author(s) 2013. Licensed under the Creative Commons License Attribution 3.0.