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Global Factors Driving Inflation and Monetary Policy: A Global VAR Assessment

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Abstract

This paper examines the nexus between inflation and central bank interest rate policies in inflation-targeting countries. First, it looks at the role of inflation among other factors affecting monetary policy. Second, it looks at the drivers of inflation alone. Thereby, the role of international spillovers from other countries is explicitly regarded as well, with the aim of assessing the extent to which inflation is driven by other countries’ inflation or monetary policy is influenced by other economies. The empirical study covers advanced countries and emerging market economies for the period 1995 - 2016 and uses Bayesian global vector autoregression to model external linkages and to account for variable uncertainty. This study finds that inflation plays an important role for monetary policy. More importantly, central banks clearly consider additional factors and notably other countries’ key indicators when setting interest rates. Inflation in turn is determined by both internal and external factors like the exchange rate and other countries’ inflation. These findings are much more comprehensive than previous literature and demonstrate that central banks consider a multitude of domestic and global factors.

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  1. Taylor (2007) proposed that CBs should explicitly watch the events in other economies, observe monetary decisions of other CBs and ideally act in a cooperative manner.

  2. Only Galesi and Lombardi, (2009) studied inflation in a similar setting using a GVAR model, but with an outdated data set and smaller country coverage. Recently, Feldkircher and Siklos, (2019) used a similar econometric approach but focused on the link between inflation and inflation expectations for a large set of countries.

  3. The sample covers all major economies and thus encompasses all major trade and financial linkages worldwide. These countries have an intra-group trade share of 60-90 percent.

  4. For a comparison of models that deal with large data sets, such as panel VARs, GVARs and factor augmented VARs, see Feldkircher et al. (2020b).

  5. For simplicity it was assumed here that all countries feature the same number of endogenous variables in xjt. In the empirical application, the dimension of \({x}_{it}^{*}\) depends on the country.

  6. Recently, other weights based on financial flows have been proposed in the literature (Eickmeier and Ng 2015). However, a sensitivity analysis of Feldkircher and Huber (2016) of weighting measures in Bayesian GVAR specifications showed that trade weights lead to a perfect model fit.

  7. For further information on the specific posterior moments and hyperparameter specifications, see Feldkircher and Huber (2016). Due to storage limits a thinning interval was used to select 6,000 out of the 30,000 posterior draws. From these, unstable posterior draws were identified, which are characterized by large eigenvalues of the companion form of the global model leading to approximately 27% of the 6,000 posterior draws upon which the empirical results are based.

  8. Traditionally, the inflation literature (Boschi and Girardi 2007; Alexova 2012) distinguishes demand-pull and cost-push (wage costs, import prices) factors for inflation. Due to data constraints, wage costs were not included in our model.

  9. A related strand of literature investigated the effect of globalization, given by trade and financial openness, on the inflation level (e.g., Badinger 2009; Gnan and Valderrama, 2006).

  10. Note that in the strict Taylor rule, CBs would set their interest rates according to deviation of inflation from a target and the output gap.

  11. In this sample, all advanced countries officially or unofficially introduced IT in the 1990s and EMEs started doing so since 2000. Only China has yet not done so (Combes et al., 2017; Jahan 2017; Benes et al., 2017).

  12. Note that the Fisher effect would also postulate a co-movement between inflation and interest rates.

  13. This is in contrast to the finding of Choi et al. (2018), who reported that the effect of the oil price on inflation is no longer found after 2 years.

  14. Note that the Brent oil price index is higher than the Russian, Mexican and Organisation of the Petroleum Exporting Countries (OPEC) oil price.

  15. For India, an equally high impact of demand-driven inflation as in our results was found by Mohanty and John (2015), but only for the non-crisis period.

  16. Also Huang et al. (2010) indicated liquidity as a major inflationary force in China.

  17. We are aware that short-term interest rates may deviate from the interest rates set by CBs if the interest pass-through is distorted.

  18. Only the Bank of England has published guidelines which explicitly state that interest rate policy should be guided by multiple domestic and international indicators, such as output growth, the exchange rate and developments in the U.S., the EA and EMEs.

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Correspondence to Gabriele Tondl.

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This paper was written while Gabriele Tondl was a visiting fellow at the Austrian National Bank. She also gratefully acknowledges funding under the Research Contract 2016 of the Anniversary Fund of the Vienna University of Economics and Business. The opinions expressed in this paper are those of the authors and do not necessarily reflect the official viewpoint of the Austrian National Bank or the Eurosystem.

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Feldkircher, M., Tondl, G. Global Factors Driving Inflation and Monetary Policy: A Global VAR Assessment. Int Adv Econ Res 26, 225–247 (2020). https://doi.org/10.1007/s11294-020-09792-2

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