10 research outputs found

    Analysing the spillover of inflation in selected Euro-area countries

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    We examined the spillover of inflation in selected Euro-area countries using monthly consumer price index (CPI) based inflation data covering the period 1955M1 to 2017M4. To achieve our objective, we used two recently developed methods of spillover: a time-domain spillover method, Diebold–Yilmaz (hereafter referred as DY method) and a frequency-domain method, Barunik–Krehlik (hereafter referred as BK method). We analysed 1–4 months and more than 4 months spillovers. The study has importance because the co-movement in the international inflation rates, among others, may be produced by common shocks, similarities in central bank reaction functions, international trade and the operation of purchasing power parity theory. However, to assess the synchronisation of inflation fluctuations across countries or regions, it is critical to understand the inflation behaviour and formulation of correct monetary policy

    Using stacking to average bayesian predictive distributions (with discussion)

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    Bayesian model averaging is flawed in the M-open setting in which the true data-generating process is not one of the candidate models being fit. We take the idea of stacking from the point estimation literature and generalize to the combination of predictive distributions. We extend the utility function to any proper scoring rule and use Pareto smoothed importance sampling to efficiently compute the required leave-one-out posterior distributions. We compare stacking of predictive distributions to several alternatives: stacking of means, Bayesian model averaging (BMA), Pseudo-BMA, and a variant of Pseudo-BMA that is stabilized using the Bayesian bootstrap. Based on simulations and real-data applications, we recommend stacking of predictive distributions, with bootstrapped-Pseudo-BMA as an approximate alternative when computation cost is an issue

    The Major Molecular Causes of Familial Hypercholesterolemia

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