Adapting the Number of Particles in Sequential Monte Carlo Methods Through an Online Scheme for Convergence Assessment Articles uri icon

publication date

  • April 2017

start page

  • 1781

end page

  • 1794

issue

  • 7

volume

  • 65

International Standard Serial Number (ISSN)

  • 1053-587X

Electronic International Standard Serial Number (EISSN)

  • 1941-0476

abstract

  • This article complements the recent literature analysing the effects of the unconventional monetary stimuli applied after the Great Recession by proposing an intuitive and easy-to-implement method to evaluate different exit strategies towards a traditional monetary context. This approach, useful for central bankers or researchers interested in the effects of tapering, allows us to evaluate the consequences of a given monetary policy path on the future evolution of key macroeconomic indicators. The results based on this methodology provide a measurement of the differences in economic performance under contractionary and expansionary policies and support the recent success of monetary stimuli in boosting real indicators while having little effect on inflation.

subjects

  • Telecommunications

keywords

  • particle filtering; sequential monte carlo; convergence assessment; predictive distribution; convergence analysis; computational complexity; adaptive complexity