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Characterizing economic trends by Bayesian stochastic model specification search

Authors
Publication Date
Keywords
  • E32 - Business Fluctuations
  • Cycles
  • C52 - Model Evaluation
  • Validation
  • And Selection
  • C22 - Time-Series Models
  • Dynamic Quantile Regressions
  • Dynamic Treatment Effect Models
Disciplines
  • Economics
  • Mathematics

Abstract

We apply a recently proposed Bayesian model selection technique, known as stochastic model specification search, for characterising the nature of the trend in macroeconomic time series. We illustrate that the methodology can be quite successfully applied to discriminate between stochastic and deterministic trends. In particular, we formulate autoregressive models with stochastic trends components and decide on whether a specific feature of the series, i.e. the underlying level and/or the rate of drift, are fixed or evolutive.

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