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Trend inflation estimates for Thailand from disaggregated data
Institution:1. Jaume I University, Spain;2. University of Barcelona, Spain;3. University of Valencia, Spain
Abstract:This paper constructs a new trend inflation measure for Thailand based on the multivariate unobserved components model with stochastic volatility and outlier adjustments (MUCSVO) of Stock and Watson (2016). Similar to core inflation, the MUCSVO produces an estimate of trend inflation utilizing information in disaggregated data, but also allows for time-varying weights that depend on the volatility, persistence and comovement of the underlying sectoral inflation series. Based on the empirical results, the majority of sectoral weights show significant time-variation in contrast to their relatively stable expenditure shares. Volatile food and energy sectors that are typically excluded from core inflation measures also turn out to help explain approximately 10 percent of MUCSVO trend inflation rate movements. Compared against other benchmark trend inflation measures, we show that the MUCSVO delivers trend estimates that are smoother, more precise, and are able to forecast average inflation over the 1–3 year horizon more accurately both in-sample and out-of-sample, especially since the year 2000.
Keywords:Disaggregated prices  Inflation  Outlier adjustment  Stochastic volatility  Time-varying parameters  Trend-cycle decomposition  Unobserved components  
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