Locally Stationary Quantile Regression for Inflation and Interest Rates

Zhuying Xu, Seonjin Kim, Zhibiao Zhao

Research output: Contribution to journalArticlepeer-review

Abstract

Motivated by the potential time-varying and quantile-specific relation between inflation and interest rates, we propose a locally stationary quantile regression approach to model the inflation and interest rates relation. Large sample theory for estimation and inference of quantile-varying and time-varying coefficients are established. In empirical analysis of inflation and interest rates relation, it is found that the estimated functional coefficients vary with time in a complicated manner. Furthermore, the relation is quantile-specific: not only do the selected orders differ for different quantiles, but also the coefficients corresponding to different quantiles can display completely different patterns.

Original languageEnglish (US)
JournalJournal of Business and Economic Statistics
DOIs
StateAccepted/In press - 2021

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Social Sciences (miscellaneous)
  • Economics and Econometrics
  • Statistics, Probability and Uncertainty

Fingerprint Dive into the research topics of 'Locally Stationary Quantile Regression for Inflation and Interest Rates'. Together they form a unique fingerprint.

Cite this