Locally Stationary Quantile Regression for Inflation and Interest Rates

• Activity Number: 167 - Data Mining and Econometrics
• Type: Contributed
• Date/Time: Tuesday, August 10, 2021 : 10:00 AM to 11:50 AM
• Sponsor: Business and Economic Statistics Section
• Author(s): Seonjin Kim* and Zhuying Xu and Zhibiao Zhao
• Companies: Miami University and Indeed Inc and Penn State University
• Keywords: Inflation; Interest rates; Locally stationary model; Nonparametric estimation; Quantile regression; Time-varying model

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.