Improving inflation prediction with the quantity theory

C-Tier
Journal: Economics Letters
Year: 2016
Volume: 149
Issue: C
Pages: 112-115

Authors (3)

Wang, Ying (not in RePEc) Tu, Yundong (not in RePEc) Chen, Song Xi (Peking University)

Score contribution per author:

0.336 = (α=2.02 / 3 authors) × 0.5x C-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

This paper focuses on the role of the quantity theory in improving inflation forecasts. We find that the cointegration-based quantity theory does not hold for the period after 1995 for the U.S. data. However, that period is well explained by an adaptive quantity theory based on a functional-coefficient cointegration that adapts to the unemployment rate. The forecasting exercises show that the adaptive quantity theory has superior predictive power for targeting future inflation.

Technical Details

RePEc Handle
repec:eee:ecolet:v:149:y:2016:i:c:p:112-115
Journal Field
General
Author Count
3
Added to Database
2026-01-25