I thank Christopher Bowdler (editor), two anonymous referees, Kazumi Asako, Takatoshi Ito, Kosuke Oya, and Akira Terai for useful comments, and Enago (http://www.enago.jp) for the English language review. This work was supported by KAKENHI (19530185, 23530255).
Measuring Inflation Expectations Using Interval-Coded Data*
Article first published online: 10 MAY 2012
© John Wiley & Sons Ltd and the Department of Economics, University of Oxford 2012
Oxford Bulletin of Economics and Statistics
Volume 75, Issue 4, pages 602–623, August 2013
How to Cite
Murasawa, Y. (2013), Measuring Inflation Expectations Using Interval-Coded Data. Oxford Bulletin of Economics and Statistics, 75: 602–623. doi: 10.1111/j.1468-0084.2012.00704.x
- Issue published online: 2 JUL 2013
- Article first published online: 10 MAY 2012
- Final Manuscript Received: April 2012
To quantify qualitative survey data, the Carlson–Parkin method assumes normality, a time-invariant symmetric indifference interval, and long-run unbiased expectations. These assumptions are unnecessary for interval-coded data. In April 2004, the Monthly Consumer Confidence Survey in Japan started to ask households about their price expectations a year ahead in seven categories with partially known boundaries. Thus one can identify up to six parameters including an indifference interval each month. This paper compares normal, skew normal (SN), skew exponential power (SEP), and skew t (St) distributions, and finds that an St distribution fits the data well. The results help us to better understand the dynamics of heterogeneous expectations.