Economics at your fingertips  

A Functional Linear Regression Model in the Space of Probability Density Functions

Yoshiyuki Arata

Discussion papers from Research Institute of Economy, Trade and Industry (RIETI)

Abstract: In this paper, we propose a functional linear regression model in the space of probability density functions. We treat a cross-sectional distribution of individual earnings as an infinite dimensional random variable. By an isometric transformation of density functions, the constrained nature of density functions is explicitly taken into account. Then, we introduce a regression model where the income distribution is a dependent variable. Asymptotic results for the significance test statistics of the coefficients are obtained. Applying this method to Japanese data, we figure out a functional relationship of the income distribution with economic growth. It is found that the change in income distribution associated with economic growth is characterized by a disproportional increase in the lower income class, reduction of the middle income earners, and irresponsiveness of the higher income earners. Since the information that the income distribution offers is preserved as a density function, this method enables us to obtain implications ignored by the usual statistical ones.

Date: 2017-03
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this paper

More papers in Discussion papers from Research Institute of Economy, Trade and Industry (RIETI) Contact information at EDIRC.
Bibliographic data for series maintained by TANIMOTO, Toko ().

Page updated 2019-02-07
Handle: RePEc:eti:dpaper:17015