Stochastic Population Analysis: A Functional Data Approach

36 Pages Posted: 14 Jul 2015

See all articles by Lei Fang

Lei Fang

Humboldt University of Berlin - Center for Applied Statistics and Economics (CASE)

Wolfgang Karl Härdle

Blockchain Research Center Humboldt-Universität zu Berlin; Charles University; National Yang Ming Chiao Tung University; Asian Competitiveness Institute

Date Written: February 2015

Abstract

Based on the Lee-Carter (LC) model, the benchmark in population forecasting, a variety of extensions and modifications are proposed in this paper. We investigate one of the extensions, the Hyndman-Ullah (HU) method and apply it to Asian demographic data sets: China, Japan and Taiwan. It combines ideas of functional principal component analysis (fPCA), nonparametric smoothing and time series analysis.

Based on this stochastic approach, the demographic characteristics and trends in different Asian regions are calculated and compared. We illustrate that China and Japan exhibited a similar demographic trend in the past decade. We also compared the HU method with the LC model. The HU method can explain more variation of the demographic dynamics when we have data of high quality, however, it also encounters problems and performs similarly as the LC model when we deal with limited and scarce data sets, such as Chinese data sets due to the substandard quality of the data and the population policy.

Keywords: Functional principal component analysis; Nonparametric smoothing; Mortality forecasting; Fertility forecasting; Asian demography; Lee-Carter model; Hyndman-Ullah method

JEL Classification: C14, C32, C38, J11, J13

Suggested Citation

Fang, Lei and Härdle, Wolfgang Karl, Stochastic Population Analysis: A Functional Data Approach (February 2015). Available at SSRN: https://ssrn.com/abstract=2630301 or http://dx.doi.org/10.2139/ssrn.2630301

Lei Fang (Contact Author)

Humboldt University of Berlin - Center for Applied Statistics and Economics (CASE) ( email )

Spandauer Strasse 1
Berlin, D-10178
Germany

Wolfgang Karl Härdle

Blockchain Research Center Humboldt-Universität zu Berlin ( email )

Unter den Linden 6
Berlin, D-10099
Germany

Charles University ( email )

Celetná 13
Dept Math Physics
Praha 1, 116 36
Czech Republic

National Yang Ming Chiao Tung University ( email )

No. 1001, Daxue Rd. East Dist.
Hsinchu City 300093
Taiwan

Asian Competitiveness Institute ( email )

Singapore

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