EJPAU 2009. Kisielińska J. TIME SERIES MODELING WITH SEASONALITY OF NONLINEARLY CHANGEABLE AMPLITUDE ON AN EXAMPLE OF INFLATION

Electronic Journal of Polish Agricultural Universities (EJPAU) founded by all Polish Agriculture Universities presents original papers and review articles relevant to all aspects of agricultural sciences. It is target for persons working both in science and industry,regulatory agencies or teaching in agricultural sector. Covered by IFIS Publishing (Food Science and Technology Abstracts), ELSEVIER Science - Food Science and Technology Program, CAS USA (Chemical Abstracts), CABI Publishing UK and ALPSP (Association of Learned and Professional Society Publisher - full membership). Presented in the Master List of Thomson ISI.

2009
Volume 12
Issue 4

Topic:

Economics

ELECTRONIC
JOURNAL OF
POLISH
AGRICULTURAL
UNIVERSITIES

Kisielińska J. 2009. TIME SERIES MODELING WITH SEASONALITY OF NONLINEARLY CHANGEABLE AMPLITUDE ON AN EXAMPLE OF INFLATION, EJPAU 12(4), #13.
Available Online: http://www.ejpau.media.pl/volume12/issue4/abs-13.html

TIME SERIES MODELING WITH SEASONALITY OF NONLINEARLY CHANGEABLE AMPLITUDE ON AN EXAMPLE OF INFLATION

Joanna Kisielińska
Department of Agricultural Economics and International Economic Relations, Warsaw Agricultural University, Poland

ABSTRACT

The paper covers modeling of processes characterized
by fluctuations. In the theory of forecasting two kinds of models are used: additive
and multiplicative models. The generalization about them is the additive model
with nonlinearly changeable amplitude of fluctuations according to any nonlinear
time function. If there is the inverse function towards the one amplitude's modeling,
dependence on time can be exchanged with dependence on the trend. If there is
assumption of constant amplitude, the presented model leads to the simple additive
model. Assumption of amplitude directly proportional to the trend leads to the
multiplicative model. The model was verified on an example of inflation
in Poland. The model with nonlinearly changeable amplitude of fluctuations resulted
in smaller errors than the ordinary multiplicative model and the multiplicative
models, where seasonality was distinguished with use of centered 12-month moving
average and Cenzus Method II X-11.

Key words: inflation forecasting, seasonality, additive and multiplicative models, amplitude of fluctuations.

Joanna Kisielińska
Department of Agricultural Economics and International Economic Relations,
Warsaw Agricultural University, Poland
166 Nowoursynowska Street, 02-787 Warsaw, Poland
email: joanna_kisielinska@sggw.pl

Responses to this article, comments are invited and should be submitted within three months of the publication of the article. If accepted for publication, they will be published in the chapter headed 'Discussions' and hyperlinked to the article.