Forecasting of a Hierarchical Functional Time Series on Example of Macromodel for the Day and Night Air Pollution in Silesia Region - A Critical Overview

• Autorzy: Daniel Kosiorowski , Dominik Mielczarek , Jerzy P. Rydlewski
• Języki publikacji: EN

Abstrakty

EN

In economics we often face a system which intrinsically imposes a structure of hierarchy of its components, i.e., in modeling trade accounts related to foreign exchange or in optimization of regional air protection policy. A problem of reconciliation of forecasts obtained on different levels of hierarchy has been addressed in the statistical and econometric literature many times and concerns bringing together forecasts obtained independently at different levels of hierarchy. This paper deals with this issue with regard to a hierarchical functional time series. We present and critically discuss a state of art and indicate opportunities of an application of these methods to a certain environment protection problem. We critically compare the best predictor known from the literature with our own original proposal. Within the paper we study a macromodel describing the day and night air pollution in Silesia region divided into five subregions. (original abstract)

Słowa kluczowe

EN

Hierarchical classification methods; Functional data analysis; Air pollution

PL

Hierarchiczne metody klasyfikacyjne; Analiza danych funkcjonalnych; Zanieczyszczenie powietrza

• Czasopismo: Central European Journal of Economic Modelling and Econometrics (CEJEME)
• Rocznik: 2018
• Tom: 10
• Numer: nr 1
• Strony: 53--73

Twórcy

autor

Daniel Kosiorowski

• Cracow University of Economics, Poland

autor

Dominik Mielczarek

• AGH University of Science and Technology Kraków, Poland

autor

Jerzy P. Rydlewski

• AGH University of Science and Technology Kraków, Poland

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