EURO 2024 Copenhagen
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1624. Forecasting regional GDP using cointegration with business cycle indicators

Invited abstract in session TA-31: Analytics and the link with stochastic dynamics I, stream Analytics.

Tuesday, 8:30-10:00
Room: 046 (building: 208)

Authors (first author is the speaker)

1. Nariyasu Yamasawa
Faculty of Management, Atomi University

Abstract

In Japan's local governments, the shortage of personnel has made it difficult to compile statistics. While regional Gross Domestic Product (GDP) is released promptly in countries like the United States and the United Kingdom, in Japan, there is a lag of about two years before annual figures are published. Several prefectures used to release preliminary figures for regional GDP on a quarterly basis, but their number has gradually decreased, and currently, only three prefectures do so. Many local governments are creating business cycle indices similar to the OECD's Composite Leading Indicator (CLI) to survey the current state of the economy. However, business cycle indices do not reveal the level of economic activity, nor do they easily allow for comparisons between different prefectures.
in this study, a method to create regional GDP from business cycle indices was explored. It is assumed that there is a long-term stable relationship (cointegration) between the economic business cycle, which represent the cycle of the economy, and regional GDP, which represents the overall movement of the region. By constructing an Autoregressive Distributed Lag (ARDL) model and initially applying it to the country as a whole, a long-term relationship was confirmed. By applying this relationship to the Gross Regional Product (GRP) of each prefecture, a method to estimate regional GDP was devised.

Keywords

Status: accepted

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