• Title/Summary/Keyword: Leads and Lags Correlation

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A Study on Forecasting Industrial Land Considering Leading Economic Variable Using ARIMA-X (선행경제변수를 고려한 산업용지 수요예측 방법 연구)

  • Byun, Tae-Geun;Jang, Cheol-Soon;Kim, Seok-Yun;Choi, Sung-Hwan;Lee, Sang-Ho
    • The Journal of the Korea Contents Association
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    • v.22 no.1
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    • pp.214-223
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    • 2022
  • The purpose of this study is to present a new industrial land demand prediction method that can consider external economic factors. The analysis model used ARIMA-X, which can consider exogenous variables. Exogenous variables are composed of macroeconomic variable, Business Survey Index, and Composite Economic Index variables to reflect the economic and industrial structure. And, among the exogenous variables, only variables that precede the supply of industrial land are used for prediction. Variables with precedence in the supply of industrial land were found to be import, private and government consumption expenditure, total capital formation, economic sentiment index, producer's shipment index, machinery for domestic demand and composite leading index. As a result of estimating the ARIMA-X model using these variables, the ARIMA-X(1,1,0) model including only the import was found to be statistically significant. The industrial land demand forecast predicted the industrial land from 2021 to 2030 by reflecting the scenario of change in import. As a result, the future demand for industrial land was predicted to increase by 1.91% annually to 1,030.79 km2. As a result of comparing these results with the existing exponential smoothing method, the results of this study were found to be more suitable than the existing models. It is expected to b available as a new industrial land forecasting model.