Prediction of the Prefectural Economy in Japan Using a Stochastic Model
No 2013-02, AGI Working Paper Series from Asian Growth Research Institute
This study develops a simple forecasting model using Japanese prefectural data. The Markov chain, known as a stochastic model, corresponds to a first-order vector auto-regressive (VAR) model. If the transition probability matrix can be appropriately estimated, a forecasting model using the Markov chain can be constructed. This study introduces a methodology for estimating the transition probability matrix of the Markov chain using least-squares optimization. The model is used first to analyze economy-wide changes encompassing all Japanese prefectures up to 2020. Second, a shock emanating from one prefecture is inserted into the transition probability matrix to investigate its influence on the other prefectures. Finally, a Monte Carlo experiment is conducted to refine the model's predicted outcomes. Although this study's model is simple, we provide more sophisticated forecasting information for prefectural economies in Japan.
Keywords: Prefectural economy; Japan; Stochastic model; Markov chain (search for similar items in EconPapers)
JEL-codes: C15 C53 C61 O53 R12 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:agi:wpaper:00000069
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