When times are good, there is less political pressure at the local level anywhere to be economically efficient or carefully scrutinize predictions that a new public works project or expensive industrial or tourism promotion scheme will lead to prosperity in 20 or 30 years.
But with their rapidly aging and declining populations and shrinking tax bases, local governments now face a daunting task in formulating political, economic, social and environmental policies that will most likely benefit the greatest number of people decades from now. In contrast to the carefree public works spending of the bubble economy of three decades ago, often based on proposals that seemed little thought out, the demand for data-driven, evidence-based projections for various policy measures among local governments has grown, lest a wrong decision lead to local economic disaster, and voter anger.
Earlier this year, Nagano Prefecture announced it would rely more on computer modeling and scenarios for local policy decisions. The decision came after the prefecture cooperated with Kyoto University's Kokoro Research Center, Hitachi Ltd. and Mitsubishi UFJ Research and Consulting to create two different models using artificial intelligence. Those were put to use in research on the best policy to realize a sustainable society and how to best take advantage of the opportunities, especially related to local tourism, that might come from the planned opening of a maglev shinkansen station in the prefecture as early as 2027.