AI-Driven Spatial Distribution Dynamics: A Comprehensive Theoretical and Empirical Framework for Analyzing Productivity Agglomeration Effects in Japan's Aging Society

TL;DR

This paper presents a comprehensive theoretical and empirical framework for analyzing how AI influences spatial distribution and productivity in aging metropolitan areas, with a focus on Japan's Tokyo.

Contribution

It introduces five novel AI-specific mechanisms into New Economic Geography and applies rigorous causal analysis and machine learning to predict future spatial and productivity changes.

Findings

AI implementation increases agglomeration by 4.2-5.2 percentage points.

High AI-readiness sectors see 8.4 percentage point increases.

Aggressive AI adoption can offset 60-80% of aging-related productivity declines.

Abstract

This paper develops the first comprehensive theoretical and empirical framework for analyzing AI-driven spatial distribution dynamics in metropolitan areas undergoing demographic transition. We extend New Economic Geography by formalizing five novel AI-specific mechanisms: algorithmic learning spillovers, digital infrastructure returns, virtual agglomeration effects, AI-human complementarity, and network externalities. Using Tokyo as our empirical laboratory, we implement rigorous causal identification through five complementary econometric strategies and develop machine learning predictions across 27 future scenarios spanning 2024-2050. Our theoretical framework generates six testable hypotheses, all receiving strong empirical support. The causal analysis reveals that AI implementation increases agglomeration concentration by 4.2-5.2 percentage points, with heterogeneous effects across industries: high AI-readiness sectors experience 8.4 percentage point increases, while low AI-readiness sectors show 1.2 percentage point gains. Machine learning predictions demonstrate that aggressive AI adoption can offset 60-80\% of aging-related productivity declines. We provide a strategic three-phase policy framework for managing AI-driven spatial transformation while promoting inclusive development. The integrated approach establishes a new paradigm for analyzing technology-driven spatial change with global applications for aging societies.