Evaluating the effectiveness of social policies and business strategies through rigorous scientific methods—and improving them based on empirical evidence—is a pressing challenge across the public sector, private enterprises, and local communities. In Japan, the promotion of Evidence-Based Policy Making (EBPM) has recently gained attention; however, its practice remains largely confined to traditional administrative data, while the diverse and rich resources held by corporations and local communities remain underutilized. Building mechanisms that enable collaboration among public, private, and academic sectors is essential for sharing knowledge that contributes to solving societal challenges.

This research employs econometric methodologies to assess the causal impacts of policies and programs implemented by governments and corporations, linking the findings to real-world applications. By integrating administrative records with diverse private-sector data—including consumption, labor, education, and health—this study seeks to generate robust evidence and contribute to the advancement of evidence-based policy and strategy formulation.

Conventional policy evaluations and social surveys have often relied on descriptive statistics and case studies, which have limited capacity to identify generalizable causal relationships. Likewise, corporate initiatives have only rarely been subject to systematic and rigorous impact evaluation. This research employs econometric causal inference methods—such as regression discontinuity design, instrumental variables, and event studies—and applies them to both large-scale administrative data and non-traditional (“alternative”) data. Compared with conventional correlation-based analyses, this approach enables more robust and practically relevant evaluations of causal effects.

Diverse Data Integration: Integrates administrative, corporate, and community data—regardless of type or continuity—to comprehensively evaluate policy and program impacts.
Rigorous Causal Inference: Applies advanced econometric methods, such as regression discontinuity design and instrumental variables, to provide evidence that goes beyond simple correlations.
Cross-Sectoral Applicability: Offers applicability across education, labor, welfare, urban policy, and consumer behavior.
Social Implementation: Directly links research outcomes to policy improvement and corporate strategy design, fostering implementation through industry–government–academia collaboration.
Capacity Building: Provides training in statistics and econometrics for municipal officials and corporate analysts, helping them build sustainable, data-driven decision-making cycles.

Public Sector: Provides scientific evidence for addressing educational inequality, designing welfare systems, labor market interventions, and urban environmental policies, thereby supporting the effective allocation of public resources.
Private Sector: Evaluates employee welfare programs, health management, workplace reforms, and reskilling initiatives, offering insights for sustainable and competitive strategic planning.
Society as a Whole: Builds sustainable and efficient social systems by integrating data and knowledge across governments, firms, and academic institutions.

• Economics
• Social Sciences
• Causal Inference
• Evidence-Based Policy Making
• EBPM
• Data Science
• Econometrics
• Policy Evaluation
• Social Implementation
• Big Data
• Alternative Data