This chapter investigates the dynamic associations between borrowed size (BS) and regional productivity by applying the Hicks-Moorsteen-Bjurek Productivity Index (HMB-PI) to a panel dataset of Japanese prefectures across manufacturing and nonmanufacturing industries. The HMB-PI framework decomposes total factor productivity change into four components: technical change (TC), efficiency change (EC), scale change (SC), and mix change (MC). Empirical results show that in the manufacturing sector, BS is statistically and positively associated with TC, SC, and MC, highlighting the role of urban proximity in driving innovation, optimal scale, and input restructuring. In contrast, for the nonmanufacturing sector, BS is statistically associated only with SC, which implies that urban externalities influence scale adjustment primarily through market thickness rather than internal efficiency or innovation. This sectoral asymmetry underscores the multifaceted and selective nature of BS. Comparisons with the static DEA results in Chap. 6 further indicate that BS is statistically associated with the level of efficiency but not with its improvement over time, suggesting a structural divergence between static performance and dynamic trajectories. This chapter replicates and extends the analytical framework of Goto et al. (Regional Studies 52(11): 1537–1547, 2018) with a focus on BS, applying updated interpretation and additional contextual analysis. In doing so, it contributes to understanding BS as a dynamic and context-dependent phenomenon and offers nuanced insights into how urban proximity shapes productivity across sectors and components.