Global Persistence, Local Residual Structure: Forecasting Heterogeneous Investment Panels

On a 93-actor quarterly panel mixing macro indicators, institutional data, and firm-level investment ratios, global factor augmentation degrades prediction for actor subgroups whose dynamics are misrepresented by the shared basis. A two-stage architecture – global pooled AR(1) for shared persistence, block-specific local models for residual dynamics – improves full-panel out-of-sample $R^2$ from 0.630 to 0.677 ($\mathrm{\Delta }=+0.047$, CI $[+0.036,+0.058]$, 10/10 windows, placebo $p\le 0.001$). A held-out decade test (block partition frozen on 2005–2014 data, evaluated on unseen 2015–2024 windows) confirms the gain ($\mathrm{\Delta }=+0.050$, 10/10), and a stratified placebo that fixes the macro/firm data-type split and permutes only firm-sector assignments corroborates ($z=7.25$, $p\le 0.001$). Cross-regime replication on a 109-actor UK/EU heterogeneous panel ($\mathrm{\Delta }=+0.017$, 8/8 windows) and a combined US + UK/EU panel of 202 actors ($\mathrm{\Delta }=+0.030$, placebo $z=9.68$ – exceeding the original US-only $z=7.82$) confirms the architecture transfers across regimes. A 146-firm CapEx/Assets robustness check refines the scope condition: the gain depends on cross-sectional dispersion in autoregressive structure, which data-type heterogeneity reliably produces but which is also present in firm-only panels under suitable ratio choices.