GPT‐Driven, Endogenous Growth

Abstract

Seven years after Helpman’s (1998) book on general purpose technologies (GPTs), there is a dearth of subsequent models. Early models employed technically complex dynamic optimising techniques which limited further development. We present a model in which sustained growth is driven by a succession of GPTs that is technically simpler than the early models yet captures stylised facts that were omitted from them. Ours has diminishing returns to inputs, and endogenous, incremental technological changes from R&D, interrupted by the occasional introduction of new GPTs. GPTs are themselves developed endogenously with payoffs that are subject to uncertainty in magnitude and timing.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 53 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.