GPT‐Driven, Endogenous Growth
构建了一个比早期模型更简单的增长模型，其中持续增长由一系列通用目的技术（GPT）驱动，包含研发带来的内生增量技术进步和新GPT的偶然引入，且GPT的研发回报在大小和时间上具有不确定性。
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. Copyright 2006 Royal Economic Society.