Data processing growth model

Abstract

This paper develops a growth model in which new ideas result from people processing data. By distinguishing between ideas and data, the model provides a transparent framework for studying how information technology affects economic growth. Information technology is decomposed into three components: data processing, data generation, and data retention. The model has two candidate balanced growth path regimes of per-capita output: (i) a path in which the long-run growth rate is governed by data-processing capacity, while changes in data generation and retention affect levels but not the growth rate; (ii) a path in which long-run growth is jointly determined by data-processing and data-retention capacities. Which balanced growth path the economy obtains depends on the strength of data-processing capacity. The central insight is that improvements in data generation or retention primarily expand data stocks and have limited implications for long-run growth unless accompanied by improvements in data-processing capacity.