Innovative Learning and Institutions in the Process of Development: On the Microfoundation of Growth Regimes

Abstract

In his recent assessment of growth theories, Moses Abramovitz refers back to the Wealth of Nations as the illustrious ancestor of a long stream of investigations on the determinants of economic growth (Abramovitz, 1989). In fact, in the famous proposition on the dynamics linking division of labour, productivity and market growth, Adam Smith identifies one of many positive feedback loops between innovative learning and economic development. Since then, the evidence on the microeconomics of learning and innovation has got much richer, especially in recent years (a survey in Dosi, 1988). However, standard growth theory has proved to be hardly suitable to incorporate the microevidence on, for example, dynamic increasing returns, path dependent learning, ‘disequilibrium’ search processes, interfirm and international differences in technological capabilities and so on, notwithstanding recent increasing returns equilibrium models (see Romer, 1986, 1990; Lucas, 1988; Aghion and Howitt, 1989; Grossman and Helpman, 1991). Neither has standard theory focused on the institutions and behavioural norms underlying economic coordination and development: that is, what are the institutional mechanisms that allow the ‘Invisible Hand’ to operate in a world that continuosly innovates? Again, that question can be traced back to Adam Smith, where he asks — in the Wealth of Nations and, especially, in the Theory of Moral Sentiments — what are the ‘moral inclinations’, beliefs and behaviours that make non-destructive interactions possible in market societies. However, since Adam Smith, attempts at an answer have mainly been left to disciplines other than economics. In that, the typical economic assumptions of ‘perfect rationality’ and equilibrium have often hindered any proper account of the sociology and ‘political economy’ of development.KeywordsMarket ShareDecision RuleLabour ProductivityTechnical ChangeTechnological LearningThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.