The Global Diffusion of Ideas

Abstract

We provide a tractable, quantitatively-oriented theory of innovation and technology diffusion to explore the role of international trade in the process of development. We model innovation and diffusion as a process involving the combination of new ideas with insights from other industries or countries. We provide conditions under which each country's equilibrium frontier of knowledge converges to a Fréchet distribution, and derive a system of differential equations describing the evolution of the scale parameters of these distributions, that is, countries' stocks of knowledge. The model remains tractable with many asymmetric countries and generates a rich set of predictions about how the level and composition of trade affect countries' frontiers of knowledge. We use the framework to quantify the contribution of bilateral trade costs to long-run changes in TFP and individual post-war growth miracles. For our preferred calibration, we find that both gains from trade and the fraction of variation of TFP growth accounted for by changes in trade more than double relative to a model without diffusion. ECONOMIC MIRACLES are characterized by protracted growth of per-capita income and productivity as well as increases in trade flows. The experiences of South Korea in the postwar period and the recent performance of China are prominent examples. These experiences suggest an important role played by openness in the process of development. 1Yet quantitative trade models relying on standard static mechanisms imply relatively small gains from openness and, therefore, cannot account for growth miracles. 2 These findings call for alternative channels through which openness can affect development. In this paper, we present and analyze a tractable, quantitatively-oriented model of an alternative suggested a strong relationship between openness and growth, although Rodriguez and Rodrik (2001) subsequently argued that many estimates in the literature suffered from econometric issues including omitted variables, endogeneity, and lack of robustness. More recent contributions to the literature have developed strategies to overcome some of these issues. To estimate the impact of trade on growth, Feyrer (2009a,b) studied the natural experiments of the decade-long closing of the Suez Canal in the 1970s and the long run decline in the cost of shipping goods by air, each of which had larger impacts on some pairs of countries than others, and Pascali (2017) studied the introduction of the steamship which affected some trade routes more than others. See also Lucas (2009b) and Wacziarg and Welch (2008), and Donaldson (2015) for reviews of the literature.2 See Connolly and Yi (2015) for a quantification of the role of trade on Korean's growth miracle. Atkeson and Burstein (2010) also found relatively small effects in a model with innovation.

Does an Imitation Strategy Promote Long-Term Firm Growth in a Dynamic Environment? A Meta-Analysis

“…From the perspective of the contingency theory, this result echoes the view by Hall et al (1968) , proposing that firm growth is greatly influenced by other conditions such as the industry environment and organizational processes within the firm. Meanwhile, this result is also consistent with research by Perla and Tonetti (2014) , König et al (2016) , and Buera and Oberfield (2020) stating that the technical complexity of a particular industry will affect the implementation process of an imitation strategy. A further new insight put forward by Baslandze et al (2021) , which is in line with this result, refers to the heterogeneous effects of knowledge spillovers on firms with an imitation strategy in industries with different technological complexity.…”

“…As a form of organizational learning ( Yang and Hyland, 2006 ), imitation also needs to be examined within the external dynamic environment to account for adaptation of the firm during the different growth stages ( Teece et al, 1997 ). These external factors influencing the implementation process of an imitation strategy are industry conditions ( Perla and Tonetti, 2014 ; Buera and Oberfield, 2020 ; Baslandze et al, 2021 ), the specifics of the countries under investigation ( Williamson and Cable, 2003 ; Zheng Zhou, 2006 ; Lee and Zhou, 2012 ), and the time horizon of firm performance ( Kim and Nelson, 2000 ; Moon and Acquaah, 2020 ). However, little work has been done to study the effectiveness of an imitation strategy by focusing on these factors.…”

Youth Awareness and Expectations about GMOs and Nuclear Power Technologies within the North American Free Trade Bloc: A Retrospective Cross-Country Comparative Analysis

“…Very little is known about cross-country differences and convergence in individuals' awareness and expectations about specific technological artifacts within integrated economies. Since convergence between integrated economies relies heavily on the diffusion of technology [13,14], knowledge [15], and increased volume of trade [16], convergence in technological awareness and expectations should be an important precondition for actual technological and economic convergence.…”

“…Therefore, technological innovation and diffusion are concerned with "potential users making decisions to adopt or reject an innovation based on beliefs that they form about the innovation" ( [18], p. 90). As such, changes in individual perceptions and attitudes (perhaps from new information/ideas [15]) are the root causes of technological innovation and diffusion at both the micro and macro levels [19]. Indeed, in the field of psychology, where applying the theory of information integration to attitudes and social judgments, [20] reported that "Integration theory has had reasonable success in the areas of learning, perception, judgment, decision-making, and personality impressions, as well as attitude change".…”

Colossal Brownian yet non-Gaussian diffusion induced by nonequilibrium noise

“…Brownian diffusion is in the limelight of present activities and enjoys seemingly never-ending interest [1][2][3][4][5][6][7][8][9][10] across a broad spectrum of scientific disciplines, extending even into socio-economics where diffusion of ideas and innovations has been considered recently [11,12]. It presents an archetype stochastic processes which is characterized by two fundamental features.…”