Aggregate Implications of Innovation Policy

Atkeson, Andrew; Burstein, Ariel

doi:10.21034/sr.459

Cited by 20 publications

(26 citation statements)

References 6 publications

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“…One would be to look at missing growth in countries other than the U.S. A second extension would be to revisit optimal innovation policy. Based on Atkeson and Burstein (2015), the optimal subsidy to R&D may be bigger if true growth is higher than measured growth. Conversely, our estimates give a more prominent role to creative destruction with its attendant business stealing.…”

Section: Resultsmentioning

confidence: 99%

Missing Growth from Creative Destruction

et al. 2017

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Section: Resultsmentioning

confidence: 99%

Missing Growth from Creative Destruction

et al. 2017

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“…As the frontier of knowledge improves, ideas must arrive more quickly in order to maintain a constant rate of growth. This feature—shared with the semiendogenous growth models of Jones (), Kortum (), and Atkeson and Burstein ()—implies that the economy's growth rate depends on the growth of the arrival of ideas and that an increase in the arrival rate of ideas leads to level effects rather than growth effects. The evolution of the detrended stock of knowledge

{\overset{λ}{true}}_{t} = λ_{t} e^{- γ false/ false(1 - β false) t}

can be summarized in terms of the detrended arrival of ideas

{\overset{α}{true}}_{t} = α_{t} e^{- γ t}

{\dot{\overset{λ}{true}}}_{t} = {\hat{α}}_{t} Γ (1 - β) {\hat{λ}}_{t}^{β} - \frac{true γ}{true 1 - β} {\hat{λ}}_{t},

and on a balanced growth path on which

\overset{α}{true}

is constant, the detrended stock of knowledge is

\hat{λ} = {[\frac{true \overset{α}{true} false(1 - β false)}{true γ} Γ (1 - β)]}^{\frac{1}{1 - β}} .

…”

Section: Idea Diffusion With a General Source Distributionmentioning

confidence: 96%

“… Jones (), and more recently, Atkeson and Burstein () featured analogous parameters that index the degree of intertemporal spillovers in innovation. Because those models do not model the spillovers explicitly, the composition of insights is irrelevant and the parameter plays only the second role.…”

mentioning

confidence: 99%

The Global Diffusion of Ideas

Buera

Oberfield

2020

ECTA

116

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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.

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“… In the previous work, the implied share of R&D in GDP can be as high as

15 normal%

and

16 normal%

(Atkeson and Burstein () and Bilbiie, Ghironi, and Melitz (), resp. ), or as low as

1 normal%

in Comin and Gertler ().…”

mentioning

confidence: 89%

Financial frictions, trends, and the great recession

Guerrón‐Quintana¹,

Jinnai

2019

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We study the causes behind the shift in the level of U.S. GDP following the Great Recession. To this end, we propose a model featuring endogenous productivity à la Romer and a financial friction à la Kiyotaki-Moore. Adverse financial disturbances during the recession and the lack of strong tailwinds post-crisis resulted in a severe contraction and the downward shift in the economy's trend. Had financial conditions remained stable during the crisis, the economy would have grown at its average growth rate. From a historical perspective, the Great Recession was unique because of the size and persistence of adverse shocks, and the lackluster performance of favorable shocks since 2010. for valuable discussions and seminar participants at several institutions and conferences for comments. Ryo Jinnai gratefully acknowledges the support by JSPS KAKENHI grants (16K17080, 16H03626, and 17H00985) as well as the Hitotsubashi Institute for Advanced Study (HIAS).1 More formally, the shift in the GDP trend is detected by the flexible estimation of trends with regime shifts recently advanced by Eo and Kim (2012). We thank Yunjong Eo for helping with the estimation using their approach. 2 The forecast is built assuming that the economy will be growing at the average growth rate for the period 2009.Q2-2015.Q1.

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Aggregate Implications of Innovation Policy

Cited by 20 publications

References 6 publications

Missing Growth from Creative Destruction

Missing Growth from Creative Destruction

The Global Diffusion of Ideas

Financial frictions, trends, and the great recession

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