 Total factor productivity in East Asia under ambiguityVelma Lee and Ariel Viale Economic Modelling, 2023, vol. 121, issue C Abstract: Most cross-country empirical studies on economic growth ignore ambiguity. We argue that ambiguity should matter a priori, given the open-endedness of growth theories. Moreover, ambiguity has received a lot of attention since the great financial crisis (GFC) of 2008, and more recently after COVID-19 and the war in East Europe. Using annual data from the Penn World Table covering 12 East Asian economies from 1954 to 2019, we show that beyond economic factors documented in the current debate about the East Asian miracle, economic agents' confidence shocks about the global economy (one dimension of ambiguity) have a significant negative impact on total factor productivity (TFP) growth. However, correlation uncertainty (another dimension of ambiguity) is low in the region given the persistent high level of connectedness of its productivity network. The empirical results are policy-relevant given that ambiguity, unlike rational expectations, implies that economic agents’ beliefs are not policy invariant. Keywords: Total factor productivity; Ambiguity; East Asia; Panel data analysis; Connectedness (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:121:y:2023:i:c:s0264999323000445 DOI: 10.1016/j.econmod.2023.106232 Access Statistics for this article Economic Modelling is currently edited by S. Hall and P. Pauly More articles in Economic Modelling from Elsevier |
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