Total Factor Productivity in East Asia Under Ambiguity

Velma Chen, Ariel M. Viale*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageAmerican English
Article number106232
JournalEconomic Modelling
Volume121
Early online dateFeb 10 2023
DOIs
StatePublished - Feb 17 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2023 Elsevier B.V.

ASJC Scopus Subject Areas

  • Economics and Econometrics

Keywords

  • Ambiguity
  • Connectedness
  • East Asia
  • Panel data analysis
  • Total factor productivity

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