Abstract
Can inflation anchoring foster growth? To answer this question, we use panel data on sectoral growth for 22 manufacturing industries from 39 advanced and emerging market economies over 1990–2014 and employ a difference-in-differences strategy based on the theoretical prediction that higher inflation uncertainty particularly depresses investment in industries that are more credit constrained. Industries characterized by high external financial dependence, liquidity needs, and R&D intensity, and low asset tangibility, tend to grow faster in countries with well-anchored inflation expectations. The results, based on an IV approach—using indicators of monetary policy transparency and central bank independence as instruments—confirm our findings.
Original language | English |
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Article number | 104279 |
Journal | Journal of Economic Dynamics and Control |
Volume | 134 |
DOIs | |
Publication status | Published - 2022 Jan |
Bibliographical note
Funding Information:Comments from the editor and two anonymous referees substantially improved the paper. We are also grateful to Noh-Sun Kwark (discussant), Nick Bloom, Sinem Kilic Celik, Yuriy Gorodnichenko, Joon-Ho Hahm, Raja Junankar, Jun Il Kim, Ksenia Koloskova, Keith Kuester, Jae Won Lee, Grace Bin Li, Marc Schiffbauer, Chansik Yoon, Bok-Keun Yu, Carlos Vegh, Guillermo Vuletin, Tim Willems, and the seminar participants at the Bank of Korea and the Korea Money and Finance Association Annual International Conference for their feedback. Jeeyeon Phi, Junhyeok Shin, and Seung Yong Yoo provided excellent research assistance. This paper was supported in part through a research project on macroeconomic policy in low-income countries with the U.K.’s Department for International Development (DFID). This research was (in part) supported by the Yonsei Signature Research Cluster Program of 2021 (2021–22–0011). The views expressed in this paper are those of the authors and should not be reported as representing the views of the IMF or DFID. Any remaining errors are the authors’ sole responsibility.
Publisher Copyright:
© 2021 Elsevier B.V.
All Science Journal Classification (ASJC) codes
- Economics and Econometrics
- Control and Optimization
- Applied Mathematics