Resource reallocation and zombie lending in Japan in the 1990s

Kwon, Hyeog Ug; Narita, Futoshi; Narita, Machiko

doi:10.1016/j.red.2015.07.001

Cited by 99 publications

(66 citation statements)

References 35 publications

(53 reference statements)

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“…These rigidities make the ©International Monetary Fund. Not for Redistribution bust more costly-especially if banks evergreen bad loans (Caballero, Hoshi, and Kashyap 2008;Kwon, Narita, and Narita 2015). A longer and bigger boom makes the necessary adjustment more painful.…”

Section: B Sectoral Activity During Good and Bad Boomsmentioning

confidence: 99%

“…The earlier literature has emphasized collateral effects that amplify shocks, strategic decisions creating excessive leverage or risk taking because of externalities, limited liability and/or competitive pressures, capacity constraints, or behavioral biases(Kiyotaki and Moore 1997;Brunnermeier and Sannikov 2014;Lorenzoni 2008;Dell'Ariccia and Marquez 2006;Bordalo, Gennaioli, and Shleifer 2018).4 Technically, misallocation depends on marginal products of inputs, which are not necessarily lower in low-TFP-growth sectors(Nishida, Petrin, and Polanec 2014;Kwon, Narita, and Narita 2015). If, say, the marginal product of labor is higher in construction, employment growth in this sector would not represent misallocation of labor.©International Monetary Fund.…”

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confidence: 99%

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Discerning Good from Bad Credit Booms

Dell’Ariccia¹,

Ebrahimy²,

Chen³

et al. 2020

Staff Discussion Notes

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Credit booms are a focal point for policymakers and scholars of financial crises. Yet our understanding of how the real sector behaves during booms, and why some booms may go bad, is limited. Despite a large and growing body of literature, most of the work has focused on aggregate economic activity, and relatively little is known about which industries benefit and which suffer during these episodes. This note aims to fill this gap by analyzing disaggregated output and employment data in a large sample of advanced and emerging market economies between 1970 and 2014.

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Section: B Sectoral Activity During Good and Bad Boomsmentioning

confidence: 99%

mentioning

confidence: 99%

Discerning Good from Bad Credit Booms

Dell’Ariccia¹,

Ebrahimy²,

Chen³

et al. 2020

Staff Discussion Notes

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show abstract

“…In 2008, only 11.5% of SMEs had received "pure credit" loans, although this is more than in 2005 (Table 5). Second, generous government support delays restructuring by keeping non-viable enterprises (socalled "zombie" firms) afloat (Caballero et al, 2008 andKwon et al, 2009). Such support distorts resource allocation and limits access to finance by viable companies, thereby reducing Japan's potential growth.…”

Section: Problems Associated With Government Intervention In Sme Finamentioning

confidence: 99%

Enhancing Dynamism and Innovation in Japan's Business Sector

Jones

Kim

2015

OECD Economics Department Working Papers

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“…Besides, in industries where zombie firms prevailed, market shares of inefficient firms were sustained largely due to bank financial support (Ahearne and Shinada, 2005). Model simulations, calibrated on Japanese data, suggest that ever-greening practices may have reduced cumulative aggregate productivity growth in the 1989-99 periods by 1.6 percentage points (Kwon et al, 2009).…”

Section: Box 2 Ever-greening In Japan In the 1990smentioning

confidence: 99%

The Benefits and Costs of Highly Expansionary Monetary Policy

Rawdanowicz

Bouis

Watanabe

2013

OECD Economics Department Working Papers

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JT03343556Complete document available on OLIS in its original format This document and any map included herein are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. ECO/WKP(2013) ABSTRACT/RÉSUMÉThe benefits and costs of highly expansionary monetary policy How far to go -and to remain -in the direction of highly expansionary monetary policy hinges on the balance of marginal benefits and costs of additional monetary easing and its expected evolution over time. This paper sketches a framework for assessing this balance and applies it to four OECD economic areas: the euro area, Japan, the United Kingdom and the United States. The effectiveness of further stimulus via quantitative easing or forward guidance in affecting asset prices, interest rates and credit flows will depend on the state of the economy and the functioning of financial markets. Marginal costs could rise due to excessive risk-taking; higher inflation expectations; higher likelihood of ever-greening; and higher risks of financial instability in the exit phase, especially when exit from monetary accommodation is close in time and signs of negative effects are already apparent. The balance of marginal benefits and costs is found to be different across the main OECD areas. In the United States, the case for additional stimulus is weakening, while the opposite is true for the euro area and Japan. In the United Kingdom, the assessment is less clear cut.JEL classification codes: E31; E43; E44; E5; F31; F32; G12; G21

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Resource reallocation and zombie lending in Japan in the 1990s

Cited by 99 publications

References 35 publications

Discerning Good from Bad Credit Booms

Discerning Good from Bad Credit Booms

Enhancing Dynamism and Innovation in Japan's Business Sector

The Benefits and Costs of Highly Expansionary Monetary Policy

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