2020
DOI: 10.2139/ssrn.3573994
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Credit Supply Driven Boom-Bust Cycles

Abstract: BIS Working Papers are written by members of the Monetary and Economic Department of the Bank for International Settlements, and from time to time by other economists, and are published by the Bank. The papers are on subjects of topical interest and are technical in character. The views expressed in them are those of their authors and not necessarily the views of the BIS. This publication is available on the BIS website (www.bis.org).

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Cited by 3 publications
(3 citation statements)
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References 92 publications
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“…Eight variables were used in the empirical analysis. These eight variables have been used in previous studies such as Owusu (2012), Balke (2000), Gilchrist and Zakrajšek (2012), Arslan et al (2021), Popov and Rocholl (2018). The dependent variable is GDP per capita (CGDP).…”
Section: Datamentioning
confidence: 99%
“…Eight variables were used in the empirical analysis. These eight variables have been used in previous studies such as Owusu (2012), Balke (2000), Gilchrist and Zakrajšek (2012), Arslan et al (2021), Popov and Rocholl (2018). The dependent variable is GDP per capita (CGDP).…”
Section: Datamentioning
confidence: 99%
“…Mian and Sufi (2019) also confirm that the credit supply conditions play a crucial role in speculative booms and busts in asset prices, which include house prices. Arslan et al (2020) present the importance of the credit supply channel during the booms, because of the higher leverage opportunities of the banking sector. The evidence suggests that the deterioration of banks´ balance sheets during a bust leads to the higher amplification of that bust.…”
Section: Literature Reviewmentioning
confidence: 99%
“…The pioneers in this area, Mian and Sufi (2014), have used regional variation to identify how the weakening of household balance sheets precipitated by the house price decline contributed to the downturn. 9 Others have focused on banks. For example, Chodorow-Reich (2014) exploits variation in bank financial health to identify how disruption in banking affected employment.…”
Section: Digging Deeper: Evidence From State Datamentioning
confidence: 99%