2013
DOI: 10.2139/ssrn.2370460
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Has Weak Lending and Activity in the United Kingdom Been Driven by Credit Supply Shocks?

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Cited by 38 publications
(42 citation statements)
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“…More specifically, we check whether the impulse responses satisfy our sign restrictions. Sign restrictions on impulse responses have been frequently used in the literature to identify VAR structural shocks (Faust, 1998;Uhlig, 2005) and, in particular, credit supply shocks (Busch et al, 2010;De Nicol o and Lucchetta, 2011;Eickmeier and Ng, 2011;Gambetti and Musso, 2012;Hristov et al, 2012;Barnett and Thomas, 2013;Houssa et al, 2013). As shown by Paustian (2007), sign restrictions can be a useful tool for recovering structural shocks from VAR residuals as long as the imposed restrictions are sufficiently numerous.…”
Section: The Identification Strategymentioning
confidence: 99%
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“…More specifically, we check whether the impulse responses satisfy our sign restrictions. Sign restrictions on impulse responses have been frequently used in the literature to identify VAR structural shocks (Faust, 1998;Uhlig, 2005) and, in particular, credit supply shocks (Busch et al, 2010;De Nicol o and Lucchetta, 2011;Eickmeier and Ng, 2011;Gambetti and Musso, 2012;Hristov et al, 2012;Barnett and Thomas, 2013;Houssa et al, 2013). As shown by Paustian (2007), sign restrictions can be a useful tool for recovering structural shocks from VAR residuals as long as the imposed restrictions are sufficiently numerous.…”
Section: The Identification Strategymentioning
confidence: 99%
“…A fast growing literature has attempted to identify credit supply shocks through vector autoregressions (VAR) by imposing sign restrictions on impulse responses (Halvorsen and Jacobsen, 2009;Busch et al, 2010;De Nicol o and Lucchetta, 2011;Eickmeier and Ng, 2011;Tam asi and Vil agi, 2011;Gambetti and Musso, 2012;Hristov et al, 2012;Barnett and Thomas, 2013;Darracq Paries and De Santis, 2013;Houssa et al, 2013;Darracq Paries et al, 2014;Kick, 2014), or by using other identification schemes Abildgren, 2012;Darracq Paries and De Santis, 2013). 1 A constant 1 There have also been attempts in the theoretical literature to better capture shifts in the supply of credit by expanding the focus beyond borrowing constraints in collateral markets and emphasizing the role of constraints on lenders (Justiniano et al, 2014). parameter approach, as adopted in almost all these studies, might not do full justice to the timevarying nature of macroeconomic relationships that these models try to capture.…”
Section: Introductionmentioning
confidence: 99%
“…Gambetti and Musso (2012) find that during 2008 and 2009, credit supply shocks can explain about one half of the decline in the annual real GDP growth in the euro area and in the United States as well as around three quarters of growth changes in the United Kingdom. Bijsterbosch and Falagiarda (2015) show that while credit supply shocks have a procyclical impact in the euro area, there is evidence of a strong rise in cross-country heterogeneity, reflecting the financial fragmentation in the euro area associated with the sovereign debt crisis and weaker banks' balance sheets. Hristov et al (2011) show that in some EU countries, e.g.…”
mentioning
confidence: 94%
“…Many authors try to specifically identify credit supply shocks using the SVAR framework (Duchi and Elbourne 2016;Furlanetto et al 2014;Gambetti and Musso 2012;Hristov et al 2011;Peersman 2011;Bijsterbosdch and Falagiarda 2015;Barnett and Thomas 2013). They typically find that credit supply shocks matter and are a substantial source of macroeconomic fluctuations, though, naturally, the degree to which the credit supply had affected the economies during the recent economic cycle does differ.…”
mentioning
confidence: 99%
“…an aggregate sVar approach like that in the previous section could obviously be used here. this approach has been undertaken by the Bank of england as in Barnett and thomas (2013) and Mcleay and thomas (2015), who use a mixture of sign, timing, and long-run restrictions to identify credit shocks. however, an aggregate approach can miss interesting sectoral dimensions.…”
mentioning
confidence: 99%