wp 2016
DOI: 10.24149/wp1605
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Economic Policy Uncertainty and the Credit Channel: Aggregate and Bank Level U.S. Evidence over Several Decades

Abstract: Economic policy uncertainty affects decisions of households, businesses, policy makers and financial intermediaries. We first examine the impact of economic policy uncertainty on aggregate bank credit growth. Then we analyze commercial bank entity level data to gauge the effects of policy uncertainty on financial intermediaries' lending. We exploit the cross-sectional heterogeneity to back out indirect evidence of its effects on businesses and households. We ask (i) whether, conditional on standard macroeconom… Show more

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Cited by 10 publications
(8 citation statements)
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“…The key challenge in this line of research is the identification of an appropriate measure of policy uncertainty. Yet, several researchers have successfully examined the impact of policy uncertainty on firms' fixed investment expenditures (Gulen and Ion, ), bank loans (Bordo et al ., ), or predicting recessions (Karnizova and Li, ) by employing a novel proxy proposed by Baker et al . ().…”
Section: Introductionmentioning
confidence: 99%
“…The key challenge in this line of research is the identification of an appropriate measure of policy uncertainty. Yet, several researchers have successfully examined the impact of policy uncertainty on firms' fixed investment expenditures (Gulen and Ion, ), bank loans (Bordo et al ., ), or predicting recessions (Karnizova and Li, ) by employing a novel proxy proposed by Baker et al . ().…”
Section: Introductionmentioning
confidence: 99%
“…Aron, et al (2010) and Bordo, et al (2016) track these respective general types of variables with the change in the real federal funds rate (ΔRFF), the percent change in the index of leading economic indicators (Δ 2 LEI), the year-over-year change in consumer installment or overall delinquency rates (Δ 4 DEL) rose, and pre-1983 bank regulations (Aron, et al, 2012) or economic policy uncertainty (Bordo, et al, 2016) Reserve announced that it would ease the regulatory burden of the DFA on smaller banks starting in early 2015. The timing of the DFA effects is faster in our model of credit standards than of loan shares because the former more quickly reflects banks' anticipation of future conditions affecting loan returns whereas loans outstanding tend to move with a lag after loan policy changes and reflect the stock of outstanding loans rather than terms on new loans.…”
Section: Evidence From Bank Credit Standards For Candi (Business) mentioning
confidence: 96%
“…These unexplained components of EPU are analogous to detrended movements in EPU, which others, such as BBD (2015) and Bordo, Duca, and Koch (2016) Notes: first differences of lagged variables omitted in the short-run results section to conserve space (full results are available). "v." denotes vector, while + , * and ** denote 90%, 95%, and 99% significance levels, respectively.…”
Section: Discussionmentioning
confidence: 99%
“…prices (Brogaard and Detzel 2013), bank loan growth (Bordo, Duca, and Koch 2016), and the yield curve (Leippold and Matthys 2015).…”
mentioning
confidence: 99%