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The Credit Channel in Monetary Policy Transmission at the 
Zero Lower Bound. A FAVAR Approach 
Master Project 
Alexandru B...
cation strategy in two key ways. First, we use the credit variables inside 
a Factor Augmented Vector Autoregression, to s...
nancial series. Second, we adopt the shadow 
rate developed by Wu  Xia (2013) as an alternative to the eective federal fun...
nd that monetary policy shocks 
have considerably larger eects through the credit supply side than the credit demand 
side...
nd the macroeconomic eects arising from 
the supply side of the credit channel to be sizable. When focusing on the recent ...
1. Introduction 
The recent global
nancial crisis has heightened the interest of both academia and 
policy circles in the empirical relevance of the credit c...
cation challenges. The breadth and heterogeneity 
of the Federal Reserves unconventional measures have undeniably expanded...
cation of credit channel in monetary policy transmission mechanism. 
Accordingly, this paper seeks to provide a framework ...
cation strategy in two important ways. First, we employ the 
credit variables inside a Factor Augmented Vector Autoregress...
nancial series. 
Second, we adopt the shadow rate developed by Wu Xia(2013) as an alternative to 
the eective federal fund...
rst application of the shadow rate to the identi
cation of the 
credit channel in monetary policy transmission at the zero lower bound. Second, the 
literature examining t...
economy, but identi
cation of credit shocks is based on bank-level balance sheet ratios. 
Third, this is the
rst methodology able to disentangle and quantify the eect of broad 
lending channel and credit demand channel, as de
ned by responses from Senior Loan 
Ocer Survey, on such a large set of macroeconomic series, as facilitated by our FAVAR. ...
cation challenges. Section 3 presents our methodology 
and proposes a proper identi
cation of the credit shock, of the monetary shock at the 
zero lower bound and of the wider macroeconomic model. Section 4...
xed investments, react long after the interest rate has reverted to trend), magnitude 
(large output 
uctuations come at o...
ndings point to the existence of a credit enhancement channel - a mecha- 
nism that ampli
es and propagates monetary policy shocks to the real economy. At its 
root lies the concept of external
nance premia: a wedge between the cost of internal
nance (liquid assets, retained earnings) and external sources of
nance (debt, equity).3 
3Conventionally, the external
nance premium is rationalized through the presence of frictions such as 
credit market imperfections, asymmetric informati...
cation. 
3
Another theoretical result is the
nancial accelerator hypothesis: the presence of en- 
dogenous dynamics in the external
nance premia across the business cycle (Bernanke, 
Gertler and Gilchrist (1996)). For identical
nancing needs, the external
nance pre- 
mia is inversely correlated with the
rm's net worth (liquid assets) and collateral value 
on illiquid assets. A small negative shock to
rms' net worth damages
rms' credit- 
worthiness, lowers access to capital, dampens investment expenditures, lowering future 
net worth, which in ...
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The Credit Channel in Monetary Policy Transmission at the Zero Lower Bound. A FAVAR Approach

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Barcelona GSE Master Project by Alexandru Barbu, Zymantas Budrys, and Thomas Walsh

Master Program: Economics

About Barcelona GSE master programs: http://j.mp/MastersBarcelonaGSE

Published in: Economy & Finance
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The Credit Channel in Monetary Policy Transmission at the Zero Lower Bound. A FAVAR Approach

  1. 1. The Credit Channel in Monetary Policy Transmission at the Zero Lower Bound. A FAVAR Approach Master Project Alexandru Barbu, Zymantas Budrys, Thomas Walsh Barcelona Graduate School of Economics Master in Economics June 7, 2014 Abstract This paper aims to provide a methodology for identifying the credit channel in US monetary policy transmission, consistent with periods at the zero lower bound. We follow Ciccarelli, Maddaloni and Peydro (2011) in identifying credit shocks through quarterly responses in the Federal Reserve's Senior Loan Ocer Survey, but augment their identi
  2. 2. cation strategy in two key ways. First, we use the credit variables inside a Factor Augmented Vector Autoregression, to summarize the information contained in a set of 110 US macroeconomic and
  3. 3. nancial series. Second, we adopt the shadow rate developed by Wu Xia (2013) as an alternative to the eective federal funds rate at the zero lower bound. We present our results through impulse response func- tions and carefully designed counterfactuals. We
  4. 4. nd that monetary policy shocks have considerably larger eects through the credit supply side than the credit demand side. Building counterfactual analyses, we
  5. 5. nd the macroeconomic eects arising from the supply side of the credit channel to be sizable. When focusing on the recent un- conventional policies, our counterfactuals show only very modest movements in credit variables, suggesting that the positive eects of unconventional monetary policy during the crisis may not have acted strongly through the credit channels. 1
  6. 6. 1. Introduction The recent global
  7. 7. nancial crisis has heightened the interest of both academia and policy circles in the empirical relevance of the credit channel for the eective trans- mission of monetary policy to the real economy. In turbulent times, however, such an analysis faces additional identi
  8. 8. cation challenges. The breadth and heterogeneity of the Federal Reserves unconventional measures have undeniably expanded the set of macroeconomic variables relevant to monetary policy assessment. 1 A second consideration is the relative lack of variation in the conventional mone- tary policy measure, the eective Federal Funds rate, since it had reached the ZLB in January 2009. Consequently, economists have sought a single measure that can par- simoniously capture the stance of the monetary policy at the zero lower bound while possibly quantifying the impact of unconventional monetary policies on the macroe- conomy.2 These arguments guide our choice of methodology and emphasise the relative impor- tance of the identi
  9. 9. cation of credit channel in monetary policy transmission mechanism. Accordingly, this paper seeks to provide a framework for identifying the credit channel in US monetary policy transmission, consistent with periods at the zero lower bound. Following Ciccarelli et al.(2013), we trust the bankers and identify credit shocks through quarterly responses in the Federal Reserves Senior Loan Ocer Survey. We augment their identi
  10. 10. cation strategy in two important ways. First, we employ the credit variables inside a Factor Augmented Vector Autoregressive model, to summa- rize the information contained in a set of 110 US macroeconomic and
  11. 11. nancial series. Second, we adopt the shadow rate developed by Wu Xia(2013) as an alternative to the eective federal funds rate for the period after January 2009. The shadow interest rate provides a measure claimed to summarize the stance of US monetary policy at the zero lower bound. Our paper makes contributions to three dierent strands of literature. To our knowledge, this is the
  12. 12. rst application of the shadow rate to the identi
  13. 13. cation of the credit channel in monetary policy transmission at the zero lower bound. Second, the literature examining the implications of the credit channel in a Factor Augmented VAR models is rather thin. Jimborean et al.(2013) provide such an analysis for the French 1For a more comprehensive review of unconventional policies, see, for example, Thornton (2012). 2Bullard (2013) provides a brief summary of the ongoing research on this topic. 2
  14. 14. economy, but identi
  15. 15. cation of credit shocks is based on bank-level balance sheet ratios. Third, this is the
  16. 16. rst methodology able to disentangle and quantify the eect of broad lending channel and credit demand channel, as de
  17. 17. ned by responses from Senior Loan Ocer Survey, on such a large set of macroeconomic series, as facilitated by our FAVAR. The paper is organized as follows: Section 2 reviews the credit channel literature and discusses its main identi
  18. 18. cation challenges. Section 3 presents our methodology and proposes a proper identi
  19. 19. cation of the credit shock, of the monetary shock at the zero lower bound and of the wider macroeconomic model. Section 4 summarizes our data. Section 5 presents the main results and interpretation, section 6 presents our evaluation and section 7 concludes. 2. Literature review A common puzzle in business cycle analysis is the observation of large and persis- tent business cycle uctuations stemming from relatively small and temporary real or monetary shocks (King and Rebello, 1999). The traditional view in the monetary policy transmission literature is that monetary authorities leverage their control over short term interest bearing securities to aect the cost of capital and subsequently real spending on durable and investment goods (Bernanke and Gilchrist, 1995) Following the literature, we interpret this transmission mechanism as the interest rate channel. Bernanke and Gertler(1995) claim the interest rate channel fails to explain empir- ical evidence in 3 important aspects: timing (some real variables, such as business
  20. 20. xed investments, react long after the interest rate has reverted to trend), magnitude (large output uctuations come at odds with the relatively small cost-of-capital eects predicted in empirical studies) and composition (large impulse responses in long lived assets to shocks in short term rates. Their
  21. 21. ndings point to the existence of a credit enhancement channel - a mecha- nism that ampli
  22. 22. es and propagates monetary policy shocks to the real economy. At its root lies the concept of external
  23. 23. nance premia: a wedge between the cost of internal
  24. 24. nance (liquid assets, retained earnings) and external sources of
  25. 25. nance (debt, equity).3 3Conventionally, the external
  26. 26. nance premium is rationalized through the presence of frictions such as credit market imperfections, asymmetric information, principal agent problems, costly monitoring or costly state veri
  27. 27. cation. 3
  28. 28. Another theoretical result is the
  29. 29. nancial accelerator hypothesis: the presence of en- dogenous dynamics in the external
  30. 30. nance premia across the business cycle (Bernanke, Gertler and Gilchrist (1996)). For identical
  31. 31. nancing needs, the external
  32. 32. nance pre- mia is inversely correlated with the
  33. 33. rm's net worth (liquid assets) and collateral value on illiquid assets. A small negative shock to
  34. 34. rms' net worth damages
  35. 35. rms' credit- worthiness, lowers access to capital, dampens investment expenditures, lowering future net worth, which in turn has negative consequences on present net worth, and so on and so forth. Testing for the empirical relevance of credit channel in business cycle dynamics exposes us to severe identi
  36. 36. cation challenges. These problems stem from the fact that uctuations in credit demand and supply are by and large unobserved variables. According to Bernanke Gertler (1995), credit aggregates are largely unable to dis- entangle the eects stemming from the credit channel from those generally associated with the interest rate channel. As shown in Bernanke, Gertler and Gilchrist (1996), following a monetary policy tightening, both the interest rate channel, through the policy rate, and credit channel, through the external
  37. 37. nance premia, predict similar dynamics in lending volumes. Aggregate credit measures fail to account for the amount of existing credit lines, whose demand tends to be countercyclical (Ciccarelli et. al., 2013). Ultimately, statis- tics of aggregate credit prices fail to control for such strategic behaviors as ight to quality. This reported tendency of banks to optimally rebalance their portfolios to- wards their most creditworthy borrowers during phases of
  38. 38. nancial fragility arti
  39. 39. cially reduces the sensitivity of credit price aggregates to changes in monetary policy. Al- ternatively, micro data takes into account actual credit granted, instead of total loan demand, being forced to make restrictive assumptions over the latter. There is an growing literature of the relevance of bank lending shocks in driving uctuations in macroeconomic variables. Amiti and Weinstein (2013)
  40. 40. nd that bank lending shocks can account for around 40% of the variation in investment expenditure in Japan. Chodorow-Reich(2014)
  41. 41. nds that the contraction of credit can explain up to half of the employment decline from a sample of SMEs following the collapse of Lehman Bros. Kashyap, Stein and Wilcox (1993) provide more evidence of a loan supply channel of monetary policy to the real economy.Following monetary tightening, the mix of external
  42. 42. nance changes such that
  43. 43. rms rely more on other external sources such as commercial paper, and less on bank loans. They
  44. 44. nd bank loan supply directly aects
  45. 45. rms' investments, suggesting that
  46. 46. rms cannot perfectly substitute bank lend- 4
  47. 47. ing. Kashyap and Stein (2000) have investigated the impact of monetary policy on lending behaviour of banks using data on one million loans. Moreover, Kashyap, La- mont and Stein (1994) show that monetary policy has signi
  48. 48. cant impacts on
  49. 49. rms inventories through liquidity constraints. 3. Methodology Given the aforementioned empirical challenges, we adopt the approach of Ciccarelli et al (2013) in identifying the credit channel through responses in the quarterly US Senior Loan Ocer Survey. A breakdown in broad lending channel and credit demand channel is done following de
  50. 50. nitions from Bernanke et. al. (1995). Senior Loan Ocer Survey Regional Feds request quarterly information on the lending standards that banks apply to customers and on the loan demand they receive from
  51. 51. rms and households. The survey applies to a representative sample of 60-70 insured, domestically chartered com- mercial banks.4 Due to data availability, we consider only commercial and industrial (CI) loans. Our series starts in 1991Q4. Respondents are asked to assess the change in lending standards they apply to business loans and credit demand they receive from business customers. Responses are weighted on a scale, from eased considerably to tightened considerably. Only credit changes in the last 3 months are considered. Re- garding the identi
  52. 52. cation of credit shocks, we follow Bernanke Gertler (1995) and denote an innovation to responses related to demand for loans as a shock to credit de- mand and an innovation to total lending standards as a shock to credit supply (broad credit channel). While the SLOS responses are qualitative, results are reported as net percentages.5 Once again, we trust the bankers in the sense that we take their responses to be true and accurate. A detailed description of the SLOS questions is provided in the annex.6 4The number of Senior Loan Ocer Survey respondents varies slightly across the series 5For any given credit variable, net percentages are constructed as the dierence between the number of banks reporting that standards have eased somewhat or considerably and the number of banks reporting that standards have tightened somewhat or considerably, divided by the number of banks in the sample. 6For a review of the relative performance of Senior Loan Ocer Survey in identifying the credit channel in the US monetary policy transmission, see LownMorgan (2006) 5
  53. 53. The shadow rate and the zero lower bound A common practice in the monetary policy transmission literature is to identify the monetary policy shock as an unexpected standardized change in the overnight Federal Funds rate.7 However, since December 2008, the Federal Funds rate has (eectively) been at the zero lower bound. The ensuing lack of variation implies the Federal Funds rate can convey little information about the changes in US monetary policy during the ZLB period. Moreover, the structural break in the variation of Federal Funds rate would cause signi
  54. 54. cant identi
  55. 55. cation challenges for a prolonged period, long af- ter the policy would have exited the zero-lower bound. Moreover, as Williams (2014) emphasizes, the frequency and duration of zero-lower bound events might be severely understated.8 Consequently, the literature has sought to
  56. 56. nd a monetary policy measure consis- tent with both normal and zero-lower bound periods. In a seminal paper, Black (1995) de
  57. 57. nes the nominal interest rate as an option with a strike price at the ZLB and the short term shadow rate as the value of its underlying asset. The nominal interest rate will equal the shadow rate for any positive values rt 0, and zero otherwise. Wu Xia (2013) use this insight to model the shadow rate through a Gaussian Ane Term Structure Model (GATSM). GATSM uses information from selected yields at dierent maturities to construct the remainder of the yield curve.9. While GATSM are very close approximators of the actual yield curves in normal times, they fail in zero-lower bound periods, as they allow for the possibility of negative nominal rates, which is implausible. To simulate the yield curve at the ZLB, Wu Xia (2013) introduce a non-linearity in their linear factor model. The short term nominal rate becomes a non-linear function of the factors. Factors are extracted from the observed yields using principal compo- nent analysis and regressed on the yields. Then the model parameters are estimated, and the estimates are used to create a counterfactual shadow rate that is ane in the factors. The shadow rate is the nominal rate that would prevail were there no physical currency. (if the ZLB would not exist). Wu Xia (2013) further provide an approximation which allows for closed form solutions in multiple factors models. Hence, it returns a model that is empirically 7A comprehensive review of monetary policy shock choices is provided by Christiano, Eichenbaum and Evans (1999). 8Williams (2014) argues that modelling the probability of ZLB occurring is chie y based on historical data from a short enough period to indicate ZLB events would practically be non-existent 9Hamilton and Wu (2010) provide derivation and intuition behind GATSM 6
  58. 58. tractable, simulates the observed ZLB yield curve with an high level of precision and returns a shadow rate that is robust to dierent speci
  59. 59. cations.10 Note, though, that the entire theoretical construct would be a risk in the event of a very persistent zero-lower bound period.11 Since in the Wu Xia (2013) model, the shadow rate is a function of forward rates, and this forward rates summarize the ex- pectations about the future short term rate, a long enough ZLB period could stabilize investors expectations of future short rates to zero for long enough for the shape of the yield curve to be impaired. However, Swanson and Williams (2013) provide evidence that the sensitivity of longer term yields to news during the current ZLB period is not signi
  60. 60. cantly altered. Evaluating the Shadow Rate as a Measure of Monetary Policy Wu Xia (2013) verify whether the shadow rate is a reliable representation of the US monetary policy stance at the ZLB. To test for a structural break in the dynamics of the monetary policy rate across pre and post crisis periods, they run a likelihood ratio test. The restricted model requires that the autoregressive coecients of the reduced from model are not signi
  61. 61. cantly dierent before and after the crisis. They cannot reject the null hypothesis of no structural break for the shadow rate, but do reject the null hypothesis for the eective federal funds rate. Given the shadow rate, by construction, closely follows the eective federal funds rate in normal times (see
  62. 62. g. 1, annex), but decouples and continues to exhibit reasonable variation at the zero lower bound, we interpret Wu Xia shadow rate as an alternative monetary policy measure consistent with the ZLB. Following the literature, we set the beginning of the ZLB period to Q1 2009. We construct a continuous series of the monetary policy rate by appending the eective Federal Funds rate before the ZLB period with the shadow rate estimates during the ZLB period. We subsequently employ the shadow rate, as an alternative measure of monetary policy rate at the ZLB, and the credit variables, as identi
  63. 63. ed from the re- sponses in the Senior Loan Ocer Survey, in a Factor Augmented VAR model, as 10For a more extensive discussion on the eectiveness of theWu Xia (2013) shadow rate in summarizing monetary policy stance at the zero lower bound, see Bullard (2012) and Hamilton (2013). 11In Black(1995) model, the prospect of non-positive longer term yields is excluded. This holds in theoretical cases with continuous time. In practice, though, with non-zero step intervals, longer rates can be negative, since there is some probability, given the current level and volatility of the shadow rate process, the rate will remain negative for the length of the horizon. 7
  64. 64. detailed below. A Factor Augmented Vector Autoregressive Model Following Sims (1980) critique of incredible identifying restrictions in dynamic simulta- neous equations models, structural vector-autoregressions have become a powerful tool in monetary policy transmission analysis. As Bernanke, BoivinEliasz (2004) explain, the VAR approach requires only a plausible identi
  65. 65. cation of the monetary policy shock and not necessarily of the remainder of the macroeconomic model. To the extent to which the monetary authority sets policy based on variables that are excluded from the model, the resulting impulse responses are likely to be biased. If Sims(1992) jus- ti
  66. 66. cation of the price puzzle as a response of the monetary authority to in ationary pressures not captured in the VAR model was right, the reasoning can be generalized for other omitted variables. We follow Bernanke, Boivin Eliasz (2005) in specifying a Factor Augmented Vector Autoregressive model of the US economy. One bene
  67. 67. t of a FAVAR is it can summarize the information contained in a large set of observed macroeconomic vari- ables Xt in a relatively compact vector of latent factors Ft. Moreover, it ameliorates degrees-of-freedom problems, mimics the large information set monetary authorities might actually use in setting policy and obtains impulse responses for a large set of macroeconomic variables of interest. Following Bernanke et. al.(2005), we specify the following factor augmented vector- autoregressive model: Ft st # = F s # + 1 Ft

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