The Bank Lending Channel: a FAVAR Analysis
ABSTRACT We examine the role of commercial banks in monetary transmission in a factor-augmented vector autoregression (FAVAR). A FAVAR exploits a large number of macroeconomic indicators to identify monetary policy shocks, and we add commonly used lending aggregates and lending data at the bank level. While our results suggest that the bank lending channel (BLC) is stronger than previously thought, this feature is not robust. In addition, our results indicate a diffuse response to monetary innovations when individual banks are grouped according to asset sizes and loan components. This suggests that other bank characteristics could improve the identification of the BLC.
- SourceAvailable from: SSRN[Show abstract] [Hide abstract]
ABSTRACT: We propose a novel approach to assess whether banks’ financial conditions, as reflected by bank-level information, matter for the transmission of monetary policy, while reconciling the micro and macro levels of analysis. We include factors summarizing large sets of individual bank balance sheet ratios in a standard factor-augmented vector autoregression model (FAVAR) of the French economy. We first find that factors extracted from banks’ liquidity and leverage ratios predict macroeconomic fluctuations. This suggests a potential scope for macroprudential policies aimed at dampening the procyclical effects of adjustments in banks’ balance sheet structures. However, we also find that fluctuations in bank ratio factors are largely irrelevant for the transmission of monetary shocks. Thus, there is little point in monitoring the information contained in bank balance sheets, above the information already contained in credit aggregates, as far as monetary policy transmission is concerned.International Journal of Central Banking. 07/2010; 6(34):71-117.
The Bank Lending Channel: a FAVAR Analysis?
University of Texas at Dallas
Scott J. Dressler
University of Texas at Dallas
We examine the bank lending channel (BLC) of monetary transmission in a factor-
augmented vector autoregression (FAVAR). A FAVAR exploits a large number of
macroeconomic indicators to identify monetary policy shocks, and we add commonly
used lending aggregates as well as lending data at the bank level. While our results
suggest that the BLC is stronger than previously thought, this feature is not robust.
In addition, our results indicate a di¤use response to monetary innovations from indi-
vidual banks grouped across asset sizes and loan components. This suggests that other
bank characteristics could improve the identi…cation of the BLC.
Keywords: Bank Lending Channel; FAVAR; Monetary Policy
JEL: E51, E52, C32
?We are grateful to seminar participants at the Federal Reserve Bank of Dallas, and to Marc Giannoni
for providing us with some of our data. All errors and omissions are those of the author.
yCorresponding author. Address: University of Texas at Dallas; School of Economic, Political and Policy
Sciences; 800 W. Campbell Rd.; Richardson, TX 75080. Phone: (972) 883-2306. Fax: (972) 883-6486.
Since Bernanke and Blinder’s (1992) observation that signi…cant movements in aggregate
bank lending volume follow changes in the stance of monetary policy, the bank lending
channel (henceforth, BLC) has been a prominent mechanism in the literature on monetary
transmission. The BLC focuses on the balance sheets of commercial banks and assumes that
insured, reservable deposits and other forms of external loan …nance (e.g. time deposits, CDs,
etc.) are not perfect substitutes due to the higher costs of acquiring the latter. Therefore, a
monetary contraction resulting in less reservable deposits should result in a decrease in the
supply of loans.
Building upon the initial intuition for the BLC, the literature has since stressed cross-
sectional di¤erences among commercial banks’ balance-sheets as well as loan components.
Kashyap and Stein (1995, 2000) considered bank assets and liquidity positions as aggregating
criteria and …nd that increases in the Federal funds rate are followed by signi…cant declines
in lending volume for the smallest (in terms of assets) and least liquid banks.1Den Haan
et al. (2007) consider loan components aggregated across banks and …nd that real estate
and consumer loans decline sharply in response to a monetary contraction while commercial
and industrial (C&I) loans increase.2While Perez (1998), Ashcraft (2006), and others have
questioned the macroeconomic signi…cance of the BLC in monetary transmission, Kashyap
and Stein (1995, 2000) and Den Haan et al. (2007) remain as evidence for its existence.
This evidence is not without its limitations. For example, the Federal funds rate com-
monly used as the monetary policy instrument may not appropriately identify monetary
policy innovations. In addition, aggregating bank lending across either asset categories or
loan components may contaminate the true responses of individual banks who are respond-
ing to both bank-speci…c and aggregate sources of ‡uctuations simultaneously. Previous
1Kishan and Opiela (2000) further …nd that banks with the weakest capital positions are the most
responsive to monetary policy.
2The authors suggest that the perverse response of C&I loans could still be consistent with the BLC due
to a bank’s preference for the relative safety and term of a C&I loan rather than a longer-term asset (such
as a real estate loan).
analyses which either support or refute the BLC are in some way subject to these limita-
tions. The goal of this paper is to put these limitations to the test by examining the lending
response of commercial banks in a new and increasingly popular empirical framework - a
factor-augmented vector autoregression (FAVAR).
A FAVAR, which combines standard structural VAR methods with factor analysis, ex-
ploits a large number of time series and summarizes the information into a relatively small
set of estimated indexes (i.e. factors).This provides many desirable properties for an
analysis of the BLC. First, utilizing a large data set of macroeconomic variables like those
used by central banks is important when properly identifying monetary policy innovations.
Bernanke et al. (2005) (henceforth, BBE) motivate the use of a FAVAR in their analysis
of the macroeconomic e¤ects of monetary policy shock by arguing that the measurement of
policy innovations is likely to be contaminated by limiting the analysis to a small number
of comprehensive macroeconomic variables.3Second, one does not need to take a stand on
speci…c observables (such as industrial production or real GDP) to correspond to theoretical
concepts (such as economic activity) because a FAVAR summarizes these concepts using large
amounts of economic information. Finally, a FAVAR provides impulse responses for every
variable in the conditioning set, as well as a decomposition of their individual ‡uctuations
into those due to aggregate factors and those due to individual, idiosyncratic innovations.
Our FAVAR framework considers the set of macroeconomic indicators used by BBE, and
extends this data by appending a variety of commercial-bank lending variables. First, total
loan growth and growth in loan components are aggregated up to the total banking system (as
in Bernanke and Blinder, 1992 and Den Haan et al., 2007) as well as up to groups according
to asset size (as in Kashyap and Stein, 1995 and 2000).4While these variables illustrate how
aggregate bank lending responds to an improved identi…cation of monetary policy shocks,
3Imperfectly controlling for the information central bankers may have is exactly Sim’s (1992) critical
interpretation of an increase in aggregate prices in response to a monetary contraction (i.e.
Puzzle) observed in traditional VAR analyses.
4Following Kashyap and Stein (1995, 2000), we consider the asset groups to be banks with assets within
the 95th percentile or less (small), banks with assets within the 95th and 99th percentile (medium), and
banks with assets within the 99th percentile or more (large).
we also consider a large amount of lending data at the individual-bank level. This allows
us to disentangle the ‡uctuations in bank-level lending data which are due to aggregate
macroeconomic factors (such as a change in monetary policy) from those that are due to
bank-speci…c conditions. To our knowledge, this is the …rst analysis which considers purely
disaggregated lending data within the same framework as their commonly used aggregates,
and compares the responses of individual and aggregate lending in response to monetary
Our …ndings are twofold. First, when appending the FAVAR of BBE with aggregated
lending data, we …nd that total, C&I, and individual consumer loan growth all signi…cantly
decline after a monetary policy contraction for the entire banking sector as well as bank
groups categorized by asset size. While this suggests that the BLC e¤ects more than just
the smallest banks (asset wise) and is stronger than previously thought, this result is not
robust when considering post-1984 data. Second, when appending the FAVAR further with
a balanced panel of bank-level lending data, we …nd that their individual responses to a
monetary policy innovation are quite di¤use. There are almost as many banks who increase
lending in response to a monetary innovation as those who decrease, and this result remains
when controlling for bank groups and loan components. A main reason for these di¤use
responses is that macroeconomic ‡uctuations explain on average between 8 and 22 percent
of the variation in individual bank lending across our various loan categories. Therefore,
most of the variation in individual bank-lending re‡ects bank-speci…c shocks to which banks
respond immediately. Nonetheless, when considering lending aggregates comprised of only
those banks we observe individually, there are signi…cant declines for all bank groups in one
or more loan components, and these declines remain when employing post-1984 data.
A goal of the empirical research in this literature is to help target and identify the
important features of intermediation in monetary transmission that prove useful to theorists
by indicating which features of banking must be incorporated into their environments. The
picture our results paint is that while particular measures of the BLC are strengthened by
our FAVAR framework, the large degree of heterogeneity observed in the individual-bank
responses cast doubt on the notion that the BLC is stronger for banks based on asset size or
loan components. This implies that other bank characteristics might prove more suitable to
di¤erentiate banks which display a BLC e¤ect. For example, Cetorelli and Goldberg (2009)
show that the degree of globalization of a commercial bank could matter for the BLC because
globalized banks can activate foreign capital markets to insulate themselves from domestic
Our analysis of bank-level lending data is related to the analysis of Boivin et al. (2009)
who append the FAVAR of BBE with sector-speci…c price data with the goal of delineating
the e¤ects of sector-speci…c price shocks from aggregate price shocks. Their results sug-
gest that individual prices appear less persistent than their aggregate due to sector-speci…c
volatility. Once the responses of the individual prices to monetary policy shocks are iden-
ti…ed, they uncover a degree of persistence which accords with that observed in aggregate
prices. Therefore, our analysis of the BLC with a large number of individual banks included
in the FAVAR allows us to characterize responses to local shocks versus aggregate shocks in
the same manner as their analysis of prices.
The rest of the paper is organized as follows. Section 2 outlines the formulation and
estimation of the FAVAR. Section 3 discusses the data. Section 4 presents our empirical
results by …rst detailing the impulse responses of loan aggregates to a monetary policy shock,
and then examining the characteristics of disaggregated loan data. Section 5 concludes.
Our implementation of the FAVAR follows BBE, and a brief outline of the framework
is as follows. Assume the economy is a¤ected by a vector Ctof common components. For
example, a measure of the stance of monetary policy is a common component, and we follow
the literature by assuming that this stance is measured by the Federal funds rate (Rt).