Bank Market Power and Monetary Policy Transmission: Evidence from a Structural Estimation
银行市场力量和货币政策传导:结构估计的证据
首次发布日期:2022 年 5 月 25 日 https://doi.org/10.1111/jofi.13159 引用次数:27
ABSTRACT 摘要
We quantify the impact of bank market power on monetary policy transmission through banks to borrowers. We estimate a dynamic banking model in which monetary policy affects imperfectly competitive banks' funding costs. Banks optimize the pass-through of these costs to borrowers and depositors, while facing capital and reserve regulation. We find that bank market power explains much of the transmission of monetary policy to borrowers, with an effect comparable to that of bank capital regulation. When the federal funds rate falls below 0.9%, market power interacts with bank capital regulation to produce a reversal of the effect of monetary policy.
我们量化银行市场力量对货币政策传导到借款人的影响。我们估计了一个动态银行模型,其中货币政策影响了不完全竞争银行的资金成本。银行优化这些成本对借款人和存款人的传递,同时面临资本和准备金监管。我们发现银行市场力量解释了货币政策传导到借款人的很大部分,其效果与银行资本监管相当。当联邦基金利率下降到 0.9%以下时,市场力量与银行资本监管相互作用,产生了货币政策效果的逆转。
We examine the quantitative impact of bank market power on the transmission of monetary policy through the banking system. This transmission channel is potentially important, given three decades of consolidation in the banking industry that has softened competitive pressure. Moreover, recent research offers qualitative evidence that bank market power affects the pass-through of monetary policy to the supply of loans (Scharfstein and Sunderam (2016), Drechsler, Savov, and Schnabl (2017)). Yet, market power is not the only friction in the banking system that influences pass-through. For example, traditional analysis of monetary policy transmission focuses on regulatory constraints, such as bank reserve or capital requirements, as the central frictions that influence monetary policy transmission (Bernanke and Blinder (1988), Kashyap and Stein (1995)). However, the qualitative nature of this evidence leaves open the question of the relative magnitude of traditional versus market-power transmission channels.
我们研究了银行市场力量对货币政策通过银行体系传导的定量影响。鉴于银行业三十年来的整合,竞争压力有所减弱,这种传导渠道可能非常重要。此外,最近的研究提供了定性证据,即银行市场力量影响货币政策传导到贷款供应(Scharfstein 和 Sunderam(2016 年),Drechsler,Savov 和 Schnabl(2017 年))。然而,市场力量并非是影响传导的银行体系中唯一的摩擦。例如,传统的货币政策传导分析侧重于监管约束,如银行准备金或资本要求,作为影响货币政策传导的中心摩擦(Bernanke 和 Blinder(1988 年),Kashyap 和 Stein(1995 年))。然而,这些证据的定性性质使传统与市场力量传导渠道的相对重要性问题尚未解决。
To do so, we use data on U.S. banks to estimate a dynamic banking model with three frictions: regulatory constraints, financial frictions, and imperfect competition. The estimation allows our data to discipline the model parameters and thus identify the relative magnitudes of these three frictions. We find that bank market power plays an important role in determining the degree of monetary policy transmission. In terms of magnitude, the effects of bank market power are comparable to those of bank capital regulation, while the effects of bank reserve requirements are limited.
为此,我们使用美国银行的数据来估计一个具有三种摩擦的动态银行模型:监管约束、金融摩擦和不完全竞争。估计使我们的数据约束模型参数,从而确定这三种摩擦的相对大小。我们发现银行市场力量在决定货币政策传导程度方面发挥着重要作用。在数量上,银行市场力量的影响与银行资本监管相当,而银行准备金要求的影响有限。
In further analysis, we first show that banks face nontrivial costs when they access external financial markets. These frictions play a pivotal role in connecting banks' deposit market power to their lending decisions, as external financing costs link banks' sources and uses of funds. In addition, these frictions help explain the differential sensitivity of lending to the policy rate between big and small banks.
在进一步分析中,我们首先展示银行在接入外部金融市场时面临非微不足道的成本。这些摩擦在将银行的存款市场力量与其放贷决策联系起来方面发挥着关键作用,因为外部融资成本将银行的资金来源和用途联系在一起。此外,这些摩擦有助于解释大型银行和小型银行对政策利率的放贷敏感性之间的差异。
Second, we show that bank market power interacts with capital regulation to reverse the effect of monetary policy when the federal funds rate is very low. Specifically, we find that when the federal funds rate is below 0.9%, further cuts in the policy rate can be contractionary. Moreover, we find external validation of this reversal rate by showing in a simple regression framework that the relation between bank capital and interest rates switches sign at a threshold predicted by the model.
其次,我们展示银行市场力量与资本监管相互作用,当联邦基金利率非常低时,可以扭转货币政策的效果。具体来说,我们发现当联邦基金利率低于 0.9%时,进一步降低政策利率可能是紧缩的。此外,我们通过在简单回归框架中展示银行资本与利率之间的关系在模型预测的阈值处转换符号来验证这种逆转率。
To provide intuition for these results, we elaborate on the model. In a dynamic industry equilibrium, imperfectly competitive banks act as intermediaries between borrowers and depositors. Banks' lending decisions are dynamic for two reasons: financial frictions that induce precautionary capital accumulation and a maturity mismatch between short-term deposits and long-term loans. In this setting, monetary policy moves the federal funds rate. Because banks are not price takers in deposit or loan markets, they choose the extent to which they pass rate movements through to depositors and borrowers. The magnitude of this pass-through depends on the tightness of regulatory constraints, the severity of financial frictions, and the intensity of competition.
为了解释这些结果,我们详细阐述了模型。在动态行业均衡中,不完全竞争的银行充当借款人和存款人之间的中介。银行的放贷决策有两个动态原因:金融摩擦导致预防性资本积累,以及短期存款和长期贷款之间的到期不匹配。在这种情况下,货币政策会影响联邦基金利率。由于银行在存款或贷款市场中不是价格接受者,他们选择将利率变动程度传递给存款人和借款人。这种传递的幅度取决于监管约束的严格程度、金融摩擦的严重程度和竞争的强度。
These frictions in our model map into four channels of monetary policy transmission. The first is the bank reserve channel, in which a high federal funds rate raises the opportunity cost of holding reserves, thus contracting deposit creation (Bernanke and Blinder (1988), Kashyap and Stein (1995)). The second is the bank capital channel, in which a high federal funds rate reduces bank capital because of a balance-sheet maturity mismatch and thus constrains banks' capacity to lend (Bolton and Freixas (2000), Van den Heuvel (2002), Brunnermeier and Sannikov (2016)). The third is the deposit market power channel, in which a high federal funds rate allows banks to charge higher markups on deposits, thus leading to a contraction in deposits and loans (Drechsler, Savov, and Schnabl (2017)). The fourth is the loan market power channel, in which banks reduce markups to mitigate the effects of monetary tightening on loan demand (Scharfstein and Sunderam (2016)).
我们模型中的这些摩擦映射为货币政策传导的四个渠道。第一个是银行准备金渠道,高联邦基金利率提高了持有准备金的机会成本,从而收缩存款创造(Bernanke 和 Blinder(1988 年),Kashyap 和 Stein(1995 年))。第二个是银行资本渠道,高联邦基金利率由于资产负债表到期不匹配而减少银行资本,从而限制了银行的贷款能力(Bolton 和 Freixas(2000 年),Van den Heuvel(2002 年),Brunnermeier 和 Sannikov(2016 年))。第三个是存款市场力量渠道,高联邦基金利率使银行能够对存款收取更高的溢价,从而导致存款和贷款收缩(Drechsler,Savov 和 Schnabl(2017 年))。第四个是贷款市场力量渠道,银行降低溢价以减轻货币紧缩对贷款需求的影响(Scharfstein 和 Sunderam(2016 年))。
To gauge the quantitative importance of these transmission channels, we estimate our model using data on U.S. commercial banks from 1994 to 2017. Our estimation combines methods used in the industrial organization literature (Berry, Levinsohn, and Pakes (1995), Nevo (2001)) with those used in the corporate finance literature (Hennessy and Whited (2005), Bazdresch, Kahn, and Whited (2018)). We begin by using demand estimation techniques to obtain the elasticities of loan and deposit demand to interest rates. We then plug these estimates into our model and use simulated minimum distance (SMD) to obtain estimates of parameters that quantify financial frictions and operating costs. The sequential use of these two techniques represents a methodological advance that enables us to consider a rich equilibrium model that would otherwise be intractable to estimate.
为了衡量这些传输渠道的数量重要性,我们使用 1994 年至 2017 年美国商业银行数据来估计我们的模型。我们的估计结合了工业组织文献中使用的方法(Berry,Levinsohn 和 Pakes(1995 年),Nevo(2001 年))以及公司融资文献中使用的方法(Hennessy 和 Whited(2005 年),Bazdresch,Kahn 和 Whited(2018 年))。我们首先使用需求估计技术来获得贷款和存款需求对利率的弹性。然后,我们将这些估计值插入我们的模型中,并使用模拟的最小距离(SMD)来获得量化金融摩擦和运营成本的参数估计。这两种技术的顺序使用代表了一种方法论上的进步,使我们能够考虑一个否则难以估计的丰富均衡模型。
We use counterfactual experiments to assess the relative importance of each transmission channel. We start with a model with all frictions as estimated and then subtract each friction one at a time. We find that eliminating reserve requirements leaves the sensitivity of lending to the federal funds rate nearly unchanged. Eliminating either capital regulation or deposit market power reduces this sensitivity, while eliminating loan market power raises it.
我们使用反事实实验来评估每个传输渠道的相对重要性。我们从一个模型开始,其中所有摩擦都被估计,然后逐个减去每个摩擦。我们发现,消除准备金要求几乎不会改变贷款对联邦基金利率的敏感性。消除资本监管或存款市场力量会降低这种敏感性,而消除贷款市场力量则会提高它。
These counterfactuals also show that rate cuts can be contractionary when rates are already low. Low rates depress bank profits by reducing bank deposit market power, as competition from cash intensifies. Lower profits then tighten the capital constraint and reduce lending. This result helps explain sluggish bank lending growth observed in the ultra-low interest rate environment after the 2008 financial crisis.
这些反事实情况也表明,当利率已经很低时,降息可能会收缩。低利率通过降低银行存款市场份额来抑制银行利润,因为现金的竞争加剧。然后,利润减少会加紧资本约束并减少贷款。这一结果有助于解释 2008 年金融危机后超低利率环境中观察到的银行贷款增长缓慢。
Our paper contributes to the literature on the role of banks in transmitting monetary policy (Bernanke and Blinder (1988), Kashyap and Stein (1995), Van den Heuvel (2002), Scharfstein and Sunderam (2016), Brunnermeier and Sannikov (2016), Drechsler, Savov, and Schnabl (2017)). We are the first to structurally estimate a dynamic banking model to quantify various transmission channels. Prior to our work, little was known about the relative importance of these channels, as this type of quantitative exercise is difficult to undertake using reduced-form methods. Moreover, previous studies usually consider these transmission channels in isolation. For example, Scharfstein and Sunderam (2016) and Drechsler, Savov, and Schnabl (2017) study market power in the loan and deposit markets separately. However, little is known about the interactions between channels. Thus, an important contribution of this paper is to provide a unified framework within which to study these interactions.
我们的论文为银行在传递货币政策方面的文献做出了贡献(Bernanke 和 Blinder(1988 年),Kashyap 和 Stein(1995 年),Van den Heuvel(2002 年),Scharfstein 和 Sunderam(2016 年),Brunnermeier 和 Sannikov(2016 年),Drechsler,Savov 和 Schnabl(2017 年))。我们是第一个结构估计动态银行模型以量化各种传输渠道的研究。在我们的工作之前,对于这些渠道的相对重要性几乎一无所知,因为使用简化形式的方法进行这种类型的定量分析是困难的。此外,以往的研究通常将这些传输渠道单独考虑。例如,Scharfstein 和 Sunderam(2016 年)以及 Drechsler,Savov 和 Schnabl(2017 年)分别研究了贷款和存款市场中的市场力量。然而,对于渠道之间的相互作用知之甚少。因此,本文的一个重要贡献是提供一个统一框架,以便研究这些相互作用。
Second, our paper is related to the theoretical literature on the effects of negative interest rate policies (Brunnermeier and Koby (2016), Eggertsson, Juelsrud, and Wold (2017), Campos (2019), Wang (2019)). While these studies are insightful, they typically treat the banking sector with a high level of abstraction. In contrast, we provide a model that is sufficiently realistic to be directly mapped onto microeconomic data. Our paper also contributes to the empirical literature on negative interest rate policy (Demiralp, Eisenschmidt, and Vlassopoulos (2017), Basten and Mariathasan (2018), Heider, Saidi, and Schepens (2019)). These studies show that negative policy rates can have perverse effects on bank lending. Our results suggest that such perverse effects can start to occur even before the policy rate turns negative because a near-zero policy rate results in a compression of banks' deposit spreads. Therefore, in countries such as the United States where the policy rate has never gone negative, the banking sector could nevertheless be hurt by an ultra-low-rate monetary policy.
其次,我们的论文与负利率政策效应的理论文献相关(Brunnermeier 和 Koby(2016 年),Eggertsson,Juelsrud 和 Wold(2017 年),Campos(2019 年),Wang(2019 年))。虽然这些研究很有见地,但它们通常以高度抽象的方式处理银行业。相比之下,我们提供了一个足够现实的模型,可以直接映射到微观经济数据上。我们的论文还为负利率政策的实证文献做出了贡献(Demiralp,Eisenschmidt 和 Vlassopoulos(2017 年),Basten 和 Mariathasan(2018 年),Heider,Saidi 和 Schepens(2019 年))。这些研究表明,负利率政策可能对银行贷款产生逆向效应。我们的结果表明,即使在政策利率变负之前,这种逆向效应也可能开始出现,因为接近零的政策利率会导致银行存款利差的压缩。因此,在像美国这样政策利率从未变负的国家,银行业仍可能受到超低利率货币政策的伤害。
Third, our paper is related to the literature on external financial frictions. Romer and Romer (1990) argue that banks can easily replace deposits with external financing, so shocks to deposits are unlikely to affect bank lending. In contrast, Kashyap and Stein (1995) argue that external financing is costly for banks, so the quantity of deposits matters for bank lending. Our study contributes to this debate, as our structural estimation approach allows us to infer the degree of bank financing costs from the relative size of their deposit taking and external borrowing. We find that this cost is economically significant and that frictions related to bank balance sheets play an important role in the transmission of monetary policy.
第三,我们的论文与外部金融摩擦的文献有关。Romer 和 Romer(1990)认为银行可以轻易用外部融资替代存款,因此存款冲击不太可能影响银行贷款。相比之下,Kashyap 和 Stein(1995)认为外部融资对银行来说是昂贵的,因此存款数量对银行贷款很重要。我们的研究为这一争论做出了贡献,因为我们的结构估计方法使我们能够从银行吸收存款和外部借款的相对规模推断出银行融资成本的程度。我们发现这种成本在经济上是显著的,并且与银行资产负债表相关的摩擦在货币政策传导中发挥着重要作用。
Finally, our paper contributes to the structural industrial organization literature on the banking system (Egan, Hortaçsu, and Matvos (2017), Buchak et al. (2018), Xiao (2020), Egan, Lewellen, and Sunderam (2022)). While this work usually features a static industry equilibrium, we introduce the dynamic adjustment of banks' balance sheets to study the role of maturity transformation and financial frictions. Our paper is also tangentially related to recent work that uses dynamic banking models to study optimal capital regulation (Begenau (2018), Begenau and Landvoigt (2021), Landvoigt, Van Nieuwerburgh, and Elenev (2021)). In particular, Corbae and D'Erasmo (2021) develop a dynamic dominant-fringe model to study the quantitative impact of regulatory policies on bank risk-taking and market structure. Our paper stands apart from this literature in that we emphasize the role of imperfect competition in monetary transmission. Moreover, our approach is more empirical in nature, as we estimate, rather than calibrate, all of our model parameters.
最后,我们的论文对银行体系的结构产业组织文献做出了贡献(Egan,Hortaçsu 和 Matvos(2017 年),Buchak 等(2018 年),肖(2020 年),Egan,Lewellen 和 Sunderam(2022 年))。虽然这项工作通常涉及静态行业均衡,但我们引入了银行资产负债表的动态调整,以研究到期转换和金融摩擦的作用。我们的论文也与最近使用动态银行模型研究最佳资本监管的相关工作有关(Begenau(2018 年),Begenau 和 Landvoigt(2021 年),Landvoigt,Van Nieuwerburgh 和 Elenev(2021 年))。特别是,Corbae 和 D'Erasmo(2021 年)开发了一个动态主导-边缘模型,以研究监管政策对银行风险承担和市场结构的定量影响。我们的论文与这一文献有所不同,我们强调了在货币传输中的不完全竞争的作用。此外,我们的方法更具实证性,因为我们估计而不是校准我们的模型参数。
The paper proceeds as follows. Section I describes our data. Section II presents the model. Section III discusses the estimation procedure and results. Section IV presents the results of our counterfactuals. Section V examines subsample heterogeneity and model robustness. Section VI concludes.
本文的内容如下。第一部分描述了我们的数据。第二部分介绍了模型。第三部分讨论了估计过程和结果。第四部分展示了我们的对照实验结果。第五部分考察了子样本的异质性和模型的稳健性。第六部分总结。
I. Data and Stylized Facts
I. 数据和事实化的事实
Our main data set is the Consolidated Reports of Condition and Income (Call Reports). This data set provides quarterly bank-level balance sheet information for U.S. commercial banks. It includes deposit and loan amounts, interest income and expense, loan maturities, salary expenses, and fixed-asset-related expenses. We merge the Call Reports with the Federal Deposit Insurance Corporation (FDIC) Summary of Deposits, which provides branch-level information on each bank since 1994 at an annual frequency. The sample period is 1994 to 2017.
我们的主要数据集是《资产和收入综合报告》(Call Reports)。这个数据集提供了美国商业银行的季度银行层面资产负债表信息。它包括存款和贷款金额、利息收入和支出、贷款到期日、工资支出以及固定资产相关支出。我们将《资产和收入综合报告》与联邦存款保险公司(FDIC)存款摘要合并,该摘要提供了自 1994 年以来每家银行的分行级信息,以年度频率。样本期为 1994 年至 2017 年。
We also use several other data sources. First, we retrieve publicly listed bank returns from the Center for Research in Security Prices (CRSP) and link these returns to bank concentration measures using the link table provided by the Federal Reserve Bank of New York. Banking industry stock returns are from Kenneth French's website. We collect Federal Open Market Committee (FOMC) meeting dates from the FOMC meeting calendar. Finally, we obtain the following time series from the Federal Reserve Economic Data (FRED) database: National Bureau of Economic Research (NBER) recession dates, the effective federal funds rate, two- and five-year Treasury yields, the aggregate amount of corporate bonds issued by U.S. firms, and the aggregate amounts of cash, Treasury bonds, and money-market mutual funds held by households. Details regarding the construction of our variables are in Table I.
我们还使用了其他几个数据来源。首先,我们从安全价格研究中心(CRSP)检索公开列出的银行回报,并使用纽约联邦储备银行提供的链接表将这些回报与银行集中度指标进行关联。银行业股票回报来自肯尼斯·弗伦奇(Kenneth French)的网站。我们从联邦公开市场委员会(FOMC)会议日历中收集 FOMC 会议日期。最后,我们从联邦储备经济数据(FRED)数据库获取以下时间序列:美国经济研究局(NBER)的衰退日期,有效的联邦基金利率,两年和五年期国债收益率,美国公司发行的公司债券总额,以及家庭持有的现金、国债和货币市场互惠基金的总额。有关我们变量构建的详细信息请参见表 I。
表 I. 变量定义
Variable 变量 | Construction 建筑 |
---|---|
Deposit market share 存款市场份额 | Deposits of a bank divided by the sum of deposits, cash, Treasury bills, and money market funds in the U.S. economy. 银行存款除以美国经济中存款、现金、国债和货币市场基金总和。 |
Loan market share 贷款市场份额 | Loans of a bank divided by the sum of U.S. household debt, corporate debt, and corporate equity. 银行贷款除以美国家庭债务、公司债务和公司股权之和。 |
Deposit rates 存款利率 | Deposit interest expense divided by deposits. 存款利息支出除以存款。 |
Loan rates 贷款利率 | Loan interest income divided by loans outstanding. 贷款利息收入除以未偿还贷款。 |
No. of branches 分支数量 | Number of local branches. 本地分支机构数量。 |
No. of employees per branch 每个分支机构的员工人数 |
Number of employees divided by number of branches. 员工人数除以分支机构数量。 |
Expenses related to fixed assets 固定资产相关的费用 |
Noninterest expenses related to the use of fixed assets divided by total assets. 与固定资产使用相关的非利息支出除以总资产。 |
Salary 工资 | Total salary expense divided by total assets. 总薪资支出除以总资产。 |
Reserve ratio 存款准备金率 | 10% times the weight of transaction deposits plus 1% times the weight of saving deposits. 交易存款重量的 10%加上储蓄存款重量的 1%。 |
Average loan maturity | Estimated maturity of each type loan weighted by the portfolio weight. Nonmortgage loan maturity is the repricing maturity and average prepayment adjusted mortgage duration comes from Landvoigt, Van Nieuwerburgh, and Elenev (2021). |
Nonreservable borrowing share | Nonreservable borrowing divided by total deposits. |
Deposit spread | Federal funds rate minus a deposit rate. |
Loan spread | A loan rate minus the corresponding five-year Treasury yield. |
Deposit-to-asset ratio | Deposits divided by total assets. |
Net noninterest expense | Noninterest expense minus noninterest income, divided by total assets. |
Leverage | Total assets divided by the book value of equity. |
Market-to-book ratio | The market value of equity divided by the book value of equity. |
Table II provides summary statistics for our sample. Three patterns are of note. First, mean deposit and loan market shares for the U.S. national market lie near the 90th percentile, indicating a very skewed distribution of market shares in which a few large banks dominate the market. Second, we see little variation in the number of employees per branch, but we see high variance and skewness in the number of branches per bank. This skewness is consistent with the skewness in market shares, as the number of branches is highly correlated with bank size. Third, we find that average loan maturity is 3.429 years.
表 II 提供了我们样本的摘要统计数据。有三个模式值得注意。首先,美国全国市场的平均存款和贷款市场份额接近 90%分位数,表明市场份额分布非常倾斜,少数大银行主导市场。其次,我们看到每家分行的员工数量变化不大,但我们看到每家银行的分行数量存在高方差和偏度。这种偏斜与市场份额的偏斜一致,因为分行数量与银行规模高度相关。第三,我们发现平均贷款期限为 3.429 年。
表 II. 摘要统计
In this table, we report summary statistics for our sample. The sample period is 1994 to 2017. The total size of the deposit market is defined as the sum of deposits, cash, and Treasury bills held by all U.S. households and nonfinancial corporations. The total size of the loan market is defined as the sum of U.S. corporate and household debt. Deposit and loan rates are calculated using interest expense and income. Expenses related to fixed assets and salaries are scaled by total assets. Deposit shares, loan shares, deposit rates, loan rates, expenses related to fixed assets, salaries, and net noninterest expenses are reported in percentages. Asset maturity is reported in years. “(vw)” indicates an asset-weighted mean, and “(ew)” indicates an equal-weighted mean. The data sources are the Call Reports and the FDIC Summary of Deposits. 在这张表中,我们报告了样本的摘要统计数据。样本期间为 1994 年至 2017 年。存款市场的总规模定义为所有美国家庭和非金融公司持有的存款、现金和国债的总和。贷款市场的总规模定义为美国公司和家庭债务的总和。存款和贷款利率是通过利息支出和收入计算的。与固定资产和工资相关的费用按总资产比例缩放。存款份额、贷款份额、存款利率、贷款利率、与固定资产相关的费用、工资和净非利息费用以百分比报告。资产到期期限以年为单位报告。“(vw)”表示资产加权平均,“(ew)”表示等权平均。数据来源是通话报告和 FDIC 存款摘要。 |
||||||||
---|---|---|---|---|---|---|---|---|
mean(vw) 平均(vw) | mean(ew) 均值(ew) | SD | p10 | p25 | p50 | p75 | p90 | |
Deposit market shares 存款市场份额 | 3.519 | 0.079 | 0.523 | 0.003 | 0.005 | 0.009 | 0.021 | 0.077 |
Loan market shares 贷款市场份额 | 1.368 | 0.033 | 0.207 | 0.001 | 0.002 | 0.004 | 0.009 | 0.034 |
Deposit rates 存款利率 | 1.706 | 2.032 | 1.292 | 0.166 | 0.873 | 2.085 | 3.150 | 3.714 |
Loan rates 贷款利率 | 5.935 | 6.921 | 1.725 | 4.540 | 5.599 | 6.959 | 8.286 | 9.061 |
No. of branches | 1778 | 69.753 | 315.678 | 7.000 | 11.000 | 17.000 | 34.000 | 94.000 |
No. of employees per branch | 53.736 | 18.338 | 17.433 | 9.109 | 11.188 | 14.306 | 19.556 | 28.500 |
Expenses of fixed assets | 0.454 | 0.480 | 0.165 | 0.270 | 0.347 | 0.448 | 0.584 | 0.798 |
Salaries | 1.590 | 1.725 | 0.486 | 1.061 | 1.348 | 1.650 | 2.036 | 2.646 |
Net noninterest expenses | 1.230 | 2.778 | 0.830 | 1.904 | 2.246 | 2.653 | 3.142 | 3.743 |
Loan-to-deposit ratio | 0.816 | 0.815 | 0.170 | 0.598 | 0.710 | 0.821 | 0.925 | 1.022 |
Borrowing-to-deposit ratio | 0.699 | 0.136 | 0.138 | 0.013 | 0.041 | 0.096 | 0.181 | 0.308 |
Deposit-to-asset ratio | 0.707 | 0.805 | 0.082 | 0.691 | 0.763 | 0.822 | 0.866 | 0.895 |
Book leverage | 11.464 | 11.114 | 2.577 | 7.947 | 9.408 | 10.990 | 12.656 | 14.390 |
Asset maturity | 3.429 | 3.772 | 1.402 | 2.163 | 2.764 | 3.560 | 4.604 | 5.698 |
In Figure 1, we show the prices that banks charge for their deposits and loans. Panel A depicts a time-series kernel regression of the average quarterly U.S. bank deposit spread on the federal funds rate, where the deposit spread is the difference between the federal funds rate and the deposit rate. Because this spread measures the price that banks charge for their depository services, in the absence of market power, one would expect to observe constant deposit spreads that equal the marginal cost of providing deposits. However, we find a positive relation between deposit spreads and the federal funds rate, which steepens when the rate is close to zero. This relation implies that banks charge higher prices for their depository services as the federal funds rate rises. Intuitively, if banks have market power, a higher federal funds rate allows them to increase profits by raising markups above marginal costs because depositors find cash costly to hold (Drechsler, Savov, and Schnabl (2017)).
在图 1 中,我们展示了银行对其存款和贷款收取的价格。面板 A 展示了美国银行平均季度存款利差随联邦基金利率的时间序列核回归,其中存款利差是联邦基金利率和存款利率之间的差异。由于这种利差衡量了银行对其存款服务收取的价格,在没有市场力量的情况下,人们会期望观察到等于提供存款的边际成本的恒定存款利差。然而,我们发现存款利差与联邦基金利率之间存在正相关关系,当利率接近零时,这种关系变得更为陡峭。这种关系意味着随着联邦基金利率的上升,银行对其存款服务收取更高的价格。直观地说,如果银行拥有市场力量,较高的联邦基金利率使它们能够通过将标记价格提高到边际成本之上来增加利润,因为存款人发现持有现金成本高昂(Drechsler,Savov 和 Schnabl(2017))。
Panel B of Figure 1 contains an analogous kernel regression of the average U.S. bank loan spread on the federal funds rate, where the loan spread is the difference between the loan rate, adjusted for loan loss provisions, and the five-year Treasury yield. We find that the loan spread falls as the federal funds rate rises. This pattern is consistent with Scharfstein and Sunderam (2016), who show that banks lower markups on loans in the face of rising rates to mitigate the effects of falling loan demand. In sum, Figure 1 suggests that market power creates wedges between the federal funds rate and the rates at which banks borrow and lend. Furthermore, the sizes of these wedges depend on the level of interest rates.
图 1 的 B 面板包含了美国银行贷款利差与联邦基金利率的类似核回归,其中贷款利差是贷款利率与五年期国债收益率之间的差异,调整了贷款损失准备金。我们发现,随着联邦基金利率的上升,贷款利差下降。这种模式与 Scharfstein 和 Sunderam(2016)一致,他们表明银行在面对上升利率时降低贷款的加价,以缓解贷款需求下降的影响。总之,图 1 表明市场力量在联邦基金利率与银行借贷利率之间产生了差距。此外,这些差距的大小取决于利率水平。
II. Model II. 模型
While this evidence suggests interesting equilibrium interactions between bank market power and monetary policy, it does not reveal any underlying mechanisms behind these patterns in the data. To understand this evidence further, we consider an infinite-horizon bank industry equilibrium model with three sectors: households, firms, and banks. In the model, households and firms solve static discrete-choice problems in which they choose from several saving and financing vehicles. Banks act as intermediaries between households and firms by taking short-term deposits from households and providing long-term loans to firms.1
尽管这些证据表明银行市场力量和货币政策之间存在有趣的均衡互动,但并未揭示这些数据模式背后的任何基本机制。为了进一步理解这些证据,我们考虑一个具有三个部门的无限期银行行业均衡模型:家庭、企业和银行。在这个模型中,家庭和企业解决静态离散选择问题,他们可以从多种储蓄和融资工具中进行选择。银行充当家庭和企业之间的中介,从家庭那里接受短期存款,并向企业提供长期贷款。
The richness of the model lies in the banking sector, as several frictions imply that monetary policy affects the extent of intermediation that banks provide. First, competition in the deposit and loan markets is imperfect, so banks strategically choose deposit and loan rates to maximize profits. Second, banks are subject to regulation. Reserve regulation links the opportunity cost of taking deposits to the prevailing federal funds rate. Capital regulation incentivizes banks to optimize their lending intertemporally, with an eye to preserving excess equity capital as a buffer against future capital inadequacy. Third, access to nondeposit external financing is more costly than taking deposits. This friction implies that shocks to the quantity of deposits are transmitted to the supply of loans, as banks cannot costlessly replace deposits with other borrowing. These frictions are important because, in their absence, banks are simply pass-through entities and bond market interest rates summarize monetary policy.
模型的丰富性在于银行业,因为几个摩擦意味着货币政策影响银行提供中介服务的程度。首先,存款和贷款市场的竞争不完全,因此银行战略性地选择存款和贷款利率以最大化利润。其次,银行受监管。准备金监管将接受存款的机会成本与当前的联邦基金利率联系起来。资本监管激励银行在时间上优化他们的贷款,以保留过剩的股本作为未来资本不足的缓冲。第三,获得非存款外部融资的成本比接受存款更高。这种摩擦意味着存款数量的冲击传导到贷款供应,因为银行无法无成本地用其他借款替代存款。这些摩擦很重要,因为在它们不存在的情况下,银行只是传递实体,债券市场利率总结了货币政策。
A. Households A. 家庭
In our infinite-horizon equilibrium model, at each time t, the economy contains a mass
在我们的无限时间视野均衡模型中,在每个时间 t,经济体包含一个质量
每个家庭都被赋予一美元。家庭将其赋予分配到三种投资选择中:现金、债券和存款。每家银行的存款构成了一种差异化产品。如果我们用 j 来索引每个选项,家庭的选择集由以下给出。
, 选项 0 代表现金,选项
代表短期债券和期权
在我们的无限时间视角均衡模型中,在每个时间 t,经济体包含一群
Each option is characterized by a yield,
家庭选择最佳选项以最大化其效用
家庭按
家庭按
是不可观测的产品层面需求冲击。我们让
代表家庭 i 选择选项 j 时的特定关系冲击
捕捉银行之间的横向差异。例如,如果家庭 i 住在靠近银行 j 的地方,则
家庭按
我们汇总所有家庭的最佳选择,计算每家银行 j 的存款市场份额。采用标准假设,
其中
B. Firms B. 公司
There is a mass K of firms, where we again drop the time subscript. Each firm wants to borrow one dollar, so aggregate borrowing demand is K. Firms can borrow by issuing long-term bonds or by taking out long-term bank loans. We assume that each bank is a differentiated lender, given factors such as geographic location and industry expertise. Letting each option be indexed by j, the firms' choice set is given by
Each of the firm's financing options is characterized by a rate,
公司随后选择最佳选项以最大化其利润
是公司 i 选择选项 j 的利润
对利率的敏感性
遵循均匀分布,均值
对非利率特征的敏感性。
, 由给定
其中
我们汇总所有公司的最佳选择,计算每家银行 j 的贷款市场份额。假设
其中
其中
C. The Banking Sector
C. 银行业
每家银行同时设定其存款利率
Similarly, given each bank j's choice of
同样,鉴于每家银行 j 的选择
公司解决了它们的利润最大化问题,从而得出了从银行借款的数量 j
由方程(9)给出。为简化表示法,我们抑制贷款和存款对相关利率的依赖,简单地表示为
同样,鉴于每家银行 j 的选择
借贷涉及资产和负债之间的到期转换。在资产方面,让
γ是银行的贴现因子。为了简化模型计算,我们假设借款人在第一年末偿还本金的一部分η加上
We assume that in each period, a random fraction of maturing loans,
我们假设在每个时期,到期贷款的随机比例,
,变得拖欠。银行将δ作为其决策问题中的外生状态变量。我们假设银行会注销拖欠的付款,核销金额等于
我们假设在每个时期,到期贷款的随机部分
The rest of the asset side of each bank's balance sheet consists of reserves,
The cost in equation (13) represents an important friction because, in its absence, banks could always raise nonreservable funding to compensate for any deposit shortfalls. The availability of such funding would disconnect banks' deposit-taking and lending decisions, so changes in bank deposits induced by federal funds rate shocks would have no impact on lending.
方程(13)中的成本代表了一种重要的摩擦,因为在没有它的情况下,银行总是可以提高非储备资金来弥补任何存款不足。这种资金的可用性会使银行的存款吸收和放贷决策脱钩,因此由联邦基金利率冲击引起的银行存款变化不会对放贷产生影响。
银行的贷款、政府证券、存款、准备金和不可准备借款的持有量必须满足资产等于负债加权益的标准条件
银行的期初账面净值
在方程(17)中,
在方程(17)中,
模型中的另一个核心摩擦是我们假设银行只能通过留存收益增加其内部股本。因此,没有新的股本发行,这意味着:
这一限制反映了银行的有限责任,因此意味着银行无法提高股本以替代存款或不可储备借款。在第五节中,我们用昂贵的股本发行替换了这一假设,发现对我们的结果影响有限,因为银行的股本发行量很少,而且在扩展模型和数据中都很罕见。
我们模型中的下一个重要成分是监管,即资本要求和准备金要求
方程(20)意味着银行下一期初的账面净值必须不小于总未偿贷款的一部分κ。方程(21)是银行的准备金要求,规定银行必须将其存款的一部分θ存入中央银行的非利息账户中。准备金零利率意味着银行没有动机持有过多准备金,因此方程(21)成立。尽管美联储自 2008 年以来支付准备金利息,但在第四部分,我们展示了对我们模型解决方案的影响有限。
D. Monetary Policy D. 货币政策
Monetary policy affects banks in two ways. First, from equation (13), the federal funds rate affects the marginal funding costs that banks pay in the nonreservable funding market. Second, the short-term federal funds rate affects long rates through expectations. Thus, both long- and short-rate movements affect banks' market power in the deposit and loan markets.
货币政策以两种方式影响银行。首先,根据方程(13),联邦基金利率影响银行在非准备金融市场支付的边际融资成本。其次,短期联邦基金利率通过预期影响长期利率。因此,长期和短期利率的变动都会影响银行在存款和贷款市场的市场力量。
E. Bank's Problem and Equilibrium
E. 银行的问题和平衡
Figure 2 shows the sequence of events in each time period. The bank enters the period and observes both the federal funds rate
如上所述,贷款和存款需求取决于经济中所有银行提供的利率。因此,当每家银行选择其自己的存款和贷款利率,以及不可储备借款和投资政府证券时,它会理性地考虑其他银行在当前和未来时期所做的选择。因此,银行的所有最佳选择都取决于银行业的构成,即银行状态的横截面分布,我们用
在每个时期,观察联邦基金利率后
和违约贷款的随机比例
银行选择最优政策,以最大化预期折现现金股利给股东
We define equilibrium in this economy as follows.
我们将这个经济中的平衡定义如下。
Definition 1.A stationary equilibrium occurs when:
定义 1.当发生静态平衡时:
- 1. All banks solve the problem given by (24), taking as given the other banks' choices of loan and deposit rates.
所有银行解决了(24)给出的问题,假设其他银行的贷款和存款利率已经确定。 - 2. All households and firms maximize their utilities given the list of rates put forth by banks.
所有家庭和企业都会根据银行提出的利率列表来最大化他们的效用。 - 3. In each period, the deposit and loan markets clear.
在每个时期,存款和贷款市场都会达到平衡。 - 4. The probability law governing the evolution of the industry,
, is consistent with banks' optimal choices.
银行问题的一个状态变量(
其中
In solving the model, which we describe in detail in Section I of the Internet Appendix, we ensure that
在解决我们在互联网附录的第一部分中详细描述的模型时,我们确保
与平衡银行选择一致,通过迭代它们的值直至达到收敛。为了检验我们解决方案的准确性,我们将模拟的总存款和贷款利率的演变回归到基于银行信念的感知运动定律上。这些近似值的 R 2 为存款市场超过 95%,贷款市场为 97%。因此,尽管银行没有考虑到完整的分布,
在解决我们在互联网附录的第一部分中详细描述的模型时,我们通过迭代
F. Monetary Policy Transmission in a Static Model
F. 静态模型中的货币政策传导
In this subsection, we use a simplified, static version of the model to highlight the intuition behind the effects of frictions on monetary policy transmission. We assume that both deposits and loans have a maturity of one year, thus precluding a maturity transformation. Because the model is then static, we drop the t subscripts. Banks face no idiosyncratic uncertainty, and their ex ante identical problems produce ex post identical solutions. In addition, all depositors have the same rate sensitivities:
F.1. Frictionless Benchmark
F.1. 无摩擦基准
First, we consider a frictionless benchmark in which the bank has no market power in either the deposit or the loan market, so the deposit and loan demand elasticities are infinite. Moreover, nonreservable borrowing is frictionless, so
In the absence of balance sheet frictions, the bank optimizes its choices of deposits and loans separately. For example, when deposits fall short of loans, a bank can make up any funding shortfall,
在没有资产负债表摩擦的情况下,银行分别优化其存款和贷款选择。例如,当存款不足贷款时,银行可以通过非准备金借款弥补任何资金不足,成本等于联邦基金利率 f,没有额外的融资成本。相反,当存款过剩时,银行可以将任何这种剩余资金投资于政府证券,并赚取联邦基金利率 f。此外,由于竞争是完美的,存款和贷款利率都等于 f。
F.2. Imperfect Competition
F.2. 不完全竞争
Equations (28) and (29) emphasize that markups depend on both rate sensitivities and market concentration. These equations imply that markups rise when the rate sensitivities,
方程(28)和(29)强调标记取决于利率敏感性和市场集中度。这些方程暗示,当利率敏感性上升时,标记会上升。
,绝对值下降。在保持银行业总规模不变的情况下,市场更集中(较低的 J)也会导致更高的标记。请注意,当银行数量趋于无穷大时,市场力量并不会完全消失,因为特异的品味冲击,如
方程(28)和(29)强调标记取决于利率敏感性和市场集中度。这些方程暗示,当利率敏感性
关键是,银行的加价也取决于联邦基金利率,因为后者影响了银行存款和贷款相对于家庭或企业的外部选择的吸引力。为了看到这一点,我们对贷款利差相对于 f 进行导数运算。
其中
接下来,我们推导存款利差和 f 之间的类似关系
国债的市场份额。我们看到,随着联邦基金利率的上升,银行的存款利差也在增加。在存款市场上,联邦基金利率的上升使银行存款相对于持有现金的外部选择更具吸引力,从而使银行能够对其存款收取更高的溢价(例如,Drechsler、Savov 和 Schnabl(2017 年))。
银行市场力量也影响着贷款数量和政策利率之间的关系。在这种简化的情况下,银行贷款的均衡数量仅取决于银行在贷款市场上的利率设定决策,因为如上所述,在没有金融或监管摩擦的情况下,贷款供应与存款数量无关。因此,银行贷款与政策利率之间的关系由以下公式给出:
这是负面的。此外,在贷款市场中,幅度随着利率敏感性增加。
这是负面的。此外,贷款市场
在这种简化的设置中,具有同质存款人利率敏感性,政策利率对银行存款数量的影响是正面的,因为当 f 上升时,家庭会将现金按比例转移到存款和计息资产中
这一结果与 Drechsler、Savov 和 Schnabl(2017 年)以及我们的完整模型中的结果形成鲜明对比,但原因具有启发性。在存款人利率敏感性缺乏异质性的情况下,logit 需求意味着不相关替代品的独立性。这一特性阻止了在我们的静态模型中联邦基金利率与存款之间存在负相关关系,因为当联邦基金利率上升时,这会阻止存款向其他计息资产的强烈替代。
Specifically, with depositor heterogeneity, deposit quantity can fall in response to an increase in the federal funds rate. When depositors are heterogeneous, an increase in the federal funds rate lowers the average yield sensitivity of banks' clientele, as yield-insensitive depositors move disproportionately from cash to deposits, rather than from cash to bonds. In response to the reduction in the average yield sensitivity, banks charge higher deposit spreads, which further drive yield-sensitive clientele to bonds. Overall deposit demand can fall if depositor heterogeneity is sufficiently large to induce a sharp rise in deposit spreads. This force is absent when depositors are homogeneous.
具体而言,随着存款人的异质性,存款数量可能会在联邦基金利率上升时下降。当存款人异质时,联邦基金利率上升会降低银行客户的平均收益敏感性,因为不那么关注收益的存款人会过度地从现金转移到存款,而不是从现金转移到债券。为了应对平均收益敏感性的降低,银行会收取更高的存款利差,进一步推动收益敏感的客户转向债券。如果存款人的异质性足够大以引发存款利差的急剧上升,总体存款需求可能会下降。当存款人是同质的时,这种力量就不存在。
F.3. Balance Sheet Frictions
F.3. 资产负债表摩擦
F.4. Reserve Requirement
F.4. 存款准备金要求
现在考虑这样一种情况,即银行面临储备规定,要求每存款一美元,银行需要将这些存款的一部分θ作为准备金保留。假设准备金的利息为零,银行的优化问题变为
Because the interest rate on reserves is zero, the reserve constraint is binding, and the opportunity cost of holding reserves is
由于准备金利率为零,准备金约束是紧缩的,持有准备金的机会成本是
由于准备金利率为零,准备金约束是紧缩的,持有准备金的机会成本为
F.5. Capital Regulation F.5. 资本监管
接下来,我们假设银行面临的监管要求银行资本超过银行资产的一定比例。在这种情况下,银行的优化问题变为
其中
Equation (36) shows that in the presence of capital regulation, movements in bank capital (
方程(36)显示,在资本监管存在的情况下,银行资本的变动(
方程(36)显示,在资本监管存在的情况下,银行资本(
A final way that monetary policy affects bank capital is through market power. Changes in the federal funds rate affect the attractiveness of bank deposits and loans relative to households' or firms' outside options. As a result, as equations (28) and (29) suggest, the markups that banks can charge on their deposits and loans depend crucially on the federal funds rate, as movements in the federal funds rate affect the profit that banks can generate from the deposit and loan markets. In turn, movements in profits affect the tightness of their capital constraints.
货币政策影响银行资本的最终方式是通过市场力量。联邦基金利率的变化影响了银行存款和贷款相对于家庭或企业的外部选择的吸引力。因此,正如方程(28)和(29)所示,银行可以在其存款和贷款上收取的溢价取决于联邦基金利率,因为联邦基金利率的变动影响了银行可以从存款和贷款市场获得的利润。反过来,利润的变动影响了他们资本约束的紧缩程度。
III. Estimation III. 估计
In this section, we describe our estimation method, present results, and conduct counterfactuals to measure the relative importance of various banking frictions for monetary policy transmission.
在本节中,我们描述了我们的估计方法,呈现了结果,并进行了反事实分析,以衡量各种银行摩擦对货币政策传导的相对重要性。
A. Estimation Procedure A. 估算程序
We estimate the model in two stages. First, we estimate the loan and deposit demand functions. Second, we plug these estimates into the model and use SMD to estimate the remaining parameters that describe banks' balance sheet frictions.
我们分两个阶段估计模型。首先,我们估计贷款和存款需求函数。其次,我们将这些估计值插入模型中,并使用 SMD 来估计描述银行资产负债表摩擦的其余参数。
We estimate deposit and loan demand, given by equations (3) and (8), using the methods in Berry, Levinsohn, and Pakes (1995) (BLP) and Nevo (2001), where the set of bank characteristics used in the demand estimation includes the number of branches, the number of employees per branch, bank, and time fixed effects. We provide a brief outline of our implementation of this procedure below. A detailed explanation is in Section III of the Internet Appendix.
我们估计存款和贷款需求,由方程(3)和(8)给出,使用 Berry、Levinsohn 和 Pakes(1995)(BLP)和 Nevo(2001)中的方法,其中用于需求估计的银行特征集包括分行数量、每个分行的员工数量、银行和时间固定效应。我们在下面简要概述了我们实施这一程序的过程。详细解释请参见互联网附录的第三部分。
We start with the definition of a market. For both our deposit and loan demand estimation, we use the U.S. national market as the market definition, where each year constitutes a separate market. This choice is necessary because data on many types of loans (e.g., commercial and industrial loans) are not available at subnational levels. However, as shown in Section IA.I of the Internet Appendix, our results are robust to estimating deposit demand at the local level.
我们从市场的定义开始。对于我们的存款和贷款需求估计,我们使用美国国家市场作为市场定义,每年构成一个独立的市场。这个选择是必要的,因为许多类型的贷款(例如商业和工业贷款)的数据在次国家级别不可用。然而,正如互联网附录的第 IA.I 节所示,我们在本地水平估计存款需求的结果是稳健的。
A key challenge in identifying demand elasticities is the natural correlation between either deposit or loan rates and any unobservable demand shocks
We need to assume that these supply shifters are orthogonal to unobservable demand shocks and thus shift the supply curve along the demand curve, allowing us to trace out the slope of the demand curve. One assumption that supports but does not guarantee identification is that customers do not care about these costs, holding product characteristics constant. Note that our identification of the demand curve does not use variation in monetary policy. In fact, any aggregate shocks are absorbed by time fixed effects, so our identification strategy avoids a common challenge that studies of monetary transmission face, namely, the endogeneity of monetary policy and aggregate bank credit supply.
我们需要假设这些供应转移者与不可观测的需求冲击正交,从而沿着需求曲线移动供应曲线,使我们能够追踪需求曲线的斜率。支持但不保证识别的一个假设是,顾客不关心这些成本,保持产品特征恒定。请注意,我们对需求曲线的识别不使用货币政策的变化。事实上,任何总量冲击都被时间固定效应吸收,因此我们的识别策略避免了货币传导研究面临的一个常见挑战,即货币政策和总体银行信贷供应的内生性。
从这个需求估计中,我们获得了方程(3)和(8)右侧的拟合值
其中
The final plug-in problem consists of inserting the estimated demand functions described in equations (37) and (38) into the banks' dynamic problem (24). This plug-in problem operationalizes the notion that banks set deposit and loan rates facing the above-specified demand curves for deposits and loans.
最终的插件问题包括将方程(37)和(38)中描述的估计需求函数插入银行的动态问题(24)中。这个插件问题使银行设定存款和贷款利率,面对上述指定的存款和贷款需求曲线。
In the second stage, we estimate seven additional parameters using SMD, which produces parameter estimates that minimize the distance between moments (or functions of moments) generated by the model and their analogs in the data. We use 10 moments to identify the remaining seven-model parameters. Parameter identification in SMD requires choosing moments whose predicted values are sensitive to the model's underlying parameters. Our identification strategy ensures that there is a unique parameter vector that makes the model fit the data as closely as possible.
在第二阶段,我们使用 SMD 估计七个额外参数,这些参数估计最小化模型生成的瞬时(或瞬时函数)与数据中的对应物之间的距离。我们使用 10 个瞬时来识别剩余的七个模型参数。在 SMD 中,参数识别需要选择那些受模型基础参数影响的瞬时。我们的识别策略确保存在一个唯一的参数向量,使得模型与数据的拟合尽可能接近。
First, we use banks' average nonreservable borrowing as a fraction of deposits to identify the cost of holding nonreservables,
首先,我们使用银行平均不可储备借款占存款的比例来确定持有不可储备资产的成本
Next, to identify the relative size of the deposit market
Finally, we include two extra moments that are important for ensuring that our counterfactuals are empirically relevant. To make our model accurately reflect bank valuation, we include banks' average market-to-book ratio. To ensure that our model correctly quantifies baseline monetary transmission from the federal funds rate to bank lending, we include the sensitivity of bank lending to the federal funds rate, again estimated using a VAR. Otherwise, it would be hard to claim that our model provides a sensible decomposition of the various monetary transmission mechanisms.
最后,我们包括了两个额外的重要时刻,以确保我们的反事实是经验相关的。为了使我们的模型准确反映银行估值,我们包括银行的平均市账比。为了确保我们的模型正确量化从联邦基金利率到银行贷款的基准货币传输,我们再次使用 VAR 包括银行贷款对联邦基金利率的敏感性进行估计。否则,很难声称我们的模型提供了各种货币传输机制的明智分解。
B. Baseline Estimation Results
B. 基准估计结果
Table III presents the point estimates for the model parameters. In Panel A, we start with the statutory parameters. We set the corporate tax rate to its statutory rate of 35% and the capital requirement to 6% according to the Basel III accord. According to the Federal Reserve Board's Regulation D, the reserve ratios are 10% for transaction deposits, 1% for saving deposits, and 0% otherwise. In our model, we include only one type of deposit, so our estimate of the reserve ratio is a weighted average of these three requirements, where the weights are the shares of a particular type of deposit in total deposits. We calibrate the number of representative banks to be six, which matches the average county-level banking concentration in the data.
表 III 呈现了模型参数的点估计。在 A 面板中,我们从法定参数开始。我们将企业税率设定为其 35%的法定税率,并根据巴塞尔 III 协议将资本要求设定为 6%。根据美联储理事会的 D 条例,交易存款的准备金比率为 10%,储蓄存款为 1%,其他为 0%。在我们的模型中,我们只包括一种类型的存款,因此我们对准备金比率的估计是这三个要求的加权平均值,其中权重是特定类型存款在总存款中的份额。我们校准代表性银行的数量为六家,这与数据中的平均县级银行集中度相匹配。
表 III. 参数估计
In this table, we report the model parameter estimates. Panel A presents calibrated parameters. Panel B presents values for parameters that can be calculated as simple averages or with simple regression methods. Panel C presents results for parameters estimated via BLP. Panel D presents results for parameters estimated via SMD. Standard errors for the estimated parameters are clustered at the bank level and reported in brackets. 在这个表格中,我们报告了模型参数估计值。面板 A 呈现了校准参数。面板 B 呈现了可以通过简单平均或简单回归方法计算的参数值。面板 C 呈现了通过 BLP 估计的参数结果。面板 D 呈现了通过 SMD 估计的参数结果。估计参数的标准误差在银行水平上进行聚类,并在括号中报告。 |
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Panel A: Calibrated Parameters 面板 A:校准参数 |
|||
Corporate tax rate 企业税率 | 0.35 | ||
θ | The reserve ratio 准备金率 | 0.024 | |
κ | The capital ratio 资本比率 | 0.06 | |
Number of representative banks 代表性银行数量 |
6 |
Panel B: Parameters Estimated Separately 面板 B:分别估计的参数 |
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μ | Average loan maturity 平均贷款期限 | 3.448 | [1.445] |
Log Federal funds rate mean 日志联邦基金利率意味着 |
−4.305 -4.305 | [0.320] | |
Std of Federal funds rate innovation 联邦基金利率创新的标准 |
0.551 | [0.723] | |
Log Federal funds rate persistence 记录联邦基金利率的持续性 |
0.900 | [0.040] | |
Log loan chargeoffs mean 日志贷款核销意味着 |
−5.905 -5.905 | [0.177] | |
Std log loan chargeoffs innovation 标准日志贷款核销创新 |
0.960 | [0.339] | |
Log loan chargeoffs persistence 记录贷款核销的持续性 |
0.600 | [0.055] | |
Corr of Federal funds rate innovation and log loan chargeoffs 联邦基金利率创新和对数贷款核销 |
−0.110 | [0.069] |
Panel C: Parameters Estimated via BLP 面板 C:通过 BLP 估计的参数 |
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Depositors' sensitivity to deposit rates 存款人对存款利率的敏感度 |
0.968 | [0.140] | |
Dispersion of depositors' sensitivity to deposit rates 存款人对存款利率的敏感度分散 |
0.553 | [0.116] | |
Borrowers' sensitivity to loan rates 借款人对贷款利率的敏感度 |
−1.462 -1.462 | [0.292] | |
Convenience of holding deposits 持有存款的便利性 |
3.440 | [0.251] | |
Convenience of holding cash 持有现金的便利性 |
1.985 | [0.242] | |
Convenience of borrowing through loans 贷款借款的便利性 |
1.151 | [1.065] |
Panel D: Parameters Estimated via SMD 面板 D:通过 SMD 估计的参数 |
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---|---|---|---|
γ | Banks' discount rate 银行的贴现率 | 0.048 | [0.007] |
Relative size of the deposit market 存款市场的相对规模 |
0.217 | [0.011] | |
Value of firms' outside option 公司的外部选择的价值 |
−9.631 -9.631 | [0.262] | |
Quadratic cost of nonreservable borrowing 不可预订借款的二次成本 |
0.010 | [0.001] | |
Bank's cost of taking deposits 银行吸收存款的成本 |
0.010 | [0.001] | |
Bank's cost of servicing loans 银行的贷款服务成本 |
0.007 | [0.001] | |
ψ | Net fixed operating cost 净固定运营成本 |
0.027 | [0.006] |
Panel B presents the parameters that we can directly quantify in the data. Specifically, we obtain the means, standard deviations, and autocorrelations of the federal funds rate and the bank-level loan default rate by direct estimation of equation (22). Next, average loan maturity, defined in Table I, is approximately 3.5 years.
面板 B 呈现了我们可以直接在数据中量化的参数。具体来说,我们通过直接估计方程(22)获得了联邦基金利率和银行级贷款违约率的均值、标准差和自相关性。接下来,根据表 I 定义的平均贷款期限约为 3.5 年。
Panel C in Table III provides the demand parameters from the first-stage BLP estimation, with details of the estimation results presented in Table IA.II in Section VI of the Internet Appendix. Not surprisingly, we find that depositors react favorably to high deposit rates, while borrowers react negatively to high loan rates. Both yield sensitivities are precisely estimated, and the economic magnitudes are significant. A 1 percentage point increase in the deposit rate increases a bank's market share by 0.968%, while a 1 percentage point increase in the loan rates decreases its market share by 1.424%. We also find that depositors exhibit significant dispersion in their rate sensitivity. Finally, we estimate depositors' and borrowers' sensitivities to nonrate bank characteristics. The estimates are also both statistically and economically significant. A 1 percentage point increase in the number of branches increases a bank's market share by 0.804% in the deposit market and 0.944% in the loan market. In comparison, the sensitivity to the number of employees per branch is smaller. A 1 percentage point increase in the number of employees per branch increases a bank's market share by 0.714% in the deposit market and 0.630% in the lending market. These estimated yield sensitivities lie close to similar estimates in the literature, with Dick (2008), Ho and Ishii (2011), and Egan, Hortaçsu, and Matvos (2017) finding deposit sensitivity estimates from 0.6 to 1.1. Comparable loan sensitivity estimates can only be found in the mortgage demand literature, which features estimates in the −1.1 to −5.2 range (DeFusco and Paciorek (2017), Buchak et al. (2018)).
表 III 中的面板 C 提供了第一阶段 BLP 估计的需求参数,估计结果的详细信息在互联网附录第 VI 节的表 IA.II 中呈现。毫不奇怪,我们发现存款人对高存款利率做出积极反应,而借款人对高贷款利率做出消极反应。两种收益敏感性都得到了精确估计,经济规模也很显著。存款利率每增加 1 个百分点,银行的市场份额就会增加 0.968%,而贷款利率每增加 1 个百分点,其市场份额就会减少 1.424%。我们还发现,存款人在利率敏感性方面存在显著差异。最后,我们估计存款人和借款人对非利率银行特征的敏感性。这些估计在统计上和经济上都具有显著意义。分行数量每增加 1 个百分点,银行在存款市场的市场份额增加 0.804%,在贷款市场增加 0.944%。相比之下,每个分行员工数量的敏感性较小。每增加 1 个百分点的分行员工数量,银行的市场份额增加 0。存款市场为 714%,贷款市场为 0.630%。这些估计的收益敏感性与文献中的类似估计非常接近,Dick(2008)、Ho 和 Ishii(2011)以及 Egan、Hortaçsu 和 Matvos(2017)发现存款敏感性估计在 0.6 至 1.1 之间。可比较的贷款敏感性估计仅在抵押贷款需求文献中找到,该文献中的估计范围为-1.1 至-5.2(DeFusco 和 Paciorek(2017)、Buchak 等(2018))。
One challenge to identification of this demand estimation is the possibility that when banks face more demand, they hire more higher-quality staff. Conversely, hiring higher-quality staff might spur demand. We confront these concerns in two ways. First, we emphasize that this issue is partially alleviated by the inclusion of bank fixed effects, which absorb the heterogeneity in demand in the cross-section of banks. Similarly, time fixed effects absorb the aggregate shocks to deposit demand. Second, because our instruments may nonetheless be correlated with bank-specific, time-varying unobservable demand shocks, as a robustness check, we also use an instrument from Dick (2008) that is less likely to capture bank-specific labor costs, namely, the weighted average of the local bank teller wages from the Bureau of Labor Statistics (BLS) over the markets in which the bank operates, where the weight is the bank's deposit share in each market relative to its total deposits. This instrument addresses the concern that the Call Report salary data likely contain a quality component that might influence demand. The results from using this instrument are in Tables IA.III and IA.IV in Section VII of the Internet Appendix. We find a deposit sensitivity of 0.668 and a loan sensitivity of −0.950. Both estimates are somewhat smaller than those in Table III, but their relative magnitudes remain intact, even though the sample period for the BLS data runs from only 1997 to 2017. Both estimates are also noisier than those in Table III, with the loan sensitivity being insignificantly different from zero, likely because loan markets are less local in nature than deposit markets. Because of the noise in these estimates, for our baseline analysis, we use the estimates in Table III.
对于这种需求估计的识别的一个挑战是,当银行面临更多需求时,它们会雇佣更多高质量的员工。相反,雇佣高质量的员工可能会刺激需求。我们以两种方式解决这些问题。首先,我们强调通过包含银行固定效应来部分缓解这个问题,这些效应吸收了银行横截面需求的异质性。同样,时间固定效应吸收了存款需求的总体冲击。其次,由于我们的工具可能仍然与银行特定的、随时间变化的不可观测需求冲击相关,作为鲁棒性检验,我们还使用了 Dick(2008)提供的一个工具,这个工具不太可能捕捉到银行特定的劳动成本,即来自劳工统计局(BLS)的当地银行出纳工资的加权平均值,其中权重是银行在每个市场的存款份额相对于其总存款的比例。这个工具解决了 Call Report 薪资数据可能包含可能影响需求的质量成分的担忧。使用这个工具的结果在表 IA.III 和 IA 中。互联网附录第七节中的 IV。我们发现存款敏感度为 0.668,贷款敏感度为-0.950。这两个估计值略小于表 III 中的值,但它们的相对大小保持不变,尽管 BLS 数据的样本期仅从 1997 年到 2017 年。这两个估计值也比表 III 中的估计值更嘈杂,贷款敏感度与零没有显著差异,可能是因为贷款市场的本质不如存款市场那么局部化。由于这些估计值的嘈杂性,我们在基线分析中使用表 III 中的估计值。
Panel D of Table III presents the parameters from our second-stage SMD estimation. We find that banks have a subjective discount rate of 4.8%, which is higher than the average federal funds rate observed in the data. Given the discount rate, banks pay out 3% of their equity value as dividends. Next, the cost of nonreservable borrowing is both statistically and economically significant. At the average level of nonreservable borrowing (30% of total deposits), a marginal dollar of nonreservable borrowing costs a bank 30 basis points (bps) above the cost implied by the prevailing federal funds rate, where we calculate this cost as
表 III 的 D 面板呈现了我们第二阶段 SMD 估计的参数。我们发现银行的主观贴现率为 4.8%,高于数据中观察到的平均联邦基金利率。根据贴现率,银行支付其净资产值的 3%作为股息。接下来,不可准备借款的成本在统计上和经济上都很重要。在不可准备借款的平均水平(总存款的 30%)下,每增加一美元的不可准备借款成本比当前联邦基金利率暗示的成本高出 30 个基点(bps),我们计算这一成本为
表 III 的 D 面板展示了我们第二阶段 SMD 估计的参数。我们发现银行的主观贴现率为 4.8%,高于数据中观察到的平均联邦基金利率。根据贴现率,银行支付其净资产值的 3%作为股息。接下来,不可准备借款的成本在统计上和经济上都很重要。在不可准备借款的平均水平(总存款的 30%)下,每增加一美元的不可准备借款成本比当前联邦基金利率暗示的成本高出 30 个基点(bps),我们计算这个成本为
In Table IV, we compare the empirical and model-implied moments. The model is able to match closely the banks' balance sheet quantities, the spreads they charge, and their valuations. Banks borrow nonreservable securities that amount to 30% of the deposit intake in the data (versus 26% in the model). In both the model and the data, the spreads that banks charge in the deposit market are significantly smaller than those in the loan market. When the federal funds rate is low, as it is in much of our sample, banks face stiffer competition from cash, so they shrink deposit spreads.
在表 IV 中,我们比较了实证和模型暗示的时刻。该模型能够与银行的资产负债表数量、他们收取的利差以及他们的估值紧密匹配。银行借入的不可储备证券占数据中存款收入的 30%(模型中为 26%)。在模型和数据中,银行在存款市场收取的利差明显小于贷款市场的利差。当联邦基金利率低时,正如我们的大部分样本中一样,银行面临来自现金的更激烈竞争,因此他们会缩小存款利差。
表格 IV. 时刻条件
In this table, we report simulated versus actual moments in the SMD estimation, along with t-statistics for the pairwise differences. The dividend yield is defined as dividends over bank equity value; the nonreservable borrowing share is defined as the ratio of nonreservable borrowing to total assets; the sensitivities of total credit and bank loans to the federal funds rate (FFR) are estimated via a vector autoregression. 在这张表中,我们报告了 SMD 估计中模拟与实际时刻的对比,以及成对差异的 t 统计量。 股息收益率定义为股息与银行股本价值之比; 不可预留借款份额定义为不可预留借款与总资产之比; 总信贷和银行贷款对联邦基金利率(FFR)的敏感性通过向量自回归进行估计。 |
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Actual Moment 实际时刻 | Simulated Moment 模拟时刻 | t-statistic t 统计量 | |
Dividend yield 股息率 | 3.38% | 2.87% | −0.856 |
Nonreservable borrowing share 不可预订的借阅份额 |
29.90% | 25.90% | −1.913 -1.913 |
Std of nonreservable borrowing 不可预订借款的标准 |
12.60% | 14.73% | 0.818 |
Deposit spread 存款利差 | 1.29% | 1.32% | 0.328 |
Loan spread 贷款利差 | 2.03% | 2.04% | 0.066 |
Deposit-to-asset ratio 存款资产比率 | 0.699 | 0.737 | 1.034 |
Net noninterest expenses 净非利息支出 |
1.20% | 1.03% | −1.654 -1.654 |
Leverage 利用 | 11.20 | 11.89 | 1.398 |
Market-to-book ratio 市场账面比率 | 2.061 | 1.796 | −1.094 -1.094 |
Credit-FFR sensitivity 信用-FFR 敏感度 | −0.995 -0.995 | −1.008 -1.008 | −0.100 |
Bank loan-FFR sensitivity 银行贷款-FFR 敏感度 |
−1.592 -1.592 | −1.641 -1.641 | −0.129 |
C. External Validity C. 外部有效性
While Table IV provides evidence of model fit, we now proceed to several external model validation exercises. First, in Figure 3, we plot the relation between banks' deposit and loan rates and the federal funds rate, as implied by our model and as calculated from our data, where we accompany the data calculations with a quarterly scatter plot. Note that we do not use these relations in our moment-matching exercise, as we target only the average levels of these rates. Figure 3 shows that the pass-through of the federal funds rate in both the deposit and loan markets is less than one to one, as indicated by the less than unitary slope of the plots. This result is consistent with the message in Table III and Table IA.II in Section VI of the Internet Appendix, as it suggests that banks have significant market power. In addition, our model-predicted deposit and loan rates track the pattern that we see in the actual data, indicating that our model can quantitatively capture banks' pricing of their products in both the deposit and the loan markets.
表 IV 提供了模型拟合的证据,我们现在进行几项外部模型验证练习。首先,在图 3 中,我们绘制了银行存款和贷款利率与联邦基金利率之间的关系,这是根据我们的模型和我们的数据计算得出的,我们将数据计算与季度散点图一起呈现。请注意,我们在矩匹配练习中不使用这些关系,因为我们只针对这些利率的平均水平。图 3 显示,联邦基金利率在存款和贷款市场中的传导小于一比一,这由图中斜率小于单位的趋势所示。这一结果与互联网附录第 VI 节中表 III 和表 IA.II 中的信息一致,表明银行具有重要的市场力量。此外,我们模型预测的存款和贷款利率跟踪了我们在实际数据中看到的模式,表明我们的模型可以定量捕捉银行在存款和贷款市场中定价产品的方式。
Second, we compare our model predictions with the reduced-form evidence in Drechsler, Savov, and Schnabl (2017) on heterogeneity in monetary transmission. In particular, we consider their finding that the sensitivity of deposit spreads to the federal funds rate rises with the local market Herfindahl-Hirschman Index (HHI) by 3 to 4 bps when moving from a local market at the 25th percentile of the HHI distribution to one at the 75th (Drechsler, Savov, and Schnabl, 2017, figure IV). Using the summary statistics in Drechsler, Savov, and Schnabl (2017) and assuming that HHIs are normally distributed, we estimate this interquartile range to be (0.15, 0.34). We find quantitatively similar results in our model when we allow the HHI in our model to vary over this range, with Panel A of Figure 4 showing a fall in the deposit rate sensitivity of 3 bps, which implies that the deposit spread sensitivity rises by 3 bps.
其次,我们将我们的模型预测与 Drechsler、Savov 和 Schnabl(2017 年)关于货币传导中异质性的简化形式证据进行比较。特别是,我们考虑到他们的发现,即存款利差对联邦基金利率的敏感性随着当地市场 Herfindahl-Hirschman 指数(HHI)的增加而提高,当从 HHI 分布的 25%百分位的本地市场移动到 75%时,存款利差对联邦基金利率的敏感性提高了 3 至 4 个基点(Drechsler、Savov 和 Schnabl,2017 年,图 IV)。利用 Drechsler、Savov 和 Schnabl(2017 年)中的摘要统计数据,并假设 HHI 呈正态分布,我们估计这个四分位数范围为(0.15,0.34)。当我们允许我们模型中的 HHI 在这个范围内变化时,我们在我们的模型中发现了类似的定量结果,图 4 的 A 面板显示存款利率敏感性下降了 3 个基点,这意味着存款利差敏感性提高了 3 个基点。
Third, Drechsler, Savov, and Schnabl (2017) find that an increase in the deposit market HHI over its interquartile range accompanies a rise in the sensitivity of deposits to the federal funds rate by 66 bps (Table III). Panel A of Figure 4 shows that in our model, an equivalent increase in the deposit market HHI accompanies a rise the sensitivity of deposits to the federal funds rate by 76 bps, which is close to the estimate in Drechsler, Savov, and Schnabl (2017). Panel A also shows that an increase the HHI over its interquartile range raises the sensitivity of deposits to the federal funds rate by 70 bps.
第三,Drechsler,Savov 和 Schnabl(2017 年)发现,存款市场 HHI 在其四分位范围内的增加伴随着存款对联邦基金利率敏感性的提高 66 个基点(表 III)。图 4 的 A 面板显示,在我们的模型中,存款市场 HHI 的等价增加伴随着存款对联邦基金利率的敏感性提高了 76 个基点,这与 Drechsler,Savov 和 Schnabl(2017 年)的估计接近。A 面板还显示,HHI 在其四分位范围内的增加会使存款对联邦基金利率的敏感性提高 70 个基点。
Fourth, our model also generates the pattern in Drechsler, Savov, and Schnabl (2017, figure IV) whereby even in regions with an extremely low HHI, the sensitivity of the deposit spread to the federal funds rate is still significantly different from zero. Drechsler, Savov, and Schnabl (2017) argue that factors beyond market concentration, such as depositor sophistication, also play a role in determining banks' market power. We find a similar pattern in our estimated model—even when the HHI is 0.1, a 100 bp increase in the federal funds rate leads to only a 80 bp increase in the deposit rate, as the deposit spread increases by 20 bps. Our model generates this result through a relatively large estimate of the yield dispersion,
第四,我们的模型还生成了 Drechsler、Savov 和 Schnabl(2017 年,图 IV)中的模式,即即使在具有极低 HHI 的地区,存款利差对联邦基金利率的敏感性仍明显不为零。Drechsler、Savov 和 Schnabl(2017 年)认为,除了市场集中度之外,存款人的复杂性等因素也在决定银行市场力量方面发挥作用。我们在估计的模型中发现了类似的模式——即使 HHI 为 0.1,联邦基金利率增加 100 个基点只会导致存款利率增加 80 个基点,因为存款利差增加了 20 个基点。我们的模型通过对收益差异的相对较大估计产生了这一结果。高差异意味着即使在市场集中度较低的市场中,相当大比例的存款人对利率不敏感。他们容忍银行收取的更高利差,从而给予银行市场力量。
Fifth, we compare the results in Scharfstein and Sunderam (2016) with predictions from our model. This comparison cannot be quantitative because Scharfstein and Sunderam (2016) examine the mortgage market, while we examine the total loan market. Nonetheless, as shown in Panel B of Figure 4, we find that the sensitivity of the loan spread to the federal funds rate falls in absolute value as the HHI rises, which implies that the transmission of the federal funds rate to lending rates becomes lower when the market becomes more concentrated. Additionally, Panel B shows that an increase in the loan market HII over its interquartile range decreases the sensitivity of loans to the federal funds rate by 82 bps. In comparison, Scharfstein and Sunderam (2016, figure 3) show that the transmission of changes in yields on mortgage-backed securities, which they use as a proxy for banks' cost of funds, is lower in counties with more concentrated loan markets. Panel B also shows that the sensitivity of the quantity of loans to the federal funds rate decreases in absolute value with the model HHI. Scharfstein and Sunderam (2016) show that the sensitivity of mortgage refinancing to the yield on mortgage-backed securities decreases with market concentration. 重试 错误原因
Sixth, we check the external validity of the estimation results in Table IV by ascertaining whether our model can match the impulse responses of several variables not used for estimation. To calculate the VARs in our data, we use the high-frequency monetary shocks (Gertler and Karadi (2015)) as external instruments. Details are in Section V of the Internet Appendix. This high-frequency approach is not possible for our actual estimation because our model is not sufficiently rich to produce these shocks. However, using it in our actual data as an external validity check is informative because the federal funds rate in our model is assumed to be exogenous, so it is natural to compare model impulse responses to well-identified data estimates.
第六,我们通过确认我们的模型是否能够匹配未用于估计的几个变量的冲击响应,来检查表格 IV 中估计结果的外部有效性。为了计算我们数据中的 VARs,我们使用高频货币冲击(Gertler 和 Karadi(2015))作为外部工具。详细信息请参见互联网附录的第五部分。这种高频方法对我们实际的估计来说是不可能的,因为我们的模型不够丰富,无法产生这些冲击。然而,在我们的实际数据中使用它作为外部有效性检查是有意义的,因为我们模型中的联邦基金利率被假定为外生的,因此将模型冲击响应与良好识别的数据估计进行比较是很自然的。
Table V presents the simple VAR coefficients generated by our model, along with the well-identified VAR coefficients estimated from our data. Panels A and B of Table V present the impulses of prices and quantities, respectively, over a two-year horizon. We find that we can closely match the sensitivities between the federal funds rate and both deposit and loan spreads. We also find that in the data, net noninterest expense is insensitive to the federal funds rate, which is also consistent with our model because we model this expense as a constant, so its sensitivity to federal funds rate shocks is zero by definition. Finally, our model generates impulse responses that match their empirical counterparts for other important bank balance sheet variables such as deposits, loans, borrowing, and securities.
表 V 呈现了我们模型生成的简单 VAR 系数,以及从我们的数据估计得出的良好识别的 VAR 系数。表 V 的 A 和 B 面板分别展示了价格和数量在两年内的冲击。我们发现我们可以很好地匹配联邦基金利率与存款和贷款利差之间的敏感性。我们还发现在数据中,净非利息支出对联邦基金利率不敏感,这也与我们的模型一致,因为我们将这笔支出建模为一个常数,因此它对联邦基金利率冲击的敏感性根据定义为零。最后,我们的模型生成的冲击响应与其他重要的银行资产负债表变量(如存款、贷款、借款和证券)的实证对应物相匹配。
表 V. 对货币冲击的额外时刻的敏感性
This table reports the sensitivities of bank deposit spreads, loan spreads, noninterest income, assets, loans, securities, deposits, and borrowing to the federal funds rate. In the second column, we report the sensitivities estimated in the data. The data are from the Call Reports and include all U.S. commercial banks from 1994 to 2008 at a quarterly frequency. We estimate impulse responses to a 1% change in the federal funds rate using the local projections method of Jordà (2005) at an eight-quarter horizon. We instrument the federal funds rate with the unexpected monetary policy shocks constructed from changes in the federal funds futures price on FOMC announcement dates, as in Bernanke and Kuttner (2005). We follow Gertler and Karadi (2015) and English, Van den Heuvel, and Zakrajšek (2018) to sum up the surprises within a quarter to form the instrument. In the third column, we report the sensitivities predicted by the model, which correspond to changes in the variables of interest over a two-year horizon scaled by their respective steady-state levels following a 1% change in the federal funds rate. 这张表报告了银行存款利差、贷款利差、非利息收入、资产、贷款、证券、存款和借款对联邦基金利率的敏感性。在第二列中,我们报告了数据中估计的敏感性。这些数据来自通话报告,包括 1994 年至 2008 年间所有美国商业银行的季度频率。我们使用 Jordà(2005 年)的本地投影方法在八个季度的时间跨度内估计对联邦基金利率 1%变化的冲击响应。我们使用联邦基金利率的意外货币政策冲击来构建工具,这些冲击是根据 FOMC 公告日期上联邦基金期货价格变化而制定的,就像 Bernanke 和 Kuttner(2005 年)所述。我们遵循 Gertler 和 Karadi(2015 年)以及 English、Van den Heuvel 和 Zakrajšek(2018 年)的做法,在一个季度内总结惊喜以形成工具。在第三列中,我们报告了模型预测的敏感性,这些敏感性对应于在一个两年的时间跨度内,根据联邦基金利率 1%变化后,感兴趣变量的变化按其各自稳态水平缩放。 |
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Panel A: Sensitivity of Prices 面板 A:价格敏感度 |
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Empirical 经验主义 | Model | |
Deposit spread 存款利差 | 0.386 | 0.310 |
Loan spread 贷款利差 | −0.024 | −0.011 |
Net noninterest expense 净非利息支出 | −0.001 | 0.000 |
Panel B: Sensitivity of Quantities 面板 B:数量的敏感性 |
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Empirical 经验主义 | Model | |
Deposit 存款 | −2.491 -2.491 | −2.482 -2.482 |
Loan 贷款 | −1.949 -1.949 | −1.641 -1.641 |
Borrowing 借款 | −3.195 -3.195 | −5.335 -5.335 |
Securities 证券 | −1.232 -1.232 | −3.052 -3.052 |
Assets 资产 | −2.587 -2.587 | −2.773 -2.773 |
Finally, we examine how the market value of bank equity reacts to an unexpected federal funds rate shock. In the data, a 1 percentage point increase in the federal funds rate leads to a 1.93% drop in bank equity value. Although our model is not geared to match asset pricing moments, the same magnitude shock generates a 1.44% drop in equity value. This result is important because models without market power can overpredict this response.
最后,我们研究了银行股权的市场价值如何对意外的联邦基金利率冲击做出反应。在数据中,联邦基金利率上涨 1 个百分点导致银行股权价值下降 1.93%。尽管我们的模型不是为了匹配资产定价时刻而设计的,但同等规模的冲击会导致股权价值下降 1.44%。这一结果很重要,因为没有市场力量的模型可能会过度预测这种反应。
This small equity market response occurs in our model because of deposit market power, which makes deposit rates insensitive to the policy rate and thereby implies that deposits effectively have long duration (Drechsler, Savov, and Schnabl (2021)). To emphasize this point, we examine the equity response in our model when we force deposit rates to move one-for-one with the federal funds rate, finding a sharp 11% drop.
这种小规模的股票市场反应发生在我们的模型中,因为存款市场的力量使存款利率对政策利率不敏感,从而意味着存款实际上具有较长的期限(Drechsler、Savov 和 Schnabl(2021 年))。为了强调这一点,我们在模型中检验了存款利率强制与联邦基金利率一一移动时的股票反应,发现股价急剧下跌了 11%。
IV. Counterfactuals IV. 反事实论。
A. Decomposing Monetary Policy Transmission
A. 货币政策传导的分解
We now examine the quantitative forces that shape the relation between aggregate bank lending and monetary policy, as embodied in the federal funds rate. Table VI depicts, for different versions of our model, the percentage change in aggregate bank lending in response to a 1 percentage point change in the federal funds rate over a two-year horizon. We show the results of an experiment in which we start with our model exactly as specified in Section II, with all frictions as estimated in Table III. We then eliminate from the model regulatory constraints and banks' market power one at a time. As such, we analyze how the absence of each of these frictions affects the transmission of monetary policy.
我们现在研究量化力量,塑造了总体银行贷款与货币政策之间的关系,这体现在联邦基金利率中。表 VI 描述了我们模型的不同版本,总体银行贷款在两年内对联邦基金利率变化 1 个百分点的响应百分比变化。我们展示了一个实验的结果,我们从我们在第 II 节中明确规定的模型开始,所有摩擦都在表 III 中估计。然后,我们逐一从模型中消除监管约束和银行市场力量。因此,我们分析了每个摩擦的缺失如何影响货币政策的传导。
表 VI. 货币政策传导的决定因素
This table presents the results of a series of counterfactual experiments in which we examine the effects of removing frictions from our model. The first column lists the frictions that are removed from the model. The second column presents the sensitivity of loans to the federal funds rate (FFR) when the corresponding frictions are removed. The sensitivity captures changes in loans over a two-year horizon scaled by the steady-state loan-level following a 1% change in the federal funds rate. The third column presents the percent change in the sensitivity relative to the baseline case in row (1). All model solutions are under the same set of parameters reported in Table III. 这张表展示了一系列反事实实验的结果,我们在这些实验中研究了从我们的模型中消除摩擦的影响。第一列列出了从模型中移除的摩擦。第二列展示了当相应的摩擦被移除时,贷款对联邦基金利率(FFR)的敏感性。敏感性捕捉了在两年的时间跨度内,贷款在联邦基金利率变化 1%后按稳态贷款水平缩放的变化。第三列展示了相对于基准情况(第 1 行)的敏感性的百分比变化。所有模型解决方案都在表 III 中报告的相同参数集下。 |
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Sensitivity of Loans to FFR 贷款对 FFR 的敏感性 |
Change Relative to Baseline (%) 相对基线的变化(%) |
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(1) | All frictions are present 所有摩擦都存在 |
−1.641 -1.641 | / |
(2) | − Reserve regulation − 保留规定 | −1.499 -1.499 | 8.65% |
(3) | − Capital regulation − 资本监管 | −1.248 -1.248 | 23.91% |
(4) | − Deposit market power - 存款市场力量 |
−1.132 -1.132 | 31.00% |
(5) | − Loan market power 贷款市场力量 |
−1.951 -1.951 | −18.91% |
Row (1) corresponds to the baseline model and shows a response of 1.64%, which is insignificantly different from the response of 1.59% that we find in the data. Row (2) presents the results from a version of the model without the reserve requirement. We find that the sensitivity of bank lending to the federal funds rate decreases by 8.6%. This modest magnitude reflects the small amount of noninterest-bearing reserves held by banks in our sample period.4 As a result, monetary policy has a limited effect on banks' marginal costs of lending through the reserve requirement.
第一行对应基准模型,显示出 1.64%的响应,与我们在数据中发现的 1.59%的响应没有显著差异。第二行展示了一个没有准备金要求版本模型的结果。我们发现银行贷款对联邦基金利率的敏感性下降了 8.6%。这种适度的幅度反映了我们样本期间银行持有的非利息准备金数量较少。因此,货币政策对通过准备金要求影响银行贷款边际成本的效果有限。
This result provides insights into a recent policy debate over interest on excess reserves. In October 2008, the Federal Reserve started paying interest on reserves. This move spawned worry over the power of monetary policy to affect bank lending. For instance, a January 1, 2019 Wall Street Journal article argues that “by paying banks not to lend, the central bank diminished its ability to control interest rates.5” Also, a June 22, 2019 article in the American Banker states that “It was thanks to interest on excess reserves that the Fed ended up stimulating so little in the economy, despite its efforts to ease so much.6” However, we find that this concern is unwarranted, as the bank reserve transmission channel is not important during our sample period. This result is also consistent with Xiao (2020), who shows that the reserve requirement is not a quantitatively important feature that distinguishes commercial banks from shadow banks.
这一结果为最近关于超额准备金利息政策辩论提供了见解。2008 年 10 月,美联储开始支付准备金利息。这一举措引发了对货币政策影响银行贷款能力的担忧。例如,2019 年 1 月 1 日《华尔街日报》的一篇文章指出,“通过支付银行不贷款,央行削弱了其控制利率的能力。”此外,2019 年 6 月 22 日《美国银行家》的一篇文章称,“正是由于超额准备金利息,美联储最终在经济中刺激了如此之少,尽管其努力如此之多。”然而,我们发现这种担忧是没有根据的,因为在我们的样本期间,银行准备金传导渠道并不重要。这一结果也与肖(2020)的研究一致,他表明准备金要求并不是区分商业银行和影子银行的重要特征。
Row (3) in Table VI presents the results from a version of the model that excludes the capital requirement. We find that the presence of the capital requirement enhances monetary policy transmission by 23.9%
表 VI 中的第三行呈现了一个不包括资本要求的模型版本的结果。我们发现,资本要求的存在使货币政策传导增强了 23.9%。
表 VI 中的第(3)行呈现了一个排除资本要求版本的模型的结果。我们发现资本要求的存在使货币政策传导增强了 23.9%。这一结果连接了关于银行资本渠道的两组长期降维证据。第一组显示,货币政策冲击可以触发银行资本的变动,因为银行资产负债表上的到期日不匹配(Flannery 和 James(1984),English,Van den Heuvel 和 Zakrajšek(2018))。第二组显示,银行资本对银行信贷有经济上显著的影响(Peek 和 Rosengren(2000),Mora 和 Logan(2012))。由于银行资本是内生的,这第二组文献经常利用银行资本的外生冲击,而不是直接关注货币政策的作用。我们的论文通过银行资本要求将货币政策与银行信贷联系起来,连接了这两组实证证据。此外,我们测量了这一长期建立的渠道的数量级。
Row (4) of Table VI shows the results from removing banks' deposit market power from the model. In this case, banks receive fixed lump-sum profits equal to their oligopolistic profits in the baseline case. They also use marginal cost pricing for deposit-intake decisions, setting the deposit rate equal to the federal funds rate minus the bank's marginal cost of servicing deposits. They then take as many deposits as depositors offer, given the deposit rate.7 Note that we do not change the parameters governing investors' preferences (the yield sensitivities and dispersion) in this counterfactual analysis. We find that once we eliminate market power in the deposit market, bank lending becomes less sensitive to changes in the federal funds rate. A 1% increase in the federal funds rate causes an almost one-to-one decrease in aggregate lending. This sensitivity is 31%
表 VI 的第四行显示了从模型中移除银行存款市场力量的结果。在这种情况下,银行获得固定的总额利润,等于基准情况下的寡头利润。他们还使用边际成本定价来做存款吸纳决策,将存款利率设定为联邦基金利率减去银行服务存款的边际成本。然后,他们根据存款利率接受存款人提供的存款。请注意,在这种反事实分析中,我们没有改变影响投资者偏好的参数(收益敏感性和离散度)。我们发现,一旦我们消除了存款市场的市场力量,银行贷款对联邦基金利率变化的敏感性降低。联邦基金利率增加 1%几乎会导致总体贷款减少一个单位。这种敏感性为 31%。
表 VI 的第四行显示了从模型中移除银行存款市场权力的结果。在这种情况下,银行获得固定的总额利润,等于基线情况下的寡头利润。他们还使用边际成本定价来做存款吸纳决策,将存款利率设定为联邦基金利率减去银行服务存款的边际成本。然后,他们根据存款利率接受存款人提供的存款。请注意,在这种反事实分析中,我们没有改变规定投资者偏好(收益敏感性和离散度)的参数。我们发现,一旦我们消除了存款市场的市场力量,银行贷款对联邦基金利率变化的敏感性降低。联邦基金利率增加 1%导致总体贷款减少几乎一对一。这种敏感性比基线情况下观察到的 1.641%敏感性小 31%。此外,敏感性的变化比我们消除资本要求时观察到的变化更大。
Intuitively, if deposit market power is in place, when the federal funds rate increases, the households' opportunity cost of holding cash rises, making cash less attractive relative to bank deposits and other interest-bearing assets. Banks react by charging higher deposit spreads, so households substitute into other interest-bearing assets and the equilibrium quantity of deposits falls. This fall in deposits impacts banks' lending decisions because they need to use expensive nonreservable borrowing to finance their loans when the amount of loans exceeds deposits. Thus, bank market power, combined with the nonreservable borrowing cost, contributes to a negative relationship between bank lending and the federal funds rate. Finally, this result is important because it highlights the interconnectedness of banks' deposit-taking and lending businesses. Banks' market power in the deposit market is passed on to the loan market and contributes to the sensitivity of bank lending to the federal funds rate.
直观地说,如果存款市场垄断存在,当联邦基金利率上升时,家庭持有现金的机会成本上升,使现金相对于银行存款和其他计息资产不那么有吸引力。银行会通过提高存款利差来做出反应,因此家庭会转向其他计息资产,存款的均衡数量会下降。存款的下降会影响银行的放贷决策,因为当贷款金额超过存款时,他们需要使用昂贵的非准备金借款来融资贷款。因此,银行市场垄断结合非准备金借款成本,导致银行放贷与联邦基金利率之间存在负相关关系。最后,这一结果很重要,因为它突显了银行的存款吸收和放贷业务之间的相互关联性。银行在存款市场的市场垄断会传导到贷款市场,并导致银行放贷对联邦基金利率的敏感性。
Row (5) of Table VI shows the results from removing banks' lending market power from the model. To isolate the effect of loan market power, we allow banks to retain their oligopolistic market power in the deposit market, but in the loan market, we assume that banks act as price takers. They adopt marginal cost pricing and set their loan rates equal to the funding cost. We find that the presence of banks' loan market power makes the aggregate quantity of loans less sensitive to the federal funds rate, with the sensitivity changing by −18.9%
表 VI 的第五行显示了从模型中移除银行贷款市场权力的结果。为了孤立出贷款市场权力的影响,我们允许银行保留其在存款市场的寡头市场权力,但在贷款市场上,我们假设银行是价格接受者。他们采用边际成本定价,并将贷款利率设定为资金成本。我们发现银行的贷款市场权力存在会使贷款总量对联邦基金利率的敏感性降低,敏感性变化为-18.9%。
表 VI 的第五行显示了从模型中去除银行贷款市场权力的结果。为了孤立出贷款市场权力的影响,我们允许银行保留其在存款市场的寡头市场权力,但在贷款市场上,我们假设银行是价格接受者。他们采用边际成本定价,并将贷款利率设定为资金成本。我们发现银行的贷款市场权力存在时,贷款总量对联邦基金利率的敏感性降低了,敏感性变化为-18.9%。这一结果量化了 Scharfstein 和 Sunderam(2016 年)以及 Corbae 和 Levine(2019 年)的直觉,他们认为并展示了贷款市场权力使银行能够通过减少贷款的加价来缓解货币紧缩对贷款的影响。
In Table IA.VIII in Section X of the Internet Appendix, we present the results of the converse experiment, in which we start with a version of the model without regulatory frictions or market power and then add these frictions back in one at a time. We find that the relative importance of the different channels remains intact, but the quantitative effects of both capital regulation and market power are weaker when we start from the frictionless case, suggesting significant complementarity between the two mechanisms.
在互联网附录的第 X 节的表 IA.VIII 中,我们展示了相反实验的结果,其中我们从一个没有监管摩擦或市场力量的模型版本开始,然后逐一添加这些摩擦。我们发现不同渠道的相对重要性保持不变,但当我们从无摩擦的情况开始时,资本监管和市场力量的定量效应较弱,表明这两种机制之间存在显著的互补性。
Overall, we find that monetary transmission channels based on market power have comparable, if not larger, effects than channels based on regulation. Thus, our findings highlight the importance of accounting for the banking system market structure in assessing monetary transmission mechanisms.
总的来说,我们发现基于市场力量的货币传导渠道的影响与基于监管的渠道相当,甚至更大。因此,我们的研究结果强调了在评估货币传导机制时考虑银行体系市场结构的重要性。
B. Reversal Rate B. 逆转率
Does the sensitivity of lending to the federal funds rate depends on its level? In Panel A of Figure 5, we show the amount of bank lending that corresponds to different levels of the federal funds rate, where we normalize steady-state lending to one. We find that aggregate bank lending in the economy is hump-shaped. When the federal funds rate rises above a certain threshold, a further increase has the usual effect of tightening lending. However, when the rate is below 0.9%, a rate increase actually expands lending. We call this region a reversal-rate environment.
贷款对联邦基金利率的敏感性取决于其水平吗?在图 5 的 A 面板中,我们展示了与不同联邦基金利率水平相对应的银行贷款金额,其中我们将稳态贷款标准化为一。我们发现经济中的总体银行贷款呈驼峰形状。当联邦基金利率上升到某个阈值以上时,进一步增加会导致收紧贷款。然而,当利率低于 0.9%时,利率上升实际上会扩大贷款。我们称这个区域为逆转利率环境。
To understand the mechanism behind the reversal rate, in Panel B, we plot the amount of desired bank lending in a world with no capital requirements, and in Panel C, we plot the level of bank capital. First, we see that desired lending always falls with the federal funds rate. However, the relation between bank equity capital and the federal funds rate is also hump-shaped, with a 2% turning point at which the relation between bank equity and the federal funds rate flips sign.
为了理解逆转率背后的机制,在面板 B 中,我们绘制了在没有资本要求的世界中所需银行贷款的金额,在面板 C 中,我们绘制了银行资本水平。首先,我们看到所需贷款总是随着联邦基金利率下降。然而,银行股本与联邦基金利率之间的关系也是呈驼峰形状的,当银行股本与联邦基金利率之间的关系翻转时,有一个 2%的转折点。
Two properties of the relations shown in Panels B and C underlie the reversal rate. The intuition behind Panel B is straightforward, as high funding costs deter firms from borrowing in equilibrium. The intuition behind Panel C is more nuanced and depends on the relative profitability of lending and deposit taking. First, as the federal funds rate rises, depositors find holding cash to be increasingly costly, so banks face weaker competition from cash in the deposit market. Hence, bank profits from the deposit market rise with the federal funds rate. Second, bank profits from lending decrease with the federal funds rate, as higher funding costs make firms' outside option of not borrowing more appealing. Our parameter estimates imply that the deposit market exerts more pressure on profits than the lending market when the federal funds rate is low. Thus, an increase in the rate leads to higher bank profits, which banks use to bolster their equity capital base. Banks accumulate equity capital instead of paying out their profits to shareholders as a precaution against being capital constrained in the future. In contrast, in a region of high federal funds rates, further rate increases erode bank capital via a standard maturity mismatch argument.
面板 B 和 C 中显示的关系的两个特性构成了逆转率。面板 B 背后的直觉很简单,因为高融资成本阻止了企业在均衡状态下借款。面板 C 背后的直觉更微妙,取决于贷款和存款的相对盈利能力。首先,随着联邦基金利率的上升,存款人发现持有现金成本越来越高,因此银行在存款市场上面对来自现金的竞争较弱。因此,随着联邦基金利率的上升,银行从存款市场获利增加。其次,随着联邦基金利率的上升,银行从贷款中获利减少,因为更高的融资成本使企业不借款的外部选择更具吸引力。我们的参数估计表明,当联邦基金利率较低时,存款市场对利润施加的压力比贷款市场更大。因此,利率上升导致银行利润增加,银行利用这些利润来增强其股本基础。银行积累股本,而不是将利润支付给股东,以防范未来受到资本限制。 相比之下,在联邦基金利率较高的地区,进一步的利率上涨通过标准的到期日不匹配论点侵蚀银行资本。
The reversal rate in Panel A arises because optimal lending is the smaller of two quantities: desired and feasible lending. The former is the optimal amount of lending in the absence of a capital requirement, and the latter is the maximal lending permitted by a bank's equity capital. When the federal funds rate is low, given firms' equilibrium heavy demand for loans in a low-rate environment, desired lending exceeds the amount allowed by the bank's equity. Thus, the capital requirement binds, and actual lending tracks the bank's equity capital, which increases with the federal funds rate. When this rate is high, the capital requirement is slack, and the actual quantity of lending is the desired amount.
面板 A 中的逆转率是因为最优放贷是两个数量中较小的一个:期望放贷和可行放贷。前者是在没有资本要求的情况下放贷的最佳金额,后者是银行股本允许的最大放贷额。当联邦基金利率较低时,鉴于企业在低利率环境中对贷款的均衡需求较大,期望放贷超过银行股本允许的金额。因此,资本要求生效,实际放贷与银行股本保持一致,而后者随着联邦基金利率的增加而增加。当这一利率较高时,资本要求较为宽松,实际放贷量为期望金额。
To bolster the intuition that the reversal rate stems from the interaction of deposit market power and capital regulation, in Panel D of Figure 5, we plot the relation between bank lending and the federal funds rate under the assumption that banks face perfectly elastic demand for deposits when deposits are priced at the federal funds rate minus the banks' marginal cost to service depositors. We find no reversal effect in this setting.
为了加强逆转率源自存款市场力量和资本监管相互作用的直觉,在图 5 的 D 面板中,我们假设银行在存款定价为联邦基金利率减去银行为服务存款人的边际成本时面临完全弹性需求,绘制了银行贷款与联邦基金利率之间的关系。我们发现在这种情况下没有逆转效应。
To understand more fully the dynamic response of bank lending to monetary policy shocks, in Figure 6, we report the simulated response of bank lending to federal funds rate shocks. The economy starts at time 0 in an initial steady state with the federal funds rate equal to the inflection point of 0.9%. At time 1, the federal funds rate either increases to 2% or decreases to 0.1%, and it stays at that level until the economy reaches a new steady state. Each variable in the graph is scaled by its level in the initial steady state.
为了更充分地了解银行贷款对货币政策冲击的动态响应,在图 6 中,我们报告了银行贷款对联邦基金利率冲击的模拟响应。经济体在时间 0 处于初始稳定状态,联邦基金利率等于 0.9%的拐点。在时间 1,联邦基金利率要么上升到 2%,要么下降到 0.1%,并保持在该水平直到经济达到新的稳定状态。图中的每个变量都按其在初始稳定状态中的水平进行缩放。
Panel A of Figure 6 depicts the response to an increase in the federal funds rate. In this case, banks face less competition from household demand for cash in the deposit market. Thus, they behave more like monopolists by charging higher spreads, which, in turn, lower household deposit demand. Lower deposit intake increases the need for banks to fund their lending by turning to the market for nonreservable borrowing, which carries increasing marginal costs. A positive federal funds rate shock also increases the cost of capital in the corporate sector, making firms more likely to switch to the outside option of not borrowing. Both effects shrink lending. Because deposits have shorter duration than loans, deposits drop sharply and converge almost instantaneously to the new steady state. In contrast, loan quantity converges slowly as the bank replaces only a fraction, η, of its long-term loans in each period. Nonreservable borrowing increases to fill the gap between deposits and loans.
图 6 的 A 面板描述了对联邦基金利率上升的反应。在这种情况下,银行在存款市场上面临来自家庭现金需求的竞争减少。因此,它们更像垄断者,通过收取更高的利差来行事,进而降低家庭存款需求。存款减少增加了银行通过向市场寻求不可储备借款来融资贷款的需求,这带来逐渐增加的边际成本。正的联邦基金利率冲击也增加了企业部门的资本成本,使企业更有可能转向不借款的外部选择。这两种效应都会减少贷款。由于存款的期限比贷款短,存款急剧下降,几乎瞬间收敛到新的稳态。相比之下,贷款数量的收敛速度较慢,因为银行每期只替换长期贷款的一部分η。不可储备借款增加以填补存款和贷款之间的差距。
Panel B of Figure 6 depicts the responses to a decrease in the federal funds rate. On the one hand, when this rate decreases, banks profit from having a maturity mismatch on their balance sheets as the rates they pay on short-term liabilities decrease instantly, while most of their long-term assets keep generating higher rates of return. This effect diminishes gradually over time as existing loans mature and are repriced. On the other hand, a lower federal funds rate leads to increasingly intense competition from cash in the deposit market. The effect is especially strong as the federal funds rate approaches the zero lower bound, in which case the spreads that banks can charge in the deposit market are squeezed, leading to a sharp drop in their profits. Given the persistence of the federal funds rate, lower profits translate into slower retained earnings accumulation and, in turn, lower bank capital. In the new steady state, banks take more deposits, which can support increased lending. Indeed, lending increases in the first year. However, banks cannot sustain this higher level of lending, as their capital requirements tighten when the federal funds rate is extremely low. Because total lending decreases, banks need less external financing and thus less nonreservable borrowing.
图 6 的 B 面板描述了联邦基金利率下降的反应。一方面,当这一利率下降时,银行从其资产负债表上的到期不匹配中获利,因为他们支付的短期负债利率立即下降,而大部分长期资产继续产生较高的回报率。随着现有贷款到期和重新定价,这种效应会随时间逐渐减弱。另一方面,较低的联邦基金利率导致存款市场现金竞争日益激烈。当联邦基金利率接近零下限时,这种效应尤为强烈,此时银行在存款市场可以收取的利差被挤压,导致利润急剧下降。鉴于联邦基金利率的持续性,较低的利润转化为较慢的留存收益积累,进而导致较低的银行资本。在新的稳定状态下,银行吸收更多存款,这可以支持增加的贷款。事实上,贷款在第一年增加。然而,当联邦基金利率极低时,银行无法维持这种更高水平的贷款,因为其资本要求会收紧。 由于总贷款减少,银行需要更少的外部融资,因此非储备借款也减少。
Note that in Figure 6, lending falls when the federal funds rate changes in either direction. Although lending moves in the same direction, the driving force differs in the two cases. When the federal funds rate increases, loans fall because higher spreads in the deposit market discourage households from making deposits. Banks turn to nonreservable borrowing to fund loans, and because of increasing costs in this market, the amount of lending is highly dependent on the quantity of deposits. Instead, when the federal funds rate decreases, the loan amount decreases because of the binding capital requirement, which, in turn, echoes changes in the banks' profit accumulation.
请注意,在图 6 中,当联邦基金利率朝任何方向变化时,贷款都会下降。尽管贷款的走向相同,但两种情况的推动力不同。当联邦基金利率上升时,贷款下降,因为存款市场的较高利差阻止家庭存款。银行转向非准备金借款来资助贷款,由于这一市场成本增加,贷款金额高度依赖存款数量。相反,当联邦基金利率下降时,贷款金额减少,因为资本要求的约束,进而影响银行利润积累的变化。
This discussion highlights two differences between the reversal rate in our model and the reversal rate in Brunnermeier and Koby (2016). First, they assume an exogenous relation between the deposit rate and the federal funds rate,
本讨论突出了我们模型中的逆转率与 Brunnermeier 和 Koby(2016)中逆转率之间的两个差异。首先,他们假设存款利率与联邦基金利率之间存在外生关系。
本讨论突出了我们模型中的逆转率与 Brunnermeier 和 Koby(2016 年)中的逆转率之间的两个差异。首先,他们假设存款利率与联邦基金利率之间存在外生关系,
The reversal-rate result is informative about the sluggish recovery of bank lending in the United States since the 2008 financial crisis. By the end of 2018, cumulative bank lending had increased only about 25% from its low in August 2009. In contrast, from trough to peak, in all recessions since 1974, bank lending grew by 60% to 120%. Although many factors such as banking regulation may have contributed to this slow recovery, the ultra-low rate policy could be an important factor.
逆转率的结果对于自 2008 年金融危机以来美国银行贷款复苏缓慢的情况提供了信息。到 2018 年底,累计银行贷款仅从 2009 年 8 月的低点增长了约 25%。相比之下,自 1974 年以来的所有衰退期间,银行贷款从低点到高点增长了 60%至 120%。尽管许多因素,如银行监管,可能导致了这种缓慢的复苏,但超低利率政策可能是一个重要因素。
C. External Validation C. 外部验证
We check external validation of the reversal-rate prediction in two ways. First, we estimate a reduced-form regression to examine the relation between bank equity returns and monetary policy news on Federal Open Market Committee (FOMC) meeting days. We measure monetary policy news released during FOMC meetings as changes in the two-year Treasury yield on FOMC meeting days, following Hanson and Stein (2015). The advantage of examining the two-year Treasury yield instead of the federal funds rate is that the former captures the effects of “forward guidance” in FOMC announcements, which has become increasingly important in recent years (Hanson and Stein (2015)).8 The identifying assumption is that unexpected changes in interest rates in a one-day window surrounding scheduled Federal Reserve announcements arise largely from news about monetary policy because macroeconomic fundamentals would not change discretely within such a short window. While our sample period runs from 1994 to 2017, we exclude the dot-com bubble collapse (2000 to 2001) and the financial crisis (2007 to 2009) because, in these crisis times, information other than conventional monetary policy news could also be released in FOMC meetings.9
我们以两种方式检查反转率预测的外部验证。首先,我们估计一个简化形式的回归,以检验银行股权回报与联邦公开市场委员会(FOMC)会议日货币政策新闻之间的关系。我们将 FOMC 会议期间发布的货币政策新闻测量为 FOMC 会议日两年期国债收益率的变化,这是根据 Hanson 和 Stein(2015)的方法。检查两年期国债收益率而不是联邦基金利率的优势在于前者捕捉了 FOMC 公告中“前瞻指导”的影响,这在近年来变得越来越重要(Hanson 和 Stein(2015))。确定性假设是,围绕预定的美联储公告的一天窗口内利率的意外变化主要源自有关货币政策的新闻,因为宏观经济基本面不会在如此短的时间窗口内离散变化。 尽管我们的样本期从 1994 年到 2017 年,但我们排除了互联网泡沫破裂(2000 年至 2001 年)和金融危机(2007 年至 2009 年),因为在这些危机时期,除了传统货币政策新闻之外,FOMC 会议上也可能发布其他信息。 9
Because Panel C of Figure 5 shows that the relation between bank capital and the federal funds rate changes sign around 2%, we split our data sample using a 2% cutoff for the federal funds rate. In Table VII, we report the regression estimates. As shown in column (1), when rates are high, interest rates and returns are negatively related. However, this conventional negative relation reverses sign in a low-rate environment. As shown in column (2), a rate increase is associated with a positive significant bank equity return, consistent with market expectations that an increase in rates will lead to an increase in bank capital. This result is not driven by a steepening of the term structure, as we control for changes in term spreads. As shown in Figure 7, the contrast between the results in columns (1) and (2) can be seen in a simple scatter plot of bank industry excess returns against monetary policy shocks on FOMC days. To examine the statistical significance of the difference between columns (1) and (2), in column (3), we report results from a regression in which we pool all sample observations and include a term for the interaction between the monetary policy shock and a dummy for a low federal funds rate. We find a highly significant positive coefficient on this interaction term, which is consistent with a strong reversal effect. In summary, we find that monetary policy has a nonmonotonic effect on bank capital. When the federal funds rate is high, the relation between the short-term rates and bank capital is negative, but when this rate is low, the relation is positive.
因为图 5 的 C 面板显示,银行资本与联邦基金利率之间的关系在 2%左右发生了变化,我们使用 2%的联邦基金利率作为分割点来分割我们的数据样本。在第七表中,我们报告了回归估计结果。如第(1)列所示,当利率较高时,利率和回报呈负相关。然而,在低利率环境中,这种传统的负相关关系会发生变化。如第(2)列所示,利率上升与银行股本回报显著正相关,与市场预期一致,即利率上升将导致银行资本增加。这一结果不是由于期限结构的陡峭化所驱动的,因为我们控制了期限利差的变化。如图 7 所示,银行业超额回报与 FOMC 日货币政策冲击的简单散点图中,第(1)列和第(2)列结果之间的对比可以看出。 为了检验列(1)和(2)之间的差异的统计显著性,在列(3)中,我们报告了一个回归的结果,其中我们汇总了所有样本观测值,并包括一个与货币政策冲击和低联邦基金利率虚拟变量之间的交互项。我们发现这个交互项上有一个高度显著的正系数,这与强烈的逆转效应一致。总之,我们发现货币政策对银行资本有非单调效应。当联邦基金利率较高时,短期利率与银行资本之间的关系是负向的,但当这个利率较低时,关系是正向的。
表 VII.货币政策冲击和 FOMC 日银行股权回报
In this table, we report the estimates of the relation between bank equity returns and monetary policy shocks on FOMC days. Monetary policy shocks are measured as one-day changes in the two-year Treasury yield on FOMC days. HHI is the Herfindahl-Hirschman Index for the local deposit market in which a bank operates. Low is a dummy variable that equals 1 when the starting level of the federal funds rate (FFR) is below 2%. The control variables include market returns and term spreads. The sample includes all publicly traded U.S. banks from 1994 to 2017. The sample for columns (1) and (4) comprises observations in which the starting level of the federal funds rate (FFR) is above 2%. The sample for columns (2) and (5) comprises observations in which the starting level of the federal funds rate is below 2%. The sample for columns (3) and (6) comprises all observations. We exclude observations during the collapse of the dot-com bubble (2000 to 2001) and the subprime financial crisis (2007 to 2009). Standard errors are clustered by time. 在这张表中,我们报告了银行股权回报与 FOMC 日货币政策冲击之间关系的估计值。货币政策冲击被定义为 FOMC 日两年期国债收益率的一日变化。HHI 是银行所在地存款市场的 Herfindahl-Hirschman 指数。Low 是一个虚拟变量,当联邦基金利率(FFR)的起始水平低于 2%时等于 1。控制变量包括市场回报和期限利差。样本包括 1994 年至 2017 年间所有在美国上市的银行。第(1)和(4)列的样本包括联邦基金利率(FFR)起始水平高于 2%的观察值。第(2)和(5)列的样本包括联邦基金利率起始水平低于 2%的观察值。第(3)和(6)列的样本包括所有观察值。我们排除了互联网泡沫破裂期间(2000 年至 2001 年)和次级房贷危机期间(2007 年至 2009 年)的观察值。标准误差按时间聚类。 |
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High 高 | Low 低 | All 全部 | High 高 | Low 低 | All 全部 | |
(1) | (2) | (3) | (4) | (5) | (6) | |
Policy shock 政策冲击 | −1.292** | 2.202** | −1.292** -1.292 ** | −0.639 -0.639 | −1.393 -1.393 | −0.639 -0.639 |
[0.615] | [0.879] | [0.612] | [0.653] | [0.852] | [0.649] | |
Low*Policy shock 低*政策冲击 | 3.494*** | −0.754 | ||||
[1.069] | [1.069] | |||||
HHI*Policy shock | −0.134 | 0.562*** | −0.134 | |||
[0.145] | [0.153] | [0.144] | ||||
Low*HHI*Policy shock | 0.696*** | |||||
[0.210] | ||||||
Control | Yes | Yes | Yes | Yes | Yes | Yes |
Observations | 27,257 | 33,805 | 61,062 | 27,257 | 33,805 | 61,062 |
Adj. R2 | 0.015 | 0.123 | 0.074 | 0.016 | 0.125 | 0.075 |
In columns (4) and (5) of Table VII, we report the results of interacting changes in the federal funds rate with the HHI of the local deposit market (county) in which a bank operates. If a bank operates in several counties, the bank-level HHI is the weighted average of local HHIs, weighted by the deposits of the bank in each county. We find that in a low-rate environment, banks with greater deposit market power experience higher positive returns. Moreover, this evidence that the reversal effect is closely linked to banks' deposit market power is reinforced by the finding in column (6) that the triple interaction between the low federal funds rate dummy, the HHI, and the policy shock is significantly positive.
在表 VII 的第(4)和(5)列中,我们报告了联邦基金利率变化与银行所在地区(县)本地存款市场 HHI 的交互作用结果。如果一家银行在多个县运营,那么银行级别的 HHI 是本地 HHI 的加权平均值,按照银行在每个县的存款加权计算。我们发现,在低利率环境下,具有更大存款市场力量的银行经历更高的正回报。此外,第(6)列的发现进一步证实了逆转效应与银行存款市场力量密切相关,即低联邦基金利率虚拟变量、HHI 和政策冲击之间的三重交互作用显著为正。
Next, we explore whether the positive relation between monetary policy shocks and bank stock returns during low-rate environments is driven by the central bank's economic outlook (Nakamura and Steinsson (2018)). In Section VIII of the Internet Appendix, we present returns for all 49 Fama-French industries. We find that the banking industry is the only industry exhibiting a switch from a negative to a positive interest sensitivity in the low-interest environment. Furthermore, we use an alternative measure of monetary policy shocks constructed by Jarocinski and Karadi (2020), who disentangle the potential information shocks from monetary policy shocks. Our results are robust to this alternative measure.
接下来,我们探讨货币政策冲击与低利率环境下银行股票回报之间的正相关关系是否受到中央银行的经济展望的影响(Nakamura 和 Steinsson(2018))。在互联网附录的第八部分,我们展示了所有 49 个法玛-法国行业的回报。我们发现银行业是唯一一个在低利率环境中从负利率敏感性转变为正利率敏感性的行业。此外,我们使用了由 Jarocinski 和 Karadi(2020)构建的另一种货币政策冲击的替代衡量方法,他们将潜在信息冲击与货币政策冲击分开。我们的结果对这种替代衡量方法具有稳健性。
对于我们的第二次外部验证练习,我们进行了一项差异分析,比较了在政策利率进入逆转区域时具有不同存款市场力量的银行。根据 Heider、Saidi 和 Schepens(2019)的研究,我们估计
在季度中是银行贷款或银行资本
是银行运营的本地存款市场的 HHI
是一个虚拟变量,当联邦基金利率低于 2%时等于 1。控制变量向量,
包括存款和贷款利率,以及记录银行资产、贷款、存款和股本。我们将银行和时间固定效应表示为
其中
The results are in Table VIII. Columns (1) and (2) show the effects of low interest rates on bank equity, and columns (3) and (4) show the effects of low interest rates on bank lending. Consistent with our model predictions, book equity and lending decrease more for high-HHI banks than for low-HHI banks when the federal funds rate falls into the reversal region.
结果见表 VIII。列(1)和(2)显示低利率对银行股本的影响,列(3)和(4)显示低利率对银行贷款的影响。与我们模型的预测一致,当联邦基金利率降至逆转区间时,高 HHI 银行的账面股本和贷款减少幅度大于低 HHI 银行。
表 VIII. 低利率对具有不同存款市场影响力的银行的影响
We report the estimates of the effect of low interest rates on banks with different deposit market power. HHI is the average Herfindahl-Hirschman Index of the local deposit markets in which a bank operates. Low is a dummy variable that equals 1 when the federal funds rate is below 2%. Each column is identified by the dependent variable. The control variables include lagged assets, lending, deposits, equity, deposit rate, loan rate, bank fixed effects, and time fixed effects. The sample includes all U.S. banks from 2000Q1 to 2004Q1. Standard errors are clustered by time. 我们报告了低利率对具有不同存款市场力量的银行的影响估计。 HHI 是银行运营的当地存款市场的平均赫芬达尔-赫希曼指数。当联邦基金利率低于 2%时,Low 是一个虚拟变量,等于 1。每列由因变量标识。控制变量包括滞后资产、贷款、存款、股本、存款利率、贷款利率、银行固定效应和时间固定效应。样本包括 2000 年第一季度至 2004 年第一季度的所有美国银行。标准误差按时间聚类。 |
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Equity 股权 | Equity 股权 | Loan 贷款 | Loan 贷款 | |
(1) | (2) | (3) | (4) | |
HHI*Low HHI*低 | ||||
(0.007) | (0.006) | (0.008) | (0.006) | |
Control 控制 | No 不 | Yes 是的 | No 不 | Yes 是的 |
Bank F.E. 银行 F.E. | Yes 是的 | Yes 是的 | Yes 是的 | Yes 是的 |
Time F.E. 时间 F.E. | Yes 是的 | Yes 是的 | Yes 是的 | Yes 是的 |
Observations 观察 | 129,950 | 127,912 | 129,339 | 127,885 |
Adj. R2 形容词 R 2 | 0.984 | 0.990 | 0.981 | 0.990 |
V. Extensions and Robustness
V. 扩展和鲁棒性
A. Heterogeneous Transmission through Large and Small Banks
大型和小型银行之间的异质传输
We extend our analysis by examining whether monetary transmission depends on bank size, motivated by the finding in Kashyap and Stein (1995) that monetary policy particularly affects lending by small banks, as they cannot replace deposits with frictionless access to nonreservable funding. However, one limitation of the data they use is the absence of a measure of the actual cost of external finance. While they use bank size as a proxy for this cost, size is correlated with many other bank attributes, whose presence compromises the interpretation of their results. For instance, small banks tend to lend to small firms, whose credit demand is more cyclical. Therefore, the higher sensitivity of smaller bank lending might be driven by demand rather than by financing frictions on the supply side.
我们通过检查货币传导是否取决于银行规模来扩展我们的分析,这是受 Kashyap 和 Stein(1995 年)的发现启发的,即货币政策特别影响小银行的贷款,因为它们无法用无摩擦访问不可储备资金来替代存款。然而,他们使用的数据的一个局限性是缺乏外部融资实际成本的衡量标准。虽然他们使用银行规模作为这一成本的代理,但规模与许多其他银行属性相关,这些属性的存在损害了他们结果的解释。例如,小银行倾向于向小企业贷款,这些企业的信贷需求更具周期性。因此,较小银行贷款的更高敏感性可能是由需求驱动而不是由供给方面的融资摩擦驱动。
To explore this issue, we split our sample at the 10th percentile of the bank size distribution and estimate a subset of the model parameters separately for the large and small banks. For these estimations, we hold constant across subsamples parameters describing household preferences and macroeconomic conditions. We also fix the banks' discount rate because we cannot identify it in the small-bank sample. Identification using dividend yields is infeasible because many small banks do not report dividends. Also, many small banks are private, so we cannot calculate their market-to-book ratios. We reestimate all of the remaining parameters.
为了探讨这个问题,我们将样本分为银行规模分布的 10%分位数,并分别为大型银行和小型银行估计模型参数的子集。对于这些估计,我们在子样本中保持不变描述家庭偏好和宏观经济状况的参数。我们还固定银行的折现率,因为我们无法在小银行样本中确定它。使用股息收益率进行识别是不可行的,因为许多小银行不报告股息。此外,许多小银行是私人的,因此我们无法计算它们的市净率。我们重新估计所有其余参数。
The results are in Table IX. We find that both external financing costs
结果见表 IX。我们发现外部融资成本都有。
固定运营成本ψ对小银行来说更大。这一结果令人震惊,因为我们没有将银行规模作为识别时刻。
结果见表 IX。我们发现,小银行的外部融资成本
表九。大银行与小银行
In this table, we report SMD estimation results for subsamples of large and small banks. Panel A contains the simulated versus actual moments, along with t-statistics for the pairwise differences. In Panel B, we report the parameter estimates. 在这个表格中,我们报告了大型和小型银行子样本的 SMD 估计结果。面板 A 包含模拟与实际时刻,以及成对差异的 t 统计量。在面板 B 中,我们报告参数估计。 银行吸收存款和服务贷款的边际成本分别为ψ是净固定运营成本 在这个表格中,我们报告了大型和小型银行子样本的 SMD 估计结果。面板 A 包含模拟与实际时刻,以及成对差异的 t 统计量。在面板 B 中,我们报告参数估计。 |
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---|---|---|---|---|---|---|
Panel A: Moment Conditions 面板 A:瞬时条件 |
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Large Banks 大型银行 | Small Banks 小银行 | |||||
Actual 实际 | Simulated 模拟 | t-statistic t 统计量 | Actual 实际 | Simulated 模拟 | t-statistic t 统计量 | |
Dividends 股息 | 3.60% | 2.89% | −3.568 | / | / | / |
Nonreservable borrowing share 不可预订的借阅份额 |
35.50% | 36.66% | 0.612 | 15.30% | 16.09% | 1.574 |
Std of nonreservable borrowing | 13.30% | 19.86% | 2.626 | 8.70% | 10.83% | 2.363 |
Deposit spread | 1.32% | 1.37% | 0.520 | 1.25% | 1.26% | 0.130 |
Loan spread | 1.77% | 1.98% | 2.068 | 2.71% | 2.42% | −2.979 |
Deposit-to-asset ratio | 0.666 | 0.688 | 0.692 | 0.784 | 0.779 | −0.382 |
Net noninterest expense | 0.96% | 0.85% | −1.117 | 1.90% | 1.76% | −1.436 |
Leverage | 11.36 | 12.54 | 2.026 | 10.78 | 10.03 | −3.796 |
Market-to-book ratio | 2.06 | 1.97 | −1.217 | / | / | / |
Total credit-FFR sensitivity | −0.995 | −0.998 | −0.010 | −0.995 | −1.027 | −0.108 |
Panel B: Parameter Estimates 面板 B:参数估计 |
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---|---|---|---|---|---|---|
ψ | Sensitivity of Loans to FFR 贷款对 FFR 的敏感性 |
|||||
Large banks 大型银行 | 0.006 | 0.010 | 0.006 | 0.013 | 0.228 | −1.235 -1.235 |
[0.001] | [0.001] | [0.001] | [0.003] | [0.007] | ||
Small banks 小银行 | 0.015 | 0.008 | 0.009 | 0.075 | 0.140 | −1.742 -1.742 |
[0.001] | [0.001] | [0.001] | [0.002] | [0.001] |
Next, we examine how the sensitivity of lending to the federal funds rate depends on the frictions embodied in
接下来,我们将研究贷款对联邦基金利率的敏感性如何取决于体现在其中的摩擦
如果我们增加大银行的融资成本
对于小银行估计的水平(0.015),大银行贷款对联邦基金利率的敏感性上升至-1.471,这一增加代表了大银行和小银行贷款敏感性差异的 47%。因为我们只允许五个参数在大银行和小银行之间有所不同,我们有效地保持了贷款需求恒定,从而隔离了金融摩擦的影响。这一结果与 Kashyap 和 Stein(1995)的假设一致,即大银行和小银行具有不同的外部融资成本,导致货币政策传导到信贷供应的差异。固定运营成本ψ也有助于较小银行之间更强的货币传导。小银行相对缺乏非利息收入来源,因此其净运营成本较高,并且积累资本缓冲较慢。因此,当利率上涨通过到期不匹配侵蚀银行资本时,这种影响对小银行的打击更为严重,导致贷款减少更为明显。
B. Changes in Transmission over Time
B. 随时间传输的变化
In this subsection, we examine how the impact of monetary policy on bank lending has changed over time. For example, in the past few decades, the average interest rate has declined substantially, and the banking industry itself has experienced a large volume of mergers, leading to increased concentration. To this end, we split our sample into two subperiods—early (1994 to 2005) and late (2006 to 2017). We then reestimate all model parameters for the two subperiods.10 The parameter estimates in Table X imply that the sensitivity of lending to the federal funds rate has declined from 1.53% to 1.22% over time. This result is consistent with evidence in the literature that monetary policy has had more muted effects on real activity and inflation in recent decades (Boivin, Kiley, and Mishkin (2010)).
在本小节中,我们将研究货币政策对银行信贷的影响随时间的变化。例如,在过去几十年中,平均利率大幅下降,银行业本身经历了大量的合并,导致集中度增加。为此,我们将样本分为两个子时期——早期(1994 年至 2005 年)和晚期(2006 年至 2017 年)。然后重新估计两个子时期的所有模型参数。表 X 中的参数估计表明,信贷对联邦基金利率的敏感性已经从 1.53%下降到 1.22%。这一结果与文献中的证据一致,即近几十年来货币政策对实际活动和通胀的影响效果较弱(Boivin,Kiley 和 Mishkin(2010 年))。
表 X. 子样本估计值:早期与晚期
In this table, we report the model parameter estimates for the early (1994 to 2005) and late (2006 to 2017) subsamples. Panel A presents calibrated parameters. Panel B presents values for parameters that can be calculated as simple averages or with simple regression methods. Panel C presents results for parameters estimated via BLP. Panel D presents results for parameters estimated via SMD. Standard errors for the estimated parameters are clustered at the bank level and reported in brackets. 在这个表格中,我们报告了早期(1994 年至 2005 年)和晚期(2006 年至 2017 年)子样本的模型参数估计值。面板 A 呈现了校准参数。面板 B 呈现了可以通过简单平均或简单回归方法计算的参数值。面板 C 呈现了通过 BLP 估计的参数结果。面板 D 呈现了通过 SMD 估计的参数结果。估计参数的标准误差在银行水平上进行聚类,并在括号中报告。 |
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Early Subsample 早期子样 | Late Subsample 晚期子样本 | ||||
Panel A: Calibrated Parameters 面板 A:校准参数 |
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Corporate tax rate 企业税率 | 0.350 | 0.350 | |||
θ | The reserve ratio 准备金率 | 0.028 | 0.022 | ||
κ | The capital ratio 资本比率 | 0.060 | 0.060 | ||
Number of representative banks 代表性银行数量 |
7 | 5 |
Panel B: Parameters Estimated Separately 面板 B:分别估计的参数 |
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μ | Average loan maturity 平均贷款期限 | 3.170 | [1.402] | 3.590 | [1.448] |
Log Federal funds rate mean 日志联邦基金利率意味着 |
−3.305 -3.305 | [0.170] | −5.605 -5.605 | [0.416] | |
Std of log federal funds rate innovation 联邦基金利率创新的标准 |
0.553 | [0.148] | 0.516 | [0.885] | |
Log Federal funds rate persistence 记录联邦基金利率的持续性 |
0.700 | [0.141] | 0.900 | [0.111] | |
Log Loan chargeoffs mean 日志贷款核销意味着 |
−6.005 -6.005 | [0.163] | −5.806 | [0.258] | |
Std of log loan chargeoffs innovation 标准的日志贷款核销创新 |
0.800 | [0.255] | 1.040 | [0.383] | |
Log Loan chargeoffs persistence 日志贷款核销持久性 |
0.600 | [0.060] | 0.600 | [0.068] | |
Corr of federal funds rate innovation and chargeoffs 联邦基金利率创新和核销 |
0.040 | [0.435] | −0.160 | [0.159] |
Panel C: Parameters Estimated via BLP 面板 C:通过 BLP 估计的参数 |
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Depositors' sensitivity to deposit rates 存款人对存款利率的敏感度 |
0.743 | [0.165] | 0.925 | [0.399] | |
Dispersion of depositors' sensitivity to deposit rates 存款人对存款利率的敏感度分散 |
0.424 | [0.144] | 0.528 | [0.279] | |
Borrowers' sensitivity to loan rates 借款人对贷款利率的敏感度 |
−1.017 -1.017 | [0.054] | −1.454 -1.454 | [0.082] | |
Convenience of holding deposits 持有存款的便利性 |
3.465 | [0.358] | 2.340 | [0.470] | |
Convenience of holding cash 持有现金的便利性 |
2.763 | [0.387] | −0.444 | [0.430] | |
Convenience of borrowing through loans 贷款借款的便利性 |
−0.016 | [0.088] | 1.804 | [0.212] |
Panel D: Parameters Estimated via SMM 面板 D:通过 SMM 估计的参数 |
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γ | Banks' discount rate 银行的贴现率 | 0.047 | [0.002] | 0.044 | [0.005] |
Relative size of the deposit market 存款市场的相对规模 |
0.184 | [0.005] | 0.254 | [0.007] | |
Quadratic cost of nonreservable borrowing 不可预订借款的二次成本 |
0.010 | [0.001] | 0.010 | [0.004] | |
Bank's cost of taking deposits 银行吸收存款的成本 |
0.009 | [0.001] | 0.009 | [0.004] | |
Bank's cost of servicing loans 银行的贷款服务成本 |
0.005 | [0.001] | 0.008 | [0.002] | |
ψ | Net fixed operating cost 净固定运营成本 |
0.048 | [0.002] | 0.010 | [0.005] |
To understand the declining impact of monetary policy on bank lending, we categorize our parameters into three groups. The first group characterizes macroeconomic conditions—the federal funds rate and the loan charge-off processes, the regulatory constraints, and the loan and deposit market sizes. The second group consists of measures of bank operating efficiency and financial frictions—discount rates, operating costs, and external financing costs. The last group consists of parameters that govern banks' market power—the number of competing banks in the local market,
To gauge the overall effect of bank market power on the observed change in the federal funds rate sensitivity, we eliminate the difference in bank market power parameters across the two subsamples by setting the late-period values to those from early period. We find that the gap between the early and late sensitivities declines by 34%.
为了衡量银行市场力量对观察到的联邦基金利率敏感性变化的整体影响,我们通过将后期数值设定为早期数值来消除两个子样本之间银行市场力量参数的差异。我们发现早期和后期敏感性之间的差距减少了 34%。
Table X also shows that fixed operating costs have fallen, likely because of bank mergers. The consequent rise in profitability allows banks to accumulate healthier capital buffers that reduce their exposure to monetary policy. Furthermore, the cost of accessing the nonreservable funding market has declined, so banks can better cushion fluctuations in deposits. If we eliminate the difference in bank operating and financing costs, the gap between the early and late sensitivities declines by 22%.
表 X 还显示,固定运营成本已经下降,可能是因为银行合并。由此带来的盈利增加使银行能够积累更健康的资本缓冲,从而降低它们对货币政策的敏感度。此外,非储备融资市场的获取成本也有所下降,因此银行可以更好地缓冲存款波动。如果我们消除银行运营和融资成本之间的差异,早期和晚期敏感性之间的差距将减少 22%。
The remaining 44% of the gap is attributable to changes in macroeconomic conditions. In particular, we find that changes in the federal funds rate process play the most important role in explaining the declining trend in the sensitivity of lending to the federal funds rate. In particular, the average federal funds rate is much lower in our late period, so the economy spends more time around the reversal-rate region, where monetary policy has a weaker, or even opposite, effect on bank lending decisions.
剩下的 44%的差距归因于宏观经济条件的变化。特别是,我们发现联邦基金利率变化过程在解释银行贷款对联邦基金利率敏感性下降趋势中起着最重要的作用。具体来说,在我们的后期,平均联邦基金利率要低得多,因此经济在逆转利率区域周围花费更多时间,这里货币政策对银行贷款决策的影响较弱,甚至相反。
C. Model Robustness C. 模型稳健性
In this subsection, we examine the implications of several ingredients that we have left out of the baseline model. First, instead of requiring dividends to be positive, we allow them to be negative, subject to a linear equity issuance cost,
Second, we introduce time-varying discount rates. Specifically, we assume that banks apply a discount rate of
Third, we address the concern that agents in our model are risk-neutral, while in reality, loan spreads contain a risk premium. To make the model and data moments comparable, we adjust the data moment by subtracting a risk premium, which we calibrate following Giesecke et al. (2011), who show that the credit risk premium in the bond market roughly equals the expected default loss. After adjusting the data moment, we reestimate the model. As shown in Table IA.VII in Section IX of the Internet Appendix, we find that the only notable difference in the new results lies in banks' estimated cost of servicing loans, which becomes insignificantly different from zero. This result suggests that omitting loan default risk in our original model causes this component to load onto loan servicing costs.
第三,我们解决了我们模型中的代理人是风险中性的这一问题,而实际上,贷款利差包含风险溢价。为了使模型和数据瞬间可比,我们通过减去一个风险溢价来调整数据瞬间,我们根据 Giesecke 等人(2011 年)的方法进行校准,他们表明债券市场中的信用风险溢价大致等于预期违约损失。在调整数据瞬间后,我们重新估计模型。如附录互联网附录第 IX 节的表 IA.VII 所示,我们发现新结果中唯一显著差异在于银行估计的贷款服务成本,这使得其与零没有显著差异。这一结果表明,在我们原始模型中省略贷款违约风险导致这一组成部分加载到贷款服务成本上。
Fourth, we address the functional form of the nonreservable financing cost in equation (13), which is quadratic. We reestimate the model under the assumption that the nonreservable cost takes a more general power-function form:
第四,我们处理方程(13)中的不可预订融资成本的功能形式,即二次的。我们在假设不可预订成本采用更一般的幂函数形式下重新估计模型:
Fifth, one simplifying assumption of the model is that the present value of all future interest payments is paid to the bank in the first period in which a loan is issued. Moreover, we implicitly assume that this payment is default free. To address these issues, we extend the model by introducing an additional state variable that represents the average contractual interest rate on outstanding loans. Details are in Section IX of the Internet Appendix. We solve the model using the parameters reported in Table III. In Table IA.VI, we show that the moment conditions are largely unchanged relative to the values in Table IV. In Figure IA.3, we show that the reversal rate result is nearly unchanged.
第五,模型的一个简化假设是,所有未来利息支付的现值在发放贷款的第一个期间支付给银行。此外,我们隐含地假设这笔支付是免除违约的。为了解决这些问题,我们通过引入一个额外的状态变量来扩展模型,该变量代表未偿贷款的平均合同利率。详细信息请参见互联网附录的第九部分。我们使用表 III 中报告的参数来解决模型。在表 IA.VI 中,我们展示了瞬时条件与表 IV 中的值基本保持不变。在图 IA.3 中,我们展示了逆转率结果几乎没有变化。
Finally, in Section XI of the Internet Appendix, we consider an extension of the model in which we endogenize the federal funds rate. Our extended model contains a standard New Keynesian block and a banking block, with the New Keynesian block determining the effects of productivity and monetary policy shocks on the nominal short-term rate and inflation. The banking block determines the transmission of the nominal short-term rate to the lending rate. In this setting, the federal funds rate process is pinned down by a Taylor rule, which depends on the monetary authority's policy as well as aggregate output and inflation.
最后,在互联网附录的第十一部分,我们考虑了模型的一个扩展,其中我们内生化了联邦基金利率。我们的扩展模型包含一个标准的新凯恩斯模块和一个银行模块,其中新凯恩斯模块确定了生产率和货币政策冲击对名义短期利率和通货膨胀的影响。银行模块确定了名义短期利率传导到贷款利率的过程。在这种情况下,联邦基金利率的过程由泰勒规则确定,该规则取决于货币当局的政策以及总产出和通货膨胀。
We assume a continuum of ex ante homogeneous households with separable preferences over real consumption and real money balances. These households face a two-stage decision-making process. First, they choose the quantity of consumption and money holdings given aggregate prices. Second, they allocate their money demand across different options—cash or deposits in any bank. Similarly, firms decide their optimal demand for capital and whether to finance this demand via corporate bonds or bank loans. We model the banking sector as in our baseline partial equilibrium setting discussed in Section II. The detailed model setup and parameter calibrations are discussed in Section XI of the Internet Appendix.
我们假设存在一个先验同质的家庭连续体,其对实际消费和实际货币余额具有可分离的偏好。这些家庭面临一个两阶段的决策过程。首先,他们在给定总体价格的情况下选择消费量和货币持有量。其次,他们将他们的货币需求分配到不同的选择中——现金或存款在任何银行。同样,企业决定他们对资本的最佳需求以及是否通过公司债券或银行贷款来融资这种需求。我们将银行业模型化为我们在第二部分讨论的基线偏离均衡设置。详细的模型设置和参数校准在互联网附录的第十一部分中讨论。
With the calibrated general equilibrium model, we first confirm that the relation between the federal funds rate and aggregate bank lending is nonmonotonic and hump-shaped. We also repeat our decomposition of monetary policy transmission mechanisms using the general equilibrium framework. We find that the sensitivity of loans to the federal funds rate is lower than in our baseline model in Section IV.A because our New Keynesian model implies a much weaker relationship between the federal funds rate and long-term real rate than what we observe in the data. Nevertheless, our main conclusions remain valid. We find that the qualitative effect of the reserve regulation remains limited, while both the deposit and loan market power channels are quantitatively important in explaining monetary transmission.
通过校准的一般均衡模型,我们首先确认联邦基金利率与总体银行贷款之间的关系是非单调的,并呈驼峰形状。我们还重复使用一般均衡框架对货币政策传导机制进行分解。我们发现,贷款对联邦基金利率的敏感性低于我们在第 IV.A 节的基准模型中的敏感性,因为我们的新凯恩斯模型暗示联邦基金利率与长期实际利率之间的关系要比我们在数据中观察到的关系要弱得多。尽管如此,我们的主要结论仍然有效。我们发现准备金监管的定性效应仍然有限,而存款和贷款市场力量渠道在解释货币传导方面具有重要的数量意义。
VI. Conclusion VI. 结论
The U.S. banking sector has experienced an enormous amount of consolidation. The market share of the top five banks has increased from less than 15% in the 1990s to over 45% as of 2017. This consolidation begs the question of whether bank market power has a quantitatively important effect on the transmission of monetary policy. We study this question by formulating and estimating a dynamic banking model with regulatory constraints, financial frictions, and imperfect competition. This unified framework is useful because it allows us to gauge the relative importance of different monetary policy transmission channels.
美国银行业经历了大量的整合。自 1990 年代以来,前五大银行的市场份额已从不到 15%增加到 2017 年的 45%以上。这种整合引发了一个问题,即银行市场力量是否对货币政策传导产生了重要的定量影响。我们通过制定和估计一个具有监管约束、金融摩擦和不完全竞争的动态银行模型来研究这个问题。这一统一框架很有用,因为它使我们能够衡量不同货币政策传导渠道的相对重要性。
In our counterfactuals, we show that the channel related to reserve requirements has limited quantitative importance. In contrast, we find that channels related to bank capital requirements and market power are very important. These quantitative findings are new to an empirical literature dominated by qualitative results (Kashyap and Stein (1995), Scharfstein and Sunderam (2016), Drechsler, Savov, and Schnabl (2017)). We also find an interesting interaction between the market power channel and the bank capital channel. If the federal funds rate is low, depressing it further can contract bank lending, as reduced profits in the deposit market impact bank capital negatively. Lastly, we show that accounting for bank market power is key to understanding cross-sectional variation in banks' responsiveness to monetary policy, while the interaction of bank market power with regulatory constraints explains most of the decline in monetary transmission effectiveness over time.
在我们的反事实中,我们展示了与准备金要求相关的渠道在数量上的重要性有限。相比之下,我们发现与银行资本要求和市场力量相关的渠道非常重要。这些数量化的发现是新的,而以定性结果为主导的实证文献(Kashyap 和 Stein(1995 年),Scharfstein 和 Sunderam(2016 年),Drechsler,Savov 和 Schnabl(2017 年))也证实了这一点。我们还发现市场力量渠道与银行资本渠道之间存在有趣的互动。如果联邦基金利率较低,进一步降低它可能会收缩银行信贷,因为存款市场利润的减少会对银行资本产生负面影响。最后,我们展示了考虑银行市场力量对于理解银行对货币政策的响应的横截面变化至关重要,而银行市场力量与监管约束的互动解释了随时间推移货币传导效果下降的大部分原因。
Editors: Stefan Nagel, Philip Bond, Amit Seru, and Wei Xiong
编辑:斯特凡·纳格尔,菲利普·邦德,阿米特·塞鲁和熊巍