Ben S. Bernanke | Macro Paper Warehouse

Chapter 21 The financial accelerator in a quantitative business cycle framework

This Handbook of Macroeconomics chapter develops a dynamic general equilibrium model – since widely known simply as “BGG” – that embeds a credit-market friction into an otherwise standard New Keynesian business-cycle framework in order to formalize and quantify the “financial accelerator”: the idea that endogenous developments in credit markets amplify and propagate, rather than merely reflect, shocks to the macroeconomy. The mechanism rests on a costly-state-verification (Townsend 1979) debt contract between risk-neutral entrepreneurs and financial intermediaries, in which lenders must pay an auditing cost to observe a borrower’s realized, privately known idiosyncratic return; this generates an external finance premium – the wedge between the cost of external and internal funds – that depends inversely on the borrower’s net worth relative to the capital being financed, since low-net-worth borrowers pose greater default risk and hence greater expected agency (monitoring) costs. Because net worth in the model is itself procyclical (rising with profits and asset prices in expansions), the external finance premium is countercyclical, so a positive shock raises net worth, lowers the finance premium, and further stimulates investment and asset prices, which raises net worth again – a feedback the authors formalize in the key relation QK = Ψ(s)N linking a firm’s capital expenditure to its net worth via a premium-dependent multiplier Ψ. Embedding this contracting problem in a Calvo-style sticky-price New Keynesian model with money and, in extensions, one-period investment decision lags and heterogeneous firms with differential credit access, the calibrated model shows the financial accelerator delivers economically large amplification and propagation: in response to an unanticipated 25-basis-point cut in the nominal interest rate, the initial output response is about 50% larger and the investment response nearly twice as large with the accelerator present than in an otherwise identical baseline with the finance premium held fixed at its steady-state level, and the real effects are far more persistent (output and investment four quarters after the shock, with the accelerator, are roughly where they stand after only two quarters without it); the external finance premium itself falls sharply and only slowly reverts to trend, consistent with the paper’s own VAR evidence that credit-spread variables rise ahead of the downturn following a contractionary policy shock. In the two-sector extension with heterogeneous credit access, investment by the more credit-constrained sector rises by nearly three times as much as investment by the better-credit-access sector after an expansionary shock, an “excess sensitivity” result the authors relate to net worth being endogenous in their model, in contrast to models such as Fisher (1996) in which borrowers’ equity positions are exogenously fixed.

Inflation Targeting: A New Framework for Monetary Policy?

This 1997 Journal of Economic Perspectives essay by Ben Bernanke and Frederic Mishkin is a survey and policy assessment, not an empirical study: it draws on comparative experience across the eight economies that had formally adopted inflation targeting by 1997 (Australia, Canada, Finland, Israel, New Zealand, Spain, Sweden, and the United Kingdom), on Germany and Switzerland as “hybrid” cases that pursue inflation goals through money-growth targets, and on existing empirical work, to assess inflation targeting (IT) as a framework for monetary policy. All eight direct targeters use CPI-based series (often “core” or “underlying” measures excluding food, energy, indirect taxes, or mortgage costs), set target levels at 4 percent or below, mostly as ranges rather than points, over horizons of one to four years, and retain short-run flexibility through supply-shock exclusions, target ranges, adjustable near-term targets, or explicit escape clauses. The paper’s central argument is that IT is best understood as “constrained discretion” — a third category distinct from both a mechanical policy rule and pure discretion, since it fixes the medium-term goal while leaving short-run tactics to the central bank’s judgment — and that it serves two functions: providing a nominal anchor that reduces uncertainty about future inflation, and creating transparency and accountability that can discipline policymakers against inflationary bias. The authors argue against treating IT as an exclusive single-goal rule, note that there is not yet evidence that IT countries have disinflated at lower sacrifice ratios than others or that announcing targets by itself moves private expectations, favor a positive target of roughly 2 percent over a zero target (citing CPI measurement bias of an estimated 0.5 to 2 percentage points per year, downward nominal-wage rigidity, and insurance against deflation), and express a mild preference for inflation targeting over nominal GDP targeting on grounds of data timeliness, the practical similarity in short-run flexibility, and public understandability, while arguing the pre-1997 Volcker-Greenspan Federal Reserve’s policymaking framework was already “de facto very similar to inflation targeting.”

Inside the Black Box: The Credit Channel of Monetary Policy Transmission

This 1995 Journal of Economic Perspectives paper by Ben Bernanke and Mark Gertler surveys the “credit channel” of monetary policy transmission — described explicitly as an amplifying mechanism, not an independent channel — under which monetary tightening raises the external finance premium (the wedge between the cost of external and internal funds) on top of its direct effect on market interest rates, thereby explaining three empirical puzzles that conventional interest-rate theory leaves unresolved: the large real effects of small interest-rate movements, the delayed timing of investment and inventory responses relative to the largely transitory rise in rates, and the unexpectedly large and rapid response of residential investment relative to business structures. Using a monthly four-variable recursive VAR (1965-1993), the authors document that after a monetary tightening, real GDP begins declining about four months later and bottoms out around two years out, even though the federal funds rate itself is back near trend within 9-12 months; inventory disinvestment accounts for a substantial part of the initial output decline, and business fixed investment (concentrated in equipment, not structures) responds with the longest lag of all spending components. The paper attributes these facts to two credit-channel mechanisms — a balance sheet (net worth) channel, under which rising rates and falling asset prices directly and cumulatively weaken borrowers’ balance sheets (evidenced by a coverage ratio that tracks the funds rate closely and by roughly 40% of the short-run profit decline coming from higher interest payments), and a bank lending channel, under which reserve drains restrict loan supply to bank-dependent borrowers (evidenced by widening CD-Treasury bill spreads during tight-money periods) — while candidly noting the two mechanisms cannot be cleanly separated empirically and that the bank lending channel has likely weakened since financial deregulation.

Measuring Monetary Policy

Bernanke and Mihov (1998, QJE) address a measurement problem in the monetary-VAR literature: the era’s dominant methods for extracting a “monetary policy shock” – Cholesky orderings built around the federal funds rate (FFR), nonborrowed reserves (NBR), or the ratio of nonborrowed to total reserves (NBR/TR, following Strongin 1995) – impose ad hoc restrictions rather than an explicit model of how the Fed actually operates in the market for bank reserves. The paper builds a “semi-structural” six-variable VAR (total reserves, nonborrowed reserves, and the federal funds rate in a policy block; real GDP, the GDP deflator, and a commodity price index in a block-exogenous macro block) over monthly U.S. data, 1965:1-1996:12, with lag length chosen by a general-to-specific procedure (13 lags retained for the full sample). Within the policy block they specify structural equations for reserves demand, borrowed-reserves supply, and the Fed’s nonborrowed-reserves supply/policy rule, estimated by two-step efficient GMM using the reduced-form VAR residuals; this yields five nested identifications – FFR, NBR, NBR/TR, borrowed-reserves (BR), and a just-identified (JI) benchmark that restricts only the reserves-demand elasticity to zero – each corresponding to different assumptions about how much the Fed accommodates reserves-demand shocks (phi^d) and borrowing shocks (phi^b). Overidentifying-restriction tests reject the NBR model in every subsample except the 1979:10-1982:10 Volcker NBR-targeting episode, favor NBR/TR as the best overall fit across subsamples, and favor FFR pre-1979 and post-1988; a Hamilton (1989) regime-switching model applied directly to (phi^d, phi^b) independently locates two structural breaks matching the conventional 1979/1982 Volcker-experiment dates, with phi^d falling from roughly 0.86 outside that window to roughly 0.18 within it. Although the five identifications generate qualitatively similar impulse responses (output rising with a 12-18 month peak, prices moving more slowly and persistently), they diverge sharply in magnitude – the cumulative output response under NBR/TR is more than twice as large as under NBR, and at a four-year horizon the price response under NBR is roughly four times that under FFR – because, the authors show algebraically, any overidentified indicator is a contaminated mixture of the true policy shock with reserves-demand and borrowing shocks whenever the Fed accommodates those shocks. This contamination framework offers an explanation for the post-1984 “vanishing liquidity effect” as a measurement artifact of using the NBR indicator rather than a change in the economy: a derived bias formula, evaluated at the JI model’s full-sample GMM estimates, is negative in the full sample (bias term -0.777) and grows more negative in 1988-1996 (-0.904) and 1984-1996 (-1.035, where it flips the estimated liquidity effect’s sign). The paper closes by constructing an overall monetary-policy-stance index from the full vector of structural innovations, normalized by a 36-month moving average, which correlates 0.71 (monthly) with the Boschen-Mills (1991) index; the authors caution that the empirical illustrations are meant only to be illustrative, since the Figure II impulse responses pool full-sample JI parameter estimates across regimes that the paper’s own regime-switching results show are unstable.

Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach

This 2005 Quarterly Journal of Economics paper by Ben Bernanke, Jean Boivin, and Piotr Eliasz proposes the Factor-Augmented VAR (FAVAR) to address a specific problem with standard small monetary VARs: because Fed policymakers actually condition on a wide range of economic and financial data, a VAR built from only a handful of observable series omits conditioning information, which biases the identified policy shock (producing the “price puzzle,” a spurious rise in prices after a tightening), makes the choice of which few variables to include arbitrary, and limits impulse responses to only the included series. The FAVAR augments a standard VAR in observable variables (in the benchmark specification, just the federal funds rate) with a small number of latent factors extracted by principal components from a large panel of 120 monthly U.S. macroeconomic series (DRI/McGraw Hill Basic Economics Database, January 1959-August 2001); the factors and the observable are then modeled jointly in a VAR (13 lags, 3 factors in the benchmark), with the policy shock identified recursively (Cholesky) by ordering the federal funds rate last, and with the factors themselves estimated in a first step using only “slow-moving” variables that do not respond contemporaneously to policy shocks, so as not to contaminate the factor estimates with the policy shock itself. Two estimation approaches are compared: a computationally simple two-step principal-components procedure (following Stock and Watson 2002), which the authors prefer for its “greater plausibility,” and a one-step Bayesian likelihood approach via Gibbs sampling (10,000 draws, 2,000 discarded as burn-in) that is more rigorous but yields qualitatively similar, quantitatively more imprecise results. Moving from a standard three-variable VAR (industrial production, CPI, funds rate), which produces a strong and persistent price puzzle, to a FAVAR with even a single additional factor considerably reduces the puzzle; the preferred three-factor, two-step-PC FAVAR generates impulse responses for many more series that are broadly consistent with standard theory (real activity and prices eventually decline, money aggregates fall, the dollar appreciates on impact), and a five-factor version leaves these qualitative conclusions unchanged. At a 60-month horizon the identified policy shock accounts for a sizeable share of the variance of interest rates (45.4% of the funds rate itself, 43.3% of the 3-month T-bill, 40.3% of the 5-year bond) but a much smaller share of real activity and prices (5.4% of industrial production, 3.8% of CPI) and of monetary aggregates (0.5% of both the monetary base and M2); the authors note that IRFs for the monetary aggregates should be interpreted with caution given the low R² of their common components (10.4% and 5.2%, respectively), and they hedge their central claim, describing the price-puzzle result as offering only “some support” for the view that the puzzle stems from omitted conditioning information rather than a definitive resolution. The sample ends in August 2001, before the financial crisis and the zero lower bound, so the paper does not speak to whether the FAVAR’s resolution of the price puzzle extends to that later, constrained-policy environment.

Monetary Policy Alternatives at the Zero Bound: An Empirical Assessment

This 2004 Brookings Papers on Economic Activity paper by Ben Bernanke, Vincent Reinhart, and Brian Sack asks whether “nonstandard” monetary policies can still work once the short-term policy rate is at or near the zero lower bound (ZLB), applying “the methods of modern empirical finance” to the recent US and Japanese experience rather than relying on theory alone. The authors group nonstandard policies into three classes — using communications to shape expected future policy, increasing the size of the central bank’s balance sheet (quantitative easing), and changing its composition (targeted asset purchases) — and use two complementary empirical strategies to assess each. For communications, a one-hour event study around 116 FOMC decisions (July 1991-2004) decomposes market reactions via a Cholesky factorization into a “current policy surprise” factor and a second “path” factor tied to the wording of the post-meeting statement; the path factor turns out to dominate, accounting for roughly four-fifths of the variance of the year-ahead Eurodollar futures rate (versus about one-fifth for the current-surprise factor) and 68 percent of the variance of the five-year Treasury yield, and the “considerable period” language introduced in August 2003 roughly tripled the ten-year yield’s sensitivity to payroll surprises (from about 4 to about 11 basis points per 100,000 jobs). For quantity/composition effects, a five-factor no-arbitrage affine term-structure VAR (estimated on macro and policy factors, monthly 1982-2004) generates a counterfactual yield-curve benchmark, against which the paper attributes the 1999-2002 Treasury debt buyback with pushing the twenty-year yield from about 20 basis points above to about 80 basis points below the model’s prediction (bootstrap probability under 10 percent), concentrated at the long end with only limited evidence of pass-through to swap spreads at short maturities. Extending the analysis to Japan (110 BOJ decisions since independence in April 1998, two-day windows given data limitations), the paper finds little evidence the BOJ used statements to move near-term policy expectations the way the Fed did, but some evidence that quantitative-easing and current-account-balance-target surprises moved the Nikkei (3-6 percent on several occasions) and that a four-factor term-structure model — adjusted by simulation to respect the ZLB — implies actual JGB yields ran persistently below model predictions after the 1999 zero-interest-rate policy and 2001 quantitative easing, with the gap widening over time. The authors describe their overall evidence as “to some degree indirect,” since the US policy rate never actually fell below roughly 100 basis points during the sample, and caution that the size and reliability of quantity/composition effects remain “quite uncertain” and subject to identification problems (for example, the 2003 “deflation scare” episode overlapping with anticipated Treasury purchases); their bottom-line policy recommendation is that central banks are best off avoiding the ZLB altogether by maintaining an inflation buffer and easing preemptively.

Nonmonetary Effects of the Financial Crisis in the Propagation of the Great Depression

Complementing Friedman and Schwartz’s monetary account of the Great Depression, Bernanke argues that the banking panics and pervasive debtor insolvency of 1930-33 independently raised the real cost of credit intermediation, and that this non-monetary credit-market channel helps explain both the unusual depth and the unusual length of the U.S. downturn. The paper’s premise is that because financial markets are incomplete, banks and other intermediaries perform a real, costly service – distinguishing creditworthy (“good”) borrowers from those who would default – and that the banking crises and widespread bankruptcies of 1930-33 impaired the financial sector’s ability to perform this service, raising what Bernanke calls the cost of credit intermediation (CCI). Runs forced banks to retrench into safe, liquid assets and abandon accumulated lending relationships, while a Fisher-style debt-deflation dynamic (nominal debts fixed while prices and incomes collapsed) eroded borrowers’ collateral, and both effects independently pushed up the effective cost of credit facing households, farmers, and small firms even as large, well-known borrowers retained access. Using monthly interwar data, Bernanke shows that adding proxies for the financial crisis – deposits of failing banks, liabilities of failing businesses, and the Baa-Treasury yield spread – to a standard Lucas-Barro “monetary/price surprise” output equation substantially improves its ability to track the collapse of industrial production between 1930 and the March 1933 bank holiday, cutting simulation error by roughly half to over ninety percent depending on specification, whereas the pure monetary-surprise equations alone explain only about half of the output decline. Because rebuilding disrupted lending relationships and rehabilitating insolvent debtors is a slow process, Bernanke argues this non-monetary channel – unlike monetary theories, which must rely on unexplained nominal rigidities – offers a natural explanation for the Depression’s unusual persistence, a claim he supports with survey evidence showing continued credit rationing of small business and mortgage borrowers as late as 1935-38, notwithstanding the credit-easing appearance created by banks’ postcrisis flight to liquid, safe assets.