The claim that an asset price bubble will not respond to a small change in interest rates has mostly been argued in the context of the stock market, where the proposition is indeed plausible. However, the stock market is not the best context in which to discuss the financial stability role of monetary policy, as stocks are held mostly by unlevered investors. Much more central is the credit market, especially when backed by residential or commercial real estate. As argued already, a difference of a quarter or half percentage in the funding cost may make all the difference between a profitable venture and a loss-making one for leveraged financial intermediaries.

We believe that focusing on the conduct of financial intermediaries is a better way to think about financial stability since it helps us to ask the right questions. Concretely, consider the following pair of questions.

Question 1. Do you know for sure there is a bubble in real estate prices?

Question 2. Could the current benign funding conditions reverse abruptly with adverse consequences for the economy?

One can answer “yes” to the second question even if one answers “no” to the first. This is because we know more about the script followed by financial intermediaries and how they react to changes in the economic environment than we do about what the “fundamental” value of a house is, and whether the current market price exceeds that value. 

In any case, for a policy maker, it is the second question which is more immediately relevant. Even if a policy maker were convinced that the higher price of housing is fully justified by long-run secular trends in population, household size, rising living standards, and so on, policy intervention would be justified if the policy maker also believed that, if left unchecked, the virtuous circle of benign funding conditions and higher housing prices will go too far, and reverse abruptly with adverse consequences for the economy.

The outline of our paper is as follows. We begin with background descriptions of financial intermediation in a market-based banking system. We then present our empirical results on the real impact of broker-dealer balance sheet changes, the determinants of balance sheet changes, and how US monetary policy has reacted to balance sheet changes. We conclude with some implications of our findings for the conduct of monetary policy.

2. Financial Intermediaries in a Market-Based Financial System

Behind the development of the market-based banking system is the growth of mortgage backed securities as an asset class. Figure 1 plots the total holding of home mortgages in the US by types of financial institution, drawn from the Flow of Funds accounts for the US. 

As recently as the early 1980s, traditional banks were the dominant holders of home mortgages, but bank-based holdings have been quickly overtaken by market-based holders of mortgages. In Figure 2, bank-based holdings are defined as the sum of the holdings of the commercial banks, the savings institutions and credit unions. The market-based holdings are the remainder – the GSE mortgage pools, private label mortgage pools and the GSE holdings themselves. Market-based holdings overtook the bank-based holdings in 1990, and now constitute two thirds of the 11 trillion dollar total stock of home mortgages.

The increased importance of the market-based banking system has been mirrored by the growth of the broker-dealer sector of the economy. Broker-dealers have traditionally played market-making and underwriting roles in securities markets. However, their importance in the supply of credit has increased in step with securitization. Thus, although the size of total broker-dealer assets is small by comparison to the commercial banking sector (it is around one third of the commercial bank sector) it has seen rapid growth in recent decades and is arguably a better barometer of overall funding conditions in a market-based financial system.

Besides growing much more rapidly than commercial bank assets, broker-dealer assets have been more volatile. Figure 4 plots the (annual) growth rates of broker-dealer assets together with the growth rates of commercial bank total assets for the US. We see that broker-dealer assets vary much more sensitively over time, as compared to commercial bank assets.

Not only is broker-dealer asset growth more volatile relative to commercial banks, the two series move in quite different ways. Figure 5 is a version of Figure 4 where the commercial bank series has been rescaled according to the right hand vertical axis. We see that the peaks and troughs of the two series differ markedly. The chart shows that traditional banking and the new market-based financial system move to a very different beat.

The balance sheet dynamics of financial intermediaries that mark their balance sheets to market have some distinctive features. Figure 6 below is taken from Adrian and Shin (2007) and shows the scatter chart of the weighted average of the quarterly change in assets against the quarterly change in leverage of the (then) five stand-alone US investment banks – Bear Stearns, Goldman Sachs, Lehman Brothers, Merrill Lynch and Morgan Stanley.

The first striking feature is that leverage is procyclical in the sense that leverage is high when balance sheets are large, while leverage is low when balance sheets are small. This is exactly the opposite finding compared to households, whose leverage is high when balance sheets are small. For instance, if a household owns a house that is financed by a mortgage, leverage falls when the house price increases, since the equity of the household is increasing at a much faster rate than assets. For investment banks, however, the relationship is reversed. It is as if the householder responded to an increase in house prices by increasing the mortgage loan to value so that leverage increases in spite of the increased value of his house.

A procyclical leverage ratio offers a window on the notion of financial system liquidity. When leverage is procyclical, the demand and supply response to asset price changes can amplify shocks. To see this, consider an increase in the price of assets held widely by leveraged market players and intermediaries. The increase in the price of assets strengthens the players’ balance sheets, since the net worth of levered players increases as a proportion of their total assets.

When balance sheets become stronger, leverage falls. To the extent that the intermediary wants to avoid holding too much equity (for instance, because return on equity is too low), it will attempt to restore leverage. One way it can do so is by borrowing more, and using the proceeds to buy more of the assets they already hold. Indeed, as we see below, the evidence points to broker-dealers adjusting leverage by adjusting the size of their balance sheets, leaving equity intact.

If greater demand for the asset puts upward pressure on its price, then there is the potential for a feedback effect in which stronger balance sheets feed greater demand for the asset, which in turn raises the asset's price and lead to stronger balance sheets. Having come full circle, the feedback process goes through another turn. The circular figure on the left illustrates the feedback during a boom. Note the critical role played by procyclical leverage.

The mechanism works in reverse in downturns. Consider a fall in the price of an asset held widely by hedge funds and banks. Then, the net worth of such an institution falls faster than the rate at which asset falls in value, eroding its equity cushion. One way that the bank can restore its equity cushion is to sell some of its assets, and use the proceeds to pay down its debt. The circular chart above on the right illustrates the feedback during a bust. Note the importance of marking to market. By synchronizing the actions of market participants, the feedback effects are amplified.

There is a more subtle feature of Figure 6 which tells us much about the financing decisions of financial intermediaries. Recall that the horizontal axis measures the (quarterly) change in leverage, as measured by the change in log assets minus the change in log equity. The vertical axis measures the change in log assets. Hence, the 45-degree line indicates the set of points where equity is unchanged. Above the 45-degree line equity is increasing, while below the 45-degree line, equity is decreasing. Any straight line with slope equal to 1 indicates constant growth of equity, with the intercept giving the growth rate of equity.

The feature to note from Figure 6 is that the slope of the scatter chart is close to 1, implying that equity is increasing at a constant rate on average. Thus, equity seems to play the role of the forcing variable, and all the adjustment in leverage takes place through expansions and contractions of the balance sheet.

There is a useful perspective on this feature that comes from the risk management policies of financial intermediaries. Banks aim to keep enough equity capital to meet its overall value at risk (VaR). If we denote by V the value at risk per dollar of assets, and A is total assets, then equity capital E must satisfy E = V  A, implying that leverage L satisfies 

L = A/E = 1/V

If value at risk is low in expansions and high in contractions, leverage is high in expansions and low in contractions – leverage is procyclical.

One further way we can understand the fluctuations in funding conditions is to look at the implicit maximum leverage that is permitted in collateralized borrowing transactions such as repurchase agreements (repos). The discussion of repurchase agreements is instructive in thinking about leverage and funding more generally, since repos are the primary source of funding for market-based banking institutions.

In a repurchase agreement, the borrower sells a security today for a price below the current market price on the understanding that it will buy it back in the future at a preagreed price. The difference between the current market price of the security and the price at which it is sold is called the “haircut” in the repo, and fluctuates together with funding conditions in the market.

The fluctuations in the haircut largely determine the degree of funding available to a leveraged institution. The reason is that the haircut determines the maximum permissible leverage achieved by the borrower. If the haircut is 2%, the borrower can borrow 98 dollars for 100 dollars worth of securities pledged. Then, to hold 100 dollars worth of securities, the borrower must come up with 2 dollars of equity. Thus, if the repo haircut is 2%, the maximum permissible leverage (ratio of assets to equity) is 50.

Suppose that the borrower leverages up the maximum permitted level. Such an action would be consistent with the objective of maximizing the return on equity, since leverage magnifies return on equity. The borrower thus has a highly leveraged balance sheet with leverage of 50. If at this time, a shock to the financial system raises the market haircut, then the borrower faces a predicament. Suppose that the haircut rises to 4%. Then, the permitted leverage halves to 25, from 50. The borrower then faces a hard choice. Either it must raise new equity so that its equity doubles from its previous level, or it must sell half its assets, or some combination of both.

Note that the increase in haircuts will do most harm when starting from very low levels. A percentage point increase from 1% to 2% will mean leverage has to fall from 100 to 50. But a percentage point increase from 20% to 21% will have only a marginal effect on the initial leverage of 5. In this sense, the “chasing of yield” at the peak of the financial cycle is especially precarious, since the unwinding of leverage will be that much more potent.

Times of financial stress are associated with sharply higher haircuts, necessitating substantial reductions in leverage through asset disposals or raising of new equity. Raising new equity or cutting assets entail adjustments for the borrower. Raising new equity is notoriously difficult in distressed market conditions. But selling assets in a depressed market is not much better.8 The evidence from the scatter chart above is that borrowers tend to adjust leverage primarily through adjustments in the size of the balance sheet, leaving equity unchanged, rather than through changes in equity directly.

For an investment bank, whose assets tend to be short term and liquid (such as short-term collateralized lending), it can adjust its balance sheet size flexibly by reducing lending and not rolling over debt. However, when the financial system as a whole holds longterm, illiquid assets financed by short-term liabilities, any tensions resulting from a sharp, synchronized contraction of balance sheets will show up somewhere in the system. Even if some institutions can adjust down their balance sheets flexibly, there will be pinch points in the system that will be exposed by the de-leveraging. We return to this issue below.

3. Macroeconomic consequences

In models of monetary economics that are commonly used at central banks, the role of financial intermediaries is largely incidental; banks and broker-dealers are passive players that the central bank uses to implement monetary policy. In contrast, our argument thus far suggests that they deserve independent study because of their impact on financial conditions and hence on real economic outcomes. In this section, we examine whether financial intermediaries’ impact on financial conditions feed through to affect real economic outcomes – in particular, on components of GDP. We find that it does, especially on those components of GDP that are sensitive to credit supply, such as housing investment and durable goods consumption.

In the language of “frictions”, our empirical findings are consistent with a set of principal-agent frictions that operate at the level of the financial intermediaries themselves. These frictions result in constraints on balance sheet choice that bind harder or more loosely depending on the prevailing market conditions. The fluctuations in haircuts and regulatory capital ratios that are critical in determining the leverage of financial intermediaries can be seen as being driven by the fluctuations in how hard these constraints bind. When balance sheet constraints bind harder, credit supply is reduced.

Broker-dealer balance sheets hold potentially more information on underlying financial conditions, as they are a signal of the marginal availability of credit. At the margin, all financial intermediaries (including commercial banks or GSEs) have to borrow in markets (for instance via commercial paper or repos). For a commercial bank, even though only a small fraction of its total balance sheet is market based, at the margin it has to tap the capital markets. But for commercial banks, their large balance sheets mask the effects operating at the margin. Broker-dealers, in contrast, give a purer signal of marginal funding conditions, as their liabilities are short term, and their balance sheets are close to being fully marked to market.

In addition, broker-dealers originate and make markets for securitized products, whose availability determines the credit supply for consumers and non-financial firms (e.g. for mortgages, car loans, student loans, etc.). So broker-dealers are important variables for two reasons. First, they are the marginal suppliers of credit. Second, their balance sheets reflect the financing constraints of the market-based financial system.

To the extent that balance sheet dynamics affect the supply of credit, they have the potential to affect real economic variables. To demonstrate that there are indeed real effects of the balance sheet behavior of intermediaries, we estimate macroeconomic forecasting regressions.

In Table 1, we report the results of regressions of the annual growth rate of GDP components on lagged macroeconomic and financial variables. In addition, we add the lagged growth rate of total assets and market equity of security broker-dealers on the right hand side.9 By adding lags of additional financial variables on the right hand side (equity market return, equity market volatility, term spread, credit spread), we offset balance sheet movements that are purely due to a price effect. By adding the lagged macroeconomic variables on the right hand side, we control for balance sheet movements due to past macroeconomic conditions. In Table 1 (and all subsequent tables), * denotes statistical significance at the 10%, ** significance at the 5% level, and *** at the 1% level. All our empirical analysis is using quarterly data from 1986Q1 to 2008Q1. Variable definitions are given in the appendix.

The growth rate of security broker-dealer total assets has strongest significance for the growth rate of future housing investment and for durable good consumption (Table 1, columns (iv) and (ii), respectively). Our interpretation of this finding is that the mechanisms that determine the liquidity and leverage of broker-dealers affect the supply of credit, which in turn affect investment and consumption. The finding that dealer total assets significantly forecast durable but not total consumption, and that they forecast housing investment but not total investment, lends support to this interpretation, as durable consumption and housing investment could be seen as being particularly sensitive to the supply of credit. The market value of security broker-dealer equity also has predictive power for housing investment, but additionally forecasts total consumption, total investment, and GDP.

In Table 1, equity is market equity, rather than book equity. To the extent that shifts in market equity is a good indicator of the shifts in the marked-to-market value of book equity, we can interpret the empirical finding that equity growth has real impact through the amplification mechanism illustrated in Figure 6, the scatter chart of leverage against assets. When balance sheets become strong, equity increases rapidly, eroding leverage. Financial intermediaries then attempt to expand their balance sheets to restore leverage. Since our data are quarterly, but balance sheets adjust quickly, the one quarter lagged assets may not fully capture this effect. However growth in market equity may be a good signal of growth of spare balance sheet capacity.

The forecasting power of dealer assets for housing investment is graphically illustrated in Figure 7. The impulse response function is computed from a first order vector autoregression that includes all variables of Table 1, Column (iv). The plot shows a response of housing investment to broker-dealer assets growth that is positive, large, and persistent. 

We next ask whether commercial bank balance sheet variables have additional forecasting power for real economic growth. One way to do so is first to orthogonalize commercial bank total asset growth and equity growth with respect to the broker-dealer variables, and then add the commercial banks variables that is unexplained by the broker-dealer variables to the regressions. The results are presented in Table 2. We find that commercial bank equity does have some additional information for housing investment, but total commercial bank assets do not. 

In Table 3, we run the same regressions as in Table 1, but with commercial bank variables instead of security-broker-dealer variables. We do find that commercial bank (market) equity is significant in explaining real economic activity, but commercial bank total assets are not. Our interpretation of these findings is that commercial bank balance sheets are less informative than broker-dealer balance sheets as they (largely) did not mark their balance sheets to market, over the time span in our regressions. However, market equity is a better gauge of underlying balance sheet constraints, and so better reflects the marginal increases in balance sheet capacity. So, whereas growth in total assets do not signal future changes in activity, growth in market equity does. 

The finding that commercial bank assets do not predict future real growth is also consistent with Bernanke and Lown (1991) who use a cross sectional approach to show that credit losses in the late 80’s and early 90’s do not have a significant impact on real economic growth across states. See Kashyap and Stein (1994) for an overview of the debate on whether there was a “credit crunch” in the recession in the early 1990s. 

In the same vein, Ashcraft (2006) finds small effects of commercial bank loans when using accounting based loan data, but Ashcraft (2005) finds large effects of commercial bank closures on real output (using FDIC induced failures as instruments). Morgan and Lown (2006) show that the senior loan officer survey provides significant explanatory power for real activity – again a variable that is more likely to reflect underlying credit supply conditions, and is not based on accounting data.

The credit supply channel sketched so far differs from the financial amplification mechanisms of Bernanke and Gertler (1989), and Kiyotaki and Moore (1997, 2005). These papers focus on amplification due to financing frictions in the borrowing sector, while we focus on amplification due to financing frictions in the lending sector. Our approach raises the question of whether the failure of the Modigliani-Miller theorem may be more severe in the lending rather than the borrowing sector of the economy. The interaction of financial constraints in the lending and the borrowing sector is likely to give additional kick to financial frictions in the macro context that mutually reinforce each other. These interactions would be fertile ground for new research.

We should also reiterate the caveats that underpin the results in Table 2. Inference for macroeconomic aggregates is difficult as all variables are endogenous. In analyzing the data, we started with the prior that balance sheets of financial intermediaries should matter for real economic growth. This prior has guided our empirical strategy. Researchers who look at the data with a different prior will certainly be able to minimize the predictive power of the broker-dealer balance sheet variable. However, analyzing the data with the prior that financial intermediary frictions are unimportant has the potential cost of overlooking the friction. Further searching examinations of the data will help us uncover the extent to which financial variables matter. In addition, we have not analyzed the importance of the balance sheets of other institutions of the market based financial system, such as the GSEs, hedge funds, etc.

We now present some additional evidence of the impact of broker-dealer assets from vector autoregressions that summarize the joint dynamics of macroeconomic variables, broker-dealer variables, and monetary policy. Figure 8 refers.

 In this exercise, we make no structural assumptions. To illustrate the impact of adding financial institutions to the monetary policy transmission mechanism, we plot the impulse response functions of housing investment growth from two vector autoregressions. In the first VAR, only GDP growth, PCE inflation, the Federal funds target, and housing investment are included (in that order). The second VAR adds the security-broker-dealer variables to the macro variables, with the macro variables ordered before the financial institution variables. Each VAR is nonstructural, and includes four lags of all variables. By adding the financial institution variables after the baseline macroeconomic variables, we are being conservative, giving the financial institution variables the least possible chance to impact shocks to the Fed funds target on housing investment. Each VAR is estimated with four lags, from 1986Q1 – 2008Q1. The impulse response functions are plotted in Figure 8.

Figure 8 shows that the dynamics of housing investment in response to monetary policy shocks differs in the two VAR specifications. The drop in housing investment in response to a Fed funds target increase is both quicker and larger in the VAR with the broker-dealer variables, compared to the baseline model. However, the recovery is also quicker. The two response functions of Figure 8 again illustrate that balance sheet variables of financial institutions have quantitatively important effects.

4. Determination of broker-dealer balance sheets

Having established that broker-dealer balance sheets matter for real activity, we investigate what determines the growth of broker-dealer balance sheets. Broker-dealers fund themselves with short term debt (primarily repurchase agreements and other forms of collateralized borrowing). Part of this funding is directly passed on to other leveraged institutions such as hedge funds in the form of reverse repos. Another part is invested in longer term, less liquid securities. The cost of borrowing is therefore tightly linked to short term interest rates in general, and the Federal funds target rate in particular. Broker-dealers hold longer term assets, so that proxies for expected returns of broker-dealers are spreads – either credit spreads, or term spreads. Leverage is constrained by risk; in more volatile markets, leverage is more risky and credit supply can be expected to be more constrained.

Increases in the Fed funds target rate are generally associated with a slower growth rate of broker-dealer assets. The first four columns of Table 4 show that this finding holds contemporaneously (column i and ii), it holds with a lag (column iii), and it holds in a forward looking sense (column iv). Put differently, expectations of increases in the Fed funds target are associated with declines in dealer assets, as are contemporaneous changes. Interestingly, we do not find that commercial bank total asset growth is significantly explained by changes in the Federal funds target. This finding is again consistent with two explanations. Either commercial bank balance sheets do not reflect the current positions of assets and liabilities properly, as their balance sheets have historically not been marked to market, or commercial banks do not manage their balance sheet as actively.

In all of the regressions of Table 4, we add GDP growth and PCE core inflation on the right hand side. Interestingly, neither growth nor inflation are significant determinants of broker-dealer total asset growth. It appears that the level of the Fed funds target is sufficient in capturing all of the macroeconomic information that is relevant for broker-dealers. We again find that commercial banks differ sharply in this respect; while their asset growth is not significantly determined by the Fed funds target, it is significantly positively correlated with GDP growth and negatively with core PCE inflation.

Financial market volatility, as measured by the VIX index of implied volatility, relates negatively to security broker-dealer asset growth, as higher volatility is associated with higher margins and tighter capital constraints, both leading inducing tighter constraints on dealer leverage. Credit spreads are positively related to dealer asset growth, as they proxy the profitability of a holding risky, illiquid, longer maturity assets.

Broker-dealers trade actively, so it would be desirable to study their balance sheet behavior at higher frequencies. Fortunately, the Federal Reserve Bank of New York collects financing data of the so called Primary Dealers at a weekly frequency. Adrian and Shin (2007) document that dealer total asset growth is tightly linked to dealer repo growth, as expansions and contractions of broker-dealer total assets are primarily financed by expansions and contractions in repos. In Table 5, we explain Primary Dealer repo borrowing by the same variables as in Table 4 (except for GDP and inflation which we had seen were insignificant anyway, and which are not available at a weekly frequency). We use 13-week changes and lags in the regression, in order to pick up correlations that occur at the same frequency as the quarterly data. We again find the negative co-movement of dealer balance sheets with changes in the Fed funds target, and we additionally uncover a positive relation between dealer repos and the term spread.

5. Monetary Policy Reactions to Balance Sheet Changes

We have seen in the previous two sections that dealer asset growth and market equity of broker-dealers and commercial banks explain future real growth of macroeconomic aggregates such as durable consumption and housing investment. In addition, we have seen that changes in the Federal funds target rate, and expectations of the future path of policy, are important determinants in broker-dealer total asset growth. Changes to the Federal funds target are further primarily determined by real growth and inflation (see Taylor (1993)). So how does monetary policy interact with the waxing and waning of financial intermediary balance sheets?

In financial crises, the tight connection between balance sheets and monetary policy certainly becomes apparent. In the fall of 1987 and again in the fall of 1998, the Fed funds target was cut in order to insulate the real economy from financial sector distress. While this interaction between monetary policy and financial sector distress is apparent in crises, what is the relationship between the two in normal times?

We find that higher balance sheet growth of broker assets is associated with a lower Fed funds target (see Table 6, column ii), except in crisis, when the sign reverses (see column iii). We also find that increases in dealer balance sheets tend to precede a lower Fed funds target in the next quarter.

One explanation for these findings may be the slow adjustment of the Fed funds rate, and the market’s anticipation of such slow adjustment. Once the interest rate cycle turns, banks expect more moves in the same direction in the future. Anticipating such future moves, banks expand balance sheets following initial cuts in the Fed funds rate. Then, the anticipated future cuts materialize. In the time series, the realized subsequent cuts trail the balance sheet expansions.

In Figure 9, we plot the impulse response function of the Fed funds target rate to a one standard deviation shock to the growth rate of security broker-dealer assets. The left hand panel draws the impulse response in crisis periods; the right hand side draws it in normal times. The left hand panel is familiar from the 1987 crash and the 1998 crisis; the Fed funds target was cut aggressively in response to financial sector distress. The right hand panel of the impulse response function is less familiar: it shows the procyclicality of Fed funds policy relative to dealer balance sheet growth.

As we outlined in section 2, when the relation between financial markets and monetary policy is discussed, the conclusion is often drawn that policy should only incorporate financial market variables insofar as they help to predict future macroeconomic variables such as future output and future inflation. It could be that broker-dealer asset growth in the policy rule is only significant because it reflects movements in asset prices that are helpful in predicting future macroeconomic variables.

Column (i) of Table 7 shows that the significance of security broker-dealer asset growth is unaffected when additional asset price controls are included in the regression. In Column (ii) of Table 7, we first regress security broker-dealer asset growth on four lags of inflation and GDP growth, and then add the predicted value from that regression to the right hand side of the policy rule regression. We see that both security broker-dealer assets and the value of security broker-dealer assets that is explained by past macroeconomic variables are both significant, so the security broker-dealer variable is not significant simply because it correlates with past macroeconomic variables.

In column (iii), we do the reverse; we first regress GDP growth and inflation on four lags of security broker-dealer growth, and add the predicted value of those regressions to the right hand side. This captures the degree to which asset growth is forecasting future macroeconomic activity. We again find that the asset growth variable becomes more significant and larger in magnitude, and the predicted values from the first stage regression are not significant. Finally, in the last column of Table 7, we show that commercial bank total asset growth is not significant in the policy rule regression. This again suggests that the transmission mechanism of monetary policy should take the liquidity and leverage of market based financial intermediaries explicitly into account.

We do not interpret the results of Tables 6 and 7 as saying that the balance sheets of broker-dealers are the only relevant measure of financial intermediary liquidity and leverage. There are other leveraged institutions (such as GSEs, hedge funds, to name but a view) whose potential to affect the economy have not been examined here. Our focus on broker-dealers is motivated by the hypothesis that they provide a useful window on the market-based financial system. Nor do we advocate any particular monetary policy rule that targets balance sheet growth. Considerations of Goodhart’s Law will be relevant here as for any simplistic macro policy rule. This point is especially relevant given our observation earlier that the association between balance sheet dynamics and Fed funds dynamics may be due to banks’ anticipation of future Fed funds changes.

One way we can visualize the policy response in setting the Fed funds rate to growth in the broker-dealer balance sheet is to compute the residual relative to a benchmark Taylor rule, and then plot the residual of the Taylor rule together with the series for the growth in broker-dealer assets. Such plots give an alternative representation of the regression results in Table 7. Figure 10 provides a panel of such plots. The bottom left panel plots the Taylor rule residuals from Table 3, column (i), which best fits the observed Fed funds target. The bottom right panel gives the residual from William Poole’s rule, as sketched in Poole (2005). We see the negative correlation between Taylor rule residuals and balance sheet growth clearly in the data.

7. Implications for Monetary Policy

In conventional monetary theory, the primary friction is the price stickiness of goods and services.11 Financial intermediaries do not play a role in these models other than as a passive player that the central bank uses to implement policy. Our findings suggest the need to give these players an independent role. Quantity variables seem to matter – especially components of financial intermediary balance sheets. Using the language of “frictions”, our results suggest a second friction, in addition to sticky prices. This second friction originates in the agency relationships embedded in the organization of market based financial intermediaries, which are manifested in the way that financial intermediaries manage their balance sheets.12 This is a friction in the supply of credit.

We are certainly not the first to study frictions in the supply of credit. There has been an extensive discussion of financial frictions within monetary economics (see, for example, the overview by Bernanke and Gertler (1995)). However, it would be fair to say that financial frictions have received less emphasis in the last few years. One reason for the lack of emphasis may be that the earlier literature that focused on commercial bank balance sheets or the borrowers’ balance sheets did not produce conclusive empirical results.

We conclude from our own study that the time is now ripe to redress the balance and bring financial institutions back into the heart of monetary economics. When we look at the appropriate balance sheet variables that reflect the underlying funding conditions ruling in the capital market, we stand a better chance of capturing the transmission mechanism through credit supply more fully. In our view, the appropriate balance sheet quantities are those that are marked to market, and hence reflect current market conditions. In this regard, we have seen that broker-dealer assets are more informative than commercial bank assets, and market equity of either commercial banks or broker-dealers do a better job of explaining future activity than (book) asset values. As commercial banks begin to mark more items their balance sheets to market, commercial bank balance sheet variables are likely to become more important variables for studying the transmission mechanism.

Fluctuations in the supply of credit arise from how much slack there is in balance sheets. The cost of leverage of market-based intermediaries is determined by two main variables – risk, and short term interest rates. The expected profitability of intermediaries is proxied by carry spreads such as the term spread and various credit spreads. Variations in the policy target determine short term interest rates, and have a direct impact on the profitability of intermediaries. When monetary policy is tightened at the end of an economic expansion, the slope of the yield curve becomes shallower and sometimes inverts. Intermediaries have to reduce the supply of credit when faced with a shallow yield curve.13 Deleveraging is particularly rapid when measured risks also increase. We have already argued that even small increases in repo haircuts can induce drastic reductions in leverage. As the economy slows, financial constraints may bind harder and prices fall more than in the absence of constraints.

To the extent that financial intermediaries play a role in monetary policy transmission through credit supply, short term interest rates matter directly for monetary policy. This perspective on the importance of the short rate as a price variable is in contrast to current monetary thinking, where short term rates matter only to the extent that they determine long term interest rates, which are seen as being risk-adjusted expectations of future short rates. Alan Blinder (1998, p.70) in his book on central banking puts it in the following terms:

"central banks generally control only the overnight interest rate, an interest rate that is relevant to virtually no economically interesting transactions. Monetary policy has important macroeconomic effects only to the extent that it moves financial market prices that really matter - like long-term interest rates, stock market values and exchange rates."

Current models in monetary economics emphasize the importance of managing market expectations. By charting a path for future short rates and communicating this path clearly to the market, the central bank can influence long rates and thereby influence mortgage rates, corporate lending rates and other prices that affect consumption and investment. The "expectations channel" has become an important consideration for monetary policy, especially among those that practice inflation targeting. Our approach entails quite different policy implications on some key issues. We mention three in particular.

One has to do with forward-looking guidance on future policy rates or the publication of the central bank’s own projections of its policy rate. Such communication not only has implications for market participants’ expectations of the future path of short rates, but also for the uncertainty around that path. If central bank communication compresses the uncertainty around the path of future short rates, the risk of taking on long-lived assets financed by short-term debt is compressed. If the compression increases the potential for a disorderly unwinding later in the expansion phase of the cycle, then such compression of volatility may not be desirable for stabilization of real activity. In this sense, there is the possibility that forward-looking communication can be counterproductive.

Secondly, there is a case for rehabilitating some role for balance sheet quantities for the conduct of monetary policy. Ironically, our call comes even as monetary aggregates have fallen from favor in the conduct of monetary policy (see Friedman (1988)). The instability of money demand functions that makes the practical use of monetary aggregates challenging is closely related to the emergence of the market-based financial system. As a result of those structural changes, not all balance sheet quantities will be equally useful. The money stock is a measure of the liabilities of deposit-taking banks, and so may have been useful before the advent of the market-based financial system. However, the money stock will be of less use in a financial system such as that in the US. More useful may be measures of collateralized borrowing, such as the weekly series on repos of primary dealers.

Finally, our results highlight the way that monetary policy and policies toward financial stability are linked. When the financial system as a whole holds long-term, illiquid assets financed by short-term liabilities, any tensions resulting from a sharp pullback in leverage will show up somewhere in the system. Even if some institutions can adjust down their balance sheets flexibly, there will be some who cannot. These pinch points will be those institutions that are highly leveraged, but who hold long-term illiquid assets financed with short-term debt. When the short-term funding runs away, they will face a liquidity crisis. The traditional lender of last resort tools (such as the discount window), as well as the recent liquidity provision innovations are tools that mitigate the severity of the tightening of balance sheet constraints. However, experience has shown time and again that the most potent tool in relieving aggregate financing constraints is a lower target rate. Past periods of financial stress such as the 1998 crisis was met by reduction in the target rate, aimed at insulating the real economy from financial sector shocks. In conducting monetary policy, the potential for financial sector distress should be explicitly taken into account in a forward looking manner.

In analyzing the interaction between financial stability and monetary policy in the time series of the last decades, it is important to keep in mind that the interaction of monetary policy and lender of last resort provision was successful in insulating the real economy from financial sector distress. So one can easily conclude that policies toward financial stability are more or less orthogonal to monetary policy analysis. To put it into Bayesian language, when analyzing the data (either via econometric or via structural approaches) with the prior that monetary policy and financial stability are orthogonal, one runs the risk of confirming that prior all too easily. The events of the past 12 months have clearly shown that now is the right time to reset the prior and to rethink the monetary policy transmission mechanism in a market based financial system.

The lesson for financial regulation is that the current risk-based capital requirements are powerless against the pull-back in lending that arises from a system-wide de-leveraging. When there are spillover effects, actions that enhance the soundness of one institution may end up by undermining another. The prudent curtailing of exposures by the creditors of Bear Stearns will be a run from the point of view of Bear Stearns itself. Secondly, even very safe assets such as reverse repos may be systemically important in that withdrawal of funding creates spillover effects on others.

As well as the implications for prudential regulation, balance sheet dynamics imply a role for monetary policy in ensuring financial stability. The waxing and waning of balance sheets have both a monetary policy dimension in terms of regulating aggregate demand, but it has the crucial dimension of ensuring the stability of the financial system. Contrary to the common view that monetary policy and policies toward financial stability should be seen separately, they are inseparable. At the very least, there is a strong case for better coordination of monetary policy and policies toward financial stability.

8. Concluding Remarks

Financial intermediaries lie at the heart of both monetary policy transmission as well as policies toward financial stability. The key thread to our discussion has been that the interaction of financial intermediaries’ balance sheet management with changes in asset prices and measured risks represents an important component in the transmission mechanism of monetary policy.

The current credit crisis has the distinction of being the first post-securitization crisis, where the market-based banking system has come into its own, and has exerted a profound influence in the playing out of events in the financial markets and the wider economy over the last twelve months.

We have shown that financial intermediary balance sheet management matters for he real economy, as well as for the soundness of the financial system. There are also important lessons for the conduct of monetary policy – some of them at variance with the current mainstream views on how monetary policy should be conducted. Due to their interaction with the leverage constraints of financial intermediaries, short rates are important prices in their own right, and a smaller term premium is associated with contractions in the supply of credit.