Journal Issue

An Overview of Macroprudential Policy Tools

Stijn Claessens
Published Date:
December 2014
  • ShareShare
Show Summary Details

I. Introduction

This paper reviews existing research on the motivations for macroprudential policies, possible specific tools, actual usage, and lessons from experiences. The recent wave of financial crises has led to a greater recognition of the large and at times adverse real economic effects of finance. It has also made clear that existing tools – whether microprudential, monetary, fiscal, or other policies – even when conducted properly and effectively in their own ways, do always not suffice to assure financial stability. Combined with a broader rethinking of macroeconomic and financial policies (e.g., Akerlof et al., 2014), this has led to a call for macroprudential policies, i.e., those policies aiming to reduce systemic risks arising from “excessive” financial procyclicality and from interconnections and other “cross-sectional” factors.

While the need for macroprudential policies is now largely accepted, many questions remain, starting from their motivations. 2 In principle, macroprudential policies should be motivated by externalities and market failures arising from various financial frictions and market imperfections that exist even when microprudential supervision and monetary policy are conducted effectively (which regrettably is often not the case in practice). Few theoretical analyses exist, however, to guide macroprudential policies this way and hardly any have been formally tested. Consequently, most often the design of policies has not started from first principles, but more arising from generic concerns. Related, the set of policies currently being considered is mostly based on existing microprudential and regulatory tools (i.e., caps on loan to value ratios, limits on credit growth, additional capital adequacy requirements, reserve requirements and other balance sheets restrictions), which have been given additional, macroprudential objectives, with forms of “Pigouvian” taxes and levies added.

Even though both the motivations and expected effectiveness of various policies are not well known, usage has often proceeded on an ad-hoc or experimental bases, especially in emerging markets. Evaluations of usage to date, mostly aimed at affecting developments in credit and housing markets, suggest that some tools can help reduce financial procyclicality and lower crisis risks. Notably, caps on loan to value and debt service to income ratios seem to help in reducing booms, and thereby busts, in real estate markets, major sources of instability. Reserve requirements and targeted levies on foreign exchange exposures also help in reducing system-wide vulnerabilities. And progress is being made to reduce the systemic risks created by large financial institutions using, among others, macroprudential policies.

Still, it is not well-known how policies are most effectively calibrated to circumstances (e.g., when and how much to raise or lower a countercyclical capital requirements) and adapted to country characteristics (e.g., which tools to use given specific financial market structures). Knowledge on which policies and how to use them for risks in capital markets is very limited. Neither is much known about the costs of policies. By definition, macroprudential policies distort some behaviors. Unless perfectly targeted at the source, i.e., where the externalities or market failures arise, which is unlikely, policies can worsen some resource allocations. And by constraining actions of agents, they can increase overall systemic risks.

Questions also arise on the best institutional design for usage, e.g., who is made in charge of macroprudential policies. Should these policies be conducted by the central bank, an existing microprudential or market conduct supervisory agency, a new “macroprudential” agency, or a committee composed of various agencies and others (such as representatives from the ministry of finance)? Institutional designs matter as the conduct of macroprudential policies can interfere with the primary objective of some agencies. A central bank may have more difficulty communicating its monetary policy stance when also in charge of macroprudential policy. And a microprudential authority may be less able to execute its goals when its staff needs multiple skills and is confronted with (at times conflicting) goals. A big concern would be if adopting these policies reduces the importance given to assuring properly conducted monetary policy – e.g., as when these policies become a substitute for monetary policy – or improving microprudential supervision, as these policies are essential in their own right and likely more important overall for reducing systemic risks.

A major issue, closely related to institutional design, is how the political economy of macroprudential policies will play out. By involving the government more directly into the allocation of resources, it (or the specific agencies in charge) will become (more) exposed to outside pressures. This risk needs to be acknowledged explicitly and addressed in institutional design(s), including accountability and transparency. Some policies may for example need to be presented to parliament for broader, public approval, to avoid exposing regulatory agencies to political risks (of ex-post not having “prevented” a crisis when it decided ex-ante not to set too low a LTV so as to allow first-time buyers to acquire a home).

Overall, while the greater system-wide focus is clearly welcome in light of recent crises, many unknowns still exist and a large research agenda remains. In the meantime, policy makers may want to move cautiously with adopting macroprudential tools and prioritize the ones they do and clearly taste their objectives. If in the end, only few policies are actually adopted, a key objective and possible main achievement could still be attained: which is greater appreciation of a more system-wide view of finance in all its aspects and of the various policies that can reduce the risk of crises and lower any excessive procyclicality.

The paper proceeds as follows. Section 2 presents the literature analyzing the motivations for macroprudential policies, considering both time-series, “procyclicality,” and cross-sectional, systemic risk, dimensions. Section III reviews the knowledge on the interactions of macroprudential policies with other policies, notably monetary, and international dimensions. Section 4 describes possible tools, choices and calibration strategies, and use to date. Section 5 presents findings of existing research and case-studies. Section 6 concludes with lessons and outstanding policy issues, including thinking on institutional design and for research.

II. Motivation for macroprudential policies

Financial crises have led to (renewed) attention on macroprudential policies. The recent global financial crisis and its aftermath have been painful reminders of the multifaceted interactions between macroeconomic and financial market developments, “macro-financial linkages.” They have led to (a call for) the adoption of macroprudential policies (as well as the review and reform of other financial policies and institutions).3 The fundamental rationales behind such policies, however, are not always clearly articulated. Proponents do not always start from the key externalities and market failures associated with activities of financial intermediaries and markets that can lead to excessive procyclicality and the buildup of systemic risk. While proper underlying focuses, procyclicality and systemic risks can arise from many factors, including aggregate shocks (e.g., commodity price shocks) and policy deficiencies (arguably, procyclicality and systemic risks mostly largely relate to weaknesses in the conduct of microprudential and monetary policies). These causes require their own approaches, including fixing deficiencies. These are not all causes that need to be addressed by macroprudential policies. Even though macroprudential policies can mitigate say the general financial or business cycle, or the presence of insufficiently disciplined large financial institutions, only externalities justify a macroprudential approach.

Identifying precisely the source of externalities operating through the financial system thus help determine the corresponding, specific macroprudential policies. While many, policy-oriented papers, notably at the BIS, had drawn attention to the need for a macroprudential approach (e.g., Borio, 2003, Borio and White 2003, White, 2006), these mostly did not adopt the formal perspectives of externalities. Several recent papers, however, have identified the externalities that can give rise to procyclicality and systemic risk, with Brunnermeier et al. (2009) one of the first to do so. De Nicolò, Favara and Ratnovski (2012), on which this section heavily draws, classify the ones known as follows (see also Allen and Carletti, 2011, Bank of England, 2011, Schoenmaker and Wierts, 2011):

1. Externalities related to strategic complementarities, that arise from the strategic interactions of banks and other financial institutions and agents, and which cause the build-up of vulnerabilities during the expansionary phase of a financial cycle;

2. Externalities related to fire sales and credit crunches, that arise from a generalized sell-off of assets causing a decline in asset prices, a deterioration of balance sheets of intermediaries and investors, and a drying up of financing, especially during the contractionary phase of a financial (and business) cycle; and

3. Externalities related to interconnectedness, caused by the propagation of shocks from systemic institutions or through financial markets or networks (“contagion”).

While one can classify externalities in other ways, the literature generally makes a similar distinction, that is, between externalities that are more of a time-series nature, i.e., give rise to procyclicality in good and bad times (under 1 and 2), and those more of a cross-sectional nature, i.e., due to interconnectedness (under 3). Table 1 organizes these along the vertical axis, with specific groups of tools (to be reviewed in section 4) along the horizontal axis. I review specific externalities under each heading next.

Table 1.The Macroprudential Toolkit
Policy Tool
Restrictions related to borrower, instrument, or activityRestrictions on financial sector balance sheet (assets, liabilities)Capital requirements, provisioning, surchargesTaxation, leviesOther (including institutional infrastructure)
Expansionary phaseTime varying caps/limits/rules on:
  • - DTI, LTI, LTV

  • - margins, hair-cuts

  • - lending to sectors

  • - credit growth

Time varying caps/limits on:
  • - mismatches (FX, interest rate)

  • - reserve requirements

Countercyclical capital requirements, leverage restrictions, general (dynamic) provisioningLevy/tax on specific assets and/or liabilities
  • - Accounting (e.g., varying rules on mark to market)

  • -Changes to compensation, market discipline, governance

Contractionary phase: fire-sales, credit crunchAdjustment to specific loan-loss provisioning, margins or hair-cuts (e.g., through the cycle, dynamic)Liquidity limits (e.g., Net Stable Funding Ratio, Liquidity Coverage Ratio)Countercyclical capital requirements, general (dynamic) provisioningLevy/tax (e.g., on non-core liabilities)
  • -Standardized products

  • -OTC vs. on exchange

  • -Safety net (Central Bank/Treasury liquidity, fiscal support)

Contagion, or shock propagation from SIFIs or networksVarying restrictions on asset composition, activities (e.g., Volcker, Vickers)Institution-specific limits on (bilateral) financial exposures, other balance sheet measuresCapital surcharges linked to systemic riskTax/levy varying by externality (size, network)
  • - Institutional infrastructure (e.g., CCPs)

  • - Resolution (e.g., living wills)

  • - Varying information, disclosure

Enhancing resilience
Dampening the cycle
Dispelling gestation of cycle

Externalities related to strategic complementarities. These externalities arise during the buildup of risks in the boom period and are due to various reasons, albeit many not well understood. Historical experiences suggest that financial intermediaries tend to assume exposures to common credit and liquidity risk in the upswing of a business cycle, amplifying financial cycles and contributing to asset price volatility.

One reason is because of strategic complementarities arising in market interactions between rational agents, meaning that the payoff from a certain strategy increases with the number of other agents undertaking the same strategy. One source relates to increased competition in boom times, which can affect economy-wide credit standards. In the presence of imperfect information, banks need incentives to assess borrowers’ risk. In boom times, incentives are less to screen potential borrowers due to lower rents prompted by fiercer competition. As a result, they reduce screening intensity and increase lending, worsening the pool of borrowers (Ruckes, 2004; Dell’Ariccia and Marquez, 2006; Gorton and He, 2008). This reverses with lower credit origination and less competitive pressures in the contractionary phase.

Other sources are reputational concerns and incentive structure for financial managers. When managers care about perceptions of ability, their credit, investment or other policies may be influenced by those of others (Rajan, 1994). Excessive long-term risk-taking can arise under pay for short-term performance (Acharya, Pagano, and Volpin, 2013). Benchmarking in various forms can lead to externalities, e.g., an institution reporting poor performance will be evaluated more leniently if many others do so similarly. Institutions then have incentives to maintain risky lending, hide losses or otherwise copy each others’ behavior until the buildup of risks forces them to “coordinate” to a strategy of loss recognition and external financing contracts (Allen and Saunders, 2003, review). Complementarities can come from institutional rules, such as mark-to-market (fair value) accounting or the required use of (similar) “value-at-risks” models (Adrian and Shin, 2010, 2014). Other sources appear more behavioral, as when investors chase similar investment opportunities (Shleifer 2000, and Barberis, 2013, review) or ‘neglect’ the possibility of rare but large shocks (Gennaioli et al., 2013).

Externalities can also arise from the optimal ex-ante response of agents to ex-post government interventions. The prospect of a bailout can mean strategic complementarities, as it can lead institutions, especially banks, to engage ex-ante in correlated asset choices. Anticipating that simultaneous failures trigger a bailout (to prevent a financial meltdown), banks may find it optimal to correlate risks to maximize the probability that any failure is a joint failure (Farhi and Tirole, 2012; Acharya and Yorulmazer, 2007). As firms mimic each others’ strategy, overall vulnerabilities increase whether through correlated asset choices, maturity and exchange rate mismatches or otherwise (Ratnovski, 2009; Allen and Carletti, 2011). These vulnerabilities in turn can lead to or deepen a financial bust.

Externalities Related to Fire Sales and Credit Crunches. A fire sale occurs when an investor is forced to liquidate an asset at a time when potential buyers are also troubled. Given limited buyers, the asset is sold at a price below its fundamental value, causing losses to the seller (Shleifer and Vishny 1992; Allen and Gale 1994). Not only does this asset fetch a lower price, but similar assets held by other financial institutions may also decline in value. This reduces the capitalization and ability to post assets as collateral of all financial institutions, forcing them to liquidate other assets. The new round of selling triggers further losses, new selling, etc., thus creating a pecuniary externality.

Fire sales and credit crunches are an obvious possibility for banks since they issue liquid liabilities to fund illiquid assets, exposing them to the risk of having to liquidate investments prematurely, as happened in the Great Depression (Rajan and Ramcharan, 2014). Although guarantees and central bank support, such as deposit insurance and liquidity facilities, reduce the likelihood of fire sales, their effectiveness can be limited when banks also rely on wholesale funding, as many did before the crisis. Or when other important players in the intermediation process, such as broker-dealers and ‘shadow banks,’ that do not (formally) benefit from such support, have to sell assets they can also depress the values of (similar) assets banks hold.

Fire sales can also trigger an external financing, credit crunch with adverse real consequences. As banks balance sheets are impaired they will cut back on their financing. And as asset prices decline and collateral becomes less valuable, final borrowers (corporations, households and sovereigns) have less access to finance, which worsens the real economy (Goldstein, Ozdenoren and Yuan, 2013). Even more generally, small financial shocks can trigger demand and other real sector externalities, including from capital flows, and aggravated by the zero lower bound on interest rates (see Korinek, 2011; Schmitt-Grohe and Uribe, 2012; Farhi and Werning, 2013; Korinek and Simsek, 2014).

Even though fire sales and credit crunch externalities manifest themselves in a downturn, the imbalances that sow the risks are often built up in booms. The reason is that atomistic agents take prices as given, but on aggregate the equilibrium price depends on their joint behavior. As they do not internalize the possible effects of a generalized fire sale on ex-post borrowing capacity, agents may overborrow, leading to excessive leverage and inflated asset prices (Bianchi, 2011, Caballero and Krishnamurthy, 2003, 2004, Lorenzoni, 2008, Jeanne and Korinek, 2010, and Stein, 2012; Manconi et al., 2012; Merrill et al., 2012; see Brunnermeier, Eisenbach and Sannikov, 2013, for a review).

Externalities Related to Interconnectedness. Banks and other financial institutions are very interconnected, with distress or failure of one affecting others. Spillovers can arise because of bilateral balance sheets (interbank) and other exposures (Allen and Gale, 2000; Diamond and Rajan, 2011; Perotti and Suarez, 2011), asset price movements (as discussed above), or aggregate feedback from the real economy (Bebchuk and Goldstein, 2011). Financial institutions can reduce but not entirely eliminate these risks as interconnectedness is often beyond their individual control and actors do not internalize their implications for systemic risk (Acemoglu et al., 2013). Also, interconnectedness may arise for genuine mutual hedging and diversification motives (Wagner, 2011). Related, as the financial networks literature (Allen and Gale, 2007; Gaia et al., 2011) has shown, while high interconnectedness mitigates the impact of small shocks by spreading them, it can amplify large shocks since they can reach more counterparties.

Interconnectedness externalities are particularly strong for systemically important financial institutions (SIFIs).4 Unlike smaller institutions, distressed SIFIs cannot easily be wound down, since they are often complex, operate internationally, provide unique services, or are backbones of the financial infrastructure, making them “too big to fail” (Strahan 2013 reviews). Historically, most interventions in SIFIs are then also de facto bailouts, which protect creditors (and sometimes even shareholders and often management) from the full scale of losses. The anticipation of bailouts perversely affects the (risk-taking) incentives for SIFIs and other market participants. It introduces a race among institutions to become systemically important, as this lowers the cost of funding, and reduces market discipline for creditors of SIFIs, especially the riskiest ones (Ueda and Weder di Mauro, 2012). In turn, these behaviors lead to aggregate risk-shifting and distorted competition (see IMF, 2014b).

The externalities of a time-series nature can interact with those of a cross-sectional nature to create systemic risks. Rapid growth of large financial institutions during a boom means procyclicality gets reinforced by contagion risks. Conversely there can be complementarities in the tools to be used to mitigate either source of externalities.

III. Interactions with other policies and international dimensions

Macroprudential policies are not the only policies aimed at economic (including price) and financial stability. Others include monetary, microprudential, fiscal, as well as competition policies. Macroprudential policies interact with these. Furthermore, some macroprudential policies can be motivated by the need to correct for the “distortions” introduced by other policies. Macroprudential policies can also have international spillovers, both inward and outward, and consequently there can be overlap and interrelationships with capital flow management (CFM) policies. How to coordinate macroprudential policies with these other policies? I review the (limited) literature on this briefly next, focusing mostly on interactions between monetary and macroprudential policies as most relevant and most studied.

A. Macroprudential and monetary policies

Both macroprudential and monetary policies are useful for countercyclical management: monetary policy primarily aimed at price stability; and macroprudential policies primarily aimed at financial stability. Since these policies interact with each other, each may enhance or diminish the effectiveness of the other. IMF (2013a and 2013b) reviews the (limited) literature on the conduct of both policies in the presence of these interactions. It first presents an ideal, but unrealistic benchmark, in which both policies perfectly achieve their objectives. It then addresses three questions: If macroprudential policies work imperfectly, what are the implications for monetary policy? If monetary policy is constrained, what is the role for macroprudential policies? And with institutional and political economy constraints, how can both be adjusted?

Benchmark world, when policies work perfectly. Monetary policy alone cannot be expected to achieve financial stability effectively or efficiently because its causes are not always related to the interest rate level or the degree of liquidity in the system (which monetary policy can affect). For mitigating the effects of financial distortions or when financial distortions are more acute in some sectors of the economy than in others, monetary policy is too blunt a tool. Pricking an asset price bubble for example can require large changes in the policy rate (Bean and others, 2010). Similarly, using macroprudential policies primarily for managing aggregate demand may create additional distortions by imposing constraints beyond where financial instability originates. For example, to limit general credit growth may be too harmful from an aggregate economic perspective. It is thus desirable, when both policies are available, to keep monetary policy primarily focused on price stability and macroprudential policies on financial stability.

Monetary policy, however, does affect financial stability: (i) by shaping ex-ante risk-taking incentives of individual agents, affecting leverage and short-term or foreign-currency borrowing (Dell’Ariccia and Marquez, 2013, review); or (ii) by affecting ex-post the tightness of borrowing constraints, possibly exacerbating asset price and related externalities and leverage cycles. Similarly, macroprudential policies can affect overall output by constraining borrowing and hence expenditures in one or more sectors. These side effects imply that one needs to consider how the conduct of both policies is affected. Most analytical papers to date find the sole presence of side effects to have no major implications for the conduct of both policies when policies operate perfectly.5 In particular, most Dynamic Stochastic General Equilibrium (DSGE) models suggest that monetary policy not to change markedly when macroprudential policies are also used, even when different types of shocks are considered. A big caveat is that most models employ limited representations of financial systems and related financial frictions, and often use assumptions that imply linear relationships, making both policies operate mostly similar (see Benes, Kumhof, and Laxton, 2014a and 2014b, for DSGE-models with non-linearities).

When either macroprudential or monetary policies work imperfectly. In the real world policies do not operate perfectly. Furthermore, neither policy is immune to political pressures and time inconsistency issues. As such, the conduct of both may need to be adjusted to consider the weaknesses in the other, but how is conceptually and empirically unclear. Weaknesses in macroprudential policies mean monetary policy more likely needs to respond to financial conditions. Indeed, in models where macroprudential policy is absent or time invariant, but with financial “distortions” still present, optimal monetary policy responds to some degree to financial conditions, in addition to output and inflation (Curdia and Woodford, 2009, Carlstrom and Fuerst, 2010, Adam and Woodford, 2013). By extension, with imperfectly targeted or effective macroprudential policies, monetary policy may need to respond to financial conditions and “lend a hand” in achieving financial stability, also because of its more general reach (e.g., as “it gets in all of the cracks;” see Stein, 2013). This “leaning against the wind” argument is, however, not generally accepted (e.g., compare Bernanke and Gertler, 2001, with BIS, 2014; see also Yellen, 2014).

Similarly, macroprudential policy may need to respond to aggregate developments related to financial activities when monetary (and other) policies are constrained, as with economies pegging their exchange rate or in currency unions. The case of the euro area shows the economic (and financial) risks that arise when booms are not (or cannot) mitigated at the national level. When the effective monetary stance gives rise to macroeconomic imbalances or excessively strong overall risk-taking incentives, national macroprudential policies may need to be used, especially when other policies are imperfectly coordinated internationally (e.g., as when foreign lenders are not constrained from lending to the country).6 Of course, the macroeconomic risks need to be related to financial activities (e.g., a housing boom that is of macroeconomic concern, even when completely financed internationally). And when monetary arrangements are not adequate, strengthening monetary policy’s effectiveness will likely be better than using macroprudential policies as imperfect substitutes.

B. Interactions with other policies

There are, besides monetary policy, many policies that can interact with or condition the use of macroprudential policies. These include fiscal, microprudential, and other structural policies. I review the research in these areas briefly.

Fiscal policy. Tax policies can contribute to systemic risk when they encourage leverage, as when interest payments are tax deductable, or affect asset prices (see De Mooij, 2011, Keen and De Mooij, 2012). Macroprudential authorities have therefore an interest in the correction of such biases. Even when not contributing directly to risks, taxes can affect the conduct of macroprudential policies. Real estate taxes (property taxes, stamp duties) can be capitalized into house prices (e.g., Van den Noord, 2005), making (future) tax policies possibly relevant for financial stability. Since various Pigouvian taxes and levies can address systemic externalities (IMF 2010), coordination between macroprudential and fiscal agencies may be needed. Little is known though on the quantitative importance of these aspects. And fiscal policy in the aggregate matters as it can counter (or be a source of) procyclicality.

Microprudential. Macroprudential policies presume effective microprudential regulation and supervision. Most often, when conducted properly microprudential objectives will be aligned with macroprudential policies, but there can be conflicts (Osiński, Seal, and Hoogduin, 2013; Angelini, Nicoletti-Altimari, and Visco, 2012). This is most clear in bad times when a macroprudential perspective may suggest relaxing regulatory requirements – as they impede the provision of credit to the economy or contribute to fire-sale effects, while the microprudential perspective may seek to retain or tighten requirements – so as to protect the interest of depositors of individual banks or investors. In good times, conflict of interests are less likely, e.g., both authorities will ask banks to build up buffers, but the macroprudential perspective will likely still call for greater prudence. Some of this conflict is institutionally related. For example, accounting indicators, more often used by microprudential authorities, likely give a more positive picture of an institution’s balance sheet in boom time than a system’s view would. While recognized, how to address these issues largely remains an open question. And, as also argued by Jeanne and Korinek (2013), an ex-post strategy of cleaning up after a crisis can be part of an efficient approach to “managing” risks, thus calling for crisis management to coordinate with ex-ante policies.

Other, structural policies. Conflicts can also arise in the design of structural policies, as when risks arise from how microprudential policies are conducted. For example, a very high loan to value ratio is likely to increase the incidence of real estate booms. Even when set optimally from a microprudential perspective, capital requirements can increase overall procyclicality (Angelini et al. 2010; Repullo and Suarez, 2013). Or a public safety net, including deposit insurance, while reducing the risk of runs on individual institutions, can give rise to greater system risks (Demirguc-Kunt and Detragiache, 2002; Demirguc-Kunt, Kane and Laeven, 2008). The use of ratings may introduce (more) procyclicality (Amato and Furfine, 2004). And accounting rules aimed at greater transparency and fostering more market discipline can mean more procyclicality as chances of fires-sales increase when institutions mark asset to market (Leuz and Laux, 2010; Ellul et al., 2012,). Also, by affecting incentives for risk-taking, there can be an inverse U-shaped relationship between bank competition and financial stability (Allen and Gale 2004; see further Beck, 2008, Ratnovski, 2013). And house price developments will be importantly affected by land use and construction policies. These examples show that macroprudential policies need to be coordinated with many policy areas, in part as the need for them arises exactly from these other policies.

C. International coordination

International financial and policy spillovers. The de-facto international financial integration of most countries affects the desired use of and effectiveness of macroprudential policies. Given financial integration, cross border spillovers may arise as when the financial cycle is in an upswing in one country but in a downswing in another, or because countries are (or are not) using macroprudential policies.7 As argued by Shin (2012) and shown by Rey (2013) and others, there is much commonality to financial cycles globally, suggesting policies are naturally coordinated. The cycle appears largely driven by conditions in major advanced countries, however, and it is thus not obvious that the commonality itself or addressing it from the major countries’ perspectives alone is optimal for all countries. Regardless, being financial integrated means countries have less control over their own financial stability.

Policy spillovers can also arise (more likely) when countries vary in policies or calibrations to deal with similar risks, or in policy effectiveness. Aiyar, Calomiris, and Wieladek (2014) show that foreign bank branches increased their lending in the UK in response to tighter measures applied to local banks, a sign of cross-border competition and regulatory arbitrage. Or when policies are not effective at the source country to stem risks related to outflows, recipient countries can be negatively affected if they cannot stop inflows. Spillovers can arise when institutions adjust to local restrictions by decreasing or increasing cross-border activities. Aiyar, Calomiris, Hooley, Korniyenko and Wieladek (2014) show that, as supervisors required UK-based banks and subsidiaries to meet higher capital requirements during the 2000s, local banks lend less abroad which may or not have been optimal. Spillovers can also arise when institutions from country A reduce cross-border flows to country B in response to its rules and increase flows to country C (see Forbes, Fratzscher, Kostka, and Straub, 2012 for the case of capital controls).

Even though the scope for (policy) spillovers is large, the case for international coordination and cooperation depends on the presence of negative externalities. While the welfare gains from coordinating macroprudential policies have not yet been much analyzed (see Jeanne and Korinek, 2014 for some thoughts), analysis on multilateral aspects of CFM tools (e.g., Ostry, Ghosh, and Korinek, 2012) relates. Building on this, Korinek (2014) argues that spillovers can lead to inefficiencies under three circumstances: if policies are “beggar-thy-neighbor;” if policy instruments to deal with externalities operate imperfectly; and if global markets are incomplete or restricted (see also Brunnermeier and Sannikov, 2014). And Jeanne (2014) shows the need to coordinate when some countries are in a liquidity trap as the global real interest rate cannot adjust sufficiently.

While there can be some (limited) scope in principle, policy coordination is hard in practice (see Ostry and Ghosh, 2013). And indeed so far, coordination has been limited, with instruments and mechanisms only defined for the countercyclical and systemic capital surcharges in Basel III. While more progress can be envisioned, (policy) spillovers are likely to remain. For individual countries, CFM tools may then sometimes be part of a useful policy response (IMF 2012c). This raises how to coordinate between CFM tools and macroprudential policies. Here Korinek and Sandri (2014) provide a useful dichotomy: macroprudential policies should address externalities related to domestic credit and CFM tools those related to exchange rate movements. How to make this operational, however, remains to be determined (see further Ostry et al., 2012).

IV. Possible macroprudential tools and actual uses

This section first reviews the toolkit available in principle, and then the actual use of policies.

A. The Toolkit Available

Many macroprudential tools have been proposed and some have been used, even before the recent crisis. The toolkit available in principle is quite large and includes existing microprudential and other regulatory tools, taxes and levies, and new instruments. Table 1 categorizes these in a 3-by-5 matrix (for other classifications, see CGFS, 2010, IMF 2011b, and ESRB, 2014). Most tools considered to date apply to the banking system, mainly given the existence of microprudential tools adaptable to macroprudential objectives and related more extensive theory and knowledge. A lack of understanding of possible externalities in other financial market segments is, however, also at play (e.g., as in shadow banking, see Claessens, Pozsar, Ratnovski, and Singh, 2012 for a review; and in insurance, see IAIS, 2013). Note further that many instruments (can) also serve other policy objectives, including, besides microprudential, assuring consumer protection or fostering greater competition, and that other tools can be considered.

The matrix covers along the vertical axis the three goals (as per section 3) and along the horizontal axis five set of tools: a) quantitative restrictions on borrowers, instruments or activities; b) capital and provisioning requirements; c) other quantitative restrictions on financial institutions’ balance sheets; d) taxation/levies on activities or balance sheet composition; and e) other, more institutional-oriented measures, such as accounting changes, changes to compensation, etc. Except for a), which aims to affect demand for financing, all can be seen as affecting the supply side of financing. The first four measures are meant to be time-, institution-, or state-varying, while the fifth one is more structural.8

Tools under the 15 (3*5) combinations include those correcting (for factors that can give rise to) externalities and market failures or compensating for policies that can contribute to adverse financial dynamics (such as the pro-cyclicality introduced by microprudential capital requirements). Besides mapping each tool to specific externalities, with some tools possibly mitigating more than one, tools are ideally also mapped to intermediate targets, such as changes in credit, leverage, asset prices, interconnections and the like. Knowledge on what intermediate indicators to use and how to calibrate tools is still limited, however (see further IMF, 2013c, 2013d).

Use and Calibration of Macroprudential Policies. The preferred use of policies, in their extensive (whether or not to use a specific tool) and intensive margins (how much to use it), will vary by the degree of amplification in the financial (and real) sector cycles, exposures to systemic shocks and risks, and the effectiveness of (specific) policies. As such, many dimensions come into play, including a country’s structural, institutional and financial market characteristics. Models provide some limited guidance for use and calibrations.

DSGE-models with financial frictions can suggest an optimal mix of macroprudential and monetary policies (e.g., Kannan, Rabanal, and Scott, 2009; Quint and Rabanal, 2013). Or some historically derived indicators of (excessive) procyclicality and systemic risks, e.g., a notion of a “credit gap,” can suggest specific dynamic provisioning surcharges (Drehmann et al. 2011). And a Pigouvian tax on SIFIs can be made to depend on measures reflecting the size of interconnectedness externalities (Kocherlakota, 2013).

Many questions exist, however, on what measures reliably indicate systemic risk build-up, with both Type I and II errors, and on the time horizon at which risks can be detected. Notably, how to account for country circumstances and characteristics is still unclear. Obviously, some factors are likely relevant: the overall depth of a country’s financial system, which differs vastly; financial structure, e.g., the importance of banks versus capital markets, with institution-based measures likely of greater importance than borrower-based measures when most financing comes from a regulated system;9 the industrial organization and ownership structure, since a more concentrated system makes the application of tools easier, or because domestic, state-owned and foreign banks react differently to policies.

International financial integration and exchange rate regime matter as well. Openness affects exposures, both directly, as regards to say capital flows risks, and indirectly, given the strong links between behavior of capital flows and banking vulnerabilities (e.g., Hahm, Shin, and Shin, 2013; Cerutti, Claessens, and Ratnovski, 2014). Financial integration also affects how effective policies may be. A very open capital account and large foreign bank presence make circumvention more likely. And with a fixed exchange rate, monetary policy cannot be a possibly complementary tool. These and other considerations will affect which policy is best and whether CFM tools can complement (e.g., Hahm, Mishkin, Shin, and Shin, 2011).

Preferred use could also vary by the availability and effectiveness of fiscal and microprudential policies. High public debt makes countercyclical fiscal policy harder, making macroprudential policies more important. Microprudential supervision may face greater challenges in some markets. Institutional (e.g., lack of data, know-how and skills in supervisory agencies), political economy, and other constraints may lead countries to adopt macroprudential policies in specific ways. Use could also vary with other tools available to mitigate systemic risks. Stress tests could complement macroprudential policies.10

Furthermore, financial reforms are proceeding in various ways, some coordinated (e.g., new liquidity requirements) and some country-specific (e.g., Vickers, Volcker and Liikanen rules), making overall institutional environments in flux and requiring further adaptations.

B. Actual Use of Macroprudential Policies

Information on the actual use of macroprudential policies is limited, in part because (the use of) tools are not always clearly identified (some countries have adopted more explicit frameworks, but most have not yet). Some data have nevertheless been collected for some 65 countries by the IMF (see Lim et al., 2011, and Cerutti et al., forthcoming, for exact coverage and data definitions). The seven specific instruments reviewed here are: caps on loan-to-value (LTV) and debt-to-income (DTI) ratios, limits on credit growth (CG), limits on foreign lending (FC), reserve requirements (RR), dynamic provisioning (DP), and counter-cyclical requirements (CTC). One can organize these measures along the categories of Table 1: those aimed at borrowers (caps on LTV and DTI ratios); those aimed at financial institutions’ assets (CG and FC) and liabilities (RR); and those aimed at building buffers (DP, CTC).

Usage of policies in general. In the sample, 42 countries – of which 28 are emerging and developing and 14 advanced – implemented at least one instrument once during 2000-2013, while 23 never used any. Most usage is by emerging markets, consistent with their greater needs, being more exposed to external shocks, including from volatile capital flows, and having more “imperfect” and generally less liberalized financial systems with more “market failures.”

Countries use LTV ratios the most (Table 2, column 1): 24 used it at least once. Next are DTI (23), FC (15), RR (10), DP (7), CG (6), and CTC (5). Weighting by the length of time and relative to overall use (column 2), most often used is again LTV, 28% of country-year combinations when a policy was used. Following closely behind is DTI (24%), then RR (15%), FC (14%), CG (9%), DP (8%), and finally CTC (2%).

Table 2.Overall Use of Macroprudential Instruments
Type of InstrumentTotal CountriesFrequency of UseEmerging MarketsAdvanced CountriesFrequency of EMs-yearFrequency of ACs-year
Total by classification42100%2814100%100%
Notes: Countries are classified into advanced versus emerging countries (source: IMF World Economic Outlook, April 2014). The frequency of use is the ratio of country-year pairs using a particular instrument to the total number of country-year pairs using a macroprudential policy (e.g., countries used LTV ratio limits 28% of the time during 2000-2013, compared to DTI ceilings 24% of the time). Source: IMF Survey as reported in Cerutti et al 2014.
Notes: Countries are classified into advanced versus emerging countries (source: IMF World Economic Outlook, April 2014). The frequency of use is the ratio of country-year pairs using a particular instrument to the total number of country-year pairs using a macroprudential policy (e.g., countries used LTV ratio limits 28% of the time during 2000-2013, compared to DTI ceilings 24% of the time). Source: IMF Survey as reported in Cerutti et al 2014.

Usage of policies by country groupings. Use varies among countries (columns 3 and 4). In advanced countries, LTV and DTI ratios are used the most, while other policies are rarely used. Differences are starker considering how long policies are used (columns 7 and 8). Emerging markets use more policies and longer than advanced countries do and tend to favor more foreign exchange and liquidity related policies (FC, RR), maybe due to their concerns with large and volatile capital flows and related systemic risks. But they also use CG more often, possibly as their systems are less liberalized. Advanced countries prefer the demand for credit related LTVs (55%) and DTIs (20%), perhaps out of concern with excessive leverage. The increased usage since the late 1990s by more countries reflects the growing recognition of the policies. Overall though policies were used four times more intensively by emerging markets than by advanced countries right before the crisis, with this ratio declining to 3.3 as advanced countries started to use them.

V. Research and other evidence on experiences

This section reviews the literature on the effectiveness of macroprudential policies. Most are cross-country, aggregate analyses, investigating cyclical aspects and notably in credit and housing markets. Some more micro, case studies exist, also largely focused on cyclical aspects, and some work focuses on cross-sectional, systemic risk aspects.

A. Aggregate, Cross-Sectional Studies, Focusing on Procyclicality

Several papers have analyzed effects of policies on various measures of financial vulnerability and stability (see also ECB, 2012, IMF, 2013a-d; notably IMF 2013d, Table 4 and 5, and ESCB, 2014, for reviews). Lim et al. (2011) document, using cross-country regressions, some policies being effective in reducing the procyclicality of credit and leverage. Specifically, tools such as LTV and DTI, ceilings on credit growth, RR, and dynamic provisioning rules can mitigate procyclicality. IMF (2013b) investigates, also in a cross-country context, how (changes in) policies affect financial vulnerabilities (credit growth, house prices, and portfolio capital inflows) and the real economy (output growth, and sectoral allocation, i.e., the share of residential investment), considering also whether effects are symmetric between tightening and loosening. Overall, both (time-varying) capital requirements and RRs significant affects credit growth, LTV limits and capital requirements (but not RRs) strongly affects house price appreciation rates, and RRs reduce portfolio inflows in emerging markets with floating exchange rates. They find no significant indication of asymmetric responses. LTVs appear to impact overall output growth, maybe through reducing construction investment, but no other policies do so.

Crowe et al. (2011) find that policies such as maximum LTV have the best chance to curb a real estate boom. They also argue that their narrower focus reduces their overall costs. And, measures aimed at strengthening the banking system (such as dynamic provisioning), even when failing to stop a boom, may still help to cope with the possible bust. IMF (2011a) finds LTV tools to be effective in reducing price shocks and containing feedback between asset prices and credit. Vandenbussche, Vogel, and Detragiache (2012) find that capital ratio requirements and non-standard liquidity measures (marginal reserve requirements on foreign funding or linked to credit growth) helped slow down house price inflation in Central, Eastern and Southeastern Europe.

Dell’Ariccia et al. (2012) find that macroprudential policies can reduce the incidence of general credit booms and decrease the probability that booms end up badly. Using specific policies, they find credit and interest controls and open foreign exchange position limits to be significant in most regressions. Consistent with a focus on vulnerabilities, policies reduce the probability of a boom that ends up in a financial crisis or subsequent economic underperformance, i.e., policies reduce the risk of a bust, while simultaneously reducing how the rest of the economy is affected by troubles in the financial system.

Claessens et al. (2013) investigate, using panel GMM regressions, how changes in balance sheets of some 2800 banks in 48 countries over 2000-2010 respond to specific policies. Controlling for endogeneity and country characteristics and macroeconomic policies (by including among others countries’ lagged GDP growth and interest rates), they find that measures aimed at borrowers – LTV and DTI caps, and CG and FC limits – are effective in reducing the growth in bank’s leverage, asset and noncore to core liabilities growth. While countercyclical buffers (such as RR, PRD, and DP) also help mitigate increases in bank leverage and assets, few policies help stop declines in adverse times, consistent with the ex-ante nature of macroprudential tools and the challenges in adjusting policies in times of stress (e.g., how quick and far to allow banks to reduce their capital buffers).

Kuttner and Shim (2013), using data from 57 countries spanning more than three decades, investigate whether nine non-interest rate policy tools, including macroprudential, help in stabilizing house prices and housing credit. Using conventional panel regressions, housing credit growth is significantly affected by changes in the maximum debt-service-to-income (DSTI) ratio, maximum LTVs, limits on exposure to the housing sector, and housing-related taxes. But only the DSTI ratio limit significantly affects housing credit growth when they use mean group and panel event study methods. And, of the policies considered, only a change in housing-related taxes discernible impacts house price appreciation.

Zhang and Zoli (2014) review the use of key macroprudential instruments and capital flow measures in 13 Asian economies and 33 other economies since 2000 and study their effects. Their analysis suggests that measures helped curb housing price growth, equity flows, credit growth, and bank leverage, with loan-to-value ratio caps, housing tax measures, and foreign currency-related measures especially effective.

While suggestive, these studies come with many caveats. Many struggle with identification and endogeneity – e.g., as policies are adopted when the cycle is already up – and other biases, which can only partially be addressed by econometric techniques (such as GMM). Almost all face challenges in controlling for other country characteristics, including the quality of microprudential supervision. Few consider both the use of a policy and its intensity (e.g., the presence of a LTV and its level, whether set high or low) or differentiate by phase of the cycle – e.g., to investigate whether policies help most in mitigating booms or building buffers for busts. Almost all focus on credit and housing developments, and none study risks in capital markets and non-bank financial institutions. And, obviously, not one identifies the specific externalities or market failures policies are supposed to address, but rather mostly analyze manifestations of financial cycles, especially asset prices, that are supposedly of “concern” (e.g., studies are less clear in how LTVs reduce systemic risks, rather than controlling house prices per se).

Nevertheless, both analytical reasoning and existing evidence suggest some basic directions. Higher sectoral capital requirements, such as the CCB and other capital surcharges, by definition can help in increasing resilience by creating additional buffers. Direct measures, such as caps on LTV and DTI ratios, can likely limit mechanisms creating positive feedback between credit growth and asset price inflation. Conversely, such caps can enhance resilience and reduce the risks of fire-sale dynamics.

B. Case and Other Studies on Procyclicality and Cross-Sectional Risks

Country-specific “case” studies investigating the role of macroprudential policies in reducing financial procyclicality often focus on specific risks or market segments, and use micro data. Jiménez et al. (2012) find for Spain that dynamic provisioning can be useful in taming credit supply cycles, even though it did not suffice to stop the boom (see also Saurina, 2009). More importantly, during bad times, dynamic provisioning helps smooth the downturn, upholding firm credit availability and performance during recessions. Using sectoral data, Igan and Kang (2012) find LTV and DTI limits to moderate mortgage credit growth in Korea. And policies appear to reduce real estate cycles in Hong Kong (Wong, Fong, Li and Choi, 2011).

Some use of macroeconomic tools can be interpreted with a macroprudential perspective. Dassatti Camors and Peydro (2014) investigate the effects of a large and unexpected increase in RR in Uruguay in 2008 using detailed, bank-firm matched data. Their evidence suggests some ambiguous results. On one hand credit growth declines on aggregate, but at the same more risky firms get more credit. They also document that larger and possibly more systemic banks are less affected. There may thus be tradeoffs using RR, since less credit does not necessarily mean less system risks (RR may still be beneficial as macroeconomic tool).

The UK is a case where the use of microprudential tools over the period 1998-2007 has been interpreted with a macroprudential perspective. Aiyar, Calomiris and Wieladek (2013) show that bank-specific higher capital requirements dampened lending by banks, with quite strong aggregate effects: an increase in requirements of 1% reduced bank lending by between 5.7% and 7.6%, a high multiplier.11 Tighter monetary policy also reduced the supply of lending, but not that of large banks.

A case study analyzing house prices for Israel (IMF, 2014a) shows that macroprudential measures have effects, but only over the six-month period following adoption, with LTVs more effective than DP and CTC. And while policies reduce somewhat transactions, evidence is limited that they contribute to curb house price inflation. Israel also shows that macroprudential policies can create challenges for communication and accountability, even more so when loose monetary policy conditions, proper in their own right, provide opposing forces. And they can have social and political sensitivities, notably when first-time buyers are excluded from the housing markets. Other countries, like Canada and Sweden, have been facing similar challenges, with, in environments of low interest rates, strong increases in house prices and household debt, even though they use some macroprudential policies.

To limit systemic liquidity risks in Korea, a macroprudential stability levy on short-term foreign exchange lending and a core funding ratio were imposed (Shin, 2010). Analysis (IMF, 2012a) suggests that these measures contributed to a shift away from short-term foreign exchange funding, mostly driven by shifts of foreign branches towards longer term funding. This in turn may have made, as Bruno and Shin (2014) show, interbank capital flows less sensitive to global financial conditions compared to other Asian countries. Aregger, Brown and Rossi (2013) find for Switzerland, where taxes vary across cantons, that higher capital gains taxes exacerbate house prices dynamics while transaction taxes have no impact.

Basel III includes a countercyclical buffer, CCB, and BCBS (2010a) has suggested a methodology for setting it, with bodies such as the ESRB (2014) providing further guidance for their regional (EU) jurisdictions. The CCB is loosely calibrated on the probability and cost of systemic crises (see Drehmann and others, 2010). The guidance suggests increasing capital if credit to GDP rises substantially above its trend value, e.g., up to 2.5 percent of risk-weighted assets if the so-called credit-to-GDP gap rise above 10 percentage points, with room for discretion whether and when to invoke (and an ability to impose a higher CCB). Some countries (UK, Switzerland, India, and New Zealand) are implementing the CCB.12 As its incentive effects are likely limited, its value derives mainly from providing higher buffers in bad times. Questions remain though, notably on what basis to release the CCB when the cycle turns (some favoring adverse developments in asset prices, which are timelier; others in credit markets, which are less subject to interpretation), but also on how to adapt the CCB when credit is a small part of overall financial intermediation (as in the US).

In terms of reducing systemic risk of a cross-sectional nature, the BCBS (2013) has agreed on a methodology for the systemic capital surcharges for G-SIBs and D-SIBs and determined (and published) the individual surcharges (from 1% up to 3.5%) for the 29 G-SIFIs identified (FSB, 2013). Some individual countries, such as Austria, Denmark, Singapore, and Sweden, have gone beyond the BIII standards and put in place higher capital requirements for their large domestic banks, and a number of other countries plan to do so as well. And the US has adopted a more stringent leverage requirement for large banks, while Switzerland has additional contingent capital and leverage requirements for its large institutions. No studies exist, however, on the impact and effectiveness of these measures or of the CCB.

Otherwise, work has mostly focused on the identification and measurement of systemic risks due to contagion and other spillovers in interbank and other financial markets (Bisias et al. 2012, and Adrian, Covitz, and Lang, 2013, reviews tools for financial system monitoring, as applied largely to the US; see Arsov et al. 2013 for a more general review). Many central banks, supervisory agencies and international agencies now also supervise their large financial institutions, including insurance corporations, more closely (as the “too big to fail” problem is still prevalent; see further IMF, 2014b, and Laeven, Tong and Ratnovski, 2014). Many also conduct (regular) stress tests, which, inter alia, help to identify those institutions more likely to cause systemic distress.13 Other relevant efforts underway are new regulations for shadow banking (Adrian and Ashcraft, 2012) and financial infrastructure reforms.

So far, however, these exercises are mainly aimed at supervisory actions – e.g., asking for more capital or winding down of weak institutions – or institutional and structural changes – e.g., greater use of central clearing counterparties. They could though also be linked to the use and intensity of macroprudential tools. Network and interconnection models, and other such cross-sectional tools, for example could help with designing and calibrating tools or infrastructures. So far, however, the mapping between risks and tools (e.g., how to map risk of contagion into preventive measures) seems not clear enough for policy applications. These country case and other studies advance over the cross-country analyses in that they are better at identifying specific channels. At the same time, they come with the caveat that they do not control for, or allow one to explore, the role of different country circumstances and conditions. Being focused on one segment of the financial system, many often do not analyze circumventions and risk transfers to other, possibly less regulated parts. The ideal, analyzing comprehensive micro data for many countries, however, has so far been largely elusive.

C. Costs and Tradeoffs

By constraining borrowing and hence expenditures in one or more sectors of the economy, macroprudential policies can affect overall output. Conceptually, the transmission of macroprudential policies to financial and real variables could vary across tools (Kashyap, Berner and Goodhart, 2011, provide a model to assess the costs and benefits of various policies). Obvious examples are CTC and RR that may affect overall lending and output, whereas LTV limits have more sectoral impacts. Policies can in principle also affect the overall price setting process (i.e., by making the allocation of resources across sectors less flexible). And these effects may differ not just by tool used but also by the stage of the country’s financial or economic cycles.

Actual quantitative effects of policies on the real economy, however, are not well known, in large part because due to a lack of data and experiences. Some papers nevertheless try to assess these impacts. The, necessarily preliminary, empirical analysis finds the short-run effects on overall output to be small, even for broad-based tools, such as capital and liquidity requirements (IMF, 2013b).14 Moreover, some of the real sector costs can be countered by appropriate variations in monetary policy (unless it itself is constrained). But these findings remain very tentative with work on the relative strength of the effects across tools even more limited (see further CGFS, 2012).

Importantly, as with other “risk”-based policies (e.g., monetary policy which takes actions under uncertainty), macroprudential policies will have to weigh Type I and Type II errors. Analytical frameworks for assessing the associated costs and benefits (as laid out in IMF 2012b, De Nicolò, Gamba and Lucchetta 2012, Blancher et al. 2013; and Arregui and others 2013a, b), while sometimes still basic (e.g., Elliott, 2011), can help to assess tradeoffs of policies in terms of specific parameters (to be estimated or judged) – like the probability of crisis, the loss given a crisis and the cost of a policy decision – and thereby offer some guidance.

VI. Broader lessons and remaining issues for research and policy making

The recent crisis has led to a reexamination of policies for macroeconomic and financial stability. Part of the evolving thinking involves the adoption of a macroprudential approach, to mitigate boom-bust patterns and systemic risks in financial markets. Many countries, advanced and emerging, have signed on to this new paradigm. Its objectives, conceptual foundations and exact features, however, are still to be determined. I highlight some major knowledge gaps and where practices at times are confused.

On the conceptual side, what the debate, and some of the literature, not always recognizes is that correcting externalities needs to be seen as an intermediate target. Only by adopting policies that control or reduce externalities can one mitigate the market failures that lead to systemic risk. As such, each externality ideally is corrected by a specific tool (of course, tools need not differ by externality and can complement each other; capital (surcharges) for example may be important in reducing several externalities). Regardless, the start is a clear recognition of the causes for systemic risk. Here much more analytical work on specific externalities arising in financial intermediation is needed. Without this, the danger arises that macroprudential policies are used for general management of business and financial cycles, which introduces distortions, adversely affecting resource allocation, undermines transparency and accountability, and (further) exposes regulators to political pressures.

With actual experiences still limited, evidence on the effectiveness of specific tools is only slowly accumulating and comes with many (economic and econometric) caveats, making it difficult to determine which policies to use and when to tighten or loosen them. Furthermore, while addressing one distortion may reduce some manifestations of risks, it can also worsen overall financial stability. Also tools may not be able to reach some activities that can lead to systemic risks, and tighter regulations create stronger incentives for circumvention, risking vulnerabilities building up outside of the regulatory perimeter and policymakers’ sight. Moreover, institutional constraints may impede the optimal deployment of instruments. Cooperation and coordination with microprudential supervisory agencies and international may be legally or institutionally difficult. Furthermore, while more data are being collected (e.g., Financial Soundness Indicators (FSI) and SIFI data by the IMF and BIS respectively),15 deficiencies in quantity and quality of data can hinder analyses and calibrations (Cerutti, Claessens and McGuire, 2014; Heath, 2013; and Brunnermeier and Krishnamurthy, 2014).

Many of these factors will vary across countries, with developing countries for example likely facing more institutional and data hurdles as well as greater risks of discretionary policy implementations. Overall the best approaches given specific country conditions and characteristics remain thus largely open questions (see Acharya, 2013, and Shin, 2013).

Besides challenges in measuring risks and calibrating tools are political economy pressures and risks. These of course relate in part to limited knowledge – on the effectiveness, costs and distortions of tools, challenge in calibrations, adaptations, perimeter (e.g., shadow banking), interactions among policies and conflict of interests with other goals, and (international) coordination – with rules-based policies thus far off. As such institutional design should allow for sufficient analytical capacity and lessons to be learned. As the recurrence of crises show, however, even with more knowledge (as exists on say microprudential policies), robust policies aimed at financial stability are not easy to implement. Similar to other attempts, macroprudential policies may fall thus short.

This makes an institutional design robust to both ex-ante pressures and ex-post risks all the more important. Design involves the location of the macroprudential policy function, with different models – centralized, inside the central bank or outside it, or using a committee structure – being considered. Each model has various benefits, but also risks (see Nier et al. 2011). Regardless of model, there is a need for transparency and accountability in the conduct of macroprudential policy as well as operational independence. While research has addressed the benefits of independence in the monetary policy function, and identified some modalities for achieving it, sounds governance arrangements for the macroprudential policy function (as well as for micro-prudential regulation and supervision) often remain to be adapted (see further IMF, 2013e).

All in all, given these and other limits on current knowledge, one should proceed with some modesty. A “Bayesian” updating approach, where those tools for which impact is well known are used while others are only used as one learns more, may then be attractive, also as it reduces some of the political economy risks (see also Calomiris, 2013). Institutional designs also have to proceed with caution. This more gradual approach does not mean progress. Policy prioritization would help avoid too much discretion, and too little transparency and accountability. And this path could still achieve a key and possible main objective of the new paradigm: a system-wide financial stability view accepted in all aspects of policy making, including microprudential, monetary, fiscal and competition areas. This change in mind-set is needed, and should proceed anyhow. As more data and research come available, one can then further improve the motivations, calibrations, adaptations, and (institutional) designs of macroprudential policies and adopt specific ones.


    AcemogluDaronAsumanOzdaglar and AlirezaTahbaz-Salehi2013Systemic Risk and Stability in Financial Networks,NBER Working Papers 18727National Bureau of Economic Research, Inc.

    AcharyaViral V.2013. “Adapting Microprudential Regulation for Emerging Markets” in OtavianoCanuto and Swati R.Ghosh (eds.) Dealing with the Challenges of Macro Financial Linkages in Emerging MarketsWorld BankWashington, D.C. pp. 5789.

    AcharyaViral V.MarcoPagano and PaoloVolpin2013. “Seeking Alpha: Excess Risk Taking and Competition for Managerial Talent,NBER Working Papers 18891National Bureau of Economic Research, Inc.

    AcharyaViral and TanjuYorulmazer2007Too Many to Fail—An Analysis of Time-inconsistency in Bank Closure Policies,Journal of Financial Intermediation16(1) pp. 131.

    AdamKlaus and MichaelWoodford2013Housing Prices and Robustly Optimal Monetary Policy,working paperJune29

    AdrianTobias and Adam B.Ashcraft2012Shadow Banking Regulation,” in Annual Review of Financial Economics4 pp. 99140 (also FRB of New York Staff Report No. 559).

    AdrianTobias and HyunSong Shin2010. “Liquidity and leverage,Journal of Financial IntermediationElsevier19(3) pp. 418437.

    AdrianTobias and HyunSong Shin2014Procyclical Leverage and Value-at-Risk,Review of Financial Studies27 (2) pp. 373403.

    AdrianTobiasDanielCovitz and NellieLang2013Financial Stability Monitoring,Staff Reports 601 Federal Reserve Bank of New York and Finance and Economics Discussion Series 2013-21Board of Governors of the Federal Reserve System.

    AiyarShekharCharles W.Calomiris and TomaszWieladek2014Does Macro-Prudential Regulation Leak? Evidence from a UK Policy Experiment,Journal of Money Credit and Banking46(s1) pp. 18121402.

    AiyarShekharCharles W.Calomiris and TomaszWieladek2013How Does Credit Supply Respond to Monetary Policy and Bank Minimum Capital Requirements?,mimeoColumbia University/Bank of England.

    AiyarShekharCharles W.CalomirisJohnHooleyYevgeniyaKorniyenko and TomaszWieladek2014The International Transmission of Bank Capital Requirements: Evidence from the UK,Journal of Financial Economics113 pp.368382.

    AkerlofGeorge A.Olivier J.BlanchardDavidRomer and Joseph E.Stiglitz (Editors) 2014What Have We Learned?: Macroeconomic Policy after the CrisisMIT Press.

    AllenFranklin and ElenaCarletti2011Systemic Risk and Macroprudential Regulation,mimeoUniversity of Pennsylvania.

    AllenFranklin and DouglasGale1994. “Limited Market Participation and Volatility of Asset Prices,American Economic Review84(4) pp. 93355.

    AllenFranklin and DouglasGale2000Financial Contagion,Journal of Political Economy108 (1) pp. 133.

    AllenFranklin and DouglasGale2004Competition and Financial Stability,Journal of Money Credit and Banking36(3) Pt.2 pp. 43380.

    AllenFranklin and DouglasGale2007Understanding Financial Crises Clarendon Lectures in Finance (Oxford, UK: Oxford University Press).

    AllenLinda and AnthonySaunders2003A survey of cyclical effects in credit risk measurement models,BIS Working Papers 126Bank for International Settlements.

    AmatoJeffery D. and Craig H.Furfine2004Are credit ratings procyclical?,Journal of Banking and Finance28 pp. 26412677.

    AngeliniPaoloAndreaEnriaStefanoNeriFabioPanetta and MarioQuagliariello2010. “Pro-cyclicality of capital regulation: is it a problem? How to fix it?,Occasional Papers 74Bank of Italy.

    AngeliniPaoloSergioNicoletti-Altimari and IgnazioVisco2012Macroprudential, Microprudential and Monetary Policies: Conflicts, Complementarities and Trade-Offs,Occasional Papers140Bank of Italy.

    AreggerNicoleMartinBrown and EnzoRossi2013Transaction Taxes, Capital Gains Taxes and House Prices,Swiss National Bank Working Paper 2013/2.

    ArreguiNicolasJaromirBenesIvoKrznarSrobonaMitra and AndreOliveira Santos2013aEvaluating the Net Benefits of Macroprudential Policy: A Cookbook,IMF Working Paper 13/167.

    ArreguiNicolasJodiScarlataMohamedNorat and AntonioPancorbo with EijaHolttinenJaySurtiChrisWilsonRodolfoWehrhahn and MamoruYanase2013bAddressing Risk Concentration and Interconnectedness: Concepts and Experiences,IMF Working Paper 13/199.

    ArsovIvailoElieCanettiLauraKodres and SrobonaMitra2013Near-Coincident Indicators of Systemic Stress,IMF Working Paper 13/115.

    Bank of England2009The Role of Macroprudential Policy,Discussion PaperNovember.

    Bank of England2011Instruments of Macroprudential Policy,Discussion PaperDecember

    Bank for International Settlements201484th Annual

    BarberisN.2013Thirty Years of Prospect Theory in Economics: A Review and Assessment,Journal of Economic Perspectives27 pp. 17396.

    Basel Committee on Banking Supervision (BCBS)2010aCountercyclical Capital Buffer Proposal, Consultative DocumentBank for International SettlementsBasel.

    Basel Committee on Banking Supervision (BCBS)2010b. “An assessment of the long-term economic impact of the new regulatory framework (of stronger capital and liquidity requirements).

    Basel Committee on Banking Supervision (BCBS)2010Assessing the Macroeconomic Impact of the Transition to Stronger Capital and Liquidity Requirements – Final ReportDecember.

    Basel Committee on Banking Supervision (BCBS)2011Basel III: A Global Regulatory Framework for More Resilient Banks and Banking Systems,

    Basel Committee on Banking Supervision (BCBS) and Financial Stability Board (FSB)2013Global systemically important banks: updated assessment methodology and the higher loss absorbency requirement,July

    BeanCharlesMatthiasPaustianAdrianPenalver and TimTaylor2010Monetary Policy after the Fall,Paper presented at the Federal Reserve Bank of Kansas City Annual ConferenceJackson Hole, WyomingAugust 31–September 1.

    BebchukLucian and ItayGoldstein2011Self-Fulfilling Market Freezes,Review of Financial Studies24(11) pp. 351955.

    BeckThorsten2008Bank Competition and Financial Stability: Friends or Foes,World Bank Policy Research Working Paper 4656.

    BenesJaromirMichaelKumhof and DouglasLaxton2014a. Financial Crises in DSGE Models: Selected Applications of MAPMOD. IMF Working Paper WP/14/56.

    BenesJaromirMichaelKumhof and DouglasLaxton2014b. Financial Crises in DSGE Models: A Prototype Model. IMF Working Paper WP/14/57.

    BernankeBen and Cara S.Lown1991The Credit Crunch,Brookings Papers on Economic Activity1991:220539.

    BernankeBen and MarkGertler2001Should Central Banks Respond to Movements in Asset Prices?American Economic Review9125357.

    BianchiJavier2010Credit Externalities: Macroeconomic Effects and Policy Implications,American Economic Review1002398402.

    BisiasDimitriosMark D.FloodAndrewLo and StavrosValavanis2012A Survey of Systemic Risk Analytics.U.S. Department of Treasury Office of Financial Research 0001. Also Annual Review of Financial Economics4: 255296.

    BlancherNicolasSrobonaMitraHananMorsyAkiraOtaniTiagoSevero and LauraValderrama2013Macroprudential Policy: A Practical Approach to Systemic Risk Monitoring,13/168.

    BorioClaudio E.V.2003Towards a Macroprudential Framework for Financial Supervision and Regulation?BIS Working Paper 128 (Switzerland: Bank of International Settlements).

    BorioClaudio E.V. and William R.White2003. “Whither Monetary and Financial Stability: the Implications of Evolving Policy Regimes?,” in Monetary Policy and Uncertainty: Adapting to a Changing EconomyConference Volume, Federal Reserve Bank of Kansas City.

    BrunnermeierMarkus KThomasEisenbach and YuliySannikov.2013. “Macroeconomics with Financial Frictions: A Survey”. Advances in Economics and Econometrics Tenth World Congress of the Econometric Society. New York: Cambridge University Press.

    BrunnermeierMarkus K.CharlesGoodhartAndrewCrocketAvinashPersaud and HyunShin2009The Fundamental Principles of Financial Regulation: 11th Geneva Report on the World Economy. CEPR/ICMB.

    BrunnermeierMarkus K. and ArvindKrishnamurthy (Editors) 2014Systemic Risk and Macro ModelingNBER/University of Chicago Press.

    BrunnermeierMarkus K. and YuliySannikov2014A Macroeconomic Model with a Financial Sector,American Economic Review104379421.

    BrunoValentina and HyunSong Shin2014Assessing Macroprudential Policies: Case of South Korea,Scandinavian Journal of Economics116 (1) pp. 128157.

    CaballeroRicardo and ArvindKrishnamurthy2003Excessive Dollar Debt: Financial Development and Underinsurance,Journal of Finance58(2) pp. 86794.

    CaballeroRicardo and ArvindKrishnamurthy2004Smoothing Sudden Stops,Journal of Economic Theory119(1) pp. 10427.

    CalomirisCharles W.2013. “Managing the risks of the new macro-prudential policy regime,Borsa Istanbul ReviewResearch Department of Borsa Istanbul13(4) pp. 6566.

    CarlstromCharles and TimothyFuerst2010Optimal Monetary Policy in a Model with Agency Costs,Journal of Money Credit and Banking42 pp. 3770.

    CeruttiEClaessensSLaevenL.2014. Macroprudential Policies. IMF Working Paper forthcoming.

    CeruttiEugenioStijnClaessens and PatrickMcGuire2014Systemic Risk in Global Banking: What Available Data Can Tell Us and What More Data are Needed?” in Systemic Risk and Macro ModelingMarkus K.Brunnermeier and ArvindKrishnamurthy (Editors) NBER/University of Chicago Press

    CeruttiEugenioStijnClaessens and LevRatnovski2014Global Liquidity and Drivers of Cross-border Bank Flows,IMF working Paper 14/69.

    ClaessensStijn2014Capital and Liquidity Requirements: A Review of the Issues and Literature,Paper for the Yale University Conference September 20 2013 forthcoming in Volume of Yale Journal on Regulation.

    ClaessensStijnDouglas D.EvanoffGeorge G.Kaufman and LauraKodres2011Macro-prudential Regulatory Policies: The New Road to Financial Stability. (Editors.) World Scientific Studies in International Economics, Pte. LtdNew Jersey.

    ClaessensStijnSwatiGhosh and RoxanaMihet2013Macro-Prudential Policies to Mitigate Financial System Vulnerabilities,Journal of International Money and Finance39:153185.

    ClaessensStijn and LauraKodres2014The Regulatory Responses to the Global Financial Crisis: Some Uncomfortable Questions,IMF working Paper 14/46 forthcoming in a book edited by EdwardBalleisenLoriBennearKimKrawiec and JonathanWiener.

    ClaessensStijnZoltanPozsarLevRatnovski and ManmohanSingh2012Shadow Banking: Economics and Policy,IMF Staff Discussion Note 12/12.

    ClementPiet2010The term “macroprudential:” origins and evolution,BIS Quarterly ReviewMarch

    Committee on the Global Financial System (CGFS)2010Macroprudential Instruments and Frameworks: A Stocktaking of Issues and Experiences,CGFS Papers 38 (Basel: Bank for International Settlement).

    Committee on the Global Financial System (CGFS)2012Operationalising the Selection and Application of Macroprudential Instruments,CGFS Papers 48 (Basel: Bank for International Settlement).

    CordellaTitoPabloFedericoCarlosVegh and GuillermoVuletin2014Reserve Requirements in the Brave New Macroprudential World.World Bank Policy Research Working Paper No. 6793.

    CrockettAndrew2000Marrying the Micro- and Macroprudential Dimensions of Financial Stability,BIS Speeches21September (Bank of International Settlements).

    CroweChristopher W.DenizIganGiovanniDell’Ariccia and PauRabanal2011How to Deal with Real Estate Booms,IMF Staff Discussion Note 11/02.

    CurdiaVasco and MichaelWoodford2009Credit Frictions and Optimal Monetary Policy,Bank for International Settlements Working Paper 278.

    Dassatti CamorsCecilia and Jose-LuisPeydro2014Macroprudential and Monetary Policy: Loan-Level Evidence from Reserve Requirements,” mimeo Universitat Pompeu FabraSpain.

    De NicolòGianniGiovanniFavara and LevRatnovski2012Externalities and Macroprudential Policy”. IMF Staff Discussion Notes No.12/05.

    De NicolòGianniAndreaGamba and MarcellaLucchetta2012Capital Regulation, Liquidity Requirements and Taxation in a Dynamic Model of BankingIMF Working Paper 12/72.

    Dell’AricciaGiovanniDenizIganLucLaeven and HuiTong with BasBakker and JeromeVandenbussche2012Policies for Macrofinancial Stability: How to Deal with Credit Booms,IMF Staff Discussion Note 12/06.

    Dell’AricciaGiovanni and RobertMarquez2006Lending Booms and Lending Standards,Journal of Finance61(5) pp. 25112546.

    Dell’AricciaGiovanni and RobertMarquez2013. “Interest Rates and the Bank Risk-Taking Channel,Annual Review of Financial Economics5(1) pp. 123141November.

    Demirgüç-KuntAsli and EnricaDetragiache.2002Does Deposit Insurance Increase Banking System Stability? An Empirical Investigation,Journal of Monetary Economics49(7).

    Demirgüç-KuntAsliEdKane and LucLaeven.2008Deposit Insurance around the World: Issues of Design and ImplementationCambridge, MA: MIT Press.

    DiamondDouglas W. and Raghuram G.Rajan2011Fear of Fire Sales, Illiquidity Seeking, and the Credit Freezes,Quarterly Journal of Economics126(2) 55791.

    DrehmannMathiasClaudioBorioLeonardoGambacortaGabrielJiménez and CarlosTrucharte2010Countercyclical Capital Buffers: Exploring Options,BIS Working Papers 298.

    DrehmannMathias and NikolaTarashev2011. “Measuring the systemic importance of interconnected banks,BIS Working Papers 342Bank for International Settlements.

    ElliottDouglas J.2011Choosing among Macroprudential Tools,The Brookings InstitutionJune2011.

    ElliottDouglas J.GregFeldberg and AndreasLehnert2013The History of Cyclical Macroprudential Policy in the United States,Office of Financial Research Working Paper No. 8 (Washington: U.S. Department of the Treasury).

    EllulAndrewChotibhakJotikasthiraChristian T.Lundblad and YihuiWang2013Mark-to-Market Accounting and Systemic Risk in the Financial Sector,Fordham University Schools of Business Research Papers17Mayavailable at

    European Central Bank2012Report on the first two years of the macro-prudential research network,

    European Systemic Risk Board Heads of Research2014Report on The Macro-Prudential Research Network (MARS),June at

    FarhiEmmanuel and JeanTirole2012Collective Moral Hazard, Maturity Mismatch, and Systemic Bailouts,American Economic Review102(1): pp. 6093.

    FarhiEmmanuel and IvánWerning2013A Theory of Macroprudential Policies in the Presence of Nominal Rigidities,NBER Working Papers 19313National Bureau of Economic Research, Inc.

    Financial Stability Board (FSB)2013Update of group of global systemically important banks (G-SIBs),

    Financial Stability Board (FSB)2014Report to G20 Leaders on financial regulatory reform progress, and Overview of Progress in the Implementation of the G20 Recommendations for Strengthening Financial Stability,Basel

    ForbesKristinMarcelFratzscherThomasKostka and RolandStraub2012. “Bubble Thy Neighbor: Portfolio Effects and Externalities from Capital Controls,NBER Working Papers 18052National Bureau of Economic Research, Inc.

    FreixasXavierLucLaeven and José-LuisPeydróforthcomingSystemic Risk Crises And Macroprudential RegulationMIT Press.

    GaiaPrasannaAndrewHaldaneSujitKapadiab2011Complexity, concentration and contagion,Journal of Monetary Economics Vol. 58 Issue 5July pp. 453470.

    GalatiGabriele and RichhildMoessner2011Macroprudential policy - a literature review,BIS Working Papers 337Bank for International Settlements.

    GalatiGabriele and RichhildMoessner2014What do we know about the effects financial macro-prudential policy?,De Nederlandsche Bank Working Papers 440.

    GennaioliNicolaAndreiShleifer and Robert W.Vishny2013A model of shadow banking,Journal of Finance68(4) pp. 13311363.

    GoldsteinItayEmreOzdenoren and KathyYuan2013Trading Frenzies and Their Impact on Real Investment,Journal of Financial Economics109(2) pp. 566582.

    GortonGary B. and PingHe2008. “Bank Credit Cycles,Review of Economic Studies75(4) pp. 11811214.

    HahmJoon-HoFrederic S.MishkinHyunSong Shin and KwanhoShin2011Macroprudential Policies in Open Emerging Economies,ProceedingsFederal Reserve Bank of San FranciscoNov pp. 63114.

    HahmJoon-HoHyunSong Shin and KwanhoShin.2013Noncore Bank Liabilities and Financial Vulnerability,Journal of Money Credit and Banking45(S1) pp. 336.

    HansonSamuelAnilKayshap and JeremyStein2011A Macroprudential Approach to Financial Regulation,Journal of Economic Perspective25(1) pp. 328.

    HeathRobert2013Why are the G-20 Data Gaps Initiative and the SDDS Plus Relevant for Financial Stability?IMF Working Paper 13/6.

    IganDeniz and HeedonKang2011Do Loan-to-Value and Debt-to-Income Limits Work? Evidence from Korea,IMF Working paper 11/297.

    International Association of Insurance Supervisors (IAIS)2013Macroprudential Policy and Surveillance in InsuranceMacroprudential Surveillance and Policy Subcommittee (MPSSC)18July (Basel: International Association of Insurance Supervisors) at

    International Monetary Fund2010A Fair and Substantial Contribution by the Financial Sector: Report to the G20,

    International Monetary Fund2011a. Housing Finance and Financial Stability—Back to Basics?

    International Monetary Fund2011bMacroprudential Policy: An Organizing Framework,

    International Monetary Fund2012aKorea: 2012 Article IV Consultation Staff Report,September

    International Monetary Fund2012bToward Operationalizing Macroprudential Policies: When to Act?,” Chapter 3 in Global Financial Stability ReportSeptember.

    International Monetary Fund2012cThe Liberalization and Management of Capital Flows—An Institutional ViewNovember.

    International Monetary Fund2013aThe Interaction of Monetary and Macroprudential Policies,IMF Policy PaperJanuary.

    International Monetary Fund2013bThe Interaction of Monetary and Macroprudential Policies—Background Paper,IMF Policy PaperJanuary

    International Monetary Fund2013cKey Aspects of Macroprudential Policy,IMF Policy PaperJune.

    International Monetary Fund2013dKey Aspects of Macroprudential Policy—Background Paper,IMF Policy PaperJune.

    International Monetary Fund2013eImplementing Macroprudential Policy—Selected Legal Issues,

    International Monetary Fund2014aSelected Issues paper on Israel,February. IMF Country Report 14/48.

    International Monetary Fund2014bHow Big is the Implicit Subsidy for Banks Seen as Too-Important-to-FailGlobal Financial Stability Report Chapter 3 World Economic and Financial SurveysApril.

    JeanneOlivier2014Macroprudential Policies in a Global PerspectiveNBER Working Paper No. 19967.

    JeanneOlivier and AntonKorinek2010Excessive Volatility in Capital Flows: A Pigouvian Taxation Approach,American Economic Review100(2) pp. 403407.

    JeanneOlivier and AntonKorinek2013Macroprudential Regulation Versus Mopping Up After the Crash,NBER Working Paper 18675December.

    JeanneOlivier and AntonKorinek2014Macroprudential Policy Beyond Banking Regulation,Banque de France Financial Stability Review18 pp. 163172.

    JiménezGabrielSteven R. G.OngenaJose-LuisPeydro and JesusSaurina Salas2012Macroprudential Policy, Countercyclical Bank Capital Buffers and Credit Supply: Evidence from the Spanish Dynamic Provisioning Experiments,European Banking Center Discussion Paper 2012-011.

    KannanPrakashPauRabanal and AlasdairScott2009Monetary and Macroprudential Policy Rules in a Model with House Price Booms,IMF Working Paper 09/251.

    KashyapAnilRichardBerner and Charles A. E.Goodhart2011The Macroprudential Toolkit,IMF Economic Review59(2) pp. 145161.

    KeenMichael and RuudDe Mooij2012Debt, Taxes and Banks,IMF Working Paper 12/48.

    KocherlakotaNarayana2013Too-Big-to-Fail: The Role of Metrics,” Remarks at the Quantifying the “Too Big to FailSubsidy WorkshopFederal Reserve Bank of MinneapolisMinneapolis, MinnesotaNovember182013

    KorinekAnton2011Foreign Currency Debt, Risk Premia and Macroeconomic Volatility,European Economic Review553. pp. 37185.

    KorinekAnton2014Global Coordination or Currency Wars?” (unpublished; Baltimore, Maryland: Johns Hopkins University).

    KorinekAnton and DamianoSandri2014Macroprudential Regulation or Capital Controls?,” mimeo Johns Hopkins University and International Monetary Fund.

    KorinekAnton and AlpSimsek2014Liquidity Trap and Excessive Leverage,NBER Working Papers 19970 National Bureau of Economic Research Inc. and IMF Working Paper 14/129.

    KuttnerKenneth N. and IlhyockShim2013Can non-interest rate policies stabilise housing markets? Evidence from a panel of 57 economies,BIS Working Papers No 433.

    LaevenLucLevRatnovski and HuiTong2014Bank Size and Systemic Risk,Staff Discussion Notes 14/4IMFWashington, D.C.

    LeuzChristian and ChristianLaux2010Did Fair-Value Accounting Contribute to the Financial Crisis?,Journal of Economic Perspectives24(1): 93118.

    LimCheng H.FrancescoColumbaAlejoCostaPiyabhaKongsamutAkiraOtaniMustafaSaiyidTorstenWezelXiaoyongWu2011Macroprudential Policy: What Instruments and How Are They Used? Lessons from Country ExperiencesIMF Working Paper 11/238.

    LorenzoniGuido2008Inefficient Credit Booms,Review of Economic Studies75(3) 80933.

    ManconiAlbertoMassimoMassa and AyakoYasuda2012The Role of Institutional Investors in Propagating the Crisis 2007-2008Journal of Financial Economics Vol. 104 No. 3 pp. 491518.

    MerrillCraig B.Taylor D.NadauldRené M.Stulz and ShaneSherland2012Did Capital Requirements and Fair Value Accounting Spark Fire Sales in Distressed Mortgage-Backed Securities?,NBER Working Paper No. 18270.

    MooijRuud A. de2011Tax Biases to Debt Finance: Assessing the Problem, Finding Solutions,IMF Staff Discussion Note 11/11.

    OsińskiJacekKatharineSeal and LexHoogduin2013Macroprudential and Microprudential Policies: Towards CohabitationIMF Staff Discussion Note 13/05.

    OstryJonathan DavidAtish R.Ghosh KarlFriedrich HabermeierLucLaevenMarcosChamonMahvashSaeed Qureshi and AnnamariaKokenyne2011Managing Capital Inflows: What Tools to Use?IMF Staff Discussion Note 11/06.

    OstryJonathan D.Atish R.Ghosh and AntonKorinek2012Multilateral Aspects of Managing the Capital Account,IMF Staff Discussion Note 12/10.

    OstryJonathan D. and Atish R.Gosh2013. “Obstacles to International Policy Coordination, and How to Overcome Them,IMF Staff Discussion Note 13/11.

    PerottiEnrico and JavierSuarez2011A Pigouvian Approach to Liquidity Regulation,International Journal of Central Banking7(4) 341.

    QuintDominic and PauRabanal2013Monetary and Macroprudential Policy in an Estimated DSGE Model of the Euro Area,IMF Working Paper 13/209.

    RajanRaghuram G1994Why Bank Credit Policies Fluctuate: A Theory and Some Evidence,The Quarterly Journal of Economics109(2) pp. 399441.

    RajanRaghuram G and RodneyRamcharan2014Financial Fire Sales: Evidence from Bank Failures,Finance and Economics Discussion Series 2014-67Federal Reserve Board.

    RatnovskiLev2009Bank Liquidity Regulation and the Lender of Last Resort,Journal of Financial Intermediation18(4) pp. 54188.

    RatnovskiLev2013Competition Policy for Modern Banks,IMF Working Paper 13/126.

    RepulloRafael and JavierSuarez2013The Procyclical Effects of Bank Capital Regulation,Review of Financial Studies26(2): pp. 452490.

    ReyHélène2013Dilemma not Trilemma: The Global Financial Cycle and Monetary Policy Independence,paper presented at the Jackson Hole SymposiumAugust.

    RuckesMartin2004Bank Competition and Credit Standards,Review of Financial Studies17(4) pp. 1073102.

    SaurinaJesus2009Dynamic Provisioning. The Experience of Spain,Crisis Response Note Number7 (Washington: The World Bank).

    Schmitt-GroheStephanie and MartinUribe2012Prudential Policy for Peggers,NBER Working Papers 18031National Bureau of Economic Research, Inc.

    SchoenmakerDirk and Peter J.Wierts2011Macroprudential Policy: The Need for a Coherent Policy Framework,DSF Policy Paper 13 (Amsterdam, The Netherlands: Duisenberg School of Finance).

    ShinHyun Song2010Non-Core Liabilities Tax as a Tool for Prudential Regulation,” Mimeo.

    ShinHyun Song2012Global Banking Glut and Loan Risk Premium,IMF Economic Review60(2) pp. 155192.

    ShinHyun Song2013Adapting Macroprudential Approaches to Emerging and Developing Economies,” in OtavianoCanuto and Swati R.Ghosh (eds.) Dealing with the Challenges of Macro Financial Linkages in Emerging MarketsWorld BankWashington, D.C. pp. 1755.

    ShleiferAndrei2000Clarendon Lectures: Inefficient MarketsOxford University Press.

    ShleiferAndrei and Robert W.Vishny1992Liquidation Values and Debt Capacity: A Market Equilibrium Approach,Journal of Finance47:4 pp. pp. 134366.

    SteinJeremy C.2012Monetary Policy as Financial-Stability Regulation,Quarterly Journal of Economics127(1) pp. 5795.

    SteinJeremy C.2013Overheating in Credit Markets: Origins, Measurement and Policy Responses,Remarks at a Research Symposium sponsored by the Federal Reserve Bank of St. LouisFebruary7.

    StrahanPhilip2013Too Big To Fail: Causes, Consequences, and Policy Responses,Annual Review of Financial Economics. 5:pp. 4361.

    ThakorAnjan V.2014Bank Capital and Financial Stability: An Economic Tradeoff or a Faustian Bargain,Annual Review of Financial Economics6December.

    UedaKenichi and BeatriceWeder di Mauro2012Quantifying the Value of the Subsidy for Systemically Important Financial Institutions,IMF Working Paper 12/128.

    Van den NoordPeter2005Tax Incentives and House Price Volatility in the Euro Area: Theory and Evidence,Economie Internationale101 pp. 2945.

    VandenbusscheJérômeUrsulaVogel and EnricaDetragiache2012Macroprudential Policies and Housing Prices—A New Database and Empirical Evidence for Central, Eastern, and Southeastern Europe,IMF Working Paper 12/303.

    WagnerWolf2011Systemic Liquidation Risk and the Diversity–Diversification Trade-Off,Journal of Finance66(4) pp. 114175.

    WhiteWilliam R.2006Procyclicality in the financial system: do we need a new macrofinancial stabilisation framework?,BIS Working Papers no 193January.

    WongEricTomFongKa-faiLi and HenryChoi2011Loan-to-Value Ratio as a Macroprudential Tools—Hong-Kong’s Experience and Cross-Country Evidence,HKMA Working Paper 01/2011 (Hong Kong: Hong Kong Monetary Authority).

    YellenJanet2014Monetary policy and financial stability,Michel Camdessus Central Banking Lecture at the IMF in Washington DCJuly2 at at

    ZhangLongmei and EddaZoli2014Leaning Against the Wind: Macroprudential Policy in Asia,IMF Working Paper 14/22.

I would like to thank Charles Calomiris, Andy Jobst, Luc Laeven, Erlend Nier, Inci Otker-Robe, Lev Ratnovski, and other colleagues at the IMF for comments and Joshua Bosshardt for data support. The paper draws on joint work with Swati Ghosh, Roxana Mihet, Lev Ratnovski, Fabian Valencia, and on work of other colleagues at the IMF.

Clement (2010) identifies the term macroprudential to be first used in the late 1970s in work on international bank lending carried out by the Euro-currency Standing Committee at the BIS. Crocket (2000) was among the first to draw attention in public forums to the need for macroprudential policies. Elliot et al. (2013) reviews the history of “macroprudential” policies in the US. Earlier literature reviews are Galati and Moessner (2011) and Hanson, Kayshap, and Stein (2011), and a recent review of empirical work is Galati and Moessner (2014). For a collection of papers, see Claessens et al. (2011). And for an extensive treatment, see Freixas, Laeven, and Peydró (2015).

For more policy-oriented reviews see IMF (2013c and 2013d) and ECBS (2014). Claessens and Kodres (2014) review financial reforms in general; see FSB (2014) for policy makers’ assessment.

While historically “systemic importance” has been associated with institutions’ size, recent events suggest a more complex picture, with interconnectedness determined by interbank market linkages and effects amplified by high leverage (Drehmann and Tarashev, 2011; Laeven, Ratnovski and Tong, 2014). Interconnectedness and systemically importance may also be present with and among nonbanks (e.g., hedge funds, money market mutual funds, or shadow banking), or institutions that support market infrastructure, such as central clearing counterparties.

Farhi and Werning (2013), however, develop a model with financial frictions and nominal rigidities where even with perfectly operating policies, monetary policy might have take on a role in assuring financial stability.

The need to conduct macroprudential policies at the regional level in currency unions can arise not just from financial frictions, but also due to “incomplete” overall design. It is, for example, generally not thought to be necessary to conduct macroprudential policies at a regional level in the US, even though booms and busts can (and have been) regional. This is, among others, since in the US the financial safety net is nationally organized and funded, fiscal stabilizers operate across regions, and labor and other factors markets are flexible enough to allow for satisfactory reallocation of resources, conditions not present to the same degree in all currency unions, including the euro.

Obviously, there are many types of international spillovers, e.g., those arising from shocks such as natural disasters, but the focus here is on financial and policy spillovers. Furthermore, many (policy) spillovers can be positive, as when risks are reduced or better diversified when one system becomes more stable due to macroprudential and other policies.

Other dimensions of relevance include whether tools are meant to be broad based vs. more targeted and rules-based vs. more discretionary.

For instance, reserve requirements are likely more effective when most deposit-like claims are subject to it. Especially in advanced economies, however, many such claims are not directly regulated, or at least not like bank deposits, creating scope for avoidance, while in emerging markets, such claims are less plentiful. Note that also that reserve requirement can fulfill monetary policy functions (see Cordella et al., 2014). Related is the issue of the shadow banking system, by definition less subject to (macroprudential) policies, but using macroprudential policies could increase its size.

Although employed for some time for financial stability assessments, some countries (e.g., US, EU) have recently been using, and making public, stress tests to help identify individual institutions’ and overall vulnerabilities (and remedial actions). Stress tests are more forward-looking than macroprudential policies and can be less coarse in their application (say by having very granular asset categories for risk scenarios). More generally, they can be more tailored to (emerging) vulnerabilities than macroprudential policies may be, especially when the latter are not properly designed and quickly adjusted to (changing) circumstances. Stress tests, however, have some drawbacks. Typically, they only cover part of financial intermediation (mainly major banks) and thus do not capture fully systemic risks. They are also less geared at ex-ante incentives as their actions to reduce risks follow in more discretionary ways (e.g., need for recapitalization).

This relates to studies on the effects of large shocks to banks on lending (and economic activity). This “credit crunch” literature (see Bernanke and Lown, 1991, for an early review) finds large impact of actual capital shortfalls. The literature on the effects of microprudentially motivated higher capital requirements, including Basel II, however, generally finds limited impacts on lending, essentially only some impact for weaker banks (Claessens 2014 and Thakor 2014 review). The difference in findings likely arises from the nature of the “experiment” – a systemic, adverse shock vs. a (gradual) increase in capital requirements – and that across banks, higher capital ratios are associated with higher lending, liquidity creation, bank values, and probabilities of surviving crises.

Switzerland has set its CCB at 2.5%, but it only applies to mortgage exposures. And the UK has of yet has not invoked it (it is set at 0%).

Experiences with stress tests in identifying such risks have been mixed, with sometimes banks or even whole systems running into subsequent stress. This is in part as financial stability concerns are hard to capture in theory and practice – current models and techniques are clearly limited. Of course, in some cases there can also be questions on the governance and the quality of the exercises.

BCBS (2010b) and BCBS-FSB (2011) analyze respectively the structural and transitional costs and benefits of higher capital adequacy requirements and lower risks of systemic crises against foregone growth due to higher financial intermediation costs.

The IMF currently collects FSI data from 98 regular reporters (at

Other Resources Citing This Publication