Monday, July 9, 2012

Macro-prudential Policy in a Fisherian Model of Financial Innovation

Macro-prudential Policy in a Fisherian Model of Financial Innovation. By Bianchi, Javier; Boz, Emine; Mendoza, Enrique G.
IMF Working Paper No. 12/181
Jul 2012

Summary: The interaction between credit frictions, financial innovation, and a switch from optimistic to pessimistic beliefs played a central role in the 2008 financial crisis. This paper develops a quantitative general equilibrium framework in which this interaction drives the financial amplification mechanism to study the effects of macro-prudential policy. Financial innovation enhances the ability of agents to collateralize assets into debt, but the riskiness of this new regime can only be learned over time. Beliefs about transition probabilities across states with high and low ability to borrow change as agents learn from observed realizations of financial conditions. At the same time, the collateral constraint introduces a pecuniary externality, because agents fail to internalize the effect of their borrowing decisions on asset prices. Quantitative analysis shows that the effectiveness of macro-prudential policy in this environment depends on the government's information set, the tightness of credit constraints and the pace at which optimism surges in the early stages of financial innovation. The policy is least effective when the government is as uninformed as private agents, credit constraints are tight, and optimism builds quickly.


Policymakers have responded to the lapses in financial regulation in the years before the 2008 global financial crisis and the unprecedented systemic nature of the crisis itself with a strong push to revamp financial regulation following a "macro-prudential" approach. This approach aims to focus on the macro (i.e. systemic) implications that follow from the actions of credit market participants, and to implement policies that influence behavior in "good times" in order to make financial crises less severe and less frequent. The design of macro-prudential policy is hampered, however, by the need to develop models that are reasonably good at explaining the macro dynamics of financial crises and at capturing the complex dynamic interconnections between potential macro-prudential policy instruments and the actions of agents in credit markets.

The task of developing these models is particularly challenging because of the fast pace of financial development. Indeed, the decade before the 2008 crash was a period of significant financial innovation, which included both the introduction of a large set of complex financial instruments, such as collateralized debt obligations, mortgage backed securities and credit default swaps, and the enactment of major financial reforms of a magnitude and scope unseen since the end of the Great Depression. Thus, models of macro-prudential regulation have to take into account the changing nature of the financial environment, and hence deal with the fact that credit market participants, as well as policymakers, may be making decisions lacking perfect information about the true riskiness of a changing financial regime.

This paper proposes a dynamic stochastic general equilibrium model in which the interaction between financial innovation, credit frictions and imperfect information is at the core of the financial transmission mechanism, and uses it to study its quantitative implications for the design and effectiveness of macro-prudential policy. In the model, a collateral constraint limits the agents' ability to borrow to a fraction of the market value of the assets they can offer as collateral. Financial innovation enhances the ability of agents to "collateralize," but also introduces risk because of the possibility of fluctuations in collateral requirements or loan-to-value ratios.  We take literally the definition of financial innovation to be the introduction of a truly new financial regime. This forces us to deviate from the standard assumption that agents formulate rational expectations with full information about the stochastic process driving fluctuations in credit conditions. In particular, we assume that agents learn (in Bayesian fashion) about the transition probabilities of financial regimes only as they observe regimes with high and low ability to borrow over time. In the long run, and in the absence of new waves of financial innovation, they learn the true transition probabilities and form standard rational expectations, but in the short run agents' beliefs display waves of optimism and pessimism depending on their initial priors and on the market conditions they observe. These changing beliefs influence agents' borrowing decisions and equilibrium asset prices, and together with the collateral constraint they form a financial amplification feedback mechanism: optimistic (pessimistic) expectations lead to over-borrowing (under-borrowing) and increased (reduced) asset prices, and as asset prices change the ability to borrow changes as well.

Our analysis focuses in particular on a learning scenario in which the arrival of financial innovation starts an "optimistic phase," in which a few observations of enhanced borrowing ability lead agents to believe that the financial environment is stable and risky assets are not "very risky." Hence, they borrow more and bid up the price of risky assets more than in a full-information ra- tional expectations equilibrium. The higher value of assets in turn relaxes the credit constraint.  Thus, the initial increase in debt due to optimism is amplified by the interaction with the collateral constraint via optimistic asset prices. Conversely, when the first realization of the low-borrowing- ability regime is observed, a "pessimistic phase" starts in which agents overstate the probability of continuing in poor financial regimes and overstate the riskiness of assets. This results in lower debt levels and lower asset prices, and the collateral constraint amplifies this downturn.

Macro-prudential policy action is desirable in this environment because the collateral constraint introduces a pecuniary externality in credit markets that leads to more debt and financial crises that are more severe and frequent than in the absence of this externality. The externality exists because individual agents fail to internalize the effect of their borrowing decisions on asset prices, particularly future asset prices in states of financial distress (in which the feedback loop via the collateral constraint triggers a financial crash).

There are several studies in the growing literature on macro-prudential regulation that have examined the implications of this externality, but typically under the assumption that agents form rational expectations with full information (e.g. Lorenzoni (2008), Stein (2011), Bianchi (2011), Bianchi and Mendoza (2010), Korinek (2010), Jeanne and Korinek (2010), Benigno, Chen, Otrok, Rebucci, and Young (2010)). In contrast, the novel contribution of this paper is in that we study the effects of macro-prudential policy in an environment in which the pecuniary externality is influenced by the interaction of the credit constraint with learning about the riskiness of a new financial regime. The analysis of Boz and Mendoza (2010) suggest that taking this interaction into account can be important, because they found that the credit constraint in a learning setup produces significantly larger effects on debt and asset prices than in a full-information environment with the same credit constraint. Their study, however, focused only on quantifying the properties of the decentralized competitive equilibrium and abstracted from normative issues and policy analysis. The policy analysis of this paper considers a social planner under two different informational assumptions. First, an uninformed planner who has to learn about the true riskiness of the new financial environment, and faces the set of feasible credit positions supported by the collateral values of the competitive equilibrium with learning. We start with a baseline scenario in which private agents and the planner have the same initial priors and thus form the same sequence of beliefs, and study later on scenarios in which private agents and the uninformed planner form different beliefs. Second, an informed planner with full information, who therefore knows the true transition probabilities across financial regimes, and faces a set of feasible credit positions consistent with the collateral values of the full-information, rational expectations competitive equilibrium.

We compute the decentralized competitive equilibrium of the model with learning (DEL) and contrast this case with the above social planner equilibria. We then compare the main features of these equilibria, in terms of the behavior of macroeconomic aggregates and asset pricing indicators, and examine the characteristics of macro-prudential policies that support the allocations of the planning problems as competitive equilibria. This analysis emphasizes the potential limitations of macro-prudential policy in the presence of significant financial innovation, and highlights the relevance of taking into account informational frictions in evaluating the effectiveness of macro-prudential policy.

The quantitative analysis indicates that the interaction of the collateral constraint with optimistic beliefs in the DEL equilibrium can strengthen the case for introducing macro-prudential regulation compared with the decentralized equilibrium under full information (DEF). This is because, as Boz and Mendoza (2010) showed, the interaction of these elements produces larger amplification both of the credit boom in the optimistic phase and of the financial crash when the economy switches to the bad financial regime. The results also show, however, that the effectiveness of macro-prudential policy varies widely with the assumptions about the information set and collateral pricing function used by the social planner. Moreover, for the uninformed planner, the effectiveness of macro-prudential policy also depends on the tightness of the borrowing constraint and the pace at which optimism builds in the early stages of financial innovation.

Consider first the uninformed planner. For this planner, the undervaluation of risk weakens the incentives to build precautionary savings against states of nature with low-borrowing-ability regimes over the long run, because this planner underestimates the probability of landing on and remaining in those states. In contrast, the informed planner assesses the correct probabilities of landing and remaining in states with good and bad credit regimes, so its incentives to build precautionary savings are stronger. In fact, the informed planner's optimal macro-prudential policy features a precautionary component that lowers borrowing levels at given asset prices, and a component that influences portfolio choice of debt v. assets to address the effect of the agents' mispricing of risk on collateral prices.

It is important to note that even the uninformed planner has the incentive to use macro-prudential policy to tackle the pecuniary externality and alter debt and asset pricing dynamics. In our baseline calibration, however, the borrowing constraint becomes tightly binding in the early stages of financial innovation as optimism builds quickly, and as a result macro-prudential policy is not very effective (i.e. debt positions and asset prices differ little between the DEL and the uninformed planner). Intuitively, since a binding credit constraint implies that debt equals the high-credit-regime fraction of the value of collateral, debt levels for the uninformed social planner and the decentralized equilibrium are similar once the constraint becomes binding for the planner. But this is not a general result.2 Variations in the information structure in which optimism builds more gradually produce outcomes in which macro-prudential policy is effective even when the
planner has access to the same information set. On the other hand, it is generally true that the uninformed planner allows larger debt positions than the informed planner because of the lower precautionary savings incentives.

We also analyze the welfare losses that arise from the pecuniary externality and the optimism embedded in agents' subjective beliefs. The losses arising due to their combined e®ect are large, reaching up to 7 percent in terms of a compensating variation in permanent consumption that equalizes the welfare of the informed planner with that of the DEL economy. The welfare losses attributable to the pecuniary externality alone are relatively small, in line with the findings reported by Bianchi (2011) and Bianchi and Mendoza (2010), and they fall significantly at the peak of optimism.

Our model follows a long and old tradition of models of financial crises in which credit frictions and imperfect information interact. This notion dates back to the classic work of Fisher (1933), in which he described his debt-deflation financial amplification mechanism as the result of a feedbackloop between agents' beliefs and credit frictions (particularly those that force fires sales of assets and goods by distressed borrowers). Minsky (1992) is along a similar vein. More recently, macroeconomic models of financial accelerators (e.g. Bernanke, Gertler, and Gilchrist (1999), Kiyotaki and Moore (1997), Aiyagari and Gertler (1999)) have focused on modeling financial amplification but typically under rational expectations with full information about the stochastic processes of exogenous shocks.

The particular specification of imperfect information and learning that we use follows closely that of Boz and Mendoza (2010) and Cogley and Sargent (2008a), in which agents observe regime realizations of a Markov-switching process without noise but need to learn its transition probability matrix. The imperfect information assumption is based on the premise that the U.S. financial system went through significant changes beginning in the mid-90s as a result of financial innovation and deregulation that took place at a rapid pace. As in Boz and Mendoza (2010), agents go through a learning process in order to "discover" the true riskiness of the new financial environment as they observe realizations of regimes with high or low borrowing ability.

Our quantitative analysis is related to Bianchi and Mendoza (2010)'s quantitative study of macro-prudential policy. They examined an asset pricing model with a similar collateral constraint and used comparisons of the competitive equilibria vis-a-vis a social planner to show that optimal macro-prudential policy curbs credit growth in good times and reduces the frequency and severity of financial crises. The government can accomplish this by using Pigouvian taxes on debt and dividends to induce agents to internalize the model's pecuniary externality. Bianchi and Mendoza's framework does not capture, however, the role of informational frictions interacting with frictions in financial markets, and thus is silent about the implications of di®erences in the information sets of policy-makers and private agents.

Our paper is also related to Gennaioli, Shleifer, and Vishny (2010), who study financial innovation in an environment in which "local thinking" leads agents to neglect low probability adverse events (see also Gennaioli and Shleifer (2010)). As in our model, the informational friction distorts decision rules and asset prices, but the informational frictions in the two setups differ.3 Moreover, the welfare analysis of Gennaioli, Shleifer, and Vishny (2010) focuses on the effect of financial innovation under local thinking, while we emphasize the interaction between a fire-sale externality and informational frictions.

Finally, our work is also related to the argument developed by Stein (2011) to favor a cap and trade system to address a pecuniary externality that leads banks to issue excessive short-term debt in the presence of private information. Our analysis differs in that we study the implications of a form of model uncertainty (i.e. uncertainty about the transition probabilities across financial regimes) for macro-prudential regulation, instead of private information, and we focus on Pigouvian taxes as a policy instrument to address the pecuniary externality.