WPS8237 Policy Research Working Paper 8237 Financial Development, Growth, and Crisis Is There a Trade-Off? Norman Loayza Amine Ouazad Romain Ranciere Development Research Group Macroeconomics and Growth Team November 2017 Policy Research Working Paper 8237 Abstract This paper reviews the evolving literature that links financial emerging and controversial literature supports the notion of development, financial crises, and economic growth in the “too much finance,” suggesting that there might be a thresh- past 20 years. The initial disconnect—with one literature old beyond which financial depth becomes detrimental for focusing on the effect of financial deepening on long-run economic growth by crowding out other productive activi- growth and another studying its impact on volatility and ties and misallocating resources. Nevertheless, the growth/ crisis—has given way to a more nuanced approach that ana- crisis trade-off is alive and strong for a large share of the world lyzes the two phenomena in an integrated framework. The economy. Recognizing the intrinsic trade-offs of financial main finding of this literature is that financial deepening development can provide a useful framework to design pol- leads to a trade-off between higher economic growth and icies targeting financial deepening, diversity, and inclusion. higher crisis risk; and its main conclusion is that, for at least In particular, acknowledging the trade-offs can highlight middle-income countries, the positive growth effects out- the need for complementary policies to mitigate the risks, weigh the negative crisis risk impact. This balanced view has from financial macroprudential policies to monetary policy been revisited recently for advanced economies, where an frameworks that monitor the growth of credit and asset prices. This paper is a product of the Macroeconomics and Growth Team, Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at nloayza@worldbank.org. The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Produced by the Research Support Team Financial Development, Growth, and Crisis: Is There a Trade-Off?* Norman Loayza Amine Ouazad Romain Ranciere The World Bank HEC Montreal University of Southern California Keywords: Finance, Financial Deepening, Development, Growth, Productivity, Crisis, Volatility, Risk, Macroprudential Policies. JEL Codes: E44, O40, G00, G01, G32, H12 * This paper has been prepared as a chapter for the forthcoming Handbook of Finance and Development, edited by Thorsten Beck and Ross Levine (Edward Elgar Publishing). We are grateful to the editors for their valuable advice and encouragement. We are also grateful to Luis Serven for insightful suggestions. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors; they do not necessarily represent the views of the institutions to which they are affiliated. 1. Introduction and Background Finance is the fuel of economic growth. Yet, the same fuel, when excessive and triggered by a shock of flame, can engender an economic crisis. For decades, the economics literature studied these two effects separately, building independently massive cases in favor of and against financial activity. Since the mid-2000s, however, the economics literature recognized that the positive and negative aspects of finance should be considered jointly. This innovation has prompted an exploration of the trade-offs involved in various aspects of financial development, such as depth, inclusion, composition, and variety. Likewise, it has induced a new type of policy debate regarding monetary and financial affairs, a debate that takes into account the trade-offs intrinsic in financial development (see, for instance, World Bank (2013)). And from this debate, a diversity of policy reforms has been implemented across the world, from financial macroprudential policies to monetary policy frameworks that monitor credit and asset price growth. The level of financial development is the degree to which financial instruments, markets, and intermediaries ameliorate the effects of information, enforcement, and transactions costs by providing broad categories of financial services to the economy: (i) producing ex ante information about possible investments, (ii) monitoring investments and exerting corporate governance, (iii) trading, diversification, and management risk, (iv) mobilizing and pooling savings, and (v) facilitating the exchange of goods and services. Each of these financial functions may influence savings and investment decisions and hence economic growth (Levine, 2005). Financial development is, therefore, a rather general term, and the literature has often used more concrete concepts and measurements to characterize it. One of the most commonly used is the concept of financial depth, which denotes the extent of credit, financial capital, and financial products in the economy. In turn, the most popular empirical proxy for measuring financial depth is the ratio of credit extended by commercial banks to the private sector over GDP (Levine, Loayza and Beck, 2000). There are other dimensions of financial development –value, quality, diversity, efficiency, and inclusiveness—and corresponding empirical proxies that can be relevant to evaluate the contribution of finance to the economy. Some of the recently used 2 proxies include the value added of the financial sector (Philippon, 2010), the share of employment in the financial sector (Cecchetti and Kharroubi, 2015), and the wages and wage premia in the financial industry (Philippon and Resheff, 2012). These additional measures might be particularly relevant to discuss the allocation or misallocation of factors between the financial sector and the rest of the economy and to test some model-based hypotheses. The first objective of this paper is to review the literature that considers the trade-offs and the sometimes opposite effects of financial deepening. The second objective of the paper is go beyond aggregate growth outcomes and consider the effect of financial depth, volatility, and crises on other socio-economic outcomes such as segregation and inequality. Before we embark on these objectives, let us examine briefly the literatures that consider, on the one hand, the link between finance and growth and, on the other hand, the link between finance and crisis. The evidence suggests that there is a strong and robust long-run relationship between financial and economic development. Moreover, there is sufficient evidence that financial development causes economic growth. King and Levine (1993) has proven to be a seminal paper in this line of research, prompting dozens of related studies in the following 25 years. Levine (1997) gives an early account of this burgeoning literature, providing also a conceptual framework to understand the connection between finance and growth comprehensively. Almost a decade later, Levine (2005) reviews critically the theoretical and empirical literature, proposing in turn an agenda of research that includes understanding the heterogeneous effects of finance on growth in different contexts. Although the long-run relationship between finance and growth has been broadly accepted, there have been two main areas of controversy.1 The first one deals with the direction of causality, and the second concerns the homogeneity of the impact in various countries, contexts, and levels of development. 1 A minority of papers has found weak or insufficient evidence that financial development causes economic growth. See Harris (1997), Ram (1998), Singh (1997), and Favara (2003). 3 On the causality issue, Levine, Loayza, and Beck (2000) provide strong, though not uncontroversial, evidence that financial depth generates larger economic growth. Working with a panel of cross-country and time observations, the paper uses both external instruments (legal origin) and internal instruments (past observations of explanatory variables) to isolate the exogenous impact of financial depth on growth, finding it to be statistically and robustly positive. Beck, Levine, and Loayza (2000) and Benhabib and Spiegel (2000) go one step further and find that the mechanism through which finance improves growth is mainly through its positive effect on total factor productivity. Studies using primarily cross-country or longitudinal panel data mainly test the causality direction from finance to growth, confirming in most cases its significance. On the other hand, papers using more intensively the time-series dimension of the data (whether for a single country or for many), test the causality in both directions. Although specific results vary, they tend to find that causality may run in both directions. See, for example, Berthelemy and Varoudakis (1996), Luintel and Khan (1999), Shan, Morris, and Sun (2001), Khalifa Al-Yousif (2002), Calderon and Liu (2003), and Ghirmay (2004). 2 The second area of controversy has been the homogeneity of the growth effect of financial deepening. Although the original papers did not pretend to measure other than average effects (although they did consider non-linearities through a log-linear regression specification), they have been criticized for advocating a one-size-fits-all approach. A large literature has emerged trying to understand how the effect of financial deepening varies according to the level of economic development, the level of financial development, and other country characteristics. See, for example, Arestis and Demetriades (1999), Deidda and Fattouh (2002), Rousseau and Wachtel (2002), Rioja and Valev (2004), Aghion, Howitt, and Mayer-Foulkes (2005), Demirguc- Kunt, Feyen, and Levine (2011), Arcand, Berkes, and Panizza (2011), and Barajas, Chami, and Yousefi (2016). Pasali (2013) provides a comprehensive review of this strand of this literature. The paper finds little consensus on whether more economically advanced countries benefit more from financial deepening than developing countries do; however, it does find an emerging 2 A few papers, however, reject bi-directionality, favoring causality from finance to growth. See Christopoulous and Tsionas (2004), Liang and Teng (2006), and Ang and McKibbin (2007). 4 consensus that the benefits of financial deepening may decrease for large levels and large accelerations of financial depth, posing the possibility of “too much finance.” While much of the empirical evidence uses cross-country data at the national scale, several studies have also shown a strong relationship between finance and growth at the local and firm levels. They have also concerned themselves with issues of causality and homogeneity. See, for example, Jayaratne and Strahan (1996), Guiso, Sapienza, and Zingales (2004), and Kendall (2012). A key paper in this vein is Rajan and Zingales (1998), which, using firm-level data, finds evidence that industrial sectors that require greater levels of external finance grow faster in countries with more developed financial markets. This documents one mechanism through which financial development can positively affect growth: a reduction in the cost of external finance to firms.3 Similarly, Demirguc-Kunt and Maksimovic (1998) show that firms in countries with developed financial institutions and efficient legal systems obtain more external financing than firms in countries with less-developed institutions. Beck, Demirguc-Kunt and Maksimovic (2005) assess the impact of financial, legal, and corruption problems on firms’ growth rates. It finds that smaller firms are more constrained by these problems but also benefit the most from financial and institutional development. Finally, Love (2001) shows that financial development diminishes financing constraints by reducing information asymmetries and contracting imperfections. Turning now to the crisis literature, it must be said that it is at least as rich and diverse as the growth literature. Here, we only review the main messages from studies that have focused on the connection between financial deepening and economic crisis. The first finding is that rapid acceleration of bank credit, sovereign debt, and equity prices are robust predictors of the occurrence and intensity of financial crisis. See, for example, Kaminsky and Reinhart (1999) and Jordá, Schularick, and Taylor (2011). The second, related finding is that this rapid acceleration in volumes and prices of financial assets is part of a boom-bust cycle, with the financial bust producing the negative effects on the real economy. Dell’Arrica et al. (2015), for instance, finds that one out of three credit booms is followed by a crisis, and that the longer is a boom, the most likely it ends in a crisis. See, in addition, Higgings and Osler (1997), Allen and Gale (1999, 2000), 3 Khan (2001) develops a theory of financial development that is based on the costs associated with the provision of finance, consistent with the evidence of Rajan and Zingales (1998). 5 Reinhart and Rogoff (2008), Allen et al. (2011), and Schularick and Taylor (2012). The third finding is that this boom-bust phenomenon can be fueled and aggravated in an international economy context, with the bust connected to the “sudden-stop” of capital flows. See, for instance, Dornbusch, Goldfajn, and Valdes (1995), Calvo (1998), Chang and Velasco (2001), and Aguiar and Gopinath (2007). The link between financial liberalization and increased instability has also been the subject of much debate, which is extensively discussed in Stiglitz (2000). While the evidence suggests that both financial institutions and financial markets influence economic growth and crisis, there is a branch of the literature dedicated to determining whether a bank-based system or market-based system is better for growth and stability. See Levine and Zervos (1998), Levine (2002), Beck (2011), and Haiss, Juvan and Mahlberg (2011). This work is summarized in Beck (2011), which concludes that there is little evidence that either financial structure is uniformly better. This ambiguity is reflected in the findings of recent papers. For instance, Gambacorta, Yang, and Tsatsaronis (2014) conclude that the services provided by banks are particularly beneficial for less developed countries and that while healthy banks are able to cushion shocks during normal downturns, this shock-absorbing capacity is impaired during financial crises. On the other hand, Langfield and Pagano (2016), focusing on advanced economies and taking into account the 2007-2008 crisis, document that an increase in the size of the banking system relative to equity and private bond markets is associated with lower growth and more systemic risk. The insight that there may be a darker side to finance is derived from two, often interrelated aspects: first, the possibility that some features of finance may be wasteful and crowd out productive activity; and second, the realization that certain characteristics of financial development may make the economy more vulnerable to crisis. This insight features prominently in recent papers, such as Gabaix and Landier (2007), Beck (2012), Beck et al. (2012), Beck, Degryse, and Kneer (2014), Law and Singh (2014), Cecchetti and Kharroubi (2015), Caldera-Sanchez and Gorri (2016), and Eden (2016). Importantly, it is at the heart of the literature that has attempted a link between financial development, growth, and crisis that started in the mid-2000s, with Tornell, Westermann, and Martínez (2003), Loayza and Ranciere (2006), and Ranciere, Tornell, and Westermann (2006). 6 The next sections of this paper assess the benefits and drawbacks of financial development in terms of growth and stability. In section 2, we document a large literature that has developed an integrated approach to study the effects of financial development on growth and crises, and that has established the presence of a higher growth-higher crisis risk trade-off, in particular for middle-income countries. In section 3, we review a more recent literature that focuses on advanced economies and suggests the possibility that pushing financial development beyond some level can be detrimental for growth and expose countries to severe crisis risk. In section 4, we explore the distributional effects of financial development, recognizing that an exclusive focus on aggregate growth outcomes runs the risk of masking important within-country distributional effects of financial development and crises. To illustrate such effects, we analyze the boom-bust credit cycle experienced by the US economy during 2000-2010, considering outcomes such as segregation and wealth distribution. Section 5 concludes, outlining some avenues for future research. 2. The Integrated Approach: A Trade-Off between Higher Growth and Higher Crisis Risk The apparent paradox between the long run growth view which emphasizes the contribution of financial development to growth (Levine, Loayza and Beck, 2000), and the early warning signals literature view which stresses credit growth as the most powerful predictor of financial crises (Schularick and Taylor, 2012) calls for an integrated approach. The central hypothesis is the existence of a trade-off associated with the dual effect of policies fostering financial development, potentially leading to both higher growth and higher crisis risk. An integrated framework should enable us to understand under what conditions contrasting effects are triggered and to quantify the net effect of financial development. Loayza and Ranciere (2006) and Ranciere, Tornell, and Westerman (2006) provide the first econometric models that allowed to estimate such dual effects. In the context of a panel error- correction model estimated by the Pooled Mean Group estimator (Pesaran, Shin, and Smith, 1995), Loayza and Ranciere (2006) show that a positive long-run relationship between financial depth and economic growth could co-exist with heterogeneous, country-specific, short-run effects that are, on average, negative. This suggests that along a long-run path in which finance 7 and growth are positively related there might be short-run fluctuations in which (excessive) credit growth is associated, on average, with output contractions. An analysis of the distribution of the estimated short-run coefficients reveals that crisis-prone countries are about twice more likely to experience a negative relationship. Crisis-related volatility is not, however, the only reason for this short-run negative dynamic: a fair share of lending booms end up in soft landing with a protracted output contraction but without experiencing a full-blown crisis, as pointed out by Gourinchas et al. (2001). Ranciere, Tornell and Westerman (2006) provide the first direct test of the dual effects of financial liberalization in an integrated framework, using the treatment effect model developed by Heckman (1978). The model combines a growth equation that includes a dummy for financial liberalization and a dummy for financial crises with a crisis equation that endogenizes the probability of a crisis. The probability of a financial crisis depends on a range of crisis predictors including the dummy for financial liberalization. In a first step, the crisis model is estimated using a standard probit model as in the Early Warning Signals literature. In a second step, the growth equation is estimated augmented by the hazard rate derived from the probit model to capture the endogeneity of crisis risk. In this two-equation model, financial liberalization has a dual effect on growth: a direct effect which reflects the impact of financial liberalization on growth in tranquil times, and an indirect effect which accounts for the expected cost of crisis. Formally, we obtain: E (Growth Gains From FL ) = E (Growth Effect of FL | No Crisis )  E (Crisis Costs )  [Pr (Crisis | FL )  Pr (Crisis | No FL)] where FL is a dummy for financial liberalization. The results based on a sample of 60 middle-income countries between 1960 and 2000 indicate that the direct growth effect (the growth gain conditional on no crisis) is positive with a point estimate of about one percentage point per year, while the indirect effect ranges between 0.25 and 0.3 percentage point per year, depending on the financial liberalization index used. Therefore, the overall net growth effect is positive at about 0.7-0.75 percentage points. To understand this result, keep in mind that while crises entail very large output costs -- typically an output contraction of about 10 percentage points -- they remain rare events even after financial 8 liberalization --financial liberalization typically raises the annual probability of crisis from 2 to 4 percentage points.4 While the hypothesis of a trade-off between instability and growth sounds reasonable by analogy with the risk-return trade-off for financial returns, it still requires a framework to be fully understood in a macroeconomic context. Ranciere, Tornell, and Westerman (2008) and Ranciere and Tornell (2016) provide such framework. The basic idea is that risk-taking is a way to alleviate contract enforceability problems that severely constrain credit and investment in growth- enhancing activities. With imperfect enforceability of contracts, lenders must limit the leverage undertaken by investors in order to curb their incentives to divert borrowed funds. When risk- taking allows entrepreneurs to reduce the effective cost of capital, it also reduces their incentives to divert funds and allows them to attain greater leverage and investment. Higher leverage for entrepreneurs comes at a cost of default in bad times and therefore the leverage gains enjoyed by entrepreneurs should be large enough for such risky strategy to arise in equilibrium. This is the crisis/growth trade-off at the microeconomic level. An important question is how the micro-level incentives for risk-taking, generate systemic risk- taking at the macroeconomic level. First, the presence of systemic bailout guarantees provides incentives to both entrepreneurs and lenders to coordinate in risk taking, a phenomenon labeled by Farhi and Tirole (2012) as collective moral hazard. 5 Second, risk-taking should generate a feedback loop between credit leverage, prices, and firm profitability that results in multiple equilibria with a solvent "tranquil-times" equilibrium and a crisis equilibrium. In an open economy, such feedback loop arises, for instance, when risk-taking takes the form of a currency mismatch between the denomination of debt liabilities and that of revenues. In the good (tranquil-times) equilibrium, lenders anticipate entrepreneurs to be solvent, and so provide enough credit so that the demand for non-tradables is sufficiently high, ensuring entrepreneurs to be indeed solvent. In the crisis equilibrium, lenders anticipate default, credit constraints 4 Razin and Rubinstein (2006) use a similar approach to look at the effects of the exchange rate regime and capital flows on growth and crisis risk and find similar results. 5 While systemic bailout guarantees are useful to understand how risk-taking is taken collectively (Farhi and Tirole, 2012), other market imperfections, such as limited liability, can also reduce the effective cost of funds and provide incentives for risk taking even in the absence of bailouts (see Dell'Arriccia et al., 2016). 9 become tighter, and the price of non-tradeables collapses (i.e. a real-exchange rate depreciation). In this case, a currency mismatch results in a balance sheet crisis where entrepreneurs default (Krugman, 1999). The framework of Ranciere, Tornell, and Westerman (2008) and Ranciere and Tornell (2016) produces two types of growth trajectories: a safe growth path, which is characterized by low credit, low leverage, and low growth but no crisis risk; and a risky growth path, which is characterized by boom-bust cycles. Under financial repression only the safe growth path exists, while under financial liberalization both the safe and the risky growth paths can arise. For which countries can we expect the growth gains to outweigh the crisis costs when they shift from safe growth to risky growth? Ranciere, Tornell, and Westerman (2008) find that they are typically the countries with an intermediate degree of contract enforcement, a group that largely consists of middle-income countries. For countries with a very low degree of contract enforcement, risk-taking allows only for limited leverage gains; growth gains are therefore modest and do not outweigh crisis costs. For countries with a high degree of contract enforceability, credit constraints are much less severe and therefore the growth gains of relaxing them are more limited. A key element for risky financial development to pay off despite the higher risk of a crisis is that relaxing credit constraints for the most constrained firms or sectors generates positive externalities for the rest of the economy. Varela (2016) provides evidence of such externality in the case of financial liberalization in Hungary by comparing the productivity of domestic firms and that of multinational firms. Following the 2001 liberalization, domestic firms were able to access more credit and to upgrade their technology, and multi-national firms reacted by also increasing their productivity-enhancing investments. As a result, competition increased and the economy became more efficient. Levchenko, Ranciere, and Thoenig (2009) provide industry-level evidence that financial liberalization favors entry and lead to a reduction of the markups. To sum up, technology upgrading (Varela, 2016), a reduction of bottlenecks through more abundant and cheaper production of key inputs for the rest of the economy (Ranciere, Tornell, and Vamvakidis, 2011; and Ranciere and Tornell, 2016), or a reduction in markups (Levchenko, Ranciere, and 10 Thoenig, 2009), are the typical channels through which higher access to credit and the associated relaxation of borrowing constraints foster growth and compensate for the increased crisis risk. A related empirical question is about how to best measure the macroeconomic volatility associated with crisis risk. A boom-bust cycles is generally characterized by a protracted and gradual credit boom that ends in a sudden and abrupt crisis when credit collapses. Such asymmetric fluctuations can, arguably, be better captured by the skewness of credit growth, which measures the degree of asymmetry of a distribution, rather than by its variance.6 Using skewness allows disentangling the incidence of rare crises from more high frequency and symmetric volatility driven, for example, by pro-cyclical fiscal policy (Kaminsky, Reinhart and Vegh, 2004). Using a sample of 83 countries over the period 1960-2000, Ranciere, Tornell, and Westerman (2008) finds that the skewness of credit growth is associated with higher long-run growth, especially so for countries with a medium capacity of contract enforceability. The positive effect of the skewness of credit growth on GDP growth –indicating that countries experiencing boom-bust cycles grow on average more rapidly than countries with more stable credit conditions—co-exists, however, with the result that the variance of credit growth reduces economic growth, a result consistent with those in Ramey and Ramey (1995) and Hnatkovska and Loayza (2005). How do financial sector policies compare with other pro-growth reforms in creating a trade-off between more growth and more exposure to crisis? Caldera-Sanchez and Gorri (2016) and Caldera-Sanchez et al. (2016) revisit empirically this possible trade-off by considering a range of reform policies for a sample of 100 countries over the period 1970-2014. They use a methodology similar to that of Ranciere, Tornell, and Westermann (2006) combining a growth equation and a crisis equation. They find that the trade-off higher growth - high crisis risk only applies to financial market liberalization policies. Product market reforms do not have any significant impact on crisis risk while trade reforms and strong active labor market programs can simultaneously increase growth and reduce the risk of crisis. 6 In other terms, the distribution of credit growth is skewed by the incidence of rare but severe crisis, which can be interpreted as the realization of an abnormal downside risk. 11 Caldera-Sanchez et al. (2016) also find that it is domestic private credit and international private debt flows that are the main driver of crisis risk. This result does not mean, however, that switching to policies favoring equity financing will necessarily ameliorate the trade-off. Debt finance provides some disciplinary mechanism in normal times even if, as a non-contingent liability, it simultaneously increases tail risk. Caldera-Sanchez et al. (2016) also finds that a higher quality of institutions improves the trade-off associated with financial reforms, with growth gains more likely to outweigh crisis costs. Most results on the trade-off higher growth/ higher volatility and crisis risk have been obtained with aggregate data and may suffer from the usual pitfalls associated with cross-country growth regression (endogeneity and simultaneity biases). There are, however, a number of papers that tackle the same issue using sector-level data and exploiting (plausibly) exogenous cross-sectoral variation, such as sectoral difference in financial dependence (Rajan and Zingales, 1998). Levechenko, Ranciere, and Thoenig (2008) using a panel of 28 sectors in 60 countries for the period 1970-2014, finds that financial liberalization increases simultaneously growth and volatlity. Interestingly, the growth effects are likely to be transitory while the volatility effects tend to be permanent. A welfare analysis a la lucas (1987) suggests, however, that because the growth effects are large enough –leading to a permanent increase in the level of output-- there are positive net welfare gains despite the increase in growth volatility being permanent. Manganelli and Popov (2015) finds that a large share of such increased volatility corresponds to sectoral reallocation that can also increase long-run growth by reducing misallocation. Popov (2014) finds that the effect of financial liberalization on the skewness of credit growth can also be observed at the sector-level. To sum up, the empirical evidence points towards the existence of a trade-off of higher growth and higher crisis risk associated with liberalization policies that foster domestic financial development and international financial openness. The trade-off seems to be mostly relevant for liberalizing middle income countries. These are countries whose institutions are typically strong enough so that they can benefit from financial liberalization in tranquil times, but weak enough so that the severity of borrowing constraints makes it worthwhile for them to take on crisis risk to boost leverage, investment, and growth. 12 3. "Too Much Finance" or “Trade-Off No More”? The crisis of 2007-2008 has re-opened the debate on whether there is an optimal degree of financial depth; or, in other terms, whether beyond some level of financial depth there is "too much finance" so that there are no more positive benefits in terms of growth and investment but still significant costs in terms of financial fragility and macroeconomic stability. A more drastic version of the "too much finance" hypothesis implies that certain types of financial activity might generate social welfare losses even in tranquil times and result in a misallocation of resources in the economy. Theoretically, what are the minimal conditions under which a deepening of financial liberalization can lead to a reduction in welfare? Ranciere and Tornell (2011 and 2016) suggest that a simple change in the menu of assets, such as the introduction of derivatives contracts on top of debt and equity contracts, can be enough to overturn the result that systemic risk-taking is growth and welfare-enhancing. In the presence of systemic bailout guarantees, the use of derivatives (such as a “catastrophe bond” or CAT) induces borrowers to shift a greater fraction of their liabilities into the crisis state in which bailouts are triggered. In such an environment, the disciplinary effect of a standard debt contract (whereby the borrower/investor should generate returns in excess of the lending rate in normal times and be exposed to losses if the risk materializes) breaks down. When this happens, projects with negative net present value are funded and the generosity of expected bailouts matters more than repayment incentives in determining leverage. Ranciere and Tornell (2011) argue that the mechanism described above was at play in the run- up to the 2007-2008 financial crisis (see also Cochrane, 2010). Prior to the crisis, many households obtained mortgages they could not repay unless real estate prices would keep increasing, allowing them to continuously refinance at low interest rates. When real estate prices stopped rising in 2006, households’ liabilities increased sharply as they lost the ability to refinance at low (“teaser”) interest rates or with interest-only loans. A large share of such price-sensitive borrowers then underwent mortgage defaults and foreclosures. By facing different interest rates in normal and crisis times, these borrowers were de facto having derivatives-like payoff 13 structures, which induced them to shift liabilities to the crisis and bailout states. The same applies to the financial institutions that packaged these loans into mortgage-backed securities (MBS) and collateralized debt obligations (CDO), and to those who insured them with Credit Default Swaps. Let us now turn to the empirics on how “too much finance” may affect the trade-off between higher growth and higher crisis risk. Specifically, do the growth effects vanish at high levels of financial depth, or is it that the volatility and crisis effects become so large that they more than offset the growth effect? Arcand, Berkes, and Panizza (2015) explore both hypotheses and conclude that only the former is not rejected by the data. Beyond a ratio of private credit to GDP of 100 percentage points, the growth effects of financial deepening are no longer significant. There is no evidence, however, that a high ratio of credit to GDP by itself is associated with higher macroeconomic volatility. This latter result is consistent with the notion that rapid growth of credit rather than high level of financial development increases crisis risk (Schularick and Taylor, 2012). The findings of Arcand et al. (2013) leave open the question on whether the interaction between high level of financial depth and some other economic trends can be the source of financial fragility and crisis risk. Kumhof, Ranciere, and Winant (2015) explore the role of income inequality as such source. Both the period prior to the great depression and the period prior to the great recession in the US have witnessed a rapid increase in household credit, a rapid increase in income inequality, and, ultimately, a deep financial crisis. A potential explanation is that the widening of income inequality generates large savings at the top of the income distribution that are, in part, recycled in the form of loans to households in the bottom part of the income distribution (who are using them to mitigate the effect of their relative fall in income). As a result, the bottom income group becomes increasingly indebted, which creates a risk for financial stability. Kumhof, Ranciere, and Winant (2015) find that quantitatively the increase in income inequality between 1983 and 2007 --where the top 5% share of the income distribution increased from 24 to 34 percent—explains more than two-thirds of the increase from 60 to 140 percentage points in the debt to income ratio of the bottom 95 percent of the income distribution. They argue that the financial innovations observed in that period, such as the emergence of a new securitization chain for subprime mortgages, were partly an endogenous response of the 14 financial system to changes in the income distribution. A feedback loop between finance and income inequality can also occur: Philippon and Resheff (2012), for instance, finds that about 15 percent of the increase in income inequality in the US since 1970 can be traced to the rapid growth in earnings in the financial sector. A recent literature has focused in explaining the source of the vanishing growth effects of financial depth, a fact first highlighted by Rousseau and Wachtel (2011). Following Beck et al. (2012), Arcand, Berkes, and Panizza (2015) studies whether the difference in the effect of household credit vs. firm credit could explain such vanishing effect. It finds evidence that firm credit is more growth conducive than household credit, and, therefore, the vanishing effect can be related to excessive household credit and, especially, mortgage loans. Furthermore, Chakraborty et al. (2016) document empirically that household credit tends to crowd-out firms’ credit, and especially so for firms that are more capital constrained. Relatedly, Mian, Sufi, and Verner (2017) show that an increase in household debt relative to GDP tends to predict lower GDP growth and higher unemployment in the medium run. The empirical evidence on the vanishing effect of finance on growth forces us to clarify the underlying theoretical hypotheses. As discussed in Levchenko, Ranciere, and Thoenig (2009), there are three competing hypotheses. The first is that finance only accelerates convergence to a given steady state, whose level depends only on technology. The second is that finance increases the GDP growth rate indefinitely, as it would be the case in AK growth models where finance enables an increase in the investment rate (see Obstfeld, 1994 and Bencivenga and Smith, 1991). The third, intermediate hypothesis is that finance allows the economy to reach a higher steady state and by so doing boosts growth in the transition process. A conclusion of the "too much finance" literature is to rule out the second hypothesis. Distinguishing between the first and last hypotheses is empirically more challenging. The results by Aghion and Mayer-Foulk (2005) and Arcand, Berkes, and Panizza (2015) seem to support the first, accelerating convergence view. Using industry-level data, Levchenko, Ranciere and Thoenig (2009) provide more support to the third hypothesis, by showing that finance has a strong effect of reducing industry mark-ups and has therefore the potential to lift the economy towards a higher (less distorted) steady state. 15 Another explanation for the vanishing effect is the view that certain financial activities crowd out more productive ones and result in a misallocation of talent in the economy that is detrimental to growth. Cecchetti and Kharroubi (2012) shows that the non-monoticity in the relationship between finance and growth is particularly strong when financial sector employment is used as a proxy for financial depth. Cecchetti and Kharroubi (2015) proposes a model to understand the source of the negative relationship between the rate of growth of the financial sector and productivity growth at high levels of financial development. The model is centered on two externalities, an investment externality through which finance favors projects with high collateral even when they are less productive, and a labor externality by which the financial sector attracts skilled labor and grows at the expense of the real economy. Using a cross-country panel of industry-level data, the paper finds supportive evidence for the two externalities. What role do financial regulation and supervision play in controlling the risk that financial deepening results in misallocation of resources and talent? Philippon and Resheff (2012) find a tight link between the wage premium commanded by the financial industry and an index of financial deregulation. By 2006, the excess wage premium in the financial industry was about 50% in absolute terms and between 20% and 30% in certainty-equivalent terms. The premium for CEOs in the financial sector was about 250% compared to CEOs elsewhere. Interestingly only one-fifth of this premium could be related to the size of assets under management, a standard explanation for the rise in CEOs pay (Gabaix and Landier, 2008). A fraction of the rest can be due to innovation in the financial sector but might also be related to risk-taking behavior, facilitated by deregulation such as the 1999 repeal of the Glass-Steagall Act. Philippon and Resheff (2013) finds cross-country evidence on the positive link between the share of the finance industry, wage premia in the financial sector, and measures of financial deregulations. Philippon and Resheff (2012) also suggest that wage premia in the financial sector render more difficult the enforcement of financial regulations, since such activities require similar skills as those sought after in the private financial sectors but command salaries that are constrained by the public sector pay scale. From a policy perspective, how shall we deal with "too much finance"? Tightening financial regulation should be balanced to prevent misallocation and abuse while also keeping the 16 incentives for innovation. Ranciere and Tornell (2011 and 2016) discuss how regulation should be designed in an environment where systemic bailouts during crises exist. If these bailouts cannot be eliminated, risk takers should also bear the consequences of their losses. Special attention must be paid to the regulation of derivatives that give the option to shift losses to the crisis state. This implies, for example, putting Credit Default Swaps on an organized exchange, with marginal calls ensuring that risks are adequately provisioned. Better financial supervision can also have an impact on wage premium and generate a larger flow of talent towards other sectors. Apart from improvements in financial regulation and supervision, taxation can be used to avoid excessive finance. Philippon (2010) proposes a theoretical framework which discusses how the financial sector and the non-financial sector (or, in schematic terms, financiers vs. entrepreneurs) should be taxed or subsidized as a function of the externalities they bring on the rest of the economy. The issue is complex since entrepreneurs face borrowing constraints and, therefore, require the service of financiers to invest efficiently. A key result is that when education and investment are properly subsidized to account for the innovation externalities, the financial sector should be taxed in exactly the same way as the non-financial sector. The recent literature on the theme of “too much finance” has been primarily focused on the vanishing growth effects of financial deepening beyond a certain level of depth. Less evidence is provided on its effect on financial stability and crisis risk even if the crisis of 2007-2008 suggests that unfettered financial liberalization and the proliferation of new financial instrument increases crisis risk. This creates the possibility that financial deepening without proper regulation can be harmful for both growth and stability. Therefore, from a policy perspective, the challenge is to find the kind of financial regulation and supervision that can, first, minimize the trade-off between higher growth and higher risk, and second, generate positive effects on growth and stability by expanding the quality of financial services from a social standpoint. 4. Beyond Aggregate Outcomes: Distributional Impacts of the U.S. Credit Boom and Bust An extensive literature in the economics of education and in labor economics has documented the potentially positive welfare effects of relaxing borrowing constraints. For instance, Brown, 17 Scholz, and Seshadri (2011) suggest that financial aid leads to an increase in educational attainment for borrowing-constrained families. The findings in Levine, Levkov, and Rubinstein (2008) imply that an increase in banking competition leads to an increase in credit supply and a decline in labor market discrimination. In standard consumer theory, borrowing constraints prevent consumption smoothing and produce a greater dependence on current income than predicted by intertemporal welfare optimization theories (such as the permanent income hypothesis). However, a recent and rather controversial literature suggests that financial deepening in the form of a greater supply of credit or of a greater diversity of financial products might have ambiguous distributional and welfare impacts, depending on how social welfare is measured. Three reasons are cited to postulate this ambiguity. First, general equilibrium effects distort price distributions. Indeed economy-wide increases in credit supply could affect the distribution of prices of products and assets in a way that may offset the partial equilibrium positive welfare impacts for a substantial fraction of households. Second, there is evidence that social preferences are present in locational choices (Krysan and Farley, 2002), consumption decisions (Bertrand and Morse, 2016), and educational production functions (Sacerdote, 2011). With such externalities, an unconstrained market equilibrium could be less efficient than a constrained market equilibrium. Third, the expansion of the supply of credit towards less creditworthy or towards more risky products can lead to large and potentially suboptimal welfare losses during downturns. Ouazad and Rancière (2016a) use transaction-level micro data to estimate the empirical relevance of the first mechanism, that is, general equilibrium effects. The paper puts forward a novel general equilibrium model of a metropolitan area to estimate the impact of the relaxation of lending standards on the distribution of housing prices. The model introduces endogenous borrowing constraints in a locational choice model, where heterogeneous households choose location across block groups based on the variation of local amenities. The paper introduces borrowing constraints by noting that the households’ choice set is constrained by mortgage originators’ lending standards. Conditional on their choice set, households choose across locations based on a comparison of the bundle of local amenities and housing prices. The probability of a given choice set is determined by the product of the probabilities of approval of 18 a mortgage application. Hence demand for a neighborhood is the weighted average of demands conditional on the choice set: P(C | x, z ) Demand ( j | x, z, C ) Demand ( j | x, z )  C {1, 2,..., J }         (1) Probability of Choice Set C conditional demand where j indexes neighborhoods {1, 2, ..., J}, x is the vector of household characteristics, and z the vector of all neighborhood amenities. The probability of a choice set C is a product of the probabilities of approval of mortgage applications: P (C | x, z )   jC P ( Approval in j| x,z )   jC 1  P ( Approval in j| x,z ) (2) In turn, approval probabilities are driven by mortgage originators’ standards. Explicitly endogenizing the choice set presents the unique advantage of allowing an analysis of the impact of changes in lending standards on each neighborhood demand. In turn, preserving the equilibrium of the city requires an adjustment of housing prices in response to the rise in neighborhood demand. Changes in lending standards thus produce a shift at each quantile of the housing price distribution. As the marginal impact of a relaxation of lending standards depends on household characteristics (e.g., race and income), housing price shifts vary across quantiles regardless of whether lending standards depend on neighborhood characteristics. Estimates based on micro data of the San Francisco Bay area for 2000-2006 suggest that the relaxation of lending standards led to a compression of the price distribution: housing prices rose more for the lower quantiles than for the higher quantiles of the housing price distribution. Such compression of the price distribution is consistent with a gentrification of lower-priced neighborhoods as the number of mixed Black-White neighborhoods is declining both in general equilibrium simulations and in observed data. Price responses to increases in lending supply typically occur in markets with low supply elasticities. While markets for consumer goods exhibit high elasticity, housing supply and the provision of higher education services can exhibit low elasticity and thus experience large and heterogeneous price responses. While Saiz's (2010) estimates suggest a large variance of housing supply across metropolitan areas, Ouazad and Rancière (2016a) finds substantially smaller neighborhood-level supply elasticities for the metropolitan area of San Francisco. Thus, changes 19 in the distribution of housing prices may be greater than what would be predicted using standard metro-level estimates. Ouazad and Rancière's (2016a) estimates of supply elasticities using 30m by 30m satellite data also display a positive correlation between supply elasticities and the distance to the central business district, a potential evidence of the importance of within-city distribution of elasticities in driving changes in wealth inequalities. Elasticities of the provision of higher education services are also likely far from the perfectly elastic benchmark. Heckman, Lochner, and Taber (1999) makes the point that general equilibrium endogenous responses to tuition subsidies can offset the estimated partial equilibrium effects and calls for a revision of microeconomic studies that do not estimate price responses. Recent developments in the use of micro data now enable a microeconomic analysis of such general equilibrium effects. Overall, as in Ouazad and Rancière (2016a), financial deepening and the rise of credit are unlikely to yield uniformly positive welfare impacts, even before the onset of a credit downturn. Another driver of financial development's welfare and distributional consequences is the presence of social spillovers, peer effects, or social externalities. Krysan and Farley (2002) use the multi-city study of urban inequality in Atlanta, Boston, Detroit, and Los Angeles to show that African-American households prefer diverse neighborhoods with about half African-American residents while White households prefer neighborhoods with greater fractions of White neighbors. With such preferences, market equilibrium in urban location choice models as in Schelling (1971) and Benabou (1996) is perfectly segregated. This is in stark contrast with market equilibrium in labor economics, where Becker (1957) predicts that competition leads to lower discrimination. Moreover, such perfect segregation at market equilibrium in a city with no credit market imperfection can be inefficient. The inefficiency of segregation or of diversity depends crucially on two key parameters: (i) whether low- and high-human capital households’ welfare is equally affected by their peers in neighborhoods and schools, and (ii) whether the marginal impact of peers is concave in the fraction of high-human capital peers. To make this clear, consider a stylized two-neighborhood city as in Benabou (1996), with two types of households, with high- and low human capital, h ∈ {hA, hB}, hA>hB. The city has a fixed density 1 of housing, and neighborhoods 1 and 2 have the same size 1/2. The total density of 20 households of human capital h = hA is n∈[0, 1] in the city, and x∈[0,1] in neighborhood 1. The welfare of an individual with human capital h and a fraction x of high-human capital neighbors is a function w(h, x). The welfare of a neighborhood is thus: W ( x)  x  w(hA , x)  (1  x)  w(hB , x) (3) The city's social optimum is reached at the maximum of W (x) + W (n − x/2). The city's optimum will be to segregate individuals if such total welfare is a convex function of x. Crucially, the optimality of segregation thus depends on two empirically measurable parameters: (i) whether high human capital individuals' welfare benefits more from high-human capital peers than low- human capital individuals, and (ii) whether welfare is a concave function of peers' human capital. 2 x ( h A , x )  x ( hB , x )  x  (hA , x)  (1  x)   2 2 w w w w (hB , x) W ( x)      x 2    x 2   (4) differential impact of peers on welfare concavity of peer effects in welfare There is evidence in some dimensions that more segregated metropolises have lower average welfare, and that low-human capital individuals benefit more from their peers than high-human capital individuals. Estimates of peer effects in schools and neighborhoods suggest that low ability peers are more affected by their peers than high ability peers (Sacerdote, 2011). Card and Rothstein (2007) find that higher segregation arguably causes a higher Black-White test score gap. A city where high human capital households are constrained in their ability to borrow could lead to higher average welfare, e.g. a third-best allocation with greater welfare than at market equilibrium. Controversially, relaxing borrowing constraints may lead to greater segregation and lower welfare, even absent a credit bust. Ouazad and Rancière (2016b) estimate the impact of the relaxation of lending standards during the housing boom of 2000-2006 on changes in racial segregation across neighborhoods within metro areas. The paper first estimates such impact for the 935 metropolitan and micropolitan statistical areas of the United States. At the metropolitan area level, a common measure of racial segregation is the set of exposure indices. For instance, the exposure of Blacks to Whites is the average fraction of White individuals in the neighborhood of an average Black resident. Despite 21 declines in overall racial segregation, the exposure of Blacks to Whites declined between the 2000 and the 2010 censuses. The paper’s first metro-level analysis correlates changes in exposure with changes in credit standards: Exposure j , 2010  2000  Credit j , 2010  2000    x j   Metro j   j (5) where ∆Creditj,2010−2000 is a measure of the change in lending standards for metropolitan area j, xj is a set of controls, including controls for demographic changes, and Metroj is a metro-area fixed effect. Two key measures of lending standards, the change in approval rate and the change in the loan-to-income ratio, experience significant changes between 2000 and 2006: the loan-to- income ratio of mortgage originations increases by 0.4, and the approval rate for mortgage applications increases by 13 percentage points. As changes in credit conditions typically reflect both shifts in the demand for credit as well as shifts in the supply of credit, identification of the causal impact β requires an exogenous source of credit supply shifts. Banks' liquidity level in the early 1990s is a significant predictor of the rise in leverage and approval rates between 2000 and 2006. Specifically, banks that were liquidity constrained or that had a less securitizable portfolio of assets in the early 1990s benefited more from the securitization boom of the early 2000s. Such boom was arguably triggered by the Federal Housing Enterprises Financial Safety and Soundness Act of 1992, by preferential treatment to banks holding mortgage-backed securities backed by the Government Sponsored Enterprises. While early 1990s bank liquidity and asset securitizability is a significant predictor of 2000-2006 changes in lending standards, there is little empirical evidence of its correlation with observable demand shifters or with observable drivers of racial segregation. Results suggest an economically significant impact of credit supply shifts on the exposure of Blacks to Whites: without the credit supply shock, Black households would have had between 2.3 and 5.2 percentage points more White neighbors in 2010. 22 Figure 1: Inflows into Census Tracts, by Percentage of Black Population in Tract Stars next to a point indicate the significance of the F test that the coefficient for high liquidity metropolitan areas and the coefficient for low liquidity metropolitan areas are identical. One star for 10% significance, two stars for 5% significance, three stars for 1 percent. Standard errors clustered by state. mB: minority black tract, fraction of Black population below 10%. Mixed: Mixed tract, fraction of Black population between 10 and 60%. MB: Mostly Black population tract, fraction of Black population above 60%. A second approach delves into metro areas' structure and estimates White, Black, Hispanic, and Asian inflows and outflows from neighborhoods based on (i) their initial composition, and (ii) credit supply shifts during the 2000-2006 boom. In that sense, the key question is whether credit supply facilitates or enables Schelling (1971)-like tipping shifts in neighborhood demographics. Figure 1 from Ouazad and Rancière (2016a) plots the coefficients of a regression of census tract- level white population changes as a fraction of initial population, on a set of dummies for quantiles of the initial fraction of Black population in 2000. The red line is the regression for metropolitan areas with high increase in approval rates as predicted by the instrument described above and the blue dotted line is for metropolitan areas with a low predicted increase in approval rate. 23 A first observation from this graph is that there is tipping as in Card, Mas, and Rothstein (2008): there are outflows of White households from neighborhoods with more than 10-15% Black residents; there are inflows of white households into other neighborhoods. More importantly, the tipping behavior is stronger in metropolitan areas with a greater credit supply increase, as the difference between the blue dotted line and the red line is statistically significant. Thus, Figure 1 provides neighborhood-level evidence that the relaxation of borrowing constraints may strengthen racial segregation. In other words, the expansion of credit supply may not be ‘a tide that lifts all boats’, as the credit boom may have led to adverse welfare consequences even prior to the credit bust. The distributional impacts of the credit bust are well established. During the four-year period between the beginning of the Great Recession in 2007 and 2011, more than half of all families lost more than 25% of their wealth (Danziger, Pfeiffer, Danziger, and Schoeni, 2013). While wealth declined at all percentiles of the distribution, the largest relative wealth losses were experienced by households already at the bottom of the wealth distribution, thus further widening the wealth dispersion. Danziger et al. (2013) documents that the median wealth of households in the bottom quintile fell up to 2011 to reach 26% of its 2003 level, while the median wealth held by the top quintile fell to 81% of its 2003 level. The Great Recession led to a widening of racial wealth gaps and a reversal of the relative gains of minority households of the late 1990s. The White-Black wealth ratio declined from a value of 12 in 1984 to 7 in 1995, reaching a historic low of 6 in 1998. The Hispanic-White wealth ratio experienced a more modest decline during the same period, from 8 to 7. The Great Recession led to more than a doubling of this wealth ratio for Blacks, and an increase of 30% for Hispanics. In 2013, the median White household's net worth was 13 times that of the median Black household and 10 times that of the median Hispanic household (Kochhar & Fry 2014). A decomposition of wealth changes sheds light on the drivers of widening inequalities. Changes in net wealth NWit are driven by shifts in asset prices, weighed by asset holdings in bonds, stocks, and housing, as well as changes in debt liabilities. NWit  pstocks, t  S i , t  pbonds, t  Bi , t  phou sin g , t  H i , t  rt  Di , t 24 with Si,t stock holdings, Bi,t bond holdings, Hi,t real estate ownership, Di,t household debt, and p and r the corresponding prices. Both stock prices pstocks,t and house prices phousing,t experienced sharp drops. The S&P 500 index lost 17% of its value between January 2006 and January 2010. The Case Shiller national house price index (resp. 20-city house price index) dropped 19% (resp. 28%). The sharpest drop in total household net worth (−19%) happened between 2007 and 2008. Both housing (−15.5%) and non-housing wealth (−22.7%) declined, with housing at about half of households' net worth. The average decline in housing wealth masks considerable heterogeneity across space, racial and ethnic groups, and initial income levels. The heterogeneity is reflected in differences both in the households' portfolio composition and in the distribution of price drops. The spatial heterogeneity in housing wealth losses was partly driven by housing supply constraints, with stronger increases during the boom and declines during the bust in the least elastic metropolitan areas (Glaeser, Gyourko, and Saiz 2008); recent evidence also points towards land hoarding as a mechanism pushing house price volatility upwards in metropolitan areas with elastic housing supply. Within metropolitan areas, the adverse effects of the decline in housing wealth are most strongly felt in specific neighborhoods rather than spread more or less evenly across space. This spatial segregation of negative welfare impacts is driven by at least two mechanisms: first, foreclosed homes increase the supply of housing in the neighborhood, thus lowering the price of nearby properties (Hartley, 2014). Second, homeowners are less likely to invest in the maintenance and upkeep of foreclosed homes, leading to externalities on neighboring properties (Gerardi, Rosenblatt, Willen, and Yao, 2015). Further, careful empirical analysis has identified economically significant impacts of vacancies on crime in the vicinity of foreclosed properties (Cui and Walsh, 2015). Foreclosure externalities reinforce a dynamic of interacting segregation and inequality. Housing-related wealth losses were also more acute among low-income and minority borrowers. Such losses are in great part explained by the highest fraction of minority households using high- cost mortgage loans, even controlling for credit score and other measures of creditworthiness (Bayer, Ferreira, and Ross 2016). This descriptive fact is the consequence of both an adverse match of lenders to borrowers, and a worse treatment of minority borrowers by lenders with 25 similar characteristics but a different race or ethnicity. The larger losses of minority households are compounded by the greater share of housing wealth in minority households' net position, even as minority households typically held smaller equity in their housing investments. An overall assessment of the net distributional impact of the boom and the bust remains beyond the scope of this paper. Nevertheless, an assessment of descriptive statistics on (i) the wealth distribution, (ii) homeownership, housing equity, and household leverage, and (iii) segregation, can shed light on the net welfare impacts of the 2000-2010 credit boom and bust cycle. First, the wealth share of the top 1% wealth holders rose from 32% to 40% during this period. Second, while the homeownership rate is almost identical in 2000 and in 2010 at 67.1%, the Black homeownership rate declined by 1.8 percentage points, from 47.4% to 45.6%, the Hispanic homeownership rate increased by 3 percentage points, from 45.7% to 48.5%, and the White homeownership rate increased by 1.1 percentage points, from 73.4% to 74.5%. Third, while overall urban racial segregation declined through a greater exposure of Whites, Blacks, and Asians to Hispanics, Blacks exposure to Whites remained virtually constant. In 2000 as in 2010, the average Black resident lives in a neighborhood (census tract) that is 35% White, substantially below the national share of Whites in U.S. population, which stood at 72.4% in 2010. 5. Concluding Remarks The literature on financial development, financial crises, and economic growth has considerably evolved in the last 20 years. The initial disconnect, with one literature focusing on the role of financial depth on long-run growth and another studying its impact on volatility and crisis, has given way to a more nuanced literature that analyzes the two phenomena in an integrated framework. The main finding of this literature is the existence of a trade-off between higher growth and higher crisis risk and the conclusion that, for at least middle-income countries, the positive growth effects outweigh the negative crisis risk impact. This balanced view has been revisited recently, especially for advanced economies. A number of findings support the notion of "too much finance," suggesting that there might be a threshold beyond which financial depth becomes detrimental to growth even in tranquil times, by crowding 26 out other productive activities and misallocating resources within and across economies. While these results are important and must be considered in the design of financial regulation in advanced countries, we should not forget that the trade-off is alive and strong for a large share of the world economy, providing a useful framework to assess the impact of policies targeting financial deepening, diversity, and inclusion (World Bank, 2013). The discussion on the existence of a growth/risk trade-off is also relevant when we look at within- country distributional impacts of financial deepening and financial crises. For instance, U.S. policy makers, who pushed in the 1990s for a large expansion of credit to less creditworthy borrowers, believed that it could bring a host of socio-economic benefits, especially for the poor and minorities. The evidence shows, first, that these policies did not sufficiently account for the trade- off inherent in financial deepening and inclusion: without proper financial regulation and supervision, the expansion of household mortgage credit led to a massive financial crisis. More controversially, there is some evidence that these financial liberalization policies in the U.S. have had, through general equilibrium effects, adverse effects on the dynamics of segregation during the credit boom and a widening of wealth gaps during the bust and its aftermath. What is the likely direction of future research? First, it will consider a larger heterogeneity of agents and impacts of financial deepening. Recent advances in both the static and dynamic modeling of household consumption decisions are pushing the frontier in the analysis of the distributional impacts of credit supply. The progress has been twofold: (i) dynamic and static models that feature rich household heterogeneity in preferences, consumption patterns, and price responses have been introduced (Bajari, Chan, Krueger, and Miller, 2013, Landvoigt, Piazzesi, and Schneider, 2015, and Ouazad and Rancière 2017), and (ii) newly available household panel data, particularly in the context of real estate tax and deeds files, has enabled the estimation of such dynamics using the most recent developments in the econometrics of discrete choice panels (Kuminoff, Smith, Timmins, 2013, and Baltagi and Bresson, 2017). Key topics in future contributions include the interaction of credit constraints, lenders’ and households’ beliefs, and life-cycle dynamics. The challenge will be to relate these heterogenous effects and complex interactions to macroeconomic outcomes regarding economic growth and crisis risk. 27 Second, from an applied perspective, new research will likely be directed at evaluating and proposing a fresh set of financial policies. Unlike the Great Depression, the Great Recession was immediately followed by massive bailouts and unconventional monetary policies. Some specialists have argued that these policy responses contributed to making the consequences of the recession less severe than those of the great depression. Looking forward, however, these large bailouts have created a dangerous precedent, that is, a potential source of moral hazard that could strongly affect the outcome of the tradeoff between higher growth and higher crisis risk. Research on financial regulation should consider policy design in a world where the commitment not to bailout is not time consistent. 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