Financial Stability and Inequality: A Challenge for Macroprudential Regulation

The global financial crisis shed new light on the role that central banks play for financial stability. In response to the financial turmoil, central banks took radical action to stabilize the financial system, by providing liquidity to banks and buying up financial assets. Following these emergency measures, central banks, financial regulators and governments implemented new macroprudential tools to reduce the risks of future imbalances for financial stability.

To design effective macroprudential policies, central banks and financial regulators must first understand the roots of financial instability. In this context, a growing body of research has highlighted the role of income and wealth inequality as potential factors of instability. This blog briefly surveys the theories and empirical evidence on this link. It then argues that central banks should keep an eye on inequality to spot potential warning signals of financial crises. They should also mitigate potential feedback loops between macroprudential policy, inequality and financial stability that may weaken the resilience of the financial system.

Inequality is a potential source of financial instability

The idea that inequality can lead to financial crises has been highlighted by several prominent economists.[1] They stress two phenomena at play: an increasing demand for debt by poor households in reaction to stagnating income, and a higher supply of savings by wealthy households, resulting from rising income. The combination of these two elements can potentially generate bubbles in debt markets, which eventually burst and trigger financial instability.

This theory makes a clear link between rising inequality, growing debt market imbalances and financial crises. If it is empirically verified, rising inequality could be an early sign of financial system weakness that central banks and financial regulators should not ignore.

From inequality to debt bubbles

The channel from increasing income and wealth inequality to financial crises relies on the development of a concomitant imbalance in debt markets. In short, inequality increases when income accrues disproportionally to wealthy households. This may contribute to higher household debt for two reasons: first, the demand for credit by poor households rises as they try to keep up with social consumption norms despite stagnating or falling real income.[2] Second, the supply of credit increases as wealthy households use part of their additional income to provide new loans. The combination of higher demand for credit by poor households and higher supply of credit by wealthy households leads to growing aggregate debt. A low interest rate environment can exacerbate this supply effect as wealthy households are more likely to search for yield and thus to lend to poor households even if the latter see their financial conditions deteriorating.[3] This can result in a combination of higher debt and higher risk taking, which ultimately weakens financial system resilience.[4]

Perrugini, Hölscher and Collie (2016) provide empirical evidence on the link between inequality and debt growth. Using a panel analysis of 18 OECD countries from 1970 to 2007, they find that higher inequality is positively related with private sector indebtedness, once other traditional drivers of debt are controlled for. This study confirms previous other evidence of a positive causal relationship from inequality to debt growth found by Bazillier and Héricourt (2014) in a literature survey.[5]

Inequality as an early warning indicator for financial crises

If inequality drives up debt, and rapid debt growth weakens financial resilience,[6] then inequality can potentially serve as an early warning signal for financial crises. Kirschenmann, Malinen and Nyberg (2016) empirically explore this hypothesis on a dataset of 14 developed countries over the years 1870 to 2008. They find that income inequality has the highest predictive power of financial crises among the variables that they consider, especially when it is at elevated levels. The role of other traditional early warning indicators, like e.g. the level of bank loans, diminishes considerably when inequality is included in the analysis. Hauner (2017) finds similar predictive power for wealth inequality for the U.S. and U.K.

To sum up, there are both theoretical and empirical grounds for central bankers and financial regulators to keep an eye on the evolution of inequality in an economy. Inequality can potentially be a cause and an early warning signal of financial instability. Policy measures that increase income and wealth inequality can also translate into higher financial instability.

There are feedback loops between macroprudential policy and inequality

One response by central banks and financial regulators to limit the risk of financial crisis is to resort to macroprudential measures. Since the 2008 crisis, there has been a renewed interest in such policies. Ceruti, Claessens and Laeven (2017) compile macroprudential measures used in 119 countries between 2000 and 2013, and find that, in advanced countries, the number of macroprudential policies in place has doubled between 2007 and 2013.

Yet macroprudential measures are not neutral in terms of income and wealth inequality; neither are income and wealth distributions without consequences for the effectiveness of these policies.

Macroprudential policy can shape inequality

Caps on loan-to-value (LTV) ratios are a good example of how macroprudential measures may impact on inequality. Caps on LTV ratios are a widely used macroprudential measure to curb imbalances on mortgage markets; they are particularly popular in advanced economies. Lowering caps is often successful in limiting credit growth and imbalances in mortgage markets,[7] but it also affects households’ access to mortgages and thus to housing. Since housing is often the key asset for a household, tightening this access with lower caps – i.e. by requiring more collateral from households to get a mortgage – may increase wealth inequality in a country.[8] However, Carpantier, Olivera and Van Kerm (2018) show that the impact of LTV-ratio caps on wealth inequality is not straightforward: higher caps on LTV ratios can theoretically decrease or increase wealth inequality depending on the underlying structure of the economy. For twelve countries in the euro area, they estimate that higher caps on LTV ratios would probably not decrease wealth inequality.

Other macroprudential measures can also have an impact on inequality. Frost and van Stralen (2018) study the link between several types of macroprudential measures and income inequality in a panel of 69 countries over the period 2000 to 2013. They find that countries with countercyclical capital buffers, concentration limits[9] or limits on credit growth tend to experience higher income inequality. By contrast, countries with specific requirements for systemically important financial institutions have lower levels of income inequality.[10]

Inequality impacts the effectiveness of macroprudential policies

Macroprudential measures have an impact on inequality, but income and wealth distributions also matter for the design of optimal macroprudential policies. Punzi and Rabitsch (2018) argue, for example, that policies that tighten lending more for highly leveraged households than for others are welfare improving compared to policies that affect everyone equally. However, the highest leveraged households are often the poorest.[11] A policy that would specifically target them would restrict their access to home ownership and potentially increase wealth inequality. Such a measure would engender a negative feedback loop: optimal macroprudential policy would increase inequality, which in turns could engender a weaker financial system. A measure initially intended to strengthen financial stability might thus potentially end up weakening it through the increase in inequality that it could generate.

By contrast, macroprudential measures that take income and wealth distribution into account can also contribute positive feedback loops between inequality and financial stability. Differentiated capital requirements for banks according to their depositors’ wealth structure are a case in point. Mitkov (2016) argues that wealth distribution influences the probability of bank runs: he shows that official deposit guarantees are usually high enough to protect all savings of poor households but not those of wealthy households, making the latter more prone to panic. Consequently, banks with wealthy depositors are more likely to experience a run than banks with poor depositors. An obvious measure to dampen this higher probability of runs would be to require higher capital or liquidity requirements for banks with wealthy depositors. This would strengthen financial stability. The additional cost induced by this measure for banks with wealthy depositors is likely to marginally reduce the return they deliver to their wealthy customers and thus marginally reduce inequality – which in turn could strengthen the whole financial system.

Inequality matters for central banks and financial regulators

Theoretical analyses and recent empirical evidence support the hypothesis that increasing inequality can pave the way to financial instability. Considering these results, central banks and financial regulators should keep a close watch on income and wealth distributions in their countries. They should be particularly attentive to a simultaneous rise in inequality and aggregate debt. They might also consider including inequality in their sets of early warning indicators for financial crises.

Central banks and financial regulators should also carefully consider the potential feedback loops between their macroprudential policy, inequality and financial stability. Some measures aimed at strengthening financial stability might increase inequality, and thus impede their initial goals. In such a case, central banks and financial regulators, perhaps in collaboration with fiscal authorities, could consider accompanying measures to mitigate the impact of macroprudential measures on inequality. When facing the choice between two policies with the same impact on financial stability, they should prefer the option that does not lead to higher inequality (or increases it the least) to avoid or reduce the side effects of higher inequality on financial stability. Finally, in accordance with their mandate regarding financial stability, central banks and financial regulators may have some reasons to support policies, e.g. fiscal policies, that mitigate the impact of inequality on financial stability.

This note builds on a presentation by the author at the NBR-IMF Financial Stability Seminar held at the National Bank of Romania in Bucharest on October 26-27, 2017. The author would like to thank Jon Frost for his useful comments.



Bazillier, R. and Héricourt, J. (2014). “The circular relationship between inequality, leverage and financial crisis: Intertwined mechanisms and competing evidence”, CEPII Working Paper no. 2014-22.

Bordo, M. and Meissner, C. (2012). “Does inequality lead to a financial crisis?”, Journal of International Money and Finance, 31(8), 2147-2161.

Borio, C. and Lowe, P. (2002). “Asset prices, financial and monetary stability: Exploring the nexus”, BIS Working Paper no. 114.

Carpentier, J.-F., Olivera, J. and Van Kerm, P. (2018). “Macroprudential policy and household wealth inequality”, Journal of International Money and Finance, 85, 262-277.

Ceruti, E. M., Claessens, S. and Laeven, L. (2017). “The use and effectiveness of macroprudential policies: New evidence”, Journal of Financial Stability, 28, 203-224.

Frost, J. and van Stralen, R. (2018). “Macroprudential policy and income inequality”, Journal of International Money and Finance, 85, 278-290.

Galbraith, J. K. (2012). Inequality and Instability: A Study of the World Economy Just Before the Great Crisis, Oxford University Press.

Goda, T. and Lysandrou, P. (2014). “The contribution of wealth concentration to the subprime crisis: A quantitative estimation”, Cambridge Journal of Economics, 38(2), 301-327.

Gu, X. and Huang, B. (2014). “Does inequality lead to a financial crisis? Revisited”, Review of Development Economics, 18(3), 502-516.

Hauner, T. (2017). “Aggregate wealth and the its distribution as determinants of financial crises”, mimeo.

IMF and ILO (2010). The Challenges of Growth, Employment and Social Cohesion, Discussion document proceeding from the joint ILO-IMF conference held in Oslo, Norway, on September 13th, 2010.

Kirschenmann, K., Malinen, T. and Nyberg, H. (2016). “The risk of financial crises: Is there a role for income inequality?”, Journal of International Money and Finance, 68, 161-180.

Kumhof, M., Rancière, R. and Winant, P. (2015). “Inequality, leverage and crises”, American Economic Review, 105(3), 1217-1245.

Lebarz, C. (2015). “Income inequality and household debt distribution: A cross-country analysis using wealth surveys”, Luxembourg Income Study Working Paper Series no. 20.

Mitkov, Y. (2016). “Inequality and financial fragility”, mimeo.

Perugini, C., Hölscher, J. and Collie, S. (2016). “Inequality, credit and financial crises”, Cambridge Journal of Economics, 40(1), 227-257.

Punzi, M. T. and Rabitsch, K. (2018). “Effectiveness of macroprudential policies under borrower heterogeneity”, Journal of International Money and Finance, 85, 251-261.

Rajan, R. (2011). Fault Lines: How Hidden Fractures Still Threaten the World Economy, Princeton University Press.

Reich, R. (2010). Aftershock: The Next Economy and America’s Future, Vintage.

Stockhammer, E. (2015). “Rising inequality as a cause of the present crisis”, Cambridge Journal of Economics, 39(3), 935-958.

UN Commission of Experts (2009). Report of the Commission of Experts of the President of the United Nations General Assembly on Reforms of the International Monetary and Financial System, United Nations, New York

Veblen, T. (1899). The Theory of the Leisure Class: An Economic Study of Institutions, Macmillan.



[1] See, e.g., UN Commission of Experts (2009), IMF and ILO (2010), Rajan (2011), Reich (2010) and Galbraith (2012).

[2] This argument goes back to Veblen’s (1899) theory of conspicuous consumption, which states that consumers’ utility is not only influenced by the absolute level of consumption, but also by its relative level compared to a reference group: a consumer who sees her level of consumption remaining constant while the consumption of others is increasing may consider herself worse off. This argument implies that an increase in income inequality will prompt people at the bottom of the income and wealth distribution to reduce savings or increase debt to keep up with increasing consumption standards observed in the rest of population.

[3] In the recent U.S. crisis, the supply effect might have been accelerated by financial deregulation (Stockhammer, 2015), and by the pressure by high-net-worth individuals on banks to deliver high yield assets through the mass production of credit derivatives (Goda and Lysandrou, 2014).

[4] These mechanisms have been modelled by Kumhof, Rancière and Winant (2015).

[5] The link from inequality to credit growth is contested by some authors. Bordo and Meissner (2012), for example, do not find any link between inequality and excessive credit in a sample of 14 advanced countries over 1920 to 2008. Gu and Huang (2014) put this result in perspective: on a similar sample but with a slightly different methodology, they do find evidence of a positive link for “financialized” (primarily Anglo-Saxon) economies.

[6]  See, e.g., Borio and Lowe (2002) and subsequent work of the BIS on this issue.

[7] See Ceruti et al. (2017) for empirical evidence on the effectiveness of caps on LTV ratios to control credit growth.

[8] Policy makers sometimes modulate caps on LTV ratios to take this concern into account. In Ireland, for example, the central bank has imposed a 90% cap for first-time-buyers of properties up to EUR 220’000 and of 80% otherwise.

[9] Concentration limits prevent banks to focus their loan portfolio on a limited number of borrowers and thus insure that their credit risk is spread over a sufficient number of borrowers.

[10] The authors highlight however that these results are based on correlation estimates, and thus cannot be interpreted as a proof that macroprudential measures is causing inequality.

[11] See Lebarz (2015) for evidence on the link between debt leverage and income distribution in 21 OECD countries.