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Macroprudential Policy and Real Estate Funds

by internationalbanker

By Manuel A. Muñoz, Senior Lead Expert, Directorate Risk Management, European Central Bank, and Frank Smets, Adviser to the Counsel to the Executive Board, European Central Bank and Professor of Economics, Ghent University



Since 2012, institutional investment in euro area real-estate assets has more than quadrupled, according to official data. This pattern is remarkable since available data seems to underestimate the size of the real estate fund industry’s investment in the euro area for a variety of reasons. In this article, we report on the development of a quantitative euro area DSGE (dynamic stochastic general equilibrium) model that captures this industry’s main features to study its macroprudential policy. Our analysis reveals leakages in the existing macroprudential framework and calls for introducing a macroprudential leverage limit—similar to Ireland’s—to stabilise and strengthen the welfare-improving capacity of macroprudential policy.


The financial reforms adopted in the aftermath of the Global Financial Crisis (GFC) resulted in a tightening of bank lending standards that has revitalised rental-housing markets, leading to higher rents and depressed homeownership rates (Gete and Reher, 2018)1. In this new regulatory environment, institutional investors have found incentives to steadily increase their presence in the real-estate sector. Recent empirical studies have shown that: (i) real estate funds and other housing investment firms (henceforth REIFs) leverage large-scale buy-to-rent real-estate investments, a pattern that seems to have conferred on them some capacity to set rents in the areas where they have concentrated (Mills et al., 2019, and Daly, 2022)2; (ii) more stringent prudential requirements on banks have incentivised REIFs to rely more on non-bank funding (Hoesli et al., 2017)3; and (iii) such patterns in the REIF industry are behind the recovery in housing investment and property prices that followed the GFC (Lambie-Hanson et al., 2019)4.

This article summarises the main empirical observations on institutional investments in the euro area’s real-estate assets and draws some conclusions on macroprudential policy based on a quantitative euro area DSGE model that captures the main features of the REIF industry. The findings underscore the importance of closing data gaps in institutional real-estate investments, as the presence of REIFs in real-estate and financial markets can have significant implications for the design and calibration of macroprudential policy.

Institutional investments in euro area real-estate assets

The euro area is one of several economies in which the increasing presence of institutional investors in housing markets has been increasingly evident. Since 2012, institutional investment in euro area real-estate assets has more than quadrupled in absolute terms and as a share of total housing investment (Figure 1). This pattern is remarkable since available data underestimates the size of the REIF industry’s investments in the euro area by relying only on the information reported by funds domiciled in the European Union (EU). (Even if the bulk of institutional investments in euro area real-estate assets comes from abroad, only REIFs domiciled in the EU are obliged [by EU legislation] to report information to corresponding national competent authorities.)

Note: This figure reports real estate funds’ flows (12 months) in the euro area both in absolute terms and as a percentage of aggregate housing investment in the euro area. The time series is set at a quarterly frequency and has been plotted for the period 2012:III-2020:I. The figures are based on Battistini et al., 20185. Sources: European Central Bank (ECB), Eurostat and own calculations.

Given that the bulk of institutional investments in the euro area’s real-estate assets come from abroad and REIFs’ lack of incentives to disclose information on their financial accounts and transactions, this translates into significant data gaps that have implications for policymaking.

Beyond the above-mentioned legislative considerations, there are other reasons to suspect that the actual leverage of REIFs domiciled in the European Union could be high. First, real estate funds operating in the EU fall within the category of funds subject to the AIFMD (Alternative Investment Fund Managers Directive), for which no leverage limits apply. Second, investment funds often lever up synthetically through the use of derivatives, which makes measuring their leverage particularly challenging. Third, the Central Bank of Ireland recently conducted a deep dive survey on the Irish REIF industry, concluding that leverage levels of REIFs domiciled in Ireland are high (Daly et al., 2021)6. The Irish property fund industry is a case study that, arguably, can help to better understand the patterns of institutional investments in euro area real-estate assets, since property funds domiciled in Ireland represent a significant share of total institutional investment in the Irish real-estate sector and a non-negligible fraction of total REIFs domiciled in the EU (ECB, 2020)7.

Some years ago, market analysts and real-estate experts started to recurrently report that many of these institutional investments were being leveraged via direct lending (in other words, lending that is not subject to regulatory LTV [loan-to-value] limits), often provided by debt funds—a situation that eventually raised fears of a credit bubble building up in the debt-fund industry8. Furthermore, recent empirical studies have found that debt funds are among the most leveraged investment funds in Europe, with fund managers in leveraged funds reacting in a relatively more procyclical manner—than those in non-leveraged funds—and leverage reportedly amplifying financial fragility in the investment-fund sector (van der Veer et al., 2017, and Molestina Vivar et al., 2020)9.

Either because REIFs are—in most jurisdictions—not subject to sectoral macroprudential (leverage) regulation or because their increasing activity is, to a large extent, being funded with non-bank lending (which is not subject to regulatory LTV limits), these empirical studies suggest that there is ample room for strengthening the macroprudential-regulatory framework on this front. The exception is Ireland again. On November 24, 2022, the Central Bank of Ireland became the first member of the EU—and probably of all advanced economies—to introduce a macroprudential leverage limit on REIFs. (Although other EU members already have leverage limits for REIFs in place as part of their national legislations, in our view, the Central Bank of Ireland’s is the first leverage limit on REIFs that is purely macroprudential as it is the first one that can be temporarily tightened or relaxed depending on macro-financial conditions.) (Central Bank of Ireland, 2021)10. This is the first time that Article 25 of the AIFMD (Alternative Investment Fund Managers Directive) has been triggered11.

To the best of our knowledge, the first contribution to the literature on macroprudential regulation proposing this measure is our work (Muñoz and Smets, 2022)12 and a previous version of it (Muñoz, 2020)13. Similar to the tool we propose and study in our research, the Central Bank of Ireland has introduced a 60-percent limit on REIFs’ leverage (total-debt-to-total-assets) ratio, which can be temporarily relaxed or tightened depending on macro-financial conditions.

A quantitative DSGE model with rental markets and real estate funds

To analyse macroprudential policy in this environment, in Muñoz and Smets (2022)14, we develop a quantitative two-sector DSGE model with REIFs and rental-housing markets calibrated to the euro area economy. The supply side of the model differentiates between housing-producing firms and non-housing-producing firms. The demand side accounts for two types of representative households that crucially differ in their roles in the housing and credit markets. Patient households save and purchase housing (as savers) to live in and supply homogeneous rental services under perfectly competitive conditions (as landlords). Impatient households become indebted against eligible (housing) collateral (as borrowers) to acquire property for their own uses and demand rental-housing services (as renters). There is a certain degree of imperfect substitutability between property and rental-housing services.

In addition, REIFs demand loans to buy real-estate assets and transform them into slightly differentiated rental-housing services supplied under monopolistic competition. (The motivation for that is twofold. Housing markets are, in practice, segmented according to some of their main features [location, type of construction, style, etc.], and the existence of a positive demand for different types of houses suggests that there is a preference for variety at the aggregate level. From the supply side, purchasing a large amount of housing with a common characteristic [e.g., the neighbourhood] grants the REIF market power in that particular market segment.) That is, the real-estate sector of this economy consists of an owner-occupied housing market and a rental-housing market. In reality, patient households and institutional investors simultaneously supply services in the rental-housing market to impatient households (borrowers) and non-housing-producing firms. For both borrowers and non-housing producers, there is a certain degree of substitutability between saver and REIFs’ rental services (and across REIFs’ rental varieties). Figure 2 illustrates the interactions across the different types of agents that populate this economy in the real-estate and credit markets employing a flow-of-funds diagram.

Note: Black arrows indicate the direction of supply in property markets. Blue arrows refer to the direction of supply in rental-housing markets. Red arrows refer to the direction of supply in mortgage markets.

Leakages of existing macroprudential regulation

In the first step, we analyse the workings of existing countercyclical LTV limits on residential mortgages (in other words, those that affect impatient households in the model). If we shut down rental-housing markets and the REIF industry, our set-up becomes a standard two-sector DSGE model with housing collateral constraints, in which this macroprudential rule unambiguously stabilises the financial and business cycle through a smoothing effect on lending supply, as already shown in the literature. (As is fairly standard in the literature, we assume in our analysis that macroprudential rules respond to changes in the output gap [e.g., Lambertini et al., 2013, and Muñoz, 2021].15)

In contrast, in our calibrated model (with rental markets and REIFs)—depending on its degree of countercyclical responsiveness—this rule can destabilise lending, housing prices and real gross domestic product (GDP) through two main mechanisms: the imperfect substitutability between owner-occupied and rental-housing services and the capacity savers have to revitalise rental markets directly by increasing the rental-housing supply themselves and indirectly by reallocating lending towards the REIF industry.

To illustrate this, Figure 3 displays the impulse responses of selected aggregates to a positive non-housing technology shock that triggers a countercyclical tightening in the LTV limit on residential mortgages. Savers are forced to restrict their lending supply to borrowers. They reallocate their resources to increase rental supply directly and indirectly (by expanding the lending supply to REIFs). That exerts downward pressure on rents, incentivising borrowers to partially replace owner-occupied housing with rental services. Such reactions exert additional downward pressure on lending to borrowers, which can eventually fall and become more volatile. As rental services become cheaper, non-housing producers further expand their outputs, responding to the shock by renting more real estate. In response, housing producers further increase housing investment, ultimately causing property prices and total output to increase more than in the absence of the macroprudential rule.

Note: Variables are expressed as percentage deviations from the steady state. The solid line refers to the baseline (i.e., no macroprudential policy) scenario. The starred, dotted and diamond lines refer to scenarios in which the LTV rule on residential mortgages is active, and they differ from one another in the degree of countercyclical responsiveness of such a rule.

Macroprudential leverage limits for real estate funds

Against this background, we then study the transmission of countercyclical LTV limits on lending to REIFs or macroprudential leverage limits on REIFs. (Given the assumptions of the set-up, including the absence of an explicit distinction between bank lending and non-bank lending and the modelling of debt as one-period loans, a countercyclical LTV limit on lending to REIFs and a macroprudential limit on REIF’s leverage [i.e., debt-to-assets] ratio are roughly equivalent.) Figure 4 plots the impulse responses of selected aggregates to the same shock under the baseline (i.e., no macroprudential) scenario and three alternative scenarios in which the macroprudential leverage limit for REIFs is active (with a varying degree of countercyclical responsiveness) and the countercyclical LTV on residential mortgages is not. In response to the tightening in the REIFs’ leverage limit induced by the expansionary shock, borrowers partially replace REIF rental services with saver rental services, since the latter have become relatively cheaper. Importantly, the model captures the empirically relevant fact that the degree of substitutability across types of rental services is higher than that between owner-occupied housing and rental housing. This implies that with this macroprudential rule, the substitution effect mainly takes place in the rental-housing market, while the property-housing stock (i.e., collateral) of borrowers—and, thus, their lenders—remains roughly unchanged. The substitutability between saver and REIF rental services is, nevertheless, imperfect, so total demand for rental services responds less prominently to the shock under this macroprudential rule than under the baseline scenario. Consequently, housing production (as well as total output) and property prices also evolve more smoothly.

Note: Variables are expressed as percentage deviations from the steady state. The solid line refers to the baseline (i.e., no macroprudential policy) scenario. The starred, dotted and diamond lines refer to scenarios in which the macroprudential leverage limit is active, and they differ from one another in the degree of countercyclical responsiveness of such a rule.

Lastly, we perform a welfare analysis of both policy rules. Interestingly, each of the two rules triggers not only volatility but also level effects through the above-described transmission mechanisms. This results in savers and borrowers facing non-trivial welfare trade-offs for each macroprudential rule. Even if the macroprudential leverage limit on REIFs is more desirable from a stabilisation perspective, the quantitative importance of the welfare-improving level effects induced by the LTV rule on residential mortgages and, ultimately, the fact that each rule operates through different mechanisms implies that jointly, the two policy rules yield larger welfare gains for savers and borrowers than they do in isolation.

Conclusion and policy recommendations

Our analysis reveals leakages in existing macroprudential regulations. The countercyclical response of existing LTV limits on residential mortgages triggers the reallocation of credit towards the unregulated sector (in other words, the REIF industry), which limits its stabilisation capacity. By way of contrast, a macroprudential leverage limit on REIFs effectively contributes to smoothing the financial and business cycle, even if the housing and debt holdings of REIFs are comparatively low. Nevertheless, due to the different mechanisms through which they operate and the quantitative importance of the non-trivial level effects they generate, both types of policy rules are welfare-improving and jointly induce more sizeable welfare gains than they do in isolation.

These findings may shed light on some potential avenues for strengthening the macroprudential-policy framework for non-banks. At least two policy instruments that are not yet in place could be considered in practice to improve the effectiveness and stabilisation capacity of the macroprudential toolkit through the mechanisms outlined: countercyclical LTV limits on non-bank lending and macroprudential leverage limits on REIFs. (They are still not in place, except in Ireland, a jurisdiction in which a macroprudential leverage limit on REIFs has been recently introduced [Central Bank of Ireland, 2022].16) Moreover, the quantitative analysis shows that such quantity regulation would allow for reference (competitive) prices in rental-housing markets to increase less abruptly during the boom, an issue that policymakers in several countries of the euro area have attempted to handle via price regulations—an alternative that could generate price distortions.


1 Oxford Academics/The Review of Financial Studies: “Mortgage Supply and Housing Rents,” Pedro Gete and Michael Reher, February 14, 2018, Volume 31, Issue 12, Pages 4884-4911.

2 Wiley Online Library/Real Estate Economics: “Large-Scale Buy-to-Rent Investors in the Single-Family Housing Market: The Emergence of a New Asset Class,” James Mills, Raven Molloy and Rebecca Zarutskie, Original article: December 19, 2016, Summer 2019, Volume 47, Issue 2, Pages 399–430.

See also:

The Statistical and Social Inquiry Society of Ireland (SSISI): “Institutional Investment in Housing: Financialisation 2.0 in the Case of Ireland,” Pierce Daly, August 24, 2022.

3 Springe Link/The Journal of Real Estate Finance and Economics: “Is Financial Regulation Good or Bad for Real Estate Companies?–An Event Study,” Martin Hoesli, Stanimira Milcheva and Alex Moss, October 12, 2017, 5 (1/2), Pages 1–39.

4 Federal Reserve Bank of Philadelphia: “Institutional Investors and the U.S. Housing Recovery,” Lauren Lambie-Hanson, Wenli Li and Michael Slonkosky, November 2019, Working Papers 19-45.

5 European Central Bank (ECB)/Eurosystem: “The state of the housing market in the euro area,” Niccolò Battistini, Julien Le Roux, Moreno Roma and John Vourdas, 2018, Economic Bulletin Articles, Issue 7.

6 Central Bank of Ireland: “Property funds and the Irish commercial real estate market,” Pierce Daly, Kitty Moloney and Samantha Myers, February 2021, Financial Stability Notes 1/FS/21, Volume 2021, Number 1.

7 European Central Bank (ECB)/Eurosystem: “Financial stability review, May 2020.”

8 See, among others:

Financial Times: “Real estate: post-crisis boom draws to a close,” J. Evans, June 18, 2019.


Financial Times: “Rise of private debt creates fears of a bubble,” R. Wigglesworth, April 13, 2017.

9 European Central Bank (ECB)/Eurosystem: “Developing macroprudential policy for alternative investment funds,” Koen van der Veer, Anouk Levels, Claudia Lambert, Luis Molestina Vivar, Christian Weistroffer, Raymond Chaudron and René de Sousa van Stralen, November 2017, Occasional Paper Series Number 202.

See also:

European Central Bank (ECB)/Eurosystem: “Burned by leverage? Flows and fragility in bond mutual funds,” Luis Molestina Vivar, Michael Wedow and Christian Weistroffe, May 2020, Working Paper Series Number 2413.

10 Central Bank of Ireland: “Macroprudential measures for the property fund sector,” November 2021, Consultation Paper 145.

11 European Systemic Risk Board (ESRB)/NBFI Monitor: “EU Non-bank Financial Intermediation Risk Monitor 2022,” Number 7, July 2022. See Box 3.

12 European Systemic Risk Board (ESRB): “Macroprudential policy and the role of institutional investors in housing markets,” Manuel A. Muñoz and Frank Smets, August 2022, Working Paper Series 137.

13 VoxEU/CEPR Org: “Institutional real estate investors, leverage, and macroprudential regulation,” Manuel A. Muñoz, November 14, 2020.

14 European Systemic Risk Board (ESRB): “Macroprudential policy and the role of institutional investors in housing markets,” Manuel A. Muñoz and Frank Smets, August 2022, Working Paper Series Number 137.

15 Science Direct/Journal of Economic Dynamics and Control: “Leaning against boom–bust cycles in credit and housing prices,” Luisa Lambertini, Caterina Mendicino and Maria Teresa Punzi, August 2013, Volume 37, Issue 8, Pages 1500–1522.

See also:

International Journal of Central Banking (IJCB): “Rethinking Capital Regulation: The Case for a Dividend Prudential Target,” Manuel A. Muñoz, September 2021, Volume 17, Issue 3, Pages 271–336.

16 Central Bank of Ireland: “The Central Bank’s macroprudential framework for Irish property funds,” report, 2022.


Author’s note: The views expressed in this article are those of the authors and do not necessarily reflect the views of the ECB or the Eurosystem.


Manuel A. Muñoz serves as the Senior Lead Expert at the European Central Bank. Prior to that, he held the position of Senior Adviser for Financial Affairs at the Minister’s Office of the Spanish Ministry of Economy and Business. He has been the Head of Service at the Spanish Treasury, first in the Financial Policy and Regulation Department and then in the Strategic Analysis and International Financial System Department. He is a member of the Senior Corps of Spanish State Economists and Trade Experts and the la Caixa Fellows’ Association.

Frank Smets is a Professor of Economics at Ghent University. He is currently on leave from the European Central Bank, where he headed the Economics Department from 2017 until 2022. Previously, he was the Adviser to the President of the European Central Bank and Head of Research. He is a research fellow of the CEPR. He has published extensively on monetary and macroeconomic topics in top academic journals. Before joining the ECB in 1998, he was a research economist at the Bank for International Settlements.


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