{"id":14741,"date":"2026-11-03T09:04:00","date_gmt":"2026-11-03T08:04:00","guid":{"rendered":"http:\/\/webecpol.esade.edu\/?p=14741"},"modified":"2026-11-03T14:08:43","modified_gmt":"2026-11-03T13:08:43","slug":"how-to-protect-todays-and-tomorrows-vulnerable-tenants-a-proposal-for-public-rent-insurance-in-spain","status":"publish","type":"post","link":"http:\/\/webecpol.esade.edu\/en\/blog\/how-to-protect-todays-and-tomorrows-vulnerable-tenants-a-proposal-for-public-rent-insurance-in-spain\/","title":{"rendered":"How to protect today’s and tomorrow’s vulnerable tenants: a proposal for public rent insurance in Spain"},"content":{"rendered":"
This post is part of a series of concrete, evidence-based policy proposals put forward by economists from a range of backgrounds, with the aim of being useful to and informing the electoral and post-electoral debate in Spain. They reflect the position of the author, not that of the centre.<\/em>This article has been written in a personal capacity. The opinions it contains are exclusively those of the author and do not necessarily represent those of any institution with which he is affiliated.<\/em><\/span><\/div>\n

 <\/p>\n

\n

Key ideas<\/h3>\n

\u2192 The problem. <\/strong>Protection for those who already rent has been strengthened since 2019, but the harder it is to recover a dwelling when the rent goes unpaid, the more carefully landlords choose whom they rent to. Between 4.7% and 5.9% of dwellings that enter the rental market suffer a severe default in their first seven years, and after a default the probability that they remain in long-term rental falls by 10 points. The result is a barrier to entry that shuts more and more low-income tenants out of the rental market.<\/p>\n

\u2192 The proposal. <\/strong>A free public guarantee, inspired by the French Visale programme, which tenants apply for before looking for a flat and present to the landlord instead of a payslip from a permanent contract or a guarantee from their parents. If the tenant stops paying, the managing agency pays the landlord the unpaid rent, up to 36 months, and the legal costs within a few weeks, and then claims the debt from the tenant. It would be open to young people aged 18 to 30 and to people over 30 with incomes of up to 1.1 times the minimum wage, with realistic limits on the rent covered by zone, based on recently signed contracts, and on beneficiaries’ personal incomes.<\/p>\n

\u2192 Its effects. <\/strong>In its first five years, at Visale’s pace of roll-out, some 440,000 guarantees would be granted and some 68,000 people would move into a rental they would not have accessed without the programme, with a range of between 25,000 and 142,000. Eight in ten would be non-students aged 26 to 30, whose emancipation rate would rise by around 1.5 points, some 37,500 more young people living outside their parents’ home. The effect on supply is more uncertain and would probably be small, with about 990 dwellings still in rental by the fifth year.<\/p>\n

\u2192 The cost. <\/strong>The net cost would be around \u20ac50 million over five years, with a range of between 45 and 60, rising from \u20ac2.8 million in the first year to 17.5 in the fifth, barely 0.5% of public spending on housing in 2024. Each additional move would cost about \u20ac400 among non-students aged 26 to 30 and about \u20ac800 across the programme as a whole. The difference comes from the guarantees for students and people over 30, which add up to some \u20ac23 million without generating moves in the central scenario.<\/div>\n

Tenant protection policy<\/h3>\n

Those who already rent in Spain are better protected today than a decade ago. Since 2019, contracts are compulsorily extended for up to five years, seven if the landlord is a company, and in stressed housing-market areas the tenant can request up to three more years. Evictions of vulnerable households with no alternative housing were suspended almost without interruption from 2020 until February 2026. And the October decrees, pending validation, would renew contracts for five-year periods unless the landlord gives six months’ notice and pays compensation.1<\/a><\/sup><\/p>\n

Although these measures seek to protect tenants from the high costs of moving home, they have an unintended effect on the tenants of the future. The harder it is to recover a dwelling when the rent goes unpaid, the more carefully landlords choose whom they rent to. Most landlords are individuals with one or two flats, accounting for almost 70% of all dwellings rented out by households, and they cannot spread the risk of default across many tenants. The growing demands for deposits, guarantees and guarantors are a response to this process, and lead to a growing exclusion of low-income tenants from the rental market: in Catalonia, for example, the share of households renting at market price that are in the lowest income quintile fell from 41% to 29% between 2020 and 2025.<\/p>\n

Policies of this kind, which benefit those already inside the rental market (insiders<\/em>) over those trying to enter it, now or in the future (outsiders<\/em>), are the most affordable option for legislators. They are practically free, can be applied immediately and are popular, above all among current tenants. However, they show a lack of vision about how to tackle a real problem (the risk of default and its consequences) in the rental market.<\/p>\n

The risk of rent default in Spain<\/h3>\n

Default processes are linked to evictions and represent a real risk, albeit a limited one that is poorly quantified by official statistics. Tax data from the Household Panel make it possible to estimate the share of dwellings that have claimed deductible expenses for doubtful debts2<\/a><\/sup>. The share of rented dwellings declaring these debts each year stands at between 0.7% and 1.2%, a small share but one that accumulates, so that seven years after the contract is signed between 4.7% and 5.9% of dwellings have suffered a severe default (Figure 1)3<\/a><\/sup>.<\/p>\n

\"Figure<\/p>\n

\"Figure<\/p>\n

The risk of default, then, although far from affecting the majority, is significant enough to affect the rental market as a whole, both directly and indirectly. Directly, these effects take the form of eviction proceedings and, indirectly, of supply being held back from long-term rental and of rented dwellings being withdrawn from the market. A first analysis (with a simple difference-in-differences model) using microdata from the Household Panel (2016-2023) shows how, after a default, the probability that a dwelling remains in long-term rental falls sharply in the following years compared with similar dwellings without a default. Specifically, the probability of remaining in ordinary rental falls by 10 points (Figure 2), while the probability of a sale and that of the dwelling becoming a second home rise by an equivalent amount.<\/p>\n

For all these reasons, it seems clear that current tenant protection fails to solve at least two problems: neither the negative effect that defaults have on rental supply nor the barrier to entry that potential tenants face when trying to access the market. To try to address both together, without creating winners and losers among tenants, a public insurance scheme looks like an effective tool, since it protects current tenants against loss of income without harming potential ones, and it is a realistic way of limiting the negative effect of these episodes on rental supply. As with almost all public policies, the key lies in its design, so below I propose a model based on the French Visale programme, adapted to Spain, and make a realistic ex ante estimate of its effects.<\/p>\n

A proposal for public rent insurance in Spain<\/h3>\n

In this model, the tenant applies for a free public guarantee and presents it to the landlord instead of a payslip, a permanent contract or a guarantee from their parents. If there is a default, the programme immediately pays the landlord the unpaid months and the legal costs, and then tries to recover the debt from the tenant. The risk that today decides who gets to rent thus shifts from the landlord to the public sector, without reducing the protection of tenants who already have a contract.<\/p>\n

For it to work, especially for tenants who want to enter the market, it is essential that the guarantee is in the tenant’s hands before the contract is signed, because that is when the landlord makes the decision. Following the Visale model, tenants would apply for the guarantee before looking for a flat and would receive a visa stating the maximum rent it could cover, based on their income and the caps that are set. They then show it to the landlord, who accepts it instead of a guarantor, and the guarantee becomes linked to that contract. If the tenant stops paying, the landlord notifies the managing agency, which pays the unpaid rent, up to 36 months, and the legal costs within a few weeks. From then on it is the managing agency, and not the landlord, that claims the debt from the tenant.<\/p>\n

\"Figure<\/p>\n

For this exercise I have treated as eligible all young people aged 18 to 30, whether studying or working, on permanent or temporary contracts, and people over 30 with incomes of up to 1.1 times the minimum wage, about \u20ac16,600 gross a year. The guarantee would operate with two limits, so that it covers neither excessively expensive flats nor contracts the tenant cannot afford. The first is a maximum rent that depends on where the dwelling is, set at the 66th percentile of contracts signed in the previous two years in four zones: Madrid, Barcelona, other municipalities with more than 100,000 inhabitants and all remaining municipalities. These caps would be about \u20ac620 a month in municipalities with fewer than 100,000 inhabitants, 710 in larger ones, 1,090 in Madrid and 1,140 in Barcelona. For students the cap is lower, following Visale’s example, set by the 50th percentile. The second limit is that the share of the rent paid by the tenant must not exceed half of their net income, a limit that, as in France, does not apply to students, who often have no income of their own.<\/p>\n

To measure its impact ex ante, the question is not how many guarantees would be signed, but how many of the people currently left out of the rental market would gain access thanks to the policy. To answer it, I transfer to Spain the effect estimated for Visale by B\u00e9zy, Levy and McQuade (2025), who use difference-in-differences to compare single people aged 26 to 30, who could use Visale, with the uncovered population aged 31 to 35. Their results imply that around one in three guarantees in the first group went to someone who would not have rented without it. I apply this effect to non-students aged 26 to 30 and slightly less than one in five to those aged 18 to 25. Out of caution, I attribute no impact to students or people over 30, because the study does not analyse them, but I do count their guarantees as part of the cost of the policy.<\/p>\n

To simulate the effects and cost of the policy, I apply this design to the 2023 population of the Household Panel, which shows who moves into a rental each year, with whom, under what tenure and with what income. The reasonable assumption is that implementation would be gradual, so that the guarantee would gain coverage until it covered 23.8% of those moves in the fifth year, at the pace observed for Visale. Finally, I assume that the default rate would be similar to that recorded by Visale, 6.5% over three years, with an average debt of just over five months’ rent, the figure reflected in the defaults declared in personal income tax (IRPF) returns4<\/a><\/sup>.<\/p>\n

\"Table<\/p>\n

Rolling out the guarantee<\/h3>\n

In 2023, some 12.9 million people would meet the requirements to apply for the guarantee if they decided to move into a rental, although the figure that matters is the number who move each year while meeting them, some 519,000 (Figure 3). Applying Visale’s coverage path to those moves, which in the first year would reach barely 4.8% of them, the programme would sign some 29,000 guarantees in its first year and some 146,000 in the fifth, so that over its first five years some 440,000 would have been granted, with a range of between 395,000 and 514,000 (Figure 4). Much of that margin comes from the moves that the policy itself would bring about and that would not have happened without it, which also sign their guarantee and whose number grows as implementation progresses.<\/p>\n

\"Figure<\/p>\n

Although Visale was designed mainly for young people, with the eligibility criteria described and uniform coverage, four in ten guarantees in the fifth year, some 58,000, would be signed by people over 30, because of the size of this group, which even with the income limit adds up to some 8.3 million eligible people and some 243,000 eligible moves a year. Non-students aged 26 to 30 would sign another 55,000, those aged 18 to 25 some 23,000 and students barely 10,000, although this last figure is probably an underestimate, since many students remain registered at the family home and the Panel does not capture their moves well. Each guarantee would cover on average about \u20ac230 a month, a relatively low figure because it only covers the share of the rent paid by each tenant, and a large proportion of those who move share a flat, with their partner or with other people.<\/p>\n

This distribution anticipates much of the subsequent results, since young people who are not studying, in whom the effect estimated in France is concentrated, would sign just over half of the guarantees, while the remaining 46%, that of students and people over 30, would generate cost without, in the central scenario, being attributed any additional move. A high number of guarantees is therefore not the right indicator of the policy’s success: to assess it, one has to look at how many of them correspond to people who would have been left out without the guarantee.<\/p>\n

Effects on moves and leaving the parental home<\/h3>\n

Like any public rent-default insurance, the one I propose reduces the landlord’s risk in all the contracts it covers, but it only changes the landlord’s decision in some of them, those of tenants who could not have accessed rental housing without that backing. Figure 5 splits the guarantees of the fifth year between those that would be signed by people who would have moved anyway, the vast majority, and those that correspond to moves that would not have happened without the programme, some 22,800, 16% of the total. This share reflects the assumptions about the effect described above, which concentrate it among non-students aged 26 to 30 and, to a lesser extent, among those aged 18 to 25. It is a very conservative estimate, since it is quite possible that some of the people over 30 covered could not have accessed rental housing without the guarantee, but we do not have an estimate for that group.<\/p>\n

\"Figure<\/p>\n

In the first five years, some 68,000 people would move into a rental they would not have obtained without the guarantee (Figure 6). Eight in ten, some 55,000, would be non-students aged 26 to 30, and the remaining 13,000 young people aged 18 to 25. The gap between the two groups is not only due to the effect being larger for the former, but also to the fact that many more of them move each year while meeting the requirements, about 155,000 versus about 80,000. As coverage grows gradually, so does the effect, which would rise from about 4,600 additional moves in the first year to about 22,800 in the fifth. In that fifth year, non-students aged 26 to 30 moving into a rental would be around 12% more than without the policy, and those aged 18 to 25 just over 5% more.<\/p>\n

\"Figure<\/p>\n

The bands in the figure reflect considerable uncertainty, mainly because the effect estimated in France is imprecise, so the range for cumulative moves over the five years runs from about 25,000 to about 142,000. Across that whole range, however, the effect remains concentrated among young people aged 26 to 30 who are not studying, an age at which many still live with their parents, which raises the question of how many of these moves would also mean leaving the parental home.<\/p>\n

The effect on leaving the parental home requires a further step, since moving into a rental thanks to the programme does not necessarily mean leaving one’s parents’ home. The move may be from another rented flat or from a shared dwelling. However, B\u00e9zy, Levy and McQuade find that almost all of Visale’s effect is explained by the formation of new households, so I assume that 85% of additional moves correspond to young people leaving the parental home. Under this assumption, the emancipation rate (the share living outside the parental home) of young people aged 26 to 30, which stood at 56.0% in 2023 according to the Panel5<\/a><\/sup>, would rise by around 1.5 points over five years, with a range of between 0.5 and 3.2 points (Figure 7). This increase accumulates year after year, because those who leave home thanks to the guarantee stay out, and it is also boosted by young people aged 18 to 25 who leave home and start counting in the rate when they turn 26, although their contribution is small, since the effect of those aged 26 to 30 alone would produce an increase of 1.35 points.<\/p>\n

\"Figure<\/p>\n

After five years, the increase of 1.5 points would be equivalent to some 37,500 more young people aged 26 to 30 living outside their parents’ home, and would put the emancipation rate for that group close to 57.5%. It may seem a modest effect, but it comes from a policy that neither builds housing nor intervenes in prices, that simply shifts the risk of default from the landlord to the public sector and that has a low cost.<\/p>\n

Effects on defaults and rental supply<\/h3>\n

The guarantee does not in itself reduce the number of defaults, but it changes who bears their consequences and can therefore limit their negative effects. With Visale’s default rate, the programme would cover the defaults of some 540 households in its first year and some 4,000 in the fifth, some 11,300 over the five years (Figure 8). The number of defaults covered grows somewhat faster than the number of guarantees, because each year the defaults from newly signed guarantees are added to those from guarantees granted in the two previous years, which are still in force and can still record defaults. Each of these households would owe on average about \u20ac2,550, a figure very similar to Visale’s6<\/a><\/sup>, which the managing agency would pay the landlord within a few weeks, compared with the months it can take today to recover it through the courts.<\/p>\n

This difference also matters for keeping supply in the market. As Figure 2 showed, a dwelling that suffers a default is about 10 points less likely to remain in long-term rental in the following years, so if the guarantee managed to avoid that effect, by the fifth year some 990 dwellings that would otherwise have left the market would still be rented, with a range of between 830 and 1,160 (Figure 8). If it only prevented the dwelling from being left empty or becoming a second home, but not its sale, the figure would be some 550.<\/p>\n

\"Figure<\/p>\n

This is, nonetheless, the weakest figure in the simulation, and it is better read as an order of magnitude. First, it assumes that the guarantee payment neutralises the whole effect of the default, when part of it is probably due to the court process itself or to the landlord’s bad experience, which payment does not erase. Second, it depends heavily on the default rate assumed: with the Panel’s rate it would be some 285 dwellings and with the ECV’s, more than 3,200. In any case, it is a small effect relative to the rental stock, so the main argument for the policy lies in access and protection against loss of income rather than in supply.<\/p>\n

The budgetary cost of the policy<\/h3>\n

The net cost of the policy, after deducting what the managing agency manages to recover from tenants, would be around \u20ac50 million accumulated over its first five years, with a range of between \u20ac45 and \u20ac60 million, and would grow each year with coverage from about \u20ac2.8 million in the first year to about 17.5 in the fifth (Figure 9). Just over half corresponds to the defaults and legal costs paid to landlords, some \u20ac34 million, of which some 6 would be recovered, while the rest, some \u20ac22 million, are administration costs, which I have set at \u20ac50 per guarantee and which therefore depend on the number of guarantees and not on the number of defaults.<\/p>\n

\"Figure<\/p>\n

Divided across all guarantees granted, the cost is equivalent to about \u20ac126 per guarantee over its whole life, practically the same as Visale’s average cost of \u20ac128. However, since most guarantees go to people who would have moved anyway, the most useful metric for assessing the policy is the cost per move it makes possible7<\/a><\/sup>. In the group for which the effect is identified, non-students aged 26 to 30, each additional move would cost about \u20ac400, a figure of the same order as the \u20ac500 to \u20ac750 that B\u00e9zy, Levy and McQuade obtain for France with a comparable calculation8<\/a><\/sup>, while for the programme as a whole it would rise to about \u20ac800. The difference is explained by the fact that the guarantees for students and people over 30, almost half of the total, account for some \u20ac23 million of cost without generating moves in the central scenario, which strengthens the case for focusing the policy on young people who are not studying.<\/p>\n

The main source of uncertainty is again the default rate of guaranteed tenants, something Spain does not measure well. With the rate derived from the Panel, which acts as a lower bound, the cost would fall to about \u20ac30 million over five years, while with that of the ECV, which captures any delay in payment, it would rise to about 115. Naturally, the cost would grow if coverage continued to rise in later years. With the coverage Visale reached in 2023, 33%, the cost would be about \u20ac71 million, although it would also generate more additional moves, some 96,000. The \u20ac17.5 million of the fifth year in the central scenario would be equivalent to barely 0.5% of the nearly \u20ac3,400 million that Spanish public administrations spent on housing policies as a whole in 2024, according to Eurostat.<\/p>\n

Conclusions<\/h3>\n

Few housing policies deliver tangible results for a budgetary cost as limited as a Visale-style rent-default guarantee. With the coverage the French programme reached five years after its launch applied to the Spanish rental market, some 68,000 people would manage to move into a rental they cannot access today and the emancipation rate of young people aged 26 to 30 would rise by around 1.5 points, some 37,500 more young people living outside their parents’ home, at a cost of about \u20ac17.5 million in the fifth year, barely 0.5% of annual public spending on housing.<\/p>\n

In addition, the guarantee provides security against loss of income and default both to the landlord, who is paid within a few weeks, and to the tenant, who answers for their debt to a public body rather than to their landlord, and it does so without shutting out those trying to enter the market. Its effects would grow as its coverage rate increased, so that with the 33% Visale reached in 2023 the emancipation rate in that age bracket would rise by about 2.1 points, and the defaults covered and the dwellings that would not leave the rental market would also increase, at a cost that would remain very low.<\/p>\n

Finally, two additional positive effects that could also arise are worth considering. First, the managing agency could issue good-payer certificates to tenants who have always paid their rent. This would be the first building block of a payment history that would make it easier for them to obtain a mortgage. In the United States, the first randomised trial on this question shows that adding on-time rent payments to credit files significantly increases the share of tenants with a credit score (Theodos, Teles and Lieberman, 2025). Second, there is the role of human capital accumulation. One of the main findings of the evaluation of Visale in France was precisely that the programme helped young people access rentals in more urbanised, higher-income areas, something the evidence has shown to be an important factor in human capital accumulation once people are in the labour market (De la Roca and Puga, 2017). In short, a public guarantee makes it possible to protect today’s tenants without closing the door of the market to the tenants of the future, with positive and realistic effects on the emancipation rate in Spain at a perfectly affordable budgetary cost.<\/p>\n

Notes<\/h3>\n
    \n
  1. Articles 9.1 and 10.3 of Ley 29\/1994 de Arrendamientos Urbanos (Urban Leases Act), as worded by Real Decreto-ley 7\/2019 and Ley 12\/2023. The suspension of evictions of vulnerable households with no alternative housing was extended almost without interruption from 2020 until Congress failed to validate Real Decreto-ley 2\/2026, on 26 February 2026. Reales Decretos-ley 28\/2026 and 29\/2026, of 6 October, provide for renewal for five-year periods and for an extraordinary right to halt eviction by paying the arrears (enervaci\u00f3n), and the Standing Committee of Congress is due to vote on their validation on 12 November. \u21a9<\/a><\/li>\n
  2. This option probably underestimates the default rate, first, because it requires defaults of long duration (more than 6 months), and it is not clear that all landlords use it. \u21a9<\/a><\/li>\n
  3. Default here means a doubtful debt deducted by the landlord in personal income tax (IRPF). Cumulative probability of first default for the 83,837 dwellings that entered the rental market between 2017 and 2022, using the Kaplan-Meier method (5.9%) and taking into account that the dwelling may leave the rental market earlier (4.7%). Author’s calculations using the Household Panel. Note that this represents a lower bound for the level of defaults in Spain compared with other estimates. To get an idea of how high a ‘maximum’ estimate could be, the Living Conditions Survey (ECV) estimates payment delays reported by tenants themselves, and the share of renting households reporting payment delays each year exceeds 10%, which naturally includes much less severe default episodes. \u21a9<\/a><\/li>\n
  4. This is in fact a midpoint between the default rate documented in the Household Panel and the ECV, so it seems a reasonable starting point. \u21a9<\/a><\/li>\n
  5. The emancipation rate here is the share of people aged 26 to 30 who do not live with their parents in the Household Panel. \u21a9<\/a><\/li>\n
  6. Between 6% and 7% of Visale contracts have at least one claim during their term, with an average cost of \u20ac2,500 to \u20ac3,000 per default (B\u00e9zy, Levy and McQuade, 2025). \u21a9<\/a><\/li>\n
  7. Lifetime cost of the guarantees divided by additional moves, as in the paper. The net cost includes defaults paid, one month of legal costs per default and \u20ac50 of administration per guarantee, minus 20% recovery. See the methodological annex. \u21a9<\/a><\/li>\n
  8. B\u00e9zy, Levy and McQuade (2025) obtain \u20ac1,000 to \u20ac1,200 per move if they take all contracts of under-30s as the base, and 500 to 750 if they take those of 26 to 30-year-olds, which is the base comparable with the Spanish figure for the identified group. \u21a9<\/a><\/li>\n
  9. Real Decreto 1135\/2025, of 10 December, regulates the guarantee line in article 76.1 of Real Decreto-ley 1\/2025. It can take the form of a free guarantee, subsidised insurance or a grant, covers rent, damage, utilities and insurance premiums, and applies to contracts in force on 30 January 2025 or signed afterwards. It does not apply in the Basque Country or Navarre. \u21a9<\/a><\/li>\n<\/ol>\n

    References<\/h3>\n

    B\u00e9zy, T., Levy, A. and McQuade, T. (2025). Insuring Landlords. Working paper, March 2025 version.<\/p>\n

    Casas-Arce, P. and Saiz, A. (2010). Owning versus renting: Do courts matter? Journal of Law and Economics, 53(1).<\/p>\n

    De la Roca, J. and Puga, D. (2017). Learning by Working in Big Cities. Review of Economic Studies, 84(1), 106-142.<\/p>\n

    Fannie Mae (2023). Fannie Mae First Quarter 2023 Financial Results Conference Call. Fannie Mae Newsroom.<\/p>\n

    Galindo, J. (2026). Valoraci\u00f3n de los Reales Decretos-ley de vivienda, medida por medida. Blog de EsadeEcPol, 1 de octubre de 2026.<\/p>\n

    Ley 29\/1994, de 24 de noviembre, de Arrendamientos Urbanos. Texto consolidado, BOE.<\/p>\n

    Raya, J. M. (2026). \u00bfC\u00f3mo podemos aumentar la vivienda social mientras la construimos? Blog de EsadeEcPol, 16 de octubre de 2026.<\/p>\n

    Real Decreto 1135\/2025, de 10 de diciembre, por el que se determinan las condiciones de la l\u00ednea de ayudas, por cuenta del Estado, para la cobertura en caso de impagos del alquiler de viviendas para j\u00f3venes y colectivos vulnerables. BOE n\u00fam. 299.<\/p>\n

    Real Decreto-ley 28\/2026 y Real Decreto-ley 29\/2026, de 6 de octubre. BOE de 7 de octubre de 2026.<\/p>\n

    Theodos, B., Teles, D. and Lieberman, S. (2025). Evaluating Rent Reporting as a Pathway to Build Credit. Urban Institute, June 2025.<\/p>\n

    \n

    Methodological annex<\/h3>\n

    1. What is simulated and how to read this annex<\/h4>\n

    This annex accompanies the article \u201cHow to protect today’s and tomorrow’s vulnerable tenants\u201d and explains, step by step, where each of the figures presented in it comes from. The simulation reproduces the first five years of a public programme that guarantees landlords payment of the rent if the tenant stops paying, free for both parties and with requirements similar to those of the French Visale programme, and applies it to the 2023 population of the Household Panel in the common-regime territory, that is, excluding the Basque Country and Navarre, which is also the scope of the guarantee regulated by Real Decreto 1135\/20259<\/a><\/sup>.<\/p>\n

    This is not a genuine impact estimate, but a simulation that combines existing estimates with Spanish microdata, which makes it possible to understand the order of magnitude of the costs, coverage and effect of a policy of this kind. The effect of the guarantee on moves into rental housing comes from the evaluation of Visale by B\u00e9zy, Levy and McQuade (2025), while the effect of a default on whether the dwelling stays in rental comes from my own estimates using Household Panel microdata, which are also the source of Figures 1 and 2 in the article. With these pieces, the simulation answers the same questions that structure the article’s results, namely how many guarantees would be signed, how many people would move into a rental thanks to the programme, how much the emancipation rate of young people aged 26 to 30 would rise, how many defaults it would cover, what its fiscal cost would be, and how many dwellings would remain in long-term rental.<\/p>\n

    So that the origin of each result can be followed, the annex follows the same order as the article and, at each step, starts from the data or assumption, shows the calculation with the central-scenario figures and arrives at the figure that appears in the text or the figures, a correspondence summarised in Table 1. The article’s figures are rounded, whereas here they are given in somewhat more detail, and unless otherwise stated they are the median of the 10,000 simulations of the central scenario, with the 90% interval in brackets (section 10). The calculations in each section, by contrast, are done with the central point without uncertainty, so they may differ from the median in the last digits.<\/p>\n

    Table 1. Where each figure in the article comes from<\/strong><\/p>\n

    Central scenario. Median and, in brackets, 90% interval<\/em><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
    Figure in the article<\/th>\nValue in the simulation<\/th>\nArticle<\/th>\nAnnex<\/th>\n<\/tr>\n
    People who would meet the requirements<\/td>\n12.88 million<\/td>\nFigure 3<\/td>\nSection 4<\/td>\n<\/tr>\n
    Eligible moves per year without the programme<\/td>\n519,100<\/td>\nFigure 3<\/td>\nSection 4<\/td>\n<\/tr>\n
    Average share of the rent covered by each guarantee<\/td>\n\u20ac227 a month<\/td>\nText<\/td>\nSection 4<\/td>\n<\/tr>\n
    Guarantees signed in year 1 and in year 5<\/td>\n29,300 and 146,300 (131,700 to 171,200)<\/td>\nFigure 4<\/td>\nSection 5<\/td>\n<\/tr>\n
    Guarantees signed over five years<\/td>\n439,000 (395,100 to 513,600)<\/td>\nFigure 4<\/td>\nSection 5<\/td>\n<\/tr>\n
    Additional moves in year 5<\/td>\n22,800 (8,200 to 47,400), 16% of guarantees<\/td>\nFigures 5 and 6<\/td>\nSection 6<\/td>\n<\/tr>\n
    Additional moves over five years<\/td>\n68,300 (24,600 to 142,200)<\/td>\nFigure 6<\/td>\nSection 6<\/td>\n<\/tr>\n
    Of which, non-students aged 26 to 30<\/td>\n55,200 (19,500 to 119,000)<\/td>\nFigure 6<\/td>\nSection 6<\/td>\n<\/tr>\n
    Increase in the emancipation rate of 26 to 30-year-olds in year 5<\/td>\n1.50 points (0.54 to 3.18), some 37,500 people<\/td>\nFigure 7<\/td>\nSection 7<\/td>\n<\/tr>\n
    Households with a covered default<\/td>\n4,000 in year 5 (3,600 to 4,800) and 11,300 over five years<\/td>\nFigure 8<\/td>\nSection 8<\/td>\n<\/tr>\n
    Average debt per household in default<\/td>\n\u20ac2,550<\/td>\nText<\/td>\nSection 8<\/td>\n<\/tr>\n
    Net cost in year 1 and in year 5<\/td>\n2.8 and 17.5 million (15.6 to 20.7)<\/td>\nFigure 9<\/td>\nSection 8<\/td>\n<\/tr>\n
    Net cost over five years<\/td>\n50.5 million (44.9 to 59.7)<\/td>\nFigure 9<\/td>\nSection 8<\/td>\n<\/tr>\n
    Lifetime cost per guarantee<\/td>\n\u20ac126 (121 to 132)<\/td>\nText<\/td>\nSection 8<\/td>\n<\/tr>\n
    Cost per additional move<\/td>\n\u20ac407 for ages 26 to 30 (261 to 909) and 819 for the programme (463 to 2,038)<\/td>\nText<\/td>\nSection 8<\/td>\n<\/tr>\n
    Dwellings remaining in rental in year 5<\/td>\n990 (830 to 1,160)<\/td>\nFigure 8<\/td>\nSection 9<\/td>\n<\/tr>\n
    Figures under other assumptions<\/td>\nTable 7<\/td>\nText<\/td>\nSection 11<\/td>\n<\/tr>\n<\/table>\n

    Source: author’s calculations, version 2.2 of the Stata simulation | EsadeEcPol.<\/span><\/p>\n

    2. Data<\/h4>\n

    The simulation relies above all on the Household Panel of the Instituto de Estudios Fiscales, the Tax Agency and the INE, which links households’ tax data with the Municipal Register and shows, for a very large sample of the population, who moves each year, to what type of dwelling, with whom and with what income. It provides the population, moves, cohabitation in the destination household and each person’s income, and also, through the personal income tax (IRPF) returns of individual landlords, the rents of new contracts and the doubtful debts used to measure the size of defaults. The other sources cover what the Panel does not record: the Living Conditions Survey is used to impute the share of young people who are students and for one of the bounds on default frequency, and the continuous Municipal Register to delimit large municipalities. Finally, the evaluation of Visale is used as the source for the effect on moves and for the parameters of the French programme itself (Table 2).<\/p>\n

    Table 2. Data sources<\/strong><\/p>\n

    Use of each source in the simulation<\/em><\/p>\n\n\n\n\n\n\n\n\n\n
    Source<\/th>\nUse in the simulation<\/th>\n<\/tr>\n
    Household Panel (IEF, AEAT and INE), 2021 to 2023<\/td>\n2023 population, moves in 2022 and 2023, cohabitation and kinship in the destination household, individual income in 2023<\/td>\n<\/tr>\n
    Panel IRPF data, contracts from 2022 and 2023<\/td>\nMonthly rent of 67,038 new long-term housing contracts from individual landlords. Caps and distributions by zone<\/td>\n<\/tr>\n
    Panel IRPF data, doubtful debts<\/td>\nMonths of unpaid rent per episode and Panel default frequency (robustness)<\/td>\n<\/tr>\n
    Living Conditions Survey (INE)<\/td>\nProbability of studying by age (2024) and frequency of repeated delays in rent payment, 2022 to 2025 (robustness)<\/td>\n<\/tr>\n
    Continuous Municipal Register (INE), 2021<\/td>\nMunicipalities with 100,000 or more inhabitants<\/td>\n<\/tr>\n
    B\u00e9zy, Levy and McQuade (2025)<\/td>\nEffect of Visale on moves, claim frequency, coverage and cost of Visale<\/td>\n<\/tr>\n
    Own estimates of defaults using the Household Panel<\/td>\nEffect of a default on whether the dwelling stays in long-term rental. Basis for Figures 1 and 2 in the article<\/td>\n<\/tr>\n<\/table>\n

    Source: author’s calculations | EsadeEcPol.<\/span><\/p>\n

    3. Programme design<\/h4>\n

    The programme I simulate, summarised in Table 1 of the article, largely replicates Visale’s rules. Each tenant receives their own guarantee, which covers only their share of the rent, so that in a couple or a shared flat there may be several guarantees linked to the same contract. It is open to all young people aged 18 to 30, whether studying or working, and to people over 30 with an individual gross income of up to 1.1 times the 2023 minimum wage, \u20ac16,632 a year, and the guarantee operates with two limits: a rent cap that depends on the zone, and an affordability rule under which the share of the rent paid by the tenant cannot exceed half of their disposable income, which, as in France, does not apply to students (Table 3).<\/p>\n

    Table 3. Requirements of the simulated programme<\/strong><\/p>\n

    Age, rent cap and income condition by group<\/em><\/p>\n\n\n\n\n\n
    Group<\/th>\nAge<\/th>\nRent cap<\/th>\nIncome condition<\/th>\n<\/tr>\n
    Students<\/td>\n18 to 30<\/td>\nP50 for their zone<\/td>\nNone<\/td>\n<\/tr>\n
    Non-students<\/td>\n18 to 30<\/td>\nP66 for their zone<\/td>\nTheir share of the rent does not exceed 50% of their monthly disposable income<\/td>\n<\/tr>\n
    Over 30<\/td>\nNo limit<\/td>\nP66 for their zone<\/td>\nThe 50% rule and an individual gross income of up to 1.1 times the 2023 minimum wage (\u20ac16,632)<\/td>\n<\/tr>\n<\/table>\n

    Source: author’s calculations based on Visale’s conditions | EsadeEcPol.<\/span><\/p>\n

    The caps are set using the 67,038 new long-term housing contracts signed in 2022 and 2023 and declared in IRPF returns by individual landlords, split into four zones: municipalities with fewer than 100,000 inhabitants, those with 100,000 or more excluding Madrid and Barcelona, and these two cities. There are 65 large municipalities, those above that threshold in the 2021 Municipal Register plus Roquetas de Mar and Rivas-Vaciamadrid, which exceed it in 2022 and 2023, and when a contract does not cover any full year, its rent is scaled up to a full year using the days let. The general cap is the 66th percentile of rents in each zone, which gives the \u20ac618, 714, 1,093 and 1,141 a month that the article rounds to about 620, 710, 1,090 and 1,140, while the cap for students is the median, between \u20ac512 and \u20ac963 depending on the zone (Table 4). I have left out the Visale exception that allows students with sufficient income to exceed their cap.<\/p>\n

    Table 4. New contracts and rent caps by zone<\/strong><\/p>\n

    Euros a month, contracts from 2022 and 2023. Unweighted number of contracts and percentiles weighted with the Panel’s grossing-up factor<\/em><\/p>\n\n\n\n\n\n\n
    Zone<\/th>\nContracts<\/th>\nP33<\/th>\nP50<\/th>\nP66<\/th>\nMedian floor area<\/th>\n<\/tr>\n
    Municipalities with fewer than 100,000<\/td>\n27,999<\/td>\n440<\/td>\n512<\/td>\n618<\/td>\n78 m\u00b2<\/td>\n<\/tr>\n
    100,000 or more excluding Madrid and Barcelona<\/td>\n24,026<\/td>\n538<\/td>\n616<\/td>\n714<\/td>\n77 m\u00b2<\/td>\n<\/tr>\n
    Madrid<\/td>\n11,383<\/td>\n798<\/td>\n900<\/td>\n1,093<\/td>\n62 m\u00b2<\/td>\n<\/tr>\n
    Barcelona<\/td>\n3,630<\/td>\n850<\/td>\n963<\/td>\n1,141<\/td>\n67 m\u00b2<\/td>\n<\/tr>\n<\/table>\n

    Source: author’s calculations using the Household Panel (IEF, AEAT and INE) | EsadeEcPol.<\/span><\/p>\n

    4. Who could apply for the guarantee<\/h4>\n

    To measure the programme’s reach, what matters is not so much the population that could apply for the guarantee as the people who move into a rental each year while meeting the requirements, since they are the ones who would actually use it. To count them I start from the 4,332,969 transitions in 2022 and 2023 among people aged 18 or over present in the Panel in two consecutive years, and I consider that a person moves into a rental when, from one year to the next, they change household and census tract and end up in a renting household without their parents, whether alone, as a couple or with other people. A renting household is one that declares the lease of its main residence or one in which none of its members is an owner. With these transitions I estimate an annual probability of moving for each combination of age, from 18 to 85 or over, place of birth, in Spain or abroad, and situation in the previous year, with parents, renting or other, to which I apply a factor by autonomous community obtained by indirect standardisation. Applied to the 2023 population, this probability gives just over 1.23 million moves into rental housing a year.<\/p>\n

    To each person aged 18 or over in the Panel in 2023 I assign their gross income, their disposable income and their income from employment and economic activities, and to the 4% of the weighted population with no income record I impute the mean of their age and zone cell. As the Panel does not identify students, among young people aged 18 to 30 with no income from employment or economic activities I impute the probability of studying recorded by the 2024 ECV for their age, smoothed with a three-age moving average, which falls from 91% at age 18 to 12% at 30.<\/p>\n

    To know what rent each person would pay, one also needs to know whom they move in with. The rent is split between the person moving and the adults in their destination household who are not relatives, whom I identify with the Panel’s relationship files from 2021 to 2023, while the partner, whether spouse, co-parent or ex-spouse, does share the rent, so that on average it is split among 2.55 adults. With that definition, among those who move I calculate, by age group and zone, the share who pay the rent alone, between two adults or among three or more. Those who pay alone are assigned a flat with a floor area equal to or below the median for their zone, and those who share, any flat, and in both cases the rent is drawn from the distribution of new contracts in their zone below the cap that applies to them. With that rent, the probability of meeting the 50% rule is the part of that distribution that the person can afford with their income, averaged with the cohabitation shares of their group. Figure A1 shows the result, in which the rule can be seen to exclude a large share of those with the lowest incomes, while the threshold of 1.1 times the minimum wage closes off access for people over 30 with higher incomes.<\/p>\n

    \"Figure<\/p>\n

    Summing these probabilities over the whole population, some 12.88 million people would meet the requirements if they decided to move into a rental, the 12.9 million in Figure 3 of the article, and of the just over 1.23 million annual moves, some 519,100, 42%, would be made while meeting them (Table 5). People over 30 account for almost half of these moves, some 242,800, because although only some of them meet the income limit they form a very large group, while non-students aged 26 to 30 contribute some 154,500, those aged 18 to 25 some 79,600, and students some 42,100, a figure that is probably an underestimate for the reasons explained in section 12. The last column of the table gives the share of the rent that each person would pay on average, between \u20ac206 and \u20ac252 a month depending on the group and about \u20ac224 overall, which rises to about 227 when weighted by the guarantees actually signed over the five years, the roughly \u20ac230 cited in the article.<\/p>\n

    Table 5. Eligible population, moves and share of the rent<\/strong><\/p>\n

    By group, 2023 population<\/em><\/p>\n\n\n\n\n\n\n\n
    Group<\/th>\nEligible people<\/th>\nEligible moves per year without the programme<\/th>\nAverage share of the rent (euros a month)<\/th>\n<\/tr>\n
    Non-students aged 26 to 30<\/td>\n1,825,840<\/td>\n154,509<\/td>\n252<\/td>\n<\/tr>\n
    Non-students aged 18 to 25<\/td>\n1,488,758<\/td>\n79,645<\/td>\n206<\/td>\n<\/tr>\n
    Students aged 18 to 30<\/td>\n1,245,614<\/td>\n42,107<\/td>\n238<\/td>\n<\/tr>\n
    Over 30<\/td>\n8,321,215<\/td>\n242,850<\/td>\n210<\/td>\n<\/tr>\n
    Total<\/strong><\/td>\n12,881,427<\/strong><\/td>\n519,111<\/strong><\/td>\n224<\/strong><\/td>\n<\/tr>\n<\/table>\n

    Source: author’s calculations using the Household Panel (IEF, AEAT and INE) and the ECV (INE) | EsadeEcPol. Note: the average share for the total is weighted by eligible moves.<\/span><\/p>\n

    5. Rolling out the guarantee<\/h4>\n

    Not everyone who could apply for the guarantee would do so, especially in the first years, when the programme would still be little known. The simulation therefore does not apply the guarantee to all eligible moves, but to a share of them, the coverage, which grows linearly over five years until it reaches 23.8%, the coverage Visale had in 2021, five years after its launch, with some 227,900 contracts out of some 957,000 new contracts a year, a ratio of 0.2381. Coverage is therefore 4.8% in the first year, 9.5% in the second, 14.3% in the third and 19.0% in the fourth, the percentages shown above the bars in Figure 4 of the article. This is my own assumption and, as section 11 shows, the one that weighs most on the number of guarantees and, together with default frequency, on the cost.<\/p>\n

    Each year’s guarantees are the sum of two parts. The first are those of people who would have moved anyway, which result from applying coverage to eligible moves, and the second, those of the additional moves brought about by the guarantee itself, which also sign it and which in the fifth year add up to some 22,700 (section 6).<\/p>\n

    Year-5 guarantees = 519,111 \u00d7 0.2381 + 22,740 \u2248 123,600 + 22,740 \u2248 146,300<\/em><\/p>\n

    In the same way, with some 24,700 and 4,550, we obtain the roughly 29,300 guarantees of the first year, and summing the five years gives some 439,000, the 440,000 in the article, with a range of 395,100 to 513,600. This interval is asymmetric, wider above than below, because almost all of its uncertainty comes from the additional moves, which depend on the effect estimated in France, whereas the guarantees of those who would have moved anyway barely vary across simulations, from about 366,400 to about 375,500 over the five years.<\/p>\n

    By group, people over 30 would sign some 173,300 guarantees over the five years, non-students aged 26 to 30 some 165,500, those aged 18 to 25 some 70,000, and students some 30,100 (Figure A2). In the fifth year these figures are some 57,800, 55,200, 23,300 and 10,000, those in Figure 5 of the article, so that four in ten guarantees that year would go to people over 30.<\/p>\n

    \"Figure<\/p>\n

    6. Additional moves<\/h4>\n

    The fact that the programme signs many guarantees does not mean that it brings about many moves, since most would go to people who would have moved anyway. What matters is what share of the guarantees corresponds to moves that would not have happened without them, and to estimate it I rely on B\u00e9zy, Levy and McQuade (2025), who measure the effect of Visale by comparing, through difference-in-differences, single people aged 26 to 30, who could use the programme, with those aged 31 to 35, who could not. The paper is limited to that age bracket because French tax data do not capture students well and because the comparison between those just below and just above age 30 is only credible within a narrow age window.<\/p>\n

    If a share s<\/em> of a group’s guarantees corresponds to additional moves, these are equivalent to s<\/em>\/(1 \u2212 s<\/em>) times the guarantees of those who would have moved anyway. For non-students aged 26 to 30, the group in which the effect is identified, I take the share implied by the paper’s own calculations in its section 7, which applies the increase of 0.6 points in the annual rate of moves into rental housing to the roughly 4 million people aged 26 to 30 in France and compares it with the 70,000 Visale contracts for that age in 2022, which gives just over a third. For those aged 18 to 25 I apply the same calculation to the roughly 6 million under-26s and their 187,600 contracts, obtained by subtracting from the 280,000 contracts of 2022 those of people over 30, 8% as read from the paper’s cumulative contracts chart, and the 70,000 of 26 to 30-year-olds. The ratio between the two calculations, 0.192 versus 0.343, is used to link the share for the youngest to that of the identified group.<\/p>\n

    s<\/em>(26 to 30) = 0.006 \u00d7 4,000,000 \/ 70,000 \u2248 0.34 \u2248 1\/3<\/em><\/p>\n

    s<\/em>(18 to 25) = (0.192 \/ 0.343) \u00d7 1\/3 \u2248 0.187<\/em><\/p>\n

    I attribute no effect to students or people over 30 in the central scenario. For students, because the paper cannot measure it and the Panel barely sees their moves, and for people over 30, because they are precisely the paper’s control group, in which only a residual effect appears up to age 32 or 33. Both decisions make the central scenario conservative, and Table 6 sets out the alternative scenarios with which they are assessed in section 11.<\/p>\n

    Table 6. Share of guarantees that are additional moves<\/strong><\/p>\n

    Central and alternative scenarios by group<\/em><\/p>\n\n\n\n\n\n\n
    Group<\/th>\nCentral scenario<\/th>\nAlternative scenarios<\/th>\n<\/tr>\n
    Non-students aged 26 to 30<\/td>\n1\/3, with a relative uncertainty of one third (the standard error of the effect)<\/td>\nNo change<\/td>\n<\/tr>\n
    Non-students aged 18 to 25<\/td>\n0.187, linked to the previous one (0.56 times the share drawn in each simulation)<\/td>\n0 and 1\/3<\/td>\n<\/tr>\n
    Students aged 18 to 30<\/td>\n0. The paper cannot measure it and the Panel barely sees their moves<\/td>\n1\/5<\/td>\n<\/tr>\n
    Over 30<\/td>\n0. They are the paper’s control group, with a residual effect up to age 32 or 33<\/td>\n1\/20 for ages 31 to 35 and 1\/5<\/td>\n<\/tr>\n<\/table>\n

    Source: author’s calculations based on B\u00e9zy, Levy and McQuade (2025) | EsadeEcPol. Note: the paper’s fifth refers to the 280,000 contracts of 2022 for all ages. The 8% share of people over 30 in 2022 has been read from the cumulative contracts chart (Figure 3) and not from a table.<\/span><\/p>\n

    With these shares, the calculation is simple. For non-students aged 26 to 30, s<\/em>\/(1 \u2212 s<\/em>) equals 0.5, so in the fifth year their 154,500 eligible moves, with coverage of 23.8%, give some 36,800 guarantees for people who would have moved anyway and half that figure, some 18,400, in additional moves. For those aged 18 to 25, s<\/em>\/(1 \u2212 s<\/em>) equals 0.2294, so their 79,600 eligible moves give some 19,000 guarantees for people who would have moved anyway and some 4,300 additional moves.<\/p>\n

    Additional moves in year 5 = 154,509 \u00d7 0.2381 \u00d7 0.5 + 79,645 \u00d7 0.2381 \u00d7 0.2294 \u2248 22,740<\/em><\/p>\n

    In total, that is some 22,700 additional moves in the fifth year, 22,800 in the median of the simulations, 16% of that year’s guarantees and the part that Figure 5 of the article shows in blue. As coverage grows linearly, so do additional moves, which rise from some 4,600 in the first year to some 22,800 in the fifth and add up to some 68,300 over the five years, of which some 55,200 are non-students aged 26 to 30 and some 13,000 are aged 18 to 25, the 68,000, 55,000 and 13,000 people in the article and in Figure 6.<\/p>\n

    In the fifth year, the 18,400 additional moves of non-students aged 26 to 30 represent 11.9% more than the 154,500 that would occur without the programme, and the 4,300 of those aged 18 to 25, 5.5% more on 79,600, which are the ‘around 12%’ and the ‘just over 5%’ in the article. The range of moves over five years, from 24,600 to 142,200, is very wide because the effect estimated in France is imprecise, with a standard error of around a third of its value, and because the share for young people aged 18 to 25 moves with it in each simulation.<\/p>\n

    7. Leaving the parental home<\/h4>\n

    The emancipation rate I use is the share of people aged 26 to 30 who do not live with their parents in the Household Panel, which in 2023 was 56.0%. Moving from additional moves to emancipations requires one more assumption, because some of those who move thanks to the guarantee may come from another rental or from a shared dwelling. As B\u00e9zy, Levy and McQuade find that almost all of Visale’s effect is due to the formation of new households, in the central scenario I consider that 85% of the additional moves of non-students aged 18 to 30 are departures from the parental home, and as a lower bound I use 40%, in line with the share of moves into rental housing by young people aged 26 to 30 that today involve leaving their parents’ home according to the Panel, 39%.<\/p>\n

    Emancipations accumulate by cohort, because those who leave home thanks to the guarantee remain independent in subsequent years and age with their cohort. Thus, young people aged 18 to 25 start to count in the 26 to 30 rate when they turn 26, and those who pass 30 stop counting in it, while the population aged 26 to 30 is held fixed at its 2023 level, some 2.50 million people. In the first year, the roughly 3,680 additional moves of non-students aged 26 to 30, multiplied by 0.85 and divided by those 2.50 million, raise the rate by just over a tenth of a point.<\/p>\n

    Increase in the rate in year 1 = 3,680 \u00d7 0.85 \/ 2,496,500 \u2248 0.13 points<\/em><\/p>\n

    Accumulating the five years, the increase reaches 1.35 points from the effect of this group alone, less than the 1.88 points that would result from directly spreading 85% of their 55,200 additional moves across that population, because some of those who leave home turn 31 before the end of the fifth year and stop counting in the rate. Adding young people aged 18 to 25 who leave home and gradually turn 26, the increase reaches 1.50 points, with a range of 0.54 to 3.18, and falls to 0.71 points if only 40% of additional moves were emancipations, which are the three lines in Figure 7 of the article. Multiplied by the 2.50 million people aged 26 to 30, the 1.50 points are equivalent to some 37,500 more young people living outside their parents’ home, and put the emancipation rate for that group at around 57.5%.<\/p>\n

    8. Defaults covered and cost<\/h4>\n

    To calculate the cost, the assumption that weighs most is how often guaranteed tenants would stop paying, something Spain does not measure well. In the central scenario I assume Visale’s rate, under which between 6% and 7% of contracts record a claim during their three years of coverage, and I take 6.5% as the central value and the range of 6% to 7% as a 95% interval in the simulations. The claims of each cohort of guarantees are spread over their three years of validity using Visale’s curve, 60% in the first, 30% in the second and 10% in the third, so that each year the claims of newly signed guarantees are added to those of guarantees signed in the two previous years, which is what makes covered defaults grow somewhat faster than guarantees.<\/p>\n

    The two available Spanish sources serve as bounds. The rate derived from the Panel, that of new episodes of doubtful debts in long-term rented dwellings in 2022 and 2023, is 0.627% a year and, converted to three years as if the episodes were independent, 1.87%, and it is a lower bound, because it only captures the persistent defaults that the landlord declares and deducts. The ECV rate, by contrast, is the share of households renting at market price, with at least one adult matching the programme’s profile, who report having been late with the rent two or more times in the last year, whatever the length of the delay, and converted to three years as a midpoint between assuming that delays always affect the same households or that they are independent from one year to the next it gives 21.2%, which with the same amount per default is an extreme upper bound. Visale’s rate lies very close to the geometric mean of the two, 6.3%, which makes it a reasonable starting point. Matching tenants and landlords by cadastral reference, the rate for the eligible profile comes out at 1.08 times the overall rate, with a range of 0.77 to 1.39, but I do not use it because the match may suffer from unobserved selection bias.<\/p>\n

    The frequency is applied to each guarantee, but as there may be several guarantees on the same contract in a couple or a shared flat, to count households I weight each claim by the inverse of the number of adults sharing the rent, which on average is slightly less than 0.5. Thus, the roughly 24,000 guarantee claims over the five years correspond to some 11,300 households with a covered default, rising from some 540 in the first year to some 4,000 in the fifth, the figures in Figure 8 of the article.<\/p>\n

    The size of each default comes from the doubtful-debt episodes in IRPF data, defined as consecutive years in which the same holder declares these debts for the same property. I divide the amount of each episode by the monthly rent in its first year, with a cap of 36 months, the maximum Visale covers, and obtain an average of 5.31 months’ rent, with a standard error of 0.17, across the 3,874 episodes starting in 2019 or 2022. I exclude those from 2020 and 2021, years in which the period for deducting these debts was reduced to three months, and those from 2023, which have no following year in the Panel. With each guarantee’s share of the rent, those 5.31 months amount to about \u20ac1,200 unpaid per guarantee with a claim and about \u20ac2,550 per household, very close to the \u20ac2,500 to \u20ac3,000 average cost per default for Visale cited in the article.<\/p>\n

    The cost of each claim is the unpaid months plus one month of legal costs, multiplied by the guarantee’s share of the rent, minus recovery of 20% of the unpaid months, to which \u20ac50 of administration is added for each guarantee signed. Recovery, legal costs and administration are my own assumptions, because there are no Spanish data with which to set them.<\/p>\n

    Net cost = claims \u00d7 (0.8 \u00d7 unpaid months + 1) \u00d7 share of the rent + 50 \u00d7 guarantees<\/em><\/p>\n

    Applied to the five years, the programme would pay some \u20ac34.3 million in defaults and legal costs, recover some 5.8 million and spend some 21.9 million on administration, which is the 439,000 guarantees times \u20ac50, giving a net cost of some \u20ac50.5 million, with a range of 44.9 to 59.7, which are the roughly \u20ac50 million in the article with its 34 million in payments, 6 in recovery and 22 in administration. Year by year, the cost rises from some \u20ac2.8 million in the first to some 17.5 in the fifth (Figure 9 of the article), and it is these 17.5 million that the article compares with the nearly \u20ac3,400 million of public spending on housing in 2024 according to Eurostat, of which they represent 0.5%.<\/p>\n

    To compare it with Visale and to assess the policy, however, one needs the cost over the whole life of each guarantee, which includes the claims that guarantees signed in the fourth and fifth years would record after the fifth year. Per guarantee, that cost is the claim frequency times the net cost of each claim plus administration, and with the average rent share of \u20ac224 it gives about \u20ac126, practically Visale’s average cost of \u20ac128.<\/p>\n

    Lifetime cost per guarantee = 0.065 \u00d7 (5.31 \u00d7 0.8 + 1) \u00d7 224 + 50 \u2248 \u20ac126<\/em><\/p>\n

    The cost per additional move divides that lifetime cost of the guarantees by the moves they bring about, as B\u00e9zy, Levy and McQuade do. For non-students aged 26 to 30, where one in three guarantees is an additional move, each move costs three times the lifetime cost of one of their guarantees, which is somewhat higher than the average, about \u20ac135.7, because so is their share of the rent, so that each additional move costs about \u20ac407, the roughly \u20ac400 in the article. For the programme as a whole, the lifetime cost of all guarantees, some \u20ac55.9 million, divided by the roughly 68,200 additional moves at the central point gives about \u20ac819, the roughly \u20ac800 in the article.<\/p>\n

    Cost per additional move, ages 26 to 30 = 3 \u00d7 135.7 \u2248 \u20ac407<\/em><\/p>\n

    Cost per additional move, whole programme = 55,900,000 \/ 68,220 \u2248 \u20ac819<\/em><\/p>\n

    The difference between the two figures is explained by how the cost is distributed across groups (Figure A3). Of the \u20ac50.5 million over the five years, some 20.2 correspond to non-students aged 26 to 30, some 7.6 to those aged 18 to 25, some 3.6 to students and some 19.1 to people over 30, so that the guarantees of students and people over 30, 46% of the total, account for some \u20ac22.6 million without generating additional moves in the central scenario, the roughly \u20ac23 million cited in the article.<\/p>\n

    \"Figure<\/p>\n

    9. Dwellings that remain in rental<\/h4>\n

    The last piece comes from my own project on defaults using the Household Panel, which estimates, with a stacked difference-in-differences model and matched control dwellings, that a dwelling that suffers a default is 10.46 points less likely to remain in long-term rental in the following years, with a standard error of 0.97, the fall of about 10 points shown in Figure 2 of the article. If the guarantee, by paying the rent to the landlord, avoided that whole effect, each household with a covered default would mean 0.1046 more dwellings in rental.<\/p>\n

    That effect only applies to defaults on contracts that would exist without the programme, because those of additional moves would not have been signed without the guarantee and there is no uncovered default to compare them with. Over the five years, those contracts accumulate some 9,500 households with a covered default, which multiplied by 0.1046 give some 990 dwellings that would still be rented by the fifth year, with a range of 830 to 1,160, the figure in Figure 8 of the article and in Figure A4. If the guarantee only prevented the dwelling from being left empty or becoming a second home, with an effect of 5.79 points, but not its sale, the figure would fall to some 550.<\/p>\n

    Dwellings remaining in rental in year 5 = 9,500 \u00d7 0.1046 \u2248 990<\/em><\/p>\n

    This is, nonetheless, the weakest figure in the simulation, for the same reasons the article points out. It assumes that the guarantee payment neutralises the whole effect of the default, when part of it may be due to the court process or to the landlord’s bad experience; the underlying estimate shows a pre-trend of \u22122.5 points three years before the default; and the result depends heavily on default frequency, so that with the Panel’s rate it would be some 285 dwellings and with the ECV’s, some 3,230.<\/p>\n

    10. Uncertainty of the results<\/h4>\n

    All figures are given as the median of 10,000 simulations, with the 90% interval between their 5th and 95th percentiles, and they combine two sources of uncertainty. Sampling uncertainty, which comes from working with a sample rather than the whole population, is captured with 200 household bootstrap replicates with Poisson(1) weights, which recalculate the moving rates and all aggregates. Parameter uncertainty is captured with 10,000 Monte Carlo draws on those replicates, in which the effect on moves is drawn, and with it that for young people aged 18 to 25, along with claim frequency, unpaid months and the effect on dwellings. Assumptions without an estimated error, such as the effect on students and people over 30, coverage, the share of emancipations, recovery, legal costs or the claims curve, are not drawn but treated as scenarios in section 11. That is why the interval for additional moves, which depends mainly on the effect estimated in France, is much wider than that for guarantees or cost.<\/p>\n

    11. Sensitivity to each assumption<\/h4>\n

    Table 7 changes one assumption at a time relative to the central scenario, and it is the source of the alternative figures cited in the article. Additional moves depend mainly on the effect attributed to the groups without an identified effect and on coverage, so that with one fifth of additional moves among students, young people aged 18 to 25 and people over 30 they would reach some 120,300, and with the 33% coverage Visale reached in 2023, some 95,600, at a cost of 70.6 million and with an increase in the emancipation rate of 2.10 points, which are the roughly 96,000 moves, 71 million and 2.1 points in the article. The cost, by contrast, depends mainly on default frequency, and would go from \u20ac50.5 million to 30.1 with the Panel’s rate and to 115.1 with the ECV’s, the roughly 30 and 115 million in the article.<\/p>\n

    Table 7. Sensitivity of the results to each assumption<\/strong><\/p>\n

    Median of each scenario. Moves and cost over five years<\/em><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
    Scenario<\/th>\nAdditional moves (thousands)<\/th>\nCost (\u20acm)<\/th>\nDwellings, year 5<\/th>\nEmancipation 26 to 30 (points)<\/th>\n<\/tr>\n
    Central<\/td>\n68.3<\/td>\n50.5<\/td>\n990<\/td>\n1.50<\/td>\n<\/tr>\n
    Non-students aged 18 to 25 with no effect<\/td>\n55.2<\/td>\n49.0<\/td>\n990<\/td>\n1.35<\/td>\n<\/tr>\n
    Non-students aged 18 to 25 with 1\/3<\/td>\n83.6<\/td>\n52.2<\/td>\n990<\/td>\n1.68<\/td>\n<\/tr>\n
    Over 30, 1\/20 for ages 31 to 35<\/td>\n70.4<\/td>\n50.7<\/td>\n990<\/td>\n1.50<\/td>\n<\/tr>\n
    One fifth for students, 18 to 25 and over 30<\/td>\n120.3<\/td>\n56.3<\/td>\n990<\/td>\n1.58<\/td>\n<\/tr>\n
    Coverage of 33%<\/td>\n95.6<\/td>\n70.6<\/td>\n1,387<\/td>\n2.10<\/td>\n<\/tr>\n
    Student cap at P33<\/td>\n68.3<\/td>\n50.2<\/td>\n990<\/td>\n1.50<\/td>\n<\/tr>\n
    Emancipation share of 40%<\/td>\n68.3<\/td>\n50.5<\/td>\n990<\/td>\n0.71<\/td>\n<\/tr>\n
    Displacement of 25%<\/td>\n51.2<\/td>\n50.5<\/td>\n990<\/td>\n1.50<\/td>\n<\/tr>\n
    Dwellings, only shift to empty or second home<\/td>\n68.3<\/td>\n50.5<\/td>\n548<\/td>\n1.50<\/td>\n<\/tr>\n
    Claims at the Panel rate<\/td>\n68.3<\/td>\n30.1<\/td>\n285<\/td>\n1.50<\/td>\n<\/tr>\n
    Claims at the ECV rate<\/td>\n68.3<\/td>\n115.1<\/td>\n3,230<\/td>\n1.50<\/td>\n<\/tr>\n
    Unpaid months from 2017 to 2022<\/td>\n68.3<\/td>\n51.0<\/td>\n990<\/td>\n1.50<\/td>\n<\/tr>\n<\/table>\n

    Source: author’s calculations, version 2.2 of the Stata simulation | EsadeEcPol.<\/span><\/p>\n

    The other assumptions carry less weight. The share of emancipations only affects the emancipation rate, which with 40% would rise by 0.71 points; the displacement scenario, in which a quarter of additional moves happen at the expense of tenants who cannot apply for the guarantee, reduces net moves to some 51,200 without changing the cost; and neither the student cap at the 33rd percentile nor the unpaid months from the 2017 to 2022 episodes move the cost by more than one million. If the rent were split between at most two adults, at the central point without uncertainty guarantees would fall from 439,000 to 412,300, additional moves from 68,200 to 64,900, and the cost would rise from 50.5 to 54.2 million, because each guarantee would cover a larger share of the rent.<\/p>\n

    Annex references<\/h4>\n

    B\u00e9zy, T., Levy, A. and McQuade, T. (2025). Insuring Landlords. Working paper, March 2025 version.<\/p>\n

    Instituto de Estudios Fiscales, Agencia Tributaria e INE. Panel de Hogares, 2016 a 2023.<\/p>\n

    INE. Encuesta de Condiciones de Vida, 2022 a 2025, y Padr\u00f3n continuo, 2021.<\/p>\n

    Real Decreto 1135\/2025, de 10 de diciembre. BOE n\u00fam. 299.<\/p>\n","protected":false},"excerpt":{"rendered":"

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