Mortgage Subsidies: International Evidence and Implications for Chile

The Chilean residential construction sector has weakened in recent years, facing both higher production costs and a large stock of unsold homes. At the same time, tighter borrowing conditions have made it more difficult for households to finance the purchase of their first property. In response to these challenges, the government introduced a program that subsidizes mortgage interest rates and provides state guarantees for the purchase of new homes. The initiative has two main objectives: improving households’ access to mortgage financing and supporting the recovery of residential construction.

More specifically, on May 29, 2025, the government introduced a subsidy of up to 60 basis points on mortgage interest rates, accompanied by a state guarantee for the first sale of new homes valued at up to UF¹ 4,000. By facilitating mortgage financing of up to 90% of the property value, the guarantee seeks to reduce the down payment typically required from buyers from 20% to 10%. After the implementing regulations were issued, the program became operational in June 2025 with an initial capacity of 50,000 loans. In August 2026, the program was expanded by adding 30,000 places, bringing its total capacity to 80,000. The expansion also raised the maximum value of eligible properties from UF 4,000 to UF 6,000 and extended the period for granting the benefits until May 31, 2028.

A comprehensive assessment of the policy’s impact will only become possible after the subsidies and guarantees have been granted and sufficient time has passed for their effects to emerge. In the meantime, evidence from comparable policies implemented in other countries can provide valuable insights and help formulate hypotheses for evaluating the Chilean program along several dimensions. This post does not attempt to estimate the program’s effects, as such an analysis would require detailed data and a suitable empirical strategy. Instead, it explains the initiative, reviews international evidence from comparable policies, and identifies hypotheses for future research.

In Latin America, a relevant comparison comes from Colombia’s Mortgage Portfolio Stabilization Reserve Fund (FRECH, by its Spanish acronym), which provided interest-rate coverage to mortgage borrowers. Hofstetter et al. (2011) estimate that the subsidy increased mortgage lending by approximately 38%. However, its pass-through was incomplete: only around 65%–74% of the subsidy reached borrowers, while part of the benefit was absorbed through an increase of 1.09 percentage points in pre-subsidy real mortgage rates. The Colombian experience suggests that an evaluation of the Chilean program should look beyond the statutory subsidy of 60 basis points. A central outcome will be the effective reduction in the final mortgage rate relative to the rate that a comparable borrower would have obtained without the program.

Carozzi et al. (2024) examine the effects of Help to Buy (HtB), a housing-credit policy introduced in the United Kingdom in April 2013. The program provided government equity loans covering up to 20% of the value of a newly built home, subject to a maximum purchase price of £600,000. Since the government contributed part of the financing, buyers were required to provide a deposit of only 5% of the property’s value. The authors find that the effects of HtB depended critically on the elasticity of housing supply. In areas where supply was relatively elastic, such as those near the English-Welsh border, the program stimulated housing construction. By contrast, in Greater London, where housing supply was severely constrained, HtB increased house prices by more than the present value of the subsidy without generating a detectable increase in construction. Complementary evidence from the United States shows that expansions in mortgage credit can also produce significant increases in house prices (Favara & Imbs, 2015).

The benefits of HtB were also unevenly distributed across households. Tracey and van Horen (2026) find that the gains were concentrated among relatively higher-income households that lacked financial assistance from their families, rather than among the lowest-income households. More generally, the UK evidence suggests that an evaluation of the Chilean program should account for heterogeneity both across households and across local housing markets. Cities and regions with large inventories of unsold homes or relatively elastic housing supply may experience stronger increases in sales and construction. By contrast, areas where housing supply is more constrained may exhibit greater capitalization of the subsidy into property prices.

In the United States, Government-Sponsored Enterprises (GSEs) benefited from an implicit government-backed guarantee that reduced the cost of mortgage financing. Jeske et al. (2013) analyze the macroeconomic and distributional implications of this arrangement. They find that government guarantees substantially expand mortgage originations but may reduce aggregate welfare by encouraging household leverage and transferring part of the default risk to taxpayers. In their model, eliminating the subsidy reduces mortgage originations but generates a welfare gain of approximately 0.5% in consumption-equivalent terms.

Garriga et al. (2019) further show that reductions in mortgage rates increase house prices, whereas the effects of relaxing loan-to-value (LTV) constraints are theoretically ambiguous. Their quantitative analysis indicates that changes in credit conditions explain a substantial share of the U.S. housing-price boom. Mortgage subsidies therefore generate two opposing effects for buyers: they reduce interest payments but also stimulate housing demand and increase property prices. Rappoport (2016) shows that when buyers respond by increasing their LTV ratios, the additional leverage can amplify the rise in house prices. Under some conditions, the resulting increase in housing expenditure may be greater than the savings from lower mortgage payments.

What could we expect in the Chilean case? The expansion of the mortgage subsidy has the potential to relax households’ liquidity constraints and support residential construction, particularly while the housing market holds a substantial inventory of unsold new homes. Nevertheless, international evidence shows that demand-side housing policies do not produce uniform effects. Their incidence depends on the degree of pass-through by financial institutions, the elasticity of housing supply, and the characteristics of eligible borrowers. The Chilean expansion therefore provides an important opportunity for future empirical evaluation. Whether it improves access to mortgage financing, stimulates construction, raises property prices, or encourages greater household leverage remains an open empirical question.

The program may increase both the number of households holding mortgage debt and their initial LTV ratios. These effects create a potential trade-off. On the one hand, lower interest payments reduce the debt-service burden and may lower the probability of default. On the other hand, households purchasing a home with approximately 10% initial equity would remain relatively exposed to changes in property values. A modest decline in nominal house prices could move them into negative equity, particularly after accounting for transaction costs. Although negative equity does not automatically result in default in Chile, it may limit households’ ability to move, refinance their mortgages, or sustain consumption following an adverse income shock.

It will also be important to examine the distributional effects of the policy. Its direct beneficiaries are likely to include households with stable formal incomes but insufficient savings, particularly younger and middle-income households without access to parental financial assistance. Developers holding inventories of eligible new homes and banks originating guaranteed mortgages may also benefit indirectly through higher sales and lending activity. By contrast, the program may provide limited assistance to low-income households that cannot meet debt-service-to-income requirements, renters who remain unable to qualify for mortgage financing, and households seeking to purchase existing homes. Future buyers could also be adversely affected if part of the subsidy is capitalized into the reference prices of eligible properties. Moreover, raising the maximum property value to UF 6,000 extends the program toward upper-middle-income households. Although this broader coverage may strengthen the stimulus to residential construction, it could also reduce the policy’s progressivity unless its benefits are carefully targeted.

Finally, the expansion is unlikely to generate significant immediate pressure on CPI inflation because its initial effect may be concentrated on the absorption of unsold housing inventories. Nevertheless, by lowering real mortgage costs for eligible borrowers, the program partially offsets the restraining effect of monetary policy on the housing market. As inventories return to more normal levels, the response may gradually shift from higher sales and construction toward higher property prices, construction costs, and household leverage. The appropriate macroeconomic assessment therefore depends on whether the subsidy remains a temporary countercyclical intervention or develops into a permanent stimulus to housing demand. Since the program covers a limited number of purchases and currently has a specified expiration date, its existing design is more consistent with the first interpretation. Whether it operates effectively as a countercyclical policy remains an empirical question.

In conclusion, the evidence should not be used merely to classify this policy (or other policies with financial implications) as either good or bad. A more informative evaluation would examine its effects across multiple outcomes, paying particular attention to those associated with its original objectives: supporting economic recovery and improving Chilean families’ access to homeownership. The analysis should also consider the externalities generated by the program, including unintended consequences that may offset its intended benefits and additional effects that may reinforce them. Finally, counterfactual exercises could help determine whether choices regarding the timing, targeting, or size of the intervention would have produced better outcomes.

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