📈 economics

Crowding In: How China’s Affordable Rental Housing Program Affected Private Rents

This paper finds that China's massive Affordable Rental Housing program unexpectedly increased private market rents by approximately 4.0 to 4.3 percent per standard deviation of planned units, driven by demand-side "crowding-in" effects in cities with high existing rents and large inflows of new urban workers, rather than the supply-side "crowding-out" typically observed in the U.S.

Original authors: MINGLEI LYU

Published 2026-10-13

📖 5 min read🧠 Deep dive

CC BY 4.0

Original authors: MINGLEI LYU

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

In the bustling cities of the developing world, a fundamental tension plays out every day: how to house the millions of people moving in search of work. When a city grows, more people need places to live, and basic economic logic suggests that if the supply of housing increases, the price of renting should go down. This is the standard expectation for social housing programs, where governments build affordable apartments to help low-income workers. In many mature markets, such as the United States, studies have shown that when the government adds subsidized units, private landlords often respond by reducing their own supply or lowering prices because the subsidized units take away their potential customers. This phenomenon is known as "crowding out," where the public program displaces the private market. However, in rapidly growing economies where the population is still expanding quickly, the rules might be different. If a city is so attractive that it draws in a constant stream of new workers, adding affordable housing might not just replace private rentals; it could make the city even more appealing, drawing in so many new people that the demand for all housing, including private rentals, actually increases.

This is the puzzle that a new study tackles by looking at China's massive Affordable Rental Housing program. Between 2021 and 2025, the Chinese government planned to build 8.7 million small, rent-controlled apartments specifically for new urban workers. This was the largest expansion of social rental housing in any country in recent decades, with 6.5 million of those units concentrated in about 40 major cities. The government did not just announce a vague goal; it negotiated specific targets with each city, ranging from a few thousand units in smaller cities to hundreds of thousands in the biggest metropolises. Because these targets were set based on local land availability and budget capacity rather than a prediction of future rent prices, they created a natural experiment. Researchers could compare cities that committed to building many units against those that committed to fewer, and see how the private rental market reacted in each place.

The researchers gathered monthly data on rental prices from 74 Chinese cities, tracking the market from 2018 through 2026. They focused on the asking prices listed by landlords, which serve as a quick signal of market conditions. By comparing the cities with the highest plans for new affordable units against those with lower plans, and controlling for other factors like local economic growth and house prices, they isolated the specific effect of the program. The results were surprising and ran counter to the established wisdom from the United States. Instead of seeing private rents fall as the new affordable units came online, the study found that private rents actually rose. In cities that planned to build more affordable units, private rents increased by roughly 4 percent for every standard increase in the number of planned units. This effect appeared within months of the program's announcement and was strongest in the cities with the highest existing rents and the largest influx of new workers.

The study explicitly rules out the idea that the government was simply replacing private landlords with public ones, which would have lowered prices. Instead, the evidence points to a different mechanism: the program acted as a magnet. By guaranteeing a supply of affordable housing, the program lowered the effective cost of living in these major cities, making them more attractive to the new workers who were already flocking there. As more workers moved in to take advantage of the city's opportunities and the new housing safety net, the overall demand for housing surged. Private landlords, facing this steeper demand, raised their prices. The effect was not uniform; it was concentrated in the high-rent, high-growth cities where new workers were most eager to settle. In cities with lower rents or fewer new arrivals, the effect was much smaller or non-existent. This suggests that in a rapidly urbanizing environment, adding supply does not always crowd out the private market; sometimes, it crowds in more demand.

The researchers are confident in these findings because the result held up under many different tests. They checked if the trend existed before the program started and found no evidence of it. They tested different ways of measuring the data and different timeframes, and the pattern of rising rents remained consistent. They also looked at whether the program might have affected house prices in a way that trickled down to rents, but the data showed the effect was specific to the rental market. The study concludes that while the program successfully provided affordable units for those eligible to receive them, it had an unintended side effect for the rest of the market. The private renters who did not qualify for the government aid ended up paying higher rents because the program made the city a more desirable place to live, drawing in more people than the new supply could fully absorb. This finding challenges the simple view that more public housing always leads to cheaper private housing, suggesting instead that in growing economies, the success of a housing program in attracting people can drive up the cost of living for everyone else.

Technical Summary: "Crowding In: How China's Affordable Rental Housing Program Affected Private Rents"

Problem and Context
This paper investigates the causal impact of China's Affordable Rental Housing (ARH) program on private market rents. Launched in 2021, the ARH program represents the largest social-rental expansion in recent decades, with a national target of 8.7 million units between 2021 and 2025, concentrated in 40 designated cities. The central research question is whether this massive injection of subsidized supply reduces private rents through a "crowding-out" mechanism (substituting for private supply) or increases them through a "crowding-in" mechanism (attracting demand).

Theoretical predictions are ambiguous. U.S. literature (e.g., Sinai and Waldfogel, 2005; Eriksen and Rosenthal, 2010) suggests that subsidized housing crowds out private supply, lowering market rents. Conversely, if subsidized housing lowers the effective cost of living in a city, it may attract more workers, shifting the private demand curve outward and raising rents. The Chinese setting offers a unique test case: a rapidly urbanizing market with a growing tenant population, where tenancy is decoupled from local public services (unlike the U.S. or Korea), potentially weakening the substitution channel.

Methodology
The study utilizes a monthly panel dataset of asking rents from 74 Chinese cities spanning August 2018 to September 2026. The identification strategy exploits quasi-experimental variation in the intensity of the ARH program across designated cities.

Treatment Variable: The key independent variable is "Plan Intensity," defined as the city-level ARH target (negotiated between municipal bureaus and the central ministry) scaled by the 2020 census population (units per 1,000 residents). Targets range from 1.6 units per 1,000 residents in Haikou to 48.4 in Xiamen.
Empirical Strategy: The primary specification is a difference-in-differences (DiD) design with a continuous "dose" treatment:
$\log(\text{Rent}_{ct}) = \beta (\text{Intensity}_c \times \text{Post}_t) + \alpha_c + \delta_t + \gamma \Delta \text{HP}_{ct} + \epsilon_{ct}$
where $\text{Post}_t$ indicates the period from January 2021 onward, $\alpha_c$ and $\delta_t$ are city and calendar-month fixed effects, and $\Delta \text{HP}_{ct}$ controls for second-hand house price inflation.
Identification Assumptions: The author argues that plan intensity is determined by bureaucratic factors (land availability, fiscal capacity, conversion stock) rather than rental market forecasts. They address potential pre-trend violations by noting that a simple binary comparison (designated vs. non-designated) fails pre-trend tests due to pre-existing trajectory differences between large and small cities. Therefore, the identification relies on the within-designated-city dose variation, which controls for the "designated" status itself.
Robustness: The study employs randomization inference (reshuffling intensity values across cities), province-by-year fixed effects to absorb regional shocks, and trend-adjusted sensitivity bounds.

Key Results
Contrary to the U.S. benchmark of crowd-out, the paper finds that the ARH program caused private rents to rise.

Magnitude: A one-standard-deviation increase in plan intensity (9.1 units per 1,000 residents) leads to a 4.0% to 4.3% increase in private asking rents over the post-period.
Dose Response: The effect is immediate, appearing within months of designation and plateauing by the second year, suggesting the mechanism is driven by information and anticipation of future supply rather than the physical completion of units.
Heterogeneity: The rent increases are concentrated in cities with high pre-program rents and large population inflows. The effect is statistically significant in high-rent and high-population cities but negligible in low-rent or low-population cities.
Mechanism: The heterogeneity supports a "demand-side attraction" mechanism. The program lowers the effective cost of settling in expensive, high-growth cities, attracting more workers. Because the private rental supply in these cities is dominated by informal, elastic landlords, the influx of new tenants drives up market rents. The lack of correlation with house-price growth gradients rules out a land-supply crowding-out channel.

Contributions and Significance
The paper makes three primary contributions to the literature:

Causal Evidence on Scale: It provides the first causal city-level estimates of the world's largest active social-rental program. It demonstrates that in a context where tenancy is not bundled with local citizenship and the tenant base is growing, the "crowding-out" prediction fails.
Reversal of Benchmarks: It documents a reversal of the standard international finding. While U.S. and Korean studies find that subsidized supply depresses private rents, this study finds that in China's rapidly urbanizing markets, subsidized supply acts as "urban attraction infrastructure," raising private rents by increasing demand.
Methodological Insight: The paper highlights the importance of using within-group dose variation when treatment assignment (city designation) correlates with market size. It demonstrates that binary comparisons between designated and non-designated cities can be biased by pre-existing trends, whereas the dose design isolates the marginal effect of program intensity.

Policy Implications
The author concludes that the ARH program should not be viewed primarily as a tool for general rent relief. While it benefits eligible tenants of the subsidized units, it raises rents for the unsubsidized margin (near-eligible and non-eligible workers). The paper suggests that for rent stabilization to be effective in high-growth cities, the scale of subsidized supply must be sufficient to counteract the inflow of new workers it attracts, rather than simply offsetting existing stock. The findings also suggest that increasing housing supply in productive cities can have efficiency gains by retaining workers, even if it results in higher private market rents.

Limitations
The study acknowledges several limitations:

Data Type: The analysis uses asking rents rather than transaction prices, which may overstate levels in a softening market.
Sample Restrictions: House price controls limit the sample to 36 designated cities, excluding key provinces like Guangdong and Jiangsu.
Decomposition: The data cannot distinguish between the demand response coming from new migration versus within-city tenure choices.
Temporal Decay: The effect appears to decay after mid-2025, a phenomenon the author cannot fully explain with the available data.

Technical Summary: "Crowding In: How China's Affordable Rental Housing Program Affected Private Rents"

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