Probabilistic Assessment of Expected Profitability in Housing Development under Land, Regulatory and Spatial Conditions: Evidence from the Greater Valparaíso Conurbation, Chile
This study employs Monte Carlo simulations and OLS regression on 74 residential projects in Greater Valparaíso, Chile, to demonstrate that higher land costs, specific regulatory constraints like minimum lot sizes, and greater distance from the coastline significantly reduce expected profitability in housing development.
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
Building a home is rarely just about laying bricks and pouring concrete; it is a high-stakes economic gamble where the price of the ground beneath the structure often dictates whether the project succeeds or fails. In the world of real estate development, investors and builders must navigate a complex web of rules, costs, and geography. They face land use regulations that dictate how many units can be built on a plot, the fluctuating costs of construction materials, and the specific location of the site, which can add value through proximity to the ocean or subtract it through distance from city centers. When these factors align poorly, a project can lose money before a single apartment is sold. Understanding how these elements interact is crucial for anyone involved in housing, yet the precise mathematical relationship between the cost of the land, the rules governing its use, and the final profit has often been treated as a collection of separate issues rather than a single, interconnected system.
A team of researchers from the Pontifical Catholic University of Valparaíso in Chile set out to untangle this knot by looking at the housing market in the Greater Valparaíso conurbation, a coastal urban system comprising five municipalities. They focused on 74 new residential apartment projects that were actively for sale in December 2025. Instead of relying on simple averages or static estimates, the researchers treated the future as uncertain. They recognized that construction costs and other expenses are never fixed numbers but rather ranges of possibilities. To capture this reality, they used a computer simulation technique that generated 2,000 different financial scenarios for each of the 74 projects. In each scenario, the costs of building and selling the apartments were allowed to vary within realistic limits, creating a probabilistic picture of what the profit margin might look like. This approach allowed them to move beyond a single guess and instead calculate an "expected" profit margin, along with the specific risk that a project might end up losing money.
The study revealed that the most powerful driver of profitability was not the raw price of the land, but rather the "effective" cost of that land once adjusted for what the local government actually allows builders to construct. In many cities, a plot of land might be expensive, but if the zoning rules are strict and limit the number of apartments that can be built, the cost per unit skyrockets. The researchers found that for every additional unit of currency per square meter in this effective land cost, the expected profit margin dropped by nearly one percentage point. This relationship was so strong that it served as the primary indicator of a project's financial health. While other regulatory factors, such as the maximum density allowed or the size of the building footprint, are often discussed as major constraints, the data showed that these specific rules did not have a statistically significant impact on the final profit margin in this particular market. The only regulatory rule that consistently mattered was the minimum size of the land plot itself; projects located in areas requiring larger minimum lot sizes tended to have slightly higher profit margins, perhaps because these larger plots often correspond to different market segments or less intense competition.
Location played a surprisingly nuanced role in the findings. The researchers measured how far each project was from the coastline, the city center, and various amenities like restaurants and parks. They discovered that being closer to the ocean was a significant advantage, associated with higher expected profit margins. This suggests that the premium buyers are willing to pay for a sea view or proximity to the beach can effectively offset the higher cost of the land in those desirable coastal zones. However, this benefit is not automatic; it depends on the balance between the high land cost and the high sale price the market will bear. The study also identified a critical threshold for land costs. When the cost of the land, adjusted for building capacity, consumed about 20 percent of the final sale price of the apartments, the profit margins began to deteriorate sharply. Below this 20 percent mark, most projects maintained healthy profits, but once land costs exceeded this level, the risk of the project becoming unprofitable increased dramatically.
Perhaps the most important takeaway from this analysis is that risk is not spread evenly across the housing market. While the average expected profit margin for these projects was a healthy 53 percent, this number masked a wide disparity. The simulations showed that while 75 percent of the projects had almost zero chance of losing money, a small subset of developments faced a 100 percent probability of negative returns. These high-risk projects were not random failures but were concentrated in specific locations where the combination of high land costs, restrictive regulations, and lower sale prices created a perfect storm for financial loss. By mapping these risks, the researchers provided a clear tool for early-stage decision-making. They demonstrated that a simple look at the price of a plot of land is insufficient; developers must calculate the effective cost of that land based on what they are legally allowed to build, weigh it against the likely sale price, and consider the location's ability to command a premium. In the complex, uncertain world of housing development, this probabilistic approach offers a way to see clearly which projects are likely to thrive and which are likely to fail before the first shovel hits the ground.
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