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UMD Economist Shows How American Frontier Policy Still Shapes Socioeconomics Today

Study Reveals Influence of 1800s Land Policies on Investment, Productivity, and Economic Opportunity

Illustration of a pioneer homestead with multiple land improvements.

Image Credit: Wikimedia Commons

May 4, 2026 Italia Peretti

Why does the way we divide land matter over time? New research from Cory Smith, an assistant professor  in the Department of Agricultural and Resource Economics (AREC) at the University of Maryland, shows that it matters more than most people expect. Smith examined how land ownership patterns from the 1800s continue to influence economic outcomes today. The results push back on the idea that markets naturally fix early imbalances. Instead, they show that the way land is first distributed can shape what happens for generations.

The study, which was published in the American Economic Journal: Applied Economics, focuses on the American frontier, where land was distributed in two very different ways. Some land was allocated to individual farmers in small plots under the Homestead Act, often around 160 acres per family. At the same time, large sections were granted to railroad companies and sold without limits on size. In some cases, buyers were able to acquire thousands of acres. This created a checkerboard pattern across the landscape. Neighboring plots had similar soil, geography, and access, but very different ownership structures. That setup allowed Smith to isolate the impact of ownership itself, not just location or land quality.

The findings are clear and measurable. Areas that started with more concentrated land ownership still show lower land values today, about 4.5% lower on average. These areas also have about 23% less fixed capital, meaning fewer long-term investments like buildings, irrigation, and infrastructure.

The effects show up in how land is used as well. Concentrated land areas historically owned by railroads and wealthy buyers were less likely to be improved for crop production and more likely to remain in lower-intensity uses like grazing. Even in modern data, those differences are still visible, though smaller than they were in the early 1900s.

One of the most interesting parts of the study is how long these effects last. Smith’s research tracked outcomes across more than 150 years using millions of land records and historical archives. While some of the gaps between small and large ownership areas narrowed over time, a significant portion remains. In many cases, today’s differences still reflect between 23% and 64% of the original gap.

A big part of the story comes down to incentives. In areas with large landowners, farming was often done by tenants rather than owner-operators. These tenant arrangements, especially share-based contracts, reduced incentives to invest in the land. The research finds that land concentration increased tenant farming rates and made these lower-investment arrangements more common.

When the person working the land does not fully benefit from improvements, those improvements are less likely to happen. Over time, that leads to lower productivity, fewer upgrades, and lower land values. Markets did shift some of this over time, but not completely. Land was bought and sold, and ownership became less concentrated in some places. Still, those changes happened slowly, and early patterns were not fully undone.

This research connects directly to the work happening in AREC. It focuses on how people make decisions about land and resources, how policy shapes those decisions, and how those effects play out over long periods of time. It also shows how something that seems like a historical detail can still influence real outcomes today.

Looking ahead, this work opens up new questions. How do different types of ownership affect environmental outcomes? What happens when similar patterns show up in other countries or in modern land markets? And what kinds of policies actually help close these long-term gaps?

For AREC, this is exactly the kind of research that matters. It connects history, policy, and real-world outcomes. It also shows that, if we want better results in the future, we need to understand how the past still shows up in today's data.