How 40 Million Immigrants Create Housing Wealth and Stabilize Communities

View the interactive map of the findings.

New research by Americas Society/Council of the Americas (AS/COA) and Partnership for a New American Economy (PNAE) finds that the 40 million immigrants in the United States have created $3.7 trillion in housing wealth, helping stabilize less desirable communities where home prices are declining or would otherwise have declined.

Evidence already shows that immigration helps stem the aging crisis that afflicting developed economies around the world. Since immigrants are more likely to be of working age, they help fill gaps in the labor force as the U.S. baby boom generation retires at a rate of more than 10,000 per day. But less attention has been paid to how immigration affects the housing market.

Immigrant workers strengthen the housing market in three ways:

• They directly drive housing demand through their own purchasing power. The 40 million immigrants in the United States represent a powerful purchasing class—reflected by their demand for housing, as well as for other locally produced goods and services—that bolster the value of homes in communities across the country.
• They indirectly generate demand by drawing U.S.-born individuals to opportunities in growing areas. The research shows that for every 1,000 immigrants settling in a county, 250 U.S.-born individuals follow, drawn by increased economic opportunity.
• They shift demand for housing within metro areas toward neighborhoods that had fallen out of favor. The research finds that immigrants often contribute to the stabilization of less desirable neighborhoods, helping those areas become viable alternatives for middle- and working-class Americans. This opens up new opportunities for those without homes to consider purchases in areas once in decline—an important trend in expensive metro areas.
• The most pronounced impact of immigration on housing values was in thriving Sun Belt cities that remain affordable and in declining Rust Belt cities where immigration acts as a barrier against even greater declines in home values. The data concludes that while immigration increases home values in many areas, it is not adding to the affordability crisis plaguing some of America’s most expensive cities, or pricing people out of expensive, highly desirable communities.

An interactive web module provides county-by-county data on the effect of immigrants in contributing to home equity. Data is searchable by zip code. This is the first in a series of new data being released by PNAE and AS/COA on specific economic contributions of immigrants, with a full report to be released this summer. This research was made possible with support from the Rockefeller Brothers Fund and the Partnership for a New American Economy Research Fund.

Some of the signature storylines of immigration’s effect on the housing market are as follows:

• Collectively immigrants add $3.7 trillion to U.S. housing wealth. Each of the 40 million immigrants in the U.S. adds, on average, 11.5 cents to the value of the average home in their local county. Given that the typical immigrant lives in a county with 800,000 housing units, this adds $3.7 trillion to U.S. housing wealth.

• The county experiencing the largest impact of immigration on the housing market is also one of the nation’s most affordable. In Harris County, TX, which includes Houston and its closest suburbs, the direct and indirect effects of immigration over the last 10 years has contributed over $25,000 to the value of a typical home. Harris is one of 12 counties nationwide where the impact of immigration on housing in the past decade is above $10,000. Most of these are Sun Belt counties that have attracted both immigrants and the U.S. born over the past decade.

• Immigration has stanched the decline of Rust Belt cities. The number of U.S.-born Americans residing in Chicago and surrounding Cook County, IL, has declined by 900,000 since 1970. The arrival of nearly 600,000 immigrants over the same time period offset most of that decline—and most likely kept additional natives from leaving—blunting what could have been a catastrophic impact on the local housing market, along the lines of those seen in Detroit and other Rust Belt cities. Immigration has even helped to stabilize the neighboring region around Gary, IN, where 13,000 immigrants have settled since 1990, adding $1,500 to the value of the average home.

• Immigration has stabilized declining rural areas. In rural North Carolina, Duplin County counted only 1 immigrant per 1,000 residents in 1970; after a population decline in the 1980s, 6,500 immigrants have settled in the county, helping to reverse the decline and boost property values by several hundred dollars. Today, Duplin mirrors the nation, with one resident in eight born abroad.

• Immigrants revitalize less desirable neighborhoods in costly metropolitan areas, opening up new alternatives for middle- and working-class Americans to buy homes. The nation’s costliest metro areas tend to have a set of highly sought after—and expensive—neighborhoods at their core, surrounded by a less-desirable and often declining periphery. Immigration has had much stronger effects on the perimeter. Examples of this include San Francisco and the East Bay or the New York area where immigrants have reversed population declines and helped to stabilize the housing market in several corners of the periphery: the Bronx, Queens, and Newark NJ. Immigration’s effects on the periphery are also seen in places like suburban Gwinnett County, GA, the most impacted segment of metropolitan Atlanta.

• Immigrants tend to avoid places with the worst housing affordability problems, in many cases becoming part of the solution. Among America’s 10-most expensive counties, where the average home costs at least $650,000, only one—Santa Clara, CA, home to Silicon Valley—has had an immigration impact above $2,000 over the past decade. Even in Santa Clara, the impact is less than a third of what is observed in Harris County since 2000. Immigrants contribute little to housing shortages—like other families, they avoid such areas when they can.

Notes on Methodology

The research, prepared by Jacob Vigdor, professor of public policy and economics at Duke University, makes use of county-level data on population and housing from the U.S. Census and American Community Survey between 1970 and 2010. The data are analyzed using a technique known as fixed-effect instrumental variables regression, designed to address a series of potential concerns—such as reverse causality and comparisons between dissimilar counties—that might exist when inferring the impact of immigration on the housing market. Housing values are derived from standard Census methodology, drawn from the decennial Census and the 2006-2010 American Community Survey. The timing of data collection implies that the inflation of the housing “bubble” between 2002 and early 2006 does not affect the analysis.

While there is sound economic logic behind the prediction that immigration will boost housing prices, a potential concern is that immigrants might gravitate toward growing communities where prices would have risen with or without them, for example because the local economy is booming. To address this, the statistical estimates in the report are based on forecasts rooted in 1970 Census data and nationwide, not local, trends in immigration. The forecasts take advantage of the well-established finding that immigrants tend to favor communities with pre-existing immigrant networks, regardless of the macroeconomic conditions in those communities. The actual number of immigrants in a county after 1970—a potential function of local economic conditions—is replaced with the forecast measure, which by construction cannot be a function of local conditions.

Housing prices in a county are determined by a number of factors aside from immigration, and the statistical models in the report use a variety of control variables to account for these determinants. The models account for all permanent differences between counties in the United States; for example, the scarcity of land in Manhattan relative to rural areas in the Great Plains. They also account for nationwide trends such as recessions and recoveries.

At the individual county level, the models control both for characteristics of the housing market itself—size in the previous decade, vacancy rates—and the physical characteristics of housing units—median age, the proportion of units in traditional single-family detached dwellings. To address the concern that many of these characteristics might have been driven by immigration, the controls pertain to conditions in counties a full decade prior to the measurement of housing prices and the forecast of immigration. Models also control for price levels one decade prior to measurement.

The results of the data analysis reflect the estimated impact of immigration to a county on housing prices in that county. The results address the counterfactual question, “what would prices be in this county had immigration not risen since a prior date, holding everything else constant.” It should be noted that the results do not specify the impact of immigration to nearby counties. For example, the settlement of 600,000 immigrants in Chicago, IL, can be expected to influence the housing market in neighboring counties even if no migrants move to those counties. For this reason, this analysis most likely understates the effect of immigration on prices in smaller counties at the periphery of large metropolitan areas.

This research was made possible with partial support from the Rockefeller Brothers Fund. The opinions and views of the authors do not necessarily state or reflect those of the Fund.