Dirk W. Early

Subsidized Housing, Emergency Shelters, and Homelessness: An Empirical Investigation Using Data from the 1990 Census

Abstract This paper uses data on the only systematic count of the homeless throughout the United States to estimate the effect on the rate of homelessness of a wide variety of potentially important determinants, including several major policy responses to homelessness that have not been included in previous studies. It improves upon estimates of the effect of previously studied determinants by using measures that correspond more closely to underlying theoretical constructs, especially by accounting for geographical price differences. It also conducts numerous sensitivity analyses and analyzes the consequences of the undercount of the homeless for point estimates and hypothesis tests. The papers most important finding from a policy perspective is that targeting the current budget authority for housing assistance on the poorest eligible households will essentially eliminate homelessness among those who apply for assistance. Achieving this goal promptly without concentrating the poorest households in housing projects and without spending more money requires vouchering out project-based assistance. The primary methodological finding of the paper is that the 1990 Decennial Census did not produce sufficiently accurate counts, especially of the street homeless, to permit very precise estimates of the effects of many factors which surely affect the rate of homelessness. The main exception is the price of housing. Other things equal, higher housing prices lead to more homelessness.

The role of subsidized housing in reducing homelessness: An empirical investigation using micro-data

Additional funding for subsidized housing is one of the most commonly proposed solutions to the problem of homelessness. For example, the Interagency Council on the Homeless has called for a

Rent control and homelessness

2 billion increase in the budget of the Department of Housing and Urban Development (HUD) to address the shortage of subsidized housing. However, research on the effect of subsidized housing in reducing homelessness is far from conclusive. This study combines data from the American Housing Survey (AHS) with a survey of the homeless to estimate the effectiveness of subsidized housing in reducing homelessness. The results indicate that subsidized housing has not targeted those most at risk of being homeless, and therefore a simple expansion of existing housing programs will have little effect on the number of homeless.

A Panel of Price Indices for Housing, Other Goods, and All Goods for All Areas in the United States 1982-2008

Abstract The purposes of this paper are to produce more precise estimates of the effect of rent control on homelessness using microdata on housed and homeless households and to provide evidence concerning the mechanisms through which rent control might affect homelessness. Our results suggest that rent control does increase homelessness by decreasing the rental vacancy rate and increasing the rental price of housing in the uncontrolled sector but that these effects of rent control are offset by other effects that decrease homelessness. We cannot reject the hypothesis that rent control has no net effect on homelessness.

A panel of interarea price indices for all areas in the United States 1982–2012

This paper produces a panel of price indices for housing, other produced goods, and all produced goods for each metropolitan area in the United States and the non-metropolitan part of each state from 1982 through 2008 that can be used for estimating behavioral relationships, studying the workings of markets, and assessing differences in the economic circumstances of people living in different areas. Our general approach is to first produce cross-sectional price indices for a single year 2000 and then use BLS time-series price indices to create the panel. Our geographic housing price index for 2000 is based on a large data set with detailed information about the characteristics of dwelling units and their neighborhoods throughout the United States that enables us to overcome many shortcomings of existing interarea housing price indices. For most areas, our price index for all goods other than housing is calculated from the price indices for categories of non-housing goods produced each quarter by the Council for Community and Economic Research. In order to produce a non-housing price index for areas of the United States not covered by their index, we estimate a theoretically-based regression model explaining differences in the composite price index for non-housing goods for areas where it is available and use it to predict a price of other goods for the uncovered areas. The overall consumer price index for all areas is based on the preceding estimates of the price of housing and other goods. The paper also discusses existing interarea price indices available to researchers, and it compares the new housing price index with housing price indices based on alternative methods using the same data and price indices based on alternative data sets. Electronic versions of the price indices are available online.

Racial Rent Differences in U.S. Housing Markets

This paper describes the production of a panel of price indices for housing services, other produced goods and services, and all produced goods and services for each metropolitan area in the United States and the non-metropolitan part of each state for each year from 1982 through 2012. Our general approach is to first produce interarea price indices for a single year 2000 and then use BLS time-series price indices to create the panel. Our geographic housing price index for 2000 is based on a large data set with detailed information about the characteristics of rented dwelling units and their neighborhoods throughout the United States that enables us to overcome many shortcomings of existing interarea housing price indices. For most areas, our price index for all goods other than housing is calculated from the price indices for categories of nonhousing goods produced each quarter by the Council for Community and Economic Research, formerly the American Chambers of Commerce Researchers Association. In order to produce a nonhousing price index for areas of the United States not covered by their index, we estimate a theoretically-based regression model explaining differences in the composite price index for nonhousing goods for areas where it is available and use it to predict a price index for these goods for the uncovered areas. The overall consumer price index for all areas is based on the preceding estimates of the price of housing and other goods. Electronic versions of the price indices are available online. The paper and its online appendices report many sensitivity analyses, and the paper compares the new housing price index with the most widely used indices of differences in the rents of identical units across areas.

An empirical investigation of the determinants of street homelessness

This paper exploits an unusually rich data set to estimate racial differences in the rents paid for identical housing in the same neighborhood in U.S. housing markets and how they vary with neighborhood racial composition. It overcomes the shortcomings of the data used in previous studies. It is large (over 400,000 observations), covers all parts of the country, and contains detailed information about the housing units and their immediate neighborhoods and the census block group of each unit. Importantly, due to the sample size, there are many blacks living in predominantly white neighborhoods and many whites in predominantly black neighborhoods. Results suggest that households led by blacks pay more for identical housing in identical neighborhoods than their white counterparts and that this rent gap increases with the fraction of the neighborhood white. In neighborhoods with the smallest fraction white, the premium is about 0.6 percent. In neighborhoods with the largest fraction white, it is about 2.4 percent. This pattern holds across different types of areas, namely the 50 largest metro areas, all other metro areas, non-metro areas, and areas with the highest and lowest levels of racial segregation in housing.