HOUSING RECOVERY

ON THE GULF COAST

PHASE II

Results of Property Owner Survey in Louisiana, Mississippi, and Texas

U.S. Department of Housing and Urban Development | Office of Policy Development and Research
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Housing Recovery on the Gulf Coast, 

Phase II

Results of Property Owner Survey in

Louisiana, Mississippi, and Texas

Prepared for

U.S. Department of Housing and Urban Development

Office of Policy Development and Research

Prepared by

Jennifer Turnham

Kimberly Burnett

Carlos Martín

Tom McCall

Randall Juras

Jonathan Spader

August 2011
I

am pleased to share this report from the U.S. Department of Housing and Urban 

Development (HUD), Housing Recovery on the Gulf Coast, Phase II: Results of Property Owner 

Survey in Louisiana, Mississippi, and Texas. The report presents findings from a survey of 

722 owners of owner-occupied and small rental residential properties that suffered major 

or severe damage from Hurricanes Katrina and Rita in 2005. This report, along with the Phase I 

report HUD published in December 2010, provides insight into how HUD programs can help 

communities more effectively recover from disasters.

This report is particularly significant in light of recent flood damage up and down the East 

Coast. Congress frequently provides supplemental appropriations through HUD’s Community 

Development Block Grant (CDBG) program to help communities recover from natural and 

manmade disasters. These Disaster Recovery Grants have been used to help New York City recover 

from the attack on the World Trade Center on September 11, 2001; to help towns in the upper 

Midwest recover from severe flooding in 1993, 1997, and 2008; and to help the Gulf Coast in the 

wake of the devastating hurricanes of 2005 and 2008.

The research reports on the experiences of households directly affected by Hurricanes Katrina 

and Rita, with the goal of drawing lessons from those trying to rebuild their homes and lives. For 

these families, three factors were most important in determining whether to rebuild their home: 

(1) whether they were covered by insurance, (2) the extent of storm damage, and (3) if there was 

extensive flood damage (as opposed to wind damage). These responses highlight the importance of 

homeowners and flood insurance, particularly for households in disaster-prone areas.

This study also examines two different models for providing homeowner assistance. Texas 

implemented a traditional home repair and rehabilitation model, in which housing assistance was 

directly tied to the home for the exclusive purpose of rebuilding. This program served roughly 

1,000 households. In contrast, Mississippi and Louisiana were forced to operate at much larger 

scales, serving approximately 28,000 and 129,000 households, respectively. As a result, these states 

received a waiver enabling them to provide homeowner assistance in the form of a “compensation” 

grant, which did not have to be used for rebuilding.

The rehab model employed by Texas appears to have resulted in more complete application of 

funds to rebuilding, in keeping with the program’s design. However, households in Louisiana 

and Mississippi that moved instead of rebuilding their home report being more satisfied with 

their neighborhood than those that stayed in their previous neighborhood. A housing assistance 

model that allows or encourages households to move rather than rebuild in high-risk areas could 

FOREWORD

Foreword
both improve the quality of life for affected households and mitigate future risks. This study 

suggests that both approaches may be appropriate, depending on the scope of the damage and the 

community’s plan for recovery.

The federal government plays an important role in response to, and recovery from, natural 

disasters. HUD hopes that this research helps to inform that role and to help disaster-affected 

communities recover faster and more fully.

Raphael W. Bostic, Ph.D.

Assistant Secretary for Policy

Development and Research

Foreword
i

HOUSING RECOVERY ON 

THE GULF COAST, PHASE II

Results of Property Owner Survey in Louisiana,

Mississippi, and Texas

Table of Contents

Contents

Acknowledgments ������������������������������������������������������������������������������������������������������������� vii

Executive Summary ����������������������������������������������������������������������������������������������������������viii

1. Introduction �����������������������������������������������������������������������������������������������������������������1

 1.1 Background ................................................................................................................2

 1.2 Key Findings from the Phase I Report ..........................................................................5

 1.3 Purpose of the Phase II Report ....................................................................................6

 1.4 Phase II Research Questions ........................................................................................7

 1.5 Organization of the Phase II Report ............................................................................7

2. Data Collection and Analysis Methodology ��������������������������������������������������������������������9

 2.1 Study Data Sources .....................................................................................................9

 2.2 Selecting the Owner Survey Sample ........................................................................... 11

 2.3 Approach to Conducting the Property Owner Survey ................................................. 14

 2.4 Survey Response Rates .............................................................................................. 17

 2.5 Response Bias ........................................................................................................... 19

 2.6 Sampling Weights ..................................................................................................... 19

 2.7 Final Sample Characteristics ...................................................................................... 20

3. Repair Needs and Rebuilding��������������������������������������������������������������������������������������� 22

 3.1 Pre-Hurricane Conditions and Hurricane Damage ..................................................... 22

 3.2 Property Ownership in 2011 ..................................................................................... 28

 3.3 Housing Conditions in 2011 ..................................................................................... 32

 3.4 Rebuilding Activity Since 2005 ................................................................................. 36

 3.5 Reasons for Not Rebuilding ...................................................................................... 45

 3.6 Summary of Chapter Findings ................................................................................... 46

4. Owner and Property Factors Affecting Rates of Rebuilding������������������������������������������� 49

 4.1 Definition of Rebuilding ........................................................................................... 49

 4.2 Property-Level Characteristics ................................................................................... 51
ii

 4.3 Owner Characteristics ............................................................................................... 53

 4.4 Multivariate Analysis................................................................................................. 55

 4.5 Summary of Chapter Findings ................................................................................... 58

5. Funding for Rebuilding and CDBG Programs �������������������������������������������������������������� 60

 5.1 Rates of CDBG Receipt ............................................................................................ 60

 5.2 Use of CDBG Funds ................................................................................................. 65

 5.3 Resources for Rebuilding ........................................................................................... 67

 5.4 Resource Gaps and Use of Personal Funds .................................................................. 70

 5.5 Resources and Rebuilding ......................................................................................... 75

 5.6 Owner Experiences with the Different Program Models .............................................. 85

 5.7 Summary of Chapter Findings ................................................................................... 88

Appendix A. State CDBG Program Descriptions ���������������������������������������������������������������� 90

Appendix B. Overview of the Property Owner Survey ��������������������������������������������������������� 94

Appendix C. Property Owner Survey Nonresponse Bias Analysis and Adjustment�������������� 102

Appendix D. Rates of Application to the CDBG Program������������������������������������������������� 108

Table of Contents (Continued)

Contents (Continued)
List of Exhibits iii

List of Exhibits

Exhibit 1-1. Housing Unit Damage Estimates by State ...............................................................3

Exhibit 1-2. Summary of CDBG-Funded Homeowner Programs ................................................4

Exhibit 2-1. Initial Allocation of Telephone Survey Sample ....................................................... 13

Exhibit 2-2. Survey Response Rates by Subgroups of Interest .................................................... 17

Exhibit 2-3. Characteristics of the Survey Sample: State and Owner Status at Time 

of Survey ............................................................................................................. 18

Exhibit 2-4. Characteristics of the Survey Sample: Occupancy at Time of Hurricanes ................ 21

Exhibit 2-5. Characteristics of the Survey Sample: CDBG Receipt ............................................ 21

Exhibit 3-1. Pre-Hurricane Property Condition by State and Overall ........................................ 23

Exhibit 3-2. Pre-Storm Home Values by State .......................................................................... 23

Exhibit 3-3. Owner-Reported Assessed Damage Amount by State—Median and 

by Percentile ....................................................................................................... 24

Exhibit 3-4. Share of Properties Leveled, Condemned, or Demolished ...................................... 25

Exhibit 3-5. Parts of Homes that Sustained Damage: Proportion with Damage .......................... 26

Exhibit 3-6. Type of Storm Damage Reported by State ............................................................. 26

Exhibit 3-7. Current Condition by Type of Hurricane Damage Reported .................................. 27

Exhibit 3-8. Ownership of Hurricane-Affected Properties in 2011 ............................................ 28

Exhibit 3-9. Buyers for Properties Sold after the Hurricanes ..................................................... 28

Exhibit 3-10. Year that 2005 Owners Ceased Owning Hurricane-Damaged Property ................... 29

Exhibit 3-11. Association Between Pre-Storm Property Characteristics and Change in 

Ownership .......................................................................................................... 30

Exhibit 3-12. Total Dollar Amount of Assessed Damage as Reported by Owners.......................... 31

Exhibit 3-13. Association Between Damage Extent and Change in Ownership** ......................... 32

Exhibit 3-14. Owner-Reported Condition of Properties in Early 2011 by State and Overall ......... 33

Exhibit 3-15. Current Housing of 2005 Owner-Occupiers Living Elsewhere in Early 2011 .......... 34

Exhibit 3-16. Owner-Reported Condition of Current Housing Occupied by Movers and 

Stayers ................................................................................................................ 34

Exhibit 3-17. Satisfaction with Current Neighborhood for Movers and Stayers ............................ 35

Exhibit 3-18. Reasons for Not Returning to Pre-Hurricane Neighborhood .................................. 35
List of Exhibits (Continued) iv

Exhibit 3-19. Extent of Rebuilding Activities ............................................................................. 36

Exhibit 3-20. Extent of Rebuilding Activities by State ................................................................ 37

Exhibit 3-21. Rebuilding by Continuing and Former Owners ..................................................... 37

Exhibit 3-22. Year Repair or Rebuilding Work Started ................................................................ 38

Exhibit 3-23. Year Repair or Rebuilding Work Was Completed ................................................... 39

Exhibit 3-24. Year Repair or Rebuilding Work Was Completed by State, Cumulative ................... 39

Exhibit 3-25. Pre-Hurricane Elevation Status ............................................................................. 40

Exhibit 3-26. Elevation Activity ................................................................................................ 41

Exhibit 3-27. Completed Elevation Activity by CDBG Receipt ................................................... 41

Exhibit 3-28. Type of Rebuilding .............................................................................................. 42

Exhibit 3-29. Estimated Cost of Repairs or Rebuilding to Address Hurricane Damage ................. 42

Exhibit 3-30. Estimated Cost of Repairs or Rebuilding to Address Hurricane Damage 

by State ............................................................................................................... 43

Exhibit 3-31. Association Between Rate of Rebuilding and Blocks with Concentrated 

Damage .............................................................................................................. 44

Exhibit 3-32. Association Between Pre-Storm and Post-Storm Neighborhood Satisfaction

and Blocks with Concentrated Damage ................................................................ 44

Exhibit 3-33. Big Reasons for Not Rebuilding Among Owners Who Undertook No Repair/

Rebuilding .......................................................................................................... 45

Exhibit 4-1. Alternative Owner-Reported Measures of Rebuilding 

(Continuing Owners Only) .................................................................................. 50

Exhibit 4-2. Rebuilding Status by State and Tenure .................................................................. 51

Exhibit 4-3. Association Between Property Characteristics and Rebuilding Status: 

Mortgage and Insurance Presence, Insurance Coverage, and Home Value ............... 52

Exhibit 4-4. Association Between Property Characteristics and Rebuilding Status: 

Type, Extent, and Value Relative to Property Value of Damage and Cost 

of Repairs ............................................................................................................ 53

Exhibit 4-5. Association Between Owner Characteristics and Rebuilding Status ......................... 54

Exhibit 4-6. Association Between Mortgage Presence and Property Insurance ............................ 55

Exhibit 4-7. Regression Analysis Results .................................................................................. 56

Exhibit 5-1. CDBG Receipt Among Properties in the Owner Survey Sample by State ................ 61

List of Exhibits (Continued)
v

Exhibit 5-2. CDBG Receipt by Option in Louisiana ................................................................ 62

Exhibit 5-3. Distribution of CDBG Award Amounts, Homeowners Only .................................. 62

Exhibit 5-4. Owner Characteristics of CDBG Recipients and Nonrecipients,

Homeowners Only .............................................................................................. 63

Exhibit 5-5. Characteristics of CDBG Recipient and Nonrecipient Properties,

Homeowners Only .............................................................................................. 64

Exhibit 5-6. Share of CDBG Homeowner Grant Funds Used for Repair/Rebuilding,

Louisiana and Mississippi Homeowners Only ....................................................... 66

Exhibit 5-7. Common Uses of CDBG Homeowner Grants for Activities Other than Repair/

Rebuilding, Louisiana and Mississippi Homeowners Only ..................................... 67

Exhibit 5-8. Total Amount of Resources (Including CDBG and Other Sources) Among CDBG 

Recipients and Nonrecipients, Homeowners Only ................................................. 68

Exhibit 5-9. CDBG Grant Relative to Total Amount of Resources of CDBG Recipients by State,

Homeowners Only .............................................................................................. 69

Exhibit 5-10. Percentage of Owners Reporting Other Sources of Funding (Other than CDBG)

and Median Amount Reported from Each Other Source, Homeowners Only .......... 70

Exhibit 5-11. Owners Reports on the Sufficiency of Total Funding by CDBG and Non-CDBG 

Receipt, Homeowners Only ................................................................................. 71

Exhibit 5-12. Total Resources Relative to Owner-Reported Damage Assessments, Homeowners 

Only ................................................................................................................... 71

Exhibit 5-13. Use of Personal Funds to Cover Rebuilding Expenses, Homeowners Only .............. 72

Exhibit 5-14. Sources of Personal Funds Used for Rebuilding, Homeowners Only ....................... 73

Exhibit 5-15. Median Assessed Damage, Total Funding Assistance, and Repair Costs for All 

Owners, by State ................................................................................................. 73

Exhibit 5-16. Median Assessed Damage, Total Funding Assistance, and Repair Costs Among CDBG 

Recipients Only by State ...................................................................................... 74

Exhibit 5-17. Median Assessed Damage, Total Funding Assistance, and Repair Costs Among 

Non-CDBG Recipients by State ........................................................................... 74

Exhibit 5-18. Funding Gaps and Rebuilding by CDBG Receipt and Application Status, 

Homeowners Only .............................................................................................. 76

Exhibit 5-19. Funding Gaps and Rebuilding by Funding Sufficiency and Use of Personal Funds,

Homeowners Only .............................................................................................. 76

List of Exhibits (Continued)

List of Exhibits (Continued)
vi

Exhibit 5-20. Property and Owner Characteristics by CDBG Receipt and Application Status, 

Homeowners Only .............................................................................................. 78

Exhibit 5-21. Property and Owner Characteristics by Funding Sufficiency and Use of Personal 

Funds, Homeowners Only ................................................................................... 80

Exhibit 5-22. Association of Presence of Funding Gap with Property Having Substantial Damage

in 2010, Based on Windshield Observation (Logit Estimation) .............................. 82

Exhibit 5-23. Association of Funding Gap Amount with Property Having Substantial Damage

in 2010, Based on Windshield Observation (Logit Estimation) .............................. 83

Exhibit 5-24. Association of Presence of a Funding Cap with Property Having Substantial Damage

in 2010, Based on Windshield Observation (Logit Estimation) .............................. 84

Exhibit 5-25. Reported Satisfaction with the CDBG Program in Texas Among CDBG Recipients 85

Exhibit 5-26. Months to Complete Repair/Rebuilding Activities (from Repair Start to Completion) 

by State ............................................................................................................... 86

Exhibit 5-27. Percent of CDBG Recipients Completing Repairs by State ..................................... 87

Exhibit B-1. Respondents, Content, and Reason for Inclusion by Survey Section and Subsection 94

Exhibit C-1. Comparison of Response Rates by Geographical County/Parish ........................... 105

Exhibit C-2. Comparison of Property Characteristics Between Respondents and

Nonrespondents ................................................................................................ 106

Exhibit D-1. Rates of Application to Homeowner Assistance Programs..................................... 109

Exhibit D-2. Reasons for Not Applying for a CDBG Award ..................................................... 109

List of Exhibits (Continued)

List of Exhibits (Continued)
Acknowledgments vii

The authors acknowledge the many individuals at Abt Associates and Abt SRBI who contributed 

to this report. Within Abt Associates, Judith Feins advised on numerous methodological and 

analytical questions and provided expert technical review, Nancy McGarry supported the analysis 

with programming and data documentation, and Missy Robinson provided desktop publishing 

and production support. Abt SRBI was responsible for the survey data collection, including 

interviewing more than 700 individuals across the country who in 2005 owned properties 

damaged by Hurricanes Katrina or Rita. Locating these individuals, many of whom had moved 

several times since the storms, was extremely challenging, and Abt SRBI made tireless efforts 

to achieve the highest response rate possible for the survey. The Abt SRBI team was led by Jodi 

Walton, with support from Ricki Jarmon and Jon Schmalz and a large team of skilled telephone 

and field interviewers.

The authors also thank several U.S. Department of Housing and Urban Development (HUD) 

staff. Paul Joice of HUD’s Office of Policy Development and Research (PD&R) served as 

Government Technical Monitor, assisting and supporting the Abt team at all stages of the project. 

In addition, several PD&R staff provided critical review and assistance over the life of the 

project: Todd Richardson, Dana Bres, Carol Star, Mark Shroder, Kevin Neary, and Rob Renner. 

HUD’s Office of Community Planning and Development (CPD) also played an important role 

in supporting the project and offered key programmatic insights. The CPD staff who provided 

comments and input for this report include Jessie Kome, Scott Davis, Jan Opper, and Mark 

Mitchell.

The study would not have been possible without assistance from the state agencies administering 

the Community Development Block Grant (CDBG) disaster assistance programs in Louisiana, 

Mississippi, and Texas. Staff from these agencies provided background information on their 

CDBG-funded programs at the start of the project and made property-level data on CDBG 

recipients available to HUD for use in this study. Particular thanks is due to David Bowman of the 

Louisiana Recovery Authority, Daron Wilson of the Mississippi Development Authority, and Kelly 

Crawford of the Texas Department of Housing and Community Affairs.

Finally, the authors thank the 722 hurricane survivors who shared their time to explain their 

experiences with rebuilding in the wake of Hurricanes Katrina and Rita. Their generosity and 

willingness to revisit a very difficult time in their lives made possible the findings of this report. 

Their insights will play an important role in informing future research and policy on disaster 

assistance.

ACKNOWLEDGMENTS
Executive Summary viii

EXECUTIVE SUMMARY

ABSTRACT OF FINDINGS

This report is the second of two prepared for a study 

of the uses of Community Development Block Grant 

(CDBG) disaster assistance funds for housing recovery 

after Hurricanes Katrina and Rita in Louisiana, 

Mississippi, and Texas. The report presents the 

findings of a survey of 722 owners of owner-occupied 

and small rental residential properties that suffered 

major or severe damage from the 2005 hurricanes 

and were located on blocks significantly affected 

by the hurricanes. The survey sample includes 345 

owners who received CDBG funds for rebuilding 

or as compensation for hurricane damage and 377 

owners who did not receive CDBG funds. The survey 

provides owner-reported information on the condition 

of these properties prior to the hurricanes and as of 

early 2011, on the type and extent of damage caused 

by the hurricanes, on changes in ownership since 

2005, and on the reasons why some owners rebuilt 

and others did not. The information presented in this 

report supplements information provided in the Phase 

I report, which analyzed the effects of CDBG receipt 

on rebuilding for a much larger sample of properties 

but did not include the information on owner 

characteristics, property characteristics, and sources of 

funding (other than CDBG).1

INTRODUCTION TO 

THE STUDY

Between August 29 and October 24, 2005, Hurricanes 

Katrina, Rita, and Wilma caused massive devastation 

in the Gulf Coast region, damaging more than 1 

million housing units across five states. In response to 

1 Turnham, et al., Housing Recovery on the Gulf Coast, Phase I: Results of Windshield 

Observations in Louisiana, Mississippi, and Texas (HUD, 2010): http://www.huduser.org/portal/publications/commdevl/hsgrec_gulfcoast1.html. This document 

is referred to as the Phase I report from this point on.

the widespread destruction caused by the hurricanes, 

Congress appropriated $19.7 billion in supplemental 

Community Development Block Grant (CDBG) 

program funds for Gulf Coast disaster recovery. Three 

states—Louisiana, Mississippi, and Texas—received 99 

percent of the supplemental CDBG funds. The states 

used the funds, in large part, to compensate property 

owners for their losses and to assist with rebuilding 

through such programs as Road Home in Louisiana, 

the Mississippi Development Authority (MDA) 

Homeowner Assistance Program in Mississippi, and the 

Homeowner Assistance Program in Texas.

In Texas, the CDBG program model was a 

rehabilitation model, in which the state made payments 

to contractors to rebuild the homes rather than making 

direct awards to individual property owners. Louisiana 

and Mississippi implemented compensation models, in 

which the state made grants to owners directly and 

owners were responsible for paying for and managing 

their own rebuilding work. There were also provisions 

in Louisiana and Mississippi for compensating owners 

who chose to sell their homes rather than try to rebuild.

The purpose of this study, Housing Recovery on the 

Gulf Coast, Phase II, is to assess the state of housing 

recovery in the states hardest hit by Hurricanes Katrina 

and Rita—Louisiana, Mississippi, and Texas—and 

to examine the role of supplemental CDBG funds in 

supporting that recovery. The study’s main research 

questions are these:

1. What is the overall state of housing recovery in 

areas most affected by Hurricanes Katrina and Rita?

2. What factors have affected the extent of housing 

recovery?
ix

3. What role have the CDBG-funded programs played 

in housing recovery?

4. How do housing outcomes and owner experiences 

differ by state and CDBG program model?

The study has three main data collection components:

Windshield observations of a sample of hurricanedamaged homes in Louisiana, Mississippi, and Texas to 

provide estimates of housing recovery.

•	Collection of administrative data from the CDBG 

programs in each of the three states.

•	A telephone survey of owners of hurricanedamaged homes to discuss their decisions about 

whether to rebuild after the storms.

This report is the second of two reports prepared 

for the study. It focuses on the efforts of owners of 

damaged housing to rebuild after the hurricanes, 

drawing primarily on information gathered through the 

telephone survey. The report presents new information 

on the rebuilding status of properties as of early 2011 

and analyzes the factors affecting owners’ decisions 

about whether to sell their storm-damaged homes or to 

stay and rebuild.

SAMPLING AND DATA 

COLLECTION APPROACH

The findings in this report are based primarily on 

analysis of data from the property owner survey with a 

sample of 722 owners of residential properties damaged 

by Hurricanes Katrina and Rita. The survey was 

conducted by telephone between late September 2010 

and early May 2011 by trained interviewers from Abt 

SRBI Inc., a national survey firm that is a subsidiary 

of Abt Associates Inc. The survey took about 30 

minutes to complete and collected detailed information 

from owners on: the pre-hurricane characteristics of 

their properties, including tenure, condition, and 

estimated value; the damage caused by the hurricanes; 

financial assistance and other funding used for repair 

and rebuilding activities; uses of CDBG assistance; 

reasons for not rebuilding; and current housing and 

neighborhood conditions.

The survey focused on the 2005 owners of hurricanedamaged properties, about one-fifth of whom no 

longer owned the property at the time of the survey. 

The starting point for the survey was a sample of 1,400 

properties that had suffered major or severe damage 

from Hurricanes Katrina and Rita as assessed by the 

Federal Emergency Management Agency (FEMA) and 

that were located on census blocks where at least three 

properties had suffered major or severe storm damage 

(known as significantly affected blocks or [SABs]).2

Nearly all the properties selected for the survey sample 

were part of the 2010 windshield observation sample 

that was the focus of the first phase of this study.3 The 

owner survey sample was designed to provide unbiased 

estimates for the population of 2005 owners of 

residential properties that were located on significantly 

affected blocks in Louisiana, Mississippi, and Texas that 

had suffered major or severe storm damage.

The survey sample was also selected to produce a 

sufficient number of responses from key subgroups 

of interest—such as owners of rental properties and 

homeowners, owners who received CDBG assistance 

and those who did not, and owners of properties 

that were rebuilt and not rebuilt—to permit nuanced 

analysis of rebuilding efforts and the effects of 

CDBG funding in each state. Unlike the windshield 

observation sample, the owner survey sample was 

not intended to produce accurate estimates for lower 

levels of geography because the sample size was not 

sufficiently large.

The survey team faced a number of hurdles to 

identifying, locating, and interviewing the 2005 

owners of storm-damaged properties 5 years after 

the hurricanes. Many 2005 owners could not be 

2 Properties were assessed for damage by FEMA following a request by the owner 

for FEMA assistance. Based on the FEMA assessments, the properties were 

determined to have severe, major, minor, or no damage. In this report, we assume 

that all properties assessed by FEMA were affected by the hurricanes, even if they 

received an assessment of no damage.

3 To increase the owner survey sample size in Texas we included some properties 

that were not included in windshield observations in 2010.

Executive Summary (Continued)
x

located through local tax assessor data or databases 

maintained by private vendors; others were reluctant 

to participate in the survey, citing fatigue with 

discussing the hurricanes and continuing hardship 

and disappointment in their rebuilding efforts. 

The survey team took many months to identify and 

locate owners and tried a number of ways to gain the 

owners’ cooperation. In the end, the survey completed 

interviews with 722 of 1,400 potential respondents (a 

52 percent response rate).

To ensure that this unusually low response rate did not 

affect the survey findings, we created statistical weights 

to adjust for bias in the sample. We also weighted the 

survey data to provide more accurate representation of 

the owner population, by state. The findings presented 

in this report represent unbiased estimates for the 2005 

owners of residential properties assessed by FEMA 

following the 2005 hurricanes as having major or severe 

storm damage and located on significantly affected blocks

in Louisiana, Mississippi, and Texas. The estimates 

are not representative of all owners of properties on 

significantly affected blocks or all owners of hurricanedamaged properties in general.

STUDY FINDINGS

This report builds on the 2010 analysis of windshield 

observations of hurricane-damaged properties, using 

a survey of a sample of people who owned these 

properties at the time of the storms. The survey 

responses provide information on rebuilding work 

to date and remaining repair needs, the reasons why 

owners chose to rebuild or not, and the sources of 

funding they used to repair or rebuild their homes.

Repair Needs and Rebuilding

In 2011, more than 5 years after the storms, the 

housing stock has not fully recovered from the 

effects of Hurricanes Katrina and Rita, according to 

owners of storm-damaged properties on significantly 

affected blocks. While most of these owners thought 

their properties were in good condition before the 

2005 hurricanes, ratings of property conditions were 

substantially lower as of early 2011. More than 90 

percent of owners in Louisiana and Mississippi and 

85 percent of owners in Texas rated their homes as 

having been in excellent or good condition before the 

hurricanes. Nearly 6 years later, among owners who still 

owned their properties, the proportion who rated their 

properties to be in excellent or good condition ranged 

from 75 percent in Louisiana to 71 percent in Texas.4

The deterioration in the condition of the housing stock 

between late summer 2005 and early 2011 is the result 

of a combination of factors, including the pre-storm 

construction quality of affected properties, the severity 

of storm damage, and the progress of rebuilding efforts 

to date. The decisions and actions related to rebuilding 

efforts are complex. Among all owners, including those 

who had sold their properties after the hurricanes, 77 

percent reported that they had done some rebuilding 

work to address hurricane damage. In most cases, the 

rebuilding consisted of repairs to an existing structure 

rather than construction of a completely new home. 

Relatively little of the repair and rebuilding work 

involved elevating the property. Across the three 

states, less than 10 percent of owners of properties 

with major or severe storm damage on SABs had 

completed elevation work on their properties as of early 

2011, a finding that is consistent with the windshield 

observations from 2010.

Rebuilding efforts are also related to owners’ decisions 

about whether to sell their properties after the 

hurricanes or to stay and rebuild. Most owners (82 

percent) retained ownership of their homes, and 

86 percent of this group reported rebuilding. The 

remaining 18 percent of the owners sold the property 

or ceased owning for other reasons (usually within 2 

years of the hurricanes), and only 34 percent of this 

group reported doing any rebuilding.

4 Although the owner survey did not collect information on the 2011 condition 

of properties that had changed hands since the hurricanes, evidence from the 

windshield observations conducted for the first phase of the study suggests that 

properties that changed ownership were less likely to be in good condition in 

2011 than those retained by the same owner. See Turnham, et al., 2010.

Executive Summary (Continued)
xi

The survey findings suggest that, as of early 2011, 

little additional repair and rebuilding work was actively 

under way or still planned for the future. Most owners 

who did any rebuilding began the work in 2005 and 

2006 and, if they completed rebuilding, finished it 

by 2008. As of early 2011, not many 2005 owners 

reported that they were still actively rebuilding their 

properties, although properties that were sold may be 

undergoing repairs or rebuilding by their new owners. 

Among continuing owners who had not done any 

rebuilding as of 2011, about two-thirds (63 percent) 

reported that they did not intend to rebuild or did not 

know if they planned to rebuild.

For owners who did not rebuild, the most commonly 

cited reason was not having sufficient funds to pay 

for the work, including: not having enough money on 

hand to do the work, not being able to get a loan to 

do the work, or waiting for a grant or other kind of 

financial assistance to get the work done. More than 

one-third of owners who did not rebuild cited the 

inability to obtain flood insurance as an important 

reason for not rebuilding. Among those who did not 

cite funding gaps as a reason for not rebuilding, nearly 

one-half stated that their lack of rebuilding was delayed 

because they were considering selling.

A significant proportion of the owner survey 

sample had relocated to a new neighborhood since 

the hurricanes and had not returned to their old 

neighborhood. About one-fourth of the owner survey 

sample reported that as of 2011 they were no longer 

living in the house that was damaged in the storm. This 

group includes owners who sold their properties as 

well as people who retained ownership of the damaged 

property but were living elsewhere. About 60 percent, 

or two-thirds, of those who had relocated lived in a 

different house than they owned, but the rest were 

renting (18 percent), living with family or friends (18 

percent), or in some other type of housing situation (3 

percent).

Despite this displacement, the evidence suggests 

that those who moved may be better off in terms of 

neighborhood satisfaction than those who stayed. 

Survey respondents who had moved were significantly 

more likely to report being very satisfied with their 

new neighborhood, compared with those who had 

stayed where they were in 2005. Owners in new 

neighborhoods were also significantly more likely to 

describe those neighborhoods as very safe during the 

day and at night. Given these views, it is not surprising 

that two-thirds of owners in new neighborhoods had no 

plans to move back.

Among owners who stayed where they lived in 2005, 

the people living on blocks that suffered more extensive 

hurricane damage in 2005 were significantly less likely 

to be satisfied with the neighborhood in early 2011 

than people living on blocks where the hurricane 

damage was less extensive.

Owner and Property Factors Affecting Rates of 

Rebuilding

We analyzed the factors affecting rebuilding using a 

measure of rebuilding that was based on the owner 

ratings of the condition of their properties as of early 

2011. A property was considered rebuilt as of 2011 

if the owner rated its condition as excellent or good. 

Because all properties in the survey sample were 

assumed to have had hurricane damage in 2005, a 

property in excellent or good condition as of 2011 is 

assumed to have been substantially repaired or rebuilt.

This measure of rebuilding is similar to the one used 

in the Phase I report, which was based on windshield 

observations made in 2010, but uses more recent 

information and takes advantage of the owners’ more 

detailed knowledge of the condition and repair needs 

of the property. However, the owner-based rebuilding 

measure is available only for those properties that had 

the same owner in both 2011 and 2005, which is 82 

percent of the survey sample.

Overall, three-fourths of properties still owned by 

the 2005 owner have been substantially rebuilt. Only 

64 percent of continuing owners reported that their 

repair or rebuilding work was complete, however. This 

Executive Summary (Continued)
xii

inconsistency suggests that although some owners had 

returned their properties to a habitable standard, the 

owners still thought that more work needed to be done. 

Rates of rebuilding were not significantly different 

across the three states in the study.

We used cross-tabulation and multivariate analysis to 

explore the relationships between rates of rebuilding 

and (1) pre-storm property characteristics (tenure, 

presence of a mortgage, presence of insurance, and 

owner-reported property value), (2) type and extent of 

hurricane damage, and (3) owner and neighborhood 

characteristics.

The multivariate analysis did not find any statistically 

significant relationship between individual owner 

characteristics and rebuilding. However, it did 

identify significant associations between property 

and neighborhood characteristics and rebuilding. 

The presence of property insurance and the extent 

of hurricane damage are the strongest predictors of 

rebuilding. The specific findings follow:

•	 Properties that had been insured before the 

hurricanes were 37 percent more likely to have been 

rebuilt than uninsured properties.

•	 Properties that had had mortgages at the time 

of the hurricanes were 13 percent less likely to 

have been rebuilt, on average, holding insurance 

constant.

•	 Properties that had experienced flood damage 

were 16 percent less likely to have been rebuilt as 

of 2011 than properties that had not experienced 

flood damage.

•	 Properties whose hurricane damage had been so 

extensive that the property had been leveled or 

demolished, or had had to be condemned, were 

39 percent less likely to have been rebuilt than 

properties with less extensive damage.

•	A 10 percent increase in the proportion of 

neighborhood residents with a high school 

education is associated with a 7 percent increase in 

the probability of rebuilding.

•	A 10 percent increase in the neighborhood owneroccupancy rate is associated with a 4 percent 

increase in the likelihood of rebuilding.

This analysis reinforces the finding from the Phase I 

report that the severity of damage is a strong negative 

predictor of rebuilding. At the same time, it shows 

that the presence of insurance before the hurricanes 

was also an important factor in rebuilding. (The Phase 

I report did not collect information on insurance.) 

Unlike the Phase I report, this analysis finds that 

most neighborhood characteristics are not significant 

factors in rebuilding. Taking into account individual 

factors available for this analysis, such as the presence 

of insurance, reduces the significance of neighborhood 

factors, such as the median house value, as a predictor 

of rebuilding.

The analysis suggests that to the people making 

rebuilding decisions, the average neighborhood 

characteristics are not as important as their own 

individual situations—in particular whether they had 

insurance, whether their mortgage was paid off, and 

whether their house was destroyed. Many of these 

individual and property characteristics are correlated 

with neighborhood characteristics, which is why 

neighborhood characteristics were significant in the 

model presented in the Phase I report.

Funding for Rebuilding and CDBG Programs

A critical focus of the owner survey was the exploration 

of CDBG funding, its implementation, and its possible 

effects on rebuilding rates when compared with other 

funding sources. We found that slightly more than onehalf of the homeowners in the owner survey sample, 

across all three states, had received CDBG homeowner 

assistance. Several significant differences in owner and 

property characteristics were found between CDBG 

recipients and non-CDBG homeowners, including 

many findings that are consistent with the intent of the 

original program:

Executive Summary (Continued)
xiii

•	 Properties valued at $300,000 or more by their 

owners before the hurricanes were less likely to have 

received CDBG.

•	 Properties that had experienced flood damage were 

more likely to have received CDBG.

•	Owners of properties who had received CDBG 

assistance were more likely to be African American 

and more likely to be of Hispanic or Latino origin.

•	 Properties with higher levels of assessed damage—

as reported by owners—were more likely to have 

received CDBG awards than properties with lower 

levels of assessed damage.

CDBG recipients in Texas used their funding 

exclusively for rebuilding, because the Texas program 

design required them to. Among homeowners in 

Louisiana and Mississippi who had received CDBG 

rebuilding grants, most (87 percent in Louisiana and 

64 percent in Mississippi) reported using all or part 

of their grants for rebuilding. However, 13 percent 

of Louisiana recipients and 36 percent of Mississippi 

recipients used all or a portion of their grants for 

something other than rebuilding, most commonly to 

purchase furniture, pay for everyday expenses, and pay 

off a mortgage or loan.

CDBG funds were meant to fill gaps in funding 

from other possible sources, including homeowners 

insurance, flood insurance, elevation grants, FEMA’s 

individual assistance program, Small Business 

Administration (SBA) loans, state programs, churches 

or charities, and friends and family. CDBG recipients 

reported receiving about $50,000 more on average 

in total financial assistance (including CDBG) than 

owners who did not receive CDBG funds. CDBG 

recipients generally reported receiving other sources of 

funding in addition to CDBG, especially in Louisiana 

and Mississippi, although in many cases recipients 

received lower amounts from non-CDBG sources than 

owners who did not receive CDBG funds. This finding 

documents the program’s intent to fill funding gaps. 

More than one-third of owners overall (including both 

CDBG recipients and nonrecipients) reported that the 

total of their funding sources was insufficient to meet 

their rebuilding needs. Slightly more than one-half 

of those reporting insufficient funding were able and 

willing to draw on personal funds for rebuilding work.

Rates of rebuilding varied across owners based on 

their access to financial assistance. Two groups of 

homeowners in particular showed notable lags in 

rebuilding: those who had applied for CDBG assistance 

and not received it, and those who reported that they 

had not received sufficient total resources to rebuild, 

and had been either unwilling or unable to use personal 

funds to supplement any assistance received. Among 

homeowners who applied for CDBG assistance but did 

not receive funds, 56 percent of properties were rebuilt 

compared with almost 75 percent of nonapplicants and 

81 percent of CDBG recipients. The estimated rate of 

rebuilding was 46 percent among homeowners who 

reported insufficient funding and who did not, or could 

not, put any of their own funds into rebuilding.

The different CDBG program models within and 

between states were also studied in relation to the 

timeliness of the rebuilding and owner satisfaction 

with the programs. We found that CDBG recipients 

in Texas (rehabilitation model) reported higher rates 

of rebuilding completion than in the other two 

states (compensation model), albeit for far fewer 

properties. The survey data also suggests that the 

physical rebuilding process (as measured by the 

number of months between the start and completion 

of rebuilding) was quicker in Texas under the 

rehabilitation model than under the compensation 

model. Variations in states’ receipt of federal funds 

and their respective grant administration, however, led 

to different overall durations to complete rebuilding 

from time of the storm events. Finally, most survey 

respondents in both Louisiana and Texas were satisfied 

with the program processes, with insufficient sample 

size in Mississippi to analyze for that state.

Executive Summary (Continued)
xiv

Overall Conclusions and Policy Implications

The need for rebuilding assistance after disasters 

will always exist. The supplemental CDBG disaster 

assistance program, mobilized after Hurricanes Katrina 

and Rita, was one of the largest efforts in U.S. history 

to provide property owners with direct rebuilding 

assistance. The findings presented in this report, along 

with the findings from the first phase of the study, 

provide preliminary lessons and policy insights of 

potential use in planning for, and responding to, future 

disasters.

The Purpose of CDBG Disaster Assistance Funds

The most critical policy question with regard to CDBG 

funds and future disaster assistance grants is whether 

these programs work. To the extent that the CDBG 

disaster assistance funds were intended to provide 

supplemental assistance for the repair and rebuilding 

of affected properties, they were successful. The 

funds largely did help owners repair and rebuild their 

properties. As documented in this report, 87 percent 

of recipients in Louisiana and 64 percent of recipients 

in Mississippi reported using the entire grant to 

repair or rebuild the hurricane-damaged property. All 

recipients in Texas used the entire grant for rebuilding, 

by definition of that state’s program model. Even when 

recipients were given options for the grant’s use, as was 

the case in Louisiana and Mississippi, most owners still 

chose to rebuild.

Whether CDBG receipt actually increased the rate 

of rebuilding among recipients as compared with 

nonrecipients is another question. Those recipients 

who opted to sell their homes either to the state or to 

another type of buyer left properties that were observed 

in 2010 to have notably lower levels of rebuilding, 

habitability, and occupancy. In these cases, CDBG 

funds did not increase repair and rebuilding, although 

they may have provided needed financial assistance for 

the recipients to reestablish themselves in new homes. 

The increased housing and neighborhood satisfaction 

reported by this group of movers is a positive outcome, 

although not related to rebuilding.

Excluding these sold properties, the Phase I report 

found that CDBG-recipient properties were nearly 

twice as likely to be rebuilt and about twice as likely to 

be reoccupied as properties without CDBG assistance. 

Although not as conclusive, this report, based on 

owner-reported information, corroborates that finding. 

It also suggests that a subset of the non-CDBG 

recipients (specifically, those who applied for CDBG 

funds and were not awarded) reported rebuilding 

at even lower rates than owners who never applied 

(presumably because they had other resources). In sum, 

additional funding helps, and CDBG funding appears 

to have helped in many ways.

The Amount of CDBG Disaster Assistance Awards and 

Incremental Rebuilding

Although the availability of CDBG awards may have 

played a role in many owners’ decision and ability to 

rebuild, they were certainly not the only source of 

funds used—nor were they intended to be. Numerous 

other sources of funds were used, including other 

federal grants, loans, and insurance. Yet the amount of 

funds coming from a CDBG award to supplement these 

other sources is an important policy issue. Several issues 

related to other sources of funds (public and private), 

their estimated dollar value payouts, and the constraints 

on individual CDBG awards must be considered.

First, combining different types of public funds was 

often not permitted (for example, CDBG receipt 

counted against SBA loans). However, most owners, 

including CDBG recipients, reported needing 

additional funds beyond their financial assistance 

sources to meet their repair needs. The interrelationship 

of multiple public funding sources could be explored 

and clarified—or changed—in future disaster assistance.

The effect of combining funding sources for rebuilding 

is another finding of interest. The Phase I report 

published in December 2010 did not find conclusive 

evidence of a relationship between the total amount 

of assistance (including CDBG) relative to the 

assessed damage and rebuilding activity: properties, 

for which the total amount of assistance covered 

Executive Summary (Continued)
xv

100 percent of the damage estimate, showed higher 

levels of rebuilding, habitability, and occupancy, but 

only occasionally were these differences statistically 

significant. The current Phase II report finds that 

CDBG recipients were more likely to self-report 

financial assistance that matched or exceeded their 

(owner-reported) assessed damage than nonrecipients, 

suggesting that the CDBG program did help address 

the funding gap for many owners. Owner-reported 

damage assessments did not necessarily match FEMA 

assessments, because owners often relied on other 

assessment sources (especially homeowner’s insurance 

assessments) or did not readily know their properties’ 

FEMA-assessed values. To better understand the 

funding gap facing households, reliable damage 

assessments and a full accounting of grantees’ funding 

sources could be more clearly detailed as requirements 

in future assistance.

A third notable issue is the establishment of a 

maximum grant value. In both Louisiana and 

Mississippi, CDBG grants were capped at $150,000. 

In Texas, the individual program awards ranged from 

$40,000 to $100,000. The CDBG grants were designed 

to fill the gaps between other financial assistance and 

repair costs as defined by damage assessments. Yet there 

are many reasons why the maximum grant value could 

be insufficient; for example, damage assessments might 

exceed the cap, or actual repair costs might change after 

the assessments because of swings in local construction 

costs. An understanding of actual damages and repair 

costs may provide some context to policymakers on 

how to set those caps.

Other restrictions on the maximum grant values were 

also noted and should be considered in future recovery 

funding. In particular, the reduction in CDBG grant 

amounts to owners without homeowner’s insurance 

(as happened in one program) penalized specific 

households and added barriers to the overall goal 

of rebuilding. In all cases, maximum grant values 

are determined based on the desire to maximize the 

number of grantees while providing adequate resources 

for each grantee. Careful modeling of how this is 

implemented should play a role in recovery funding.

CDBG Program Models and Implementation

The different models in each state for CDBG program 

administration provide an opportunity to observe the 

relative efficiency and effectiveness of each program. 

However, the regional differences in damage types, 

housing stocks, and numbers of grant awards makes 

comparison across the states very difficult. The survey 

findings presented in this report, based on a very small 

sample of homeowners in each state, suggest that 

Texas’s rehabilitation model (payment to contractors 

rather than direct awards to individual property 

owners) resulted in a more complete application of 

funds to rebuilding uses and no significant difference 

in the amount of time to complete rebuilding—an ideal 

outcome for a policy initiative intended only to repair 

or rebuild damaged properties. The effectiveness of 

Texas’s program model, however, may be predicated on 

its small program size and may not be easily brought to 

scale.

The compensation models in Louisiana and Mississippi 

allowed owners to sell properties and not rebuild, as 

well as to use the funds for other needs—a positive 

outcome for a policy intended to assist disaster 

victims and to allow some amount of autonomy in 

decisionmaking. This flexibility was conveyed through 

the different explicit program options in the two 

states. Owners who chose not to rebuild and instead 

to move away reported high levels of satisfaction with 

their current neighborhoods, an important outcome, 

even though it does not contribute to local rebuilding 

efforts.

Among those who chose to keep their homes, some 

owners took advantage of the local flexibility to 

use their CDBG funds for activities other than the 

rebuilding of their properties. States could integrate 

clearer communication and enforcement of penalties 

for noncompliance into program designs, if rebuilding 

is the sole or foremost desired outcome. To the extent 

possible, federal agencies might also provide guidance 

to states on the requirement terms and enforcement 

strategies for these flexible options.

Executive Summary (Continued)
Chapter 1: Introduction 1

Between August 29 and October 24, 2005, 

Hurricanes Katrina, Rita, and Wilma caused 

massive devastation in the Gulf Coast region, 

damaging more than 1 million housing 

units across five states. The first storm was Hurricane 

Katrina, which hit New Orleans on August 29, 2005 

and was the costliest natural disaster in U.S. history, 

inflicting most of its damage in Louisiana, Mississippi, 

and Alabama. Less than 1 month later, on September 

24, Hurricane Rita made landfall. Its accompanying 

storm surge caused extensive damage mainly in east 

Texas and western Louisiana, although it also reflooded 

portions of already devastated New Orleans. The 

last storm of that record-breaking hurricane season, 

Hurricane Wilma, hit the United States on October 24, 

2005.

In response to the widespread destruction caused 

by the hurricanes, Congress appropriated $19.7 

billion in supplemental Community Development 

Block Grant (CDBG) program funds for Gulf Coast 

disaster recovery.5

 The three states hardest hit by 

Hurricanes Katrina and Rita—Louisiana, Mississippi, 

and Texas—received 99 percent of the supplemental 

CDBG funds ($19.4 billion). The remaining funds 

were allocated to Florida and Alabama. Allocations 

were based primarily on the number of housing units 

in the state that sustained major or severe damage, as 

assessed by the Federal Emergency Management Agency 

(FEMA). Louisiana received about 68 percent of total 

supplemental CDBG funds ($13.4 billion), Mississippi 

received 28 percent ($5.5 billion), and Texas received 

3 percent ($503 million). In comparison, the regular 

5 Created in 1974, CDBG is one of the oldest programs administered by the 

Department of Housing and Urban Development (HUD), providing funding to 

states, cities, and counties nationwide to support neighborhood revitalization, 

housing rehabilitation, and economic development. With its network of state 

and municipal grantees and subgrantees, CDBG offers a convenient way for the 

federal government to disburse large amounts of funds to local areas in the wake 

of large-scale disasters.

1. INTRODUCTION

CDBG allocations for fiscal year 2005 were $69.5 

million for Louisiana, $39.2 million for Mississippi, 

and $286.4 million for Texas.

The purpose of this study is to assess the state of 

housing recovery in Louisiana, Mississippi, and Texas, 

to evaluate the role that CDBG funding has played in 

the housing recovery in those states, and to identify 

the factors affecting owners’ willingness and ability 

to rebuild or repair their storm-damaged properties 

with and without CDBG funding. The study focuses 

on recovery from Hurricanes Katrina and Rita, while 

recognizing that other hurricanes—especially Hurricane 

Ike in Texas—later created substantial further housing 

damage. The study focuses on a sample of owneroccupied and small rental residential properties (most 

of which suffered major or severe damage from the 

hurricanes) on significantly affected blocks. The study 

findings are intended to help the federal government 

understand and design effective recovery assistance 

programs for future disasters.

The study has three main data collection components: 

windshield observations of a sample of storm-damaged 

properties in Louisiana, Mississippi, and Texas to assess 

their current condition, administrative data from the 

CDBG disaster recovery programs in each of the three 

states to understand the relationship between assistance 

and rebuilding, and telephone interviews with a sample 

of the people whose properties were damaged by 

the 2005 hurricanes to discuss their decisions about 

whether to rebuild.

This report, Phase II, is the second of two reports 

prepared for the study. It details the results of the 

telephone interviews with property owners and draws 

on the prior analysis of windshield observation findings 

and administrative data.6

6 See the Phase I report: Turnham, et al., 2010.
Chapter 1: Introduction 2

This chapter provides background on the use of 

the supplemental CDBG disaster recovery funds in 

Louisiana, Mississippi, and Texas. It also summarizes 

the key findings of the study’s first phase, restates the 

research questions addressed in each phase of the study, 

and describes the content and organization of the 

current report.

1.1 BACKGROUND

The purpose of the supplemental CDBG funding 

was to support disaster relief, long-term recovery, 

and restoration of infrastructure in the areas most 

affected by the 2005 hurricanes.7 Within this broad 

mandate, the states were given considerable flexibility 

in determining how to use the funds. All three states in 

the study designated most of their supplemental CDBG 

funds to housing recovery (directly and indirectly), 

mostly to help homeowners rebuild or repair their 

homes. For homeowners, CDBG funds were generally 

intended to fill the gap between the cost of repairing 

or rebuilding the damaged unit and the funds available 

to the owner from private or hazard insurance, FEMA 

grants, and Small Business Administration (SBA) loans.

From August 2005 to February 2006, FEMA conducted 

damage assessments of residential properties affected 

by Hurricanes Katrina, Rita, and Wilma.8 The U.S. 

Department of Housing and Urban Development 

(HUD) used the results of the FEMA assessments, 

largely based on direct inspection by FEMA contract 

inspectors, to create four categories of hurricane 

damage: no damage, minor, major, and severe. 

Although the criteria for categorization are somewhat 

complex, minor implies assessed damage of less than 

$5,200, major implies assessed damage of at least 

$5,200 but less than $30,000, and severe implies 

assessed damage of $30,000 or more.9

7 The first appropriation was made on December 30, 2005, when President 

Bush signed the FY 2006 Defense Appropriation Act providing $11.5 billion 

in CDBG disaster supplemental funding to the areas impacted by Hurricanes 

Katrina, Rita, and Wilma. A second supplemental appropriation of $5.2 billion in 

CDBG funds was made in June 2006. A third appropriation was for $3 billion.

8 FEMA conducted damage assessments on all housing units whose occupants 

registered for FEMA housing assistance after the hurricanes.

9 For more detail on damage categories, see Richardson, Todd and Robert Renner, 

“Geographic Information Systems Supporting Disaster and Recovery,” Cityscape: 

A Journal of Policy Development and Research, 9:1, 2007.

Louisiana had both the largest number of units 

affected by the storms and the most severe damage. 

As shown in exhibit 1-1, 40 percent of the damaged 

units in Louisiana were in the major or severe damage 

categories, compared with 28 percent in Mississippi 

and 9 percent in Texas. Within the three states, damage 

from the storms was concentrated geographically. In 

Louisiana, 89 percent of the homes that suffered major 

or severe damage were located in Orleans Parish (which 

includes New Orleans) or in one of the four parishes 

that border Orleans Parish. In Mississippi, damage 

was most extensive in the three coastal counties: 

Jackson, Harrison, and Hancock. Damage in Texas 

was concentrated in the eastern part of the state, with 

90 percent of the units with major or severe damage 

located in eight counties near the Louisiana border.

Within the universe of storm-damaged housing units 

in Louisiana, Mississippi, and Texas, this study focuses 

on particular geographic areas and housing types. First, 

the study focuses on those parts of the states with 

high concentrations of residential damage from the 

2005 hurricanes. As a way of identifying areas with 

high levels of housing damage, HUD developed the 

concept of the significantly affected block (SAB). An 

SAB is a U.S. Census-defined block (which often, but 

not always, corresponds to a standard city block) on 

which three or more housing units suffered major or 

severe hurricane damage as assessed by FEMA. This 

study focuses on a sample of 230 SABs in Louisiana, 

Mississippi, and Texas, selected to be representative 

of all SABs across the three states. The study also 

primarily targets properties with major and severe 

damage, with a few exceptions as noted in section 2.2.

In addition to focusing on areas with high levels of 

housing damage, this study limits its focus to two types 

of housing: housing that was owner occupied at the 

time of the hurricanes, including single-family and 

multifamily owner-occupied properties, and housing 

that had one to four rental units at the time of the 

hurricanes, also known as small rental properties. 

Rental properties with five or more units are not part

of this study.
Chapter 1: Introduction 3

Exhibit 1-1. Housing Unit Damage Estimates by State

Level of Damage Louisiana Mississippi Texas Overall

Minor 310,512 (60%) 158,998 (72%) 127,807 (91%) 597,317 (68%)

Major 98,086 (19%) 45,776 (21%) 10,523 (8%) 154,385 (18%)

Severe 106,651 (21%) 15,610 (7%) 1,580 (1%) 123,841 (14%)

Total assessed units 515,249 220,384 139,910 875,543

Sources: U.S. Department of Housing and Urban Development, Current Housing Unit Damage Estimates, February 12, 2006

The study’s focus on owner-occupied properties and 

small rental properties reflects how the states chose to 

use most of their CDBG disaster assistance funds. All 

three states in the study funded large disaster assistance 

programs for homeowners. In addition, Louisiana and 

Mississippi created separate programs for owners of 

small rental properties, although, with roughly $700 

million in awards across the two states, the small rental 

programs are dwarfed by the homeowner assistance 

programs in those states, which have made awards of 

about $10.7 billion.10 Support for multifamily housing 

redevelopment generally came from different funding 

sources, and this housing type is not included in this 

study.

Exhibit 1-2 summarizes the key program elements of 

the CDBG-funded homeowner programs in Louisiana, 

Mississippi, and Texas and the small rental programs 

in Louisiana and Mississippi. (Texas did not create a 

program specific to owners of small rental properties.) 

At the time of this report, none of the programs are 

accepting new applications, but they continue to 

process applications and appeals and distribute funds.

States applied similar formulae to calculate the amount 

of assistance the homeowner was entitled to, although, 

as shown in the exhibit, the maximum grant amount 

varied. The states also differed in how they provided 

the assistance to homeowners. In Louisiana and Mississippi, homeowners received CDBG grants directly as a 

lump sum, for use either in rebuilding their homes or 

10 CDBG administrative data, April 2011.

to cover uncompensated losses. This method of providing assistance is known as the compensation model.11

Applicants to Louisiana’s The Road Home Homeowner 

Program were required to choose one of three options, 

which affected the calculation and amount of the 

compensation as well as whether they were required to 

rebuild:

•	Option 1: Remain in the home.

•	Option 2: Sell to the state and purchase another 

home in the state.

•	Option 3: Sell to the state and become a renter in 

Louisiana or move out of state.

As a condition of accepting the grant, owners who 

chose Option 1 agreed to covenants on the property. 

These covenants require the property owner to use 

the house as a primary residence within 3 years from 

the date of closing, to maintain hazard insurance 

on the home (as well as flood insurance if the home 

was located in a flood plain), to comply with base 

flood elevations adopted by local government, and 

to conform with local building codes in conducting 

rebuilding or repair. Owners who do not meet these 

requirements within the 3-year period of the covenants 

can apply for up to two 1-year extensions. Grant 

recipients who do not meet the terms of the covenants 

may be required to repay the entire amount of the 

grant.

11 Louisiana initially paid homeowners in increments as they produced evidence 

of rebuilding, but this aspect of the program was dropped and the majority of 

CDBG recipients have been awarded a lump sum payment.
Chapter 1: Introduction 4

Exhibit 1-2. Summary of CDBG-Funded Homeowner Programs

Program 

Model Eligibility Criteria Form ofAssistance

Maximum Amount of 

Assistance

Closings 

to Date

CompensationRehabilitationOwner-occupant at time of hurricaneOwner incomeSpecific countiesMajor or severe damageFlood damage onlyGrantLoan

Homeowner Programs

Louisiana The 

Road Home 

Homeowner 

Program √ √ √ √

Up to $150k total; basic 

compensation grant, $50k for 

additional compensation grant 

(low-income homeowners), 

$20–30k for elevation 

incentive

128,255

Mississippi 

Homeowner 

Assistance 

Program

√ √ √ √ √ √ √

Up to $150k for Phase I plus 

$30k for elevation, $100k for 

Phase II plus $30k for elevation, $50–$100k for Phase III

27,751

Texas COG 

Programs √ √ √ √ √ √ √ $65k–$100k, varies by COG 358

Texas 

Homeowner 

Assistance 

Program

√ √ √ √ √ √ √

$60k–$75k 1,850

Texas Sabine 

Pass 

Restoration 

Program

√ √ √ √ √ √

Up to $40k for rebuilding, plus 

$30k for elevation and $15k 

for accessibility

61

Rental Property Programs

Louisiana 

Small Rental 

Property 

Program

√ √ √ √

Varies, up to 100% of repair 

cost

4,718

Mississippi 

Small Rental 

Assistance 

Program

√ √ √ √ √

Up to $30k per unit for a 4BR 

unit, up to $120k total

3,907a

CDBG = Community Development Block Grant. COG = Council of Government.

a Units under construction or completed construction, not closings.

Sources: Louisiana—The Road Home Small Rental Property Program Incentive Operations Status Report April 25, 2011 (based on 

commitment letters and amount committed and obligated to applicants active in the Constructive Management Initiative Option), 

CDBG administrative data, April 2011; Mississippi—CDBG administrative data, May 2, 2011; Texas—CDBG administrative data, March 2010 

and April 2011
Chapter 1: Introduction 5

Mississippi’s Homeowner Assistance Program (HAP) 

for homeowners had three phases:

•	 Phase 1 targeted homeowners living outside the 

established flood zones who had homeowners 

insurance at the time of the storm.

•	 Phase 2 was designed for homeowners not eligible 

for Phase 1. Applicants were not required to have 

carried homeowners insurance, and their homes 

could have been located inside or outside the 100-

year flood plain.12

•	 Phase 3 was designed for Phase 1 and Phase 2 

grant applicants who no longer own their damaged 

residence, have an uncompensated loss, and who 

have not been able to attach the required covenants 

to the damaged property.

Properties that sustained only wind damage from the 

hurricane (no flood damage) were not eligible for 

assistance under any phase of Mississippi’s Homeowner 

Assistance Program.

In contrast to Mississippi and Louisiana, Texas followed 

a rehabilitation model, in which CDBG funds were 

explicitly for repairs or reconstruction projects and 

were not provided directly to homeowners. Instead, the 

state agency subcontracted with contractors to repair 

or rebuild owners’ homes on the owners’ behalf and 

paid the contractors using the CDBG grant funds. The 

Texas Department of Housing and Community Affairs 

(TDHCA) used CDBG disaster recovery funding for 

three separate homeowner programs: the Council of 

Government (COG) Programs, HAP, and the Sabine 

Pass Restoration Program.

More detailed descriptions of each state’s CDBGfunded disaster assistance programs can be found in 

appendix A.

12 The 100-year flood plain is the area expected to be inundated only in very 

extreme floods (happening approximately once every 100 years, or with a probability of 1 percent in any year).

1.2 KEY FINDINGS FROM 

THE PHASE I REPORT

Given that this report builds on the previous research 

conducted under this study, it is useful to highlight 

the main findings of the Phase I report as well as 

introduce the key terminology developed for the study. 

The Phase I report provided estimates (as of 2010) of 

the repair needs and occupancy of hurricane-affected 

properties, estimates of the extent of rebuilding that 

had taken place, and a preliminary analysis of the role 

of neighborhood characteristics and CDBG assistance 

in rates of rebuilding. The estimates presented in this 

summary are based on rigorous statistical analysis of 

windshield observation data, FEMA damage assessment 

data, and CDBG administrative data conducted for the 

Phase I report.

Estimates of Current Repair Needs and 

Occupancy of Hurricane-Affected Properties

Based on windshield observations of 3,511 residential 

properties on 230 significantly affected blocks, we 

estimate that as of early 2010, approximately 11 

percent of properties no longer contained a residential 

structure, 15 percent of properties contained a 

residential structure with substantial repair needs, 

and 75 percent of properties contained a residential 

structure with no substantial repair needs. Substantial

repair needs means the property had at least one repair 

need observable from the outside and was not rated by 

the windshield observers as being in either excellent or 

good condition.

While about three-fourths of all properties did not 

have substantial repair needs, this varied by the level 

of assessed damage from the hurricanes, by the tenure 

of the property at the time of the hurricanes, and by 

the location of the property. Properties assessed by 

FEMA to have experienced severe damage in 2005 were 

less likely to have been substantially rebuilt as of early 

2010, as were properties occupied by renters at the time 

of the hurricanes, and properties located in some of 

the hardest hit areas: St. Bernard Parish and the Lower 
Chapter 1: Introduction 6

Ninth Ward in New Orleans, and Hancock County, 

Biloxi, and Waveland and Bay St. Louis in Mississippi.

Using data from the U.S. Postal Service (USPS), we 

estimate that 82 to 89 percent of hurricane-affected 

properties on SABs were occupied as of early 2010.13 

Properties that were owner occupied at the time of the 

hurricanes and properties with no substantial repair 

needs (as assessed by FEMA) were most likely to be 

occupied. However, the data suggest that a nontrivial 

number of households may have been living in housing 

with substantial repair needs.

Estimates of Rebuilding of Hurricane-Affected 

Properties

We developed two measures to analyze rebuilding 

among hurricane-affected properties:

•	Observed rebuilding, which captures ongoing 

construction visible in early 2010, and

•	Inferred rebuilding, which captures the percentage 

of properties that had major or severe hurricane 

damage but as of 2010 had no substantial repair 

needs.

We found that less than 5 percent of properties were 

actively under construction as of early 2010, but that 

approximately 70 percent of properties had been rebuilt 

since the hurricanes. On some blocks and in some 

neighborhoods, however, less than one-half of the 

properties had been rebuilt.

Role of Neighborhood Factors and CDBG 

Assistance in Rebuilding

Analysis of neighborhood-level census data showed 

that neighborhoods with the lowest rates of rebuilding 

as of early 2010 tended to be those with less resources 

before the hurricanes, as indicated by lower house 

values, lower household incomes, and lower rates of 

homeownership.

13 USPS data from December 2009 were used to estimate occupancy rates among 

the properties in the windshield sample. Documentation for the USPS vacancy 

data is available on the HUD User website [http://www.huduser.org/portal/datasets/usps.html]. Users can also download quarterly occupancy data for aggregated 

geographies. USPS vacancy data was available for 3,414 of the 3,511 addresses 

in our analysis sample. The 97 addresses with missing USPS data were dropped 

from analyses using the USPS measure of occupancy.

Analysis of property-level CDBG data found that, after 

adjusting for neighborhood characteristics, properties 

that received CDBG assistance were more likely to be 

rebuilt and reoccupied than properties that did not 

receive CDBG assistance. The exception is the set of 

properties that received grant awards through Options 

2 and 3 of The Road Home program in Louisiana. 

These properties—which were sold by their owners to 

the Louisiana Land Trust—show notably lower levels of 

rebuilding, habitability, and occupancy.

The current report picks up where the Phase I findings 

left off—in particular, learning more about the 2011 

condition of hurricane-affected properties, analyzing 

further repair needs and rebuilding, and understanding 

how the availability and amount of CDBG assistance 

affected property owners’ rebuilding and reoccupancy 

decisions.

1.3 PURPOSE OF THE 

PHASE II REPORT

In contrast to the Phase I report, which documented 

the findings from the windshield observations as well 

as updated administrative data, the Phase II report 

presents the findings from the owner survey.

A limited number of additional findings, with regard 

to the physical condition of the affected homes 

(specifically with regard to interior damage that could 

not be detected in the windshield observations), are 

also provided in this report to supplement the Phase 

I report findings. These findings are based on owner 

reports rather than physical observations. The Phase 

II report primarily provides a richer description of 

the range of possible factors that affected individual 

rebuilding decisions, including the influence of the 

availability and form of CDBG assistance.
Chapter 1: Introduction 7

1.4 PHASE II RESEARCH 

QUESTIONS

The overall study seeks to answer four main research 

questions related to the housing recovery from the 2005 

hurricanes:

1. What is the overall state of housing recovery in 

areas most affected by Hurricanes Katrina and Rita?

2. What factors have affected the extent of housing 

recovery?

3. What role have the CDBG-funded homeowner and 

small rental property programs played in housing 

recovery?

4. How do housing outcomes and owner experiences 

differ by state and CDBG program model?

Phase I of the study focused on research questions 1 

and 2, and to a lesser extent research question 3.

This current phase of the study primarily seeks to 

answer research questions 3 and 4, using detailed 

information collected directly from owners of 

hurricane-damaged properties using a telephone survey. 

We surveyed 722 individuals who, at the time of the 

2005 hurricanes, owned properties that were located 

on significantly affected blocks and that suffered 

major storm damage. Three-fourths of the survey 

respondents were homeowners at the time of the 

hurricanes, and one-fourth were owners of small rental 

properties. The survey collected information on the 

level of interior damage from the hurricanes (damage 

not observable through the windshield observations), 

on the characteristics and value of the properties 

before the hurricanes, and on owner demographic 

characteristics for use in analyzing further the property 

and owner characteristics associated with rebuilding. 

The survey also collected detailed information on the 

experiences of owners applying for and using CDBG 

assistance, the other types of financial assistance used 

for rebuilding, the extent to which they were able 

to complete rebuilding, and the myriad factors that 

affected decisions about whether to rebuild. Using data 

collected through the windshield observations, the 

survey included owners who had and had not rebuilt, 

as well as owners who had and had not received CDBG 

assistance.

The survey data, combined with the windshield 

observations and CDBG administrative data that were 

analyzed for Phase I, are the main basis for the Phase II 

report. (Chapter 2 describes the data sources in some 

detail.) These data enable us to analyze more closely the 

financial and human factors that affect homeowners’ 

decisions about whether to rebuild, as well as how the 

availability of CDBG assistance plays into those factors. 

With survey data from CDBG recipients in all three 

states, we are also able to compare outcomes and owner 

experiences across the different CDBG programs.

1.5 ORGANIZATION OF 

THE PHASE II REPORT

The remainder of this report is organized as follows:

•	Chapter 2 reviews the data sources and collection 

methods, focusing on the sampling approach, 

survey instrument, and survey implementation 

strategies related to the owner survey. It also 

describes nonresponse bias in the telephone 

survey and the approach taken for correcting and 

minimizing this bias.

•	Chapter 3 presents the findings of the owner 

survey with regard to the state of repair needs and 

activity. Although property conditions were largely 

addressed in the Phase I report, answers to the 

research questions about the physical conditions of 

the affected housing stock are supplemented with 

additional findings presented here.

•	Chapter 4 analyses the property and owner 

characteristics that may be associated with repair 

and rebuilding.
Chapter 1: Introduction 8

•	Chapter 5 discusses the role that CDBG grants and 

other sources of funding have played in the housing 

recovery process, as well as differences between 

the program models in terms of the use of CDBG 

funds and owner satisfaction with the program.

The report has four appendices. Appendix A provides 

descriptions of the CDBG disaster assistance programs 

for homeowners and owners of small rental properties 

in Louisiana, Mississippi, and Texas. Appendix B 

provides a summary of the property owner survey. 

Appendix C provides details of the nonresponse bias 

analysis conducted for the property owner survey to 

create sampling weights for the analysis. Appendix D 

presents survey findings regarding rates of application 

to the CDBG program and reasons for not applying 

among owners of hurricane-damaged properties.
Chapter 2: Data Collection and Analysis Methodology 9

2. DATA COLLECTION AND 

ANALYSIS METHODOLOGY

This report focuses on telephone survey 

findings from 722 individuals who, in 

2005, owned owner-occupied and small 

rental properties in Louisiana, Mississippi, 

and Texas that suffered significant (primarily, major

or severe) damage from Hurricanes Katrina or Rita 

and were located on significantly affected blocks. The 

telephone survey findings build on those from the 

windshield observations conducted in early 2010 and 

summarized in the Phase I report.

The main objective of the property owner survey was 

to understand the rebuilding process for owners of 

properties damaged by the hurricanes and the role of 

federal CDBG disaster recovery assistance in owners’ 

rebuilding decisions. The survey was designed to 

provide unbiased information on the experiences of 

property owners affected by the storms, including 

owners who received disaster assistance through the 

CDBG program and those who did not, and owners of 

properties that were rebuilt following the storms and 

owners of properties that continue to have substantial 

repair needs or are no longer standing.

In this chapter, we describe the data collection and 

analytic methodology for this report. First, we provide 

an overview of all the data sources used in the analysis 

and a more detailed description of the property owner 

survey. Next, we describe the sampling approach for 

the owner survey, which takes as its starting point the 

windshield observation sample. Following that, we 

discuss our approach to locating survey respondents, 

conducting the survey, and maximizing response rates. 

Finally, we discuss the nonresponse bias analysis and 

sampling weights applied to the survey findings.

2.1 STUDY DATA SOURCES

The overall study draws upon three main sources 

of data: windshield observations, a variety of 

administrative and public data sources, and a 

property owner survey. The windshield observations 

are described in full—with findings—in the Phase 

I report, chapter 2. A variety of administrative data 

was also utilized, primarily for the Phase I report. 

The administrative data sources that were used for the 

current report include the following:

•	 Federal Emergency Management Agency

(FEMA) Damage Assessment Data Set. This data 

set contains basic household information for all 

FEMA assessed properties located on the sampled 

significantly affected blocks (SABs).14 This 

information includes the address, number of units, 

tenure, and property type. Most importantly, this 

data set also includes the level of damage from the 

2005 hurricanes under the following nomenclature: 

minor, major, and severe. The damage assessments 

are used for analysis of subsequent housing 

recovery.15 This data set also includes contact 

information for the person who requested the 

FEMA assessment, but this was generally for the 

occupant rather than the owner of the unit, and 

was therefore of limited use in identifying survey 

respondents.

14 A SAB is a census block on which three or more housing units sustained major or 

severe damage according to the FEMA damage assessments.

15 FEMA Flood Insurance Rate Maps (FIRMs) and Advisory Base Flood Elevation (ABFE) Maps, and the U.S. Geological Survey (USGS) National Elevation Dataset, were also collected to analyze the observed and owner-reported 

elevations for each rebuilt property against the recommended elevations for those 

properties. The share of property owners reporting elevation work in the owner 

survey sample, however, was only approximately 10 percent. Because of the weak 

statistical value of this subsample, an analysis of the reported versus recommended elevations is not included in this report.
Chapter 2: Data Collection and Analysis Methodology 10

•	CDBG Administrative Data. Property-level data 

from each state’s CDBG program from March 

2010 provides information on which properties 

in the sample received CDBG awards, the type of 

award received (homeowner or small rental) and the 

amount the award, as well as select information on 

other sources of funding used for calculating the 

CDBG award amount.

The primary data source for this report, however, 

is the property owner survey. While the study is 

not intended to infer causality from receiving and 

not receiving CDBG funds on repair or rebuilding 

decisions, the owner survey provides data for describing 

the processes of applying for and using CDBG funds 

across the different state programs, other funding 

sources and their role in comparison to CDBG, barriers 

to rebuilding, other concerns related to the owners’ 

use of CDBG funds and the associations between 

CDBG funds of different program models and housing 

recovery. The owner survey instrument addressed these 

varied concerns in the following specific categories:

•	Baseline Property Characteristics and

Conditions. The instrument sought to uncover 

the pre-storm tenure, quality, and value of the 

property, and neighborhood characteristics, to form 

a baseline for comparison. All owners were asked 

these questions, but owners who purchased the 

property after 2005 were asked about the property 

at the time of purchase.

•	Current Ownership. All 2005 owners, regardless of 

current (2011) ownership status, were asked about 

the properties’ current ownership status (including 

foreclosure) and, if sold by the owner respondent, 

the value at the time of sale.

•	Current Occupancy and Property Condition. 

Only current property owners (including those not 

living on the property itself ) were asked about the 

current characteristics and condition of the home 

(or rebuilt home, if applicable) and neighborhood 

characteristics. Included in this series of questions 

were ones about the current interior condition 

of homes—information not available from the 

windshield observations.

•	Former Occupants’ Status. Respondents who no 

longer occupy the property in question were asked 

about their current housing status and conditions—

that is, the status of the location to which they 

moved.

•	Damage. All owners were asked about the source 

and extent of damage by the 2005 storms, as well 

as the entity that performed a damage assessment, 

and the amount of assessed damage. The survey 

also asked about the specific parts of the structure 

damaged by the hurricanes.

•	Repair and Rebuilding. All 2005 owners, 

regardless of current ownership, were asked about 

repair and rebuilding activities undertaken in 

response to the 2005 storm damage. This series of 

questions probed the kind of repair or rebuilding 

(both in general and with regard to specific 

interventions such as structural elevations), its 

timing and costs, its level of completion, reasons 

for incompletion, and the materials and contractors 

used. Owners who purchased the property after 

2005 were also asked whether repairs or rebuilding 

had been performed before the purchase. This 

information was designed to supplement the repair 

and rebuilding information provided in the Phase I 

report based on exterior windshield observation.

•	Reasons for Not Rebuilding. All 2005 owners who 

did not perform any repair or rebuilding were asked 

if they intended to rebuild (if they still owned the 

property) and the reasons why they did not rebuild.

•	Funding Sources. All 2005 owners were asked 

about the sources of the funding that they might 

have received after the storms, such as insurance 

payouts, charity assistance, personal funds, 

and public assistance grants, the amount of the 

funding, and whether all of the sources totaled were 

sufficient to cover repair or rebuilding costs. For 
Chapter 2: Data Collection and Analysis Methodology 11

public assistance grants in particular, owners who 

did not receive CDBG funds were asked whether 

they applied, why they did not apply, why they 

withdrew their application (if applicable), and 

why they were rejected if they applied but did 

not receive assistance. For owners who did receive 

CDBG-related program funds, the survey posed 

a series of questions about the specific program 

options that they selected, their use of the funds, 

and the process of applying. The questions were 

tailored to address the nomenclature and the 

program requirements of the program models in 

each of the three states—for example, Texas owners 

were asked about construction completion in 

addition to applying for and receiving assistance. 

The information provided from this series of 

questions directly responds to the broader area 

of inquiry regarding the access, use, and role of 

CDBG funds in housing recovery.

•	Owner Demographics. All survey respondents 

were asked basic demographic information, such as 

marital status, employment, household income and 

finances, household size, race, and ethnicity.

Appendix B provides further detail on the content and 

structure of the property owner survey.

2.2 SELECTING THE 

OWNER SURVEY SAMPLE

The starting point for selecting the owner survey 

sample was the set of windshield observations 

completed in the Phase I report. We selected the 

owner survey sample from among those properties 

for which we had completed windshield observations 

because we needed to use the results of the windshield 

observations to ensure that the survey sample included 

a mix of properties with substantial rebuilding, partial 

rebuilding, or no rebuilding at all. The windshield 

sample consists of 3,511 properties across the three 

states. Among the 3,511 properties, 2,833 were

designated by FEMA as having suffered severe or major 

hurricane damage in 2005, and 678 were designated as 

having minor damage.16

The owner survey was designed to focus on owners 

of damaged properties who, in the aftermath of 

Hurricanes Katrina and Rita, could potentially receive 

CDBG disaster assistance funds. Because the state 

CDBG disaster assistance programs were generally 

limited to owners of properties with “major” or severe 

assessed damage, we elected to select the owner survey 

sample primarily from among the 2,833 severe or 

major damage properties. (As discussed in a following 

section, in Texas we included in the sample some 

properties assessed by FEMA as having minor damage 

but that received CDBG disaster assistance awards.) 

Given project resource limitations, it was not possible 

to interview all owners of residential properties that 

experienced major or severe damage in the windshield 

sample. Instead, we planned to survey a total of 1,400 

owners across the three states.

The windshield observation sample was selected to 

be a representative sample of all properties located on 

SABs across the three states and 17 subgeographies 

to provide statistically reliable estimates of housing 

recovery. In contrast, the most important criterion for 

the owner survey sample was to have sufficient numbers 

of respondents of each owner type—homeowners and 

owners of rental properties, CDBG recipients and 

nonrecipients, and owners of properties that were 

ultimately rebuilt as of early 2010 and those that 

were not—to analyze the factors that affect rebuilding 

decisions. Our allocation of the survey sample focused 

on the power for detecting differences between the 

groups of interest in the overall population, not 

for specific geographies. Whereas the windshield 

observations oversampled properties from 8 of the 17 

geographies requested by HUD, our telephone survey 

sample eliminated this oversampling. We also adjusted

16 As described in chapter 1, minor implies assessed damage of less than $5,200, 

major implies assessed damage of at least $5,200 but less than $30,000, and severe

implies assessed damage of $30,000 or more.
Chapter 2: Data Collection and Analysis Methodology 12

the sample based on proportional allocation, with an 

oversample of properties with partial or no rebuilding 

activity. Because properties with partial or no 

rebuilding activity are a primary focus of the study, this 

oversample was intended to ensure an adequate sample 

size for this subset of properties.

For Louisiana and Mississippi, where the sampling 

universe contained a sufficient number of properties, 

we allocated the total sample for the telephone survey 

across the geographic strata used for the windshield 

observations in approximate proportion to the number 

in the sampling frame in each stratum, but also to 

ensure that the sample was not unbalanced across the 

three dimensions of interest: pre-hurricane tenure, 

CDBG receipt, and 2010 rebuilding status.

In Texas, the sampling universe for the owner survey 

contained fewer properties than anticipated. Of the 

2,833 properties with major or severe damage in the 

windshield sample, only 57 were in Texas; of those 

57, only 1 had received CDBG assistance. Texas had 

a much higher proportion of properties designated by 

FEMA as having minor damage than the other two 

states. In addition, local officials report that substantial 

damage occurred to Texas properties in fall 2005, after 

the FEMA assessments were conducted, as a result 

of damaged roofs and heavy rainfall. By the time the 

properties in Texas were evaluated for CDBG assistance 

the overall damage was assessed to be greater than what 

FEMA had found earlier.

To increase the owner survey sample size in Texas, and 

to include some properties that had received CDBG 

awards, we had to sample additional SABs in Texas 

beyond the 10 blocks in that state included in the 

windshield observations. We sampled an additional 

83 SABs in Texas to reach the desired sample size of 

120 for the owner survey in Texas. The survey sample 

of 120 included 45 homeowners who received CDBG 

grants, 45 homeowners who did not receive CDBG 

grants, and 30 rental properties. To reach the sample 

size of 45 homeowners who received CDBG grants, we 

sampled all homeowners on the 83 blocks who received 

CDBG awards for properties assessed by FEMA as 

having major or severe damage, and a portion of 

homeowners who received CDBG awards for properties 

assessed by FEMA as having minor damage.

Exhibit 2-1 shows the initial sample for the telephone 

survey sample by geography (state and county/parish 

level only), pre-hurricane tenure, CDBG receipt, and 

2010 rebuilding status.
Chapter 2: Data Collection and Analysis Methodology 13

Exhibit 2-1. Initial Allocation of Telephone Survey Sample

Homeowner Properties Rental Properties

Total Substantially 

Rebuilt

Partial and 

No Rebuilding

Substantially 

Rebuilt

Partial and 

No Rebuilding

CDBG No 

CDBG CDBG No CDBG CDBG No CDBG CDBG No CDBG

Louisiana 210 155 205 95 17 119 28 161 990

Calcasieu and 

Cameron Parishes 6 3 3 5 0 2 0 4 23

Jefferson Parish 26 41 4 4 2 36 0 5 118

Orleans Parish 122 61 126 52 15 70 26 134 606

St. Bernard Parish 34 28 59 22 0 5 2 12 162

St. Tammany Parish 6 17 4 4 0 3 0 1 35

Other Louisiana 

Parishes 16 5 9 8 0 3 0 5 46

Mississippi 73 54 47 45 0 22 0 49 290

Hancock County 13 4 17 16 0 1 0 6 57

Harrison County 10 24 10 13 0 8 0 26 91

Jackson County 50 22 20 14 0 13 0 16 135

Other Mississippi 

Counties 0 4 0 2 0 0 0 1 7

Texasa 35 20 10 25 0 10 0 20 120

Total for all states 318 229 262 165 17 151 28 230 1,400

CDBG = Community Development Block Grant.

a The rebuilding status of properties in Texas is not known because most of the owner survey sample was not part of the windshield sample. 

The allocation of the Texas sample across the rebuilding categories is an estimate.
Chapter 2: Data Collection and Analysis Methodology 14

2.3 APPROACH TO 

CONDUCTING THE 

PROPERTY OWNER SURVEY

Abt SRBI, a national survey firm and an Abt Associates 

subsidiary, conducted the property owner survey 

between late September 2010 and early May 2011. 

The survey’s first significant challenge came in locating 

the 2005 owners of properties damaged by Hurricanes 

Katrina and Rita. As described in the Phase I report, 

the windshield observations found that as of early 

2010, about 11 percent of storm-damaged properties 

on significantly affected blocks, across the three 

states, no longer contained a residential structure, 

and almost 15 percent either contained no residential 

structure or contained a residential structure that was 

not habitable.17 Furthermore, as shown in exhibit 

2-1 previously, nearly one-half of the survey sample 

(49 percent) participants were owners of properties 

that, as of early 2010, were either not rebuilt at all or 

only partially rebuilt. With such a large share of the 

properties uninhabitable or under construction, and 

with many properties having changed ownership since 

the 2005 hurricanes, additional steps were required for 

identifying and locating the 2005 owners, as well as 

soliciting their responses to the survey. The pilot test of 

the survey was conducted in October and November of 

2011, and the survey was implemented through midMay 2011. The bulk of survey responses were provided 

from February to May 2011 and were due to the 

increased use of field efforts described in a following 

section.

Identifying and Locating the 2005 Owners of 

Hurricane-Damaged Properties

The survey team used a variety of means to accurately 

identify and then locate the owners in the survey 

sample. Starting with a list of 1,400 property addresses, 

the first task was to identify the owners of those 

properties as of August 2005. Pilot testing of the phone 

survey instrument in October and November of 2010 

resulted in 207 completes, but left the remaining bulk 

17 See Turnham, et al. (2010), p. 31 and p. 39.

of the owner sample to be determined. For each address 

in the sample, we used a combination of data sources to 

identify the 2005 owner:

•	The FEMA Damage Assessment Data Set. We 

used the FEMA data set to develop the survey 

sample, because it provided (in most cases) the 

name of the occupant of the property at the time a 

FEMA claim had been made for hurricane damage. 

The FEMA data set was a useful starting point for 

identifying the owners of properties believed to 

be owner occupied at the time of the hurricanes, 

approximately 70 percent of the survey sample. 

This data set was particularly useful for Mississippi 

and parts of Louisiana. However, because it 

included only the names of occupants, not owners, 

the FEMA data set was not helpful for identifying 

the 2005 owners of those properties that were 

renter occupied at the time of the hurricanes.

•	 State CDBG Administrative Data. In March 2010, 

we obtained administrative data from the state 

administrators of the CDBG disaster assistance 

programs in the three states. We used these data to 

help identify and locate owners of properties who 

received CDBG assistance. These data were helpful 

for the approximately 45 percent of the survey 

sample who had received CDBG assistance, but the 

level of information available for individual CDBG 

recipients that could be useful for locating these 

owners varied within and across the three data sets.

•	 Parcel-Level Data from County/Parish Tax

Assessor’s Offices. We attempted to obtain parcellevel data on the 2005 ownership of each property 

in the survey sample using three sources: data 

maintained by HUD, data maintained by private 

vendors and available for purchase, and data 

available online from county/parish tax assessors. 

Using these three sources, we were able to find a 

tax assessor record for about three-fourths of the 

properties in the survey sample. The remaining 

properties, slightly more than one-half of which 

were identified in the FEMA data set as being 
Chapter 2: Data Collection and Analysis Methodology 15

renter occupied at the time of the hurricanes, 

could not be located in the available assessor data. 

For the properties that were found in the assessor 

records, the information available on owners varied. 

In many cases, we were able to use the assessor 

data to corroborate the owner information in the 

FEMA data set for owner-occupied properties, or to 

identify clearly a different owner as of 2005. This 

process was helpful in all three states. However, 

many of the records available through our three 

sources did not go back as far as 2005, and in other 

cases the ownership of the property as of 2005 was 

unclear. Ultimately, reliable owner names were not 

available for 30 percent of the properties in the 

survey sample.

•	In-Person Efforts to Identify Owners. For those 

cases in which we were not able to obtain an 

owner name, we sent interviewers to the property 

address to ask the property’s current inhabitants 

and neighbors about the identity of the 2005 owner 

and his or her current location. Local tax assessor’s 

records were also mined in the field in cases of 

incomplete owner identification. This tactic was 

particularly useful in Orleans Parish, Louisiana. 

We also sent mailings to all addresses in the survey 

sample, informing the occupants of the survey 

activities and encouraging 2005 owners to call in to 

a toll-free number to complete the survey.

By early February 2011, the ownership identification 

for approximately 79 percent of the sample had been 

confirmed. The procedures described previously for 

identifying the owners overlapped with procedures for 

locating the owners, because in-person field efforts were 

increasingly required. These procedures for locating the 

2005 owner can be categorized in the following order:

•	 Finding Current Contact Information. After 

we had an owner name for the property, we 

used several means of locating the owner and 

encouraging him or her to complete the survey. 

First, we ran all the owner names (and any other 

information available) through the United States 

Postal Service National Change of Address (NCOA) 

Database to obtain an updated address. We then 

used Accurint, a private database vendor used by 

credit companies to locate individuals, to obtain 

further address updates and telephone numbers for 

owners in the sample. In most cases, the Accurint 

data provided at least one telephone number for 

the owner, and in many cases it provided multiple 

telephone numbers. Ultimately, 359 records with 

contact phone information were available and sent 

to the phone center at this phase. Another 536 

records with no contact phone information for 

identified owners were sent directly to the field for 

additional locating, along with 273 records that 

still required owner identification.

•	 Phone Center Initiation. This contact information 

was used by the survey’s phone center to initiate 

the survey response when available. Letters were 

sent to the owners’ last known addresses informing 

the owners of the survey, confirming the owners’ 

contact information, and included invitations 

to complete the survey. The phone center would 

repeat initiation steps for a period of 3 weeks before 

releasing the owner information to the field for 

additional locating. A total of 299 records were 

released to the field during this process, including 

preliminary refusals along with unsuccessful 

initiations.

•	 Field Initiation. Cases involving identified owners 

for whom no phone contact information was 

available were sent immediately to the field for inperson contact similar to the identification efforts. 

Many of the procedures described previously for 

owner identification in the field were implemented, 

including conducting additional searches in local 

public records, visiting the property address, and 

inquiring with current residents or neighbors. Indepth individual Accurint search updates were also 

employed, with findings used directly in the field.
Chapter 2: Data Collection and Analysis Methodology 16

The challenges described previously in identifying 

and locating the 2005 owners of hurricane-damaged 

properties, approximately 5 years after the hurricanes, 

necessitated an intensive field effort over many months. 

Ultimately, more than one-half of the completed 

interviews originated with an infield locating effort 

rather than simple telephone locating efforts. Overall, 

through all the efforts, the survey team was able to 

locate the 2005 owners for 70 percent of the properties 

in the survey sample (977 of 1,400).

Increasing the Response Rate

After identifying and locating owners, the third 

challenge involved successful completion of the survey 

by the sample respondents—that is, increasing the 

response rate. This effort overlapped somewhat with 

the location efforts, because the field staff attempted 

to both confirm the 2005 owners and to have them 

complete the survey—either by appointment with the 

phone center or at the point of field contact. A series of 

additional steps were employed for this activity:

•	 Local Contact Information. Local phone numbers 

(with local area codes that would appear in callerID screens) were employed to reach out to the 

identified owners who might not be willing to 

speak to a more distant phone center.

•	 Local Mailings. Additional mailings using local 

postmarks and identifying a local phone for 

initiating the survey were provided to increase 

responses.

•	In-Person Attempts. Visits to properties both 

during locating efforts and after confirming 

locations were employed. When no occupant 

answered, cards with local numbers were left.

•	In-Person Contact. Personal contact, when 

possible, was employed to convert previous refusals 

at the phone center.

•	 Financial Incentives. All respondents who 

completed all or part of the interview were paid 

$25 for their time in the form of a money order. 

The $25 was intended to provide respondents with 

further incentive to complete the interview, beyond 

the opportunity to share their experiences with the 

challenges of rebuilding after the hurricanes and 

provide feedback on the CDBG-funded disaster 

assistance programs. At the very end of the survey 

period, when the research team encountered 

increased resistance to completing the interview, 

the team increased the respondent incentive 

payment to $50.18 When successfully reached, 

respondents took an average of 30 minutes to 

complete the interviews. Respondents were allowed 

to skip questions they did not feel comfortable 

answering and to stop the interview at any time. 

The results of these efforts to increase response 

rates, as well as a fuller explanation of response 

concerns, are described in a following section.

18 This change was approved by Abt Associates’ Institutional Review Board in April 

2011. 120 of the 722 survey respondents received the higher incentive payment.
Chapter 2: Data Collection and Analysis Methodology 17

2.4 SURVEY RESPONSE 

RATES

A total of 722 individuals completed the property 

owner survey, for an overall response rate of 52 percent. 

As shown in exhibit 2-2, the survey response rates were 

highest in Texas and among owner-occupied properties, 

recipients of CDBG assistance, and for owners of 

properties that as of early 2010 were substantially 

rebuilt.

Exhibit 2-2. Survey Response Rates by Subgroups of Interest

Survey Sample Size Total Respondents Response Rate

State

Louisiana 990 467 47%

Mississippi 290 171 59%

Texas 120 84 70%

Occupancy (Fall 2005, based on FEMA data)

Owner occupied 974 544 56%

Renter occupied 426 178 42%

CDBG Receipt (March 2010, based on CDBG administrative data)

Received CDBG 625 362 58%

Did not receive CDBG 775 360 46%

Rebuilding Status (February 2010, based on windshield observation)a

Substantially rebuilt 650 369 57%

Partial rebuilding or no rebuilding 630 269 43%

Overall: all subgroups 1,400 722 52%

CDBG = Community Development Block Grant. FEMA = Federal Emergency Management Agency.

a The Texas sample is excluded from this part of the exhibit because the 2010 rebuilding status is not known for most of the survey sample.

Sources: FEMA data set (for occupancy); CDBG administrative data (for CDBG receipt); 2010 windshield observations (for rebuilding 

status)
Chapter 2: Data Collection and Analysis Methodology 18

Exhibit 2-3 summarizes the reasons for survey 

nonresponse. Almost two-thirds (62 percent) of the 

678 potential respondents who did not complete 

an interview simply could not be located by the 

interview team. This group includes cases, as described 

previously, in which the 2005 owner of the property 

could not be identified, as well as cases in which the 

owner was identified but could not be located, or an 

owner who ignored all efforts by the survey team to get 

in touch. Some of these owners could also have been 

deceased, but the survey team could not confirm that 

this was the case.

The second biggest reason for survey nonresponse was 

respondent refusal. Despite efforts by the survey team 

to try to address their concerns and to encourage them 

to do so, 134 people refused to do the interview. The 

survey field staff reported that most people who refused 

to complete the survey provided one of the following 

reasons: 

•	 Hurricane Katrina Fatigue. About five and a half 

years after the hurricanes, people said they were 

simply “tired of talking about Katrina.” For many 

people, talking about their experiences in the 

aftermath of the hurricanes continues to bring up 

very painful memories.

•	Antigovernment Sentiment. Some people 

expressed antigovernment, anti-HUD, and 

anti-FEMA sentiments. As several put it, “the 

government was not there for me [at the time of 

the hurricanes], so I will not help them now.” 

Frustration at the slow pace of assistance and 

recovery has been well documented and persists to 

this day.

•	 Fear of Another “Scam.” People were skeptical of 

the legitimacy of the survey and were concerned 

that the interviewers might be out to take 

advantage of them in some way.

The survey team observed that the rate of refusal was 

high regardless of the age of the respondent. Typically, 

survey response rates are higher among older people, 

who often have more time and interest in talking about 

their experiences, but this was not the case with this 

survey.

Exhibit 2-3. Characteristics of the Survey Sample: State and Owner Status at Time of Survey

Number Weighted 

Number Percent

State (N = 202,102)

Louisiana 467 145,518 72.0

Mississippi 171 47,626 23.6

Texas 84 8,958 4.4

Owner Status (N = 202,102)

Owned property in 2005 and 

currently owns property 574 160,797 79.6

Owned property in 2005 and no longer owns property 128 35,158 17.4

Purchased property after 2005

as a rental property and currently owns property 19 5,638 2.8

Purchased property after 2005 

as a rental property and no longer owns property 1 508 0.3

Source: 2011 Property Owner Survey
Chapter 2: Data Collection and Analysis Methodology 19

2.5 RESPONSE BIAS

In addition to the high refusal rates noted during the 

owner survey, a variety of cognitive biases may have 

influenced owner responses; several studies have noted 

the possibility of these biases in populations affected 

by natural disasters.19 In particular, researchers are 

concerned with how respondents may have described 

the pre-storm era more positively than realistically, 

how the trauma of the events may have psychologically 

influenced responses, and how the length of time since 

the storm may have biased their responses. Some of 

these biases may be the result of psychological and 

sociological behaviors similar to those that resulted 

in nonresponse. For example, several studies note 

that hurricane victims suffered from mental illnesses 

typical of other natural disaster survivors, although 

local factors affected individuals’ experiences and 

symptoms.20 The magnitude of post-traumatic distress 

among victims of this specific event, however, was 

unique: both severe and moderate mental illness almost 

doubled after Hurricane Katrina.21

Several cognitive biases that are products of these 

psychological conditions may have played a role in 

the responses, in addition to more mundane biases 

that are present in similar surveys that demand recall 

of an event or set of facts in the distant past. Memory 

biases are perhaps the most likely biases associated 

with responses to the owner survey; in particular, rosy 

retrospection, in which subjects rate their circumstances 

before the disaster more positively than they would 

have rated them before the event occurred. This bias 

may have shaped the owners responses to questions 

on pre-storm neighborhood conditions and property 

19 For example: Ashley and Sheuren, “Considerations In The Study Design of a 

Mobile Phone Survey of the Haitian Population” and Fisher, “Survey Administration in the Wake of a Natural Disaster” presented at the Joint Statistical Meetings of the American Sociological Association, Vancouver, Canada. August 2010; 

and Kessler et al., “Sample and Design Considerations in Post-Disaster Mental 

Health Needs Assessment Tracking Surveys,” International Journal of Methods in 

Psychiatric Research 17(S2): S6–S20 (2008).

20 Weems et al. “The psychosocial impact of Hurricane Katrina: contextual differences in psychological symptoms, social support, and discrimination.” Behaviour 

Research and Therapy: October 2007, Vol. 45 (10), pp. 2295–306.

21 Kessler et al. “Mental illness and suicidality after Hurricane Katrina.” Bulletin of 

the World Health Organization 2006; Vol. 84, pp. 930–939.

conditions. Because respondents were asked to describe 

events leading up to their current rate of rebuilding 

(and lack of rebuilding, in some cases), hindsight bias—

or the inclination to describe past events in ways that 

predict or justify current conditions—may also play a 

role. These biases are likely combined with more typical 

memory distortions; the owner survey took place in 

early 2011, more than 5 years after the hurricanes.

Neither the presence of these biases, nor their 

magnitude or direction, is obvious. The study did not 

attempt to overcome these biases, although the survey 

was designed to compensate for owner recall issues by 

allowing owners to report ranges rather than specific 

dollar amounts for things like home sales values, 

damage assessments, funding amounts, and repair costs. 

Issues related to the effect of a traumatic event like the 

2005 hurricanes on owners’ perceptions of their living 

conditions before the event and on owners’ ability to 

remember important information (such as the amount 

of damage assessed to their property) that would have 

been received in the midst of the traumatic event, 

should be the subject of future research.

2.6 SAMPLING WEIGHTS

To produce population-based estimates from the 

property owner survey, each sample property was 

assigned a sampling weight that consists of two parts: 

the base weight and the nonresponse adjustment factor. 

The base sampling weight is simply the reciprocal 

of the probability of selecting the property into the 

sample. If all sample property owners had responded 

to the survey, these weights would ensure that the 

sample included in the evaluation was representative 

of the population of properties with major or severe 

damage in the geographical areas from which they were 

selected.

The subset of sample property owners who responded 

to the surveys may not be representative of this 

population, however, if certain types of property 

owners, or property owners in certain geographical 

areas, were more likely to respond to the survey than 
Chapter 2: Data Collection and Analysis Methodology 20

other owners, as suggested previously in exhibit 2-2. 

For that reason, we adjusted our sampling weights 

for nonresponse to account for differential response 

rates for different subgroups of property owners. 

The nonresponse adjustment factor adjusts for 

characteristics available for all sample members who 

were determined to be correlated with the probability 

of responding to the survey, including CDBG receipt, 

occupancy type, type of damage, and whether the 

property was substantially rebuilt according to the 

windshield survey. To compute the nonresponse 

adjustment factor for each property, we first estimated 

a logistic regression model of nonresponse and used 

the fitted model to find the response probability (also 

known as a propensity score) for each property. The 

inverse of the propensity score was then used to adjust 

the base weight. Appendix C provides further detail 

on the nonresponse bias analysis conducted for the 

property owner survey.

2.7 FINAL SAMPLE 

CHARACTERISTICS

The weighted survey data presented in this report 

provide estimates for a population of 202,102 owners 

whose properties in Louisiana, Mississippi, and Texas 

were located on blocks that sustained significant 

damage from Hurricanes Katrina or Rita, and that 

suffered major or severe storm damage.

Exhibits 2-3 through 2-5 show the characteristics of the 

weighted survey sample of 202,102 property owners. 

Slightly less than three-fourths of the sample (72.0 

percent) owned a property in Louisiana at the time of 

the hurricanes, about one-fourth (23.6 percent) owned 

a property in Mississippi, and the remainder (4.4 

percent) owned a property in Texas.

More than three-fourths of the owners in the survey 

sample (79.6 percent) owned the property at the time 

of the hurricanes and still owned the property in early 

2011, 17.4 percent owned the property at the time of 

the hurricanes but no longer owned it in early 2011, 

and 3.1 percent purchased the property after the 

hurricanes as a rental property (most of these owners 

still owned the property in 2011).

Although the vast majority of survey respondents (96.9 

percent) are people who owned a property in 2005 that 

was damaged by the hurricanes, we permitted owners 

who purchased the property after 2005 to complete 

the property owner survey provided they purchased the 

property as a rental property. This group was included 

because these owners were eligible to apply for the 

CDBG-funded small rental property assistance 

programs in Louisiana and Mississippi, and the study 

was interested in the population of owners eligible to 

apply for CDBG. The CDBG homeowner programs 

were available only to people who owned at the time of 

the hurricanes; thus, the survey was not open to people 

who purchased a damaged property after the hurricanes 

for use as a homeowner property.

As shown in exhibit 2-4, more than three-fourths of 

properties were owner occupied at the time of the 

hurricanes, most without rental units (69.7 percent), 

but some with rental units (8.5 percent). Of all the 

properties, 18.4 percent were rental (or investment) 

properties at the time of the hurricanes, and less than 

1 percent were vacation homes. About 3 percent of 

properties were not identified by the owner as an 

owner-occupied house, a rental property, or a vacation 

home; most likely these properties were some other 

type of housing not occupied at the time of the 

hurricanes. (Owners of nonresidential properties were 

screened out at the start of the survey.)

Less than one-half of the weighted survey sample 

received a CDBG award (exhibit 2-5). We used the 

CDBG administrative data provided by each of the 

states in March 2010 to determine rates of CDBG 

receipt. Most were recipients of CDBG homeowner 

grants (42.5 percent), but a small number received 

assistance through the CDBG small rental program 

(2.0 percent). The small number of small rental grant 

recipients in the sample is not surprising, given that, 

in the larger windshield observation sample, we found 

that only 2.6 percent of all properties in Louisiana 
Chapter 2: Data Collection and Analysis Methodology 21

and Mississippi (8.8 percent of rental properties) had 

received a CDBG small rental grant.22 The CDBG 

small rental grant programs provided less funding than 

22 Percentages for all properties were derived from exhibit 5-1 in Turnham, et al.

(2010), summing the raw numbers columns.

the CDBG homeowner programs. Given the very small 

number of survey respondents who received CDBG 

small rental grants, we focus our analysis in chapter 5 

on homeowners and recipients of CDBG homeowner 

grants.

Exhibit 2-4. Characteristics of the Survey Sample: Occupancy at Time of Hurricanes

Number Weighted 

Number Percent

Occupancy and Use of Property at Time of Hurricanes (N = 195,955)

Owner occupied, no rental units 505 136,672 69.7

Owner occupied, with rental units 55 16,619 8.5

Rental property (not owner 

occupied) 114 36,021 18.4

Vacation home 2 402 0.2

None of the above 23 5,432 2.8

Don’t know or refused 3 808 0.4

Note: Does not include properties purchased after 2005.

Sources: 2011 Property Owner Survey; 2010 windshield observations

Exhibit 2-5. Characteristics of the Survey Sample: CDBG Receipt

Number Weighted 

Number Percent

CDBG Receipt (N = 202,102)

Received a CDBG homeowner grant 343 85,867 42.5

Received a CDBG small rental 

program grant 19 4,069 2.0

Did not receive a CDBG grant 360 112,165 55.5

CDBG = Community Development Block Grant. 

Source: Property Owner Survey matched to CDBG administrative data from March 2010. 
Chapter 3: Repair Needs and Rebuilding 22

3. REPAIR NEEDS

AND REBUILDING

This chapter presents the information 

gathered in the owner survey on the overall 

state of physical recovery among the 

population of homes that were located on 

significantly affected blocks and that suffered major 

or severe damage in the hurricanes. This chapter 

supplements what is known from the earlier windshield 

observations, the findings of which are described in 

the Phase I report. While the windshield observations 

provided direct field reports of the exterior physical 

conditions of a wider sample of properties, the owner 

survey responses provide additional detail and nuance, 

particularly with regard to the pre-hurricane condition 

of the properties as well as the specific systems damaged 

by the hurricanes—although for a smaller sample of 

properties. In addition to focusing primarily on repair 

needs and rebuilding status, we pay particular attention 

in this chapter to two overlapping special populations: 

former owners (and the disposition of their properties) 

and movers (and their new housing and neighborhood 

conditions). This information is presented in this 

report because of the connection between the level of 

damage and consequent repair need and the decision to 

leave the property.

The first section of the chapter discusses the survey 

findings on the pre-hurricane condition of properties 

and the severity and type of hurricane damage. The 

second section then discusses the ownership status 

of the sampled properties as of 2011, because many 

properties have changed owners since the hurricanes, 

to determine any association between pre-hurricane 

condition and damage with ownership changes. The 

third section presents the survey findings on the 

condition of the hurricane-damaged properties as of 

early 2011, and the fourth section discusses the repair 

and rebuilding that owners report undertaking since 

the storms. The chapter concludes with a discussion 

of the reasons for not rebuilding among owners who 

reported they did no repair or rebuilding work on their 

hurricane-damaged properties.

3.1 PRE-HURRICANE 

CONDITIONS AND 

HURRICANE DAMAGE

The property owner survey asked owners about the 

overall condition of their properties in August 2005, 

immediately before the hurricanes struck. Owners 

were asked to rate the condition of their properties as 

excellent or good, fair, or poor. Based on the survey 

findings, we estimate that most of these properties 

(among the study population of owned properties that 

suffered major or severe storm damage and were located 

on significantly affected blocks) were in excellent 

or good condition before the arrival of Hurricanes 

Katrina, Rita, and Wilma in August 2005.

As shown in exhibit 3-1, 94.8 percent of owners in 

Texas, Louisiana, and Mississippi considered their 

homes to have been in excellent or good condition 

before the storms based on their own subjective 

assessment. Comparing the three states, owners in 

Texas were significantly less likely to have considered 

their homes to be in excellent or good condition 

before the hurricane (85.4 percent), and significantly 

more likely to rate their homes as having been in fair 

condition (13.0 percent). By contrast, about 95 percent 

of property owners in Louisiana and Mississippi rated 

their properties as having been in excellent or good 

condition before the hurricanes, and 5 percent said 

they had been in fair or poor condition. Differences in 

responses between owners in Louisiana and Mississippi 

were not statistically significant.
Chapter 3: Repair Needs and Rebuilding 23

Exhibit 3-1. Pre-Hurricane Property Condition by State and Overall

Note: Weighted population estimates based on 702 survey responses.

Source: 2011 Property Owner Survey

Exhibit 3-2. Pre-Storm Home Values by State

Louisiana Mississippi Texas

Percentile CI Percentile CI Percentile CI

Less than $80,000 15.3 11.4–19.1 13.9 7.9–20.0 34.4 22.6–46.2

At least $80,000 but 

less than $175,000 48.8 43.1–54.4 50.1 41.0–59.2 53.1 40.1–66.0

At least $175,000 but 

less than $300,000 22.6 18.6–26.6 20.4 12.6–28.3 3.0 0.0–7.5

$300,000 or more 9.6 6.4–12.8 8.0 1.2–14.8 0.2 0.0–0.5

Don’t know/refused 3.8 2.4–5.1 7.5 3.8–11.2 9.3 1.7–16.9

CI = 90 percent confidence interval.

Note: Weighted population estimates based on 702 property owners who owned the property in 2005 before the hurricane. 

Source: 2011 Property Owner Survey

This finding is consistent with the Texas program’s 

emphasis on income and geographic targets, and is 

further supported by an analysis of the differences in 

pre-storm home values by state, as shown in exhibit 

3-2. Texas had a larger share of properties with home 

values less than $175,000 than either Mississippi or 

Texas. There was a significant difference in pre-storm 

value at the 1 percent level between properties in Texas 

and Louisiana and between properties in Texas and 

Mississippi.

100%

95%

90%

85%

80%

75%

Louisiana

Poor condition

Fair condition

Excellent or good 

condition

Mississippi Texas Overall

95.8

4.1

0.1 0.6 0.3

1.5

93.8

5.6

85.4

13

4.8

94.8
Chapter 3: Repair Needs and Rebuilding 24

Severity of Hurricane Damage

As described in chapter 2, the property owner survey 

was designed to focus on owners of properties that 

experienced major or severe damage from the 2005 

hurricanes. The survey asked owners about the damage 

assessments they had received or commissioned and 

the amount of damage assessed. About 75 percent of 

2005 owners reported receiving a damage assessment 

for their property.23 The damage assessments came 

from several sources, and about 47 percent of owners 

reported that more than one damage assessment was 

done. Most commonly, damage assessments were from 

an insurance company (77.4 percent), followed by 

FEMA (9.7 percent) or The Road Home program in 

Louisiana (3.2 percent).

Not surprisingly, owners reported substantial levels of 

damage to their properties based on these assessments. 

Exhibit 3-3 presents the distribution of reported 

damage amounts by state, based on the highest assessed 

amount reported for owners who reported having 

23 In the property owner survey, 144 respondents reported not having an assessment done, 2 refused to have an assessment done, and 28 did not know if 

they had had an assessment done, though the early FEMA assessments were 

performed for most houses in our database. See the analysis by the U.S. Department of Housing and Urban Development’s Office of Policy Development and 

Research titled “Current Housing Unit Damage Estimates: Hurricanes Katrina, 

Rita, and Wilma” of February 12, 2006.

received multiple assessments.24 The assessed damage 

amounts were highest in Louisiana, with a median 

amount of $89,523, and lowest in Texas, with a median 

amount of $35,124. Both the median and the 75th 

percentile assessed damage amounts were substantially 

lower in Texas than in the other two states. In all three 

states, however, the 25th percentile damage amount 

is substantially higher than the FEMA threshold 

for major damage, which is $5,200 (see discussion 

in chapter 1). This is true even in Texas, where (as 

described in chapter 2) the owner survey sample 

included some properties assessed by FEMA as having 

minor damage but which nonetheless received CDBG 

assistance. The owner damage assessments suggest that 

these properties indeed sustained greater damage than 

was captured by the FEMA assessment.

24 Survey respondents were encouraged to report damage assessments in the following specific priority: assessments by (1) insurance providers, (2) FEMA, (3) 

the CDBG programs, (4) any other type. However, in many cases in which the 

owner cited multiple assessments, the dollars amounts provided were substantially different, making interpretation difficult. The highest assessment amount 

may exaggerate the amount of damage somewhat, but it provides a consistent rule 

for handling cases in which the same property has multiple assessments that are 

different in amount.

Exhibit 3-3. Owner-Reported Assessed Damage Amount by State—Median and by Percentile

Louisiana Mississippi Texas

Percentile CI Percentile CI Percentile CI

25th percentile $44,700 $32,029–

$57,369 $24,328 $13,717–$34,939 $23,772 $10,859–$36,684

Median $89,523 $77,704– 

$101,342 $74,227 $58,957–$89,495 $35,124 $18,756–$51,492

75th percentile $145,535 $133,008– 

$158,061 $125,639 $81,182–

 $170,094 $66,084 $29,084– $104,026

CI = 90 percent confidence interval. 

Note: Weighted population estimates based on 340 survey responses. For owners who reported receiving more than one damage 

assessment, we used the highest damage assessment reported.

Source: 2011 Property Owner Survey
Chapter 3: Repair Needs and Rebuilding 25

In general, however, the owner-reported damage 

assessment amounts should be treated with caution. 

In comparing the owner-reported assessed damage 

amount to the assessed damage amount contained in 

the CDBG administrative data for CDBG recipient 

properties, we found a weak correlation between the 

owner-reported amounts and the amounts in the 

administrative data for the same properties. Assuming 

the information in the CDBG administrative data is 

relatively accurate, this suggests that owners either 

had difficulty recalling with accuracy their assessed 

damage amounts or misinterpreted the findings of their 

assessment. Nevertheless, the owner-reported damage 

amounts are the best source available for the full survey 

sample and provide useful descriptive information. We 

do not use the owner-reported damage amounts in any 

multivariate analysis, given the uncertainty about the 

data quality.

In addition to asking about assessed damage amounts, 

the survey asked owners about the type and extent 

of damage. One measure is whether the damage was 

such that the structure was condemned or had to 

be leveled or demolished. Overall, 23.2 percent of 

owners reported that their structures had been leveled, 

condemned, or demolished (exhibit 3-4). Owners in 

Texas were more likely to report this type of damage 

(31.6 percent) than owners in Louisiana (22.2 percent) 

or Mississippi (24.5 percent), a finding that may be 

partially explained by the lower pre-storm home values 

in that state.

Exhibit 3-4. Share of Properties Leveled, Condemned, or Demolished

Percent CI

Louisiana 22.2 16.7 – 27.8

Mississippi 24.5 13.8–35.1

Texas 31.6 19.6–43.6

All states 23.2 18.5 –27.8

CI = 90 percent confidence interval.

Note: Weighted population estimates based on 702 survey responses.

Source: 2011 Property Owner Survey

Types of Hurricane Damage

The parts of homes that sustained damage also varied 

across states. Overall, damage to the roof was the 

most common type of exterior damage (85.4 percent 

of properties), and damage to the paneling, ceiling, 

and drywall was the most common type of damage to 

the property’s interior (90.6 percent of properties). 

Damage to doors or windows (74.6 percent), electrical 

system (76.3 percent), and air conditioning or heating 

system (77.6 percent), and interior mold damage (75.4 

percent), were also very common. The least common 

type of damage was to foundations or to septic tanks 

(for properties with septic tanks).

As shown in exhibit 3-5, nearly all Texas owners 

reported roof damage (96.9 percent); damage to siding 

or exterior walls was also more likely to be reported in 

Texas than in Mississippi or Louisiana, as was damage 

to porches, stairs, and foundations. A larger share of 

owners reported damage to electrical systems (79.6 

percent) and air conditioning or heating systems (81.1 

percent) in Louisiana than in other states; interior 

mold damage was also most common in Louisiana 

(81.9 percent).
Chapter 3: Repair Needs and Rebuilding 26

Exhibit 3-5. Parts of Homes that Sustained Damage: Proportion with Damage

Percent of Owners Reporting 

Each Type of Damage: Texas Mississippi Louisiana Overall

Paneling, ceiling, or drywall 86.6 90.0 91.0 90.6

Roof 96.9 87.7 84.0 85.4

Air conditioning or heating 

system 54.0 70.6 81.1 77.6

Electrical system 65.3 67.6 79.6 76.3

Interior mold damage 59.3 57.3 81.9 75.4

Doors or windows 73.1 65.7 77.4 74.6

Siding or exterior walls 75.0 50.1 58.3 57.2

Plumbing 46.3 37.1 55.6 51.1

Garage 45.6 49.9 47.5 47.9

Other 34.0 38.7 44.1 42.4

Porch or stairs 54.0 41.6 40.6 41.4

Foundation 37.2 22.1 24.9 24.8

Septic tank 9.6 5.8 7.3 7.0

Note: Weighted population estimates based on 702 survey responses.

Source: 2011 Property Owner Survey

Differences between the specific parts of homes that 

were damaged are related to the type of storm damage 

suffered in the state. As shown in exhibit 3-6, the 

likelihood of flooding was significantly higher in 

Louisiana and Mississippi than in Texas, where only 

32.6 percent of owners reported flood damage. In 

comparison, 89.1 percent of owners in Louisiana 

reported flood damage—consistent with the high shares 

of owners reporting interior mold damage in Louisiana 

described previously. In Texas, other types of storm 

damage—most often wind—were the most common, 

which corresponds with the high share of owners 

reporting roof damage in Texas.

Exhibit 3-6. Type of Storm Damage Reported by State

Louisiana Mississippi Texas

Number % CI Number % CI Number % CI

Flood damage 125,087 89.1 85.6–92.5 38,110 80.6 72.4–88.8 2,717 32.6 20.6–44.7

No flood 

damage 

(typically 

wind)

14,976 10.7 7.4–14.0 8,945 18.9 10.9–27.0 5,612 67.4 55.3–79.4

Don’t know/

refused 274 0.2 0.0–0.5 236 0.5 0.0–1.3 0 0 N/A

Total 140,337 100 47,291 100 8,329 100

CI = 90 percent confidence interval.

Note: Weighted population estimates based on 702 survey responses.

Source: 2011 Property Owner Survey
Chapter 3: Repair Needs and Rebuilding 27

The survey investigated the specific home systems 

damaged in the 2005 hurricanes to determine an 

association between that damage and the current 

owner-reported condition of the home. Looking at the 

array of 2005 damaged systems (exhibit 3-7), homes 

that incurred foundation and septic tank damage 

were in poorer condition than other homes as of the 

time of the 2011 owner survey, although (as noted) 

foundation and septic tank damage was reported with 

less frequency than other damaged systems.

Exhibit 3-7 further suggests that while 69.4 percent of 

homes were generally rated by their owners as being 

in excellent or good condition,25 only 46.7 percent of 

properties that sustained damage to the foundation and 

25 Note that this percentage increases to 70.3 percent when respondents who did 

not answer the question, or said they did not know, are excluded, as is shown in 

exhibit 3-13.

58.2 percent of properties that sustained damage to 

the septic tank were given this rating. Likewise, while 

13.8 percent of homes overall were characterized as 

being totally destroyed, this was true for 25.0 percent 

of homes with damage to the foundation and 20.0 

percent of homes with damage to the septic tank. 

Given the importance of these systems to the structural 

integrity and habitability of the properties, persistent 

inhabitability because of their being damaged is not 

surprising. This does pose the possibility that other 

barriers to their repair may have been present, however, 

such as lack of sufficient funding to cover the costs of 

these primary systems, a lack of specialized contractors, 

or a poorer original construction quality. Further, many 

of these barriers are likely present for rural households, 

mirroring the fact that septic systems tend to be located 

in rural properties without infrastructure.

Exhibit 3-7. Current Condition by Type of Hurricane Damage Reported

Current 

Condition

Percentage of Respondents Reporting by Damage Type

RoofSiding/Exterior WallsDoors or WindowPorch/StairsFoundationPlumbingSeptic TankElectrical SystemAir ConditioningMoldPanelingGarageOtherOverall

Excellent or 

good 71.8 61.7 68.9 62.0 46.7 65.5 58.2 70.1 70.7 69.1 72.4 73.7 64.4 69.4

Fair 13.1 15.3 11.7 13.4 13.6 10.1 15.1 12.2 11.9 12.8 12.1 15.4 17.0 10.7

Poor but 

people 

could live 

there

1.7 2.2 2.0 2.6 3.6 1.9 — 1.1 0.9 1.6 1.7 0.8 1.9

10.7

Poor and 

people 

couldn’t live 

there

2.7 5.0 4.7 4.5 8.9 6.1 6.7 4.4 4.6 4.4 3.8 2.1 3.3

Totally 

destroyed 9.2 14.1 11.0 14.3 25.0 14.4 20.0 10.3 10.1 10.3 8.8 6.2 11.3 13.8

Don’t know/

refused 1.5 1.8 1.4 3.2 2.2 1.8 — 1.7 1.7 1.6 1.2 1.7 2.2 1.2

Note: Weighted population estimates based on 594 survey responses.

Source: 2011 Property Owner Survey
Chapter 3: Repair Needs and Rebuilding 28

3.2 PROPERTY 

OWNERSHIP IN 2011

At the time of the property owner survey in early 

2011, about 82 percent of owners continued to own 

the property that was damaged in the storm, while 

the remaining 18 percent had sold or otherwise 

relinquished ownership of the property.

Exhibit 3-8 shows the ownership of properties in 

2011 in the sample overall and by state. Properties 

in Louisiana were significantly more likely to have 

changed ownership than properties in the other two 

states. In Louisiana, 20.5 percent of hurricane-damaged 

properties had a new owner as of 2011 compared with 

10.0 percent of properties in Mississippi and 12.3 

percent in Texas.

In most cases in which the property changed 

ownership, the property was sold. Among the group of 

former owners, 84.4 percent reported having sold the 

property and 5.4 percent said they had lost the home to 

foreclosure. The remaining 10.2 percent ceased owning 

the property for some other reason.

In Louisiana, 17.5 percent of 2005 owners sold their 

properties between 2005 and 2011, compared with 8.8 

percent in Mississippi and 5.0 percent in Texas. The 

higher share of sellers in Louisiana is partially explained 

by the option for that states’ residents of selling to the 

state through the CDBG program; 21 percent of sellers 

in Louisiana reported selling to the Louisiana Land 

Trust or to The Road Home program (exhibit 3-9). 

The higher proportion of sellers in Louisiana may also 

reflect the greater severity of hurricane damage in that 

state, making it less likely that owners would think it 

worthwhile to stay and invest in their properties and 

neighborhoods.

Exhibit 3-8. Ownership of Hurricane-Affected Properties in 2011

Louisiana

(N = 145,518)

Mississippi

(N = 47,626)

Texas

(N = 8,958)

All

(N = 202,102)

N % CI N % CI N % CI N % CI

Continuing 

owner 115,716 79.5 73.1–

 86.0 42,862 90.0 86.3– 93.7 7,857 87.7 79.3– 96.1 166,242 82.4 77.4– 87.3

Former 

owner 29,801 20.5 14.0–

 26.9 4,763 10.0 6.3–13.7 1,102 12.3 3.9– 20.7 35,666 17.6 12.7– 22.6

CI = 90 percent confidence interval.

Note: Weighted population estimates based on 722 survey responses.

Source: 2011 Property Owner Survey

Exhibit 3-9. Buyers for Properties Sold After the Hurricanes

N %

An individual person 21,679 72.0

Louisiana Land Trust/Road Home Program 5,287 17.6

Another type of buyer 1,073 3.6

A real estate company 860 2.9

A nonprofit organization 609 2.0

A bank or financial institution 604 2.0

Total 30,112 100.0

Note: Weighted population estimates based on 105 survey responses.

Source: 2011 Property Owner Survey
Chapter 3: Repair Needs and Rebuilding 29

Most transfers of ownership happened within 2 years of 

the hurricanes. As shown in exhibit 3-10, 75 percent of 

former owners stopped owning in 2007 or before, and 

another 14 percent stopped owning in 2008.

The property owner survey is not able to provide 

information on the 2011 condition of properties no 

longer owned by the 2005 owners, since it did not ask 

owners about the current condition of the properties 

that they no longer owned. This means that we do 

not have a measure by which to compare directly the 

2011 condition of properties that kept the same owner 

since 2005 with properties that changed owners. The 

windshield observations conducted in early 2010 

provide an approximate measure—in Louisiana and 

Mississippi only—of how properties that transferred 

ownership fared.

Applying the windshield observation data to the 

owner survey sample, we estimate that 76.9 percent 

of properties with the same owner in 2011 as in 

2005 were substantially rebuilt as of 2010, where 

substantially rebuilt means the property was rated by 

the observer as being in good or excellent condition, 

with no major repair needs.26 By contrast, we estimate 

that only 63.1 percent of properties that changed 

ownership were substantially rebuilt as of 2010. Given 

that properties that changed ownership were less likely 

to be rebuilt as of 2010, it is important to explore the 

property and owner characteristics associated with the 

change in ownership.

26 A detailed discussion of the rebuilding measure developed based on the windshield observations can be found in Turnham, et al. (2010), pp. 43–44.

Exhibit 3-10. Year that 2005 Owners Ceased Owning Hurricane-Damaged Property

Weighted population estimates based on 118 survey responses.

Source: 2011 Property Owner Survey

30%

40%

20%

35%

15%

25%

10%

5%

0%

2005 2006 2007 2008 2009 2010

10%

35%

30%

14%

5% 6%
Chapter 3: Repair Needs and Rebuilding 30

Property Characteristics Associated with 

Change in Ownership

There are several property-level characteristics that 

could be associated with the likelihood that a property 

damaged in the hurricanes would be sold (or otherwise 

change ownership) at some point afterwards. These 

characteristics include pre-storm attributes of the 

properties, such as tenure and house value in 2005, as 

well as the type and level of damage experienced during 

the hurricane.

Exhibit 3-11 examines four pre-storm property 

characteristics that could be associated with an owner’s 

decision to get rid of the property: tenure, presence of 

a mortgage, presence of insurance, and owner-reported 

home value. Properties that changed ownership after 

the hurricanes were more likely to be owner occupied 

at the time of the storms than properties that did not 

change ownership, and this difference is statistically 

significant at the 5 percent level. This result is 

interesting and somewhat surprising, given that one 

might hypothesize that homeowners are more attached 

to their properties than owners of rental properties. 

However, it may be that owners of rental properties 

were more able to hold on to a damaged property as an 

investment while homeowners needed either to rebuild 

the property or to sell it quickly in order to have a 

place to live.

Exhibit 3-11. Association Between Pre-Storm Property Characteristics and Change in Ownership

Property Changed 

Ownership

Property Did Not

Change Ownership

Percent CI Percent CI

Tenure*

Owner occupied 88.1 82.1–94.2 76.1 71.9–80.3

Renter occupied 8.5 2.9–14.1 20.5 16.3–24.8

Vacation/other 2.6 1.0–4.2 3.1 1.8–4.3

Don’t know/refused 0.8 0.0–2.1 0.3 0.0–0.8

Mortgage Presence

Mortgage 56.0 46.4–65.5 49.2 44.4–54.0

No mortgage 44.0 34.5–53.6 50.0 45.2–54.8

Don’t know/refused 0.0 0 0.8 0.2–1.5

Insurance Presence

Insurance (homeowners’ or flood) 86.0 79.2–92.8 80.3 77.0–83.6

No insurance 11.8 5.8–17.8 16.2 13.1–19.4

Don’t know/refused 2.2 0.0–5.1 3.4 2.1–4.8

Owner-Reported Value

Value less than $80,000 12.3 6.6–18.0 16.5 13.2–19.8

Value $80,000–$175,000 45.8 36.8–54.7 50.0 45.1–54.9

Value $175,000–$300,000 25.9 19.6–32.2 20.2 16.4–24.1

Value $300,000+ 12.8 6.6–19.0 8.0 5.1–10.8

Don’t know/refused 3.2 0.4–6.1 5.3 3.7–6.9

CI = 90 percent confidence interval. **p < 0.01; *p < 0.05; +p < 0.10.

Note: Weighted population estimates based on 702 survey responses.

Source: 2011 Property Owner Survey
Chapter 3: Repair Needs and Rebuilding 31

In addition to being more likely to be owner occupied, 

properties that changed ownership were also more 

likely to have had a mortgage, more likely to have 

had insurance, and more likely to have been valued at 

$175,000 at the time of the hurricanes, based on the 

owner’s assessment.27 These differences, however, are 

not statistically significant.

We also explored the relationship between the 

hurricane damage experienced by the property and 

the likelihood that the property had changed owners 

after 2005, using three measures of damage: the 

assessed damage amount reported by owners, whether 

the damage was from flooding or wind alone, and 

whether the damage had resulted in the structure 

needing to be leveled, condemned, or demolished. 

We find that the median assessed damage amount 

was higher for properties that had changed ownership 

after 2005, suggesting that owners with properties 

that had sustained more damage were more likely 

to leave their properties (exhibit 3-12). The median 

damage assessment reported by continuing owners was 

$78,125, compared with $98,720 for former owners. 

This difference is not statistically significant, however.

27 The interviewers asked owners how much they think the house and lot would 

have sold for in August 2005, around the time of the hurricanes.

Consistent with the higher damage assessment 

amounts for properties that had changed owners, 

these properties that changed owners after 2005 were 

also more likely to have had damage so substantial 

that the structure had been leveled, condemned, or 

demolished. Specifically, 37.6 percent of properties that 

had changed owners had been leveled, condemned, or 

demolished, compared with 20.0 percent of properties 

with the same owner in 2011 as 2005 (exhibit 3-13). 

This difference is statistically significant, indicating 

that 2005 owners were more likely to sell if their 

structure had been leveled or condemned, or had to 

be demolished. About one-fourth of the homes in 

Louisiana that were sold in this condition were sold to 

the Louisiana Land Trust (LLT) as part of The Road 

Home program. Among owners who reported selling to 

the LLT, 83 percent said the damage to the home was 

such that it was leveled, condemned, or demolished.

Exhibit 3-12. Total Dollar Amount of Assessed Damage as Reported by Owners

Property Did Not

Change Ownership

Property Changed

Ownership

Percentile CI Percentile CI

25th percentile $34,391 $25,749–$43,032 $63,921 $38,769–$89,072

Median $78,125 $68,933–$87,317 $98,720 $80,061–$117,378

75th percentile $143,407 $127,288–$159,525 $136,886 $125,710–$148,061

CI = 90 percent confidence interval.

Notes: Weighted population estimates based on survey responses from 289 continuing owners and 51 former owners who provided 

a damage assessment amount. For owners who reported receiving more than one damage assessment, we used the highest damage 

assessment reported.

Source: 2011 Property Owner Survey
Chapter 3: Repair Needs and Rebuilding 32

Exhibit 3-13. Association Between Damage Extent and Change in Ownership

Property Did Not

Change Ownership

Property Changed

Ownership

Percentile CI Percentile CI

Structure was leveled, 

demolished, or condemned 20.0 15.9–24.1 37.6 28.3–46.9

Structure was not leveled, 

demolished, or condemned 78.8 74.7–83.0 60.9 51.9–70.0

Don’t know/refused 1.2 N/A 1.5 N/A

Total 100 100

CI = 90 percent confidence interval. **p < 0.01; *p < 0.05; +p < 0.10.

Notes: Weighted population estimates based on 702 survey responses. Percentages do not sum to 100 because a small number of survey 

respondents did not answer the question.

Source: 2011 Property Owner Survey

Owner Characteristics Associated With Change 

in Ownership

In addition to looking at property characteristics, 

we also used the survey findings to explore owner 

characteristics that might be associated with the 

decision to sell or get rid of a hurricane-damaged 

property rather than to stay in the home and rebuild. 

For example, we hypothesized that such decisions 

might be conditioned by life stage (elderly might 

be less likely to move) and income (people with less 

resources might be more willing to sell than to stay 

and rebuild). We considered owner age, presence 

of dependents in household, disability status, prestorm income, and race. However, we did not find a 

statistically significant association between any of these 

owner characteristics and the likelihood that a property 

would have changed ownership after the hurricanes.

3.3 HOUSING CONDITIONS 

IN 2011

For properties that had the same owner in early 2011 

as in 2005, the owner survey provided the opportunity 

to collect information from those owners on the 2011 

condition of the property, taking into account external 

as well as internal systems and repair needs.

Exhibit 3-14 shows the condition of hurricanedamaged properties in early 2011 based on reports 

by continuing owners. The owner ratings of 2011 

housing conditions are quite different from the ratings 

of conditions before the hurricanes, which are shown 

in exhibit 3-1. Exhibit 3-14 shows that 74.6 percent of 

owners said their hurricane-damaged properties were in 

excellent or good condition as of early 2011, compared 

with 94.8 percent in 2005. More than 15 percent 

of owners rated their property as being in fair (10.8 

percent) or poor (4.9 percent) condition at the time 

of the survey, and 9.7 percent said it had been totally 

destroyed.28

28 The excellent or good category includes 56 cases (out of 588 surveyed) in which 

the hurricane-damaged residential structure was totally destroyed but the lot 

contains a second structure built to replace the one destroyed by the storm and 

rated by the owner as being in excellent or good condition.
Chapter 3: Repair Needs and Rebuilding 33

Exhibit 3-14. Owner-Reported Condition of Properties in Early 2011 by State and Overall

Note: Weighted population estimates based on 588 survey responses.

Source: 2011 Property Owner Survey

These owner-reported ratings of overall property 

condition in 2011 can be compared with the findings 

from the windshield observations on the condition of 

properties about a year earlier and based only on what 

could be seen from the outside. 29 It is important to 

note that the distributions are quite similar between 

the two surveys: 73.6 percent of properties were in 

excellent or good condition based on the windshield 

observations in 2010, 10.1 were in fair condition, 4.6 

percent were in fair condition, and 11.6 were destroyed 

or in the process of being rebuilt. This finding suggests 

that the owner-reported conditions among current 

owners are credible.

Housing Conditions in 2011 for Movers Versus 

Stayers

One question of interest to the study is how people 

who were unable to or chose not to move back to their 

homes at the time of the storm are faring in their new 

locations. Approximately one-fourth of the weighted 

survey sample—51,377 of 202,102—were people 

who in 2005 owned and lived on a property that was 

29 See Turnham, et al. (2010).

damaged by the hurricanes, but who as of early 2011 

were living elsewhere regardless of ownership. Slightly 

more than 10 percent of these people identified their 

current housing as being in the same neighborhood as 

the property they had owned in 2005, but most were 

living in a different neighborhood, county, or state. 

These people were also no longer all homeowners. As 

shown in exhibit 3-15, 60.4 percent lived in a home 

they owned, but 17.8 percent were renting a house, 

apartment, or mobile home; another 17.8 percent were 

living with family or friends (some rent free); and 2.8 

percent were living in a FEMA trailer or in some other 

situation.

80%

90%

100%

60%

70%

40%

50%

20%

30%

10%

0%

Louisiana

Poor

Totally destroyed

Fair

Excellent or good

Mississippi Texas Overall

74.8

11.6

6.1

7.5

16.1

0.4

9.7

11.2

8.4

74.6

8.9

70.6

9.8

10.8

4.9

74.6
Chapter 3: Repair Needs and Rebuilding 34

Exhibit 3-15. Current Housing of 2005 Owner-Occupiers Living Elsewhere in Early 2011

Percent Number

Living in a home that you own 60.4 31,011

Renting a house, apartment, or mobile home 17.8 9,128

Living with family or friends and not paying rent 10.8 5,557

Living with family or friends and paying part of the rent 7.0 3,598

FEMA trailer or other temporary housing provided after the storm 0.3 162

Some other housing situation 2.5 1,266

Don’t know/refused 1.3 654

Total 100.0 51,377

Note: Weighted population estimates based on 201 survey responses.

Source: 2011 Property Owner Survey

As described previously, the survey asked owners to 

rate the current condition of their housing, as of early 

2011. When comparing the responses of those people 

who in 2011 were living on the same property as in 

2005 (stayers) to the responses of people who had 

moved elsewhere (movers), we find that people who 

moved away rated the condition of their 2011 housing 

somewhat more highly than those who stayed, but that 

these differences are not statistically significant (exhibit 

3-16).

We find a greater difference in levels of satisfaction 

with the current neighborhood. Movers were 

significantly more like to be very satisfied with their 

2011 neighborhood than stayers. As shown in exhibit 

3-17, 70.4 percent of movers said they were very 

satisfied with their current neighborhood, compared 

with 47.8 percent of stayers. Even with small sample 

sizes, this is a statistically significant difference. Movers 

were also significantly more likely to describe their 

neighborhoods as very safe than stayers were, although 

in both cases 85 percent or more of respondents 

described their neighborhoods as either safe or very safe.

Exhibit 3-16. Owner-Reported Condition of Current Housing Occupied by Movers and Stayers

Movers Stayers

Number Percent CI Number Percent CI

Excellent or good condition 46,633 90.8 86.4–95.1 90,724 84.7 81.0–88.3

Fair condition 4,348 8.5 4.3–12.6 14,066 13.1 9.7–16.6

Poor condition 396 0.8 0.0–1.7 2,045 1.9 0.8–3.0

Don’t know/refused — — 322 0.3

Total 51,377 100.0 107,157 100.0

CI = 90 percent confidence interval.

Notes: Weighted population estimates based on 201 mover responses and 376 stayer responses. Among stayers, does not include survey 

respondents who indicated they lived in a FEMA trailer or other temporary housing.

Source: 2011 Property Owner Survey
Chapter 3: Repair Needs and Rebuilding 35

Exhibit 3-17. Satisfaction with Current Neighborhood for Movers and Stayers

Movers Stayers

Number Percent CI Number Percent CI

Very satisfied 36,158 70.4 64.1–76.7 52,125 47.8 43.4–52.2

Somewhat satisfied 12,222 23.8 18.3–29.3 37,305 34.2 30.0–38.4

Neither satisfied nor 

dissatisfied 1,829 3.6 0.9–6.3 4,746 4.4 2.6–6.1

Somewhat dissatisfied 495 1.0 0.0–1.9 11,035 10.1 7.6–12.6

Very dissatisfied 673 1.3 0.2–2.4 3,275 3.0 1.3–4.8

Total 51,377 100 108,486 100

CI = 90 percent confidence interval.

Note: Weighted estimates based on 201 mover responses and 381 stayer responses.

Source: 2011 Property Owner Survey

Given the level of satisfaction expressed with their new 

neighborhoods, it is not surprising that most people 

who moved away from their 2005 neighborhood did 

not plan to return, regardless of housing condition. 

Overall, two-thirds (66 percent) of those who moved to 

a different neighborhood after the hurricanes reported 

that they were not interested in moving back. Among 

all movers, the three most common reasons for not 

having moved back were a preference for the current 

neighborhood, a belief that the old neighborhood was 

not safe, and a belief that the old neighborhood was 

not ready for people to move back (exhibit 3-18).

Exhibit 3-18. Reasons for Not Returning to Pre-Hurricane Neighborhood

Notes: Weighted population estimates based on 171 mover responses. Exhibit does not include movers who moved to a different property but 

stayed within the same neighborhood.

Source: 2011 Property Owner Survey

Neighborhood is not safe

Prefer current neighborhood

Cannot afford to move

Neighborhood is not ready

Family no longer lives there

Cannot find housing there

Poor health

Cannot find a good job there

Divorce or widowhood

No schools for my children Small reason

Big reason

60%

36%

34%

35%

24%

27%

15%

15%

14%

10%

16%

10%

12%

8%

12%

7%

10%

7%

4%

7%

0% 20% 40% 60% 80%
Chapter 3: Repair Needs and Rebuilding 36

3.4 REBUILDING ACTIVITY 

SINCE 2005

This section describes the state of rebuilding in early 

2011 in response to hurricane damage. In contrast to 

the windshield survey, which either directly observed or 

(more commonly) inferred rebuilding activity based on 

visual appearance, the owner-reported findings in this 

report provide a richer depiction of rebuilding activity. 

These data address the completion level, scheduling, 

cost, and extent of rebuilding, or the explicit reasons 

for not rebuilding—information that is obviously not 

available through visual observation.

Rebuilding Activity and Completion

Overall, we estimate that about three-fourths (77.0 

percent) of owners of properties with major or severe 

storm damage on significantly affected blocks had done 

some rebuilding in the 5.5 years since the hurricanes. 

As shown in exhibit 3-19, as of early 2011, 57.5 

percent of owners had completed rebuilding, and 

19.5 had started rebuilding but had given up, not yet 

completed the work, or sold the property before they 

completed the work. We estimate that 23.0 percent of 

owners did no rebuilding at all.

Exhibit 3-19. Extent of Rebuilding Activities

Number Percent CI

Repair or rebuilding completed 116,165 57.5 53.2–61.8

Repair or rebuilding started but not completed 39,493 19.5 16.3–22.8

Repair or rebuilding never started 46,443 23.0 18.0–28.0

Total 202,102 100

CI = 90 percent confidence interval.

Note: Weighted population estimates based on 722 survey responses.

Source: 2011 Property Owner Survey

Exhibit 3-20 shows that owners in Louisiana were 

somewhat less likely to have completed rebuilding than 

owners in the other states, but the differences between 

the distributions are not statistically significant. The 

estimates in exhibits 3-19 and 3-20 are based on survey 

responses from all owners surveyed, including those 

who sold or otherwise got rid of the property at some 

point after the hurricanes.

As described previously in section 3.2, we estimate that 

18 percent of the 2005 owners of hurricane-damaged 

properties on significantly affected blocks no longer 

owned the property in 2011. Not surprisingly, former 

owners are significantly less likely to have engaged in 

any rebuilding (before the property changed hands) 

than owners who held on to the property (see exhibit 

3-21).
Chapter 3: Repair Needs and Rebuilding 37

Exhibit 3-20. Extent of Rebuilding Activities by State

Note: Weighted population estimates based on 467 survey responses in Louisiana, 171 survey responses in Mississippi, and 84 survey 

responses in Texas.

Source: 2011 Property Owner Survey

80%

90%

100%

60%

70%

40%

50%

20%

30%

10%

0%

Louisiana

N = 145,518

Mississippi

N = 47,626

Texas

N = 8,958

Repair/rebuilding completed

Repair/rebuilding started but not completed

No repairs or rebuilding

24.8%

19.4%

55.8% 61.2% 64.9%

17.8%

21.0%

21.1%

14.0%

80%

90%

100%

60%

70%

40%

50%

20%

30%

10%

0%

Continuing Owners

N = 166,436

Former Owners

N = 35,666

Any repair or rebuilding

14% No repair or rebuilding

86%

34%

66%

Exhibit 3-21. Rebuilding by Continuing and Former Owners

Note: Weighted population estimates based on 594 survey responses for continuing owners and 127 survey responses for former owners.

Source: 2011 Property Owner Survey

ongoing repair or rebuilding activity.30 Overall, we estimate that about 10 percent of all Because the 

continuing owners of hurricane-damaged properties on 

significantly affected blocks had work actively under 

way as of early 2011. As a point of comparison, the 

estimates from the windshield observations conducted 

in 2010 were that about 5 percent of properties with 

major or severe hurricane damage had observable 

owners can report on interior work not observable from 

the street, these estimates are not inconsistent.

Among continuing owners who have not done any 

rebuilding as of 2011, about two-thirds (63 percent) 

30 Turnham, et al. (2010), p. 44.
Chapter 3: Repair Needs and Rebuilding 38

reported that they do not intend to rebuild or do 

not know if they plan to rebuild. This is consistent 

with our observation that most owners who rebuilt 

(including continuing and former owners) began 

rebuilding in 2005 and 2006 (exhibit 3-22) and, if 

they completed rebuilding, finished the work by 2008 

(exhibit 3-23).

Owners who completed rebuilding did so faster in 

Texas and Mississippi than in Louisiana. As shown 

in exhibit 3-24, 40 percent of Texas owners who 

completed rebuilding did so in 2005, compared with 

20 percent in Mississippi and 10 percent in Louisiana. 

By 2006, about three-fourths of the owners in Texas 

and Mississippi who would complete rebuilding had 

done so, compared with less than one-half the owners 

in Louisiana. This may be a further indication of the 

greater severity of damage in Louisiana, requiring 

more time to rebuild, as well as contention over flood 

damage versus other hurricane damage and what 

damages flood and homeowners insurance would cover. 

As shown previously in exhibit 3-3, Louisiana had the 

highest assessed damage amounts of the three states, 

although Texas owners were most likely to report their 

properties had been condemned or had had to be 

demolished.

Exhibit 3-22. Year Repair or Rebuilding Work Started

Note: Weighted population estimates based on 458 survey responses from owners who engaged in some repair or rebuilding work to their 

hurricane-damaged property between 2005 and early 2011.

Source: 2011 Property Owner Survey

30%

45%

50%

40%

20%

35%

15%

25%

10%

5%

0%

2005 2006 2007 2008 2009 2010

47%

35%

12%

4%

1% 1%
Chapter 3: Repair Needs and Rebuilding 39

Exhibit 3-23. Year Repair or Rebuilding Work Was Completed

Note: Weighted population estimates based on 348 survey responses from owners who completed repair or rebuilding work to their 

hurricane-damaged property.

Source: 2011 Property Owner Survey

Exhibit 3-24. Year Repair or Rebuilding Work Was Completed by State, Cumulative

Note: Weighted population estimates for owners who completed repair or rebuilding based on 208 survey responses in Louisiana, 87 survey 

responses in Mississippi, and 57 survey responses in Texas.

Source: 2011 Property Owner Survey

30%

45%

40%

20%

35%

15%

25%

10%

5%

0%

2005 2006 2007 2008 2009 2010 2011

41%

13%

24%

11%

4% 6%

1%

Louisiana

Mississippi

Texas

80%

90%

100%

60%

70%

40%

50%

20%

30%

10%

0%

2005 2006 2007 2008 2009 2010 2011
Chapter 3: Repair Needs and Rebuilding 40

Elevation Activity and Completion

One particular kind of rebuilding of interest to this 

study is the elevation of properties located within 

100-year flood plains, in anticipation of future 

possible disasters. FEMA established advisory base 

flood elevations (ABFEs) for several of these regions 

after the storms, which, when formally adopted by the 

municipalities, become base flood elevations (BFEs). 

CDBG funds in each state also included elevation 

grant options that stipulated specific requirements for 

elevating homes. For example, Louisiana’s The Road 

Home Elevation Incentive program required grantees 

to elevate their homes within 3 years of grant receipt 

to the minimum ABFE requirements for a particular 

parish or the BFE levels in effect on August 26, 2006.

For those receiving other CDBG funding, the 

requirements as well as the specific height standards 

were less clear. In Louisiana, Option 1 recipients 

were required to comply with BFEs adopted by local 

government. In Mississippi, all Phase I and Phase II 

recipients of funds were required to elevate to the 

advisory BFEs if they rebuilt or substantially repaired, 

but recipients who only repaired did not seem to 

understand the terms of this constraint. 

Elevation grants were disbursed to recipients in 

stages upon proof of permit and then certification. 

Many of the Mississippi recipients, however, did not 

live in the flood plain and were therefore not likely 

to be required to elevate. In Southeast Texas, an 

additional grant was available for properties located 

within certain flood zones. CDBG elevation grants 

involved attaching covenants to affected properties 

that were later sold. These requirements were unclear, 

and this ambiguity was further compounded by the 

inconsistent availability of FEMA, ABFE, and BFE 

recommendations across sites.

The owner survey results regarding the properties’ 

pre-storm elevation levels are depicted in exhibit 

3-25, which shows that 60.8 percent of properties 

were not elevated at all and 28.2 percent of properties 

were elevated less than 3 feet across all states. The 

2010 windshield observations found that 59 to 63 

percent of properties were rated in excellent or good 

condition, and therefore presumed to have completed 

rebuilding activities, but were still elevated less than 3 

feet from street level.31 This suggests that only minimal 

elevation had occurred, if any. Given that a substantial 

share of housing in New Orleans was already built 

with some elevation, much of the elevation observed 

among rebuilt properties probably existed before the 

hurricanes.

31 Turnham, et al. (2010), p. 48.

Exhibit 3-25. Pre-Hurricane Elevation Status

Status

Louisiana

N = 133,003

Mississippi

N = 45,456

Texas

N = 7,134

Total

N = 185,594

% CI % CI % CI % CI

Not 

elevated 61.7 54.9–68.4 58.8 49.0–68.6 58.8 43.5–74.1 60.8 55.4–66.3

Elevated at or 

less than 3 feet 27.3 21.7–33.0 28.7 20.1–37.3 40.2 24.9–55.5 28.2 23.5–32.8

Elevated more 

than 3 feet 11.0 7.3–14.7 12.5 6.2–18.9 1.0 0.3–1.8 11.0 8.0–14.0

CI = 90 percent confidence interval.

Note: Weighted population estimates based on 656 survey responses.

Source: 2011 Property Owner Survey
Chapter 3: Repair Needs and Rebuilding 41

Indeed, few respondents in the 2011 property owner 

survey reported elevating their homes as part of their 

repair and rebuilding activities. As shown in exhibit 

3-26, across the three states we estimate that less than 

10 percent of owners of properties with major or severe 

storm damage on SABs had completed elevation work 

on their properties. This modest level of elevation 

activity is consistent with the windshield observation 

findings and has also been documented elsewhere.32

It is true that not all properties need to elevate. We 

attempted to determine the number of properties in 

the owner survey sample that would need to be elevated 

32 For example, a recent report by the HUD Office of Inspector General for Investigation’s Inspections and Evaluations Division, titled “Inspection of the State of 

Louisiana’s The Road Home Elevation Incentive Program: Homeowner Compliance” (March 2010), found that a high percentage of recipients of CDBG-funded 

elevation grants had not elevated their properties.

based on the ABFE or BFE formula, but could not do 

so, because information on the elevation requirements 

was not available for a large share of sampled 

properties. Nevertheless, owners who received CDBG 

grants seem more likely to have completed elevation 

activity, perhaps as a consequence of the terms of 

award. About two-thirds of the owners who completed 

elevation work in Louisiana and Mississippi were 

CDBG recipients, suggesting that CDBG recipients 

in those states were more likely to elevate than 

nonrecipients, although the difference in Mississippi is 

not statistically significant. In Texas, most owners who 

elevated did not receive CDBG, but this likely reflects 

the much lower rates of CDBG receipt in that state 

overall (see chapter 5, exhibit 5-1).

Exhibit 3-26. Elevation Activity

Louisiana

N = 10,698

Mississippi

N = 2,769

Texas

N = 1,073

Total

N = 14,540

% CI % CI % CI % CI

No elevation 

work started 89.6 86.7–92.6 92.9 88.2–97.6 84.1 73.9–94.3 90.2 87.8–92.7

Elevation work 

started but not 

completed

1.6 0.4–2.8 — — — — 1.1 0.3–2.0

Elevation work 

completed 8.3 5.7–10.9 7.1 2.4–11.8 15.7 5.5–25.9 8.3 6.1–10.5

Refused 0.1 0.0–0.3 — — — — 0.1 0.0–0.2

Don't know 0.4 0.0–1.2 — — 0.2 0.0–0.6 0.3 0.0–0.7

CI = 90 percent confidence interval.

Note: Weighted population estimates based on 512 survey responses.

Source: 2011 Property Owner Survey

Exhibit 3-27. Completed Elevation Activity by CDBG Receipt

Louisiana

N = 133,003

Mississippi

N = 45,456

Texas

N = 7,134

Total

N = 185,594

% CI % CI % CI % CI

CDBG recipients who 

completed elevation work 63.9 50.8–77.0 67.5 40.8–94.3 5.6 0.0–

12.1 59.8 49.8–69.8

Non-CDBG recipients who 

completed elevation work 36.1 23.0–49.2 32.5 5.7–59.2 94.4 88.0–100 40.2 30.2–50.2

CDBG = Community Development Block Grant. CI = 90 percent confidence interval.

Note: Weighted population estimates based on 51 responses.

Sources: 2011 Property Owner Survey; CDBG administrative data
Chapter 3: Repair Needs and Rebuilding 42

Extent and Cost of Rebuilding

In most cases, the rebuilding activities undertaken 

by 2005 owners consisted of repairs to an existing 

structure rather than construction of a completely new 

home. As shown in exhibit 3-28, we estimate that in 

9 of 10 cases in which rebuilding work was initiated 

or completed between 2005 and 2011, the work 

involved repairs to an existing structure rather than the 

construction of a new house.

The survey asked owners who had done at least some 

rebuilding work to estimate the total cost of that 

work to date, including any elevation work. About 

two-thirds of owners (66.4 percent) reported total 

costs of $50,000 or more, including 36.7 percent who 

reported costs of $100,000 or more (exhibit 3-29). 

The estimates include owners who started but did not 

complete the rebuilding work, as well as those who 

completed it. Limiting the sample to owners who 

completed the work does not change the distribution.

Exhibit 3-28. Type of Rebuilding

Number Percent CI

Building a new house/building 8,621 5.6 3.6–7.6

Repairing the existing structure 143,598 93.1 90.9–95.4

Don’t know 1,946 1.3 0.4–2.1

Total 154,166 100.0

CI = 90 percent confidence interval.

Note: Weighted population estimates based on 512 survey responses.

Source: 2011 Property Owner Survey

Exhibit 3-29. Estimated Cost of Repairs or Rebuilding to Address Hurricane Damage

Note: Weighted population estimates based on 465 survey responses.

Source: 2011 Property Owner Survey

30%

40%

20%

35%

15%

25%

10%

5%

0%

Less than $5,200 At least $5,200 

but less than 

$10,000

At least $10,000 

but less than 

$50,000

$100,000 or 

more

At least $50,000 

but less than 

$100,000

5.7% 4.3%

23.6%

29.7%

36.7%
Chapter 3: Repair Needs and Rebuilding 43

Exhibit 3-30 compares the distribution of estimated 

rebuilding costs by state for all owners who undertook 

some repair or rebuilding to address hurricane damage. 

In general, repair and rebuilding costs are highest in 

Louisiana and lowest in Texas; there is a significant 

difference at the 1 percent level in rebuilding cost 

between properties in Louisiana and Texas, between 

properties in Louisiana and Mississippi, and between 

properties in Texas and Mississippi. This is consistent 

with the higher assessed damage amounts in Louisiana 

reported in exhibit 3-3 and with the lower assessed 

damage amounts in Texas.

Additional analysis of rebuilding activity based on 

the level of neighborhood damage is also revealing. 

In particular, we look at blocks with concentrated 

damage—that is, where FEMA assessments reported 

more than 50 percent of properties on the block 

as having major or severe damage.33 One possible 

hypothesis would be that owners of properties on these 

more heavily damaged blocks would have less incentive 

to rebuild, and would be less satisfied with their 

neighborhoods after the storm, than those owners with 

properties on less damaged blocks. However, as shown 

in exhibit 3-31, there is no significant difference in 

rebuilding rates between these two kinds of properties 

overall. The sole exception to this is the difference 

between properties on blocks with concentrated 

damage in Mississippi and properties not on these 

blocks, which is statistically significant at the 10 

percent level. For these reasons, funding for rebuilding 

may have leveled out the difference.

33 Note that only properties with FEMA assessments were studied to determine 

the level of block damage, although this is believed to be a good mirror for total 

properties on the block. We estimate the share of all the SABs in the sample that 

have this definition of concentrated damage to be at 67.8 percent.

Exhibit 3-30. Estimated Cost of Repairs or Rebuilding to Address Hurricane Damage by State

Louisiana Mississippi Texas

Percent 90% CI Percent 90% CI Percent 90% CI

Less than $5,200 5.8 3.1–8.5 2.9 0.9–4.9 9.8 2.8–16.7

At least $5,200 but less than 

$10,000 2.1 0.9–3.3 8.6 2.6–14.5 6.2 0.0–12.7

At least $10,000 but less than 

$500,000 16.8 13.2–20.3 30.6 21.0–40.2 48.3 32.9–63.7

At least $50,000 but less than 

$100,000 29.3 24.7–33.9 25.0 18.1–31.8 9.9 2.2–17.6

$100,000 or more 38.6 33.1–44.2 25.2 15.6–34.9 5.5 0.0–11.5

Don’t know/refused 7.4 5.2–9.6 7.7 3.1–12.3 20.3 8.9–31.7

CI = 90 percent confidence interval.

Note: Weighted population estimates based on 512 property owners who conducted repairs addressing damage inflicted from the 

hurricanes.

Source: 2011 Property Owner Survey
Chapter 3: Repair Needs and Rebuilding 44

Exhibit 3-31. Association Between Rate of Rebuilding and Blocks with Concentrated Damage

Properties on Block with 

Concentrated Damage

Properties on Block without 

Concentrated Damage

Rebuilding CI Rebuilding CI

Texas (N = 7,857) 50.0 0.0–100 70.7 58.3–83.1

Mississippi (N = 42,037)+ 70.4 59.9–80.9 87.4 77.2–97.7

Louisiana (N = 114,474) 74.2 69.5–79.0 77.8 67.6–88.1

Rebuilding rate 73.3 68.9–77.7 79.0 72.5–85.4

CI = 90 percent confidence interval. **p < 0.01; *p < 0.05; +p < 0.10.

Notes: Weighted population estimates based on 588 owners who currently own the property and report don’t know/refused. Only two 

properties in Texas were on blocks with concentrated damage.

Source: 2011 Property Owner Survey

As shown in exhibit 3-32, we found that owners of 

storm-damaged properties located on blocks with 

concentrated damage were less likely to be very satisfied 

with their properties in 2011 than owners of properties 

located on blocks where there was not concentrated 

storm damage. This difference is statistically significant 

at the 5 percent level. We found no significant 

difference in pre-storm neighborhood satisfaction 

between owners on blocks with concentrated damage 

and owners on blocks without that extensive damage, 

suggesting that the difference in satisfaction observed 

in 2011 is likely to be related to the level of damage 

that occurred (and that might still remain) on the 

block.

Exhibit 3-32. Association Between Pre-Storm and Post-Storm Neighborhood Satisfaction and Blocks 

with Concentrated Damage

Property on Block with 

Concentrated Damage

Property on Block without

Concentrated Damage

Percent 90% CI Percent 90% CI

Pre-Storm Neighborhood Satisfaction

Very satisfied 84.6 80.5–88.8 81.6 74.2–88.9

Somewhat satisfied 13.3 9.6–17.0 17.2 10.3–24.2

Neither satisfied nor dissatisfied 0.9 0.0–1.8 0.1 0.0–0.2

Somewhat dissatisfied 1.2 0.0–2.5 0.4 0.0–0.1

Very dissatisfied 0.0 — 1.1 0.0–2.8

Post-Storm Neighborhood Satisfaction*

Very satisfied 44.4 38.3–50.5 54.2 46.1–62.2

Somewhat satisfied 34.2 29.1–39.3 36.1 28.1–44.0

Neither satisfied nor dissatisfied 4.4 2.5–6.3 4.9 0.1–8.9

Somewhat dissatisfied 12.8 9.3–16.4 4.5 1.5–7.4

Very dissatisfied 4.2 1.7–6.7 0.4 0.0–1.0

CI = 90 percent confidence interval. **p < 0.01; *p < 0.05; +p < 0.10.

Notes: Weighted population estimates based on 370 survey responses who owned the property before the hurricane and currently resides 

on the property. To conduct a valid significance test, all response categories need at least one observation. Because no owners residing 

in concentrated damage blocks reported being very dissatisfied with their neighborhood before the hurricane, any owners residing in 

nonconcentrated damage blocks that reported being very dissatisfied with their neighborhood were excluded from the significance test.

Source: 2011 Property Owner Survey
Chapter 3: Repair Needs and Rebuilding 45

3.5 REASONS FOR NOT 

REBUILDING

The owner survey also collected information on the 

reasons for not rebuilding from owners who reported 

that they did no repair or rebuilding work on their 

hurricane-damaged properties. The survey presented 

a list of possible reasons for not rebuilding and asked 

respondents to characterize each one as a big reason, 

a small reason, or not a reason for their decision not 

to rebuild. Respondents could identify more than one 

reason as a big reason. Exhibit 3-31 presents the most 

common big reasons for not rebuilding identified by 

survey respondents.

An important finding—and one that is further explored 

in chapter 5 with regard to CDBG funding—is that 

the most common reasons for not rebuilding involved 

owners not having sufficient funds to pay for the work. 

This was expressed in terms of not having enough 

money on hand to do the work (cited as a big reason 

by 67.0 percent of owners), not being able to get a loan 

to do the work (51.1 percent), or waiting for a grant or 

other kind of financial assistance to get the work done 

(35.7 percent). Furthermore, the data suggest that the 

inability to obtain flood insurance—either not being 

able to qualify or not being able to afford it—was a 

big reason for 36.5 percent of the owners who did no 

rebuilding.

Other big reasons for not rebuilding were a lack of 

contractors or volunteer labor to do the work (33.3 

percent) and the homeowners’ interest in selling the 

property (33.8 percent). (Note that the estimates 

presented in exhibit 3-33 include owners who no 

longer owned as of early 2011.) For about one in 

four owners, the general lack of rebuilding in the 

neighborhood—either few households returning 

to the neighborhood or incomplete infrastructure 

(schools, roads, and sewers)—was a big reason for not 

rebuilding.

Exhibit 3-33. Big Reasons for Not Rebuilding Among Owners Who Undertook No Repair and 

Rebuilding

Note: Weighted population estimates based on 205 survey responses.

Source: 2011 Property Owner Survey

Waiting for a grant or other financial assistance

Cannot obtain/afford flood insurance

Cannot get a loan to pay for the work

Don’t have enough money to do the work

Waiting for contractors or volunteer labor

Considering selling the property

Waiting for more people in neighborhood to rebuild

Waiting for infrastructure/schools to be completed

Waiting for new elevation requirements

Waiting for the economy to improve

Do not want to move back/settled where I am

Waiting for permits to do the work

36.5%

51.1%

67.0%

35.7%

33.8%

33.3%

25.1%

23.4%

18.8%

17.1%

13.5%

11.5%

0% 20% 40% 60% 80%
Chapter 3: Repair Needs and Rebuilding 46

For the 33 percent of homeowners who did not cite 

having money on hand as a big reason, the big reasons 

cited were also primarily not related to funding access; 

their most common big reason was that they were 

considering selling the property (reported by 46.5 

percent of this group). Waiting for other infrastructure, 

not wishing to resettle in the home (presumably 

reported by households who had moved but still owned 

the house), and waiting for contractors or volunteer 

labor were other big reasons for this group’s decision 

not to rebuild.

3.6 SUMMARY OF 

CHAPTER FINDINGS

This chapter presents findings from the property owner 

survey on the pre-hurricane and current condition of 

properties that sustained major storm damage and were 

located on blocks where at least two other housing 

units suffered major storm damage as well.

Pre-Storm and Post-Storm Housing Condition

The survey results suggest that most owners of stormdamaged properties on significantly affected blocks 

thought them to be in good condition before the 

2005 hurricanes. More than 90 percent of owners in 

Louisiana and Mississippi and 85 percent of owners in 

Texas rated their homes as being in excellent or good 

condition before the hurricanes, and no more than 2 

percent of owners in any state rated them as being in 

poor condition. By contrast, at the time of the property 

owner survey in 2011, the proportion of owners rating 

the condition of their properties as excellent or good 

ranged from 75 percent in Louisiana to 71 percent 

in Texas. Although these ratings were available only 

for the subset of survey respondents who still owned 

the property in 2011, we can infer from the 2010 

windshield observations that properties that changed 

ownership after the hurricanes were less likely to be in 

good condition as of 2011 than those that remained 

with the same owner. The 2011 reports of conditions, 

also, corroborated the 2010 windshield findings closely.

Hurricane Damage

The fact that owners rated their housing to be in worse 

condition in early 2011 than before the hurricanes 

reflects a combination of the damage wrought by the 

storms and the incomplete rebuilding efforts to date. 

All of the properties selected for the owner survey were 

assessed by FEMA as having major or severe hurricane 

damage, and owners confirmed that, reporting median 

assessed damage amounts of $89,523 in Louisiana and 

$74,227 in Mississippi. The median assessed damage 

amount in Texas was lower ($35,124), reflecting lower 

rates of damage from flooding in that state. But Texas 

owners nevertheless reported that about one-third of 

their properties were demolished, leveled, or had had 

their structure condemned after the hurricanes.

Decision to Stay or Sell

After the hurricanes, owners faced a decision whether 

to sell their properties or to stay and rebuild. The 

owner survey results suggest that 82 percent of owners 

of severely damaged properties on significantly 

affected blocks retained ownership of their homes, 

while 18 percent got rid of the property, primarily by 

selling to a private owner. Most people who sold or 

otherwise transferred ownership did so within 2 years 

of the hurricanes, by 2007. We found few statistically 

significant differences between the pre-storm 

characteristics of properties that changed owners versus 

those retained by the 2005 owners, except that rental 

properties were more likely to be kept than homeowner 

properties. This somewhat counter-intuitive finding 

might reflect the fact that owners of rental properties 

are more able to hold on to those properties without 

rebuilding, whereas homeowners who need to rebuild 

also need to find a new place to live. The extent of 

damage does appear to be a predictor of whether a 

storm-damaged property changed owners: properties 

where the structure had been condemned or had to be 

leveled or demolished due to hurricane damage were 

significantly more likely to be sold than properties with 

less extensive damage.
Chapter 3: Repair Needs and Rebuilding 47

Housing Conditions and Neighborhood 

Satisfaction for Movers and Stayers

As of 2011, about one-fourth of the owner survey 

sample reported that they were no longer living in the 

house that was damaged in the storm. This includes 

owners who sold their properties, as well as people 

who retained ownership of the damaged property but 

are living elsewhere. About two-thirds of surveyed 

homeowners still lived in a house that they owned, but 

18 percent were renting, and the rest were either living 

with family or friends (18 percent) or in some other 

type of housing situation (3 percent). Owners who were 

no longer living in the same neighborhood as they were 

in 2005 were significantly more likely to report being 

very satisfied with their new neighborhood, compared 

with owners who stayed in the same neighborhood 

as in 2005. Owners in new neighborhoods were 

also significantly more likely to describe those 

neighborhoods as very safe during the day and at night. 

Not surprisingly, in light of these responses, two-thirds 

of owners in new neighborhoods had no plans to move 

back. Among all movers, the three most common 

reasons for not having moved back were a preference 

for the current neighborhood, a belief that the old 

neighborhood was not safe, and a belief that the old 

neighborhood was not ready for people to move back.

Rebuilding Activity and Completion

Among all owners, including those who had sold 

their properties, slightly more than three-fourths (77 

percent) reported that they had done some rebuilding 

work to address hurricane damage. In most cases, the 

rebuilding consisted of repairs to an existing structure 

rather than construction of a completely new home. As 

might be expected, continuing owners were much more 

likely to have done some rebuilding work (86 percent) 

than owners who had sold or otherwise relinquished 

ownership of the property (34 percent). Among 

continuing owners who have not done any rebuilding 

as of 2011, about two-thirds (63 percent) reported that 

they do not intend to rebuild or do not know if they 

plan to rebuild. This is consistent with the finding that 

most owners who did any rebuilding began the work 

in 2005 and 2006 and, if they completed rebuilding, 

finished it by 2008. Not many 2005 owners are still 

actively rebuilding their properties, although properties 

that have been sold may be being worked on by their 

new owners.

Few survey respondents reported doing elevation work 

as part of their rebuilding. Across the three states, 

we estimate that less than 10 percent of owners of 

properties with major or severe storm damage on SABs 

had completed elevation work on their properties. This 

modest level of elevation activity is consistent with the 

windshield observation findings.

Owners of properties whose neighbors also experienced 

extensive damage (that is, properties on blocks where 

more than one-half the properties experienced major or 

severe damage per FEMA assessments) did not report 

significantly different rebuilding rates than owners of 

properties on less severely damaged blocks. This finding 

contrasts with the hypothesis that property owners in 

severely affected neighborhoods would be less likely 

to rebuild, and it suggests that rebuilding decisions 

were based more on individual owner circumstances. 

The owners of properties on severely damaged blocks 

reported being significantly less satisfied with their 

neighborhoods currently, however.

Among owners who did not rebuild, the most 

commonly cited reason was not having sufficient funds 

to pay for the work. This was expressed in terms of 

not having enough money on hand to do the work, 

not being able to get a loan to do the work, or waiting 

for a grant or other kind of financial assistance to get 

the work done. The inability to obtain flood insurance 

was another important reason reported by more than 

one-third of owners who did not rebuild. For owners 

who did not rebuild but did not cite lack of funding as 

a reason, nearly one-half reported delaying rebuilding 

because they were considering selling. Similarly, 

for owners who ended up selling their property, the 

decision to sell was also an important reason for not 

rebuilding, just as the inability or unwillingness to 

engage in rebuilding was likely part of the reason 
Chapter 3: Repair Needs and Rebuilding 48

for selling. The property and owner characteristics 

associated with rebuilding among continuing owners, 

most but not all of whom rebuilt, are described and 

analyzed in chapter 4. Chapter 5 then explores the 

relationship between the availability of financial 

assistance, especially CDBG grants, and rates of 

rebuilding.
Chapter 4: Owner and Property Factors Affecting Rates of Rebuilding 49

4. OWNER AND PROPERTY 

FACTORS AFFECTING 

RATES OF REBUILDING

While the preceding chapter provides 

descriptions of physical conditions, 

repair, and rebuilding, this chapter 

considers the relationships among 

property and owner characteristics and rebuilding. The 

chapter makes use of the new information obtained 

through the owner survey—on pre-storm housing 

characteristics, owner characteristics, and level and 

type of damage as reported by owners—to supplement 

the analysis conducted in the Phase I report on the 

property and neighborhood characteristics associated 

with rebuilding.

The Phase I report used a measure of rebuilding 

constructed from the 2010 windshield observation 

to analyze factors related to rebuilding. The 

factors analyzed included pre-storm neighborhood 

characteristics (based on 2000 Census data), severity 

of hurricane damage (based on the FEMA assessment), 

and receipt of CDBG disaster assistance (based on 

CDBG administrative data). From that analysis, the 

severity of damage was determined to be a strong 

negative predictor of rebuilding. The median home 

value in 2000 in the neighborhood where a property 

was located was a significant, positive predictor 

of rebuilding. We also found that properties were 

more likely to be rebuilt if they were located in 

neighborhoods with higher percentages of Black or 

African American and Hispanic households before the 

hurricanes.

This chapter uses an alternative measure of rebuilding 

based on the owner assessment of the condition of the 

property as of 2011 and focusing on continuing owners 

(that is, people who still own the storm-damaged 

property) only. Section 4.1 discusses this alternative 

measure of rebuilding. The chapter explores the owner 

and property characteristics that could be associated 

with rebuilding using cross-tabulations (sections 

4.2–4.3) and multivariate analysis (section 4.4). Most 

of the characteristics that we examined were found 

not to have a statistically significant association with 

rebuilding. The multivariate analysis identifies which 

characteristics are most relevant for understanding the 

factors that affect rates of rebuilding.34

4.1 DEFINITION OF 

REBUILDING

Several options were potentially available as a measure 

of rebuilding for this analysis, including one from 

the windshield observations conducted in early 2010 

and two from the property owner survey. We used a 

measure of rebuilding from the owner survey that was 

based on the owner ratings of the condition of their 

properties as of early 2011. Properties were considered 

to be rebuilt as of 2011 if the owner of the property 

rated its current condition as excellent or good. Since 

all properties in the survey sample were assumed to 

have hurricane damage,35 a property that is in excellent 

or good condition as of 2011 can be assumed to have 

been substantially repaired or rebuilt.

The measure of rebuilding used in this chapter is 

similar to the measure of rebuilding used in the Phase 

I report based on windshield observation in 2010: 

properties assessed by FEMA as having major or severe 

damage in 2005 that were rated by observers as being 

34 The relationship between rebuilding and the presence of CDBG and other funding sources is discussed in chapter 5.

35 As discussed in appendix C, in Texas the owner survey sample included 20 properties that were not designated by FEMA as having major or severe damage but 

that nonetheless received CDBG assistance. These properties were included in 

the survey sample to increase the number of CDBG recipients in the sample, and 

because representatives of the CDBG program in Texas told us that the FEMA 

designations were not accurate in Texas, and that properties that received CDBG 

assistance would have had major or severe damage confirmed via state assessment.
Chapter 4: Owner and Property Factors Affecting Rates of Rebuilding 50

in excellent or good condition in 2011 (with no major 

repair needs) were assumed to have been substantially 

rebuilt. There are two key differences between the 

owner-based measure of rebuilding reported in this 

chapter and the windshield-based measure used in the 

Phase I report:

•	The owner-based measure provides more recent 

information (early 2011 versus early 2010). 

•	The measure is based on the owner’s more detailed 

knowledge of the condition and repair needs of the 

property, particularly interior conditions that are 

not observable from the sidewalk vantage point of 

the windshield observers.

Another difference between the owner-based measure 

and the windshield-based measure is that the ownerbased measure of rebuilding is available only for those 

properties that had the same owner in 2011 as in 2005, 

82 percent of the survey sample. This is because the 

survey did not ask former owners (those who sold their 

homes, often several years before the survey) to assess 

the 2011 condition of the property they no longer 

owned. By comparison, the windshield observations 

cover 88 percent of the owner survey sample.36

An alternative to the measure of rebuilding based on 

owners’ rating of the condition of the property in 

36 We do not have windshield observations for 100 percent of the properties in the 

owner survey sample, because the owner survey sample includes properties from 

Texas added after the windshield observations were complete in order to increase 

the sample size of CDBG recipients in Texas. See discussion in chapter 2, section 

2.2.

2011 would be a measure based on what the owner 

reported about the rebuilding work he or she has 

done since 2005. As discussed in chapter 3, owners 

provided information on whether they did any repair 

or rebuilding work to address hurricane damage and 

whether the work was substantially complete by the 

time of the survey. Thus, an alternative indicator of 

a rebuilt property could be that the owner reported 

having completed repairs.

Exhibit 4-1 compares the two owner-based measures.37

Overall, 74.6 percent of continuing owners’ homes are 

considered rebuilt per the owners’ assessment of the 

property condition (rated as either excellent or good). 

In comparison, only 64.0 percent of owners report 

that the repair or rebuilding work is substantially 

completed. Although a property is in good or excellent 

condition, an owner might still desire or plan further 

work and not consider the work to be complete. The 

share of properties considered rebuilt that also have 

owners reporting rebuilding work as complete, is 

closest in Texas, where 70.6 percent of properties are 

defined as rebuilt and 70.1 percent of owners report 

that the work is complete. The difference is largest 

in Mississippi, where 74.6 percent of properties are 

considered rebuilt, but owners report that work is 

complete for only 62.7 percent.

37 Section 3.4 describes slightly different rebuilding rates based on a different 

number of survey responses based on the exclusion of residents who sold or 

ceased to own. This was necessary to be able to a comparison with owner-reported conditions (only asked of continuing owners).

Exhibit 4-1. Alternative Owner-Reported Measures of Rebuilding (Continuing Owners Only)

Louisiana Mississippi Texas Overall

Percent rebuilt based on 

owner report of excellent 74.8 74.6 70.6 74.6

or good condition

Percent rebuilt based on 

owner report of having 

completed repair or 64.1 62.7 70.1 64.0

rebuilding work

Note: Weighted population estimates based on 575 survey responses.

Source: 2011 Property Owner Survey
Chapter 4: Owner and Property Factors Affecting Rates of Rebuilding 51

Although work may not be complete from the owner’s 

perspective, for the remainder of this report we define 

a property as being substantially rebuilt if the owner 

assessed its condition as either good or excellent at the 

time of the owner survey in 2011.

4.2 PROPERTY-LEVEL 

CHARACTERISTICS

This section reviews property-level characteristics 

as reported by the owners, in relation to repair and 

rebuilding status. We include financial, tenure, and 

other indicators, as well as the type of damage incurred 

from the hurricanes.

Location and Property Tenure as Factors in 

Rebuilding

Despite differences in the nature and impact of the 

hurricanes in Louisiana, Mississippi, and Texas and 

differences in homeowner assistance programs, rates 

of rebuilding are similar for the three states. As shown 

in exhibit 4-2, the point estimate of rebuilding in 

Louisiana is the highest, at 74.8 percent, and the 

estimate in Texas is the lowest, at 70.6 percent, but 

these differences are not significant.

The rates of rebuilding by state presented in exhibit 

4-2 are different from those presented in the Phase I 

report that is based on windshield observations. Based 

on windshield observations, the estimated percent 

of properties with major or severe damage that were 

rebuilt as of 2010 was 69.4 percent for Louisiana, 69.4 

percent for Mississippi, and 80.7 percent for Texas. In 

addition to differences in the two samples—windshield 

and owner survey—rebuilding rates based on the owner 

survey measure are generally higher because the survey 

measure includes only properties whose ownership 

has not changed since 2005 (although it is also the 

case that the data were collected approximately 1 year 

later). As discussed in chapter 3, we can infer from the 

windshield observations that rebuilding rates are lower 

for properties that changed ownership, so excluding 

them from the sample produces a higher estimate of 

rebuilding. The lower rebuilding rate based on survey 

responses for Texas is surprising, but, given the very 

small survey sample size in Texas, the point estimate of 

70.6 percent in exhibit 4-2 is very imprecise.

Rebuilding rates also varied by the tenure of the 

property at the time of the 2005 hurricanes, but the 

differences are not sufficiently large to be statistically 

significant. The point estimate for rebuilding is 75.7 

percent among properties that were owner occupied as 

of 2005, 70.5 percent for properties that were renter 

occupied, and 58.3 for properties that were vacation 

homes or some other type of housing.

Exhibit 4-2. Rebuilding Status by State and Tenure

Percent Rebuilt CI

Location (N = 164,367 based on 588 survey responses)

Louisiana 74.8 70.5–79.2

Mississippi 74.6 66.4–82.8

Texas 70.6 58.2–83.0

Overall 74.6 70.9–78.3

2005 Tenure (N = 158,729 based on 569 survey responses)

Owner occupied 75.7 71.8–79.6

Renter occupied 70.5 61.7–79.3

Vacation/other 58.3 40.7–76.0

CI = 90 percent confidence interval.

Source: 2011 Property Owner Survey
Chapter 4: Owner and Property Factors Affecting Rates of Rebuilding 52

Mortgage and Insurance Presence, Insurance 

Coverage, and Home Value as Factors in 

Rebuilding

We examined four financial characteristics of the 

survey properties for their relationship with rebuilding, 

with results shown in exhibit 4-3. These factors are 

potentially relevant because they affect the household’s 

ability to rebuild. We did not find a statistically 

significant difference in the distributions of rebuilding 

between homes that had mortgages at the time of 

the hurricane (74.8 percent) and homes that did not 

have mortgages (72.9 percent). We did find a large 

and statistically significant difference at the 1 percent 

level in the distribution of rates of rebuilding for 

properties with and without insurance coverage (either 

homeowners or flood) at the time of the hurricanes. 

Of properties reported in the owners’ survey as having 

insurance coverage, 79.4 percent were rebuilt on the 

owner-reported measure, compared with 47.9 percent 

of properties without.

As part of the survey, owners were asked to estimate 

how much their house and lot would have sold for 

immediately before the 2005 hurricanes. Comparing 

the rebuilding status of properties with different 

estimated values, we find a statistically significant 

difference in the distributions of rate of rebuilding 

among properties from the distribution among 

properties not rebuilding. As shown in exhibit 4-3, 

properties at all pre-storm values were more likely to 

be rebuilt than not. This difference in distributions 

is statistically significant at the 10 percent level, and 

corroborates the windshield observation findings 

reported in the Phase I report, that homes in census 

blocks with higher median value before the hurricanes 

were more likely to have rebuilding activity.

Exhibit 4-3. Association Between Property Characteristics and Rebuilding Status: Mortgage and 

Insurance Presence, Insurance Coverage, and Home Value

Percent Rebuilt CI

Mortgage Presence (N = 157,553 based on 563 survey responses)

Mortgage 74.8 69.1–80.4

No mortgage 72.9 68.0–77.9

Insurance Presence** (N = 160,797 based on 575 survey responses)

Insurance (homeowners’ or 

flood insurance) 79.4 75.4–83.3

No insurance 47.9 37.7–58.1

Pre-Storm Value+ (N = 158,729 based on 569 survey responses)

Value less than $80,000 61.3 52.8–69.9

Value $80,000–$175,000 76.3 71.0–81.7

Value $175,000–$300,000 80.7 72.7–88.8

Value $300,000 76.5 62.9–90.1

CI = 90 percent confidence interval. **p < 0.01; *p < 0.05; +p < 0.10.

Note: Significance tests were performed for distributions of rebuilding rates across builders and nonrebuilders, but nonrebuilders are not 

portrayed in the exhibit for simplicity.

Source: 2011 Property Owner Survey
Chapter 4: Owner and Property Factors Affecting Rates of Rebuilding 53

Type and Extent of Damage and Cost of Repairs 

as Factors in Rebuilding

Characteristics related to storm damage could 

influence the desire to rebuild; the extent of damage 

may determine the household’s ability to do so. As 

shown in exhibit 4-4, homes that experienced flood 

damage reported less rebuilding than those that 

did not: 68.4 percent of homes with flood damage 

were rebuilt compared with 82.8 percent of homes 

experiencing damage from other sources (mostly 

wind). On the whole, flood-related damage is more 

costly to repair because it is usually more extensive 

and severe. Specifically, flooding affects more area, 

rooms, and systems in a home, while typical wind 

damage affects the roof and building envelope only. As 

a result, the damage caused by wind and wind driven 

rain is typically less than for flooding, and this damage 

severity may explain the lower rebuilding rate.

Properties that were leveled, demolished, or condemned 

also were associated with significantly lower levels of 

rebuilding. Only 46.5 percent of these homes were 

rebuilt, compared with 81.2 percent of properties that 

were not leveled or condemned and did not have to be 

demolished. Perhaps this is explained by the fact that 

the costs of total reconstruction can be significantly 

higher than the cost of repairing a damaged but still 

structurally habitable property. It is also possible that 

the commitment to rebuild is less likely when nothing 

of the old home is salvageable.

We also examined the relationship between the assessed 

damage amount as a percentage of the pre-storm value 

and the rate of rebuilding, and between the ownerreported cost of repairs and the rate of rebuilding, but 

we found no statistically significant differences between 

rebuilt and nonrebuilt properties.

Exhibit 4-4. Association Between Property Characteristics and Rebuilding Status: Type, Extent, and 

Value Relative to Property Value of Damage and Cost of Repairs

Percent Rebuilt CI

Type of Damage* (N = 158,220 based on 567 survey responses)

Flooding 72.6 68.3–76.9

No flooding 82.8 77.1–88.5

Extent of Damage** (N = 158,729 based on 569 survey responses)

Leveled/demolished/condemned 46.5 37.4–55.6

Not leveled/demolished/

condemned 81.2 77.6–84.7

CI = 90 percent confidence interval. **p < 0.01; *p < 0.05; +p < 0.10.

Notes: Table includes only those properties for which damage assessments were performed. Based on highest value assessment 

if multiple assessors.

Source: 2011 Property Owner Survey

4.3 OWNER 

CHARACTERISTICS

This section reviews owner characteristics (selfreported) in relation to rebuilding status. The owner 

characteristics examined in this report are household 

demographic indicators that may have played a factor 

in rebuilding decisions. This analysis complements 

analysis presented in the Phase I report, which 

analyzed the relationship between the demographic 

characteristics of neighborhood residents before 

the storms—using 2000 Census data at the census 

block level—and rates of rebuilding in 2010 based 

on external observation. The analysis in this report 

is of individual owner characteristics associated with 

rebuilding, as reported by the owners in 2011.

Five characteristics were analyzed as possible factors 

in rebuilding: age, presence of dependents under the 

age of 18, the disability status of the owner, the pretax 

household income in 2004, and the race of the owner. 

The results are shown in exhibit 4-5.
Chapter 4: Owner and Property Factors Affecting Rates of Rebuilding 54

Exhibit 4-5. Association Between Owner Characteristics and Rebuilding Status

Percent Rebuilt CI

Age (N = 159,640 based on 572 survey responses)

18–44 75.3 66.4–84.2

45–64 73.1 66.6–79.5

65+ 76.1 70.5–81.7

Dependents Under the Age of 18 (N = 159,640 based on 572 survey responses)

Household includes dependents < age 18 76.3 70.3–82.3

Household does not include dependents < age 18 73.9 69.3–78.6

Disability Status of Owner/Co-Owner (N = 159,640 based on 572 survey responses)

Has a disability that limits/prevents work 67.9 60.4–75.3

Does not have a disability that limits/prevents work 76.9 72.8–81.0

Pretax Household Income in 2004 (N = 159,640 based on 572 survey responses)

Less than $30,000 71.9 65.2–78.6

At least $30,000 but less than $60,000 73.0 65.2–80.7

At least $60,000 but less than $90,000 73.3 65.1–81.4

$90,000 or more 85.3 78.1–92.5

Race* (N = 159,640 based on 572 survey responses)

Black or African American alone 68.4 62.8–74.0

White alone 82.5 77.3–87.7

Other race or multiple race 62.4 51.3–73.5

CI = 90 percent confidence interval. **p < 0.01; *p < 0.05; +p < 0.10.

Source: 2011 Property Owner Survey

None of the individual owner characteristics, with 

the exception of race, were found to be significantly 

correlated with rebuilding. We found that owners 

reporting their race as Black or African American, 

with no other race, were significantly less likely to 

rebuild than owners reporting their race as White, 

with no other race, or owners reporting multiple 

races. However, in the multivariate analysis discussed 

in the next section, these differences were found not 

to be statistically significant when other factors were 

controlled.
Chapter 4: Owner and Property Factors Affecting Rates of Rebuilding 55

4.4 MULTIVARIATE 

ANALYSIS

To this point, this chapter has described the 

relationships between individual property-level and 

owner characteristics and rebuilding, one at a time. 

However, it is not always easy to interpret such 

relationships without digging deeper. For example, 

we observed previously that homes with mortgages at 

the time of the storm were rebuilt at a slightly higher 

rate (74.8 percent) than those without (72.9 percent), 

although this result is not statistically significant.

On its own, the interpretation of this finding is 

not obvious: should we say that having a mortgage 

promotes rebuilding? (A possible policy implication 

would be that homeowners should be encouraged not 

to pay off their mortgages in hurricane-prone areas, to 

promote subsequent rebuilding.) The interpretation 

of the mortgage variable becomes clearer when we 

take into account its relationship with other study 

variables. For example, insurance presence is also 

positively correlated with rebuilding; owners who have 

insurance are substantially more likely to rebuild (and 

the difference is statistically significant). Multivariate 

analysis indicates that these two variables are not 

independent: Exhibit 4-6 shows the relationship 

between mortgage presence and insurance coverage 

using weighted survey data.

The table shows that insurance coverage is positively 

and strongly correlated with mortgage presence—nearly 

all properties with a mortgage carry insurance. This 

leads to a rather different interpretation of the effect of 

mortgage presence on the decision to rebuild: perhaps 

owners with mortgages are more likely to rebuild 

because they are insured. (In fact, as we indicate in 

a following section, owners who have a mortgage are 

less likely to rebuild than owners without a mortgage, 

when both are fully insured). The policy implication 

would shift from promoting mortgages to promoting 

insurance coverage.

The purpose of the multivariate regression analysis in 

this section is to provide a more nuanced interpretation 

of the relationship between owner characteristics and 

rebuilding activities, by controlling for correlations 

between the characteristics of interest. This analysis 

covers only continuing owners (excluding owners 

who sold their properties between 2005 and 2011). 

The analysis addresses the relationship between 

rebuilding and four categories of owner and property 

characteristics:

1. Tenure (renter versus owner occupied).

2. Financial and mortgage characteristics.

3. The type and extent of storm damage.

4. Demographic characteristics.

5. Average characteristics of the census block-group 

in which the property is located.

Four of these categories—tenure, financial and 

mortgage characteristics, demographic characteristics, 

and census block-group characteristics—include only 

pre-hurricane characteristics. Thus, these variables can 

be thought of as exogenous; there is no reason to worry 

that they might have been affected by the decision to 

rebuild. Therefore, the results of the analysis can be 

interpreted as providing evidence regarding how the 

decision to rebuild was influenced by these pre-existing 

characteristics.

Exhibit 4-6. Association Between Mortgage Presence and Property Insurance

Insurance No Insurance Total

Mortgage Presence

Mortgage 98% 2% 100%

No mortgage 69% 31% 100%

Source: 2011 Property Owner Survey
Chapter 4: Owner and Property Factors Affecting Rates of Rebuilding 56

Because rebuilding status is a binary outcome (that 

is, it takes the value of 0 for not rebuilt or 1 for 

rebuilt), we estimate how the probability of rebuilding 

is affected by each of the characteristics of interest. 

Specifically, we estimate the relationships using a 

logistic regression model (logit), which constrains the 

predicted probability of rebuilding to be between 0 

and 1. This approach also enables us to compute the 

marginal effect of any one variable at meaningful values 

of the other variables in the model. So, for example, 

we can estimate the relationship between insurance 

and rebuilding for property owners who do not have 

mortgages, while holding all other variables constant 

at their average values. The logit model takes the 

following form:

P(y = 1|X) = G(β0 + XT βT + XF βF + XH βH + XD βD + ε)

Where

P(y = 1|X) is the conditional probability of 

rebuilding;

G(z) is the logistic function: exp(z)/[1+exp(z)]

XT is the tenure variable;

XF is a vector of financial and mortgage 

characteristics;

XH is a vector of hurricane damage 

characteristics;

XD is a vector of demographic characteristics;

βT ,F ,H,D are the coefficients of interest; and

ε is an error term.

The magnitudes of the coefficients (β) are not 

especially useful by themselves. For that reason, we 

report average partial effects for each of the variables 

of interest in exhibit 4-7. For variables found to be 

statistically significant, we explain in the text how these 

variables can be interpreted. In addition, the analysis 

controls for geographic region and incorporates

sample weights.38

Exhibit 4-7. Regression Analysis Results

 Variables Rebuilt

Owner and Property Characteristics:

Owner occupancy – 0.02 (0.055)

Presence of mortgage – 0.13* (0.057)

Presence of insurance 0.37*** (0.098)

Pre-storm home value 

($100,000s) – 0.02** (0.011)

Flood damage – 0.16*** (0.047)

Property was destroyed – 0.39*** (0.071)

Age of owner – 0.00 (0.002)

Presence in household of 

dependents – 0.03 (0.064)

Disability status of owner – 0.02 (0.062)

Owner race—White 0.12 (0.090)

Owner race—Black or 

African American – 0.04 (0.105)

Block Group Characteristics (2000 Census):

Percent Black or African 

American 0.07 (0.178)

Percent Hispanic – 0.10 (0.880)

Percent occupied 0.46 (0.382)

Percent owner occupied 0.37* (0.207)

Average household size – 0.03 (0.111)

Median home value 0.00 (0.000)

Median household income 

($100,000s) 0.00 (0.000)

Percent with high school 

education 0.65* (0.386)

Percent unemployed – 0.28 (0.347)

Percent receiving public 

assistance 0.51 (0.959)

Observations 461

*p < 0.01; **p < 0.05; ***p < 0.1.

Note: Robust standard errors in parentheses.

38 The regression above does not contain two variables of interest—pre-hurricane 

owner income and the estimated damage relative to pre-storm value—because 

these variables have missing values for many observations. For the former, 

while 468 observations are included in the original regression analysis, adding 

pre-hurricane income reduces the number of available observations to 374. To 

compensate for this, a sensitivity analysis including pre-hurricane income in the 

regression was performed using the larger sample for better statistical precision. This check shows that this characteristic is not of statistical or practical 

significance when controlling for other variables, and it does not change the 

interpretation of the relationship between any other characteristic and rebuilding. 

Including damage relative to pre-storm value reduces the number of available observations to 174. This substantially reduces statistical power and may introduce 

bias, if the properties with missing data on this characteristic are systematically 

different than those for which data is present.
Chapter 4: Owner and Property Factors Affecting Rates of Rebuilding 57

Tenure

After controlling for other owner and property 

characteristics, we find no significant relationship 

between tenure status and rebuilding rates. Specifically, 

for the average property owner, we estimate that owneroccupancy is associated with less than a 2 percent 

decrease in the probability of rebuilding, and this 

relationship is not statistically significant.

Financial and Mortgage Characteristics

Insurance is estimated to have a large and highly 

significant relationship with rebuilding. On average, 

insured properties are nearly 37 percent more likely 

to have been rebuilt than uninsured properties. At 

the same time, the relationship between mortgage 

presence and rebuilding is estimated to be negative 

and significant, with mortgaged properties 13 percent 

less likely to be rebuilt, on average, holding insurance 

constant at its average value. To see how these factors 

interact, we estimate that among fully insured 

properties, those with a mortgage were more than 11 

percent less likely to have been rebuilt, on average.

Pre-storm home value was not found to be associated 

with rebuilding, but pre-storm home value was found 

to have a negative relationship with rebuilding when 

holding median home value in the neighborhood 

constant. This can be interpreted to mean that, as 

the pre-storm value of a property increases relative to 

neighboring properties, it is less likely to be rebuilt. 

Although this association is statistically significant, it 

is not large: we estimate that a $10,000 increase in prestorm value is associated with a 0.2 percent decrease 

in rebuilding rates, holding the median home value in 

the census block-group constant. This finding suggests 

that, within a particular neighborhood, the owners of 

higher valued homes may have less incentive to rebuild.

Damage Characteristics

We found that two damage characteristics are 

significantly associated with rebuilding: whether the 

property sustained flood damage, and whether it was 

completely destroyed. Flood-damaged properties are, 

on average, 16 percent less likely to have been rebuilt 

than properties that did not sustain flood damage. 

Properties categorized as being leveled, demolished, 

or condemned are 39 percent less likely to have been 

rebuilt, holding all other characteristics constant.

Demographics

When controlling for other characteristics, we did 

not find any statistically significant or substantively 

important relationships between owner demographic 

characteristics (including age, disability status, race, 

and presence of dependents in the household) and the 

probability of rebuilding.

Block-Group Characteristics

Two characteristics of the census block group in which 

the property is located were found to be significantly 

associated with rebuilding. Areas with more 

education—in particular a higher proportion of adults 

with at least a high school education—experience more 

rebuilding. Specifically, a 10 percent increase in the 

proportion of residents with a high school education is 

associated with a 7 percent increase in the probability 

of rebuilding. Likewise, properties are more likely to 

have been rebuilt in census block groups that have 

a higher proportion of owner-occupied houses. A 

10 percent increase in the owner-occupancy rate is 

associated with a 4 percent increase in the likelihood of 

rebuilding. No other neighborhood characteristics were 

found to be significantly correlated with rebuilding.
Chapter 4: Owner and Property Factors Affecting Rates of Rebuilding 58

4.5 SUMMARY OF 

CHAPTER FINDINGS

This chapter analyzed the owner and property factors 

affecting rates of rebuilding in Louisiana, Mississippi, 

and Texas. Rebuilding estimates are taken from 

the owner survey and are based on owner-reported 

information on the condition of their properties as of 

early 2011. The 575 survey responses (which include 

only continuing owners, who are presumably well 

informed about the 2011 condition of hurricanedamaged properties) are weighted to represent the 

160,797 continuing owners of homes that individually 

experienced major hurricane damage and also were 

located on census blocks that were significantly affected 

by the storms of 2005.

Overall, we found that three-fourths of continuing 

owners rate the current condition of their properties 

as excellent or good. Given that all of the properties 

incurred major damage in the hurricanes, we assume 

that properties in excellent or good condition as of 

2011 have been substantially rebuilt. However, only 

64 percent of continuing owners report that the repair 

or rebuilding work to address hurricane damage is 

substantially complete. This suggests that some owners 

have brought their properties to a habitable standard 

but nonetheless think more work needs to be done. 

Comparing rates of rebuilding across states, using the 

measure of rebuilding based on the owner-reported 

condition of the property in 2011, we do not find 

significant differences across the three states in the 

study.

We used cross-tabulation and multivariate analysis to 

explore the relationships between pre-storm property 

characteristics (tenure, presence of a mortgage, presence 

of insurance, and owner-reported property value) and 

rebuilding, type and extent of hurricane damage and 

rebuilding, and owner and neighborhood demographic 

characteristics and rebuilding.

The multivariate analysis did not find any statistically 

significant correlation between individual owner 

characteristics and rebuilding. However, it did identify 

four property characteristics and two neighborhood 

characteristics that were significantly associated with 

rebuilding: presence of insurance before the hurricanes 

(positively associated with rebuilding), presence of a 

mortgage before the hurricanes (negatively associated 

with rebuilding), flood damage from the hurricanes 

(negatively associated with rebuilding), extent of 

damage caused by the hurricanes (negatively associated 

with rebuilding), education level (positively associated 

with rebuilding), and the proportion of houses in the 

neighborhood that are owner occupied (positively 

associated with rebuilding). In addition, the value 

of a house relative to the median home value in the 

neighborhood was found to be negatively associated 

with rebuilding.

The presence of insurance and the extent of hurricane 

damage were the strongest predictors of rebuilding.

The estimated sizes of all of the statistically significant 

effects are as follows:

•	 Properties with insurance before the hurricanes 

were 37 percent more likely to have been rebuilt 

than uninsured properties.

•	 Properties with mortgages at the time of the 

hurricanes were 13 percent less likely to be rebuilt, 

on average, holding insurance constant.

•	 Properties that experienced flood damage were 16 

percent less likely to be rebuilt as of 2011 than 

properties that did not experience flood damage.

•	 Properties with hurricane damage so extensive that 

the structure was leveled or demolished or had to 

be condemned were 39 percent less likely to have 

been rebuilt than properties with less extensive 

damage.
Chapter 4: Owner and Property Factors Affecting Rates of Rebuilding 59

•	A 10 percent increase in the proportion of 

neighborhood residents with a high school 

education at the time of the hurricanes is associated 

with a 7 percent increase in the probability of 

rebuilding.

•	A 10 percent increase in the owner-occupancy rate 

when the hurricanes struck is associated with a 4 

percent increase in the likelihood of rebuilding.

The findings in this chapter reinforce some of the 

findings from the Phase I report. In particular, this 

analysis reinforces the finding that the severity of 

damage is a strong negative predictor of rebuilding. 

The Phase I report used the FEMA assessment as the 

main measure of damage. The owner survey provided 

an additional measure—whether the home was leveled, 

demolished, or condemned. This chapter shows that 

the presence of insurance before the hurricanes was an 

equally important factor in rebuilding, a factor that was 

not available for the analysis in the Phase I report.

Further, the findings from the multivariate analysis 

improve upon those reported in the Phase I report by 

adding individual owner and property characteristics 

as explanatory variables of rebuilding activity.39 Taking 

into account individual factors, such as the presence 

of insurance, reduces the significance of neighborhood 

factors such as the median house value as a predictor 

of rebuilding. The analysis presented in this chapter 

suggests that average neighborhood characteristics 

are not as important to owners’ rebuilding decisions 

as their individual personal and property situation—

whether they have insurance, whether their mortgage 

is paid off, and whether their house was destroyed, 

for example. Many of these individual and property 

characteristics are correlated with neighborhood 

characteristics, which is why neighborhood 

characteristics were significant in the model presented 

in the Phase I report. Although the owner survey did 

not collect information on the educational attainment 

of individual owners, it is likely that, if we were able 

39 For multivariate analysis of the association of neighborhood characteristics and 

rebuilding see Turnham, et al. (2010), pp. 60–62.

to include an individual measure of owner education 

level in the regression model, we would find that 

individual owner education was significantly associated 

with rebuilding, while average education in the 

neighborhood was not; however, with the information 

available, average education in the neighborhood is the 

best proxy for individual education level.

As individual owner and property characteristics at 

the time of the storms are explanatory variables for 

the rebuilding of these affected properties, the study 

explores individual sources and uses of funding for 

rebuilding after the storm as well. This topic is taken 

up in the next chapter.
Chapter 5: Funding for Rebuilding and CDBG Programs 60

5. FUNDING FOR 

REBUILDING AND

CDBG PROGRAMS

The role and nature of CDBG funding is a 

key focus of this study. How did receipt 

of CDBG affect individual rebuilding 

decisions? How did recipients use the funds 

in the two states where rebuilding was not mandatory? 

How were other sources of funding, including personal 

ones, used to supplement or substitute for CDBG 

funds? The Phase I report analyzed rates of CDBG 

receipt across the 230 significantly affected blocks 

sampled for the windshield observations and explored 

the relationship between CDBG receipt and rebuilding 

for the individual properties observed. Here, we 

supplement this analysis with new, owner-reported 

information on the range of financial resources that 

CDBG recipients obtained to support their rebuilding 

activities and, equally important, the funding used by 

owners of hurricane-damaged properties who did not 

receive CDBG assistance.

This chapter presents the findings and analysis 

related to CDBG receipt and rebuilding, and explores 

differences across the three states and program designs. 

The information on CDBG receipt and grant amounts 

presented in this chapter comes from the propertylevel administrative data obtained from the state 

CDBG programs in March 2010. Due to the very small 

number of recipients of CDBG small rental grants in 

the sample, the analysis focuses on homeowners and, in 

turn, the CDBG homeowner programs unless otherwise 

noted.

The chapter begins by providing a descriptive overview 

of the rates of CDBG receipt among the owner survey 

sample and the characteristics of CDBG homeowner 

grant recipients compared with nonrecipients. Section 

5.2 then compares the use of CDBG funds across 

states. The next sections examine the various financial 

resources that were employed, including CDBG 

(section 5.3), the gaps reported between available 

resources and estimated cost of rebuilding, and the 

use of personal funds for rebuilding (section 5.4), and 

the association between these various resources and 

rebuilding activity (section 5.5). Finally, section 5.6 

discusses owner satisfaction with the CDBG programs 

and the pace of rebuilding across program models.

5.1 RATES OF CDBG 

RECEIPT

Exhibit 5-1 presents weighted estimates of the owners 

in the population from the survey sample who received 

CDBG homeowner and small rental program grants. 

This table is comparable to that presented in the Phase 

I report for the properties with major or severe damage 

included in the windshield observation sample.40 The 

weighted estimates suggest that in Louisiana and 

Mississippi, 50 to 60 percent of properties with major 

or severe damage received CDBG assistance. The 

rate of CDBG receipt was much lower among Texas 

homeowners, with a point estimate for the weighted 

sample of 6.5 percent and a confidence interval of 4.1 

to 9.1 percent.41 CDBG funding was more limited in 

Texas and as a result the program was more targeted by 

geography and income.

40 Turnham, et al. (2010), exhibit 5-1, p. 72.

41 The raw numbers for Texas show a much higher rate of CDBG than the weighted numbers. This is because, as described in chapter 2, we oversampled CDBG 

recipients in Texas in order to obtain a sufficient number of survey responses 

from that group to permit analysis.
Chapter 5: Funding for Rebuilding and CDBG Programs 61

Exhibit 5-1. CDBG Receipt Among Properties in the Owner Survey Sample by State

Louisiana Mississippi Texas

Raw 

Numbers

Weighted 

Estimatesa

Raw 

Numbers

Weighted 

Estimates

Raw 

Numbers

Weighted 

Estimates

Owner-Occupied Properties

Total properties 353 106,870 138 39,277 70 7,159

Number with CDBG awards 211 58,660 79 21,879 37 467

Percent with CDBG awards* 59.8 54.9 

(49.6-60.2) 57.2 55.7 (46.3–65.1) 52.9 6.5 (4.1–9.0)

Rental Properties

Total properties 82 29,166 24 6

Number with CDBG awards 17 4,561 1 0

Percent with CDBG awards 20.7 15.6 

(6.7–24.5) 4.2 0.0

CDBG = Community Development Block Grant. 

a 90 percent confidence intervals shown in parentheses.

Notes: Excludes properties identified as vacation homes or for which tenure in 2005 was not provided. Where the number of sampled 

properties or CDBG recipients is small (fewer than 25 properties and fewer than 10 CDBG recipients), we do not show weighted estimates.

Sources: 2011 Property Owner Survey; CDBG administrative data

Only Louisiana and Mississippi offered CDBG disaster 

assistance programs aimed at owners of small rental 

properties, and these programs were very small in scale 

compared to the homeowner programs. As shown in 

exhibit 5-1, we estimate that 15.6 percent of rental 

properties on significantly affected blocks in Louisiana 

received CDBG assistance; in Mississippi the survey 

sample size was too small to calculate a weighted 

estimate. Given the very small number of recipients of 

CDBG small rental grants in the owner survey sample, 

the remainder of this chapter (after exhibit 5-1) focuses 

exclusively on homeowners.

As described in chapter 2, recipients of CDBG 

homeowner funds in Louisiana (The Road Home 

program) had to choose one of three options: stay in 

the home and rebuild (Option 1), sell to the State and 

buy elsewhere in Louisiana (Option 2), or sell to the 

State and become renters in Louisiana or move out 

of state (Option 3). As shown in exhibit 5-2, most 

recipients in the owner survey sample (89.5 percent) 

chose Option 1, while 8.4 percent chose Option 2, and 

2.2 percent chose Option 3.42

42 Statewide, 91.8 percent of recipients selected Option 1, 6.4 percent selected 

Option 2, and 1.8 percent selected Option 3. See Road Home Weekly Situation 

and Pipeline Report, Week 258, June 3,2011–June 9, 2011, available at http://www.

road2la.org/Docs/pipeline/week258pipeline.pdf.
Chapter 5: Funding for Rebuilding and CDBG Programs 62

Exhibit 5-2. CDBG Receipt by Option in Louisiana

Percent of CDBG Recipients CI

Option 1 89.5 84.8–94.2

Option 2 8.4 4.0–12.7

Option 3 2.2 1.2–3.1

Total 100.0

CDBG = Community Development Block Grant. CI = 90 percent confidence interval.

Notes: Weighted population estimates based on 216 survey responses. The CDBG administrative data did not indicate program option for all 

CDBG recipients in the survey sample.

Sources: 2011 Property Owner Survey; CDBG administrative data

Since CDBG administrative data do not provide 

detailed demographic characteristics for CDBG 

recipients, the findings from the 2011 owner 

survey provide new descriptive information on the 

characteristics of homeowners who received CDBG 

assistance compared with those who did not (exhibit 

5-4). For two of the characteristics examined, race 

and ethnicity, the observed differences between 

CDBG recipients and nonrecipients were statistically 

significant. CDBG recipients were more likely to be of 

Hispanic or Latino origin and more likely to be African 

American than nonrecipients.

Exhibit 5-3 shows the distribution of CDBG 

homeowner assistance amounts by state for the owner 

survey sample. The median award amount was $78,949 

in Louisiana, $66,577 in Mississippi, and $73,248 in 

Texas. This information is presented here to provide 

context for the analysis that follows, but it should be 

noted that the Phase I report provided comprehensive 

information on the distribution of CDBG award 

amounts for all recipients statewide and for the sample 

of properties included in the windshield observations, 

which is nearly five times as large as the owner survey 

sample.43

43 See Turnham, et al. (2010), exhibits 1-4 and 5-5. The distribution of award 

amounts for the CDBG programs statewide is presented in exhibit 1-4, and 

the distribution of award amounts for the windshield observation sample in 

Louisiana and Mississippi is presented in exhibit 5-5 of that report. In Louisiana, 

the median award amount for the owner survey sample is higher than the median 

award amount for the windshield observation sample ($78,949 compared with 

$65,000). The median award amounts for the owner survey sample and the windshield observation samples in Mississippi are nearly identical ($66,577 compared 

with $66,750).

Exhibit 5-3. Distribution of CDBG Award Amounts, Homeowners Only

Louisiana Mississippi Texas

25th percentile $38,657 $42,547 $62,812

50th percentile (median) $78,949 $66,577 $73,248

75th percentile $115,802 $98,334 $81,449

CDBG = Community Development Block Grant. 

Note: Weighted population estimates based on 335 survey responses.

Sources: 2011 Property Owner Survey; CDBG administrative data
Chapter 5: Funding for Rebuilding and CDBG Programs 63

Exhibit 5-4. Owner Characteristics of CDBG Recipients and Nonrecipients, Homeowners Only

CDBG Recipients Nonrecipients

Percent CI Percent CI

Age

18–44 13.6 10.6–16.7 17.5 12.9–22.1

45–64 45.9 40.2–51.7 45.7 39.1–52.1

65+ 40.4 34.7–46.2 36.8 30.5–43.1

Pretax Household Income in 2004

Less than $30,000 33.9 28.6–39.2 32.3 25.8–38.7

At least $30,000, less than $60,000 34.1 29.1–39.2 29.3 23.0–35.5

At least $60,000, less than $90,000 17.1 12.9–21.3 18.9 13.5–24.4

$90,000 or more 14.9 11.0–18.9 19.6 13.9–25.2

Ethnicity+

Hispanic or Latino 4.4 2.5–6.2 1.7 0.4–3.1

Not Hispanic or Latino 95.6 93.8–97.5 98.3 96.9–99.6

Race*

Black or African American 45.1 37.8–52.4 32.2 24.8–39.6

White alone 46.9 39.6–54.2 58.9 50.5–67.2

Other or multiple race 8.0 5.2–10.9 8.9 5.6–12.2

CDBG = Community Development Block Grant. CI = 90 percent confidence interval. **p < 0.01; *p < 0.05; +p < 0.10.

Note: Weighted population estimates based on 551 survey responses.

Sources: 2011 Property Owner Survey; CDBG administrative data

Exhibit 5-5 shows the property characteristics 

of CDBG recipients and nonrecipients. Like the 

demographic characteristics of owners, this information 

is largely unavailable in the CDBG administrative 

data. The properties that received CDBG assistance 

are different from those that did not receive CDBG in 

several ways that are consistent with the program goals 

and design. Each of these differences is statistically 

significant:

•	 Properties valued at $300,000 or more by their 

owners before the hurricanes are less likely to have 

received CDBG.

•	 Properties that experienced flood damage are 

more likely to have received CDBG. This holds 

true even if we exclude recipients in Mississippi, 

where properties had to have some flood damage to 

qualify for CDBG homeowner assistance.

•	 Properties with higher levels of assessed damage—

as reported by owners—are more likely to have 

received CDBG than properties that did not receive 

assistance.
Chapter 5: Funding for Rebuilding and CDBG Programs 64

Exhibit 5-5. Characteristics of CDBG Recipient and Nonrecipient Properties, Homeowners Only

CDBG Recipients Nonrecipients

Percent CI Percent CI

Insurance Status

Insurance 88.2 84.3–92.2 86.5 82.5–90.4

No insurance 11.8 7.8–15.7 13.5 9.6–17.5

Mortgage Status

Mortgage 57.7 51.8–63.6 54.5 47.6–61.4

No mortgage 42.3 36.4–48.2 45.5 38.6–52.4

Pre-Storm Value*

Value less than $80,000 15.2 11.5–19.0 14.9 10.0–19.8

Value $80,000–$175,000 54.5 48.7–60.4 47.5 40.0–54.9

Value $175,000–$300,000 23.8 18.6–29.1 22.2 16.8–27.6

Value $300,000+ 6.4 3.6–9.1 15.5 9.6–21.4

Extent of Hurricane Damage*

Leveled/demolished/condemned 25.9 19.4–32.4 21.9 16.4–27.5

Not leveled/demolished/condemned 74.1 67.6–80.6 78.1 72.5–83.6

Type of Damage**

Flooding 95.4 93.2–97.7 73.8 67.4–80.2

No flooding 4.6 2.3–6.8 26.2 19.8–32.6

Assessed Damage Amount**

Less than $10,000 3.9 1.4–6.4 11.9 6.6–17.2

At least $10,000 but less than $50,000 14.3 9.0–19.7 26.5 19.4–33.6

At least $50,000 but less than $100,000 34.2 27.3–41.1 22.3 15.8–28.9

$100,000 or more 47.6 39.3–60.0 39.2 30.5–47.9

CDBG = Community Development Block Grant. CI = 90 percent confidence interval. **p < 0.01; *p < 0.05; +p < 0.10.

Note: Weighted population estimates based on 561 survey responses (assessed damage amount based on 296 responses).

Sources: 2011 Property Owner Survey; CDBG administrative data
Chapter 5: Funding for Rebuilding and CDBG Programs 65

5.2 USE OF CDBG FUNDS

Findings from the owner survey also shed more light 

on how CDBG recipients used their funds, beyond 

those uses laid out in the different program models 

(like selling the property in Louisiana’s Options 2 and 

3, or only repair and rebuilding uses in Texas). The 

states had wide latitude in designing CDBG programs 

to assist owners of property affected by Hurricanes 

Katrina and Rita. The specifics of the programs 

are detailed in appendix A. But broadly speaking, 

the homeowner assistance programs in Mississippi 

and Texas were more targeted than the program 

in Louisiana, both by income and geography. In 

addition, the homeowner programs in Mississippi and 

Louisiana followed a compensation model, providing 

funds directly to homeowners, while the program in 

Texas used a rehabilitation model, in which funds 

were explicitly for repairs or reconstruction projects 

conducted by the state (through contractors) on the 

owner’s behalf.

The compensation model used in Louisiana and 

Mississippi gave homeowners discretion in how to 

address the damage to their homes, and also opened the 

possibility that some homeowners would use CDBG 

grants for purposes other than repairing or rebuilding 

their storm-damaged homes. There was no possibility 

of this in Texas, which reimbursed contractors and 

did not provide funds directly to homeowners. Not 

all grant recipients in Louisiana and Mississippi were 

required to repair or rebuild their homes. The Road 

Home program recipients in Louisiana who selected 

Option 1 agreed to ensure that their home would 

be repaired or rebuilt. Recipients who selected The 

Road Home Option 2 or 3 agreed to sell the damaged 

property and received the grant in compensation, so 

there was no expectation that they would rebuild their 

storm-damaged homes. In Mississippi, Phase 3 grant 

recipients in Mississippi—those who received grants 

under the Sold Home program—had already sold their 

properties and were not required to ensure that the 

damage was repaired. Anecdotally, there was also more 

latitude in rebuilding requirements for the recipients of 

other Mississippi phases than in Louisiana’s Option 1 

recipients.

For the remaining homeowners who were required 

to repair or rebuild, the extent to which CDBG 

recipients used their grant funds other than for 

repairing or rebuilding their storm-damaged homes is 

an important question for this study. If grant recipients 

in Louisiana and Mississippi used a large share of their 

grants for purposes other than rebuilding or repair, it 

would suggest that greater restrictions on the use of 

funds might be warranted if the goal is to encourage 

rebuilding.

The owner survey data suggest that most recipients 

used their grants for repairing or rebuilding activities 

only. As shown in exhibit 5-6, 86.5 percent of 

recipients in Louisiana and 64.0 percent of recipients 

in Mississippi reported using the entire grant to repair 

or rebuild the hurricane-damaged property. But, 7.1 

percent of Louisiana recipients and 20.3 percent 

of Mississippi recipients used some, but not all, of 

their grant funds for repair and rebuilding. And 6.4 

percent of recipients in Louisiana and 15.7 percent 

in Mississippi reported that they spent none of their 

grant funds on repair and rebuilding. Even with the 

small sample size, the difference observed between the 

two states in the proportion of CDBG funds used for 

rebuilding (all, none, or part) is statistically significant. 
Chapter 5: Funding for Rebuilding and CDBG Programs 66

Exhibit 5-6. Share of CDBG Homeowner Grant Funds Used for Repair and Rebuilding, Louisiana and 

Mississippi Homeowners Only

CDBG = Community Development Block Grant.

Note: Weighted population estimates based on 128 survey responses in Louisiana and 40 survey responses in Mississippi among CDBG 

recipient homeowners.

Sources: 2011 Property Owner Survey; CDBG administrative data

The sample size from the owner survey limits the 

opportunity to perform rigorous analysis of the uses 

of CDBG funds for purposes other than repair or 

rebuilding. Among the small share of CDBG recipients 

who reported using at least part of their CDBG 

grants for something other than repair and rebuilding, 

however, the most common use of funds was to 

purchase furniture (54.6 percent), followed by paying 

for everyday expenses (45.1 percent), and paying off 

a mortgage or loan (30.1 percent) (see exhibit 5-7). 

Rebuilding rates among those CDBG recipients who 

did not use any CDBG funds for repair and rebuilding 

were 38.2 percent in Louisiana and 22.2 percent in 

Mississippi—considerably lower than the 80.6 percent 

rebuilding rate among all CDBG recipients reported 

later in this chapter, although, again, the size of this 

subpopulation is too small for statistical comparison.

80%

90%

100%

60%

70%

40%

50%

20%

30%

10%

0%

All of grant Part of grant None of grant

Mississippi (N = 11,602)

Louisiana (N = 41,619)

64.0%

86.5%

20.3%

15.7%

7.1% 6.4%
Chapter 5: Funding for Rebuilding and CDBG Programs 67

Exhibit 5-7. Common Uses of CDBG Homeowner Grants for Activities Other than Repair and 

Rebuilding, Louisiana and Mississippi Homeowners Only

Weighted population estimates based on 59 survey responses. Includes The Road Home Option 2 and 3 recipients.

Sources: 2011 Property Owner Survey; CDBG administrative data

5.3 RESOURCES FOR 

REBUILDING

Given the small sample of owners who used CDBG 

grants for purposes other than repair or rebuilding, 

more interesting findings can be expected when 

analyzing the amount of CDBG grants in relation to 

all other potential sources of repair and rebuilding 

funding. CDBG grants were intended to provide 

resources to cover all, or at least a portion up to the 

grant maximum, of the costs associated with rebuilding 

for recipients beyond what other financial sources 

could cover, including homeowner or NFIP insurance 

payouts, SBA loans, and FEMA assistance.

The owner survey asked all owners to list each source 

of funding received for repair or rebuilding activities 

and to provide an estimate of the amount of funding 

received from each source. In addition to CDBG 

assistance, the survey asked owners about financial 

assistance received from homeowners insurance, flood 

insurance, Increased Cost of Compliance, Hazard 

Mitigation Grant Program, FEMA’s individual 

assistance program, SBA loans, state programs, 

churches or charities, and friends and family.

We calculated a total amount of resources received for 

each survey respondent using the owner-reported dollar 

amount for each funding source except for CDBG 

assistance. For CDBG assistance, we used the CDBG 

administrative data provide by each state, matched to 

To make some other large purchase

To pay off a mortgage/loan

To pay for everyday expenses

To purchase furniture

To pay for moving expenses

To pay for temporary housing

To purchase a vehicle

Rent another place to live

Purchase a home

30.1%

45.1%

54.6%

21.8%

21.3%

18.5%

15.0%

14.8%

14.0%

0% 10% 20% 30% 40% 50% 60% 70%

Percent of CDBG recipients who

reported using funds for something

other than rebuilding
Chapter 5: Funding for Rebuilding and CDBG Programs 68

the owner survey, as we determined that it would be 

more accurate than owner recall.

For the funding amounts reported by owners for 

sources other than CDBG, we relied solely on the 

owner-reported amounts. In a small number of cases—

less than 1 percent of the sample—we were able to 

determine that the information owners provided on 

funding gaps was clearly inaccurate (for example, 

amounts reported in excess of $1 million from any one 

source, or exceeding those sources’ stated award caps), 

and these responses were excluded from analysis. Other 

funding amounts that may have been over or under 

reported by owners, such as SBA loan amounts, could 

not be tested and these observations remain in the 

analysis.

Exhibit 5-8 compares the total resources reported 

among CDBG recipients and nonrecipients. CDBG 

recipients reported having substantially more resources 

than nonrecipients. The average (mean) amount of 

total resources reported by CDBG recipients was 

$144,963, compared with $95,211 for nonrecipients. 

This difference is statistically significant.

Exhibit 5-8. Total Amount of Resources (Including CDBG and Other Sources) Among CDBG 

Recipients and Nonrecipients, Homeowners Only

CDBG Recipients

(N = 80,155)

Nonrecipients

(N = 55,428)

Estimate CI Estimate CI

25th percentile $85,497 $76,243–$94,752 $14,751 $9,305–$20,196

Median $121,165 $111,423–$130,908 $51,159 $33,669–$68,648

Mean* $144,963 $131,117–$158,810 $95,211 $74,535–$115,887

75th percentile $177,549 $155,370–$199,729 $119,948 $89,425–$150,470

CDBG = Community Development Block Grant. CI = 90 percent confidence interval. **p < 0.01; *p < 0.05; +p < 0.10.

Note: Weighted population estimates based on 499 survey responses.

Sources: 2011 Property Owner Survey; CDBG administrative data

Further analysis of the survey data suggests that 

recipients also supplemented their CDBG assistance 

with other types of funding for repair and rebuilding 

after the hurricanes. Exhibit 5-9 shows how the share 

of CDBG assistance relative to total resources varies 

by state. The exhibit shows that less than one-fourth 

of recipients in Louisiana and Mississippi cited CDBG 

as their only source funding for repair or rebuilding. 

In Texas, the situation is reversed: for 71.1 percent 

of CDBG recipients, CDBG was the only source 

of financial assistance for rebuilding. This is what 

we would expect, given that recipients of CDBG 

assistance in Texas did not pay for the rebuilding work 

themselves, but rather had their homes repaired or 

rebuilt by state-hired contractors.

The owner survey provides us with the picture (exhibit 

5-9) of the total value of all resources among the 

population. It provides additional insight into how 

CDBG grants fit into recipients’ resource mix. But, 

while non-CDBG recipients certainly tapped into 

other sources of funds, most CDBG recipients also 

supplemented their CDBG grants with other sources 

of funds. A deeper explanation of the sources of these 

other funds is warranted.
Chapter 5: Funding for Rebuilding and CDBG Programs 69

Exhibit 5-9. CDBG Grant Relative to Total Amount of Resources of CDBG Recipients by State, 

Homeowners Only

CDBG as Percentage of 

Total Resources

Percentage of CDBG Recipients per State

Louisiana Mississippi Texas

1–49% 37.9 27.6 7.5

50–99% 39.7 55.7 20.9

100% 22.4 16.7 71.7

CDBG = Community Development Block Grant. 

Note: Weighted population estimates based on 335 responses.

Sources: 2011 Property Owner Survey; CDBG administrative data (for CDBG assistance amounts)

One might expect homeowners who did not receive 

CDBG to draw on a wider or different array of funding 

sources than CDBG recipients. This is not borne 

out by the survey findings. Exhibit 5-10 shows, for 

each source of funding covered in the owner survey, 

the percent of CDBG recipients and nonrecipients 

using the source, and the median amount reported 

from that source. In general, we see no significant 

differences between CDBG recipients and non-CDBG 

recipients in the rate at which they reported using 

other sources of funding. However, CDBG recipients 

were significantly more likely to report receiving 

assistance through the SBA loan and HMGP elevation 

programs.44

Exhibit 5-10 also shows the median amounts reported 

by owners for each funding source. Among the more 

common sources of funding for rebuilding other than 

CDBG funds, flood insurance payouts provided the 

highest median amounts to both CDBG and nonCDBG owners, followed by SBA loans, homeowners 

insurance payouts, and FEMA Individual Assistance 

grants. Comparing the median dollar amounts reported 

44 In Louisiana and Mississippi, the Hazard Mitigation Grant Program’s (HMGP’s) 

elevation grants and CDBG programs were linked based on similar eligibility 

requirements and on their cumulative meeting of owners’ needs. For example, 

CDBG recipients in Louisiana could apply for both The Road Home Elevation 

Incentives and the State’s HMGP elevation grants. However, HMGP funds were 

based on the costs of construction beyond funds covered first by other sources 

and then by The Road Home Elevation Incentive. The Road Home incentive 

was capped at $30,000 per home ($20,000 for manufactured homes) and was 

included in the $150,000 total The Road Home grant cap; the HMGP grant was 

capped at $100,000 based on the total construction cost but not subject to The 

Road Home grant cap. In all cases, only The Road Home Option 1 recipients 

were eligible for either. See www.road2la.org/homeowner/faqs.htm#9 and www.

mitigatela.org/Elevate.aspx.

by CDBG and non-CDBG recipients, we find that 

CDBG recipients generally reported lower levels of 

funding from sources other than CDBG compared 

with nonrecipients. For example, the median amount 

of homeowners insurance payouts for CDBG recipients 

was $16,250, while for nonrecipients it was $24,603. 

Similarly, the median payout from flood insurance, 

National Flood Insurance Program (NFIP) insurance 

policies, and the NFIP’s Increased Cost of Compliance 

(ICC) funds was $63,295 for CDBG recipients, 

while it was $99,125 for nonrecipients.45 Although 

reported to be used at higher rates, the median CDBG 

recipients’ SBA loan was $38,231; the median nonCBBG recipients’ SBA loan amount was $82,904.46 

The findings from exhibit 5-8 suggest that CDBG 

recipients were not dissimilar from nonrecipients in 

drawing on a range of funding sources to meet their 

rebuilding needs, although in many cases they received 

less assistance from these other (non-CDBG) sources 

than their non-CDBG counterparts. This is consistent 

with the design of the program, which was intended to 

make up the shortfall between rebuilding costs and the 

funding available to owners from other sources.

45 Increased Cost of Compliance is an NFIP bonus allowance to improve disaster 

mitigation for flood affected properties.

46 In Louisiana specifically, applicants who received The Road Home assistance 

under Option 1 and also had an SBA loan for costs to repair or rebuild their 

home were required by SBA to repay or reduce their SBA loan to the extent that 

the homeowner’s total benefits (SBA assistance plus The Road Home funds plus 

other assistance) exceeded the need. The SBA determined the amount of The 

Road Home award that it considered to be a duplication of benefits. So, the SBA 

loan amounts of CDBG recipients, on the whole, would be smaller than nonCDBG owners. See www.road2la.org/homeowner/faqs.htm#16.
Chapter 5: Funding for Rebuilding and CDBG Programs 70

Exhibit 5-10. Percentage of Owners Reporting Other Sources of Funding (Other than CDBG) and 

Median Amount Reported from Each Other Source, Homeowners Only

CDBG Recipients Nonrecipients

Percent CI Median 

Amount Percent CI Median Amount

Homeowners insurance payout 64.1 59.5–68.7 $16,250 62.3 57.0–67.7 $24,603

Flood insurance, NFIP, or 

ICC payout 36.8 29.3–44.3 $63,295 39.1 31.6–46.6 $99,127

FEMA individual assistance 

grant 27.4 22.8–31.9 $5,823 21.7 17.4–26.0 $4,029

SBA loan* 28.2 23.1–33.3 $38,231 10.3 6.1–14.6 $82,904

Church or charity 11.3 8.2–14.4 $723 8.4 4.8–12.0 $455

Friends or relatives 5.2 3.2–7.1 $1,927 7.0 4.3–9.7 $905

Other type of financial 

assistance 7.2 4.5–9.8 $1,041 3.5 1.8–5.1 $500

HMGP elevation grant* 7.3 4.4–10.1 $28,132 0.9 0.0–1.9 $21,480

Another state loan or grant 1.9 0.5–3.2 $65,947 0.3 0.0–0.8 $150,000

None of the above sources 12.7 9.4–16.0 — 16.7 12.5–20.9 —

CDBG = Community Development Block Grant. CI = 90 percent confidence interval. FEMA = Federal Emergency Management Agency. 

HMGP = Hazard Mitigation Grant Program. ICC = Increased Cost of Compliance. NFIP = National Flood Insurance Program. SBA = Small 

Business Administration. **p < 0.01; *p < 0.05; +p < 0.10.

Note: Weighted population estimates based on 592 responses.

Sources: 2011 Property Owner Survey; CDBG administrative data (for CDBG assistance amounts)

5.4 RESOURCE GAPS AND 

USE OF PERSONAL FUNDS

In addition to asking owners to report the amount of 

funding received, the assessed damage to their homes, 

and the actual repair costs incurred (from which 

funding sufficiency could be calculated), the property 

owner survey directly asked owners whether the total 

funding from all sources—including CDBG, when 

applicable—was sufficient to cover their rebuilding 

expenses. Exhibit 5-11 shows the percentage of owners 

reporting that their total funding was not sufficient 

to cover rebuilding expenses for CDBG recipients and 

nonrecipients. Across both groups, more than onethird of owners said their funding was not sufficient. 

The observed difference between CDBG recipients and 

nonrecipients is not statistically significant.

Exhibit 5-12 combines the owner-reported information 

on the total funding received for rebuilding and 

the amount of their damage assessment after the 

hurricanes, to show total funds received as a percent 

of assessed damage among CDBG recipients and 

nonrecipients. In contrast to the differences in exhibit 

5-11, the observed differences between CDBG 

recipients and nonrecipients in exhibit 5-12 are 

statistically significant. CDBG recipients were more 

likely than nonrecipients to have total funding that 

equaled or exceeded the assessed damage amount and 

less likely to have funding that fell short of the damage 

amount.
Chapter 5: Funding for Rebuilding and CDBG Programs 71

Exhibit 5-11. Owner Reports on the Sufficiency of Total Funding by CDBG and Non-CDBG Receipt, 

Homeowners Only

CDBG Recipients Nonrecipients

Percent CI Percent CI

Funding sufficient to cover rebuilding 

expenses

33.7 28.0–39.4 37.5 31.3–43.8

Funding not sufficient to cover 

rebuilding expenses 64.6 59.1–70.1 55.7 49.6–61.9

Don't know/refused 1.7 0.5–2.9 6.7 3.3–10.1

CDBG = Community Development Block Grant. CI = 90 percent confidence interval.

Note: Weighted population estimates based on 542 responses.

Source: 2011 Property Owner Survey

The higher share of owners for whom the amount of 

financial assistance for rebuilding matched the assessed 

damage among CDBG recipients suggests that the 

CDBG program did help address the funding gap 

for many owners. However, the findings presented in 

exhibits 5-11 and 5-12 are inconsistent. In particular, 

exhibit 5-12 suggests a smaller gap between total 

resources and needs than what owners reported in 

exhibit 5-11. It could be that the actual cost of repairs 

Exhibit 5-12. Total Resources Relative to Owner-Reported Damage Assessments, Homeowners Only

proved to be higher than the assessed damage amount. 

It could also be that owner reports of the assessed 

damage amount (or the amounts of funding received) 

are unreliable, as discussed previously in section 3.1. 

For that reason, the multivariate analysis presented in 

section 5.5 uses the owner reports that funding was not 

sufficient to cover rebuilding expenses (as presented in 

exhibit 5-11) rather than the share of damage covered 

by total resources shown in exhibit 5-12.

CDBG Recipients Nonrecipients

Percent CI Percent CI

Total funding = less than 50% of assessed damage 5.5 2.7–8.2 16.0 10.7–21.3

Total funding = 50%–99% of assessed damage 12.3 6.6–18.1 19.6 12.6–26.7

Total funding = 100% of assessed damage or more 82.2 76.0–88.4 64.3 56.2–72.5

CDBG = Community Development Block Grant. CI = 90 percent confidence interval.

Note: Weighted population estimates based on 281 responses.

Source: 2011 Property Owner Survey
Chapter 5: Funding for Rebuilding and CDBG Programs 72

The differences between CDBG and non-CDBG 

findings may not be surprising; however, the fact that 

CDBG recipients report insufficient levels of total 

resources to meet their rebuilding need is. Both CDBG 

and non-CDBG recipients sought out a variety of 

sources of assistance and also tapped into their personal 

resources. As shown in exhibit 5-13, for both recipients 

and nonrecipients, most homeowners reported using 

their own money to cover rebuilding expenses.47 The 

differences between the two groups are not statistically 

significant, suggesting that CDBG recipients were no 

less likely to tap into personal resources than owners 

who did not receive CDBG assistance.

Owners who reported using personal funds were asked 

to identify the various sources of personal funds used. 

As shown in exhibit 5-14, most of these owners (85.6 

percent) reported using their personal checking and 

savings accounts to fill their funding gaps. Credit 

cards were the second most cited source of personal 

funds (30.1 percent), with retirement accounts, mutual 

47 Of those CDBG recipients who used no portion of their CDBG funds for rebuilding, 21.3 and 54.2 percent used their own funds for rebuilding in Louisiana 

and Mississippi, respectively. Although too small a sample size to analyze statistically, this suggests that some of this group could have tapped into their personal 

funds after exhausting CDBG funds on nonrepair uses.

funds, and other homeowner financing products cited 

at lower rates.

The exploration of these owners with insufficient 

funds, their alternative funding sources, and their use 

of personal funds focuses attention away from those 

owners who reported having sufficient funds from 

all financial assistance (including CDBG and other 

funding sources). As reported previously, more than 

one-third of owners reported that their funding was 

sufficient to cover their rebuilding expenses. When 

looking across the total owner population, and between 

the CDBG and non-CDBG recipient groups, we can 

visually compare the median assessed damage, total 

funding (including CDBG grant value for recipients), 

and repair costs across the states. This is shown in 

exhibit 5-15 for all owners including CDBG and nonCDBG recipients, exhibit 5-16 for CDBG recipients, 

and exhibit 5-17 for non-CDBG recipients.48

48 In these exhibits, owner-reported values for damage assessment, funding from 

non-CDBG sources, and repair costs are taken from the owner survey but administrative data provide the values for CDBG grants matched to these recipients. 

Damage assessments and repair costs among CDBG recipients in Texas are likely 

distorted since recipients did not receive the funding directly and may not have 

known the exact values.

Exhibit 5-13. Use of Personal Funds to Cover Rebuilding Expenses, Homeowners Only

CDBG Recipients Nonrecipients

Percent CI Percent CI

Used own money to cover expenses 59.6 54.2–65.0 52.2 45.9–58.5

Did not use own money to cover expenses 40.0 34.7–45.4 47.6 41.2–53.9

Don't know/refused 0.4 0.0–0.9 0.2 0.0–0.6

CDBG = Community Development Block Grant. CI = 90 percent confidence interval.

Note: Weighted population estimates based on 500 responses.

Source: 2011 Property Owner Survey
Chapter 5: Funding for Rebuilding and CDBG Programs 73

Exhibit 5-14. Sources of Personal Funds Used for Rebuilding, Homeowners Only

Note: Weighted population estimates based on 259 survey responses.

Source: 2011 Property Owner Survey

Exhibit 5-15. Median Assessed Damage, Total Funding Assistance, and Repair Costs for All Owners by 

State

Note: Estimates of assessed damage based on 231 respondents in Louisiana, 88 respondents in Mississippi, and 33 respondents in Texas. 

Estimates of total funding assistance based on 423 respondents in Louisiana, 166 respondents in Mississippi, and 74 respondents in Texas. 

Estimates of repair costs based on 246 respondents in Louisiana, 105 respondents in Mississippi, and 52 respondents in Texas.

Sources: 2011 Property Owner Survey; state administrative data; weighted population estimates

Mutual funds

Retirement savings account

Credit card

Checking or savings account

Home equity loan

Refinance

Life insurance

Other type of loan

Other

21.2%

30.1%

85.6%

15.5%

8.1%

6.5%

6.5%

2.5%

0.8%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

$120,000

$80,000

$40,000

$0

Louisiana Mississippi Texas

Median repair costs

Median assessed damage

Median total funding

100,214

69,863

7,612

89,523

74,227

35,124

86,842

49,356

26,525
Chapter 5: Funding for Rebuilding and CDBG Programs 74

Exhibit 5-16. Median Assessed Damage, Total Funding Assistance, and Repair Costs Among CDBG 

Recipients Only by State

Median funding non-CDBG

Median funding CDBG

Median assessed damage

Median repair costs

$120,000

$60,000

$90,000

$30,000

$0

Louisiana Mississippi Texas

48,463

39,242

76,648

66,736

72,998

98,285

78,569

36,376

98,709

69,790 68,030

CDBG = Community Development Block Grant.

Note: CDBG funding values are based on administrative data, but this information was missing for 9 Louisiana recipients—that is, estimates 

of CDBG value for Louisiana are based on 224 respondents. Estimates of assessed damage based on 118 respondents in Louisiana, 47 

respondents in Mississippi, and 14 respondents in Texas. Estimates of total funding assistance based on 232 respondents in Louisiana, 84 

respondents in Mississippi, and 37 respondents in Texas. Estimates of repair costs based on 134 respondents in Louisiana, 52 respondents in 

Mississippi, and 28 respondents in Texas.

Sources: 2011 Property Owner Survey; state administrative data; weighted population estimates

Exhibit 5-17. Median Assessed Damage, Total Funding Assistance, and Repair Costs Among 

Non-CDBG Recipients by State

Louisiana Mississippi Texas

Median repair costs

Median assessed damage

Median total funding

38,549

16,780

6,054

84,345

38,847 35,014

77,277

29,451 24,609

$120,000

$60,000

$90,000

$30,000

$0

CDBG = Community Development Block Grant.

Notes: Estimates of assessed damage based on 113 respondents in Louisiana, 41 respondents in Mississippi, and 19 respondents in Texas. 

Estimates of total funding assistance based on 191 respondents in Louisiana, 82 respondents in Mississippi, and 37 respondents in Texas. 

Estimates of repair costs based on 112 respondents in Louisiana, 53 respondents in Mississippi, and 24 respondents in Texas.

Sources: 2011 Property Owner Survey; state administrative data; weighted population estimates
Chapter 5: Funding for Rebuilding and CDBG Programs 75

5.5 RESOURCES AND 

REBUILDING

The discussion in the preceding sections suggests 

that owners of hurricane-damaged properties on 

significantly affected blocks received substantial 

resources from insurance, the federal government, 

and local sources to use toward repair and rebuilding. 

At the same time, most owners—including those 

who received CDBG assistance and those who did 

not—reported that all of the resources they received 

combined were not sufficient to cover their rebuilding 

expenses.

Whether CDBG should have fully covered the costs 

of rebuilding for a smaller group of owners (versus 

spreading resources more thinly) is an important 

policy issue. The information collected through the 

property owner survey can shed light on this question 

by exploring whether additional CDBG funding might 

have resulted in increased rebuilding. We do this by 

examining the relationship between gaps in funding 

and rebuilding—using the same measure of rebuilding 

as in chapter 4, which is based on owner assessment 

of the condition of the storm-damaged property as of 

early 2011.

The question of whether additional funding would 

have increased rebuilding applies to both CDBG 

recipients and nonrecipients. For owners who did 

not receive CDBG assistance, the question is whether 

access to CDBG funds would have increased their rates 

of rebuilding. Among CDBG recipients, the question 

is whether additional CDBG funds would have 

increased their rates of rebuilding further. This section 

examines the gaps in funding assistance for both 

groups, identifying the characteristics of households 

that experienced funding gaps and describing the 

relationship between funding gaps and rebuilding.49

Because the information for much of this analysis 

comes from the owner survey, a limitation of the 

analysis is that the measures of rebuilding, CDBG 

application, and the adequacy of funding are reported 

by the property owners after the fact—and owners’ 

responses may be colored by whether they managed 

to achieve rebuilding. In other words, owners who 

managed to rebuild might be more likely to report 

that they had sufficient funds to do so, and vice versa. 

It is worth reiterating here that the Phase I report 

found that—excluding properties that were sold to 

the state through The Road Home Options 2 and 3—

properties that received CDBG assistance were nearly 

twice as likely to be rebuilt as of early 2010 (based 

on windshield observation) as properties that did not 

receive CDBG.

Access to Resources and Rebuilding

Exhibit 5-18 describes the reported funding gaps 

and rebuilding rates for three groups of homeowners: 

owners who received CDBG grants, owners who 

applied for CDBG assistance but did not receive 

a grant, and owners who did not apply for CDBG 

assistance at all. The exhibit shows that the group 

of homeowners who applied for but did not receive 

CDBG funds lagged significantly in rebuilding. This 

set of homeowners includes a higher proportion of 

homeowners who reported insufficient funds and fewer 

properties that can be classified as rebuilt based on 

owner assessment of their condition in early 2011.

Exhibit 5-19 compares the amount of the funding gap 

(according to the owners) and the rate of rebuilding for 

homeowners who reported having insufficient funds 

for rebuilding, separating those who did not put their 

49 In this report we have not tried to replicate the results presented in the Phase I 

report showing that properties that received CDBG funding (with the exception 

of those assisted through The Road Home Options 2 and 3) were significantly 

more likely to be rebuilt as of early 2010 than properties without this funding. 

The Phase I analysis was based on a sample of properties more than six times as 

large as the sample of properties with owner survey data relevant for this analysis. 

As a result, we limited our analysis in this report to questions that could be 

answered using only the information collected from the property owner survey.
Chapter 5: Funding for Rebuilding and CDBG Programs 76

personal funds into rebuilding from those who did. It 

also shows the rate of rebuilding for homeowners who 

did not report a funding gap. The exhibit suggests that, 

among households who reported insufficient assistance, 

there are substantial differences between those who 

used their personal funds (or who had personal funds 

available for use) and those who did not.

Exhibit 5-18. Funding Gaps and Rebuilding by CDBG Receipt and Application Status, Homeowners 

Only

Received CDBG Applied for but Did 

Not Receive CDBG

Did Not Apply 

for CDBG

Percent who reported insufficient 

funding 64.9% 83.0%** 56.3%

Amount of gap (if funds insufficient) $60,564** $94,288** $34,214

Percent who use own funds (if funds 

insufficient) 44.1%** 32.1% 28.5%

Amount of own funds $44,964** $47,223** $20,055

Percent rebuilt 80.6% 58.1%+ 74.7%

Number of survey responses 242 105 172

CDBG = Community Development Block Grant. **p < 0.01; *p < 0.05; +p < 0.10.

Notes: Weighted population estimates based on 519 responses. The percent of CDBG recipients who reported insufficient funding is slightly 

different from the percent reported in exhibit 5-11 previously, because this exhibit excludes anyone who answered “don’t know” or “refused” 

to the question of funding insufficiency or the question of whether they applied for CDBG assistance. Significant differences are determined 

between “Received CDBG” and “Did not apply for CDBG” and “Applied for but did not receive CDBG” and “Did not apply for CDBG” 

separately, with significance indicators on the first two respective columns.

Sources: 2011 Property Owner Survey; CDBG administrative data

Exhibit 5-19. Funding Gaps and Rebuilding by Funding Sufficiency and Use of Personal Funds, 

Homeowners Only

Insufficient Funds and 

No Personal Funds Put 

into Rebuilding

Insufficient Funds and 

Personal Funds Put into 

Rebuilding

Sufficient Funds 

Amount of gap $90,398 $45,856 $0

Percent rebuilt 46.2%** 80.7%+ 88.9%

Number of survey 

responses

179 181 177

**p < 0.01; *p < 0.05; +p < 0.10.

Note: Weighted population estimates based on 537 responses.

Sources: 2011 Property Owner Survey; CDBG administrative data
Chapter 5: Funding for Rebuilding and CDBG Programs 77

The rebuilding measure, in particular, lags among 

those who reported not spending any of their own 

money on rebuilding, with only 46 percent of those 

properties rebuilt. This finding may suggest that a lack 

of funds prevented rebuilding activity for many of 

these homeowners. We did not ask the owners directly 

whether they had funds available that they did not use. 

However, it might also be a reflection of the decision 

not to rebuild—and therefore not to invest personal 

funds—by some homeowners.

In exhibits 5-18 and 5-19, tests of differences in means 

are applied to the figures in each table. In exhibit 5-18, 

each of the first two columns is compared against the 

set of homeowners who did not apply for CDBG. In 

exhibit 5-19, each of the first two columns is compared 

against the set of homeowners who reported that their 

total assistance was sufficient to cover rebuilding costs. 

Because this group—by definition—did not report a 

funding gap, no tests were performed to compare the 

amount of the funding gap in exhibit 5-19.

The overall conclusion from exhibits 5-18 and 5-19 

is that the two groups of homeowners within the 

survey exhibit lower rates of rebuilding and might have 

benefited from additional funds. First, homeowners 

who applied for CDBG assistance but did not receive 

grants were less likely to rebuild. Among these 

homeowners, 58 percent of properties were rebuilt as 

of early 2011, compared with more than 75 percent 

among other homeowners. Second, among households 

who reported insufficient funding and did not or 

could not invest any of their own funds, 46 percent of 

properties were rebuilt. The exhibits that follow seek 

to describe the characteristics of each group to better 

understand the impact of CDBG eligibility rules and 

funding on their decisions to rebuild. Although there is 

some overlap between the two groups, it is nevertheless 

instructive to consider them separately.

Exhibit 5-20 provides descriptive statistics on the 

property attributes and demographic characteristics 

of homeowners who applied for but did not receive 

CDBG, compared with CDBG recipients and 

nonapplicants. The exhibit shows that the homeowners 

who did not apply for CDBG are more likely to be 

White and to have wind damage only. (The latter is 

not surprising, given that eligibility for Mississippi’s 

CDBG program was limited to properties with flood 

damage.) Homeowners who applied for, but did not 

receive, CDBG are more likely than owners who did 

not apply to have flood insurance and to no longer own 

the property.
Chapter 5: Funding for Rebuilding and CDBG Programs 78

Exhibit 5-20. Property and Owner Characteristics by CDBG Receipt and Application Status, 

Homeowners Only

Received CDBG Applied for but Did 

Not Receive CDBG

Did Not Apply 

for CDBG

Property Attributes 

Presence of hazard insurance 58.8% 53.7% 58.8%

Presence of flood insurance 32.3%** 48.4%** 16.4%

Flood damage only 14.8% 13.1% 14.6%

Wind damage only 5.4%** 3.0%** 36.3%

Flood and wind damage 79.8%** 83.9%** 49.2%

Change in owner since 2005 9.8%* 45.2%** 18.3%

Property received FEMA grant 22.6% 20.5% 24.5%

Property received SBA loan 22.5%** 19.5%* 9.0%

Property received elevation grant 7.1%** 1.7% 0.6%

Owner Demographics

Income < $30,000 36.0% 27.3% 31.3%

Income $30,000–$59,999 34.8% 31.4% 30.8%

Income $60,000–89,999 17.2% 21.1% 16.5%

Income $90,000+ 12.0%+ 20.1% 21.3%

Age of property owner 60.9 58.9 58.6

Number of household members 2.6 2.7 2.7

Presence of dependent minor 25.4% 26.6% 30.6%

White alone 44.0%** 46.1%+ 66.0%

Black or African American alone 50.0%** 42.6%+ 23.6%

Other/multiple races 5.7% 10.6% 10.3%

Number of survey responses 242 105 172

CDBG = Community Development Block Grant. FEMA = Federal Emergency Management Agency. SBA = Small Business Administration. 

**p < 0.01; *p < 0.05; +p < 0.10.

Note: Weighted population estimates based on 519 responses.

Sources: 2011 Property Owner Survey; CDBG administrative data
Chapter 5: Funding for Rebuilding and CDBG Programs 79

More than 45 percent of owners who applied for 

CDBG but did not receive a grant, no longer own 

the property, compared with 9.8 percent of CDBG 

recipients and 18.3 percent of owners who did not 

apply. There are two potential explanations. It may be 

that some owners who applied for the grants decided to 

(or needed to) sell their properties in the long interval 

it took for this funding to come through. Alternatively, 

homeowners who did not receive CDBG may have sold 

their homes rather than partially rebuild or try to fund 

the rebuilding themselves. 

To explore the comparisons in exhibit 5-20 further, 

we performed multinomial logit regressions that 

identify the association between the property and 

owner attributes and the categories of CDBG 

receipt. The findings from the regression analyses 

reinforce the comparisons shown in exhibit 5-20, 

providing little evidence that collinearity between the 

characteristics carries implications for interpreting 

these comparisons.50

Exhibit 5-21 presents similar information, but for 

homeowner groups defined by the reported sufficiency 

of total resources to cover rebuilding costs and use of 

personal funds for rebuilding expenses. The findings 

suggest that the set of homeowners who reported 

insufficient funds, but did not invest their own money, 

differ in several ways from other households. First, 

41 percent of these homeowners no longer own the 

property, compared with 7 percent of homeowners 

who reported having insufficient funds but invested 

their own money and 13 percent of homeowners who 

reported having sufficient funds. Echoing the previous 

discussion, the causality of this relationship is unclear. 

It may be that owners planning to sell were not willing 

to invest their own funds into rebuilding. Alternatively, 

it could be that owners who did not have the financial 

resources to rebuild had no alternative but to sell the 

property and find another place to live.

50 The exception is that adding state dummy variables (for location in Louisiana, 

Mississippi, or Texas) results in the difference between groups with respect to the 

presence of flood insurance becoming smaller and no longer statistically significant across CDBG categories.

The set of homeowners who reported insufficient 

funds and did not invest their own money also differs 

in its racial composition. White homeowners are more 

likely to report that their funds were sufficient, while 

African-American homeowners are more likely either to 

report insufficient funds and invest their own money 

or to report insufficient funds and not invest their own 

money. Lastly, homeowners who report insufficient 

funds and did not invest their own money appear to 

be less likely to have had hazard insurance, although 

the difference between the groups has a large enough 

standard error that the difference is not statistically 

significant. Multinomial logit regressions that include 

the property and owner characteristics again reinforce 

the basic comparisons shown in exhibit 5-21.

Taken as a whole, the descriptive analyses do not offer 

a clear characterization of either group. Exhibits 5-18 

and 5-19 suggest that rebuilding rates are lower for 

two groups: homeowners who applied for but did not 

receive CDBG funds, and homeowners who reported 

insufficient funds but did not invest their own money 

in rebuilding the property (or had no money to 

invest). In each case, the most striking characteristic 

of the homeowners in the group is a high frequency 

of homeowners who no longer own the property. This 

may represent an undesired outcome for some of these 

homeowners—deciding to sell in response to not being 

able to afford the costs of rebuilding. However, the 

absence of rebuilding may also reflect a purposeful 

decision by some homeowners to relocate and sell the 

property.

Ideally, we might be able to supplement the above 

analyses with a direct investigation of whether the 

presence and magnitude of a funding gap reduces the 

likelihood of rebuilding. Unfortunately, the sample size 

is too small to support this type of analysis for the set 

of interviewed owners. The nature of the owner survey 

also presents an obstacle, as respondents’ self-reported 

measures of rebuilding and funding gaps would 

likely suffer from endogeneity issues. The alternative 

approach is to rely on the state administrative CDBG 

data for the subset of CDBG recipients.
Chapter 5: Funding for Rebuilding and CDBG Programs 80

Exhibit 5-21. Property and Owner Characteristics by Funding Sufficiency and Use of Personal Funds, 

Homeowners Only

Insufficient Funds and 

No Personal Funds Put 

into Rebuilding

Insufficient Funds and 

Personal Funds Put 

into Rebuilding

Sufficient Funds 

Property Attributes 

Presence of hazard 

insurance 49.2% 60.2% 59.9%

Presence of flood 

insurance 30.6% 29.3% 29.7%

Flood damage only 17.5% 10.6% 15.1%

Wind damage only 8.6%** 15.5% 19.7%

Flood and wind damage 73.9% 73.8%+ 65.2%

Change in owner 

since 2005 40.8%** 7.2% 12.7%

Property received 

FEMA grant 23.4% 19.0% 25.6%

Property received 

SBA loan 17.5% 18.7% 16.7%

Property received 

elevation grant 0.7% 7.3%+ 3.2%

Owner Demographics

Income < $30,000 44.1% 22.4%* 35.7%

Income $30,000–$59,999 28.3% 41.3%* 26.4%

Income $60,000–$89,999 12.9% 20.3% 18.8%

Income $90,000+ 14.7% 16.0% 19.1%

Age of property owner 58.3 60.3 59.8

Number of household members 2.7 2.6 2.7

Presence of dependent minor 28.9% 25.5% 29.6%

White alone 42.9%* 51.1%+ 60.6%

Black or African 

American alone 48.8%* 38.7% 31.4%

Other/multiple races 8.1% 9.6% 8.0%

Number of survey responses 179 181 177

CDBG = Community Development Block Grant. FEMA = Federal Emergency Management Agency. SBA = Small Business Administration. 

**p < 0.01; *p < 0.05; +p < 0.10.

Note: Weighted population estimates based on 537 responses.

Sources: 2011 Property Owner Survey; CDBG administrative data
Chapter 5: Funding for Rebuilding and CDBG Programs 81

Resource Restrictions and Rebuilding

The next component of the analysis of CDBG funding 

therefore uses the state CDBG administrative data 

to examine the impact of funding gaps on rebuilding 

activity among the set of CDBG recipients. Using the 

administrative data has two major advantages. 

First, the measures of award amounts for CDBG and 

other sources of assistance come directly from the 

information used to calculate the CDBG award, so 

they are likely to be reliable. Second, the administrative 

data are available for the full windshield survey sample, 

providing far greater sample size and statistical power. 

The limitation is that this sample and measures do not 

directly correspond to the other analyses in this report. 

In particular, the measure of rebuilding is the measure 

used for the windshield survey sample in the Phase I 

report—defined in section 3.4. Another limitation is 

that these data do not permit comparison of grantees 

with other owners who did not receive (or did not 

apply for) CDBG funding.

The analysis of the CDBG administrative data directly 

examines the relationship between funding gaps and 

rebuilding. Using the program’s recorded damage 

estimate, we define a funding gap as the difference 

between the damage estimate recorded in the CDBG 

administrative data and the total amount of assistance 

received from insurance, FEMA, CDBG program, and 

other sources of assistance as recorded in the CDBG 

administrative data (other sources of assistance is 

available for Mississippi only). The analysis examines 

whether a gap is present and, if so, the amount of the 

gap.

To isolate the sample of homeowners who intended to 

rebuild their properties, the sample excludes CDBG 

recipients who chose Options 2 and 3 in Louisiana’s 

The Road Home program and the Sold Home option 

in Mississippi. The remaining analysis sample contains 

1,104 homeowners who received CDBG grants 

through Option 1 in Louisiana and Phases I and II in 

Mississippi. Of this sample, 39 percent of homeowners 

have a positive gap (insufficient funds) between their 

damage estimate and the total amount of assistance 

recorded. The mean gap amount for these homeowners 

is $57,479.

The association between funding gaps and rebuilding 

activity for this sample therefore reflects the decisions 

of homeowners who received grants contingent on 

rebuilding the damaged property. Exhibit 5-22 shows 

the association between funding gaps and whether the 

property still exhibited substantial damage in early 

2010—that is, it was not yet substantially rebuilt at 

the time of the windshield observations—using three 

different regression specifications (Models 1, 2, and 3). 

For each specification, the exhibit presents the odds 

ratio and significance level produced by the logistic 

regression. The odds ratio measures the relative change 

in the likelihood of the outcome that is associated 

with a one unit change in the independent variable. 

An odds ratio of 1 indicates that no association exists, 

and odds ratios significantly greater than 1 indicate 

that an increase in the measure (for example, in the 

presence of a funding gap) is associated with a higher 

likelihood that the outcome (for example, a property 

with substantial repair needs in 2010) is observed. 

Because the models use logistic estimation techniques, 

the odds ratio is reported with a z-statistic that is used 

to determine the level of statistical significance for each 

estimate.51

In exhibit 5-22, the funding gap variable is defined as 

a binary measure—whether a gap exists or does not 

exist. The bivariate regression (Model 1) shows a clear 

association. Homeowners with any funding gap are 

more than 2.4 times as likely to still have substantial 

damage showing on their properties in the windshield 

survey. This relationship is diminished when the 

models adjust for the extent of damage and presence of 

insurance. Model 2 adds covariates that reflect the level 

of damage recorded by FEMA, an indication of the 

initial level of damage to the property. It also includes 

51 The z-statistic is analogous to the t-statistic in least squares regression. It reflects 

the ratio of the coefficient estimate to the standard error, providing a measure of 

how confidently the estimate can be distinguished from the null hypothesis of no 

effect. A larger z-statistic implies a higher level of confidence.
Chapter 5: Funding for Rebuilding and CDBG Programs 82

block-level fixed effects to control for any unobserved 

factors that may be common to properties on the same 

block. In this model, the presence of a gap is associated 

with a property being 54 percent more likely to show 

substantial damage. Model 3 shows that this effect is 

further moderated by whether the homeowner had 

insurance. Not having insurance greatly increases the 

likelihood that substantial damage is observed (that 

is, properties without insurance are less likely to have 

been rebuilt). Controlling for the presence of insurance 

reduces the effect of a funding gap (which is no longer 

a statistically significant factor).

Exhibit 5-22. Association of Presence of Funding Gap with Property Having Substantial Damage in 

2010, Based on Windshield Observation (Logit Estimation)

Model 1: Gap Only

Model 2: Gap, Plus 

Extent of Damage and 

Geographic Factors

Model 3: Gap, Extent of 

Damage, Presence of 

Insurance, and 

Geographic Factors

Odds Ratio (z-statistic) Odds Ratio (z-statistic) Odds Ratio (z-statistic)

Funding gap exists 2.423**

(5.27)

1.540*

(1.96)

1.194 

(0.86)

FEMA damage 

assessment: minor or 

no damage

N/A 0.158**

(3.58)

0.127**

(4.10)

FEMA damage 

assessment: major or 

severe damage

N/A 0.262**

(4.17)

0.240**

(4.32)

No insurance at time 

of hurricanes N/A N/A 3.883**

(4.87)

Block fixed effects No Yes Yes

FEMA = Federal Emergency Management Agency. N = 1,104 properties. **p < 0.01; *p < 0.05; +p < 0.10.

Sources: 2010 windshield observations; CDBG administrative data

Exhibit 5-23 repeats this analysis with the funding 

gap variable defined as the size (dollar amount) of 

the gap rather than just whether a gap is present. 

Again, the bivariate regression (Model 1) shows a clear 

relationship. A $10,000 increase in the amount of a 

funding gap is associated with a property being 7.5 

percent more likely to show substantial damage (odds 

ratio is 1.075). This effect is reduced to 3.6 percent in 

the model that controls for the level of initial damage 

and block fixed effects (Model 2). Adding a covariate 

that reflects whether the homeowner had insurance 

further reduces the effect so that it is no longer 

statistically significant (Model 3). Lack of insurance is 

again a very powerful factor.

The main finding from both models is that the 

presence of a funding gap is correlated with the 

extent of damage (levels of FEMA assessment), but 

that this relationship largely reflects the reduced 

rebuilding activity among homeowners who did not 

previously have insurance. For such homeowners, 

reduced rebuilding may reflect the lack of funding 

following the hurricanes. However, it may also reflect 

unobserved attributes of homeowners willing to go 

without insurance, such as a higher tolerance for risk 

or a lower ability to afford regular insurance premiums. 

In either case, the effects shown in exhibits 5-22 and 

5-23 suggest that homeowners with funding gaps may 

have been less likely to rebuild, particularly if they were 

uninsured.
Chapter 5: Funding for Rebuilding and CDBG Programs 83

Exhibit 5-23. Association of Funding Gap Amount with Property Having Substantial Damage in 2010, 

Based on Windshield Observation (Logit Estimation)

Model 1: Gap Only

Model 2: Gap, Plus 

Extent of Damage and 

Geographic Factors

Model 3: Gap, Extent of 

Damage, Presence of 

Insurance, and 

Geographic Factors

Odds Ratio (z-statistic) Odds Ratio (z-statistic) Odds Ratio (z-statistic)

Gap amount ($10,000s) 1.075**

(4.18)

1.036+

(1.81)

1.024 

(1.16)

FEMA damage 

assessment: minor or no 

damage

N/A 0.157**

(3.57)

0.158**

(4.04)

FEMA damage 

assessment: major or 

severe damage

N/A 0.262**

(4.20)

0.262**

(4.31)

No insurance at time 

of hurricanes N/A N/A 3.946**

(4.80)

Block fixed effects No Yes Yes

FEMA = Federal Emergency Management Agency. N = 1,104 properties. **p < 0.01; *p < 0.05; +p < 0.10.

Sources: 2010 windshield observations; CDBG administrative data

An extension of the analysis in the two preceding 

exhibits is to isolate the gaps in funding that result 

directly from CDBG program rules. Although the 

funding gaps among CDBG recipients arise for a 

variety of reasons, the calculation of CDBG grant 

amounts contains four specific gaps of policy interest:

1.The maximum CDBG grant amount is $150,000: 

7.8 percent of sample homeowners—including 

owners in both Louisiana and Mississippi—had a 

funding gap because they hit the maximum CDBG 

funding amount.

2.The CDBG grant is capped at $120,000 if the 

homeowner qualifies for and claims the full 

elevation grant of $30,000: 4.8 percent of sample 

homeowners (all in Louisiana) hit the CDBG 

maximum grant amount of $120,000 because they 

also claimed an elevation grant of $30,000.

3.The CDBG grant amount is reduced to 70 percent 

of its full value for homeowners who do not 

have homeowners insurance: 5 percent of sample 

homeowners (all in Louisiana) are penalized 30 

percent of the award amount for not carrying the 

proper levels of insurance.

4.The grant amount is capped at $100,000 for 

homeowners in Mississippi’s Phase II program: 2.5 

percent of sample homeowners (all in Mississippi) 

receive the maximum Mississippi Phase II grant 

amount of $100,000.

Exhibit 5-24 examines the relationship between gaps 

due to each of these CDBG program rules and the 

level of rebuilding. Exhibit 5-24 defines the grant cap 

variable as a binary measure—whether the grant is 

capped or is not capped. Each of the models includes 

covariates that reflect the level of hurricane damage 

(FEMA damage categories) and block fixed effects (that 

is, the models are analogous to Model 2 in exhibits 

5-19 and 5-20). Model 1 in exhibit 5-24 shows that 

properties that encountered any one of these four 

grant caps were 54 percent more likely to still have 

substantial damage by 2010. Model 2 separates this 

variable into the specific grant caps and suggests that 

this effect is concentrated almost entirely among 

the homeowners who received the maximum Phase 

II award in Mississippi. These properties were 3.1 

times more likely to have substantial damage than 
Chapter 5: Funding for Rebuilding and CDBG Programs 84

other properties. The magnitude of the odds ratio for 

variables receiving a 30 percent penalty in Louisiana 

is also large, but the effect is not significant. Model 3 

shows that both effects are moderated by whether the 

homeowner had insurance.52

The patterns shown in exhibit 5-24 echo the findings 

from exhibits 5-22 and 5-23. The presence of a 

52 We also conducted this analysis defining the grant cap as the amount of the 

funding gap resulting from the gap. The results were consistent with those presented in exhibit 5-21.

funding gap is positively associated with reduced 

rebuilding, but primarily among homeowners who did 

not have insurance. In the case of the grant caps, the 

rules governing the award amounts were structured 

to penalize homeowners who did not carry adequate 

property insurance. The findings presented in this 

section suggest that these rules carry implications for 

the eventual levels of rebuilding.

Exhibit 5-24. Association of Presence of a Funding Cap with Property Having Substantial Damage in 

2010, Based on Windshield Observation (Logit Estimation)

Model 1: Presence of 

Cap Only

Model 2: Specific 

Program Caps

Model 3: Specific 

Program Caps

Odds Ratio (z-statistic) Odds Ratio (z-statistic) Odds Ratio (z-statistic)

Any cap 1.54* (1.96) N/A N/A

Cap: $100,000 

(Mississippi Phase II) N/A 3.1 (2.31) 1.355 (0.57)

Penalty: 70% award 

(Louisiana) N/A 2.047 (1.38) 0.761 (0.55)

Cap: $120,000 

(Louisiana) N/A 1.306 (0.56) 0.902 (0.22)

Cap: $150,000 

(Louisiana and 

Mississippi)

N/A 1.045 (0.12) 0.91 (0.24)

FEMA damage 

assessment: minor or no 

damage

0.158 (3.58) 0.155 (3.69) 0.123 (4.16)

FEMA damage 

assessment: major or 

severe damage

0.262 (4.17) 0.272 (4.01) 0.238 (4.29)

No insurance at time of 

hurricanes N/A 4.235 (4.97)

Block fixed effects Yes Yes Yes

FEMA = Federal Emergency Management Agency. N = 1,104 properties. **p < 0.01; *p < 0.05; +p < 0.10.

Sources: 2010 windshield observations; Community Development Block Grant administrative data

When interpreting this finding, it is useful to keep 

in mind the overall level of rebuilding. More than 70 

percent of homeowners who reported a funding gap did 

not show substantial damage by the windshield survey’s 

definition—compared with 86 percent of homeowners 

without a funding gap. This figure drops to only 60 

percent for homeowners who both have a funding gap 

and did not have insurance. As a result, the rebuilding 

patterns documented in this section apply to the 

relative differences in rebuilding rates between these 

groups.

In sum, differences in the likelihood of rebuilding do 

exist, with moving (selling the property) and funding 

gaps predicting lower levels of rebuilding.
Chapter 5: Funding for Rebuilding and CDBG Programs 85

5.6 OWNER EXPERIENCES 

WITH THE DIFFERENT 

PROGRAM MODELS

Louisiana and Mississippi

The owner survey asked recipients of CDBG funds in 

Louisiana and Mississippi whether they experienced 

any problems with the programs that delayed their 

rebuilding efforts and (if so) what those problems 

were. The sample size was too small in Mississippi to 

use the survey data. In Louisiana, however, 186 people 

reported receiving a CDBG award and answered this 

question about their experience, permitting some 

analysis. (We did not weight these data to create 

population estimates because the sample size is so 

small.) Of these respondents, 129 (69 percent) said 

they had not experienced any problems with the 

program, but 57 (31 percent) said they had experienced 

one or more problems. The most common problems 

reported were delays in getting the application accepted 

(24 people), problems reaching program staff (19 

people), delays in receiving program funds (14 people), 

problems determining what paperwork to bring in 

(13 people), and delays in completing the damage 

assessment for the property (11 people).

Texas

In the Texas CDBG program, state contractors 

built or rebuilt the homes of CDBG recipients. The 

property owner survey offered an opportunity to 

assess recipients’ experiences with the state-managed 

rebuilding program. Of the 83 survey respondents 

in Texas, only 31 reported having a new home built 

through a state or local program, so the findings 

reported here should be treated as exploratory only. 

However, the survey findings suggest a moderate level 

of satisfaction with the Texas CDBG program among 

recipients. As shown in exhibit 5-25, 58 percent of 

survey respondents were very satisfied overall with 

the program and another 19 percent were somewhat 

satisfied. Less than one-half of the survey respondents 

(45 percent) reported being very satisfied with the 

quality of the construction work, although less 

than one in five reported being dissatisfied. Most 

respondents (77 percent) were satisfied with the length 

of time that it took to complete construction.

Exhibit 5-25. Reported Satisfaction with the CDBG Program in Texas Among CDBG Recipients

Number Percent

Satisfaction with the Program Overall

Very satisfied 18 58

Somewhat satisfied 6 19

Somewhat dissatisfied 4 13

Very dissatisfied 3 10

Total 31 100

Satisfaction with the Quality of the Construction Work

Very satisfied 14 45

Somewhat satisfied 11 35

Somewhat dissatisfied 1 3

Very dissatisfied 5 16

Total 31 100

Satisfaction with Length of Time from Application to Construction Completion

Satisfied 24 77

Not satisfied 7 23

Total 31 100

CDBG = Community Development Block Grant. 

Sources: 2011 Property Owner Survey; unweighted survey data
Chapter 5: Funding for Rebuilding and CDBG Programs 86

Time Taken to Complete Rebuilding Under the 

Compensation and Rehabilitation Models

One important consideration in comparing the 

compensation and rehabilitation models of CDBG 

assistance is the length of time that it takes to 

complete rebuilding. We might hypothesize that the 

compensation model of Louisiana and Mississippi 

CDBG programs, in which owners receive a lump sum 

to pay for rebuilding they arrange themselves, would 

allow rebuilding to occur more quickly than under the 

rehabilitation model in effect in Texas, in which state 

contractors do the work and environmental and other 

reviews are needed to comply with federal and state 

regulations. However, we might further hypothesize 

that fewer recipients under the compensation model 

would actually complete rebuilding, because of the 

level of effort required on the part of the owner, 

the greater potential for contractor fraud, and the 

opportunity to use the funds to address other needs. 

The survey findings shed light on both hypotheses.

Neither the CDBG administrative data nor the owner 

survey provides information on when owners received 

their CDBG grants. However, the survey asked owners 

for the month and year in which they began rebuilding 

activities and (as applicable) the month and year in 

which the repairs were completed. This enables us to 

calculate the number of months spent on rebuilding 

among CDBG recipients in each state. Exhibit 5-26 

presents the results of this analysis.

The survey data suggest that rebuilding from the 

start of repair activity to completion took longer in 

Louisiana and Mississippi under the compensation 

model than in Texas under the rehabilitation model. 

On average, recipients of CDBG funds under the 

compensation models in Louisiana and Mississippi 

took 13.9 and 10 months, respectively, to rebuild 

compared with 8.1 months under the Texas 

rehabilitation model. The average rebuilding time 

for Louisiana recipients is significantly longer than 

the average rebuilding time for Texas recipients. The 

average rebuilding time for Mississippi recipients is also 

longer than for Texas recipients but the difference is 

not statistically significant. This difference between the 

combined compensation models and the rehabilitation 

model is statistically significant. Yet the difference in 

program model alone does not necessarily explain this 

difference.

Exhibit 5-26. Months to Complete Repair and Rebuilding Activities (from Repair Start to Completion) 

by State

Louisiana Mississippi Texas

Estimate 90% CI Estimate 90% CI Estimate 90% CI

25th percentile 4.9 3.2–6.7 3.0 2.1–3.8 1.0 0.0–2.2

Median 9.6 7.4–11.8 5.8 4.2–7.5 4.4 1.8–6.9

Mean 13.9 11.3–16.4 10.0 7.1–12.9 8.1 4.6–11.6

75th percentile 16.9 13.1–20.6 11.4 5.8–17.0 9.3 4.9–13.6

CDBG = Community Development Block Grant. CI = 90 percent confidence interval.

Notes: Weighted population estimates based on 152 survey responses by CDBG recipients who completed rebuilding. Excludes eight 

owners who reported starting and completing repairs on the same month.

Sources: 2011 Property Owner Survey
Chapter 5: Funding for Rebuilding and CDBG Programs 87

This analysis, for example, only compares actual 

construction times—that is, from repair start to 

completion—as opposed to other measures of time 

for rebuilding. Equally valid comparisons could be 

made from either the time of the 2005 storms to 

the point of rebuilding (probably the measure of 

greatest interest to the owners themselves) or from 

the time of program start to the point of rebuilding 

(of concern to national policymakers looking at 

administrative implementation). In fact, the average 

time to complete rebuilding in Texas from the time 

of the 2005 storm events is substantially longer than 

those of Louisiana and Mississippi from the same 

time.53 This finding stands in contrast to the lower 

average time for rebuilding in Texas than the other 

two states when just considering construction. It also 

demonstrates differences in timing for appropriations 

and program implementation for each state. Louisiana 

administrators, for example, had the highest program 

allocation and the highest number of recipient owners. 

The involvement of regional governments in Texas early 

on delayed the acceptance of first applications there. In 

53 Hurricanes Katrina and Rita made landfall on August 29 and September 23, 

2005, respectively. Assuming a post-storm start date of September 1, 2005 for 

Louisiana and Mississippi and a post-storm start date of October 1, 2005 for 

Texas, as recommended by HUD, the average (mean) time to rebuild was 23.8 

months in Louisiana, 13.5 months in Mississippi, and 39.8 months in Texas. The 

time to rebuild was significantly shorter in Louisiana compared with Texas, but 

significantly longer in Louisiana compared with Mississippi. Correspondingly, 

the time to rebuild in Mississippi was significantly shorter than in Texas. These 

differences are statistically significant at the 1 percent level.

all states, the timing of federal allocations also partially 

determined the individual program start dates.

The rebuilding rates for CDBG recipients across 

the three states provide additional insight into the 

respective models’ outcomes. Exhibit 5-27 shows the 

percent of CDBG recipients in each state reporting 

that rebuilding was complete. In Texas, 89.4 percent 

of CDBG recipients reported that rebuilding was 

complete as of early 2011, compared to 69.0 percent 

in Louisiana and 64.2 percent in Mississippi. The 

differences between Louisiana and Texas, and the 

difference between Mississippi and Texas, are both 

statistically significant. While the rate of completion 

is higher in Texas, where the rehabilitation model 

was in effect, it is also true that the Texas program 

operated on a much smaller scale than the programs 

in Louisiana and Mississippi. As chapter 1 described, 

only about 2,300 Texas homeowners received CDBG 

awards for damage from the 2005 hurricanes, compared 

with 28,000 in Mississippi and 128,000 in Louisiana. 

The different types and scale of damage across the 

three states—particularly the virtual absence of flood 

damage in Texas—also makes comparison difficult. 

Yet, it is possible that the concentration of accredited 

contractors in Texas, level of contract management 

by the program, as well as the lower severity of 

damage among Texas CDBG recipients’ properties all 

contributed to this more timely construction schedule.

Exhibit 5-27. Percent of CDBG Recipients Completing Repairs by State

Louisiana Mississippi Texas

Estimate 90% CI Estimate 90% CI Estimate 90% CI

Percent of recipients who 

completed rebuilding 69.0 62.7–75.1 64.2 54.1–74.2 89.4 80.7–98.0

CDBG = Community Development Block Grant. CI = 90 percent confidence interval.

Note: Weighted estimates based on 257 survey responses.

Sources: 2011 Property Owner Survey; CDBG administrative data
Chapter 5: Funding for Rebuilding and CDBG Programs 88

5.7 SUMMARY OF 

CHAPTER FINDINGS

This chapter presented analyses related to CDBG 

receipt and rebuilding and explored differences across 

the three states and program designs. The information 

on CDBG receipt and grant amounts presented in this 

report came from the property-level administrative data 

obtained from the state CDBG programs in March 

2010, although we use owner-reported information 

on the uses of CDBG grants. Due to the very small 

number of recipients of CDBG small rental grants in 

the sample, the analysis focused on homeowners and 

the CDBG homeowner programs.

Across all three states, slightly more than one-half of 

the homeowners in the owner survey sample received 

CDBG homeowner assistance. In Texas, receipt of 

CDBG assistance meant that the state had conducted 

repair and rebuilding activities on the owners’ behalf. 

In Louisiana and Mississippi, receipt of CDBG 

assistance took the form of financial assistance provided 

primarily for rebuilding activities to be undertaken by 

owners themselves. In Louisiana, owners could decide 

to sell their property to the state, rather than rebuilding 

it, and receive financial compensation. Slightly more 

than 10 percent of the owners in the Louisiana survey 

sample (and about 8 percent of the owners statewide) 

selected The Road Home Options 2 or 3, and sold 

their properties to the state. The rest received CDBG 

grants designed to help them stay in their homes and 

rebuild. Mississippi grant recipients had options to sell 

as well, but were also given more latitude with regard 

to rebuilding requirements.

Many of the property and owner characteristics 

of CDBG recipients, notably, followed the grant 

program’s original intent. The subsequent use of the 

funds, however, varied across the programs. Among 

CDBG recipients in Louisiana and Mississippi who 

received CDBG rebuilding grants (that is, excluding 

Option 2 and 3 recipients in Louisiana), most owners 

reported using all or part of their grants for rebuilding. 

In Louisiana, 87 percent of CDBG recipients reported 

using the entire grant for rebuilding, 7 percent reported 

using part of the grant for rebuilding, and 6 percent 

reported using none of the grant for rebuilding. In 

Mississippi, a significantly higher share of recipients 

used their grants for something other than rebuilding, 

including 20 percent who said they used only part of 

their grant for rebuilding and 16 percent who said 

they spent none of their grant funds for rebuilding. 

Analysis of reported uses of funds among the minority 

of CDBG recipients who used their grant funds for 

something other than rebuilding shows that the most 

common use of funds was to purchase furniture, 

followed by paying for everyday expenses, and paying 

off a mortgage or loan.

Survey respondents were asked to estimate the amount 

of funding received for the purpose of repairing or 

rebuilding their hurricane-damaged properties from a 

variety of sources, including homeowners insurance, 

flood insurance, elevation grants, FEMA’s individual 

assistance program, SBA loans, state programs, 

churches or charities, and friends and family, as well 

as the CDBG disaster assistance programs. Taking into 

account all of these sources plus the CDBG grant, 

CDBG recipients reported receiving about $50,000 

more in financial assistance than owners who did not 

receive CDBG.

CDBG recipients in Louisiana and Mississippi 

generally reported receiving other sources of funding in 

addition to CDBG; this was less often the case among 

CDBG recipients in Texas. In general, the survey 

findings suggest that CDBG recipients were similar to 

nonrecipients in drawing on a range of funding sources 

to meet their rebuilding needs, although they received 

less assistance from these other (non-CDBG) sources. 

This is consistent with the design of the program, 

which was intended to make up the shortfall between 

rebuilding costs and the funding available to owners 

from other sources.

Despite the general differences in funding amounts, 

more than one-third of both CDBG recipients and 
Chapter 5: Funding for Rebuilding and CDBG Programs 89

non-CDBG recipients said their funding was not 

sufficient to meet their needs. As a consequence, a 

slight majority of owners in both groups reported 

supplementing their financial assistance with personal 

funds (usually from personal bank accounts) to rebuild.

The analysis also provided evidence that the rates of 

rebuilding varied by homeowners’ access to funding 

and the presence and size of funding gaps. Specifically, 

when analyzing the rates of rebuilding across owners 

with various types and quantities of funding, we 

identified two groups of owners with particular 

rebuilding lags: (1) people who applied for CDBG 

assistance but did not receive it and (2) people who 

reported that they did not receive sufficient resources 

to rebuild and were not able to (or chose not to) 

use personal resources to supplement the assistance 

received.

Among homeowners who applied for CDBG assistance 

but did not receive funds, only 58 percent of properties 

were rebuilt, compared with more than 75 percent of 

other homeowners who either did not apply at all or 

who applied and received funds. In a similar pattern, 

only 46 percent of properties were rebuilt among 

households who reported having insufficient funding 

and who did not use their own funds. For both groups, 

the rate of moving away from the property was also 

significantly higher. Additional analysis demonstrates 

that the presence of a funding gap (for example, 

by reaching the grant caps for the various CDBG 

programs) is correlated with the continued presence 

of observable damage in early 2010, although this 

relationship largely reflects the lower level of rebuilding 

activity among homeowners who did not have property 

insurance at the time of the hurricanes.

Finally, the chapter included two findings related to 

owner experiences with the different CDBG program 

models. First, most survey respondents in both 

Louisiana and Texas reported satisfaction with the 

CDBG programs in their states, although the measures 

were different for the two states. Second, Texas CDBG 

recipients, under the rehabilitation model, reported 

faster rebuilding in terms of construction time than 

recipients in Louisiana and Mississippi. Texas CDBG 

recipients were also more likely to complete rebuilding 

activities than CDBG recipients in the other two states, 

although actual implementation of grant programs and 

issuing of grants varied significantly between the states. 

These differences paint a different picture with regard 

to overall rebuilding efforts, starting with the time of 

the storms.
Appendix A: State CDBG Program Descriptions 90

APPENDIX A. STATE CDBG 

PROGRAM DESCRIPTIONS

LOUISIANA

In Louisiana, the CDBG-funded disaster recovery 

program is known as The Road Home program, 

administered by the state’s Louisiana Recovery 

Authority and Office of Community Development’s 

Disaster Recovery Unit. The Road Home program 

provides compensation to homeowners and owners of 

small rental properties whose properties were damaged 

by Hurricanes Katrina and Rita and for whom the other 

sources of disaster assistance funding (private insurance, 

FEMA housing assistance, and SBA loans) did not 

cover the cost of repairing or rebuilding the property.

The Road Home Homeowner Program

The Road Home Homeowner Program provided 

financial compensation, an average of about $68,000, 

for roughly 128,000 Louisiana homeowners whose 

residences were damaged as a result of the 2005 

storms.54 Applicants to The Road Home Homeowner 

Program were required to choose one of three options, 

which affected the calculation and amount of the 

compensation:

•	Option 1: Remain in the home.

•	Option 2: Sell to the state and purchase another 

home in the state.

•	Option 3: Sell to the state and become a renter in 

Louisiana or move out of state.

The majority of Road Home recipients (92 percent, or 

118,058 recipients as of July 14, 2011) chose Option 

1.55 The maximum total compensation amount for 

all three options was $150,000. Homes sold to the 

54 Figures based on CDBG administrative data, April 2011.

55 Based on state CDBG administrative data from April 2011. Of recipients of The 

Road Home homeowner funds, 92 percent selected Option 1, 6 percent selected 

Option 2, and 2 percent selected Option 3.

state under Options 2 (8,238 homes) and 3 (2,310 

homes) were transferred to the Louisiana Land Trust 

(LLT), the holding agency for properties owned by the 

state of Louisiana. LLT has about 10,500 homes in its 

inventory.56

As a condition of accepting the grant, owners who 

chose Option 1 placed covenants on the property. The 

covenants require the property owner to use the house 

as a primary residence within 3 years from the date of 

closing, to maintain hazard insurance on the home (as 

well as flood insurance if the home is located in a flood 

plain), comply with base flood elevations adopted by 

local government, and conform with local building codes 

in conducting rebuilding or repair. Owners who do not 

meet these requirements within the 3-year period of the 

covenants can apply for up to two 1-year extensions. 

Grant recipients who do not meet the terms of the 

covenants may be required to repay the entire amount of 

the grant.

Three different types of assistance were available:

•	The basic compensation grant was the primary 

tool used to assist homeowners. This grant was 

based on either the uncompensated damage cost 

(that is, the estimated cost of damage minus any 

other compensation the applicant received) or the 

uncompensated loss of value (that is, the pre-storm 

value minus any other compensation the applicant 

received).

•	The additional compensation grant offered up to 

$50,000 to owners with incomes equal to or less 

than 80 percent of Area Median Income (AMI) and 

who chose to remain in their homes or sell their 

homes to the state.

56 Current Property Listing as of 5/13/11, downloaded from www.lalandtrust.us.
Appendix A: State CDBG Program Descriptions 91

•	Owners who opted to rebuild their homes and who 

were located in a floodplain based on FEMA’s Base 

Flood Elevation (BFE) or Advisory Base Flood 

Elevation (ABFE) were eligible to apply for an 

elevation incentive to elevate their homes to meet 

the BFE or ABFE standard. The award amount 

is $30,000 for site-built homes and $20,000 for 

manufactured homes.

The Road Home Small Rental Property Program

The Road Home Small Rental Property Program offered 

funding to encourage property owners in nine specific 

parishes to repair their one- to four-unit rental properties 

and make these dwellings available to low- and moderateincome tenants at affordable rents. Funding was offered 

in the form of a no-interest, no-payment, forgivable loan, 

provided either as up-front financing or reimbursement 

after repairs had been made and the property met local 

building codes. In return, the owner agreed to maintain 

affordable rent levels for 10 years. The amount of funding 

available varied based on the income level of the tenants to 

be served, with the largest amount of funding available to 

owners who agreed to offer the lowest rents. The total loan 

amount could not exceed 100 percent of the estimated cost 

to repair or reconstruct the rental property.

As of April 2011, about 4,700 awards had been made 

to rental property owners, in an average amount of 

about $102,000.57

MISSISSIPPI

Mississippi’s CDBG-funded programs for homeowners 

and small landlords are administered by the Mississippi 

Development Authority (MDA). The program for 

homeowners is the Homeowner Assistance Program 

(HAP). The program for owners of one- to four-unit 

rental properties is the Small Rental Property Assistance 

Program. Eligibility for both programs required the 

property to be located in one of four Mississippi counties 

(Hancock, Harrison, Jackson, or Pearl River) and to have 

suffered flood damage as a result of Hurricane Katrina.58

57 The Road Home Small Rental Property Program Incentive Operations Status 

Report April 25, 2011. Based on commitment letters and amount committed and 

obligated to applicants active in the Constructive Management Initiative Option.

58 Properties that sustained only wind damage from the hurricane (no flood damage) were not eligible for assistance under either phase.

Homeowner Assistance Program 

HAP provided financial compensation for Mississippi 

homeowners whose residences were damaged as a result 

of Hurricane Katrina. As in Louisiana, the program 

provided one-time grant payments to homeowners. The 

maximum grant amount was $150,000 for Phase 1, 

$100,000 for Phase 2, and either 50 or 70 percent of 

the Phase 1 or Phase 2 grant for Phase 3. In Mississippi, 

almost 28,000 homeowner awards were made, with an 

average award amount of about $72,500.59

Phase 1 and Phase 2 HAP recipients agreed to place 

covenants on the storm-damaged property to ensure 

that any rebuilding or repairs would be made in 

accordance with local codes, that the home would 

be elevated in accordance with FEMA advisory flood 

elevations, and that the homeowner and successors 

in title would obtain and maintain both homeowners 

insurance and flood insurance on the property, whether 

or not the property was located in a flood plain.

Elevation grants in an amount up to $30,000 were also 

available to homeowners to defray the cost of elevating 

homes to FEMA’s flood requirements. Elevation 

grant funds could be used to raise homes on the same 

footprint or on expanded or changed footprints, or to 

replace an existing unit with an elevated one. Elevation 

grant funds could be combined with Phase 1 or Phase 

2 HAP grants, but could only be used to cover the 

increased cost of elevating the structure.

To be eligible for HAP funds, the applicant had to 

have owned and occupied the property at the time of 

the storm. The two phases targeted different owner 

groups, however. Phase 1 targeted homeowners 

living outside the established flood zones who had 

homeowners insurance at the time of the storm. Phase 

2 was designed to assist homeowners not eligible under 

Phase 1. Phase 2 applicants were not required to have 

carried homeowners insurance, and their homes could 

have been located inside or outside the 100-year flood 

plain.60 Eligibility was also limited to owners with 

incomes equal to or less than 120 percent of AMI.

59 CDBG administrative data, April 2011.

60 The 100-year flood plain is the area that would be expected to be inundated only 

in very extreme floods (happening approximately once every 100 years, or with a 

probability of 1 percent in any year).
Appendix A: State CDBG Program Descriptions 92

Phase 3 of the HAP, also known as the Sold Home 

program, was designed for Phase 1 and Phase 2 grant 

applicants who no longer own their damaged residence, 

have an uncompensated loss, and who have not been able 

to attach the required covenants to the damaged residence 

property. Originally, MDA had allowed applicants who 

sold their homes to receive grant funds if a covenant was 

attached to the damaged residence by the new owners of 

that property. But many Phase 1 and Phase 2 applicants 

indicated that the new homeowners were unwilling to 

sign the covenants. MDA created the Sold Home program 

to enable these applicants to qualify for grant money, 

independent of the cooperation of the new owner(s) of 

their damaged former residence.

Most awards made under the homeowner program were 

made under Phase 1 (67 percent, more than 18,500 

recipients) and Phase 2 (31 percent, more than 8,600 

recipients).61

Small Rental Assistance Program

The Small Rental Assistance Program targeted owners 

of small rental properties with a goal of renovating 

and restoring small rental properties in stormdamaged neighborhoods. The program provided 5-year 

forgivable loans under one of four program options:

•	Option A: Rental subsidy

•	Option B: Rehabilitation or construction of 

Hurricane Katrina damage

•	Option C: Reconstruction or conversion of nonHurricane Katrina damage property

•	Option D: New construction reimbursement

The maximum award was $30,000 for a four-bedroom 

rental unit, meaning that the maximum award that any 

one property could receive was $120,000 (for a fourunit property in which all units had four bedrooms). 

Recipients agreed to attach a covenant to the property 

for 5 years that includes compliance with local and state 

building code requirements, maintenance of hazard, flood, 

61 Based on analysis of state CDBG administrative data from March 2010.

and commercial liability insurance, and an agreement to 

rent 51 percent or more of the available units to tenants 

with an income equal to or less than 80 percent of the 

AMI, with 100 percent of units being rented to tenants 

with incomes equal to or less than 120 percent of AMI.

In order to be eligible for Small Rental Assistance 

awards, properties had to pass a site inspection and 

environmental review at MDA’s expense. Applicants 

also had to have a good credit history and a satisfactory 

owner-manager experience surrounding the property. 

Applicants did not have to own the property at 

the time of Hurricane Katrina, and individuals, 

corporations, partnerships, trusts, churches, and 

nonprofit organizations were eligible to apply.

As of April 2011, about $227 million had been 

awarded for about 3,900 units, in an average amount of 

about $58,000 per unit.62

TEXAS

The state of Texas received two rounds of CDBG 

disaster recovery funding to address damage caused by 

Hurricane Rita.63 The Texas Department of Housing 

and Community Affairs (TDHCA) used this funding 

for three separate homeowner programs: the Council 

of Government (COG) Programs, the Homeowner 

Assistance Program (HAP), and the Sabine Pass 

Restoration Program. Texas did not create a program 

specific to owners of small-scale rental properties. A 

total of about 2,270 awards had been made under all 

three programs as of April 2011.64

Council of Government Programs

TDHCA allocated $40 million in supplemental 

CDBG funds to homeowner assistance programs 

administered by three COGs: Deep East Texas COG, 

Houston-Galveston Area COG, and the Southeast 

62 CDBG administrative data, May 2, 2011. Note that amounts for Mississippi are 

per unit, not per property owner, so average amounts between the two states are 

not comparable.

63 In 2008, Texas also received $3.1 billion in supplemental CDBG funding to 

address damage caused by Hurricanes Ike and Dolly. The use of those funds for 

housing recovery is outside the scope of this study.

64 CDBG administrative data, March 2010 and April 2011.
Appendix A: State CDBG Program Descriptions 93

Texas Regional Planning Commission COG. Together, 

these COGs assisted approximately 350 homeowners 

to repair or replace their homes damaged by Hurricane 

Rita.

In the COG programs, as in the other Texas programs, 

CDBG funds are used to pay for contractors to perform 

the rehab or reconstruction work. If the property is 

located in a flood zone, the owner assumes a zerointerest, 3-year forgivable loan for the amount of 

the funding. The three COGs vary in the amount of 

assistance provided:

•	Deep East Texas offered up to $40,000 for 

rehabilitation and up to $65,000 for reconstruction 

and new construction.

•	 Houston-Galveston offered up to $25,000 for 

rehabilitation and up to $65,000 for reconstruction 

and new construction.

•	 Southeast Texas offered up to $65,000 

for rehabilitation and up to $100,000 for 

reconstruction and new construction. The program 

also offered up to $35,000 for elevation of 

properties in certain flood zones and $5,000 per lot 

for demolition. Total assistance could not exceed 

$100,000.

Eligibility for the program was restricted to singlefamily homes that were located in certain specified 

counties and were damaged or destroyed by Hurricane 

Rita. Applicants also had to have incomes equal to or 

less than 80 percent of AMI and had to have owned 

and occupied the property at the time of the hurricane. 

Additional minor eligibility criteria varied by COG.

Homeowner Assistance Program 

HAP provided assistance in the form of a forgivable 

loan for properties located in special flood hazard areas; 

otherwise, the assistance took the form of a grant. 

The maximum award amount in HAP is $75,000 per 

property.65 The award is calculated based on the Storm 

Damage Cost Gap, which is the amount of storm damage 

(based on the cost of completed repairs or a damage 

65 Interview with TDHCA staff, August 20, 2009.

assessment by FEMA, SBA, private insurance, or another 

approved damage assessor) minus any assistance received 

from FEMA grants, insurance proceeds, National Flood 

Insurance Program (NFIP) proceeds, or SBA loans. As 

with the COG program, HAP funds are disbursed directly 

to contractors selected by TDHCA at specified intervals in 

the construction process.

Only owners of single-family homes with income 

equal to or less than 80 percent of AMI were eligible 

to apply for HAP funds. In addition, the owner must 

have occupied the property as a primary residence at 

the time of Hurricane Rita. Finally, the property had 

to be located in 1 of the 22 counties eligible for FEMA 

assistance and must have sustained major or severe 

storm damage.

Sabine Pass Restoration Program

The Sabine Pass Restoration Program provided assistance 

to residents of the coastal community of Sabine Pass. The 

program offered three types of assistance, all in the form 

of a deferred forgivable loan:

•	 Up to $40,000 to assist with home rehabilitation 

and reconstruction.

•	 Up to $30,000 to help with the costs of elevating 

repaired or rebuilt homes.

•	 Up to $15,000 for accessibility-related costs 

associated with elevating the dwelling.

As with the HAP, funds were disbursed directly to 

contractors selected by TDHCA at specified intervals in 

the construction process.

To be eligible for the Sabine Pass Restoration program, 

homeowners had to have lived in Census Tract 

4824501160 and have storm damage to their home 

caused by Hurricane Rita. The program was available 

to families who had insurance (but with an insufficient 

amount of coverage), as well as those who did not have 

homeowners insurance. Owners with incomes up to 150 

percent of AMI were eligible to apply for rehabilitation 

and reconstruction assistance. Households of all income 

levels were eligible to apply for elevation assistance.
Appendix B: Overview of the Property Owner Survey 94

APPENDIX B. OVERVIEW 

OF THE PROPERTY 

OWNER SURVEY

The property owner survey questionnaire consisted 

of an introduction and 12 sections (Sections A-L). 

Multiple sections were needed to accommodate 

the different state CDBG programs and different 

rebuilding paths taken by owners. Most respondents 

answered only 5-6 sections of the survey. Exhibit B-1 

presents, for each section of the survey, the intended 

respondents for the section, the types of questions 

included in the section, and the reason for including 

the questions.

Exhibit B-1. Respondents, Content, and Reason for Inclusion by Survey Section and Subsection

 Survey Section Subsection Respondents, Content, and Reason for Inclusion

Introduction N/A Respondents: All respondents.

Content:

•	Description of survey purpose, length, and confidentiality.

•	Invitation to participate in the interview and rescheduling 

if necessary.

•	Screener questions to ensure that all respondents either 

owned a storm-damaged residential property in 2005 or 

purchased a storm-damaged property after 2005 as a 

rental property.

Reason: The screener questions are necessary to ensure that the 

respondent is the correct person of interest.

A: Baseline Property 

Characteristics and 

Condition

A1. Respondents: Owners (as of August 2005) of properties that 

sustained hurricane damage.

Content:

•	Characteristics and condition of property and 

neighborhood pre-storm.

•	Tenure (owner/renter) and occupancy pre-storm.

•	Pre-storm market value, mortgage status, and insurance 

coverage.

Reason: To provide baseline information on the characteristics 

and value of the property prior to the 2005 hurricanes and 

distinguish between homeownership and rental properties.
Appendix B: Overview of the Property Owner Survey 95

 Survey Section Subsection Respondents, Content, and Reason for Inclusion

A: Baseline Property 

Characteristics and 

Condition

(continued)

A2. Respondents: Owners who purchased the property after the 

2005 hurricanes as rental properties.

Content:

•	Characteristics, condition, and occupancy of property at 

time of purchase.

Reason: To provide information on the characteristics and value 

of the property at time of purchase as a baseline against which to 

compare its current characteristics.

B: Current Ownership 

of Property

N/A Respondents: All respondents.

Content:

•	Current ownership of property.

•	If no longer own, whether sold or lost to foreclosure.

Reason: To establish the current ownership of the property. 

Respondents who lost the property to foreclosure may be less 

likely to have rebuilt prior to losing the property.

C: Current 

Occupancy and 

Condition of the 

Property

N/A Respondents: Current owners only.

Content:

•	Current characteristics and condition of property and 

neighborhood.

•	Current tenure (owner/renter) and occupancy.

•	Current neighborhood satisfaction and neighborhood 

safety.

Reason: To document current housing and neighborhood 

conditions among properties that sustained significant storm 

damage.

D: Housing Status of 

Homeowners Living 

Elsewhere

N/A Respondents: Respondents no longer living on the property.

Content:

•	Current housing conditions and neighborhood satisfaction 

for relocated households.

•	Interest in returning to pre-storm neighborhood and 

obstacles to returning.

Reason: To document housing and neighborhood conditions 

among households that relocated.
Appendix B: Overview of the Property Owner Survey 96

 Survey Section Subsection Respondents, Content, and Reason for Inclusion

E: Extent of 

Hurricane Damage

N/A Respondents: Owners as of August 2005.

Content:

•	Level and type of storm damage.

Reason: To provide information on the level and type of storm 

damage necessary for analyzing whether owners received the 

resources they needed to rebuild and determining which owners 

may not have been eligible for CDBG assistance based on the 

type of damage their properties sustained.

F: Repair and 

Rebuilding Activities

F1. Respondents: Owners as of August 2005 who still own 

the property.

Content:

•	Repair and rebuilding activities since hurricanes—nature 

and extent of the work and whether the work was 

completed.

•	Barriers to rebuilding.

•	Incidence of contractor fraud.

Reason: To provide information on the rebuilding status of the 

property and on obstacles to rebuilding and factors that affected 

the pace of rebuilding.

F2. Respondents: Owners as of August 2005 who no longer own the 

property.

Content:

•	Same as F1.

Reason: Same as F1.

F3. Respondents: Owners who purchased the property after 2005 

and still own it.

Content:

•	Same as F1.

Reason: Same as F1.
Appendix B: Overview of the Property Owner Survey 97

 Survey Section Subsection Respondents, Content, and Reason for Inclusion

F: Repair and 

Rebuilding Activities

(continued)

F4. Respondents: Owners who purchased the property after 2005 

and no longer own it.

Content:

•	Same as F1.

Reason: Same as F1.

G: Reasons for Not 

Rebuilding

G1. Respondents: Respondents who still own the property but have 

not done any rebuilding or repair work to date.

Content:

•	Reasons for not rebuilding.

•	Expectations for when rebuilding will start.

•	Plans for property once rebuilding is complete.

Reason: To provide information on obstacles to rebuilding and on 

respondents’ intention for the property, which could affect their 

propensity to rebuild.

G2. Respondents: Respondents who no longer own the property and 

did not do any rebuilding or repair work while they owned it.

Content:

•	Same as G1, except no questions on plans for property.

Reason: Same as G1.

H: Sources and Uses 

of Funds—Louisiana

H1. Respondents: Respondents who owned a storm-damaged 

property in Louisiana.

Content:

•	Sources of funding received for rebuilding or as 

compensation for damage caused by hurricanes Katrina or 

Rita.

•	Amounts of funding received.

•	Gap between funding received and rebuilding/repair 

needs.

•	Owner resources spent on rebuilding/repair.

Reason: To provide information on the amounts and types of 

funding received, including CDBG funds, and whether those 

funds were sufficient to cover the cost of repairs.
Appendix B: Overview of the Property Owner Survey 98

 Survey Section Subsection Respondents, Content, and Reason for Inclusion

H: Sources and Uses 

of Funds—Louisiana

(continued)

H2. Respondents: Respondents who owned a storm-damaged 

property in Louisiana and indicated that they did not receive 

assistance through the CDBG-funded Road Home Homeowner 

Program or Road Home Small Rental Program.

Content:

•	Whether respondent applied for funds.

•	Reasons for denial of application or failure to followthrough on application.

Reason: To provide information on obstacles to accessing CDBG 

program funds and reasons for not applying.

H3. Respondents: Respondents who owned a storm-damaged 

property in Louisiana and indicated that they received assistance 

through the CDBG-funded Road Home Homeowner Program or 

Road Home Small Rental Program.

Content:

•	Program option selected and reasons.

•	Use of funds for housing repairs.

•	Use of funds for other purposes.

Reason: To provide information on how Louisiana CDBG 

recipients used their grants—and how much was spent on 

housing needs—given that the program did not place restrictions 

on how people used the money.

H4. Respondents: Respondents who owned a storm-damaged 

property in Louisiana and indicated that they applied for or 

received assistance through the CDBG-funded Road Home 

Homeowner Program or Road Home Small Rental Program.

Content:

•	Problems with applying for CDBG funds and other sources 

of financial assistance.

•	Program problems that delayed rebuilding.

Reason: To provide information on problems with CDBG program 

delivery in Louisiana.
Appendix B: Overview of the Property Owner Survey 99

 Survey Section Subsection Respondents, Content, and Reason for Inclusion

I: Sources and Uses 

of Funds—Mississippi

I1. Respondents: Respondents who owned a storm-damaged 

property in Mississippi.

Content:

•	Sources of funding received for rebuilding or as 

compensation for damage caused by hurricanes Katrina or 

Rita.

•	Amounts of funding received.

•	Gap between funding received and rebuilding/repair 

needs.

•	Owner resources spent on rebuilding/repair.

Reason: To provide information on the amounts and types of 

funding received, including CDBG funds, and whether those 

funds were sufficient to cover the cost of repairs.

I2. Respondents: Respondents who owned a storm-damaged 

property in Mississippi and indicated that they did not receive 

assistance through the CDBG-funded MDA Homeowner Program 

or MS Small Rental Program.

Content:

•	Whether respondent applied for funds.

•	Reasons for denial of application or failure to followthrough on application.

Reason: To provide information on obstacles to accessing CDBG 

program funds and reasons for not applying.

I3. Respondents: Respondents who owned a storm-damaged 

property in Mississippi and indicated that they received 

assistance through the CDBG-funded MDA Homeowner Program 

or MS Small Rental Program.

Content:

•	Program option selected and reasons.

•	Use of funds for housing repairs.

•	Use of funds for other purposes.

Reason: To provide information on how Mississippi CDBG 

recipients used their grants—and how much was spent on 

housing needs—given that the program did not place restrictions 

on how people used the money.
Appendix B: Overview of the Property Owner Survey 100

 Survey Section Subsection Respondents, Content, and Reason for Inclusion

I: Sources and Uses 

of Funds—Mississippi

(continued)

I4. Respondents: Respondents who owned a storm-damaged 

property in Mississippi and indicated that they applied for or 

received assistance through the CDBG-funded MDA Homeowner 

Program or MS Small Rental Program.

Content:

•	Problems with applying for CDBG funds and other sources 

of financial assistance.

•	Program problems that delayed rebuilding.

Reason: To provide information on problems with CDBG program 

delivery in Mississippi.

J: Sources and Uses 

of Funds—Texas

J1. Respondents: Respondents who owned a storm-damaged 

property in Texas.

Content:

•	Sources of funding received for rebuilding or as 

compensation for damage caused by Hurricane Rita.

•	Amounts of funding received.

•	Gap between funding received and rebuilding/repair 

needs.

•	Owner resources spent on rebuilding/repair.

Reason: To provide information on the amounts and types of 

funding received, including CDBG rebuilding/repair assistance, 

and whether those funds/assistance were sufficient to cover the 

cost of repairs.

J2. Respondents: Respondents who owned a storm-damaged

property in Texas and indicated that they did not receive 

assistance through the CDBG-funded TX Homeowner Assistance 

Program.

Content:

•	Whether respondent applied for CDBG-funded assistance.

•	Reasons for denial of application or failure to follow 

through on application.

Reason: To provide information on obstacles to accessing CDBG 

program assistance and reasons for not applying.
Appendix B: Overview of the Property Owner Survey 101

 Survey Section Subsection Respondents, Content, and Reason for Inclusion

J: Sources and Uses 

of Funds—Texas

(continued)

J3. Respondents: Respondents who owned a storm-damaged 

property in Texas and indicated that they received assistance 

through the CDBG-funded TX Homeowner Assistance Program.

Content:

•	Overall satisfaction with home repairs/rebuilding 

conducted by state.

•	Satisfaction with design, size, and building materials.

•	Satisfaction with workmanship.

Reason: To provide information on the level of satisfaction among 

Texas CDBG recipients with the work conducted on their behalf.

J4. Respondents: Respondents who owned a storm-damaged 

property in Texas and indicated that they applied for or received 

assistance through the CDBG-funded TX Homeowner Assistance 

Program.

Content:

•	Problems with applying for CDBG funds and other sources 

of financial assistance.

•	Program problems that delayed rebuilding.

Reason: To provide information on problems with CDBG program 

delivery in Texas. 

K: Owner 

Demographics

N/A Respondents: All individual respondents. (Excludes 

representatives of corporate owners of rental properties.)

Content:

•	Age, marital status, employment status, disability, income, 

financial hardship, household composition, race, ethnicity.

Reason: To provide information on the demographic 

characteristics of respondents that may affect their propensity to 

rebuild.

L: Closing N/A Respondents: All respondents.

Content:

•	Confirmation of current mailing address and spelling 

of name.

Reason: To ensure that the respondent can receive the $25 in 

compensation for completing the interview.
Appendix C: Property Owner Survey Non-Response Bias Analysis and Adjustment 102

APPENDIX C. PROPERTY 

OWNER SURVEY 

NON-RESPONSE BIAS 

ANALYSIS AND ADJUSTMENT

This appendix describes our approach to creating 

sampling weights for the property owner survey. 

We begin with a brief discussion of the reasons for 

weighting, followed by discussions of computing base 

weights, assessing non-response bias, and computing 

non-response weights.

WHY WEIGHT?

The need for sampling weights arises because 

observations are not a simple random sample from the 

population of interest; the sample was selected with 

known but unequal probabilities of selection. In this 

study, factors such as geography and extent of storm 

damage were used to stratify the sample of properties. 

Compensating for factors like this is relatively 

straightforward, and involves the construction of base 

weights.

Second, the desired information may not be obtained 

from all sampled units (non-response). In general, 

non-response reduces the precision of estimates using 

the survey data. But there is a more important problem 

if systematic differences between the respondents 

and non-respondents are present: estimates based 

only on the respondents may be biased. The size of 

the bias in an estimate depends on the non-response 

rate and the difference between the respondents and 

non-respondents in the characteristic of interest. A 

substantial literature shows that the non-response 

rate alone is a weak predictor of non-response bias 

(Groves, 2006). Nonetheless, when a low response 

rate is observed, it is incumbent on the researcher 

to determine whether non-response bias is present 

and, when possible, to make corrections. There are 

several methods of assessing the potential degree of 

non-response bias, and correcting for it involves the 

construction of non-response adjustment factors to 

adjust the base weights—i.e., non-response weights. In 

the following sections we discuss base weights, assessing 

non-response bias, and non-response adjusted weights.

COMPUTING BASE 

WEIGHTS

As with the windshield observations, the sampling 

design for the property owner survey allows 

representative estimates to be calculated for states, 

counties, parishes, and jurisdictions through the 

creation of base weights at the block and property level. 

In general, the base weight of a sampled unit is the 

reciprocal of its probability of selection into the sample.

We used a two-stage sampling design to select the 

owner survey sample. In the first stage, we selected a 

random sample of significantly affected blocks (SABs) 

from Louisiana, Mississippi, and Texas. The second 

stage differed by state. In Louisiana and Mississippi, 

properties with major and severe damage were selected 

within the SABs such that there was a .5/.5 allocation 

between substantially rebuilt properties and properties 

with partial or no rebuilding within each geographic 

stratum. In Texas, very few properties in the windshield 

observation blocks received a CDBG grant, so an 

oversample was necessary to select 45 CDBG recipients, 

45 non-CDBG recipients, and 30 rental properties in 

total. All properties selected in the Texas sample were 

assessed by FEMA as having major or severe damage, 

with the exception of 20 CDBG recipients. The 

original oversample of properties in Texas included only 

25 CDBG recipients with major/severe damage. The 

set of 45 sampled CDBG recipients includes 20 CDBG 

recipients whose properties were classified by FEMA 
Appendix C: Property Owner Survey Non-Response Bias Analysis and Adjustment 103

as minor/no damage. These properties were included 

in the sample to get to the desired total of 45 CDBG 

recipients, and because representatives of the CDBG 

program in Texas told us that the FEMA designations 

were not accurate in Texas, and that properties that 

received CDBG assistance would have had major or 

severe damage confirmed via state assessment. We 

tested this assumption as part of the data analysis.

Because the property-level selection mechanism differs 

by state, a different weighting scheme was used for 

Louisiana and Mississippi than for Texas.

In all states, the block-level base weights can be defined 

as the inverse of the sampling probability:

Where h indexes the (geographical) stratum, nh is the 

number of (significantly affected) blocks drawn in 

stratum h, and N is the total number of (significantly 

affected) blocks in stratum h.

In Texas, property-level weights can be calculated as 

follows:

Where again h indexes geographical stratum,66 p

indexes the property, and wh is the block-level weight 

corresponding to that property. Rhp is an indicator 

variable with three states: Rhp = 0 indicates a CDBGrecipient property classified by FEMA as having major 

or severe damage. Because all such properties were 

sampled, the property-level weight is equal to the 

block-level weight. Rhp = 1 indicates a CDBG-recipient 

66 Note that, unlike Louisiana and Mississippi, Texas is considered a single geographical stratum.

property classified by FEMA as having less than major 

damage. For these properties, the weight is calculated 

as the ratio of n1h (the number of CDBG-recipient 

properties with less than major damage that were 

sampled—because 45 total CDBG properties were 

sampled, n1h will be a number less than 45) and N1h

(the total number of CDBG-recipient properties with 

less than major damage). Rhp = 2 indicates a rentaloccupied property with major or severe damage that 

is not a CDBG recipient. For these properties, the 

weight is calculated as a function of the ratio of n2h

(the number of non-CDBG renter-occupied properties 

with major or severe damage that were sampled—equal 

to 30 by design) and N2h (the total number of nonCDBG renter-occupied properties with major or severe 

damage). Rhp = 3 indicates an owner-occupied property 

with major or severe damage that is not a CDBG 

recipient. For these properties, the weight is calculated 

as a function of the ratio of n3h (the number of nonCDBG owner-occupied properties with major or severe 

damage that were sampled—equal to 45 by design) and 

N3h (the total number of non-CDBG owner-occupied 

properties with major or severe damage).

In Louisiana and Mississippi, property-level weights 

can be calculated as follows:

Where h indexes (geographical) stratum, p indexes the 

property, and wh is the block-level weight corresponding 

to that property. Dhp is an indicator variable for whether 

a property has been substantially rebuilt. N4h is the 

number of substantially rebuilt properties with major or 

severe damage sampled from stratum h, N4h is the total 

number of substantially rebuilt properties with major 

or severe damage in stratum h, n5h is the number of 

properties with major or severe damage and partial or no 

rebuilding sampled from stratum h, and N5h is the total 

number of properties with major or severe damage and 

partial or no rebuilding in stratum h.
Appendix C: Property Owner Survey Non-Response Bias Analysis and Adjustment 104

ASSESSING

NON-RESPONSE BIAS

The first step in addressing non-response bias is 

to assess whether bias is present, and—if it is—to 

determine which characteristics of sample units appear 

to be correlated with the probability of response. 

Although the response rate to the owner survey was 

low, this alone is not a good predictor of whether there 

is non-response bias. Of course the only characteristics 

that can be used to assess non-response bias are those 

characteristics on which we have information for all 

sample members. Sources of explanatory variables 

available for sample units in the property owner 

survey include administrative data and the windshield 

observations. While certain administrative data 

are available for all 1,400 properties in the sample, 

windshield observation data are limited to a subsample 

of 1,285 properties. The non-response analysis includes 

both types of data.

Following is a list of characteristics available for all 

1,400 properties:

1. Geographical stratum—17 values in total

2. Level of assessed hurricane damage in 2005—

major or severe (FEMA assessment admin data)

3. Type of insurance—flood, hazard, both, or none 

(FEMA admin data)

4. Tenure of the property at time of hurricane—

owner-occupied or renter-occupied (FEMA 

admin data)

5. Located in a flood plain—yes or no (FEMA 

admin data)

6. CDBG receipt (state level admin data)

7. Flood and/or wind damage (FEMA admin data)

8. Occupancy (USPS data)

9. Block-level demographic data (Census 2000)

10. For the subsample of 1,285 properties included 

in the windshield observations, additional 

variables are present:

11. Habitability of the property (windshield 

observations)

12. Condition of the property (windshield 

observations)

13. Observed and inferred rebuilding as of 2010 

(windshield observations)

14. Occupancy (windshield observations)

For CDBG recipients in Louisiana and Mississippi, 

there is also information on:

15. Damage amount in dollars (state CDBG data)

16. CDBG award amount

Because certain data are available only for the 

windshield observation sample, we conducted nonresponse analyses for both the full sample of properties 

and for the windshield subsample. Based on a review of 

the non-response bias literature, we took the following 

approach:

1. First, we compared response rates across 

geographical strata (exhibit C-1). Response 

rates varied substantially by geography, from a 

low of 30 percent in Calcasieu and Cameron 

Parishes in Louisiana to a high of 70 percent in 

Texas. Statistical tests reveal that the distribution 

of response rates differs from what we would 

expect if the variation were simply random. 

This geographical variation in response rates is 

likely due to a combination of factors, including 

underlying demographic characteristics that vary 

by geography and also affect response rates (e.g., 

poverty).
Appendix C: Property Owner Survey Non-Response Bias Analysis and Adjustment 105

Exhibit C-1. Comparison of Response Rates by Geographical County/Parish

Geographical Area

Respondents Non-Respondents Response Rate

N N %

Among All Properties Sampled for the Owner Survey (N = 1,400)

Louisiana 467 523 47

Calcasieu and Cameron 

Parishes 7 16 30

Jefferson Parish 60 58 51

Orleans Parish 301 305 50

St. Bernard Parish 68 94 42

St. Tammany Parish 11 24 31

Other LA Parishes 20 26 43

Mississippi 171 119 59

Hancock County 31 26 54

Harrison County 45 46 49

Jackson County 91 44 67

Other Mississippi 

Counties 4 3 57

Texas 84 36 70

Total (all states) 722 678 52

2. Second, we used administrative data on the full 

sample and windshield data on the subsample 

to compare key characteristics of respondents 

and non-respondents (Exhibit C-2). The 

property owner survey was designed to permit 

three types of comparisons: (1) CDBG recipients 

vs. non-recipients; (2) owners vs. renters; and 

(3) substantially rebuilt properties vs. partially 

rebuilt or not rebuilt properties. For that reason, 

it was especially important to see whether these 

characteristics appeared to be correlated with 

the probability of survey response. We also 

compared respondents and non-respondents in 

terms of the set of administrative and windshield 

observation characteristics listed in exhibit 

C-2. Nine of these characteristics proved to be 

unconditionally correlated with non-response 

(that is, without taking into account any of 

the other characteristics), including all four 

administrative characteristics available for the 

full sample (CDBG receipt, owner occupancy, 

type of damage, and whether the property was 

substantially rebuilt). USPS occupancy status 

was significantly correlated with non-response; 

however, USPS data were not available for all 

properties in the windshield sample and therefore 

we could not include an occupancy variable in 

the logistic regression model of non-response.
Appendix C: Property Owner Survey Non-Response Bias Analysis and Adjustment 106

Exhibit C-2. Comparison of Property Characteristics Between Respondents and Non-Respondents

Characteristic

Respondents Non-Respondents Difference

Significant?

% of Respondents 

Having This 

Characteristic

% of Non-Respondents Having This 

Characteristic

P-Value

Among All Properties Sampled for the Owner Survey (N = 1,400)

Received CDBG assistance 50 39 Yes ( < 0.01)

Owner-occupied (vs. renteroccupied) at time of hurricane 75 63 Yes ( < 0.01)

Suffered flood damage 77 84 Yes ( < 0.01)

Substantially rebuilt 63 47 Yes ( < 0.01)

Among Properties Selected for Windshield Observation (N = 1,285)

Exhibits substantial repair needs 23 30 Yes ( < 0.01)

Overall Condition:

Excellent/good condition 57 43 Yes (< 0.01)

Fair condition 15 17

Poor condition 7 12

Totally destroyed 1 1

Structure is being built or 

undergoing complete renovation 1 1

Lot does not contain a 

permanent residential structure 19 26

Habitable 72 58 Yes (< 0.01)

Occupied (Windshield) 66 49 Yes (< 0.01)

Occupied (USPS) 74 56 Yes (< 0.01)

CDBG award amount (in dollars) 77,758 (mean) 77,226 (mean)

Damage amount (in dollars) 206,713 185,450
Appendix C: Property Owner Survey Non-Response Bias Analysis and Adjustment 107

3. Third, using data from the administrative and 

windshield observations as well as Census blockgroup demographic data, we estimated a logistic 

regression model to determine which of these 

factors are significantly correlated with nonresponse. We conducted separate analyses for 

the full sample and the windshield observation 

subsample. The full-sample regression model 

was able to predict approximately 9.4 percent 

of the variation in response. The subsample 

regression model, which included the full set 

of windshield observation characteristics and 

Census block-group demographic characteristics, 

was able to explain approximately 11.3 percent 

of the variation. After controlling for geographic 

stratum and the four characteristics available for 

the full sample in the latter regression, none of 

the additional windshield-survey or demographic 

characteristics had significant explanatory power 

with the exception of windshield observationidentified occupancy. We conclude that, after 

controlling for geography, CDBG receipt, source 

of damage, owner-occupancy, rebuilding status, 

and windshield-survey identified occupancy 

status, there was not significant differential nonresponse due to demographic or other observable 

characteristics. In other words, no factors other 

than these six were found to be predictive of 

whether a property owner responded to the 

survey.

NON-RESPONSE WEIGHTS

Because there was not significant differential nonresponse due to demographic or other observable 

characteristics available for only windshield observation 

properties, we created only one set of non-response 

weights for the full sample of 1,400 properties that 

will be sufficient for all analyses. We created weights by 

estimating a logistic regression model of non-response 

and used the predicted probabilities from that model to 

generate inverse probability weights. The procedure for 

doing so is fairly straightforward. We estimated a logistic 

regression with dummy variables for each geographic 

stratum, and covariates for the other variables of interest 

(CDBG receipt, rebuilt status, source of damage, and 

owner-occupancy). Then, we used the fitted model to 

predict the probability of response for each property 

(based on the estimated coefficients and actual values of 

all variables) and used those predicted probabilities to 

create an inverse probability weight for each property.

FINAL SURVEY WEIGHTS

Final Survey Weights are simply a combination of 

the base weights and the non-response weights. That 

is, Survey Weight = (Base Weight * Non-Response 

Weight).
Appendix D: Rates of Application to the CDBG Program 108

APPENDIX D. RATES OF 

APPLICATION TO THE 

CDBG PROGRAM

The owner survey provided an opportunity to explore 

owners’ experiences with applying for the CDBG 

program and receiving assistance. One of the questions 

of interest is the number of owners who applied to 

the programs in each state as compared to the number 

who received assistance. Exhibit 5-17 shows rates of 

CDBG receipt and application among homeowners. 

As shown above in exhibit 5-1, homeowners in 

Louisiana and Mississippi (roughly 55 percent in both 

states) were much more likely to receive a CDBG 

homeowner award than those in Texas (only 6.5 percent 

received an award). With a smaller amount of CDBG 

funding—$503 million compared to $13.4 billion in 

Louisiana and $5.5 billion in Mississippi—the CDBG 

homeowner programs in Texas were more narrowly 

targeted, by income and geography, than the programs 

in the other two states.67 Perhaps as a result, the 

majority (75.0 percent) of survey respondents in Texas 

did not apply for the CDBG program; in comparison, 

23.7 percent of respondents in Louisiana and 34.2 

percent of respondents in Mississippi did not apply.

Although Louisiana homeowners were most likely to 

apply for CDBG homeowner funds, among applicants, 

Mississippi owners were most likely to obtain an 

award. Among owners that applied for the program in 

Mississippi, 88 percent received an award, compared to 

73 percent in Louisiana and 40 percent in Texas.

There were a number of reasons that some owners in 

the survey sample did not apply for a CDBG award. 

As shown in exhibit 5-18, a common reason for not 

applying for funding across all states was that the owner 

had other funding to pay for rebuilding. In Louisiana, 

49.8 percent of respondents gave this response, similar 

to the 47.2 percent of respondents in Mississippi and 

56.6 percent in Texas, where this was the most common 

reason cited. Perhaps this is because owners in Texas 

67 See appendix A for program descriptions.

had lower repair and rebuilding costs than owners in 

Mississippi and Louisiana.

Aside from the availability of other funding to pay for 

repairs or rebuilding, the reasons given for not applying 

for a CDBG grant varied by state. The most common 

reason given in Louisiana was that the respondent 

did not think he/she would meet the eligibility 

requirements for the program (57.0 percent of 

respondents gave this reason). Fewer survey respondents 

said this in Mississippi (40.1 percent) or in Texas (33.8 

percent). In Mississippi, the most common reason for 

not applying was that the respondent was not aware 

of the program (55.8 percent).68 Respondents in 

Louisiana (26.7 percent) were significantly less likely to 

give this response.

In Louisiana, the least common reason given for not 

applying was that the owner was not planning to 

rebuild (10.4 percent of respondents gave this reason). 

In comparison, owners in Mississippi and Texas were 

more likely to say they were not planning to rebuild 

(13.4 percent in Mississippi, and 21.3 percent in 

Texas). In both Mississippi and Texas, owners were 

least likely to cite that they “heard everyone was 

being turned down” as a reason for not applying. 

More respondents cited this reason in Louisiana (20.4 

percent).

Lack of availability of the program when rebuilding 

began was more commonly cited as a reason for not 

applying for a CDBG award for owners in Louisiana 

(23.1 percent) than in Texas, where only 5.3 percent of 

owners gave this reason.

68 One problem with this measure for Mississippi in particular is that many 

survey respondents said that they did not receive a CDBG award although the 

administrative data obtained from the state suggests that they did. As described 

in chapter 5, in Mississippi the terminology used in the survey for the CDBG 

program may not have been familiar to some respondents. If this is the case, some 

people in Mississippi may have reported not being aware of the program when 

they might have known of it using another name.
Appendix D: Rates of Application to the CDBG Program 109

Exhibit D-1. Rates of Application to Homeowner Assistance Programs

Louisiana Mississippi Texas

Percent CI Percent CI Percent CI

Applied for CDBG program 

and received an award 55.0 49.2–60.8 56.6 47.3–66.0 7.2 4.2–10.2

Applied for CDBG program 

but no award 20.6 14.8–26.4 7.8 2.5–13.2 10.7 1.4–20.0

Did not apply for CDBG 

program

23.7 18.5–28.8 34.2 23.9–44.4 75.0 63.4–86.5

Don’t Know 0.7 0.0–1.4 1.4 0.0–3.1 7.1 0.0–15.5

Total 100 100 100

Note: Weighted estimates for 155,976 recipients based on 564 survey responses.

Source: 2011 Property Owner Survey

Exhibit D-2. Reasons for Not Applying for a CDBG Award

Louisiana

N = 45,321 Based on 

130 Survey Responses

Mississippi

N = 25,305 Based on 

95 Survey Responses

Texas

N = 38 Based on 6,123 

Survey Responses

Percent CI Percent CI Percent CI

Not aware of the program 26.7 18.9–34.5 55.8 47.1–64.5 43.1 29.8–56.5

Program not available when 

rebuilding began 23.1 16.1–30.1 19.5 11.7–27.2 5.3 0.0–11.8

Did not think eligibility 

requirements were met 57.0 49.3–64.7 40.1 27.2–53.0 33.8 19.4–48.2

Heard everyone was being 

turned down 20.4 14.1–26.7 10.9 6.5–15.4 3.3 0.0–7.3

Did not have the necessary 

paperwork 19.6 12.6–26.7 18.5 10.7–26.2 18.2 6.5–29.9

Property ownership issues too 

complicated 24.0 1.5–32.5 11.9 5.4–18.3 12.9 2.7–23.1

Application process too 

complicated for me to handle 33.9 25.1–42.8 15.2 9.7–20.7 19.9 8.0–31.8

Had other funding to pay for 

rebuilding 49.8 42.1–57.5 47.2 36.1–58.3 56.6 40.6–72.6

Not planning to rebuild 10.4 6.4–14.4 13.4 5.7–21.2 21.3 8.5–34.1

Not worth the hassle 38.5 31.0–45.9 26.5 17.8–35.2 25.2 12.1–38.3

Other reasons for not 

rebuilding 13.9 8.3–19.5 5.8 2.0–9.6 7.3 0.0–16.0

Note: Shaded percentages indicate a more common reason.

Source: 2011 Property Owner Survey
U.S. Department of Housing and Urban Development

Office of Policy Development and Research

Washington, DC 20410-6000

November 2011