Study of Subdivision Requirements as a 

Regulatory Barrier 

Prepared for:

U.S. Department of Housing and Urban Development 

Office of Policy Development and Research 

Washington, DC 

Prepared by:

NAHB Research Center 

Upper Marlboro, MD

April 2007 
Acknowledgement 

The NAHB Research Center would like to recognize the contributions of ECONorthwest of 

Eugene Oregon in cooperation with the Community Planning Workshop at the University of 

Oregon who prepared Section 3 (Existing Regulations), Section 5 (Regulatory Cost Barriers), 

and Appendix A – Survey of Regulations for this report. The literature review and comments 

on the draft final report were provided by Professor Gerrit Knapp of the University of 

Maryland. 

The research team also appreciates the assistance provided by the National Association of 

Counties (NACo) Center for Sustainable Communities in securing participation by 

municipal/county land planners in its expert survey for land development benchmarks. Mr. 

Martin Harris of NACo obtained cooperation from several county land planning commissions 

that greatly facilitated the focus group evaluation of regulatory barriers. The following 

individuals participated in the expert panel for land development benchmarks: Bill Kreager, 

architect, Mithun Partners, Inc.; Edward Tombari, planner, NAHB; Douglas Nataluk, developer, 

Neumann Homes; Gerald Eid, developer, Eid Companies; Charles L. Baker, general manager, 

Department of Land Use New Castle County Delaware; Eric Young, land planner, Washoe 

County, Nevada; Bill Florea, land planner, Boone County, Missouri; David Petersen, land 

planner, Spring Hills, Kansas; Martin Rivarola, community development director, City of 

Mission, Kansas; James E. Harpool, principal/president, Dial Realty; Phil L. Stuepfert, director of 

planning, Illinois SEC Planning Consultants; Richard Dooley, environmental land planner, 

Arlington County, Virginia. 

Special thanks also to Ms. Debra Bassert, vice president for land development policy at NAHB, 

for thoughtful review and comments on the benchmarks and unit cost methods. Finally, the 

Research Center would like to acknowledge the support, project guidance and helpful 

comments on the Executive Summary provided by Mr. Edwin Stromberg of HUD’s Office of 

Policy Development and Research. 

Disclaimer 

Neither the NAHB Research Center, Inc., nor any person acting on its behalf, makes any 

warranty, express or implied, with respect to the use of any information, apparatus, method, or 

process disclosed in this publication or that such use may not infringe privately owned rights, or 

assumes any liabilities with respect to the use of, or for damages resulting from the use of, any 

information, apparatus, method or process disclosed in this publication, or is responsible for 

statements made or opinions expressed by individual authors. 
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Introduction 

Local subdivision regulations represent a major tool by which local governments manage and 

shape the housing development process. In addition to laying land plats or site plans, these 

regulations establish infrastructure or site requirements to support new residential 

development, i.e., they establish specifications for streets, sidewalks, water and sewer, drainage, 

curbs and gutters, street signs, landscaping. In many cases, subdivision regulations also provide 

for trees, utility easements, and dedications of land or fees for recreational and/or school 

facilities. Subdivision regulations are intended to ensure that proposed housing developments 

are cost-effective (i.e., reduce extensive long-term maintenance by the locality), meet health and 

safety requirements, are properly designed, and have a favorable impact on the community. 

The cost of these requirements represents a significant share of the cost of producing new 

housing. Such requirements can reasonably be considered “regulatory barriers” to affordable 

housing if the locally determined requirements are greater (and hence, more costly) than those 

necessary to achieve health and safety requirements in the community. This has been a 

concern for many years, and has been identified in the report, Not in My Backyard (prepared by 

the President’s Commission on Regulatory Barriers to Affordable Housing) as a potential major 

contributor in raising the cost of housing and limiting the supply of affordable housing in 

communities. 

To determine whether subdivision requirements exceed what is necessary to meet health and 

safety requirements, and hence likely to become a regulatory barrier, the Department of 

Housing and Urban Development commissioned a nationwide study. The key objective of the 

study was to develop a national estimate of the cost of excessive land and site development 

standards on single-family detached housing built in subdivisions. This is the type of housing 

most closely associated with the idea of homeownership in America. In order to measure 

which local standards are in fact excessive, the study commissioned nationally recognized land 

development experts to devise benchmark subdivision standards. Benchmark standards are 

standards necessary to achieve minimum acceptable health and safety benefit for the 

community. Such standards, and their corresponding monetary values, were devised for the 

most important development standards: lot size, floor space requirements, lot width, roadway 

width, sidewalk requirements, and curb & gutter drainage. The expert group in land and 

housing development consisted of residential land developers, architects, civil engineers, and 

land planners and was asked to develop benchmark standards for this study. Based on the 
responses from this group, consensus benchmark standards were developed and used in this 

study as the basis for determining whether existing local standards were excessive. 

METHODOLOGY: The study used a four-step methodology for developing the national cost 

estimates for those subdivision rules that constitute regulatory barriers: (1) collect regulatory 

standards from a nationally representative sample of jurisdictions for the selected subdivision 

and related zoning rules; (2) establish benchmark values and unit costs for each requirement; 

(3) produce a cost estimate for excessive regulation based on the application of the benchmark 

values and costs to the regulatory standards from the national sample of jurisdictions; and (4) 

create a national estimate of the costs of excessive regulations. For practical reasons, this study 

focused on only one type of zoning district- those that allowed the densest single-family 

residential development. If the study had examined all zoning districts in all jurisdictions, which 

would have included lower density districts, greater levels of regulatory cost barriers most 

likely would have been found. 

SUMMARY OF FINDINGS 

The overwhelming majority of communities in the study—94%-- mandate one or more land 

development standards for residential subdivisions. The most common regulatory standards 

were for lot size, front setbacks, off-street parking, and lot width. The least common 

requirements were for floor area and open space. 

Ninety-one percent (91%) of all the communities had one or more regulatory standards that 

exceeded the benchmarks. Jurisdictions exceeded the benchmarks most frequently for offstreet parking, front setbacks, lot width, and lot size. Jurisdictions exceeded the benchmarks 

least frequently for floor area, sidewalk requirements, open space, and sidewalk width 

requirements. 

Lot size, lot width, and floor area accounted for the largest percentage of total costs for a 

variety of reasons: 

Excessive lot size regulations accounted for the largest percentage of cost (65%). The cost of 

land is a major component of the cost of housing, so it should not be surprising that regulations 

mandating excessive lot sizes results in such a finding. Coincidentally, sixty-five percent of 

jurisdictions in the sample exceeded the lot size benchmark. On average, jurisdictions with 

excessive lot size requirements exceeded the benchmarks by 6,573 square feet (or more than 

one-seventh of an acre). The frequency and magnitude of lot size requirements greater than 

the benchmarks, combined with the cost of land, resulted in the regulatory cost barrier for lot 

size accounting for the majority of total costs of the regulatory cost barriers for all the land and 

site development variables considered in this study. 

NAHB Research Center ii April 2007 
Excessive lot width requirements account for a moderate share of costs (9%), with 63 percent 

of jurisdictions containing lot width regulations exceeding the benchmarks. Excessive lot widths 

also have clear secondary cost impacts, i.e., they increase costing for land, sanitary sewer main, 

water main, street paving, curb and gutter, sidewalk construction, landscaping, and storm 

sewer. 

Floor area had a disproportionately large impact on total regulatory barrier costs in proportion 

to the number of jurisdictions with excessive floor area requirements. While only 8 percent of 

jurisdictions had excessive floor area requirements, the regulatory cost barriers for floor area 

for those jurisdictions accounted for 17 percent of the total regulatory cost barriers for all land 

development variables for all the jurisdictions in the study. This resulted from the relatively high 

cost per square foot of required floor area and the fact that the mean differential between 

required floor area and benchmark floor areas was 354 square feet (or more than $26,000 per 

dwelling unit). 

Key Findings 

The average cost of excessive regulation resulting from subdivision standards for one dwelling 

unit was about 5 percent of the average cost of a new home. For the land development 

standards studied, the average regulatory barrier cost for one dwelling unit was $11,910. In 

comparison with the average cost for a new single-family dwelling in the United States in 2004 

($244,000), the average per-unit regulatory cost barrier is 4.8 percent of that average selling 

price. 

The regulatory barriers cost varied. The regulatory barriers cost varied considerably across 

communities, as well as across regions and Metropolitan Statistical Area (MSA) status. Given 

that the sample is representative of all jurisdictions in the nation, the national regulatory cost 

barriers will vary by region and whether the jurisdiction is part of an MSA. The actual 

regulatory barrier cost for any given jurisdiction of course, depends on actual local regulations 

and costs of development. 

Of the two types of “models” used to make the national estimates—aggregated and 

disaggregated--the disaggregated model provides the best national estimate of the land 

development regulatory barrier costs. The disaggregated model accounts for variations in 

regulatory standards and costs among the Census regions and MSA status better than the 

aggregated model. The total mean regulatory cost barriers for land and site development 

standards in the disaggregated model was about $14.6 billion for the nation in 2004. 

Conclusion 

This study is the first effort to quantify, on a nationwide basis, the costs of excessive site 

development regulation on affordable housing. The common rationale for such requirements is 

NAHB Research Center iii April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

that they enhance the soundness, livability, and sustainability of a community. The purpose of 

this study, however, has not been to deny that such standards have important benefits for the 

community, but to broaden the perspective of what other values and goals can and should be 

embodied in the housing development regulatory process, and to call attention to the impacts 

that excessive requirements have upon affordable housing. The additional cost pressures such 

standards impose on new housing may also help increase the prices of existing housing. 

The findings themselves are not surprising; but they confirm and quantify, through an empirical 

study, what has been well-known, but unverified, throughout the workforce housing 

community—that large lot zoning and various site development requirements—limit or prevent 

the development of affordable housing. Such requirements, then, can harm a community’s 

ability to provide what is, or ought to be, a high priority community goal. 

The $14.6 billion national estimate for the land development regulatory barriers costs is a very 

conservative estimate. For practical reasons, this study focused on only on one type of zoning 

district, i.e., one that allowed the densest single-family residential development. If the study had 

examined all zoning districts in all jurisdictions, which most likely would have included lower 

density districts, far greater levels of regulatory barriers cost would have been found. For 

example, in medium-density residential zoned districts typically found next to the dense zoning 

districts, required minimum lot areas are generally larger. One would expect to find greater 

regulatory barrier costs in such neighborhoods vis a vis. high-density areas. Hence, the 

regulatory barriers cost resulting from required lot sizes greater than the benchmark lot areas 

would have been larger if these medium-density residential zoned districts had been included in 

the regulatory barrier cost analysis. Also, the estimate of housing construction costs on a 

square foot basis associated with excessive floor area standards was relatively conservative. 

Further, in lower density areas experiencing high housing construction, regulatory cost barriers 

based on average land costs and total housing construction starts for the Census region may 

underestimate the actual regulatory cost barrier from lot size requirements within that region. 

The results presented here can serve as an opportunity and an invitation for communities as 

part of their commitment to affordable housing, to review and assess their own land and site 

development requirements. In order for local and state policies to have the greatest impact on 

the reduction of regulatory cost barriers associated with land and site development standards, 

efforts should focus on the most significant land and site development regulatory barriers 

identified in this study: excessive zoning regulations and excessive house size requirements. 

Local advocates for reduction in regulatory cost barriers may wish to use the regulatory barrier 

costing tool, described in section 4.2.1.1 (and presented in Appendix G) to determine the 

regulatory barriers costs that apply in specific locations. This computer-based tool incorporates 

the benchmark standards used in this study as the baseline for judging a community’s regulatory 

NAHB Research Center iv April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

standards. A community’s calculation would be based on local land costs and on the cost of 

land development standards adopted by the local land planning jurisdiction or jurisdictions. 

Communities committing to this self-assessment exercise, will not only be contributing to our 

understanding of a significant dimension of regulatory barriers costs, but will also be advancing 

their own efforts to expand affordable housing opportunities. 

NAHB Research Center v April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

Table of Contents 

1. Introduction ............................................................................................................................................1-1

2. Background..............................................................................................................................................2-1

2.1 Subdivision Regulations and Zoning Ordinances..................................................................2-2

2.1.1 Literature Review...........................................................................................................2-3

2.1.2. Regulatory Cost Barriers.............................................................................................2-3

2.1.3 Quantifying Cost Barriers for Specific Land-Use Regulations..............................2-5

3. Existing Regulations...............................................................................................................................3-1

3.1 Sampling of Jurisdictions.............................................................................................................3-2

3.2 Selection of Land Development Standards............................................................................3-4

3.3 Definitions.....................................................................................................................................3-5

3.4 Analytical Framework.................................................................................................................3-5

4. Standards, Benchmarks, and Unit Costs...........................................................................................4-1

4.1 Benchmarks...................................................................................................................................4-1

4.1.1 Lot size .............................................................................................................................4-4

4.1.2 Lot Width ........................................................................................................................4-7

4.1.3 Setbacks............................................................................................................................4-8

4.1.4 Floor Area Minimums...................................................................................................4-9

4.1.5 Road Widths .................................................................................................................4-10

4.1.6 Sidewalks........................................................................................................................4-11

4.1.7 Open Space ...................................................................................................................4-11

4.2 Unit Costs and Regulatory Cost Barriers............................................................................4-11

4.2.1 Lot Size...........................................................................................................................4-12

4.2.2 Minimum Square Footage Dwelling Requirements ..............................................4-15

4.2.3 Lot Width ......................................................................................................................4-15

4.2.4 Road Width...................................................................................................................4-16

4.2.5 Front yard set-back requirements............................................................................4-17

4.2.6 Sidewalk Requirements...............................................................................................4-17

4.2.7 Open Space Requirements ........................................................................................4-18

5. Regulatory Cost Barriers.....................................................................................................................5-1

5.1 Cost Analysis of the Sample Jurisdictions..............................................................................5-1

5.1.1 Methods ...........................................................................................................................5-1

5.1.2 Results..............................................................................................................................5-4

5.2 National Estimates of the Regulatory Cost Barriers for Housing in Subdivisions........5-8

NAHB Research Center vi April 2007 
5.3 

Study of Subdivision Requirements as a Regulatory Barrier 

5.2.1 Methods ...........................................................................................................................5-8

5.2.2 Results ............................................................................................................................5-13

5.2.3 Sensitivity Analysis .......................................................................................................5-15

Key Findings and Conclusions.................................................................................................5-16

6. Conclusions.............................................................................................................................................6-1

7. References...............................................................................................................................................7-1

8. Endnotes ..................................................................................................................................................8-1

Appendix A: Survey of Regulatory Standards............................................................A-1

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List of Tables 

Table 2.1: Average Per-Unit-of-Measure Costs of Selected Land Improvements in

Waukesha County, Wisconsin ..................................................................................................................2-7

Table 2.2: Lot Improvement Costs for Various Lot Widths in Waukesha 

County, Wisconsin.......................................................................................................................................2-7

Table 3.2: Summary of Means Testing for Variance within Five Subcomponents 

of the Sample ...............................................................................................................................................3-10

Table 4.1: Expert Responses for Land Development Benchmarks for "More Dense" 

Development, Statistical Summary of Responses Used for Comparison in MSAs (N=12).........4-2

Table 4.2: Expert Responses for Land Development Benchmarks for "Less Dense" 

Development, Statistical Summary of Responses Used for Comparison in MSAs (N=8) ...........4-3

Table 4.3: Estimated Raw Land Costs by U.S. Bureau of Census Region......................................4-13

Table 5.1: Summary of Jurisdictions with Regulatory Standards and Jurisdictions 

Exceeding the Benchmarks by Variable ...................................................................................................5-5

Table 5.2: Summary of Regulatory Cost Barriers for All Jurisdictions and Costs Per 

Dwelling Unit by Variable ...........................................................................................................................5-6

Table 5.3: Results of Sensitivity Testing on Total and Mean Regulatory Cost

Barriers in the Sample Jurisdictions..........................................................................................................5-8

Table 5.4: Number of Building Permits Issued for Single-Family Detached Dwellings in the 

United States and Each Census Region and MSA Status, 2004........................................................5-12

Table 5.5: Aggregated Model Estimates of the Regulatory Cost Barriers for All 

Building Permits Issued for Detached Single-Family Dwelling Units in the Nation, 2004..........5-13

Table 5.6: Disaggregated Model Estimates of Regulatory Cost Barriers for All 

Building Permits Issued for Single-Family Dwelling Units in the Nation, 2004.............................5-14

Table 5.7: Results of Sensitivity Tests of the Aggregated and Disaggregated Models of the 

National Regulatory Cost Barrier Estimates, 2004.............................................................................5-15

List of Figures 

Figure 3.1: Sample Database Report Output Format Showing Data Collected for Each 

Jurisdiction......................................................................................................................................................3-2

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Study of Subdivision Requirements as a Regulatory Barrier 

Table 3.1: Summary of Descriptive Statistics of the Variables Reviewed ........................................3-7

Figure 4.1: Lot Area Comparison of Benchmarks to Reference Values ..........................................4-5

Figure 4.2: Benchmarks for Lot Width Compared with Reference Values.....................................4-7

Figure 4.3: Jurisdictions with Standards for Lot Width in Width Ranges as a 

Percentage of Total Jurisdictions with Standards (342).......................................................................4-8

Figure 4.4: Interior Floor Space Benchmarks and Reference Criteria..............................................4-9

Figure 5.1: Process for Determining the Costs of Excessive Land Use Regulation for 

Jurisdictions in the Sample..........................................................................................................................5-2

Figure 5.2: Process for Modeling the Nationwide Regulatory Cost Barriers ...............................5-10

NAHB Research Center ix April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

1. IInnttrroodduuccttiioonn

This study addresses the characterization on a national basis of the regulatory cost barriers 

associated with land subdivision, specifically barriers to the subdivision of land that can be 

developed with single-family detached (SFD) dwellings. Previously, this issue has been addressed 

only on a very small geographic scale. Previous approaches have not been used to examine 

regulatory cost barriers at the national level. 

As discussed in the Executive Summary, there are two distinguishable types of regulatory 

barriers for the subdivision of land to construct single family detached dwellings: — 

a) barriers which lengthen the time for approval of a subdivision and b) land development and 

site development standards which are more costly than a set of minimum “benchmark” 

standards selected to provide for public health and safety. Benchmark standards are intended to 

be appropriate for affordable single-family detached dwellings without adding costs that would 

not bring commensurate public health and safety benefits. There are added costs when land is 

developed according to standards larger than the benchmark standards and there may also be 

benefits associated with those larger standards. The question of whether the added benefits are 

commensurate with the added costs is dependent upon many considerations. The evaluation of 

whether some of the benefits may be commensurate with the costs is an area that merits 

considerable investigation but is outside the scope of this study. 

Land development standards investigated by the research team included standards associated 

with zoning requirements such as lot size as well as standards associated with subdivision rules 

such as lot width, interior floor space, building setbacks from the street, rear and side property 

lines, street widths, requirements for sidewalks and requirements for open space. This specific 

set of land development standards was selected for study by the research team based on our 

literature review. These specific standards have been identified as having the potential to 

significantly increase the costs of residential building lots. Based on existing research 

approaches, measuring the costs which are attributable to the differences between the existing 

land development standards and the benchmark standards require: 

1. Knowledge and analysis of existing local requirements or standards 

2. A set of alternative standards (the benchmark standards) which provide for public health 

and safety and could apply to a broad range of jurisdictions across the county 

3. A methodology for costing the existing and the benchmark standards 

4. A methodology for projecting the implications of the cost differences, if any, to the price 

of housing 

5. A methodology to estimate the number of families affected by the cost differential 

between the existing standards and the “benchmark“ standards 

NAHB Research Center 1-1 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

Measuring administrative and process costs in a quantitative approach was outside of the scope 

of this study. A quantitative approach to these costs would require extensive knowledge of the 

local administrative review process, the out-of-pocket costs associated with the local review 

process, assumptions about time and opportunity costs, a methodology for measuring such 

costs, and a benchmark review process, either actual or model, against which to compare actual 

administrative and process costs. 

The present study examined the standards that are currently enforced in subdivision controls 

and zoning ordinances. Toward that end, the research team developed and executed a plan to 

systematically collect and analyze, via a Microsoft Access database, a nationally-representative 

sample of the land development and site development standards contained in subdivision rules 

and zoning ordinances. 

A set of benchmark standards was developed using a survey of land development professionals 

in both the private and public sectors. The benchmark standards represent “best professional 

judgment” of the respondents to the survey. All such surveys are open to criticism with respect 

to the selection of the group being surveyed and the possible bias present in the individuals 

responding to the survey as compared with those individuals who did not respond to the 

survey. The research team reviewed the benchmark standards as compared with published 

model standards by several organizations. Where applicable, the benchmark standards were 

also reviewed with respect to median or the average values for the standards contained in our 

nationally representative database of existing land development regulations and with the median 

or average values of dwelling and house lot characteristics from the 2005 U.S. Census of 

Residential Construction. 

The currently enforceable land and site development standards were then compared with the 

benchmark standards that would promote public health and safety. The research team also used 

engineering construction cost estimating methods to establish the incremental cost differences 

between the land development standards contained in the nationally representative database 

and the benchmark standards. This approach allowed the team to estimate the regulatory cost 

barriers due to land or site development standards greater than the benchmark standards for 

each of the planning jurisdictions recorded in the database. 

Where the standards of a given jurisdiction were found to be the same or less expensive that 

the benchmark standards, there were no cost barriers related to land or site development 

standards in that planning jurisdiction. Conversely, if the standards of the jurisdiction were 

greater and more costly than the benchmark standards, the team assigned quantifiable 

regulatory cost barriers due to the standards enforceable in that jurisdiction. 

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Study of Subdivision Requirements as a Regulatory Barrier 

A data weighting method was developed using the cost barrier estimates from the study’s 

nationally representative sampling of planning jurisdictions to estimate the cost barriers existing 

in the general population of all planning jurisdictions in the United States. 

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Study of Subdivision Requirements as a Regulatory Barrier 

2. BBaacckkggrroouunndd

Since the early 20th century, there has been concern about the impact of regulations on 

housing costs, and whether certain regulations are too complex or have excessive standards. 

Many studies have been conducted to address these issues. One of the missions of the U.S. 

Department of Housing and Urban Development (HUD) is to promote policies which lead to 

a sufficient amount of affordable housing nationwide. In support of that mission, HUD 

maintains the “Regulatory Barriers Clearinghouse” for issues and information relevant to the 

promotion of affordable housing.i. Ratios of median house prices to median household 

incomes are currently at a 25-year high in more than half the evaluated metropolitan areas in 

the United States (Harvard, 2005). 

Most previous research on the regulatory cost barriers to affordable housing considered the 

effects of whole categories of regulations, of non-subdivision regulations (such as building 

codes), or of general development patterns. Few studies have focused on individual, 

subdivision rules or zoning ordinances, or have analyzed them on a national scale. One reason 

for this, as noted by the U.S. President’s Commission on Urban Housing (1969), has been 

“the lack of a comprehensive, up-to-date survey on the provision of ordinances throughout 

the nation...” For the purpose of the present study, a regulatory barrier is a public regulatory 

requirement or process that increases the cost of single-family detached dwellings with 

respect to benchmark standards that are intended to protect public health and safety. 

One seminal study in Waukesha County, Wisconsin, used a cost barrier evaluation method 

based on estimated construction costs for various infrastructure standards. This study 

compared the costs for the range of land development standards present within that county. 

According to government definitions of affordable housing, families should devote no more 

than 30 percent of their income to rent or mortgage payments and utilities. ii “Affordable 

housing" often simply means housing whose residents do not pay too large a share of their 

income on rent or mortgage. In the context of this study, “affordable means affordable to 

families earning less than four-fifths (80%) of the area's median income.“ iii These families are 

officially "lower income" households. The median family income in the United States is 

approximately $60,000 per year.iv Based on the guideline of the 30 percent of income for 

housing and 80 percent of median income standards, affordable housing on a national average 

would cost no more than $1,200 per month for rent or mortgage plus real estate taxes. 

While often motivated by the intention to preserve existing property values within the 

community, subdivision rules and zoning ordinances may, as a side effect, increase the cost to 

build new single-family dwellings. The goal of this research project was to quantify the 

NAHB Research Center 2-1 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

regulatory cost barriers crated by planning jurisdiction requirements that are greater than 

benchmark standards for house square foot floor area, lot size, road width, etc. 

This study also qualitatively characterized the reasons for delays that occur during the 

interactive process between a land developer and a planning jurisdiction during the approval 

of a proposed residential land subdivision. According to a developer in Phoenix, Arizona, who 

participated in a regulatory cost barrier focus group managed by the research team, the delay 

of one year in obtaining a subdivision approval for a typical subdivision of 40 acres and 160 

homes would add about $2,250 to the cost of each home for interest charges alone. v 

2.1 Subdivision Regulations and Zoning Ordinances 

Local subdivision regulations represent a major tool by which local governments shape and 

control the housing development process. Subdivision regulations establish infrastructure 

(land development) and site (building lot development) requirements to support new 

residential development—i.e., they establish specifications for streets, sidewalks, water and 

sewer, drainage, curbs and gutters, street signs, landscaping, trees, utility easements, and 

dedications of land or fees for recreational and/or school facilities. Subdivision regulations are 

intended to ensure that proposed housing developments are cost-effective (i.e., reduce longterm maintenance), meet health and safety requirements, are properly designed, and have a 

favorable impact on the community. 

Land use controls which exceed appropriate requirements, particularly subdivision regulation 

and zoning, which determine the type and design of development that may be built in a 

community, is identified in Not in My Backyard (HUD, 1991) as a major contributor in raising 

the cost of housing and limiting the supply of affordable housing in communities. This study 

stated that regulations (as a group, and not just their excessive elements) add 20-35 percent 

to the costs of new homes. According to U.S. Department of Housing and Urban Development 

(HUD)- sponsored Joint Venture for Affordable Housing demonstration, reducing the cost of the vi “developed lot” was the greatest single factor in achieving housing affordability.

These studies have identified two significant categories of costs associated with subdivision 

regulation: (1) administrative or process costs, which refer to the costs associated with 

developing and processing subdivision requests through the local government review process, 

including the out-of-pocket costs, application costs, and review costs, and costs of delay (time 

costs, opportunity costs); and (2) costs resulting from land and site development standards 

 ( specified design and materials requirements for infrastructure and site features, such as 

requirements for rights of way, curbs/gutters, water and drainage systems, and land 

dedication requirements) which are greater than the standards needed solely to protect 

public health and safety. 

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Study of Subdivision Requirements as a Regulatory Barrier 

Since the purpose of this study is to probe the link between subdivision regulations/zoning 

ordinances and housing prices, the research team’s review of the literature covers two 

topics—model regulations and the cost of regulations. The first topic concerns what are 

considered minimum or typical standards. It can be argued that some regulations that exceed 

minimum standards add unnecessary costs to the subdivision process, and these costs can 

show up in the price of housing. 

2.1.1 Literature Review 

Introduction 

The literature review for the most part revealed that very little published work has been 

done that has direct relevance to the quantification of regulatory cost barriers on a national 

basis. Few studies have been done examining the costs associated with subdivision regulations 

in general, much less those analyzing individual regulations or done on a national scale. One 

relevant study that quantified regulatory cost barriers for a single county in Wisconsin is 

reviewed in section 2.1.3. 

A review of literature related to subdivision regulations could cover numerous topics, such as 

legal framework, historical rationale, and the actual subdivision process. As the purpose of 

this study is to probe the link between subdivision regulations and housing prices, this review 

covers existing land use regulations, model land use regulations, benchmark standards and 

costs of regulations where the required standard is greater than an applicable benchmark. 

The literature of model land use regulations discusses what are considered minimum or 

typical standards. These standards are generally approached only from a performance 

perspective, without regard to the cost effectiveness of the proposed or recommended 

standard. The literature on the second topic, costs of land use regulations, is even more 

incomplete, because few studies have been done examining the costs associated with 

subdivision regulations in general, much less those analyzing individual regulations or done on 

a national scale. 

Many codes also address one or more other subdivision issues, such as administrative 

processes, growth management tools such as fees and exactions, and environmental 

protection. These are not discussed here, for one or more reasons (such as, their presence 

varies widely across codes, or it is difficult to assign costs to them). 

2.1.2. Regulatory Cost Barriers 

Several references on model land use regulations were reviewed as part of the literature vii review ; however these references were not of significant value in developing our estimates 

of the regulatory cost barriers associated with land and site development standards. 

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Study of Subdivision Requirements as a Regulatory Barrier 

Nelson et al (2002), The Link Between Growth Management and Housing Affordability: The 

Academic Evidence, is a comparison of the economic impacts on housing prices of two land use 

regulation categories: traditional zoning and growth management. This paper makes an 

important point—housing prices are influenced by many factors, not just the costs of 

development and construction. Luger and Temkin (2000), Red Tape and Housing Costs: How 

Regulations Affects New Residential Development, documents procedural and administrative cost 

barriers to land development. From interviews of people involved in development in several 

communities, the authors of this document developed an idea of reasonable versus excessive 

regulations, and then calculated the costs of those excessive regulations to be $10,000 to 

$20,000 per unit. In the current context, a significant limitation of this study is the fact that it 

calculated costs for regulations as a group, not for just subdivision regulations and not for 

individual regulations. 

Kennedy (2002), in The Impact of Municipal Governments on Residential Housing: A Case Study of 

Single-Family Detached Housing, in Cary North Carolina, identifies five development activities that 

affect housing costs—impact fees, restrictive zoning interpretation, administrative fees, 

excessive building codes, and required capital improvements (on- and off-site). The 

significance of this study’s conclusions related to the overall costs of the development 

activities is limited by the fact that it is a case study of only one town, and the determination 

of “excessive” was made based on interviews of two employees of a developer. 

Reducing Housing Costs Through Regulatory Reform: A Handbook for Colorado Communities (1999) 

reviews the literature on two issues—the financial impacts of various regulations, and the 

relative costs of regulations in general. On the first issue, the only study it mentions related to 

subdivision regulations is by Weitz (1982), Affordable Housing: How Local Regulatory 

Improvements Can Help. That study found the cost of excessive right-of-way widths was $700 

per lot. Excessive was defined as the magnitude or quality of the standard exceeding what a 

developer would provide absent the regulation. 

A study by German (1993), Under Siege: What Regulations Cost Builders and Buyers, compared 

the costs of building houses in two jurisdictions with different levels of regulation. The study 

found that regulations added $20,420 more to housing costs in the more regulated 

jurisdiction. However, this study only considered fees and building codes. 

In 1987, the NAHB Research Center published a paper called “Affordable Residential Land 

Development: A Guide for Local Government and Developers.” This paper reported results 

from the Joint Venture for Affordable Housing, an effort involving multiple organizations and 

more than 100 demonstration projects across the country to reform regulations and 

administration and determine the housing cost savings. Reforms fell into four categories— 

zoning regulations (primarily related to density), subdivision regulations, building construction 

innovations, and administration. On average, reforms saved $8,573 per unit, with threeNAHB Research Center 2-4 April 2007
Study of Subdivision Requirements as a Regulatory Barrier 

fourths of this coming from land use regulations, which means at most one-fourth, or $2,143, 

came from subdivision regulations. 

2.1.3 Quantifying Cost Barriers for Specific Land-Use Regulations 

As a first step in identifying the land development requirements that were appropriate to 

examine from the cost barrier perspective, the research team identified those infrastructure 

elements with standards that are most commonly referenced in subdivision rules and zoning 

ordinances (see Table B-1, Appendix B) : 

• Streets (right-of-way width, grade) 

• Street access (block length) 

• Sidewalks (width) 

• Parking (number of parking spaces required) 

• Sanitary sewerage 

• Utilities (easement widths) 

• Open space (amount required) 

However, there is considerable discrepancy across codes on the numerical standards 

proposed for these infrastructure elements. For some, such as sidewalk surface thickness and 

minimum number of parking spaces, there seems to be general agreement on standards: 

• Sidewalk minimum surface thickness = 4 inches 

• Minimum number of parking spaces = 2 per unit 

But for most regulations that are commonly covered by subdivision codes, the proposed 

standards vary significantly. For example the following ranges of land use standards were 

present in the regulations reviewed: 

• Minimum right-of-way width = 47-60 feet 

• Vehicle lane width = 9-15 feet 

• Maximum grade = 8-15 percent 

• Minimum curb radius at intersection = 5-25 feet 

• Minimum block length = 125-400 feet 

• Sidewalk requirement criteria = from “where appropriate” to “always” 

• Minimum amount of open space = 5-10 percent of gross area 

NAHB Research Center 2-5 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

One of the few studies to examine the costs of individual regulations is Schuetz and White 

(1992), Identifying and Mitigating Local Regulatory Barriers to Affordable Housing in Waukesha 

County, Wisconsin. The authors established three ways in which subdivision and zoning 

regulations can affect housing costs—through land costs, lot improvement costs, and housing 

construction costs. The effect of subdivision application processing delays and the impact of 

the delays on interest charges paid by the developer were not explicitly addressed. Schuetz 

and White collected the subdivision and zoning regulations for several jurisdictions in 

Waukesha County, and examined the minimum standards for each regulation. Minimum 

standards were defined by reputable agencies or by using the smallest values found in the 

County’s jurisdictions. They then calculated the costs of County and minimum regulations, 

and compared these costs to determine which regulations unnecessarily raised housing costs 

and by how much. 

The subdivision regulations that were found to have a significant impact on costs in the 

Waukesha study were: 

• Sidewalk requirements 

• Curb and gutter requirements 

• Storm sewer requirements 

• Impact fees 

• Excessive right-of-way widths 

Additionally, they found that certain excessive zoning regulations unnecessarily increase the 

costs of certain subdivision elements, by increasing the amount of materials needed. 

• Excessive lot widths increase the costs of sewer mains, water mains, streets, 

sidewalks, storm sewers, and curbs and gutter. 

• Excessive front yard setbacks increase the costs of sewer and water laterals. 

The costs associated with these elements of subdivision construction are reported in Table 

2.1. Note that these costs are per some unit associated with the material (for example, the 

street pavement costs are per square foot of pavement), not per housing unit. 

NAHB Research Center 2-6 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

Table 2.1: Average Per-Unit-of-Measure Costs of Selected 

Land Improvements in Waukesha County, Wisconsin 

Selected improvements Average Cost 

Sanitary sewer/front foot (FF) $25.01 

Sanitary sewer laterals/lineal foot (LF) $23.62 

Water main total/FF $18.80 

Water lateral/LF $16.00 

Storm sewer/FF $18.52 

Street without curb and gutter/FF $18.72 

Mountable curb/LF $5.48 

Boulevard curb/LF $6.23 

Concrete sidewalk 4' W x 4" D/FF $6.00 

Source: Village of Menomonee Falls; Mike Mucha, City Engineer, Mequon, WI.; 

the University of Wisconsin-Milwaukee Urban Research Center, 1992

The Waukesha study estimated the unit costs for infrastructure elements related to the width 

of the lot based on a tabulation of contractor bids for land development. These unit costs 

were utilized to estimate the aggregate infrastructure costs for the roads, sidewalks, and 

utilities associated with the range of lot widths specified in each municipality within the 

county—from 60 feet, the smallest allowable lot width, to 200 feet, the most restrictive 

requirement for lot widths within the county (See Table 2.2). 

Table 2.2: Lot Improvement Costs for Various Lot Widths in Waukesha County, Wisconsin 

Lot Front Street Curb and Sanitary Storm Total Cost of 

Width Setback Width Gutter Sewer Water Water Street Sidewalk Improvements 

60 50 27 $ 328.80 $2,569 $1,788 $ 957 $ 907 $ 360 $ 6,910

 66 50 27 $ 361.68 $2,699 $1,884 $1,053 $ 998 $ 396 $ 7,391

 80 50 27 $ 438.40 $3,000 $2,110 $1,276 $1,210 $ 480 $ 8,515 

100 50 27 $ 548.00 $3,431 $2,433 $1,595 $1,512 $ 600 $10,120 

120 50 27 $ 657.60 $3,862 $2,756 $1,914 $1,814 $ 720 $11,724 

130 50 27 $ 712.40 $4,078 $2,917 $2,074 $1,966 $ 780 $12,527 

180 50 27 $ 986.40 $5,155 $3,724 $2,871 $2,722 $1,080 $16,539 

200 50 27 $1,096.00 $5,586 $4,047 $3,190 $3,024 $1,200 $18,144 

Source: Minimum zoning regulations adopted by Waukesha County municipalities, average local improvement 

costs. University of Wisconsin-Milwaukee Urban Research Center, 1992. 

Other factors that need to be accounted for in assessing infrastructure costs for wider lots 

are costs for the extensions in the length of the sidewalks and the planting strips between the 

edge of the roadway and sidewalks. In addition to the costs to improve the raw land for the 

roads, sidewalks, and planting strips, there is an additional cost for the purchase of the raw 

land for these elements of infrastructure. The cost of infrastructure improvements associated 

with the street length (water supply, sanitary sewer, paving of road, sidewalk construction, 

and storm drainage) increased from approximately $7,000 to $18,000 per lot as the frontage 

per lot increased from 60 to 200 feet—equivalent to approximately $80 per linear foot of lot 

NAHB Research Center 2-7 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

frontage requirement. To put these on a per dwelling unit basis, you would divide by two 

assuming that you need to divide the additional cost s between the two facing houses across 

the street from each other. Also keep in mind these costs are in 1992 dollars. 

The minimum and the median front setback requirements for Waukesha County, Wisconsin 

were 25 feet and 50 feet, respectively. In the study, the cost for the utility lateral lines plus 

the cost for driveway paving at the 25-foot setback was $2,000, and the cost at the 50-foot 

setback was $3,200. The difference in costs for these values of front setbacks was 

approximately $50 per foot of setback (1992 dollars). 

Within Waukesha County, communities which are more urbanized or in high-growth areas 

allow development of smaller single-family lots than do more rural towns and villages. The 

smallest lot size approved for SFD homes in Waukesha County, Wisconsin in 1992 was 4,800 

square feet. The median value for the minimum lot size for the highest density residential 

district permitting SFD homes for the 32 communities in Waukesha County was 20,000 

square feet. The report did not attribute a specific cost differential to larger lot size 

requirements, probably due to the high spatial variability of land cost. 

Minimum interior floor area requirements were noted as a possible significant contributor to 

regulatory cost barriers for affordable housing in the Waukesha study. The adopted 

minimums for the communities ranged from 900 to 1,500 square feet. The median required 

minimum floor area adopted in Waukesha County for a SFD residence in 1992 was 1,100 

square feet; although the most frequently adopted minimum floor area was 1,200 square feet. 

These values for minimum floor area requirements are near the average values found by the 

research team for the nationally representative sample of jurisdictions. The study noted that 

although most of these minimum floor area requirements are considerably smaller than the 

homes built during the previous decade, the minimums can still be adjusted to allow more 

affordable housing to be constructed. 

Open space requirements in subdivision rules may be stated in one of the principal formulae: 

• Percentage of total subdivision land 

• Number of square feet per dwelling unit 

• Number of square feet per person 

Using the applicable minimum lot area for a subdivision and the median household population 

in the United States—2.69 people per household based on the 2000 U.S. Census—the three 

measures of open space can be expressed in the same units of number of square feet per 

dwelling unit. 

NAHB Research Center 2-8 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

Open space requirements in Waukesha County at the time of the study ranged from 1,500 to 

7,500 square feet per dwelling unit when sewer was available, and from 9,400 to 15,000 

square feet in areas without municipal sanitary sewer service. Depending on the costs for 

additional raw land to provide for subdivision open space requirements, these standards may 

be a significant contributor to regulatory cost barriers. 

Based on a comparison with the minimum development standards adopted in the county 

which were considered to be reasonable guideline minimums, the Waukesha County study 

listed the following five items as the most obvious steps to reduce the cost of finished 

dwellings: 

• Decreasing the minimum lot size in the highest density single-family zone 

• Reducing required lot width in these zones 

• Reducing the front yard setback requirements in these zones 

• Reducing the minimum floor area required in these zones 

• Reducing the street pavement width in these zones 

NAHB Research Center 2-9 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

3. EExxiissttiinngg RReegguullaattiioonnss

For the study detailed in this report, the project team assessed the cost impacts of regulatory 

barriers to the construction of SFD dwellings within subdivisions. In the quantitative portion of 

this study, the research team estimated the cost impacts of subdivision rules and zoning 

ordinances which require land or site development standards in excess of what is needed to 

protect public health and safety. 

For the quantitative assessment of the cost barriers, the team sampled the land and site 

development standards in the subdivision rules and zoning ordinances of 469 separate municipal 

or county level planning jurisdictions. The sample was selected using statistical considerations in 

order to be representative of planning jurisdictions throughout the United States. Specifically, 

the team looked at the standards that applied to the subdivision of land for the construction of 

SFD dwellings. In most jurisdictions there is more than a single zoning district that allows these 

dwellings. In these cases, the study considered the zoning district that allowed the smallest lot 

sizes for SFD dwellings. 

Land development and site development standards data were entered into a Microsoft Access 

database where they could be analyzed for a range of statistical measures and to quantify the 

effect of subcomponents of the sample. The team recorded key characteristics of each planning 

jurisdiction in the sample to ascertain the role of these characteristics with respect to the 

requirements for land and site development standards. These subcomponents of the sample 

included: 

• Planning jurisdiction government type 

• U.S. Bureau of Census region (Northeast, South, Mid-West, and West) 

• Membership in a Metropolitan Statistical Area (MSA) 

• Central city or outside central city 

• Population separated into quartiles 

The research team developed a basic descriptive reporting format for the collected data, which 

presents the recorded standards for each jurisdiction. An example of this format is presented in 

Figure 3.1. 

NAHB Research Center 3-1 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

Figure 3.1: Sample Database Report Output Format Showing Data Collected for Each Jurisdiction

 Source: EcoNorthwest, 2006 

3.1 Sampling of Jurisdictions 

The foundation of this study is a statistically representative sample of local governments 

(municipal and county level) in the United States that have the authority to adopt land use 

regulations. The sampling challenge was to develop a methodology that resulted in a random 

sample that is representative of the population. The objective of the project was to develop a 

sample that was: (1) geographically representative; (2) reflected the national distribution of 

population (including jurisdiction size); (3) reflected both fast and slow growing jurisdictions; 

and (4) represented a range of government types. 

The project team selected jurisdictions based on weighing the sample by population in states 

and the amount of growth in each local government between 1996 and 2000. This methodology 

placed emphasis on the amount of population in each state, and ensured that both fast and slow 

NAHB Research Center 3-2 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

growing governments were represented. The rationale for the sampling methodology is 

described in sub-appendix A-2, contained in Appendix A – Survey of Regulatory Standards. 

The sampling methodology originally intended to examine subdivision rules from 1,100 

jurisdictions. When the project team began evaluating which standards to measure, it found 

that many of the relevant standards were in zoning ordinances, rather than subdivision rules. 

After consultation with HUD, the team decided to review both the zoning ordinances and 

subdivision rules and to reduce the sample size to 500 jurisdictions, reflecting the increased 

labor required for the collection and analysis of the zoning ordinances. In cases where the 

ordinances could not be obtained from the jurisdiction, the team employed a substitution 

method to choose a different jurisdiction. Ultimately 469 separate jurisdictions were included in 

the sample utilized for the national regulatory barrier cost estimates. 

After selecting the sample, the project team collected zoning ordinances for review. The 

structure of a typical zoning ordinance presents some inherent analytical challenges. A typical 

zoning ordinance has three or more residential districts. The research team concluded that 

reviewing every residential district for each jurisdiction in the sample would be infeasible. Thus, 

the team developed a protocol for gathering ordinances that significantly reduced the data 

collection effort. The team focused on the "border" zone between low-density single-family 

development and high-density multifamily development because the land requirements are 

smaller (e.g., minimum lot sizes are typically smaller), which should result in lower housing 

costs. The "border" zone was defined based on the following characteristics: it permitted 

detached single-family houses outright; it had the smallest minimum lot size and setbacks; and, 

where applicable, it allowed a mixture of detached single-family houses and duplexes or 

multifamily housing. In cases where it was unclear which zone to choose after evaluating these 

characteristics, the research team opted for the zone with the smallest minimum lot size where 

SFD homes are permitted outright. 

After collecting ordinances, identifying the appropriate zone for analysis, and inputting data, the 

research team conducted a statistical analysis of the sample. The analytical approach focused on 

two types of statistical analysis: (1) basic descriptive analysis; and (2) inferential statistics in the 

form of means testing. The basic descriptive analysis consisted of the following statistics: mean, 

median, mode (most frequently reported value), frequencies, range, and standard deviation. The 

means testing used chi-square and ANOVA with post-hoc testing to determine if the variables 

varied systematically by class membership within subcomponents of the sample including 

government type, Census region, membership in a Metropolitan Statistical Area (MSA), central 

city, and population quartiles. 

NAHB Research Center 3-3 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

3.2 Selection of Land Development Standards 

The project began with a list of about 75 land or site development standards (referred to as 

“variables”) that were considered for inclusion in this study. The team narrowed the list of 

variables by reviewing ordinances from 10 jurisdictions to assess whether subdivision 

ordinances commonly contained the standards on the list. Many site-specific variables on the 

original list were not in the initial 10 ordinances. 

At that point, the team began considering expanding the scope of the project to include some 

variables from zoning ordinances because the preliminary research indicated that many 

standards, especially those related to lot size, which have substantial impact on housing costs, 

are not typically included in subdivision ordinances. The team reduced the number of variables 

to 15 and conducted a second review of 10 jurisdictions' subdivision and zoning ordinances to 

determine how frequently these variables occurred in the ordinances. This review showed that 

the variables on the reduced list were frequently found. 

The list of variables was finalized based on the following criteria: 

• Expected impact of the variable on housing cost. This was a critical factor. Some 

of the variables initially considered were estimated to have minimal impact on the cost of 

housing. For example, many of the jurisdictions in the preliminary review contained 

standards for the angle of street intersections, but, based on the team’s expertise in 

residential construction, it was understood that this factor has little impact on the cost of 

housing in a subdivision. 

• Likelihood and ease of finding the variables within a zoning or subdivision 

ordinance. A number of the variables that the team was originally interested in measuring 

were not generally found in either subdivision or zoning ordinances. For example, the 

minimum diameter of a sewer lateral or street pavement surface thickness was not often 

found in either the zoning or subdivision ordinances. 

• Ease of measuring the variables. Some of the variables that were considered were 

difficult to measure. For example, landscaping standards vary substantially among ordinances. 

The team was unable to find a way to quantify such diverse standards. Instead, the 

researchers chose to identify whether or not each jurisdiction had landscaping requirements 

in their zoning or subdivision ordinances. 

The following variables were selected for inclusion in the review of subdivision rules and zoning 

ordinances for this study: 

• Lot width minimums • Yard set-back minimums (front yard, 

• Lot size minimums side yards, rear yard) 

• Floor area minimums 

NAHB Research Center 3-4 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

• Off-street parking requirements • Sidewalk requirements 

• Curb and gutter requirements • Open space requirements 

• Minimum street right-of-way width • Landscaping requirements 

• Minimum pavement width 

3.3 Definitions 

This section includes definitions of terms that are used for the statistical analysis. 

Means testing. This includes tests that describe the variation with in the sample. Types of 

means tests include: chi-squared and ANOVA. 

Statistically significant. Results are referred to as statistically significant or significant if a 

statistical test shows a difference that is unlikely to occur by chance. 

Chi-square. A statistical procedure used to test for differences between groups of categorical 

data. This technique makes use of data classified into a contingency table, and the results are 

based on a comparison of expected frequencies with observed frequencies. (For further details 

see http://www.statistics.com/content/glossary/c/chisqtest.php.) 

ANOVA (Analysis of Variance). Techniques used to determine if differences between two 

or more groups are significant. This type of test is based on an assessment of the variation 

between groups relative to variation not associated with differences in group membership. (For 

further details see http://www.animatedsoftware.com/statglos/sg_anova.htm.) 

3.4 Analytical Framework 

For this project, the analytical approach focused on two types of analysis—basic descriptive 

analysis, and means testing. The basic descriptive analysis consisted of the following statistics: 

mean, median, mode, frequencies, range, and standard deviation. The means testing consisted of 

using chi-square and ANOVA tests. 

The means tests showed statistically significant1

 differences among the jurisdictions. Jurisdictions 

were separated by certain characteristics, such as population size or whether the jurisdiction 

belonged to an MSA. These groupings, which represent subcomponents of the sample, allowed 

the research team to perform the means testing to compare the regulatory standards between 

regions within the sample, rather than the entire sample. Using these groupings allowed for 

comparisons that showed regional variation among the subcomponents of the sample. The 

subcomponents included: 

1 For the remainder of the report, “statistically significant” results will be denoted as “significant.” 

NAHB Research Center 3-5 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

Government type. Jurisdictions were separated by six government types—county, city, 

town, township, village, and other government type. Counties and parishes were combined 

because there are few parishes, and they serve a similar function as counties. All the other 

government types were combined as well because they made up less than 3 percent of the 

governments in the study. 

Census region. States were grouped into the four regions used by the U.S. Census: 

viii Northeast, Midwest, South, and West.

Part of an MSA. Jurisdictions were grouped by whether they are a part of a Metropolitan 

Statistical Area (MSA), as defined by the U.S. Census. Jurisdictions belonging to an MSA are 

more likely to be located in an area where the population is densely distributed. 

Central city. Jurisdictions were grouped based on whether they are a central city, as defined 

by the U.S. Census. A central city is the largest city of a Metropolitan Area (MA) and is a basis 

for establishment of an MA. Jurisdictions that are a central city are typically more densely 

populated than jurisdictions that are not a central city. 

Population. The sample jurisdictions were grouped into quartiles based on their populations 

from the 2000 U.S. Census. The groups were as follows: fewer than 5,491 people; 5,492 to ix 25,176 people; 25,177 to 97,268 people; and more than 97,268 people.

The means tests indicated whether sample subcomponents, such as government type or Census 

region, make a difference in the standards that jurisdictions establish. For example, the means 

testing tells whether a variable such as lot size is likely to be different if the government is a city 

or county or if it is located in the east or west, etc. The research team used two forms of 

means testing—chi-square and ANOVA. 

The team performed chi-square tests on each variable using the five subcomponents of the 

sample. The chi-square indicated which variables had significant differences for the 

subcomponents of the sample. It is likely that significant differences were caused by differences 

in the variables for the subcomponents. In other words, if the chi-square for lot size by 

government type is significant, then it is likely that lot size varied in a significant pattern by 

government type. 

The research team then performed an ANOVA test to identify which subcomponents had 

significant differences. Where the chi-square test can indicate a significant difference among all 

of the subcomponents, the ANOVA can show the significant differences between each of the 

subcomponents. For example, this test might show that lot sizes are statistically different in 

cities than in counties. Researchers performed this test for the government type, Census 

region, and population subcomponents. 

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Study of Subdivision Requirements as a Regulatory Barrier 

In cases where the team found standards for the variables in fewer than 100 jurisdictions, it did 

not perform any means testing because there were too few data to produce meaningful results. 

Appendix A – Survey of Regulatory Standards includes additional details about statistical 

procedures. 

3.5 Summary of Descriptive Analysis of Regulatory Standards 

Table 3.1 below and the following general observations on the sample provide summary of 

descriptive statistics for the variables reviewed in the study. 

Table 3.1: Summary of Descriptive Statistics of the Variables Reviewed 

Standard 

N Mean Median Mode Deviation Minimum Maximum 

Lot size 419 9,924 6,000 5,000 16,946 750 217,800 

Lot width 342 62 60 50 25 20 250 

Front yard 413 25 25 25 13 0 100 

Side yard 417 8 8 5 5 0 30 

Rear yard 404 21 20 25 9 0 65 

Minimum floor area 86 1,060 1,000 1,000 359 500 2,500 

Off-street parking 367 2 2 2 1 0 4 

Open space requirements 

Percent of total land in subdivision 47 13 10 10 9 3 50 

Number of square feet per dwelling unit 18 1,562 795 871 3,447 310 15,246 

Number of square feet per person 34 229 218 218 112 87 436 

Sidewalk width 153 4 4 4 1 3 10 

Planting strip width 37 5 5 5 1 2 8 

Street pavement width 

Street right-of-way width 

192 

262 

28 

52 

28 

50 

30 

50 

6 

8 

16 

20 

45 

80 

Source: Study of Subdivision Requirements as a Regulatory Barrier to Affordable Housing, Descriptive Analysis, CPW 2006 

Units are linear feet except minimum floor are in square feet 

The statistical analysis led the research team to the following broad conclusions: 

The sample is roughly representative of each state by population and geography. 

The sampling methodology was designed to draw a sample of jurisdictions based on the states' 

populations proportionate to the U.S. population. It was also designed to ensure geographic 

diversity by including a minimum of two jurisdictions per state, regardless of population. 

Jurisdictions in the sample represent 26 percent of the entire U.S. population. 

Most of the 469 jurisdictions reviewed had zoning and subdivision ordinances. 

Ninety percent of the jurisdictions had a zoning ordinance and 86 percent had a subdivision 

ordinance. Six percent of the jurisdictions had neither a subdivision nor a zoning ordinance. 

Lot size requirements were highly variable among jurisdictions. The smallest minimum 

lot size in the study was 750 square feet and the largest was 217,800 square feet (5 acres). 

NAHB Research Center 3-7 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

Forty-one percent of the jurisdictions in the sample had minimum lot sizes between 5,000 and 

6,999 square feet. Statistical testing showed significant differences in lot size requirements for 

each subcomponent of the sample. For example, there were significant differences in minimum 

lot sizes for each of the four Census regions (one of the subcomponents of the sample), with 

larger minimum lot sizes in the Northeast than in the other three regions. 

Lot widths varied across jurisdictions. The smallest lot width requirement was 20 feet, the 

largest was 250 feet, and the median was 60 feet. Fifty-five percent of jurisdictions required 

minimum lot widths of 50 to 69 feet. As with lot sizes, statistical testing showed significant 

differences in lot width requirements for each subcomponent of the sample. 

The mean front set-back requirement was 25 feet. Fifty-six percent of jurisdictions had 

front setbacks between 20 and 29 feet. Like lot size and width, front setbacks differ in a 

significant way for each subcomponent of the sample. 

The mean side set-back requirement was 8 feet per side. Fifty-eight percent of 

jurisdictions required minimum side yard setbacks of between 5 to 9 feet. Side setbacks differed 

in significant ways for each subcomponent of the sample. 

The mean rear set-back was 21 feet. The smallest requirement for a rear set-back was 

zero feet and the largest was 65 feet. Fifty-five percent of jurisdictions required rear set-back of 

between 20 and 29 feet. Rear yard setbacks differed in significant ways for each of the five 

subcomponents of the sample, except for population quartiles. 

Fewer than 20 percent of jurisdictions had minimum floor area requirements. For 

those jurisdictions that have such requirements, the mean floor area was 1,060 square feet and 

the median 1,000 square feet. The smallest floor area requirement was 500 square feet per 

dwelling unit and the largest 2,500 square feet. 

More than three-quarters of the jurisdictions required two off-street parking 

spaces. The mean number of off-street parking spaces required per dwelling unit was 1.88 and 

the median was 2 parking spaces. Further statistical testing showed that the number of offstreet parking spaces required differed in a statistically significant way based on population 

quartile, as well as between central cities and non-central cities. 

Fewer than half of the jurisdictions had landscaping standards. Forty-two percent of 

the jurisdictions had landscaping standards specifically for subdivisions or the zoning district that 

were examined for the study. Differences in landscaping requirements are significant for the 

following subcomponents of the sample: Census region, if the jurisdiction is part of an MSA, and 

population quartile. 

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Twenty percent of jurisdictions had quantitative open space requirements. The 

research team collected three types of requirements for open space: (1) percent of total land in 

the subdivision; (2) number of square feet per dwelling unit; and (3) number of square feet per 

person. About 20 percent of the jurisdictions in the sample used at least one of these methods 

for determining open space requirements. 

Fifty-one percent of all jurisdictions n the sample explicitly required sidewalks. Of 

those jurisdictions, 51 percent (e.g., about one-quarter of all jurisdictions in the sample) 

required sidewalks on both sides of the street. The average sidewalk width was 4 feet. 

Requirements for sidewalks varied systematically by the following subcomponents of the 

sample: government type; membership in an MSA; and the jurisdiction's population. In contrast, 

sidewalk width requirements did not vary systematically based on any of the subcomponents of 

the sample. 

Relatively few (8%) jurisdictions had requirements for planting strips. The planting 

strip is a landscaped area between the sidewalk and curb. The mean and median planting strip 

width was 5 feet. 

Curbs and gutters were required by 50 percent of the jurisdictions in the study. 

The mean and median pavement width for streets was 28 feet. Most jurisdictions' 

standards for pavement width were either from 20 to 24 feet wide, from 25 to 29 feet wide, or 

from 30 to 34 feet wide. Pavement width differed in a statistically significant way for each 

subcomponent of the sample. 

The mean street right-of-way was 52 feet. Fifty-six percent of jurisdictions with right-ofway standards require right-of-ways no smaller than 50 to 54 feet; and 24 percent of 

jurisdictions require right-of-ways at least 60 to 64 feet wide. Street right-of-way requirements 

vary systematically by Census region. 

3.6 Summary of Means Testing Of Regulatory Standards 

The results of means testing, including chi-square and ANOVA tests, are summarized by 

variable below. Table 3.2 shows a summary of the results of the chi-square tests. Statistically 

significant results are denoted with a star (*). A significance level of less than 0.05 is considered 

significant. 

A statistically significant result means that it is highly probable that there is a difference within 

the subcomponent for the variable. For instance, off-street parking requirements are only 

statistically significant for central city and population. That means that off-street parking 

requirements are different for jurisdictions that are a central city and jurisdictions that are not a 

NAHB Research Center 3-9 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

central city. Likewise, off-street parking standards are different for jurisdictions with different 

sized populations. 

Table 3.2: Summary of Means Testing for Variance within Five Subcomponents of the Sample 

Government Census Part of 

type region MSA Central city Population 

Lot size 0.000* 0.000* 0.000* 0.000* 0.000* 

Lot width 0.000* 0.000* 0.000* 0.000* 0.000* 

Front yard 0.000* 0.000* 0.000* 0.000* 0.000* 

Side yard 0.000* 0.000* 0.000* 0.000* 0.000* 

Rear yard 0.007* 0.000* 0.001* 0.029* 0.055 

Off-street parking 0.804 0.556 0.622 0.000* 0.011* 

Open space requirement 0.216 0.003* 0.058 0.460 0.200 

Landscaping requirement 0.054 0.002* 0.018* 0.783 0.000* 

Sidewalk required 0.007* 0.096 0.000* 0.143 0.001* 

Sidewalk width 0.841 0.060 0.565 0.156 0.251 

Street pavement width 

Street right-of-way width 

0.001* 

0.903 

0.000* 

0.000* 

0.050* 

0.233 

0.046* 

0.323 

0.021* 

0.387 

Source: Study of Subdivision Requirements as a Regulatory Barrier to Affordable Housing, Descriptive Analysis, CPW 

2006. Calculations by ECONorthwest. 

Note: Statistically significant results are noted with an star (*) for p < .05. 

The means tests led the research team to the following broad conclusions: 

Lot size requirements were statistically significant for all subcomponents of the 

sample. Table 3.2 shows that lot size requirements were significantly different for each 

subcomponent of the sample. For example, lot size requirements were different based on the 

jurisdiction’s type of government or whether the jurisdictions was within an MSA. 

Further statistical testing showed the differences in lot sizes among subcomponents of the 

sample.2

 Lot size varied within each subcomponent in the following ways: 

Government type: City lot sizes were significantly smaller than county, town, and 

township lot sizes. 

Census region: Lot sizes in the Northeast were statistically larger than lot sizes in the 

other three regions. 

Population: Lot sizes in the first quartile, jurisdictions with the fewest people, were 

statistically larger than lot sizes in other quartiles. 

2 This form of statistical testing, an ANOVA, required a minimum of three groups within the subcomponent. The project team 

conducted this test for the government type, Census region, and population subcomponents. 

NAHB Research Center 3-10 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

The differences observed within both types of means testing reinforce the conclusion that 

statistical differences resulted from differences in lot size within the subcomponents. 

Lot width requirements were statistically significant for all subcomponents of the 

sample. Table 3.2 shows that lot width requirements were significantly different for each 

subcomponent of the sample. For example, jurisdictions located in different Census regions had 

significantly different lot width requirements. Further statistical testing showed that lot width 

varied in the following ways: 

Government type: Lot widths were statistically different between the following 

groups—cities had smaller average lot widths than villages, towns, or townships; and 

counties had larger average lot widths than towns or townships. 

Census region: Lot widths were statistically different between the Northeast and all 

other regions. The Northeast had larger average lot widths than any other region. Lot 

widths in the Midwest were statistically larger than those in the West. 

Population: Lot widths were statistically different between the first population 

quartile, jurisdictions with the fewest people, and the other quartiles. The first quartile 

had larger average lot widths than the other quartiles. In addition, the second quartile 

had significantly larger lot widths than the fourth quartile. 

The differences observed within both types of means testing reinforce the conclusion that 

statistical differences resulted from differences in lot width within the subcomponents. 

Front yard requirements were statistically significant for all subcomponents of the 

sample. Table 3.2 shows that front yard requirements were significantly different for each 

subcomponent of the sample. Further statistical testing showed that front yard requirements 

varied in the following ways: 

Government type: Front setbacks were statistically different for the following 

groups—counties had smaller average front setbacks than townships; and cities had 

smaller average front setbacks than towns, townships, and villages. 

Census region: The West had statistically smaller average front setbacks than any 

other region. The South had statistically smaller average front setbacks than the 

Midwest and Northeast. 

The differences observed within both types of means testing reinforce the conclusion that the 

statistical differences result from fundamental differences in front setbacks within the 

subcomponents. 

NAHB Research Center 3-11 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

Side yard requirements were significant for all subcomponents of the sample. Table 

3.2 shows that side yard requirements were significantly different for each subcomponent of the 

sample. Further statistical testing showed that side yard requirements varied in the following 

ways: 

Government type: Side setbacks are statistically different for the following groups— 

counties have smaller average front setbacks than towns and townships; and cities have 

smaller average front setbacks than towns, townships, and villages. 

Census region: The Northeast has larger average side setbacks, a significant difference 

between the Northeast and the other regions. The West has smaller average side 

setbacks than any other region, which is also significant. 

Population: The first population quartile—jurisdictions with the fewest people—have 

larger average side setbacks, which is significantly different from each other quartile. 

Likewise, the second population quartile has larger average side setbacks than the third 

and fourth quartiles, which is also significant. 

The differences observed within both types of means testing reinforce the conclusion that the 

statistical differences resulted from fundamental differences in side yard requirements within 

the subcomponents. 

Rear yard requirements were significantly different for most subcomponents of the 

sample. Table 3.2 shows that rear yard requirements were statistically significant for each 

subcomponent except population. Further statistical testing showed that side yard 

requirements varied in the following ways: 

Government type: Rear setbacks were on average smaller in counties than townships, 

a significant difference. Cities had smaller average rear setbacks than towns and 

townships. 

Census region: The West had significantly different re0ar setbacks, which were 

generally smaller than the other regions. The South’s rear setbacks were also 

statistically different from other regions. The South had larger rear setbacks than the 

West and smaller rear setbacks than the Northeast or Midwest. 

Population: Jurisdictions in the fourth quartile of population (having the largest 

populations) had smaller average setbacks than any other quartile. This difference was 

significant between the fourth quartile and the first and second quartiles. 

NAHB Research Center 3-12 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

The differences observed within both types of means testing reinforce the conclusion that the 

statistical differences resulted from fundamental differences in rear yard requirements within 

the subcomponents. 

Off-street parking requirements varied significantly for two subcomponents of the 

sample. Table 3.2 shows that off-street parking requirements were significantly different within 

the central city and population subcomponents. In other words, the number of off-street 

parking spaces required varied, depending on whether the jurisdiction was a central city and the 

amount of population the jurisdiction had. 

Additional statistical testing showed that off-street parking requirements varied for the 

population subcomponent. Jurisdictions in the fourth quartile of population (having the largest 

populations) require less off-street parking than jurisdictions in the second population quartile. 

This result reinforces the conclusion that the statistical differences resulted from fundamental 

differences in off-street parking requirements within population quartiles. 

Open space requirements varied significantly among Census regions. Table 3.2 shows 

that open space requirements only varied significantly among Census regions. For example, 

whether a jurisdiction required open space or not was not significantly different for jurisdictions 

located in a central city and those not within a central city. The research team did not perform 

further tests for open space because open space had only two possible values (yes or no) and 

the ANOVA test requires three or more possible values (i.e., yes, no, maybe). 

Landscaping requirements varied significantly for some subcomponents. Landscaping 

requirements varied significantly for the following subcomponents—Census region, 

membership in an MSA, and population. For example, landscaping requirements varied 

significantly based on whether the jurisdiction was part of an MSA or not. The research team 

did not perform further tests for landscaping because landscaping had only two possible values 

(yes or no) and the ANOVA test requires three or more possible values (i.e., yes, no, maybe). 

Sidewalk requirements varied significantly for some subcomponents but sidewalk 

width requirements did not vary significantly for any subcomponent. Whether a 

jurisdiction required a sidewalk varied significantly among the following subcomponents— 

government type, membership in an MSA, and population. The research team did not perform 

further tests for sidewalk requirements because it had only two possible values (yes or no) and 

the ANOVA test requires three or more possible values (i.e., yes, no, maybe). 

Sidewalk width requirements did not vary significantly by any subcomponent of the sample, 

which is consistent with the findings shown in Table 3.2 that sidewalk widths had little variation. 

NAHB Research Center 3-13 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

Street pavement width varied significantly for each subcomponent of the sample. 

Table 3.2 shows that street pavement widths varied significantly for all subcomponents. For 

instance, street pavement requirements were significantly different for the Census regions, with 

jurisdictions in some regions requiring wider pavement widths than in other regions. 

Additional statistical testing showed differences in pavement widths within subcomponents of 

the sample. The tests showed differences within government type and Census region, indicating 

that pavement widths varied significantly by government type and Census region. Although the 

chi-square statistical test indicated that pavement widths were statistically different among 

population quartiles, additional statistical testing indicated that there are no significant 

differences in pavement widths for population quartiles. Pavement widths varied within each 

subcomponent in the following ways: 

Government type: Cities had the largest average pavement widths of any government 

type. This difference in pavement widths was significant between cities and towns. 

Census region: Pavement widths were statistically different between the West and the 

Northeast and South. The West had larger average pavement widths. 

Population: There were no significant differences in pavement widths when analyzed 

by population quartiles. 

The differences observed within both types of means testing reinforce the conclusion that the 

statistical differences resulted from fundamental differences in pavement width requirements 

within the subcomponents. 

Street right-of-way width varied significantly among Census regions. Table 3.2 shows 

that right-of-way widths only varied significantly among Census regions. Additional statistical 

testing shows that street right-of-way widths were statistically different between the Midwest 

and all other regions. The Midwest had larger average right-of-way widths than the other 

regions. This result reinforces the conclusion that the statistical differences resulted from 

fundamental differences in right-of-way widths within Census regions 

NAHB Research Center 3-14 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

4. SSttaannddaarrddss,, BBeenncchhmmaarrkkss,, aanndd UUnniitt CCoossttss

The research team assumed that an SFD dwelling developed in conformance with appropriate 

land and site development standards for the protection of public health and safety would be 

characterized by a minimum benchmark set of land development standards for lot size, floor 

space requirements, lot width, etc. The benchmark standards are based on 12 individuals 

responding to a survey of 25 land development professionals including residential land 

developers, civil engineers, architects, land planners in private practice, and land planners 

employed by planning jurisdictions. The individuals solicited in the survey were recommended 

by the National Association of Home Builders (NAHB) and the National Association of 

Counties (NACo). 

4.1 Benchmarks 

The benchmark standards in Tables 4.1 and 4.2 were set at the mean value of the benchmark 

values suggested by the 12 respondents to the survey described above. The respondents were 

asked to submit benchmark standards appropriate to geographic areas with “more dense” 

development. The more dense development scenario was defined as a median lot size of 7,000 

square feet or 0.16 acre. 

x

 These benchmarks were used for comparison with jurisdiction requirements for Metropolitan 

Statistical Areas (MSA). Separate standards were solicited for communities with “less dense” 

development. The “less dense” development scenario was described as a community with a xi median lot area of 22,000 square feet or 0.50 acre. These benchmarks were used for 

comparison with jurisdiction requirements outside Metropolitan Statistical Areas (non-MSA). 

NAHB Research Center 4-1 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

Table 4.1: Expert Responses for Land Development Benchmarks for "More Dense" Development, 

Statistical Summary of Responses Used for Comparison in MSAs (N=12) 

Land Development 

Standard 

Lot size ( feet ) 2 

Mean 

4,250 

Minimum 

2,750 

Maximum 

7,000 

Lot widths (feet) 39 30 60 

Front, side, and rear setbacks 

FRONT (feet) 13 0 30 

SIDE (feet) 5 3.5 6 

REAR (feet) 16 10 30 

Floor area minimums (feet) 2 981 400 1,750 

Paved roadway width (feet) 

On-street parking 

allowed one side only 24 21 28 

On-street parking 

allowed on both sides 27 22.5 32 

Width of planting strip 

required (feet) 5.1 3.5 10 

Sidewalk width (feet) 3.94 3 5 

Number of off-street parking 

places required 

Open space requirements 

(% of total land in subdivision) 

1.56 

12.9 

1 

0 

2 

40 

NAHB Research Center 4-2 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

Table 4.2: Expert Responses for Land Development Benchmarks for "Less Dense" Development, 

Statistical Summary of Responses Used for Comparison in MSAs (N=8) 

Land Mean Minimum Maximum 

Development 

Standard 

Lot size (feet ) 2 9,411 3,200 20,000 

Lot widths (feet) 54 20.0 90 

Front, side, and rear setbacks 

FRONT 19 0.0 35 

(feet) 

SIDE 8 0.0 20 

(feet) 

REAR 21 10 50 

(feet) 

Floor area (feet)2 1,481 800 2,500 

Paved roadway width (feet) 

On-street 

parking allowed 23 20 28 

one side only 

On-street 

parking allowed 28 22.5 36 

both sides 

Width of planting 

strip required 6.1 3.5 10 

(feet) 

Sidewalk width 

(feet) 3.93 3 5 

7 out of 8 respondents 

indicate swales/ drainage Curb and Gutter drainage ditches should be considered 

for alternate drainage 

Number of offstreet parking 1.6 1 2 

places required 

Should required 

parking be under consensus of 7 out of 8 

cover? respondents : No 

Open space 

requirements 11.5 4.0 25.0 (% of total land in 

subdivision) 

NAHB Research Center 4-3 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

As expected, the expert survey result for the benchmark lot sizes, lot widths, minimum front, 

rear, and side setbacks, and for minimum square foot floor areas are all significantly smaller for 

the “more dense” population scenario as compared with the “less dense” population scenario. 

This reflects that a more compact development pattern is generally followed in more urbanized 

locations. 

Costs to a homebuyer for developed lots which conform to the benchmark standards will be 

lower in general as compared to developed lots with larger lot areas, frontage widths, and 

interior floor space. The cost differential between a lot developed according to the benchmark 

standards and the more common larger lot sizes and dwelling characteristics seen in existing 

residential subdivisions are classified as a regulatory cost barrier in this report. Notwithstanding 

this designation, larger, wider lots with larger interior floor space are considered more 

desirable single-family homes to many potential homebuyers who would be willing to pay more 

for these dwellings as compared with a benchmark lot and dwelling. The requirement for large, 

wide lots and large interior floor space is an actual cost barrier to the home buyer who has the 

resources to afford a home developed according to the benchmark standards but is less able to 

afford a home developed according to the larger and more costly standards adopted by many 

planning jurisdictions. 

4.1.1 Lot Size 

The average benchmark value for lot size developed by the expert panel was 4,250 square feet 

for “more dense” communities, and 9,411 square feet for “less dense” communities (see figure 

4.1). As can be seen, the “required lot sizes”, i.e., the median zoned lot sizes for the “more 

dense” and the “less dense” communities—7000 square feet and 22,000 square feet, 

respectively—were both significantly in excess of the benchmarks used for these communities. 

In the more dense communities, required lot sizes were sixty-five percent (65%) greater than 

the benchmark standard; in the less dense communities,required lot sizes were over 200% 

greater than the benchmark standard. 

NAHB Research Center 4-4 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

Figure 4.1: Lot Area Comparison of Benchmarks to Reference Values 

0 

2000 

4000 

6000 

8000 

10000 

12000 

14000 

16000 

18000 

20000 

Benchmark for 

"more dense" 

communities 

Benchmark for 

"less dense" 

communities 

2005 SFD new 

sales Median 

2005 SFD new 419 419 HUD Average HUD Average Design Center 

construction construction 

sales Average 

jurisdicitons w/ 

standards: standards: (gross) (estimated Sustainability 

Median 

jurisdicitons w/ 

Average 

for 7 SFDs for 7 SFDs 

Net) 

for 

benchmark 

Identification of benchmark or comparison value 

area in square feet 

4250 

9411 9110 

17567 

6000 

9924 

5150 

4230 

3230 

The U.S. Census Survey of Construction classifies new SFD homes in the following categories 

of lot size—under 7,000 square feet; 7,000 to 9,000 square feet; 9,000 to 11,000 square feet; 

11,000 to 22,000 square feet; and over 22,000 square feet. On a national basis, including 2005 

sales in all price ranges, 29 percent of sales fell in the category which included the benchmark 

value for “more dense” communities—less than 7,000 square feet. The applicable percentages 

for the other lot size categories for 2005 sales were 19 percent for 7,000 to 9,000 square feet, 

17 percent for 9,000 to 11,000 square feet, 22 percent for 11,000 to 22,000 square feet, and 13 

percent for over 22,000 square feet.xii The median lot size for 2005 sales of SFD homes in the 

United States was 9,110 square feet and the average lot size was 17,567 square feet. 

These values for the benchmark lot sizes show the same trend to larger minimum lot sizes in 

“less dense” communities as is noted in the statistical characteristics for lot size in the survey of 

existing regulations—planning jurisdictions in non-MSAs had significantly larger minimum lot 

size requirements than jurisdictions located in MSAs. 

The benchmark minimum lot size for “more dense” communities is 28 percent smaller (1,750 

square feet)than the median lot size standard of 6,000 square feet for the 419 jurisdictions with 

standards listed in Table 3.1 The benchmark minimum lot size standard of 4,250 square feet in 

“more dense” communities is larger than existing minimum lot size standards in 37 of the 419 

NAHB Research Center 4-5 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

jurisdictions with lot size standards—only 37 jurisdictions had lot size standards of less than 

4,000 square feet. The 4,250 square foot benchmark is smaller than lot size standards in 348 of 

the 419 jurisdictions with standards. Those 348 jurisdictions had standards which were 5,000 

square feet or greater. Thirty jurisdictions (seven percent of the 419 with standards) are in the 

range that includes the benchmark standard (4,000-5,000 square feet). Because the 

“benchmark” lot size for “more dense” communities is considerably smaller than the median 

and the mean lot size requirements on a national basis, land planning jurisdictions require on 

average 2000-6000 square feet more than the benchmark and at a national average raw land 

cost of about $2 per square foot, this is a regulatory cost barrier of $4000 -12000 for lot size 

alone. 

The benchmark lot size of 9,411 square feet for “less dense” communities is very close to the 

mean minimum lot size of 9,924 square feet for the 419 jurisdictions in the sample which had 

standards for lot area. The median value for the lot sizes for new SFD home sales nationally in 

the U.S. Census of Construction for 2005 was about 3 percent less than the 9,411 square foot 

benchmark. 

Of the seven SFD developments listed in the HUD web-based resource “Affordable Housing 

xiii Design Advisor,” the number of dwelling units per acre ranged from 5 to 16 with an average 

of 8.4 (gross area of 5,150 square feet per unit). The actual average lot size for those seven SFD 

developments will be smaller than 5,150 square feet since the number of units per acre density 

includes the roadway areas serving 8.4 lots. Assuming 40-foot lot frontages, a 50-foot right of 

way, and a 26-foot wide road, the road area would occupy about 18 percent of the total area, 

leaving each lot with an area of approximately 4,230 square feet. This is very close to the 

“benchmark” standard for “more dense” communities developed by the research team, which 

lends independent support for the benchmark used in this study. 

An even smaller lot size standard that the average lot size based on the seven SFD 

developments referenced above has been suggested as a means of reducing the costs of 

developed lots by the Design Center for Sustainability at the University of British Columbia 

(Canada). They recommended decreasing in the minimum residential single family detached 

building lot size from a current standard of 7,247 square feet to 3,230 square feet, a standard 

xiv which was adopted in a neighboring community.

NAHB Research Center 4-6 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

4.1.2 Lot Width 

The benchmark lot width of 39 feet in “more dense” communities is 65 percent of the median 

lot width of 60 feet listed in Table 3.1 for the 342 jurisdictions which had minimum lot width 

standards (see Figure 4.2). 

Figure 4.2: Benchmarks for Lot Width Compared with Reference Values 

39 

54 

60 62 

0 

10 

20 

30 

40 

50 

60 

70 

Benchmark for 

"More Dense" 

Communities 

Benchmark for 

"Less Dense" 

Communities 

Median for 

Jurisdictions 

with Lot Width 

Standards 

Average for 

Jurisdictions 

with Lot Width 

Standards 

Lot Width Benchmark or Reference Comparison 

Lot Width (fe

et) 

The benchmark lot width of 54 feet in “less dense” communities is 90 percent of the median lot 

width in the 342 jurisdictions with lot width standards. Of those jurisdictions, 6.4 percent (22) 

had standards equal to or lower than the 39-foot benchmark for “more dense” communities 

and 93.6 percent (320) had lot-width standards greater than this benchmark (Figure 4.3). 

NAHB Research Center 4-7 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

Figure 4.3: Jurisdictions with Standards for Lot Width in Width Ranges as a Percentage of Total 

Jurisdictions with Standards (342) 

# jurisdictions with 

standards less than or 

equal to 39 feet 6% 

10% # jurisdictions with 

standards 40-49 feet 

# jurisdictions with 

52% standards 50-59 feet 

# jurisdictions with 

standards 60 feet or 

greater 

32% 

In comparison with the 54-foot lot width benchmark for “less dense” communities, 110 of 342 

jurisdictions (32%) had standards within the range of 50 to 60 feet, more than any other 10-

foot width increment range. Fifty-five jurisdictions (16%) had lot width standards smaller than 

50 feet; 177 jurisdictions (52%) had standards that were 60 feet or greater. 

Lot widths of 40 feet or smaller have been proposed by a number of jurisdictions in 

conjunction with “zero lot line” zoning. This is a placement of house with the edge of the 

building coincident with one of the lot lines. The single side yard extends from each dwelling to 

the lot line on the opposite side. This configuration of house and side yard preserves a sense of 

xv private open space for narrow lots.

4.1.3 Setbacks 

The average value for the benchmark front setback is 13 feet in “more dense” communities and 

19 feet in less dense communities. Of the 419 jurisdictions in the sample with front setback 

standards, 9 percent were 14 feet or less, 80 percent were 20 feet or more, and 11 percent 

were in the range of 14 to 20 feet. The range of the benchmarks for “more dense” 

communities was 0 to 30 feet, and 0 to 35 feet for “less dense” communities. In the range of 13 

to 19 feet, approximately one car length can be accommodated between the street and the 

front of the dwelling. If the driveway were 16 feet wide, then two vehicles could comfortably be 

accommodated side by side. At the high end of the benchmark range, two vehicles may be 

accommodated end to end between the dwelling and the street. 

NAHB Research Center 4-8 April 2007 
Interior Floor Space Benchmarks and Reference 

Criteria

Study of Subdivision Requirements as a Regulatory Barrier 

A number of planning jurisdictions have adopted reduced setbacks to reduce the cost of lot 

development. In its affordable housing overlay district, the front setback for the San Louis 

Obispo, California planning jurisdiction is 18 feet. 

4.1.4 Floor Area Minimums 

The benchmark floor area minimums of 981 square feet in MSAs and 1,481 square feet in non-MSAs 

are both significantly smaller than the median national interior floor areas for construction of 

single-family detached dwellings in 2005—2,275 square feet for MSAs and 1,841 square feet for 

xvi non-MSAs (Figure 4.4). Interestingly, the 981-square foot average benchmark value of 

minimum floor area for “more dense” communities is very close to the 1,000-square foot 

median value for the floor area required in the 86 out of 469 jurisdictions with standards for 

interior floor area. 

Figure 4.4: Interior Floor Space Benchmarks and Reference Criteria 

981 

1481 

1000 

2275 

1841 

0 

500 

1000 

1500 

2000 

2500 

"more 

dense" 

community 

benchmark 

"less dense" 

community 

benchmark 

median for 

jurisdictions 

with floor 

area 

standards 

median for 

SFD sales 

in 2005 in 

MSAs 

median for 

SFD sales 

in 2005 in 

non-MSAs 

Benchmark or Reference Criteria 

Square Feet 

Of reported sales of 2005 new SFD homes in the United States, 2 percent of interior floor 

areas fell in the range of the benchmark standards for MSA areas—less than 1,200 square feet 

floor area. Thirteen percent of those homes fell in the range that includes the non-MSA 

benchmark interior floor area—1,200 to 1,600 square feet. Most sales fell in larger size ranges 

for floor areas—19 percent in the range 1,600 to 2,000 square feet; 19 percent in the range or 

2,000 to 2,400 square feet; 22 percent in the range of 2,400 to 3,000 square feet; and 25 xvii percent greater than 3,000 square feet.

NAHB Research Center 4-9 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

4.1.5 Road Widths 

The average value of the benchmark standard for paved street width for streets with parking 

restricted to one side only in “more dense” communities is 24 feet. For streets with parking on 

both sides of street, the benchmark standard is 27 feet. For “less dense” communities, the 

average benchmark is 23 feet for parking on one side only and 28 feet for parking allowed on 

both sides. The difference between 23 feet “more dense" communities and 24 feet “less dense" 

communities for one side only parking is not statistically significant given the small sample size. 

Also not significant for the same reason is the difference between 27 feet in "more dense" 

communities” and 28 feet in “less dense" communities for both sides of street parking. 

The average value of the benchmark standard for paved street width for streets with parking 

restricted to one side only in “more dense” communities is 24 feet. For streets with parking on 

both sides of street, the benchmark standard is 27 feet. For “less dense” communities, the 

average benchmark is 23 feet for parking on one side only and 28 feet for parking allowed on 

both sides. In the database of existing regulations, the average required street width is 28 feet 

and the most frequent street width requirement, the mode, is 30 feet. The required minimum 

road widths based on the survey of existing regulations were in the range of 20 to 24 feet for 

55 out of the 192 (29%) jurisdictions with road width standards. Road widths of 25 to 29 feet 

were required by 53 jurisdictions (28%) with road width standards. 

The NAHB Research Center (1993) provides guidance for required road widths. For access 

roads with estimated vehicular traffic of 0 to 250 average trips per day, and a maximum posted 

speed of 20 miles per hour, with both on-street and off-street parking, the listed range of 

minimum acceptable street widths is 18 to 22 feet. For the larger sub-collector streets with 

both on- and off-street parking, the listed minimum paved width is 26 to 28 feet. 

A standard 32-foot wide paved street with parking on both sides of the street will typically have 

a 7-foot wide lane on each side for parking and two 9-foot wide travel lanes. Under traditional 

design standards, where parking is restricted to one side of the street, the parking lane may 

have a width of 8 feet with two 10-foot wide travel lanes, for a total width of 28 feet. 

Street widths can be reduced by using parking lanes as “queuing” lanes. For example, a 26-foot 

wide street with parking allowed on both sides of the street may have two queuing lanes and a 

single travel lane. The travel lane would typically be 12 feet wide with each queuing lane at 7 

feet wide. Cars need to move from the travel lane into the opposite queuing lanes as two 

vehicles pass each other. For parking restricted to one side only, the use of a 7-foot wide 

queuing lane and a 13-foot wide travel lane for a total width of 20 feet is recommend to 

minimize street widths (NAHB Research Center, 2003). Suggested street width standards in 

these subdivision design guides generally reference the need to consider the wheelbase and 

turning requirements of fire and emergency equipment that will serve the development. 

NAHB Research Center 4-10 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

Current trends for the reduction of development impacts to the water or hydrologic cycle, 

known as “low impact development,” emphasize the benefits of reducing paved road surfaces as 

a means of reducing stormwater runoff amounts. The Seattle Department of Public Works 

(2005) pioneered a low impact development residential access road design with a paved width 

of 14 feet. All parking is off-street in this area. The design includes 2-foot flat concrete curbs on 

each side for a total width of 18 feet from the outside edge of curbing to the outside edge of 

opposite curbing. Besides cost savings on actual paving, the quantity of stormwater runoff is 

reduced due to less paved surface and having all drainage flow off the curbing into grass 

drainage swales, eliminating the need for more costly curb and gutter drainage. 

4.1.6 Sidewalks 

The benchmark survey for this study indicated a consensus that alternative pedestrian paths 

could be utilized and that sidewalks should not be required in “less dense” communities. This is 

the benchmark used to compare requirements in non-MSA jurisdictions. 

4.1.7 Open Space 

The average benchmarks for required minimum amounts of open space are 12.9 percent of the 

total subdivision area for “more dense” communities and 11.5 percent of the subdivision area 

for “less dense” communities. For the 47 out of 133 jurisdictions with open space requirements 

based on a percentage of land area in the subdivision, the mean value was 13 percent. The 

majority (60%) of the jurisdictions with standards for open space had requirements in the range 

of 10 to 19 percent. About one-fifth of the jurisdictions with standards for open space had 

higher requirements for open space and approximately the same percentage had lower 

requirements for open space. 

Much higher open space requirements are generally applied to “open space conservation 

subdivisions," also known as “cluster” subdivisions, as compared with standard lot layout 

subdivisions. In the cluster design, the allowable number of dwellings on the parcel being 

subdivided is often set at the number of dwellings that could be constructed at the underlying 

zoning density. The dwellings are placed on the parcel in a manner to maximize the percent of 

undeveloped land, usually in the range of 40 to 60 percent, while the lot size for each dwelling 

is reduced proportionately. 

4.2 Unit Costs and Regulatory Cost Barriers 

The research team for this study compared the individual jurisdiction land development 

standards (lot size, lot width, etc.) with benchmark values for those standards. Where the 

requirements of the individual land development standard contained in a jurisdiction’s 

NAHB Research Center 4-11 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

subdivision rules or zoning ordinances exceed the benchmarks, a regulatory cost barrier was 

estimated using raw land costs together with data taken from the 2005 R.S. Means Site Work 

and Landscape Cost Data manual and the 2005 RS Means Residential Cost Data manual. 

The team quantified the incremental unit costs for both raw land and for additional 

infrastructure such as road paving, lengths of storm sewer pipe, sanitary sewer pipe, and water 

supply piping within a subdivision. These individual cost estimation methods are presented xviii below for each land development or site development standard considered.

4.2.1 Lot Size 

Due to the high cost of land in MSAs, especially in the Northeast and West U.S. Census 

regions, the cost differential for building lot sizes larger than the benchmark lot standards can 

be significant. It is not completely straightforward to attribute a fixed cost of the lot per square 

foot because the per-square-foot cost of land will generally be lower for larger lots. Within a 

jurisdiction, the per-square-foot cost of a buildable lot will be a function of the required area 

for the minimum lot size. If the requirements are changed, there could be a direct effect on the 

cost of lots on a square-foot basis. 

One particular concern for the research team was obtaining a credible source of data to 

estimate the unit cost of the raw land in order to quantify the lot size cost barrier. Land costs 

vary on a smaller spatial scale than that of the easily available data on averages for finished lot 

costs and lot sizes from U.S. Bureau of Census, while costs for finished building lots vary 

significantly between neighboring communities. ,The building lot cost averages used by the 

research team were from very large geographic regions of the United States, as summarized by 

the U.S. Census of Residential Construction for the following census regions: Northeast, South, 

Midwest, and West. The costs are broken down as to lots located in MSAs and lots located in 

non-MSAs. 

The team used these average costs and average lot sizes from U.S. Census Bureau data with the 

understanding and anticipation that if more accurate and representative local data were 

required for a specific jurisdiction, those local costs, if available from local sources of land sale 

records, could be substituted for the average land costs used in this chapter. 

The data are based on responses to the 2005 U.S. Census of Residential Construction survey. 

The data from this survey serve as the basis of average costs for residential building lots and 

average lot sizes for 2004 annual recorded sales in each of the four U.S. Census regions (see 

Appendix B – Methods for Unit Infrastructure Costing). 

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Study of Subdivision Requirements as a Regulatory Barrier 

The U.S. Census of Residential Construction survey asks builders what they paid for the lot 

that was permitted for construction in 2004. If this lot was bought several years prior to 

construction, land prices would generally have been lower at that time. 

For the purpose of this research, the lot costs were modified by a factor of 50 percent to 

represent a national average for the ratio of the raw land cost to the finished lot cost (Carliner, 

2006). Carliner used builder-supplied data from all four major U.S. Census regions to estimate 

the breakdown of raw land versus development costs for building lots. 

For each of the 469 jurisdictions in the database, the average raw land cost to the builder per 

square foot (2005 costs) was estimated separately for each of the four major U.S. Census 

regions and either MSAs or non-MSAs based on the following quantities: 

A. Average cost of SFD building lots 

B. Percentage of the cost of the lot attributed to raw land (50%) 

C. Average size of the single-family dwelling building lots 

The average raw land cost per square foot is set at the product of the lot price A, multiplied by 

50 percent, then divided by the lot area C. 

These average raw land costs calculated using the method referenced above are presented in 

Table 4.3. 

Table 4.3: Estimated Raw Land Costs by U.S. Bureau of Census Region 

2004 Average Raw Land Cost (per square foot) 

(Inflated to 2005 $) 

Northeast Midwest South West National 

Metro $1.61 $1.55 $1.74 $4.36 $2.22 

Non-Metro $0.87 $0.80 $0.85 $1.80 $1.05 

For each jurisdiction with a lot area requirement greater than the benchmark, the research 

team estimated the regulatory cost barrier for required lot sizes greater 4,250 square feet for 

MSA areas and 9,963 square feet for non-MSAs listed in Tables 4.1 and 4.2. For example, if the 

jurisdiction is located in an MSA in the Northeast Census region, and the jurisdiction minimum 

lot size is 1,000 square feet greater than the benchmark, the regulatory cost barrier due to the 

lot size regulation is estimated at $1.61 per square foot multiplied by 1,000 square feet, which 

equals $1,610. 

Infrastructure and land development costs vary somewhat from region to region due to 

differing costs for labor but the material costs do not vary significantly. The jurisdictions in the 

West U.S. Census region MSAs have the highest finished lot costs, and the estimation method 

NAHB Research Center 4-13 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

indicates they have the highest raw land costs, as well. Conversely, in the Midwest U.S. Census 

region non-MSAs, the land costs are much lower than the national average. 

Once the team determined the aggregate cost barrier for excess raw land requirements for the 

entire United States, it weighted the average raw land regulatory cost barrier for each of the 

four Census regions and MSA or non-MSA by the annual numbers of housing starts within that 

area, and then summed the results from each region and area. It should be noted that the spatial 

scale of available land cost data is at a gross level and is not conclusive as to whether or not the 

housing starts are evenly distributed across areas within a Census region/MSA area that have 

lower than average, average, or greater than average land costs. If the actual number of housing 

starts that occur within higher-than-average cost neighborhoods is greater that the number of 

housing starts in neighborhoods with below-average land costs, then the estimated aggregate 

Census region/MSA area regulatory cost barrier for excess lot size requirements will be 

skewed on the low side. 

4.2.1.1 Use of Localized Land Costs 

For more locally accurate estimates of the regulatory cost barrier due to lot size requirements 

greater than the benchmarks, it would be necessary to use locally appropriate building lot costs. 

To address that possibility the research team developed a template for a regulatory barrier 

costing (RBC) tool that could be made available to users over the Internet. As of this date the 

tool has not been verified. The use of the tool can not be recommended until this verification 

xix has taken place. 

The RCB tool would allow the user to input locally relevant cost factors such as land costs. The 

user is asked to supply the local jurisdiction’s requirements for the various standards utilized by 

the research team in developing the regulatory barrier cost analysis—lot size, lot width, street 

width (including whether or not one side or both side parking is permitted), front setback 

distance, interior floor space requirements, sidewalk requirements, off-street parking 

requirements, and open space requirements. 

The RBC tool also provides user input options for unit infrastructure costs where the user 

wishes to modify the assumptions used by the research team. The tool would then perform the 

set of calculations used by the research team in Section 5.0 of this report to estimate the 

regulatory cost barriers for each of the land planning jurisdictions in the database used for the 

current study. The RBC tool would calculate the regulatory cost barrier for each land 

development requirement and would sum all costs to show the aggregate or total regulatory 

cost barrier. The RCB tool would provide an option for sharing the results with the 

administrator of a database containing all shared responses. An Excel file prototype for this tool 

is included in Appendix G. 

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Study of Subdivision Requirements as a Regulatory Barrier 

4.2.2 Minimum Square Footage Dwelling Requirements 

Where the planning jurisdiction required a minimum square foot floor area that is larger than 

the benchmark standards of 981(MSA) to 1,481 (non-MSA) square feet listed in Tables 4.1 and 

4.2, a regulatory cost barrier was calculated. The unit cost factor for square foot floor area 

requirements greater than the benchmark standards was estimated to be $74.60 per square 

foot. This cost is based on an average of the costs for various sizes and qualities of slab-ongrade structures, and is based on combinations of siding and framing types for economy grade 

xx and average grade slab foundation houses.

According to the 2005 U.S. Census of Construction, 14 percent of all new single-family 

dwellings had reported costs for construction per square foot in the category that includes the xxi value selected for this project—$70-80 per square foot. For all new detached house sales in 

xxii the United States in 2005, the median cost of construction per square foot is $82.59.

The regulatory cost barrier for excess floor area requirements is equal to the difference 

between the jurisdiction-required interior floor area square foot space and the benchmark 

square foot area, multiplied by the residential unit construction cost factor. As an example, if the 

jurisdiction requires a minimum square foot floor area that is 100 square feet greater than the 

benchmark, the regulatory cost barrier for this requirement is estimated at $74.60 per square 

feet multiplied by 100 square feet, which equals $7,460. 

4.2.3 Lot Width 

If a planning jurisdiction requires a minimum lot width, or street frontage, larger than the 

benchmark widths of 39 feet (MSA) or 54 feet (non-MSA), the research team calculated a 

regulatory cost barrier. The greater costs are due to the requirement for construction of the 

additional length of street, the additional land for the longer street, and the associated 

infrastructure within the street as compared with the benchmark lot width. 

Lot width is a significant determinant of total land improvement costs because the most 

expensive site improvements (i.e., roads, sewer, and water) cost proportionately more as the 

required length of street frontage for each lot increases. The requirement by a planning 

jurisdiction for greater than the benchmark lot widths listed in Tables 4.1 and 4.2 will cost the 

subdivision developer more for both the land and the paving required for longer streets. If the 

required lot widths are 50 percent greater than the benchmark widths, the street length 

required for a given number of fronting lots will be 50 percent longer than for lots which utilize 

the benchmark widths. The length of the sanitary sewer, storm sewer, water main, and other 

utilities which run in easements within the right-of-way associated with the street will also be 

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Study of Subdivision Requirements as a Regulatory Barrier 

increased in proportion to the road length. Sewer and water supply connection fees are 

generally based on the length of the street frontage for each property being connected. 

The aggregate unit costs for road construction for a given length of roadway depends on the 

required width of the roadway. For a typical subdivision access roadway width of 28 feet, which 

is the median value for the jurisdictions sampled, using national average cost estimates for 

sanitary sewer, storm sewer, water main, and 4- foot concrete sidewalks, and using national 

average MSA land costs, the unit cost for excess lot width is approximately $125 per linear xxiii foot. This is one-half of the total cost of the greater frontage length since it accounts for 

the distribution of the costs between two dwellings on opposite sides of the street. 

The regulatory cost barrier for lot width requirements is equal to the difference between the 

jurisdiction-required lot width and the benchmark lot width, multiplied by the unit length cost 

for the roadway (which is dependent upon the required roadway paved width) and associated 

utilities. For example, if the required lot width exceeds the benchmark lot width by 20 feet, the 

regulatory cost barrier is estimated at $125/linear foot multiplied by 20 feet, which equals 

$2,500. 

4.2.4 Road Width 

If the planning jurisdiction required a minimum paved road width larger than benchmark widths 

of 23 to 24 feet listed in Tables 4.1 and 4.2, researchers estimated a regulatory cost barrier 

based on the additional land required and additional paving of the road. 

The unit cost factor for bituminous asphalt paved road construction, based on estimates 

xxiv developed using construction cost data in RS Means Site Work Construction Costs, 2005, is 

projected to be $1.15 per square foot. The estimate of $2.30 per square foot was reduced by 

50 percent to account for the costs per dwelling unit being split between two units on opposite 

sides of the street. 

The regulatory cost barrier for road widths greater than the benchmark value, is estimated to 

be the difference between the jurisdiction-required and the benchmark value for street widths, in 

feet, multiplied by the jurisdiction-required minimum lot frontage in feet, multiplied by cost per 

square foot for roadway construction. For example, if the required road width is 5 feet greater 

than the benchmark width and if the required lot width is 60 feet, the cost for the additional 5 

feet of road width is $1.15 multiplied by 5 feet, multiplied by 60 feet, which equals $345 per 

dwelling unit. Furthermore, researchers assumed that additional land costs of approximately the 

same unit costs as the paving would be incurred as well as additional costs for lengths of sewer 

laterals and water supply laterals. 

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Study of Subdivision Requirements as a Regulatory Barrier 

4.2.5 Front Yard Setback Requirements 

If the planning jurisdiction required a minimum dwelling setback distance from the edge of the 

street larger than the 13-foot “more dense” benchmark or 19-foot “less dense” benchmarks 

listed in Tables 4.1 and 4.2, the research team calculated a regulatory cost barrier due to the 

additional required infrastructure as compared with the benchmark setbacks. 

Dwelling setback requirements from the paved edge of the street affect the cost of housing 

because they impact the distance between the house utility connections to the water and sewer 

laterals, and the right-of-way area utilized for the water supply and the sewer main pipes. In 

some cases, these water and sewer pipes may be beneath the roadway itself or it may be 

beneath the grassed boulevard strip between the edge of the sidewalk pavement and the edge 

of the roadway. The front setback distance will also affect the required driveway length and will 

thus affect driveway construction costs as well. Front, rear, and side setbacks greater than the 

benchmark values can also drive the total lot size requirement if the setbacks, when added to a 

proposed building footprint, comprise a total area which exceeds the minimum lot size specified 

in the zoning. 

The cost factor per linear foot for the longer driveway will depend on the material of 

construction (asphalt or concrete) and on the width of the driveway. For this study, the team 

assumed a conservative width of eight feet, which is a required design width for a single-vehicle 

parking space. The estimated construction costs were taken as the average of the unit costs for 

concrete driveways and asphalt paved driveways. Adding the costs for installation of water 

supply lateral piping and sewer drain piping to the cost for driveway construction, the additional 

cost for each foot of front setback is approximately $60. 

If the required setback between the building and the edge of the roadway exceeds the 

benchmark setbacks listed in Table 4.1 and 4.2, the regulatory cost barrier is the difference 

between the jurisdiction-required front setback and the benchmark front setback, multiplied by 

the combined unit length costs for longer driveways, sanitary sewer lateral, and water supply 

xxv lateral installation. If the required front setback is 10 feet greater than the benchmark front 

setback, then the cost barrier for this requirement is approximately $600 per dwelling unit. 

4.2.6 Sidewalk Requirements 

Due to a lack of consensus regarding the standards for sidewalks in denser MSAs, the research 

team did not attribute any cost barrier to sidewalk requirements in MSAs. The unit cost for 

concrete sidewalks, as indicated in Appendix B – Methods for Unit Infrastructure Costing, is 

$4.18 per square foot. The cost barrier for sidewalk requirements in non-MSAs was equal to 

NAHB Research Center 4-17 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

the unit cost factor for sidewalks, multiplied by the required width of the sidewalk (typically 4 

feet), multiplied by the required lot width. 

For a street frontage of 60 feet, the cost barrier for one sidewalk in a non-MSA area is 60 feet, 

multiplied by 4 feet, multiplied by $4.18 per square foot, which equals $1,003. This cost is then 

divided by two to obtain a per-dwelling unit cost of $501.50, which accounts for costs being 

spread over two dwellings on opposite sides of the street. 

4.2.7 Open Space Requirements 

If a planning jurisdiction required a minimum percentage of land reserved for open space larger 

than benchmarks indicated in Tables 4.1 and 4.2—11.5 percent of the total land in the 

subdivision in “less dense” communities or 12.9 percent in “more dense” communities—the 

research team calculated a regulatory cost barrier due to the additional land required with 

respect to the benchmark standards for open space. 

In some cases the open spaces will be designated as active recreational areas and will be 

landscaped and possibly include additional plantings. If the rules of the subdivisions or zoning 

ordinances require that the open space be developed as “parkland,” there will be additional 

costs not addressed in this study for footpaths or sidewalks, street lights, landscaping, park 

benches, and possibly other park amenities. The costs for any required landscaping or parkrelated amenities were not accounted for in this study because the need for these amenities of 

the required open space is generally not specified in either subdivision rules or zoning 

ordinances. 

The unit cost for open space was taken to be the raw land cost presented in Table 4.3. The 

cost depends on whether or not the jurisdiction is in an MSA or non-MSA, and on the U.S. 

Census region in which the jurisdiction is located. In areas where non-buildable wetland or 

stormwater retention areas can satisfy the jurisdiction requirements for open space, the actual 

unit cost would likely be lower than the national average raw land costs in Table 4.3. 

If the jurisdiction-required subdivision open space exceeds the benchmark open space listed in 

Tables 4.1 and 4.2, the regulatory cost barrier is the difference between the jurisdictionrequired open space and the benchmark open space, multiplied by the cost per unit area for raw 

land. To convert the values to a per-dwelling-unit basis, the percentage difference between 

benchmark and the required open space is multiplied by the required minimum lot area. For 

example, if the required minimum lot area for an MSA jurisdiction is 6,000 square feet (based 

on national average MSA land costs), and the difference between the required open space and 

the benchmark open space is 5 percent, the regulatory cost barrier for this requirement is 

6,000 square feet, multiplied by 0.05, multiplied by $2.22 per square foot, which equals $666. 

NAHB Research Center 4-18 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

NAHB Research Center 4-19 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

5. RReegguullaattoorryy CCoosstt BBaarrrriieerrss

A key objective of this study was to develop a national estimate of the cost of excessive land 

and site development standards on SFD housing built in subdivisions. The study uses a four-step 

methodology for developing the national cost estimates: (1) collect regulatory standards from a 

sample of jurisdictions for selected variables; (2) establish benchmark values and unit costs for 

each variable; (3) produce a cost estimate for regulatory cost barriers based on the application 

of the benchmark values and costs to the regulatory standards from the sample jurisdictions; 

and (4) create a national estimate of the regulatory cost barriers. 

The previous chapter presented the results of the survey of regulatory standards, the 

benchmarks used to estimate regulatory cost barriers, and the unit costs attributed to each 

variable. This chapter presents the results of applying the benchmarks to the regulatory 

standards for the sample jurisdictions and the resulting regulatory cost barriers. It presents two 

models for generalizing the regulatory cost barriers from the sample jurisdictions to the nation, 

and includes four cost estimates of regulatory cost barriers for the nation. 

5.1 Cost Analysis of the Sample Jurisdictions 

This section presents the methodology and results of the cost analysis for the sample 

jurisdictions. It includes a description of the methodology for the estimated cost of excessive 

regulation for the sample jurisdictions. It concludes with a sensitivity analysis of the costs of 

excessive regulation. 

5.1.1 Methods 

The first step in developing the national cost estimates was to produce an estimate of the 

regulatory cost barriers for the 469 sample jurisdictions. The estimate of the total regulatory 

cost barriers of the sample jurisdictions was built from estimates of the regulatory cost barriers 

for each of the nine variables. This sample estimate also allowed average per-dwelling costs to 

be calculated for the variables. 

The data presented in Sections 3.0 Existing Regulations, and 4.0 Standards Benchmarks and Unit 

Costs provide the foundation for the national costs estimates: (1) a summary of the survey of 

regulatory standards; (2) a summary of the benchmark survey; and (3) the unit cost of 

exceeding the benchmark values for each of the variables. 

NAHB Research Center 5-1 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

Figure 5.1 shows the steps in developing the estimates of the regulatory cost barriers for the 

469 sample jurisdictions. The process for estimating the regulatory cost barriers in the sample 

jurisdictions is summarized below Figure 5.1 and presented in detail in Appendix E – Cost 

Estimation Methods for Sample Jurisdictions and National Costs. 

Figure 5.1: Process for Determining the Costs of Excessive Land Use Regulation for Jurisdictions 

in the Sample 

Source: ECONorthwest, 2006 

The process for estimating the regulatory cost barriers in the sample jurisdictions included the 

following steps: 

NAHB Research Center 5-2 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

1. Select variables. The first step was to select the land and site development variables to 

examine from subdivision and zoning ordinances. 

2. Review ordinances from sample jurisdictions. The next step was ordinance review, which 

involved collecting regulatory standards for each of the variables from the zoning and 

subdivision ordinances from the sample jurisdictions. 

3. Establish benchmarks. The benchmark survey established benchmark values for each 

variable. 

4. Develop unit cost assumptions. The cost analysis required unit cost assumptions for each 

variable. For example, cost per square foot of land or per lineal foot of sewer line. 

5. Identify variance from benchmarks. The benchmarks (from Step 3) were applied to the 

data collected for each variable in each jurisdiction (from Step 2) to determine the 

degree to which a category of land development standard exceeded the benchmark 

value for that category of standard. 

6. For each variable, estimate cost of regulations requiring a variance from the benchmarks. The 

unit cost of each variable (from Step 4) was applied to the amounts of variance from the 

benchmark (from Step 5) to estimate the costs of the regulation that required the 

variance from the benchmark. These costs are all on a per-dwelling-unit basis. 

7. Aggregate costs to reflect total costs for sample. The costs of regulations requiring a 

variance from the benchmark (from Step 6) were summed for all jurisdictions in the 

sample to produce a total regulatory cost barrier for the required variances from each 

of the benchmarks. 

8. Estimate mean and median costs of regulatory barriers for the sampled jurisdictions. From the 

total regulatory cost barrier for each variable , summed over the sample of 469 

jurisdictions (from Step 7), the mean and median regulatory cost barriers for each 

variable were determined. These means and medians apply to the subset of the total 

sample of jurisdictions in which there was a calculated non-zero regulatory cost barrier 

for that variable. 

The following provides an example of how these steps were applied to regulatory 

requirements for one of the nine variables, minimum floor areas. 

1. The project team included minimum floor area requirements as a variable in the study. 

2. Ordinance review showed that 86 of the sample jurisdictions had minimum floor area 

requirements. 

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Study of Subdivision Requirements as a Regulatory Barrier 

3. The benchmark survey established maximum values for floor area requirements of 981 

square feet for jurisdictions within an MSA and 1,481 square feet for jurisdictions 

outside an MSA. 

4. The project team established a unit cost factor of $75 per square foot for excessive 

floor area requirements. 

5. The benchmark value (from Step 3) was subtracted from the floor area requirement in 

each jurisdiction (from Step 2), resulting in the variance between the required and the 

benchmark floor area requirement for each jurisdiction. 

6. The variance in floor area requirements (from Step 5) was multiplied by $75 per square 

foot (from Step 4), resulting in the total regulatory barrier cost of floor area regulation xxvi for each jurisdiction.

7. The total regulatory cost barrier for floor area regulation for each jurisdiction was 

summed, producing an aggregate regulatory cost barrier of excessive floor area 

requirements for the sample jurisdictions. As indicated in Table 5.2, this value is 

$880,000. 

8. The mean and median costs of excessive floor area regulation for the sample of 

jurisdictions were calculated, resulting in two estimates of the regulatory cost barrier of 

floor area regulation for one SFD dwelling unit. As indicated in Table 5.2, the mean was 

$26,581 and the median was $16,425. 

5.1.2 Results 

Table 5.1 shows a summary of the number of jurisdictions with requirements from each 

variable. Of the 469 jurisdictions in the study, 439 had regulatory standards for one or more of 

the variables listed in the table. The most common regulatory standards were for lot size, front 

setbacks, off-street parking, and lot width. The least common requirements were floor area and 

open space. 

Table 5.1 also shows the number of jurisdictions that exceeded the benchmarks. Of the 439 

jurisdictions with one or more regulatory standards, 425 jurisdictions had one or more 

regulatory standards that exceeded the benchmarks. Jurisdictions exceeded the benchmarks 

most frequently for off-street parking, front setbacks, lot width, and lot size. Jurisdictions 

exceeded the benchmarks least frequently for floor area, sidewalk requirements, open space, 

and sidewalk width requirements. 

NAHB Research Center 5-4 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

Table 5.1: Summary of Jurisdictions with Regulatory Standards and Jurisdictions Exceeding the 

Benchmarks by Variable 

Jurisdictions with 

regulatory standards 

Percent of 

Variable Number total 

Lot size 419 89% 

Lot width 342 73% 

Front setbacks 413 88% 

Floor area 86 18% 

Pavement 192 41% 

Sidewalk 241 51% 

Sidewalk width 153 33% 

Off-street parking 367 78% 

Open space 99 21% 

Total 439 94% 

Jurisdictions that exceed benchmarks 

Percent of 

jurisdictions 

with regulatory Percent of all 

Number standards jurisdictions 

305 73% 65% 

295 86% 63% 

370 90% 79% 

36 42% 8% 

134 70% 29% 

40 17% 9% 

60 39% 13% 

15 4% 3% 

27 27% 6% 

425 97% 91% 

Source: Survey of Regulatory Standards, University of Oregon Community Planning Workshop, with calculations by ECONorthwest 

Table 5.2 shows the costs of excessive regulation by variable for all jurisdictions. 

The total regulatory cost barriers for the jurisdictions in the sample was about $5.6 million and 

the average cost per dwelling unit was more than $13,000. 

The variables with the largest share of total costs were lot size, floor area, and lot width. The 

variables with the smallest share of the costs were sidewalk width, off-street parking, and open 

space requirements. 

The detailed analysis of the results for each land development variable is provided in Appendix 

F – Excel Workbook for Regulatory Cost Barrier Calculations. Lot size, lot width, and floor 

area accounted for the largest percentage of total costs for a variety of reasons, described 

below. 

• Lot size regulations accounted for the largest percentage of cost (65 percent). Land that is 

permitted for residential development is costly and is the major component of the costs of 

excessive lot size requirements. 

• Sixty-five percent of jurisdictions in the sample exceeded the lot size benchmark. On 

average, jurisdictions with excessive lot size requirements exceeded the benchmarks by 

6,573 square feet. The frequency and magnitude of lot size requirements greater than the 

benchmarks, combined with the cost of land resulted in the regulatory cost barrier for lot 

NAHB Research Center 5-5 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

size accounting for the majority of total costs of the regulatory cost barriers for all the land 

and site development variables considered in this study. 

• Excessive lot width requirements account for a moderate share of costs (9%) because 63 

percent of jurisdictions with lot width regulations exceeded the benchmarks. The costs 

associated with lot widths included land, sanitary sewer main, water main, street paving, 

curb and gutter, sidewalk construction, landscaping, and storm sewer. 

• Floor area had a disproportionately large impact on total regulatory barrier costs in 

proportion to the number of jurisdictions with excessive floor area requirements. Only 8 

percent of jurisdictions had excessive floor area requirements, but the regulatory cost 

barriers for floor area for those jurisdictions accounted for 17 percent of the total 

regulatory cost barriers for all land development variables for all the jurisdictions in the 

study. This resulted from the relatively high cost per square foot of required floor area and 

the fact that the mean differential between required floor area and benchmark floor areas 

was 354 square feet (or more than $26,000 per dwelling unit). 

Table 5.2 shows that the mean cost per dwelling unit for regulatory cost barriers associated 

with all the land development variables was $13,142 and the median cost was $4,950. Floor 

area had the largest mean and median cost per dwelling unit, followed by lot size. Sidewalk 

width and street pavement width had the smallest mean and median cost per dwelling unit. 

Table 5.2: Regulatory Cost Barriers for All Jurisdictions and Costs Per Dwelling Unit Variable 

Costs for all 

jurisdictions 

Percent 

Variable Total of total 

Lot size $ 3,648,726 65% 

Lot width $ 526,529 9% 

Front setbacks $ 231,952 4% 

Floor area $ 956,925 17% 

Pavement $ 64,993 1% 

Sidewalk $ 63,001 1% 

Sidewalk width $ 14,631 0% 

Off-street parking $ 22,183 0% 

Open space $ 56,620 1% 

Total $ 5,585,560 100% 

Costs of excessive regulation per dwelling unit 

Mean Median Minimum Maximum 

$ 11,963 $ 5,596 $ 216 $ 405,099 

$ 1,785 $ 1,120 $ 36 $ 16,142 

$ 627 $ 570 $ 52 $ 4,195 

$ 26,581 $ 16,425 $ 1,425 $ 113,925 

$ 485 $ 354 $ 12 $ 2,134 

$ 1,575 $ 1,672 $ 468 $ 3,344 

$ 244 $ 211 $ 0 $ 1,782 

$ 1,479 $ 1,079 $ 270 $ 2,159 

$ 2,097 $ 616 $ 7 $ 24,846 

$ 13,142 $ 4,950 $ 2 $ 407,429 

Source: Survey of Regulatory Standards, University of Oregon Community Planning Workshop, with calculations by ECONorthwest 

5.1.3 Sensitivity Analysis 

The benchmark values were determined by a survey of land-use experts, as described in 

Chapter 4. The purpose of the survey was to establish a consensus on reasonable minimum 

NAHB Research Center 5-6 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

regulatory requirements for each variable. The benchmark standards are the average value for 

each surveyed standard from all survey respondents. 

Recognizing that reasonable people might have different conclusions with respect to where the 

benchmarks should be set, the research team performed sensitivity testing on the benchmarks 

to determine how changes would impact the cost estimates. The team used the minimum and 

maximum benchmark values for each variable as input values for the sensitivity testing. 

Table 5.3 shows the results of sensitivity testing on the total and mean costs for the sample 

jurisdictions. The estimate of the cost of excessive regulation for the study sample using the 

mean values for the benchmarks was $5.6 million for all jurisdictions in the sample. The mean 

estimate of cost of excessive regulation per dwelling unit was $13,142. The total cost for the 

sample jurisdictions using the smallest benchmark values was $10.7 million and the mean cost 

per dwelling was $24,475 (smaller benchmark values resulted in more jurisdictions exceeding 

the benchmarks). When the research team used the largest benchmarks (which decrease the 

amount of excessive regulation), the total cost for all jurisdictions in the sample was $2.6 

million and the mean cost per dwelling unit was $10,013. 

The data in Table 5.2 show that the variables with the greatest share of the costs were lot size 

and floor area. When using the smallest and largest benchmark values these variables continue 

to make-up the majority of costs of excessive regulation. 

Using the mean value benchmarks, lot size accounted for 65 percent of the total costs and floor 

area accounted for 17 percent of total costs. The total cost of excessive regulation of lot size 

was $3.6 million and floor area cost about $957,000. 

• With the smallest benchmarks, lot size accounted for just over 50 percent of the total 

regulatory cost barrier. The total cost of excessive regulation of lot size was about $5.5 

million. 

• With the smallest benchmarks, floor area accounted for one-third of the total costs of 

excessive regulation because using the smallest floor area benchmark resulted in 

considerably larger variances between the required floor areas and the benchmark floor 

areas. This change in benchmark values resulted in a much larger total regulatory cost 

barrier for floor size which was estimated at $3.4 million for all sampled jurisdictions. 

• With the largest benchmarks, lot size accounted for about 82 percent of total regulatory 

cost barriers. The total regulatory cost barrier was about $2.1 million. The maximum lot 

size benchmark value was much larger than the mean lot size benchmark, resulting in a 

smaller number of jurisdictions exceeding benchmarks. However, the aggregate regulatory 

cost barrier for lot size for all jurisdictions did not show a proportional decrease to the 

decrease in the numbers of jurisdictions which exceeded benchmarks. This resulted in a 

NAHB Research Center 5-7 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

larger average regulatory cost barrier for lot size using the largest benchmarks ($21,279 for 

largest benchmarks versus $11,963 for the mean benchmarks). 

• With the largest benchmark, floor area accounted for 4 percent of the total costs of 

excessive regulation because the maximum floor area benchmark was much bigger than the 

mean floor area benchmark. This change in benchmark values resulted in smaller regulatory 

cost barriers for floor area requirements, decreasing the percentage of total costs 

accounted for by floor area regulation. The total regulatory cost barrier using the largest 

benchmarks was only $101,250. Only 7 out of the 86 jurisdictions with standards for floor 

area had regulatory cost barriers using the largest floor area benchmarks. 

Table 5.3: Results of Sensitivity Testing on Total and Mean Regulatory Cost Barriers in the Sample 

Jurisdictions 

Study benchmark assumptions Smallest benchmark values Largest benchmark values 

% of % of % of 

total Mean total Mean total Mean 

Total Costs costs Costs Total Costs costs Costs Total Costs costs Costs 

Lot size $ 3,648,726 65% $ 11,963 $ 5,492,460 51% $ 13,697 $ 2,106,601 82% $ 21,279 

Lot width $ 526,529 9% $ 1,785 $ 899,847 8% $ 2,719 $ 142,864 6% $ 1,742 

Front setbacks $ 231,952 4% $ 627 $ 537,979 5% $ 1,306 $ 43,814 2% $ 996 

Floor area $ 956,925 17% $ 26,581 $ 3,438,000 32% $ 43,519 $ 101,250 4% $ 14,464 

Pavement $ 64,993 1% $ 485 $ 59,082 1% $ 372 $ 54,154 2% $ 685 

Sidewalk $ 63,001 1% $ 1,575 $ 63,001 1% $ 1,575 $ 63,001 2% $ 1,575 

Sidewalk width $ 14,631 0% $ 244 $ 14,631 0% $ 244 $ 14,631 1% $ 244 

Off-street parking $ 22,183 0% $ 1,479 $ 22,183 0% $ 1,479 $ 22,183 1% $ 1,479 

Open space $ 56,620 1% $ 2,097 $ 192,970 2% $ 2,053 $ 24,812 1% $ 6,203 

Total $ 5,585,560 100% $ 13,142 $ 10,720,154 100% $ 24,475 $ 2,573,310 100% $ 10,013 

Source: Survey of Regulatory Standards, University of Oregon Community Planning Workshop, with calculations by ECONorthwest 

5.2 National Estimates of the Regulatory Cost Barriers for Housing in 

Subdivisions 

This section presents the methodology and results of the national cost estimate. It includes a 

brief description of two ways to model the national costs of excessive regulation. The section 

presents the cost of excessive regulation for the nation and sensitivity testing of the national 

cost of excessive regulation. 

5.2.1 Methods 

A key objective of this study was to develop a national estimate of the cost of excessive 

regulation on housing developed in subdivisions. The methodology used (a national sample of 

jurisdictions with the authority to adopt regulations) was intended to result in sample data that 

could be inferred to the national level. To accomplish this, the research team developed and 

NAHB Research Center 5-8 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

tested several models to weight the sample data to represent the regulatory cost barriers for 

land development requirements for the entire United States. 

The models for estimating the national regulatory cost barriers build from the results of the 

cost analysis, and use the mean estimates of regulatory cost barriers per dwelling unit for the 

sample jurisdictions. Because the sample data resulted in cost estimates on a per-dwelling-unit 

basis, the team weighted the regulatory cost barriers from the sample to the national level by 

using the U.S. Census Bureau’s Census of Construction estimates of single-family building xxvii permits issued for the nation in 2004.

The research team developed two models of the national regulatory cost barriers—an 

aggregated model and a disaggregated model. The models use different assumptions about the 

geographic distribution of regulatory standards for the land development variables listed in 

Table 5.3. 

The aggregated model assumed that the geographic distribution of regulatory 

standards for the land development variables would not vary based on Census 

region or MSA status within the nation. The aggregated model is based on the assumption 

that development of new SFD housing in each of the four U.S. Census regions and whether or 

not the development is located within an MSA would average about the same regulatory cost 

barriers for each land development variable as the 469 sample jurisdictions. In other words, the 

regulatory cost barriers would be about the same for all parts of the nation. 

The advantage of the aggregated model is that the size of the study sample is big enough that 

we are relatively certain that the average regulatory cost barrier that we found for each 

variable in the study is close to the true average of the regulatory cost barriers for that variable, 

on a national basis. 

The disadvantage of the aggregated model is that it doesn’t allow for separate consideration of 

regional variations in the distributions of standards, which results in higher estimates of national 

aggregate regulatory cost barrier as compared with the national disaggregated estimate of the 

regulatory cost barrier. 

The disaggregated model assumed that the regulatory cost barriers would vary 

across regions and urban and rural areas within the nation. The disaggregated model is 

based on the assumption that the regulatory cost barriers vary between different regions in the 

nation and between urban and rural areas. The disaggregated model applies different regulatory 

cost barriers to new SFD development based on location (one of the four Census regions) and 

density of development (whether the development takes place in an MSA or not). 

NAHB Research Center 5-9 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

The research team developed two models of the national regulatory cost barriers —an 

aggregated model and a disaggregated model. Figure 5-2 shows the steps in developing the 

national estimate of the cost of excessive regulation on housing in subdivisions. Below is a 

summary of the process used in each model. A detailed description of the methodologies for 

the models is presented in Appendix E – Cost Estimation Methods for Sample Jurisdictions and 

National Costs. 

Figure 5.2: Process for Modeling the Nationwide Regulatory Cost Barriers 

 Source: ECONorthwest, 2006 

The process for estimating the regulatory cost barriers at the national level included the 

following steps: 

NAHB Research Center 5-10 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

1. Develop sample cost estimates. The cost analysis provided the following information: the 

number of jurisdictions in the sample with requirements for each variable; estimates of xxviii total regulatory cost barriers for each variable; the mean cost of each variable for 

the sample jurisdictions; and the percent of jurisdictions in the sample with regulatory 

cost barriers for each variable. 

2. Collect building permit data. The next step was to gather the number of building permits 

issued in 2004 for the nation and the four Census regions. Table 5.4 presents this 

information. 

3. Apply building permit data to sample cost estimates. The information from the cost analysis 

(Step 1) was combined with the number of building permits issued in 2004 (Step 2) to 

produce two estimates of the national regulatory cost barriers for each variable. These 

estimates were based on the following models: 

• The aggregated model used the cost estimates for the sample jurisdictions from 

Tables 5.1 and 5.2 and the number of building permits issued nationwide in 2004 

(Table 5.4). 

• The disaggregated model used cost estimates for the sample jurisdictions where 

the jurisdictions were grouped by the Census regions and whether they belonged 

to an MSA. These cost estimates are presented in Appendix E – Cost Estimation 

Methods for Sample Jurisdictions and National Costs in Tables E.3 through E.9. 

The disaggregated model used the number of building permits issued for each 

Census region and MSA status in 2004 (Table 5.4). 

4. Weight costs to national level. The final step was to sum the estimates of the regulatory 

cost barriers for each variable to produce two estimates of the national costs of 

excessive regulation, one estimate for the aggregated model and another estimate for 

the disaggregated model. 

Table 5.4 shows the number of building permits issued for SFD dwellings in 2004. The 

aggregated model used the estimate of approximately 1.6 million building permits issued for 

SFD dwellings in the United States. The disaggregated model used the estimates of the number 

of building permits issued for SFD dwellings in each of the Census regions and MSA status. 

NAHB Research Center 5-11 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

Table 5.4: Number of Building Permits Issued for Single-Family Detached Dwellings 

in the United States and Each Census Region and MSA Status, 2004 

2004 

Building 

Region and MSA status permits 

U.S. 1,613,445 

Northeast MSA 102,571 

Northeast non-MSA 29,187 

Midwest MSA 240,241 

Midwest non-MSA 55,281 

South MSA 665,526 

South non-MSA 90,613 

West MSA 384,627 

West non-MSA 45,399 

Source: U.S. Census of Construction, 2006 

The following example shows how these steps were applied to determine national costs of 

regulatory cost barriers for lot size using the aggregated model. 

1. The cost analysis provided the following information about lot sizes from the sample 

jurisdictions—65 percent of jurisdictions had regulatory barriers for lot size (Table 5.1), 

and the mean regulatory cost barrier for lot size regulation was $11,963 per dwelling 

unit (Table 5.2) 

2. Table 3.4 shows that approximately 1.6 million building permits were issued for SFD 

dwelling units in the United States in 2004. 

3. The regulatory cost barrier for lot size was calculated in the following way—the percent 

of jurisdictions with excessive lot size regulation (65%) was multiplied by the number of 

building permits issued for the nation in 2004 (1,613,445 dwelling units). The result 

(1,048,739 dwelling units with regulatory cost barriers for lot size) was multiplied by the 

mean regulatory cost barrier for lot size regulation from the sample ($11,963 per 

dwelling unit). The result was that the regulatory cost barrier for regulation of lot sizes 

was approximately $12.5 billion nationwide in 2004. 

4. This process was repeated for the other eight variables to produce national estimates of 

the regulatory cost barrier for each variable. These costs were added to produce a 

national estimate of the regulatory cost barriers of the land use standards considered in 

this study of approximately $19.2 billion. 

The process for estimating the costs of excessive regulation for the disaggregated model was 

very similar to the process presented above. The difference is that the disaggregated model 

used the information presented in Tables E-3 through E-9 in Appendix E to create cost 

estimates for each Census region and MSA status. 

NAHB Research Center 5-12 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

5.2.2 Results 

Table 5.5 shows the results of the aggregated model of the regulatory cost barriers for the 

nation. The national estimate of regulatory cost barriers for land and site development 

regulations was $19.2 billion for 2004. 

The variables with the largest proportion of excessive costs were lot size, floor area, and lot 

width. The average regulatory cost barriers for one dwelling unit was $11,910. This is equal to 

the mean cost per dwelling unit for regulatory cost barriers ($13,142), multiplied by the percent 

of jurisdictions in the sample that exceeded any benchmark standards (91%). In comparison 

with the average cost for a new single-family dwelling in the United States in 2004, which was 

$244,000, the average per-unit regulatory cost barrier is approximately 5 percent of that 

average selling price. 

Table 5.5: Aggregated Model Estimates of the Regulatory Cost Barriers for All Building Permits 

Issued for Detached Single-Family Dwelling Units in the Nation, 2004 

Aggregated model Cost estimates 

National cost of excessive regulation $ 19,215,338,860 

Lot size $ 12,552,280,392 

Lot width $ 1,811,355,507 

Front setbacks $ 797,956,481 

Floor area $ 3,291,995,430 

Pavement $ 223,586,056 

Sidewalk $ 216,734,720 

Sidewalk width $ 50,334,294 

Off-street parking $ 76,312,500 

Open space $ 194,783,479 

Per single family dwelling unit $ 11,910 

 Source: ECONorthwest, 2006 

Table 5.6 shows the estimate of regulatory cost barriers for the disaggregated model. The total 

cost of regulatory cost barriers for the nation according to the disaggregated estimate was 

about $14.6 billion for 2004. 

In this model, the variables with the largest proportion of excessive costs were lot size, lot 

width, and front setbacks. The average regulatory cost barriers for one dwelling unit was 

$9,051. 

NAHB Research Center 5-13 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

Table 5.6: Disaggregated Model Estimates of Regulatory Cost Barriers for All Building Permits 

Issued for Single-Family Dwelling Units in the Nation, 2004 

Disaggregated model Cost estimates 

National cost of excessive regulation $ 14,603,018,827 

Lot size $ 11,137,670,615 

Lot width $ 1,551,371,592 

Front setbacks $ 743,335,966 

Floor area $ 872,800,196 

Pavement $ 96,777,852 

Sidewalk $ 36,107,707 

Sidewalk width $ 21,564,900 

Off-street parking $ 73,915,367 

Open space $ 69,474,632 

Per single family dwelling unit $ 9,051 

Source: ECONorthwest, 2006 

The cost estimates for the aggregated model are higher than for the disaggregated model 

because the aggregated model costs did not take into account variations in the regulatory cost 

barriers among the regions and MSA status. The aggregated model used the same mean cost 

estimate for each variable for all Census regions and for both MSAs and non-MSAs. The 

disaggregated model took these variations into account, which resulted in lower estimates of 

the cost of excessive regulation. 

Table 5.2 shows the mean costs of excessive regulation per dwelling unit for each variable, 

which were used in the aggregated model. The cost estimates used in the disaggregated model 

are shown in Appendix E Table E-8 and are separated by region and MSA status. The mean and 

median regulatory cost barriers for each variable differed between the aggregated and 

disaggregated models. Some instances of these variations are illustrated below. 

• Differences in assumptions about excessive floor area requirements accounted for more 

than half of the difference in total costs between the aggregated and disaggregated models. 

The aggregated model estimated that the mean regulatory cost barrier for regulation of 

floor area was $26,581 and that 8 percent of jurisdictions exceeded the benchmark for 

floor area requirements (Tables 6.1 and 6.2). In Appendix E, Table E-11 shows that these 

assumptions resulted in a total regulatory cost barrier for floor area regulation of about 

$3.3 billion for the nation in 2004. In contrast, in the disaggregated model nearly all the 

jurisdictions with excessive floor area requirements were located within an MSA. The 

frequency of excessive floor area requirements within an MSA ranged between a high of 16 

percent of jurisdictions in the South, to a low of 6 percent of jurisdictions in the West 

(Appendix E, Table E-6). The disaggregated model used mean regulatory cost barriers for 

floor area requirements of between $35,175 per dwelling unit in the Northeast to $16,425 

per dwelling unit in the Midwest (Appendix E, Table E-8). Table E-13 shows that the total 

regulatory cost barrier for floor area from these assumptions was about $872 million for 

the nation in 2004. 

NAHB Research Center 5-14 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

• Differences in lot size assumptions accounted for nearly one-third of the cost differences 

between the aggregated and disaggregated models. Table 5.2 shows that the mean 

regulatory cost barrier for lot size requirements for all jurisdictions in the sample was 

$11,963. Table E-8 in Appendix E shows that the mean cost of excessive regulation of lot 

size varied across regions and whether the jurisdiction belonged to an MSA. For instance, 

jurisdictions in the sample located outside an MSA in the South had a mean regulatory cost 

barrier for lot size of $4,488 per dwelling unit. Jurisdictions located in the Midwest within 

an MSA had mean regulatory cost barrier for lot size of $16,425. These differences were 

caused by differences in the cost of land between the regions and differences in the degree 

of variance from the benchmarks between regions. The aggregated model does not allow 

for these types of variations in costs and requirements, resulting in greater estimates of the 

regulatory cost barriers for lot size requirements. The regulatory barrier estimate for lot 

size requirements for the disaggregated model was $11.1 billion as compared with $12.5 

billion for the aggregated model. 

5.2.3 Sensitivity Analysis 

The research team performed the same sensitivity analysis on the national models of the 

regulatory cost barriers as it performed on the cost analysis for the sample jurisdictions. The 

team used the smallest and largest benchmark values to get an idea of what the range of 

national regulatory cost barriers might be. 

Table 5.7 shows the results of the sensitivity analysis. For the aggregate model, the total 

national regulatory cost barrier using the study benchmark values was $19.2 billion for 2004. 

With the smallest benchmarks, this rose to $36.9 billion in 2004. Using the largest benchmark 

values, it dropped to $8 billion for 2004. 

For the disaggregated model, the total national regulatory cost barrier using the study 

benchmark values was $14.6 billion for 2004. With the smallest benchmarks, it rose to $24.6 

billion in 2004. Using the largest benchmarks, the total national regulatory cost barrier estimate 

dropped to $6.6 billion for 2004. 

Table 5.7: Results of Sensitivity Tests of the Aggregated and Disaggregated Models 

of the National Regulatory Cost Barrier Estimates, 2004 

Study Smallest Largest 

benchmarks benchmarks benchmarks 

Aggregated model $ 19,215,338,860 $ 36,879,271,157 $ 8,852,653,304 

Disaggregated model $ 14,603,018,827 $ 24,665,695,261 $ 6,622,266,833 

NAHB Research Center 5-15 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

5.3 Key Findings and Conclusions 

• The average cost of excessive regulation for one dwelling unit was about 5 

percent of the average cost of a new home. For the land development standards 

studied by the research team, the average regulatory cost barrier for one dwelling unit was 

$11,910. This is equal to the mean cost per dwelling unit for excess regulatory costs 

($13,142), multiplied by the percent of jurisdictions in the sample that exceeded any 

benchmark standards (91%). In comparison with the average cost for a new single-family 

dwelling in the United States in 2004 ($244,000), the average per-unit regulatory cost 

barrier is 4.8 percent of that average selling price. 

• The regulatory cost barriers varied. The regulatory cost barriers varied considerably 

in the sample jurisdictions, as well as across regions and MSA status. Assuming that the 

sample is representative of all jurisdictions in the nation, the national regulatory cost 

barriers should vary by region and whether the jurisdiction is part of an MSA. 

It is probable that the regulatory cost barriers also vary substantially within the U.S. Census 

regions. For instance, the cost of land often varies within a single metropolitan area, which 

would produce variation in the cost of excessive regulation within the metropolitan area. 

The actual regulatory cost barrier for any given jurisdiction depends on local regulations and 

costs of development. 

• The estimates of the regulatory cost barriers varied with changes in the 

benchmarks but they remained within an order of magnitude of the estimates. 

The sensitivity analysis showed that the costs for the sample jurisdiction and national 

models of the regulatory cost barriers varied substantially depending on the benchmark 

values. However, the changes in either direction were neither twice nor one-half of the cost 

estimates. In other words, the actual regulatory cost barriers may be somewhat more or 

less than the estimates but the actual costs are relatively close to the estimates. 

• The disaggregated model provided the best national estimate of the regulatory 

cost barriers. The disaggregated model accounted for variations in regulatory standards 

and costs among the Census regions and MSA status better than the aggregated model. The 

total mean regulatory cost barriers for land and site development standards in the 

disaggregated model was about $14.6 billion for the nation in 2004. 

NAHB Research Center 5-16 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

• The $14.6 billion estimate of the national regulatory cost barriers is a 

conservative estimate. Given the results of the study, the research team believes this 

estimate is conservative for several reasons. In the survey of regulatory standards, where 

there were multiple zoning districts in a jurisdiction, the team examined the residential 

zoning district that allowed the densest development. Where multiple zoning districts were 

present in a jurisdiction, the team collected data for the "border" zoning districts which 

were the densest zoned districts that allowed detached single-family dwellings. These 

border zones are generally located between high-density (apartments, townhouses) and 

medium-density single-family detached residential development. If the researchers had 

examined all zoning districts for every jurisdiction in the sample (which was impractical), 

greater levels of regulatory cost barriers may have been found. In the medium-density 

residential zoned districts adjacent to the border zones, required minimum lot areas are 

generally larger than in the border zones; hence the regulatory cost barriers due to 

required lot sizes greater than the benchmark lot areas would have been larger if these 

medium-density residential zoned districts had been included in the regulatory cost barrier 

analysis. 

The estimates of costs associated with the variables were relatively conservative. The cost 

assumption for floor area was $75 per square foot. This is highly dependent on the quality 

of the construction and the architectural and interior design features of the house. This cost 

was an average estimate for “economy” and “average” grade of construction for homes 

built with slab-on-grade foundations. If a jurisdiction requires expensive architectural details 

within its building code standards, the additional unit cost of floor area construction could 

result in considerably higher costs for excessive regulation of floor area. Of single-family 

detached homes sold nationwide in 2005, 31 percent had costs (exclusive of the lot cost) of 

less than $70 per square foot; 14 percent had costs in the range $70 to $80 per square xxix foot; and 56 percent had costs of greater than $80 per square foot.

In reality, land costs may vary substantially on a neighborhood-to-neighborhood level in 

some areas. Compared with the “average” communities within a U.S. Census region, the 

communities within that Census region that have higher than average land costs may also be 

experiencing higher than average rates of new construction starts. In this case, regulatory 

cost barriers based on average land costs and total housing construction starts for the 

Census region may underestimate the actual regulatory cost barriers due to lot size 

requirements within that region. 

NAHB Research Center 5-17 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

6. CCoonncclluussiioonnss

Residential land developers and home builders recognize that excessive requirements for lot

xxx xxxi size and lot width add significantly to the cost of the finished dwelling.

The costs to the developer, to the builder, and ultimately to the homebuyer, for lots and 

dwellings using smaller lot widths and smaller lot areas will be significantly lower than for 

dwellings developed on larger lots. 

When a land planning jurisdiction has adopted land and site development standards which are 

larger than the set of minimum benchmark land development standards intended for protection 

of safety and public health, a significant regulatory cost barrier may be imposed on new 

residential single-family detached dwellings. There are added costs for the land development 

standards greater than the benchmark standards and there may also be benefits associated with 

those higher standards. The question of whether the added benefits are commensurate with 

the added costs is dependent upon many considerations. The evaluation of whether some of 

the benefits may be commensurate with the costs is an area that merits considerable 

investigation but is outside the scope of the present study. 

For those jurisdictions with one or more regulatory cost barriers for land development 

standards, the mean per-housing-unit regulatory cost barrier is approx $12,000. Of all the 

planning jurisdictions in the nation, approximately 91 percent have one or more regulatory cost 

barriers for land development standards. The mean regulatory cost barrier for jurisdictions 

with a barrier, multiplied by the percentage of all jurisdictions that have one or more barriers, 

equals the average regulatory cost barrier for all planning jurisdictions. On a national average 

basis, the estimate for this regulatory cost barrier for the 1.6 million new SFD housing units 

constructed in the United States in 2004 is approximately $11,000. 

The research team’s estimate of the regulatory cost barrier due to land and site development 

standards imposed by planning jurisdictions is based on the “disaggregated” national regulatory 

cost barrier model, which accounts for differences between U.S. Census regions and between 

MSAs and non-MSAs. To the extent that the increased cost of new dwellings also raises the 

costs for existing dwellings or for existing vacant buildable lots,xxxii there are additional cost 

barriers, not quantified in this study, due to the influence of new housing prices on existing lot 

prices in the same general area. 

In order for HUD’s policies to have greatest impact on the reduction of regulatory cost 

barriers associated with land and site development standards, effort should focus on the most 

significant land and site development standards listed below in order of cost on a national basis: 

NAHB Research Center 6-1 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

• Lot size 

• Interior square foot floor area 

• Lot width 

The other site and land development standards evaluated in the study had relatively small cost 

barriers in comparison with these three. 

Local advocates for reduction in regulatory cost barriers may wish to use the regulatory barrier 

costing tool described in section 4.2.1.1 and presented in Appendix G to determine the 

regulatory cost barriers that apply in specific locations. This calculation would be based on local 

land costs and on the land development standards adopted by the local land planning 

jurisdiction or jurisdictions. 

Based on the research team’s focus group evaluation of procedural barriers to the land 

subdivision process, presented as Appendices 3 and 4, the three main procedural barriers 

resulting in increased costs to residential land developers which are passed on to builders and 

ultimately to homebuyers are: 

• Local anti-growth political climate 

• Inefficiency in the application process by large numbers of government review agencies 

• Critical infrastructure deficiency in rural areas 

Recently, the U.S. Department of Housing and Urban Development awarded 14 communities 

with the Robert L Woodson, Jr. Award for reducing burdensome regulations that unnecessarily 

inflate the cost of homes (NAHB, 2006, d). Specific noted reasons for the award that are 

consistent with the results of this study generally fall into the following categories: 

• Reduction in land cost to the developer 

• Reduction in the site and land development standards, leading to lower infrastructure costs 

for development of lots and for the construction of dwellings 

• Reduction in time and costs to the developer for obtaining the required permits from a 

range of municipal land development authorities 

The actions by these communities should be considered in other communities seeking to 

reduce regulatory cost barriers within the subdivision rules and zoning ordinances. 

NAHB Research Center 6-2 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

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Study of Subdivision Requirements as a Regulatory Barrier 

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Seattle Washington Department of Public Works (2005) Seattle Street Edge Alternatives 

website 

http://www.ci.seattle.wa.us/util/About_SPU/Drainage_&_Sewer_System/Natural_Drainage_Syst

ems/Street_Edge_Alternatives/index.asp. 

NAHB Research Center 7-2 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

Planning Advisory Service, 2004. Codifying New Urbanism. Chicago, IL: American Planning 

Association, report no 526. 

Planning Advisory Service, 1998. Principles of Smart Development. Chicago, IL: American 

Planning Association, report no 479. 

Schuetz, M. and White, S., 1992. Identifying and Mitigating Local Regulatory Barriers to 

Affordable Housing in Waukesha County, Wisconsin. Working paper for Urban Research 

Center, University of Wisconsin-Milwaukee. Available online: 

http://www.huduser.org/rbc/docs/milwaukee071102.pdf 

Transportation and Growth Management Program, 1999. Model development code and user’s 

guide for small cities. Salem, OR: Oregon Department of Transportation. Available online: 

http://www.oregon.gov/lcd/tgm/docs/model_dev.zip 

U.S. President’s Committee on Urban Housing, 1968. A decent home: the report of the 

President’s Committee on Urban Housing. Washington, DC: Govt. Printing Office. 

Weitz, S., 1982. Affordable Housing: How Local Regulatory Improvements Can Help. Product 

of the Joint Venture for Affordable Housing. Washington, DC: U.S. Department of Housing and 

Urban Development, Office of Policy Development and Research, September 1982. 

NAHB Research Center 7-3 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

8. EEnnddnnootteess

i

 Regulatory Barriers Clearinghouse P.O. Box 23268 Washington, DC 20026-3268 available 

online: http://www.huduser.org/rbc/ 

ii Myths and Facts About Affordable and High Density Housing, California Planning Roundtable, 

downloaded from http://www.abag.ca.gov/services/finance/fan/housingmyths2.htm 

iii Ibid 

iv U.S. Department of Housing and Urban Development NOTICE PDR-2006-01 

downloaded from http://www.huduser.org/datasets/il/il06/MedianNotice_2006.pdf 

v

 “It's a relatively simple formula -- developer builders are ’for profit‘ entities and each dollar 

added to construction goes right back into the cost of the home. The ability to manage/reduce 

construction costs by increasing efficiency will result in lower home pricing. Reducing 

processing times ultimately reduces the carrying costs associated with projects. Locally, 

processing times for some municipalities have almost doubled in the past five years. Quick math 

would indicate that a year longer in processing theoretically adds ~$2,250 per home in carrying 

costs (purchase 40 acres @ $150k = $6m; at 6 percent assume $360,000 in annual interest 

charges incurred; assuming 4 units per acre yields 160 homes; $360,000 interest/160 homes = 

$2,250).” Personal Communication, Mike Brilz, VP of Planning and Development, Pulte Homes, 

West Valley Division, Scottsdale AZ, March 14 2006 

vi US Department of Housing and Urban Development Proposed Model land Development 

Standards and Accompanying Model State Enabling Legislation, 1993 edition, p. 1. 

vii Freilich and Schultz (1995), Model Subdivision Regulations: Planning and Law; Knoxville-Knox 

County Minimum Subdivision Regulations (2004); Proposed Model Land Development Standards and 

Accompanying Model State Enabling Legislation (1993), written by the NAHB Research Center for 

the U.S. Department of Housing and Urban Development;; Smart Neighborhoods: Managing 

Maryland’s Growth (2001), and Oregon’s model code, Model Development Code and User’s Guide 

for Small Cities (1999); American Planning Association’s (APA) Principles of Smart Development 

(1998); APA’s Codifying New Urbanism (2004); Nelson et al (2002), The Link Between Growth 

Management and Housing Affordability: The Academic Evidence;; 

viii The U.S. Census groups states by region in two ways. One grouping method is by four 

regions, which include: the Northeast, Midwest, South, and West. The other grouping method 

divides the four regions into nine divisions, which include: New England, Middle Atlantic, South 

Atlantic, East South Atlantic, West South Central, East North Central, West North Central, 

Mountain, and Pacific. This study uses the four regions to group states. 

NAHB Research Center 8-1 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

ix The research team created four quartiles for population of jurisdictions within the sample. 

Each quartile is comprised of 25 percent of the jurisdictions in the sample 

x The U.S. Census of Construction for 2004 lists the median lot size in the West census sub 

region as 7000 sq feet. 

xi The U.S. census of Construction for 2004 lists the median lot size in the New England sub 

region as 22,000 sq. feet. 

xii U.S. Census of Construction for 2005. Downloaded from 

http://www.census.gov/const/C25Ann/lotsizesolddetpr.pdf 

xiii HUD’s Affordable Housing Design Advisor Web site http://www.designadvisor.org/ 

xiv Design Centre for Sustainability at UBC downloaded from 

http://www.sgog.bc.ca/uplo/Sq1Housing.pdf 

xv Ibid 

xvi U.S. Census of Construction Survey for 2005, Median and Average Square Feet of Floor 

Area in New One-Family Houses Completed by Location: Built For Sale. Downloaded from 

http://www.census.gov/const/C25Ann/sfforsalemedavgsqft.pdf 

xvii U.S. Census of Construction Survey for 2005: Interior floor areas. Downloaded from 

http://www.census.gov/const/C25Ann/soldsqftdetach.pdf 

xviii The details on the land cost estimation is given in the Appendix B. The details on the 

assumptions used with the RS Means costing approach is given in Appendix B. The details on 

the unit costs for infrastructure elements are given in the Appendix B and in Excel spreadsheet 

“Current cost analysis.” Appendix F. Summaries for all land and site development standards are 

given in the “cost” tab. Details for each land or site development standard given in the 

worksheet labeled as that standard. 

xixDiscussions with potential local user groups such as Home Builder Associations are needed 

to verify that there is interest in using the tool to obtain estimates of regulatory cost barriers 

for a relatively well defined geographic area. 

The research team is evaluating possible funding mechanisms for the verification and 

deployment of this tool. Possible steps that would need to be taken for verification include: 

 a) one or more local user groups supplies the local land cost information and possibly local 

infrastructure cost factors; b) the tool computes the regulatory cost barriers associated with 

NAHB Research Center 8-2 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

land and infrastructure and provides the results in a simple report format; c) the local user 

evaluates the utility of the report format and provides feedback for modification if necessary 

xx 1 story economy grade - 1200 square foot structure $70.25; 1800 square foot structure 

$61.50; 2 story average quality grade 1800 square foot structure $85.03; 2,000 square foot 

average grade structure $81.63 from 2005 RS Means Residential Construction costs. see 

Appendix B Unit Cost Estimates 

xxi U.S. Census of Construction data for price of housing per square foot. Downloaded from 

http://www.census.gov/const/C25Ann/soldpricesqftdetach.pdf 

xxii U.S. Census of Construction data for median cost of construction per square foot. 

Downloaded from http://www.census.gov/const/C25Ann/soldmedavgppsfdetach.pdf 

xxiii See Appendix B; detailed formula given in “Lot Width” worksheet in Subdivision 

Requirements as a Regulatory Barrier to Affordable Housing ; Cost Analysis Workbook, 

Appendix F 

xxiv See Appendix 3.3; detailed formula given in “Pavement Width” worksheet in Subdivision 

Requirements as a Regulatory Barrier to Affordable Housing current cost analysis 0329.xls ; 

xxv See Appendix 3.3; detailed formula given in “Front Setback” worksheet in Subdivision 

Requirements as a Regulatory Barrier to Affordable Housing current cost analysis 0329.xls; 

xxvi

 If the benchmark was larger than a jurisdiction’s minimum requirement for a variable, the 

result of Step 6 would be a negative cost. In other words, the jurisdiction’s requirements 

allowed for less expensive development than the benchmark. We excluded negative costs from 

our calculations because the focus on the study was the costs of excessive regulation. 

xxvii This figure includes all permits issued for single-family dwellings in 2004. This includes 

dwellings on lots in subdivisions and other dwellings. The Census Bureau’s Current 

Construction Reports, the data source used for building permits, does not distinguish between 

single-family permits issued in subdivisions and other permits. 

xxviii The cost analysis included calculation of the mean and median cost of regulatory cost 

barriers for each variable. In creating the national estimate of the cost of excessive regulation, 

we used the mean cost estimates. The mean cost estimates provide a better estimate of 

regulatory cost barriers because mean cost estimates use the average costs, rather than the 

mid-point costs. In other words, the mean cost estimates reflect the total aggregate regulatory 

cost barriers for all jurisdictions divided by the number of jurisdictions with one or more 

regulatory cost barrier. 

xxix U.S. Census of Construction 2006, New Detached One-Family Housing Units Sold by Price 

per Square Foot, downloaded from 

http://www.census.gov/const/C25Ann/soldpricesqftdetach.pdf 

NAHB Research Center 8-3 April 2007 
Study of Subdivision Requirements as a Regulatory Barrier 

xxx “On the development side, some municipalities locally are starting to require minimum lot 

sizes (i.e., no lots less than 60 feet wide). This type of ordinance will likely eliminate entry level 

housing, as land costs are ~25 percent of a house cost -- the ability to efficiently use the land 

over a few more lots reduces the overall cost per home.” (Brilz, 2006) 

xxxi According to Denver land planner David Clinger, as quoted a recent issue of Land 

Development Magazine (NAHB 2006, a) “Some cities realize that four to the acre zoning prices 

their own employees out of homeownership.” Using non rectangular lot geometries and 

alternating wider and narrower lot street frontages known as “keyhole” or “zipper” type lot 

design, as well as judicious use of side yard use easements and creative landscaping and privacy 

fences, a wide range of award-wining designs have been developed for SFD homes at 7 to 10 

units per acre (NAHB, 2006, b) 

xxxii According to a King County Washington news release in Dec 2000, “The average cost of 

vacant urban land as a proportion of the average price of a new home has remained nearly the 

same over the last 20 years.“ downloaded from 

http://www.metrokc.gov/exec/news/2000/121300.htm 

NAHB Research Center 8-4 April 2007 
Appendix A 

 Survey of Regulatory 

Standards 

A-1
Summary 

This report presents a statistical analysis of regulatory data gathered from subdivision and 

zoning ordinances for the national Study of Subdivision Requirements as a Regulatory Barrier to 

Affordable Housing. It serves as a technical appendix to the main report that discusses the 

implications of regulation on housing cost in the U.S. 

The broader purpose of this study is to explore the connection between subdivision and 

zoning regulations and housing prices. The approach of the study is to investigate regulatory 

standards and requirements that raise the cost of residential development. This is done by 

examining regulatory standards that lend themselves to direct measurement and analysis of 

their cost implications. 

The project has several distinct parts: (1) conducting review of literature available about the 

topic; (2) choosing regulatory variables and collecting data on them for a nationwide 

representative sample of jurisdictions; (3) determining excessive values for the variables and 

determining the associated costs; and (4) assessing the administrative and processing costs of 

the regulations. 

This report documents the second part of the study: data collection for specific variables 

for a national sample of jurisdictions. The core of the report is a descriptive analysis of the 14 

variables included as part of the sample. The report presents the sampling methods and 

procedures for collecting the data. 

METHODS 

SAMPLING METHODS 

This report is based on a sample of 469 local governments in the U.S. that have the 

authority to adopt land use regulations. The sampling challenge was to develop a methodology 

that resulted in a random sample that is representative of the population. The objective was to 

develop a sample that was (1) geographically representative of jurisdictions across the nation, 

(2) reflected the national distribution of population (including jurisdiction size), (3) reflected 

both fast and slow growing jurisdictions, and (4) represented a range of government types. 

The methodology we used to draw the sample weighted the sample by population in states 

(e.g., the number of samples for each state is proportional to its population) and then by 

amount of population growth in each local government between 1996 and 2000. This 

methodology placed emphasis on the amount of population in each state, and ensured that both 

fast and slow growing governments were represented. 

The sampling methodology originally intended to examine subdivision ordinances from 

1,100 jurisdictions. When the Project Team began evaluating which standards to measure, we 

found that many of the relevant standards were in zoning ordinances, rather than subdivision 

ordinances. After consultation with HUD, the Project Team decided to review zoning 

ordinances and subdivision ordinances and to reduce the sample size to 500 jurisdictions to 

reflect the increased work of gathering data from multiple ordinances. We chose the smaller 

sample of 500 jurisdictions from the previous sample of 1,100 jurisdictions. In cases where the 

Appendix A: Statistical Analysis of Regulations A-2
ordinances could not be obtained from the jurisdiction, we used a substitution method to 

choose a different jurisdiction. 

Analysis of the sample jurisdictions performed after data collection was completed showed 

that the sample is roughly representative of each state by population and geography. 

Jurisdictions in the sample represent 26% of the entire U.S. population. 

ORDINANCE REVIEW PROCEDURES 

Ordinance review consisted of five steps. 

1. Choose the residential district to review. The first step in ordinance review was choosing 

the correct residential district to review. This step was the most critical step in 

ordinance review. The methods for choosing the zoning district are presented below. 

2. Gather data from the zoning ordinance. The following information was generally found in 

the section of the ordinance that described the chosen zoning district: lot width, lot 

size, floor area, and setbacks. The zoning ordinance often contained landscaping 

requirements and off-street requirements. 

3. Gather data from the subdivision ordinance. The following standards were generally found 

in the design standards section of the subdivision ordinance: sidewalk requirements, 

street width standards, open space requirements, and curb and gutter requirements. 

Some jurisdictions included landscaping or off-street parking requirements in the 

subdivision ordinance. 

4. Search both ordinances for missing standards. When researchers did not find standards in 

the usual ordinance, they searched the other ordinance for the standards. For example, 

if landscaping standards were not found in the subdivision ordinance, the researcher 

searched the zoning ordinance for landscaping standards for the chosen zoning district. 

5. Gather administrative data. The final step was to gather administrative data about the 

ordinances, such as the last date the ordinance was updated and the type of update. 

METHODS FOR CHOOSING ZONING DISTRICTS 

Zoning ordinances presented some inherent challenges to analysis of the variables. A typical 

zoning ordinance has three or more residential districts. The Project Team quickly concluded 

that reviewing every residential district for each jurisdiction in the sample would be infeasible. 

Thus, we developed a protocol for gathering standards that significantly reduced the data 

collection effort. 

We focused our attention on the "border" zone between low-density single-family 

development and high-density multifamily development. These “border” zones typically had 

smaller minimum regulations for lot size and other lot dimension variables than other singlefamily zones. We focused on this zone because it presents a greater opportunity for 

development of affordable housing than zones that require larger lot sizes. 

We chose the "border" zone based on the following characteristics: it permitted detached 

single-family houses outright; it had the smallest minimum lot size and setbacks; and (where 

Appendix A: Statistical Analysis of Regulations A-3
Appendix A: Statistical Analysis of Regulations A-4

applicable) it allowed a mixture of detached single-family houses and duplexes or multifamily 

housing. In cases where it was unclear which zone to choose after evaluating these 

characteristics, we always chose the zone with the smallest minimum lot size where detached 

single-family homes are permitted outright. 

ANALYTICAL APPROACH 

The analytical approach focused on two types of statistical analysis: (1) basic descriptive 

analysis; and (2) means testing. The basic descriptive analysis consisted of the following 

statistics: mean, median, mode, frequencies, range, and standard deviation. The means testing 

used chi-square and ANOVA with post-hoc testing to determine if the variables varied 

significantly by class membership within subcomponents of the sample including government 

type, census region, membership in a Metropolitan Statistical Area (MSA), central city, and 

population quartiles. These tests showed whether and how the variables differed by these 

subcomponents and which differences were significant. 

SUMMARY OF FINDINGS

Table 1 provides a summary of descriptive statistics for the variables reviewed in the study. 

The findings for each variable are discussed below. 

Table 1. Summary of descriptive statistics of the variables reviewed 

N Mean Median Mode

Standard 

Deviation Minimum Maximum

Minimum lot size (square feet) 419 9924 6,000 5000 16,946 750 217,800

Minimum lot width (linear feet) 342 61.92 60 50 25 20 250

Minimum front setbacks (linear feet) 413 25.15 25 25 13 0 100

Minimum side setbacks (linear feet) 417 8.257 8 5 5 0 30

Minimum rear setbacks (linear feet) 404 20.55 20 25 9 0 65

Minimum floor area (square feet) 86 1060 1,000 1000 359 500 2,500

Minimum off-street parking spaces 367 1.878 2 2 1 0 4

Minimum open space requirements

Percent of total land in subdivision 47 13.1 10 10 9 3 50

Number of square feet per dwelling unit 18 1562 795 871 3,447 310 15,246

Number of square feet per person 34 229.4 218 218 112 87 436

Minimum sidewalk width (linear feet) 153 4.487 4 4 1 3 10

Minimum planting strip width (linear feet) 37 4.608 5 5 1 2 8

Minimum street pavement width (linear feet) 192 27.81 28 30 6 16 45

Minimum street right-of-way width (linear feet) 262 52.24 50 50 8 20 80

Source: Survey of Regulatory Standards, CPW 2006 

Most of the 469 jurisdictions reviewed had zoning and subdivision ordinances. 

Eighty-three percent of the jurisdictions had both zoning and subdivision ordinances. Six 

percent of jurisdictions only had zoning ordinances, 4% of jurisdictions only had subdivision 

ordinances, and 6% of jurisdictions had neither ordinance. The jurisdictions with neither 

ordinance were included in the study to represent jurisdictions with less regulation. 

Lot size requirements were highly variable among jurisdictions. The smallest 

minimum lot size in the study was 750 square feet and the largest was 217,800 square feet (5 

acres). Forty-one percent of the jurisdictions in the sample had minimum lot sizes between 

5,000 and 6,999 square feet. Statistical testing showed significant differences in lot size 
requirements for each subcomponent of the sample. This indicated that there were 

fundamental differences in minimum lot sizes for each of the subcomponents of the sample. For 

example, there were significant differences in minimum lot sizes for each of the four Census 

regions (one of the subcomponents of the sample), with larger minimum lot sizes in the 

Northeast than in the other three regions. 

Lot widths varied across jurisdictions. The smallest lot width requirement was 20 feet, 

the largest 250 feet, and the median 60 feet. Fifty-five percent of jurisdictions required minimum 

lot widths of 50 to 69 feet. As with lot sizes, statistical testing showed significant differences in 

lot width requirements for each subcomponent of the sample. 

The mean front setback requirement was 25 feet. Fifty-six percent of jurisdictions 

had front setbacks between 20 to 29 feet. Like lot size and width, front setbacks differ in a 

significant way for each subcomponent of the sample. 

The mean side setback requirement was eight feet per side.. Fifty-eight percent of 

jurisdictions required minimum side yard setbacks of between five to nine feet. Side setbacks 

differed in significant ways for each subcomponent of the sample. 

The mean rear setback was 21 feet. The smallest requirement for a rear setback was 

zero feet and the largest was 65 feet. Fifty-five percent of jurisdictions required rear setback of 

between 20 to 29 feet. Rear yard setbacks differed in significant ways for each of the five 

subcomponents of the sample, except for population quartiles. 

Fewer than 20% of jurisdictions had minimum floor area requirements. For these, 

the mean floor area was 1,060 square feet and the median 1,000 square feet. The smallest floor 

area requirement was 500 square feet per dwelling unit and the largest 2,500 square feet. 

More than three-quarters of the jurisdictions required two off-street parking 

spaces. For these, the mean number of off-street parking spaces required per dwelling unit was 

1.88 and the median was 2 parking spaces. Further statistical testing showed that the number of 

off-street parking spaces required differed in a significant way based on population quartile, as 

well as between central cities and non-central cities. 

Fewer than half of the jurisdictions had landscaping standards. Forty-two percent 

of the jurisdictions had landscaping standards specifically for subdivisions or the zoning district 

that we examined for the study. Differences in landscaping requirements were significant for 

the following subcomponents of the sample: Census region, whether the jurisdiction is part of 

an MSA, and population quartile. 

Open space standards show substantial variation. We collected three types of 

requirements for open space: (1) percent of total land in the subdivision, (2) number of square 

feet per dwelling unit, and (3) number of square feet per person. About 20% of the jurisdictions 

in the sample used one of these methods for determining open space requirements. 

Fifty-one percent of jurisdictions explicitly required sidewalks. Twenty-six percent 

of all jurisdictions required sidewalks on both sides of the street. The average sidewalk width 

Appendix A: Statistical Analysis of Regulations A-5
Appendix A: Statistical Analysis of Regulations A-6

was four feet. Requirements for sidewalks varied in a significant way by the following 

subcomponents of the sample: government type, whether the jurisdiction is part of an MSA, and 

the jurisdiction's population. In contrast, sidewalk width requirements did not vary significantly 

based on any of the subcomponents of the sample. 

Relatively few (8%) jurisdictions had requirements for planting strips. The planting 

strip is a landscaped area between the sidewalk and curb. The mean and median planting strip 

width was five feet. 

Curbs and gutters were required by 50% of the jurisdictions in the study. 

The mean and median pavement width for streets was 28 feet. Most jurisdictions' 

standards for pavement width were either 20 to 24 feet wide, 25 to 29 feet wide, or 30 to 34 

feet wide. Pavement width differed in a significant way for each subcomponent of the sample. 

The mean street right-of-way was 52 feet. Fifty-six percent of jurisdictions with rightof-way standards require right-of-ways no smaller than 50 to 54 feet and 24% of jurisdictions 

require right-of-ways at least 60 to 64 feet wide. Street right-of-way requirements varied 

significantly by Census region. 

GENERAL OBSERVATIONS ABOUT DATA COLLECTION AND ANALYSIS

The following section presents observations about the data collection and analysis phases of the 

survey of regulatory standards. 

Most jurisdictions regulated one or more of the variables. Ninety-four percent of 

the jurisdictions in the sample had standards for one or more of the study variables. More than 

three-quarters of the jurisdictions had standards for lot size, front setbacks, and off-street 

parking spaces. About one-fifth of the jurisdictions had standards for open space and floor area. 

The population varied among jurisdictions. The size of jurisdictions within the sample 

varied substantially. They ranged in population from 9.5 million people to 132 people, from 

some of the largest cities and most densely developed counties in the U.S. to small rural towns. 

These differences presented challenges in analyzing the regulatory standards. We addressed 

these challenges by separating the sample into population quartiles and comparing regulatory 

standards among the quartiles. 

Some of the variables had a broad range of values. This indicates that jurisdictions 

are applying a wide range of regulatory standards. The basic statistical analysis showed that 

several of the variables had substantial variation. The following variables had a large range of 

values and large standard deviation compared to their mean: lot size, lot width, front setback, 

side setback, and open space. For example, a rural jurisdiction is likely to have larger minimum 

requirements for lot size and lot width than an urban city. We addressed these differences by 

separating the sample subcomponents and comparing regulatory standards within the 

subcomponent groupings. The subcomponents included government type, census region, 

membership in a Metropolitan Statistical Area (MSA), and central city. 
Introduction 

This report presents a statistical analysis of regulatory data gathered from subdivision and 

zoning ordinances for the national Study of Subdivision Requirements as a Regulatory Barrier to 

Affordable Housing. It serves as a technical appendix to the main report that discusses the 

implications of regulation on housing cost in the U.S. This report begins with an overview of the 

study—the context and the research approach. It then describes characteristics of the sample 

of zoning and subdivision regulations from 469 local governments. The core of the report is a 

descriptive analysis of the 14 variables included as part of the sample. It discusses the 

implications of the sample in the context of the broader study. This report also includes a 

number of appendices that describe the sampling methods and procedures. 

BACKGROUND

This study is designed to assess, on a nationwide scale, the occurrence and magnitude of 

land use controls as regulatory barriers to building affordable housing. To date there is only 

local and regional research available on the topic, much of which is outdated. Prior studies have 

focused on the effect of regulatory barriers to affordable housing from a broad perspective. For 

instance, Not In My Backyard: Removing Barriers to Affordable Housing, published by the President’s 

Advisory Commission in 1991, found that exclusionary, discriminatory, and unnecessary 

regulations were significant barriers to affordable housing. According to that study, these 

barriers deter the development of housing within the means of lower-income, and increasingly 

middle-income “work force” families. 

The regulations that this study focused on are generally found in subdivision and zoning 

ordinances. Subdivision and zoning regulations can increase the cost of housing through setting 

excessive standards for development, such as lot size or street width. Until now, there had 

been no nationwide study that explores the impact of these specific regulations on the 

affordability of housing. 

Subdivision and zoning ordinances are used by jurisdictions to regulate development. The 

ordinances serve different purposes in the development process. 

• Subdivision ordinances regulate the division of land for development, most 

frequently for residential purposes. Subdivision ordinances generally include two types of 

requirements: (1) administrative procedures and requirements for dividing land into smaller lots 

and (2) standards for developing shared infrastructure, such as streets and sidewalks, within the 

area of development. 

• Zoning ordinances regulate development by dividing the jurisdiction into multiple 

zones, based on compatible uses. For example, a jurisdiction may have several different zones 

for residential development, each geared towards different densities of residential development. 

Zoning ordinances include many types of regulation and requirements. This study focuses on 

the requirements found in the densest residential zone that permits development of detached 

single-family housing outright. This zone represents the “border” between multi-family housing 

and low-density single-family housing. The requirements for less land in this zone increase the 

likelihood of affordable housing being developed in this zone because land accounts for a 

substantial share of the costs of residential development. 

Appendix A: Statistical Analysis of Regulations A-7
• The United States Department of Housing and Urban Development (HUD) contracted 

with the National Association of Homebuilders (NAHB) Research Center to conduct this 

study. The NAHB assembled a Project Team to investigate this issue, which included the 

National Center for Smart Growth Research and Education at the University of Maryland and 

ECONorthwest. ECONorthwest contracted with the Community Planning Workshop (CPW) 

to conduct the data collection portion of the study. This technical appendix was written by 

CPW and ECONorthwest. 

PURPOSE

The broader purpose of this study is to explore the connection between subdivision and 

zoning regulations and housing prices. The approach of the study is to investigate regulatory 

standards and requirements that raise the cost of residential development. This is done by 

examining regulatory standards that lend themselves to direct measurement and analysis of 

their cost implications. 

The project has several distinct parts: (1) conducting review of literature available about the 

topic, (2) choosing regulatory variables and collecting data on them for a nationwide 

representative sample of jurisdictions, (3) determining excessive values for the variables and 

determining the associated costs, and (4) assessing the administrative and processing costs of 

the regulations. 

This report documents the second part of the study, data collection for specific variables 

for a national sample of jurisdictions. The report presents the methodology for collecting the 

data, as well as a descriptive analysis of the variables. Specifically this report presents: 

• Protocol and methods used to obtain the data 

• Characteristics of the sample as compared to all jurisdictions in the U.S. 

• Descriptive analysis of each variable included in the study 

• Discussion of deviation among jurisdictions for each variable 

• Comparisons of geographic regions, jurisdiction types, and population for selected 

variables 

MEASURING REGULATORY STANDARDS 

The Project Team worked together to design and execute the data collection portion of the 

study. This part of the study involved the following components: 

• Choosing the variables. This involved creating a list of land use regulatory variables 

that contribute to construction costs and evaluating whether these variables are found in 

subdivision ordinances. During the design phase we found that some of the variables that 

contribute the most to residential development costs are found in zoning ordinances, rather 

than subdivision ordinances. As a result, we chose to expand the study to include these zoning 

standards. This process is summarized in Appendix 1. 

Appendix A: Statistical Analysis of Regulations A-8
• Sampling methodology. One goal of the study was to produce conclusions that can 

be applied to the entire U.S. An essential part of this task was to creating a representative 

nationwide sample of jurisdictions to include in the data collection portion of the study. 

• Collecting ordinances. Ordinance collection was an essential task for the study. 

• Ordinance review. Ordinance review involved locating the variables in either the 

subdivision or zoning ordinance and choosing the minimum values for each variable. We 

focused on regulations impacting development of new single-family detached dwellings, 

especially development in subdivisions. 

• The steps above resulted in a sample of 469 local governments with the authority to 

adopt land use regulations. 

ORGANIZATION OF THE REPORT

The remainder of this report is organized as follows: 

Chapter 2: Characteristics of the sample presents information about the sample, 

including a summary of the sampling methods used to choose jurisdictions, variations among 

ordinances, and comparisons of the sample with all local governments in the U.S. 

Chapter 3: Descriptive analysis of variables from sample jurisdictions presents 

analysis of the variables taken from the ordinances. The analysis includes lot standards, 

landscaping standards, open space standards, and street standards. 

Chapter 4: Observations presents our general observations about the variables and 

study. 

This report also contains an Appendix 1: Choice of review variables summarizes the 

variables used in the project and the reasons for including each variable. 

Appendix A: Statistical Analysis of Regulations A-9
CHARACTERISTICS OF THE SAMPLE 

The Project Team developed a sampling methodology to choose a nationwide 

representative sample of jurisdictions. This chapter contains a description of the sample and the 

methods used to draw the sample. The chapter is separated into the following sections: a 

summary of methods, a comparison of the sample against all jurisdictions in the U.S., and a 

description of the ordinances in the sample. 

SUMMARY OF METHODS

This section provides short summaries of our sampling methods and our the method for 

choosing zoning districts for the study. 

SAMPLING METHODS 

This report is based on a sample of 469 local governments in the U.S. that have the 

authority to adopt land use regulations. The sampling challenge was to develop a methodology 

that resulted in a random sample that is representative of the population. The objective of this 

exercise was to develop a sample that was (1) geographically representative of jurisdictions 

across the nation, (2) reflected the national distribution of population (including jurisdiction 

size), (3) reflected both fast and slow growing jurisdictions, and (4) represented a range of 

government types. 

According to the U.S. Census of Local Governments, 38,966 governmental entities existed 

in 2002 that had the authority to develop and adopt subdivision regulations. These local 

governments represent the population of interest in this study. Further evaluation of the data 

indicates that local governments are far from being evenly distributed through the U.S. 

Moreover, the geographic distribution of local governments is significantly different than the 

geographic distribution of population. Thus, weighting the sample by the number of 

governmental entities would result in a sample that had a much higher proportion of small 

jurisdictions. 

The methodology we used to draw the sample weighted the sample by population in states 

(e.g., the number of samples for each state is proportional to its population) and them by 

amount of population growth in each local government between 1996 and 2000. This 

methodology placed emphasis on the amount of population in each state, and ensured that both 

fast and slow growing governments were represented. 

The sampling methodology originally intended to examine subdivision ordinances from 

1,100 jurisdictions. When the Project Team began evaluating which standards to measure, we 

found that many of the relevant standards were in zoning ordinances, rather than subdivision 

ordinances. After consultation with HUD, the Project Team decided to review zoning 

ordinances and subdivision ordinances and to reduce the sample size to 500 jurisdictions to 

reflect the increased work of gathering data from multiple ordinances. We chose the smaller 

sample of 500 jurisdictions from the previous sample of 1,100 jurisdictions. In cases where the 

ordinances could not be obtained from the jurisdiction, we used a substitution method to 

choose a different jurisdiction. 

By the time we made the decision to reduce the number of jurisdictions in the study, we 

had already pulled a sample of 1,100 jurisdictions. We selected the 500 jurisdictions from the 

Appendix A: Statistical Analysis of Regulations A-10
1,100 jurisdictions. We separated the process of choosing jurisdictions into two parts: (1) we 

chose the two largest jurisdictions in each state to ensure that each state was represented in 

the study and (2) we chose the remaining 400 jurisdictions randomly from the remaining 1,000 

jurisdictions. 

In cases where we were unable to obtain the ordinances from the jurisdiction, we used a 

substitution method to choose a different jurisdiction. In short, we returned to the remainder 

of the sample of 1,100 jurisdictions and chose a new jurisdiction from the same state, with a 

similar size and government type if possible. 

COMPARISON OF THE SAMPLE WITH ALL JURISDICTIONS IN THE U.S. 

A comparison of the jurisdictions included in the sample provides an indication of whether 

the sample is representative of all governments in the U.S. If it is not representative, this 

comparison should show the ways that the sample is not representative. This section includes 

comparisons of the sample against the entire U.S. for the following: jurisdictions by type of 

government, jurisdictions by region, jurisdictions by state based on population, and jurisdictions’ 

population by region. 

It is worth reviewing the sampling priorities since they determined the characteristics of the 

sample. The sample was weighted by the following factors for each jurisdiction: 

1. Population 

2. Growth rate 

3. Geographic representation (each state got at least 2 samples regardless of population) 

 Note that the key weighting criteria did not include the number of local governments. If we 

had used the number of local governments as a weighting criteria, then states such as North 

Dakota that have a lot of local governments would have had many more samples that states like 

California that have far fewer local governments. We focused on jurisdictions’ population and 

growth rate rather than the type of local government because the focus of the study is the cost 

of excessive regulation on new development, which occurs more frequently in areas with more 

population and higher growth rates. 

Table 2-1 shows the total number of each government type in the U.S. and the study 

sample, as well as the percentage differences. The table shows that the study sample overrepresents cities and under-represents townships. To a lesser degree, villages and towns are 

also underrepresented. The main reason that townships, towns, and villages are 

underrepresented in the sample is that our sampling methodology favored geographic diversity 

and population distribution over government type. This finding is consistent with the sampling 

methodology described above. 

Appendix A: Statistical Analysis of Regulations A-11
Table 2-1. Comparison between the number and proportion of the types of 

governments in the United States and the study sample 

Government type Number Percent Number Percent

Borough 1,233 3.2% 7 1.5% -1.7%

Charter Township 126 0.3% 4 0.9% 0.5%

City 10,048 25.8% 258 55.0% 29.2%

City and Borough 3 0.0% 0 0.0% 0.0%

City and County 5 0.0% 3 0.6% 0.6%

City/Parish 2 0.0% 0 0.0% 0.0%

Civil Township 5 0.0% 0 0.0% 0.0%

Consolidated Government 3 0.0% 0 0.0% 0.0%

Corporation 2 0.0% 0 0.0% 0.0%

County 2,963 7.6% 47 10.0% 2.4%

Metropolitan Government 3 0.0% 1 0.2% 0.2%

Municipality 4 0.0% 1 0.2% 0.2%

Parish 60 0.2% 1 0.2% 0.1%

Plantation 35 0.1% 0 0.0% -0.1%

Town 7,973 20.5% 77 16.4% -4.0%

Township 12,759 32.7% 44 9.4% -23.4%

Unified Government 2 0.0% 1 0.2% 0.2%

Urban County Government 1 0.0% 1 0.2% 0.2%

Village 3,740 9.6% 24 5.1% -4.5%

Total 38,967 100.0% 469 100.0% 0.0%

U.S. Study Sample Percent 

difference

Source: U.S. Census and Source: Survey of Regulatory Standards, CPW 2006 

Note: The selection of the jurisdictions is not proportionate between different government types for the U.S. and the sample because 

our sampling methods placed a stronger emphasis on geography and jurisdiction size than government type. 

Table 2-2 shows the number of jurisdictions in each Census region for the entire U.S. and 

the study sample. The South and West make up a higher proportion of jurisdictions in the 

study sample than in the entire U.S. The South has the greatest representation in the sample, 

with 164 jurisdictions. The Northeast has the least representation in the sample, with 84 

jurisdictions. This is proportionate to the region's share of the total number of jurisdictions in 

the U.S. The Midwest has the greatest number of jurisdictions in the U.S. (56%), but its 

representation in the sample is proportionately smaller (23%). The selection of the jurisdictions 

is not proportionate between different regions within the U.S. and the sample because our 

sampling methods placed a stronger emphasis on jurisdiction size than geographic distribution. 

Appendix A: Statistical Analysis of Regulations A-12
Appendix A: Statistical Analysis of Regulations A-13

Table 2-2. Number and percentage of jurisdictions by region 

for the U.S. and the study sample 

Number Percent Number Percent

Northeast 6,440 17% 84 18%

South 7,898 20% 164 35%

Midwest 21,918 56% 109 23%

West 2,710 7% 112 24%

Total 38,966 100% 469 100%

U.S. Sample

Source: U.S. Census and Study of Subdivision Requirements as a 

Regulatory Barrier to Affordable Housing Descriptive Analysis, CPW 2006 

Note: The selection of the jurisdictions is not proportionate between different regions within the U.S. and the sample because our 

sampling methods placed a stronger emphasis on jurisdiction size than geographic distribution. 

The sampling methodology was designed to draw a sample of jurisdictions based on the 

states' populations, proportionate to the U.S. population. The exception was that, to ensure 

geographic diversity, we chose two jurisdictions from each state, regardless of population. 

Proportionate to each state’s population, five states were under-represented by at least three 

jurisdictions in the sample: Florida, New York, Ohio, Pennsylvania, and Texas. One reason for 

this under-representation is the fact that some jurisdictions were not responsive to our 

attempts to obtain their ordinances.1 Another explanation for the under-representation is that 

every state had a minimum of two jurisdictions in the sample, which redistributed jurisdictions 

from states with larger populations to states with small populations. 

Table 2-3 shows the 2000 Census population and percentage by region for the U.S. and the 

study sample. The study sample represents 26% of the entire U.S. population. The region with 

greatest representation by population in the sample is the West, with 39% of the population in 

the sample. Population in the West is over represented in the sample and population in the 

South and Midwest are underrepresented in the sample. One explanation for this discrepancy is 

that six of the thirteen jurisdictions in the sample with greater than 1 million residents are 

located in the West, including Los Angeles County, which has approximately 9.5 million 

residents. 

 

1

 We chose substitute jurisdictions to replace the unresponsive jurisdictions but were unable to contact some of the substitute 

jurisdictions. We stopped substituting jurisdictions near the end of data collection because there was not enough time to obtain 

and review ordinances for additional substitute jurisdictions. 
Table 2-3. Number and percent of population per 

region for the U.S. and the study sample, 2000 

Persons Percent Persons Percent

Northeast 53,594,378 19% 12,843,013 17%

South 100,236,820 36% 19,937,361 27%

Midwest 64,392,776 23% 12,108,851 16%

West 63,197,932 22% 29,163,713 39%

Total 281,421,906 100% 74,052,938 100%

U.S. Sample

Source: U.S. Census and Study of Subdivision Requirements as a Regulatory 

Barrier to Affordable Housing Descriptive Analysis, CPW 2006 

Note: The figures for the sample population in Table 2-3 are approximations because the sample had some instances where a 

county and a jurisdiction within the county were included in the sample. In those cases, we subtracted the population for the 

jurisdiction but counted the rest of the county’s population. 

CHARACTERISTICS OF THE ORDINANCES

The ordinances that we reviewed varied in a number of ways, including: whether the 

jurisdiction had both subdivision and zoning ordinances, the last date the ordinances were 

modified, the type of update, and the media the ordinance was available in. This section 

describes these differences among the ordinances. 

Our sample included 500 jurisdictions, and CPW was able to perform ordinance reviews for 

469 of them. We were unable to obtain ordinances for the remaining 31 jurisdictions, many of 

which were substitute jurisdictions. We chose to stop attempting to collect ordinances towards 

the end of the ordinance review process because it took several weeks to receive the 

requested ordinances. The main problem in obtaining ordinances was that some jurisdictions 

did not have their ordinances available on the Internet and were unresponsive to our attempts 

at contact. 

In some cases, staff at the jurisdictions that we contacted indicated that they did not have a 

subdivision and/or zoning ordinance. We included these jurisdictions in the review because the 

lack of regulation for particular standards could affect housing affordability. 

Table 2-4 shows 83% of the jurisdictions had both ordinances. Six percent of the 

jurisdictions only had a zoning ordinance and 4% of the jurisdictions only had a subdivision 

ordinance. Twenty-seven (6%) had neither a subdivision nor a zoning ordinance. 

Table 2-4. Jurisdictions with ordinances 

Number Percent

Both ordinances 391 83%

Zoning only 30 6%

Subdivision only 21 4%

Neither ordinance 27 6%

Total jurisdictions 469 100%

Source: Survey of Regulatory Standards, CPW 2006 

One indication that the ordinances are frequently used or that there has been development 

activity is the frequency of ordinance updates. Table 2-5 shows the date that the ordinances 

were last updated or adopted. The oldest zoning ordinance in our sample was last updated in 

Appendix A: Statistical Analysis of Regulations A-14
June 1966. The most recently updated zoning ordinance was updated in November 2005. Most 

zoning ordinances in our sample have been updated since April 2003. 

The subdivision ordinances were generally not updated as recently as the zoning 

ordinances. The oldest subdivision ordinance in our sample was updated in January 1950, and 

the most recent update was December 2005. Most subdivision ordinances in our sample have 

been updated since February 2001. 

Table 2-5. Date that the ordinances 

were last updated or adopted 

Date

Zoning ordinances

Date last updated

Oldest June 1966

Most recent November 2005

Mean date December 1999

Median date April 2003

Subdivision ordinances

Date last updated

Oldest January 1950

Most recent December 2005

Mean date April 1997

Median date February 2001

Source: Survey of Regulatory Standards, CPW 2006 

We also collected information about the type of ordinance update. If the ordinance has not 

been updated since adoption, we classified the ordinance as "adopted." If the ordinance had 

been updated since adoption, we classified the ordinance as "amended." In some cases, we were 

unable to determine the type of update and left this data blank. We experienced this problem 

most frequently in cases where the subdivision or zoning ordinances were a part of a larger 

ordinance, such as a unified development code. In these cases, we frequently only had the 

zoning and/or subdivision sections of the larger ordinance and could not determine the data of 

last update and/or the type of update. 

Table 2-6 shows the most recent type of update for the ordinances. Forty-five percent of 

the zoning ordinances in the sample were amended, while 22% were not updated since 

adoption. We were unable to determine the type of update for the remaining 33% of zoning 

ordinances. Thirty-eight percent of the subdivision ordinances were amended and 24% 

remained as adopted. We were unable to determine the type of update for the remaining 37% 

of subdivision ordinances. 

Appendix A: Statistical Analysis of Regulations A-15
Appendix A: Statistical Analysis of Regulations A-16

Table 2-6. Ordinance last update 

Number Percent

% of Total 

Sample

Zoning ordinances

Adopted 101 32% 22%

Amended 211 68% 45%

Total 312 67%

Subdivision ordinances

Adopted 114 39% 24%

Amended 180 61% 38%

Total 294 63%

Source: Survey of Regulatory Standards, CPW 2006 

We collected electronic copies of the ordinances where possible. Table 2-7 shows the type 

of media for each ordinance, either electronic or paper. Of the jurisdictions with a zoning 

ordinance, 77% of the ordinances were available in electronic form and 23% were only available 

in paper form. Of the jurisdictions with a subdivision ordinance, 73% of the ordinances were 

available in electronic form and 27% were only available in paper form. 

Table 2-7. Ordinance media 

Number Percent

% of Total 

Sample

Zoning ordinances

Electronic 326 77% 70%

Paper 95 23% 20%

Total 421 90%

Subdivision ordinances

Electronic 294 73% 63%

Paper 109 27% 23%

Total 403 86%

Source: Survey of Regulatory Standards, CPW 2006 

Note: The total for "% of Total Sample" does not equal 100% because not all jurisdictions in our sample had both ordinances, as

noted previously. 

In summary, the study sample was geographically diverse and represented at least two 

jurisdictions from each state. Cities were over-represented in the sample and villages, towns, 

and townships under-represented. 

The study sample consisted of 469 jurisdictions, 83% of which had both a zoning and 

subdivision ordinance. More than half of the ordinances that gave the data of last update were 

last modified within the last five years. And about three-quarters of ordinances were in 

electronic form. 

One final note: the researchers from the Community Planning Workshop at the University 

of Oregon found it surprisingly difficult and time consuming to obtain and compile ordinances 

for review. The initial hypothesis was that the majority of ordinances would be easy to find online. This was far from the case. Researchers considering such samples in the future are 

encouraged to provide plenty of time and budget for the seemingly simple process of finding 

and obtaining ordinances. In addition, not all ordinances available in electronic format are easy 
Appendix A: Statistical Analysis of Regulations A-17

to work with. CPW found a surprising number of ordinances that were in html or pdf format 

and were published section-by-section, or page by page in separate files. 
Appendix A: Statistical Analysis of Regulations A-18 

Analysis of Variables 

This chapter presents an analysis of the variables collected from zoning and 

subdivision ordinances. It represents the core of this report and the basis for the cost 

estimates that are the overarching objective of this study. The categories of variables in 

this study include: lot standards, landscaping standards, open space standards, sidewalk 

standards, and street standards. 

ANALYTICAL FRAMEWORK

Our analytical approach focused on two types of analysis: (1) basic descriptive 

analysis, and (2) inferential statistics in the form of means testing. The basic descriptive 

analysis consisted of the following statistics: mean, median, mode, frequencies, range, 

and standard deviation. The means testing consisted of using chi-square and ANOVA 

tests. 

The means tests showed statistically significant2 differences among the jurisdictions. 

We separated the jurisdictions by certain characteristics, such as population size or 

whether the jurisdiction belonged to an MSA. These groupings, which represent 

subcomponents of the sample, allowed us to perform the means testing between the 

subcomponents of the sample, rather than the entire sample. This was helpful because 

the types of statistical tests we used work best when there is little variation within the 

sample and the descriptive analysis showed that the data had substantial variation. In 

other words, grouping the jurisdictions by subcomponents created more homogenous 

groups and allowed for comparisons of the standards within the subcomponents. The 

subcomponents included: 

• Government type: We separated government types into six categories: county, 

city, town, township, village, and other government types. We combined counties and 

parishes because there are few parishes, and they serve a similar function as counties. 

We combined all the other government types presented in Table 2-1 because they 

made up less than 3% of the governments in the study. 

• Census region: We grouped states into the four regions used by the U.S. 

Census: Northeast, Midwest, South, and West.3

• Part of an MSA: We grouped jurisdictions by whether they are a part of a 

Metropolitan Statistical Area (MSA), as defined by the U.S. Census. Jurisdictions 

belonging to a MSA are more likely to be located in an area where the population is 

densely distributed. 

 

2

 For the remainder of the chapter, we refer to “statistically significant” results as “significant.” 

3

 The U.S. Census groups states by region in two ways. One grouping method is by four regions, which include: the 

Northeast, Midwest, South, and West. The other grouping method divides the four regions into nine divisions, which 

include: New England, Middle Atlantic, South Atlantic, East South Atlantic, West South Central, East North Central, 

West North Central, Mountain, and Pacific. This study uses the four regions to group states. 

A-18
Appendix A: Statistical Analysis of Regulations A-19 

• Central city: We grouped jurisdictions based on whether they are a central city, 

as defined by the U.S. Census. A central city is the largest city of a Metropolitan Area 

(MA) and is a basis for establishment of an MA. Jurisdictions that are a central city are 

typically more densely populated than jurisdictions that are not a central city. 

• U.S. population: We grouped the sample jurisdictions into quartiles based on 

their populations from the 2000 U.S. Census. The groups were as follows: fewer than 

5,491 people; 5,492 to 25,176 people; 25,177 to 97,268 people, and more than 97,268 

people.4

The means tests allowed us to determine if the variables varied in a significant 

pattern by class membership within certain subcomponents of our sample. In other 

words, the means testing indicated whether sample subcomponents, such as 

government type or Census region, make a difference in the standards that jurisdictions 

establish. For example, the means testing tells whether a variable such as lot size is likely 

to be different if the government is a city or county or if it is located in the east or west, 

etc. We used two forms of means testing: chi-square and ANOVA. 

We performed chi-square tests on each variable using the five subcomponents of 

the sample. The chi-square indicated which variables had significant differences for the 

subcomponents of the sample. It is likely that significant5 differences were caused by 

differences in the variables for the subcomponents. In other words, if the chi-square for 

lot size by government type is significant, then it is likely that lot size varied in a 

significant pattern by government type. 

We then performed an ANOVA with a Bonferroni post-hoc test to identify which 

subcomponents had significant differences. This type of test required subcomponents 

with three or more categories. In our data, qualifying subcomponents included: 

government type, census region, and population. It also required continuous data in the 

variables. Where the chi-square test can indicate a significant difference among all of the 

subcomponents, the ANOVA with a Bonferroni post-hoc test can show the significant 

differences between each of the subcomponents. For example, this test might show that 

lot sizes are statistically different in cities than in counties. 

In cases where we found standards for the variables in fewer than 100 jurisdictions, 

we did not perform any means testing because we had too little data to produce 

meaningful results. 

METHODS FOR CHOOSING ZONING DISTRICTS 

Zoning ordinances presented some inherent challenges to the standards analysis. A 

typical zoning ordinance has three or more residential districts. The Project Team 

quickly concluded that reviewing every residential district for each jurisdiction in the 

 

4

 We created four quartiles for population of jurisdictions within the sample. Each quartile is comprised of 25% of the 

jurisdictions in the sample. The first quartile had jurisdictions with 5,491 or fewer residents. The second quartile had 

populations of 5,492 to 25,176. The third quartile had jurisdictions with populations of 25,177 to 97,268. And the 

fourth quartile had jurisdictions with 97,269 or more residents. 

5

 When we use the term "significant" in the context of a statistical analysis, we mean "significant." 
sample would be infeasible. As a result, we developed a protocol for gathering 

ordinances that significantly reduced the data collection effort. 

The review of each jurisdiction's zoning requirements was based on the standards 

from one zone in the zoning ordinance. The reason that we focused on one zoning 

ordinance is that most jurisdictions have three or more zoning districts that allow for 

single-family housing development, each with different requirements for the study 

variables. Collecting information about each of these zones was not practical because of 

the amount of time and resources involved in doing so. Instead, we focused our 

attention on the "border" zone between low-density single-family development and 

high-density multifamily development. The "border" zone generally allowed a mixture of 

high-density single-family dwellings with duplexes and multifamily dwellings. 

We chose the "border" zone based on the following characteristics: it outright 

permitted detached single-family houses; it had the smallest minimum lot size and 

setbacks; and (where applicable) it allowed a mixture of detached single-family and 

duplexes or multifamily housing. In cases where it was unclear which zone to choose, 

we always selected the zone with the smallest minimum lot size that outright permitted 

detached single-family housing. We focused on the "border" zone because the land 

requirements are smaller, which should result in lower housing costs. 

LOT STANDARDS

The Project Team collected seven lot-related variables, including minimums for: lot 

size, lot width, front yard setbacks, side yard setbacks, rear yard setbacks, floor area, 

and off-street parking. In all cases, we took standards from the densest zone that 

outright permitted detached single-family dwellings. Our assumption was that housing in 

this zone would be more affordable than zones with larger minimum lot size 

requirements because land cost is a large contributor to housing costs. We used 

standards for interior lots, rather than corner or other lot configurations. 

We found the lot variables in the zoning ordinance more than 90% of the time, with 

10% of the lot variables coming from the subdivision ordinance. In most cases, the lot 

standards were single-point values, which we recorded in the database. In a few cases, 

one or more of the lot standards was given as a range or formula, which we could not 

record in the database. For example, several jurisdictions gave formula for calculating 

minimum side yard setbacks based on the lot width and other factors. In those cases, we 

did not record the side setbacks in the database but tracked them in a separate text 

document. These cases are not included in this analysis. 

Table 3-1 presents summary statistics for each of the lot variables. The statistics are 

discussed in conjunction with each standard. 

Appendix A: Statistical Analysis of Regulations A-20
Table 3-1. Minimum lot variable summary statistics 

N Mean Median Mode

Standard

Deviation Minimum Maximum

Lot size 419 9,924 6,000 5,000 16,946 750 217,800

Lot width 342 62 60 50 25 20 250

Front yard 413 25 25 25 13 0 100

Side yard 417 8 8 5 5 0 30

Rear yard 404 21 20 25 9 0 65

Minimum floor area 86 1,060 1,000 1,000 359 500 2,500

Off-street parking 367 1.88 2.00 2.00 0.51 0.00 4.00

Source: Survey of Regulatory Standards, CPW 2006 

LOT SIZE

Lot size is one of the key variables in this study because the minimum lot size 

determines the amount of land required for a single-family detached dwelling. Most of 

the other lot variables are related to size and placement of the dwelling on the lot. 

Lot size is the most commonly encountered standard in the study, and it has the 

greatest variation. We found lot size standards in 95% of the jurisdictions with zoning or 

subdivision ordinances. Table 3-1 shows that minimum lot size has a mean value of 9,924 

square feet and a median of 6,000 square feet, with a standard deviation of 16,946 

square feet. This shows that minimum lot sizes vary substantially. The smallest minimum 

lot size in the study was 750 square feet and the largest was 217,800 square feet (5 

acres). 

Figure 3-1 shows a breakdown of the minimum lot sizes, grouped in 2,000 square 

foot increments. About two-thirds of jurisdictions set their minimum lot sizes between 

4,000 and 7,999 square feet. Only seven jurisdictions allow lots smaller than 2,000 

square feet. Eighteen jurisdictions require lot sizes of at least 30,000 square feet or 

more. 

Appendix A: Statistical Analysis of Regulations A-21
Figure 3-1. Minimum lot size requirements, percentage, and frequency, 

grouped by 2,000 square foot increments 

0% 5% 10% 15% 20% 25% 30% 35%

Less than 1,999

2,000 to 3,999

4,000 to 5,999

6,000 to 7,999

8,000 to 9,999

10,000 to 11,999

12,000 to 13,999

14,000 to 15,999

16,000 to 17,999

18,000 to 19,999

20,000 to 21,999

22,000 to 23,999

30,000 or more

Square feet

Percent

7

30

127

133

31

29

14

15

1

12

1

1

18

Source: Survey of Regulatory Standards, CPW 2006 

Figure 3-2 shows lot sizes grouped in 1,000 square foot increments. This closer 

examination of lot size requirements show that 23% of jurisdictions have minimum lot 

sizes between 5,000 and 5,999 square feet and an additional 18% of jurisdictions allow 

lots between 6,000 and 6,999 square feet. 

Appendix A: Statistical Analysis of Regulations A-22
Figure 3-2. Minimum lot size percentage and frequency, grouped by 1,000 

square foot increments 

0% 5% 10% 15% 20% 25%

Less than 1,999

2,000-2,999

3,000-3,999

4,000-4,999

5,000-5,999

6,000-6,999

7,000-7,999

8,000-8,999

9,000-9,999

10,000-10,999

more than 11,000

Square feet

Percent

7

10

20

31

96

77

56

21

10

28

63

Source: Survey of Regulatory Standards, CPW 2006 

Table 3-2 shows the results of statistical analysis of lot size compared to the five 

subcomponents. The significance level column describes the statistical relationship 

between the variable and each subcomponent of the sample. A significance level of less 

than 0.05 is considered significant. If the significance level is less than 0.05, we have 

entered "yes" in the "statistically significant difference" column, and if it is greater than 

0.05, we have entered "no." The analysis shows that lot size is statistically different for 

each subcomponent of the sample. 

Table 3-2. Statistical comparisons of lot sizes for 

jurisdictions grouped by subcomponents of the sample 

Statistically 

significant 

difference

Significance 

level

Government type Yes 0.000

Census region Yes 0.000

Part of MSA / Not part of MSA Yes 0.000

Central city / Not central city Yes 0.000

U.S. Population grouped in quartiles Yes 0.000

Source: Survey of Regulatory Standards, CPW 2006 

Appendix A: Statistical Analysis of Regulations A-23
Appendix A: Statistical Analysis of Regulations A-24

Further, statistical testing shows the differences in lot sizes among subcomponents 

of the sample.6 The differences observed within both types of means testing reinforce 

the conclusion that statistical differences result from differences in lot size within the 

subcomponents. Lot size varies within each subcomponent in the following ways: 

• Government type City lot sizes are significantly smaller than county, town, 

and township lot sizes. 

• Census region Lot sizes in the Northeast are statistically larger than lot sizes in 

the other three regions. 

• U.S. population Lot sizes in the first quartile, jurisdictions with the fewest 

people, are statistically larger than lot sizes in other quartiles. 

LOT WIDTH

Lot widths varied across jurisdictions but not as greatly as lot size. Table 3-1 

shows that 342 or about 77% of jurisdictions with ordinances had minimum lot width 

standards. The mean lot width requirement was 62 feet and the median was 60 feet, 

with a standard deviation of 25 feet. The smallest lot width requirement was 20 feet and 

the largest was 250 feet. 

Figure 3-3 shows lot widths in 10-foot increments. Most jurisdictions with minimum lot 

widths require lot widths of at least 50 to 69 feet. Thirty two percent of jurisdictions 

require minimum lot widths of 50 to 59 feet and 23% of jurisdictions require lot width 

minimums between 60 to 69 feet. Three percent of jurisdictions have minimum lot 

widths of less than 30 feet and 10% require lot widths of more than 100 feet. 

 

6

 This form of statistical testing, an ANOVA with a Bonferroni post-hoc test, required a minimum of three groups 

within the subcomponent. We conducted this test for the following subcomponents: government type, census region, 

and U.S. population. 
Figure 3-3. Minimum lot widths percentage and frequency, grouped in 10-

foot increments 

0% 5% 10% 15% 20% 25% 30% 35%

Less than 29

30 to 39

40 to 49

50 to 59

60 to 69

70 to 79

80 to 89

90 to 99

More than 100

Lot width in feet

Percent of total

12

33

22

39

79

110

34

3

10

Source: Survey of Regulatory Standards, CPW 2006 

Table 3-3 shows statistical comparisons between lot widths and five subcomponents 

of the sample. A significance level of less than 0.05 is considered significant. If the 

significance level is less than 0.05, we have entered "yes" in the "statistically significant 

difference" column, and if it is greater than 0.05, we have entered "no." Like lot size, 

comparison of lot widths indicated significant differences within each of the five 

subcomponents of the sample. 

Table 3-3. Statistical comparisons of lot widths for 

jurisdictions grouped by subcomponents of the sample 

Statistically 

significant 

difference

Significance 

level

Government type Yes 0.000

Census region Yes 0.000

Part of MSA / Not part of MSA Yes 0.000

Central city / Not central city Yes 0.000

U.S. Population grouped in quartiles Yes 0.000

Source: Survey of Regulatory Standards, CPW 2006 

Additional statistical testing using ANOVA shows the differences in minimum lot 

widths within subcomponents of the sample. These differences reinforce the conclusion 

that the statistical differences result from fundamental differences in lot widths within 

the subcomponents. Lot widths vary within each subcomponent in the following ways: 

• Government type Lot widths are statistically different between the following 

groups: Cities have smaller average lot widths than villages, towns, or townships; and 

Appendix A: Statistical Analysis of Regulations A-25
Appendix A: Statistical Analysis of Regulations A-26

counties have larger average lot widths than towns or townships. The county 

regulations did not generally apply to the incorporated jurisdictions located within the 

county. 

• Census region. Lot widths are statistically different between the Northeast and 

all other regions. The Northeast has larger average lot widths than any other region. 

Lot widths in the Midwest are statistically larger than those in the West. 

• U.S. population. Lot widths are statistically different between the first 

population quartile, jurisdictions with the fewest people, and the other quartiles. The 

first quartile has larger average lot widths than the other quartiles. In addition, the 

second quartile has significantly larger lot widths than the fourth quartile. 

SETBACKS

We examined three types of setbacks in this study: front, side, and rear setbacks. In 

each case, we examined setbacks for interior lots. 

The front yard setback is the distance from the front of the dwelling unit to the 

property line or street. Table 3-1 shows that 93% or 413 of jurisdictions with 

ordinances had minimum standards for front yard setbacks. The mean and median front 

setback requirement was 25 feet, with a standard deviation of 13 feet. Minimum front 

setbacks ranged from zero to 100 feet. 

Table 3-4 shows front yard setback requirements in 5-foot increments. The majority 

of jurisdictions had minimum setbacks between 20 and 29 feet. Twenty-five percent of 

jurisdictions had minimum setbacks between 20 and 24 feet and minimum 31% of 

jurisdictions had setbacks of 25 to 29 feet. One percent of jurisdictions had minimum 

setbacks less than 9 feet and 3% of jurisdictions had minimum setbacks of 55 feet or 

greater. 

Table 3-4. Minimum front yard 

setbacks in 5-foot increments 

Frequency Percent

Less than 9 4 1%

10 to 14 31 8%

15 to 19 45 11%

20 to 24 103 25%

25 to 29 126 31%

30 to 34 49 12%

35 to 39 16 4%

40 to 44 10 2%

45 to 49 4 1%

50 to 54 13 3%

More than 55 12 3%

Total 413 100%

Source: Survey of Regulatory Standards, CPW 2006 
Table 3-5 shows statistical comparisons between front yard setbacks and five 

subcomponents of the sample. A significance level of less than 0.05 is considered 

significant. If the significance level is less than 0.05, we have entered "yes" in the 

"statistically significant difference" column, and if it is greater than 0.05, we have entered 

"no." Differences in front yard setbacks were significant within each of the five 

subcomponents of the sample. 

Table 3-5. Statistical comparisons of front yard setbacks 

with subcomponents of the sample 

Statistically 

significant 

difference

Significance 

level

Government type Yes 0.000

Census region Yes 0.000

Part of MSA / Not part of MSA Yes 0.000

Central city / Not central city Yes 0.000

U.S. Population grouped in quartiles Yes 0.000

Source: Survey of Regulatory Standards, CPW 2006 

Additional ANOVA statistical testing shows the differences in front setbacks within 

subcomponents of the sample. The differences observed within both types of means 

testing reinforce the conclusion that the statistical differences result from fundamental 

differences front setbacks within the subcomponents. Front setbacks vary within each 

subcomponent in the following ways: 

• Government type Front setbacks are statistically different for the following 

groups: Counties have smaller average front setbacks than townships; and cities have 

smaller average front setbacks than towns, townships, and villages. 

• Census region. The West has statistically smaller average front setbacks than 

any other region. The South has statistically smaller average front setbacks than the 

Midwest and Northeast. 

• U.S. population. Front setbacks are statistically different between the first 

population quartile (the fewest people per jurisdiction) and the other quartiles. The first 

quartile has larger average front setbacks than the other quartiles. In addition, the 

second quartile has statistically larger front setbacks than the fourth quartile. 

We also examined side yard setbacks for interior lots. Table 3-1 shows that 417 or 

94% of jurisdictions with ordinances had minimum side yard setback requirements. The 

mean and median side yard setback was eight feet per side, with a standard deviation of 

five feet. The smallest side yard setback requirement was zero feet and the largest was 

thirty feet per side. 

Table 3-6 shows the side yard setbacks in five-foot increments. Fifty-eight percent of 

jurisdictions required minimum side yard setbacks of between five to nine feet. Onequarter of jurisdictions required side setbacks between ten to fourteen feet. Six percent 

required minimum side setbacks of less than five feet and 3% required setbacks of 

greater than twenty-five feet. 

Appendix A: Statistical Analysis of Regulations A-27
Appendix A: Statistical Analysis of Regulations A-28

Table 3-6. Minimum side yard setbacks 

in 5-foot increments 

Frequency Percent

Less than 5 27 6%

5 to 9 240 58%

10 to 14 104 25%

15 to 19 24 6%

20 to 24 10 2%

More than 25 12 3%

Total 417 100%

Source: Survey of Regulatory Standards, CPW 2006 

Side yard setbacks consist of a setback for each side of the yard. Most ordinances 

present the setbacks for one side of the yard but some ordinances present a total size 

for both side setbacks. Seventeen percent of the jurisdictions with side yard setback 

requirements presented their minimum setbacks as a total number to be divided 

between the two sides. For example, a jurisdiction might require ten feet of side yard 

setbacks between the two sides but the minimum setback on either side might be four 

feet. The other setback would have to be at least six feet. In these cases, we divided the 

combined side setback in half and recorded that number. In our example, we would 

record five feet as the minimum side setback. 

Table 3-7 shows statistical comparisons between side yard setbacks and five 

subcomponents of the sample. A significance level of less than 0.05 is considered 

significant. If the significance level is less than 0.05, we have entered "yes" in the 

"statistically significant difference" column, and if it is greater than 0.05, we have entered 

"no." Differences in side yard setbacks were significant for each of the five 

subcomponents of the sample. 

Table 3-7. Statistical comparisons of side yard setbacks for jurisdictions 

grouped by subcomponents of the sample 

Statistically 

significant 

difference

Significance 

level

Government type Yes 0.000

Census region Yes 0.000

Part of MSA / Not part of MSA Yes 0.000

Central city / Not central city Yes 0.000

U.S. Population grouped in quartiles Yes 0.000

Source: Survey of Regulatory Standards, CPW 2006 

Further statistical testing using ANOVA shows the differences in minimum side 

setbacks among subcomponents of the sample. The differences observed within both 

types of means testing reinforce the conclusion that the statistical differences result 

from fundamental differences side setbacks within the subcomponents. Side setbacks 

vary within each subcomponent in the following ways: 
• Government type Side setbacks are statistically different for the following 

groups: Counties have smaller average front setbacks than towns and townships; and 

cities have smaller average front setbacks than towns, townships, and villages. 

• Census region The Northeast has larger average side setbacks, a significant 

difference between the Northeast and the other regions. The West has smaller average 

side setbacks than any other region, which is also significant. 

• U.S. Population The first population quartile, jurisdictions with the fewest 

people, have larger average side setbacks, which is significantly different from each other 

quartile. Likewise, the second population quartile has larger average side setbacks than 

the third and fourth quartiles, which is also significant. 

The final type of setback was rear yard setbacks. Table 3-1 shows that 404 or 91% of 

jurisdictions with ordinances had minimum rear yard setback requirements. The mean 

rear setback was 21 feet and the median was 20 feet, with a standard deviation of 9 feet. 

The smallest requirement for a rear setback was zero feet and the largest was 65 feet. 

Figure 3-4 shows the rear yard setback requirements in five-foot increments. The 

majority of rear yard setback minimums range from 15 feet to 29 feet. The most 

common minimum rear yard setbacks are between 20 to 24 feet (22% of jurisdictions) 

and 25 to 29 feet (23% of jurisdictions). One percent of jurisdictions have minimum rear 

setbacks of less than five feet and four percent of jurisdictions have minimum rear 

setbacks of greater than 40 feet. 

Appendix A: Statistical Analysis of Regulations A-29
Figure 3-4. Minimum rear yard setbacks percentage and frequency, 

grouped in 5-foot increments 

0% 5% 10% 15% 20% 25%

Less than 5

5 to 9

10 to 14

15 to 19

20 to 24

25 to 29

30 to 34

35 to 39

More than 40

Rear yard setback in feet

Percent of total

5

23

15

14

45

94

89

66

53

Source: Survey of Regulatory Standards, CPW 2006 

Table 3-8 shows statistical comparisons between rear setbacks and five 

subcomponents of the sample. A significance level of less than 0.05 is considered 

significant. If the significance level is less than 0.05, we have entered "yes" in the 

"statistically significant difference" column, and if it is greater than 0.05, we have entered 

"no." 

The differences were significant for each of the five subcomponents of the sample, 

except for the jurisdictions grouped by U.S. population. This means that rear setbacks 

are not statistically different based on the population quartile. 

Table 3-8. Statistical comparisons of rear yard setbacks for jurisdictions 

grouped by subcomponents of the sample 

Statistically 

significant 

difference

Significance 

level

Government type Yes 0.007

Census region Yes 0.000

Part of MSA / Not part of MSA Yes 0.001

Central city / Not central city Yes 0.029

U.S. Population grouped in quartiles No 0.055

Source: Survey of Regulatory Standards, CPW 2006 

Additional statistical testing using ANOVA shows the differences in minimum rear 

setbacks within subcomponents of the sample. The differences observed reinforce the 

conclusion that the statistical differences result from fundamental differences rear 

Appendix A: Statistical Analysis of Regulations A-30
Appendix A: Statistical Analysis of Regulations A-31

setbacks within the subcomponents. Rear setbacks vary within each subcomponent in 

the following ways: 

• Government type Rear setbacks are on average smaller in counties than 

townships, a significant difference. Cities are statistically different than towns and 

townships, with smaller average rear setbacks. 

• Census region The West has significantly different rear setbacks, which are 

generally smaller than the other regions. The South’s rear setbacks are also statistically 

different from other regions. The South has larger rear setbacks than the West and 

smaller rear setbacks than the Northeast or Midwest. 

• U.S. Population Jurisdictions in the fourth quartile of population (having the 

largest populations) have smaller average setbacks than any other quartile. This 

difference is significant between the fourth quartile and the first and second quartiles. 

FLOOR AREA

The lot variables so far are related to the size of the lot and placement of the 

dwelling on the lot. The next lot variable, floor area, is related to the amount of living 

space within the dwelling unit, expressed as the minimum number of square feet of floor 

space within the dwelling. 

Table 3-1 shows that 86 jurisdictions or 18% of jurisdictions with ordinances had 

requirements for floor area. The mean floor area requirement was 1,060 square feet 

and the median requirement was 1,000 square feet, with a standard deviation of 359 

square feet. The smallest floor area requirement was 500 square feet per dwelling unit 

and the largest 2,500 square feet. 

Table 3-9 shows the distribution of the floor area minimum requirements. Twentyseven percent of jurisdictions with floor area requirements required no less than 800 to 

999 square feet and 24% required no less than 1,000 to 1,199 square feet. Twenty 

percent of jurisdictions with floor area standards had minimums less than 800 square 

feet and 10% required more than 1,600 square feet. 

Table 3-9. Minimum floor area in square feet 

Frequency Percent

Less than 800 17 20%

800 to 999 23 27%

1,000 to 1,199 21 24%

1,200 to 1,399 12 14%

1,400 to 1,599 4 5%

More than 1,600 9 10%

Total 86 100%

Source: Survey of Regulatory Standards, CPW 2006 

We did not do statistical analysis of floor area requirements based on the five 

subcomponents of the sample because the number of jurisdictions in the study with 

floor area requirements was so small that the statistical analysis would have little 

meaning. 
Appendix A: Statistical Analysis of Regulations A-32

OFF-STREET PARKING REQUIREMENTS

The final lot variable was requirement of off-street parking spaces. Table 3-1 shows 

that 367 or 83% of the jurisdictions had off-street parking requirements. The mean 

number of off-street parking spaces required was 1.88 and the median was two spaces. 

The standard deviation was 0.51 spaces. The fewest spaces required was zero and the 

most spaces required was four. Off-street parking requirements were found most 

frequently in the zoning ordinance. 

Table 3-10 shows that more than three-quarters of jurisdictions with off-street 

parking standards require two spaces. Sixteen percent of jurisdictions require one offstreet parking space. Four percent of jurisdictions require three or four off-street 

parking spaces. 

Table 3-10. Minimum number of 

parking spaces per dwelling unit 

Frequency Percent

1 per du 57 16%

1.5 per du 9 2%

2 per du 284 78%

2.25 per du 1 0%

2.3 per du 1 0%

3 per du 6 2%

4 per du 7 2%

Total 365

Source: Survey of Regulatory Standards, CPW 2006 

About 4% of the jurisdictions based their requirement on the number of bedrooms. 

In general, the more bedrooms, the greater the requirements for off-street parking. In 

half of these cases, the minimum number of off-street parking spaces was two. In the 

remaining cases, the minimum requirement was one or 1.5 spaces. 

Table 3-11 shows statistical comparisons between off-street parking requirements 

within five subcomponents of the sample. A significance level of less than 0.05 is 

considered significant. If the significance level is less than 0.05, we have entered "yes" in 

the "statistically significant difference" column, and if it is greater than 0.05, we have 

entered "no." 

Differences were significant for the following subcomponents: central city and 

population quartiles. In other words, the number of off-street parking spaces required 

varies, depending on whether the jurisdiction is a central city and what the population 

quartile is. Additional ANOVA testing shows that jurisdictions in the fourth quartile of 

population (having the largest populations) require less off-street parking than 

jurisdictions in the second population quartile. 
Table 3-11. Statistical comparisons of the number of off-street parking 

spaces for jurisdictions grouped by subcomponents of the sample 

Statistically 

significant 

difference

Significance 

level

Government type No 0.804

Census region No 0.556

Part of MSA / Not part of MSA No 0.622

Central city / Not central city Yes 0.000

U.S. Population grouped in quartiles Yes 0.011

Source: Survey of Regulatory Standards, CPW 2006 

LANDSCAPING STANDARDS

Many jurisdictions include landscaping standards in their ordinances. Landscaping 

standards vary by jurisdiction and the type of development. We were concerned with 

landscaping standards related to residential subdivisions and residential zones, especially 

the residential zone we examined. 

Landscaping requirements vary in several ways. First, landscaping requirements vary 

in the amount of landscaping required. Some jurisdictions require extensive landscaping 

and others require less landscaping. Secondly, ordinances vary in the level of detail about 

landscaping requirements. Some jurisdictions' ordinances have general language about 

landscaping requirements and its locations. Other ordinances have very specific 

requirements about the types, locations, and size of the plants in the landscaping. Finally, 

different types of landscaping may be required in different circumstances. For example, 

street trees may be required along streets and other types of landscaping may be 

required at the entrance to a subdivision. 

Quantifying these standards would pose significant difficulties. As a result, we chose 

to track whether ordinances contain landscaping standards for development of 

residential subdivisions or development in the zoning district that we reviewed. Table 3-

12 shows that 42% of the jurisdictions in the study had landscaping requirements. 

Appendix A: Statistical Analysis of Regulations A-33
Appendix A: Statistical Analysis of Regulations A-34

Table 3-12. Requirements of landscaping 

Frequency Percent

Required standards 195 42%

No standards required* 274 58%

Source: Survey of Regulatory Standards, CPW 2006, 

*Note: We found no landscaping standards for these jurisdictions in the ordinances we reviewed but they may have 

required landscaping standards in other ordinances. 

Table 3-13 shows that we found landscaping standards in both subdivision and 

zoning ordinances. The total number of ordinances that we found landscaping standards 

in is larger than the total number of jurisdictions that required landscaping because 

some ordinances said that landscaping may be required under some circumstances, such 

as trees along certain streets or in parking lots, in swales or other drainage areas, or at 

the entrance to the subdivision. 

Table 3-13. Ordinances that 

specified landscaping standards 

Frequency Percent

Subdivision 122 47%

Zoning 83 32%

Both 53 21%

Total 258

Source: Survey of Regulatory Standards, CPW 2006 

Table 3-14 shows statistical comparisons on whether jurisdictions require 

landscaping within the five subcomponents of the sample. A significance level of less than 

0.05 is considered significant. If the significance level is less than 0.05, we have entered 

"yes" in the "statistically significant difference" column, and if it is greater than 0.05, we 

have entered "no." 

Differences in landscaping requirements were significant for Census regions, 

whether the jurisdiction is part of an MSA, and the jurisdiction's population. We did not 

perform an ANOVA test for landscaping because landscaping had two possible values 

(yes or no) and the ANOVA requires three or more possible values (i.e. yes, no, or 

maybe). 

Table 3-14. Statistical comparisons of landscaping requirements for 

jurisdictions grouped by subcomponents of the sample 

Statistically 

significant 

difference

Significance 

level

Government type No 0.054

Census region Yes 0.002

Part of MSA / Not part of MSA Yes 0.018

Central city / Not central city No 0.783

U.S. Population grouped in quartiles Yes 0.000

Source: Survey of Regulatory Standards, CPW 2006 
Appendix A: Statistical Analysis of Regulations A-35

The following are some examples of landscaping requirements, quoted from several 

different ordinances. The examples are fragments of the landscaping standard, related to 

one type of development. 

1. All lots shall be planted with grass or other suitable ground cover approved 

by the Planning Board, from the roadside edge of the unpaved right-of-way 

back to a distance of 25 feet behind the principal residence on the lot.7

2. A minimum of two (2) trees shall be required per single or two-family 

residential lot. The trees shall be placed in the front yard area at least ten 

(10) feet from the curb line. On corner lots and cul-de-sac lots, one of the 

trees may be placed in the side yard area. All remaining lot area not used for 

structures, parking area, or driveway shall be landscaped with turf grass, 

native grasses, ground cover, or other perennial flowering plants, vines, 

shrubs, or trees.8

3. All single-family developments will have one tree per 40 lineal feet, or 

fraction thereof. These trees will be located in the swale (green) area in 

between the roads edge and the sidewalks. Trees that are located in swales 

that are six to eight foot in width will require the use of a root barrier to 

protect the sidewalk from root damage. The root barrier will be installed per 

the manufacturer’s recommendation. In right-of-ways with less than a sixfoot swale area the street trees will be located in the front yard five feet 

from the sidewalk and a root barrier will be used along the sidewalk adjacent 

to the tree.9

4. Single-family residential landscaping requirements. 

a. These standards shall apply to all detached and attached single-family 

residential districts. These standards may be met by saving existing trees 

on the site or planting new trees from the approved list. Lot size 

designations shall apply to the zoning classification(s) of the subdivision 

rather than to each individual lot. 

b. One shade tree (2.5" caliper minimum) shall be provided for all singlefamily residential lots less than 6,000 square feet. 

c. Two shade trees (2.5" caliper minimum) shall be provided for all singlefamily residential lots of 6,000 square feet to less than 9,000 square feet. 

d. Three shade trees (2.5" caliper minimum) shall be provided for all singlefamily residential lots of 9,000 square feet or more. 

 

7

 Millbrook Village, NY subdivision ordinance, p 21. 

8

 Faribault, MN subdivision ordinance, chapter 4. 

9

 Pembroke Pines, FL code of ordinances Title XV, Section 153, Section 153.19. 
Appendix A: Statistical Analysis of Regulations A-36

e. All required trees must be planted prior to request for final building 

inspection of dwelling units. 10

OPEN SPACE STANDARDS

Open space standards refer to land that is undeveloped and devoted to public uses, 

such as parkland. About 28% or 133 of the jurisdictions in the sample had regulations 

requiring dedication of land for open space uses. Of these jurisdictions, 59% or 78 

jurisdictions allowed payments (fee-in-lieu) of land dedications. These requirements 

were most often found in the subdivision ordinance. 

While open space requirements do not vary as much as landscaping standards, the 

types of open space requirements do vary substantially. We found three common 

standards for dedicating land to open space in new development: a percentage of the 

total land in a subdivision, a number of square feet per dwelling unit, and a number of 

square feet per person. Ninety-nine of the 133 jurisdictions that with open space 

requirements used one of these three methods for specifying the amount of open space 

required. Table 3-15 provides a statistical summary of these standards, which we will 

discuss below. 

Table 3-15. Statistical summary of different standards for requiring open 

space 

Open space standard N Mean Median Mode

Standard 

deviation Minimum Maximum

Percent of total land in subdivision 47 13 10 10 9.0 3 50

Number of square feet per dwelling unit 18 1,562 795 871 3,446.9 310 15,246

Number of square feet per person 34 229 218 218 112.0 87 436

Source: Survey of Regulatory Standards, CPW 2006 

The most common method for establishing the amount of open space for new 

residential development is requiring dedication of a percentage of land within the 

subdivision for open space. Table 3-15 shows that 47 or 47% of jurisdictions with open 

space standards use this method of calculating open space requirements. The mean 

percentage of total land required for open space in a new subdivision is 13% and the 

median is 10%, with a standard deviation of 9%. The smallest requirement is 3% and the 

greatest requirement is for 50% of the land in a subdivision. 

Table 3-16 shows a breakdown of the amount of land required for open space. Sixty 

percent of the jurisdictions using this method require between 10% and 19% of the land 

in the subdivision for open space. Twenty-one percent of jurisdictions require 

dedications of 20% or more of the land in the subdivision for open space. Nineteen 

percent of jurisdictions require that a minimum of 9% or less of the land in the 

subdivision is dedicated to open space. 

 

10 Lewisville, TX General Development Ordinance Chapter 6, Article VI, Section 6-122. 
Table 3-16. Percent of land in a subdivision required 

for open space 

Frequency

% of 

jurisdictions

Percent of all 

jurisdictions

9% of land or less 9 19% 2%

10% to 19% of land 28 60% 6%

20% or more of land 10 21% 2%

Total 47 100% 10%

Source: Survey of Regulatory Standards, CPW 2006 

Another method for calculating the amount of land to dedicate to open space is 

based on the number of dwelling units in the subdivision, with requirements for a 

specific amount of land for open space per dwelling unit. Table 3-15 shows that 18 

jurisdictions use this method of calculation. The mean number of square feet of land per 

dwelling unit is 1,562, and the median amount is 795 square feet of land per dwelling 

unit, with a standard deviation of 3,447 square feet of land per dwelling unit. The 

smallest amount of land is 310 square feet and the largest is 15,246 square feet per 

dwelling unit. 

Table 3-17 presents a breakdown by percent of jurisdictions of the number of 

square feet of land per dwelling unit required for open space. It shows the variability in 

the amount of land required per dwelling unit. Forty-four percent of jurisdictions 

require a minimum of 500 or fewer square feet per dwelling unit. An equal number of 

jurisdictions require 500 to 999 square feet per dwelling unit or more than 1,000 square 

feet per dwelling unit. 

Table 3-17. Number of square feet per dwelling unit required for open space 

Frequency

% of 

jurisdictions

Percent of all 

jurisdictions

Fewer than 500 square feet per du 8 44% 2%

500 to 999 square feet per du 5 28% 1%

More than 1,000 square feet per du 5 28% 1%

Total 18 100% 4%

Source: Survey of Regulatory Standards, CPW 2006 

The third method for calculating open space requirements is based on the number 

residents in the subdivision, with dedications of a certain number of square feet per 

resident. Table 3-15 shows that 34 jurisdictions, 34% of the jurisdictions who require 

open space, use this method. The mean amount of land required in this method is 229 

square feet per person, and the median is 218 square feet per person, with a standard 

deviation of 112 square feet per person. The smallest amount of land required is 87 

square feet per person, and the largest is 436 square feet per person. 

Table 3-18 shows a breakdown of the amount of land required for open space per 

resident. Seventy-six percent of jurisdictions require either fewer than 200 square feet 

of land per person or 200 to 299 square feet of land per person. 

Appendix A: Statistical Analysis of Regulations A-37
Appendix A: Statistical Analysis of Regulations A-38

Table 3-18. Number of square feet per person required for open space 

Frequency

% of 

jurisdictions

Percent of all 

jurisdictions

Fewer than 200 square feet per person 13 38% 3%

200 to 299 square feet per person 13 38% 3%

300 to 399 square feet per person 3 9% 1%

More than 400 square feet per person 5 15% 1%

Total 34 100% 7%

Source: Survey of Regulatory Standards, CPW 2006 

One-hundred thirty-three of the jurisdictions in the sample had open space 

requirements. Table 3-19 shows statistical comparisons on whether jurisdictions require 

open space within the five subcomponents of the sample. A significance level of less than 

0.05 is considered significant. If the significance level is less than 0.05, we have entered 

"yes" in the "statistically significant difference" column, and if it is greater than 0.05, we 

have entered "no." 

Differences in landscaping requirements were significant for Census regions. We did 

not perform an ANOVA test for requiring open space because requiring open space had 

two possible values (yes or no) and the ANOVA requires three or more possible values 

(i.e. yes, no, or maybe). 

Table 3-19. Statistical comparisons of landscaping requirements for 

jurisdictions grouped by subcomponents of the sample 

Statistically 

significant 

difference

Significance 

level

Government type No 0.216

Census region Yes 0.003

Part of MSA / Not part of MSA No 0.058

Central city / Not central city No 0.460

U.S. Population grouped in quartiles No 0.200

Source: Survey of Regulatory Standards, CPW 2006 

SIDEWALK STANDARDS

One of the most commonly required improvements in new residential development 

is sidewalks. This section includes information collected in the study about sidewalks, 

planting strips, and curbs. 

In our review, we kept track of the jurisdictions that explicitly require sidewalks in 

either their subdivision or zoning ordinances. A number of other jurisdictions implied 

that sidewalks might be required or stated that they would be required under certain 

circumstances. We did not count these jurisdictions as requiring sidewalks, even though 

it is possible that they do. 

Fifty-one percent of the jurisdictions in the study explicitly require sidewalks. These 

requirements are most frequently found in the subdivision ordinances. Table 3-20 shows 

that sidewalks are required on both sides of the street in 51% of the jurisdictions with 
Appendix A: Statistical Analysis of Regulations A-39

sidewalk standards. Fourteen percent of jurisdictions with sidewalk standards require 

them on one side of the street and the remaining jurisdictions do not specify where 

sidewalks are required. 

Table 3-20. Where sidewalks are required 

Frequency

% of 

jurisdictions

Percent of all 

jurisdictions

One side 33 14% 7%

Both sides 123 51% 26%

Unspecified 85 35% 18%

Not required 228 N/A 49%

Source: Survey of Regulatory Standards, CPW 2006 

Table 3-21 provides a summary of required sidewalk width and planting strip width. 

Thirty-three percent of jurisdictions in the study had a minimum sidewalk width. The 

mean and median sidewalk width is four feet, with a standard deviation of one foot. The 

smallest requirement is three feet and the largest requirement is 10 feet. 

Table 3-21. Summary of statistical standards for sidewalks, in feet 

Street standard N Mean Median Mode

Standard 

deviation Minimum Maximum

Sidewalk width 153 4 4 4 1 3 10

Planting strip width 37 5 5 5 1 2 8

Source: Survey of Regulatory Standards, CPW 2006 

Table 3-22 shows a distribution of sidewalk widths. It shows that 59% of jurisdictions 

with sidewalk width standards require sidewalks of at least four feet wide. Thirty-one 

percent require sidewalks at least five feet wide. 

Table 3-22. Minimum required sidewalk width 

Frequency

% of 

jurisdictions

Percent of all 

jurisdictions

3 ft. 2 1% 0%

4 ft. 91 59% 19%

4.5 ft. 4 3% 1%

5 ft. 48 31% 10%

6 ft. 4 3% 1%

More than 6 ft. 4 3% 1%

Total 153 100% 33%

Source: Survey of Regulatory Standards, CPW 2006 

Table 3-23 shows statistical comparisons between whether sidewalks are required 

and five subcomponents of the sample. A significance level of less than 0.05 is 

considered significant. If the significance level is less than 0.05, we have entered "yes" in 

the "statistically significant difference" column, and if it is greater than 0.05, we have 

entered "no." 
Appendix A: Statistical Analysis of Regulations A-40

Differences were significant for government type, whether the jurisdiction is part of 

an MSA, and the jurisdiction's population. Sidewalk requirements were not significantly 

different for jurisdictions grouped by region or whether the jurisdiction is a central city. 

Table 3-23. Statistical comparisons of whether sidewalks 

are required for jurisdictions grouped by subcomponents 

of the sample 

Statistically 

significant 

difference

Significance 

level

Government type Yes 0.007

Census region No 0.096

Part of MSA / Not part of MSA Yes 0.000

Central city / Not central city No 0.143

U.S. Population grouped in quartiles Yes 0.001

Source: Survey of Regulatory Standards, CPW 2006 

Table 3-24 shows statistical comparisons between sidewalk widths and five 

subcomponents of the sample. A significance level of less than 0.05 is considered 

significant. If the significance level is less than 0.05, we have entered "yes" in the 

"statistically significant difference" column, and if it is greater than 0.05, we have entered 

"no." 

Differences in sidewalk widths are not significant for any of the five groupings of 

jurisdictions. This means that sidewalk width does not vary significantly based on these 

subcomponents of the sample. 

Table 3-24. Statistical comparisons of sidewalk widths for jurisdictions 

grouped by subcomponents of the sample 

Statistically 

significant 

difference

Significance 

level

Government type No 0.841

Census region No 0.060

Part of MSA / Not part of MSA No 0.565

Central city / Not central city No 0.156

U.S. Population grouped in quartiles No 0.251

Source: Survey of Regulatory Standards, CPW 2006 

Table 3-25 shows statistical comparisons between the number of sides of the street 

that sidewalks are required on and five subcomponents of the sample. A significance 

level of less than 0.05 is considered significant. If the significance level is less than 0.05, 

we have entered "yes" in the "statistically significant difference" column, and if it is 

greater than 0.05, we have entered "no." 

Statistical comparison sidewalk widths are not significant for groupings of 

jurisdictions, except for region. The ANOVA test shows that there is no significant 

difference in sidewalk widths within the subcomponents of the sample. 
Appendix A: Statistical Analysis of Regulations A-41

Table 3-25. Statistical comparisons of the number of sides of the street that 

sidewalk are required on for jurisdictions grouped by subcomponents of 

the sample 

Statistically 

significant 

difference

Significance 

level

Government type No 0.856

Census region Yes 0.040

Part of MSA / Not part of MSA No 0.638

Central city / Not central city No 0.400

U.S. Population grouped in quartiles No 0.831

Source: Survey of Regulatory Standards, CPW 2006 

Table 3-21 shows that 37 (8%) jurisdictions in the study have requirements for 

planting strips, a grassy buffer between the sidewalk and the curb The mean and median 

width of the strip was five feet, with a one-foot standard deviation. The smallest width 

requirement was two feet and the largest was eight feet. 

Table 3-26 shows the distribution of planting strip minimum widths. Of the 

jurisdictions with planting strip width standards, 30% required five foot wide planting 

strips and 19% of jurisdictions required either four foot or six foot planting strips. 

Table 3-26. Minimum width for 

planting strip 

Frequency

% of 

jurisdictions

Percent of all 

jurisdictions

2 ft. 4 11% 1%

3 ft. 4 11% 1%

3.5 ft. 1 3% 0%

4 ft. 7 19% 1%

5 ft. 11 30% 2%

6 ft. 7 19% 1%

7 ft. 2 5% 0%

8 ft. 1 3% 0%

Total 37 100% 8%

Source: Survey of Regulatory Standards, CPW 2006 

Another commonly required improvement in new residential development is curbs 

and gutters. Like sidewalks, we recorded the jurisdictions that explicitly require curbs 

and gutters in either their subdivision or zoning ordinances. A number of jurisdictions 

implied that curbs and gutters were required improvements or may be required. We 

did not count these jurisdictions as requiring curbs and gutters, even though it is 

possible that they do. 

Curbs and gutters were required by 234 or 50% of the jurisdictions in the study. We 

found most of the requirements in the subdivision ordinance. 
Appendix A: Statistical Analysis of Regulations A-42

STREET VARIABLES

Streets are an essential improvement in residential development. In this study we 

collected information about minimum pavement width and minimum street right-of-way 

width. When we found these standards they were in the subdivision ordinances 92% of 

the time. 

Table 3-27 provides a summary of pavement and right-of-way widths. Forty-one 

percent of the jurisdictions in the study had minimum pavement widths in their 

subdivision or zoning ordinances. The mean and median minimum pavement width was 

28 feet, with a standard deviation of six feet. The smallest minimum pavement width was 

16 feet and the largest minimum pavement width was 45 feet. 

Table 3-27. Statistical summary of minimum street pavement and right-ofway widths 

Street standard N Mean Median Mode

Standard 

deviation Minimum Maximum

Street pavement width 192 28 28 30 6 16 45

Street right-of-way width 262 52 50 50 8 20 80

Source: Survey of Regulatory Standards, CPW 2006 

Figure 3-5 shows minimum pavement width, grouped in increments of five feet. The 

majority of jurisdictions' standards were divided between 20 to 24 feet wide, 25 to 29 

feet wide, and 30 to 34 feet wide. Three percent of jurisdictions with this standard 

allowed streets in new residential development that are less than 20 feet wide and 6% 

required pavement widths of 40 feet or greater. 
Figure 3-5. Minimum pavement width percentage and frequency, grouped 

in 5-foot increments 

0% 5% 10% 15% 20% 25% 30% 35%

Less than 20 ft.

20 to 24 ft.

25 to 29 ft.

30 to 34 ft.

35 to 39 ft.

40 ft. or more

Pavement width

Percent

6

10

13

55

53

55

Source: Survey of Regulatory Standards, CPW 2006 

Table 3-28 shows statistical comparisons between pavement width and five 

subcomponents of the sample. A significance level of less than 0.05 is considered 

significant. If the significance level is less than 0.05, we have entered "yes" in the 

"statistically significant difference" column, and if it is greater than 0.05, we have entered 

"no." Differences in pavement width were significant for each of the five subcomponents 

of the sample. 

Table 3-28. Statistical comparisons of pavement widths for jurisdictions 

grouped by subcomponents of the sample 

Statistically 

significant 

difference

Significance 

level

Government type Yes 0.001

Census region Yes 0.000

Part of MSA / Not part of MSA Yes 0.050

Central city / Not central city Yes 0.046

U.S. Population grouped in quartiles Yes 0.021

Source: Survey of Regulatory Standards, CPW 2006 

Additional statistical testing showed the differences in pavement widths within 

subcomponents of the sample. The tests showed differences within government type 

and census region, indicating that pavement widths vary significantly by government type 

and Census region. Although the chi-square statistical test indicated that pavement 

width are statistically different by population quartiles, additional post-hoc statistical 

Appendix A: Statistical Analysis of Regulations A-43
testing indicates that there are no significant differences in pavement widths for 

population quartiles. Pavement widths vary within each subcomponent in the following 

ways: 

• Government type. Cities have the largest average pavement widths of any 

government type. This difference in pavement widths is significant between cities and 

towns. 

• Census region. Pavement widths are statistically different between the West 

and the Northeast and South. The West has larger average pavement widths. 

• U.S. Population. There are no significant differences in pavement widths when 

analyzed by population quartiles. 

Table 3-27 shows that 262 or 56% of jurisdictions had minimum right-of-way widths 

in their ordinances. The mean right-of-way was 52 feet and the median was 50 feet, with 

a standard deviation of 8 feet. The smallest right-of-way width was 20 feet and the 

largest was 80 feet. 

Figure 3-6 shows the distribution of street right-of-way widths in five-foot increments. 

Fifty-six percent of jurisdictions with this standard require right-of-ways no smaller than 

50 to 54 feet, and 24% of jurisdictions require right-of-ways at least 60 to 64 feet wide. 

Four percent of jurisdictions' minimum right-of-way width is less than 40 feet, and 6% 

have a minimum of 65 feet or more. 

Appendix A: Statistical Analysis of Regulations A-44
Figure 3-6. Minimum right-of-way width percentage and frequency, grouped 

in 5-foot increments 

0% 10% 20% 30% 40% 50% 60%

Less than 40 ft.

40 to 44 ft.

45 to 49 ft.

50 to 54 ft.

55 to 59 ft.

60 to 64 ft.

65 ft. or more

Right-of-way width

Percent

11

15

63

4

148

10

11

Source: Survey of Regulatory Standards, CPW 2006 

Table 3-29 shows statistical comparisons between street right-of-way widths and 

five subcomponents of the sample. A significance level of less than 0.05 is considered 

significant. If the significance level is less than 0.05, we have entered "yes" in the 

"statistically significant difference" column, and if it is greater than 0.05, we have entered 

"no." 

Statistical comparisons of right-of-way widths were significant for jurisdictions 

grouped by region. Street right-of-way widths did not vary significantly based on 

government type, whether the jurisdiction is part of an MSA, whether the jurisdiction is 

a central city, or the jurisdiction's population. 

Appendix A: Statistical Analysis of Regulations A-45
Table 3-29. Statistical comparisons of street right-of-way 

width for jurisdictions grouped by subcomponents 

of the sample 

Statistically 

significant 

difference

Significance 

level

Government type No 0.903

Census region Yes 0.000

Part of MSA / Not part of MSA No 0.233

Central city / Not central city No 0.323

U.S. Population grouped in quartiles No 0.387

Source: Survey of Regulatory Standards, CPW 2006 

Additional statistical testing shows that street right-of-way widths are statistically 

different between the Midwest and all other regions. The Midwest has larger average 

right-of-way widths than the other regions. This reinforces the conclusion that right-ofway width varied significantly by region. 

Appendix A: Statistical Analysis of Regulations A-46
OBSERVATIONS 

This chapter presents a few observations about the data collection phase of the 

study. The focus of this phase of the study was gathering data and presenting a 

descriptive analysis of the data. This majority of the conclusions from the study will 

come from the cost analysis portion of the study. Our observations about the data and 

data collection are as follows. 

Most jurisdictions regulated one or more of the variables. Ninety-four 

percent of the jurisdictions in the sample had standards for one or more of the study 

variables. More than three-quarters of the jurisdictions had standards for lot size, front 

setbacks, and off-street parking spaces. About one-fifth of the jurisdictions had standards 

for open space and floor area. 

The population varied among jurisdictions. The size of jurisdictions within the 

sample varied substantially. They ranged in population from 9.5 million people to 132 

people, from some of the largest cities and most densely developed counties in the U.S. 

to small rural towns. These differences presented challenges in analyzing the regulatory 

standards. We addressed these challenges by separating the sample into population 

quartiles and comparing regulatory standards among the quartiles. 

Some of the variables had a broad range of values. The basic statistical 

analysis showed that several of the variables had substantial variation. The following 

variables had a large range of values and large standard deviation compared to their 

mean: lot size, lot width, front setback, side setback, and open space. For example, a 

rural jurisdiction is likely to have larger minimum requirements for lot size and lot width 

than an urban city. We addressed these differences by separating the sample 

subcomponents and comparing regulatory standards within the subcomponent 

groupings. The subcomponents included government type, census region, membership 

in a Metropolitan Statistical Area (MSA), and central city. 

Difficulty in obtaining ordinances. Obtaining ordinances was difficult, especially 

with smaller jurisdictions. Some jurisdictions made their ordinances available via the 

Internet, making it easy to get their ordinances. Where the ordinance was only available 

directly from the jurisdiction, we were more likely to have problems getting the 

ordinances. Some jurisdictions were unresponsive to our phone calls and requests for 

ordinances, resulting in their exclusion from the sample. 

Appendix A: Statistical Analysis of Regulations A-47
Appendix A: Statistical Analysis of Regulations A-48

Choice of Review Variables 

This appendix summarizes the process for choosing variables for the database. It 

includes our reasoning for choosing particular variables, as well as the list of variables 

for the study. 

PROCESS FOR CHOOSING VARIABLES

The entire team participated in choosing the variables for reviewing the ordinances, 

including representatives from the NAHB, ECONorthwest, and CPW. This process 

took several weeks and was documented in several memorandums, which are 

summarized in this appendix. 

We began the project with a list of about 75 variables that we considered including 

in this study. We narrowed the list of variables by reviewing ordinances from ten 

jurisdictions to assess whether subdivision ordinances commonly contained the 

standards in our list. We found that many of site-specific variables in our original list 

were not in the initial ten ordinances. 

At that point, we began considering expanding the scope of the project to include 

some variables from zoning ordinances because our research indicated that these 

variables, especially those related to lot size, have substantial impact on housing costs. 

As a result of the decision to include variables from zoning ordinances, we reduced our 

sample size from 1,100 jurisdictions to 400 jurisdictions11. 

We reduced the number of variables to about fifteen and conducted a second 

review of ten jurisdictions' subdivision and zoning ordinances to determine how 

frequently these variables occurred in the ordinances. This review showed that the 

variables in our list were frequently found. 

We finalized our list of variables, based on the following criteria: 

• Likelihood and ease of finding the variables within a zoning or subdivision 

ordinance. A number of the variables that we were originally interested in 

measuring were not generally found in either of these ordinances. For example, the 

minimum diameter of a sewer lateral or street pavement surface thickness were not 

often found in either the zoning or subdivision ordinances. 

• Ease of measuring the variables. Some of the variables that we considered were 

difficult to measure. For example, landscaping standards vary substantially among 

ordinances. We were unable to find a way to quantify such diverse standards. 

Instead, we chose to collect whether or not each jurisdiction had landscaping 

requirements in their zoning or subdivision ordinances. 

• Expected impact of the variable on housing cost. Some of the variables that 

we had originally considered including in the study probably had minimal impact on 

the cost of housing. For example, many of the jurisdictions in our preliminary review 

 

11 Ordinance review and collection took less resources than we initially thought, and we were able to increase the 

sample size. We ultimately reviewed 469 ordinances. 
Appendix A: Statistical Analysis of Regulations A-49

contained standards for the angle of street intersections but the angle of an 

intersection probably has little impact on the cost of housing in a subdivision. 

The variables that we selected for review included: 

• Lot-width minimums 

• Lot-size minimums 

• Yard setback minimums (front yard, side yards, rear yard) 

• Floor area minimums 

• Off-street parking requirements 

• Curb and gutter requirements 

• Minimum street right-of-way width 

• Minimum pavement width 

• Sidewalk requirements 

• Open space requirements 

• Landscaping requirements 

As we began ordinance review, we added several variables to address administrative 

concerns. These variables gave us information about the ordinances themselves and 

allowed for certain types of comparison between ordinances. They include: 

• The type(s) of ordinance: zoning and/or subdivision 

• Last update for each ordinance 

• Type of update (adopted or amended) 

• Ordinance media (electronic or paper) 

• Name of the zoning district used for review 

• Type of quality assurance review (short check or long check) 

The next step was quantifying each variable and building the data collection database.