113
scholars have made use of property tax information for measuring inadequate housing (Koebel
1986; Smith et al. 2003; Sumka 1977; Zwick and
Schneider 1990; Kutty 1999). The works by
Koebel (1986) and Smith (2003) are of particular
interest for this study because they are the most
promising for implementation at the neighborhood level.
Koebel’s work (1986) took a hedonic modeling approach to create an index of housing quality using 22 variables combining property taxes
and census information. He later validated the
index by comparing it with a record of housing
inspections for code violations. In his work,
Koebel found the use of this strategy at the metropolitan level problematic because of the variation of housing stock. Unfortunately, Koebel’s
model misclassified some units and is not very
easy to implement by small organizations that do
not necessarily have the analytical skills to build
such an index. Koebel’s strategy of using code
violations to verify the results of his index is used
in this case study.
Smith et al. (2003) performed a descriptive
analysis using the American Housing Survey
(AHS) information and tax assessor records for
the Tampa-St. Petersburg metropolitan area.
Using the indicators suggested in recent literature
as the most relevant (area of unit, cost of new
construction, and land and housing values) the
authors propose a measure – the ratio of market
value to unit value new – which then they used to
estimate the proportion of units considered inadequate. The authors contrast their results against
the data reported by the AHS. Although in principle the authors aim to create a single measure to
estimate the quantity and degree of substandard
housing in a community at the neighborhood
level, the research is mainly framed at the metropolitan level. The proposed value ratio measure is
used for the creation of the second composite
indicator in this paper. This case study will contribute to the limited literature using secondary
indicators to measure inadequate housing at the
neighborhood level.
9.3
Methodology and Data
The data for this paper comes from a communitybased research project originated to support the
efforts of a neighborhood association in the
downtown area of the City of St. Cloud in
Minnesota interested in determining the conditions of housing units in the area.
5
The neighborhood is also home to the main campus of St.
Cloud State University (SCSU) (see Fig. 9.1 for
location).
The neighborhood association, known as
Neighborhood University Community Council
(NUCC), has been concerned with the deterioration of housing, but it lacks any precise data
about the amount, conditions, and the extent of
the presence of inadequate housing. It is in this
context that a research project emerged as a collaboration between local officials, the neighborhood association, and the SCSU. The questions
driving this research effort were: When do housing units start to deteriorate, and what is the proportion of housing units in need of rehabilitation
in the neighborhood? More precisely, how can
one obtain an indicator of inadequate housing to
support a policymaking process?
To answer these questions, the main objective
driving this research project was to come up with
an efficient way to create indicators that could
yield detailed information and that could be easily replicated. Based on this premise and the
experience in the literature about measuring
inadequate housing, the strategy was the creation
of two composite indicators or indices. One index
was created using existing information contained
in tax appraisal records, and the other index was
created based on data from a traditional visual
assessment of exterior conditions of units in the
neighborhood.
The first composite indicator (hereafter “value
ratio index”) gives a fast look at the amount and
age-related conditions of housing stock. The
5 The dataset used in this paper is available at Estevez
2019.
9 Helping the Neighborhood: Creating a Sustainability Indicator of Substandard Housing
scholars have made use of property tax information for measuring inadequate housing (Koebel
1986; Smith et al. 2003; Sumka 1977; Zwick and
Schneider 1990; Kutty 1999). The works by
Koebel (1986) and Smith (2003) are of particular
interest for this study because they are the most
promising for implementation at the neighborhood level.
Koebel’s work (1986) took a hedonic modeling approach to create an index of housing quality using 22 variables combining property taxes
and census information. He later validated the
index by comparing it with a record of housing
inspections for code violations. In his work,
Koebel found the use of this strategy at the metropolitan level problematic because of the variation of housing stock. Unfortunately, Koebel’s
model misclassified some units and is not very
easy to implement by small organizations that do
not necessarily have the analytical skills to build
such an index. Koebel’s strategy of using code
violations to verify the results of his index is used
in this case study.
Smith et al. (2003) performed a descriptive
analysis using the American Housing Survey
(AHS) information and tax assessor records for
the Tampa-St. Petersburg metropolitan area.
Using the indicators suggested in recent literature
as the most relevant (area of unit, cost of new
construction, and land and housing values) the
authors propose a measure – the ratio of market
value to unit value new – which then they used to
estimate the proportion of units considered inadequate. The authors contrast their results against
the data reported by the AHS. Although in principle the authors aim to create a single measure to
estimate the quantity and degree of substandard
housing in a community at the neighborhood
level, the research is mainly framed at the metropolitan level. The proposed value ratio measure is
used for the creation of the second composite
indicator in this paper. This case study will contribute to the limited literature using secondary
indicators to measure inadequate housing at the
neighborhood level.
9.3
Methodology and Data
The data for this paper comes from a communitybased research project originated to support the
efforts of a neighborhood association in the
downtown area of the City of St. Cloud in
Minnesota interested in determining the conditions of housing units in the area.
5
The neighborhood is also home to the main campus of St.
Cloud State University (SCSU) (see Fig. 9.1 for
location).
The neighborhood association, known as
Neighborhood University Community Council
(NUCC), has been concerned with the deterioration of housing, but it lacks any precise data
about the amount, conditions, and the extent of
the presence of inadequate housing. It is in this
context that a research project emerged as a collaboration between local officials, the neighborhood association, and the SCSU. The questions
driving this research effort were: When do housing units start to deteriorate, and what is the proportion of housing units in need of rehabilitation
in the neighborhood? More precisely, how can
one obtain an indicator of inadequate housing to
support a policymaking process?
To answer these questions, the main objective
driving this research project was to come up with
an efficient way to create indicators that could
yield detailed information and that could be easily replicated. Based on this premise and the
experience in the literature about measuring
inadequate housing, the strategy was the creation
of two composite indicators or indices. One index
was created using existing information contained
in tax appraisal records, and the other index was
created based on data from a traditional visual
assessment of exterior conditions of units in the
neighborhood.
The first composite indicator (hereafter “value
ratio index”) gives a fast look at the amount and
age-related conditions of housing stock. The
5 The dataset used in this paper is available at Estevez
2019.
9 Helping the Neighborhood: Creating a Sustainability Indicator of Substandard Housing