Overview of the Neighborhood Change Analysis and Tax Credit Programs
Quick Insights
For the Neighborhood Change Model: A good indication for
gentrification is the identification of poor and diverse neighborhoods
that experience growth over a period of time. During that time of growth
the diversity decreases and the population becomes more affluent pushing
out the original occupants. It was found that there was a decrease in
MHV from 1990 to 2000 while there was a large increase in MHV from 2000
to 2010. Gentrification of neighborhoods may be a factor.
For Tax Credit Programs: Based off of the interpretations in Chapter
3, we can conclude that both the NMTC and LIHTC programs are effective
at catalyzing neighborhood improvement, but he NMTC Program can be
considered more effective.
Overview / Research Question Program Details
-
Was the a change in Median Home Value (MHV) between the years 1990
and 2000 positive or negative? Looking at urban areas, what
percentage experienced gentrification during this time frame?
-
Was the a change in Median Home Value (MHV) between the years 2000
and 2010 positive or negative? Was the change in MHV impacted by the
selected control variables?
-
Between NMTC and LIHTC, which program was the most effective in
promoting neighborhood revitalization between 2000 to 2010?
Data
The data used for analyzing neighborhood change is from the Census
Longitudinal Tabulated Database (LTDB). Variables from the long-form
version of the census, the American Community Survey, and the Decennial
Census short form are compiled together into a dataset.
The data used for analyzing neighborhood change and the tax credit
programs is from the data set on the New Market Tax Credit Federal
program and US Department of Housing and Urban Development (HUD)
National Low Income Housing Tax Credit (LIHTC) Database.
Methods
For Part I: This report contains a model for predicting the change in
Median Home Value. It will focus on three main variable available in the
Census data. The first a test of different variables that are believed
to be correlated to changes in Median Home Value as a proxy for
gentrification. The chosen variables are:
- Median Household Income
- Percent of population with less than a high school education
- Percent of population that are unemployed
Change in Median Household Income is believed to be a good variable for
change as a signal that more money is flowing into the community. The
idea is that this would be due to certain investments and economic
changes that lead to gentrification.
Percent of population with less than a high school education is expected
to be an indication of gentrifiable communities with the assumption that
new families would move into the area with higher levels of education.
Percent unemployed is a variable that seeks to directly measure some
type of economic shift, gentrified neighborhoods may introduce more
working opportunities given certain economic developments.
For Part II: Tax Credit Programs will be analyzed. In reviewing the
different tax programs the log-linear difference-in-difference model was
used. It was used to assess whether or not the federal NMTC and LIHTC
programs are effective at catalyzing neighborhood improvement. For
control variables, the same variables as the Neighborhood Change model
were used:
- Median Household Income
- Percent of population with less than a high school education
- Percent of population that are unemployed