Research Question

Overview of the Neighborhood Change Analysis and Tax Credit Programs

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.

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.

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:

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: