The Path Analysis Diagram defines our hypothesis. Human Capital has an impact on:
Home Affordability (-) as highly educated wage earners bid up prices of homes,
Demographic/youth (-) more youth fewer older people with degrees, and
Unemployment (-) as Human Capital lowers unemployment.
In turn, those intermediary variables impact Homeownership rate:
Housing Affordability (+), if homes are more affordable homeownership goes up.
Demographic-Youth (% of population between 20 and 29), (-) as younger people can ill afford homes, and
Unemployment (-) as unemployed lack the income to buy homes.
The Actual Correlations We embedded the correlations within the diagram. We also added a correlation directly from Human Capital to Home ownership. Most correlation signs support the hypothesis except Unemployment.
The Path Coefficients Given that the variables are standardized, all bivariate correlations already represent Path coefficients (in white). We’ll calculate the Path coefficients in yellow with a regression model. Dependent variable is Homeownership rate
Correlations vs Path Coefficients Correlations reflect the relationship between just two variables. The Path coefficients reflect the effect one variable has on another when controlled for the other three variables. Now the Path coefficient of Unemployment rate is negative.
Direct and Indirect Effects The Correlation of the independent variable can be decomposed into its Direct Effect and Indirect Effect on the dependent variable. The Causal Effect is the sum of the mentioned Effects and should equal the Correlation.
Human Capital Direct and Indirect Effects Human Capital causal effect (-0.176) on Homeownership equals its correlation.