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Student Analyzes Social Mobility Data

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Student Analyzes Social Mobility Data

A group of Fordham students from a variety of schools created the app to widen access to mental health (The Owen Corrigan/The Fordham Ram).

A group of Fordham students from a variety of schools created the app to widen access to mental health (The Owen Corrigan/The Fordham Ram).

A group of Fordham students from a variety of schools created the app to widen access to mental health (The Owen Corrigan/The Fordham Ram).

A group of Fordham students from a variety of schools created the app to widen access to mental health (The Owen Corrigan/The Fordham Ram).


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By Helen Stevenson

A group of Fordham students from a variety of schools created the app to widen access to mental health (The Owen Corrigan/The Fordham Ram).

As a college student, you may find yourself questioning your future and what you can do to ensure financial stability. But what if your potential earnings are affected by certain unchangeable factors? How much, if at all, do these predetermined factors benefit or inhibit your social mobility? Connor Redpath, first year PhD student and FCRH ’17, attempts to answer these questions in a research study entitled

“Unequal Opportunities: Measuring and Predicting Social Mobility.”
Redpath bases his research on a Panel Study on Income Dynamics from the University of Michigan. The data set focuses on parent/child pairs and their social and economic status. He then used econometric tools to tease out which social variables affect intergenerational mobility – of which he found to be parental income, sex and age.

“I carried out all the data analysis in Matlab, which required a lot of coding. I registered to use this data and followed some of their guidelines and techniques for figuring out how to measure the effects, with the help of Professor Troy Tassier,” he said.
“Once I had the results, I had to think a lot about interpreting the numbers. Organizing the data and writing the code and make it (relatively) presentable – in the end was no small task,” he said.

One of the most significant effects on a person’s potential income is held to be his or her parent’s income. This is determined by holding constant factors such as age, race, location in urban or rural environment, sex of parent, sex of child and education. According to Redpath, the effect is very statistically significant. There is nearly a 100 percent chance that the effect will not be zero.

“For every increase in your parent’s relative income decile, there is a 14 percent increase in the child’s decile,” he says. “This means, a $100 movement in parent’s real earnings trickles down to a movement of $14 in child’s real earnings.”

Redpath also concluded that the effect would have large dollar amounts at higher incomes while at lower incomes the dollar amounts are smaller. In analysis of the panel study, gender also played an influential role in determining future financial success. Redpath says that his results are statistically similar to the 77 cents per dollar statistic that is currently cited for the gender wage gap.

“If men are “normal” then women have an income penalty; if women are “normal” then men have an income bonus,” says Redpath. “The former is about a 1.4 decile drop. So a woman with the same education (measured in years), race, and parents as some man would be about 86 percent as rich.”

Age, unsurprisingly is likely the most important variable when examining relative income. “We know that children have no income, students have very little income, and retired people also have a small income,” says Redpath.

According to prominent academics doing research in this area, the height of financial growth is normalized to 40 years old. “However, as age increases relative income increases, and as your age is farther away from 40 (a rough estimate for peak earnings) your relative income decreases,” says Redpath. “This is pretty intuitive, but it’s a little more complex than a linear relationship.”

What Redpath found to be curious, however, was the lack of effect that education played when determining a person’s social and income mobility. “Surprisingly, in the sample I used, education of the parent mattered more than the education of the child, which effectively did not matter. Even ‘number of children’ and ‘age at first child’ are more significant.” However, he cited this finding as an imperfection of his analysis.

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