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A few various trends taking place in the US:

  • Skill-biased technological change and a steady polarization of the workforce.
  • Repetitive tasks shifting away from labor to capital.
  • Women going to college in increasing numbers meaning more two-income households. The trend is so strong that in most undergraduate universities that women outnumber men.
  • This is leading to lower fertility, steady aging of the population and delayed child rearing.
  • “Great Stagnation”
  • Elevated unemployment (possibly structural).
  • Most job creation occurring in non-tradable sectors (so much for competitiveness).
  • Finance taking a larger slice of the aggregate GDP pie.

So I decided to look up income data by education and created a ratio of bachelors degree holders vs HS diploma holders. The higher the ratio, the higher the income premium in going to college is favored. This ratio is steadily going up over time for both genders. The ratio is a multiple of how many times your income will go up through completion of college.

For 2008 (the most recent year of numbers) men will experience a 2.939 income multiple by going to college.

Women will experience a 2.505 income multiple.

Men experience a larger premium from going to college than women do.

This could be self-selection bias as by eye-balling various majors in college such as engineering, one will notice a larger male presence. Engineering is one of the highest paid majors for those with a bachelors degree. Men are highly represented in finance and computer sciences too.

Also interesting to note, the ratio for women declining after the early 1990s recession and just before the dot-com bubble. Where college was guaranteeing less of a premium for women. Without looking at anymore numbers I would think that incomes of lower skilled women were improving very fast in the mid-90s rather than a decline in incomes for college-educated women.

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1.) All data are from the American Time Use Survey.

2.) All data for Table 1, Chart 1, Chart 2 reflect the amount of hours per week that the average high school student puts in to various activities.  Chart 1 and Chart 2 are visualizations of Table 1.

3.) Data for Table 2 and Chart 3 reflect the average number of hours that mothers spend with their children on educational activities and all other activities.

4.) These averages control for differences across groups in the number and age of children, education of the mother and marital status.

5.) . This U.S. government survey measures the time use of thousands of individuals from 2003 to 2009 based on time diaries, which are considered the most accurate way to measure time use. It includes data on individuals ages 15 and older.

A few findings:

  • Not all Asian mom’s are hardcore tiger mom’s.
  • White students spend time doing a diverse array of activities.
  • Not many differences in terms of mother’s spending time with their kids with regards to educational activities. Though 0.6 hours in the large scheme of things may mean a lot.
  • More or less, it’s fairly concrete, you can infer your own conclusions.

Table 1

Chart 1Chart 2

Table 2

Chart 3

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Using ACS data that is easily available on the Census website for 2010, I was curious to see the composition of wealthy Hispanic households by national origin.

Mexican households are somewhere around 65% to 70% of all Hispanic households but the overall composition tilts to the other national groups as you filter through higher and higher income levels.  The general heuristic is that slightly less than half of wealthy Hispanics are Mexican, about a quarter are Cuban/Puero Rican and another quarter is Central American/South American.

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I noticed I had a plethora of data regarding fertility and female illiteracy. These two variables are highly correlated with one another. In fact female literacy correlates more strongly than general literacy. The issue here is that men’s literacy starts to go up at an earlier date than female literacy.

As you poke around the data, the interesting thing you notice that the numbers go all over the map for female literacy, the Muslims/Hindus don’t consistently top one another. But outside of Madhya Pradesh, Muslims have consistently higher TFR’s than the Hindus do.

Sources: International Institute for Population Sciences, National Family Health Survey 1998-1999, ORC, Macro, WorldBank Dataset


The table appears small, here is a link to the table.

These next two tables show rank differences by state.

I subtracted (Muslim – Hindu) for both variables.

The higher the number, the greater the disparity is in the Hindu’s favor for the first chart, it is measuring illiteracy. A lower number indicates a Muslim edge.

This is literally measuring how many more kids Muslims have than Hindus. Ranging from as high as 3.2 to zero.

Islam tends to have a pro-natalist effect, even in that states where Muslim women have lower illteracy rates, they have higher fertility rates than Hindu women.

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From the GSS, tracking turnout in the 2008 election by educational attainment. The overall partisan affect of this turnout pattern hurts the Democrats.

The partisan makeup of “partisan” Democrats and “partisan” Republicans as based on GSS data and defined as people who self-identified as “strong” in their leanings. I also restricted it to solely White voters just in case of race skewing or biasing the data.

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