“[L]ive up to the conventional standard” vs. “outdo those with whom we are in the habit of classing ourselves.”

Chapter Five of Thorstein Veblen’s The Theory of the Leisure Class (1899), The Pecuniary Standard of Living, begins as follows:

For the great body of the people in any modern community, the proximate ground of expenditure in excess of what is required for physical comfort is not a conscious effort to excel in the expensiveness of their visible consumption, so much as it is a desire to live up to the conventional standard of decency in the amount and grade of goods consumed. This desire is not guided by a rigidly invariable standard, which must be lived up to, and beyond which there is no incentive to go. The standard is flexible; and especially it is indefinitely extensible, if only time is allowed for habituation to any increase in pecuniary ability and for acquiring facility in the new and larger scale of expenditure that follows such an increase. It is much more difficult to recede from a scale of expenditure once adopted than it is to extend the accustomed scale in response to an accession of wealth.

Effective U.S. federal tax rate vs. income

The congressional budget office provides data about the distribution of the federal tax burden (including income tax, social security tax and excise tax) among the different income groups. The chart below shows the 2005 distribution. The area of the entire chart represents the total household income in 2005 ($9.7 trillion).

The chart is divided by solid lines into 5 vertical bars, corresponding to the five household income quintiles, sorted in order of increasing household income from left to right. The bars’ widths correspond to the total income of the quintile (i.e., income per household in the group times the number of households in the group). The top income quintile is split with a dotted vertical line into the two groups – the top 1% on the right and the rest of the top quintile (percentiles 80 to 99) on the left. Those subgroups within the top quintile are broken down further into the following percentile brackets (not marked with vertical lines): [80-90], [90-95], [95-99], [99-99.5], [99.5-99.9], [99.9-99.99], and [99.99-100].

Each bar has a shaded portion corresponding to the share of the income group’s income which is collected as federal taxes. Thus the total shaded area corresponds to the federal tax total ($2 trillion = 20.5% of $9.7 trillion).

The tax rates increase from 4.3% for the bottom quintile to 32.1% for the [99.9-99.9] percentile bracket, before dipping slightly to 31.5% for the top hundredth of percentile.

Breakdown of U.S. household expenses

The chart below shows the breakdown of the average U.S. household yearly expenditure in 2007. I removed the “pensions and social security” category from the total, since this category should be seen as a tax, a benefit or savings rather than as an expense. I also carried out some grouping of expenditure categories for visual clarity. Some of the low expense categories, for example, were grouped under the heading “other” together with the category “miscellaneous”.

When comparing expenditure patterns for higher and lower income households (under $70,000 vs. over $70,000), it turned out that the proportions allocated to each of the categories are quite stable – with differences of no more than 2% in each category, and no obvious trends.

Data source: Bureau of Labor Statistics, Consumer Expenditure Survey.

History of work hours per person vs. median income

The following chart shows the trend of average weekly work hours per person in the U.S. and the trend of CPI-adjusted median U.S. household income. Both quantities rose by about 25% over the last 45 years.

Average weekly work hours per person are calculated as weekly work hours aggregates (total workers times average hours per worker) divided by the total size of the population (including non-workers of all ages). CPI-adjusted household income is shown in 2008 dollars.

Car and air transportation by income

The Consumer Expenditure Survey (2007 data) shows (1, 2) that the higher a household’s income is, the more its members travel. Households whose income is above $150,000 a year spend on average about $4,000 a year on gasoline and motor oil, while household whose income is under $15,000 a year spend about $1,000.

The BLS groups air travel together with cruiseboat travel and mass transit under the heading “public transportation”. Most of the amount under this heading is spent on air travel, with the proportion increasing with income. The amount spent on “public transportation” is therefore a good indicator of the distance covered in travel by air, and inequalities in the expenditure in this category can serve as lower bounds for the inequalities in air travel. The expenditure within this category is overwhelmingly by the rich. The top 10% of households account for about half of the total expenditure on “public transportation” – a proportion similar to their share in the total income.

Income of richest households vs. tax on high incomes

During the last 90 years the U.S. has experienced large changes in the share of the total national income controlled by the richest households. The (pre-tax) share of the richest 0.01% of households, for example, was under 1% in the late 1970’s, but over 5% in the late 1920’s and in the years 2005 and 2006.

Over the same period, income tax rates on high incomes varied greatly. The top income rate fluctuated between over 90% (1950’s and early 1960’s) and under 40% (1920’s and 1987 to the present day).

As is evident in the chart below, those two phenomena are strongly negatively correlated over time. The correlation factor is about -74%. Of course, correlation does not imply causation, but even if high tax rates on high incomes do not directly translate to smaller (pre-tax) income for the rich, the correlation supports the notion that inequality in income is determined to a large extent by public policy rather than by an “impersonal phenomenon, the market price”.

Data: Income data are from Thomas Piketty and Emanuel Saez, “Income Inequality in the United States, 1913-1998″; updated version and updated data files available at Saez’s website. Tax rate data are from “Personal Exemptions and Individual Income Tax Rates, 1913-2002″, an IRS publication.

Household income distribution, 2007

The graph below shows a histogram of the household income distribution in the US in 2007. It was constructed using data from the Current Population Survey (CPS), Table HINC-06. I smoothed the table by merging pairs of $2,500-wide intervals into $5,000-wide intervals, since the narrow intervals showed marked oscillation, as people apparently tend to report their income in multiples of $5,000.

The three vertical dashed lines indicate the 25th, 50th and 75th percentiles. The corresponding values are $25,100, $50,300 and $88,400, respectively.

The following table gives the deciles of the distribution:

Percentile	10	20	30	40	50	60	70	80	90
Income, $1000’s	12.3	20.8	29.8	39.4	50.3	62.7	78.6	100.8	141.9

All percentile points were calculated by interpolating linearly within the income bins.

Steven Levitt misrepresenting his source

Steven Levitt has risen to stardom by riding on the overblown rhetoric resting on the overblown claims of Freakonomics. It is, unfortunately, in the nature of popular books that they oversimplify and over-claim. Academic literature is supposed to be different: rigorous, cautious and, of course, peer-reviewed for accuracy.

Of course, if all those attributes really applied, a career like that of Levitt would have been impossible, since the econometric methodology he employs is far too weak to be able to produce with any credibility the kind of results Levitt is aiming at. It is clear, therefore, that within the community within which Levitt works, some standards of critical thought have been suspended. However, even when credulity is being stretched and poorly supported statements are taken as proven, one may still hope for the superficial ground rules to apply. Specifically, for example, one hopes that when previous research is cited and summarized the findings of the research are fairly represented.

Share of income of top percentiles of U.S. households

Note: This post deals with the proportion of total US income taken up by the households controlling the most income. The percentiles of the income distribution are given in a different post: Household income distribution, 2007.

The chart below is based on data of Saez and Piketty (Table A3), who rely on IRS publications.

The year 2006, the latest year for which data is available, has seen concentration of income by the top percentiles which has not been observed since the late 1920’s. Following a three-decade long process of increasing concentration of income by top percentiles, in 2006, a tenth of the U.S. population controlled half the national income, a hundredth of the population controlled a quarter of the income, a thousandth of the population controlled an eighth of the income and one ten-thousandth of the population controlled one-sixteenth of the income. Thus, the top x percentile group controls about 2 times more income than the top x/10 percentile group.

It is important, however, to note that even at the years of least concentration – the late 1950’s to the late 1970’s – the top percentiles controlled very disproportionate shares of the national income. The top 10% controlled at least one third of the income throughout the 20’s century. During those “golden years” of income dispersal, the top x percentile group controlled about 3 times more income than the top x/10 percentile group. The change in the share between the “golden years” and today is therefore not very significant at the top 10% level, but, by the repeated multiplication by a factor of 3/2, it is much more significant at the top 0.01 percentile level (these households now control (1/2)⁴ = 1/16 of the income, as opposed to controlling a mere (1/3)⁴ = 1/81 of the national income in, say, 1960).

One interesting implication of the fact that half the national income goes to the top 10% of households: if the national income were re-distributed so that each household received an equal share of the national income, the income available to each household would then be equal to the income of the household which currently is at the 90% percentile of the income distribution. Thus each household in the U.S. would, in such a situation, be making over $100,000 annually.

Update (22-Oct-2009): Added data for top 400 households for the years 1992-2006, made available by the IRS. The top 400 households (out of about 150 million) represent the top 0.0002667% of households. This tiny fraction of the households controlled in 2006 over 1.3% of the entire national income. The pattern of income share of top income groups described above holds tolerably well for this group as well: (1/2) to the power of log₁₀(400 / 150 million) = 2.1%.

Self reported cost of living vs. CPI

The figure below shows the distributions of answers to two Gallup surveys – taken in the years 1937 and 2007 – asking the respondents for the smallest amount of money a family of four would need each year to get along in their community.

The ratio between the median amounts is about 43,700 / 1,500 = 29. The increase in the official measure of the consumer price index for the period 1937 – 2007 is by a factor of 14.4.

In 2007 the median household income was $50,233. The median household income for 1935-1936 was about $1,068. The increase is about 47-fold. The income of the median income of a family of four increased from $3,292 in 1947 to $75,675 in 2007, an increase of about 23 times.

Data: Gallup questionnaire database: poll #84, question 4, 5/24/1937; question 8, SOCIAL SERIES WORLD AFFAIRS, 2/1-4/2007. The 1937 question was phrased in terms of weekly sum of money needed – the data was adjusted to give the yearly sum by multiplying by 365 / 7. Inflation calculator. Statistical Abstract of the US, 1940. Census bureau, historical income tables – Housholds. Census bureau, historical income tables – Families.

Distribution percentiles ($1000’s):

Percentile	10	20	30	40	50	60	70	80	90
1937	0.99	1.27	1.27	1.43	1.51	1.79	1.95	2.03	2.47
2007	24.5	29.75	34	39	43.75	49	55	57.5	77.5