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GDP Per Capita: An Accurate Gauge or a Bum Steer?
GDP Per Capita: An Accurate Gauge or a Bum Steer?
by Bulent Temel

### Bulent Temel for The 2004 Moffatt Prize in Economics

Gross Domestic Product (GDP) is the main measure used to show national incomes.  United States adapted GDP as the main income measurement in 1992 as the former agent, Gross National Product (GNP) began misrepresenting US output due to increasing international transactions.  Accelerating foreign investments, globalization and international mergers led national economies to accept a measure of income that only counts for in-house production.  GDP sums up total production of goods and services in a country at a given year, whereas GNP ignores foreign production made stateside but adds the national production overseas.  Total value of production is the income of some people in the country, as Jean-Baptiste Say reasoned years ago while explaining how supply creates its own demand.  GDP is a valid scoreboard of a nation’s aggregate income on a macro level.

GDP could be a solid measure of “national income”, but not necessarily GDP per capita is for “average national income”.  In capitalist economies in which few people get overwhelmingly rich while the majority of the nation progresses just modestly, how accurate would simple arithmetic mean be in representing average level of income?  Do the highest figures in the highly heterogeneous US income distribution cause arithmetic mean formula yield a value with a small frequency?  In other words, is US GDP per capita an income that is made by only few Americans?

Answer to this question lies at how higher “highest incomes” are than the “others”, and what percentage of US citizens earns them.  To see where US is on the issue, let’s play with government income numbers[1] using the concept of statistical median.  Suppose we lay out all families in the United States on a giant football field.  We place them according to ascending order of their income.  (Income level rises as we move from one goal post towards the other).  Then let’s ask families make stacks of \$100 bills that total their incomes.  So, for instance, the household at the 50-yard line (family with the median income) would build a stack of bills that are…

= US median income divided by dollar value of each bill, and re-divided by the height of a bill

= \$40,000 / \$100 / 0.004 inches

= 1.6 inches high.

When all families erect their stacks, we end up with the below picture[2].

As seen clearly, a vast majority of American households are making annual incomes that are not even comparable with those of few wealthiest people.  The transition to this “L-Curve” from the traditional “Bell-Curve” is why GDP per capita is no longer a good measure of America’s average income.

Political philosopher David Schweickart pinpoints income inequality reality with a dramatic statement:  "…If we divided the income of the US into thirds, we find that the top ten percent of the population gets a third, the next thirty percent gets another third, and the bottom sixty percent get the last third.  If we divide the wealth of the US into thirds, we find that the top one percent own a third, the next nine percent own another third, and the bottom ninety percent claim the rest.  Actually, these percentages true a decade ago, are now out of

date.  The top one percent are now estimated to own between forty and fifty percent of the nation's wealth, more than the combined wealth of the bottom 95%.”[3]

Current standing is touchy.  How about the future?  According to Internal Revenue Service, just between 1995 and 1997, average after-tax income rose 9 times faster for those at the top of the income spectrum than for most other Americans.  Average after-tax income of the top 1% of tax filers jumped up by 31% (\$121,000), whereas same figure for the bottom 90% was only 3.4%.[4]  BusinessWeek magazine wrote that the disparity between the highly paid and the normally paid workers in the US has increased from 40 to 419 in the past 20 years.  Put shortly, the gap has been deepening.

An historical outlook on US income distribution supports the hypothesis that GDP per capita is representing real average income less and less every passing year.  If we divide all US incomes into 5 equal pieces (“quintiles”), middle quintile (Quintile-3) would be where GDP per capita –by definition- falls in.  Table-1 (Appendix) shows how percentage of 3rd quintile in the total distribution has been declining since 1967.  In other words, GDP per capita is showing an income that is earned by fewer Americans every year.  Below chart derived from the same data, visualizes this phenomenon.

On the other hand, not surprisingly, share of those who eat the top 5% of the pie has been growing.

One indicator of per capita GDP’s declining validity is national progress improving slower than economic progress.  Social progress refers to the overall quality of life in a country, and is measured by “International Index of Social Progress” (IISP).  IISP, by assessing 40 aspects of life including quality of health, education, environment, level of democracy, military spending, etc; is the grade of a country’s ability to provide a good standard life.  Thanks to its multi-variate nature, IISP shows a life standard both qualitatively and quantitatively in a way superior to GDP per capita, which merely and misleadingly refers to quantitative standards.

United States, the country with the second highest average income in the world -in terms of GDP per Capita-, ranks only 27th in social progress criterion.[5]  Richard Estes, a Social Studies Professor at University of Pennsylvania, explains why: “The failure to make progress on the wave of a historic economic boom in the 90’s is explained in part by the passage of welfare reform.  The wealth was concentrated in upper income brackets and never reached the poor.  Welfare reform meant giving the poorest less [time-limits on eligibility, work requirements with no child-care support] than what they had before.”

Top-10 countries with the highest life standards according to IISP have an unsurprising commonality: A more evenly distributed national income.  Shown by “GINI Index”, level of income inequality in these countries is lower than in other developed countries like USA and UK.  Below table that compares the levels of income inequality (GINI) and average income (GDP per Capita) in both groups helps making the point of this study:

 IISP Ranking[6] Country GINI Value[7] GDP Per Capita[8] 1 Denmark 24.7 \$28,900 2 Norway 25.8 \$33,000 3 Sweden 25.0 \$26,000 4 Australia 35.2 \$26,900 5 Netherlands 32.6 \$27,200 6 France 32.7 \$26,000 7 Germany 30.0 \$26,200 8 Italy 27.3 \$25,100 9 Finland 25.6 \$25,800 10 Belgium 28.7 \$29,200 Average: - 28.8 \$27,430 13 UK 36.8 \$25,500 27 USA 40.8 \$36,300 Average: - 38.8 \$30,900

Lower social progresses of the nations where incomes are shared unequally (USA, UK) indicate GDP per capita overestimates average incomes in these countries.  Living standards that remain relatively constant is a strong sign of GDP per Capita’s lessening meaning.

Capitalism being criticized to “deepen the gap between rich and poor” is not a new debate.  Neither is “but today’s poor are richer” counter-argument.  Indeed, it takes only 13 minutes for an average worker to earn enough money to buy a pair of socks, a major improvement from 1.5 hour of the year 1950.  Today, people of lower income levels own more than those half a century ago.  However, merely concentrating on “how much” question, but ignoring “how much to whom” may only be an approach of hoodwinker politicians, but not socially liable economists.

A major drawback of income inequality is its contributions to economic fluctuations (which, in turn, hurts lower income groups more than others).  Combined with factors such as a weak banking system, trade deficit, contractionary fiscal policies and problematic corporate structures; income inequality leads to crises as it did in 1929 Great Depression.  In late 1920s, only 5% of Americans were earning one third of the total US income.  Top 1% owned an all-time high %36.3 of the nation’s assets.  Luxury consumptions and speculative capital investments of this society volatilized American economy.  Their excessive incomes turned back to money markets resulting in loans available to riskier borrowers.  Many people failed to pay their loans back due to their insufficient incomes.  Tax reductions in 1921, 1924, 1926 and 1928 made the situation worse by helping high-income earners piled up their disposable incomes.

Another problem with income inequality is that it causes political instability.  When a majority of a nation is aware of their earnings being way lower than some others, they become dissatisfied with their economic status, and therefore constantly search for better governments.  Political instability increases the risks of investment and discourages foreign capital flow.  Lower investment grades of countries resulting in less funds coming from abroad; undermine a nation’s growth potential.  Income inequality also deteriorates business confidence in domestic markets.  It discourages economic entities about commitment and trust.  Higher risks of conducting business, and higher costs of enforcing contracts impede economic transactions.

Unequally shared national incomes take some economic weapons away from policy practitioners.  One of these public finance tools, “pricing” loses its functionality in highly unequal income distributions.  For instance, in needs of higher energy efficiency, unequally distributed national incomes would turn off governments to raise prices due to fear of poverty.

## “WEIGHTED AVERAGE GDP”

All above are how bad US income distribution is and the logic behind GDP per capita’s sophistry.  If per capita GDP does not work, then what does?  Stratification is where the answer is.  Earlier, we divided US incomes into 5 equal pieces called “quintiles”.  Now, these income intervals will be our sub-populations under name “strata”.  Proposed formula is one that averages the sum-total of each stratum’s percentage proportion in total population multiplied with its mean income.  It is denoted as …

= S (mi X Wi) / S Wi

where

i: Stratum, and i є {1,5}

m: Arithmetic mean of all incomes in a stratum

W: % share of the total number of people who earn the

corresponding income, and 0 < W < 1

From Table-1 (Appendix) that shows percentage share of each stratum, and Table-2 that shows average income in each stratum between 1967 and 2001; (weighted) average income per household for year 2000 is…

= [(1st stratum’s mean income X 1st stratum’s % share in total distribution) + (2nd stratum’s mean income X 2nd stratum’s % share in total distribution) + (3rd stratum’s mean income X 3rd stratum’s % share in total distribution) + (4th stratum’s mean income X 4th stratum’s % share in total distribution) + (5th stratum’s mean income X 5th stratum’s % share in total distribution)] / Total % shares

= [(\$10,157 X 0.03) + (\$25,361 X 0.08) + (\$42,233 X 0.14) + (\$65,653 X 0.23) + (\$142,269 X 0.49)] / 100%

= (\$304 + \$2,028 + \$5,912 + \$15,100 + \$69,711) / 1

= \$93,055 per household

Total income, then would be this average income per household multiplied by total number of households[9].

= \$93,055 per household X 105,500,000 households

= \$9,817,302,500,000

Finally, per capita income would be total income divided by total population[10].

= \$9,817,302,500,000 / 281,400,000 people

= \$34,887 per person.

#### CONCLUSIONS

Average income generated by the proposed weighted average formula supported the hypothesis of this study.  Average US income computed (\$34,887) is smaller than the traditional GDP per capita figure for year 2000, which is \$35,100.  Finding is in compliance with the argument that GDP per capita overestimates the real average income.  A crucial analysis now is the historical difference between these two figures (past US average incomes announced and the ones that would have been found if weighted formula were used in those years). Income figures[11] between 1967 and 1992 promises an increasing difference for following years and the future:

 YEAR Average Income Average Income Variance (Weighted Avg Method) (GDP per Capita Method) (GDP method-Weighted method) 1967 \$3,680 \$4,273 \$593 1968 \$3,906 \$4,646 \$740 1969 \$4,314 \$4,935 \$621 1970 \$4,602 \$5,108 \$506 1971 \$4,871 \$5,520 \$649 1972 \$5,409 \$6,107 \$698 1973 \$5,867 \$6,733 \$866 1974 \$6,309 \$7,235 \$926 1975 \$6,757 \$7,907 \$1,150 1976 \$7,387 \$8,612 \$1,225 1977 \$8,146 \$9,546 \$1,400 1978 \$9,047 \$10,810 \$1,763 1979 \$10,367 \$11,766 \$1,399 1980 \$11,226 \$12,755 \$1,529 1981 \$12,232 \$13,843 \$1,611 1982 \$13,154 \$14,220 \$1,066 1983 \$14,013 \$15,694 \$1,681 1984 \$15,214 \$17,014 \$1,800 1985 \$16,395 \$18,054 \$1,659 1986 \$17,548 \$18,821 \$1,273 1987 \$18,841 \$20,049 \$1,208 1988 \$19,950 \$21,360 \$1,410 1989 \$21,564 \$22,484 \$920 1990 \$21,976 \$23,257 \$1,281 1991 \$22,352 \$23,920 \$1,568 1992 \$23,039 \$25,106 \$2,067

Graphically…

As this graphics and pure mathematics logic merge, this assertation concludes with below statement: “Due to the highly unequal distribution of US national income, GDP per capita has been increasingly over-estimating the real average income in America.  A new measure, such as “weighted arithmetic average of GDP” proposed in this paper, is likely to give more accurate figures for the nation’s average income.

APPENDIX

.Table-1: Household Shares of Aggregate Income by Fifths of the Income Distribution between 1967 and 2001.[12]
 YEAR 1st Quintile 2nd Quintile 3rd Quintile 4th Quintile 5th Quintile 1967 4.0 10.8 17.3 24.2 43.8 1968 4.2 11.1 17.5 24.4 42.8 1969 4.1 10.9 17.5 24.5 43.0 1970 4.1 10.8 17.4 24.5 43.3 1971 4.1 10.6 17.3 24.5 43.5 1972 4.1 10.5 17.1 24.5 43.9 1973 4.2 10.5 17.1 24.6 43.6 1974 4.4 10.6 17.1 24.7 43.1 1975 4.4 10.5 17.1 24.8 43.2 1976 4.4 10.4 17.1 24.8 43.3 1977 4.4 10.3 17.0 24.8 43.6 1978 4.3 10.3 16.9 24.8 43.7 1979 4.2 10.3 16.9 24.7 44.0 1980 4.3 10.3 16.9 24.9 43.7 1981 4.2 10.2 16.8 25.0 43.8 1982 4.1 10.1 16.6 24.7 44.5 1983 4.1 10.0 16.5 24.7 44.7 1984 4.1 9.9 16.4 24.7 44.9 1985 4.0 9.7 16.3 24.6 45.3 1986 3.9 9.7 16.2 24.5 45.7 1987 3.8 9.6 16.1 24.3 46.2 1988 3.8 9.6 16.0 24.0 46.3 1989 3.8 9.5 15.8 24.0 46.8 1990 3.9 9.6 15.9 24.0 46.6 1991 3.8 9.6 15.9 24.2 46.5 1992 3.8 9.4 15.8 24.2 46.9 1993 3.6 9.0 15.1 23.5 48.9 1994 3.6 8.9 15.0 23.4 49.1 1995 3.7 9.1 15.2 23.3 48.7 1996 3.7 9.0 15.1 23.3 49.0 1997 3.6 8.9 15.0 23.2 49.4 1998 3.6 9.0 15.0 23.2 49.2 1999 3.6 8.9 14.9 23.2 49.4 2000 3.6 8.9 14.8 23.0 49.8 2001 3.5 8.7 14.6 23.0 50.1

Table-2: Mean Income of each fifth in the income distribution between 1967 and 2001.[13]

 Year 1st Quintile 2nd Quintile 3rd Quintile 4th Quintile 5th Quintile 1967 1,626 4,433 7,078 9,903 17,946 1968 1,832 4,842 7,679 10,713 18,762 1969 1,957 5,216 8,335 11,674 20,520 1970 2,029 5,395 8,688 12,247 21,684 1971 2,126 5,529 8,965 12,745 22,583 1972 2,316 5,898 9,625 13,817 24,806 1973 2,568 6,366 10,402 14,954 26,521 1974 2,911 6,973 11,206 16,181 28,259 1975 3,034 7,204 11,787 17,117 29,809 1976 3,278 7,780 12,762 18,521 32,320 1977 3,513 8,291 13,671 20,018 35,091 1978 3,807 9,112 15,010 21,980 38,791 1979 4,114 10,021 16,495 24,193 42,990 1980 4,483 10,819 17,807 26,219 46,053 1981 4,836 11,589 19,141 28,512 49,942 1982 5,003 12,238 20,195 30,026 54,164 1983 5,239 12,796 21,105 31,667 57,303 1984 5,606 13,634 22,547 33,944 61,648 1985 5,797 14,330 23,735 35,694 65,841 1986 5,944 14,961 24,979 37,622 70,340 1987 6,167 15,584 26,055 39,383 74,897 1988 6,504 16,317 27,291 41,254 78,759 1989 7,021 17,401 28,925 43,753 85,529 1990 7,195 18,030 29,781 44,901 87,137 1991 7,263 18,149 30,147 45,957 88,130 1992 7,288 18,181 30,631 47,021 91,110 1993 7,412 18,656 31,272 48,599 101,253 1994 7,762 19,224 32,385 50,395 105,945 1995 8,350 20,397 34,106 52,429 109,411 1996 8,596 21,097 35,486 54,922 115,514 1997 8,872 22,098 37,177 57,582 122,764 1998 9,223 23,288 38,967 60,266 127,529 1999 9,940 24,436 40,879 63,555 135,401 2000 10,157 25,361 42,233 65,653 142,269 2001 \$10,136 \$25,468 \$42,629 \$66,839 \$145,970

Table-3: Given and computed income data between years 1967 and 1992

 YEAR % of % of % of % of % of Quintile-1 Quintile-2 Quintile-3 Quintile-4 Quintile-5 1967 4.0 10.8 17.3 24.2 43.8 1968 4.2 11.1 17.5 24.4 42.8 1969 4.1 10.9 17.5 24.5 43.0 1970 4.1 10.8 17.4 24.5 43.3 1971 4.1 10.6 17.3 24.5 43.5 1972 4.1 10.5 17.1 24.5 43.9 1973 4.2 10.5 17.1 24.6 43.6 1974 4.4 10.6 17.1 24.7 43.1 1975 4.4 10.5 17.1 24.8 43.2 1976 4.4 10.4 17.1 24.8 43.3 1977 4.4 10.3 17.0 24.8 43.6 1978 4.3 10.3 16.9 24.8 43.7 1979 4.2 10.3 16.9 24.7 44.0 1980 4.3 10.3 16.9 24.9 43.7 1981 4.2 10.2 16.8 25.0 43.8 1982 4.1 10.1 16.6 24.7 44.5 1983 4.1 10.0 16.5 24.7 44.7 1984 4.1 9.9 16.4 24.7 44.9 1985 4.0 9.7 16.3 24.6 45.3 1986 3.9 9.7 16.2 24.5 45.7 1987 3.8 9.6 16.1 24.3 46.2 1988 3.8 9.6 16.0 24.0 46.3 1989 3.8 9.5 15.8 24.0 46.8 1990 3.9 9.6 15.9 24.0 46.6 1991 3.8 9.6 15.9 24.2 46.5 1992 3.8 9.4 15.8 24.2 46.9
 Year Mean Income Mean Income Mean Income Mean Income Mean Income Quintile-1 Quintile-2 Quintile-3 Quintile-4 Quintile-5 1967 1,626 4,433 7,078 9,903 17,946 1968 1,832 4,842 7,679 10,713 18,762 1969 1,957 5,216 8,335 11,674 20,520 1970 2,029 5,395 8,688 12,247 21,684 1971 2,126 5,529 8,965 12,745 22,583 1972 2,316 5,898 9,625 13,817 24,806 1973 2,568 6,366 10,402 14,954 26,521 1974 2,911 6,973 11,206 16,181 28,259 1975 3,034 7,204 11,787 17,117 29,809 1976 3,278 7,780 12,762 18,521 32,320 1977 3,513 8,291 13,671 20,018 35,091 1978 3,807 9,112 15,010 21,980 38,791 1979 4,114 10,021 16,495 24,193 42,990 1980 4,483 10,819 17,807 26,219 46,053 1981 4,836 11,589 19,141 28,512 49,942 1982 5,003 12,238 20,195 30,026 54,164 1983 5,239 12,796 21,105 31,667 57,303 1984 5,606 13,634 22,547 33,944 61,648 1985 5,797 14,330 23,735 35,694 65,841 1986 5,944 14,961 24,979 37,622 70,340 1987 6,167 15,584 26,055 39,383 74,897 1988 6,504 16,317 27,291 41,254 78,759 1989 7,021 17,401 28,925 43,753 85,529 1990 7,195 18,030 29,781 44,901 87,137 1991 7,263 18,149 30,147 45,957 88,130 1992 7,288 18,181 30,631 47,021 91,110 1993 7,412 18,656 31,272 48,599 101,253 1994 7,762 19,224 32,385 50,395 105,945 1995 8,350 20,397 34,106 52,429 109,411 1996 8,596 21,097 35,486 54,922 115,514 1997 8,872 22,098 37,177 57,582 122,764 1998 9,223 23,288 38,967 60,266 127,529 1999 9,940 24,436 40,879 63,555 135,401 2000 10,157 25,361 42,233 65,653 142,269
 YEAR Income per H'shold # of Total Nt'nal Income Population (Weighted Avg Method) Households (Weighted Avg Method) 1967 \$12,025 60,813,000 \$731,276,325,000 198,712,056 1968 \$12,602 62,214,000 \$784,020,828,000 200,706,052 1969 \$13,791 63,401,000 \$874,363,191,000 202,676,946 1970 \$14,567 64,778,000 \$943,621,126,000 205,052,174 1971 \$15,170 66,676,000 \$1,011,474,920,000 207,660,677 1972 \$16,635 68,251,000 \$1,135,355,385,000 209,896,021 1973 \$17,796 69,859,000 \$1,243,210,764,000 211,908,788 1974 \$18,959 71,163,000 \$1,349,179,317,000 213,853,928 1975 \$20,027 72,867,000 \$1,459,307,409,000 215,973,199 1976 \$21,723 74,142,000 \$1,610,586,666,000 218,035,164 1977 \$23,596 76,030,000 \$1,794,003,880,000 220,239,425 1978 \$26,041 77,330,000 \$2,013,750,530,000 222,584,545 1979 \$28,883 80,776,000 \$2,333,053,208,000 225,055,487 1980 \$30,970 82,368,000 \$2,550,936,960,000 227,224,681 1981 \$33,603 83,527,000 \$2,806,757,781,000 229,465,714 1982 \$36,312 83,918,000 \$3,047,230,416,000 231,664,458 1983 \$38,412 85,290,000 \$3,276,159,480,000 233,791,994 1984 \$41,341 86,789,000 \$3,587,944,049,000 235,824,902 1985 \$44,097 88,458,000 \$3,900,732,426,000 237,923,795 1986 \$47,092 89,479,000 \$4,213,745,068,000 240,132,887 1987 \$50,097 91,124,000 \$4,565,039,028,000 242,288,918 1988 \$52,546 92,830,000 \$4,877,845,180,000 244,498,982 1989 \$57,018 93,347,000 \$5,322,459,246,000 246,819,230 1990 \$58,128 94,312,000 \$5,482,167,936,000 249,464,396 1991 \$58,913 95,669,000 \$5,636,147,797,000 252,153,092 1992 \$60,935 96,426,000 \$5,875,718,310,000 255,029,699
 Year Average Income (Weighted Formula) Average Income (GDP Per Capita) 1967 \$12,025 \$4,273 1968 \$12,602 \$4,646 1969 \$13,791 \$4,935 1970 \$14,567 \$5,108 1971 \$15,170 \$5,520 1972 \$16,635 \$6,107 1973 \$17,796 \$6,733 1974 \$18,959 \$7,235 1975 \$20,027 \$7,907 1976 \$21,723 \$8,612 1977 \$23,596 \$9,546 1978 \$26,041 \$10,810 1979 \$28,883 \$11,766 1980 \$30,970 \$12,755 1981 \$33,603 \$13,843 1982 \$36,312 \$14,220 1983 \$38,412 \$15,694 1984 \$41,341 \$17,014 1985 \$44,097 \$18,054 1986 \$47,092 \$18,821 1987 \$50,097 \$20,049 1988 \$52,546 \$21,360 1989 \$57,018 \$22,484 1990 \$58,128 \$23,257 1991 \$58,913 \$23,920 1992 \$60,935 \$25,106

[1] Source: CIA World Factbook 2003

[3] David Schweickart, “After Capitalism: New Critical Theory”. Rowman & Littlefield (2002).

[4] Shapiro & Springer, “The Not-Rich Are Getting Not Richer”, Los Angeles Times (2000)

[5]IISP report-2003”, 5th International Conference of the International Society for Life Quality Studies (2003).

[6]IISP report-2003”, 5th International Conference of the International Society for Life Quality Studies (2003).

[7] Source: World Bank

http://www.worldbank.org/poverty/data/2_8wdi2002.pdf

[8] Source: CIA

http://www.cia.gov/cia/publications/factbook/rankorder/2004rank.html

[9] Source: US Census Bureau

[10] Source: US Census Bureau

[11] Computations in Table-3 at Appendix.

[12] Source of data: US Census Bureau.     http://www.census.gov/hhes/income/histinc/ie3.html

[13] Source of data: US Census Bureau.  http://www.census.gov/hhes/income/histinc/h03.html

This was an entry for The 2004 Moffatt Prize in Economics. See the contest rules for more information.

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