Pr20110321 - Family Income Distribution by Mr Tomas Africa_FINAL (1)

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1 A presentation by Mr. Tomas Africa at Social Weather Stations, Quezon City 18 March 2011 Family Income Distribution in the Philippines, 1985-2009: Essentially the Same 2 A. Median Income B. Income of Top 1% families C. Coefficient of Variation of the Percentiles D. Gini Coefficient E. ABCDE Socio-economic Classification F. A Digression: Cut-offs for the Middle Income Class G. Summary Outline of Presentation

Transcript of Pr20110321 - Family Income Distribution by Mr Tomas Africa_FINAL (1)

Page 1: Pr20110321 - Family Income Distribution by Mr Tomas Africa_FINAL (1)

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A presentation by Mr. Tomas Africa

at Social Weather Stations, Quezon City

18 March 2011

Family Income Distribution in the

Philippines, 1985-2009:

Essentially the Same

2

A. Median Income

B. Income of Top 1% families

C. Coefficient of Variation of the Percentiles

D. Gini Coefficient

E. ABCDE Socio-economic Classification

F. A Digression: Cut-offs for the Middle

Income Class

G. Summary

Outline of Presentation

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Table 1. Median Income and Income Distribution, 1961 - 2009

Family Income 1961 1985 2000 2003 2006 2009

Median income

(x P1,000) 1 20 89 95 111 135

% Income Share of

upper 50% families 82 80 82 81 81 80

% Income Share of

lower 50 % families 18 20 18 19 19 20

From 1961 to 2009, nearly half a century:

• Upper 50 percent of families had 80 percent of

income.

• Lower half had 20 percent.

As of 2009, the distribution appeared to be the

same at the end of Martial Law days.

A. Median Income

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Table 2. Top 1% Families and Bottom % Families – Income Comparison

1985 2000 2003 2006 2009

Number of Top 1% Families (x1000) 100 150 165 174 185

with

Aggregate Income (PhP billion) 31.4 251.2 235 256.3 342.7

Equivalent to

Number of Families (in millions) 3.15 5.8 5.3 5.2 5.5

% of Total 32% 38% 32% 30% 30%

with

Aggregate Income (PhP billion) 31.3 249.6 227.1 257.9 343

B. Income of Top 1% Families

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Table 2. Top 1% Families and Bottom % Families – Income Comparison

1985 2000 2003 2006 2009

Number of Top 1% Families (x1000)100 150 165 174 185

with

Aggregate Income (PhP billion) 31.4 251.2 235 256.3 342.7

Equivalent to

Number of Families (in millions) 3.15 5.8 5.3 5.2 5.5

% of Total 32% 38% 32% 30% 30%with

Aggregate Income (PhP billion) 31.3 249.6 227.1 257.9 343

The 1:30 ratio in 2009 remained, or stabilized, at the same ratio in

2006.

B. Income of Top 1% Families

The top individual taxpayers of 2009 released by the Bureau of

Internal Revenue (BIR) in accordance with Section 71 of the

National Internal Revenue Code of 1997. These individuals may not

have been covered by the survey as their transactions would be

categorized as ‘statistical rare events’ and thus would have little

chance or probability of being selected as samples.

B. Income of Top 1% Families

Table 3. BIR Top Individual Taxpayers 2009

Rank Taxpayer Tax Due Rank Taxpayer Tax Due

1 Elaine B. Gardiola P59.54M 6 Henry Sy, Sr P25.18M

2 Wilfredo B. Revillame P57.25M 7 Carlos D.C. Ejercito P25.02M

3 Ronaldo R. Soliman P36.70M 8 Bonifacio D. Gumboc, Jr P24.74M

4 Ramon S. Ang P26.44M 9 Ma. Teresa P. Gallego P24.45M

5 Oscar M. Lopez P25.70M 10 Felipe L. Gozon P22.20M

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B. Income of Top 1% Families

• Families in top 1 percent in income distribution might be

under-represented in FIES.

• Highest gross income in 2009 FIES P 30.4 million.

• Using a 28.50% effective rate on the average; i.e. that is

how much of gross income is paid as tax (from Former

Finance Undersecretary Milwida Guevarra). Tax Due of

biggest income earner in 2009 FIES roughly estimated

at P 8.65 million.

• From BIR data, the respondent could be among the top

85 taxpayers.

Table 3. BIR Top Individual Taxpayers 2009

Rank Taxpayer Tax Due Rank Taxpayer Tax Due

84 Eric Van Oppens P8.83M 85 John Lloyd Cruz P8.60M

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B. Income of Top 1% Families

• The total income of 100th percentile in 2009 FIES

P 342.74 billion.

• The percentage undercount of the top 1 percent can

be roughly estimated to be 1.3 percent (PhP 4.45

billion divided by PhP 342.74 billion).

• This is not too significant an amount to alter

percentage shares of the income distribution.

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C. Coefficient of Variation of Percentiles

Coefficient of variation (CV) is the

standard error expressed in terms of the

arithmetic mean (average).

It is a measure of dispersion, a measure

of disparity.

CV is useful because the standard error of

samples can be better understood in the

context of the arithmetic mean of the data.

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C. Coefficient of Variation of

Percentiles, 2009

Inc ome C Vs F IE S 2009

-

1.00

2.00

3.00

4.00

5.00

1st

4th

7th

10th

13th

16th

19th

22nd

25th

28th

31st

34th

37th

40th

43rd

46th

49th

52nd

55th

58th

61st

64th

67th

70th

73rd

76th

79th

82nd

85th

88th

91st

94th

97th

100th

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C. Coefficient of Variation of

Percentiles, 2006

Income CVs FIES 2006

0.00%

0.50%

1.00%

1.50%

2.00%

2.50%

3.00%

3.50%

1st 4th

7th

10th

13th

16th

19th

22nd

25th

28th

31st

34th

37th

40th

43rd

46th

49th

52nd

55th

58th

61st

64th

67th

70th

73rd

76th

79th

82nd

85th

88th

91st

94th

97th

100th

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C. Coefficient of Variation of

Percentiles, 2003

Income CVs FIES 2003

0.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%

7.00%

8.00%

Perce

ntile 3r

d6t

h9t

h12

th15

th18

th21

st24

th27

th30

th33

rd36

th39

th42

nd45

th48

th51

st54

th57

th60

th63

rd66

th69

th72

nd75

th78

th81

st84

th87

th90

th93

rd96

th99

th

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C. Coefficient of Variation of

Percentiles, 2000

Income CVs FIES 2000

0.00%

2.00%

4.00%

6.00%

8.00%

10.00%

12.00%

1st 4th 7th10th

13th16th

19th22nd

25th28th

31st34th

37th40th

43rd46th

49th52nd

55th58th

61st64th

67th70th

73rd76th

79th82nd

85th88th

91st94th

97th

100th

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C. Coefficient of Variation of

Percentiles, 1985

Income CVs FIES 1985

0.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%

7.00%

Percentile 3rd 6th 9th

12th15th

18th21st

24th27th

30th33rd

36th39th

42nd45th

48th51st

54th57th

60th63rd

66th69th

72nd75th

78th81st

84th87th

90th93rd

96th99th

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C. Coefficient of Variation of

Percentiles

Any significant change aside from those at the

tails, both at lowest & highest ends?

The general look of the distribution is that of a

‘flat-liner’, bereft of activity showing change.

Family incomes are clustered closely

together.

Groupings due to a cut-off, for instance, a

point/line representing the poverty threshold,

would appear to be insufficient

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C. Coefficient of Variation of

Percentiles

In 2009, eighty-nine

(89) of the 100

percentile CVs

were no greater

than 0.1 percent

Table 4. Distribution of

Percentile CVs, 2009

CV (in %) Frequency

0.01 -0.1 89

0.11 - 0.2 6

0.21 - 0.3 2

0.31 - 0.4 --

0.41 - 0.5 1

0.51 - 0.6 --

0.61 - 0.7 --

0.71 - 0.7 --

0.81 - 0.9 --

0.91 – 1.0

1.01 +

1

1

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C. Coefficient of Variation of

Percentiles

Income alone may not be a valid

indicator of poverty

classification because of

observed ‘homogeneity’ of

incomes

--- multidimensionality of poverty

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D. GINI COEFFICIENT

Gini coefficient - a measure of the

inequality of a distribution, a value of 0

expressing total equality and a value of 1

maximal inequality.

Gini coefficient - usually defined

mathematically based on the Lorenz

curve, which plots the proportion of total

income of population (y axis) that is

cumulatively earned by the bottom x% of

population (see diagram).

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D. GINI COEFFICIENT

• However, a low coefficient does not always

mean an ideal condition.

• It could be that many incomes are similar

(either low or high).

• In the Philippine example, the

acknowledged ‘income-poor’ Autonomous

Region of Muslim Mindanao (ARMM) has

the lowest coefficient followed by ‘richer’

regions, such as National Capital Region

(NCR) & Central Luzon (Region III)

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D. GINI COEFFICIENT

Table 4. Gini ratios, 2009

Region Ratio Region Ratio

N C R 0.3953 REGION 7 0.4601

C A R 0.4212 REGION 8 0.4841

REGION 1 0.4086 REGION 9 0.4738

REGION 2 0.4425 REGION 10 0.4737

REGION 3 0.3727 REGION 11 0.4275

REGION 4 A 0.4063 REGION 12 0.4425

REGION 4 B 0.4004 CARAGA 0.4595

REGION 5 0.4164 ARMM 0.2948

REGION 6 0.4197

ARMM had lowest Gini ratio while Regions

8, 9 and 10 had the highest ratios

Table 5. Gini ratios, 2006

Region Ratio Region Ratio

N C R 0.3988 REGION 7 0.4639

C A R 0.4418 REGION 8 0.4828

REGION 1 0.3953 REGION 9 0.5054

REGION 2 0.4216 REGION 10 0.4806

REGION 3 0.3994 REGION 11 0.4225

REGION 4A 0.4082 REGION 12 0.4006

REGION 4B 0.4106 CAAGA 0.4452

REGION 5 0.4428 ARMM 0.3113

REGION 6 0.4326

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D. GINI COEFFICIENT

Movement of coefficient at national level

showed an indication of more equality or less

inequality over the years, with highest being in

1997 and 2000

Table 6. Gini Coefficient, Philippines

Year Gini Coefficient

1985 0.4466

1988 0.4446

1991 0.4680

1994 0.4507

1997 0.4872

2000 0.4822

2003 0.4605

2006 0.4580

2009 0.4484

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D. GINI COEFFICIENT

Gini Coefficients, Philippines, 1985-2009

0.42

0.43

0.44

0.45

0.46

0.47

0.48

0.49

0.5

1 2 3 4 5 6 7 8 9

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D. GINI COEFFICIENT

Of 135 countries and dependencies

listed in the World Fact Book of the

Central Intelligence Asia (CIA), the

following rankings can be obtained.

It is clear that the Gini ratio is not

always reflective of state of a

country’s development.

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D. GINI COEFFICIENT

Table 7. Countries with the

lowest Gini Ratios

CountryGini

Coefficient

Reference

Year

Sweden 23 2005

Norway 25 2008

Austria 26 2007

Czech Republic 26 2005

Luxembourg 26 2005

Malta 26 2007

Serbia 26 2008

Slovakia 26 2005

Albania 26.7 2005

Germany 27 2006

Table 8. Countries with the

highest Gini Ratios

CountryGini

Coefficient

Reference

Year

Brazil 56.7 2005

Colombia 58.5 2008

Bolivia 59.2 2006

Haiti 59.2 2001Central African

Republic 61.3 1993

Sierra Leone 62.9 1989

Botswana 63 1993

Lesotho 63.2 1995

South Africa 65 2005

Namibia 70.7 2003

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D. GINI COEFFICIENT

Among the Association of Southeast Asian

Nations (ASEAN), it was Laos with the

lowest Gini, and Singapore with the highest.

Table 9. ASEAN Countries Gini Ratios

CountryGini

Coefficient

Reference

Year

Laos 34.6 2002

Vietnam 37 2004

Indonesia 39.4 2005

Cambodia 43 2007 est.

Thailand 43 2006

Philippines 45.8 2006

Malaysia 46.1 2002

Singapore 48.1 2008

Myanmar N/A N/A

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Market/opinion researchers classify according

through proxies of wealth/assets, aside from

measure of income, to segment the (consumer)

market.

• Conditions in community where household

is

• Type of materials used for house

• Household furnishing

• Ownership of house and/or lot

E. ABCDE SOCIO-ECONOMIC

CLASSIFICATION

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E. ABCDE SOCIO-ECONOMIC

CLASSIFICATION

Table 10: Percent Distribution of Families, by Socio-

Economic Class

Socio Economic

Class

Percent Share of Families to Total

2007 2010 My guess-timate

ABC 7 9 10

of which: AB n.a. 0.3* 1

C n.a. 8.6 9

D 68 62 60

E 25 29 30

Source: Pulse Asia, in consultation with Dr. Ana Tabunda

Note: * - Undercounted due to refusals of AB respondents

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• From the 16 April 2007 release of Pulse Asia,

its nationally-representative sample has seven

(7) percent making up classes A, B, and C;

sixty-seven (67) percent, class D; and twenty-

five (25) percent, class E. This breakdown has

a sampling error of +/- 3 percent.

• Statistically speaking, classes ABC may be 4

to 10 percent of the population; class D, 64-70

percent; and class E, 22-28 percent.

E. ABCDE SOCIO-ECONOMIC

CLASSIFICATION

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In 2010, the breakdown became: 9

percent for class ABC; 62 percent for

class D; and 29 percent for class E.

Class ABC can be further subdivided into

class AB, 0.3 percent, and class C, 8.6

percent, although Pulse Asia estimates

an undercount of class AB.

E. ABCDE SOCIO-ECONOMIC

CLASSIFICATION

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While statistical rigor will not be as

robust, we can apply the above

percentages [my guess-timates] to the

income distribution and find out how

much income these classes earned

during the reference years.

E. ABCDE SOCIO-ECONOMIC

CLASSIFICATION

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E. ABCDE SOCIO-ECONOMIC

CLASSIFICATION

Table 11. Percent Distribution of Families & Incomes,

by Socio-Economic Class, 1985

Class

Families Cumulative Income Average

IncomeNo. Share Amount Share

(x 1000) % (x PhP 1 mil.) % (x PhP 1 thsd.)

ABC985

10 111,420 36 113

D 5,908 60 165,857 54 28

E 2,954 30 28,498 9 10

Total 9847 100 305,775 100 31

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E. ABCDE SOCIO-ECONOMIC

CLASSIFICATION

Table 12. Percent Distribution of Families & Incomes,

by Socio-Economic Class, 2000

Class

Families Cumulative Income Average

IncomeNo. Share Amount Share

(x 1000) % (x PhP 1 mil.) % (x PhP 1 thsd.)

ABC 1,507 10 838,445 38 556

D 9,043 60 1,174,919 54 130

E 4,522 30 173,886 8 38

Total 15072 100 2,187,250 100 145

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E. ABCDE SOCIO-ECONOMIC

CLASSIFICATION

Table 13. Percent Distribution of Families and

Incomes, by Socio-Economic Class, 2003

Class

Families Cumulative Income Average

IncomeNo. Share Amount Share

(x 1000) % (x PhP 1 mil.) % (x PhP 1 thsd.)

ABC 1,648 10 884,478 36 537

D 9,888 60 1,346,581 55 136

E 4,944 30 206,191 8 42

Total 16480 100 2,437,250 100 148

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E. ABCDE SOCIO-ECONOMIC

CLASSIFICATION

Table 14. Percent Distribution of Families and Incomes,

by Socio-Economic Class, 2006

Class

Families Cumulative Income Average

IncomeNo. Share Amount Share

(x 1000) % (x PhP 1 mil.) % (x PhP 1 hsd.)

ABC 1,740 10 1,082,478 36 622

D 10,442 60 1,669,309 56 160

E 5,221 30 254,316 8 49

Total 17,403 100 3,006,104 100 173

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E. ABCDE SOCIO-ECONOMIC

CLASSIFICATION

Table 15. Percent Distribution of Families and

Incomes, by Socio-Economic Class, 2009

Class

Families Cumulative Income Average

IncomeNo. Share Amount Share

(x 1000) % (x PhP 1 mil.) % (x PhP 1 thsd.)

ABC 1,845 10 1,343,697 35 728

D 11,071 60 2,117,478 56 191

E 5,536 30 343,150 9 62

Total 18,452 100 3,804,325 100 206

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When class ABC is further

subdivided into class AB and class

C, it becomes apparent that class

AB could be the top 1 percent, with

an income share equal to that of

class E.

E. ABCDE SOCIO-ECONOMIC

CLASSIFICATION

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E. ABCDE SOCIO-ECONOMIC

CLASSIFICATION

Table 15-A. Percent Distribution of Families and Incomes,

by Modified Socio-Economic Class, 2009

CLASS

Families Cumulative IncomeAverage

IncomeNo. Share Amount Share

(x 1000) % (x PhP 1 mil.) % (x PhP 1 thsd.)

AB 185 1 342,736 9 1,857

C 1,661 9 1,000,960 26 603

D 11,071 60 2,117,478 56 191

E 5,536 30 343,150 9 62

Total 18,452 100 3,804,325 100 206

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In summary, the shares of income of class

ABC ranged from 35-38, class D, from 54-

56, and class E, from 8-9 percent during the

period from 1985-2009, nearly a quarter-

century

E. ABCDE SOCIO-ECONOMIC

CLASSIFICATION

The good news is that the income

distribution has not worsened. The bad

news is that it has remained essentially the

same..

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F. A DIGRESSION: CUT-OFF FOR

MIDDLE INCOME CLASS?

Many have been asking about the middle

class in the Philippines but literature on

this has been scarce.

• As an exercise & perhaps to start a

discussion on what would be the middle-

class, I would proceed with a simplistic

assumption of equal income shares

across groups.

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F. A DIGRESSION: CUT-OFF FOR

MIDDLE INCOME CLASS?

If income is to be divided into five (5) more or less equal

shares [1st 20% share, next 20% share,…, highest 20%

share] the cut-offs will fall in these percentiles:

Table 16. Percentile Cut-offs in an Income

Distribution Divided into Five Equal Groups

Class 1985 2000 2003 2006 2009

A & B 96 97 96 96 96

B & C 88 89 88 87 87

C & D 73 75 74 74 73

D & E 49 53 51 51 50

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F. A DIGRESSION: CUT-OFF FOR

MIDDLE INCOME CLASS?

Family Income, by Percentile, 2009

-

50,000,000,000

100,000,000,000

150,000,000,000

200,000,000,000

250,000,000,000

300,000,000,000

350,000,000,000

400,000,000,0001s

t

4th

7th

10th

13th

16th

19th

22nd

25th

28th

31st

34th

37th

40th

43rd

46th

49th

52nd

55th

58th

61st

64th

67th

70th

73rd

76th

79th

82nd

85th

88th

91st

94th

97th

100t

h

DE BC A

poverty

threshold

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F. A DIGRESSION: CUT-OFF FOR

MIDDLE INCOME CLASS?

If income is divided into three (3) more or less

equal parts, the cut-offs will fall in these

percentiles:

Table 17. Percentile Cut-offs in an Income

Distribution Divided into Three Equal Groups

Class 1985 2000 2003 2006 2009

A & B 91 92 91 91 91

B & C 66 69 67 67 66

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Family Income, by Percentile, 2009

-

50,000,000,000

100,000,000,000

150,000,000,000

200,000,000,000

250,000,000,000

300,000,000,000

350,000,000,000

400,000,000,0001s

t

4th

7th

10th

13th

16th

19th

22nd

25th

28th

31st

34th

37th

40th

43rd

46th

49th

52nd

55th

58th

61st

64th

67th

70th

73rd

76th

79th

82nd

85th

88th

91st

94th

97th

100t

h

F. A DIGRESSION: CUT-OFF FOR

MIDDLE INCOME CLASS?

C B A

poverty

threshold

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F. A DIGRESSION: CUT-OFF FOR

MIDDLE INCOME CLASS?

• Estimates of class ABC (Table 16)

show 11-13 percent, not far from

percentages (9-10) in Table 10.

• However, estimates of lower class that

would be of concern; in Table 16, about

50 percent (one-half), and in Table 17,

about 67 percent (two-thirds).

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F. A DIGRESSION: CUT-OFF FOR

MIDDLE INCOME CLASS?

• The middle class would be

somewhere in-between. In Table 16,

the size of middle class [C] is about 15

percent, and if measured as difference

between top (A) and bottom (E)

classes, about 25 percent.

• In Table 17, about 25 percent.

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F. A DIGRESSION: CUT-OFF FOR

MIDDLE INCOME CLASS?

The National Statistical Coordination Board

(NSCB) in its website http://www.nscb.gov.ph/headlines/StatsSpeak/2010/061510_

rav_joe.asp#table1 posted a feature article on ‘How

Rich is Rich?’ One of tables as presented below

can be compared to Table 17, with a significant

difference with respect to high income class.

This however compares with Pulse Asia

estimate of 0.3 percent of class AB in Table 10.

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F. A DIGRESSION: CUT-OFF FOR

MIDDLE INCOME CLASS?

Table 18. Percent Share and Magnitude of Families, by Income Class:

2000, 2003, and 2006

Year

Income ClassEstimated

Total

Number of

Families

Low Income Middle Income High Income

Level Percent Level Percent Level Percent

2006 14,065,921 80.8 3,317,824 19.1 19,738 0.1 17,403,483

2003 13,182,297 79.9 3,286,010 19.9 25,849 0.2 16,494,156

2000 11,598,258 77 3,422,524 22.7 51,160 0.3 15,071,942

Source: Special computations made by the NSCB Technical Staff using the results

of the 2000, 2003, and 2006 Family Income and Expenditures Survey of the National

Statistics Office

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G. SUMMARY

From the following data and

discussion we can surmise that

development efforts for the past

five (5) decades have failed to

effect an equitable/equal

distribution of income.

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G. SUMMARY

The income split at the

median has been at 82:18 to

80:20 in favor of the families

at the upper 50 percent over

the past 50 years.

50

G. SUMMARY

The top one (1) percent families earned

income equivalent to income earned by 32

percent of the families at the bottom of the

income ladder in 1985. This peaked to 38

percent in 2000, was replicated in 2003,

and moved down to 30 percent in 2006 and

2009.

In twenty-five (25) years the top 1 percent

gave up two (2) percent to the families at

the bottom rungs.

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G. SUMMARY

The CVs show very little variation

at the percentiles except those at

the extreme ends, indicating little

spread of income across the entire

distribution. (Sampling

implications?)

52

G. SUMMARY

The Gini coefficient, with its measure

of inequality subject to

misinterpretation, had moved up

during the ‘Baht’ financial crisis, and

down from then on. The Gini ratio of

the Philippines is neither among the

highest nor the lowest in the world,

including ASEAN.

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G. SUMMARY

The shares of income of class ABC

ranged from 35-38%; class D, from

54-56%; and class E, from 8-9 %

percent the past 25 years, from 1985-

2009.

My computations and that of NSCB

seem to agree on a very large ‘low’

income class.

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G. SUMMARY

• Utter lack of information on distribution

of family income which the government,

particularly the NSO and the statistical

system, need to address.

• Perhaps one of reasons why the

distribution has generally remained

unchanged is because even if many think

that this is so, there has been insufficient

empirical evidence to establish its extent

and chronicity

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G. SUMMARY

• I also urge the NSCB to come up with an

official definition of the often-used ABCDE

socio-economic classification & the

‘generic’ low-middle-high income classes in

cooperation with academe and private

sector. Many policy and decision-makers &

the general public have accepted & used

these rather than deciles, quintiles and

percentiles. These can also help improve

statistical literacy of society, in this case

understanding income distribution.

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