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  • 标题:The distribution of purchasing power in Pakistan, 1985-86.
  • 作者:de Kruijk, Hans
  • 期刊名称:Pakistan Development Review
  • 印刷版ISSN:0030-9729
  • 出版年度:1989
  • 期号:December
  • 语种:English
  • 出版社:Pakistan Institute of Development Economics
  • 摘要:Suppose that you and I earn the average income of Pakistan and that we are looking at a parade in which the whole population of Pakistan takes part. It is a spectacular parade because the size of all marchers is proportionate to their income. We have the average height. Anyone who earns more than the average is taller than we are; anyone who earns less than the average is smaller. The procession is organized in such a way that the smallest walks in front and the tallest in the rear. The parade moves at uniform speed and its duration is one hour exactly. What do we see? What is the size of the marchers in front and in the rear? Who passes by during the first ten minutes, the second ten minutes, etc.? Where do they live, in which province, in urban or in rural areas? How long does it take before we see people of our own length? Who are they? Section 4 presents the Pakistani Parade and tries to answer these questions. (1)
  • 关键词:Income distribution;Personal income;Purchasing power

The distribution of purchasing power in Pakistan, 1985-86.


de Kruijk, Hans


I. INTRODUCTION

Suppose that you and I earn the average income of Pakistan and that we are looking at a parade in which the whole population of Pakistan takes part. It is a spectacular parade because the size of all marchers is proportionate to their income. We have the average height. Anyone who earns more than the average is taller than we are; anyone who earns less than the average is smaller. The procession is organized in such a way that the smallest walks in front and the tallest in the rear. The parade moves at uniform speed and its duration is one hour exactly. What do we see? What is the size of the marchers in front and in the rear? Who passes by during the first ten minutes, the second ten minutes, etc.? Where do they live, in which province, in urban or in rural areas? How long does it take before we see people of our own length? Who are they? Section 4 presents the Pakistani Parade and tries to answer these questions. (1)

But before being able to form the queue by putting everybody in its correct position, we need to discuss the way of estimating the size of each person, and therefore, the choice of the concepts of income and income units (Section 3), the data base, the choice between using grouped data versus tape data, and the related type of computer required (PC versus mainframe) for these calculations (Section 2).

Actually, the contribution of this paper is twofold. First, the presentation of the Pakistani Parade, and secondly, after having made adjustments for economies of scale of households earlier by using equivalence scales [Kruijk (1987)], this paper standardizes these adjusted household incomes further by correcting for differences in average price levels between provinces and between urban and rural areas as announced but not executed in Kruijk (1986). After these adjustments, the term 'distribution of income' is no longer a proper description of what finally is ranked. Accordingly, the title of the present paper is now called 'The distribution of purchasing power in Pakistan, 1985-86'.

2. THE DATA BASE

Although not ideal, the Household Income and Expenditure Survey (HIES) is the best data source on household incomes in the country. It presents data on household composition, sources and levels of household income, structures and levels of household expenditures. Most likely, the Pakistani HIES is--like all other HIESs in the world--incomplete and bad at the top. The rich are not easily accessible to investigators and their extent of under-representation is not known. In a situation where data are consistently incomplete, there is no other option than being pragmatic. Unfortunately, it is not always possible to check and supplement HIES data by data from other sources like income tax data from the Central Board of Revenue (as the late Javaid Azfar had done in the 1970s).

Further, to raise the sample size to 'actual' population figures, population trends are extrapolated by applying annual compound growth rates (of the in-between Census period of September 1972--March 1981)at the most disaggregated level available in published form, i.e. population figures of urban and rural areas by province (eight regions).

This paper makes use of published data in the form of grouped data and not of unpublished individual income data from computer tapes. Undoubtedly, inequality calculated on the basis of grouped data is an under-estimation of true inequality because inequality within brackets is neglected. However, as reported earlier on the basis of data of other countries, the extent of under-estimation is insignificant in cases where the number of income groups is more than ten [Kruijk (1986)]. In the Pakistan case with twelve income groups, the level of Theft coefficients calculated on the basis of published grouped data appears to be consistently (overall Pakistan, urban and rural separate) about 0.002 points lower than on the basis of tape data for the year 1984-85 at a level of about 0.270, which is an under-estimation of about one percent only [Government of Pakistan (1989)]. This implies that published data can be used, and--more important--that a (super)mini or mainframe computer which can handle large data tapes is not required. A personal computer is adequate enough, which makes this kind of analysis accessible to a much wider group of researchers. In fact, all calculations presented in this paper are constructed in an ordinary spreadsheet.

3. CONCEPTS OF INCOME AND INCOME UNITS

Choice of the Income Unit

The intention of forming a parade is to get a picture of the distribution of welfare in the country. If the size of each marcher would be based on his or her individual income like in Pen's parade for the Netherlands and for England, [see Pen (1971) and The Economist (1987)] it happens that some wives and children, who supplement the family income, are reduced to pygmies and have to walk in the front of the parade, whereas the husband/father, who is the main income earner of the family, might be taller than average. This situation is not acceptable in our parade. It is more satisfying to organize the parade in such a way that everybody joins in the parade and that members of the same household have equal size and walk hand in hand alongside. In that case, it seems more appropriate to consider household incomes instead of individual incomes as the basis for everybody's size, but unfortunately it is not as easy as that. Measuring welfare on the basis of income per household ignores the reality that households differ in size and composition. A one-person household earning Rs 1000 per month is much better off, of course, than a six-person household with Rs 1000 per month. An often used remedy to adjust for household size is simply to deflate household income by household size, so that income is expressed in per capita terms. However, such an approach is equally unacceptable because in that case it is believed that a single person with Rs 1000 is as well off as a two-person household with Rs 2000, and a six-person household with Rs 6000, which obviously is not so.

Economies of scale in household consumption cannot be denied. However, it is not easy to suggest a proper equivalence scale. Since the one I proposed earlier has been rejected by Kemal (1987), the old proposal is replaced, herewith, by a new suggestion for an equivalence scale which has been applied in this paper and which has the advantage of being very simple: the head of the household is one (as always), but now any additional person counts for 0.5. This scale implies that a one-person household with Rs 1000 has the same level of welfare as a two-person household with Rs 1500, a three-person household with Rs 2000, etc. The result of using this scale to adjust for economies of scale in the household is presented in Table 2.

Choice of the Income Concept

Although standardizing household incomes by taking the size of the household into account is an improvement, it is still not sufficient for estimating the size of each person. Generally speaking, the cost of living in rural areas is lower than in the urban areas. In other words, one rupee has more purchasing power in rural areas than in urban areas. Welfare estimates should take these price differences into account. The HIES presents detailed data on family expenditures (in rupees) and on shopping-baskets (in units) disaggregated into provinces and urban and rural areas (eight regions). On the basis of these figures, it is not difficult to calculate prices of the various items per region. Table 1 present these prices as well as a (weighted) average family shopping-basket which is constructed on the basis of regional shopping-baskets. With this information it is feasible to estimate regional price indexes with the qualification that these are based on food items only.

After having estimated these regional price indexes all (household size adjusted) family incomes are first divided by their index before determining the size of all marchers. The effect of this price adjustment for the level of average income in each region is indicated in Table 2. It is clear that the sequence of e.g. all residents of urban areas in Punjab in file parade changes with respect to residents of other areas, but not with respect to each other, because all (adjusted) household incomes of urban Punjab are divided by the same amount i.e. 1.037. Both adjustments (for household size and for regional prices differences) can be summarized in the following formula:

Y [stan.sub.i, r] = [Y.sub.i] x 1 + 0.5([[bar.S] - 1])/1. + 0.5 ([S.sub.i] - 1) x 100/[p.sub.r]

in which:

Y [stan.sub.i,r] = Standardized income of household i in region r;

[Y.sub.i] = Income of household i;

[bar.S] = Average household size ([bar.S] = 6.34 in 1985-86);

[S.sub.i] = Size of household i; and

[P.sub.r] = Price index of region r.

Table 2 shows that the standardization mentioned above have a substantial impact on the ranking of average monthly household incomes of the eight regions. According to unstandardized HIES data, Punjab ranks last in urban areas and third in rural areas, which is not in line with the popular perception of its being the most prosperous province [see also Naseem (1986)]. After standardization the picture becomes much more in line with commonsense. Now Punjab ranks second in urban areas after Sind which is dominated by cosmopolitan Karachi; in rural areas Punjab has now the highest average income, while Baluchistan and NWFP are the poorest and not the richest provinces in rural areas as suggested by unadjusted figures.

4. THE PAKISTANI PARADE

After having discussed the way in which everybody's size has been determined, it is high time to watch the parade. Graph 1 facilitates to visualize the cortege a bit, each bar illustrates one minute of the parade. Table 3 shows the Pakistani Parade in figures. Each major group of Tables 3 and 4 represents ten minutes. Table 4 gives an indication of the over-representation of the eight regions (the shaded segments) in the six groups of ten minutes In this paper only one attribute has been selected, viz. the eight regions of the country. Of course, it is possible-and also desirable--to extend the number of characteristics like occupation, working status, age, level of education, etc. of the over-represented parties in each group.

What do we see? In the first seconds, we see very tiny gnomes pass by, the size of a match-stick. (2) But this does not go on for long, the average length during the very first minute is already more than two feet (see Graph 1 and Table 3). During the first ten minutes an over-represented group from rural Baluchistan, rural Punjab and urban NWFP passes by (see Table 4). The impact of standardization on each position in the queue is illustrated once more by Table 3. The average size of the marchers going by after exactly ten minutes (NWFP-urban) is not (according to unstandardized incomes) twice as high as those of the first minute (Baluchistan-urban), but they are less than fifty percent taller. They are still dwarfs of about 3.5 feet. During the second period of ten minute, the size of the marchers does not increase much. After twenty minutes people are about four feet. In this group residents from rural areas of NWFP and Baluchistan are highly over-represented. As far as townsmen are concerned, Punjab and Baluchistan are over-represented. Twenty minutes is a long time to keep seeing small people passing by who barely reach to our midriff.

[GRAPHIC 1 OMITTED]

Looking in the direction of the approaching parade to see what we can expect next, we still cannot observe normal people. We keep seeing dwarfs. After half an hour the size of the marchers is less than 4.7 feet. During the last ten minutes, we have seen many Sindhi's. In fact, this is the first group where Sindhis--both from rural and from urban areas are over-represented. It takes exactly forty minutes before we can see people of our own size arriving (average standardized household income is 1900 rupees per month in 1985-86). They mainly belong to the rich of the countryside. The group of 'normal' people is fairly small. After fifty minutes the size of the marchers has increased to over 6.5 feet. More than fifty percent of the richest group are city-dwellers, while the overall percentage of urban population is about thirty percent only. Urban areas of all the four provinces are over-represented in the richest group. The average size of marchers passing by in the last few minutes increases rapidly. Average size in the last minute is nearly twenty feet. During the last few seconds, we see people like tower flats. The highest household income reported in 1984-85 HIES corresponds with a size of about five hundred feet. This giant family has an income of Rs 244,000 per month. (3)

5. CONCLUSIONS

First, the impact of standardization is substantial. Nominal incomes have to be adjusted for household size, economies of scale within households, and last but not least for regional price differences.

Secondly, the parade is a more fascinating and appealing way of looking at the distribution of income than other inequality indicators like Gini or Theft coefficients. The parade is mainly a parade of dwarfs with a few giants only. It takes forty 'minutes before average income passes by.

Thirdly, the parade has the attractive property that the participants can be identified which is extremely useful for policy preparation and for analyzing changes in the relative positions of household groups over time. Distribution indicators like Gini and Theft coefficients are not affected by a mutual exchange of households in the distribution. In other words, if two households exchange positions in the queue, the distribution itself will remain the same. However, exchange of positions is important information for understanding determinants of the distribution and for analyzing the impact of distribution policies. As mentioned earlier, in this paper only one attribute has been selected, viz. regions. Of course, it is possible to extend the number of characteristics like occupation, working status, age, education, source of income, etc.

Finally, although these kind of exercises do not give great precision, it is a challenge to keep trying to be as accurate as possible and to see what can be done with the available data.

Comments on "The Distribution of Purchasing Power in Pakistan, 1985-86"

Kruijk has an interesting paper. It is a snapshot of Pakistan's income distribution/purchasing power at one point in time, 1985-86. Jan Pen described the typical income distribution in a market economy as a parade of countless dwarfs and a few giants in 1971. Kruijk uses the same device.

Estimation

He uses HIES grouped data. The basic unit used for comparison is the household. To make different family sizes equivalent, household income is divided by a deflated family Size. Dividing income by family size alone does not make per capita incomes comparable. Economies of scale in household consumption accrue to larger families. So dividing by family size reduces income for large households disproportionately. Kruijk alternatively uses 1 for head of household, and 0.5 for each family member. I suggest alternatively 1 for adults and 0.5 for children.

Results

The most important aspect of this paper is that it does a regional comparison of purchasing power. Given the debate on regional access to resources, this kind of analysis is needed. He uses purchasing power/household to rank provinces. All urban areas have the highest rank, followed by rural areas in the following order.

Urban : Sind, Punjab, Baluchistan, NWFP.

Rural : Punjab, Sind, Baluchistan, NWFP.

So the two most prosperous provinces are Punjab and Sind. The result also shows a clear urban bias.

He ranks provinces within each income group. The sample is divided into 6 income groups. For a non-biased distribution, provincial distribution within each income group should be same as provincial distribution of the population c.f. rural Punjab has 39 percent of total population. So within each income group rural Punjab should have a 39 percent share. But actually in the poorest group rural Punjab has a 52 percent share so it is over-represented. So rural Punjab is both the most prosperous and has the largest percentage of the poor. This polarisation of income is a very interesting result, a product of the high rate of growth and the particular pattern of growth in rural Punjab.. However this is not pointed out by Kruijk.

In fact this is the fundamental shortcoming of this paper, that it presents a set of interesting statistics but makes no attempt to analyse them. There is no attempt to establish a regional pattern to this income distribution. There is no attempt to explain a priori why a particular regional pattern should hold. No hypotheses about growth of income across provinces. There is no attempt to explain a fortiori why a regional pattern does hold--no testing of these hypotheses and a causal explanation of the prevalent phenomena.

I do see a regional pattern. And I can venture some hypotheses to explain this pattern.

(a) The Punjab has had high growth and structural change in agriculture. Therefore polarization of income is expected in agriculture. It has had high growth in manufacturing. Growth in manufacturing in itself does not lead to polarization, but to a skewed distribution towards the upper end of the scale. Table 4 shows that the Punjab is over-represented in the poorest and two richest income groups. Rural Punjab is over represented in the poorest and richest groups. This supports polarization of rural income. Urban Punjab is over represented in the richest income group. This supports skewness of manufacturing income.

(b) Sind has not had any structural change in agriculture, so no rural polarization is expected. Sindh has had high growth in manufacturing. This should lead to a skewed distribution of urban income. This should also lead to a skewed distribution of total income for Sindh. Table 4 shows that Sind is over-represented in the richest income group. And this is due to urban Sind. Rural Sind shows no polarization.

(c) NWFP and Baluchistan have had neither structural change in agriculture nor significant growth in manufacturing. So neither polarization nor skewness of income is expected in each province. Table 4 shows that both provinces are not over-represented in the poorest and richest income groups.

So the statistics presented have a tot of potential. But they are just dead figures without analysis and causal explanations.

Moazam Mahmood

Pakistan Institute of Development Economics, Islamabad.

REFERENCES

Kemal, A. R. (1987) Some Comments on Sources of Income Inequality in Pakistan. The Pakistan Development Review 26 : 4.

Kruijk, Hans de (1986) Inequality in the Four Provinces of Pakistan. The Pakistan Development Review 25 : 4.

Kruijk, Hans de (1987) Sources of Income Inequality in Pakistan. The Pakistan Development Review 26 : 4.

Naseem, S. M. (1986) Comments on Inequality in the Four Provinces of Pakistan. The Pakistan Development Review 25 : 4.

Pakistan, Government of (1989) Some Developments of Income Inequality in Pakistan during the Period 1979-1986-87. Islamabad: Federal Bureau of Statistics. (A Summary Report to the Economic Coordination Committee of the Cabinet)

Pen, Jan (1971) Income Distribution. Middlesex, England: Penguin Books. The Economist (1987) From Rags to Riches in 60 Minutes 28-29.

(1) The idea of organizing such a parade has been put forward by the dutch economist Prof. Jan Pen (1971).

(2) The lowest monthly household income reported is Rs 30, which corresponds with a size of less than two inches (this figure together with the highest income reported are the only two figures that are derived from tape data; since the tape of 1985-86 is not operational yet, these extreme figures are from the tape of 1984-85, as mentioned earlier all other calculation are based on grouped data and made on a personal computer).

(3) Commenting upon an earlier draft of this paper, Pen points to the non-appearance of real giants in this parade: 500 feet is not much compared to e.g. the Duke of Westminster who is about 20 miles [see The Economist (1987)]. Apparently, in Pakistan, these giants do not report to the HIES.

HANS de KRUIJK, The author is associated with the Centre for Development Planning, Faculty of Economics, Erasmus University, Rotterdam.
Table 1
Estimation of a Regional Price Index on the
Basis of Food Prices, 1985-86
Price per Region (in Rupees per Unit)

 Price
 per
 Region
 (in
 Rupees
 per
 Unit)

 Punjab
Shopping-basket Rural

Wheat and Wheat Flower (KG) 10.96 2.1
Rice and Rice Flower (KG) 1.28 5.1
Gram-whole (KG) 0.04 8.5
Gram-split (KG) 0.20 8.0
Mash (KG) 0.09 11.6
Moong (KG) 0.10 10.4
Masoor (KG) 0.06 15.8
All Other Pulses (KG) 0.03 7.0
Milk (Fresh & Boiled) (LT) 6.67 3.3
MilkPacked (Tetra, etc.) (LT) 0.03 5.0
Milk (Dry & Condensed) (KG) 0.03 6.0
Butter (KG) 0.06 36.0
Ghee (Desi) (KG) 0.10 36.8
Yogurt (KG) 0.18 3.8
Vegetable Ghee (KG) 0.58 14.0
Mustard Oil (KG) 0.03 10.0
Mutton (KG) 0.12 25.3
Beaf (KG) 0.42 12.0
Fish Fresh (KG) 0.06 12.0
Chickens (KG) 0.06 22.8
Eggs (NO) 1.54 1.0
Banana (NO) 2.94 0.4
Moosmi, Malta, Keeno (ft) 2.40 0.4
Mango (KG) 0.04 9.0
Apple (KG) 0.05 9.7
Mellon (KG) 0.06 3.5
Other Fruit = +Grapes (KG) 0.12 6.7
Potatoes (KG) 0.78 2.4
Tomatoes (KG) 0.27 4.8
Onion (KG) 0.70 2.4
All other Vegetables (KG) 1.62 3.0
Salt (KG) 0.24 1.4
Chillies (KG) 0.00 15.9
Refined Sugar (KG) 0.79 9.1
Sugar (Desi) (KG) 0.04 6.2
Gur and Shakar (KG) 0.39 4.6
Tea (Black / Green) (KG) 0.06 64.3

Bill per Region (Rupees) 112.2

Price Index 100.00 93.7

 Price per Region
 (in Rupees per Unit)

 Sindh Sindh NWFP
Shopping-basket Rural Urban Rural

Wheat and Wheat Flower 2.3 2.6 2.4
Rice and Rice Flower 3.0 4.4 4.9
Gram-whole 8.0 8.5 7.0
Gram-split 8.5 6.0 8.3
Mash 10.5 10.7 10.2
Moong 9.9 9.9 10.0
Masoor 14.8 13.6 5.5
All Other Pulses 7.1 6.8 8.4
Milk (Fresh & Boiled) 3.4 5.1 4.8
MilkPacked (Tetra, etc.) 4.0 9.0 5.8
Milk (Dry & Condensed) 4.8 28.7 17.0
Butter 30.4 37.0 64.0
Ghee (Desi) 30.5 27.0 48.5
Yogurt 5.2 7.1 6.4
Vegetable Ghee 14.0 13.9 14.3
Mustard Oil 15.5 14.0 17.0
Mutton 29.3 29.0 12.0
Beaf 14.1 15.7 12.0
Fish Fresh 17.1 14.6 14.0
Chickens 22.0 17.9 25.8
Eggs 0.9 0.8 0.9
Banana 0.3 0.3 0.4
Moosmi, Malta, Keeno 0.4 0.5 0.4
Mango 7.0 7.0 3.0
Apple 9.7 9.3 11.3
Mellon 2.6 3.0 2.0
Other Fruit = +Grapes 5.5 6.7 8.2
Potatoes 2.8 2.5 2.7
Tomatoes 3.0 3.4 4.1
Onion 2.1 2.1 2.9
All other Vegetables 3.5 3.8 3.2
Salt 1.1 1.3 1.2
Chillies 16.1 16.4 15.7
Refined Sugar 8.7 8.7 9.4
Sugar (Desi) 7.5 7.0 7.9
Gur and Shakar 5.0 4.0 5.6
Tea (Black / Green) 63.0 68.5 59.1

Bill per Region (Rupees) 112.4 130.1 128.9

Price Index 93.8 108.6 107.6

 Price per Region
 (in Rupees per Unit)

 Balu- Balu-
 NWFP chistan chistan
Shopping-basket Urban Rural Urban

Wheat and Wheat Flower 2.6 2.5 2.3
Rice and Rice Flower 6.1 4.0 6.4
Gram-whole 9.0 6.0 12.0
Gram-split 7.9 9.0 9.7
Mash 6.6 10.9 11.9
Moong 4.8 11.6 10.9
Masoor 12.5 14.7 15.0
All Other Pulses 9.3 8.7 9.0
Milk (Fresh & Boiled) 4.9 4.5 4.9
MilkPacked (Tetra, etc.) 4.8 4.0 9.3
Milk (Dry & Condensed) 11.0 14.2 44.0
Butter 50.0 50.0 50.0
Ghee (Desi) 56.0 37.3 43.7
Yogurt 5.7 5.7 5.0
Vegetable Ghee 13.8 14.9 15.5
Mustard Oil 12.5 15.1 18.3
Mutton 16.0 28.1 28.3
Beaf 11.9 13.5 13.9
Fish Fresh 16.0 15.2 14.9
Chickens 25.3 22.8 22.8
Eggs 1.0 0.9 1.0
Banana 0.4 0.4 0.4
Moosmi, Malta, Keeno 0.4 0.6 0.5
Mango 7.0 8.8 2.4
Apple 11.7 7.4 9.4
Mellon 3.0 3.4 4.1
Other Fruit = +Grapes 7.3 17.7 16.5
Potatoes 2.4 3.2 3.0
Tomatoes 3.6 4.4 4.3
Onion 2.5 2.6 2.5
All other Vegetables 3.9 3.4 4.5
Salt 1.2 1.3 1:3
Chillies 16.3 10.4 17.9
Refined Sugar 9.2 9.3 9.1
Sugar (Desi) 6.5 5.8 5.5
Gur and Shakar 5.2 5.5 5.0
Tea (Black / Green) 75.7 66.4 75.0

Bill per Region (Rupees) 132.7 129.1 137.5

Price Index 110.8 107.8 114.8

Table 2
Average Income per Household per Region, Adjusted for Differences
in Household Size and Average Price Level per Region

 Income per Income per
 Household Household Average
 Published Calculated Household
 in HIES from HIES Size
 Region (Rs) (Rs)

1. Sindh-urban 2884 2828 7.10
2. Punjab-urban 2333 2295 6.56
3. Baluchistan-urban 2519 2428 6.47
4. NWFP-urban 2334 2445 6.83
5. Punjab-rural 1618 1622 6.07
6. Sindh-rural 1599 1645 6.31
7. Baluchistan-rural 1621 1638 5.59
8. NWFP-rural 1777 1789 6.65

 Household Purchasing
 Income per Regional Power per
 Standard Price Standard
 Household Index Household
 Region (Rs) (Rs)

1. Sindh-urban 2563 108.60 2360
2. Punjab-urban 2228 103.70 2149
3. Baluchistan-urban 2386 114.80 2078
4. NWFP-urban 2292 110.80 2069
5. Punjab-rural 1684 93.70 1797
6. Sindh-rural 1652 93.80 1761
7. Baluchistan-rural 1824 107.80 1692
8. NWFP-rural 1717 107.60 1595

Table 3
The Pakistani Parade in Figures (each Major
Group is Ten Minutes)

 No. of
 Income Household Household
Region Class (Millions) Size

Group I
 Balochistan-urban 600-700 0.00 4.30
 NWFP-urban < 600 0.01 2.81
 Punjab-rural < 600 0.50 3.06
 Balochistan-rural 600-700 0.05 3.94
 Punjab-urban < 600 0.08 2.84
 Balochistan-urban 700-800 0.00 4.38
 NWFP-urban 600-700 0.01 3.68
 NWFP-rural 700-800 0.08 4.40
 NWFP-rural < 600 0.08 2.42
 NWFP-urban 600-700 0.06 3.70
 Punjab-urban 600-700 0.06 3.89
 NWFP-urban 700-800 0.01 4.04
 Balochistan-rural < 600 0.04 2.45
 Punjab-rural 600-700 0.31 4.04
 NWFP-rural 800-1000 0.23 5.07
 NWFP-rural 800-1000 0.02 4.83
 Punjab-urban 700-800 0.07 4.17
 Balochistan-urban 700-800 0.06 3.89
 Sindh-rural < 600 0.07 2.64
 Sindh-rural 600-700 0.06 3.71
 Punjab-rural 700=800 0.36 4.39
 Balochistan-rural 800-1000 0.14 4.52
 Sindh-rural 700-800 0.07 4.32
 Sindh-urban < 600 0.01 2.04
 Sindh-urban 700-800 0.02 3.56
 Punjab-urban 800-1000 0.21 4.62
 Punjab-rural 800-1000 0.85 5.00
 Sindh-urban 800-1000 0.07 4.30
 Sindh-rural 800-1000 0.26 4.93
 NWFP-urban 1000-1500 0.06 5.96
 Average

Group 2
 NWFP-rural 1000-1500 0.59 5.96
 Balochistan-rural 1000-1500 0.30 5.56
 Punjab-urban 1000-1500 0.60 5.88
 Balochistan-urban 800-1000 0.01 3.60
 Balochistan-urban 1000-1500 0.03 4.96
 NWFP-rural 1500-2000 0.38 7.46
 Punjab-rural 1000-1500 0.75 5.92
 Average

Group 3
 Punjab-rural 1000-1500 1.00 5.92
 Sindh-rural 1000-1500 0.63 5.80
 NWFP-urban 1500-2000 0.06 7.20
 Sindh-urban 1000-1500 0.26 5.03
 Balochistan-urban 1500-2000 0.03 6.23
 Balochistan-rural 1500-2000 0.13 6.29
 Sindh-urban 1500-2000 0.30 6.58
 Punjab-urban 1500-2000 0.45 6.58

Average

Group 4
 Sindh-rural 1500-2000 0.42 7.27
 NWFP-rural 2000-2500 0.21 8.13
 Sindh-urban 600-700 0.01 1.76
 NWFP-urban 2000-2500 0.03 7.67
 Punjab-rural 1500-2000 1.11 6.92
 NWFP-urban 2500-3000 0.02 9.13
 Balochistan-rural 4000-4500 0.01 14.46
 Sindh-urban 2000-2500 0.21 7.33
 Balochistan-rural 2500-3000 0.03 8.85
 NWFP-rural 2500-3000 0.10 8.93
 Average

Group 5
 Punjab-urban 2000-2500 0.29 7.36
 Balochistan-urban 2000-2500 0.02 6.70
 NWFP-rural 3000-3500 0.07 10.07
 Balochistan-rural 2000-2500 0.09 6.52
 Sindh-rural 2000-2500 0.19 7.54
 Sindh-rural 2500-3000 0.10 9.34
 Punjab-rural 2000-2500 0.58 7.39
 Balochistan-rural 3000-3500 0.02 9.48
 Sindh-urban 2500-3000 0.15 7.59
 NWFP-urban 3000-3500 0.01 8.75
 Balochistan-urban 2500-3000 0.01 7.00
 Balochistan-rural 3500-4000 0.01 10.72
 Punjab-urban 2500-3000 0.18 7.69
 Punjab-rural 2500-3000 0.29 8.42
 Balochistan-urban 3000-3500 0.01 8.26
 Average

Group 6
 Sindh-rural 3000-3500 0.05 9.95
 Sindh-urban 3000-3500 0.10 8.37
 NWFP-rural 3500-4000 0.04 9.84
 Balochistan-urban 3500-4000 0.00 8.92
 NWFP-urban 3500-4000 0.01 9.12
 Punjab-rural 3000-3500 0.17 8.84
 Punjab-urban 3000-3500 0.13 7.75
 NWFP-rural 4000-4500 0.02 9.70
 Punjab-urban 3500-4000 0.10 8.34
 Sindh-urban 3500-4000 0.06 7.88
 Punjab-rural 3500-4000 0.11 9.16
 NWFP-urban 4000-4500 0.01 8.75
 Sindh-urban 4000-4500 0.04 9.04
 Sindh-rural 3500-4000 0.03 8.91
 Balochistan-urban 4000-4500 0.01 7.67
 Sindh-rural 4000-4500 0.02 9.47
 Punjab-rural 4000-4500 0.07 9.11
 Punjab-urban 4000-4500 0.07 7.82
 Balochistan-urban >4500 0.01 10.07
 NWFP-rural >4500 0.07 11.35
 Sindh-urban >4500 0.20 9.44
 Sindh-rural >4500 0.04 10.34
 Punjab-urban >4500 0.22 8.73
 NWFP-urban >4500 0.03 8.06
 Punjab-rural >4500 0.18 9.27
 Balochistan-rural >4500 0.04 7.29

 Average

 Average/Total 15.4 6.34

 Cumulative Income per
 Population Population Household
Region (Millions) (Millions) (Rs)

Group I
 Balochistan-urban 0.02 0.02 486
 NWFP-urban 0.02 0.02 486
 Punjab-rural 1.52 1.55 470
 Balochistan-rural 0.20 1.75 660
 Punjab-urban 0.22 1.97 496
 Balochistan-urban 0.01 1.98 773
 NWFP-urban 0.03 2.02 650
 NWFP-rural 34 2.35 750
 NWFP-rural 0.20 2.56 476
 NWFP-urban 0.24 2.80 655
 Punjab-urban 0.24 3.04 667
 NWFP-urban 0.03 306 758
 Balochistan-rural 0.10 3.16 509
 Punjab-rural 1.27 4.43 656
 NWFP-rural 1.16 5.59 910
 NWFP-rural 0.10 569 909
 Punjab-urban 0.30 6.00 767
 Balochistan-urban 0.23 6.23 757
 Sindh-rural 0.20 6.42 505
 Sindh-rural 0.23 6.65 656
 Punjab-rural 1.56 8.22 755
 Balochistan-rural 0.65 8.87 898
 Sindh-rural 0.31 9.18 754
 Sindh-urban 0.02 9.20 503
 Sindh-urban 0.07 9.27 773
 Punjab-urban 0.99 10.25 918
 Punjab-rural 4.25 14.51 905
 Sindh-urban 0.29 14.80 938
 Sindh-rural L..9 16.09 914
 NWFP-urban 0.38 16.47 1268
 Average

Group 2
 NWFP-rural 3.49 19.96 1242
 Balochistan-rural 1.66 21.62 1228
 Punjab-urban 3.54 25.16 1264
 Balochistan-urban 0.04 25.20 936
 Balochistan-urban 0.16 25.36 1239
 NWFP-rural 2.81 28.16 1727
 Punjab-rural 4.45 32.62 1242
 Average

Group 3
 Punjab-rural 5.92 38.54 1242
 Sindh-rural 3.68 42.21 1227
 NWFP-urban 0.46 42.68 1759
 Sindh-urban 1.29 43.97 1301
 Balochistan-urban 0.18 44.15 1757
 Balochistan-rural 0.85 45.00 1690
 Sindh-urban 1.95 46.95 1787
 Punjab-urban 2.95 49.89 1734

Average

Group 4
 Sindh-rural 3.06 52.96 1730
 NWFP-rural 1.73 54.68 2217
 Sindh-urban 0.01 54.69 678
 NWFP-urban 0.26 54.95 1661
 Punjab-rural 7.69 62.65 1729
 NWFP-urban 0.19 62.83 2763
 Balochistan-rural 0.10 62.93 4145
 Sindh-urban 1.51 64.43 2280
 Balochistan-rural 0.22 64.66 2703
 NWFP-rural 0.91 65.57 2732
 Average

Group 5
 Punjab-urban 2.15 67.72 2268
 Balochistan-urban 0.11 67.83 2345
 NWFP-rural 0.70 68.53 3212
 Balochistan-rural 0.59 69.13 2238
 Sindh-rural 1.46 70.59 2226
 Sindh-rural 0.95 71.54 2707
 Punjab-rural 4.29 75.83 2231
 Balochistan-rural 0.14 75.97 3264
 Sindh-urban 1.16 77.13 2784
 NWFP-urban 0.12 77.25 3223
 Balochistan-urban 0.09 77.34 2766
 Balochistan-rural 0.11 77.44 3861
 Punjab-urban 1.40 78.85 2760
 Punjab-rural 2.43 81.28 2713
 Balochistan-urban 0.06 81.34 3314
 Average

Group 6
 Sindh-rural 0.50 81.84 3238
 Sindh-urban 0.87 82.71 3272
 NWFP-rural 0.41 83.12 3797
 Balochistan-urban 0.04 83.17 3754
 NWFP-urban 0.09 83.25 3789
 Punjab-rural 1.46 84.71 3215
 Punjab-urban 1.04 85.75 3256
 NWFP-rural 0.18 85.93 4233
 Punjab-urban 0.84 86.77 3737
 Sindh-urban 0.44 87.22 3763
 Punjab-rural 1.03 88.24 3730
 NWFP-urban 0.07 88.31 4245
 Sindh-urban 0.39 88.70 4315
 Sindh-rural 0.24 88.94 3700
 Balochistan-urban 0.05 88.99 4233
 Sindh-rural 0.17 89.16 4240
 Punjab-rural 0.63 89.79 4226
 Punjab-urban 0.52 90.31 4212
 Balochistan-urban 0.13 90.44 6940
 NWFP-rural 0.78 91.22 7513
 Sindh-urban 1.91 93.13 7081
 Sindh-rural 0.45 93.57 6890
 Punjab-urban 1.91 95.49 7040
 NWFP-urban 0.28 95.76 7030
 Punjab-rural 1.68 97.45 7113
 Balochistan-rural 0.26 97.70 7962

 Average

 Average/Total 97.7 97.7 1900

 Purchasing Standized
 Power per Income
 Standard Size In
Region Household Feet

Group I
 Balochistan-urban 846 2.44
 NWFP-urban 846 2.44
 Punjab-rural 907 2.62
 Balochistan-rural 910 2.63
 Punjab-urban 915 2.64
 Balochistan-urban 919 2.65
 NWFP-urban 934 2.69
 NWFP-rural 47 2.73
 NWFP-rural 949 2.74
 NWFP-urban 951 2.74
 Punjab-urban 965 2.78
 NWFP-urban 996 2.87
 Balochistan-rural 1006 2.90
 Punjab-rural 1019 2.94
 NWFP-rural 1022 2.95
 NWFP-rural 1033 2.98
 Punjab-urban 1050 3.03
 Balochistan-urban 1055 3.04
 Sindh-rural 1086 3.13
 Sindh-rural 1089 3.14
 Punjab-rural 1097 3.17
 Balochistan-rural 1109 3.20
 Sindh-rural 1109 3.20
 Sindh-urban 1118 3.22
 Sindh-urban 1,145 3.30
 Punjab-urban 1157 3.34
 Punjab-rural 1182 3.41
 Sindh-urban 1196 3.45
 Sindh-rural 1.06 3.48
 NWFP-urban 120 3.48
 Average 1090 3.15

Group 2
 NWFP-rural 1217 3.51
 Balochistan-rural 1275 3.68
 Punjab-urban 1300 3.75
 Balochistan-urban 1301 3.75
 Balochistan-urban 1329 3.83
 NWFP-rural 1393 4.02
 Punjab-rural 1407 4.06
 Average 1325 3.82

Group 3
 Punjab-rural 1407 4.06
 Sindh-rural 1412 4.07
 NWFP-urban 1421 4.10
 Sindh-urban 1459 4.21
 Balochistan-urban 1554 4.48
 Balochistan-rural 1579 4.56
 Sindh-urban 1594 4.60
 Punjab-urban 1619 4.67

Average 1480 4.27

Group 4
 Sindh-rural 1637 4.72
 NWFP-rural 1657 4.78
 Sindh-urban 1661 4.79
 NWFP-urban 1702 4.91
 Punjab-rural 1711 4.94
 NWFP-urban 1808 5.22
 Balochistan-rural 1826 5.27
 Sindh-urban 1850 5.34
 Balochistan-rural 1869 5.39
 NWFP-rural 1877 5.41
 Average 1717 4.95

Group 5
 Punjab-urban 1920 5.54
 Balochistan-urban 1947 5.62
 NWFP-rural 1980 5.71
 Balochistan-rural 2027 5.85
 Sindh-rural 2039 5.88
 Sindh-rural 2048 5.91
 Punjab-rural 2084 6.01
 Balochistan-rural 2122 6.12
 Sindh-urban 2190 6.32
 NWFP-urban 2191 6.32
 Balochistan-urban 2211 6.38
 Balochistan-rural 2244 6.47
 Punjab-urban 2248 6.49
 Punjab-rural 2257 6.51
 Balochistan-urban 2289 6.60
 Average 2101 6.06

Group 6
 Sindh-rural 2314 6.67
 Sindh-urban 2360 6.81
 NWFP-rural 2389 6.89
 Balochistan-urban 2420 6.98
 NWFP-urban 2481 7.16
 Punjab-rural 2560 7.39
 Punjab-urban 2635 7.60
 NWFP-rural 2699 7.79
 Punjab-urban 2833 8.17
 Sindh-urban 2864 8.26
 Punjab-rural 2877 8.30
 NWFP-urban 2885 8.32
 Sindh-urban 2905 8.38
 Sindh-rural 2921 8.43
 Balochistan-urban 3122 9.01
 Sindh-rural 3169 9.14
 Punjab-rural 3276 9.45
 Punjab-urban 3381 9.75
 Balochistan-urban 4009 11.57
 NWFP-rural 4150 11.97
 Sindh-urban 4584 13.22
 Sindh-rural 4754 13.71
 Punjab-urban 5123 14.78
 NWFP-urban 5142 14.83
 Punjab-rural 5428 15.66
 Balochistan-rural 6542 18.87

 Average 3746 10.81

 Average/Total 1900 5.50

Table 4
Estimated Population Share per Income Group,
Pakistan, 1985-86 (in percentages)

ALL GROUPS

 Urban Rural Total

Punjab 16.6 39.0 55.6
Sindh 10.4 12.7 23.1
NWFP 2.0 13.2 15.2
Balochistan 0.9 5.2 6.1
Total 29.9 70.1 100

GROUP 1 (Poorest)

 Urban Rural Total

Punjab 10.6 52.3 62.9
Sindh 2.3 12.3 14.6
NWFP 3.4 11.8 15.2
Balochistan 0.1 7.2 7.3
Total 16.5 83.6 100

GROUP 3

 Urban Rural Total

Punjab 17.0 34.2 51.2
Sindh 18.0 21.3 40.1
NWFP 2.7 2.7
Balochistan 1.1 4.9 6.0
Total 39.6 60.4 100

GROUP 5

 Urban Rural Total

Punjab 22.5 42.6 65.1
Sindh 7.3 15.3 22.6
NWFP 0.7 4.5 5.2
Balochistan 1.7 5.4 7.1
Total 32.2 67.8 100

GROUP 2

 Urban Rural Total

Punjab 21.9 27.6 49.5
Sindh
NWFP 39.0 39.0
Balochistan 1.2 10.3 11.5
Total 23.1 76.9 100

GROUP 4

 Urban Rural Total

Punjab 49.1 49.1
Sindh 9.7 19.6 29.3
NWFP 2.8 16.8 19.6
Balochista 2.0 2.0
Total 12.5 87.5 100

GROUP 6 (Richest)

 Urban Rural Total

Punjab 26.3 29.3 55.6
Sindh 22.1 8.3 30.4
NWFP 2.6 8.4 11.0
Balochistan 1.4 1.6 3.0
Total 52.4 47.6 100
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