economic activities: how the poor earn...

Economic Activities: How the Poor Earn Income

This annex investigates the economic activities and income sources of the poor using the IHSES 2007

data, with a particular focus on self-employed agricultural workers.

The main findings can be summarized as follows. Wage earners compose slightly less than 60 percent of

employed poor workers. Around 50 percent of poor workers are employed either in agriculture (of whom

90 percent are self-employed) or in construction (of whom 99 percent are wage earners). According to

the IHSES data, poor wage earners work longer hours than their nonpoor counterparts and are paid a

very similar hourly wage. Hence, their being poor does not seem to depend on underemployment or low

productivity. Labor productivity of self-employed poor workers, as measured by income per hour worked,

averages two-thirds that of the nonpoor self-employed. Furthermore, poor workers on average seemingly

have higher productivity as wage earners than when self-employed, while a much smaller gap exists for

nonpoor workers. Self-employed agricultural productivity is estimated to be 40 percent lower than in all

other economic sectors, both for poor and nonpoor workers. Nonpoor self-employed agricultural

workers, however, display a large variability in productivity while poor ones appear more uniformly less

productive. No clear evidence of plant production specialization is found between poor and nonpoor

workers.

1. Economic Activities of the Poor

According to the IHSES 2007, labor force participation in Iraq is very similar for the poor and nonpoor

(around 43 percent).2 Among the employed at the national level, the share of wage earners is lower

among poor (58.3 percent) than among nonpoor (68.4 percent) workers (see Table 5.6-1). This is due to

the situation in rural areas, where only 42.4 percent of poor employed workers earn wages (compared

with 48.9 percent of nonpoor ones).

Table 5.6-1. Distribution of Employed Workers 15 and Older by Professional and Poverty Status

Iraq Urban Rural

Nonpoor Poor All Nonpoor Poor All Nonpoor Poor All

Self-employed 31.6 41.7 33.6 26.1 24.2 25.8 51.2 57.6 53.5

Wage earner 68.4 58.3 66.4 73.9 75.9 74.2 48.9 42.4 46.5

Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

Source: Our estimates using IHSES 2007 data

2 This annex considers those individuals who are at least 15 years of age.

Annex 5. Employment, Income, and Agriculture 5.6 Economic Activities: How the Poor Earn Income

388

Table 5.6-2. Distribution of Employed Workers 15 and Older by Economic Activity and Poverty

Status

Of poor workers

Economic Activity Nonpoor Poor All Wage

earners Self-

employed

Agriculture, hunting, forestry, and fishing 12.1 30.3 15.7 10.2 89.8

Manufacturing 9.5 9.9 9.6 90.7 9.3

Construction 10.4 18.1 11.9 99.0 1.0

Wholesale and retail trade 18.8 12.8 17.6 43.1 56.9

Transport, storage, and communications 11.2 8.1 10.6 46.7 53.3

Financial intermediation, real estate 5.3 2.0 4.7 88.2 11.8

Public administration and defense 10.9 7.2 10.2 98.1 1.9

Education 10.6 3.5 9.2 99.9 0.1

Health and social work 3.2 2.0 3.0 80.0 20.0

Other community, social, and personal services 8.0 6.0 7.6 87.2 12.8

Total 100.0 100.0 100.0 58.3 41.7

Source: See Table 5.6-1.

Poor workers are relatively concentrated in a few economic sectors: almost half are employed either in

agriculture or construction (Table 5.6-2). A further 22.7 percent work in trade or manufacturing. The

comparable shares for nonpoor workers are 22.5 percent for agriculture or construction and 28.3 percent

for trade or manufacturing. Furthermore, poor workers have very different professional status profiles in

their two main sectors of employment: 90 percent of those in agriculture are self-employed while almost

all those in construction are wage earners. In the next two highest sectors of concentration among poor

workers, trade shows a less polarized distribution between the self-employed and wage earners (roughly a

57–43 tilt), while manufacturing is similar to construction (although less extreme with a share of wage

earners equal to 90.7 percent).

Wages and Hours Worked

In the entire economy, the median hourly wage (ID 1,900) is not significantly different between poor and

nonpoor workers (Table 5.6-3).3 Among the sectors where most poor workers are employed, the pattern is

differentiated. In particular, while the median hourly wage in construction barely changes with poverty

status (ID 2,200 for poor and ID 2,300 for nonpoor workers), the rate for poor workers in agriculture

averages three-quarters of that for nonpoor workers (ID 1,500 versus ID 2,000, respectively). However, as

Table 5.6-2 notes, wage earners comprise only about 10 percent of all poor agricultural workers, or,

around 3 percent of all employed poor workers. Very small and probably not statistically significant

differences in wages across poverty status are also found in other activities such as trade; manufacturing;

3 Table 5.6-3 presents the median because it is less sensitive to extreme values than the mean. However, the overall

pattern would not change if the mean were considered. Weekly work hours have been calculated using questions

1314 (weekly hours of work), 1315 (annual days of holidays), and 1316 (annual days of vacation) in the IHSES

2007. More precisely, the following formula has been used:

(q1314*52 – ((q1314/7)*(q1315 + q1316)))/52. [5.6-1]

That is, the number of hours corresponding to the days of holidays and vacations have been subtracted from the total

number of annual hours of work, obtained multiplying the weekly figure by 52,.Weekly figures have then been

obtained by dividing annual figures by the number of weeks in a year.


389

transport, storage and communications; public administration and defense; and other community, social,

and personal services where a considerable share of poor workers are employed. Meanwhile larger wage

gaps are observed where the shares of poor workers are smaller, that is, in education, health and social

work, and financial intermediation and real estate. Finally, hourly wages in construction are the highest of

any category for poor workers (and the second highest for nonpoor workers). To the extent that wages

reflect labor productivity, the evidence in Table 5.6-3 points to the possibility that productivity

differentials between poor and nonpoor wage earners may not be large in many economic sectors.

Table 5.6-3. Median Hourly Wages by Economic Activity and Poverty Status

(ID 1,000/hour)


Median hourly wages also show regional variations (see Table 5.6-4). In particular, they vary for poor

employed workers from ID 1,100 in Duhouk to ID 2,800 in Kirkuk, while ranging for nonpoor workers

from ID 1,400 in Ninevah to ID 2,200 in Kirkuk. As these variation ranges indicate, the median hourly

wage is higher for poor than for nonpoor workers in some governorates. The largest gaps in favor of poor

workers are observed in Sulaimaniya and Kirkuk, while the largest in favor of nonpoor workers are found

in Duhouk and Kerbela. This evidence seems to point to factors beside the hourly wage as determinants of

an employed worker’s poverty status. It also suggests that productivity differentials between poor and

nonpoor wage earners vary across governorates. This is at least partly due to the geographical distribution

of economic activities.

Economic activity Nonpoor Poor All

Agriculture, hunting, forestry and fishing 2.0 1.5 1.9

Manufacturing 1.7 1.6 1.7

Construction 2.3 2.2 2.2

Wholesale and retail trade 1.4 1.5 1.4

Transport, storage, and communications 1.8 1.6 1.7

Financial intermediation, real estate 1.8 1.3 1.8

Public administration and defense 1.9 2.0 1.9

Education 2.4 1.8 2.3

Health and social work 1.8 1.4 1.8

Other community, social, and personal services 1.6 1.7 1.7

Total 1.9 1.9 1.9


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Table 5.6-4. Median Hourly Wages by Governorate and Poverty Status (ID 1,000/hour)

Governorate Nonpoor Poor All

Duhouk 1.6 1.1 1.6

Ninevah 1.4 1.5 1.4

Sulaimaniya 1.9 2.6 1.9

Kirkuk 2.2 2.8 2.3

Erbil 1.9 1.5 1.9

Diala 2.0 1.6 1.9

Al-Anbar 2.1 2.4 2.1

Baghdad 1.9 1.9 1.9

Babil 1.8 1.9 1.8

Kerbela 2.0 1.5 1.8

Wasit 2.0 1.8 1.9

Salahuddin 1.8 2.1 1.9

Al-Najaf 1.7 1.5 1.6

Al-Qadisiya 1.8 1.8 1.8

Al-Muthanna 2.0 2.0 2.0

Thi Qar 2.0 1.8 1.9

Missan 2.0 2.2 2.1

Basrah 2.1 2.1 2.1

Total 1.9 1.9 1.9


The median number of weekly hours worked shows substantive variation both across sectors and between

poor and nonpoor workers (Table 5.6-5). In particular, at the level of the entire economy, poor workers

work longer hours per week than nonpoor ones (36.0 versus 30.1 respectively). This pattern exists in most

economic sectors, with only a few exceptions. One is construction, where the number of hours worked are

very similar (37.5 for poor and 36.0 for nonpoor workers). Very small differences also are observed in

trade, education, and other community, social, and personal services. Education is the sector where the

shortest hours are observed (15.1 for poor and 14.8 for nonpoor workers). The longest weekly hours are

lodged by poor workers in public administration and defense (44.8) and by nonpoor workers in trade

(40.7).


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Table 5.6-5. Median Number of Weekly Hours Worked by Economic Activity

and Poverty Status


If the mean rather than the median number of weekly hours worked is considered (Table 5.6-6), the

results differ somewhat, but the pattern remains very similar.







Transport, storage, and communications 30.1 40.0 31.2



Education 14.8 15.1 14.9


Other community, social, & personal services 32.5 31.5 32.3

Total 30.1 36.0 31.6

Table 5.6-6. Mean Number of Weekly Hours Worked

by Economic Activity and Poverty Status






Transport, storage and communications 34.4 42.7 35.4



Education 16.3 18.7 16.5


Other community, social, personal services 35.8 36.0 35.9

Total 33.5 38.2 34.3


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.

The evidence in Tables 5.6-3–6 suggests that (a) underemployment does not seem a cause of living

standards for poor wage workers because they generally work longer hours than do nonpoor wage earners

and (b) low productivity also does not seem to be a factor since poor and nonpoor workers generally are

paid very similar hourly earnings.

2. Labor and Self-Employment Income

Labor income—a more comprehensive variable including not only wages but also self-employment

earnings—can also be measured using IHSES 2007 data, although only at the household level. Therefore,

the labor income per hour presented in Table 5.6-7 is calculated as the ratio between household labor

income and the total hours worked by all household members.4 It can be observed that this more

comprehensive variable shows lower values for people living in poor than in nonpoor households. The

difference is larger if the mean value is considered, but it is also present using the median value.

Table 5.6-7. Labor Income per Hour Worked by Poverty Status (ID 1,000/hour)

Mean Median

Standard

Deviation

Nonpoor 2.8 1.9 6.4

Poor 2.1 1.7 2.7

All 2.7 1.9 5.8


The gap in favor of nonpoor households also is observed at the governorate level with respect to both the

mean and the median values (Table 5.6-8).5 For some governorates (Baghdad, Ninevah, and Missan), the

median values are equal between poor and nonpoor people. The largest differences (ID 700 per hour) are

found in Sulaimaniya and Erbil.

Median hourly labor income for poor workers ranges between ID 1,000 in Al-Najaf and ID 2,200 in Erbil.

Meanwhile for nonpoor workers it ranges between ID 1,600 in Ninevah and Diala and ID 2,900 in Erbil.

Hence the highest median governorate hourly labor income for a poor worker is 2.2 times greater than the

lowest governorate rate, while the corresponding ratio among nonpoor workers is 1.8.

4 Table 5.6-7 is based on the number of hours worked as measured in question 1204 of the IHSES 2007, where the

time is recorded separately for each of the seven days preceding the interview. However, similar results can be

obtained using question 701, which registers only the total hours worked in the same seven days. 5 The main exception is Erbil, where a higher mean but a lower median value is found for poor workers. Although

here the result for the first indicator can be due to extreme values to which the second one is less sensitive.


393

Table 5.6-8. Labor Income per Hour Worked by Governorate and Poverty Status (ID 1,000/hour)

Poor Nonpoor

Mean Median

Standard

deviation Mean Median

Standard

deviation

Duhouk 2.4 1.4 2.4 3.4 1.7 8.4 Ninevah 2.2 1.6 2.5 2.5 1.6 3.3 Sulaimaniya 2.3 1.3 3.2 3.5 2.0 9.3 Kirkuk 1.8 1.8 1.1 2.3 1.9 2.4 Erbil 7.7 2.2 15.1 5.4 2.9 11.7 Diala 1.6 1.4 1.7 2.1 1.6 2.5 Al-Anbar 1.9 1.4 1.6 2.4 1.9 2.2 Baghdad 2.2 1.9 1.9 2.3 1.9 1.6 Babil 2.0 1.4 2.9 3.0 1.9 5.6 Kerbela 2.0 1.5 1.5 2.9 2.0 3.3 Wasit 2.4 1.8 4.4 2.9 2.2 2.4 Salahuddin 2.1 1.6 1.8 2.5 2.0 2.0 Al-Najaf 1.5 1.0 1.9 4.9 2.1 22.4 Al-Qadisiya 2.5 1.5 5.3 3.0 1.9 6.3 Al-Muthanna 2.3 1.8 1.9 2.9 2.3 2.5 Thi Qar 1.6 1.4 1.1 2.3 1.7 2.7 Missan 2.3 2.0 1.8 2.6 2.0 2.4 Basrah 1.9 1.9 1.0 2.7 2.0 3.3 Total 2.1 1.7 2.7 2.8 1.9 6.4


The IHSES 2007 data allow one to measure self-employment income per hour worked at the household

level as the ratio of total household income from self-employment to the total hours worked by the self-

employed members. This indicator can be interpreted as an average measure of labor productivity across

self-employment activities and economic sectors. The figure for poor individuals is, on average, around

two-thirds of that for nonpoor individuals using both mean and median values (Table 5.6-9). Furthermore,

while the median hourly self-employment income is only slightly lower than the median hourly wage for

nonpoor workers (ID 1,800 and ID 1,900 respectively), self-employment income for poor workers is

substantially lower than wages (ID 1,200 and ID 1,900 respectively). Hence to the extent that these

figures reflect productivity, one can argue that poor workers average higher productivity when employed

as wage earners than when self-employed. A similar gap also exists for nonpoor workers, but it is small in

size.

Table 5.6-9. Self-Employment Income per Hour Worked by Poverty Status (ID 1,000/hour)

Mean Median

Standard

deviation

Nonpoor 3.2 1.8 10.0

Poor 2.0 1.2 3.3

All 2.9 1.6 8.7



394

The average self-employment income per hour worked also is higher for nonpoor than for poor

individuals at the governorate level (Table 5.6-10).6 There are two exceptions to this pattern, both using

the mean (Baghdad and Ninevah7) and the median values (Baghdad and Missan). Furthermore, the ratio

between poor and nonpoor hourly incomes varies substantially across governorates: from 20 percent (in

Sulaimaniya and Erbil) to 160 percent (in Ninevah) using mean values, and from 20 percent (again in

Sulaimaniya) to 110 percent (Baghdad and Missan) using median values.

Table 5.6-10. Self-Employment Income per Hour Worked by Governorate and Poverty Status

(ID 1,000/hour)

Poor Nonpoor

Mean Median

Standard


Standard

deviation

Duhouk 1.0 0.6 1.0 3.0 1.4 8.3

Ninevah 4.1 1.5 6.8 2.6 1.7 3.2

Sulaimaniya 0.4 0.3 0.7 2.6 1.4 4.6

Kirkuk 1.4 0.7 1.4 2.1 1.5 2.6

Erbil 1.3 0.9 0.8 7.5 2.6 20.7

Diala 0.5 0.3 0.4 1.4 0.7 3.6

Al-Anbar 1.0 0.7 0.8 1.9 1.4 1.8

Baghdad 3.1 2.4 2.9 2.7 2.1 2.3

Babil 1.6 1.0 3.1 3.5 1.7 9.4

Kerbela 2.0 1.7 1.7 3.2 2.2 5.6

Wasit 2.7 1.7 5.5 3.3 2.6 3.4

Salahuddin 1.5 1.1 1.3 2.3 1.7 1.9

Al-Najaf 1.6 0.9 2.5 8.5 2.1 33.3

Al-Qadisiya 1.9 0.9 5.4 2.3 1.3 3.7

Al-Muthanna 2.7 1.6 3.1 3.5 2.2 4.0

Thi Qar 1.0 0.7 1.0 2.1 1.3 2.7

Missan 2.0 2.1 1.6 2.4 2.0 2.4

Basrah 1.6 1.2 1.2 3.3 1.6 7.1

Total 2.0 1.2 3.3 3.2 1.8 10.0


3. Self-Employed Agricultural Workers

Given the sizable share of poor workers who are employed in agriculture (30.3 percent) and their

frequency of self-employment (almost 90 percent), this section delves more deeply into the situation of

self-employed agricultural workers.

Using median values, self-employment income per hour worked is around 40 percent lower in agriculture

than in all the other sectors, both for poor and nonpoor workers (Table 5.6-11). However, the mean value

of this productivity measure for nonpoor agricultural workers is larger than that in all the other sectors,

indicating, together with the very high variability, that some of these nonpoor workers are very

6 Small sample sizes are likely responsible for the low values observed among poor self-employed workers in the

Kurdistan regions. 7 The results for Ninevah using mean values could be driven by some extreme observations to which median values

are less sensitive.


395

productive. In contrast, poor self-employed agricultural workers are more uniformly less productive.

Using median values the productivity ratios of poor and nonpoor workers are similar in the agricultural

and nonagricultural sectors: 75 and 79 percent respectively. However the presence of some highly

productive nonpoor workers in agriculture reduces the productivity ratio in this sector between poor and

nonpoor workers with respect to the rest of the economy calculated using mean values: the figures are 46

and 71 percent, respectively.

Table 5.6-11. Self-Employment Income per Hour Worked by Poverty Status and Economic

Activity (ID 1,000/hour)


The IHSES 2007 data contain information on other aspects of self-employed agricultural worker

activities. We now compare the different types of plant production, the shares of auto-consumption, and

the demographic characteristics of agricultural workers in poor and nonpoor households.

The overwhelming majority of self-employed agricultural workers are engaged in crop production—91

percent at the national level, with little difference by poverty status (92 and 90 percent for poor and

nonpoor workers, respectively).

Figure 5.6-1. Type of Plant Production by Poverty Status

(Percent of market value of total plant production)

Source: Authors’ estimates using IHSES 2007 data

0

10

20

30

40

50

60

Nonpoor

Poor

Agriculture Nonagricultural sectors

Mean Median Standard


Standard

deviation

Nonpoor 3.5 1.2 18.3 3.1 1.9 7.0

Poor 1.6 0.9 3.2 2.2 1.5 2.8

All 2.6 1.0 13.8 2.9 1.8 6.4


396

Very similar figures for poor and nonpoor agricultural workers also are found in considering the

production of various types of plants as portions of total plant production (Figure 5.6-1)—providing, in

other words, no clear evidence of productive specialization between poor and nonpoor workers.

Moreover, the share of total production not sold in the market (which can be interpreted as a proxy for

auto-consumption) is very similar among poor and nonpoor households (Table 5.6-12). These figures,

however, are averages of more diversified ones, as can be seen if shares are considered at the level of per

capita expenditure quintile. These shares increase from 28.8 percent at the poorest to 38.2 percent at the

middle quintile before decreasing to a minimum of 21.2 percent in the richest quintile. This evidence

suggests that the poorest households cannot afford to keep a large enough share of their production to

satisfy their own consumption needs.

Table 5.6-12. Share of Total Production Not Sold in the Market by Poverty Status and Per Capita

Expenditure Quintile

% total production not sold in market

Poor 29.7

Nonpoor 32.8

Per capita expenditure quintile

1 (poorest) 28.8

2 36.9

3 38.2

4 34.3

5 (richest) 21.2


Finally, the IHSES 2007 also collects information about the characteristics of the first four household

members involved in agricultural activity, and particularly in land cultivation. Table 5.6-13 shows that the

share of males among these agricultural workers is not significantly different across poor and nonpoor

households (the average being 78 percent). Among poor households, the average age of the people

participating in agricultural work is slightly lower than in nonpoor households. Finally, the share of

working children is slightly higher in poor than in nonpoor households. However, many household

members are not captured in the indicators supplied in Table 5.6-13, particularly for poor households in

rural areas, where the average household size is 9.7 people. And the characteristics of the unconsidered

members who participate in agricultural work may well be different from those of the first four members.

For instance, the actual shares of children participating in agricultural work may be higher than the

figures reported in Table 5.6-13, in particular in poor larger households. If this was the case, the actual

demographic characteristics of household members participating in agricultural work could be different

between poor and nonpoor households.


397

Table 5.6-13. Household Members Participating in Land Cultivation by Poverty Status

Male (%) Age (years)

Working

children (%)

Nonpoor 78.2 37.8 4.1

Poor 77.7 34.9 6.3

All 78.0 36.8 4.8



398

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