Perceptions of Good Jobs

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BACKGROUND PAPER FOR THE WORLD DEVELOPMENT REPORT 2013

Perceptions of Good Jobs

Tewodros Kebede Anne Hatløy Huafeng Zhang Ingunn Bjørkhaug

Analytical Report

Urban Cairo and Rural Fayoum, Egypt

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Fafo-report 2012:20 ISBN: 978-82-7422-881-8

The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the World Development Report 2013 team, the World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

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Chapter 1 Introduction

Jobs have taken a center stage in the policy debate due to recent world developments ranging from consequences of the financial crises to that of the Arab uprising that is partly fueled by youth unemployment as well as political discontentment. The World Development Report 2013 focuses mainly on jobs and their connections with important dimensions of economic and social development. To this end, jobs can be seen as having transformational roles in three dimensions:

living standards, productivity and social cohesion. In essence, focusing on what a good job for development is from these perspectives will provide insights help address diverse job agendas.

The notion of a good job may seem normative but can also be anchored in basic economic arguments. Instead of having a list of criteria such as structure of earning, health benefits, and pension plans to characterize a job as good job, the WDR 2013 calls for focusing on the overall features of a job as seen from its value in terms of increasing living standards, productivity growth, and increasing social cohesion. However, it may be difficult to identify a single type of job that is considered as good job in all dimensions. A job that is considered good in one aspect, such as increasing income, may not necessarily be considered as prestigious job. Instead of trying to focus on a single job, one may be interested to look into various facets of a given job and conduct an assessment from different perspectives.

This study attempts to understand and explain how jobs are perceived in various countries. The report is primarily targeted to provide inputs towards the WDR 2013 and is part of a series of studies conducted on perception of good jobs in four countries: Colombia, China, Egypt and Sierra Leone. The main emphasis will be exploring the nature of jobs that affect living standards and enhance social cohesion. With this main objective, the report addresses the following research questions:

- What are the most important factors affecting labor force participation?

- What are the relations between jobs and household wealth?

- In addition to the limited availability of opportunities for work, can perceptions and stereotyping of jobs be regarded as constraints for job creation?

- What are the linkages between job benefits and job stability?

- What are the determinants of job satisfactions?

- Jobs can be evaluated using a human empowerment perspective by focusing on three features of job: cognitive, creative and autonomous activities. What is the relationship between job status and human empowerment?

- Understanding any substantial differences will suggest that job is an important factor to build trust and hence social cohesion in a given society. Does having a job contribute to increased social trust and confidence in institutions?

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This study is conducted in urban Cairo and rural Fayoum, Egypt. This report is organized as follows. This chapter provides background to the study area. In chapter two a description of the methodology used in this study is presented. Chapter three presents description of the data collected for this study, including socio-economic background and characteristics of labor force in the study area. Chapter four outlines the results and discusses main findings. Summary of the main findings are made in the last chapter.

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Chapter 2 Methods

2.1 Good jobs survey

The main objective of the survey was to obtain data on perceptions of jobs in addition to obtaining information on basic labor force indicators, economy and social trust.

The main design characteristics of the sample used in this study were as follows:

1. The target population of the study was all households living in urban Cairo and rural Fayoum

2. The sample frame was based upon the 2006 Egypt Population Census.

3. The survey should be able to provide statistics break down on urban and rural areas for Cairo and Fayoum governorates in Egypt.

4. Each domain received allocation of 45 primary sampling units (PSUs) (clusters) 5. The selection of clusters was based on probability proportionate to size (PPS)

6. In each of the clusters, 12 households were randomly selected using random walk procedures

7. One household member was randomly selected from all household members aged 18 and above to answer the questions on perceptions of good job.

With this design, the survey was conducted in 90 clusters making up a total sample size of 1080 households.

2.2 Questionnaire

To understanding the population‟s own perception of jobs calls for detailed information about what „good‟ and „bad‟ job characteristics are and constraints to accessing good jobs in the local context. In addition, barriers to labor market entry and potential solutions for these barriers are important indicators that could have policy relevance. An associated concept of job stereotypes could also help highlight what is regarded as a good job and is obtained through vignettes depicting various types of jobs. To obtain these and associated indicators relevant for this study, two the instruments are developed.

Part I was administered at the household level. The respondent for this part of the questionnaire is the household head or any other eligible knowledgeable person who can provide information for the household as well as other household members. The household member is called for responding to questions on household level information such as demographics, education, labor force participation to household members (age 14 and above), household economic conditions and assets.

Part II was administered to randomly selected individual (RSI) among the members of the household with age 18 and above. The second instrument calls for the randomly selected

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individual to respond to specific questions about the person‟s current job status and its associated features; the person‟s own perceptions of jobs; issues regarding social trust, confidence on various institutions and participations on social organizations. These question items are intended to be answered only by the randomly selected individual. The structure of the questionnaire is depicted in Figure 1 below.

Figure 1 Overview of structure of instruments

2.3 Empirical methods

Descriptive statistical methods including frequencies, means, graphs and tables are used to describe the various indicators used in this study. In addition to the descriptive statistics, the study employs regression models to explore relationship with various factors affecting the dependent variable under investigation. Generally, the perception indicators used in this study are measured using five Likert items: 1=Not at all satisfied; 2=Somewhat unsatisfied; 3=Neither;

4=Somewhat satisfied; 5=Very satisfied. These values make up an ordinal set and ordinary least square (OLS) regression will not be suitable to explain the various job satisfaction indicators used in the study. Hence, ordered logit regressions are used to explain factors affecting job satisfaction.

Another type of indicator used in the study takes binary values (0 or 1). Specifically, labor force participation is recorded as whether individuals are in or out of the labor force. OLS will not be suitable for dummy variable indicators either. So, logistic regression is used to explore factors influencing labor force participation.

Multiple Correspondence Analysis (MCA) was used in this report to analyze the pattern of relationships of several categorical variables. It is an extension of correspondence analysis (CA), which was developed by Hirschfeld (1935) and Jean-Paul Benzecri (1973). MCA is part of a family of descriptive methods, such as Principal Components Analysis, that use mathematical procedure to reveal pattern in complex data sets. It is very useful in mapping both variables and

All Household Members (PART I)

 Demographics

 Household composition

 Education

 Labor force participation

 Housing

 Economic conditions

 Assets

Selection of RSI

Information on RSI’s (PART II)

 Job status and features

 Perceptions on job

 Social trust and participation

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individuals so as to construct complex visual maps whose structuring can be interpreted. The increasing use of visualizations in presentations makes this method more popular in illustrating complex relationships between variables. The method is particularly suitable when responses to question items are recorded in categorical scale. In this report, we employed Multiple Correspondence Analysis in analyzing perception of different of jobs, social trust and confidence in institutions. Technical description of the method can be obtained in Greenacre and Blasius.

2006.

This report also constructs a wealth index from a set of assets owned by the household. This wealth index is a linear asset-based index, constructed following procedures as in the Demographic and Health Surveys (Rustein and Kiersten 2004). It considers households‟ access to durable consumer goods and other asset indicators related with housing, water, sanitary facilities and other amenities owned by households. To construct this asset index, we use the following set of mixed asset-based and health-related variables for determining wealth tertiles:

- Household ownership of consumer durables (mobile phone, sofa set, chair, table, bed, mattress, mat, sewing machine, gas cooker, stove, water heater, water filter, electric fan, vacuum cleaner, microwave, fridge, freezer, air conditioner, washing machine, TV, radio, bicycle motorbike, cars, DVD player, satellite connection, internet access, personal computer, photo camera, video camera)

- Characteristics of households‟ dwelling (number of rooms, floor material, electricity, toilet facility, water sources)

- Households‟ ownership of dwelling

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Chapter 3 Data

The survey was planned to cover 1080 households in urban Cairo and rural Fayoum. The survey has a response rate of 99.6 percent (including partially completed interviews) resulting in final sample size of 1074 households as shown in Table 1. Regarding the randomly selected individual survey, the response rate is 98.7 percent resulting in a final sample size of 1065 RSIs including partly completed interviews.

Table 1 Interview status for households and randomly selected individual

Interview status Households (%) Randomly selected individual (%)

Interview completed 99.4 98.2

Interview partly completed 0.2 0.4

Refusal 0.5 0.1

No contact 0.0 0.6

Incomplete household interview - 0.7

Total 100 100

Sample Size 1080 1080

In this survey, no substitution has been made for households and RSIs that could not be contacted during the survey period. This is mainly needed so as not to introduce a bias that may be due to systematic absence of households and RSIs. In situations where people who do not work are more likely to be at home, carrying out substitutions would increase a sampling bias through oversampling of RSIs that are unemployed or outside the labor force. During the survey implementation, repeated visits have been made to interview selected households and individuals and hence reduce non-response rates of the survey.

3.1 Demographic and dwelling characteristics

The sex structure of individuals covered under the study exhibited that there are slightly higher percentage of females in urban areas (51 percent) while it is lower in rural Fayoum (49 percent).

Rural Fayoum has a young population with 50 percent of the population below 20 years while urban Cairo has a higher median age of 28 years.

In urban Cairo 99 percent of household live in an apartment while in rural Fayoum majority of them (64 percent) live in standalone houses. While 46 percent of urban dwellers rent their apartments, 84 percent of rural dwellers own their houses. Almost all houses are connected to electricity and have piped water into their apartments in urban Cairo. In rural Fayoum access to electricity is almost universal while 90 percent of household have piped water into their dwelling.

Around 9 percent of the households in rural Fayoum have piped water from public tap. Regarding sanitation facilities, 90 percent of urban dwellers have toilets with a flush to piped sewer system with the remaining households having either to a flush to septic tank or pit latrine. On the other hand in rural Fayoum, 80 percent of households have flus to pit latrine toilet facilities with the remaining having a flus to piped sewer system to septic tank.

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3.2 Economic situations

Based on a set of consumer goods owned by households together with other asset indicators such as sanitation facilities we constructed a wealth index to identify households‟ economic situations.

When ranking the households‟ wealth index, household size was taken into account, that is, the ranking of the wealth index was based on the population.

Figure 2 shows the distribution of households by the value of the wealth index for rural and urban areas. The differences in distribution between rural and urban areas are quite clear. In urban areas, the index is skewed to the left while it is skewed in to the right in the rural areas with the majority of households below the mean value.

Figure 2 Distribution of household wealth index scores by urban-rural location

In addition to using objective measure of wealth based on household assets, households were interviewed to provide a subjective assessment of their economic situations that are classified into three different categories: live well; neither rich nor poor and poor. The households‟ subjective assessments on the economic situation indicate that 20 percent of urban households considered

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themselves as being poor while 17 percent of rural households considered themselves as being poor (Table 2).

Table 2 Household economic situation

Urban (%) Rural (%)

Subjective assessment on household

economic situation

We live well 27 32

We are neither rich nor poor 53 51

We are poor 20 17

Satisfaction with current financial situation

Fully satisfied 6 19

Rather satisfied 54 56

Neither 4 6

Less than satisfied 22 15

Not at all satisfied 16 4

Financial situation during last year

Save money 4 3

Just get by 60 76

Spent some savings 9 3

Spent savings and borrowed money 11 1

Only borrowed money 16 16

Sample size 532 538

In addition to these indicators households were also asked how satisfied that they were regarding their current financial situation. Thirty eight percent of the household were not satisfied with their current financial situation while 19 percent of households in rural Fayoum expressed dissatisfaction in their financial situations as shown in Table 2. In relation to this 36 percent of urban households have spent their savings or borrowed money during the last year while in rural Fayoum, about 20 percent of households have either spent their savings or borrowed money.

3.3 Labor force participation

For the purpose of this study we have used the ILO definition for unemployment. ILO defines the unemployed as „the person who during the past seven days was without work, was currently available for work and was seeking for work‟. Of the 44 percent economically active individuals, there was higher unemployment rate in urban areas (9 percent) as shown in Table 3 as compared to 4 percent of unemployment in rural Fayoum. The gender disparity in the labor market was quite contrasting where more women were out of labor force than men in both urban and rural areas. In all the interviewed households, around 80 percent of women aged 18 and above were out of labor force. Among those in the labor market, more women were unemployed than men reflecting a gender inequality in terms of labor market participation.

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Table 3 Employment status (Age 18 and above)

Urban Rural

Male Female Total Male Female Total

Employment status Employed 67 17 42 81 19 51

Unemployed 7 2 4 3 2 2

Out of labourforce 26 81 54 16 79 47

Sample size 687 712 1399 682 661 1343

Unemployment rate - ILO definition

Employed 91 89 91 97 93 96

Unemployed 9 11 9 3 7 4

Sample size 508 137 645 574 136 710

3.4 Characteristics of randomly selected individuals

Altogether 1065 RSIs were interviewed, among whom 532 were in urban area and 533 in rural area. Table 4 shows the age and gender distribution, marital status, educational level, employment status of the interviewed RSIs in the survey. In line with the age structure of the study population, more RSIs of age below 34 were interviewed in rural Fayoum than urban Cairo.

Table 4 RSI characteristics

Urban (%) Rural (%)

Age 18-34 36 49

35-49 26 31

50-64 26 15

65+ 11 5

Gender Male 44 40

Female 56 60

Marital status Single 21 12

Married/Cohabitant 59 76

Widow/Divorced/Separated 19 12

Education No school or no stage completed 32 52

Elementary or intermediate completed 21 13

Secondary (high school) or higher completed 47 35

Employment status Wage work 27 24

Farm work 0 11

Enterprises 11 12

Unemployed 4 1

Out of labor force 58 52

Physical or psychological illness of prolonged nature

Yes 27 12

No 73 88

The educational level completed by the interviewed RSI varied quite much. As many as 47 percent of the urban RSIs completed secondary high school or higher education, while it was 37 percent in rural area. On the other hand 52 percent of RSI from rural Fayoum had no school while in urban Cairo it was 32 percent.

As to the employment status, a quarter of RSIs were wage earners in both urban and rural areas.

Farm work is limited to only rural areas and hence 11 percent of rural respondent were engaged

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in farming owned or rented by a member if the household. Equal percent of households in both urban and rural areas were engaged in self owned enterprise activities.

Chapter 4 Results

In this chapter, we will present the main results. Section 4.1 presents determinants of labor force participation among the population age 18 and above. The relationship between wealth and jobs are explored in section 4.2. Section 4.3 deals with job stereotype and how this differs by different social categories. Section 4.4 presents job benefits to wage workers. Job satisfactions assessed from different perspectives are presented in section 4.5. The role of job in empowering people is presented in section 4.6. The last section presents how having a job influences social trust and confidence in institutions.

4.1 Determinants of labor force participation

The previous section discussed characteristics of people in and outside the labor force. In this section, we will investigate the features of individuals that are relevant for labor force participation. We conducted a logistic regression for the population in age group 18-65 and the results are shown in Table 5 below.

Table 5 Logistic regression of labor force participation

Variables Estimate Std.

Error P-value³ Odds ratio

Female, compared to Male -3.416 0.128 0.000 ** 0.033

Age 0.373 0.030 0.000 ** 1.452

Age squared -0.459 0.038 0.000 ** 0.632

Elementary completed¹ -0.063 0.000 0.757 0.939

Intermediate completed¹ 0.072 0.204 0.728 1.074

Secondary or higher level completed¹ 0.537 0.207 0.000 ** 1.710 Slightly difficult health condition² -1.185 0.149 0.000 ** 0.306

Difficult health condition² -1.192 0.000 0.000 ** 0.303

Household size -0.135 0.275 0.166 0.874

Dependency ratio 0.401 0.272 0.118 1.493

Wealth index -0.006 0.097 0.953 0.994

Urban compared to Rural -0.321 0.257 0.060 * 0.725

Constant -1.272 0.093 0.017 ** 0.280

-2 Log likelihood 2191,382a

1 Compared to No Education; ²Compared to No health problems;

3 Significant at 5% level(**) and 10% level (*) Household population 18-65 years old, n=1933

Women are less likely to participate in the labor market

The logistic regression model shows that women are less likely to participate in the labor market as compared to men exhibited by the negative and significant relationship with likelihood of

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labor force participation. This is in line with the descriptive observation made earlier in that women are mainly out of the labor force.

Higher education is key for labor force participation

Secondary or higher education is positively related to probability of participating in the labor force. The relatively insignificant but negative relationship of lower level education shows the relative importance of having a higher education to participate in the labor market.

Health matters

Self-reported chronic health status of individuals is a key indicator that determines labor force participation. The reported chronic health status is classified into three categories: individuals who has no reported health problem; individuals with slightly difficult health situation in that they have reported health problem but are less hindered to go out on their own; individuals who have health problems that makes it difficult to move around by themselves. Individuals with difficult health conditions are less likely to participate in the labor force. Those with slight health problem are also less likely to participate in labor force signifying the role of health related problems in labor market decisions.

Inverted U-relationship between age and labor force participation

Labor force participation-age relationship is exhibited to be inverted U-shaped in that labor force participation increases as age increase but tends to decrease after the turning point is reached.

Household size, dependency ratio and location

Household size and dependency ratio are found to have statistically insignificant relationship with that of labor force participation. However, as indicated by the signs, household size negatively influences the likelihood of labor force participation. On the other hand, when the dependency ratio increases, individuals are highly likely to participate in the labor force. Urban dwellers are significantly less likely to participate in the labor force than the rural dwellers.

4.2 Jobs and household wealth

Employment status has positive relationship with household wealth

Table 6 shows the ranking of households‟ wealth index in all the interviewed households in the study area by the proportion of employed members in the household. The distribution of wealth and employment status is similar in urban and rural areas. In rural Fayoum, the more people are employed in the household the higher their wealth is. This trend is also similar in urban Cairo.

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Table 6 Household wealth index by proportion of employed persons

Proportion of members employed

Wealth index tertile (%)

Total (%) Sample size Poor

third Mid third Rich third

Urban

No employed member 43 32 25 100 132

0.01 to 0.40 32 35 33 100 256

0.41 to 0.99 25 34 41 100 119

Total 34 34 32 100 507

Rural

No employed member 50 29 21 100 76

0.01 to 0.40 34 32 33 100 322

0.41 to 0.99 26 33 41 100 129

Total 35 32 33 100 527

4.3 Perception about job types

Randomly selected individuals were asked to choose from eight different types of professions and rank them according to their preference. This is in order to understand job stereotyping that will shed light on features of good jobs by ranking them across three different dimensions:

preference for them, most important to society and easiest to pursue.

The preferred jobs are similar in booth urban Cairo and rural Fayoum. The most preferred job in the urban Cairo among men was to work as a government employee. More than 20 percent of the men answered that this would be their first choice of work in both urban and rural areas (Figure 3). On the other hand, females in urban areas prefer teaching as their choice and while rural women rank doctor as their first preferred job. Government employment ranked third by women as their preferred job where as it is the first choice for men in both urban and rural areas. It is interesting to note that in rural areas, farming ranked 4^th by men and women.

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Figure 3 Preferred job by location and gender

On the question of what job that is easiest to pursue, shop owner and government employee rank on the same level by men while shop owner rank the highest among women followed by teacher in urban areas. The picture in rural area is quite different in that both men and women perceive farming as an easiest to pursue. The perception of men and women in rural areas in what they think is easiest to pursue is similar (Figure 4). .

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Figure 4 Job type easiest to pursue by location and gender

The response to what type of job is most important for the society is quite similar across location and gender (Figure 5). Doctors and teachers rank the highest, followed by farmers. Government employment ranked fourth in both urban and rural areas even if it is the type of job that people would like to pursue. Taxi drivers, hair dressers, carpenters and shop owners are ranked low along the dimension of importance for society.

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Figure 5 Most important job by location and gender

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4.4 Job benefits for wage workers

In this section, we will describe job associated benefits for wage employees. This will help assess the labor market situation for wage employees in addition to providing a basis for assessing job satisfaction in the subsequent sections. All wage employees with long term contract receive health insurance from their employers. In addition to health insurance, pension after retirement, transportation allowance and learning opportunities are provided to employees with long term contracts. Job benefits is strongly related to the type of job contract a person has and as can be seen from Table 7, employees with long term wage contract has more benefits as compared to employees with short term contracts (less than one year).

Table 7 Benefits from employer by contract status

Job related benefits Short term contract (%) Long term contract (%)*

Health insurance from employer 10 92

Pension after retirement 7 90

Bonuses 11 77

Maternity leave 4 73

Learning opportunities 6 27

Transportation allowances 4 10

School fees 1 10

Unemployment benefits 4 9

Stock shares 1 4

Free meals 11 3

Housing allowances 1 3

* Long term contract=contract for one year or more

The contrast between benefits for employees with long and short term contracts becomes sharp when the number of benefits provided is taken into account. To this end, long-term contract employees have large number of benefits as compared to short term contract employees (Figure 6).

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Figure 6 Distribution of benefits among wage workers¹

The work benefits had a high correlation with people‟s satisfaction in the work. All the interviewed wage earners were classified into one of the four groups, according to the number of work benefits they get from employers. In Figure 7 these four groups of people and their satisfaction with job stability, form of contract, training and skill development, social status from job, potential for future personal development and level of income are listed. The answers “very satisfied” and “somewhat satisfied” were grouped to be presented as “satisfied” for all the questions. This group of people who enjoyed most work benefits was most satisfied with almost all aspects of their work, and in particular satisfied with relationship with colleagues, job status, and job stability. Those who had very limited or no access to the work benefits were most dissatisfied with the potential of their job for future personal developments.

1 n=271 wageworkers in urban Cairo and rural Fayoum, Egypt: February 2012

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Figure 7 Satisfaction and number of job benefits

4.5 Job satisfaction

Job satisfaction is an indicator of workers‟ happiness and is in a number of studies shown to be good both for workers and employers. Workers that are satisfied have positive organizational behavior and tend to perform better and are more likely to receive rewards realized in the form of promotion and pay rises (Clark and Oswald 1996, Diener and Seligman 2004, Fassina et al 2008).

In this study, workers were asked about their satisfaction with difference facets of their job.

As shown in Figure 8 very few people were satisfied with their current income level in both urban Cairo and rural Fayoum. People were not very satisfied with their job stability, their possibility for training and skill development, and their potential for future personal development.

On the other hand, they were rather satisfied with the practical conditions of their work such as the work hours, the distance to the work place and the relationship with colleagues.

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Figure 8 Level of jab satisfaction

Among the various aspects in which people have evaluated their level of satisfaction, we focus on three facets: satisfaction with their level of income; satisfaction in their job potential for future development and satisfaction in social status they obtain from their job. We conducted ordered logit regression analysis on each of these satisfaction indicators that are measured as a single index on likert scale (1=not at all satisfied, 2=somewhat satisfied, 3=neither, 4=somewhat satisfied, 5=very satisfied.) The results are shown in (Table 8). As wealth increased the level of satisfaction the level of income also increased. Satisfaction on level of income was also significantly related to the number of jobs people are conducting indicating the use of diversification for providing sustained level of income. This is further strengthened by the positive relationship between number of hours and level of satisfaction with income. Self- employed people are less satisfied with their level of income indicating wage employment is a better alternative. Urban workers were less satisfied with their job compared to rural workers.

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Table 8 Ordered logit regression estimates for satisfaction with level of income

Variables Estimate Std. Error P-value¹

Female, compared to Male 0.162 0.235 0.490

Age -0.018 0.050 0.724

Age squared 0.033 0.062 0.598

Wealth 0.520 0.157 0.001 **

More than one job 1.095 0.326 0.001 **

Employment status² -0.301 0.126 0.017 **

Number of hours worked per week 0.009 0.005 0.067 *

Type of tasks (Creative versus routine) -0.033 0.036 0.359

Level of Independence 0.157 0.034 0.000 **

Level of Meaningfulness of Job -0.014 0.042 0.734

Usefulness of job for:

Establishing contacts with people -0.083 0.124 0.505

Learning new things 0.116 0.100 0.249

Information about other jobs -0.104 0.091 0.254

Information about societal matters -0.089 0.100 0.374

Information about Good Deals 0.021 0.081 0.798

Decision Making in household 0.047 0.096 0.621

Urban compared to Rural -1.108 0.302 0.000 **

-2 log likelihood 1132

Sample size ( All employed RSIs) 419

1 Significant at 5% level (**) and 10% level (*)

2 Self-employed versus wage employment

Another important factor that determines the level of satisfaction with the future potential of the job people conduct (Table 9) was the level of meaningfulness they attached to the job they carried out. The level of satisfaction was also related to opportunity provided as a result of having the job towards learning new things, obtaining information about other job opportunities and societal matters. Similar to the dimension of level of income, urban workers were less satisfied with their job‟s potential for future personal development compared to rural workers.

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Table 9 Ordered logit regression estimates for satisfaction with job potential for future development

Age 0.028 0.049 0.577

Age squared -0.017 0.061 0.782

Wealth 0.924 0.159 0.000 **

More than one job 0.789 0.318 0.013 **

Number of hours worked per week 0.004 0.005 0.397

Type of tasks (Creative versus routine) 0.009 0.035 0.810

Level of Independence 0.005 0.033 0.880

Level of Meaningfulness of Job 0.128 0.042 0.002 **

Learning new things 0.238 0.099 0.016 **

Information about other jobs 0.046 0.090 0.607

Information about societal matters -0.299 0.100 0.003 **

Information about Good Deals 0.084 0.080 0.294

Decision Making in household 0.067 0.095 0.482

1 Significant at 5% level (**)

Jobs can be classified as good or bad depending on the social status people associate with their activities. This could be a barrier for unemployed people to engage themselves in income earning work. Hence, the level of satisfaction in social status from a given job is another indicator of a good job. This level of satisfaction was positively influenced by wealth, wage work versus self- employment, level of meaningfulness of the job they carry out, and usefulness of their current work in terms of learning new things as well as obtaining information about societal matters (Table 10). The usefulness of a given job in providing decision making capabilities at the household level is positively related to level of job satisfaction regarding social status from job.

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Table 10 Ordered logit regression estimates for satisfaction with social status from job

Age 0.037 0.050 0.459

Age squared -0.011 0.062 0.855

Wealth 0.573 0.156 0.000 **

More than one job 0.019 0.318 0.952

Number of hours worked per week -0.005 0.005 0.300

Type of tasks (Creative versus routine) 0.044 0.036 0.220

Level of Independence 0.045 0.033 0.175

Level of Meaningfulness of Job 0.140 0.042 0.001 **

Learning new things 0.072 0.099 0.466

Information about other jobs -0.160 0.091 0.079 *

Information about societal matters 0.025 0.100 0.798

Information about Good Deals -0.059 0.081 0.465

Decision Making in household 0.217 0.095 0.023 **

1 Significant at 5% level (**)

From these various satisfaction assessments, we understand that perception of good job is related to location, age, wealth, employment type, meaningfulness of the job as well as ability to obtain information relevant for job related and societal issues. Most importantly, the ability to have a diversified source of income is a determining factor for various aspects of job satisfaction.

4.6 Jobs and empowerment

Jobs can be perceived from a human empowerment perspective (Alexander and Welzel 2011) with three dimensions of work activities: cognitive, creative and autonomous dimensions (CCA).

As shown in Table 11, the jobs in the study area are characterized by being manual labor, dominated by routine work, and with a high level of autonomy. In addition people who work find their work meaningful – more than 50 percent rate their job as meaningful with a sense of doing something useful. These patterns are the same independent of education and current job status, as shown in Table 11. However there is a tendency that people with wage employment have slightly more cognitive work than the self-employed have while the self-employed have much more autonomy in their work than the wage workers. People with higher education have jobs that are characterized as more cognitive and creative than the ones without education. However, work autonomy does not seem to be influenced by the lack of education.

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Table 11 Feature of job by education and type of work in percent

Job status (%) Education (%) Total (%)

Wage employment

Self- employment

No stage completed

Elementary/

intermediate

Secondary or higher Cognitive¹

Manual 45 60 71 70 34 51

Intermediate 22 31 23 21 28 25

Cognitive 33 10 6 9 39 24

Creative²

Routine 56 65 75 65 48 59

Both 27 24 16 22 33 26

Creative 17 11 9 13 19 15

Autonomy³

Low 40 14 28 36 30 30

Medium 40 17 19 27 38 31

High 20 69 53 38 32 40

Meaning- fullness in the job⁴

Low 10 11 15 9 8 10

Medium 37 33 38 34 34 35

High 53 56 47 57 58 54

Total 100 100 100 100 100 100

Sample size 269 177 150 56 240 446

1Cognitive: Are the task in your work mostly manual or mostly cognitive. Rate from 1 (mostly manual) to 10 (mostly cognitive) – Manual 1-3; Intermediate 4-7; Cognitive 8-10

2Creative: Are the task you perform mostly routine or mostly creative. Rate from 1 (mostly routine) to 10 (mostly creative) – Routine 1-3; Both 4-7; Creative 8-10

3 Autonomy: How much independence do you have in performing your tasks at your main job? Rate from 1 (No independence at all) to 10 (complete independence) – Low 1-3; Medium 4-7; High 8-10

4 Meaningfulness in the job: How meaningful is your main job? Rate from 1 (Not meaningful at all) to 10 (Very meaningful and gives a sense of doing something useful) ) – Low 1-3; Medium 4-7; High 8-10

Regarding how meaningful people find their job, there is little difference between the wage workers and the self-employed. However, those with at least some education find the job more meaningful than people without any education. Table 12 shows that the more people characterize their job as cognitive, creative and autonomous, the more meaningful they find their job.

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Table 12 How meaningful people find their work related to empowerment?

Meaningfulness in the job (%)

Not

meaningful Medium Very

meaningful Total (%) Sample size Cognitive¹

Manual 15 38 47 100 227

Intermediate 8 46 46 100 112

Cognitive 3 20 78 100 107

Creative²

Routine 14 31 54 100 264

Both 4 50 46 100 115

Creative 5 28 68 100 65

Autonomy³

Low 22 27 51 100 132

Medium 7 50 43 100 134

High 5 31 64 100 176

Total 10 35 54 100

1Cognitive: Are the task in your work mostly manual or mostly cognitive. Rate from 1 (mostly manual) to 10 (mostly cognitive) – Manual 1-3; Intermediate 4-7; Cognitive 8-10

2Creative: Are the task you perform mostly routine or mostly creative. Rate from 1 (mostly routine) to 10 (mostly creative) – Routine 1-3; Both 4-7; Creative 8-10

3 Autonomy: How much independence do you have in performing your tasks at your main job? Rate from 1 (No independence at all) to 10 (complete independence) – Low 1-3; Medium 4-7; High 8-10

4Meaningfulness in the job: How meaningful is your main job? Rate from 1 (Not meaningful at all) to 10 (Very meaningful and gives a sense of doing something useful) ) – Low 1-3; Medium 4-7; High 8-10

4.7 Jobs, social trust and institutions

Several variables have been identified to capture the degree of social trust including trust in family, neighbors, friends, people met for the first time, people from workplace, another religion and another ethnic group. Two categories ”Trust completely” and ”Trust somewhat” were merged as ”Trust”, while two categories ”Not trust very much” and ”Not trust at all” were merged as ”Not trust”. As can be seen in Table 13, people showed higher trust on the family, friends and neighbors than other people.

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Table 13 Level of trust by employment status

Trust towards people Wage

employment Farming

Self- employment

Out of labor force

Family Trust 100 100 100 99

Difficult to say - - - -

Neighbors Trust 85 95 88 90

Difficult to say 1 - - -

Friends Trust 90 94 87 89

Difficult to say - - 1 1

People met for first time Trust 27 36 31 35

Difficult to say 2 - - -

People from workplace Trust 77 77 63 49

Difficult to say 2 - 5 6

People from another religion

Trust 41 30 46 39

Difficult to say 5 4 8 5

People form another ethnic group

Trust 15 13 17 17

Difficult to say 18 8 17 14

Sample size 272 56 121 584

Values show percentage of people who have complete or somehow complete trust

Since there are more than one social trust indicators, it is important to identify the underlying components of the indicators while maximizing the amount of variance accounted for in those indicators. While many respondents chose the “difficult to say” category, together with the scale categories of the questions on trust and confidence, it is then inappropriate to treat these variables as scale variables. Therefore, MCA is a more appropriate tool to analyze the relationships of questions on trust towards people, and questions on confidence in institutions, respectively.

The joint plot of category points in Figure 9 identifies two dimensions of trust towards people.

Apparently, “difficult to say” has its own dimension which is captured in the second dimension, while first dimension captures people‟s general trust level. In the first dimension, the higher the loading is, the less people trusted others; while the lower the loading is, the more people trusted others. Therefore, we can construct an index of trust by using the object scores on dimension one.

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Figure 9 MCA loadings across two dimensions of trust indicators

In order to understand the role of job on social trust, we conducted a regression analysis by using the trust index and the results from regression are presented in Table 14. As the higher index indicates a low trust, we reverse the index in order to simplify the interpretation, that is, the higher index represents higher trust level. Employment status does not have a significant relationship with the level of trust. However, the rural urban divide is quite clear in that there is high level of trust in rural Fayoum compared to urban Cairo. Wealth is also significant and positively related to social trust.

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Table 14 Regression results for index of trust

Variables

Trust Index

Estimate Std. Error P-value

Constant -0.717 0.297 0.016

Women compared to men 0.000 0.012 0.666

Age 0.038 0.089 0.982

Age squared 0.009 0.013 0.493

Rural compared to urban 0.373 0.100 0.000 **

Employment status:

Farming -0.138 0.162 0.395

Self-employment/ family business¹ -0.068 0.114 0.551

Out of labor force¹ -0.075 0.101 0.459

Wealth Index 0.098 0.049 0.046 **

Sample size 1053

1 Base category is wage worker

**Significance level 5%

In addition to the trust indicators, respondents were asked to provide information on their level of confidence in various institutions. These institutions range from governmental institutions to that of local and international organizations. The percentages of people that had confidence or found it difficult to say are shown in Table 15. Again, quite a few people reported “difficult to say” on the confidence questions.

Perceptions of Good Jobs