Using the home for income-generation

Pergamon

PII: S0264-2751(98)00037-7

Cities, Vol. 15, No. 6, pp. 417–427, 1998  1998 Elsevier Science Ltd. All rights reserved Printed in Great Britain 0264-2751/98 $19.00 ⫹ 0.00

Using the home for incomegeneration The case of Kumasi, Ghana Irit Sinai Institute for Reproductive Health, Georgetown University Medical Centre, 3PHC, 3800 Reservoir Road, NW, DC 20007, USA

A widespread phenomenon in many cities in developing countries is using homes not only for shelter, but also for income-generation through informal-sector activities. Using survey data from Kumasi, Ghana, I examine the characteristics of households that undertake such economic activities compared to those that do not. Descriptive analyses of socioeconomic characteristics, migration history, housing and location indicators, and tenure are presented. Discriminant analysis comparing the two groups is used to summarize the findings. Results show that female-headed households and larger households with older but less educated heads use their housing for income-generation more than other households. Migration history also distinguishes the two groups, but not in the expected direction. None of the location characteristics examined discriminate between the groups. Households that use their home for income-generation occupy more rooms, but their housing quality is not as good as the housing quality of other households.  1998 Elsevier Science Ltd. All rights reserved Keywords: Housing, home-based enterprises, Ghana

In cities where the level of self-employment in the informal-sector is high, households often treat housing not only as shelter, but also as a source for the generation of income (Fass, 1987). Thus, a woman can cook in her kitchen and sell meals in the market or at street corners, and a family store or workshop can be located at home. I focus on this phenomenon. Using the home for income-generation activities is more widespread in some cities than others. In his survey of four Bogota communities, Gilbert (1988) found stores everywhere in people’s homes. Few of those stores where impressive commercial enterprises, and most offered only limited ranges of products. A survey conducted in the Dakshinpuri settlement in South Delhi in 1987 demonstrated that in that neighborhood 20.3% of all housing was used for incomegeneration. Over half of the dwellings that were used for income-generation where wholly or partly rented out, while the remaining households operated business, service, or manufacturing enterprises (Raj and Mitra, 1990). The authors show that Dakshinpuri

households with lower income were more likely to use their housing for income-generation. A 1981 survey conducted in Colombo, Sri Lanka, which excluded squatter settlements, showed that a quarter of all dwellings housed a home business (Strassmann, 1987). Strassmann also discusses surveys in Peru and Zambia, which suggest that home enterprises were more widespread in poorer and smaller cities. Not much is known about the characteristics of households that use their home for income-earning activities. The scant literature on such activities focuses on the characteristics of the business and not the household (see, for example, Tipple, 1993) and ignores economic activities that are not visibly a part of a business (such as cooking food to sell elsewhere and storage). Strassmann (1987, p 125) stressed that “home-based family-operated enterprises are qualitatively different and are the core of the informal-sector because of two traits, the dwelling and the family”. He studied the effect of gender and location on income of home-based enterprises, and concluded that 417

Using the home for income-generation: I Sinai

the type of good or service produced by a home business determines its income less than other characteristics of the business, such as location, type of customers, education of the person who runs the business, and floor space used in the business. The purpose of this article is to study the socioeconomic and housing characteristics of households that use their housing for income-generation, compared to those that do not, in a traditional westAfrican city – Kumasi, Ghana. The study is based on data collected in Kumasi in 1996. I begin with a brief description of housing in the city and of the data set used for the study. The body of the article consists of a descriptive analysis of the demographic, economic, and housing characteristics of households that use housing for income-generation and those that do not. Finally, discriminant analysis is used to compare the two groups.

Kumasi Kumasi is situated within a dense rain forest, about 260 km from the capital, Accra, and the Atlantic coast. It was established in the 17th century at the crossroads of the trans-Saharan trade routes. The metropolitan area of Kumasi is estimated to have a population of about one million, making it Ghana’s second largest city. It covers about 150 km2 and is the administrative capital of Ashanti region (one of ten regions in the country). The location of the city in the center of the country, at a crossroads between the different regions of Ghana and neighboring countries, encourages its continuing role as a marketing center (Korboe and Tipple, 1995). About half of Kumasi’s residents live in traditional compound houses. Typically, a compound house is a one-storey structure consisting of a series of single rooms surrounding a square courtyard. Entrance to most rooms is from the yard, which provides a center for daytime activities and interaction between compound residents (Korboe, 1992). Some rooms have an additional entrance via a veranda that is opened directly to the street (Tipple et al., 1997). These verandas are remnants of the business and administrative rooms on the street side of important people’s houses in precolonial days. Most rooms have a smaller veranda on the yard side. A typical compound house covers an area of about 100m2. Three sides of the compound consist of 10–16 rooms. The fourth side often includes a bathroom (usually a cubicle with a small drainage hole at the base of the wall), a kitchen (a shelter open on the courtyard side, used for storage of cooking utensils), and sometimes a bucket latrine. These cooking and bathing facilities are shared by all households residing in the compound. Many compound houses have no latrines. Instead they have a cubicle for urination, with a drainage hole at the base, 418

and residents use public toilets or the bush1 for defecation (Tipple and Willis, 1991). A variation of the single-storey compound house is the multiple-storey compound, which has two or more floors. The upper floors are reached via a staircase in the courtyard. Each floor has a veranda facing the yard. Rooms in the upper floors are accessed from this veranda. Kitchen, bathroom, and bucket latrine are usually found at each level and are shared by all households residing on that floor. About a quarter of the Kumasi population lives in multi-storey compound houses (Korboe, 1992). Korboe (1992) suggested that about 75% of Kumasi residents live in single- or multi-storey compound houses. The remaining quarter of the population occupies three types of housing: the villa type house, government-built houses, and employer-built housing. Villas, like compound houses, are large. However, a typical villa house does not have a courtyard, and resembles large single-family houses in the United States. Villas are currently the typical mode of building. Government public housing in Kumasi is comprised of rows of single rooms, or small detached or semidetached bungalows. Seven housing estates were built in Kumasi. Most of these units were initially for rent, and the tenants were given an option to purchase them. Finally, large employers often provide housing for their workers at nominal rents. The houses range from rows of four or five rooms sharing kitchen, bathing, and toilet facilities through single-family houses for senior staff.

The data The data were collected in a survey conducted in 1996 in the Kumasi Metropolitan District. Data collection involved detailed interviews of 596 heads of households. The questionnaire asked about housing quality indicators, location characteristics, the use of housing for income-generation, and other economic and demographic characteristics of household heads. Data collection employed a two-stage sampling design. In the first stage, 31 city blocks were selected. Enumerators then systematically listed every household residing in the selected blocks. Out of 3133 listed households, 617 were selected. Of these, 596 were successfully interviewed. Recent migrants and households that had recently undertaken intraurban residential mobility were oversampled. The data are, therefore, weighted in the forthcoming analysis, and all results presented in the text, tables, and figures of this article refer to weighted data. The interview was administered to household heads only.

1 In the context of a big city, such as Kumasi, where there is little unused space, the bush is mostly areas used for home-based agriculture, along streams and drainage areas, or open space around dilapidated or abandoned public toilets (Wittington et al., 1993).

Using the home for income-generation: I Sinai

Housing uses in Kumasi Virtually every compound house in Kumasi is used for income-generation by one or more resident household, but often households residing in other types of housing also undertake such activities. This makes Kumasi an ideal location for the study of households using their homes for income-generation. The compound shown in Fig. 1 is a good example. The photograph shows the front of the house. The room on the left stores chairs and canopies that are rented out for funerals. The household that operates that business lives in another room in the compound. In the center is the veranda of a one-man shoemaker/contractor business. The contractor, who makes and repairs shoes on the veranda when his contracting business is slow, lives in the room behind the veranda. When he is not on the veranda working, his tools are stored in his room. The family residing in the room on the right sells boot-legged alcoholic beverages from the room. The main entrance to the compound is on the left of the house (not seen in the photograph). Shops are not the only income-generating activities that can take place in people’s homes. Almost all economic sectors are represented, with the exception of heavy industry. Out of 596 households in the survey 144 (24.2%) use their home for income-generation. Table 1 shows the type of economic activities undertaken from the home. Renting rooms to others is different from other economic activities taking place in the home in that it is passive – it does not require work. Many landlords have a job, and renting rooms to others is not the only income source for the household. Households that rent rooms to others have a common characteristic – they have to be home owners. Only 105 respondents (17.5%) own their homes. Of those, 40 households rent rooms to others. To prevent bias in

the results, using the home for income-generation through renting rooms to others is excluded from my analysis. Different parts of the home can be used for incomegeneration activities. First, the house itself – for most households this means the bedroom, since the majority of households in Kumasi occupy just one room (see discussion below); second, the yard, which is shared with all households residing in the compound; third, the veranda, which some households have exclusive use of, and others share with one or more other households (while some verandas face the street, most are on the courtyard side); finally, the street adjacent to the house, which is part of the plot the house is built on. The latter usually plays an integral part in compound life, and household chores, such as cooking and laundry, are often undertaken there. Fig. 2 shows the percentages of households using different parts of the home. Note that only 34 households used a part of the house exclusively for their income-generating activities.

Background characteristics Table 2 shows some characteristics of households that use their home for income-generation activities compared to households that do not undertake such activities. Moser (1987) showed that in developing countries women have a triple role in society – child care, community participation, and income-earning work. Using the home for income-earning activities allows them to accomplish the three roles. This is clearly evident in these data, where the percentage of femaleheaded households is much larger among households using their home for income-generation. It is also not surprising that households that use

Figure 1 A compound house in Kumasi

419

Using the home for income-generation: I Sinai Table 1 The economic uses of housing in Kumasi Economic use of the house

Weighted n (%)

Prepare food at home to sell in the house, to shops, in the market, or in the street Manufacture at home something other than food, to sell to shops, in the market, in the streets, or on order (for example, furniture, cement blocks, soap, clothing, shoes, and artifacts)

56 (9.4)

Operate a shop in the house or yard Work in the house or yard repairing things for people (such as radios, sewing machines, and watches)

21 (3.5) 5 (0.8)

Provide services from the home for pay (such as hairdressing, shoe shining, and day care services)

10 (1.7)

Raise livestock or grow fruit trees in the yard to sell produce Store things for sale in the market or in the street (these are petty traders who sell their ware by carrying it on their heads for people to see. Since the quantity they can carry is limited, they store surplus merchandise in the house)a Rent rooms to others for pay Totalb

20 (3.3)

4 (0.7) 39 (6.5)

40 (6.6) 144 (24.2)

a There are probably more than 39 petty traders in the sample, but many cannot afford to have surplus merchandise. They buy in the morning what they sell during the day, so they have no need for storage space in the house. b Many respondents specified more than one activity. Hence, the numbers total 195.

facilitates entry into formal-sector jobs. It should be noted, however, that in Kumasi access to formal jobs does not necessarily discourage households from undertaking informal-sector activities. Formal-sector jobs are more prestigious, but they often do not pay enough to sustain households. Therefore many formal-sector workers also have to undertake informalsector occupations.

Migration history

Figure 2 Part of the house used for income generation

their housing for income-generation are larger. After all, a larger number of adults or older children in the households means that there are more people who can undertake income-earning activities. Heads of households in which one or more members undertake income-generation at home are, on average, older. Table 2 also shows that household heads who use their housing for income-generation are clearly less educated than heads of other households. This trend is apparent even when controlling for gender and age (Fig. 3). It is not surprising, since better education 420

More than 60% of household heads in the sample are lifetime migrants, born outside of Kumasi, either in another part of Ghana (58.2%) or in a foreign country (2.4%). In addition, 23 respondents were born in Kumasi but left the city and lived somewhere else for a period of five or more years. These are return migrants and are considered migrants in the analysis. Goldscheider (1989), in his review of the literature on migrant assimilation in developing-country cities, concludes that there is no apparent structural feature that prevents migrants from participating in the urban occupational system relative to their skill level, after a short settling-in period. Goldscheider suggests, however, that migrants tend to concentrate more on informal-sector occupations than urban natives, especially in their first years in the city. Since using their housing for income-generation is largely associated with informal-sector occupations, Goldscheider’s claim implies that using the house in this way will be inversely related to length of the stay in the city. That is, the longer a migrant is in the city, the less likely he/she is to use his/her housing for work. This assertion is refuted in these data. About the same percentage of migrants and nonmigrants use their

Using the home for income-generation: I Sinai Table 2 Characteristics of respondents Characteristic

Mean household size Mean age of household head Female headed households (%) Household heads with no formal education (%) Household heads with O-level diploma or highera (%) Weighted n

Households using their housing for income-generation

Households not using their housing for income-generation

6.4 47.6 43.5 29.7 10.1

Total

4.5 45.0 31.2 20.0 23.6

120

4.9 45.6 34.0 22.2 20.5

475

595

a

In Ghana, the O-level diploma is given part way through high school.

Figure 3 Education level by gender and age Table 3 Length of stay of migrants in Kumasi by use of home and age

Use housing for income generation Do not use housing for income generation Weighted n F ⫽ 3.6851, significant at ⬍ 0.05 level

Age 0–34

Age 35 ⴙ

Weighted n

21.6 years 18.0 years 171

31.9 years 30.3 years 425

137 459 596

homes for income-generation activities (23.4% of nonmigrants; 22.8% of migrants). The average length of stay in Kumasi of migrant household heads who use their housing for income-generation is 29.8 years, but it is only 26.5 years for migrants who do not use their homes for work. This relationship is held when controlling for age (Table 3). These findings indicate that in Kumasi informalsector jobs are not a transition stage on the way to finding formal-sector positions. Another factor that influences these results is the improved education system in Ghana in recent years. As in most developing

countries (Zachariah and Conde´, 1981), migrants in Ghana are often young adults. Young adults today are better educated than young adults 10 and 20 years ago. This means that recent migrants are, on average, more educated than migrants who have been in the city longer, and better education means easier access to formal-sector occupations.

Income The informal-sector is characterized by a large number of small-scale production and service activities. 421

Using the home for income-generation: I Sinai

Workers in this sector are generally unskilled and lack capital resources, so that productivity tends to be lower in the informal-sector than in the formal-sector. As a result, informal-sector workers have lower income than formal-sector workers (Sethuraman, 1981). The data in this study confirm this assertion. Table 4 shows total monthly household income. Respondents were asked to provide information on household income in a typical month from wages and earnings of all household members, business profits, rental income, and remittances. These were summed to arrive at total household income in a typical month. The table shows that total monthly income of households that use their housing for income-generating activities is somewhat lower than income of other households. A better measure of economic well-being is the total monthly household income per capita, that is, income divided by the number of people in the household. As Table 4 shows, the difference in this ratio between households that use their housing for income and those that do not is substantial. Some households use their home for income as a way to increase total household income, because they have low incomes; other households undertake informalsector economic activities in the house because they cannot or do not want to find other work, and their income is lower because informal-sector jobs generate lower income than formal-sector ones. Recall, that in households that use their home for income-earning activities there may also be one or more members who are occupied in the formal-sector. Regardless, the income per person of these households is much lower than in other households. This income information, however, should be taken with a grain of salt, because income data in Ghana is notoriously unreliable. Several surveys found that income questions produced figures that only averaged about 40% of reported expenditures. These studies consider the expenditure information to be realistic, which means that income information is not (Tipple et al., 1997). Respondents do not report income accurately because they often do not include income from petty business, commissions, remittances, “dash” (tips or bribes), and various opportunities for small favors and profit. An index that is often used to measure relative household wealth, and one considered more reliable, is the possession of consumer goods. The mode of

calculation presented here was introduced in Tipple et al. (1997) in their study of wealth and home ownership in Kumasi and Berekrum (another city in Ghana). Consumer goods included in the calculation of the index are fan, sewing machine, radio/cassette player, television set, refrigerator, and a car. These goods represent a wide range of costs, and it is perceived that most households in Kumasi would wish to own the full set if they could afford to (though some may own none of the items). The index was calculated based on the estimated cost of these goods and the relative frequency of ownership of each good by sample households. It is interesting to see that the mean index score of households that use their housing for income-generation (0.127) and households that do not (0.129) is almost the same. This result suggests that income levels are the same for formal and informal jobs in Kumasi.

Housing characteristics and tenure Gilbert (1988, p 21) commented on “the strange divorce of academic work between that concerned with ‘work’ and that concerned with ‘housing’”. It is interesting, therefore, to examine the two concepts together, by comparing the housing characteristics of households that use their homes for income-generation and those that do not. Most respondents (90.7%) occupied rooms in compound houses, sharing cooking, bathing, and toilet facilities with other households residing in the compound. Villa residents do not use their homes for income-generation (5.1%) as much as compound dwellers (10.7%). The dominant form of residence arrangement in Kumasi is renting. More than 60% of households in the sample rent their rooms, mostly from private landlords (18 respondents rent their dwelling from a government agency or from their employer). Another common form of residence in Kumasi is rent-free family housing, an arrangement resulting from the traditions of the Asante people, the ethnic majority in Kumasi. Asantes have obligations to members of their lineage (a group of people sharing uterine descent from a common ancestress). Social convention does not allow a house owner to resist requests from lineage members for a room in the house – they have a

Table 4 Mean income in 1000s Cedisa

Use housing for income generation Do not use housing for income generation

Mean total income in a typical month

Mean income per household member

Weighted n

151.58 158.71

30.14 48.69

137 456

F ⫽ 0.166 Not significant

F ⫽ 4.899 Significant at ⬍ 0.05 level

At the time of the survey the exchange rate was $1 ⬇ 1600 Cedis.

a

422

Using the home for income-generation: I Sinai Table 5 Tenure arrangement

Use housing for income generation Do not use housing for income generation Weighted n ␹2 ⫽ 0.128 (df ⫽ 2), not significant

Rent

Rent-free family housing

Own

Weighted n

61.3% 61.2% 105 (61.2%)

20.4% 20.6% 127 (21.2%)

61.1% 60.9% 366 (61.3%)

137 459 596 (100%)

right to a room (Willis and Tipple, 1991). As a result, it is very common for people to occupy rooms in houses owned by a lineage member – rent free. About 21% of households in the sample enjoy this arrangement. Only 17.5% of sample households own their own dwelling. Table 5 presents the tenure arrangements of respondents. It shows that there are only minor differences in tenure arrangement between households that use their housing for income-generation and households that do not. Fig. 4 shows the number of rooms households occupied. The majority of households in Kumasi occupy just one room. In these data 64.6% of respondents occupied one room, and 20.8% occupied two rooms. Only 14.6% occupied three or more rooms. Since economic uses of the house take space, it makes intuitive sense that households that occupy more rooms would tend to undertake such activities more than households that occupy just one room. This is confirmed in these data. It is surprising that households that have use of a veranda (facing the street or the yard) use their housing for income-generation less than households that do not. Of the 524 sample households dwelling in compounds, 429 (81.9%) have a veranda by their room/s. Of these, 22.2% use their housing for incomegeneration, compared to 29.6% of compound dwellers with no access to a veranda. A housing quality index was constructed to estimate housing quality of respondents. The index is a modification of indices used in other housing studies (Johnson and Nelson, 1984; Lacey and Sinai, 1996;

Muoghalu, 1991). Housing quality indicators included in the index are the materials of the roof, walls, floors, and windows; the availability of water and electricity; the types of toilet and cooking area used; accessibility to a veranda; and the number of households sharing bathing and cooking facilities with the responding household. The scores of all indicators were normalized and aggregated. The final housing quality index is a continuous variable ranging from 39 to 95, with a mean of 68.5 and a median of 69. Table 6 shows that the housing quality of households that use their housing for income-generation is somewhat inferior to that of households that do not.

Figure 4 Number of occupied rooms

2

Location characteristics Kumasi is a large city, with a population of close to 1 000 000 and land area of about 150km2. It is, however, a collection of villages. With the exception of the very center of the city, which is densely built, small tracts of undeveloped land within the city boundaries are still used for subsistence or market agriculture. Most villages have a core area of traditional compound houses (in the larger villages there are also multi-storey compounds). Urban sprawl is all around them in the form of villa type houses. A typical example is the village of Ayeduase.2 The village is adjacent to the University of Science and Technology, about 8 km from the roundabout that is considered to be the center of the city. According to the 1984 census, the village had a population of 1834. I expect that today the population is much larger, because of the higher density in the existing compounds and because of all the new development around them. Maps of the village, drawn in 1991 by The Land Valuation Board, show that the village consists of seven city blocks of compound houses (two of them very old, built of laterite, and the rest newer, built of cement). There is one two-storey compound in the village; the rest are all single storey. Around this traditional core is a large area of 12 city blocks of villa type houses, that keeps expanding towards neighboring villages. In the traditional blocks the maps show 110 residential compound houses, and eight more under construction. In the new blocks of the village the maps show 67 residential houses, and 107 more under construction. The village of Ayeduase is where I lived during my stay in Ghana.

423

Using the home for income-generation: I Sinai Table 6 Housing quality index

Use housing for income generation Do not use housing for income generation Total sample n F ⫽ 5.293, significant at ⬍ 0.05 level

All respondents

Respondents who reside in compounds

66.51 69.10 68.51 596

65.8 66.8 66.5 540

Table 7 Residence in core area or periphery

Use housing for income generation Do not use housing for income generation Weighted n ␹2 ⫽ 0.074, not significant

Core area n (%)

Periphery n (%)

Weighted n

68 (22.1) 241 (77.9) 309 (51.9)

69 (24.0) 218 (76.0) 287 (48.1)

137 (23.0) 459 (77.0) 596 (100.0)

As a result of this type of development, prevalent throughout the city, neighborhoods cannot be easily classified by income. All income groups are represented in most areas of the city. This means that indicators which are often used to classify quality of life in communities are not useful here. For example, a 200-year-old laterite compound house can be on one side of the road and a huge villa housing a single family on the other. The former has no latrine and one water tap in the yard, shared by numerous households; the latter has running water and a modern kitchen. Both share the same access road, both can smell the same public toilet (although only the residents of the compound use it), and both are located at the same distance from schools, health facilities, and markets. Strassmann (1987) found in his study of Kalutara, Sri Lanka, that the location of home-based enterprises affects their income. Businesses located in middle- or high-income neighborhood yielded a higher income than those situated in low-income areas. However, the concept of low- or high-income neighborhood does not conform with the layout of Kumasi. Other characteristics may distinguish between neighborhoods: the centrality of the area, accessibility to different amenities, and cleanliness. The core area of Kumasi is surrounded by a circular road. Of the 31 blocks selected for this study, eight (25.8%) lie within the circle, and 23 in the periphery. Since core area blocks are densely populated, the eight blocks account for 48.1% of respondents.3 The proportion of respondents who use their housing for income-generation is somewhat higher among households living in the periphery, but, as Table 7 shows,

using the homes for income-earning is very prevalent all over the metropolitan area. To measure accessibility, respondents were asked how long it took them to reach the work location of the household member who earns the most income and the markets they used most often. Table 8 shows their responses. Because people can use different modes of transportation, such as walking, public transportation, and driving, this measure of accessibility is subjective – the same block can be very accessible to a household that owns a car, and not as accessible to households that use public transportation. In addition respondents were asked how long it took them to walk to the nearest public transportation route.4 Responses are also presented in Table 8. When households use their home for income-generation, it is not always the occupation of the household earners who earns the most money. But it is still not surprising that these households live closer to the work place of that household member than other households. The location of households in both groups are equally accessible to markets and public transportation. Another characteristic of neighborhoods people live in is how clean they are. Interviewers were asked to examine the cleanliness of the block that the house is a part of. For each block they observed: (1) whether drainage systems were cemented or just dug-out and whether drainage was free-flowing or blocked; (2) whether there is a refuse dump in the block, and if yes, whether garbage is collected regularly or burned; (3) the existence of and smell from public toilets on the blocks; and (4) the general cleanliness of the block. These were aggregated to arrive at a cleanli-

3 Since households were selected systematically from a complete listing of all households residing in each block, residents of core areas were not oversampled, so these figures represent higher density.

4 Public transportation in Kumasi is mostly in the from of taxies or small vans, that travel along transportation arteries and the main streets of villages, picking and dropping passengers on demand, not in designated stops.

424

Using the home for income-generation: I Sinai Table 8 Accessibility of location

Travel time Travel time to work of main income earner Less than 5 mina 5–14 min 15 min or more Weighted n Travel time to market used most often Less than 5 min 5–14 min 15 min or more Weighted n Walking time to neareast public transportation route Less than 5 min 5–14 min 15 min or more Weighted n

Households using their housing for income generation (%)

Households not using their housing for income generation (%)

Weighted n (%)

35 (27.5) 32 (25.0) 60 (47.5) 127

55 (13.4) 98 (24.0) 257 (62.6) 410

90 (16.7) 130 (24.2) 317 (59.1) 536

13 (9.8) 72 (52.6) 51 (37.5) 136

37 (8.2) 267 (58.6) 151 (33.2) 455

51 (8.6) 339 (57.2) 202 (34.2) 591

81 (60.0) 50 (37.0) 4 (3.0) 135

277 (60.9) 164 (36.0) 14 (3.1) 455

358 (60.7) 214 (36.3) 18 (3.0) 590

a

Including those who work at home

ness score for each block. This variable ranges from 5 (dirtiest) to 13 (cleanest). The data show that households that use their housing for income-generation and those that do not live in equally clean (or dirty) neighborhoods. The mean cleanliness score for both groups is 8.8.

Multivariate analysis Discriminant analysis is used to summarize the findings presented here. Discriminant analysis is a multivariate statistical technique that can be used to study the differences between two or more groups of respondents. In our case, the analysis compares households in which one or more members use the home for income-generation to all other households. The discriminating function is the linear equation that most “discriminates” between the groups. It is calculated to maximize the differences between the groups relative to differences within each group. The independent variables are the discriminators, and their coefficients can tell how well they discriminate between the groups, and which variables discriminate more powerfully (Klecka, 1980). Table 9 shows the independent variables included in the analysis and Table 10 shows the results of the discriminant analysis of the use of housing for income-generation. Since nine of the variables included in the analysis make, at best, a minimal contribution to distinguish between the two groups of respondents, a second analysis was conducted with a reduced variable set. This provides a test of the stability of the coefficients that have the highest values, given the absence of those variables that do not contribute to the discrimination initially. The reduced model is also presented in Table 10. The results are not surprising. Household size is by

far the most discriminating variable. Larger households include more members who can work from the home (even older children can work after school), and can contribute to the higher income needed to sustain more people. Education also discriminates between the groups. Heads of households that use the home for income-generation are less educated. This is not surprising, because work in the informal-sector is often associated with lower levels of education. This variable is followed by the number of rooms the household occupies. Households that use two or more rooms have more space that they can designate to economic activities. Gender is also important. Female-headed households use their home for income-generation more than male-headed ones. In addition to number of occupied rooms, two housing variables also distinguish between the groups (though their discriminating power is lower): housing quality and type of house. Households that do not use their homes for income-generation enjoy a better quality of housing than households that do. Households that reside in self-sufficient houses (singlehousehold houses or apartments) use their home for income-generation purposes less than those residing in compounds. Migrants and nonmigrants undertake income-generation activities at their home equally – the longer the migrants stay in the city, the more likely they are to do so. This confirms that in Kumasi migrants do not use informal-sector jobs as a stepping stone to formal-sector ones. But recall that for nonmigrants the value of the variable for length of stay in the city is their age, and age has a similar discriminating affect – households of older heads use their homes for income-generation more. It is interesting to note that tenure arrangement does not distinguish between the groups. Owners, renters, and those residing rent-free in family housing, 425

Using the home for income-generation: I Sinai Table 9 Variables included in the discrminant analysis Variable

Description

Type

Range

An index constructed from several housing quality variables, including materials of roof, walls, floors, and windows; availability of water and electricity; types of toilet and cooking area used; accessibility to a veranda; and number of households sharing bathing and cooking facilities with the responding households Number of rooms household occupies Type of housing household occupies

Continuous

39–95, higher values mean better housing quality

Dichotomous Dichotomous

1 ⫽ more than one, 0 ⫽ one room 1 ⫽ villa type, 2 ⫽ compound

Household owns dwelling Household lives rent free in family housing

Dichotomous Dichotomous

1 ⫽ yes, 0 ⫽ no 1 ⫽ yes, 0 ⫽ no

Travel time to markets used most often

Dichotomous

0 ⫽ less than 15 min, 1 ⫽ 15 min or more

Walking time to nearest public transportation route

Dichotomous

0 ⫽ less than 5 min, 1 ⫽ 5 min or more

Neighborhood cleanliness index

An index of several indicators including drainage system, refuse dump, public toilet, and general cleanliness

Continuous

5–13, 13 is cleanest

Periphery 3. Migration history Migrant

Location in core area of Kumasi or periphery

Dichotomous

1 ⫽ periphery, 0 ⫽ core

Whether household head is a life-time migrant to Kumasi Number of years migrants have been living in Kumasi. For nonmigrants this is their age

Dichotomous

1 ⫽ yes, 2 ⫽ no

Continuous

1–80

Gender of household head Age of household head

Dichotomous Continuous

1 ⫽ male, 0 ⫽ female 18–86

Household size Goods owned

Number of people in household An index of household goods the household owns

Continuous Continuous

1–20 0–1, higher values mean more goods owned

Income

Total household monthly income (in 1000s Cedis)

Continuous

1875–1 500 000 Cedis (total household income ranges 7500– 3 062 500)

Education

Highest level of education completed

Ordinal

0–13, 0 ⫽ no formal education, 13 ⫽ some university

1. Housing variables Housing quality index

Number of rooms House type Tenure arrangement Owner Family 2. Location variables Location accessibility

Length of stay in city 4. Background Male Age

(base category is renting)

are equally likely to use their home for income-generation. Similarly, location of the dwelling in the periphery (vs. city core), and accessibility to markets and public transportation, do not distinguish between the groups. Income, shown to be quite different for households that use their home for income-generation and other households, does not show this relationship in the multivariate setting, and has virtually no distinguishing power.

Conclusion I examined different characteristics of households that use their housing for income-generation compared to households that do not. Using the home for incomegeneration appears to be a universal phenomenon in Kumasi. Households undertake such activities in the 426

city core and the periphery, regardless of income, tenure arrangement and accessibility to markets and public transportation. Larger households, female-headed households, and those with older or less educated heads, use the home for income-generation more. Three housing variables differentiate between the groups. First, those residing in self-sufficient houses (single-household houses or apartments) use their home for income-generation less than compound dweller. Second, households that use their home for income-generation occupy more rooms, but their housing quality is not as good as the housing quality of other households. This suggests that perhaps 5 Rents are so low in Kumasi, that they do not really have much economic pull. However, since rent-control has been lifted, rents are slowly increasing.

Using the home for income-generation: I Sinai Table 10 Discriminant analysis of the use of housing

Acknowledgements

Variable

I wish to thank Stephen Owusu, David Korboe, and Sam Afrane, from the University of Science and Technology in Kumasi, Ghana, for their support and assistance in data collection for this study.

Standardized coefficientsa Full Reduced variable set variable set

Household size Education Number of rooms Male Housing quality index Length of stay in city Age House type Travel time to market Income Neighborhood cleanliness index Walking time to public transportation Owner Family Periphery Goods owned index Migrant Canonical correlationb Eigenvaluec ␹2 df Significant at

0.760 ⫺ 0.413 0.361 ⫺ 0.328 ⫺ 0.261 0.259 0.239 ⫺ 0.239 ⫺ 0.117 ⫺ 0.038 ⫺ 0.035 ⫺ 0.020 0.017 ⫺ 0.013 0.012 ⫺ 0.012 ⫺ 0.012 0.341 0.132 70.395 17 ⬍ 0.001

0.807 ⫺ 0.442 0.379 ⫺ 0.333 ⫺ 0.275 0.262 0.245 ⫺ 0.238

0.320 0.114 63.044 8 ⬍ 0.001

a These standardized discriminant function coefficients represent the relative contribution of each variable to discriminating between households that use their housing for income generation and households that do not. The possible values range from 0 to 1.0 and are directly comparable across variables. For example, a value of 0.4 indicates twice the discriminating ability of a value of 0.2. Positive/negative signs are arbitrary. The equation would work just as well if all signs were reversed. b The canonical correlation is a measure of the degree of association (Pearson correlation coefficient) between the discriminant scores and the group variable, which is coded 0 and 1. c Eigenvalue is the ratio of the between-groups to within-groups sums of squares. Large eigenvalues are associated with “good” functions.

households that use their housing for income-generation sacrifice the potential expense of improved housing quality, so that they can afford to occupy more rooms.5 Further research is necessary to determine if this is indeed the case, that is, if households decide to occupy more rooms so that they can have more space to divert for income-generation activities. If this is the case, the implication is that for these households the choice to occupy more rooms is a business decision, an not only a shelter-related one.

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