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African Population Studies
Union for African Population Studies
ISSN: 0850-5780
Vol. 19, Num. 1, 2004, pp. 165-185

African Population Studies/Etude de la Population Africaine, Vol. 19, No. 1, April 2004, pp. 165-185

The Migration Effects of the Economic Structural Adjustment Programme on a Rural Community in Zimbabwe

Dick RANGA

Centre for Population Studies, University of Zimbabwe, P. O. Box MP167, Mt. Pleasant, Harare, Zimbabwe

Code Number: ep04009

ABSTRACT

This paper examines factors influencing long-distance migration during a period of economic reforms, from Nyamaropa Communal Area in Nyanga district of Manicaland Province in eastern Zimbabwe, to various intra-country destinations. The economic reforms were implemented in phases and the study is particularly concerned about the effects of the first phase, dubbed the Economic Structural Adjustment Programme (ESAP, 1991-5). Primary data was collected using a household questionnaire between 1998-2000 and captured both pre- and post- ESAP periods. However, the limitation of such data is separating what could have happened without the reforms. This limitation is relevant in the case of Zimbabwe because there was a severe countrywide drought between 1992-3, just after the ESAP started in 1991. Data analysis involved both bivariate and multivariate procedures and results indicated that: higher levels of education, singleness, and having off-farm income were all less associated with long distance migration. This is contrary to findings of distance decay studies, which suggest greater frictional role of distance on the less educated and married individuals, particularly in the case of labour migration. The study, however, did not only focus on labour migration, but all mobility patterns. Two types of migrants emerged: women moving long-distance to join husbands in Harare accompanied by children, and short-distance migrants related to casual work. The latter could not have been the effect of drought but ESAP’s economic hardships.

INTRODUCTION

The International Monetary Fund (IMF) and World Bank economic reforms in Zimbabwe were in two phases, both implemented for five-years periods, namely: the Economic Structural Adjustment Programme (ESAP) between 1991-95 and the Zimbabwe Programme for Economic and Social Transformation (ZIMPREST) between 1996-2000. While the former involved the usual SAP policies of domestic deregulation and liberalization (trade and markets), the latter incorporated social reforms aimed at human resources development, in addition to the usual economic policies. The majority of these policies affected urban more than rural dwellers simply because the former are more linked to the cash economy than the latter. Only agricultural reforms would directly impact on the lives of people in rural areas.

However, the two areas, rural (particularly communal areas) and urban, are closely linked through migrant remittances, such that changes in livelihoods in urban areas gradually impact livelihoods in the rural areas too. Historically, what are called communal areas today were formerly Tribal Trust Lands (TTLs) or ‘reserves’. These were agriculturally barren portions of the country where the majority black Rhodesians (now Zimbabweans) were allocated land for settlement during colonialism through the Land Apportionment Act of 1930 (Ranga, 2003). This Act alienated considerable tracts of land from Africans so that by 1963 only 50,000 square miles were set aside for the use and occupation of 2,630,000 Africans, against 75,000 square miles for some 215,000 Europeans (Gann 1963). Thereafter, the colonialists used mechanisms such as the ‘hut tax’, which had to be paid in cash, to force the blacks to move out of the ‘reserves’and look for wage labour in white-owned farms or firms.

Now that Zimbabwe as well as other sub-Saharan African countries have tasted the prescription provided by the Bretton-Woods institutions in the form of Structural Adjustment Programmes (SAPs), there is need to assess their direct or indirect influences on areas that have received less attention such as the spatial pattern of population mobility. The SAPs do not have specific `prescriptions’to influence the distance travelled by migrants, but during their implementation they unintentionally instigated changes in migration distance patterns. However, what we know from neo-classical economics is that, generally, economists favour geographical mobility since it moves people from places where they are less productive to places where they are more productive (Layard 2003).

There is evidence that ESAP was structured to achieve this general goal. For example, Amendments to the Labour Relations Act were implemented to allow more ‘flexible hiring and firing of labour to improve firms’efficiency and competitiveness’1. In the neoclassical economic sense, this strategy keeps production costs low by reducing the costs of labour and at the same time, moves labour from where it is less productive. Hence, the Social Dimensions of Adjustment Programme (SDA) was designed to temporarily take care of the welfare of this displaced labour while waiting to get into other jobs, formal or informal, where their labour is more productive.

PROBLEM STATEMENT

As mentioned above, some of the ESAP policies indirectly affected mobility patterns and in most cases negatively, as in the case of insecure families due to labour displacement or relocation. Such policies were explicitly related to certain sectors including, labour, transport, foodstuff prices, and agriculture. As expressed in the Government’s policy document, Zimbabwe: Framework for Economic Reform (1991-95), domestic deregulation policies were designed to see that wage labour, basic commodity pricing (including food and transport), and agricultural pricing, were all determined by market forces, instead of the government meddling in such affairs.

The effects of deregulation varied with each sector. Chipika (1998) reported that retrenchment of workers was severe, with 32,440 formal sector jobs lost by December 1995 compared to the original target of 20,000. Cuts in public transport subsidies and decontrolling of these prices saw fewer households in Harare being able to pay for transport to work (Kanji, 1995:43). A number of men and women had begun trekking to work or had arranged lifts, which cost less than the bus service, and this basically affected the lower-paid workers.

Although there are no studies on the effects of these policies on the long-distance rural public transport sector, what happened in urban areas was precisely the case in rural areas. At that time, it was common to see on national television stranded passengers during major public holidays, particularly Christmas, because most urban migrants adjusted their rural visits to once a year. At the same time, public-transport operators continued to hike fares, citing high operation costs due to the devaluation of the Zimbabwe dollar. In the rural areas, the removal of subsidies resulted in the prices of commodities such as seeds and fertilizers rising, dramatically.

The overall effects were massive erosion of farmers' incomes and increasingly poorer and insecure households (separated by long distance and facing risk of break-ups), whose major income sources, farming and migration, had run dry. Households, particularly lower-income migrant ones, had to devise strategies to deal with this critical situation. Among others, possible strategies included, considerations for re-migration for the retrenched, having single residence (temporarily close the rural residence) for those who still worked in urban areas, or seeking transfer to smaller urban areas closer to the migrant’s rural home.

However, some of these strategies posed serious dilemmas for the families involved simply because they were also less feasible due to structural constraints. For example, for those who wished to re-migrate or relocate to nearby smaller towns, they were faced with an economy infested with problems like increased unemployment and intensified de-industrialization (Tevera 1998). This was also a period when most foreign investors would prefer to start their businesses in the capital city, where infrastructure already existed.

The Migration Effects of the Economic Structural Adjustment Programme The Migration Effects of the Economic Structural Adjustment Programme Standing (1991) argues that, as a result of deregulation, forms of labour security around the world have been eroded and conditions have deteriorated. There was strong purpose in the Zimbabwe Government's intervention in the labour market prior to ESAP, as Kadenge et al. (1992:188) argues: The Migration Effects of the Economic Structural Adjustment Programme The Migration Effects of the Economic Structural Adjustment Programme The Migration Effects of the Economic Structural Adjustment Programme The Migration Effects of the Economic Structural Adjustment Programme The Migration Effects of the Economic Structural Adjustment Programme The Migration Effects of the Economic Structural Adjustment Programme The Migration Effects of the Economic Structural Adjustment Programme The Migration Effects of the Economic Structural Adjustment Programme

Study Significance

A study of the migration effects of SAPs is necessary in order to draw lessons that can benefit other countries going through economic reforms, particularly since this area has received little attention. The study would be of more practical use if the results would inform more about how long-distance migrant families responded to the dilemmas stated above. It is however, worth noting that the study does not provide a conclusive causal analysis of the relationship between structural adjustment programmes and long-distance migration. This is because it was not easy to separate the effects of ESAP (1991-5) and others events such as the drought in 1992-3. The study simply places in context of SAPs the factors that influence long-distance migration and by so doing provides a case study of migration effects during SAPs.

Objectives and Hypotheses

The study assessed the effects of individual and household characteristics on the likelihood of long-distance migration during the Economic Structural Adjustment Programme (ESAP, 1991-5) from Nyamaropa Communal Area in eastern Zimbabwe.

The study mainly hypothesized that the likelihood of long-distance migration would be lower during the post-ESAP than the pre-ESAP period. Borrowing from Raveinstein’s ‘laws of migration’and distance decay models, the study also hypothesized that:

    1. The likelihood of long-distance migration would decrease as age of migrant increases.
    2. Males were more likely to migrate over long distance than their female counterparts.
    3. The likelihood of long-distance migration would increase as level of education attended increases.
    4. Married migrants were less likely to travel longer distances than unmarried migrants and those whose marriages were disrupted, that is, divorced, separated or widowed.

Definition of Migration and its Problems

The study focuses on the spatial dimension of migration. Thus, short-distance migration is defined as those moves to places within a radius of 200km from villages of origin in Nyamaropa communal area. With reference to a map of Manicaland Province in Zimbabwe, short-distance moves would take one across Nyanga district, to Rusape town in the west, and to the provincial capital, Mutare, in the southwest direction from Nyamaropa communal area. Long-distance moves, on the other hand, were defined as any other moves beyond the 200km radius and such distance would take migrants to the capital city, Harare, as well as to the second capital, Bulawayo. The selection of these areas was based on a preliminary analysis, which indicated areas within a 200km radius from Nyamaropa as the most common destinations of the majority of migrants from this area who moved for business, shopping, social visits, and/or marriage

However, a note should be made of the problems associated with such a spatial definition of migration. For instance, a major definitional problem cited by Hugo (1982) is that of determining the administrative areas between which moves can be classified as migration. Due to this problem there have been difficulties of comparing migration rates and patterns internationally since the national division of the country into areas is variable so that in some `migration' is measured as movement between large states and some between much smaller geographic units. A second problem originates from the meaning of `distance'. The concept of distance is not a straightforward matter of miles and kilometres, but involves three principal concepts including geographical, economic, and social distance. These two problems are relevant to this study.

Regarding geographical distance, there is a problem of determining the distance over which moves are classified as `migration'. Statisticians have argued that there are particular statistical problems with taking short-distance movements as the criterion for migration. However, the selection of types of areas between which moves are classified as migration might have profound implications for the observed incidence or pattern of migration. The notion of ‘economic distance’, which is also relevant during SAPs, involves costs and availability of communication, information and transport networks. This is separated from the notion of social distance, which includes separation from an accustomed circle of family and neighbours or from particular ethnic group or from other particularistic social groupings to which the mover belongs. Hugo (1982) argued that not all moves involve both types of separation, but movement across national boundaries involves the greatest social distance in the migration process. Although international migrations should have been significant during ESAP, they are beyond the scope of this paper.

LITERATURE REVIEW

Literature on the migration effects of SAPs is both limited and scanty. But, what is plenty are the impacts of SAPs on other aspects of people’s lives, including employment, health, education, and general standard of living. In most cases, these studies are conducted in urban rather than rural areas. Hence, literature discussion is separated into two parts: that related to (a) the effects of SAPs, particularly the effects of those policies that would indirectly influence mobility patterns, and (b) the patterning of long-distance migration according to individual or household characteristics of the migrants or other events such as drought.

Standing (1991) argues that, as a reult of deregulation, forms of labour security around the world have been eroded and conditions have deteriorated. There was strong purpose in the Zimababwe Government's intervention in the labour market prior to ESAP, as Kadenge et al. (1992:188) aruges:

...Government intervention in the labour market has been at two levels, that is, wage determination and regulations designed to provide job security to workers. With regard to the first level, the major objective was to reduce income inequalities inherited from the colonial regime. In this regard, Government introduced minimum wage legislation to improve the living conditions of low wage earners, while at the same time imposing direct control on wage increases depending on levels of income.

The Government's reversal of regulations that were initially aimed at ensuring job security obviously resulted in job losses. Government had estimated that the number of job losses in relation to the private sector was going to be around 20 000 (Government of Zimbabwe, 1991). But, Chipika (1998) reported that retrenchment of workers was severe, with 32,440 formal sector jobs lost by December 1995 compared to the original target of 20,000. Furthermore, several researchers (e.g. Kadenge et al., 1992; Chakaodza, 1993 and Tevera, 1998) all argue that, already there was a high level of unemployment in Zimbabwe before ESAP, but the Government's and the private sector's retrenchments increased the unemployment rate to unprecedented proportions.

By the end of 1995, Government had removed all price controls except on a few basic foodstuffs. According to Kadenge et al. (1992:183), the purpose of having price controls prior to ESAP were three-fold:

...Firstly, they were aimed at protecting low-income households by making the cost of basic foodstuffs affordable. Secondly, because of foreign currency shortages and other production bottle-necks, companies could take advantage of the situation of excess demand over supply and increase prices to earn scarcity rents. Price controls were aimed at curbing this practice. Lastly, the high degree of concentration allowed for monopolistic pricing which is exploitative and would hit low-income households particularly hard.

The implications of the removal of government price controls for the people of Zimbabwe, particularly low-income households, were several. Prices naturally rose as well as inflation. For instance, in May 1991, the Consumer Council of Zimbabwe reported that the average price increase stood at 47% (Sunday Mail, May 12, 1991) and between 1992-3, Chakaodza (1993:65) reported that inflation was close to 50%. According to Kadenge et al. (1992), the increase in prices implied the erosion of real incomes given that there was no equal increase in nominal wages and/or incomes. Chakaodza (1993:65) argued that the removal of price controls increased costs on the working people. This in turn led to social problems like unprecedented levels of crime, begging by `street kids', prostitution, the AIDS epidemic and drug abuse, as well as the impoverishment of significant strata of the urban and rural populations. Tevera (1995) argued that after the removal of price controls, food prices and transport fares rose rapidly, and vulnerable groups in both urban and rural areas were unable to meet basic needs such as food, shelter, education and health. Kanji (1995:39) argues that the ‘increased prices of basic foods in this period was a direct result of the lifting of food subsidies and not the importation of food as a result of drought’.

At the same time, cuts in public transport subsidies and decontrolling of these prices saw fewer households in Harare being able to pay for transport to work. In rural areas most peasant households blamed the soaring bus fares during the economic reforms for their sons’, daughters’or spouses’failure to pay them visits and hence, their lack of financial support, which is associated with visits by the migrants. Usually when they visit home, migrants bring remittances with them, which are mainly in the form of groceries and cash.

Finally, deregulation saw the removal of agricultural producer price controls, marketing monopolies by parastatals, and lifting of subsidies on crop inputs. Before the introduction of ESAP in 1991, agricultural marketing parastatals [e.g. Grain Marketing Board (GMB) and Cotton Marketing Board (CMB)] were sole marketing channels through which producers were obliged by law to deliver their agricultural products. The implication of agricultural price decontrol was quite clear: agricultural incomes improved. But this improvement was not sustained in the long term because the removal of subsidies resulted in the prices of commodities such as seeds and fertilizers rising, dramatically.

Literature on the effects of individual characteristics on long-distance migration suggests that a larger proportion of men than women usually migrate for longer distances to urban centres as well as internationally to work for wages. This indicates the less influence exerted by distance on males than on females. For example, in Southern Africa the majority of migrants from Zimbabwe, Mozambique and Zambia moving to mines and farms in South Africa are men. The tendency by females to migrate to nearby places is a result of the restriction on females' autonomy by a male-dominated society.

However, Oberai (1990) argued that more women in Africa and South Asia are now joining their husbands working in longer-distance towns or are independently migrating to cities. Traditionally, women were expected to be either housewives or peasant farmers, while it was proper for the husbands to go out sometimes for long distances and find work. In addition, at the time of marriage women were instructed by aunties to look for suitors from nearby places and this was designed to avoid the psychic costs associated with longer-distance migrations for marriage. In other words, it was easy for a woman to get married to a husband who spoke the same language and who came from the same cultural background in order to avoid integration and adjustment costs. Such trends are, however, likely to change with major economic reforms such as ESAP because it affects almost all aspects of people’s lives forcing them to use different adaptive strategies.

Gwaunza (1998) analysed the impact of distance on mine workers at Mhangura Copper Mine2 in Mashonaland province, Zimbabwe. She found that the impact of distance from home areas and tribal influence was to an extent alleviated by the spirit of tribal interaction engendered at the mine. In her case study of Mhangura, she found that:

...The mine has attempted to create the organization of workers along ethnic lines. For each ethnic group represented, there is a `chief'. Every new recruit is required to indicate his tribal origins, after which he will be assigned to the appropriate tribal `chief'. Although the `chiefs' are not chiefs in the conventional sense of the word, they are to an extent expected to know, uphold and enforce the general customs and practices of their tribes within their communities. (Gwaunza 1998:52)

Hence, the case study of Mhangura Mine has shown that management has attempted to make the process of integration and adjustment to a workplace distant from home as easy as possible to the migrant workers, while at the same time they could work and earn their wages with peace of mind.

Literature on the migration-distance relationship has also focused on the correlation between migration to nearby places and short-duration, cyclical movements. In Asia, Hugo (1982) found that factors such as the distance between town and village, the costs of traversing it, the availability of work in the home village, and others, all contributed to the frequency with which short-term migrants moved.

Drought, whose effects can be related to other times of hardships such as the period of ESAP, has been found to shift the choice of destinations by migrants in favour of nearby places. This is because long-duration migrations, which are correlated with long-distance movements, usually require fairly sizeable travelling expenses and support while the migrant looks for work. The migrant must have a larger resource base upon which to draw as well as more money with which to finance the journey. In addition, they need more education and job experience to improve their chances in competitive labour markets, and more contacts at the destination that can help them get jobs or who can support them until they can support themselves. Because these concerns have to be planned for, long-distance and long-duration migrations are impractical as spontaneous responses to a drought-induced crop failure (Findley, 1994).

Instead, those who are already migrants will be expected to intensify their remittances, but families may lack the resources to suddenly sponsor a new long-distance migrant and all available funds will be diverted to more urgent food needs. As a result, short-duration labour migration to nearby places should rise during a drought. And this effect of drought on the shift in the choice of destination areas could be the counterfactual when we analyse the migration effects of ESAP.

Conceptual Framework

Different scholars have used several variables to estimate the choice of destinations by migrants. Initially, one of Ravenstein's (1985) laws stated that females are more migratory than males within the kingdom of their birth, but males more frequently venture beyond. Oberai (1990) supported this law when he argued that, in Africa and much of Asia, men predominate in rural-urban migration flows, while women often form the majority of short-distance, rural-rural migrants.

Stillwell (1991:43) used data on mean migration distances for National Health Service (NHS) patients moving between eighteen zones of a system of metropolitan and non-metropolitan areas in the United Kingdom (UK) to illustrate how distance over which migration occurs varied with age. He found that, indeed, the propensity to migrate over distance and the distance over which migration occurred did vary with age. In the early age groups, distance exerted most influence on migrants aged between 10-14 and least influence on those aged 20-24. Thereafter, the frictional effect of distance increased steadily to around retirement age before levelling off.

Stillwell (1991) was correct when he concluded that the manner in which the propensity to migrate over distance changes by age is indicative of the various motivations, which influence individuals at various stages in the life cycles. But, he was silent about the fact that these motivations vary according to the stage of development of the area where the survey is being carried out. For the UK, which Stillwell (1991) was writing about, data showed that longer-distance population redistribution involved a larger proportion of labour migrants changing their jobs as well as moving house, whereas shorter-distance migrants had a higher proportion of individuals who were moving purely for housing and environmental reasons. On the other hand, while some of the motivations, which influence individuals at various stages in the life cycle in Zimbabwe, may be similar to those in the UK, the majority are different between the two countries because they are at different levels of development. For example, longer-distance population movement may still involve a larger proportion of labour migrants like in the UK, but in Zimbabwe most of these migrants would be searching for their first jobs especially after finishing school, instead of changing jobs. Furthermore, instead of a higher proportion of shorter-distance migrants moving purely for housing and environmental reasons (Stillwell 1991), the majority of shorter-term migrants in the Zimbabwean situation are likely to move for different reasons including seasonal labour, seasonal visits, education, etc.

Oberai (1990) hypothesized that the frictional effect of distance is more applicable to the low-income and less educated migrants. In other words, low-income migrants are less positioned to bear the high costs of traversing a longer distance separating village and destination area and therefore, tend to go to nearby places. The same applies to the less educated whose chance of getting employed in longer-distance urban areas is slim and if they do get employed in town, their income would not be enough to outlay the costs of transport and initial cost during job search. This was precisely the case in the period of economic reforms and de-industrialization.

Oberai (1990) also highlighted the importance of the accessibility and availability of transportation and communications networks in the whole migration-distance equation. In addition, Guilmoto (1998) argued that short-term moves are logically oriented towards closer destinations. In his West African study in the Senegal Valley, Guilmoto (1998) found that more than 22% of short-term migrants remained in the same Saint-Louis region, from which they originated, whereas less than 12% of these migrants went for longer distances. Other variables necessary to include in the estimation model are marital status and family responsibility, which are likely to be negatively correlated to longer-distance migration.

METHODS AND MATERIALS

This section describes the source and collection of data and the statistical method used. This article is part of a larger study conducted by the author comparing the effects of the Economic Structural Adjustment Programme (ESAP) on migration between a dry region and a wetter region in Zimbabwe. Nyamaropa communal area was selected in the larger study to represent the wetter region. Nyamaropa communal area is situated in Nyanga, a district that lies along Zimbabwe's eastern border with Mozambique. More specifically, Nyamaropa is about 180km northeast of Manicaland province's capital, Mutare, and also about 70km east of the small town of Nyanga (Magadlela 2000). The entire communal area stretches over several kilometres within a valley, which is surrounded by hills that stretch northward from the Inyangani Mountains in the south.

Climatically, the area is classified under agro-region IIb, which is `an agro-ecological zone marking the limits of the dry-land cropping zone, receiving mean annual rainfall of 600-800 mm' (Madondo, 1997:355), and experiences tropical Savannah characterized by strong seasonality (wet summer and dry winter) with constantly high temperatures. It could be noted that while the area around Nyanga town comprises high altitude and cool temperatures, Nyamaropa Communal Area is situated in a low-lying area and therefore, experiences hotter temperatures and high humidity than Nyanga town. Hence, dry-land farming is feasible here, but added to this advantage Nyamaropa has one of the most successful irrigation schemes in the country. Crops grown in the irrigation scheme include grains, such as maize; vegetables; and cash crops, such as cotton, paprika, tobacco and beans.

The paper draws from data collected by the author between 1998-2000 by means of household questionnaires aimed at capturing household migration during two time phases, 1988-90 (pre-ESAP) and 1996-98 (post-ESAP). This two-set retrospective survey was administered to a sample of 200 households from Ward 12 (Nyamaropa irrigation scheme) and another 200 households from Ward 13 (Nyamubarawanda dry land farming area) in Nyamaropa communal lands within Nyanga district, Zimbabwe.

The selection of the two Wards was purposive as the author expected to find out different spatial patterns in out-migration from the Ward with irrigation and that with dry-land farming. The rationale is that the irrigation scheme was likely to repel longer-distance migration, but at the same time attract short-distance migration, which is related to movements to purchase inputs and sell farm produce. However, systematic selection methods were used in the selection of households in villages within the Wards. In addition, the author supplemented questionnaire data with data from in-depth Interviews with randomly selected household heads, as well as Focus Group Discussions with villagers of different ages and sex. However, the results are not discussed in this paper.

A multivariate model was used for statistical analysis of the data. The multivariate analysis used a simple logistic regression model. This was due to the fact that the dependant variable, migration distance, is measured by two categories: (1) short-distance, and (2) long-distance, and is therefore binary. The logistic regression model is mathematically represented below, but the specific interaction variables and the reasons for adopting them will be discussed with the results.

Y = (bi Xi + ej)

= b0 + b1X1 + b2X2 + b3X3 + b4X4 + …ej

Where:

Y = a dummy equal to 1 if an individual out-migrated for long distance and zero if an individual out-migrated for short distance.

bi = the regression coefficients

Xi = the predictor variables which were collected at the individual, household and community levels, and

ej = the error term.

RESULTS

Data analysis began with descriptive statistics including frequency counts and cross-tabulations of relevant variables (see Annex 1 and 2) and testing for relations using chi-square tests. Annex 1 shows the distribution of short-distance and long-distance out-migrants by characteristics, and Annex 2 displays the spatial distribution of the two types of migration from Nyamaropa Community Area. Table 1 presents the results of a multivariate logistic regression of the relative risk of long-distance migration.

The overall Model Chi-square was highly significant, P < .01. The independent variables correctly predicted about 77.05% of the variation in migration distance. Level of education had a highly significant result. That is, individuals who had attained primary school were less likely to have migrated for longer distance than the uneducated and secondary or higher school leavers. At the same time, individuals who had attained secondary or higher levels of education were less likely to have migrated for long distance than the uneducated and those who had attained primary education.

These results were inconsistent with the expectation that the frictional effect of distance would be more applicable to the less educated migrants. However, this expectation was based on the assumption that most of the migration would be in search of wage labour particularly in the urban formal sector where a higher level of education would be required. But the fact that the results of descriptive statistics (see Annex 1) indicate that most of the long-distance out-movers include children visiting and women joining their husbands in town could have changed the usual nature of the relationship between migration distance and level of education attained, hence the negative results.

One of the parameters of marital status was significant, P < 0.1. More specifically, never married individuals were significantly less likely to have migrated for longer distance, than married individuals and those with disrupted marriage. These results were consistent with the effects of movement by more married women joining their husbands in town, mainly Harare. However, the same pattern would be depicted when both married men and those with disrupted marriage move in search of wage labour in order to support their families back home. The majority of these men could have ended up joining the urban informal sector, which at that time had expanded.

Table 1: Relative Risk of Long-Distance Out-Migration

Variable

Relative Risk of Long-Distance Out-Migration (B*)

Time Phase

Pre-ESAP (1988-90)

1.00

post-ESAP (1996-98)

1.12

Age (complete years)

0-15

1.00

16-40

1.29

41+

1.23

Sex

Male

0.78

Female

1.00

Education Level Attended

No education

1.00

Primary

0.60***

Secondary & higher

0.68*

Marital Status

Never married

0.40*

Married

0.99

Disrupted

1.00

Whether hh owned cattle

Yes

0.88

No

1.00

Duration of absence

Commuter

1.00

Short-term

5.13***

Long-term

8.45***

Relationship to hh head

Head/spouse

1.00

Own child

1.56

Other

1.58

Whether hh had crop income

Yes

1.13

No

1.00

Whether hh had non-farm income

Yes

1.37*

No

1.00

Whether hh had off-farm income

Yes

0.65***

No

1.00

Model Chi-square 198.6***
Overall cases correctly predicted 77%
Sample Size 1351 persons

HH/hh –Household *Significant at 10% ** Significant at 5% *** Significant at 1%
Source: 1998-2000 Survey Results

The paper, on the other hand, had predicted that married men especially heads of households would move to nearby places as they are usually tied down to within their home areas by responsibilities they hold over the welfare of their households. However, one can find that in most cases in Zimbabwe women are de facto heads (CSO, 1998), managing the daily welfare of the household as men out-migrate in search of wage labour.

In the case of the effect of duration of absence on migration distance, two major findings emerged. Firstly, short-term out-migrations were significantly more likely to have been oriented towards longer distance destinations than commuters and long-distance migrations. Secondly, long-term out-migrations were more likely to have been oriented towards longer-distance destinations than commuters and short-distance out-migrations. But the latter explanation was more significant and stronger than the former.

These results were logically consistent with the expectation that commuters including shoppers, local visitors, petty traders and school children attending sports would normally migrate to nearby places including other local rural areas, Nyanga District town and the provincial city, Mutare. Precisely as expected, long-term migrants more significantly and strongly migrated for longer distance than both short-term migrants and commuters. Since long-distance migrations are very expensive and take a long time to prepare, therefore, the migrant should also take a longer time at destination searching for wage labour or taking up a formal job. If the longer-distance migrants were women joining their husbands, this meant that such women prolonged their stay in town with their husbands. This is also logical since most families were likely to stay together in town where the husband works in order to minimize the cost of having to sustain two households at the same time, one in town and the other in the rural areas. This also meant that farming in the rural areas would be left to a caretaker or other extended family members.

Among indicators of household wealth, only the parameter for the household's access to non-farm income was significant. Individuals from households with non-farm income, including income from a local formal job, selling crafts, and petty trading were more likely to have migrated for longer distance than individuals from households without non-farm income. This result strongly supported the previous explanation that women migrants could have migrated to join their husbands and live together for a long period. Presumably, incomes from local non-farm jobs were used (or aided) to finance long-distance trips to join husbands.

In the final analysis, individuals from households with off-farm income, including income from hired farm labour in the communal areas and seasonal labour on nearby commercial farms, were less likely to have out-migrated for longer distance than individuals from households without off-farm income. These results were consistent with the effect of movement by these individuals to work on the nearby commercial farms. Thus, this was probably a separate and second group of migrants from Nyamaropa Communal Area. Efforts to work as casual labour should have increased during ESAP given poor households’ desperation for off-farm incomes since crop inputs were no longer affordable for them.

On the other hand, several variables were insignificant, including time period, sex, age, relationship to household head, cattle ownership, and farm incomes. In the case of the main variable of interest, time phase, the study expected a greater likelihood of out-migration to long-distance places during pre-ESAP than during post-ESAP. It could be argued that the frictional effect of distance would be more applicable to the post-ESAP period for three reasons.

Firstly, very high transport costs, which were the consequence of the deregulation of the public transport sector and the devaluation of the Zimbabwe dollar, would limit long-distance migration. The same effect was expected because of the dearth in formal jobs particularly in the capital city, Harare, where people looking for jobs were far numerous beyond the average annual numbers of jobs available in industries and government departments. Finally, the fear of increasing social distance during a period of economic hardships disfavoured long-distance migration. This is because migrants in town were more in need of support from home during the period of economic hardships given that there were high costs of food, accommodation and transport in the major cities, than during pre-ESAP.

Despite these expectations, the results were insignificant, indicating an equal chance of long-distance or short-distance out-migration from Nyamaropa communal area between the time phases. This indicates that ESAP did not directly affect short- and long-distance migration patterns. In other words, movement to Harare by school leavers in search of wage labour continued, for example, because most industries and a few new industrial investments have been concentrated there. In addition, people could still move out to Harare for vocational training and higher education since the spatial distribution of the major colleges and Universities has not effectively changed in favour of rural areas and small growth points.

Furthermore, the study’s failure to separate the effects of the 1992-3 drought from those of ESAP may have contributed to this insignificant result. This is because the drought could have increased long-distance migration to Harare. Kanji’s (1995:45) report on Harare supports this view:

Instead, the dependency ratio, that is the number of dependents per paid worker, increased from 3.2 in 1991 to 3.8 in 1992. This was a result of the influx of dependent relatives from rural areas due to the drought, and from other settlements in Harare due to retrenchments.

The increased movement by women joining their husbands in Harare, often accompanied by children, could also have contributed to the insignificant result. This type of movement was likely to have increased in post-ESAP period due to migrant households’ strategy of cutting costs by have single residence. Furthermore, although the frequency of visits per year by women and children could have declined, it was unlikely that such visits had ceased indefinitely. Instead, visits by women and children who would stay in town for the whole dry season period would be more logical in economic terms than a visit to the rural areas by the migrant who would stay over the weekend only.

The insignificant results for sex, which indicated no differences in the preference for long-distance over short-distance migration between males and females were both surprising and unexpected. The study had predicted that men would migrate for longer distance to urban centres more than women (Mitchell, 1989; Oberai, 1990; Raveinstein, 1885). The logic behind this expectation is that in sub-Saharan Africa large proportions of urban women do not work unlike in Latin America, West Africa, and South-east Asia where according to Oberai (1990) economic motives for female migration are correspondingly important. However, the paper found no difference between males and females in long-distance out-migration particularly to Harare because according to Connel et al. (1976) cited in Oberai (1990) "more women in Africa are joining their husbands in town or independently migrating to cities". This supports the significant results discussed earlier.

The insignificant results for both age and marital status were unexpected since individuals between 16-40 years of age and particularly unmarried men would migrate especially for economic reasons and for long distances. But because recently, more women who are married join their husbands in town and migrate with their children who would be below 15 years of age, this has led to less conspicuous selectivity among migrants according to age and marital status. The same reason explained why there were no differences among the head or spouse, the household's own children, and other relatives in long-distance out-moves mostly to the capital city, Harare. Overall, these insignificant results were due to the fact that the study considered all moves instead of restricting itself to migration for economic reasons where age and sex selectivity are always more conspicuous.

CONCLUSION AND RECOMMENDATIONS

When individual variables were entered in the equation of long-distance migration, only two variables, level of education attained and marital status, were significant. These significant results indicated that married women were more likely to have migrated for longer distance to join their husbands in town and probably stayed over a long period (6 months or more). At the household level, households with incomes from non-farming sources also dominated as long-distance out-migrants. This was because this variable included those with incomes from a formal job and therefore, was automatically linked to the migrant women who migrated to join their migrant husbands.

In a nutshell, the effects of predictor variables at the individual and household levels were related in the following ways. Migrants from Nyamaropa Communal Area, the majority of whom worked in Harare, accumulated wealth in their rural homes in the form of cattle and also invested in farming through their ability to purchase inputs like treated seeds, fertilizers and labour. Hence, when the process of economic reforms started in the late 1980s, these migrants took their families to live with them since it was then expensive to support two households at the same time, one in town and the other in the rural areas. In addition, it was also then expensive for either the husband working in town to constantly visit his family in the rural areas or for the wife and children to visit the migrant in town because of the hike in public transport fares. This explains why women and children were more likely to move for long distance to town, mainly Harare, and then stay there for longer periods (6 months or more).

On the other hand, another group of migrants emerged and this was related to those who engaged in off-farm work including casual labour on large farms and paid labour on other peasant farms. This group was likely to be dominated by poor households, which could not produce enough to eat because of expensive crop inputs. Therefore, they looked for nearby casual jobs since they incurred low transport costs during the process.

This is contrary to findings of distance decay studies, which suggest greater frictional role of distance on the less educated and married individuals. However, while distance decay models primarily focus on labour migration, this study did not, but analysed all out-migrations. Hence, less educated, married women seemed to dominate long-distance internal migration from Nyamaropa Communal Area and most of these were to the capital city, Harare where most of their husbands probably worked and stayed (see Annex 2). The study concludes that the period of economic reforms made it necessary for one member of a couple to move. In most cases it was more economically rational for the wife to join the husband given that she can stay for a longer period whereas the husband would only stay over the weekend or take a short-term leave from work.

The fact that families are nucleating in towns has several policy implications. For individual families, this means that when the husband and breadwinner loses his job in town there is more suffering since farming in the rural areas by women and children used to be a way of maximizing household income for migrant households. Economic security in the form of insurance and effective pension funds should be ensured so that migrant families would be able to sustain their lives in urban areas even when the husband and breadwinner loses his job. Alternatively, decentralization of industries is needed so that some migrants can relocate to urban centres closer to their communal areas. In this case, they can constantly visit their families in the rural areas and continue with rural farming in order to maximize their incomes. Thus, as Waddington (2003) argues, population mobility is an integral part of the development process and must not be ignored in formulating development policies.

REFERENCES

  • Central Statistical Office. 1998. Poverty in Zimbabwe. Harare: CSO.
  • Chakaodza A.M. 1993. Structural Adjustment in Zambia and Zimbabwe: Reconstructive or Destructive? Third World Pub. House (pvt) ltd, Harare
  • Chipika 1998. cited in Kaseke, E. (ed) 1998, Social Security Systems in Rural Zimbabwe, Friedrich Ebert Stiftung, Harare
  • Connel et al., 1976. cited in Oberai, A.S (1990), ‘Migration, Urbanization &
  • Development’, in Training in Population Human Resources & Development Planning, vol.5, ILO Geneva
  • Findley, S. 1994. ‘Does drought increase migration? A study of migration from rural Mali during the 1983-1985 Drought’. International Migration Review, vol. XXVIII No.3: 543-550.
  • Gann, L.H 1963. ‘The Southern Rhodesia Land Apportionment Act, 1930: An Essay in Trusteeship’, National Archives Occasional Paper No. 1, June, 1963.
  • Government of Zimbabwe 1991. Zimbabwe: A Framework for Economic Reform (1991-1995), Zimbabwe Government Printers, Harare
  • Guilmoto, C.Z. 1998. ‘Institutions and Migrations: Short-term Versus Long-term Moves in Rural West Africa’, Population Studies, vol. 52:93-98.
  • Gwaunza, E. 1998. The Impact of Labour Migration on Family Organization in
  • Zimbabwe pp 49-55. In Labour and Migration in Southern Africa, Edited by L. Sachikonye. Harare: SAPES Books.
  • Hugo, G.J. 1982. Circular Migration in Indonesia. Population & Development Review, vol. 8, no.1:59-79.
  • Kadenge, P. et al 1992. ‘Zimbabwe's Structural Adjustment Programme: The First Year Experience’, in Mwanza, A (ed.), Structural Adjustment Programmes in SADC, SAPES Books, Harare
  • Kanji, N. 1995. ‘Gender, Poverty and Economic Adjustment in Harare, Zimbabwe’. Environment and Urbanization, Vol. 7, No. 1:37-55
  • Layard, R. 2003. Lecture 3: What Would Make a Happier Society?
  • http://cep.Ise.ac.uk/events/lectures/layard/RL050303.pdf
  • Madondo, A. 1997. Trees and Spaces as Emotion and Norm Laden Components of Local Ecosystems in Nyamaropa Communal Land, Nyanga District, Zimbabwe. Agriculture and Human Values, Vol. 14: 355-362. Kluwer Academic Publishers
  • Magadlela, D. 2000. Irrigating Lives: Development Intervention and Dynamics of Social Relationships in an Irrigation Project. The Hague: Wageningen
  • Mitchell, J.C. 1989. The Causes of Labour Migration pp 28-53. In Forced Labour and Migration Patterns of Movement Within Africa, Edited by A. Zegeye and S. Ishemo. London: Hans Zell Pub.
  • Oberai, A.S. 1990. Migration, Urbanization & Development. Training in Population Human Resources & Development Planning, vol.5:35-50. Geneva: ILO
  • Ranga, D. 2003. ‘Sub-region Differentials in Migration and Remittances in Zimbabwe Between 1988-90 and 1996-8-98’, in EASSRR Vol. XIX, No. 2, June 2003, Addis Ababa: OSSREA
  • Ravenstein, E.G. 1889. The Laws of Migration. Journal of the Royal Statistical Society, vol. 52, part 2.
  • Standing, G. 1991. ‘Structural Adjustment and Labour Market Policies: Towards Social Adjustment?’, in Standing, G. and V. Tokman (ed.), Towards Social Adjustment: Labour Market Issues in Structural Adjustment. pp. 5-52. ILO, Geneva
  • Stillwell, J. 1991. Spatial Interaction Models and the Propensity to migrate over distance. In Migration Models: Macro and Micro Approaches, Edited by J. Stillwell and P. Congdon. London and New York: Belhaven Press.
  • Tevera, D.S. (1995), ‘Indigenisation of the Zimbabwe Economy & the Emerging Economic & Social-spatial Impacts’, Eastern Africa Social Science Research Review, vol. XII, no.2, OSSREA.
  • Tevera, D. S. 1998. Micro and Small-scale Enterprises in Shamva District within the Context of an Adjusting National Economy pp 253-292. In Economic Policy Reforms and Meso-Scale Rural Market Changes in Zimbabwe: The Case of Shamva District, Edited by L. Masuko. Harare: IDS.
  • The Sunday Mail, May 2 1991, Zimpapers, Harare
  • Waddington, C. (2003), ‘National Policy an Internal Migration’, Paper presented at the Regional Conference on Migration, Development and Pro-Poor Choices in Asia. http://livelihoods.org/hot_topics/docs/Dhaka_CP_12.pdf

Notes

1 Government of Zimbabwe (1991), Zimbabwe: A Framework for Economic Reform (1991-1995), Zimbabwe Government Printers, Harare

2 Regretfully, however, as the author was compiling this thesis, the Mhangura Copper Mine was shut down and authorities cited a large debt and viability problems under the economic recession (The Sunday Mail, 5 November 2000: 1).

Annex 1: Percentage Distribution of Short-distance and Long-distance out- Movers by Characteristics

Variable Movement Status
Short-Distance Long-Distance
Time Phase % %
pre-ESAP (1988-90) 49.5 47.2
post-ESAP (1996-98) 50.5 52.8
Age (complete years)
0-15 46.2 31.0
16-40 31.7 41.9
41+ 22.1 27.1
Sex
Male 43.9 34.8
Female 56.1 65.2
Education Level Attended
No education 26.3 25.1
Primary 52.2 48.1
Secondary & higher 21.5 26.8
Marital Status
Never married 54.9 40.4
Married 40.5 52.5
Disrupted 4.6 7.1
Whether hh owned cattle
Yes 71.4 65.8
No 28.6 34.2
Duration of absence
Commuter 77.1 40.7
Short-term 19.9 47.8
Long-term 3.0 11.5
Relationship to hh head
Head 19.5 18.3
Spouse 23.8 36.6
Own child 53.1 40.7
Other 3.5 4.4
Whether hh had crop income
Yes 81.9 77.6
No 18.1 22.4
Whether hh had non-farm income
Yes 60.4 56.9
No 39.6 43.1
Whether hh had off-farm income
Yes 36.9 29.2
No 63.1 70.8

HH/hh - household
Source: 1998-2000 Survey Results

Annex 2: Migration Distance by Destination (from Nyamaropa Communal Area)

Destination

Migration Distance (%)

Short-Distance (75% of all moves)

Nyanga rural

60.8

Nyanga town

12.1

Other rural in Manicaland

8.0

Mozambique rural

4.9

Mutare city

12.6

Rusape town

1.4

Long-Distance (25% of all moves)

Harare

73.5

Masvingo

0.6

Bulawayo

6.8

Gweru

1.2

Kwekwe

1.5

Other town outside Manicaland

15.3

Other rural outside Manicaland

1.2

Source: 1998-2000 Survey Results

Copyright 2004 - Union for African Population Studies

African Population Studies/Etude de la Population Africaine, Vol. 19, No. 1, April 2004, pp. 165-185

The Migration Effects of the Economic Structural Adjustment Programme on a Rural Community in Zimbabwe

Dick RANGA

Centre for Population Studies, University of Zimbabwe, P. O. Box MP167, Mt. Pleasant, Harare, Zimbabwe

Code Number: ep04009

ABSTRACT

This paper examines factors influencing long-distance migration during a period of economic reforms, from Nyamaropa Communal Area in Nyanga district of Manicaland Province in eastern Zimbabwe, to various intra-country destinations. The economic reforms were implemented in phases and the study is particularly concerned about the effects of the first phase, dubbed the Economic Structural Adjustment Programme (ESAP, 1991-5). Primary data was collected using a household questionnaire between 1998-2000 and captured both pre- and post- ESAP periods. However, the limitation of such data is separating what could have happened without the reforms. This limitation is relevant in the case of Zimbabwe because there was a severe countrywide drought between 1992-3, just after the ESAP started in 1991. Data analysis involved both bivariate and multivariate procedures and results indicated that: higher levels of education, singleness, and having off-farm income were all less associated with long distance migration. This is contrary to findings of distance decay studies, which suggest greater frictional role of distance on the less educated and married individuals, particularly in the case of labour migration. The study, however, did not only focus on labour migration, but all mobility patterns. Two types of migrants emerged: women moving long-distance to join husbands in Harare accompanied by children, and short-distance migrants related to casual work. The latter could not have been the effect of drought but ESAP’s economic hardships.

INTRODUCTION

The International Monetary Fund (IMF) and World Bank economic reforms in Zimbabwe were in two phases, both implemented for five-years periods, namely: the Economic Structural Adjustment Programme (ESAP) between 1991-95 and the Zimbabwe Programme for Economic and Social Transformation (ZIMPREST) between 1996-2000. While the former involved the usual SAP policies of domestic deregulation and liberalization (trade and markets), the latter incorporated social reforms aimed at human resources development, in addition to the usual economic policies. The majority of these policies affected urban more than rural dwellers simply because the former are more linked to the cash economy than the latter. Only agricultural reforms would directly impact on the lives of people in rural areas.

However, the two areas, rural (particularly communal areas) and urban, are closely linked through migrant remittances, such that changes in livelihoods in urban areas gradually impact livelihoods in the rural areas too. Historically, what are called communal areas today were formerly Tribal Trust Lands (TTLs) or ‘reserves’. These were agriculturally barren portions of the country where the majority black Rhodesians (now Zimbabweans) were allocated land for settlement during colonialism through the Land Apportionment Act of 1930 (Ranga, 2003). This Act alienated considerable tracts of land from Africans so that by 1963 only 50,000 square miles were set aside for the use and occupation of 2,630,000 Africans, against 75,000 square miles for some 215,000 Europeans (Gann 1963). Thereafter, the colonialists used mechanisms such as the ‘hut tax’, which had to be paid in cash, to force the blacks to move out of the ‘reserves’and look for wage labour in white-owned farms or firms.

Now that Zimbabwe as well as other sub-Saharan African countries have tasted the prescription provided by the Bretton-Woods institutions in the form of Structural Adjustment Programmes (SAPs), there is need to assess their direct or indirect influences on areas that have received less attention such as the spatial pattern of population mobility. The SAPs do not have specific `prescriptions’to influence the distance travelled by migrants, but during their implementation they unintentionally instigated changes in migration distance patterns. However, what we know from neo-classical economics is that, generally, economists favour geographical mobility since it moves people from places where they are less productive to places where they are more productive (Layard 2003).

There is evidence that ESAP was structured to achieve this general goal. For example, Amendments to the Labour Relations Act were implemented to allow more ‘flexible hiring and firing of labour to improve firms’efficiency and competitiveness’1. In the neoclassical economic sense, this strategy keeps production costs low by reducing the costs of labour and at the same time, moves labour from where it is less productive. Hence, the Social Dimensions of Adjustment Programme (SDA) was designed to temporarily take care of the welfare of this displaced labour while waiting to get into other jobs, formal or informal, where their labour is more productive.

PROBLEM STATEMENT

As mentioned above, some of the ESAP policies indirectly affected mobility patterns and in most cases negatively, as in the case of insecure families due to labour displacement or relocation. Such policies were explicitly related to certain sectors including, labour, transport, foodstuff prices, and agriculture. As expressed in the Government’s policy document, Zimbabwe: Framework for Economic Reform (1991-95), domestic deregulation policies were designed to see that wage labour, basic commodity pricing (including food and transport), and agricultural pricing, were all determined by market forces, instead of the government meddling in such affairs.

The effects of deregulation varied with each sector. Chipika (1998) reported that retrenchment of workers was severe, with 32,440 formal sector jobs lost by December 1995 compared to the original target of 20,000. Cuts in public transport subsidies and decontrolling of these prices saw fewer households in Harare being able to pay for transport to work (Kanji, 1995:43). A number of men and women had begun trekking to work or had arranged lifts, which cost less than the bus service, and this basically affected the lower-paid workers.

Although there are no studies on the effects of these policies on the long-distance rural public transport sector, what happened in urban areas was precisely the case in rural areas. At that time, it was common to see on national television stranded passengers during major public holidays, particularly Christmas, because most urban migrants adjusted their rural visits to once a year. At the same time, public-transport operators continued to hike fares, citing high operation costs due to the devaluation of the Zimbabwe dollar. In the rural areas, the removal of subsidies resulted in the prices of commodities such as seeds and fertilizers rising, dramatically.

The overall effects were massive erosion of farmers' incomes and increasingly poorer and insecure households (separated by long distance and facing risk of break-ups), whose major income sources, farming and migration, had run dry. Households, particularly lower-income migrant ones, had to devise strategies to deal with this critical situation. Among others, possible strategies included, considerations for re-migration for the retrenched, having single residence (temporarily close the rural residence) for those who still worked in urban areas, or seeking transfer to smaller urban areas closer to the migrant’s rural home.

However, some of these strategies posed serious dilemmas for the families involved simply because they were also less feasible due to structural constraints. For example, for those who wished to re-migrate or relocate to nearby smaller towns, they were faced with an economy infested with problems like increased unemployment and intensified de-industrialization (Tevera 1998). This was also a period when most foreign investors would prefer to start their businesses in the capital city, where infrastructure already existed.

The Migration Effects of the Economic Structural Adjustment Programme The Migration Effects of the Economic Structural Adjustment Programme Standing (1991) argues that, as a result of deregulation, forms of labour security around the world have been eroded and conditions have deteriorated. There was strong purpose in the Zimbabwe Government's intervention in the labour market prior to ESAP, as Kadenge et al. (1992:188) argues: The Migration Effects of the Economic Structural Adjustment Programme The Migration Effects of the Economic Structural Adjustment Programme The Migration Effects of the Economic Structural Adjustment Programme The Migration Effects of the Economic Structural Adjustment Programme The Migration Effects of the Economic Structural Adjustment Programme The Migration Effects of the Economic Structural Adjustment Programme The Migration Effects of the Economic Structural Adjustment Programme The Migration Effects of the Economic Structural Adjustment Programme

Study Significance

A study of the migration effects of SAPs is necessary in order to draw lessons that can benefit other countries going through economic reforms, particularly since this area has received little attention. The study would be of more practical use if the results would inform more about how long-distance migrant families responded to the dilemmas stated above. It is however, worth noting that the study does not provide a conclusive causal analysis of the relationship between structural adjustment programmes and long-distance migration. This is because it was not easy to separate the effects of ESAP (1991-5) and others events such as the drought in 1992-3. The study simply places in context of SAPs the factors that influence long-distance migration and by so doing provides a case study of migration effects during SAPs.

Objectives and Hypotheses

The study assessed the effects of individual and household characteristics on the likelihood of long-distance migration during the Economic Structural Adjustment Programme (ESAP, 1991-5) from Nyamaropa Communal Area in eastern Zimbabwe.

The study mainly hypothesized that the likelihood of long-distance migration would be lower during the post-ESAP than the pre-ESAP period. Borrowing from Raveinstein’s ‘laws of migration’and distance decay models, the study also hypothesized that:

    1. The likelihood of long-distance migration would decrease as age of migrant increases.
    2. Males were more likely to migrate over long distance than their female counterparts.
    3. The likelihood of long-distance migration would increase as level of education attended increases.
    4. Married migrants were less likely to travel longer distances than unmarried migrants and those whose marriages were disrupted, that is, divorced, separated or widowed.

Definition of Migration and its Problems

The study focuses on the spatial dimension of migration. Thus, short-distance migration is defined as those moves to places within a radius of 200km from villages of origin in Nyamaropa communal area. With reference to a map of Manicaland Province in Zimbabwe, short-distance moves would take one across Nyanga district, to Rusape town in the west, and to the provincial capital, Mutare, in the southwest direction from Nyamaropa communal area. Long-distance moves, on the other hand, were defined as any other moves beyond the 200km radius and such distance would take migrants to the capital city, Harare, as well as to the second capital, Bulawayo. The selection of these areas was based on a preliminary analysis, which indicated areas within a 200km radius from Nyamaropa as the most common destinations of the majority of migrants from this area who moved for business, shopping, social visits, and/or marriage

However, a note should be made of the problems associated with such a spatial definition of migration. For instance, a major definitional problem cited by Hugo (1982) is that of determining the administrative areas between which moves can be classified as migration. Due to this problem there have been difficulties of comparing migration rates and patterns internationally since the national division of the country into areas is variable so that in some `migration' is measured as movement between large states and some between much smaller geographic units. A second problem originates from the meaning of `distance'. The concept of distance is not a straightforward matter of miles and kilometres, but involves three principal concepts including geographical, economic, and social distance. These two problems are relevant to this study.

Regarding geographical distance, there is a problem of determining the distance over which moves are classified as `migration'. Statisticians have argued that there are particular statistical problems with taking short-distance movements as the criterion for migration. However, the selection of types of areas between which moves are classified as migration might have profound implications for the observed incidence or pattern of migration. The notion of ‘economic distance’, which is also relevant during SAPs, involves costs and availability of communication, information and transport networks. This is separated from the notion of social distance, which includes separation from an accustomed circle of family and neighbours or from particular ethnic group or from other particularistic social groupings to which the mover belongs. Hugo (1982) argued that not all moves involve both types of separation, but movement across national boundaries involves the greatest social distance in the migration process. Although international migrations should have been significant during ESAP, they are beyond the scope of this paper.

LITERATURE REVIEW

Literature on the migration effects of SAPs is both limited and scanty. But, what is plenty are the impacts of SAPs on other aspects of people’s lives, including employment, health, education, and general standard of living. In most cases, these studies are conducted in urban rather than rural areas. Hence, literature discussion is separated into two parts: that related to (a) the effects of SAPs, particularly the effects of those policies that would indirectly influence mobility patterns, and (b) the patterning of long-distance migration according to individual or household characteristics of the migrants or other events such as drought.

Standing (1991) argues that, as a reult of deregulation, forms of labour security around the world have been eroded and conditions have deteriorated. There was strong purpose in the Zimababwe Government's intervention in the labour market prior to ESAP, as Kadenge et al. (1992:188) aruges:

...Government intervention in the labour market has been at two levels, that is, wage determination and regulations designed to provide job security to workers. With regard to the first level, the major objective was to reduce income inequalities inherited from the colonial regime. In this regard, Government introduced minimum wage legislation to improve the living conditions of low wage earners, while at the same time imposing direct control on wage increases depending on levels of income.

The Government's reversal of regulations that were initially aimed at ensuring job security obviously resulted in job losses. Government had estimated that the number of job losses in relation to the private sector was going to be around 20 000 (Government of Zimbabwe, 1991). But, Chipika (1998) reported that retrenchment of workers was severe, with 32,440 formal sector jobs lost by December 1995 compared to the original target of 20,000. Furthermore, several researchers (e.g. Kadenge et al., 1992; Chakaodza, 1993 and Tevera, 1998) all argue that, already there was a high level of unemployment in Zimbabwe before ESAP, but the Government's and the private sector's retrenchments increased the unemployment rate to unprecedented proportions.

By the end of 1995, Government had removed all price controls except on a few basic foodstuffs. According to Kadenge et al. (1992:183), the purpose of having price controls prior to ESAP were three-fold:

...Firstly, they were aimed at protecting low-income households by making the cost of basic foodstuffs affordable. Secondly, because of foreign currency shortages and other production bottle-necks, companies could take advantage of the situation of excess demand over supply and increase prices to earn scarcity rents. Price controls were aimed at curbing this practice. Lastly, the high degree of concentration allowed for monopolistic pricing which is exploitative and would hit low-income households particularly hard.

The implications of the removal of government price controls for the people of Zimbabwe, particularly low-income households, were several. Prices naturally rose as well as inflation. For instance, in May 1991, the Consumer Council of Zimbabwe reported that the average price increase stood at 47% (Sunday Mail, May 12, 1991) and between 1992-3, Chakaodza (1993:65) reported that inflation was close to 50%. According to Kadenge et al. (1992), the increase in prices implied the erosion of real incomes given that there was no equal increase in nominal wages and/or incomes. Chakaodza (1993:65) argued that the removal of price controls increased costs on the working people. This in turn led to social problems like unprecedented levels of crime, begging by `street kids', prostitution, the AIDS epidemic and drug abuse, as well as the impoverishment of significant strata of the urban and rural populations. Tevera (1995) argued that after the removal of price controls, food prices and transport fares rose rapidly, and vulnerable groups in both urban and rural areas were unable to meet basic needs such as food, shelter, education and health. Kanji (1995:39) argues that the ‘increased prices of basic foods in this period was a direct result of the lifting of food subsidies and not the importation of food as a result of drought’.

At the same time, cuts in public transport subsidies and decontrolling of these prices saw fewer households in Harare being able to pay for transport to work. In rural areas most peasant households blamed the soaring bus fares during the economic reforms for their sons’, daughters’or spouses’failure to pay them visits and hence, their lack of financial support, which is associated with visits by the migrants. Usually when they visit home, migrants bring remittances with them, which are mainly in the form of groceries and cash.

Finally, deregulation saw the removal of agricultural producer price controls, marketing monopolies by parastatals, and lifting of subsidies on crop inputs. Before the introduction of ESAP in 1991, agricultural marketing parastatals [e.g. Grain Marketing Board (GMB) and Cotton Marketing Board (CMB)] were sole marketing channels through which producers were obliged by law to deliver their agricultural products. The implication of agricultural price decontrol was quite clear: agricultural incomes improved. But this improvement was not sustained in the long term because the removal of subsidies resulted in the prices of commodities such as seeds and fertilizers rising, dramatically.

Literature on the effects of individual characteristics on long-distance migration suggests that a larger proportion of men than women usually migrate for longer distances to urban centres as well as internationally to work for wages. This indicates the less influence exerted by distance on males than on females. For example, in Southern Africa the majority of migrants from Zimbabwe, Mozambique and Zambia moving to mines and farms in South Africa are men. The tendency by females to migrate to nearby places is a result of the restriction on females' autonomy by a male-dominated society.

However, Oberai (1990) argued that more women in Africa and South Asia are now joining their husbands working in longer-distance towns or are independently migrating to cities. Traditionally, women were expected to be either housewives or peasant farmers, while it was proper for the husbands to go out sometimes for long distances and find work. In addition, at the time of marriage women were instructed by aunties to look for suitors from nearby places and this was designed to avoid the psychic costs associated with longer-distance migrations for marriage. In other words, it was easy for a woman to get married to a husband who spoke the same language and who came from the same cultural background in order to avoid integration and adjustment costs. Such trends are, however, likely to change with major economic reforms such as ESAP because it affects almost all aspects of people’s lives forcing them to use different adaptive strategies.

Gwaunza (1998) analysed the impact of distance on mine workers at Mhangura Copper Mine2 in Mashonaland province, Zimbabwe. She found that the impact of distance from home areas and tribal influence was to an extent alleviated by the spirit of tribal interaction engendered at the mine. In her case study of Mhangura, she found that:

...The mine has attempted to create the organization of workers along ethnic lines. For each ethnic group represented, there is a `chief'. Every new recruit is required to indicate his tribal origins, after which he will be assigned to the appropriate tribal `chief'. Although the `chiefs' are not chiefs in the conventional sense of the word, they are to an extent expected to know, uphold and enforce the general customs and practices of their tribes within their communities. (Gwaunza 1998:52)

Hence, the case study of Mhangura Mine has shown that management has attempted to make the process of integration and adjustment to a workplace distant from home as easy as possible to the migrant workers, while at the same time they could work and earn their wages with peace of mind.

Literature on the migration-distance relationship has also focused on the correlation between migration to nearby places and short-duration, cyclical movements. In Asia, Hugo (1982) found that factors such as the distance between town and village, the costs of traversing it, the availability of work in the home village, and others, all contributed to the frequency with which short-term migrants moved.

Drought, whose effects can be related to other times of hardships such as the period of ESAP, has been found to shift the choice of destinations by migrants in favour of nearby places. This is because long-duration migrations, which are correlated with long-distance movements, usually require fairly sizeable travelling expenses and support while the migrant looks for work. The migrant must have a larger resource base upon which to draw as well as more money with which to finance the journey. In addition, they need more education and job experience to improve their chances in competitive labour markets, and more contacts at the destination that can help them get jobs or who can support them until they can support themselves. Because these concerns have to be planned for, long-distance and long-duration migrations are impractical as spontaneous responses to a drought-induced crop failure (Findley, 1994).

Instead, those who are already migrants will be expected to intensify their remittances, but families may lack the resources to suddenly sponsor a new long-distance migrant and all available funds will be diverted to more urgent food needs. As a result, short-duration labour migration to nearby places should rise during a drought. And this effect of drought on the shift in the choice of destination areas could be the counterfactual when we analyse the migration effects of ESAP.

Conceptual Framework

Different scholars have used several variables to estimate the choice of destinations by migrants. Initially, one of Ravenstein's (1985) laws stated that females are more migratory than males within the kingdom of their birth, but males more frequently venture beyond. Oberai (1990) supported this law when he argued that, in Africa and much of Asia, men predominate in rural-urban migration flows, while women often form the majority of short-distance, rural-rural migrants.

Stillwell (1991:43) used data on mean migration distances for National Health Service (NHS) patients moving between eighteen zones of a system of metropolitan and non-metropolitan areas in the United Kingdom (UK) to illustrate how distance over which migration occurs varied with age. He found that, indeed, the propensity to migrate over distance and the distance over which migration occurred did vary with age. In the early age groups, distance exerted most influence on migrants aged between 10-14 and least influence on those aged 20-24. Thereafter, the frictional effect of distance increased steadily to around retirement age before levelling off.

Stillwell (1991) was correct when he concluded that the manner in which the propensity to migrate over distance changes by age is indicative of the various motivations, which influence individuals at various stages in the life cycles. But, he was silent about the fact that these motivations vary according to the stage of development of the area where the survey is being carried out. For the UK, which Stillwell (1991) was writing about, data showed that longer-distance population redistribution involved a larger proportion of labour migrants changing their jobs as well as moving house, whereas shorter-distance migrants had a higher proportion of individuals who were moving purely for housing and environmental reasons. On the other hand, while some of the motivations, which influence individuals at various stages in the life cycle in Zimbabwe, may be similar to those in the UK, the majority are different between the two countries because they are at different levels of development. For example, longer-distance population movement may still involve a larger proportion of labour migrants like in the UK, but in Zimbabwe most of these migrants would be searching for their first jobs especially after finishing school, instead of changing jobs. Furthermore, instead of a higher proportion of shorter-distance migrants moving purely for housing and environmental reasons (Stillwell 1991), the majority of shorter-term migrants in the Zimbabwean situation are likely to move for different reasons including seasonal labour, seasonal visits, education, etc.

Oberai (1990) hypothesized that the frictional effect of distance is more applicable to the low-income and less educated migrants. In other words, low-income migrants are less positioned to bear the high costs of traversing a longer distance separating village and destination area and therefore, tend to go to nearby places. The same applies to the less educated whose chance of getting employed in longer-distance urban areas is slim and if they do get employed in town, their income would not be enough to outlay the costs of transport and initial cost during job search. This was precisely the case in the period of economic reforms and de-industrialization.

Oberai (1990) also highlighted the importance of the accessibility and availability of transportation and communications networks in the whole migration-distance equation. In addition, Guilmoto (1998) argued that short-term moves are logically oriented towards closer destinations. In his West African study in the Senegal Valley, Guilmoto (1998) found that more than 22% of short-term migrants remained in the same Saint-Louis region, from which they originated, whereas less than 12% of these migrants went for longer distances. Other variables necessary to include in the estimation model are marital status and family responsibility, which are likely to be negatively correlated to longer-distance migration.

METHODS AND MATERIALS

This section describes the source and collection of data and the statistical method used. This article is part of a larger study conducted by the author comparing the effects of the Economic Structural Adjustment Programme (ESAP) on migration between a dry region and a wetter region in Zimbabwe. Nyamaropa communal area was selected in the larger study to represent the wetter region. Nyamaropa communal area is situated in Nyanga, a district that lies along Zimbabwe's eastern border with Mozambique. More specifically, Nyamaropa is about 180km northeast of Manicaland province's capital, Mutare, and also about 70km east of the small town of Nyanga (Magadlela 2000). The entire communal area stretches over several kilometres within a valley, which is surrounded by hills that stretch northward from the Inyangani Mountains in the south.

Climatically, the area is classified under agro-region IIb, which is `an agro-ecological zone marking the limits of the dry-land cropping zone, receiving mean annual rainfall of 600-800 mm' (Madondo, 1997:355), and experiences tropical Savannah characterized by strong seasonality (wet summer and dry winter) with constantly high temperatures. It could be noted that while the area around Nyanga town comprises high altitude and cool temperatures, Nyamaropa Communal Area is situated in a low-lying area and therefore, experiences hotter temperatures and high humidity than Nyanga town. Hence, dry-land farming is feasible here, but added to this advantage Nyamaropa has one of the most successful irrigation schemes in the country. Crops grown in the irrigation scheme include grains, such as maize; vegetables; and cash crops, such as cotton, paprika, tobacco and beans.

The paper draws from data collected by the author between 1998-2000 by means of household questionnaires aimed at capturing household migration during two time phases, 1988-90 (pre-ESAP) and 1996-98 (post-ESAP). This two-set retrospective survey was administered to a sample of 200 households from Ward 12 (Nyamaropa irrigation scheme) and another 200 households from Ward 13 (Nyamubarawanda dry land farming area) in Nyamaropa communal lands within Nyanga district, Zimbabwe.

The selection of the two Wards was purposive as the author expected to find out different spatial patterns in out-migration from the Ward with irrigation and that with dry-land farming. The rationale is that the irrigation scheme was likely to repel longer-distance migration, but at the same time attract short-distance migration, which is related to movements to purchase inputs and sell farm produce. However, systematic selection methods were used in the selection of households in villages within the Wards. In addition, the author supplemented questionnaire data with data from in-depth Interviews with randomly selected household heads, as well as Focus Group Discussions with villagers of different ages and sex. However, the results are not discussed in this paper.

A multivariate model was used for statistical analysis of the data. The multivariate analysis used a simple logistic regression model. This was due to the fact that the dependant variable, migration distance, is measured by two categories: (1) short-distance, and (2) long-distance, and is therefore binary. The logistic regression model is mathematically represented below, but the specific interaction variables and the reasons for adopting them will be discussed with the results.

Y = (bi Xi + ej)

= b0 + b1X1 + b2X2 + b3X3 + b4X4 + …ej

Where:

Y = a dummy equal to 1 if an individual out-migrated for long distance and zero if an individual out-migrated for short distance.

bi = the regression coefficients

Xi = the predictor variables which were collected at the individual, household and community levels, and

ej = the error term.

RESULTS

Data analysis began with descriptive statistics including frequency counts and cross-tabulations of relevant variables (see Annex 1 and 2) and testing for relations using chi-square tests. Annex 1 shows the distribution of short-distance and long-distance out-migrants by characteristics, and Annex 2 displays the spatial distribution of the two types of migration from Nyamaropa Community Area. Table 1 presents the results of a multivariate logistic regression of the relative risk of long-distance migration.

The overall Model Chi-square was highly significant, P < .01. The independent variables correctly predicted about 77.05% of the variation in migration distance. Level of education had a highly significant result. That is, individuals who had attained primary school were less likely to have migrated for longer distance than the uneducated and secondary or higher school leavers. At the same time, individuals who had attained secondary or higher levels of education were less likely to have migrated for long distance than the uneducated and those who had attained primary education.

These results were inconsistent with the expectation that the frictional effect of distance would be more applicable to the less educated migrants. However, this expectation was based on the assumption that most of the migration would be in search of wage labour particularly in the urban formal sector where a higher level of education would be required. But the fact that the results of descriptive statistics (see Annex 1) indicate that most of the long-distance out-movers include children visiting and women joining their husbands in town could have changed the usual nature of the relationship between migration distance and level of education attained, hence the negative results.

One of the parameters of marital status was significant, P < 0.1. More specifically, never married individuals were significantly less likely to have migrated for longer distance, than married individuals and those with disrupted marriage. These results were consistent with the effects of movement by more married women joining their husbands in town, mainly Harare. However, the same pattern would be depicted when both married men and those with disrupted marriage move in search of wage labour in order to support their families back home. The majority of these men could have ended up joining the urban informal sector, which at that time had expanded.

Table 1: Relative Risk of Long-Distance Out-Migration

Variable

Relative Risk of Long-Distance Out-Migration (B*)

Time Phase

Pre-ESAP (1988-90)

1.00

post-ESAP (1996-98)

1.12

Age (complete years)

0-15

1.00

16-40

1.29

41+

1.23

Sex

Male

0.78

Female

1.00

Education Level Attended

No education

1.00

Primary

0.60***

Secondary & higher

0.68*

Marital Status

Never married

0.40*

Married

0.99

Disrupted

1.00

Whether hh owned cattle

Yes

0.88

No

1.00

Duration of absence

Commuter

1.00

Short-term

5.13***

Long-term

8.45***

Relationship to hh head

Head/spouse

1.00

Own child

1.56

Other

1.58

Whether hh had crop income

Yes

1.13

No

1.00

Whether hh had non-farm income

Yes

1.37*

No

1.00

Whether hh had off-farm income

Yes

0.65***

No

1.00

Model Chi-square 198.6***
Overall cases correctly predicted 77%
Sample Size 1351 persons

HH/hh –Household *Significant at 10% ** Significant at 5% *** Significant at 1%
Source: 1998-2000 Survey Results

The paper, on the other hand, had predicted that married men especially heads of households would move to nearby places as they are usually tied down to within their home areas by responsibilities they hold over the welfare of their households. However, one can find that in most cases in Zimbabwe women are de facto heads (CSO, 1998), managing the daily welfare of the household as men out-migrate in search of wage labour.

In the case of the effect of duration of absence on migration distance, two major findings emerged. Firstly, short-term out-migrations were significantly more likely to have been oriented towards longer distance destinations than commuters and long-distance migrations. Secondly, long-term out-migrations were more likely to have been oriented towards longer-distance destinations than commuters and short-distance out-migrations. But the latter explanation was more significant and stronger than the former.

These results were logically consistent with the expectation that commuters including shoppers, local visitors, petty traders and school children attending sports would normally migrate to nearby places including other local rural areas, Nyanga District town and the provincial city, Mutare. Precisely as expected, long-term migrants more significantly and strongly migrated for longer distance than both short-term migrants and commuters. Since long-distance migrations are very expensive and take a long time to prepare, therefore, the migrant should also take a longer time at destination searching for wage labour or taking up a formal job. If the longer-distance migrants were women joining their husbands, this meant that such women prolonged their stay in town with their husbands. This is also logical since most families were likely to stay together in town where the husband works in order to minimize the cost of having to sustain two households at the same time, one in town and the other in the rural areas. This also meant that farming in the rural areas would be left to a caretaker or other extended family members.

Among indicators of household wealth, only the parameter for the household's access to non-farm income was significant. Individuals from households with non-farm income, including income from a local formal job, selling crafts, and petty trading were more likely to have migrated for longer distance than individuals from households without non-farm income. This result strongly supported the previous explanation that women migrants could have migrated to join their husbands and live together for a long period. Presumably, incomes from local non-farm jobs were used (or aided) to finance long-distance trips to join husbands.

In the final analysis, individuals from households with off-farm income, including income from hired farm labour in the communal areas and seasonal labour on nearby commercial farms, were less likely to have out-migrated for longer distance than individuals from households without off-farm income. These results were consistent with the effect of movement by these individuals to work on the nearby commercial farms. Thus, this was probably a separate and second group of migrants from Nyamaropa Communal Area. Efforts to work as casual labour should have increased during ESAP given poor households’ desperation for off-farm incomes since crop inputs were no longer affordable for them.

On the other hand, several variables were insignificant, including time period, sex, age, relationship to household head, cattle ownership, and farm incomes. In the case of the main variable of interest, time phase, the study expected a greater likelihood of out-migration to long-distance places during pre-ESAP than during post-ESAP. It could be argued that the frictional effect of distance would be more applicable to the post-ESAP period for three reasons.

Firstly, very high transport costs, which were the consequence of the deregulation of the public transport sector and the devaluation of the Zimbabwe dollar, would limit long-distance migration. The same effect was expected because of the dearth in formal jobs particularly in the capital city, Harare, where people looking for jobs were far numerous beyond the average annual numbers of jobs available in industries and government departments. Finally, the fear of increasing social distance during a period of economic hardships disfavoured long-distance migration. This is because migrants in town were more in need of support from home during the period of economic hardships given that there were high costs of food, accommodation and transport in the major cities, than during pre-ESAP.

Despite these expectations, the results were insignificant, indicating an equal chance of long-distance or short-distance out-migration from Nyamaropa communal area between the time phases. This indicates that ESAP did not directly affect short- and long-distance migration patterns. In other words, movement to Harare by school leavers in search of wage labour continued, for example, because most industries and a few new industrial investments have been concentrated there. In addition, people could still move out to Harare for vocational training and higher education since the spatial distribution of the major colleges and Universities has not effectively changed in favour of rural areas and small growth points.

Furthermore, the study’s failure to separate the effects of the 1992-3 drought from those of ESAP may have contributed to this insignificant result. This is because the drought could have increased long-distance migration to Harare. Kanji’s (1995:45) report on Harare supports this view:

Instead, the dependency ratio, that is the number of dependents per paid worker, increased from 3.2 in 1991 to 3.8 in 1992. This was a result of the influx of dependent relatives from rural areas due to the drought, and from other settlements in Harare due to retrenchments.

The increased movement by women joining their husbands in Harare, often accompanied by children, could also have contributed to the insignificant result. This type of movement was likely to have increased in post-ESAP period due to migrant households’ strategy of cutting costs by have single residence. Furthermore, although the frequency of visits per year by women and children could have declined, it was unlikely that such visits had ceased indefinitely. Instead, visits by women and children who would stay in town for the whole dry season period would be more logical in economic terms than a visit to the rural areas by the migrant who would stay over the weekend only.

The insignificant results for sex, which indicated no differences in the preference for long-distance over short-distance migration between males and females were both surprising and unexpected. The study had predicted that men would migrate for longer distance to urban centres more than women (Mitchell, 1989; Oberai, 1990; Raveinstein, 1885). The logic behind this expectation is that in sub-Saharan Africa large proportions of urban women do not work unlike in Latin America, West Africa, and South-east Asia where according to Oberai (1990) economic motives for female migration are correspondingly important. However, the paper found no difference between males and females in long-distance out-migration particularly to Harare because according to Connel et al. (1976) cited in Oberai (1990) "more women in Africa are joining their husbands in town or independently migrating to cities". This supports the significant results discussed earlier.

The insignificant results for both age and marital status were unexpected since individuals between 16-40 years of age and particularly unmarried men would migrate especially for economic reasons and for long distances. But because recently, more women who are married join their husbands in town and migrate with their children who would be below 15 years of age, this has led to less conspicuous selectivity among migrants according to age and marital status. The same reason explained why there were no differences among the head or spouse, the household's own children, and other relatives in long-distance out-moves mostly to the capital city, Harare. Overall, these insignificant results were due to the fact that the study considered all moves instead of restricting itself to migration for economic reasons where age and sex selectivity are always more conspicuous.

CONCLUSION AND RECOMMENDATIONS

When individual variables were entered in the equation of long-distance migration, only two variables, level of education attained and marital status, were significant. These significant results indicated that married women were more likely to have migrated for longer distance to join their husbands in town and probably stayed over a long period (6 months or more). At the household level, households with incomes from non-farming sources also dominated as long-distance out-migrants. This was because this variable included those with incomes from a formal job and therefore, was automatically linked to the migrant women who migrated to join their migrant husbands.

In a nutshell, the effects of predictor variables at the individual and household levels were related in the following ways. Migrants from Nyamaropa Communal Area, the majority of whom worked in Harare, accumulated wealth in their rural homes in the form of cattle and also invested in farming through their ability to purchase inputs like treated seeds, fertilizers and labour. Hence, when the process of economic reforms started in the late 1980s, these migrants took their families to live with them since it was then expensive to support two households at the same time, one in town and the other in the rural areas. In addition, it was also then expensive for either the husband working in town to constantly visit his family in the rural areas or for the wife and children to visit the migrant in town because of the hike in public transport fares. This explains why women and children were more likely to move for long distance to town, mainly Harare, and then stay there for longer periods (6 months or more).

On the other hand, another group of migrants emerged and this was related to those who engaged in off-farm work including casual labour on large farms and paid labour on other peasant farms. This group was likely to be dominated by poor households, which could not produce enough to eat because of expensive crop inputs. Therefore, they looked for nearby casual jobs since they incurred low transport costs during the process.

This is contrary to findings of distance decay studies, which suggest greater frictional role of distance on the less educated and married individuals. However, while distance decay models primarily focus on labour migration, this study did not, but analysed all out-migrations. Hence, less educated, married women seemed to dominate long-distance internal migration from Nyamaropa Communal Area and most of these were to the capital city, Harare where most of their husbands probably worked and stayed (see Annex 2). The study concludes that the period of economic reforms made it necessary for one member of a couple to move. In most cases it was more economically rational for the wife to join the husband given that she can stay for a longer period whereas the husband would only stay over the weekend or take a short-term leave from work.

The fact that families are nucleating in towns has several policy implications. For individual families, this means that when the husband and breadwinner loses his job in town there is more suffering since farming in the rural areas by women and children used to be a way of maximizing household income for migrant households. Economic security in the form of insurance and effective pension funds should be ensured so that migrant families would be able to sustain their lives in urban areas even when the husband and breadwinner loses his job. Alternatively, decentralization of industries is needed so that some migrants can relocate to urban centres closer to their communal areas. In this case, they can constantly visit their families in the rural areas and continue with rural farming in order to maximize their incomes. Thus, as Waddington (2003) argues, population mobility is an integral part of the development process and must not be ignored in formulating development policies.

REFERENCES

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  • Development’, in Training in Population Human Resources & Development Planning, vol.5, ILO Geneva
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Notes

1 Government of Zimbabwe (1991), Zimbabwe: A Framework for Economic Reform (1991-1995), Zimbabwe Government Printers, Harare

2 Regretfully, however, as the author was compiling this thesis, the Mhangura Copper Mine was shut down and authorities cited a large debt and viability problems under the economic recession (The Sunday Mail, 5 November 2000: 1).

Annex 1: Percentage Distribution of Short-distance and Long-distance out- Movers by Characteristics

Variable Movement Status
Short-Distance Long-Distance
Time Phase % %
pre-ESAP (1988-90) 49.5 47.2
post-ESAP (1996-98) 50.5 52.8
Age (complete years)
0-15 46.2 31.0
16-40 31.7 41.9
41+ 22.1 27.1
Sex
Male 43.9 34.8
Female 56.1 65.2
Education Level Attended
No education 26.3 25.1
Primary 52.2 48.1
Secondary & higher 21.5 26.8
Marital Status
Never married 54.9 40.4
Married 40.5 52.5
Disrupted 4.6 7.1
Whether hh owned cattle
Yes 71.4 65.8
No 28.6 34.2
Duration of absence
Commuter 77.1 40.7
Short-term 19.9 47.8
Long-term 3.0 11.5
Relationship to hh head
Head 19.5 18.3
Spouse 23.8 36.6
Own child 53.1 40.7
Other 3.5 4.4
Whether hh had crop income
Yes 81.9 77.6
No 18.1 22.4
Whether hh had non-farm income
Yes 60.4 56.9
No 39.6 43.1
Whether hh had off-farm income
Yes 36.9 29.2
No 63.1 70.8

HH/hh - household
Source: 1998-2000 Survey Results

Annex 2: Migration Distance by Destination (from Nyamaropa Communal Area)

Destination

Migration Distance (%)

Short-Distance (75% of all moves)

Nyanga rural

60.8

Nyanga town

12.1

Other rural in Manicaland

8.0

Mozambique rural

4.9

Mutare city

12.6

Rusape town

1.4

Long-Distance (25% of all moves)

Harare

73.5

Masvingo

0.6

Bulawayo

6.8

Gweru

1.2

Kwekwe

1.5

Other town outside Manicaland

15.3

Other rural outside Manicaland

1.2

Source: 1998-2000 Survey Results

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