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GENDER MAINSTREAMING IN POVERTY ERADICATION AND THE MILLENNIUM DEVELOPMENT GOALS >
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ID: 42963Added: 2003-08-28 9:25Modified: 2006-08-31 21:18Refreshed: 2009-01-08 00:36 
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Document(s) 5 of 13
IntroductionThis chapter discusses attempts to integrate gender into macroeconomic analysis. It looks at both: (a) mainstream economists working within a conventional neo-classical framework; and (b) other economists working within political economy frameworks. It starts by exploring some of the theory and then looks at a number of empirical findings. These findings offer some important insights into the relationship between gender and poverty. Gender Bias in Macroeconomic AnalysisNeo-classical economics is mainly concerned with the factors influencing the supply of, and demand for, goods and services by a variety of individual economic agents (producers, consumers, workers, entrepreneurs, etc.). The activities of these agents together give rise to the aggregated forces of supply and demand in an economy. Economists have conventionally viewed markets simply as places where individuals meet to engage in economic transactions, guided by the pursuit of private gain. However, it is increasingly recognised that certain conditions have to be in place for markets to work effectively. These include open entry, competitive rather than monopolistic prices, enforceable contracts, respect for property and the absence of coercion or interference with individual choice. Economic analysis has therefore had to consider not only individual behaviour but also institutional factors. Analysis at the macro-level looks at the economy in terms of total marketed output (domestic, private sector and public sector production plus imports) and expenditure (consumption, private investment, government expenditure plus exports). It is concerned with the broad stocks and flows of goods and services in an economy that influence national income (economic growth) as well the rate of returns to different factors of production (distribution). Its categories of analysis are the measures of these stocks and flows: Gross National Product (GNP), investment, savings, balance of payments, etc. Economic policy instruments try to influence economic behaviour by intervening either: (a) at the broad macro level (e.g. exchange rates, public revenues and expenditures, interest rates, imposing or removing barriers to trade); or (b) at the meso level (e.g. changes in the provision of social services, such as health or transport, or investments in economic infrastructure, such as roads and bridges). It has been extremely difficult to have gender included as a variable in macroeconomic analysis – or even to get macro-economists to acknowledge that its omission might be a problem. This can be seen by looking at some of the models of economic growth contributed by macroeconomic theorists to the field of development studies. Early models of economic growthModels of economic growth in the post-war decades barely recognised the role of the ‘human factor’ in development. Many of them assumed that the rate of growth of the labour force was given by the rate of population growth and hence exogenous to (i.e. outside) the model. The influential Harrod-Domar model, for example, emphasised the attainment of a full-employment, steady growth path. It centred on two variable rates of growth:
In the model itself, a balanced rate of economic growth in the long run in conditions of full-employment depended on the ‘natural’ and ‘warranted’ rates being in line with each other. Since there was no mechanism to link them, only chance would bring this about. There was thus a ‘knife-edge’ balance between cumulative deflation when the warranted rate of growth exceeded the natural and cumulative inflation when it fell short. A great deal of subsequent work on this model explored this instability problem and whether there were adjustment mechanisms in the economy that could help achieve a balance. Neo-classical economists focused on shifts in technology that would reflect labour scarcity or labour surplus in the economy. Neo-Keynesians focused on adjustments through the distribution of income between capital and labour, the former being associated with higher propensity to save than the latter. Variations in the distribution of income when the full employment barrier was reached or when there was growing unemployment would lead to variations in savings and help bring about an adjustment between natural and warranted rates of growth. An important modification to neo-classical models was made by ‘endogenous growth’ theories (see box 2.1). These saw labour as an endogenous variable (i.e. to be explained by the model rather than taken as a given). As will be seen below, they opened up a space for the introduction of gender concerns into theories of growth.
Economic models that looked at developing countries paid more attention to the role of labour. Of these the best known is the two-sector model. It suggested that most developing countries had both: (a) a traditional subsistence sector dominated by family farming, with an ‘unlimited’ supply of unskilled labour; and (b) a modern industrial sector that used reproducible capital and produced for profit. The labour surplus would allow wages to be set initially at subsistence levels rather than being competitively determined through market forces. Reinvestment of profit and constant wages would lead to economic growth. Then, once the surplus was absorbed, competition would set in between the sectors to retain or attract labour. The rise in real wages in the agricultural sector would lead in due course to the emergence of competitive, commercialised agriculture where productivity would be equal to that in industry. The gender bias in macroeconomic analysisThis kind of macroeconomic analysis did not consider the human dimensions of economic growth except at a very general and abstract level. It is therefore not surprising that it had almost no concern with gender. There has been some debate about what this absence of gender concerns means in conceptual and practical terms. Some writers made a distinction between policy ‘intent’ and policy ‘impact’. They saw macroeconomic models as gender-neutral in themselves, and suggested that the policies led to gender-biased outcomes because they were implemented in a world of gender inequality. However, Elson argued that the gender-neutrality of macroeconomic analysis was an illusion. It was not only the impact of policies but also the view of the economy on which they were based that was gender-biased. Human resources were treated as ‘non-produced factors of production’ like natural resources. The implication was that they could be transferred between activities without cost in the same way that land could be used for growing different crops at different times. Yet this is clearly not the case. Alongside the stream of activities that are labelled ‘production’ by economists, there is a parallel stream of activities that constitute ‘reproduction’ (see box 2.2).
Reproductive work has typically been excluded from economic analysis. There is a tendency to view it as a ‘natural’ aspect of women’s roles and as not being ‘work’ because it is unpaid. By using male economic activity as its standpoint, economic analysis has become skewed and failed to appreciate what is distinctive about women’s work patterns. It has thus had an ‘iceberg’ view of the economy, seeing only the tip of what actually goes on by way of productive work. The activities that entered the System of National Accounts (SNA) and help to calculate the GNP are only those that represent market transactions (see Fig. 2.1). Strategies for economic growth aimed to increase the volume and value of marketed activities in an economy, with different strategies prioritising different sectors. While early growth strategies focused on the internationally ‘traded’ sector, Figure 2.1: The ‘Iceberg’ View of the Economy
it was largely to produce goods domestically that would reduce their reliance on imports. Recent liberalisation policies have also been concerned with the traded sector, but the emphasis has shifted to the production of goods for export. Regardless of their specific focus, however, both sets of strategies focus on market-oriented activity at the expense of non-market work. Beyond the visible economy, however, there is a less visible, informal economy. Here goods and services are still marketed but go undocumented by official statistics. This is the informal economy. Beyond that is the subsistence economy, where goods and services are produced for own consumption. All these activities, in turn, rest on the unpaid work of reproduction and care in the household that ensures the production and productivity of the labour power that keeps the entire economy working. Although the 1993 SNA was revised to assign a market value to some subsistence activities, where goods were produced and consumed in the household, the bias against this unpaid work remains. Yet it is critical to the reproduction, care and maintenance of labour as well as to the accumulation of human capital. These are both seen as increasingly important in the ‘new growth theories’ as well as in current policy agendas. The relative size of these sub-economies varies considerably across the world. In general, however, the visible economy is smaller and the less visible economy larger, the poorer the country and, within poor countries, the poorer the household. Production and reproduction in poor countries are far more ‘socially embedded’ in family, kinship and community than has been recognised by conventional economic analysis. The gender dimensions of this can be seen by comparing the gender distribution of labour between SNA and non-SNA activities in different parts of the world (see box 2.3).
Activities outside the formal economy are often overlooked in official data-gathering exercises because they tend to be irregular, part-time, subsistence-oriented or else carried out as unpaid family labour. By extension, data on women’s labour force participation are most likely to be incomplete, unreliable and underestimates. This is because: (a) more economically active women are likely to be found in the informal economy and in subsistence production; and (b) many more are likely to be classified as unpaid family labour than paid workers. To overcome this problem, the International Labour Organization (ILO) has adopted two definitions of economic activity: (a) a conventional one that includes only activities done for pay or profit; and (b) an ‘extended’ one that also includes productive work done for own consumption. The difference made by these different definitions can be illustrated by a number of examples (see box 2.4). Estimates of female labour force participation based on the first definition provide information on women’s contributions in the ‘visible’ economy. Estimates based on the second definition give a more accurate idea of the extent of their productive contribution across the economy. However, neither provides information on women’s contribution to the care and maintenance of the family, and hence of the labour efforts that underpin survival, subsistence and accumulation. In addition, the continued tendency to record only primary activity often leads to women being classified as ‘housewives’ despite the variety of different ways in which they contribute economically. To make macroeconomic analysis more gender-aware, therefore, it is necessary to:
Women in Mali collect firewood for cooking
Making models less gender-blindA major source of gender blindness in early models of economic growth was their lack of interest in how the labour supply is produced (and hence in the reproductive sector). More attention to this, however, makes it clear that the family is the key institution in the reproductive economy. It also becomes apparent that influences other than population growth can contribute to, or reduce, the effectiveness and availability of labour. A wide range of labour-related variables can then be seen to play a role in economic growth, including care, fertility, health, nutrition and education. All of these have gender implications. In fact, there is long-standing evidence that rates of population are not ‘given’, as suggested by Malthusian theories. Instead, they respond to levels of income, both in society as a whole and in family-based households where reproductive decisions are made. There is emerging evidence that the costs and incentives associated with bearing and caring for children are unevenly distributed across gender and generation due to the way households are organised. Women and men may have different stakes in both the quantity and ‘quality’ of children they have. The ‘quality’ of children refers to the resource investments per child. This is generally taken by economists to refer to education, but it could equally refer to health, nutrition and even time investments. Economists suggest that there is a trade-off between quantity and quality since both more children and higher quality children cost more. The ‘quantity-quality trade-off’ is one route by which economies move from reliance on unlimited supplies of ‘basic labour’ to relying on a more skilled, healthy and educated labour force. When ‘endogenous’ growth theories showed that the labour supply could be improved through investments in human capital, it became possible to see labour itself as something that is ‘produced’ and that thus requires prior commitments of other labour and goods. This provides another promising opening for integrating gender perspectives in macroeconomic theory. In particular, if women and men have different attitudes to investing in their children, then the gender distribution of income should be recognised as a significant determinant of economic growth. A re-interpretation of the two-sector model from the perspective of the reproductive economy would also enrich macroeconomic understanding of the limits to growth. This would mean considering women’s actual activities instead of treating them as part of the pool of ‘surplus labour’ in the traditional sector. Efforts to improve the productivity of labour in the unpaid ‘care’ economy would have important implications for the growth process – and for women themselves. Gender and micro-economic responsesOther studies that show the relevance of gender to macroeconomic analysis started by looking at micro-economic responses. Much of this analysis focused on the economic recession and structural adjustment policies (SAPs) of the 1980s. The ‘gender-efficiency’ approach looked at how gender inequalities limited effective adjustment through market liberalisation, while ‘the vulnerable group’ approach examined the costs of adjustment to women. However, many studies went beyond specific policy initiatives to make broader generalisations about the economy. Collier, for example, argued that in order to understand the economic environment in which SAPs were to be implemented – and hence their likely impact – it was necessary to understand that men and women were located in different sectors and faced different incentives and constraints. He identified four different factors that might account for the differences:
Other writers have pointed to gender differences in the ability to cope with the changing costs of reproduction (e.g. the cut-backs in public expenditure associated with adjustment) and to respond to changing incentives for production. Such differences reflect constraints caused by gender discrimination, the multiple demands on women’s time, etc. Collier suggested that it was necessary to disaggregate market and non-market sectors, capital and consumption goods, tradable and non-tradable goods, and protected and non-protected industries. In order to understand the constraints that women were likely to face, he also suggested disaggregation by institutional location (waged work, enterprise work, home-based work, etc.) and by nature of the contract (waged labour; family-based work, etc.). Palmer, looking at sub-Saharan Africa, suggested that relations in the household should be at the centre of macroeconomic policy. This was where responses to market signals took place that determined rates of economic growth in areas of smallholder farming. Gender inequalities: (a) in the household meant that market prices failed to assign the correct value to labour; and (b) in market and state provision led to resources in the economy not necessarily going to those who could make the best use of them. These gender inequalities are found in:
Institutions and actors in a gendered economyElson has integrated the insights from these various theories into her analysis of what she calls the ‘gendered economy’. She argues that economies are organised through institutions that determine what is ‘appropriate’ male and female behaviour. These institutions include not only family and kinship structures but also private firms and the state. They are all governed by social relationships that structure the way activities, resources, power and authority are divided between women and men. Thus although economic institutions may be seen as gender-neutral, they are not. Whether economic analysis is conducted at the macro-, meso- or micro-level, it therefore needs to ask questions about the gender division of labour, resources, power and decision-making: 1. Macro-level analysis involves examining the gender division of the labour force between the different productive sectors (agriculture, industry and services) and in the unpaid reproductive sector. In principle, national accounts can be produced that give monetary value to activities in the reproductive economy. UNDP, for example, has estimated that women’s ‘invisible’ non-SNA output amounts to around US$11,000 billion a year worldwide. This is equivalent to an extra 48 per cent of the world’s GDP. 2. Meso-level analysis looks at the institutions – firms, community-based organisations, local government offices, etc. – that help structure the distribution of resources and activities at micro-level. It involves examining gender inequalities in public provision as well as gender biases in the rules of operation of different markets. It also explores the structure of decision-making at this level – for example, in different ministries and in corporations and financial institutions. For policy purposes, Elson draws attention in particular to the activities of the state in the provision of physical and social infrastructure and to the operation of labour, commodity and other markets. 3. Micro-level analysis explores in greater detail the gender division of labour, resources, responsibility and decision-making in different sectors in terms of paid and unpaid work. It also examines the structure of decision-making, particularly in the household. Such analysis is central to understanding: (a) how macroeconomic forces, filtered through the various institutions of society, impact on, and are responded to by, individual women and men in households, firms and other organisations; and (b) how their responses in turn feed into the wider economy. Empirical FindingsAlong with these various theoretical attempts to integrate gender into macroeconomic analysis, a number of studies have explored the empirical links between gender and the macro-economy. This section looks at two approaches to this research. The impact of macro-level policyThe imposition of SAPs gave rise to a large body of research on its gender implications, and those of economic recession, at the micro-level and how these affected macro-level outcomes. Some studies used small-scale, often qualitative data and documented a ‘scissors-effect’ on women’s time:
The long hours that women – particularly poorer women – worked in and outside the home was at the expense either of their own sleep, leisure and, in the long-run, health or their daughters’ education or leisure. Women’s time emerged as a crucial variable of adjustment, as it was allocated to numerous different responsibilities in the home, market and community. At the same time, preconceptions about the primacy of the male breadwinner led in several countries to women being excluded from social fund programmes put in place to protect the poor in the course of structural adjustment (e.g. Honduras, Mexico and Nicaragua). This was because it was assumed that a reduction of men’s poverty would automatically help women. Other studies used large-scale data to look at the micro-level impacts of macro-level change. One example is research on the negative supply response to market liberalisation in Zambian agriculture (see box 2.5).
Gender and ‘computable general equilibrium’ (CGE) modelsStudies exploring micro-level responses to macroeconomic change are necessarily ‘partial’ in their analysis since they look at particular sub-sets of the population or particular sectors of the economy. They cannot capture how SAPs – or any other form of macroeconomic policy – affect the economy as a whole. Recent attempts to incorporate gender-related variables into computable general equilibrium (CGE) models offer a promising way around this problem. CGE models are simulation models. Their major advantage lies in the way they can track how changes in one sector of the economy affect other sectors. For example, partial forms of analysis have concentrated on women’s increasing share of employment in a number of countries as a result of the switch to export-oriented manufacturing. However, they have largely ignored the simultaneous loss of employment opportunities due to industries having to compete with increasing imports. CGE analysis can show how macroeconomic changes affect women and men in different sectors of the economy and reveal whether the net overall effect is beneficial, adverse or biased. However, such studies are still few and far between because the data requirements of these models are extremely demanding. A CGE model was used to simulate the gendered effects of changes in trade policies and capital flows in Bangladesh (see box 2.6). It tracks how the effects in specific sectors affect the rest of the market economy. Unusually for CGE models, it also considers how these influence, and are influenced by, behaviour in the unpaid household economy where women are the main workers. Examining interactions both among different sectors of the market economy and between market and non-market spheres makes it possible to understand or predict the effects of changes in policies or other economic circumstances on women.
Gender Equality and Economic Growth: Competing HypothesesA final set of studies, which take a macro-level approach to gender analysis, are based on cross-country and, in some cases, time series comparisons. Their findings have been somewhat varied and often conflicting. Some suggest a positive relationship between gender inequality and economic growth. Seguino, for example, found that gender inequality in wages led to higher levels of economic growth while another study found that high levels of gender inequality in secondary education had a similar effect. On the other hand, Dollar and Gatti found that: (a) gender equality in education and legal rights led to an increase in per capita economic growth; and (b) increases in per capita GNP led to increases in equality for women. Similarly, a study found that gender inequalities had a significant negative impact on economic growth (see box 2.7).
There are various reasons for these apparently contradictory findings. Firstly, there is a differential use of cross-sectional versus time-series data and different time periods. Country-based cross-sectionals tend to average out important country level differences and may lead to false ‘similarities’ between different countries. Secondly, the studies use somewhat different measures of gender inequality. For example, most focus on gender equalities in education while Dollar and Gatti also look at life expectancy and ‘rules and conventions’ relating to gender equality. Seguino, on the other hand, focuses on wage inequality. There is also a difference in country coverage. Dollar and Gatti focus on rich developed countries and poor developing countries while Seguino focuses on middle-income, semi-industrialised countries with a high reliance on export-led growth. Bearing these caveats in mind, a more detailed account is given below of Dollar and Gatti, who suggest a (qualified) synergy, and of Seguino as an example of a study that suggests a trade-off between gender equality and economic growth. a. The ‘positive synergy’ hypothesisThe study by Dollar and Gatti is one of the few of its kind that explores both the effects of gender inequality on economic growth and, conversely, the effects of economic growth on gender inequality. It also includes a measure of gender equality of rights and looks at social as well as economic variables. It found that:
A second set of findings found that female educational attainment – mainly measured by secondary education – had a positive effect on economic growth. The effects of both male and female education on per capita income were low for less developed countries where female secondary attainment covered less than 10 per cent of the population. Once countries had achieved a certain level of female education, however, an increase of 1 per cent in the share of women with secondary school education implied a 0.3 per cent increase in per capita income. The authors suggest that the absence of a relationship between gender equality in education and economic growth in poor, primarily agrarian economies is due to the limited returns that female secondary education brings. There is little reason to invest in it if men have preferred access to types of employment for which secondary education is a qualification. Certain aspects of the study will be returned to in the course of the discussion in the rest of this book: 1. Gender equality has a positive effect on per capita economic growth once a certain stage of development has been reached. Thus the growth-based rationale for reducing the gender gap in education in poorer countries is in terms of long-run rather than immediate returns. 2. Regional as well as religious differences are important sources of variation in the relationships between gender equality and economic growth. 3. While the focus on education as a measure of inequality reflects the increasing importance given to ‘human capital’ in the international development agenda, ‘capital’ can also include material and financial resources and social relationships and networks. Gender inequalities in access to credit, land, wages, capital equipment and trade networks may be more relevant for economic growth in poorer countries than inequalities in education or even formal rights. 4. It is crucial to distinguish between intrinsic and instrumental arguments for policies relating to gender inequality (see box 2.8).
b. The trade-off hypothesisSeguino’s study focused on the relationship between gender inequality and economic growth in the context of export-
Women on a cosmetic industry assembly line in Seoul, Republic of Korea oriented industrialisation. It looked at the relationship between economic growth and gender inequality in wages. Her sample was drawn from lower and middle-income countries (as defined by the 1995 World Development Report). The findings from the cross-country analysis suggested that, along with levels of human capital and investment, inequality in male and female wages was positively associated with economic growth. A 10-point increase in the gap between male and female returns per year of secondary education was seen to raise GDP growth by .10 per cent. Or to put it another way, 4 percentage points of the gap between the rate of GDP growth in the Republic of Korea (9.2%) and Costa Rica (3.9%) between 1985 and 1989 could be explained by the gender wage gap. The results from the time-varying country specific analysis confirm the significance of investment as well as human capital, but suggest that female educational attainment has a more significant effect than male. The wage gap variables remain significant. Gender disparities in wages were found to increase levels of investment. The study concludes that gender inequality in returns to labour have led to higher rates of growth in countries that have relied on export-oriented industrialisation. Seguino notes that the gender disparities in earnings are only partly related to a country’s GNP. Other factors that play a role include policy regimes as well as the ‘gender regimes’ prevailing in different countries. It is striking that of the Asian countries for which she provides data, three of the four fast-growing ‘miracle’ economies, all East Asian, report the largest gender disparities in earnings (Republic of Korea, Singapore and Taiwan). However, it also suggests that economic growth is likely to be higher in this set of countries if investments in female education co-exist with greater gender disparities in wages. Overall, Dollar and Gatti’s findings provide support for gender equality on ‘efficiency’ grounds and for greater economic growth on equity grounds. Seguino’s findings suggest that there may be a trade-off between gender equality and economic growth due to the intensified competition unleashed by globalisation. However, the findings clearly need to be explored further through more detailed analysis at the country level. ConclusionThis chapter has touched on some theoretical and empirical attempts to explore the relevance of gender to macroeconomic analysis and policy. A number of the studies have drawn attention to ‘institutions’ as a concept for understanding gender inequality. Certain recurring themes include:
Most of these studies give a central place to the household and family in understanding gender inequality. However, while many note discriminatory provisions in the legal system and state provision, they vary in the degree of attention paid to discrimination in the market place. Orthodox economists, particularly neo-liberals, tend to see market forces as impersonal aggregations of numerous individual activities. At the other end of the spectrum, feminist political economists insist that markets be recognised as social institutions in which social networks and norms have as important a role to play as economic agency and incentives. An institutional focus suggests a very different approach to the analysis of gender inequality than an individualistic one. This can be illustrated by comparing the explanations that the authors of the two studies discussed in the last section give for their findings on gender inequality. Dollar and Gatti interpret the fact that religion features as statistically significant in explaining variations in gender inequality across countries as showing the importance of different ‘cultural preferences’. They conclude that “those who control resources in the society have a preference for gender inequality that they are willing to pay for”. However, this does not take account of either the extent to which individuals who do not share these ‘cultural preferences’ can challenge them or of the division between those who have the power to express and enforce their preferences socially and those who pay the price. Seguino, on the other hand, concludes that the systemic nature of gender inequalities reflect how institutions are structured in different countries. She suggests that gender disparity in wages is likely to have more positive effects on growth in countries with patriarchal gender systems because their institutions “reinforce the internalisation of social norms that favour men, reducing political resistance and therefore the costliness of gender inequality”. It is clear from the studies in this chapter that gender inequality is relevant in a range of contexts and that it varies across them. These variations reflect a number of different factors, including strategies for achieving growth, levels of per capita GNP, various forms of public policy (particularly those directly related to gender equality) and investments in human capital. In addition, the analysis suggests that institutions – and more specifically their patriarchal construction – are a particularly important factor. This is explored in the next chapter.
Document(s) 5 of 13
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