Pro-gender policies and the empowerment of women in the DRC

Abstract

Purpose

The purpose of this study was to show how pro-gender public policies in the agricultural sectors can contribute to the reduction of gender inequalities in the labour market and the diversification of the Congolese economy.

Design/methodology/approach

Computable general equilibrium model that has been adapted to the Congolese economy from the Democratic Republic of the Congo (DRC)'s SAM.

Findings

The results reveal that policies of increasing women's land allocation and government cash transfers to rural female households contribute to the reduction of inequalities in the labour market. However, only the policy of increasing women’s land allocation improves economic diversification.

Research limitations/implications

The implementation of the policy of government cash transfers to rural women's households comes at a cost to the government. Future studies to look at the most effective mode of financing for this policy. Moreover, the policy of increasing women's land allocation is feasible in the DRC as there is a lot of unused arable land available.

Social implications

In Pillar 1 of the National Strategic Development Plan (PNSD) on Economic Diversification and Transformation, the policy of increasing land allocation to women could be added to the objectives related to strengthening the contribution of agriculture to economic growth and employment creation. In Pillar 3 of the PNSD on Social Development and Human Resource Development, the policy of increasing land allocation to women as well as the policy of increasing government transfers to female rural households could be added to the objectives related to the promotion of employment of youth, women and vulnerable groups.

Originality/value

To the best of the authors’ knowledge, this is the first study of its kind for the DRC, which highlights the impact of pro-gender policies on women's employment, particularly in the agricultural sectors and in the diversification of the Congolese economy. This study contributes to policy orientation in DRC. The two policies (increasing land allocation to women and cash transfers to rural women) analysed in this study were chosen in light of the DRC's National Strategic Plan, the first phase of which focuses on promoting employment for vulnerable groups and economic diversification through the development of agricultural sectors.

Citation

Joshi, C.L., Maisonnave, H., Baroki, R.L. and Mariam, A.B. (2024), "Pro-gender policies and the empowerment of women in the DRC", Journal of Agribusiness in Developing and Emerging Economies, Vol. 14 No. 1, pp. 44-59. https://doi.org/10.1108/JADEE-01-2022-0016

1. Introduction

Gender inequality is increasingly costly. Further progress on gender equality around the world could add an additional $12 trillion to global growth, and closing the gender gap in the workplace would not only be more equitable in the broader sense but could also double women's contribution to global GDP growth between the years 2014 and 2025 (McKinsey Global Institute, 2015). The United Nations Development Program reveals that the estimated annual cost of gender inequality in sub-Saharan Africa in 2014 was US$105bn or roughly 6% of the regional GDP. The average annual loss was estimated at $95bn over the 2010–2014 period (UNDP-United Nations Development Program, 2016).

Gender discrimination in social institutions as well as the low participation rate of women in the labour market have negative impacts on economic growth and per capita income (World Bank, 2001; Klasen and Lemanna, 2009; Bandara, 2015; Teignier and Cuberes, 2014; Ferrant and Kolev, 2016). Furthermore, the impact of income on household socio-economic aspects is 20 times greater if it is in the hands of a woman rather than in the hands of a man (Bradshaw et al., 2013). For these reasons, the United Nations General Assembly has made gender equality and the empowerment of women and girls, one of the Sustainable Development Goals (United Nations, 2015). Achieving this target is considered to have the potential to accelerate the implementation of the UN 2030 agenda given its interconnection with the other goals (UNDP-United Nations Development Program, 2018). Some progress is cited on some aspects of gender inequality around the world, but a considerable gap remains regarding women's access to employment opportunities (Seguino, 2016; Klasen, 2017).

Despite the signing of various international agreements on gender equality by the Congolese government (Ministry of Gender, Children and Family, 2015), the DRC is among the 10 most unequal countries in the world in terms of gender equality (Human Development Report, 2012, as cited in Seguino and Were, 2014). Despite a slight improvement in terms of gender discrimination in social institutions reported by the OECD's Social Institutions and Gender Index (SIGI), which stood at 0.467 in 2014 and 0.394 in 2019, the DRC is listed as one of the countries in Africa marked by high levels of gender inequality, as reported in Africa's Gender Inequality Index, drawn up by the United Nations Economic Commission for Africa (UNECA, 2017, p. 10).

These inequalities are also visible in the Congolese labour market, where women are still under-represented, with an activity rate of 63.7% compared to 71.5% for men and an employment rate of 58.9% compared to 63.4% for men and an unemployment rate of 19.6% compared to 15.2% for men (INS, 2014). In terms of income, women are paid much less, with an average monthly salary equivalent to half that of their male counterparts, irrespective of where they live (INS, 2014). In Kinshasa, the average monthly wage is 140,937 CDF for men, compared to 75,506 CDF for women, and 95,206 CDF for men in other urban centres compared to 45,702 CDF for women. In rural areas, the average monthly wage is 39,371 CDF for men and 20,000 CDF for women (INS, 2014).

Gender inequalities in employment lead to poverty among women and children (World Bank, 2018). The poverty rate in the DRC is thus more pronounced in rural areas, where most of the female labour force is concentrated and mainly employed in the agricultural sector which employs 78% of the female labour force compared to 62% of the male labour force (ILO, 2014). The overall poverty rate of households is 56.1% in rural areas, compared to 50.8% in urban ones, with a rate of 49.1% for rural female households compared to 48.5% for urban female households and with a poverty rate of 57.1% for rural male households compared to 51.5% for urban male households.

In addition to these gender inequalities, is the fragility of the Congolese economy, which is highly dependent on the mining sector. Indeed, this sector contributes to approximately 20% of GDP and 36% of the economic growth achieved between the years 2010 and 2015, as well as contributing to more than 90% of total exports (Banque centrale du Congo, 2017; ECA, 2017, 2018). It is also the sector that provides the largest portion of wages (29.4% of total wages). The decline in world prices always has negative repercussions on the national economy, thus contributing to the further worsening of gender inequalities in the labour market.

Faced with gender inequalities in the labour market and the dependence of its economy on fluctuations in the prices of natural resources, the Congolese state has become aware of the need to implement a policy of economic diversification while at the same time promoting female employment. The government has thus set priority objectives for job creation, poverty reduction and economic diversification in the agricultural sector, which has a high growth potential (UNDP-United Nations Development Program, 2015).

Furthermore, the gender issue should be included within the various government plans and programmes in order to ensure that the targeted economic development benefits both men and women in an equitable and sustainable way (UNDP-United Nations Development Program, 2016). This is all the more important since gender inequalities in terms of access to employment negatively impact economic growth, especially in developing countries (Seguino, 2017; Seguino and Were, 2014; Klasen, 2002) and economic development based on the mining sector alone, will not have any positive impact on reducing gender inequalities (Klasen, 2017). Hence the need for policies focused on promoting livelihood and employment strategies for women (Seguino and Grown, 2006; Seguino, 2016).

Among the suggested public policies to address gender inequalities and promote female employment is access to social infrastructures as well as the promotion of pro-gender public policies supporting female labour-intensive sectors (Klasen, 2019). Policies to provide women with productive assets are also recommended. Johnson et al. (2016), Mishra and Sam (2016), Anderson and Eswaran (2008) and Rosetti and Kakande (2010) highlight the positive impact of a policy that involves allocating more land to women on female production and employment.

Furthermore in the DRC, a key barrier to agricultural production is access to inputs and funding (World Bank, 2018). These constraints are even more acute for women, who are victims of socio-cultural obstacles that prevent them from accessing land as well as financial capital and from investing in assets that could improve their productivity and, therefore, their income on the labour market (World Bank, 2018). Hence the choice of a policy to increase the amount of land allocated to women, especially since the DRC has a large amount of unallocated arable land and Congolese law stipulates that the soil and subsoil belong to the state. Dorward et al. (2014) show that policies aimed at strengthening the ability of rural farmers, the majority of whom are women, to acquire inputs and access funding can improve their productivity and enhance their chances of participating in commercial agriculture. In this way, a policy of cash transfers would help reduce the economic vulnerability of rural female farmers. It would also encourage work and ensure economic security (Standing, 2007) and economic growth (Barrientos, 2008). The choice to analyse these two policies is justified by the fact that the DRC's National Strategic Development Plan (PNSD) gives priority to the agricultural sectors, being the main sectors of activity for Congolese women, as the main diversification of the Congolese economy. Consequently, targeted policies in these sectors are needed to support rural/agricultural women, reduce gender inequalities and increase the share of the agricultural sectors in GDP. This study is thus a contribution to the literature but also to the orientation of policies in the DRC through the analysis of the effectiveness of these two policies on both gender inequality and economic diversification.

The objective of this study is to analyse how pro-gender public policies in the agricultural sectors may contribute to the reduction of gender inequalities in the labour market and to the diversification of the Congolese economy, which are the main priorities of the DRC government. Thus, on the one hand, we will assess the effects of increasing the amount of land allocated to women, and on the other hand, the effects of cash transfers to rural female households.

In order to assess the impact of these two pro-gender public policies on the Congolese economy, we use a computable general equilibrium model. This type of tool is particularly suitable as it allows for the effects of feedback from the different sectors within the economy and for the gender dimension to be taken into account (Were and Kiringai, 2003; Cockburn et al., 2007). In addition to the impacts of these two policies on employment and income redistribution, we are interested in whether a pro-gender policy can also contribute to the diversification of the economy, which is another major economic objective of the DRC. Indeed, by targeting pro-gender public policies in the agricultural sectors, the DRC would be able to make progress towards achieving MDG number 5 on gender equality and the empowerment of women and girls, but also in building a more robust economy that is less dependent on natural resources.

The rest of the paper is organised as follows. Section 2 deals with the literature review. Sections 3 and 4 present the methodology and results of the study. Section 5 focuses on the conclusion and policy implications.

2. Literature review

The study of the impacts of pro-gender public policies on women's employment is covered by a variety of papers. The work on this subject has often been confined to female-intensive sectors, particularly the agricultural sector.

Using estimates applied to rural Bangladeshi data, Anderson and Eswaran find that labour income from female-owned land has a greater effect on the empowerment of women than rental income from female-owned land. Furthermore, the study reveals that the employability of the woman outside her husband's farm contributes significantly to her autonomy (Anderson and Eswaran, 2008). Johnson et al. (2016) point out that the ownership of assets is important in the reduction of poverty, and women's ownership of assets is linked to positive development outcomes at both the household and individual levels. Mishra and Sam (2016) highlight that female land ownership in Nepal enhances their empowerment. This is reflected in the creation of employment opportunities for women and the redirection of their resources towards marginal opportunities, including increased investment in human (household) capital. Rosetti and Kakande (2010) simulate a 5% annual increase in female land ownership in Uganda and find a positive impact on agricultural output growth (approximately by 0.3% per year), on the overall rate of economic growth, and particularly on the employability of women in the agricultural sector.

Meinzen-Dick et al. (2019) point out that rural households are dependent on a wide range of natural resource assets as a means of subsistence and that land is the most valuable asset in most rural household portfolios. The authors draw on an extensive body of literature that makes the link between women's land rights and poverty reduction as well as improved welfare and incomes of female households in rural areas (Quisumbing and Kumar, 2014; Deininger et al., 2008; Dillon and Voena, 2017). The authors also review the vast body of literature that exists regarding the relationship between land security, livelihoods and poverty (Prosterman et al., 2009). They show that there is a correlation between the ownership and control of assets held by women and the improvement of socio-economic indicators for themselves and their families (Quisumbing and Maluccio, 2003; Doss, 2006).

In addition to the studies assessing the impact of increasing the production factors held by women, other studies focus on the impact of cash transfer policies on improving women's employment opportunities.

In their 2017 study, Hagen-Zanker et al. (2017) show different ways in which cash transfers can impact women and girls compared to men. Among their four conclusions, they point out that cash transfers can be an effective policy instrument to enhance the well-being of women and girls; and that the productive impacts of cash transfers can be enhanced when targeting women. Other studies also reveal positive impacts of cash transfers in developing countries in sub-Saharan Africa, with economic characteristics more or less similar to those of the DRC. This is the case of the study by Levine et al. (2011) for the case of Namibia, …. Furthermore, Bastagli et al. (2019) provide a literature review of studies on the impact of cash transfers in middle- and low-income countries. Although CGEM (Computable General Equilibrium Model) is not applied in these studies, we find in the literature a number of studies where CGE modelling, sometimes accompanied by microsimulation, is applied.

Using a CGE model combined with a microsimulation model, Kyophilavong (2011) analyses the impact of cash transfers to poor households with children, located in rural and urban areas of Laos, on poverty and income distribution in the face of external shocks, such as the global financial crisis. He finds that cash transfers have a significant impact on poverty and income distribution and that these transfers lead to a greater reduction in poverty in rural areas than in urban ones. Cury (2016) also uses a CGE model combined with a microsimulation model to assess the effectiveness of Brazil's two largest cash transfer programmes (Bolsa Família [PBF] and Benefício de Prestação Continuada [BPC]) in achieving poverty reduction and reducing income inequality.

The results reveal a positive impact on the reduction of inequality from 2003 to 2005, although the impact on the reduction of poverty was not as strong or as significant. Novella et al. (2012) examine how the bargaining power structure of households affects the parental labour supply response to conditional cash transfer programmes. Using randomised experimental designs from rural Honduras (PRAF), Mexico (PROGRESA) and Nicaragua (RPS), they find that cash transfer programmes slightly alter the supply of paternal and maternal labour and that this effect depends on the distribution of power in the household. Hagen-Zanker et al. (2017) point out, in détail, that cash transfers have a positive impact on the well-being and opportunities of women and girls, particularly, in education and employment; and that there is empirical evidence to support the fact that female-headed households make greater productive investments than male-headed households.

Levy and Robinson (2014) on Cambodia find strong complementarities between social protection (transfers, etc.) and rural development policies. They point out that at a given level of public expenditure, a combination of these two types of policies is likely to generate more poverty reduction than cash transfers alone, while also significantly benefiting the local economy. Social protection programmes are, therefore, more effective when implemented simultaneously with productivity-enhancing policies (Levy and Robinson, 2014).

Our study offers a number of contributions. On the one hand, it focuses on a country where gender inequalities are blatant and where few studies have been conducted. On the other hand, by focusing on a country that is highly dependent on natural resources, it emphasises the importance of a more resilient economic diversification policy plan. And finally, the results of our study may be useful to the DRC government to help them in their choice of policies.

From a methodological point of view, this literature review shows that CGE modelling is one of the appropriate methods for analysing the impact of the policy of increasing land allocation to women and cash transfers to rural female households at the sectoral level and at the level of economic agents, more specifically, female households and female workers. However, it should be noted that there are other pro-gender policies, such as a policy to raise women's skills by promoting girls' education, etc. The two policies analysed in this study were chosen in the light of the DRC's National Strategic Plan, the first phase of which relates to the promotion of employment for vulnerable groups and economic diversification through the development of the agricultural sectors. Hence the targeting these two policies is to support rural/agricultural women, reduce gender inequalities and increase the share of the agricultural sectors in GDP.

3. Methodology

3.1 The model

In order to assess the impact of the land reallocation policy on the one hand, and of transfers on the other, we use a CGE model based on the PEP 1–1 model by Decaluwé et al. (2013). Some assumptions have been modified to accommodate the structure of the Congolese economy. In line with the Social Accounting Matrix (SAM) that we use, the model includes 41 sectors and 41 products. The production of each sector is a Leontief-type function between total value added and intermediate consumption. Intermediate consumption is also a Leontief function between intermediate demands of the branches. Total value added is disaggregated according to gender, into male and female value-added, the two being linked through a constant elasticity of substitution (CES) function. Each type of labour is mobile across sectors, while capital remains fixed (see Figure 1).

Regarding external trade, goods produced on the domestic level can either be exported or sold on the local market. Exports and local sales are thus linked by a CET (constant elasticity of transformation) function in order to account for their imperfect substitutability. In contrast, imported and domestically produced goods are linked by a CES function. The description of the economic agents and their sources of income, primarily the government and households by gender and place of residence of the household head, is presented in the following subsection.

3.2 The social accounting matrix (SAM)

The SAM used in this study was developed by the INS and UNDP-United Nations Development Program (2017). It includes 41 sectors and products, including 5 of which relate to agricultural activities, including subsistence agriculture, industrial agriculture, livestock and hunting, forestry and logging and fishing and fish farming. It has three production factors: labour, capital and land. There are three production factors: labour, capital and land. For the purposes of the study, these production factors were disaggregated according to gender using the 1-2-3 survey for the disaggregation of the labour factor (INS, 2014), and the agricultural survey for the disaggregation of the capital and land factors (INS, 2014).

The economic agents are households, businesses, government and the rest of the world. The Government obtains its income from the remuneration of capital as well as from transfers from companies and households and from various taxes, notably: deductible VAT, taxes and duties on imports, taxes on production net of subsidies, taxes on household and business income, other taxes on products and finally taxes on exports. Taxes on mining exports make up a very large share of export taxes, which contribute significantly to government revenues.

We also disaggregated the household account by gender and place of residence into six categories (rural female and male households, urban female and male households in Kinshasa and female and male households in other urban centres, i.e. other cities in the DRC). This disaggregation is particularly useful because, as Table 1 shows, the distribution of income is very different across households.

The share of income received by male households is higher for all sources of income, notably as regards the remuneration of the land factor. The share of female household income remains lower than that of male households, regardless of the place of residence. The last column of Table 1 provides information on the share of total income per household type and shows significant differences in income according to gender, exacerbated for rural households.

It should also be noted that households in Kinshasa (especially male-headed ones) benefit more from government transfers than other households. However, male-headed households in rural and other urban centres benefit most from transfers received from other economic agents, and women generally benefit less from transfers from both the government and other economic agents. This can be explained by the fact that, most households are headed by men, receiving more social benefits (more pronounced in Kinshasa and often justified by the high cost of living in the Congolese capital) than female-headed households. Furthermore, discriminatory practices against women in terms of inheritance, etc. mean that women do not enjoy all the rights that their husbands were entitled to, especially when they find themselves as heads of households following the death of their spouses, divorce, etc. Other rules, such as the fact that women do not attend community barzas, even though it is through these meetings that certain public aid is channelled or that beneficiaries of certain public subsidies are at least identified, means that women are losing out.

It can be seen that the main source of income for households in Kinshasa (both male and female) is the capital return (Table 2). However, the main source of income for all other household types is from labour.

In addition to the SAM, additional data is needed to make the model operational. For the elasticity values, we referred to the World Bank study (2017). However, for the elasticity values relating to the gender disaggregation of the labour market, we referred to the study carried out by Fontana (2001) on Zambia, which is a country with similar economic characteristics to the DRC. As regards the closure of the model, we assume that the exchange rate is the numeraire, world prices are exogenous and that the current account balance, minimum household consumption, government transfers to households, government expenditure, the supply of production factors and stock variation are fixed.

4. Results

4.1 Description of the scenarios

Diversification of the Congolese economy and job creation are among the main objectives of the PNSD, which is currently being implemented in the DRC. However, the PNSD does not clearly identify policies or interventions that would promote both the reduction of gender inequalities in the labour market and economic diversification. Thus, we evaluate the impact of a policy of increasing land allocations for women and a policy of government cash transfers to rural female households.

1. In 2018, the World Bank report highlights that Congolese women's poor access to land and financial capital does not allow them to invest in assets that will improve their productivity and, consequently, their earnings. The first scenario (SIM1) takes into account the enormous agricultural potential of the DRC. In fact, the DRC has the second largest amount of arable land in the world after Brazil, amounting to 80 million hectares, of which only less than 10% is exploited (Ministry of Planning, 2011). However, women make up only 8.9% of land owners (FAO statistics) and own only 25% of the total cultivated land in the DRC. Given the low ownership of land by women and the large availability of cultivable arable land, we simulate a 40% increase in the amount of land allocated to women. The implementation of this policy does not involve expropriation costs as the land is available and not currently in use.

2. For the second scenario (SIM 2), according to the World Bank (2018), one of the obstacles hindering agricultural production, smallholder marketing and overall agricultural growth in the DRC is poor access to both inputs and funding. These constraints are even more acute for women, as socio-cultural norms prevent them from acquiring assets (World Bank, 2018). We have, therefore, chosen to simulate a policy of transfers to rural female households by doubling the amount currently provided. As we have shown in Table 2, government transfers account for only a small share of rural women's household income.

4.2 Results

In terms of results, we expect that the policy of increasing women's access to land, which is a supply-side policy and consists of increasing the availability of a production factor, will contribute to increased production in the agricultural sectors, particularly in the food crop sector and those sectors linked to it. This has knock-on effects on the rest of the economy. However, this increased level of production will be accompanied by an increased demand for labour (both women and men) in the agricultural sectors and may attract workers from other sectors.

On the other hand, the second policy of transfers to rural female households is a demand policy. This policy would contribute to increasing the income of this specific type of household (rural female households) and thereby increase their consumption, especially of foodstuffs, forest products, meat and fish, flour and cereals. These products make up more than 60% of their overall consumption. The sectors producing these products will be encouraged to produce more. The potential negative effect comes from the decline in government savings ceteris paribus and consequently the impact on the sectors producing investment goods. The net effect cannot be defined ex ante.

4.2.1 Impact on production

The first policy (Sim 1) leads to a 4.26% increase in production in the subsistence agricultural sector. Indeed, the increase in the land factor leads to an increase in value-added, which favours the increase in production in the subsistence agricultural sector as well as in the sectors that depend on it (in particular the grain processing sector and the manufacture of cereal-based products sector). In order to produce more, the subsistence agriculture sector will require additional workers as well as intermediate consumption. So we have spill-over effects from the agricultural sector to the other sectors. It is worth noting that the increase in the female ownership of land leads to a decrease in the remuneration of this production factor in the subsistence agricultural sector, especially for women. Overall, this policy causes an increase in real GDP at basic prices by 0.33%.

The impact of the second policy is transmitted through the economy via the income of rural female households. Effectively, this policy increases the income of rural female households which increases their level of savings and consumption, mainly of food products, forest products, meat and fish, flour and cereals. This increase in consumption contributes to the increase in total demand and thus to an increase in production. However, given the very small fraction of government transfers to rural female households, this policy does not have significant effects on sectoral output nor on real GDP at basic prices, as can be seen in Table 3. This is normal since there is no increase in the production factors (see Table 3 below).

4.2.2 Impact on female labour demand and wages

Increasing female land ownership leads to an increase in the demand for female labour, followed by an increase in their wages, mainly in the subsistence agricultural sector (15%) and those sectors that depend on it such as the grain processing sector (1.4%), etc. This increase in production factors leads to an increase in value-added and production. There is also an improvement in the wage rate.

The second policy leads to a slight increase in the labour demand of both men and women in almost all sectors. In the agricultural sectors, the small improvement in the demand for female labour is 0.03% in the subsistence agriculture sector, 0.01% in the industrial agriculture sector, 0.03% in the livestock and hunting sector, 0.06% in the forestry and logging sector and 0.05% in the fisheries and fish farming sector. However, this slight increase is due to the limited impact of this policy on production (see above).

With regard to wages, the first policy (SIM1) improves the composite wage rate by roughly 0.35%, with a greater increase in women's wages (2.88% on average) in both the agricultural and non-agricultural sectors. The second policy leads to a slight increase in the wages of both women (0.02% on average) and men (0.01% on average).

4.2.3 Impact on household income and consumption according to place of residence

Compared to the second policy which has a positive impact on the total income of rural female households (approx. 0.72%) and other household types; the first policy has somewhat limited impacts on the incomes of rural female households (see Table 4). This is due to the dominant effects of the decline in their capital income (over 40%) resulting from the increase in women's land ownership and, therefore, in their demand for land. It should also be noted that transfers received by rural female households from other agents decline.

Regarding the level of household consumption, the first policy favours an increase in consumption of almost all households in food products and flour and in basic necessities by male households in Kinshasa and by both male and female households in other urban centres. However, this increase in consumption is not as apparent among rural female households.

These households, however, become the major beneficiaries of the government transfer policy, which induces the greatest increase in real consumption in these households.

4.2.4 Impact government revenues

The two pro-gender policies have different impacts on total government revenue and its components. Even though the impact is not significant enough, the first policy decreases total government revenue by 0.42%, given that capital taxes constitute the largest share of government revenue (20%). On the other hand, the second policy helps to marginally increase total government revenue (Table 5). Nevertheless, it can be pointed out, that on the one hand, this transfer policy increases the public deficit, with a decline in public savings by approximately 0.3%, because financing this policy involves the release of funds by the government. On the other hand, this policy does not lead to a significant increase in government transfers to economic agents despite a significant increase (of approximately 100%) in government transfers to rural female households.

Both policies, however, fail to improve the incomes of the economic agents, particularly households and the government significantly enough. They also fail to stimulate their respective savings, increase total savings (and thus investment) and improve the demand for goods for investment purposes.

4.2.5 Impact on foreign trade

As can be seen from Table 6, the first policy favours increased exports in the subsistence agricultural sector and in other sectors that are highly dependent on it, notably the grain processing sector, the cereal-based food manufacturing sector and the other food industries sector. As a result of the price effects, the export of agricultural products (foodstuffs) shows remarkable growth. However, the second policy does not contribute to the increase in exports. One of the reasons for this is that the level of production has remained constant due to the insignificant impact of this policy on sectoral production (see Table 6).

As can be seen in Table 6, the first policy leads to a decrease in agricultural imports, especially in the subsistence agricultural sector and dependent sectors, as a result of increased production.

In terms of economic diversification (Table 7), the results of the first simulation reveal a slight increase in the share of agricultural value added in total value added. This share, which is 10.43% in the reference situation, increases to 10.83% after the first simulation. However, the impact of the second simulation is insignificant, given the fact that the share of agricultural value added in total value added remains unchanged (10.43% in the reference situation and 10.432% after the second simulation). In terms of the diversification of exports, the impact is very small for the first simulation (increase of 0.013%) and not at all significant for the second one (as can be seen in Table 7). This is not surprising given that the second simulation does not have a significant impact on production as there is no increase in production factors. As such, it has no impact in terms of export diversification.

5. Conclusion and policy implications

The objective of this study was to show how pro-gender public policies in the agricultural sectors can contribute to the reduction of gender inequalities in the labour market and to the diversification of the Congolese economy.

The results reveal that a policy of increasing female land ownership by approximately 40% would increase the demand for female labour in subsistence agriculture and related sectors and subsequently increase their remuneration. From a macroeconomic perspective, this policy has a positive impact on GDP (0.33%). As for the policy of doubling government cash transfers to rural female households, it brings about a small improvement in the labour demand of both women and men in almost all sectors. However, the impacts of this policy are more apparent for rural women who experience an increase in their real consumption. Our results are in line with the literature and reveal that both these pro-gender policies are effective, would contribute to the enhancement of female employment and contribute to the reduction of gender inequalities (Mishra and Sam, 2016; Anderson and Eswaran, 2008; Hagen-Zanker et al., 2017, and references therein).

Nevertheless, only the policy of increasing female land ownership can contribute to both the reduction of gender inequalities and to economic diversification, through increased production and exports in the agricultural sectors, especially in the subsistence agricultural sector; Rosetti and Kakande (2010) also highlight this. It should, therefore, be prioritised. Moreover, this policy is feasible in the DRC as there is a lot of unused arable land available.

The DRC's PNSD prioritises the agricultural sectors as the primary vehicle for diversifying the Congolese economy and creating jobs for vulnerable groups, including agricultural/rural women. Both policy options would contribute to the improvement of women's employment and are, therefore, recommendable as policies to reduce gender inequalities in the Congolese labour market. However, only the policy of increasing land allocation to women could contribute both to the reduction of gender inequalities and to economic diversification, through economic diversification, through increased production and exports in the agricultural sectors. In view of the revision of the PNSD, we propose the following roadmap for the implementation of the recommendations arising from this study.

1. In Pillar 1 of the PNSD on Economic Diversification and Transformation, the policy of increasing land allocation to women could be added to the objectives related to strengthening the contribution of agriculture to economic growth and employment creation;

2. In Pillar 3 of the PNSD on Social Development and Human Resource Development, the policy of increasing land allocation to women as well as the policy of increasing government transfers to female rural households could be added to the objectives related to the promotion of employment of youth, women and vulnerable groups.

Figures

Figure 1

Production structure

Table 1

Main sources of household income according to gender and place of residence (%)

	Factor income		Transfers received			Total income
	Labour	Capital	Land	Other agents	Gvt
Male households in Kinshasa	13	42	0	2	45	22
Female households in Kinshasa	3	9	3	1	11	5
Male households in other urban centres	27	30	0	37	37	27
Female households in other urban centres	4	4	0	1	1	3
Rural male households	45	16	80	58	5	38
Rural female households	8	0	17	1	0	5
Total	100	100	100	100	100	100

Source(s): Authors, based on the SAM

Table 2

Sources of household income (as % of total income of each household type)

	Factor income			Transfers received		Total income
	Labour	Capital	Land	Other agents	Gvt
Male households in Kinshasa	29	55	0	1	15	100
Female households in Kinshasa	28	49	5	2	17	100
Male households in other urban centres	48	31	0	10	10	100
Female households in other urban centres	60	34	0	3	3	100
Rural male households	56	12	20	11	1	100
Rural female households	67	0	30	2	1	100

Source(s): Authors, based on the SAM

Table 3

Impact of gender policies on production (in %)

Main sectors	Production_SIM1	Production_SIM2
Subsistence agriculture	4.26	0.01
Industrial agriculture	−0.34	0.01
Livestock and hunting	−0.15	0.03
Forestry and logging	−0.91	0.06
Fishing and fish farming	−0.71	0.06
Mining	−0.46	−0.01
Grain processing	2.65	0.02
Manufacture of cereal-based food products	0.45	0.03
Other food industries	3.14	0.002
Trade	0.39	0.01
Health and social work	0.05	0.01
Real GDP at basic prices	0.33	0.000

Note(s): With SIM1: Simulating the increase in female-owned land

SIM2: Simulating government cash transfers to rural female households

Source(s): Authors, based on simulations

Table 4

Impact of pro-gender policies on household incomes (%)

	Labour income		Capital income		Transfer income		Total income
Households	Sim1	Sim2	Sim1	Sim2	Sim1	Sim2	Sim1	Sim2
Male households in Kinshasa	−0.11	0.01	0.18	0.01	−0.002	0.00	0.07	0.01
Female households in Kinshasa	2.88	0.02	−3.34	0.04	−0.1	0.00	−1.01	0.03
Male households in other urban centres	−0.11	0.01	0.18	0.01	−0.09	0.01	−0.02	0.01
Female households in other urban centres	2.88	0.02	0.87	0.03	0.51	0.01	2.05	0.02
Rural male households	−0.11	0.01	−3.66	0.12	−0.42	0.02	−1.27	0.04
Rural female households	2.88	0.02	−45.0	0.19	−8.48	28.99	−11.86	0.72

Note(s): SIM1: Simulation of the increase in female-owned land

SIM2: Simulation of government cash transfers to rural female households

Source(s): Authors, based on simulations

Table 5

Impacts of pro-gender policies on the main sources of government revenue (%)

Source of government revenue and government expenditure	Impact of pro-gender policies
	Sim1	Sim2
Indirect taxes on products	−0.40	0.01
Taxes on production	−0.23	−0.01
Taxes on corporate income	0.36	0.01
Taxes on imports	−0.39	−0.01
Taxes on household income	−1.16	0.07
Taxes on exports	−0.25	−0.00
Transfers received	−0.98	0.02
Total government revenue	−0.42	0.01
Savings	−0.91	−0.29
Government transfers	−1.69	0.1

Note(s): SIM1: Simulating the increase in female-owned land, SIM2: Simulating government cash transfers to rural female households

Source(s): Authors, based on simulations

Table 6

Impact of pro-gender policies on agricultural imports and exports (in %)

Sectors	EXP_SIM1	EXP_SIM2	IMP_SIM1	IMP_SIM2
Subsistence agriculture	15.24	−0.12	−5.20	0.11
Industrial and export agriculture	−0.47	0.00	0.03	0.03
Forestry and logging	−0.79	0.02	−0.67	0.07
Mining	−0.46	−0.01	−0.18	−0.02
Grain processing	6.34	−0.04	−0.35	0.05
Manufacture of cereal-based food products	1.34	0.00	−0.55	0.05
Other food industries	5.21	−0.04	−0.65	0.05

Note(s): With EXP: Exports, IMP: Imports, SIM1: Simulation of the increase in female-owned land, SIM2: Simulation of government cash transfers to rural female households

Source(s): Authors, based on simulations

Table 7

Impact of pro-gender policies on the contribution of the agricultural sector to total VA and total exports (in %)

Diversification indicators	Ref	Sim1	Sim2
Share of agricultural VA in total VA	10.43	10.83	10.432
Share of agricultural exports in total exports	0.009	0.0103	0.009

Note(s): With Ref: Baseline situation, with SIM1: Simulating the increase in female-owned land, SIM2: Simulating government cash transfers to rural female households

Source(s): Authors, based on simulations