Kenya

Transactions with M-Pesa in Kenya appears in African Economic Outlook 2009.

Governments and providers of development co-operation increasingly use Sustainable Development Goal indicators to guide their policies and practices. The close examination of three large recipients of development co-operation: Ethiopia, Kenya and Myanmar across the sectors of Education, Sanitation and Energy reveals four inter-related challenges in using SDG indicators at country level. First, the cost of using specific SDG indicators varies in relation to indicator complexity – complementary investments in country statistical systems may be necessary. Second, providers synchronising their country-level results planning with partner countries find it easier to align to and measure SDG indicators together with the partner country and other providers. Third, reliance on joint monitoring approaches is helping providers reduce the cost of SDG monitoring. Finally, while disaggregating SDG data by gender and by urban-rural dimensions is common, other data disaggregation relevant to ensure that no one is left behind are rare.

This strategic foresight report assesses the interaction between demographics, economic development, climate change and social protection in six countries in East Africa between now and 2065: Ethiopia, Kenya, Mozambique, Tanzania, Uganda and Zambia. The report combines population projections with trends in health, urbanisation, migration and climate change and identifies the implications for economic development and poverty. It concludes by identifying policies to address seven grand challenges for social protection planners in national governments and donor agencies which emerge from the projections. These include: eliminating extreme poverty; extending social insurance in a context of high informality; the rapid growth of the working-age population, in particular the youth; adapting social protection to urban settings; protecting the poor from the effects of climate change; harnessing a demographic dividend; and substantially increasing funding for social protection.

Kenya’s National Climate Change Action Plan (NCCAP) covers both mitigation and adaptation. A complementary National Performance and Benefits Measurement Framework (NPBMF) has been proposed. The objective of the framework is to track both mitigation and adaptation actions and the synergies between the two. It is informed by a methodology developed by the International Institute for Environment and Development (IIED) called Tracking Adaptation and Measuring Development (TAMD). The framework combines top-down indicators that assess institutional (adaptive) capacity and bottom-up indicators that measure vulnerability. The proposed indicators are linked to national level indicators already being measured on a regular basis.

This dataset includes pension funds statistics with OECD classifications by type of pension plans and by type of pension funds. All types of plans are included (occupational and personal, mandatory and voluntary). The OECD classification considers both funded and book reserved pension plans that are workplace-based (occupational pension plans) or accessed directly in retail markets (personal pension plans). Both mandatory and voluntary arrangements are included. The data includes plans where benefits are paid by a private sector entity (classified as private pension plans by the OECD) as well as those paid by a funded public sector entity. Data are presented in various measures depending on the variable: millions of national currency, millions of USD, thousands or unit.

This dataset includes pension funds statistics with OECD classifications by type of pension plans and by type of pension funds. All types of plans are included (occupational and personal, mandatory and voluntary). The OECD classification considers both funded and book reserved pension plans that are workplace-based (occupational pension plans) or accessed directly in retail markets (personal pension plans). Both mandatory and voluntary arrangements are included. The data includes plans where benefits are paid by a private sector entity (classified as private pension plans by the OECD) as well as those paid by a funded public sector entity. Data are presented in various measures depending on the variable: millions of national currency, millions of USD, thousands or unit.

This dataset includes pension funds statistics with OECD classifications by type of pension plans and by type of pension funds. All types of plans are included (occupational and personal, mandatory and voluntary). The OECD classification considers both funded and book reserved pension plans that are workplace-based (occupational pension plans) or accessed directly in retail markets (personal pension plans). Both mandatory and voluntary arrangements are included. The data includes plans where benefits are paid by a private sector entity (classified as private pension plans by the OECD) as well as those paid by a funded public sector entity. Data are presented in various measures depending on the variable: millions of national currency, millions of USD, thousands or unit.

This dataset comprises statistics pertaining to pensions indicators.It includes indicators such as occupational pension funds’asset as a % of GDP, personal pension funds’ asset as a % of GDP, DC pension plans’assets as a % of total assets. Pension fund and plan types are classified according to the OECD classification. Three dimensions cover this classification: pension plan type, definition type and contract type.

This dataset comprises statistics pertaining to pensions indicators.It includes indicators such as occupational pension funds’asset as a % of GDP, personal pension funds’ asset as a % of GDP, DC pension plans’assets as a % of total assets. Pension fund and plan types are classified according to the OECD classification. Three dimensions cover this classification: pension plan type, definition type and contract type.