1887

Nigeria

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Blockchain is mainstreaming, but the number of blockchain for development use-cases with proven success beyond the pilot stage remain relatively few. This paper outlines key blockchain concepts and implications in order to help policymakers reach realistic conclusions when considering its use. The paper surveys the broad landscape of blockchain for development to identify where the technology can optimise development impact and minimise harm. It subsequently critically examines four successful applications, including the World Food Programme’s Building Blocks, Oxfam’s UnBlocked Cash project, KfW’s TruBudget and Seso Global. As part of the on-going work co-ordinated by the OECD’s Blockchain Policy Centre, this paper asserts that post-COVID-19, Development Assistance Committee (DAC) donors and their development partners have a unique opportunity to shape blockchain’s implementation.

This paper uses network analysis to map and characterise live animal trade in West Africa. Building on a database of 42 251 animal movements collected by the Permanent Inter-State Committee for Drought Control in the Sahel (CILSS) from 2013-17, it describes the structure of regional livestock trade at the network, trade community and market levels. Despite yearly fluctuations in the volumes and spatial patterns of trade, the paper shows that regional livestock trade operates on well-established trade corridors as animals flow in specific directions. The study also confirms that livestock trade is structured around several national and cross-border groups of markets that exchange more animals than expected by chance. Close to two-thirds of all animals are shipped internationally, indicating that regional animal trade in the Economic Community of West African States (ECOWAS) is remarkably cross-border. Finally, the paper finds that the hub markets that concentrate the most shipments also handle more animals and trade with more markets. Additionally, peripheral markets have more defined roles as primarily origins or destinations of animal shipments than markets in the core of the network. Of the nine key markets identified, three are close to borders, highlighting the importance of Nigeria as a livestock consumption destination for regional livestock production.

This chapter examines the policy framework for investment in Lagos State. The chapter analyses its various facets in which Lagos State Government has the largest policy space in terms of encouraging investment at state level to support economic growth and sustainable development. These areas include: the resolution of business disputes, where Lagos has proved to be a forerunner in promoting innovative and alternative dispute resolution means; access to land for investors in Lagos State; the institutional framework governing investment promotion in Lagos State, with a particular focus on the newly created Investment Promotion Unit; measures to enhance the business environment, facilitate investment and improve consultations with the private sector; free trade zones development and investment incentives; business linkages and measures to support SMEs operating in Lagos State; and the policy framework for private sector participation in the development of state infrastructure with a focus on clean energy and public-private partnerships.

This overview chapter provides a background analysis of the Nigerian economy, the role of private investment in its development and the recent FDI trends. It shows how the country became the preferred destination for foreign direct investment in Africa while also still facing a number of challenges affecting the investment climate. The chapter also summarises the key OECD policy recommendations made at both federal and Lagos State levels that are developed in other chapters of the report.

This dataset contains tax revenue collected by Nigeria. It provides detailed tax revenues by sector (Supranational, Federal or Central Government, State or Lander Government, Local Government, and Social Security Funds) and by specific tax, such as capital gains, profits and income, property, sales, etc.

This dataset contains tax revenue collected by Nigeria. It provides detailed tax revenues by sector (Supranational, Federal or Central Government, State or Lander Government, Local Government, and Social Security Funds) and by specific tax, such as capital gains, profits and income, property, sales, etc.

This dataset contains tax revenue collected by Nigeria. It provides detailed tax revenues by sector (Supranational, Federal or Central Government, State or Lander Government, Local Government, and Social Security Funds) and by specific tax, such as capital gains, profits and income, property, sales, etc.

  • 28 Feb 2001
  • OECD, Sahel and West Africa Club
  • Pages: 43

Economic integration in West Africa is a major political objective for all the States in the region and is supported by the main economic players in the region. The weight of Nigeria -- which accounts for 50% of the regional economy -- the many constraints to formal trade, linguistic barriers, these all raise as many hopes as fears among the economic players in neighbouring countries with respect to their future relations with this powerful neighbour.

Prospects for Trade between Nigeria and its Neighbours, a study undertaken by the Laboratoire d’Analyse Regional et d’Expertise Sociale (LARES) in Cotonou, commissioned by the Club du Sahel, examines the issues. It describes the still largely informal trade in the region, analysing constraints to its growth and some possible future developments.

Presented as a series of concise, well documented "fact sheets", this study will be of interest to those in both public and private spheres who believe that regional trade development is a necessary response to globalisation. Prospects for Trade between Nigeria and its Neighbours has formed the basis of a workshop organised by the Club du Sahel and the West African Enterprise Network for English and French entrepreneurs in December 2000 in Cotonou, Benin.

French

Investment promotion and facilitation measures, including incentives, can be effective instruments to attract investment, provided they aim at correcting market failures and are developed in a way that can leverage the strong points of a country’s investment environment. This chapter provides an analysis of the framework for investment promotion and facilitation in Nigeria. It examines existing strategies and institutions governing investment promotion and facilitation with a particular focus on the Nigerian Investment Promotion Commission. It highlights important measures that have been taken by the government to improve the business environment and attract foreign investment in various sectors of the economy. It also provides recommendations on the investment incentives regime as well as on actions to encourage business linkages and other policies to boost foreign investments’ spillovers on domestic small and medium-sized enterprises.

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 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 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.
French
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.
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