1887

Mauritius

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Given the fast pace of global socio-economic development, more tailored, focused, and localised efforts to strengthen public sector capacity in small island developing states (SIDS) is increasingly important. SIDS have unique vulnerabilities, rich histories and contexts, and strengths that can be harnessed for sustainable development. Development partners need to adapt how they provide capacity-strengthening support, taking individual SIDS’ circumstances and needs into account to better help them achieve their ambitions. This report summarises perspectives from small island developing states (SIDS) on current experiences and opportunities to improve capacity-strengthening support to make it more tailored, impactful, and sustainable. The report uses the broad definition of capacity-strengthening as activities that improve the competencies and abilities of individuals, organisations, and broader formal and informal social structures in a way that boosts organisational performance. It concentrates on public sector capacity, including interactions with other stakeholders across sectors.

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 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.

Small island developing states (SIDS) have been acutely affected by the economic impacts of the COVID-19 pandemic. This paper takes a broader perspective to explore how the revenue effects of this crisis in SIDS are connected to their unique financing and development challenges. It also suggests how SIDS governments and development co-operation providers can better partner together to strengthen mobilisation of domestic revenues – in particular tax revenues – in the recovery post-COVID-19.

Corporate tax incentives reduce investment costs for businesses, which may affect investment and location decisions. They apply through different designs and interact with countries’ standard tax systems, often making it difficult for tax policy makers and researchers to compare their generosity and assess their impacts across countries. This paper develops a methodology to calculate forward-looking corporate effective tax rates (ETRs) summarising tax relief from investment tax incentives into comparable indicators. It presents ETR indicators for seven Sub-Saharan African countries. Empirical results show that tax incentives substantially lower corporate taxation across these countries. On average, tax incentives reduce ETRs by 30% in the food and automotive industries compared to the standard tax treatment. ETRs often differ among taxpayers in a same sector and country - by up to 55%. The most generous tax treatment is typically offered within Special Economic Zones, where tax incentives can reduce ETRs to near zero.

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.
  • 05 Apr 2022
  • OECD
  • Pages: 110

As a small, open economy, Mauritius needs a well-performing regulatory system that provides necessary protections while enabling the development of trade and investment and limiting administrative burdens. A robust regulatory impact assessment (RIA) framework can enhance Mauritius’ business environment and attractiveness as a trade and investment partner. In particular, RIA can help Mauritius strengthen its rule-making framework, for example by increasing scrutiny and taking a more evidence-based approach to rulemaking.

This report presents OECD recommendations on to how establish a RIA framework in Mauritius. These recommendations are based upon an analysis of the country’s strengths and challenges, as well as extensive engagement with stakeholders. The recommendations also draw on lessons learnt from RIA implementation in a range of countries and an initial benchmarking of RIA-related best practices and guidance material from various relevant jurisdictions.

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 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 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 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.

  • 25 Mar 2015
  • OECD
  • Pages: 264

This publication provides comprehensive and consistent information on African central government debt statistics for the period 2003-2013. Detailed quantitative information on central government debt instruments is provided for 17 countries to meet the requirements of debt managers, other financial policy makers and market analysts. A cross country overview on African debt management policies and country policy notes provides background information on debt issuance as well as on the institutional and regulatory framework governing debt management policy

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