Organisation for Economic Co-operation and Development

Environmentally related taxes are effective policy instruments to shape relative prices of goods and services. The Environmental Related Tax Revenue Database (ERTR) categorises taxes based on their environmental relevance, constructing environmentally related tax revenue with a breakdown by tax-base category (including energy, transport, pollution, and resources) and 22 environmental domains. Note that tax-base categories are mutually exclusive, while domains are not. Therefore, one should not aggregate revenue across domains as it may lead to double counting.

Revenue Statistics in LAC Countries is a joint publication by the OECD Centre for Tax Policy and Administration, the OECD Development Centre, the Economic Commission for Latin America and the Caribbean (ECLAC) , the Inter-American Center for Tax Administrations (CIAT) and the Interamerican Development Bank (IDB). It presents detailed, internationally comparable data on tax revenues for 24 Latin American and Caribbean economies, two of which (Chile and Mexico) are OECD members. Its approach is based on the well-established methodology of the OECD Revenue Statistics (OECD, 2016), which has become an essential reference source for OECD member countries. Comparisons are also made with the average for OECD economies. Comparable tables show total tax revenue data and by tax as a percentage of GDP, and, for the different types of taxes, as a share of total taxation. Detailed country tables show information in national currency values

A key set of information for policy analysis is i) how much revenue is collected; ii) in what ways is it collected; iii) from which institutional units of the economy are revenues raised for each particular financing scheme; and iv) which financing schemes receive those revenues. This dataset provides information about the contribution mechanisms the particular financing schemes use to raise their revenues. Understanding the nature of the flows is of importance from the perspective of both health and public finance policy. For example, the classification of revenues make it possible to distinguish between public and private funding of health care finance. Understanding how resources are raised by financing schemes is important for many countries, as many health systems are struggling with the issue of funding. The classification of revenues of financing schemes is suitable for tracking the collection mechanisms of a financing framework. Furthermore, the new classification makes it possible to analyse the contribution of the institutional units to health financing.