IMF Working Papers

Tax Policy Measures in Advanced and Emerging Economies: A Novel Database

By David Amaglobeli, Valerio Crispolti, Era Dabla-Norris, Pooja Karnane, Florian Misch

May 11, 2018

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David Amaglobeli, Valerio Crispolti, Era Dabla-Norris, Pooja Karnane, and Florian Misch. Tax Policy Measures in Advanced and Emerging Economies: A Novel Database, (USA: International Monetary Fund, 2018) accessed December 7, 2024

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Summary

This paper describes a new, comprehensive database of tax policy measures in 23 advanced and emerging market economies over the last four decades. We extract this information from more than 900 OECD Economic Surveys and 37,000 tax-related news from the International Bureau of Fiscal Documentation using text-mining techniques. The innovation of this dataset lies in its granularity: changes in the rates and bases of personal and corporate income taxes, value added and sale taxes, social security contributions, excise, and property taxes are systematically documented. In addition, the database provides information on the announcement and implementation dates, whether the measures represent major changes, are part of a broader tax package, and phased in over several years. The paper also presents a range of stylized facts suggesting that information from this database is useful to deepen the analysis of tax policy changes for research and policy purposes.

Subject: Corporate income tax, Personal income tax, Revenue administration, Social security contributions, Tax type organization, Taxes, Value-added tax

Keywords: CIT, Corporate income tax, Global, Implementation Lags, Major tax, Personal income tax, PIT, Political Economy, Rate change, Reform package, Social security contributions, Tax, Tax measure, Tax package, Tax Policy, Tax Reforms, Tax type organization, Text Mining, Value-added tax, VAT, VAT measure, WP

Publication Details

  • Pages:

    60

  • Volume:

    ---

  • DOI:

    ---

  • Issue:

    ---

  • Series:

    Working Paper No. 2018/110

  • Stock No:

    WPIEA2018110

  • ISBN:

    9781484354865

  • ISSN:

    1018-5941

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