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

Abstract

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.

Macroeconomic Effects of Tax Rate and Base Changes: Evidence from Fiscal Consolidations

“…In this regard, expanding the dataset to include additional countries and non-consolidation years would be fruitful. Another potential direction would be to classify base measures in more detail, similar to Amaglobeli et al (2018), and indicate whether theoretically they would be expected to increase tax efficiency or not. This would make it possible to analyze the macroeconomic impact of different types of base measures, and zoom in on those more likely to be beneficial during consolidations.…”

“…In addition, we classify each measure as a tax rate or a tax base change following the classification proposed in Amaglobeli et al (2018). A tax rate measure is defined as any change to the main statutory tax rate inclusive of surtax.…”

“…Relative toDevries et al (2011) andAlesina et al (2015), we exclude Belgium, Denmark, Finland, Ireland, Japan, the Netherlands and Sweden, since we do not have enough detailed information on all tax changes, especially for earlier years. A partial version of the dataset can be found inAmaglobeli et al (2018).6 We use the 2016 edition of the OECD classification of taxes and interpretative guide, which is available at http://dx.doi.org/10.1787/rev_stats-2017-10-en 5 ©International Monetary Fund. Not for Redistribution…”

The Possibilities for Developing the Tax Potential of the Constituent Entities of the Russian Federation

“…Так, ряд зарубежных авторов рассматривает перспективы развития налогового потенциала с точки зрения как внедрения альтернативных инструментов (налогового кредита) [15][16][17][18][19][20][21][22], так и использования существующих ме-ханизмов (эффективная налоговая политика) [23][24][25][26] мера общей площади установлено в Тюменской области 4 для объектов недвижимого имущества в отношении административно-деловых центров и торговых центров (комплексов), введенных в эксплуатацию до 1 января 2010 г., составляет 10 000 м 2 . (до 2018 г.…”

How Loose, How Tight? A Measure of Monetary and Fiscal Stance for the Euro Area

“…In the empirical literature these announced policy changes are studied also in a narrative approach (see, e.g.,Amaglobeli et al, 2018) 7 The Kalman filter is used to evaluate the likelihood function, which combined with the prior distribution of the parameters yields the posterior distribution. Then, the Monte-Carlo-Markov-Chain Metropolis-Hastings (MCMC-MH) algorithm with two parallel chains of 500, 000 draws each is used to generate a sample from the posterior distribution in order to perform inference.8 The precise starting date of the estimation, however, changes slightly across countries due to data availability.…”