Taxation

Peter Egger, Nicole Loumeau, 16 January 2019

Innovative activity is unevenly distributed geographically, with regional characteristics such as global market accessibility or an innovation-promoting policy environment affecting the spatial distribution. Using global data on regional characteristics, regional patenting output, and innovation-promoting policy environments, this column examines the origins of innovation clusters, and particularly the role of R&D tax policy instruments, in attracting innovative firms. It estimates that innovation-promoting R&D tax policy instruments contribute to about one-tenth of the long-term economic growth around the globe.

Jing Cai, Yuyu Chen, Xuan Wang, 17 December 2018

R&D tax breaks are often offered to businesses to encourage innovation. This column uses evidence from a tax reform in China to study the relationship between tax enforcement and firm innovation. Lower taxes improve both the quantity and quality of firm innovation, and have a bigger impact on those firms that are either financially constrained or those that engage more in tax evasion. 

Fabian Kindermann, Lukas Mayr, Dominik Sachs, 04 December 2018

Although inheritance taxes are of growing importance for Western economies in raising government revenue, little is known about how inheritance taxation affects individuals’ incentives to work. This column explores how much additional labour income tax revenue from heirs the government can expect to obtain for each euro of revenue raised directly through inheritance taxes. It concludes that additional labour tax payments from heirs, resulting from an increase in bequest taxes, are of sizable magnitude and should be taken into account in fiscal planning and welfare analysis.

Ufuk Akcigit, 23 November 2018

Firms like to be politically connected, because it makes it easier for them to do business. But is it good for the rest of us? Ufuk Akcigit of the University of Chicago tells Tim Phillips about the consequences of connecting to power.

Monica Andini, Emanuele Ciani, Guido de Blasio, Alessio D'Ignazio, 21 November 2018

The impact of a public policy partly depends on how effective it is in selecting its targets. Machine learning can help by exploiting increasingly available amounts of information. Using data from Italy, this column presents two examples of how to employ machine learning to target those groups that could plausibly gain more from the policy. It illustrates the benefits of machine-learning targeting when compared to the standard practice of employing coarse policy assignment rules based on a few arbitrarily chosen characteristics.

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