Tom Smits is a researcher at SEO, specialising in building (financial) economic models, econometric analyses, and machine-learning techniques.
Tom has helped develop the SEO’s method for calculating direct and indirect effects on production and employment effects of government investments and policies. This method, which, among others, makes use of input-output tables, has since been used in many of the cost-benefit analyses and effect studies done by SEO on behalf of the Dutch Government. In this context, Tom has, for example, calculated the benefits of government investments in the Square Kilometre Array radio telescope and the return on investment of government aid for seaports. Tom also employs these methods for the Turistika Model, which calculates the effects of tourism on the economy of Curaçao.
Tom has extensive experience in (econometrically) analysing micro data related to Dutch households and companies. Among others, he has worked on the further development of the distribution model for the Participation Act and on various projects relating to international trade and trade agreements. He also performed quantitative analyses of different policy evaluations, such as the evaluation of entrepreneur tax schemes, the evaluation of tax schemes for business transfers, and the evaluation of the development fund Fondo Desaroyo Aruba.
In addition to his econometric experience, Tom possesses great knowledge on machine-learning techniques such as feature engineering, text mining, and neural networks. For instance, he has used the text in online reviews in order to explain and predict customer satisfaction. For the Ministry of Economic Affairs, Tom has built the tax burden model for companies, using cluster analysis on microdata sets of Statistics Netherlands (CBS) to find the best way in which to group companies.
Tom holds a master’s degree in Econometrics from the University of Amsterdam, where he specialized in mathematical economics. In addition, he holds a master’s degree in Civil Engineering.
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