Veni grant for FEB researchers Artūras Juodis and Ward Romeijnders

FEB researchers Artūras Juodis and Ward Romeijnders of the Faculty of Economics and Business have both been awarded a Veni grant as part of the Innovational Research Incentives Scheme run by the Netherlands Organisation for Scientific Research (NWO).

The personal Veni grants are worth up to a maximum of € 250,000 and enable talented researchers who have just completed a PhD to conduct research of their own choice.

• Dr. Artūras Juodis: We do not live in a bubble: economic shocks in misspecified panel data models
  Economics, Econometrics and Finance

Much of economic data at individual and country level is observed over time. To properly describe the co-movements of economic units over time, common shocks and trends have to be accounted for. Juodis’ project investigates the impact of common shocks in misspecified panel data models.

Juodis: ‘In my project, I want to investigate the impact of using simple linear regression-type models in setups where the relationships between the objects of interest can be non-linear. In such a case it is important to understand the meaning of the quantities one obtains from the data when all units (individuals or countries) are affected by common shocks. For example, re-evaluate the knowledge of the impact trade agreements have on trade flows, given that all countries are exposed to global economic factors. By the end of this project I want to understand better the meaning of the correlation patterns observed in data, in situations when causality can be difficult to establish and the dependence between units (individuals, firms, countries) is difficult to model precisely.’

• Dr. Ward Romeijnders: Planning for the unknown
  Operations Management & Operations Research

Many practical decisions have to be made before key information is known. To support decision making in such situations, Romeijnders will develop new algorithms for the underlying mathematical optimization problems, exploiting recently discovered properties of these problems. The new algorithms will be applied to investment decisions in electricity networks.

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