Summary
Productivity growth is key to wealth and high living standards. For many years, Europe’s productivity growth has been declining and since 2005, falls below 1 percent. A possible way to raise productivity is to increase investments in intangible (knowledge based) assets such as workforce skills and Research and Development (R&D). To design policy measures that will effectively facilitate these investments and boost productivity growth, it is essential to understand the firms’ decision-making process in R&D and worker skills investments. In this project, I address the questions
(1) What are the incentives each firm faces when making investment decisions in R&D and worker skills improvement? (2) What is the optimal level of investment for each firm? Moreover, what are the implications of these investments for the firms' longrun productivity development?
I propose to develop and estimate a dynamic model of firm investment decision in R&D and worker skills improvement in the service industries. The estimation results will shed lights on firms’ investment incentives by quantifying the firm-specific longrun returns and costs to these investments. The estimated model predicts firm-specific responses to changes in their economic environment, therefore allows for ex-ante policy evaluation that aims at fostering productivity growth. In answering the questions raised, the project contributes to the knowledge on productivity and firm investments by providing insights on the (i) multidimensional productivity development in the service industries, (ii) complementarity between different intangible assets such as R&D and worker skills, and (iii) firm decision-making process.
(1) What are the incentives each firm faces when making investment decisions in R&D and worker skills improvement? (2) What is the optimal level of investment for each firm? Moreover, what are the implications of these investments for the firms' longrun productivity development?
I propose to develop and estimate a dynamic model of firm investment decision in R&D and worker skills improvement in the service industries. The estimation results will shed lights on firms’ investment incentives by quantifying the firm-specific longrun returns and costs to these investments. The estimated model predicts firm-specific responses to changes in their economic environment, therefore allows for ex-ante policy evaluation that aims at fostering productivity growth. In answering the questions raised, the project contributes to the knowledge on productivity and firm investments by providing insights on the (i) multidimensional productivity development in the service industries, (ii) complementarity between different intangible assets such as R&D and worker skills, and (iii) firm decision-making process.
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More information & hyperlinks
Web resources: | https://cordis.europa.eu/project/id/898949 |
Start date: | 01-09-2020 |
End date: | 25-03-2023 |
Total budget - Public funding: | 187 572,48 Euro - 187 572,00 Euro |
Cordis data
Original description
Productivity growth is key to wealth and high living standards. For many years, Europe’s productivity growth has been declining and since 2005, falls below 1 percent. A possible way to raise productivity is to increase investments in intangible (knowledge based) assets such as workforce skills and Research and Development (R&D). To design policy measures that will effectively facilitate these investments and boost productivity growth, it is essential to understand the firms’ decision-making process in R&D and worker skills investments. In this project, I address the questions(1) What are the incentives each firm faces when making investment decisions in R&D and worker skills improvement? (2) What is the optimal level of investment for each firm? Moreover, what are the implications of these investments for the firms' longrun productivity development?
I propose to develop and estimate a dynamic model of firm investment decision in R&D and worker skills improvement in the service industries. The estimation results will shed lights on firms’ investment incentives by quantifying the firm-specific longrun returns and costs to these investments. The estimated model predicts firm-specific responses to changes in their economic environment, therefore allows for ex-ante policy evaluation that aims at fostering productivity growth. In answering the questions raised, the project contributes to the knowledge on productivity and firm investments by providing insights on the (i) multidimensional productivity development in the service industries, (ii) complementarity between different intangible assets such as R&D and worker skills, and (iii) firm decision-making process.
Status
SIGNEDCall topic
MSCA-IF-2019Update Date
28-04-2024
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