Periodic Reporting for period 1 - INVPROD (Firm Dynamic Investments in Research and Development and Skills in Service Industries.)
Reporting period: 2020-09-01 to 2022-08-31
In my project, I investigate productivity in service industries, focusing on how firms decide to invest in research and development (R&D) and worker training. These investments are vital for boosting productivity because they create new knowledge and technologies, allowing companies to produce more with the same resources. Although it seems logical for firms to invest in R&D and skill development, not all do, and those that do often differ vastly from each other in their invested amount. The project explores the incentives for companies to invest in R&D and worker training and how these investments impact their productivity in the long run.
Investigating productivity, how to facilitate the growth is important because productivity growth is the reason we can enjoy today a living standard that our grandparents could not imagine. For example, a country with high productivity level can produce more output with its inputs compared to a country with low productivity. This “more” in output means wealth and high living standard. The project contributes to this context because of several reasons. First, it provides insights into optimal investment levels. This is crucial for companies. Firms do not want to invest too little and forgo opportunities or invest too much and waste resources that can otherwise be used more profitably. Second, the project contributes to the understanding about why and how firms choose to invest a specific amount. Understanding the decision-making processes behind these investments and their effects helps firms and policymakers foster productivity improvements in the service sector.
The overall objectives of this action are:
i) To develop and estimate a dynamic model of firm investment decision in the service industries to assess the role of R&D and worker skills investments on firm longrun performance and provide insights on the firm’s investment decision-making process
ii) To participate in training activities that help me become a distinguished internally recognized scholar in empirical innovation economics.
Investigating productivity, how to facilitate the growth is important because productivity growth is the reason we can enjoy today a living standard that our grandparents could not imagine. For example, a country with high productivity level can produce more output with its inputs compared to a country with low productivity. This “more” in output means wealth and high living standard. The project contributes to this context because of several reasons. First, it provides insights into optimal investment levels. This is crucial for companies. Firms do not want to invest too little and forgo opportunities or invest too much and waste resources that can otherwise be used more profitably. Second, the project contributes to the understanding about why and how firms choose to invest a specific amount. Understanding the decision-making processes behind these investments and their effects helps firms and policymakers foster productivity improvements in the service sector.
The overall objectives of this action are:
i) To develop and estimate a dynamic model of firm investment decision in the service industries to assess the role of R&D and worker skills investments on firm longrun performance and provide insights on the firm’s investment decision-making process
ii) To participate in training activities that help me become a distinguished internally recognized scholar in empirical innovation economics.
The project was structured as four work packages (WPs).
WP1 focuses on studying the effects of firm investments like R&D and worker training on productivity. It looks at how these investments impact labor productivity and the productivity of other inputs in the service sector. The research reveals that worker training and R&D investment allow companies to use their workforce more efficiently.
WP2 involves modeling and estimating the levels of investment in R&D and professional development training. This work is designed to measure the long-term benefits and costs of these investments and helps in evaluating how firms might react to subsidy programs before they are implemented. This part of the project develops a dynamic model of firm investment, outlines estimation steps and includes programming codes for estimating model parameters and investment levels.
WP3 covers the training and knowledge transfer for the researcher. The researcher has participated in nine intensive training workshops aimed at developing skills in communication, leadership and networking. The fellow has also attended conferences and seminars to interact with other researchers, assumed a leadership role within the department, led a task force on diversity and interdisciplinarity, and taken on a co-supervision role for PhD students. During this period, the researcher earned a university teaching qualification, received an award for efforts in promoting technology-enhanced education, secured the Elinor Ostrom Grant to support female researchers at Maastricht University, received the NWO Starter Grant at Maastricht University, and initiated new collaborations on topics related to AI and productivity. The researcher also invited guest researchers to the department.
WP4 is about disseminating the research findings. The researcher has organized a conference to bring together experts in the field and will present the project results. The fellow has moderated roundtables and engaged young students in scientific projects through internships or incorporating research questions into educational activities and assisting other researchers in writing grant proposals.
WP1 focuses on studying the effects of firm investments like R&D and worker training on productivity. It looks at how these investments impact labor productivity and the productivity of other inputs in the service sector. The research reveals that worker training and R&D investment allow companies to use their workforce more efficiently.
WP2 involves modeling and estimating the levels of investment in R&D and professional development training. This work is designed to measure the long-term benefits and costs of these investments and helps in evaluating how firms might react to subsidy programs before they are implemented. This part of the project develops a dynamic model of firm investment, outlines estimation steps and includes programming codes for estimating model parameters and investment levels.
WP3 covers the training and knowledge transfer for the researcher. The researcher has participated in nine intensive training workshops aimed at developing skills in communication, leadership and networking. The fellow has also attended conferences and seminars to interact with other researchers, assumed a leadership role within the department, led a task force on diversity and interdisciplinarity, and taken on a co-supervision role for PhD students. During this period, the researcher earned a university teaching qualification, received an award for efforts in promoting technology-enhanced education, secured the Elinor Ostrom Grant to support female researchers at Maastricht University, received the NWO Starter Grant at Maastricht University, and initiated new collaborations on topics related to AI and productivity. The researcher also invited guest researchers to the department.
WP4 is about disseminating the research findings. The researcher has organized a conference to bring together experts in the field and will present the project results. The fellow has moderated roundtables and engaged young students in scientific projects through internships or incorporating research questions into educational activities and assisting other researchers in writing grant proposals.
This research has pushed the frontier in studying the impact of firm investments on productivity, with a particular emphasis on worker training in service industries. It examines various types of investments and their effects on different production factors, while also highlighting specifics that are unique to the service sector.
In the service sector, worker training plays an important role. The amount firm spent on training tend to be small, but even these small investments can have significant impacts on firm productivity. This insight is crucial for policymakers when focusing more on programs that encourage worker training. As a result, firms are likely to place a greater emphasis on the skills of their workforce, encouraging firms and workers to invest in their skills development. In societies where lifelong learning are valued, there is a stronger ability to adapt to changes, leading to increased resilience and sustainable growth.
Engaging researchers from different fields and involving young students in research can boost the appeal and acceptance of this field. Demonstrating that skilled workers and training are valuable to companies hence higher wages for employees. This also enhances the public's perception of economics as fields that are relevant to everyday life.
In the service sector, worker training plays an important role. The amount firm spent on training tend to be small, but even these small investments can have significant impacts on firm productivity. This insight is crucial for policymakers when focusing more on programs that encourage worker training. As a result, firms are likely to place a greater emphasis on the skills of their workforce, encouraging firms and workers to invest in their skills development. In societies where lifelong learning are valued, there is a stronger ability to adapt to changes, leading to increased resilience and sustainable growth.
Engaging researchers from different fields and involving young students in research can boost the appeal and acceptance of this field. Demonstrating that skilled workers and training are valuable to companies hence higher wages for employees. This also enhances the public's perception of economics as fields that are relevant to everyday life.