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Global Finance

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What are the key topics in public finance and budgeting, how have they changed, and what future topics should professionals and practitioners research more closely?

Ken Chen and two of his former doctoral students, Xiang Zhao at Syracuse University and Boyuan Zhao at Florida International University, technique – Structural Theme Modeling (STM) – to identify these themes and their dynamics over the past 40 years. topic Recently published in the journal Public Budgeting and Finance.

Using STM, Chen and his colleagues identified 15 hidden themes in the public budget, public finance and public sectors. From the titles and abstracts of 1,028 articles published in the journal from 1981 to 2020. They compared these topics with those covered in the Certified Public Finance Officers (CPFO) standardized exams and found a great deal of overlap. However, some topics that are mentioned less frequently may point to research agendas in PB&F.

Chen, an associate professor of public management and policy in the Andrew Young School of Policy Studies, directs the college’s Ph.D. I program . After presenting the research at the Next Generation Public Finance Conference hosted by Georgia State University, he received helpful feedback and comments for which he is grateful. In the Q&A that followed, Chen revealed more about the journal, the results, and his motivation for conducting the study with his colleagues.

What inspired you to study this?

The journal was 40 years old, so we wanted to do something to celebrate its anniversary, a review of the journal’s history. Another reason is that the methodology we used, machine learning, was new to this publication. Traditionally, articles were reviewed manually. We used technology to conduct smart reviews.

And more importantly, doctoral students sometimes come to me and ask if I understand what the big trends in the field are. They should master it in their first year, so they ask me about the overall landscape of public budgeting and finance: What are the current hot topics in the field? With this study we can look back 40 years and, more importantly for doctoral students, through its recent history to determine trends.

Where did you get the idea to use machine learning and text mining to find trends and themes?

When I came to Georgia State, I was using AYSPS to promote our Digital Landscape Initiative. So for analytics, I thought, “Oh, great! This is a great method, and the school wants us to use it.”

Other fields use machine learning to analyze large data sets—engineering, science, and technology—but to our understanding, ours is one of the first research efforts to apply machine learning and text mining methods to public budgets and Introduced in the field of finance. That’s what we’re all about, using ideas from other disciplines and applying them to our own discipline.

What key trends did your research reveal?

The first and most important thing I should mention is the practitioners. The journal was founded to promote the exchange of knowledge between practitioners and scholars. We found that, historically, we were seeing less and less of this exchange from practitioners publishing in journals. We need to foster more engagement with practitioners. And we need doctoral students to better understand a practitioner’s perspective on the field.

Our findings have important implications for assisting scholars, practitioners, and students of government budgeting and finance in keeping track of the overall landscape of this literature. It is useful in gaining in-depth understanding of research areas and helping them to form collaborations between researchers with different specializations.

This research may be useful in developing new topics of study for doctoral students and others. We need to do more research on public budgeting and finance in relation to future big challenges such as health care, technology and climate change. These are key areas that we can research in public finance and budgeting to help society address these challenges.

Why is your analysis important? Who will it affect?

First, it is vital that students, practitioners, and scholars know both the big picture and the evolution of the field. It is even more important to think about the future direction of this public budget and finance research and the areas we need to spend more time studying in the future.

In addition, many practitioners were writing academic papers on the journal’s early history and in public budgeting and finance. Now, it is very difficult to find those people—practitioners—writing and publishing. But this is a very practical field, so scholars need to think about how to write articles that better represent the field and practice, and collaborate with experts to foster this exchange of knowledge. Do the work.

More information:
Can Chen et al, Machine Learning Meets Journal of Public Budgeting and Finance: Themes and Trends Over 40 Years, Public Budgeting and Finance (2023). DOI: 10.1111/pbaf.12348

Reference: Q&A: Machine Learning Model Tracks Trends in Public Finance Research (2024, February 16) Accessed 17 February 2024 at https://phys.org/news/2024-02-qa-machine-tracks-trends.html Obtained from

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