What is it about?

Ever since Glickman first cooked up the idea of mixing input-output (IO) analysis with econometric models, it's become a hot topic in the research world. People love it because it's a forecasting superstar and can give us fairly accurate predictions. This study dives into three ways of mixing IO analysis and econometric modeling: embedded, coupled, and linked. We put these approaches to the test using the Illawarra economy as our econ lab. We even throw in a fun scenario of moving around government spending to see which sectors create the most jobs. It's like a forecasting showdown to find the most reliable approach. You can find all the juicy details in this paper that we contributed to the International Symposium of Next Generation Infrastructure proceedings.

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Why is it important?

It's important because combining input-output analysis with econometric models is like bringing together two powerhouses that can unlock valuable insights about the economy. This integration allows us to make more accurate predictions and assess the impact of policies on various sectors. By understanding which sectors generate the most jobs for each dollar of government expenditure, policymakers can better allocate resources to drive economic growth and maximize employment opportunities. This research helps us make smarter decisions that can strengthen regional economies and improve the well-being of individuals and communities.

Perspectives

As part of my PhD research, writing this article was an incredibly fulfilling journey. It allowed me to contribute to the limited research on regional economics in Australia, which was both exciting and rewarding. This experience also encouraged me to pursue a postdoc research, and deepen my interest in econometric modelling.

Dr Ashkan Masouman
University of Ottawa

Read the Original

This page is a summary of: Incorporating Time-Series Into an Interindustry Analysis to Model the Regional Economic Structure: A Case Study of the Illawarra, January 2014, University of Wollongong Library,
DOI: 10.14453/isngi2013.proc.31.
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Contributors

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