What is it about?
The integration of input–output and econometric models at regional level has gained popularity for its superior performance in forecasting employment and examining the impacts of policies. There are a number of approaches to integrate the two models. This paper examines the integration of input–output with econometric modelling using two merging methodologies, namely coupling and holistic embedding. Each methodology is analyzed with respect to the accuracy of the results of total and sectoral employment forecasting. Both methodologies are applied to a regional economy in Australia. The methodology which shows superior forecasting accuracy is applied to examine the significance of sectors that generate the highest number of employments relative to other sectors.
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Why is it important?
Combining input-output and econometric models at the local level helps us predict job trends and understand how policies shape our economy. This study explores two approaches, "coupling" and "holistic embedding," to see which one does a better job at forecasting overall and sector-specific employment. When we know which sectors are the job creators, policymakers can craft smart strategies to make them even stronger. It's all about building a thriving economy that benefits everyone!
Perspectives
This is the last article that was associated with my PhD research. The aim was to generate some practical implications and excitement about seemingly dry and abstract areas such as input-output economics and econometrics. It highlights the relevance and impact of understanding regional economies and employment forecasting. Ultimately, the article strives to provoke thought and engage readers in these significant topics.
Dr Ashkan Masouman
University of Ottawa
Read the Original
This page is a summary of: Forecasting, impact analysis and uncertainty propagation in regional integrated models: A case study of Australia, Environment and Planning B Urban Analytics and City Science, April 2018, SAGE Publications,
DOI: 10.1177/2399808318767128.
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