Melbourne Business School - Theses
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ItemEssays on structural transformation of Australia's economy( 2021)Structural transformation is a dynamic long-run process of resource reallocation within an economy, resulting in changes to industry shares of total employment. This thesis develops general equilibrium and dynamic economic and econometric models to identify and quantitatively assess the relative importance of factors underlying structural transformation in Australia between 1960 and 2018. These factors include non homothetic preferences (demand side) and relative industry technology changes (supply-side). The first general equilibrium model is of a small open economy with four industries: agriculture, mining, services, and an aggregation of manufacturing and construction. Three underlying factors drive structural transformation: a demand-side factor through non homothetic preferences, a supply side factor through relative industry technology changes, and world-determined output price changes. Comparative static analysis and model simulations reveal that for the services industry and the manufacturing/construction industry, non homotheticity of preferences is the dominant factor for explaining structural transformation. For agriculture and mining, the most influential factor underlying structural transformation is output price changes on world markets. The second general equilibrium model builds on the first by introducing dynamics through capital investment and international borrowing and lending. There are two sectors: a traded goods sector and a non traded services sector. Equilibrium is characterised through a social planner solution. Model simulations suggest both demand side and supply side factors are important in determining structural transformation in Australia, with the demand-side factor relatively more influential. The thesis then considers more atheoretical models based on recent approaches to dynamic stochastic econometrics. The econometric analysis covers five industries: agriculture, construction, mining, manufacturing, and services. For each industry, a vector error correction model is estimated, consisting of the industry share of total employment, industry relative prices (supply-side factor), and aggregate real household consumption per capita (the demand side factor). A structural vector error correction model is also identified, specified, and estimated. The results suggest that supply-side shocks are important for explaining the movement of the services industry’s share of total employment, which contrasts with the findings of the general equilibrium modelling where the demand-side factor dominates. Demand-side shocks are likewise the dominant factor for agriculture and mining, while nominal shocks (transitory deviations of relative hours from their long run level) are dominant for construction and manufacturing. The COVID-19 pandemic may have a long-lasting impact on industry shares of total employment. A scenario analysis based on the VECM model suggests a third COVID 19 wave would result in a positive long run effect on agriculture’s share of total employment, a negative effect on mining, and no significant long-run effects on the remaining industries. A second scenario of a vaccine-led recovery in 2021 followed by the emergence of a vaccine-resistant strain in 2022, shows a pronounced negative impact on the construction industry’s share of total employment in both the short and long-run. Agriculture and services also experience negative effects in the immediate term while the mining and manufacturing industry shares of total employment fall over the long-run.