An econometric approach to measuring productivity: Australia as a case study
dc.contributor.author | Agbenyegah, Benjamin K. | |
dc.contributor.supervisor | Assoc. Prof. Gary Kerr | |
dc.contributor.supervisor | Prof. Harry Bloch | |
dc.date.accessioned | 2017-01-30T09:47:20Z | |
dc.date.available | 2017-01-30T09:47:20Z | |
dc.date.created | 2008-05-14T04:43:49Z | |
dc.date.issued | 2007 | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/219 | |
dc.description.abstract |
Seminal papers of Solow (1957) and Swan (1956) stimulated debate among economists on the role of technical change in productivity improvements and for that matter economic growth. The consensus is that technological change accounts for a significant proportion of gross national product (GNP) growth in industrialised economies. In the case of Australia, the aggregate productivity performance was poor in the 1970s and 1980s, but picked up very strongly by the 1990s, and was above the OECD average growth level for the first time in its productivity growth history. However, this high productivity growth rate could not be sustained and Australia started to experience a slowdown in productivity growth since 2000. This study empirically measures the performance of productivity in Australia’s economy for the period 1950-2005, using an econometric approach. Time-series data are used to develop econometric models that capture the dynamic interactions between GDP, fixed capital, labour units, human capital, foreign direct investment (FDI) and information and communication technology (ICT). The Johansen (1988) cointegration techniques are used to establish a long-run steady-state relation between or among economic time series. The econometric analysis pays careful attention to the time-series properties of the data by conducting unit root and conintegration tests for the variables in the system.This study finds that Australia experienced productivity growth in the 1950s, a slow down in the mid 1960s, a very strong productivity growth in the mid 1990s and another slowdown from 2000 onwards. The study finds evidence that human capital, FDI and ICT are very strong determinants of long-run GDP and productivity growth in Australia. The study finds that the three, four and the five factor models are likely to give better measures of productivity performance in Australia as these models recognise human capital, FDI and ICT and include them as separate factors in the production function, This study finds evidence that the previous studies on the Australia’s productivity puzzle have made a very significant omission by not considering human capital, FDI and ICT as additional exogenous variables and by excluding them from the production function for productivity analysis. | |
dc.language | en | |
dc.publisher | Curtin University | |
dc.subject | FDI | |
dc.subject | Granger casuality | |
dc.subject | human capital | |
dc.subject | ICT | |
dc.subject | technical change | |
dc.subject | total factor productivity | |
dc.subject | forecast error variance decomposition | |
dc.subject | cointegration | |
dc.subject | impulse response analysis | |
dc.title | An econometric approach to measuring productivity: Australia as a case study | |
dc.type | Thesis | |
dcterms.educationLevel | PhD | |
curtin.thesisType | Traditional thesis | |
curtin.department | School of Economics and Finance | |
curtin.identifier.adtid | adt-WCU20071112.132724 | |
curtin.accessStatus | Open access |