Evaluating Research Policy in Australian Broadacre Agriculture - Accounting for Interactions between the Beef, Sheep Meat, Wool, and Grains Industries. This project studies the returns from R&D investments in Australia's broadacre agricultural industries and equity in the funding of these investments. The contribution is to explicitly recognise the interaction across cattle, sheep and cropping enterprises, while past analyses have been single industry approach. Econometric models of multi-output ....Evaluating Research Policy in Australian Broadacre Agriculture - Accounting for Interactions between the Beef, Sheep Meat, Wool, and Grains Industries. This project studies the returns from R&D investments in Australia's broadacre agricultural industries and equity in the funding of these investments. The contribution is to explicitly recognise the interaction across cattle, sheep and cropping enterprises, while past analyses have been single industry approach. Econometric models of multi-output profit function for Australian broadacre agriculture and demand systems involving these products are estimated. A multi-industry equilibrium displacement model is developed to simulate the incidence of both costs and returns of agricultural R&D, with cross-industry interaction recognised. The project is likely to contribute to the way agricultural research is administered and funded in Australia.Read moreRead less
New Approaches to the Analysis of Count Time Series. The focus of this proposal is on the analysis of data that enumerate events over time. Occurrences of such count data abound in economics and business, examples being observations on insurance claims, loan defaults and individual product demand. This project develops a suite of innovative methods for modelling and predicting event counts. The methods explicitly accommodate both the discreteness of the data and possible complexities in its evo ....New Approaches to the Analysis of Count Time Series. The focus of this proposal is on the analysis of data that enumerate events over time. Occurrences of such count data abound in economics and business, examples being observations on insurance claims, loan defaults and individual product demand. This project develops a suite of innovative methods for modelling and predicting event counts. The methods explicitly accommodate both the discreteness of the data and possible complexities in its evolution over time. In so doing, they enable both accurate inferences regarding the dynamic structure of the data to be drawn and accurate forecasts of future event counts to be produced.Read moreRead less