The Estimation of Supply Response in Australian Agriculture: The Cresh/ Creth Production System

Vincent, David; Dixon, Peter; Powell, Andrew

doi:10.2307/2526250

Cited by 44 publications

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“…To a large extent, the results depend on the estimates of transformation and hence cross-price elasticities between product groups in each zone. These parameter estimates proved reasonably robust; see Vincent et al (1980) for details. The weakest part of the story is obviously the assumption (forced upon us by the limitations of the data base for estimation) that commodities are produced in fixed proportions in the "other products" group.…”

Section: High Rainfall Zonementioning

confidence: 82%

“…For technical reasons, the reduced form was not used for the other two zones. Fora detailed discussion see Vincent et al (1980). wool and sheep are considerably less than those of the two other product categories distinguished.…”

Section: High Rainfall Zonementioning

confidence: 98%

“…CRETH generalizes CET in the same way as CRESH generalizes CES. See Hanoch (1971) for CRESH, Powell and Gruen (1968) for CET, Arrow et al (1961) for CES and Vincent et al (1980) for CRETH.…”

Section: Theoretical Specificationmentioning

confidence: 99%

“…(22a)'). Unfortunately, the time-series data on which the estimation of the relevant transformation frontiers was based were not detailed enough to support an econometric analysis of the transformation behavior of components of the other products categories; see Vincent et al (1980).…”

Section: Outputsmentioning

confidence: 99%

“…As explained above, to date the CRETH system has been estimated only for the first three agricultural industries, that is for the three BAE zones. Details of the econometric work and various alternative presentations of the results can be found in Vincent et al (1980). Here we draw heavily on that source to present the results of the analysis for each zone as an asymmetric matrix of own-and cross-price elasticities of supply.…”

Section: Transfonnation Parameters and Supply Elasticitiesmentioning

confidence: 99%

See 4 more Smart Citations

Modeling Growing Economies in Equilibrium and Disequilibrium

Landau¹,

Kelley²,

Sanderson³

et al. 1984

Southern Economic Journal

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v PREFACEDuring the 1960s and early 1970s multisectoral models developed along two distinct paths.In the first tradition, "systems" models of global growth (e .g., Meadows et aI., 1972) dealt with cumulative interactions among sectors, and showed that resource-intensive rapid growth would result in economic collapse, and, worse yet, that the world would not recognize the catastrophe before it occurred. These models possessed no prices to encourage resource saving, nor did they induce technological change to augment supply, both of which would attenuate or eliminate the predicted catastrophe. At the same time, there appeared a set of increasingly complex planning models, characterized by highly disaggregated inputoutput structures, and focusing on "internal-consistency" compromises to reconcile various demand and supply imbalances implied by the process of economic growth (for a review, see Blitzer et al., 1975). Here too, little attention was paid to how these inconsistencies could be reconciled without invoking ad hoc government policies to ameliorate their consequences.A second and quite different tradition began with the pioneering study by Johanson (l959); in his general equilibrium model, price adjustments reconcile demand and supply and optimal resource allocation is generated endogenously without the intervention of ad hoc policy.The 1970s saw an explosion of complex multisectoral growth models in the first tradition. They incorporated fairly rigid technological relations, utilized large and expanding data bases, and relied extensively on computers for their solution and analysis. These complex models stressed sectoral detail and did not dwell on the actions of the economic agents that in the real world tie these sectors together into a viable political economy. Rather, governments largely represented the agents responsible for setting goals and "reconciling" perceived shortages or glu ts of commodities and factors. These models were expanding black boxes with thousands of equations and an even larger number of parameters designed to guide the policy makers in aggregate economic management.The first tradition had its detractors and many scholars were beginning to recognize the possibility that complex government planning models were yielding diminishing returns: their data requirements were excessive; they highlighted limited choices rather than flexible tradeoffs; they demanded sophisticated control systems to implement their objectives; and they were unreliable in predicting the future course of economic events (see , for a review ofsome of these models). At the same time, macroeconomic theory was being treated with increasing skepticism, and scholars showed an increasing interest in the microeconomic foundations of the aggregate economy (for a review, see Weintraub, 1977).The stage was set to move back toward the second tradition, to simpler general equilibrium models, which highlight specifications of microeconomic behavior. For modeling market economies this meant increased attention to the role of p...

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Section: High Rainfall Zonementioning

confidence: 82%

Section: High Rainfall Zonementioning

confidence: 98%

Section: Theoretical Specificationmentioning

confidence: 99%

Section: Outputsmentioning

confidence: 99%

Section: Transfonnation Parameters and Supply Elasticitiesmentioning

confidence: 99%

See 3 more Smart Citations

Modeling Growing Economies in Equilibrium and Disequilibrium

Landau¹,

Kelley²,

Sanderson³

et al. 1984

Southern Economic Journal

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show abstract

Response to price and production risk: The case of Australian wheat

Rambaldi

Simmons

2000

J. Fut. Mark.

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A model of Australian wheat grower supply response was specified under the constrainsts of price and yield uncertainty, risk aversion, partial adjustment, and quadratic costs. The model was solved to obtain area planted. The results of estimation indicate that risk arising from prices and climate have had a significant influence on producer decision making. The coefficient of relative risk aversion and short‐run and long‐run elasticities of supply with respect to price were calculated. Wheat growers' risk premium, expected at the start of the season for exposed price and yield risk, was 2.8 percent of revenue or 10.4 percent of profit as measured by producer surplus. © 2000 John Wiley & Sons, Inc. Jrl Fut Mark 20: 345–359, 2000.

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Forecasting small-area agricultural incomes using a CGE model of the Australian economy

Higgs

Powell

1990

Ann Reg Sci

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The Estimation of Supply Response in Australian Agriculture: The Cresh/ Creth Production System

Cited by 44 publications

References 0 publications

Modeling Growing Economies in Equilibrium and Disequilibrium

Modeling Growing Economies in Equilibrium and Disequilibrium

Response to price and production risk: The case of Australian wheat

Forecasting small-area agricultural incomes using a CGE model of the Australian economy

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