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Microsimulating farm business performance

Record type: Article

Microsimulation of business performance based on sample survey data is a relatively underdeveloped field, but its application in government economic policy formulation is potentially great since it can be used to measure the distributional effects of change rather than just average change. Techniques which account for the dynamic response of businesses to macro level price expectations have recently been developed (Kokic et al., 1993). These allow individual level business performance to be forecast from sample survey data. In this paper we outline a general methodology for combining these forecasting techniques with Monte Carlo simulation in order to produce a microsimulation of business performance that accurately captures the true distributional characteristics of the underling survey data. Applying this methodology to Australian farm survey data, we show that these methods may be used to forecast the distribution of farm business production and performance within arbitrary subdomains of the surveyed population conditional on a given set of expected commodity price outcomes. The microsimulations reflect both the uncertainty due to climatic variation from one year to the next, which in the Australian context depends largely on geographic location, as well as the uncertainty of commodity prices.

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Citation

Kokic, P., Chambers, R. and Beare, S. (1997) Microsimulating farm business performance University of Southampton, Department of Social Statistics Technical Report, (3), p. 11.

More information

Published date: 1997
Keywords: expectile regression, kernel smoothing, M-quantile regression, performance measurement, supply modelling

Identifiers

Local EPrints ID: 34171
URI: http://eprints.soton.ac.uk/id/eprint/34171
PURE UUID: 78234a21-96ed-4570-82e3-eae29ab36af6

Catalogue record

Date deposited: 21 Aug 2008
Last modified: 17 Jul 2017 15:51

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Contributors

Author: P. Kokic
Author: R. Chambers
Author: S. Beare

University divisions


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