An Applied Procedure for Estimating and Simulating Multivariate Empirical (MVE) Probability Distributions In Farm-Level Risk Assessment and Policy Analysis

Richardson, James W.; Klose, Steven L.; Gray, Allan W.

doi:10.1017/s107407080002037x

Cited by 181 publications

(110 citation statements)

References 6 publications

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“…The Monte Carlo method (Richardson and Mapp 1976;Richardson et al 2000) can be used to sample the results of the stochastic distribution generated by the stochastic budget model and create a visual representation of the probability cases created by the stochastic budget. In this study, 10 000 iterations of the Monte Carlo method were run.…”

Section: Revenue Budget and Risk Simulationmentioning

confidence: 99%

The effects of spring versus summer calving on beef cattle economic performance in western Canada

et al. 2015

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. 2015. The effects of spring versus summer calving on beef cattle economic performance in western Canada. Can. J. Anim. Sci. 95: 475Á486. The choice of calving date influences the net revenue of a calving operation as it affects the number of days that calves spend in each feeding phase and when they are subsequently marketed. These two factors determine the costs, revenue, and risk (variance) of each calving system for the calving phase of a beef system. The majority of cowÁcalf producers in western Canada have adopted early calving (EC) in spring due to management factors. However, late calving (LC) in the summer is an alternative beef calving system associated with higher returns due to lower system costs and higher beef prices. It may offer a better match between cow nutritional requirements and pasture availability. The objective of this study was to compare the revenues and risks for a traditional EC system and an alternative LC system at three sites in western Canada. Biological and economic data from three field experimental sites in western Canada (Brandon Research Centre in Manitoba, Western Beef Development Centre in Lanigan, Saskatchewan and Semi-Arid Prairie Agriculture Research Centre in Swift Current, Saskatchewan) were used to determine the costs and benefits of the alternative beef calving system. The results showed that even though the EC has higher cost than the LC, the EC is slightly better than LC in terms of higher net revenue potential, but it comes at a greater risk due to higher revenue variances. The EC system is usually more preferable for risk-neutral producers, whereas the LC system is more preferable for risk-averse producers. Les effets du veˆlage au printemps par rapport au veˆlage a`l'e´te´sur la performance e´conomique des bovins de boucherie dans l'ouest du Canada. Can. J. Anim. Sci. 95: 475Á486. Le choix de la date de veˆlage influence le revenu net d'un e´tablissement de veˆlage puisqu'il a un effet sur le nombre de jours que les veaux passent dans chaque phase d'alimentation ainsi que leur mise en marche´par la suite. Ces deux facteurs de´terminent les couˆts, le revenu et le risque (variance) de chaque syste`me pour la phase de veˆlage chez les bovins de boucherie. La majorite´des producteurs de vaches-veaux de l'ouest du Canada ont adopte´le veˆlage pre´coce (EC Á « early calving ») au printemps pour accommoder des facteurs de gestion. Par contre, le veˆlage tardif (LC Á « late calving ») a`l'e´te´est un syste`me alternatif de veˆlage des bovins associe´s a`des rendements plus e´leve´s imputable aux couˆts plus faibles et une hausse des prix du baeuf. Il pourrait offrir un meilleur accommodement entre les besoins nutritionnels des bovins et la disponibilite´des paˆturages. L'objectif de cette e´tude e´tait de comparer les revenus et les risques des syste`mes traditionnels EC et syste`mes alternatifs LC a`trois sites dans l'ouest du Canada. Les donne´es biologiques et e´conomiques de trois sites d'expe´riences sur le terrain dans l'ouest du Canada (le Centre de Recherche d...

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Section: Revenue Budget and Risk Simulationmentioning

confidence: 99%

The effects of spring versus summer calving on beef cattle economic performance in western Canada

et al. 2015

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“…The stochastic budgeting procedure, on the other hand, allows the decision maker (DM) to assess the probability of failure or success of an enterprise before committing resources to a project. Since in reality, outcomes always change, the stochastic budget helps in obviating some of the shortcomings of the deterministic budget, by accounting for uncertainties and providing distributions of outcomes (Richardson et al, 2000). The stochastic budgeting model was programmed in Excel® and simulated using Simetar® through a three step process.…”

Section: Harvesting and Transportation Costsmentioning

confidence: 99%

An economic viability assessment of sisal production and processing in Limpopo: A stochastic budgeting analysis

Dlamini¹,

Verschoor²,

Tshabalala³

2014

J. Dev. Agric. Econ.

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Creating sustainable jobs in the agricultural sector is an important aspect of rural development. Agriculture is often viewed as a sine qua non for rural development, because it provides the necessary economic stimulus for rural households to participate in productive economic activities. Yet, identifying viable agricultural projects that have the potential to create jobs in rural areas has continued to overwhelm policymakers. In this paper, the economic feasibility of sisal production and processing in Limpopo province is analysed. The study was motivated by the sisal crop's proven abilities to create many jobs and the growing appeal that natural fibres are currently receiving globally. Using both a deterministic and stochastic budget, this paper shows that sisal production and processing could be a viable investment in Limpopo. However, given the high costs of labour, investors are cautioned to look for community partnerships in order to spread the economic costs and benefits of sisal production and processing in Limpopo.

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“…One way to undertake such smoothing is to use the multivariate kernel density estimation procedure, proposed by Richardson et al (2006). The procedure is a smoothed multivariate distribution extension of the multivariate empirical (MVE) distribution estimate procedure described by Richardson et al (2000). The procedure uses a kernel density estimation (KDE) function to smooth the limited sample data of variables in a system individually, and then the dependencies present in the sample are used to model the system via use of a copula.…”

Section: Data Smoothingmentioning

confidence: 99%

“…The resulting continuous probability distribution for each random variable smoothed out the irregularities caused by small samples. Correlations between activity net revenues were derived directly from the historical data and used to simulate the kernel distributions as a multivariate distribution using the MVE procedure described by Richardson et al (2000).…”

Section: States Of Nature Datamentioning

confidence: 99%

Risk programming analysis with imperfect information

et al. 2009

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A Monte Carlo procedure is used to demonstrate the dangers of basing (farm) risk programming on only a few states of nature and to study the impact of applying alternative risk programming methods. Two risk programming formulations are considered, namely mean-variance (E,V) programming and utility efficient (UE) programming. For the particular example of a Norwegian mixed livestock and crop farm, the programming solution is unstable with few states, although the cost of picking a sub-optimal plan declines with increases in number of states. Comparing the E,V results with the UE results shows that there were few discrepancies between the two and the differences which do occur are mainly trivial, thus both methods gave unreliable results in cases with small samples.

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An Applied Procedure for Estimating and Simulating Multivariate Empirical (MVE) Probability Distributions In Farm-Level Risk Assessment and Policy Analysis

Cited by 181 publications

References 6 publications

The effects of spring versus summer calving on beef cattle economic performance in western Canada

The effects of spring versus summer calving on beef cattle economic performance in western Canada

An economic viability assessment of sisal production and processing in Limpopo: A stochastic budgeting analysis

Risk programming analysis with imperfect information

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