The Conditional Beta Distribution as a Stochastic Production Function

Nelson, Carl H.; Preckel, Paul V.

doi:10.2307/1241595

Cited by 169 publications

(87 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Out of the 38 distribution functions fitted, 12 were Weibull, 11 Triangular, 4 Gamma, 7 BetaGeneral, 2 Logistic and lastly, 2 Logistic distributions. Such distributions have been proposed in earlier literature for crop yield modelling in agricultural economics (Atwood et al, 2003;Gallagher, 1987;Nelson and Preckel, 1989;Sherrick et al, 2004;Tolhurst and Ker, 2015). Results of these density fits are available from the authors upon request.…”

Section: Asymmetric Informationmentioning

confidence: 99%

Agricultural insurance policies in Spain and the EU: an analysis of existent and new risk management tools focusing on indirect risk assessment, and asymmetric information

Vera¹

View full text Add to dashboard Cite

Section: Asymmetric Informationmentioning

confidence: 99%

Agricultural insurance policies in Spain and the EU: an analysis of existent and new risk management tools focusing on indirect risk assessment, and asymmetric information

Vera¹

View full text Add to dashboard Cite

“…Thus, we assume that the random productive shocks ε follow a beta distribution. The beta distribution has the advantage of being empirically supported and popular in stochastic yield modeling at the local level (see, among others, Nelson andPreckel, 1989, Babcock andHennessy, 1996), and of having bounded support, which is computationally convenient. We assume the distribution to have shape parameters 2 and 2, which makes it unimodal at 0.5, and symmetric.…”

Section: Calibrationmentioning

confidence: 99%

Optimal food price stabilisation policy

Gouel

2013

European Economic Review

View full text Add to dashboard Cite

Classification JEL : D52; Q11; Q18This paper proposes a framework for designing optimal food price stabilisation policies in a self-sufficient developing country. It uses a rational expectations storage model with risk-averse consumers and incomplete markets. Government stabilises food prices by carrying public stock and by applying a state-contingent subsidy/tax to production. The policy rules are designed to maximise intertemporal welfare. The optimal policy under commitment crowds out all private stockholding activity by removing the profit opportunity from speculation. The countercyclical subsidy/tax to production helps price stabilisation by subsidising production in periods of scarcity and by taxing it in periods of glut. It contributes little to welfare gains, most of which come from stabilisation achieved through public storage.Cet article propose un cadre d'analyse de politique optimale de stabilisation des prix alimentaires dans un pays en développement auto-suffisant. Il utilise un modèle de stockage à anticipations rationnelles avec des consommateurs averses au risque et des marchés incomplets. Le gouvernement stabilise les prix alimentaires par du stockage public et en appliquant une règle contingente de subvention/taxe à la production. Les règles de décision publique sont conçues pour maximiser le bien-être. La politique optimale avec engagement de l'état évince toute activité de stockage privé du fait qu'elle réduit les opportunités de profit spéculatif. La subvention/taxe contracyclique à la production aide à la stabilisation des prix en subventionnant la production en période de rareté et en la taxant en période d'abondance. Elle contribue peu aux gains de bien-être, qui proviennent majoritairement de la stabilisation apportée par le stockage public

show abstract

“…In other words, the distribution is then "conditional" on the value of economic variables, shifting the distribution over time as economic variables change. I adopt the approach of Nelson and Preckel (1989), utilizing the conditional beta distribution to model the probability distribution of population density individually for each of the sixteen EPPA regions. Nelson and Preckel (1989) demonstrated the broad application of the conditional beta distribution by using it to model the probability distribution of agricultural output, estimating a stochastic production function and allowing the shape-parameters of the distribution of output to be functions of economic variables (i.e.…”

Section: Empirical Models and Datamentioning

confidence: 99%

“…As Nelson and Preckel (1989) point out, the functions α(Z) and β(Z) must be consistent with the regularity conditions for maximum likelihood estimation. In addition, "…arguments for simplicity and parsimony might justify linear or log-linear functions" (p. 372).…”

Section: Empirical Models and Datamentioning

confidence: 99%

Simulating the spatial distribution of population and emissions to 2100

Asadoorian

2007

Environ Resource Econ

View full text Add to dashboard Cite

The MIT Joint Program on the Science and Policy of Global Change is an organization for research, independent policy analysis, and public education in global environmental change. It seeks to provide leadership in understanding scientific, economic, and ecological aspects of this difficult issue, and combining them into policy assessments that serve the needs of ongoing national and international discussions. To this end, the Program brings together an interdisciplinary group from two established research centers at MIT: the Center for Global Change Science (CGCS) and the Center for Energy and Environmental Policy Research (CEEPR). These two centers bridge many key areas of the needed intellectual work, and additional essential areas are covered by other MIT departments, by collaboration with the Ecosystems Center of the Marine Biology Laboratory (MBL) at Woods Hole, and by short-and long-term visitors to the Program. The Program involves sponsorship and active participation by industry, government, and non-profit organizations.To inform processes of policy development and implementation, climate change research needs to focus on improving the prediction of those variables that are most relevant to economic, social, and environmental effects. In turn, the greenhouse gas and atmospheric aerosol assumptions underlying climate analysis need to be related to the economic, technological, and political forces that drive emissions, and to the results of international agreements and mitigation. Further, assessments of possible societal and ecosystem impacts, and analysis of mitigation strategies, need to be based on realistic evaluation of the uncertainties of climate science.This report is one of a series intended to communicate research results and improve public understanding of climate issues, thereby contributing to informed debate about the climate issue, the uncertainties, and the economic and social implications of policy alternatives. Titles in the Report Series to date are listed on the inside back cover.

show abstract

The Conditional Beta Distribution as a Stochastic Production Function

Cited by 169 publications

References 12 publications

Agricultural insurance policies in Spain and the EU: an analysis of existent and new risk management tools focusing on indirect risk assessment, and asymmetric information

Agricultural insurance policies in Spain and the EU: an analysis of existent and new risk management tools focusing on indirect risk assessment, and asymmetric information

Optimal food price stabilisation policy

Simulating the spatial distribution of population and emissions to 2100

Contact Info

Product

Resources

About