Scrap Value Functions in Dynamic Decision Problems

Ikefuji, Masako; Laeven, Roger J. A.; Magnus, Jan R.; Muris, Chris

doi:10.2139/ssrn.1649990

Cited by 3 publications

(3 citation statements)

References 26 publications

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“…But the linear scrap value function has some problems. These are discussed in Ikefuji et al (2010a), where we also propose the non-linear scrap value function,…”

Section: Scrap Valuesmentioning

confidence: 99%

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Expected utility and catastrophic risk in a stochastic economy–climate model

Ikefuji

Laeven

Magnus

et al. 2020

Journal of Econometrics

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In the context of extreme climate change, we ask how to conduct expected utility analysis in the presence of catastrophic risks. Economists typically model decision making under risk and uncertainty by expected utility with constant relative risk aversion (power utility); statisticians typically model economic catastrophes by probability distributions with heavy tails. Unfortunately, the expected utility framework is fragile with respect to heavy-tailed distributional assumptions. We specify a stochastic economyclimate model with power utility and explicitly demonstrate this fragility. We derive necessary and sufficient compatibility conditions on the utility function to avoid fragility and solve our stochastic economy-climate model for two examples of such compatible utility functions. We further develop and implement a procedure to learn the input parameters of our model and show that the model thus specified produces quite robust optimal policies. The numerical results indicate that higher levels of uncertainty (heavier tails) lead to less abatement and consumption, and to more investment, but this effect is not unlimited.

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“…But the linear scrap value function has some problems. These are discussed in Ikefuji et al (2010a), where we also propose the non-linear scrap value function,…”

Section: Scrap Valuesmentioning

confidence: 99%

“…The scrap value function for both utility functions, developed in Ikefuji et al (2010a), is defined as…”

Section: Compatibility: Non-normality and Burr Utilitymentioning

confidence: 99%

Expected utility and catastrophic risk in a stochastic economy–climate model

Ikefuji

Laeven

Magnus

et al. 2020

Journal of Econometrics

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“…where β = (1 + ρ) −1 is a discount factor, ρ is a constant discount rate, r t is a state return function, p y is a constant price for yield, p P and p N denote constant prices for P and N, respectively, y t denotes an average expected yield at time t (Equation (13) is an expectation of Equation (1) for a given t), ∅ T denotes a scrap value [66], which approximates the following value of land after the production period:…”

Section: Phase V: Model Application For Economic Optimizationmentioning

confidence: 99%

Phosphorus and Nitrogen Yield Response Models for Dynamic Bio-Economic Optimization: An Empirical Approach

et al. 2018

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Nitrogen (N) and phosphorus (P) are both essential plant nutrients. However, their joint response to plant growth is seldom described by models. This study provides an approach for modeling the joint impact of inorganic N and P fertilization on crop production, considering the P supplied by the soil, which was approximated using the soil test P (STP). We developed yield response models for Finnish spring barley crops (Hordeum vulgare L.) for clay and coarse-textured soils by using existing extensive experimental datasets and nonlinear estimation techniques. Model selection was based on iterative elimination from a wide diversity of plausible model formulations. The Cobb−Douglas type model specification, consisting of multiplicative elements, performed well against independent validation data, suggesting that the key relationships that determine crop responses are captured by the models. The estimated models were extended to dynamic economic optimization of fertilization inputs. According to the results, a fair STP level should be maintained on both coarse-textured soils (9.9 mg L −1 a −1 ) and clay soils (3.9 mg L −1 a −1 ). For coarse soils, a higher steady-state P fertilization rate is required (21.7 kg ha −1 a −1 ) compared with clay soils (6.75 kg ha −1 a −1 ). The steady-state N fertilization rate was slightly higher for clay soils (102.4 kg ha −1 a −1 ) than for coarse soils (95.8 kg ha −1 a −1 ). This study shows that the iterative elimination of plausible functional forms is a suitable method for reducing the effects of structural uncertainty on model output and optimal fertilization decisions.

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Expected Utility and Catastrophic Risk in a Stochastic Economy-Climate Model

Ikefuji

Laeven

Muris³

et al. 2010

SSRN Journal

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Expected Utility and Catastrophic Risk in a Stochastic Economy-Climate ModelIkefuji, M.; Laeven, R.J.A.; Magnus, J.R.; Müris, C.H.M. General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.-Users may download and print one copy of any publication from the public portal for the purpose of private study or research -You may not further distribute the material or use it for any profit-making activity or commercial gain -You may freely distribute the URL identifying the publication in the public portal Take down policyIf you believe that this document breaches copyright, please contact us providing details, and we will remove access to the work immediately and investigate your claim. Chris MurisCentER, Tilburg University * We are grateful to Graciela Chichilnisky, John Einmahl, Reyer Gerlagh, Johan Eyckmans, Sjak Smulders, Peter Wakker, Aart de Zeeuw, Amos Zemel, and seminar participants at the Tilburg Sustainability Center for helpful comments. This research was funded in part by the JSPS under grant C-22530177 (Ikefuji) and by the NWO under grant Vidi-2009 (Laeven). E-mail addresses: ikefuji@iser.osaka-u.ac.jp (Ikefuji), r.j.a.laeven@uvt.nl (Laeven), magnus@uvt.nl (Magnus), chrismuris@gmail.com (Muris). Abstract: In the context of extreme climate change, we ask how to conduct expected utility analysis in the presence of catastrophic risks. Economists typically model decision making under risk and uncertainty by expected utility with constant relative risk aversion (power utility); statisticians typically model economic catastrophes by probability distributions with heavy tails. Unfortunately, the expected utility framework is fragile with respect to heavy-tailed distributional assumptions. We specify a stochastic economyclimate model with power utility and explicitly demonstrate this fragility. We derive necessary and sufficient compatibility conditions on the utility function to avoid fragility and solve our stochastic economy-climate model for two examples of such compatible utility functions. We further develop and implement a procedure to learn the input parameters of our model and show that the model thus specified produces quite robust optimal policies. The numerical results indicate that higher levels of uncertainty (heavier tails) lead to less abatement and consumption, and to more investment, but this effect is not unlimited.JEL Classification: D81; Q5.

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Scrap Value Functions in Dynamic Decision Problems

Cited by 3 publications

References 26 publications

Expected utility and catastrophic risk in a stochastic economy–climate model

Expected utility and catastrophic risk in a stochastic economy–climate model

Phosphorus and Nitrogen Yield Response Models for Dynamic Bio-Economic Optimization: An Empirical Approach

Expected Utility and Catastrophic Risk in a Stochastic Economy-Climate Model

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