The Experts below are selected from a list of 312 Experts worldwide ranked by ideXlab platform

Santanu Roy - One of the best experts on this subject based on the ideXlab platform.

  • optimality of ramsey euler policy in the Stochastic Growth Model
    Journal of Economic Theory, 2017
    Co-Authors: Tapan Mitra, Santanu Roy
    Abstract:

    Abstract For the canonical one sector Stochastic optimal Growth Model, we outline a new set of conditions for a policy function that satisfies the Ramsey–Euler equation to be optimal. An interior Ramsey–Euler policy function is optimal if, and only if, it is continuous or alternatively, if, and only if, both consumption and investment are non-decreasing in output. In particular, we show that under these conditions, the Stochastic paths generated by the policy must satisfy the transversality condition; the implication is that in applying our result, one does not need to verify the transversality condition when checking for optimality of a policy function.

  • Optimality of Ramsey–Euler policy in the Stochastic Growth Model
    Journal of Economic Theory, 2017
    Co-Authors: Tapan Mitra, Santanu Roy
    Abstract:

    Abstract For the canonical one sector Stochastic optimal Growth Model, we outline a new set of conditions for a policy function that satisfies the Ramsey–Euler equation to be optimal. An interior Ramsey–Euler policy function is optimal if, and only if, it is continuous or alternatively, if, and only if, both consumption and investment are non-decreasing in output. In particular, we show that under these conditions, the Stochastic paths generated by the policy must satisfy the transversality condition; the implication is that in applying our result, one does not need to verify the transversality condition when checking for optimality of a policy function.

Andrea Veglio - One of the best experts on this subject based on the ideXlab platform.

  • The shade avoidance syndrome: a non-Markovian Stochastic Growth Model.
    Journal of theoretical biology, 2010
    Co-Authors: Andrea Veglio
    Abstract:

    Plants at high population density compete for light, showing a series of physiological responses known as the shade avoidance syndrome. These responses are controlled by the synthesis of the hormone auxin, which is regulated by two signals, an environmental one and an internal one. Considering that the auxin signal induces plant Growth after a time lag, this work shows that plant Growth can be Modelled in terms of an energy-like function extremization, provided that the Markov property is not applied. The simulated height distributions are bimodal and right skewed, as in real community of plants. In the case of isolated plants, theoretical Growth dynamics and speed correctly fit Arabidopsis thaliana experimental data reported in literature. Moreover, the Growth dynamics of this Model is shown to be consistent with the biomass production function of an independent Model. These results suggest that memory effects play a non-negligible role in plant Growth processes.

  • The shade avoidance syndrome: a non-markovian Stochastic Growth Model
    arXiv: Other Quantitative Biology, 2010
    Co-Authors: Andrea Veglio
    Abstract:

    Plants at high population density compete for light, showing a series of physiological responses known as the shade avoidance syndrome. These responses are controlled by the synthesis of the hormone auxin, which is regulated by two signals, an environmental one and an internal one. Considering that the auxin signal induces plant Growth after a time lag, this work shows that plant Growth can be Modelled in terms of an energy-like function extremization, provided that the Markov property is not applied. The simulated height distributions are bimodal and right skewed, as in real community of plants. In the case of isolated plants, the theoretical expressions for the Growth dynamics and the Growth speed excellently fit experimental data for Arabidopsis thaliana. Moreover, the Growth dynamics of this Model is shown to be consistent with the biomass production function of an independent Model. These results suggest that memory effects play a non-negligible role in plant Growth processes.

Noah Williams - One of the best experts on this subject based on the ideXlab platform.

  • Small Noise Asymptotics for a Stochastic Growth Model
    Journal of Economic Theory, 2004
    Co-Authors: Noah Williams
    Abstract:

    Abstract We develop analytic asymptotic methods to characterize time-series properties of nonlinear dynamic Stochastic Models. We focus on a Stochastic Growth Model which is representative of the Models underlying much of modern macroeconomics. Taking limits as the Stochastic shocks become small, we derive a functional central limit theorem, a large deviation principle, and a moderate deviation principle. These allow us to calculate analytically the asymptotic distribution of the capital stock, and to obtain bounds on the probability that the log of the capital stock will differ from its deterministic steady-state level by a given amount. This latter result can be applied to characterize the probability and frequency of large business cycles. We then illustrate our theoretical results through some simulations. We find that our results do a good job of characterizing the Model economy, both in terms of its average behavior and its occasional large cyclical fluctuations.

  • Small Noise Asymptotics for a Stochastic Growth Model
    SSRN Electronic Journal, 2003
    Co-Authors: Noah Williams
    Abstract:

    In this paper we develop analytic asymptotic methods to characterize time series properties of nonlinear dynamic Stochastic Models. We focus on a Stochastic Growth Model which is representative of the Models underlying much of modern macroeconomics. Taking limits as the Stochastic shocks become small, we derive a functional central limit theorem, a large deviation principle, and a moderate deviation principle. These allow us to calculate the asymptotic distribution of the capital stock, and to obtain bounds on the probability that the log of the capital stock will differ from its deterministic steady state level by a given amount. This latter result can be applied to characterize the probability and frequency of large business cycles. We then illustrate our theoretical results through some simulations. We find that our results do a good job of characterizing the Model economy, both in terms of its average behavior and its occasional large cyclical fluctuations.

Tapan Mitra - One of the best experts on this subject based on the ideXlab platform.

  • optimality of ramsey euler policy in the Stochastic Growth Model
    Journal of Economic Theory, 2017
    Co-Authors: Tapan Mitra, Santanu Roy
    Abstract:

    Abstract For the canonical one sector Stochastic optimal Growth Model, we outline a new set of conditions for a policy function that satisfies the Ramsey–Euler equation to be optimal. An interior Ramsey–Euler policy function is optimal if, and only if, it is continuous or alternatively, if, and only if, both consumption and investment are non-decreasing in output. In particular, we show that under these conditions, the Stochastic paths generated by the policy must satisfy the transversality condition; the implication is that in applying our result, one does not need to verify the transversality condition when checking for optimality of a policy function.

  • Optimality of Ramsey–Euler policy in the Stochastic Growth Model
    Journal of Economic Theory, 2017
    Co-Authors: Tapan Mitra, Santanu Roy
    Abstract:

    Abstract For the canonical one sector Stochastic optimal Growth Model, we outline a new set of conditions for a policy function that satisfies the Ramsey–Euler equation to be optimal. An interior Ramsey–Euler policy function is optimal if, and only if, it is continuous or alternatively, if, and only if, both consumption and investment are non-decreasing in output. In particular, we show that under these conditions, the Stochastic paths generated by the policy must satisfy the transversality condition; the implication is that in applying our result, one does not need to verify the transversality condition when checking for optimality of a policy function.

Claudio Floris - One of the best experts on this subject based on the ideXlab platform.

  • First-passage time study of a Stochastic Growth Model
    Nonlinear Dynamics, 2019
    Co-Authors: Claudio Floris
    Abstract:

    In this paper, a Stochastic nonlinear Growth Model is proposed, which can be considered a generalization of the Stochastic logistic Model. It can be applied to the Growth of a generic population as well as to the propagation of the fracture in engineering materials. The excitation is assumed to be a stationary Gaussian white noise Stochastic process, which affects the system parametrically. A preliminary study of the Stochastic differential equation governing the Model reveals that there is a phase transition when the nonlinearity parameter c reaches one: when $$c 1 . In any case, the numerical analyses show that the survival probability decays fast.

  • First-passage time study of a Stochastic Growth Model
    Nonlinear Dynamics, 2019
    Co-Authors: Claudio Floris
    Abstract:

    In this paper, a Stochastic nonlinear Growth Model is proposed, which can be considered a generalization of the Stochastic logistic Model. It can be applied to the Growth of a generic population as well as to the propagation of the fracture in engineering materials. The excitation is assumed to be a stationary Gaussian white noise Stochastic process, which affects the system parametrically. A preliminary study of the Stochastic differential equation governing the Model reveals that there is a phase transition when the nonlinearity parameter c reaches one: when $$c