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3 edition of Dynamic commodity models: specification, estimation, and simulation found in the catalog.

Dynamic commodity models: specification, estimation, and simulation

Walter C. Labys

Dynamic commodity models: specification, estimation, and simulation

  • 273 Want to read
  • 17 Currently reading

Published by Lexington Books in Lexington, Mass .
Written in English

    Subjects:
  • Commercial products -- Mathematical models.,
  • Coconut oil.,
  • Palm oil.

  • Edition Notes

    Bibliography: p. 272-309.

    Other titlesCommodity models.
    Statement[by] Walter C. Labys.
    Classifications
    LC ClassificationsHF1040.7 .L32
    The Physical Object
    Paginationxvii, 351 p.
    Number of Pages351
    ID Numbers
    Open LibraryOL5410472M
    ISBN 100669818771
    LC Control Number73000986

    1. “The Dynamics of Price Discovery,” with Bingchen Yan, and “Simulation-Based Estimation of Stochastic Volatility Models” presented at the Machine Learning in Finance Workshop (part of the Neural Information System Processing Conference), Whistler BC, December. 2.   The authors study the transmission of business cycle fluctuations for developed (N) to developing economies (S) with a two-country, asymmetric, dynamic stochastic general equilibrium (DSGE) model with endogenous development of new technologies in N, and sunk costs of exporting and transferring the production of the intermediate goods to S.   Summary. High‐dimensional non‐stationary time series, which reveal both complex trends and stochastic behaviour, occur in many scientific fields, e.g. macroecoCited by: 8.


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Dynamic commodity models: specification, estimation, and simulation by Walter C. Labys Download PDF EPUB FB2

Dynamic commodity models: specification, estimation, and simulation [Walter C Labys] on *FREE* shipping on qualifying by: Get this from a library.

Dynamic commodity models: specification, estimation, and simulation. [Walter C Labys] -- Estimation with the theory and methods required for specifying, estimating, validating, and applying commodity models which describe behavior of a quarterly or annual nature, though certain. An Integrated Exhaustible Resource Model of Copper Market Dynamics.

Authors; Authors and affiliations W.C. (), Dynamic Commodity Models: Specification, Estimation and simulation book Simultation, Heath Lexington Books U.S. Bureau of Mines (), Joint Aluminium/Copper Forecasting and Simulation Model, Final Report and Appendices A and B, Open File Cited by: 2.

Dynamic commodity models: specification, estimation, and simulation avg rating — 0 ratings — published Want to Read Dynamic commodity models: specification /5. Abstract. Problems of resources, energy and regional planning need to be solved within a strong analytical framework.

This has given rise to a number of modeling approaches or methodologies which can analyze problems, test policies and make forecasts of estimation : Walter C.

Labys. Read "Econometric modelling of agricultural commodity markets, D. Hallam, Routledge, London and New York, ISBN 0‐‐‐5, cloth, $ Pp. iii +Journal of Applied Econometrics" on DeepDyve, the largest online rental service for scholarly research with thousands of academic publications available at your fingertips.

Indonesia is one of the mineral rich and simulation book countries in the world. Indonesia has Dynamic commodity models: specification large quantity of mineral resources such as natural oil and gas, hard minerals (metallic, estimation metallic/industrial mineral, coal, and stone), because it is located in the Pacific ring of fire.

Mineral and energy commodities have always been giving contribution to And simulation book Domestic Product (GDP) of Indonesia. Estimation role of leads in the dynamic OLS estimation of cointegrating regression models Article in Mathematics and Computers in Simulation 79(3) December with Reads.

Downloadable. We present a method to estimate jointly the parameters of a standard commodity storage model and the parameters characterizing the trend in commodity prices.

This procedure allows the influence of Dynamic commodity models: specification possible trend to be removed without restricting the model specification, and allows Dynamic commodity models: specification and trend selection Dynamic commodity models: specification on statistical criteria.

Downloadable (with restrictions). We study the finite-sample properties of some of the standard techniques used to estimate modern term structure models.

For sample sizes and models similar to those used in most empirical work, we reach three surprising conclusions. First, while maximum likelihood works well for simple models, it produces strongly biased parameter estimates when the model Cited by: The models were utilized using monthly data from January to December as estimation period, providing a total of observations and data was used as an ex-post forecasts.

The book fulfills, to some extent, both of these requirements because of its division into two parts. Part 1 (chapters 2) includes more general information on the model.

Part 2 (chapters ) Dynamic commodity models: specification details on modelling different sectors of the British economy discussed in Author: Lucja Tomaszewicz.

the dynamic Dynamic commodity models: specification is Nerlove's geometric lag model. This model is based on 4 Labys, Walter C., Dynamic Commodity Models: Specification, Estimation, and Simulation, and simulation book, Massachusetts: Lexington Books), Griliches, Zvi, "Estimates of the Aggregate U.S.

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ROBERT S. PINDYCK is the Mitsubishi Bank Professor in Economics and Finance in the Sloan School of Management at M.I.T. He is also a Research Associate of the National Bureau of Economic Research, and a Fellow of the Econometric Society, and has been.

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This general specification nests the constant elasticity of variance, stochastic volatility, stochastic interest rate, and jump-diffusion models. Most attention has focussed upon Black and Scholes () assumption of geometric Brownian motion: with σ and r assumed constant.

Excluded from consideration are option pricing models with jumps in the. Book Description. Commodity Modeling and Pricing provides extensions and applications of state-of-the-art methods for analyzing resource commodity behavior.

Drawing from the seminal work of Professor Walter Labys on the development of econometric methods for forecasting commodity prices, this collection of essays features expert contributors ranging from practitioners in private industry. A time series is a series of data points indexed (or listed or graphed) in time order.

Most commonly, a time series is a sequence taken at successive equally spaced points in time. Thus it is a sequence of discrete-time data. Examples of time series are heights of ocean tides, counts of sunspots, and the daily closing value of the Dow Jones Industrial Average.

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However, models with the disturbances that are prominently non-normally distributed and contain sizeable outliers fail estimation by the Least Squares method. An intensive research has established that in such cases estimation by the Least Absolute Deviation (LAD) method performs well.

Monte Carlo simulation: Drawing a large number of pseudo-random uniform variables from the interval [0,1] at one time, or once at many different times, and assigning values less than or equal to as heads and greater than as tails, is a Monte Carlo simulation of the behavior of.

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