A Monte Carlo Study on the Fit of a Cost Function by a Fourier Flexible Functional Form*
نویسندگان
چکیده
We use the simulation model ofCbalfallt and Gallant (IUS5) to investigate the fit of a Fourier flexible form to a cost function when interest is t.o estimate elasticities of substitution. The data is subject to errors in variables and the estimation method is seemingly unrelated regressions. \IVe use two approximating Fourier functional forms * Hesearch supported by C:-IPq ** Banco do Brasil, C .. dec Prcsidencia, BrasIlia DF *** Enbrapa and Thpartmrento de Estatlstica! UnB, BrasfliaD F R. d e Economctria Rio d e Janeiro v. 15,119 2, pp.:n�54 Novembro/?vlar<;o 1996 A Monte Carlo study on the fit of a'cost function with 13 (1'1'1'13) and 22 (1'1'1'22) parameters. The biases in point estimation are negligible for 1'1'1'13. The classical t statistics do not follow, in general, the Student's distribution. Even when estimates are properly centered and scaled there are cases where the normal approximation does not hold. Palavras-Chave: Flexible forms, fador demand systems, translog cost function, Fourier flexible form, estimation of elasticities C6digo J EL: C15, D21
منابع مشابه
محاسبه کارایی بانکهای ایران با استفاده از شکل تبعی انعطافپذیر جامع فوریر و تحمیل شرایط نظم نظری
This paper tries to provide an estimate of efficiency in eight Iranian banks, namely, Melli, Saderat, Mellat, Tejarat, Sepah, Refah, Keshavarzi and Maskan during 1996-2008, using the globally flexible Fourier Cost Functional Form and imposing theoretical regularities, discussed in Neoclassic microeconomic theory. One of the efficiency estimation methods is to estimate the cost function of ...
متن کاملComparison of the performances of neural networks specification, the Translog and the Fourier flexible forms when different production technologies are used
This paper investigates the performances of artificial neural networks approximation, the Translog and the Fourier flexible functional forms for the cost function, when different production technologies are used. Using simulated data bases, the author provides a comparison in terms of capability to reproduce input demands and in terms of the corresponding input elasticities of substitution esti...
متن کاملProject Time and Cost Forecasting using Monte Carlo simulation and Artificial Neural Networks
The aim of this study is to present a new method to predict project time and cost under uncertainty. Assuming that what happens in projects implementation which is expressed in the form of Earned Value Management (EVM) indicators is primarily related to the nature of randomness or unreliability, in this study, by using Monte Carlo simulation, and assuming a specific distribution for the time an...
متن کاملOn the Canonical-Based Goodness-of-fit Tests for Multivariate Skew-Normality
It is well-known that the skew-normal distribution can provide an alternative model to the normal distribution for analyzing asymmetric data. The aim of this paper is to propose two goodness-of-fit tests for assessing whether a sample comes from a multivariate skew-normal (MSN) distribution. We address the problem of multivariate skew-normality goodness-of-fit based on the empirical Laplace tra...
متن کاملEconomic optimization of solar systems in uncertain economic conditions using the Monte Carlo method
Solar energy is an environmentally sustainable energy source as it is clean and inexhaustible. Solar systems are very common and cost-effective, thus, can be used for many home applications. In this paper, a new method is presented to optimize solar systems economically, regarding to energy cost fluctuations. In spite of conventional analyses, in which the inflation is considered constant, ...
متن کامل