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	Provedor de dados AgEcon (2) Autor Hennessy, David A. (1) Rambaldi, Alicia N. (1) Roosen, Jutta (1) Zapata, Hector O. (1) Palavra-chave Likelihood ratio (2) Research Methods/ Statistical Methods (2) Affiliation (1) Auction (1) Causality tests (1) Cointegration (1) Monte Carlo Experiments (1) Order-restricted inference (1) Stochastic order (1) Wald statistic (1) Mais... Tipo do documento Working or Discussion Paper (2) Ano 2003 (1) 1996 (1) País United States (2) Idioma Inglês (2)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 2 Primeira ... 1 ... Última TESTING FOR THE MONOTONE LIKELIHOOD RATIO ASSUMPTION AgEcon Roosen, Jutta; Hennessy, David A.. Monotonicity of the likelihood ratio for conditioned densities is a common technical assumption in economic models. But we have found no empirical tests for its plausibility. This paper develops such a test based on the theory of order-restricted inference, which is robust with respect to the correlation structure of the distributions being compared. We apply the test to study the technology revealed by agricultural production experiments. For the data under scrutiny, the results support the assumption of the monotone likelihood ratio. In a second application, we find some support for the assumption of affiliation among bids cast in a multiple-round Vickrey auction for a consumption good. Tipo: Working or Discussion Paper Palavras-chave: Affiliation; Auction; Likelihood ratio; Order-restricted inference; Stochastic order; Research Methods/ Statistical Methods. Ano: 2003 URL: http://purl.umn.edu/18398 MONTE CARLO EVIDENCE ON COINTEGRATION AND CAUSATION AgEcon Zapata, Hector O.; Rambaldi, Alicia N.. The small sample performance of Granger causality tests under different model dimensions, degree of cointegration, direction of causality, and system stability are presented. Two tests based on maximum likelihood estimation of error-correction models (LR and WALD) are compared to a Wald test based on multivariate least squares estimation of a modified VAR (MWALD). In large samples all test statistics perform well in terms of size and power. For smaller samples, the LR and WALD tests perform better than the MWALD test. Overall, the LR test outperforms the other two in terms of size and power in small samples. Tipo: Working or Discussion Paper Palavras-chave: Causality tests; Cointegration; Likelihood ratio; Wald statistic; Monte Carlo Experiments; Research Methods/ Statistical Methods. Ano: 1996 URL: http://purl.umn.edu/31690 Registros recuperados: 2 Primeira ... 1 ... Última

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