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The Effect of the Japan 2011 Disaster on Nuclear and Alternative Energy Stocks Worldwide: An Event Study

Ferstl, Robert; Utz, Sebastian; Wimmer, Maximilian - In: BuR - Business Research 5 (2012) 1, pp. 25-41

This event study investigates the impact of the Japanese nuclear disaster in Fukushima-Daiichi on the daily stock prices of French, German, Japanese, and U.S. nuclear utility and alternative energy firms. Hypotheses regarding the (cumulative) abnormal returns based on a three-factor model are...

Persistent link: https://www.econbiz.de/10010421368

Changes in the technical and scale efficiency of rice production activities in the Mekong delta, Vietnam

Tung, Diep Thanh - In: Agricultural and Food Economics 1 (2013), pp. 1-16

I used bootstrapping data envelopment analysis (DEA) to measure changes in technical and scale efficiency in rice production in the Mekong delta region, Vietnam. The data include sample production sets from 1998 and bi-annual updates from 2002 to 2010. Technical efficiency changed significantly...

Persistent link: https://www.econbiz.de/10010500527

On comparison of stochastic reserving methods with bootstrapping

Tee, Liivika; Käärik, Meelis; Viin, Rauno - In: Risks 5 (2017) 1, pp. 1-21

, bootstrap method is considered. In the bootstrapping framework, we discuss the choice of residuals, namely the Pearson residuals …

Persistent link: https://www.econbiz.de/10011709580

Testing for a set of linear restrictions in VARMA models using autoregressive metric: An application to Granger causality test

DiIorio, Francesca; Triacca, Umberto - In: Econometrics 2 (2014) 4, pp. 203-216

In this paper we propose a test for a set of linear restrictions in a Vector Autoregressive Moving Average (VARMA) model. This test is based on the autoregressive metric, a notion of distance between two univariate ARMA models, M0 and M1, introduced by Piccolo in 1990. In particular, we show...

Persistent link: https://www.econbiz.de/10011755267

Asymptotic distribution and finite sample bias correction of QML estimators for spatial error dependence model

Liu, Shew Fan; Yang, Zhenlin - In: Econometrics 3 (2015) 2, pp. 376-411

In studying the asymptotic and finite sample properties of quasi-maximum likelihood (QML) estimators for the spatial linear regression models, much attention has been paid to the spatial lag dependence (SLD) model; little has been given to its companion, the spatial error dependence (SED) model....

Persistent link: https://www.econbiz.de/10011755286

On bootstrap inference for quantile regression panel data: A Monte Carlo study

Galvão Júnior, Antônio Fialho; Montes-Rojas, Gabriel - In: Econometrics 3 (2015) 3, pp. 654-666

This paper evaluates bootstrap inference methods for quantile regression panel data models. We propose to construct … confidence intervals for the parameters of interest using percentile bootstrap with pairwise resampling. We study three different … bootstrapping procedures. First, the bootstrap samples are constructed by resampling only from cross-sectional units with …

Persistent link: https://www.econbiz.de/10011755298

Größe ist nicht alles – Die Effizienz der kommunalen Leistungserstellung am Beispiel Sachsen-Anhalts

Haug, Peter; Illy, A. - In: Wirtschaft im Wandel 17 (2011) 10, pp. 347-355

Befürworter von Gemeindegebietsreformen – wie z. B. der erst kürzlich beendeten Reform in Sachsen-Anhalt – erwarten von Gemeindezusammenlegungen und zentralisierten Verwaltungsformen (Einheitsgemeinde statt Verwaltungsgemeinschaft) Kosteneinsparungen bzw. Effizienzsteigerungen bei der...

Persistent link: https://www.econbiz.de/10011502008

Bootstrap methods for inference in the Parks model

Moundigbaye, Mantobaye; Messemer, Clarisse; Parks, … - In: Economics: The Open-Access, Open-Assessment E-Journal 14 (2020) 2020-4, pp. 1-18

This paper shows how to bootstrap hypothesis tests in the context of the Parks's (1967) Feasible Generalized Least … Squares estimator. It then demonstrates that the bootstrap outperforms FGLS(Parks)'s top competitor. The FGLS(Parks) estimator …

Persistent link: https://www.econbiz.de/10012160886

Novel Approach to Choosing Principal Components Number in Logistic Regression

Vrigazova, Borislava - In: ENTRENOVA - ENTerprise REsearch InNOVAtion 7 (2021) 1, pp. 1-12

contribution of each principal component to the total variance of the target variable. A combination of possible important … principal components can be chosen to explain a big part of the variance in the target. Sometimes several combinations of … the bootstrap procedure for model selection. We call this procedure the Bootstrapped-ANOVA PCA selection. Our results …

Persistent link: https://www.econbiz.de/10013336908