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1 – 10 of over 31000In this paper we use Monte Carlo sampling experiments to examine the properties of pretest estimators in the random parameters logit (RPL) model. The pretests are for the presence…
Abstract
In this paper we use Monte Carlo sampling experiments to examine the properties of pretest estimators in the random parameters logit (RPL) model. The pretests are for the presence of random parameters. We study the Lagrange multiplier (LM), likelihood ratio (LR), and Wald tests, using conditional logit as the restricted model. The LM test is the fastest test to implement among these three test procedures since it only uses restricted, conditional logit, estimates. However, the LM-based pretest estimator has poor risk properties. The ratio of LM-based pretest estimator root mean squared error (RMSE) to the random parameters logit model estimator RMSE diverges from one with increases in the standard deviation of the parameter distribution. The LR and Wald tests exhibit properties of consistent tests, with the power approaching one as the specification error increases, so that the pretest estimator is consistent. We explore the power of these three tests for the random parameters by calculating the empirical percentile values, size, and rejection rates of the test statistics. We find the power of LR and Wald tests decreases with increases in the mean of the coefficient distribution. The LM test has the weakest power for presence of the random coefficient in the RPL model.
Fuli Li, Xin Lai and Kwok Leung
Purpose – This chapter provides an overview of multilevel modeling with a focus on the application of hierarchical linear modeling (HLM) in international management…
Abstract
Purpose – This chapter provides an overview of multilevel modeling with a focus on the application of hierarchical linear modeling (HLM) in international management research.
Findings – The key topics covered include an introduction to hierarchical linear models, how to apply appropriate hierarchical linear models to address different types of international management research questions, and six methodological issues concerning international management research with a multilevel analysis.
Originality/value – The overview of HLM and its relevance for international management research facilitates researchers to apply this powerful analytical strategy in their future research.
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William W. Cooper, Vedran Lelas and David W. Sullivan
This paper provides a theoretical framework for application of Chance-Constrained Programming (CCP) in situations where the coefficient matrix is random and its elements are not…
Abstract
This paper provides a theoretical framework for application of Chance-Constrained Programming (CCP) in situations where the coefficient matrix is random and its elements are not normally distributed. Much of the CCP literature proceeds to derive deterministic equivalent in computationally implementable form on the assumption of “normality”. However, in many applications, such as air pollution control, right skewed distributions are more likely to occur. Two types of models are considered in this paper. One assumes an exponential distribution of matrix coefficients, and another one uses an empirical approach. In case of exponential distributions, it is possible to derive exact “deterministic” equivalent to the chance-constrained program. Each row of the coefficient matrix is assumed to consist of independent, exponentially distributed random variables and a simple example illustrates the complexities associated with finding a numerical solution to the associated deterministic equivalent. In our empirical approach, on the other hand, simulated data typically encountered in air pollution control are provided, and the data-driven (empirical) solution to the implicit form of deterministic equivalent is obtained. Post-optimality analyses on model results are performed and risk implications of these decisions are discussed. Conclusions are drawn and directions for future research are indicated.
Petros Messis and Achilleas Zapranis
The purpose of this paper is to examine the predictive ability of different well-known models for capturing time variation in betas against a novel approach where the beta…
Abstract
Purpose
The purpose of this paper is to examine the predictive ability of different well-known models for capturing time variation in betas against a novel approach where the beta coefficient is treated as a function of market return.
Design/methodology/approach
Different GARCH models, the Kalman filter algorithm and the Schwert and Seguin model are used against our novel approach. The mean square error, the mean absolute error and the Diebold and Mariano test statistic constitute the measures of forecast accuracy. All models are tested over nine consecutive years and three different samples.
Findings
The results show substantial differences in predictive accuracy among the samples. The new approach of modelling the systematic risk overwhelms the rest of the models in longer samples. In the smallest sample, the Kalman filter random walk model prevails. The examination of parameters between two groups of stocks with best and worst accuracy results depicts significant variations. For these stocks, the iid assumption of return is rejected and large differences exist on diagnostic tests.
Originality/value
This study contributes to the literature with different ways. First, it examines the predictive accuracy of betas with different well-known models and introduces a novel approach. Second, after constructing betas from the estimated models’ parameters, they are used for out-of-sample instead of in-sample forecasts over nine consecutive years and three different samples. Third, a more closely examination of the models’ parameters could signal at an early stage the candidate models with the expected lowest forecasting errors. Finally, the study carries out some diagnostic tests for examining whether the existence of iid normal returns is accompanied by better performance.
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Dan Mahoney and Wesley W. Wilson
Over the past 50 years, air travel in the United States has increased from approximately 33 million passengers in 1960 to over 607 million passengers in 2007 (National…
Abstract
Over the past 50 years, air travel in the United States has increased from approximately 33 million passengers in 1960 to over 607 million passengers in 2007 (National Transportation Statistics, 2011, Table 1–40). This is over an 18-fold increase in air travel in the past five decades. Over that same time period, the number of airports increased modestly, from 15,161 in 1980 to 19,750 in 2009. The number of those airports serving public commercial traffic is even smaller, and has declined from 730 airports in 1980 to 559 in 2009 (National Transportation Statistics, 2011, Table 1–3). Together, these two facts point to phenomenal growth among airports (measured by the number of passenger trips).
Samson Yusuf Dauda and Jongsu Lee
The purpose of this paper is to evaluate the perceptions of Nigerian banking customers regarding customers’ evaluation of their banks service quality based on their banks actual…
Abstract
Purpose
The purpose of this paper is to evaluate the perceptions of Nigerian banking customers regarding customers’ evaluation of their banks service quality based on their banks actual performance on current banking service delivery.
Design/methodology/approach
A survey has been used to collect primary data and 1,245 usable questionnaires were used in the analysis. A conjoint analysis with stated preference data were used to construct the consumers’ behavior, while discrete choice method was employed to evaluate the preferences. More information was obtained by in cooperating heterogeneity into the model by the random coefficient and the test variance with the primary attributes and social demographics and individual characteristics.
Findings
Discrete choice analysis shows that bank management should focus on: reduction of transaction errors, transaction cost, waiting time and initial online learning time. This four attributes have strong impact on customer’s satisfaction depending on quality performance. Relative to other services the reduction in waiting time and transaction cost are the most important services to the Nigerian banking customers. Other findings of willingness to pay and consumer preference for other attributes reveal more information for improved banking policies.
Research limitations/implications
The sample only focussed on the urban areas and did not consider rural dwellers. Future research should aim to improve on these by including a variable in the utility set up that captures the distance of the respondent to the main city.
Practical implications
Nigerian banking customers do not care about a friendly smile as customer care. Rather, they value more on the waiting time and transaction cost showing that convenience and cost dimensions have strong and direct effect on service quality. Other dimensions identified includes, reliability, product portfolio, security and privacy, ease of use, accessibility, and competence and credibility.
Originality/value
This study has drawn on a sample of 1,245 Nigerian banking customers and evaluating how the survey respondents perceive their respective banks’ performance by their evaluation of the current banking service delivery.
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Thomas Andrén and Björn Gustafsson
This article estimates a control function estimator with training effect modelled as a random coefficient, partitioned into an observed and unobserved component. The article…
Abstract
This article estimates a control function estimator with training effect modelled as a random coefficient, partitioned into an observed and unobserved component. The article analyzes the earnings effect of participating in labor market training programs for three cohorts during the 1980s and the beginning of the 1990s. It separates the analysis between Swedish and foreign‐born to identify differences in their responses to training. The results indicate that there is positive sorting in training: slightly positive effects for both groups but somewhat larger for the foreign‐born. Further, consistent with results from several previous studies, the article finds that being young often means no positive pay‐off from training, and the same is found for persons with only a primary education. In conflict with earlier studies, the article finds that males have a better pay‐off from training than females. Rewards from training are higher for foreign‐ than for native‐born and rewards among the former vary by place of birth and how long they have been in the country.
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Bao Yong, Fan Yanqin, Su Liangjun and Zinde-Walsh Victoria
This paper examines Aman Ullah’s contributions to robust inference, finite sample econometrics, nonparametrics and semiparametrics, and panel and spatial models. His early works…
Abstract
This paper examines Aman Ullah’s contributions to robust inference, finite sample econometrics, nonparametrics and semiparametrics, and panel and spatial models. His early works on robust inference and finite sample theory were mostly motivated by his thesis advisor, Professor Anirudh Lal Nagar. They eventually led to his most original rethinking of many statistics and econometrics models that developed into the monograph Finite Sample Econometrics published in 2004. His desire to relax distributional and functional-form assumptions lead him in the direction of nonparametric estimation and he summarized his views in his most influential textbook Nonparametric Econometrics (with Adrian Pagan) published in 1999 that has influenced a whole generation of econometricians. His innovative contributions in the areas of seemingly unrelated regressions, parametric, semiparametric and nonparametric panel data models, and spatial models have also inspired a larger literature on nonparametric and semiparametric estimation and inference and spurred on research in robust estimation and inference in these and related areas.
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Ahmed S Abutaleb, Yuzo Kumasaka and Michael G Papaioannou
This paper presents a new adaptive technique for forecasting the Yen/U.S. Dollar exchange rate. The proposed method assumes a time-varying model to describe the evolution of the…
Abstract
This paper presents a new adaptive technique for forecasting the Yen/U.S. Dollar exchange rate. The proposed method assumes a time-varying model to describe the evolution of the exchange rate. Weekly predictions of the Yen/U.S. Dollar rate are dominated by weekly announcements of unexpected changes in the relative unemployment claims between the U.S. and Japan. Monthly predictions are more sensitive to monthly releases of the difference between the expected and announced value of the National Association of Purchasing Managers index. The predictive results of the proposed method are found more accurate than that of conventional ARMA techniques.