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‘A MAP OF THE WORLD that does not include Utopia is not worth glancing at’ wrote Oscar Wilde. ‘It leaves out the one country at which humanity is always landing. And when it lands there it looks out and, seeing a better country, sets sail again. Progress is the realization of Utopias’.
IN the two years since the last Farnborough Air Show was held by the Society of British Aerospace Companies the aircraft industry has achieved an almost complete…
IN the two years since the last Farnborough Air Show was held by the Society of British Aerospace Companies the aircraft industry has achieved an almost complete metamorphosis from the body blows in the form of major programme cancellations that almost felled it in 1965 to the very healthy position that it holds today.
Measurement of diminishing or divergent cross section dispersion in a panel plays an important role in the assessment of convergence or divergence over time in key economic indicators. Econometric methods, known as weak σ-convergence tests, have recently been developed (Kong, Phillips, & Sul, 2019) to evaluate such trends in dispersion in panel data using simple linear trend regressions. To achieve generality in applications, these tests rely on heteroskedastic and autocorrelation consistent (HAC) variance estimates. The present chapter examines the behavior of these convergence tests when heteroskedastic and autocorrelation robust (HAR) variance estimates using fixed-b methods are employed instead of HAC estimates. Asymptotic theory for both HAC and HAR convergence tests is derived and numerical simulations are used to assess performance in null (no convergence) and alternative (convergence) cases. While the use of HAR statistics tends to reduce size distortion, as has been found in earlier analytic and numerical research, use of HAR estimates in nonparametric standardization leads to significant power differences asymptotically, which are reflected in finite sample performance in numerical exercises. The explanation is that weak σ-convergence tests rely on intentionally misspecified linear trend regression formulations of unknown trend decay functions that model convergence behavior rather than regressions with correctly specified trend decay functions. Some new results on the use of HAR inference with trending regressors are derived and an empirical application to assess diminishing variation in US State unemployment rates is included.
Whereas investments in new attractions continue to rise within the theme park industry, knowledge regarding the effects of new attractions on theme park performance and…
Whereas investments in new attractions continue to rise within the theme park industry, knowledge regarding the effects of new attractions on theme park performance and attendance remains scarce. In order to isolate these effects, the purpose of this paper is to present the results of an econometric study explaining the variance in theme park visitor numbers and quantifying the effects of new attractions on theme park attendance.
The paper is based on an econometric study, in which models were produced for four European theme parks. No pooled modelling was used, meaning that four different models were created; one for each participating theme park. Various variables affecting theme park attendance were identified and quantified, and subsequently the effects of new attractions on visitor numbers were isolated.
Findings indicate that all new attractions opened at Park D during the research period have had a positive long‐term influence on attendance. This positive influence lasted for no more than two years. No significant short‐term influence was found. There were significant differences in effect between new attractions which could not yet be explained.
The research by design only takes into account the economic effects of new attractions and disregards all environmental and socio‐cultural effects. Even though the research provides an accurate approximation of the effects of new attractions on attendance, this effect should, according to the author, not be perceived as a stand‐alone effect yet as a part of a complex system. A situational approach taking into account several other situational as well as qualitative factors would do the complex reality more justice than a, even though effective, simplified and general approach.
Industry operators can now use the econometric model presented in this paper to determine the effects of new attractions on their theme park's attendance and use this knowledge to further fine‐tune their investment policy.
The paper presents the first econometric model successful at isolating and quantifying a new attraction's effect on theme park attendance and can thus be a valuable tool in perfecting one's investment policy. The paper furthermore includes a brief introduction to a situational approach of determining a new attraction's effects on theme park performance.
We provide a new characterization of the equality of two positive-definite matrices A and B, and we use this to propose several new computationally convenient statistical…
We provide a new characterization of the equality of two positive-definite matrices A and B, and we use this to propose several new computationally convenient statistical tests for the equality of two unknown positive-definite matrices. Our primary focus is on testing the information matrix equality (e.g. White, 1982, 1994). We characterize the asymptotic behavior of our new trace-determinant information matrix test statistics under the null and the alternative and investigate their finite-sample performance for a variety of models: linear regression, exponential duration, probit, and Tobit. The parametric bootstrap suggested by Horowitz (1994) delivers critical values that provide admirable level behavior, even in samples as small as n = 50. Our new tests often have better power than the parametric-bootstrap version of the traditional IMT; when they do not, they nevertheless perform respectably.
This paper considers a class of parametric models with nonparametric autoregressive errors. A new test is established and studied to deal with the parametric specification…
This paper considers a class of parametric models with nonparametric autoregressive errors. A new test is established and studied to deal with the parametric specification of the nonparametric autoregressive errors with either stationarity or nonstationarity. Such a test procedure can initially avoid misspecification through the need to parametrically specify the form of the errors. In other words, we estimate the form of the errors and test for stationarity or nonstationarity simultaneously. We establish asymptotic distributions of the proposed test. Both the setting and the results differ from earlier work on testing for unit roots in parametric time series regression. We provide both simulated and real-data examples to show that the proposed nonparametric unit root test works in practice.
There is a growing literature in nonparametric econometrics in the recent two decades. Given the space limitation, it is impossible to survey all the important recent developments in nonparametric econometrics. Therefore, we choose to limit our focus on the following areas. In Section 2, we review the recent developments of nonparametric estimation and testing of regression functions with mixed discrete and continuous covariates. We discuss nonparametric estimation and testing of econometric models for nonstationary data in Section 3. Section 4 is devoted to surveying the literature of nonparametric instrumental variable (IV) models. We review nonparametric estimation of quantile regression models in Section 5. In Sections 2–5, we also point out some open research problems, which might be useful for graduate students to review the important research papers in this field and to search for their own research interests, particularly dissertation topics for doctoral students. Finally, in Section 6 we highlight some important research areas that are not covered in this paper due to space limitation. We plan to write a separate survey paper to discuss some of the omitted topics.
The purpose of this paper is to analyze the fat, saturated fatty acid and trans fatty acid contents in ready-to-eat foods distributed at amusement parks to develop an…
The purpose of this paper is to analyze the fat, saturated fatty acid and trans fatty acid contents in ready-to-eat foods distributed at amusement parks to develop an appropriate food safety management system for children.
In all, 322 ready-to-eat food samples categorized into 17 types were collected from nine Korean amusement parks and their fat, saturated fatty acid and trans fatty acid contents were assessed.
Fat, saturated fatty acid and trans fatty acid contents were relatively high in flour-based products. On the basis of the Korea Food and Drug Administration classification, the samples in 12 categories were classified as high-fat foods. The samples in nine categories were classified as high-saturated fatty acid foods. Most samples also contained non-negligible levels of trans fatty acids. The fat, saturated fatty acid and trans fatty acid contents of samples even in the same category varied markedly.
This research will inform the necessity of an appropriate safety management system for ready-to-eat foods distributed at amusement.
Although the fat contents of foods distributed around school area were often observed, the potential risk of those in ready-to-eat foods distributed at amusement parks have rarely been assessed. As patterns of food intakes vary world-widely, a periodic monitoring data like this study may be useful for international organizations and researchers.