A nonlinear approach to testing the unit root null hypothesis : an application to international health expenditures

In this article, we examine the unit root null hypothesis for per capita total Health Expenditures (HEs), per capita private HEs and per capita public HEs for 29 Organization for Economic Co-operation and Development (OECD) countries. The novelty of our work is that we use a new nonlinear unit root test that allows for one structural break in the data series. We find that for around 45% of the countries, we are able to reject the unit root hypothesis for each of the three HE series. Moreover, using Monte Carlo simulations, we show that our proposed unit root model has better size and power properties than the widely used Augmented Dickey–Fuller (ADF) and Lagrange Multiplier (LM) type tests.

Energy consumption at the state level: the unit root null hypothesis from Australia

In this paper, our goal is to examine the unit root null hypothesis in energy consumption for Australian states and territory. We consider sectoral energy consumption for Australia and its six states and one territory using time series data for the period 1973-2007. This is the first study that does this. Generally, except for some cases in South Australia, we find strong support that shocks to energy consumption have a temporary effect on energy consumption in Australia. © 2009 Elsevier Ltd. All rights reserved.

Can Peto's paradox be used as the null hypothesis to identify the role of evolution in natural resistance to cancer? A critical review

BACKGROUND: Carcinogenesis affects not only humans but almost all metazoan species. Understanding the rules driving the occurrence of cancers in the wild is currently expected to provide crucial insights into identifying how some species may have evolved efficient cancer resistance mechanisms. Recently the absence of correlation across species between cancer prevalence and body size (coined as Peto's paradox) has attracted a lot of attention. Indeed, the disparity between this null hypothesis, where every cell is assumed to have an identical probability to undergo malignant transformation, and empirical observations is particularly important to understand, due to the fact that it could facilitate the identification of animal species that are more resistant to carcinogenesis than expected. Moreover it would open up ways to identify the selective pressures that may be involved in cancer resistance. However, Peto's paradox relies on several questionable assumptions, complicating the interpretation of the divergence between expected and observed cancer incidences. DISCUSSIONS: Here we review and challenge the different hypotheses on which this paradox relies on with the aim of identifying how this null hypothesis could be better estimated in order to provide a standard protocol to study the deviation between theoretical/theoretically predicted and observed cancer incidence. We show that due to the disproportion and restricted nature of available data on animal cancers, applying Peto's hypotheses at species level could result in erroneous conclusions, and actually assume the existence of a paradox. Instead of using species level comparisons, we propose an organ level approach to be a more accurate test of Peto's assumptions. SUMMARY: The accuracy of Peto's paradox assumptions are rarely valid and/or quantifiable, suggesting the need to reconsider the use of Peto's paradox as a null hypothesis in identifying the influence of natural selection on cancer resistance mechanisms.

Is the efficient market hypothesis day-of-the-week dependent? Evidence from the banking sector

In this article, we propose a new hypothesis: that the efficient market hypothesis is day-of-the-week-dependent. We apply the test to firms belonging to the banking sector and listed on the NYSE. We find significant evidence that the efficient market hypothesis is day-of-the-week-dependent. Overall, for only 62% of firms, the unit root null hypothesis is rejected on all the five trading days. We also discover that when investors do not account for unit root properties in devising trading strategies, they obtain spurious profits.

A panel CUSUM test of the null of cointegration

This paper proposes a simple residual-based panel CUSUM test of the null hypothesis of cointegration. The test has a limiting normal distribution that is free of nuisance parameters, it is robust to heteroskedasticity and it allows for mixtures of cointegrated and spurious alternatives. Our Monte Carlo results suggest that the test has small-size distortions and reasonable power. In our empirical application to international R&D spillovers, we present evidence suggesting that total factor productivity is heterogeneously cointegrated with foreign and domestic R&D capital stocks. © Blackwell Publishing Ltd, 2005.

Does elite competition inhibit growth and delay maturation in some gymnasts? quite possibly

Today, elite young gymnasts undertake training programs of progressive volume and intensity from an early age. For example, talented young female gymnasts often commence training at age 5 or 6 and train more than 20 to 30 hours per week year-round throughout childhood and adolescence. Despite the "normal" short stature of top-level gymnasts and the obvious health benefits of physical activity during growth, there is concern that elite level or those gymnasts involved in heavy training regimens may be at risk for adverse effects on growth and maturation. This concern has been the source of much debate in the literature and is complicated by the difficulties in distinguishing between the genetic predisposition to short stature and late or delayed maturation, and the effect of environmental factors such as nutrition and exercise that may influence growth and maturation. The effect of gymnastics training on growth and maturation is often reported as averaged data: an approach that does not identify individual growth patterns. Finding no difference between groups is not proof that there is "in fact" no difference. Accepting the null hypothesis without the appropriate critical review of both the methodological and statistical power to detect differences is a flawed endeavor. We believe there is compelling "circumstantial" evidence to build a case that preparation for advanced gymnastics competition may place some children and youth at risk of reduced growth and delayed maturation.

Forecasting inflation, industrial output and exchange rates : a template study for India

This paper reports results from a forecasting study for inflation, industrial output and exchange rates for India. We cannot reject the null hypothesis for linearity for all series used except for the growth rate of the foreign exchange series and our analysis is based on linear models, ARIMA and bivariate transfer functions and restricted VAR. Forecasting performance is evaluated using the models’ root mean-squared error differences and Theil’s inequality coefficients from recursive origin static, fixed origin dynamic and rolling origin dynamic forecasts. For models based on weekly data, based on RMSEs, we find that the bivariate models improve upon the forecasts of the ARIMA model while for models based on monthly data the ARIMA model has almost always better performance. In choosing between the two bivariate models on the basis of RMSEs, our overall results tend to support the use of a restricted VAR, as this model had the best forecasting performance more frequently than the transfer function model.

Contrasting genetic structuring between colonies of the world's smallest penguin, Eudyptula minor (Aves: Spheniscidae)

The Little Penguin, Eudyptula minor, is a seabird that nests in colonies throughout New Zealand and southern Australia. Individuals from different colonies in southeast Australia differ significantly in morphology and ecology, suggesting that some genetic structuring may exist among colonies. In contrast, the marking of individuals with flipper bands has revealed some, albeit infrequent, movement between colonies. To determine the extent of genetic structuring, we tested the null hypothesis of substantial gene flow within southeast Australia by examining patterns of genetic variation across seven colonies separated by up to 1,500 km. Phylogeographic structuring was absent for mitochondrial control region sequences (2–3 individuals per colony). Microsatellite allele frequencies at five loci and mitochondrial haplotype frequencies (50 individuals per colony) were also homogenous among the majority of colonies sampled, although two colonies at the western periphery of the sampling range were distinct from those to the east. The genetic homogeneity among the majority of colonies can be explained by low but consistent contemporary gene flow among them, or a recent founder event in Bass Strait following the last marine transgression. The genetic break towards the western end of the sampling distribution appears best explained by differences in sea surface temperature and, consequentially breeding phenology, the latter hindering genetically effective migration.

Are G7 per capita real GDP levels non-stationary, 1870–2001?

In this paper we examine whether or not G7 per capita income can be classified as a stationary process using data for over a century. The unit root null hypothesis is tested using the recently developed Lagrange multiplier test which allows for at most two structural breaks. We are able to reject the unit root null hypothesis for all the countries at the 5 percent level or better, except for Italy and Germany.

Labour productivity trends in Australian manufacturing : some time series properties

Labour productivity plays a significant role in economic growth, labour demand and employment situation of a particular economy. In this light, the presence of a structural break in productivity, and its unit root property, has important consequences for the overall economy and in major sectors such as manufacturing. In this article, using some recently developed unit root tests, we examine: (i) the null hypothesis of a unit root in the log-level of labour productivity for 38 manufacturing subdivisions against the alternative of trend stationarity over a three-decade period; and (ii) the presence of a structural break in the series, and whether the break has had a permanent or a transitory effect on manufacturing labour productivity. Our main finding is that shocks to labour productivity have had a transitory effect, implying that policies are likely to have only short-term effects.

Structural breaks and unit roots in Australian macroeconomic time series

We examine the unit root properties of 16 Australian macroeconomic time series using monthly data spanning the period 1960–2004. In addition to the standard Augmented Dickey Fuller (ADF) test, we implement one- and two-break endogenous structural break ADF-type unit root tests as well as one- and two-break Lagrange multiplier (LM) unit root tests. While the ADF test provides relatively little evidence against the unit root null hypothesis, once we allow for structural breaks we are able to reject the unit root null for just under half of the variables at the 10% level or better.

A review of cashmere nutrition experiments with suggestions for improving their design and conduct

The scientific literature contains divergent views about the effects of nutrition on cashmere. The consequences of ignoring nutrition will be an increase in the number of goats suffering lower production, increased welfare risks and premature mortality. This review evaluated published reports to identify current knowledge and best practice in regard to the design and management of cashmere nutrition experiments. The ability of experiments to distinguish between treatments was evaluated based on their statistical evidence. Many experiments had serious deficiencies in their design, conduct and reporting. Six of 16 papers did not provide statistical information that would enable a reader to verify differences between treatments. For most experiments to detect nutrition affects at P < 0.05, they required a difference between treatments of 0.2–0.8 μm in cashmere mean fibre diameter and 15–42 g in clean cashmere production. Government Research Institutes research was characterised by more experienced authors conducting longer (P < 0.05) and larger (P < 0.05) experiments than those conducted by Universities. Much of the “debate” regarding the affects of nutrition on cashmere production arises from the misinterpretation of both experiments that did not detect statistically significant effects and of experiments that did detect statistically significant effects. Based on a comparison between experiments reporting responses to nutrition with those reporting no response, 13 design and management features were identified that are related to the ability of experiments to detect significant treatment affects. Methods must be adopted to reduce the variance in cashmere production within treatments, by using sufficient animals per treatment, and having replication to provide sufficient degrees of freedom to reduce error terms in analysis. The power of experimental designs should be evaluated before experiments commence. Cashmere production records from a previous full production year could be used as co-variants during statistical analyses but this requires that potential experimental goats are managed in one flock, without variations resulting from different grazing, reproduction or other management for a year prior to an experiment. It is preferable to use more productive and older goats, and goats that are used to handling, and to the conditions and feed to be used. Allocation of animals to treatments must take into account live weight. Nutrition treatments need to be sufficiently different to produce different growth curves. An appropriate control is needed such as live weight maintenance. Evidence of both nutrition intake and growth curves must be published with cashmere production data so the claims made can be verified by the actual responses. As cashmere production is an order of magnitude less than fibre production of Merino sheep or Angora goats and is more difficult to measure, the requirements for measurement, sampling and testing cashmere fleeces are summarised. The use of mid side cashmere patches to determine cashmere growth and quality is seriously biased and must be avoided, preferably by shearing goats prior to and at the end of experiments. In order to obtain higher fleece growth responses and improve the ability of experiments to detect treatment effects it is preferable to start cashmere growth experiments by midsummer and conduct experiments for at least 4 months. These requirements make it difficult for many university students to plan, undertake and complete long-term cashmere nutrition experiments without considerable management support. It is not possible for experiments to disprove the Null hypothesis regarding the effects of nutrition on cashmere production as they can only report a failure to detect treatment effects. Researchers and journals need to be more rigorous in providing statistical information including: degrees of freedom for error terms, treatment variances, standard error of differences or similar to enable readers to compare treatment effects. Publications that do not provide sufficient statistical information should be disregarded from future discussions. Claims that an experiment shows no responses to nutrition should be subject to rigorous examination using the issues identified in this review.

Changing philosophies and tools for statistical inferences in behavioral ecology

Recent developments in ecological statistics have reached behavioral ecology, and an increasing number of studies now apply analytical tools that incorporate alternatives to the conventional null hypothesis testing based on significance levels. However, these approaches continue to receive mixed support in our field. Because our statistical choices can influence research design and the interpretation of data, there is a compelling case for reaching consensus on statistical philosophy and practice. Here, we provide a brief overview of the recently proposed approaches and open an online forum for future discussion (https://bestat.ecoinformatics.org/). From the perspective of practicing behavioral ecologists relying on either correlative or experimental data, we review the most relevant features of information theoretic approaches, Bayesian inference, and effect size statistics. We also discuss concerns about data quality, missing data, and repeatability. We emphasize the necessity of moving away from a heavy reliance on statistical significance while focusing attention on biological relevance and effect sizes, with the recognition that uncertainty is an inherent feature of biological data. Furthermore, we point to the importance of integrating previous knowledge in the current analysis, for which novel approaches offer a variety of tools. We note, however, that the drawbacks and benefits of these approaches have yet to be carefully examined in association with behavioral data. Therefore, we encourage a philosophical change in the interpretation of statistical outcomes, whereas we still retain a pluralistic perspective for making objective statistical choices given the uncertainties around different approaches in behavioral ecology. We provide recommendations on how these concepts could be made apparent in the presentation of statistical outputs in scientific papers.

A new poolability test for cointegrated panels

This paper proposes a new test of the null hypothesis that the parameters in a cointegrated panel data regression are equal across the cross-section. The asymptotic distribution of the new test statistic is derived and simulation results are provided to suggest that it performs very well in small samples. An empirical application to the monetary exchange rate model is also provided.

Interobserver reliability of classification and characterization of proximal humeral fractures: a comparison of two and three-dimensional CT

Interobserver reliability for the classification of proximal humeral fractures is limited. The aim of this study was to test the null hypothesis that interobserver reliability of the AO classification of proximal humeral fractures, the preferred treatment, and fracture characteristics is the same for two-dimensional (2-D) and three-dimensional (3-D) computed tomography (CT). Members of the Science of Variation Group--fully trained practicing orthopaedic and trauma surgeons from around the world--were randomized to evaluate radiographs and either 2-D CT or 3-D CT images of fifteen proximal humeral fractures via a web-based survey and respond to the following four questions: (1) Is the greater tuberosity displaced? (2) Is the humeral head split? (3) Is the arterial supply compromised? (4) Is the glenohumeral joint dislocated? They also classified the fracture according to the AO system and indicated their preferred treatment of the fracture (operative or nonoperative). Agreement among observers was assessed with use of the multirater kappa (κ) measure. Interobserver reliability of the AO classification, fracture characteristics, and preferred treatment generally ranged from "slight" to "fair." A few small but statistically significant differences were found. Observers randomized to the 2-D CT group had slightly but significantly better agreement on displacement of the greater tuberosity (κ = 0.35 compared with 0.30, p < 0.001) and on the AO classification (κ = 0.18 compared with 0.17, p = 0.018). A subgroup analysis of the AO classification results revealed that shoulder and elbow surgeons, orthopaedic trauma surgeons, and surgeons in the United States had slightly greater reliability on 2-D CT, whereas surgeons in practice for ten years or less and surgeons from other subspecialties had slightly greater reliability on 3-D CT. Proximal humeral fracture classifications may be helpful conceptually, but they have poor interobserver reliability even when 3-D rather than 2-D CT is utilized. This may contribute to the similarly poor interobserver reliability that was observed for selection of the treatment for proximal humeral fractures. The lack of a reliable classification confounds efforts to compare the outcomes of treatment methods among different clinical trials and reports.