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Cellular signalling pathways, mediating receptor activity to nuclear gene activation, are generally regarded as feed forward cascades. We analyse measured data of a partially observed signalling pathway and address the question of possible feed-back cycling of involved biochemical components between the nucleus and cytoplasm. First we address the question of cycling in general, starting from basic assumptions about the system. We reformulate the problem as a statistical test leading to likelihood ratio tests under non-standard conditions. We find that the modelling approach without cycling is rejected. Afterwards, to differentiate two different transport mechanisms within the nucleus, we derive the appropriate dynamical models which lead to two systems of ordinary differential equations. To compare both models we apply a statistical testing procedure that is based on bootstrap distributions. We find that one of both transport mechanisms leads to a dynamical model which is rejected whereas the other model is satisfactory.

In applied settings, hypothesis testing when a nuisance parameter is identifiable only under the alternative often reduces to a problem of testing one hypothesis multiple times (TOHM). Specifically, a fine discretization of the space of the nonidentifiable parameter is specified, and the null hypothesis is tested against a set of sub-alternative hypotheses, one for each point of the discretization. The resulting sub-test statistics are then combined to obtain a global p-value. We propose a computationally efficient inferential tool to perform TOHM under stringent significance requirements, such as those typically required in the physical sciences, (e.g., a p-value < 10−7). The resulting procedure leads to a generalized approach to performing inferences under nonstandard conditions, including non-nested model comparisons.

This paper studies the least squares model averaging methods for two non-nested linear models. It is proved that the Mallows model averaging weight of the true model is root- n consistent. Then the authors develop a penalized Mallows criterion which ensures that the weight of the true model equals 1 with probability tending to 1 and thus the averaging estimator is asymptotically normal. If neither candidate model is true, the penalized Mallows averaging estimator is asymptotically optimal. Simulation results show the selection consistency of the penalized Mallows method and the superiority of the model averaging approach compared with the model selection estimation.

The identification of new rare signals in data, the detection of a sudden change in a trend, and the selection of competing models are among the most challenging problems in statistical practice. These challenges can be tackled using a test of hypothesis where a nuisance parameter is present only under the alternative, and a computationally efficient solution can be obtained by the \"testing one hypothesis multiple times\" (TOHM) method. In the one-dimensional setting, a fine discretization of the space of the non identifiable parameter is specified, and a global p-value is obtained by approximating the distribution of the supremum of the resulting stochastic process. In this article, we propose a computationally efficient inferential tool to perform TOHM in the multidimensional setting. Here, the approximations of interest typically involve the expected Euler characteristics (EC) of the excursion set of the underlying random field. We introduce a simple algorithm to compute the EC in multiple dimensions and for arbitrarily large significance levels. This leads to an highly generalizable computational tool to perform hypothesis testing under nonstandard regularity conditions. Supplementary materials for this article are available online.

The primary objective of the paper is twofold. , to answer the question posed in the title by arguing that the conundrums: [C1] the non-standard sampling distributions, [C2] the low power of unit-root tests for ∈ [0.9, 1], and [C3] their size distortions, [C4] issues in handling , and [C5] the framing of and in testing = 1, as well as [C6] two competing parametrizations for the AR(1) models, (B) = + + , (C) = + + + , viewing these models as aPriori Postulated (aPP) stochastic difference equations driven by the error process . , to use R.A. Fisher’s model-based statistical perspective to unveil the statistical models implicit in each of the AR(1): (B)-(C) models, specified entirely in terms of probabilistic assumptions assigned to the observable process underlying the data , which is all that matters for inference. The key culprit behind [C1]–[C6] is the presumption that the AR(1) nests the unit root [UR(1)] model when = 1, which is shown to belie Kolmogorov’s existence theorem as it relates to . Fisher’s statistical perspective reveals that the statistical AR(1) and UR(1) models are grounded on (i) two distinct processes , with (ii) different probabilistic assumptions and (iii) statistical parametrizations, (iv) rendering them , and (v) their respective likelihood-based inferential components are free from conundrums [C1]–[C6]. The claims (i)–(v) are affirmed by analytical derivations, simulations, as well as proposing a non-stationary AR(1) model that nests the related UR(1) model, where testing = 1 relies on likelihood-based tests free from conundrums [C1]–[C6].

This paper investigates the notion of the financial Kuznets curve in an emerging country-Jordan. Both variants of the financial Kuznets curve (growth financial Kuznets curve and inequality financial Kuznets curve) have been examined using different time series methodologies applying to a sample period from 1993 to 2017. The unobserved components model results provide evidence for both variants of the financial Kuznets curve when using private credit to GDP as a proxy for financial-sector development. Moreover, non-nested model tests suggest that financial intermediaries are relatively more important than stock markets for income inequality. Overall, this paper provides evidence for the financial Kuznets curve in emerging countries. Moreover, it provides new insights for policymakers in Jordan in their challenge to boost economic growth and decelerate income inequality, by reversing the trend towards the concentration of power in the financial sector and creating public-financial institutions that provide affordable credit to small businesses and households.

Recent work in the study of legislative politics has uncovered associations between the Big Five personality traits and myriad phenomena in the United States Congress. This literature raises new questions about political representation in terms of the Big Five, specifically, whether voters are more likely to support legislators with similar personality traits to their own, who would presumably have similar process preferences, or legislators with valence personality traits, regardless of congruence, which are associated with better leadership. We first revisit the measurement validity of voter assessments of legislator personality in the 2014 and 2016 Cooperative Congressional Election Studies to demonstrate that such survey items are meaningful. Subsequently, we use these data to construct measures of personality congruence and valence and apply them to predict voters’ job approval of legislators. Our results support the claim that voters evaluate legislators’ job performance on the basis of perceived valence traits rather than legislators’ congruence to voters’ own personality dispositions.

Using data from a household survey carried out in the French overseas territory of Réunion, we investigate the price of drinking-water perceived by households faced with an increasing, multi-step pricing scheme. To this purpose we use an improved version of the method introduced by Shin (Rev Econ Stat 67(4):591–598, 1985 ) to estimate the demand for residential water when consumers are imperfectly informed about their pricing schedule. The empirical results suggest that Réunion households underestimate the price of water and thus consume more than what is economically rational. Providing information to households about the marginal price of water may be an innovative means of inducing them to respond to pricing policies designed to promote water conservation.

This paper explores the implications of consumption heterogeneity between domestic and foreign investors on the cross-section of stock returns in a host country. We argue that foreign investors in a small open economy integrated into global financial markets may face consumption risk, which could result in risk premia being reflected in stock returns. To account for the potential influence of foreign investors on asset prices in a host country, we develop a two-country durable consumption model under market incompleteness, which extends the one-country durable consumption model. The proposed model includes both domestic and foreign pricing factors. We investigate the empirical performance of our model with Fama–French portfolios for Korea, taking U.S. investors as representative foreign investors. The empirical results advocate the two-country durable consumption model, confirming the significant role of foreign factors in the cross-section of domestic stock returns. Additionally, R2 tests conducted with different sets of test assets show that the explanatory power of our model is comparable to that of the Fama–French three-factor model.

Purpose The purpose of this paper is to examine two alternative consumer behavioural intention models that have been developed from the marketing and information systems disciplines in a service environment. Specifically, it reports an empirical assessment of the two non-nested structural models in the context of Australian restaurant industry. Design/methodology/approach This study used a web-based survey by an online research organization and structural equation modelling with AMOS was used to compare the two non-nested behavioural intention models. Findings This study found that the second model that incorporates expectation-confirmation theory outperformed the first model in terms of model fit with the empirical data. Practical implications The findings of this study provide service managers with important insights into the appropriate design of service delivery systems to increase consumer satisfaction which, in turn, leads to more positive behavioural intentions. Moreover, the restaurant research setting means that marketing managers in the growing tourism and hospitality industry should benefit from the study findings. Originality/value This study synthesized two consumer behavioural intention models from different disciplines and provided an approach to the empirical comparison of the non-nested structural models.