Jessica Pileri, Giulia Rocchi, Federica Luciani, Matteo Reho, Giorgio Veneziani and Carlo Lai
This study investigated the role of epistemic trust in shaping consumers intentions towards purchasing sustainable food products by examining the relationships between epistemic…
Abstract
Purpose
This study investigated the role of epistemic trust in shaping consumers intentions towards purchasing sustainable food products by examining the relationships between epistemic trust, credibility of science, scepticism about climate change and intentions to purchase sustainable food.
Design/methodology/approach
Data were collected using a survey. A total of 391 consumers participated in the study. Structural equation modelling was employed for data analysis.
Findings
The results showed that the trust dimension was significantly and positively associated with credibility of science (p = 0.004) and negatively with scepticism about climate change (p = 0.018); mistrust was significantly and negatively associated with credibility of science (p = ≤0.001); credibility of science had a significant negative effect on scepticism about climate change (p = ≤0.001) and scepticism about climate change had a significant direct and negative impact on intention to purchase sustainable food (p = ≤0.001). Furthermore, results indicated that the link between trust, mistrust and intention to purchase sustainable food was significantly mediated by the credibility of science and scepticism about climate change.
Practical implications
The results can preliminarily suggest policies promoting transparency and direct consumer experiences in organisational practices, with implications extending to other sectors like education and public information.
Originality/value
For the first time, epistemic trust is specifically considered as an antecedent of intentions to purchase sustainable food, while also examining its relationships with scepticism about climate change and the credibility of science.
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Stefania Chiappini, Alessio Mosca, Andrea Miuli, Francesco Di Carlo, Giacomo d'Andrea, Alessandra Napolitano, Monica Santangelo, Corradina Esposito, Anna Rosazza, Elena Haefele, Gilberto Di Petta, Mauro Pettorruso, Stefano L. Sensi and Giovanni Martinotti
This paper aims to investigate the role of aripiprazole once monthly as a maintenance treatment in a sample of patients with schizophrenia comorbid with alcohol and substance use…
Abstract
Purpose
This paper aims to investigate the role of aripiprazole once monthly as a maintenance treatment in a sample of patients with schizophrenia comorbid with alcohol and substance use disorder (AUD/SUD).
Design/methodology/approach
A sample of 24 Italian adult patients has been recruited and treated with aripiprazole once monthly after clinical stabilization with oral aripiprazole during May 2021 and June 2022. Clinical evaluations have been performed at the baseline (T0) and after 12 (T1) and 24 (T2) weeks.
Findings
During the study period, an improvement of both the clinical condition and general health from baseline was observed, as well as a reduction of craving for alcohol/substances. However, from T0, the number of patients who continued with this study decreased at T1 (n = 8) and then at T2 (n = 4). No serious adverse events were reported, including changes in weight, lipid/glucose metabolism, electrocardiogram and extra-pyramidal side effects.
Originality/value
Although limited by the high number of drop outs, this observational real-world study provided insights into the use of aripiprazole once monthly among a sample of patients with schizophrenia and comorbid SUD/AUD. Further studies of longer duration and on a larger sample are needed.
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Tze Leung Lai and Haipeng Xing
This paper shows that volatility persistence in GARCH models and spurious long memory in autoregressive models may arise if the possibility of structural changes is not…
Abstract
This paper shows that volatility persistence in GARCH models and spurious long memory in autoregressive models may arise if the possibility of structural changes is not incorporated in the time series model. It also describes a tractable hidden Markov model (HMM) in which the regression parameters and error variances may undergo abrupt changes at unknown time points, while staying constant between adjacent change-points. Applications to real and simulated financial time series are given to illustrate the issues and methods.
Jean-Joseph Minviel, Yawose Kudawoo and Faten Ben Bouheni
Recent advances in stochastic frontier analysis (SFA) suggest two alternative approaches to account for unobserved heterogeneity and to distinguish between persistent and…
Abstract
Purpose
Recent advances in stochastic frontier analysis (SFA) suggest two alternative approaches to account for unobserved heterogeneity and to distinguish between persistent and transient inefficiency. The first approach is the generalized true random effects (GTRE) model, and the second approach is an autoregressive inefficiency (ARI) model. This study compares them to highlight whether they capture similar inefficiency aspects.
Design/methodology/approach
Using recent methodological advances in SFA, the authors estimate the GTRE and the ARI models using a Monte Carlo experiment and two real datasets from two industries (banking and agriculture).
Findings
The authors find that the two models provide quite different results in terms of inefficiency persistence and overall inefficiency (combination of transient and persistent inefficiency), regardless of the dataset considered.
Practical implications
The study findings suggest that researchers should be careful when referring to these two models because they do not capture the same inefficiency aspects, even though they have the same conceptual basis. This work is a warning about the empirical aspects of the persistent and transient efficiency framework, in order to convey a consistent story to the reader on firms' performance.
Originality/value
Even though they are used in a large number of studies, the present paper contributes to the productivity and efficiency literature by providing the first comparison of the GTRE and the ARI models.
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Bruce E. Hansen and Jeffrey S. Racine
Classical unit root tests are known to suffer from potentially crippling size distortions, and a range of procedures have been proposed to attenuate this problem, including the…
Abstract
Classical unit root tests are known to suffer from potentially crippling size distortions, and a range of procedures have been proposed to attenuate this problem, including the use of bootstrap procedures. It is also known that the estimating equation’s functional form can affect the outcome of the test, and various model selection procedures have been proposed to overcome this limitation. In this chapter, the authors adopt a model averaging procedure to deal with model uncertainty at the testing stage. In addition, the authors leverage an automatic model-free dependent bootstrap procedure where the null is imposed by simple differencing (the block length is automatically determined using recent developments for bootstrapping dependent processes). Monte Carlo simulations indicate that this approach exhibits the lowest size distortions among its peers in settings that confound existing approaches, while it has superior power relative to those peers whose size distortions do not preclude their general use. The proposed approach is fully automatic, and there are no nuisance parameters that have to be set by the user, which ought to appeal to practitioners.
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Recent studies indicating long term dependence in stock market indices have found a mean reversion process. However, studies using rescaled range (R/S) analysis have not found…
Abstract
Recent studies indicating long term dependence in stock market indices have found a mean reversion process. However, studies using rescaled range (R/S) analysis have not found evidence of a mean reversion or ergodic process. Instead, evidence from these studies indicate either long term persistence in a nonperiodic cycle or short run Markovian dependence with no long term persistence. The purpose of this paper is to study the issue of long term dependence using rescaled range analysis. The empirical results obtained in this study support the persistent dependence/nonperiodic cycle results and suggest that the dependence arises from the general economic cycle.
Dongqing Zhang, Xuanxi Ning and Xueni Liu
As the conventional multistep‐ahead prediction may be unsuitable in some cases, the purpose of this paper is to propose a novel method based on joint probability distributions…
Abstract
Purpose
As the conventional multistep‐ahead prediction may be unsuitable in some cases, the purpose of this paper is to propose a novel method based on joint probability distributions, which provides the most probable estimation for the predicted trajectory.
Design/methodology/approach
Many real‐time series can be modeled in hidden Markov models. In order to predict these time series online, sequential Monte Carlo (SMC) method is applied for joint multistep‐ahead prediction.
Findings
The data of monthly national air passengers in China are analyzed, and the experimental results demonstrate that the method proposed and the corresponding online algorithms are effective.
Research limitations/implications
In this paper, SMC method is applied for joint multistep‐ahead prediction. However, with the increasing of prediction step, the number of particles is increasing exponentially, which means that the prediction steps cannot be too large.
Practical implications
A very useful advice for researchers who study time‐series forecasts.
Originality/value
A novel method of multistep‐ahead prediction based on joint probability distribution is proposed and SMC method is applied to prediction time series online. This paper is aimed at those researchers who focus on time‐series forecasts.
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The standard method to estimate a stochastic frontier (SF) model is the maximum likelihood (ML) approach with the distribution assumptions of a symmetric two-sided stochastic…
Abstract
The standard method to estimate a stochastic frontier (SF) model is the maximum likelihood (ML) approach with the distribution assumptions of a symmetric two-sided stochastic error v and a one-sided inefficiency random component u. When v or u has a nonstandard distribution, such as v follows a generalized t distribution or u has a
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Cássio da Nóbrega Besarria, Nelson Leitão Paes and Marcelo Eduardo Alves Silva
Housing prices in Brazil have displayed an impressive growth in recent years, raising some concerns about the existence of a bubble in housing markets. In this paper, the authors…
Abstract
Purpose
Housing prices in Brazil have displayed an impressive growth in recent years, raising some concerns about the existence of a bubble in housing markets. In this paper, the authors implement an empirical methodology to identify whether or not there is a bubble in housing markets in Brazil.
Design/methodology/approach
Based on a theoretical model that establish that, in the absence of a bubble, a long-run equilibrium relationship should be observed between the market price of an asset and its dividends. The authors implement two methodologies. First, the authors assess whether there is a cointegration relationship between housing prices and housing rental prices. Second, the authors test whether the price-to-rent ratio is stationary.
Findings
The authors’ results show that there is evidence of a bubble in housing prices in Brazil. However, given the short span of the data, the authors perform a Monte Carlo simulation and show that the cointegration tests may be biased in small samples. Therefore, the authors should be caution when assessing the results.
Research limitations/implications
The results obtained from the cointegration analysis can be biased for small samples.
Practical implications
The information on the excessive increase of the prices of the properties in relation to their fundamental value can help in the decision-making on investment of the economic agents.
Social implications
These results corroborate the hypothesis that Brazil has an excessive appreciation in housing prices, and, as Silva and Besarria (2018) have suggested, this behavior explains, in part, the fact that the central bank has taken this issue into account when deciding about the stance of monetary policy of Brazil.
Originality/value
The originality is linked to the use of the Gregory-Hansen method of cointegration in the identification of bubbles and discussion of the limitations of the research through Monte Carlo simulation.