Economics - Research Publications

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    Statistical analyses of ordinal outcomes in randomised controlled trials: a scoping review
    Selman, CJ ; Lee, KJ ; Ferguson, KN ; Whitehead, CL ; Manley, BJ ; Mahar, RK (BMC, 2024-04-06)
    BACKGROUND: Randomised controlled trials (RCTs) aim to estimate the causal effect of one or more interventions relative to a control. One type of outcome that can be of interest in an RCT is an ordinal outcome, which is useful to answer clinical questions regarding complex and evolving patient states. The target parameter of interest for an ordinal outcome depends on the research question and the assumptions the analyst is willing to make. This review aimed to provide an overview of how ordinal outcomes have been used and analysed in RCTs. METHODS: The review included RCTs with an ordinal primary or secondary outcome published between 2017 and 2022 in four highly ranked medical journals (the British Medical Journal, New England Journal of Medicine, The Lancet, and the Journal of the American Medical Association) identified through PubMed. Details regarding the study setting, design, the target parameter, and statistical methods used to analyse the ordinal outcome were extracted. RESULTS: The search identified 309 studies, of which 144 were eligible for inclusion. The most used target parameter was an odds ratio, reported in 78 (54%) studies. The ordinal outcome was dichotomised for analysis in 47 ( 33 % ) studies, and the most common statistical model used to analyse the ordinal outcome on the full ordinal scale was the proportional odds model (64 [ 44 % ] studies). Notably, 86 (60%) studies did not explicitly check or describe the robustness of the assumptions for the statistical method(s) used. CONCLUSIONS: The results of this review indicate that in RCTs that use an ordinal outcome, there is variation in the target parameter and the analytical approaches used, with many dichotomising the ordinal outcome. Few studies provided assurance regarding the appropriateness of the assumptions and methods used to analyse the ordinal outcome. More guidance is needed to improve the transparent reporting of the analysis of ordinal outcomes in future trials.
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    On the impact of outliers in loss reserving
    Avanzi, B ; Lavender, M ; Taylor, G ; Wong, B (SPRINGER HEIDELBERG, 2024-04)
    Abstract The sensitivity of loss reserving techniques to outliers in the data or deviations from model assumptions is a well known challenge. It has been shown that the popular chain-ladder reserving approach is at significant risk to such aberrant observations in that reserve estimates can be significantly shifted in the presence of even one outlier. As a consequence the chain-ladder reserving technique is non-robust. In this paper we investigate the sensitivity of reserves and mean squared errors of prediction under Mack’s Model (ASTIN Bull 23(2):213–225, 1993). This is done through the derivation of impact functions which are calculated by taking the first derivative of the relevant statistic of interest with respect to an observation. We also provide and discuss the impact functions for quantiles when total reserves are assumed to be lognormally distributed. Additionally, comparisons are made between the impact functions for individual accident year reserves under Mack’s Model and the Bornhuetter–Ferguson methodology. It is shown that the impact of incremental claims on these statistics of interest varies widely throughout a loss triangle and is heavily dependent on other cells in the triangle. Results are illustrated using data from a Belgian non-life insurer.
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    Detection and treatment of outliers for multivariate robust loss reserving
    Avanzi, B ; Lavender, M ; Taylor, G ; Wong, B (CAMBRIDGE UNIV PRESS, 2024-03)
    Abstract Traditional techniques for calculating outstanding claim liabilities such as the chain-ladder are notoriously at risk of being distorted by outliers in past claims data. Unfortunately, the literature in robust methods of reserving is scant, with notable exceptions such as Verdonck & Debruyne (2011, Insurance: Mathematics and Economics, 48, 85–98) and Verdonck & Van Wouwe (2011, Insurance: Mathematics and Economics,49, 188–193). In this paper, we put forward two alternative robust bivariate chain-ladder techniques to extend the approach of Verdonck & Van Wouwe (2011, Insurance: Mathematics and Economics,49, 188–193). The first technique is based on Adjusted Outlyingness (Hubert & Van der Veeken, 2008. Journal of Chemometrics,22, 235–246) and explicitly incorporates skewness into the analysis while providing a unique measure of outlyingness for each observation. The second technique is based on bagdistance (Hubert et al., 2016. Statistics: Methodology, 1–23) which is derived from the bagplot; however; it is able to provide a unique measure of outlyingness and a means to adjust outlying observations based on this measure. Furthermore, we extend our robust bivariate chain-ladder approach to an N-dimensional framework. The implementation of the methods, especially beyond bivariate, is not trivial. This is illustrated on a trivariate data set from Australian general insurers and results under the different outlier detection and treatment mechanisms are compared.
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    Posterior Manifolds over Prior Parameter Regions: Beyond Pointwise Sensitivity Assessments for Posterior Statistics from MCMC Inference
    Jacobi, L ; Kwok, CF ; Ramirez-Hassan, A ; Nghiem, N (De Gruyter, 2023)
    Increases in the use of Bayesian inference in applied analysis, the complexity of estimated models, and the popularity of efficient Markov chain Monte Carlo (MCMC) inference under conjugate priors have led to more scrutiny regarding the specification of the parameters in prior distributions. Impact of prior parameter assumptions on posterior statistics is commonly investigated in terms of local or pointwise assessments, in the form of derivatives or more often multiple evaluations under a set of alternative prior parameter specifications. This paper expands upon these localized strategies and introduces a new approach based on the graph of posterior statistics over prior parameter regions (sensitivity manifolds) that offers additional measures and graphical assessments of prior parameter dependence. Estimation is based on multiple point evaluations with Gaussian processes, with efficient selection of evaluation points via active learning, and is further complemented with derivative information. The application introduces a strategy to assess prior parameter dependence in a multivariate demand model with a high dimensional prior parameter space, where complex prior-posterior dependence arises from model parameter constraints. The new measures uncover a considerable prior dependence beyond parameters suggested by theory, and reveal novel interactions between the prior parameters and the elasticities.
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    Non-linear associations between HPA axis activity during infancy and mental health difficulties during early childhood among children in rural Pakistan
    Frost, A ; Hagaman, A ; Baranov, V ; Chung, EO ; Bhalotra, S ; Sikander, S ; Maselko, J (CAMBRIDGE UNIV PRESS, 2023-10)
    Hypothalamic pituitary adrenal (HPA) axis activity may be a mechanism linking early adversity to child mental health difficulties. However, there is a dearth of longitudinal evidence for the association between HPA axis activity and mental health among children in low-resource contexts. The goal of this study is to examine linear and curvilinear associations between HPA axis activity during infancy and mental health difficulties in early childhood among children in rural Pakistan. Participants included 104 children (46% male) from the Bachpan study, a longitudinal cohort embedded within a maternal depression trial in Pakistan. We examined the associations between hair-derived cortisol and dehydroepiandosterone (DHEA) at 12 months old and mental health difficulties, measured with the Strengths and Difficulties Questionnaire (SDQ), at 36 months old. There was a significant quadratic association between hair cortisol and SDQ scores, with results showing a U-shaped relationship (i.e., having relatively high or low cortisol predicted increased mental health difficulties). DHEA showed a quadratic association with SDQ scores with an inverted U-shaped relationship (i.e., high and low DHEA was associated with decreased mental health difficulties). Results provide evidence of longitudinal and curvilinear effects of cortisol and DHEA during infancy on mental health difficulties in early childhood.
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    Economic conditions and health: Local effects, national effect and local area heterogeneity
    Janke, K ; Lee, K ; Propper, C ; Shields, K ; Shields, MA (Elsevier BV, 2023-10-01)
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    Replication: Belief elicitation with quadratic and binarized scoring rules
    Erkal, N ; Gangadharan, L ; Koh, BH (Elsevier, 2020-12-01)
    Researchers increasingly elicit beliefs to understand the underlying motivations of decision makers. Two commonly used methods are the quadratic scoring rule (QSR) and the binarized scoring rule (BSR). Hossain and Okui (2013) use a within-subject design to evaluate the performance of these two methods in an environment where subjects report probabilistic beliefs over binary outcomes with objective probabilities. In a near replication of their study, we show that their results continue to hold with a between-subject design. This is an important validation of the BSR given that researchers typically implement only one method to elicit beliefs. In favor of the BSR, reported beliefs are less accurate under the QSR than the BSR. Consistent with theoretical predictions, risk-averse subjects distort their reported beliefs under the QSR.
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    Inward foreign investment screening targets China: interdisciplinary perspectives
    Mccalman, P ; Puzzello, L ; Voon, T ; Walter, A (EDWARD ELGAR PUBLISHING LTD, 2023-06)
    Screening of inward foreign investment in numerous countries worldwide has heightened in recent years for a range of reasons, one of which is the volume of Chinese outward investment. Moulding screening policies around concerns about Chinese investment has been a common pattern, particularly among developed countries and allies of the United States. The application of screening measures to Chinese investments in particular is also seen in recent practice in numerous countries. These developments create potential inconsistencies with international investment law, at least for those countries with an international investment agreement with China. The 2020 arbitral award in Global Telecom v Canada shows that even a provision that explicitly excludes investment screening decisions from a bilateral investment treaty may not apply to prevent all related investment treaty claims. The increased use of screening as a policy tool, with respect to China and otherwise, also raises questions about economic rationale and impact. Put simply, blocking a foreign investment proposal may have negative effects on shareholders, jobs and the economy itself, while even the existence of a restrictive screening regime and the threat of the imposition of conditions on a deal may dampen the appeal for foreign investors.
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    The dragon Down Under: the regional labour market impact of growth in Chinese imports to Australia
    Coelli, M ; Maccarrone, J ; Borland, J (ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD, 2023-11-02)
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    Pricing extreme mortality risk in the wake of the COVID-19 pandemic
    Li, H ; Liu, H ; Tang, Q ; Yuan, Z (ELSEVIER, 2023-01)
    In pricing extreme mortality risk, it is commonly assumed that interest rate and mortality rate are independent. However, the COVID-19 pandemic calls this assumption into question. In this paper, we employ a bivariate affine jump-diffusion model to describe the joint dynamics of interest rate and excess mortality, allowing for both correlated diffusions and joint jumps. Utilizing the latest U.S. mortality and interest rate data, we find a significant negative correlation between interest rate and excess mortality, and a much higher jump intensity when the pandemic experience is considered. Moreover, we construct a risk-neutral pricing measure that accounts for both diffusion and jump risk premia, and we solve for the market prices of risk based on mortality bond prices. Our results show that the pandemic experience can drastically change investors' perception of the mortality risk market in the post-pandemic era.