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Thought about scientific models and modelling practices in the sciences has a long tradition. It has recently been argued that this practice of science also exists in metaphysics. In this paper, I show that this view has two significant historical forerunners: Hans Vaihinger and Salomon Maimon. Vaihinger provided what is today often seen as the starting point of the contemporary debate on scientific models as fictions. He argued that fictions can be equally useful in the sciences as in metaphysics. However, Vaihinger‘s position is problematic. Firstly, he mainly credits Kant for providing the first comprehensive account of the method of fictions in the sciences. I will argue that contrary to his claims, it was Maimon – whom Vaihinger only mentions in passing – who first adapted Kant‘s doctrine of ideas to serve the purposes of a fictionalist agenda. I will show that Maimon‘s account of scientific fictions already contains many of the features which Vaihinger claims to have discovered himself. Secondly, Vaihinger’s failure to distinguish between the use of fictions in the sciences and metaphysics creates a problem for some types of metaphysical fictions. I show that Maimon‘s account of metaphysical fictions identifies and avoids this problem. [ABSTRACT FROM AUTHOR]

Individuals utilizing Life Cycle Assessment within the emerging field of circular carbon might phrase and understand matters differently, causing ambiguity, due to different educational backgrounds and lacking definitions of central terms. Our research addresses the question, whether misleading or ambiguous terms exist, which impair transparency and scientific accuracy in carbon (dioxide) accounting in LCA. A structured literature research was performed to screen LCA standards, ISO standards, and the European legal database EUR-Lex. Nine terms with potential ambiguity in meaning or usage in LCA were identified: Avoided burden, avoided carbon, avoided CO2, carbon capture, carbon credit, circular carbon, circular CO2, negative emission, and net zero emission. A workflow was introduced to either obtain a consensus-based definition from standard literature or from peer-reviewed publications. For all terms, except avoided carbon, a recommended definition was found and showcased within case studies on the topic of mechanical recycling of plastics to produce a taxonomy suggestion for precise descriptions of different carbon dioxide (equivalent) accounting methods in LCA. [ABSTRACT FROM AUTHOR]

In this article, we examine the contestations and compromises that underpin the Paris Agreement's enhanced transparency framework, with the aim to analyze whose climate action priorities are reflected in these arrangements. Key mandatory obligations of the transparency framework relate to submission of greenhouse gas inventories and reporting and review of mitigation-related climate actions. Less analyzed are the non-mitigation focused transparency provisions, particularly those relating to adaptation, loss and damage and financial support, all of which are of key importance to developing countries. We address this research gap here by unpacking what different groups of countries desired with regard to these less examined aspects of the enhanced transparency framework, in the lead-up to finanalization of the Paris Agreement in 2015, and the nature of the political compromises reached on each. Furthermore, we analyze how these agreed transparency provisions are being operationalized since 2015. We find that many of the compromises reached on the scope of the enhanced transparency framework, but perhaps even more so in its subsequent operationalization, marginalize certain aspects of reporting and review that are of the highest priority to developing countries. These include, for example, reporting on adaptation needs, on having voluntary information on loss and damage be reviewed by international experts, and having access to comparable and actionable reporting on support provided by developed countries. This highlights the need for future research to assess the domestic consequences of engaging in global climate transparency arrangements for developing countries; and whether and how such engagement aligns with domestic priorities. Key policy insights: The Paris Agreement's enhanced transparency framework goes beyond a mitigation-focus to include adaptation, loss and damage and support, which was a key demand of developing countries, yet important caveats lie in its detailed operationalization. Reporting on adaptation needs, a priority for developing countries, is covered only in a cursory manner in the enhanced transparency framework. Loss and damage too features only marginally in the enhanced transparency framework, as a sub-element of adaptation reporting and review. Reporting on support provided is mandatory for developed countries, as demanded by developing countries, but the devil is in the detail, with provision of ex-ante information relegated to a different process and little progress towards common accounting methods. It remains unclear whether participation in the enhanced transparency framework will help developing countries to generate information relevant to furthering domestic climate action priorities. [ABSTRACT FROM AUTHOR]

An important activity of entrepreneurs is to justify the value of an innovation to gain support from stakeholders. We examine how entrepreneurs can develop an accounting methodology to demonstrate the value of a proposed innovation, focusing on the case of a charitable foundation's promotion of social enterprise and its efforts to develop the accounting methodology of Social Return on Investment (SROI). We show how the process for designing new accounting methods that helps in demonstrating the value of innovations involves entrepreneurs (1) imagining the expectations of their stakeholders (2) putting in place the necessary infrastructure through which numbers can be generated and (3) iteratively reconfiguring the accounting methodology and the espoused value the innovation is expected to generate. Our study furthers understanding of the role of accounting numbers in the entrepreneurial process, particularly in situations where entrepreneurs seek to generate new accounting methodologies to develop persuasive stories about the benefits of their innovations. [ABSTRACT FROM AUTHOR]

Ammonia (NH3) emissions negatively impact air, soil, and water quality, hence human health and biodiversity. Significant emissions, including the largest sources, originate from single or multiple structures, such as livestock facilities and wastewater treatment plants (WWTPs). The inverse dispersion method (IDM) is effective in measuring total emissions from such sources, although depositional loss between the source and point of measurement is often not accounted for. We applied IDM with a deposition correction to determine total emissions from a representative dairy housing and WWTP during several months in autumn and winter in Switzerland. Total emissions were 1.19 ± 0.48 and 2.27 ± 1.53 kg NH3 d-1 for the dairy housing and WWTP, respectively, which compared well with literature values, despite the paucity of WWTP data. A concurrent comparison with an inhouse tracer ratio method at the dairy housing indicated an offset of the IDM emissions by < 20%. Diurnal emission patterns were evident at both sites mostly driven by changes in air temperature with potential lag effects such as following sludge agitation. Modeled deposition corrections to adjust the concentration loss detected at the measurement point with the associated footprint were 22-28% of the total emissions and the cumulative fraction of deposition to emission modeled with distance from the source was between 7% and 12% for the measurement distances (60-150 m). Although estimates of depositional loss were plausible, the approach is still connected with substantial uncertainty, which calls for future validation measurements. Longer measurement periods encompassing more management activities and environmental conditions are required to assess predictor variable importance on emission dynamics. Combined, IDM with deposition correction will allow the determination of emission factors at reduced efforts and costs, thereby supporting the development and assessment of emission reducing methods and expand the data availability for emission inventories. Implications: Ammonia emissions must be measured to determine emission factors and reporting national inventories. Measurements from structures like farms and industrial plants are complex due to the many different emitting surfaces and the building configuration leading to a poor data availability. Micrometeorological methods provide high resolution emission data from the entire structure, but suffer from uncertainties, as the instruments must be placed at a distance from the structure resulting in a greater loss of the emitted ammonia via dry deposition before it reaches the measurement. This study constrains such emission measurements from a dairy housing and wastewater treatment plant by applying a simple correction to account for the deposition loss and compares the results to other methods. [ABSTRACT FROM AUTHOR]

Accounting information system (AIS) is becoming increasingly paramount for SMEs in order to boost decision-making effectiveness (DME). The issue is no longer whether SMEs use AIS or not, but rather about the extent of benefits and effectiveness that can be achieved from such use. This paper aims to assess how AIS success impacts DME among SMEs in less developed countries (LDCs). Specifically, this paper develops a study model and validates it with empirical evidence gathered from the Yemeni business environment. This paper is based on DeLone and McLean (D&M) model to establish the relationship between AIS success and DME among SMEs in Yemen, a less developed country. A questionnaire is built and sent to owners and managers of 323 Yemeni SMEs from different sectors. PLS-SEM software was employed to analyze and test the gathered data. The findings exhibit important positive links between the success of AIS and DME. In particular, the outcomes appear that AIS information quality, use, and user satisfaction positively influence decision-making effectiveness; system and information quality are significant precedents of AIS usage and satisfaction; AIS usage is positively impacted by satisfaction. However, service quality is showed insignificant towards AIS usage and user satisfaction. Theoretically, this study reduces research gaps related to AIS success in SMEs from a management perspective (i.e., DME) and LDCs context. Practically, the study model can serve as a device for SMEs to assess and anticipate the success of implemented AIS applications. Moreover, the study results can help SMEs' managers and owners to gain a clear insight into the positive role of AIS success in boosting decision-making effectiveness in their businesses. On the other hand, the study results may motivate those who depend on conventional manual accounting methods to make the transition to AIS. Also, this study offers practical guidelines for the government on AIS success importance among SMEs and its role in economic development. This research is deemed one of the first to introduce empirical evidence on the influence/relationship of AIS success on/and DME among SMEs in LDCs, Yemeni case. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Paper Conservation is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Due to the current shortage of accountants and the various pipeline initiatives taking place, our research aims to address the instructor's role in the accounting classroom. We survey students on their perceptions regarding teaching and assessment methods used in university accounting courses. Results for both in person and online courses suggest students prefer instruction that involves instructor demonstration of exercises and real-world examples, while relying on the instructor's personal experiences with accounting. We offer valuable perspectives to educators aiming to improve both the caliber of accounting education and the student learning experience to help combat the drastic shortage. [ABSTRACT FROM AUTHOR]

Assessing the agreement between an established and a new measurement system is a practical and important challenge in many application areas. The probability of agreement (PoA) has recently been introduced as a metric to assess such agreement when repeatability, the precision of the measurement system itself, represents the overall measurement system variation. However, it is common in practice for the measurement system to be operated by multiple individuals, and their effects can be an important part of the overall variation. Reproducibility represents the measurement variability attributable to different operators. This article extends the PoA methodology to account for both the repeatability and reproducibility of each measurement system along with the relative bias between them. The developed methodology also allows imbalanced replicate measurements across operators and systems, while the operator effects can either be fixed or random. We use maximum likelihood estimation to estimate the PoA. The proposed approach is illustrated using two case studies. In the first one, we compare the agreement between an old and a new measurement system used for quality inspections in an industrial context. The second case study which is presented in file assesses the agreement between two devices used to measure respiratory rates. [ABSTRACT FROM AUTHOR]

This article reports a study on a flexible neural network regression method within the functional analysis of variance framework that aims to adapt to the underlying structure of the target function. We develop a novel penalization scheme where a concept of node impurity is introduced in the neural network framework. The node impurity in neural networks represents the homogeneity of the effects of the inputs on the node. We first define the effect of individual input on node and in turn, measure the node impurity based on the effects of inputs on node. We adopt the sum of node impurities as a penalty function whose usage makes the connections from inputs to nodes sparse, which improves estimation accuracy by reducing unnecessary complexity and enables data-adaptive structure identification. Our method takes into account of a large parameter space of the networks ranging from a fully-connected structure to sparsely connected structures. Among possible node connection structures, an optimal model is selected based purely on observed data. Numerical studies based on simulated and real datasets show that the proposed method performs well in identifying the inherent structure of the regression function and produces good estimation accuracy. for this article are available online. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to suggest an accounting framework for India for implementation of its nationally determined contributions (NDCs) and design the appropriate modality for reporting its capacity building needs and priorities in a manner that is in consonance with the provisions of the Paris Rule book from the perspective of a developing country. The suggested accounting methodology considers India's national greenhouse gas (GHG) inventory and climate mitigation policies. The Key Category Analysis concept of the Intergovernmental Panel on Climate Change for accounting GHG inventory estimation at the national level is used to identify and rank the key inventory categories for India. Accounting of various national level mitigation policies is undertaken by assessing their impact on the key categories, subsequently recognizing 'Key Policies' in accordance with the provisions of the Paris rulebook. 'Key Policies' are found to have a definite role in driving the progress of implementation of NDCs. The study recommends a modality that developing countries can use to report their needs for capacity building support for full implementation of their 'key policies' while accounting their future NDCs, using the flexibilities provided under the Paris Rule book. [ABSTRACT FROM AUTHOR]

This paper empirically investigates corruption-related disclosure in the banking industry, aiming to shed light on the reasons why financial institutions disclose corruption-related information in their annual financial reports. Using a total sample of 88 banks from the GIPSI countries during the period 2011-2019, our results reveal that, on average, banks involved in corruption issues disclose less on corruption-related matters than banks not involved in any corruption scandal. Moreover, banks not involved in corruption cases disclose even more information after other banks' corruption events become public. These basic relationships, however, are shaped by the characteristics of each particular country in terms of control of corruption and the specific regulation on non-traditional banking activities. Our results are robust to different specifications of econometric models, to alternative empirical methods accounting for potential reverse causality and sample selection concerns and to the inclusion of internal corporate governance mechanisms. [ABSTRACT FROM AUTHOR]

We have framed a detailed account of the synthetic methods and the bioactivity and pharmacological aspects available for aminopyrazolecarbonitriles as they have substantial role as a building block and starting materials for producing enormous biologically active heterocyclic skeletons. Hydrazine derivatives are important precursors in the synthesis of aminopyrazolecarbonitriles where, the nucleophilic addition of hyrazines to monocyano, dicyano, tricyano and tetracyanoethylenes led to the formation of the target compounds via the formation of two C–N bonds. Multicomponent reactions (MCRs) of hydrazines, aromatic aldehydes, and malononitrile is considered an efficient one pot protocol for the synthesis of aminopyrazolecarbonitriles. Intramolecular cyclization involves one bond formation and functional group transformations are used to prepare aminopyrazolecarbonitriles. [ABSTRACT FROM AUTHOR]

Objective: Iverson (2001) expanded on reliable change methodology by accounting for the variability in scores at Time 2 in the calculation of change scores. However, due to limitations in available data, an incomplete picture of variables affecting change was presented. The current paper sought to address some of these limitations and clarify the methodology for assessing reliable change. Method: Using one-year test-retest data on the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) in older adults who were cognitively intact or had mild Alzheimer's disease (AD), change scores were calculated, and various models, consistent with or divergent from Iverson, were presented. Results: Across the RBANS, individuals with intact cognition tended to show less variable scores, especially at Time 2, which resulted in larger change scores than those with AD. When applied to an independent sample, different patterns of change were observed, with: (1) models that used intact data showed more cognitive change than those using AD data; (2) the model that corrected for practice effects and used intact data showed the most decline; and (3) the model that corrected for practice effects and used AD data showed the most improvement. The models that showed the strongest association in classifying independent cases as decline/stable/improve were those that used intact data and were discordant on the use of practice effects. Conclusions: Overall, findings highlight the complexity of calculating reliable change, and they lend additional caution to Iverson's original limitations. However, the use of data from individuals classified as cognitively intact and a correction for practice effects seems warranted. [ABSTRACT FROM AUTHOR]

The spread of global value chains (GVCs) has given rise to new statistical tools, the inter-country input–output tables, and new analytical frameworks aimed at properly identifying production linkages between and within economies. However, several important questions remain unaddressed. This paper proposes a new toolkit for value-added accounting of trade flows at the aggregate, bilateral, and sectoral levels. The paper shows how different empirical issues require distinct accounting perspectives and maps these methodologies onto the economic questions they are best suited to address. We provide novel accounting perspectives that allow us to properly address important empirical issues. With respect to other accounting methodologies previously proposed in the literature, we offer more accurate or, in some cases, more exhaustive value-added decompositions of trade flows (e.g. by covering both domestic and foreign value-added). In addition, the paper gathers a significant amount of the related literature under one comprehensive framework. [ABSTRACT FROM AUTHOR]

Scour has been recognized as one of the leading causes of bridge collapse in the United States. Therefore, it is essential to be able to build models that accurately capture the response of bridges vulnerable to scour, including those located in layered rather than homogeneous soil deposits. Simple removal of soil springs due to scour ignores the effect of stress history for layered soils, which can lead to unconservative designs of foundations. This article proposes a methodology called the equivalent stress history and layered effects (ESHaLE) approach to capture the impact of soil stress history of layered soils on vulnerability assessment of scoured bridges. It utilises conservation of strength and mass to derive corresponding soil and depth parameters. Results show that neglecting to include stress history impacts in layered soils can lead to an underestimation of the single pile axial displacements by up to 35% in static analysis, and underestimation of the probability of exceeding bridge deck deflection thresholds by up to 25% in seismic fragility assessment. The study presents a method to include both soil stress history and layered effects in soil modeling and shows the importance of including these soil effects in the assessment of bridges vulnerable to scour. [ABSTRACT FROM AUTHOR]

Money markets, finance, credit instruments, and other markers of what Lenin called "the highest stage of capitalism" are the mechanism through which global inequalities are maintained, expanded, and determined. Accounting practices like double-entry bookkeeping and cost accounting have long determined what is thinkable within this realm. Scholars and political actors have also employed the term "authoritarian neoliberalism" to signal the particular ideological constellation and subsequent subjectivities that are salient in the present moment. This paper posits a theoretical framework for delineating accounting as a political tactic for changing the mode of production of knowledge and supporting revolutionary accounting subjects. Consulting the literature on critical accounting theory, this paper engages ideas such as "citizen public debt audits" and "emancipatory accounting" in order to investigate the dynamics of tactical resistance that have emerged around issues of finance and accounting within a radical democratic and Marxist tradition of theorizing political strategy. [ABSTRACT FROM AUTHOR]

A two-stage analysis of the support-rock interaction is carried out using a proposed numerical procedure. The procedure provides a simplified solution for readily obtaining the final support load and rock mass displacement that is easier to use than the conventional Convergence-Confinement Method (CCM). The procedure accounts for the strain-softening behaviour of the rock mass and the effect of delayed support installation. Based on the procedure, a method to determine the delayed distance and allowable displacement for the support installation is presented. A Modified Ground Reaction Curve (MGRC) that relates the rock mass displacement to the final support load is introduced. The effects of the rock mass quality, initial stress, support type and strain-softening, dilatancy behaviours on the delayed distance and allowable displacement are investigated. A comparison between the predictions of the MGRC and GRC is conducted. The results indicate that the influence of the rock mass quality and initial stress on the support-rock interaction is more significant than that of the strain-softening and dilatancy behaviours. An approximate support design using the GRC may be acceptable for a weak rock mass, whereas the GRC results in an overly conservative support design for an excellent rock mass. [ABSTRACT FROM AUTHOR]

Corporate income tax constitutes a significant portion of financial costs in business operations. A typical tax system is characterized by the tax structure, accounting method, and loss carryover rule. In this article, we study the optimal inventory policies under taxation and accrual accounting. We consider a lost-sales periodic-review inventory system under a proportional tax with loss carryforward. We formulate the problem as a cyclic stochastic dynamic program with multiple accounting periods, each of which consists of multiple review periods. We show that an incomedependent basestock policy is optimal. We find that tax function convexity and loss carryforward may introduce conflicting incentives into inventory decisions: the former drives risk-averse decisions whereas the latter induces risk-seeking behavior. We identify two intertemporal effects of taxation, the intra-accounting-period effect and the inter-accounting-period effect, both inducing smaller basestock levels. We further extend the analysis to the progressive tax, backordering system, and cash accounting method. Our numerical study examines the effects of various characteristics of taxation on the optimal policies. Our results demonstrate that ignoring taxation in inventory decisions may lead to significant losses especially when the tax rate and demand uncertainty are sufficiently high, which reveals the value of tax considerations in inventory management. [ABSTRACT FROM AUTHOR]

To comprehensively analyze the current research status, hot trends, and influencing factors of tourism carbon footprint, this paper conducts a bibliometric analysis. We find that (1) tourism carbon footprint is the topic with the highest attention in the field of tourism footprint research; (2) economic effects, tourism carbon footprint accounting methods, and the consciousness drive of each subject in the tourism industry are still important research directions; (3) tourism activity items such as accommodation and transportation are the main influencing factors while the behavioral preferences and characteristics of tourists, government and tourism operators become important directions for future empirical research. [ABSTRACT FROM AUTHOR]

We revisit the classic situation in functional data analysis in which curves are observed at discrete, possibly sparse and irregular, arguments with observation noise. We focus on the reconstruction of individual curves by prediction intervals and bands. The standard approach consists of two steps: first, one estimates the mean and covariance function of curves and observation noise variance function by, e.g. penalized splines, and second, under Gaussian assumptions, one derives the conditional distribution of a curve given observed data and constructs prediction sets with required properties, usually employing sampling from the predictive distribution. This approach is well established, commonly used and theoretically valid but practically, it surprisingly fails in its key property: prediction sets constructed this way often do not have the required coverage. The actual coverage is lower than the nominal one. We investigate the cause of this issue and propose a computationally feasible remedy that leads to prediction regions with a much better coverage. Our method accounts for the uncertainty of the predictive model by sampling from the approximate distribution of its spline estimators whose covariance is estimated by a novel sandwich estimator. Our approach also applies to the important case of covariate-adjusted models. [ABSTRACT FROM AUTHOR]

Ferri et al. and Van Helden et al.'s articles should be useful for the IPSASB when updating its Chapter 3, and may also convince the IPSASB to reconsider the qualitative characteristics of understandability and readability. Presentation of financial statements The issue of simplification (highlighted by Cordery, [11]) and readability as a qualitative characteristic (highlighted by Ferri et al., [12]) are factors that would prove fundamental for the IPSASB's planned project on I IPSAS 1 - Presentation of financial statements i . These authors voice the opinion of government accounting practitioners with hands-on experience on public sector accounting systems that have been subjected to changes over an extended period of 15 years - namely, accounting practitioners in Polish local governments. Counter accounting is a response from critical accounting scholars to fight fake news and obfuscation or manipulation of information. [Extracted from the article]

In an era where fake news and political rhetoric must constantly be fact checked, this article seeks to raise awareness within the public sector about how the use of counter accounting can help to challenge official versions of events and actions and influence public debate. While counter accounting has most frequently been used by those investigating sustainability issues within accounting, this article aims to stimulate debate about how counter accounting can also be used to make an impact within the public accountability and management arena, through the presentation of alternative accounts and narratives to counter the official accounts produced by governments and other public sector organizations. The article also encourages the authors of counter accounting work to disseminate their findings on a timely basis to a wider audience, for example through more targeted use of social media. This article explores what counter accounting is and how this methodology can offer a different way of presenting accounting and accountability information. It enables academics and activists external to the organizations being examined to challenge prevailing official positions through the provision of alternative narratives and/or financial statements. Many counter accounts produced to date focus on sustainability and social audit issues in the corporate world. This article recommends that the same techniques can be used to good effect in the public accountability and management context to challenge governments and other public sector bodies. It gives examples from the literature and identifies the topics of health and welfare, education, climate change, acts of war and disaster responses as suitable areas for further study. Given that counter accounting has yet to influence significant transformative societal change, it suggests greater use of social media as a timely way of building greater public awareness. [ABSTRACT FROM AUTHOR]

The relative density of seabed determines its bearing capacity and affects the site selection, construction, and maintenance of offshore projects. As the modal-identification-based method for monitoring pile foundation scour depth does not account for the relative density of seabed, it cannot be implemented in engineering practice. Therefore, experiments and finite element simulations of a pile–soil model with different scour depths were conducted in this study to update and verify the modal-identification-based method to account for relative soil density using the Winkler foundation model. The results show that for a given scour depth, the average error decreased as the relative soil density increased, and for a given relative density, the average error decreased as the scour depth increased. The accuracy of the updated method was then improved according to the variation of the average error according to soil density and shown to exhibit strong engineering applicability. [ABSTRACT FROM AUTHOR]

This article presents a comprehensive multiple account evaluation (MAE) framework that is intended to inform public interest determinations in impact assessment (IA). Using MAE methodology; which involves separating impacts into government revenue, economic activity, environmental, social, health, and Indigenous accounts; the proposed 'Public Interest MAE Framework' seeks to inform senior government decision makers on all the positive and adverse consequences associated with a proposed project in a manner that allows for analysis of key trade-offs from the perspective of society as a whole. The proposed framework is applied to a case study to demonstrate how the framework functions in practice. Additionally, a survey is conducted with IA practitioners, experts, stakeholders, and Indigenous groups to evaluate the proposed Public Interest MAE Framework. The primary conclusion of this study is that the Public Interest MAE Framework has the potential to inform public interest determinations and overcome many of the limitations associated with other estimation methods used in IA. Finally, opportunities and challenges associated with integrating the Public Interest MAE Framework into IA are explored. [ABSTRACT FROM AUTHOR]

This paper presents a new method for predictive crime hotspot analysis that further improves the kernel density estimation (KDE) method and the spatio-temporal kernel density estimation (STKDE) method by accounting for temporal crime cycles and is therefore termed the 'cyclically adjusted STKDE (cSTKDE) method'. The case study on robbery incidents in Baton Rouge, Louisiana, shows a temporal cycle with a 6-month period of statistical significance from January 2010 to May 2018. This identified period is incorporated into the temporal kernel function of the new cSTKDE method. For validation, the Forecast Accuracy Index (FAI) and Forecast Precision Index (FPI) are used to evaluate the performance across 52 weeks in 2013. For 11 consecutive weeks since the beginning of 2013, the cSTKDE method outperforms the STKDE by 89% lower average abs(1-FAI) and 17% higher average FPI, and outperforms the KDE by 90% lower average abs(1-FAI) and 8% higher average FPI. Overall, the scenario with the best predictive accuracy by the cSTKDE is recommended over the traditional KDE or STKDE method as most feasible and effective in implementation of hotspot policing in practice. [ABSTRACT FROM AUTHOR]

Temporal correlation in crash counts is an important issue that road safety researchers face when developing crash prediction models. Several modelling methods have been proposed to date to address this issue. Random effects negative binomial (RENB) model, random parameters negative binomial (RPNB) model, multilevel negative binomial (MLNB) model, negative multinomial (NM) model, and generalized estimating equation (GEE) model are the most frequently used ones. Although those models have been applied successfully, it is not clear to researchers what their differences are and how to make a choice among them. This study attempts to answer these questions through describing the main features of the five models, showing their connections, illustrating their applications to predict the crash frequency on basic freeway segments, and discussing their differences that can guide the choice making. The application results show that the RENB, MLNB, and RPNB models are superior to others in terms of predictability (for the current data set), capability, usability, and interpretability. Three fundamental differences, including the ways to handle temporal correlation, whether to account for other heterogeneities, and the interpretation of estimated coefficients, provide some guidance on the model choice. [ABSTRACT FROM AUTHOR]

Networks are widely used to describe relational data among objects in a complex system. As network data often exhibit clustering structures, research interest often focuses on discovering clusters of nodes. We develop a novel concordance-based method for node clustering in networks, where a linear model is imposed on the latent position of each node with respect to a node-specific center and its covariates via linear transformation. By maximizing a triangular concordance function with a concave pairwise penalty, the latent positions are estimated so that each node would be more likely to be close to its neighbors in contrast to non-neighbors and nodes are clustered by their node-specific centers. We develop an alternating direction method of multipliers algorithm for parameter estimation and an intimacy score between unlinked nodes for link prediction. Our method takes into account common characteristics of network data (i.e., assortativity, link pattern similarity, node heterogeneity and link transitivity), while it does not require the number of clusters to be known. The clustering effectiveness and link prediction accuracy of our method are demonstrated in simulated and real networks. for this article are available online. [ABSTRACT FROM AUTHOR]

Copyright of Public Money & Management is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, I analyze the consequences of cash flow hedge accounting on portfolio earnings of firms focusing on main changes between IFRS 9 and IAS 39. For this purpose, I develop a simulation study which illustrates the quantitative effects on the accounting entries according to the currently applicable hedge accounting methods. It is especially addressed what accounting differences arise and how these distinctions may affect a firm's earnings. Furthermore, I examine to which firms early switching becomes especially desirable or burdensome. This information is particularly useful to managers and investors. The paper shows that portfolio earnings are affected differently. In the model, IAS 39 may lead to higher or lower earnings for increasing deviations between foreign and domestic interest rates. Additionally, sensitivity to volatility changes varies among the methods. Moreover, a partly ineffective hedging relationship does not necessarily decrease earnings compared to its fully effective counterpart. [ABSTRACT FROM AUTHOR]

This study examines US household methods used to access their bank account, and implications for the use of Alternative Financial Services (AFS) and financial well-being. Latent class analysis and multinomial logistic regression were conducted. Results indicated that 7.7% of households are very likely to access their account through a bank teller (Bank Teller Access Method), 25% are very likely to use all types of technology (All Technology Access Method), 33.5% use all types of access methods but not their smartphone (Traditional Technology Access Method), and 33.8% use all methods (All Modes Access Method). Access method is associated with AFS use. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of COVID-19 and family ownership on earnings management (EM), both accruals (DA) and real (REM). This research also seeks to determine whether there is a substitutional or complementary relationship between DA and REM.The study's sample includes firms listed on the Jordanian market after excluding the banking and insurance sectors from 2017 to 2021. It used feasible generalised least squares estimation (FGLS) regressions to achieve the study's goals. The results reveal a negative and significant correlation between COVID-19 and discretionary accruals (DA), which indicates that COVID-19 restricts DA in Jordanian companies. However, the outcome shows a significant positive relationship between COVID-19 and REM, which indicates that COVID-19 encourages Jordanian companies to practice REM. According to the entrenchment theory, the majority shareholders in a family-owned business environment seek to expropriate the rights of the minority shareholders. Consistent with this theory, the result documents a significant positive correlation between family ownership and DA, indicating that high family ownership manages earnings through accruals. However, this study finds a significant negative relationship between family ownership and REM, indicating that a high concentration of family ownership restricts the practice of REM. This finding aligns with the alignment theory, which argues that the interests of minority and majority shareholders are compatible. These findings indicate a lack of accuracy and reliability in the financial reports in the Jordanian industrial and service enterprises due to the practicing DA by the family-owned companies as well as the outbreak of COVID-19 that led to a rise in the practice of REM. Finally, the findings document that Jordanian companies use REM and DA as complementary tools to maximise their impact on earnings. The findings of earlier research on EM who have used Jordanian-listed companies might not be beneficial in light of the current COVID-19 pandemic. Thus, the current study is one of the first empirical attempts to examine the impact of the COVID-19 pandemic and family ownership on the quality of financial reporting using both EM (DA and REM) in the context of the Jordanian market. The current study's findings are an important contribution to the literature on how family ownership affects the quality of financial reporting (QFR) and how COVID-19 affects the practice of EM. Therefore, the findings of this study can provide all stakeholders with information regarding the QFR in family-controlled companies and explore the accounting implications of the pandemic in order to assist all interested parties, particularly those in developing markets, in making more informed decisions. [ABSTRACT FROM AUTHOR]

This paper investigates total factor productivity growth (TFPG) and its determinants in the Indonesian palm oil sector industries. TFPG is estimated using a growth accounting method. This paper applies the fixed effects model to investigate the determinants of the TFPG. The data is sourced from a manufacturing survey of the Indonesian Bureau of Central Statistics (Badan Pusat Statistika/BPS) for the period 2000–2017. This paper finds that the TFPG of the Indonesian palm oil industry is relatively low. Moreover, output growth, output per worker, export activity, and wages per worker have significant effects on the TFPG. The effect of output growth, which is dominated by the large use of inputs, raises concerns in the aspect of environmental sustainability due to uncontrolled land expansion. [ABSTRACT FROM AUTHOR]

This study examines whether accounting for the nonlinearity of realized volatility leads to better forecast performance. We propose a new realized volatility forecasting model that considers nonlinearities without the assumption of a particular nonlinear model. The proposed model uses the Taylor series approximation method to account for nonlinearities. We applied it to the realized volatility of representative stock indices from the U.S., Japan, the U.K., and China and observed their in-sample nonlinearities. Additionally, we evaluate out-of-sample forecast performance. The empirical results show that realized volatility has nonlinearity, and the proposed models exhibit better forecast performance than standard models. [ABSTRACT FROM AUTHOR]

Generalized estimating equations (G E E) are widely used to analyze longitudinal data; however, they are not appropriate for heteroscedastic data, because they only estimate regressor effects on the mean response – and therefore do not account for data heterogeneity. Here, we combine the G E E with the asymmetric least squares (expectile) regression to derive a new class of estimators, which we call generalized expectile estimating equations (G E E E). The G E E E model estimates regressor effects on the expectiles of the response distribution, which provides a detailed view of regressor effects on the entire response distribution. In addition to capturing data heteroscedasticity, the GEEE extends the various working correlation structures to account for within-subject dependence. We derive the asymptotic properties of the G E E E estimators and propose a robust estimator of its covariance matrix for inference (see our R package, ). Our simulations show that the GEEE estimator is non-biased and efficient, and our real data analysis shows it captures heteroscedasticity. [ABSTRACT FROM AUTHOR]

Starting from a development pilot project that aimed to introduce new water accounting procedures to Cambodia, this article examines interactions between technical experts from abroad and government officials. Drawing on STS, performativity theory, and the anthropology of development, the article shows that the dynamics at the project interface are characterized by parallel and incongruent performances. Visiting technical experts work on the assumption that they are operating at a science-policy interface. Meanwhile, officials align with the demands of technical rationality, aware of its discrepancy with the performance of politics outside the project frame. Two versions of project realities and their relation to broader Cambodian realities are thus performed simultaneously, but awareness of this is not evenly distributed, with significant consequences for the aspiration of development organizations to transfer knowledge. The case study feeds into a subsequent characterization of a more general pattern of sparks and fizzles, in which projects continuously start up, while efforts to bootstrap technology transfer peter out as they end. This pattern may be endemic to development projects that operate on the assumption of a science-policy interface that is not really there. [ABSTRACT FROM AUTHOR]

We investigate the value relevance of two different accounting methods, predecessor vs. acquisition, for business combination under common control (BCUCC) in China. Based on the return and price models, we find that net income under the predecessor method is of higher value relevance than that under the acquisition method. Further analysis suggests that the difference appears to be driven by uncertainties in fair value estimation surrounding the BCUCC and that net incomes under predecessor method can better predict future earnings and future operating cash flows than under the acquisition method. Our research provides some initial evidence to support the use of the predecessor method in China, and at the same time, we discuss implications for the IASB standard setting project for the BCUCC. [ABSTRACT FROM AUTHOR]

Rangeland conditions in the Lesotho highland dam catchment areas is important for local livelihoods and regional water supply. We investigated changes in land cover and condition from 1991 (before construction) to 2013, using Landsat imagery. The Normalised Difference Vegetation Index (NDVI) decreased in the catchment areas, while increasing within two protected areas. NDVI decreases were greatest close to the dams and in the high altitude summer grazing areas. Land cover maps were generated for 1993, 2005 and 2013, using structural vegetation classes, as well as categories of grassland based on NDVI. High altitude areas were characterised by grasslands changing to lower NDVI categories, indicating overgrazing in climax sourveld grasslands. Mid-altitude areas were characterised by grasslands changing to higher NDVI categories and increases in woody vegetation, indicating overgrazing in Sweetveld. At lower altitudes, the increase in cultivated areas suggested disproportionately high population growth in the catchment areas. The results suggest that there has been widespread degradation that appears to be more as a result of overgrazing than climate change. The study demonstrates the importance of using a combination of land cover, NDVI and field data in assessing degradation. Natural capital accounting methods provide a useful framework for documenting, monitoring and understanding changes in ecosystem condition. [ABSTRACT FROM AUTHOR]

Annual CO2emission tallies for 210 coal-fired power plants during 2009 were more accurately calculated from fuel consumption records reported by the U.S. Energy Information Administration (EIA) than measurements from Continuous Emissions Monitoring Systems (CEMS) reported by the U.S. Environmental Protection Agency. Results from these accounting methods for individual plants vary by ± 10.8%. Although the differences systematically vary with the method used to certify flue-gas flow instruments in CEMS, additional sources of CEMS measurement error remain to be identified. Limitations of the EIA fuel consumption data are also discussed. Consideration of weighing, sample collection, laboratory analysis, emission factor, and stock adjustment errors showed that the minimum error for CO2emissions calculated from the fuel consumption data ranged from ± 1.3% to ± 7.2% with a plant average of ± 1.6%. This error might be reduced by 50% if the carbon content of coal delivered to U.S. power plants were reported. [ABSTRACT FROM PUBLISHER]

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This article considers the problem of testing a finite number of moment inequalities. For this problem, Romano, Shaikh, and Wolf proposed a two-step testing procedure. In the first step, the procedure incorporates information about the location of moments using a confidence region. In the second step, the procedure accounts for the use of the confidence region in the first step by adjusting the significance level of the test appropriately. Its justification, however, has so far been limited to settings in which the number of moments is fixed with the sample size. In this article, we provide weak assumptions under which the same procedure remains valid even in settings in which there are "many" moments in the sense that the number of moments grows rapidly with the sample size. We confirm the practical relevance of our theoretical guarantees in a simulation study. We additionally provide both numerical and theoretical evidence that the procedure compares favorably with the method proposed by Chernozhukov, Chetverikov, and Kato, which has also been shown to be valid in such settings. [ABSTRACT FROM AUTHOR]

The paper examines if COVID-19 crisis has brought changes in companies' approach on corporate reporting, with focus on annual reports. The research method is based on text mining techniques in order to build measures of readability and tone of uncertainty of annual reports, given the information published by the companies listed on four stock exchanges from Europe, namely the Bucharest Stock Exchange, ATHEX Stock Exchange, IBEX-35, and WIG-20 between 2017–2020. Findings emphasize, through text mining, multivariate analysis, and topic modeling, that the analyzed reports are less extensive in times of pandemic and tend to become more generic. Among firms' financial performance metrics considered in our models, we found that there is a significant association only between annual reports textual characteristics and respectively, firm size, price earnings ratio and accruals reported. We prove as well significant stock exchange effects and industry effects. Our results show a slight decrease in annual reports readability, while the tone of uncertainty is more prominent within firms listed on less mature stock exchanges. [ABSTRACT FROM AUTHOR]

Catalyst free efficient and straightforward method is accounted for the synthesis of 2,4-disubstituted quinazolines utilizing urea was seen as a modest, nontoxic, easily biodegradable, and powerful reaction medium. This productive and straight forward method furnished the corresponding 2,4-disubstituted quinazolines in significant yields employing a one-pot three-component reaction of 2-amino benzophenones, aldehyde, and urea under aerobic oxidation conditions. Additionally, 2-methyl-4-phenylquinazolines were synthesized using ammonium acetate with readily available 2-amino benzophenones. [ABSTRACT FROM AUTHOR]

What do people really think of when they say they believe in repressed traumatic memory? In two studies (NStudy 1 = 3158; NStudy 2 = 305) using an integrative method taking into account recent methodological discussions, we found that, in total, 2458 participants (71% of the two combined samples) reported that they believed in repressed memory. In Study 1, based on separate questions on the whole group, we found 71% of agreement with the concept of repression, 74% with the concept of unconscious repression, and 54% with the concept of deliberate memory suppression. Participants with no memory of childhood abuse endorsed unconscious and deliberate mechanisms less than those with such memories. In Study 2, the order in which the items were presented was not associated with the beliefs in the different statements. Overall, our results show that people see repression as an unconscious mechanism. We suggest the use of within-subject designs and/or follow-up questions to determine how people understand the concept of repression. Such adherence to this controversial concept can have adverse implications in the clinical and legal arenas. [ABSTRACT FROM AUTHOR]

My article focuses on Descartes' Third Meditation, in which he seeks to gain a knowledge of God as his creator. While Descartes offers two proofs of God's existence in this meditation—the first to prove that God is the cause of his idea of God, and the second to prove that God is the cause of his idea of God and that God is the cause of Descartes, insofar as he is a thinking thing—I show that these proofs fail to establish that God is the cause of Descartes. This is not a failure on the part of these proofs, for ultimately Descartes intends the knowledge of God as his creator to be obtained through meditation, and not argumentation. The two proofs of God's existence have a role to play in guiding Descartes to grasp, through meditation, the relation of his idea of God and the idea of the self qua thinking thing. Toward the end of the article, I show that my study is in accordance with Descartes' account of the method he employs in the Meditations, as detailed in the Replies to Objections II. [ABSTRACT FROM AUTHOR]

In this study, we examine the trade-offs between earnings management (both accruals and real) and covenant violations by examining how they are associated with future accounting and stock market performance. We analyze a matched-pair sample of covenant violation firms with non-violation firms that have a similar risk of a covenant violation. We have three main findings. First, our evidence indicates that covenant violations are costly events for shareholders as lenders appear to use their control rights in ways that increase the likelihood of loan repayment but impose costs for shareholders. Second, there is limited evidence indicating covenant-related accrual-earnings management activities impose significant costs on shareholders, but we find shareholders are worse off following unsuccessful real earnings management. Third, our evidence indicates that, on average, shareholders at high violation risk firms are better off when their firms successfully engage in accruals earnings management to avoid a violation compared to shareholders at firms that violate a covenant but do not manage earnings. Thus, covenant-related earnings management may be in the best interests of shareholders and is not necessarily evidence of shareholder-manager agency conflicts. [ABSTRACT FROM AUTHOR]

Policy evaluation is interested in studying what works, for whom, and under which circumstances. That is, it is interested in outcomes and their causes. Analyzing the former involves particular challenges when dealing with development policy since development is a contested concept. Therefore, it is pertinent to discuss the ends of policy. The Capability Approach (CA), a people-centered approach that defines development as freedom, is described. For the analysis of the means to those ends, which is the study of causality, fuzzy set Qualitative Comparative Analysis (fsQCA), a method useful to account for multiple causality, is introduced. Since policies are likely to establish similar goals for different beneficiaries from different contexts, this article argues that employing the CA and fsQCA in tandem for the assessment of policy can prove rewarding. [ABSTRACT FROM AUTHOR]

It used to be said that academics doing ethnographic research were able to have brief forays into other cultures, but to have permanent membership would result in 'career suicide'. Our methodology takes into account the changing nature of academia, both exploiting and endorsing the dual role status held by many academics who have fractional appointments at higher education institutions. We use data from a study on women's experiences of discovering partner infidelity to explore the benefits and drawbacks of being a 'Worker-Researcher'. Participants were interviewed whilst having an eyelash extension treatment carried out by the second author who was employed as a part-time beauty therapist. The data produced using this methodology was rich and revealing, due in part to the level of rapport engendered by the relationship between the two protagonists and also due to the confessional culture of beauty salons. The reduction or reversal of traditional researcher/participant hierarchy soothes the frequently discussed concerns about exploitation of participants. The exploitation of Worker-Researchers is discussed as a potential drawback of this methodology. [ABSTRACT FROM AUTHOR]

Previous research has tended to use a global threshold of proximity to determine neighbors, neglecting spatial heterogeneity. Flexible thresholds implemented by adaptive search radii methods account for either the spatial structures or the non-spatial similarities of objects, but few consider both. By combining the spatial and non-spatial information of objects, we propose a novel approach that can automatically determine the neighbors that are strongly related to the object of interest. We introduce the sparse reconstruction technique from the signal processing domain, which aims to remove trivial relationships in a dataset. We extend the sparse reconstruction model by assuring three principles in spatial data, including retention of the correlation of data in the non-spatial attribute domain, preservation of local dependencies in the spatial domain, and removal of trivial relationships. Extensive experiments, based on road network missing value imputation and building clustering, show that our approach can make better use of both spatial and non-spatial information than a simple addition of them. [ABSTRACT FROM AUTHOR]

In prognostic/diagnostic medical research, it is often the goal to identify a biomarker that differentiates between patients with and without a condition, or patients that will have good or poor response to a given treatment. The statistical literature is abundant with methods for evaluating single biomarkers for these purposes. However, in practice, a single biomarker rarely captures all aspects of a disease process; therefore, it is often the case that using a combination of biomarkers will improve discriminatory ability. A variety of methods have been developed for combining biomarkers based on the maximization of some global measure or cost-function. These methods usually create a score based on a linear combination of the biomarkers, upon which the standard single biomarker methodologies (such as the Youden's index) are applied. However, these single biomarker methodologies do not account for the multivariable nature of the combined biomarker score. In this article we present generalized inference and bootstrap approaches to estimating confidence intervals for the Youden's index and corresponding cut-point for a combined biomarker. These methods account for inherent dependencies and provide accurate and efficient estimates. A simulation study and real-world example utilize data from a Duchene Muscular Dystrophy study are also presented. [ABSTRACT FROM AUTHOR]