The Impact of Initial Information Ambiguity on the Accuracy of Analytical Review Judgments

2012 ◽  
Vol 31 (2) ◽  
pp. 113-129 ◽  
Author(s):  
Benjamin L. Luippold ◽  
Thomas E. Kida
Keyword(s):  
Financial Data ◽  
Data Availability ◽  
Data Set ◽  
Judgment Accuracy ◽  
Initial Information ◽  
Information Set ◽  
Analytical Review ◽  
Analytical Procedures ◽  
Information Ambiguity ◽  
The Impact

SUMMARY Analytical procedures require that auditors develop and test hypotheses about possible fluctuations in a firm's financial data. Research in psychology suggests that the initial information ambiguity that exists prior to hypothesis generation may affect not only the initial hypothesis set, but also final judgment accuracy. We argue in this paper that information ambiguity can be caused by two primary variables, data sufficiency and data complexity, and examine how these variables affect judgment accuracy during analytical review. Ninety-four staff auditors completed analytical procedures for a company with an error seeded into its financial statements. Information ambiguity was varied across three levels by manipulating both the sufficiency and complexity of the data (insufficient/complex, sufficient/complex, and sufficient/not complex). Participants generated hypotheses that might explain the observed fluctuations in the data, then received a comprehensive financial data set (that was identical for all groups) and were asked to identify the cause of the fluctuations. The results indicate that when auditors are initially exposed to more ambiguous information (either due to its insufficiency or complexity), they are less likely to ultimately identify the error causing the fluctuations, even though they have access to the same unambiguous information set prior to making their final judgments. Implications of these results for audit research and practice are discussed. Data Availability: Contact the authors.

Land under roads and the power of politic

2018 ◽  
Vol 30 (1) ◽  
pp. 73-91
Author(s):  
Hassan Mohamed Abdalla Elhawary
Keyword(s):  
Financial Reporting ◽  
Local Governments ◽  
Relevant Literature ◽  
Policy Recommendations ◽  
Data Set ◽  
Financial Reports ◽  
Content Type ◽  
Early Adoption ◽  
Analytical Review ◽  
The Impact

Purpose The purpose of this paper is to answer the following questions: What are the theoretical and practical antecedents for recognising land under roads (LUR) as an asset in local government financial reports? Why was the process of regulating this aspect of accounting practice so protracted and so controversial? Design/methodology/approach The method used a critical analytical review and synthesis of relevant literature. Findings This study rejects the recognition of LUR, and suggests that the requirements to account for LUR should be withdrawn immediately. Regardless of the way that the debate has evolved as to the need or otherwise to value LUR or the methodology to be adopted, until the issue of a consistent, standards-based data set is addressed, there is unlikely to be a unified useful outcome. Research limitations/implications The study’s findings provided opportunity to reach an overall conclusion and make policy recommendations regarding the saga of accounting for LUR by Australian local governments. However, the ability to generalise beyond Australia to other countries would need to be tested by additional research. Practical implications The study’s findings provided assessment of the impact of valuing LUR on financial reporting by local governments and suggested policy recommendations. Social implications This study provided an understanding of Australian local governments’ accounting choices in regard to the valuation of LUR and documented the history of early adoption of valuation of LUR by local governments. Originality/value The literature on the public sector and accrual accounting is extensive and varied. However, there have been only isolated studies on the specific issue of LUR (Barton, 1999a, 1999b; Hoque, 2004; Rowles et al., 1998a, 1998b, 1998c, 1999). This study adds to the few isolated studies on the specific issue of accounting for LUR. Originality/value – This study provided policymakers with rich information about accounting for LUR and, it should have the capacity to impact on the future policy directions and recommendations.

scholarly journals Brazilian Modeling of COVID-19(BRAM-COD): a Bayesian Monte Carlo approach for COVID-19 spread in a limited data set context

2020 ◽  
Author(s):  
Samy Dana ◽  
Alexandre B. Simas ◽  
Bruno A. Filardi ◽  
Rodrigo N. Rodriguez ◽  
Leandro da Costa Lane Valiengo ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Critical Care ◽  
Current Trend ◽  
Sao Paulo ◽  
Data Availability ◽  
Monte Carlo Algorithm ◽  
São Paulo ◽  
Data Set ◽  
Major Health Problem ◽  
The Impact

1ABSTRACT1.1BackgroundThe new coronavirus respiratory syndrome disease (COVID-19) pandemic has become a major health problem worldwide. Many attempts have been devoted to modeling the dynamics of new infection rates, death rates, and the impact of the disease on health systems and the world economy. Most of these modeling concepts use the Susceptible-Infectious-Susceptible (SIS) and Susceptible-Exposed-Infected-Recovered (SEIR) compartmental models; however, wide imprecise outcomes in forecasting can occur with these models in the context of poor data, low testing levels, and a nonhomogeneous population.1.2ObjectivesTo predict Brazilian ICU beds demand over time and during COVID-19 pandemic “peak”.1.3MethodsIn the present study, we describe a Bayesian COVID-19 model combined with a Hamiltonian Monte Carlo algorithm to forecast quantitative predictions of infections, number of deaths and the demand for critical care beds in the next month in the Brazilian context of scarce data availability. We also estimated COVID-19 spread tendency in the state of São Paulo and forecasted the demand for critical care beds, as São Paulo is the epicenter of the Latin America pandemic.1.4ResultsOur model estimated that the number of infected individuals would be approximately 6.5 million (median) on April 25, 2020, and would reach 16 to 17 million (median) by the end of August 2020 in Brazil. The probability that an infected individual requires ICU-level care in Brazil is 0.5833%. Our model suggests that the current level of mitigation seen in São Paulo is sufficient to reach Rt < 1, thus attaining a “peak” in the short term. In São Paulo state, the total number of deaths is estimated to be around 9,000 (median) with the 2.5% quantile being 6,600 deaths and the 97.5% quantile being around 13,350 deaths. Also, São Paulo will not attain its maximum capacity of ICU beds if the current trend persists over the long term.1.5ConclusionsThe COVID-19 pandemic should peak in Brazil between May 8 and May 20, 2020 with a fatality rate lower than that suggested in the literature. The northern and northeastern regions of Brazil will suffer from a lack of available ICU beds, the southern and central-western regions appear to have sufficient ICU beds, finally, the southeastern region seems to have enough ICU beds only if it shares private beds with the publicly funded Unified Health System (SUS). The model predicts that, if the current policies and population behavior are maintained throughout the forecasted period, by the end of August 2020, Brazil will have around 7.6% to 8.2% of its population immune to COVID-19.

Realigning Auditors' Accountability: Experimental Evidence

2018 ◽  
Vol 94 (3) ◽  
pp. 233-250 ◽  
Author(s):  
Patrick J. Hurley ◽  
Brian W. Mayhew ◽  
Kara M. Obermire
Keyword(s):  
Audit Quality ◽  
Institutional Design ◽  
Additional Treatment ◽  
Data Availability ◽  
Third Party ◽  
Judgment Accuracy ◽  
The Third ◽  
Experimental Economic ◽  
Economic Markets ◽  
The Impact

ABSTRACT We use experimental economic markets to examine the impact of changing institutional design features on audit quality. Specifically, we manipulate auditors' economic accountability to managers by altering who hires the auditor—a manager or an independent third party—and auditors' psychological accountability to investors by explicitly stating that the auditor is hired on the investors' behalf. Our design shifts auditors' accountability from managers, who have directional goal preferences, to investors, who prefer judgment accuracy. We find that removing auditors' economic accountability to managers and replacing it with psychological accountability to investors significantly increases audit quality. This increase in audit quality occurs despite the independent third party randomly hiring auditors. In an additional treatment, we incorporate auditor accuracy into the third-party hiring algorithm and find even higher audit quality. Our results suggest that altering auditors' accountability relationships can significantly enhance audit quality. Data Availability: The laboratory market data used in this study are available from the authors upon request.

scholarly journals Drug Positivity Findings from a Universal Umbilical Cord Tissue Drug Analysis Program in Appalachia

2020 ◽  
Author(s):  
Panitan Yossuck ◽  
Danyel H Tacker
Keyword(s):  
Drug Use ◽  
Umbilical Cord ◽  
Drug Exposure ◽  
Parent Drug ◽  
Drug Analysis ◽  
Data Availability ◽  
Data Sets ◽  
Data Set ◽  
Umbilical Cord Tissue ◽  
The Impact

Abstract Background West Virginia has high rates of opioid-related health crises and deaths that extend to pregnant women and newborns. Our institutional screening approach has included universal umbilical cord tissue drug analysis (UCTDA) since 2013. The objective of this study was to retrospectively report incidence of in utero drug exposure using UCTDA data. Methods Two sequential UCTDA data sets (October 2013 to September 2015, and October 2016 to September 2018) represent interrupted epochs given changes in interfaced data availability. UCTDA positivity (by drug class and parent drug) and numbers of drugs detected in each specimen were retrospectively analyzed. THC was removed from the analysis because of discontinuous testing, and 4 opioids were separated from the data set given the potential for both therapeutic and illicit use. Results UCTDA specimens that were positive for drugs (22% overall) decreased between Epochs 1 and 2, from 25% to 20%. Increased positivity was noted for hydrocodone (+407%), oxycodone (+240%), amphetamines (+506%), and cocaine (+417%). Fentanyl and morphine positivity decreased by 75% and 18%, respectively, whereas buprenorphine detection increased 195%. Most positive specimens (80% overall) had 1 drug present, but specimens positive for 2 to 6 discrete drugs were found. Conclusion Universal UCTDA allows for unbiased assessment of drug exposure in infants. With the additional knowledge of therapeutic indications for drug use, UCTDA may allow for analysis of trends in illicit drug use and the impact of interventions to curb neonatal abstinence syndrome.

scholarly journals Which spatial discretization for which distributed hydrological model?

2007 ◽  
Vol 4 (2) ◽  
pp. 777-829 ◽  
Author(s):  
J. Dehotin ◽  
I. Braud
Keyword(s):  
Land Use ◽  
Input Data ◽  
Data Availability ◽  
Hydrological Processes ◽  
Distributed Hydrological Model ◽  
Spatial Discretization ◽  
Water Balance Components ◽  
Data Set ◽  
Distance Map ◽  
The Impact

Abstract. Distributed hydrological models are valuable tools to derive distributed estimation of water balance components or to study the impact of land-use or climate change on water resources and water quality. In these models, the choice of an appropriate spatial scale for the modelling units is a crucial issue. It is obviously linked to the available data and their scale, but not only. For a given catchment and a given data set, the "optimal" spatial discretization should be different according to the problem to be solved and the objectives of the modelling. Thus a flexible methodology is needed, especially for large catchments, to derive modelling units by performing suitable trade-off between available data, the dominant hydrological processes, their representation scale and the modelling objectives. In order to represent catchment heterogeneity efficiently according to the modelling goals, and the availability of the input data, we propose to use nested discretization, starting from a hierarchy of sub-catchments, linked by the river network topology. If consistent with the modelling objectives, the active hydrological processes and data availability, sub-catchment variability can be described using a finer nested discretization. The latter takes into account different geophysical factors such as topography, land-use, pedology, but also suitable hydrological discontinuities such as ditches, hedges, dams, etc. For small catchments, the landscape features such as agricultural fields, buildings, hedges, river reaches can be represented explicitly, as well as the water pathways between them. For larger catchments, such a representation is not feasible and simplification is necessary. For the sub-catchments discretization in these large catchments, we propose a flexible methodology based on the principles of landscape classification, using reference zones. These principles are independent from the catchment size. They allow to keep suitable features which are required in the catchment description in order to fulfil a specific modelling objective. The method leads to unstructured and homogeneous areas within the sub-catchments, which can be used as modelling units. It avoids map smoothing by suppressing the smallest units, the role of which can be very important in hydrology, and provides a confidence map (the distance map) for the classification. The confidence map can be used for further uncertainty analysis of modelling results. The final discretization remains consistent with the scale of input data and that of the source maps. We present an illustration of the method using available data from the upper Saône catchment (11 700 km2) in France. We compare the results with more traditional mapping approach, according to the landscape representation and input data scale.

The Effects of Visualization and Interactivity on Calibration in Financial Decision-Making

2013 ◽  
Vol 26 (1) ◽  
pp. 25-58 ◽  
Author(s):  
Fengchun Tang ◽  
Traci J. Hess ◽  
Joseph S. Valacich ◽  
John T. Sweeney
Keyword(s):  
Decision Making ◽  
Visual Representations ◽  
Decision Makers ◽  
Financial Data ◽  
Data Availability ◽  
Financial Decision Making ◽  
Interactive Visualizations ◽  
Financial Decision ◽  
Informational Cues ◽  
The Impact

ABSTRACT With the increased use of XBRL, financial data are readily available in a universal format, enabling users to dynamically render data with a variety of visual, interactive representations. However, the impact of these interactive visual representations on financial decision-making has received little attention. Further, decision-making research suggests that the presentation of a task (i.e., presentation format) can influence decision-making outcomes such as accuracy, confidence, and the calibration between accuracy and confidence. This study examines how visualization and interactivity affect accuracy, confidence, and calibration in a financial decision-making context. Decision-makers are typically overconfident, and this research proposes that visualization and interactivity provide more informational cues, which can actually further increase overconfidence and reduce calibration in some contexts. An experiment conducted with 157 participants supports the prediction that visualization and interactivity features can increase decision-maker overconfidence. However, interactive visualization, when both interface features are present, increases confidence while also increasing accuracy. As a result, when interactivity and visualization are offered individually, decision-makers are less calibrated, but when both features are offered, decision-makers are more calibrated. Implications for users and designers of interactive visualizations with financial data are discussed. Data Availability: Data are available from the authors upon request.

Commodity exports to China and economic growth

2015 ◽  
Vol 6 (4) ◽  
pp. 401-416
Author(s):  
Ariuna Taivan ◽  
Gibson Nene ◽  
Inoussa Boubacar
Keyword(s):  
Economic Growth ◽  
Growth Rate ◽  
Time Frame ◽  
Data Availability ◽  
African Countries ◽  
Data Set ◽  
Content Type ◽  
Commodity Export ◽  
Per Capita ◽  
The Impact

Purpose – The purpose of this study is to empirically examine the effect of commodity exports from Africa to China on the growth rate of per capita gross domestic product (GDP) after controlling for variables that have been found to be important determinants of economic growth. This study uses a panel of 23 African countries for the period of 2001-2011. Design/methodology/approach – The authors make use of a Barro-type empirical economic growth model which uses per capita GDP as the dependent variable. With regard to independent variables, the authors examine the China effect after controlling for variables that have been found to affect economic growth. To account for the China effect, we use the following three measures of trade with China: commodity export to China, commodity export to China relative to total export and commodity export to China relative to the world. The authors use panel data from 2001 to 2011. Findings – Results indicate that the magnitudes of the effect, while statistically significant, are not large enough to induce positive growth rates. The results also indicate that the magnitudes of the effects depend on the colonial origin of the African countries. Research limitations/implications – The data are limited to the 2001-2011 time frame because of data availability issues. This time frame does capture the era when China increased its trade with Africa. The choices of variables were also affected by data availability. However, the authors managed to find data on the main drivers of economic growth. Further research is needed to gain a more comprehensive analysis of the effects of commodity trade with China on Africa’s economy, given the partial character of the data set used in this study. Similarly, there is also a need for more detailed information on China’s trade activities. Practical implications – While the results of this study show an improvement in the per capita growth rate, the changes are not large enough to put African countries on a path to a sustained prosperity. African governments which trade with China should consider investing more in manufacturing, so that they create more jobs locally and benefit more from their exports. Social implications – The China–Africa relationship shows a small positive impact on societal well-being. Originality/value – To the best of the authors’ knowledge, none of the existing studies on China–Africa relations attempted to understand the impact of China’s economic activity on the standards of living of African residents, where standard of living is measured by economic growth. The current study aims to bridge this gap. This study complements existing studies and uses a data set and methodology that has not been used before on this issue.

Age at Exposure to Parental Suicide and the Subsequent Risk of Suicide in Young People

Crisis ◽  
2018 ◽  
Vol 39 (1) ◽  
pp. 27-36 ◽  
Author(s):  
Kuan-Ying Lee ◽  
Chung-Yi Li ◽  
Kun-Chia Chang ◽  
Tsung-Hsueh Lu ◽  
Ying-Yeh Chen
Keyword(s):  
Young People ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Birth Registry ◽  
Data Set ◽  
Parental Suicide ◽  
The Impact ◽  
Age At Exposure

Abstract. Background: We investigated the age at exposure to parental suicide and the risk of subsequent suicide completion in young people. The impact of parental and offspring sex was also examined. Method: Using a cohort study design, we linked Taiwan's Birth Registry (1978–1997) with Taiwan's Death Registry (1985–2009) and identified 40,249 children who had experienced maternal suicide (n = 14,431), paternal suicide (n = 26,887), or the suicide of both parents (n = 281). Each exposed child was matched to 10 children of the same sex and birth year whose parents were still alive. This yielded a total of 398,081 children for our non-exposed cohort. A Cox proportional hazards model was used to compare the suicide risk of the exposed and non-exposed groups. Results: Compared with the non-exposed group, offspring who were exposed to parental suicide were 3.91 times (95% confidence interval [CI] = 3.10–4.92 more likely to die by suicide after adjusting for baseline characteristics. The risk of suicide seemed to be lower in older male offspring (HR = 3.94, 95% CI = 2.57–6.06), but higher in older female offspring (HR = 5.30, 95% CI = 3.05–9.22). Stratified analyses based on parental sex revealed similar patterns as the combined analysis. Limitations: As only register-­based data were used, we were not able to explore the impact of variables not contained in the data set, such as the role of mental illness. Conclusion: Our findings suggest a prominent elevation in the risk of suicide among offspring who lost their parents to suicide. The risk elevation differed according to the sex of the afflicted offspring as well as to their age at exposure.

The Impact of Partner Knowledge on Judgment Accuracy

2007 ◽  
Author(s):  
Matthew E. Jacovina ◽  
Richard J. Gerrig
Keyword(s):  
Judgment Accuracy ◽  
The Impact ◽  
Partner Knowledge
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