scholarly journals Using the Newcomb–Benford law to study the association between a country’s COVID-19 reporting accuracy and its development

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Vadim S. Balashov ◽  
Yuxing Yan ◽  
Xiaodi Zhu
Keyword(s):  
Goodness Of Fit ◽  
Developed Countries ◽  
Cumulative Number ◽  
Reporting Accuracy ◽  
Universal Healthcare ◽  
Developmental Indicators ◽  
Developmental Index ◽  
Reported Data ◽  
The Relationship ◽  
Benford Law

AbstractThe COVID-19 pandemic has spurred controversies related to whether countries manipulate reported data for political gains. We study the association between accuracy of reported COVID-19 data and developmental indicators. We use the Newcomb–Benford law (NBL) to gauge data accuracy. We run an OLS regression of an index constructed from developmental indicators (democracy level, gross domestic product per capita, healthcare expenditures, and universal healthcare coverage) on goodness-of-fit measures to the NBL. We find that countries with higher values of the developmental index are less likely to deviate from the Newcomb-Benford law. The relationship holds for the cumulative number of reported deaths and total cases but is more pronounced for the death toll. The findings are robust for second-digit tests and for a sub-sample of countries with regional data. The NBL provides a first screening for potential data manipulation during pandemics. Our study indicates that data from autocratic regimes and less developed countries should be treated with more caution. The paper further highlights the importance of independent surveillance data verification projects.

scholarly journals Who Manipulates Data During Pandemics? Evidence From Newcomb-Benford Law

2021 ◽  
Author(s):  
Vadim S. Balashov ◽  
Yuxing Yan ◽  
Xiaodi Zhu
Keyword(s):  
Gdp Per Capita ◽  
Swine Flu ◽  
Cumulative Number ◽  
Healthcare Expenditures ◽  
Universal Healthcare ◽  
Developmental Indicators ◽  
Healthcare Coverage ◽  
Per Capita ◽  
Benford Law ◽  
Universal Healthcare Coverage

Abstract The COVID-19 pandemic has spurred controversies related to whether countries manipulate reported data for political gains. We study the association between accuracy of reported COVID-19 data and developmental indicators. We use the Newcomb-Benford law (NBL) to gauge data accuracy. We run an OLS regression of developmental indicators (EIU index, GDP per capita, healthcare expenditures, and universal healthcare coverage index) on goodness-of-fit measures to the NBL. We find that democratic countries, countries with the higher gross domestic product (GDP) per capita, higher healthcare expenditures, and better universal healthcare coverage are less likely to deviate from the Newcomb-Benford law. The relationship holds for the cumulative number of reported deaths and total cases but is more pronounced for the death toll. The findings are robust for second-digit tests, for a sub-sample of countries with regional data, and in relation to the previous swine flu (H1N1) 2009–2010 pandemic. The NBL provides a first screening for potential data manipulation during pandemics. Our study indicates that data from autocratic regimes and less developed countries should be treated with more caution. The paper further highlights the importance of independent surveillance data verification projects.JEL classification: F5, I10, I18, O1, O57, P52.

Enhancing Spatial Ability Through Sport Practice

2012 ◽  
Vol 33 (2) ◽  
pp. 83-88 ◽  
Author(s):  
David Moreau ◽  
Jérome Clerc ◽  
Annie Mansy-Dannay ◽  
Alain Guerrien
Keyword(s):  
Mental Rotation ◽  
Spatial Representations ◽  
Mental Rotation Test ◽  
Sport Training ◽  
Sport Practice ◽  
Undergraduate University Students ◽  
Before And After ◽  
Cognitive Plasticity ◽  
Reported Data ◽  
The Relationship

This experiment investigated the relationship between mental rotation and sport training. Undergraduate university students (n = 62) completed the Mental Rotation Test ( Vandenberg & Kuse, 1978 ), before and after a 10-month training in two different sports, which either involved extensive mental rotation ability (wrestling group) or did not (running group). Both groups showed comparable results in the pretest, but the wrestling group outperformed the running group in the posttest. As expected from previous studies, males outperformed women in the pretest and the posttest. Besides, self-reported data gathered after both sessions indicated an increase in adaptive strategies following training in wrestling, but not subsequent to training in running. These findings demonstrate the significant effect of training in particular sports on mental rotation performance, thus showing consistency with the notion of cognitive plasticity induced from motor training involving manipulation of spatial representations. They are discussed within an embodied cognition framework.

scholarly journals Using Benford’s law to assess the quality of COVID-19 register data in Brazil

2020 ◽  
Author(s):  
Lucas Silva ◽  
Dalson Figueiredo Filho
Keyword(s):  
Goodness Of Fit ◽  
Epidemiological Surveillance ◽  
Evidence Based ◽  
Mean Absolute Deviation ◽  
Chi Square ◽  
Absolute Deviation ◽  
Distortion Factor ◽  
Benford Law ◽  
Official Data

Abstract We employ Newcomb–Benford law (NBL) to evaluate the reliability of COVID-19 figures in Brazil. Using official data from February 25 to September 15, we apply a first digit test for a national aggregate dataset of total cases and cumulative deaths. We find strong evidence that Brazilian reports do not conform to the NBL theoretical expectations. These results are robust to different goodness of fit (chi-square, mean absolute deviation and distortion factor) and data sources (John Hopkins University and Our World in Data). Despite the growing appreciation for evidence-based-policymaking, which requires valid and reliable data, we show that the Brazilian epidemiological surveillance system fails to provide trustful data under the NBL assumption on the COVID-19 epidemic.

scholarly journals Early Education Care from Its Practitioners to Achieve Sustainability

2021 ◽  
Vol 13 (6) ◽  
pp. 3396
Author(s):  
Óscar Gavín-Chocano ◽  
David Molero ◽  
Inmaculada García-Martínez
Keyword(s):  
Early Intervention ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Satisfaction With Life ◽  
Well Being ◽  
Satisfaction With Life Scale ◽  
Life Scale ◽  
Fit Index ◽  
The Relationship ◽  
Early Intervention Professionals

(1) Background: Early intervention professionals are involved in the reconceptualisation of their service due to the exceptional situation caused by the COVID-19 epidemic, within the family context and aware of the children’s needs, with an impact on their emotional well-being to ensure sustainability. An analysis of their socio–emotional profile and training is increasingly needed to face their professional development effectively; (2) Methods: In this study, 209 early intervention professionals participated (n = 209), with an average age of 37.62 (±9.02). The following instruments were used: Satisfaction with Life Scale (SWLS), Wong Law Emotional Intelligence Scale (WLEIS-S) and the Utrecht Work Engagement Scale (UWES-9). The purpose of the study was to examine the relationship between early intervention (EI) and engagement as predictors of greater life satisfaction using Structural Equation Modelling (SEM). (3) Results: There exists a relationship between some dimensions of the instruments used (p < 0.01). The model obtained good structural validity (χ² = 3.264; Root Mean Square Error of Approximation (RMSEA) =.021; Goodness-of-Fit Index (GFI) = 0.991; Comparative Goodness of Fit Index (CFI) = 0.999; Incremental Fit Index (IFI) = 0.999). Subsequently, the results described above were verified through Bayesian statistics, thereby reinforcing the evidence provided; (4) Conclusions: Findings highlight the importance of providing professionals with emotional tools and strategies, from the educational context, in order to carry out their activity effectively and ensure the sustainability within the current situation, while remaining fully engaged.

scholarly journals Time series analysis of the relationship between diarrhea in children and Rota 2 vaccine in the Fanteakwa District of the eastern region of Ghana

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
James Atampiiga Avoka ◽  
Elvis J. Dun-Dery ◽  
Issah Seidu ◽  
Armel N. E. Abou ◽  
Paul Twene ◽  
...  
Keyword(s):  
Pearson Correlation ◽  
Developed Countries ◽  
Seasonal Effects ◽  
Eastern Region ◽  
Least Developed Countries ◽  
R Software ◽  
Significant Difference ◽  
Severe Gastroenteritis ◽  
Access To Medical Care ◽  
The Relationship

Abstract Background Rotavirus is considered the main causal factor of severe gastroenteritis among infants and children globally. The association with severe rotavirus infection is mostly worse among the least developed countries, mainly due to inadequate access to medical care and poverty. This study was conducted to determine the seasonal effects in respect of diarrhea cases in children, the association between diarrhea cases and Rota2 vaccine in the Fanteakwa District of the Eastern Region of Ghana. Methods The study compares monthly diarrhea cases against children vaccinated with Rota2 extracted from DHIMS2 spanning May 2012 to December 2017 in Fanteakwa District. A univariate association between diarrhea cases and children vaccinated with Rota 2 was conducted using the R-software version 3.4.4 with the use of forecast, tseries and TSAPred. Pearson Correlation coefficient was also computed between monthly diarrhea cases and Rota 2 as well as lagged values of Rota 2 and Diarrhea cases. Results The study shows that February recorded the highest average number of diarrhea cases (172) over the period 2012 to 2017 with a standard deviation of 59. However, a one-way analysis of variance shows a significant difference amongst the monthly averages with an F-statistic of 0.042 and P-value of 0.064. It is observed that the correlations between each of the Rota2 doses and the lagged cases are positive, showing higher Rota2 doses a month ago ((Xt − 1),0.346 to0.735), two months ago ((Xt − 2),0.383 to 0.746), three months ago ((Xt − 3), 0.330 to 0.737) and four months ago ((Xt − 4), 0.236 to 0.723) are associated with lower diarrhea cases. The results also show that an increase in the previous two month’s Rota2 figures by 100 is associated with a significant decrease in the currently expected diarrhea cases by approximately 36. Conclusion Seasonal variations exist in the occurrence of diarrhea in children, with January recording the highest number of diarrhea cases (172). There is a relationship between episodes of diarrhea in children and Rota2 (p-value = 0.064); thus, the more children are vaccinated with Rota2, the less diarrhea cases are recorded. Diarrhea cases in Fanteakwa district are generally low, except 2013 and 2016 where the cases are higher than the rest of the other years.

scholarly journals Temporal trends and variation in out-of-pocket expenditures and patient cost sharing: evidence from a Chinese national survey 2011–2015

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Vicky Mengqi Qin ◽  
Yuting Zhang ◽  
Kee Seng Chia ◽  
Barbara McPake ◽  
Yang Zhao ◽  
...  
Keyword(s):  
Prescription Drugs ◽  
Cost Sharing ◽  
Temporal Trends ◽  
Absolute Amount ◽  
Financial Protection ◽  
Patient Cost ◽  
Older Chinese ◽  
Using Data ◽  
Reported Data ◽  
The Relationship

Abstract Objectives This study aims to examine: (1) temporal trends in the percentage of cost-sharing and amount of out-of-pocket expenditure (OOPE) from 2011 to 2015; (2) factors associated with cost-sharing and OOPE; and (3) the relationships between province-level economic development and cost-sharing and OOPE in China. Setting A total of 10,316 adults aged ≥45 years from China followed-up from 2011 to 2015 were included in the analysis. We measured two main outcome variables: (1) patient cost sharing, measured by the percentage of OOPE as total healthcare expenditure, and (2) absolute amount of OOPE. Results Based on self-reported data, we did not find substantial differences in the percentage of cost sharing, but a significant increase in the absolute amount of OOPE among the middle-aged and older Chinese between 2011 and 2015. The percentage of cost-sharing was considerably higher for outpatient than inpatient care, and the majority paid more than 80% of the total cost for prescription drugs. Provinces with higher GDP per capita tend to have lower cost-sharing and a higher OOPE than their counterparts, but the relationship for OOPE became insignificant after adjusting for individual factors. Conclusion Reducing out-of-pocket expenditure and patient cost sharing is required to improve financial protection from illness, especially for those with those with chronic conditions and reside in less developed regions in China. Ongoing monitoring of financial protection using data from various sources is warranted.

Overcoming the Dark Side of Closed Networks in Cultural Tourism Clusters: The Importance of Diverse Networks

2017 ◽  
Vol 59 (3) ◽  
pp. 239-256 ◽  
Author(s):  
Ángela Martínez-Pérez ◽  
Marie-Michele Beauchesne
Keyword(s):  
Social Capital ◽  
Developed Countries ◽  
Cultural Tourism ◽  
Dark Side ◽  
Negative Effects ◽  
Firm Level ◽  
Firm Innovation ◽  
Closed Networks ◽  
The World ◽  
The Relationship

Despite the recognized importance of tourism as an engine of economic growth in developed countries, research on the antecedents of innovation in this sector has been sparse, especially in the context of tourism clusters. Scholars have suggested that social capital is a key determinant of firm innovation in the context of tourism clusters, but empirical evidence has been lacking. The aim of this article is to empirically study the interplay between social capital and innovation in the context of tourism clusters at firm level. More specifically, we analyzed the effects of closed networks and diverse networks on firm innovation using a sample of 215 hospitality and tourism firms located in the World Heritage Cities of Spain. Results showed an inverted-U-shaped relationship between closed networks and firm innovation. Consistent with existing literature, these findings suggest that whereas a certain degree of strength and density helps to promote innovation, a critical point may exist beyond which innovation stabilizes or deteriorates when the information of the network becomes too redundant. In addition, we found that diverse networks positively moderated the relationship between closed networks and firm innovation. In other words, structural holes appear to mitigate the negative effects arising from excess strength and density and encourage the development of innovations beyond what a firm relying solely on closed networks could achieve. In practice, these results suggest firms in tourism clusters should not exclusively focus on typical closed networks but also create connections with diverse agents to maximize their potential for innovation.

Predicting effects of selected impregnation processes on the observed bending strength of wood, with use of data mining models

BioResources ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. 4891-4904
Author(s):  
Selahattin Bardak ◽  
Timucin Bardak ◽  
Hüseyin Peker ◽  
Eser Sözen ◽  
Yildiz Çabuk
Keyword(s):  
Data Mining ◽  
Goodness Of Fit ◽  
Bending Strength ◽  
Wood Preservation ◽  
Ambient Conditions ◽  
Data Mining Algorithms ◽  
Use Of Data ◽  
The Cost ◽  
Mining Algorithms ◽  
The Relationship

Wood materials have been used in many products such as furniture, stairs, windows, and doors for centuries. There are differences in methods used to adapt wood to ambient conditions. Impregnation is a widely used method of wood preservation. In terms of efficiency, it is critical to optimize the parameters for impregnation. Data mining techniques reduce most of the cost and operational challenges with accurate prediction in the wood industry. In this study, three data-mining algorithms were applied to predict bending strength in impregnated wood materials (Pinus sylvestris L. and Millettia laurentii). Models were created from real experimental data to examine the relationship between bending strength, diffusion time, vacuum duration, and wood type, based on decision trees (DT), random forest (RF), and Gaussian process (GP) algorithms. The highest bending strength was achieved with wenge (Millettia laurentii) wood in 10 bar vacuum and the diffusion condition during 25 min. The results showed that all algorithms are suitable for predicting bending strength. The goodness of fit for the testing phase was determined as 0.994, 0.986, and 0.989 in the DT, RF, and GP algorithms, respectively. Moreover, the importance of attributes was determined in the algorithms.

Does investment in innovation impact firm performance in emerging economies? An empirical investigation of the Indian food and agricultural manufacturing industry

2021 ◽  
Vol 13 (2) ◽  
pp. 233-248
Author(s):  
Manogna R.L. ◽  
Aswini Kumar Mishra
Keyword(s):  
Firm Performance ◽  
Manufacturing Industry ◽  
Emerging Market ◽  
Developed Countries ◽  
Emerging Economy ◽  
Content Type ◽  
Agricultural Industry ◽  
Indian Food ◽  
The Impact ◽  
The Relationship

Purpose The study aims to analyze the impact of Research & Development (R&D) intensity on the firm’s performance, measured by growth of sales in the emerging market like India. Innovation strategy and its outcomes for firms may be different in developing countries as compared to developed countries. Thus, a study that focuses on the emerging economy like India, with a majority of the population dependent on agriculture, is of prime importance to the firm performance in the food and agricultural manufacturing industry. For this study, the broader focus will be on one widely recognised factor which may influence the growth rate of firms, i.e. investment in innovations which is in terms of R&D expenditure. Design/methodology/approach The paper investigates the relationship between the R&D efforts and growth of firms in the Indian food and agricultural manufacturing industry during 2001–2019. To empirically test the relationship between firm’s growth (FG) and R&D investments, system generalised method of moments technique has been used, hence enabling to avoid problems related to endogeneity and simultaneity. Findings The findings reveal that investments in innovations have a positive effect on the growth of firms in the Indian food and agricultural manufacturing industry. Investment in R&D also enables the firms to reap benefits from externalities present in the industry. Further analysis reveals that younger firms grow faster when they invest in R&D. More specifically, this paper finds evidence in the case of the food and agricultural industry that import of raw materials negatively affects the FG and export intensity positively affects the growth in the case of R&D firms. Research limitations/implications This study suggests that the government should encourage the industries to invest optimally in R&D projects by providing favourable fiscal treatments and R&D subsidies which are observed to have positive effects in various developed countries. Originality/value To the best of the author’s knowledge, the current paper is the first to analyse the impact of innovation in food and agricultural industry on firm’s performance in an emerging economy context with the latest data. This paper agrees that a government initiative to increase private R&D expenditure would have favourable effects on FG as growing investments in R&D lead to further growth of the firms.

Sign in / Sign up

Export Citation Format

Share Document