An Examination of the Effect of CPA Firm Type on Bank Regulators' Closure Decisions

1999 ◽  
Vol 18 (2) ◽  
pp. 143-158 ◽  
Author(s):  
Roselyn E. Morris ◽  
Jerry R. Strawser
Keyword(s):  
Regression Models ◽  
The State ◽  
Ceteris Paribus ◽  
Going Concern ◽  
Reporting Incentives ◽  
Firm Type ◽  
Cpa Firm ◽  
Financial Characteristics ◽  
Closure Decisions

This study examines the effect of CPA firm type on regulators' decisions with respect to the closure of banks. Using a sample of 116 closed and 116 nonclosed banks in the state of Texas during 1990–1991, we estimate regression models which include (1) financial characteristics of the sample banks, (2) other characteristics of the sample banks, (3) the type of auditor's opinion received by the bank (with respect to the bank's ability to continue as a going concern), and (4) the CPA firm type (Big 6 vs. non-Big 6). Our results indicate that banks receiving modified opinions from Big 6 firms were more likely to be continued (not closed) by regulators than those receiving modified opinions from non-Big 6 firms. In contrast, banks receiving nonmodified opinions from non-Big 6 firms were more likely to be closed than those receiving nonmodified opinions from Big 6 firms. These findings indicate that, ceteris paribus, banks audited by Big 6 firms are more likely to be continued, consistent with regulators' perceptions that economic reporting incentives may result in Big 6 firms being more likely to modify their opinions to reflect going-concern uncertainties.

scholarly journals Sociodemographic associations of geographic variation in paediatric tonsillectomy and adenoidectomy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Aimy H. L. Tran ◽  
Danny Liew ◽  
Rosemary S. C. Horne ◽  
Joanne Rimmer ◽  
Gillian M. Nixon
Keyword(s):  
Geographic Variation ◽  
Language Proficiency ◽  
Regression Models ◽  
English Language ◽  
Population Analysis ◽  
English Language Proficiency ◽  
The State ◽  
The Public ◽  
Factors Associated ◽  
Administrative Datasets

AbstractGeographic variation of paediatric tonsillectomy, with or without adenoidectomy, (A/T) has been described since the 1930s until today but no studies have investigated the factors associated with this variation. This study described the geographical distribution of paediatric A/T across the state of Victoria, Australia, and investigated area-level factors associated with this variation. We used linked administrative datasets capturing all paediatric A/T performed between 2010 and 2015 in Victoria. Surgery data were collapsed by patient residence to the level of Local Government Area. Regression models were used to investigate the association between likelihood of surgery and area-level factors. We found a 10.2-fold difference in A/T rates across the state, with areas of higher rates more in regional than metropolitan areas. Area-level factors associated with geographic variation of A/T were percentage of children aged 5–9 years (IRR 1.07, 95%CI 1.01–1.14, P = 0.03) and low English language proficiency (IRR 0.95, 95% CI 0.90–0.99, P = 0.03). In a sub-population analysis of surgeries in the public sector, these factors were low maternal educational attainment (IRR 1.09, 95% CI 1.02–1.16, P < 0.001) and surgical waiting time (IRR 0.99635 95% CI 0.99273–0.99997, P = 0.048). Identifying areas of focus for improvement and factors associated with geographic variation will assist in improving equitable provision of paediatric A/T and decrease variability within regions.

scholarly journals Predictors of Death Rate during the COVID-19 Pandemic

Healthcare ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 339 ◽  
Author(s):  
Ian Feinhandler ◽  
Benjamin Cilento ◽  
Brad Beauvais ◽  
Jordan Harrop ◽  
Lawrence Fulton
Keyword(s):  
Health Status ◽  
Repeated Measures ◽  
Regression Models ◽  
State Level ◽  
Political Influence ◽  
The State ◽  
The Political ◽  
County Level ◽  
Political Factor ◽  
Death Rates

Coronavirus (COVID-19) is a potentially fatal viral infection. This study investigates geography, demography, socioeconomics, health conditions, hospital characteristics, and politics as potential explanatory variables for death rates at the state and county levels. Data from the Centers for Disease Control and Prevention, the Census Bureau, Centers for Medicare and Medicaid, Definitive Healthcare, and USAfacts.org were used to evaluate regression models. Yearly pneumonia and flu death rates (state level, 2014–2018) were evaluated as a function of the governors’ political party using a repeated measures analysis. At the state and county level, spatial regression models were evaluated. At the county level, we discovered a statistically significant model that included geography, population density, racial and ethnic status, three health status variables along with a political factor. A state level analysis identified health status, minority status, and the interaction between governors’ parties and health status as important variables. The political factor, however, did not appear in a subsequent analysis of 2014–2018 pneumonia and flu death rates. The pathogenesis of COVID-19 has a greater and disproportionate effect within racial and ethnic minority groups, and the political influence on the reporting of COVID-19 mortality was statistically relevant at the county level and as an interaction term only at the state level.

scholarly journals Trends in mortality due to breast cancer among women in the state of Rio de Janeiro, Brazil, 1996-2011

2015 ◽  
Vol 20 (3) ◽  
pp. 895-903
Author(s):  
Daniele Bittencourt Ferreira ◽  
Inês Echenique Mattos
Keyword(s):  
Breast Cancer ◽  
Rio De Janeiro ◽  
Regression Models ◽  
Polynomial Regression ◽  
Population Group ◽  
Mortality Rates ◽  
The State ◽  
Data Source ◽  
Polynomial Regression Models ◽  
Series Study

A descriptive time series study was conducted in order to analyze the mortality rates for breast cancer in two age brackets (< 60 years and ≥ 60 years), in areas of the state of Rio de Janeiro (inland, metropolitan area, capital and state). The data source was the Mortality Information System. Mortality rates were analyzed for four-year periods, between 1996 and 2011, and the ratios between the incidences for the two age brackets in each area. The trend in annual mortality rates was analyzed with the Joinpoint program and polynomial regression models. The ratios between the incidences observed were 7-8 times higher in women aged 60 years or older. Joinpoint analyses indicated a linear decline in mortality rates in the state and the capital for the whole population and for women aged 60 and over in the same areas. The polynomial regression models allowed the observation of periods of increasing and decreasing rates and a tendency to stabilization at the end of the period. Despite the declining trend, the magnitude of mortality from breast cancer is still high among women aged 60 and older, and it is important to investigate associated factors in this population group.

The impact of strategy on public sector set-aside programs: the case of the state of Ohio

2018 ◽  
Vol 18 (1) ◽  
pp. 31-49 ◽  
Author(s):  
Ian Y. Blount ◽  
Jay Seetharaman ◽  
Trevor L. Brown
Keyword(s):  
Program Implementation ◽  
Regression Models ◽  
Implementation Strategy ◽  
State Level ◽  
The State ◽  
State Agencies ◽  
Linear Regression Models ◽  
Content Type ◽  
Program Strategy ◽  
The Impact

Purpose The purpose of this study is to examine the impact of program strategy on the implementation of the efficacy of a procurement set-aside program at the state level. Design/methodology/approach This study examines the impact of program implementation strategy across two administrations considering the most compelling alternative arguments for what drives agency purchasing through contracts with MBEs. Findings The results of mixed effects linear regression models on the procurement expenditures of 70 state agencies in Ohio from 2008-2015 show significantly higher rates of procurement expenditures with MBEs under the Kasich administration. Originality/value These results provide support for the argument that changes in program implementation strategy led to substantive increases in the use of MBEs by state agencies in Ohio.

scholarly journals Regression models for prediction of corn yield in the state of Paraná (Brazil) from 2012 to 2014

2018 ◽  
Vol 40 (1) ◽  
pp. 36494
Author(s):  
Rodolfo Seffrin ◽  
Everton Coimbra De Araújo ◽  
Claudio Leones Bazzi
Keyword(s):  
Regression Models ◽  
The State ◽  
Corn Yield

scholarly journals ECONOMIC MODELLING OF THE IMPACT OF INFRASTRUCTURE INDUSTRIES ON THE SUSTAINABLE DEVELOPMENT OF THE REGION

2020 ◽  
Author(s):  
А.М. Гасанов
Keyword(s):  
Sustainable Development ◽  
Economic Development ◽  
Regression Models ◽  
The State ◽  
Economic Modelling ◽  
Effective Parameters ◽  
The Sustainable Development ◽  
Factor Regression ◽  
The Impact

В статье рассматриваются вопросы экономического моделирова- ния влияния инфраструктуры на устойчивое развитие отраслевой экономики ре- гионов СКФО. При этом целью исследования является построить многофактор- ные регрессионные модели результативных параметров предприятий. Исходя из цели определены и задачи исследования. Провести анализ состояния и проблемы развития экономики отраслевой составляющей региона в условиях инновацион- ных преобразований предприятий, а также методов ее оценки. The article deals with the issues of the infrastructure impact of economic modelling on the sustainable development of the sectoral economy of the NCFD regions. At the same time, the study aims to develop multi-factor regression models of effective parameters of enterprises. In accordance with the aim, the objectives of the study have also been defi ned. To carry out an analysis of the state and problem of economic development of the sectoral region in the context of innovative changes of enterprises, as well as methods of its evaluation.

scholarly journals Financial Impact on the Accountability of Malaysian State Islamic Religious Councils (SIRC)

2018 ◽  
Vol 15 (2) ◽  
pp. 21-38
Author(s):  
Rosnia Masruki ◽  
Khaled Hussainey ◽  
Doaa Aly
Keyword(s):  
Voluntary Disclosure ◽  
Regression Models ◽  
Annual Report ◽  
Control Variable ◽  
Financial Statements ◽  
Annual Reports ◽  
Policy Makers ◽  
Financial Report ◽  
Financial Characteristics

This paper aims to identify whether Malaysian State Islamic Religious Councils (SIRC) financial characteristics have a significant impact on the accountability of Malaysian State Islamic Religious Councils (SIRC). A content analysis approach was used to examine the extent and quality of disclosure in the annual reports of SIRC, indicating accountability of SIRCs. This paper used the self-developed disclosure index that applies specifically for SIRC. Multiple regression was used to examine the financial determinants of the extent and quality of disclosure. The result of the regression models revealed that the extent and quality of SIRC disclosure is influenced by organisational characteristic, namely size. This study suggests that disclosure in the annual report, in particular the non-financial performance, increases with the amount of zakat collection, thereby demonstrating SIRC’s responsibility. Next, the control variable of accessibility is found to be significantly related to financial statements. Obliged to produce financial statements, SIRC are more likely to disclose more information in the financial statements. This research finding has important implications for regulators, policy makers and top officials in SIRC, by monitoring the quality of disclosure, supporting the notion of public accountability, which appreciates the public’s right to get inform about SIRC. Despite the voluntary disclosure of a non-financial report, SIRC should consider producing a comprehensive annual report for the discharge of their accountability and thus, encourage more funding. They should be more transparent to enhance accessibility, concerning the extent and quality of the disclosure.

scholarly journals Logistic Regression Models and Classification Tree for Deaths and Recovered Patients Records of Covid-19 in the State of Minas Gerais, Brazil

2020 ◽  
Vol 7 (10) ◽  
pp. 150-160
Author(s):  
Fabrício Pelizer Almeida ◽  
Moisés Keniel Guilherme de Lima ◽  
Demóstenes Coutinho Gomes ◽  
Esther Ferreira de Souza
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Classification Tree ◽  
Minas Gerais ◽  
The State ◽  
Logistic Regression Models

scholarly journals Epidemiology of Megninia spp. in laying flocks from the State of Minas Gerais, Brazil

2015 ◽  
Vol 24 (2) ◽  
pp. 198-203 ◽  
Author(s):  
Leandro do Carmo Rezende ◽  
Lucas Maciel Cunha ◽  
Nelson Rodrigo da Silva Martins ◽  
Cristina Mara Teixeira ◽  
Paulo Roberto de Oliveira
Keyword(s):  
Regression Models ◽  
Minas Gerais ◽  
The State ◽  
Multiple Logistic Regression ◽  
Protection Factor ◽  
Cross Sectional ◽  
Logistic Regression Models ◽  
Layer Chicken ◽  
Chicken House ◽  
Commercial Farms

Aspects related to the epidemiology of Megninia ginglymura were studied, in order to determine predisposing factors for the ocurrence in layer chicken houses of commercial farms in the State of Minas Gerais, Brazil. An observational, cross-sectional, analytical survey was conducted for identifying major risks or protection factors for infestations. Four hundred thirty-one houses located in forty-three farms were visited in 2012. Regarding the farms, 17 (39.53%) had chickens infested by M. ginglymura and 1 (2.32%) presented Megninia cubitalis. The epidemiological aspects of the occurrence of M. ginglymura were investigated using multiple logistic regression models. The chicken house organization was an important protection factor involved in the occurrence of M. ginglymura (odds ratio [OR] = 0.85). The presence of subsistence breedings of poultry within the premises or at the proximity of a farm was characterized as a risk factor for the occurrence of infestations (OR = 3.92). The use of mineral oil (OR = 0.16) was considered protective against new infestations. Some regions of the state were characterized by a higher risk for mite infestation than others.

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