scholarly journals Improved Public Services and Tax Compliance of Small and Medium Scale Enterprises in Nigeria: A Generalised Ordered Logistic Regression

2020 ◽  
Vol 10 (7) ◽  
pp. 833-860 ◽  
Author(s):  
Oluwafadekemi S. Areo ◽  
Obindah Gershon ◽  
Evans Osabuohien
Keyword(s):  
Logistic Regression ◽  
Public Services ◽  
Tax Compliance ◽  
Medium Scale ◽  
Ordered Logistic Regression

scholarly journals Personal Income Tax Compliance in Nigeria: A Generalised Ordered Logistic Regression

2020 ◽  
Vol 11 (3) ◽  
pp. 261
Author(s):  
Oluwafadekemi S. Areo ◽  
Obindah Gershon
Keyword(s):  
Logistic Regression ◽  
Empirical Research ◽  
Psychological Factors ◽  
Tax Compliance ◽  
Personal Income ◽  
Personal Income Tax ◽  
Ordered Logistic Regression ◽  
The Subject ◽  
Proper Analysis ◽  
Income Taxpayers

This paper builds on already existing theoretical and empirical research on the economic and psychological factors used in explaining tax compliance. The likelihood that personal income taxpayers in Nigeria will be tax non-compliant, low tax compliant or tax compliant for either economic or psychological factors and a combination of both factors are evaluated using the Generalised ordered logistic regression. The findings in this paper provide extra information on the mixed results that have been obtained by empirical research on the subject matter of tax compliance by revealing how economic and psychological factors have different likelihood values for individuals to fall into the tax compliant category. This paper recommends that a proper analysis of the peculiar traits of the Nigerian tax system be conducted before decisions are made on either of the economic or psychological factors to be employed, to move personal income taxpayers to the tax compliant category.

scholarly journals Least Likely Observations in Regression Models for Categorical Outcomes

2002 ◽  
Vol 2 (3) ◽  
pp. 296-300 ◽  
Author(s):  
Jeremy Freese
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Binary Logistic Regression ◽  
Positive Outcome ◽  
Ordinary Least Squares ◽  
Parameter Estimates ◽  
Least Squares Regression ◽  
Binary Logistic Regression Model ◽  
Ordered Logistic Regression ◽  
Negative Outcome

This article presents a method and program for identifying poorly fitting observations for maximum-likelihood regression models for categorical dependent variables. After estimating a model, the program leastlikely will list the observations that have the lowest predicted probabilities of observing the value of the outcome category that was actually observed. For example, when run after estimating a binary logistic regression model, leastlikely will list the observations with a positive outcome that had the lowest predicted probabilities of a positive outcome and the observations with a negative outcome that had the lowest predicted probabilities of a negative outcome. These can be considered the observations in which the outcome is most surprising given the values of the independent variables and the parameter estimates and, like observations with large residuals in ordinary least squares regression, may warrant individual inspection. Use of the program is illustrated with examples using binary and ordered logistic regression.

scholarly journals Multivariate ordered logistic regression analysis of the postoperative effect of symptomatic discoid lateral meniscus

2021 ◽  
Author(s):  
Shun-Jie Yang ◽  
Jian Li ◽  
Yang Xue ◽  
Zhong Zhang ◽  
Gang Chen
Keyword(s):  
Logistic Regression ◽  
Age Of Onset ◽  
Univariate Analysis ◽  
Arthroscopic Surgery ◽  
Lateral Meniscus ◽  
Postoperative Outcomes ◽  
Discoid Lateral Meniscus ◽  
Work Intensity ◽  
Duration Of Symptoms ◽  
Ordered Logistic Regression

Abstract Introduction The postoperative effect of arthroscopy in the treatment of symptomatic discoid lateral meniscus (DLM) varies greatly among individuals. Therefore, this study aims to investigate the factors affecting the postoperative outcomes of symptomatic DLM. Materials and methods According to the inclusion and exclusion criteria, patients with symptomatic single-knee DLM who underwent arthroscopic surgery at our hospital from 9/2008 to 9/2015 were included. Retrospectively collected 16 factors probably affecting postoperative outcomes. The Ikeuchi grade system was used to evaluate the knee joint function. Univariate analysis was performed by Kruskal–Wallis rank-sum test or Mann–Whitney U test, and multivariate analysis by ordered logistic regression. P < 0.05 was considered statistically significant. Results A sum of 502 patients was included, including 353 females (70.3%) and 149 males (29.7%). Difference between preoperative and postoperative Ikeuchi grade was statistically significant (P < 0.001). Female was bad to obtain a good Ikeuchi grade (P = 0.009, OR 0.458). Outerbridge grade (P = 0.018, OR 0.638) was negatively correlated with Ikeuchi grade. BMI (P = 0.001, OR 0.875) and work intensity (P = 0.020, OR 0.611) were inversely correlated with Ikeuchi grade. Age of onset (P < 0.001, OR 0.956) and symptoms duration (P < 0.001, OR 0.988) were negatively correlated with Ikeuchi grade. Besides, compared to total meniscectomy, meniscoplasty with a repair was an unfavourable factor for Ikeuchi grade (P = 0.044, OR 0.245). Conclusions With the increase of BMI, work intensity, age of onset, duration of symptoms, and the severity of cartilage lesion, the postoperative results become worse. Moreover, female and meniscoplasty with repair are risk factors for the postoperative outcomes.

scholarly journals Catastrophic Household Expenditure Associated with Out-of-Pocket Healthcare Payments in Spain

2021 ◽  
Vol 18 (3) ◽  
pp. 932
Author(s):  
Samuel López-López ◽  
Raúl del Pozo-Rubio ◽  
Marta Ortega-Ortega ◽  
Francisco Escribano-Sotos
Keyword(s):  
Health Care ◽  
Logistic Regression ◽  
Regression Models ◽  
Financial Risk ◽  
Household Expenditure ◽  
Financial Protection ◽  
Logistic Regression Models ◽  
Ordered Logistic Regression ◽  
Out Of Pocket Payments ◽  
The Subject

Background. The financial effect of households’ out-of-pocket payments (OOP) on access and use of health systems has been extensively studied in the literature, especially in emerging or developing countries. However, it has been the subject of little research in European countries, and is almost nonexistent after the financial crisis of 2008. The aim of the work is to analyze the incidence and intensity of financial catastrophism derived from Spanish households’ out-of-pocket payments associated with health care during the period 2008–2015. Methods. The Household Budget Survey was used and catastrophic measures were estimated, classifying the households into those above the threshold of catastrophe versus below. Three ordered logistic regression models and margins effects were estimated. Results. The results reveal that, in 2008, 4.42% of Spanish households dedicated more than 40% of their income to financing out-of-pocket payments in health, with an average annual gap of EUR 259.84 (DE: EUR 2431.55), which in overall terms amounts to EUR 3939.44 million (0.36% of GDP). Conclusion. The findings of this study reveal the existence of catastrophic households resulting from OOP payments associated with health care in Spain and the need to design financial protection policies against the financial risk derived from facing these types of costs.

State legitimacy and tax compliance among small and medium scale enterprises: a case study of Dodowa district, Ghana

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abraham Gyamfi Ababio ◽  
Arthur Gnonsio Mangueye
Keyword(s):  
Sample Selection ◽  
Tax Compliance ◽  
Probit Model ◽  
Content Type ◽  
Medium Scale ◽  
State Legitimacy ◽  
Negative Effect ◽  
Sizable Proportion

Purpose Improving tax compliance would drive the needed development in Ghana. Small and medium scale enterprises (SME) constitute a sizable proportion of the Ghanaian economy but its contribution to tax revenue is below expectation. This study aims to determine whether SME's perception of state legitimacy affects tax compliance. Design/methodology/approach A structured questionnaire was administered to 200 SMEs randomly drawn from Dodowa in the Shai-Osudoku District of Greater Accra Region. Descriptive statistics and the Probit model with sample selection were used to analyse the data. Findings The study found that SME's perception of government legitimacy exerts a significant negative effect on reducing profit to avoid tax liability (ß = −0.0305, p < 0.05). Other factors such as education and fear of fines and penalties were also found to reduce the likelihood that the firm would reduce profit to avoid high tax liability. Still, tax knowledge had a positive effect on this behaviour. Practical implications This study would help deepen policymakers' knowledge of how to improve tax compliance among SMEs in Ghana. Originality/value The originality of this work is that it explicitly models the role of fiscal exchange theory in explaining tax compliance among SMEs in Ghana by using robust methodology.

scholarly journals Ordered Logistic Analysis of Farmers’ Market Regulations: Who Finds Them Easy?

2016 ◽  
Vol 8 (12) ◽  
pp. 1
Author(s):  
Jean Dominique Gumirakiza ◽  
Amber Daniel
Keyword(s):  
Logistic Regression ◽  
Fresh Produce ◽  
Farmers Markets ◽  
Online Surveys ◽  
Farmers Market ◽  
Policy Makers ◽  
Logistic Analysis ◽  
South Central ◽  
Ordered Logistic Regression ◽  
Western Kentucky

This study applies an ordered logistic regression to data collected in 2015 using in-person survey, mail, and online surveys from fresh produce vendors at farmers’ markets within the south central and western Kentucky regions. The purpose was to explain levels of difficult the vendors face when complying with market regulations. Results indicate that an average fresh produce vendor at farmers’ market is 26 percent likely going to comply with market regulations easily, 69 percent moderately, and 4 percent hardly. Participating in CSA and “local” labeling programs, years of farming experience, and being a male vendor are associated with finding relatively easy to comply with farmers markets regulations. Market managers and policy makers will find this study useful in ensuring that those regulations pose no greater difficult to the vendors. Likewise, findings are useful to the vendors for they indicate variables that make easier for them to comply with the regulations.

scholarly journals The preferences of general practitioners regarding family physician contract in the underprivileged areas of Iran in using conjoint analysis

2019 ◽  
Author(s):  
Sima Rafiei ◽  
Rafat Mohebbifar ◽  
Mohammad Ranjbar ◽  
Fatemeh Akbarirad
Keyword(s):  
Logistic Regression ◽  
General Practitioners ◽  
Family Physician ◽  
Family Doctor ◽  
Medical Specialty ◽  
Cross Sectional Study ◽  
International Standards ◽  
Cross Sectional ◽  
Ordered Logistic Regression ◽  
The Family

Background: One of the most important methods for improving the fair access of people to health services is the family physician program, which is facing many challenges. One of these challenges is the lack of policymakers' understanding of physicians' preferences regarding the provisions of the family physician contract. Therefore, this study was aimed to investigate general practitioners' preferences regarding the type of family doctor contract in one of the underprivileged regions of Iran. Methods: An analytical-cross-sectional study was conducted among 150 general practitioners (GPs) who registered in Ministry of Health and Medical Education (MoHME) family physician plan and were working in the health network of deprived regions in Iran. A discrete choice experiment (DCE) questionnaire was developed by the researchers and then distributed to GPs. Results were analyzed using Ordered Logistic Regression. Data were collected using a questionnaire designed by orthogonal method in SPSS 20. Data analysis was performed using logistic regression model in Stata 13 software. Results: Findings revealed that “type of employer” had the most significant effect on GPs’ preferences (OR = 2.5), followed by “allocating quota for admission to medical specialty courses after 5 years” (OR = 2.25), being allowed to give medical services to population without geographical restriction (OR = 2.8), being allowed to provide services out of the defined service packet (OR =   1.4), and “decreased length of contract” (OR  =  0.93). Conclusion: The amendment of the provisions of the family physician contract in accordance with physicians' preferences increases the probability of their participation in and compliance with the family physician program. However, the compliance of the provisions of this contract with relevant international standards and upstream laws of the country should be maintained as much as possible.  

Extending Extended Logistic Regression: Extended versus Separate versus Ordered versus Censored

2014 ◽  
Vol 142 (8) ◽  
pp. 3003-3014 ◽  
Author(s):  
Jakob W. Messner ◽  
Georg J. Mayr ◽  
Daniel S. Wilks ◽  
Achim Zeileis
Keyword(s):  
Logistic Regression ◽  
Probability Distribution ◽  
Calibration Method ◽  
Logistic Distribution ◽  
Censored Regression ◽  
Ensemble Forecasts ◽  
Predictive Distributions ◽  
Logistic Regression Models ◽  
Weather Forecasts ◽  
Ordered Logistic Regression

Abstract Extended logistic regression is a recent ensemble calibration method that extends logistic regression to provide full continuous probability distribution forecasts. It assumes conditional logistic distributions for the (transformed) predictand and fits these using selected predictand category probabilities. In this study extended logistic regression is compared to the closely related ordered and censored logistic regression models. Ordered logistic regression avoids the logistic distribution assumption but does not yield full probability distribution forecasts, whereas censored regression directly fits the full conditional predictive distributions. The performance of these and other ensemble postprocessing methods is tested on wind speed and precipitation data from several European locations and ensemble forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF). Ordered logistic regression performed similarly to extended logistic regression for probability forecasts of discrete categories whereas full predictive distributions were better predicted by censored regression.

scholarly journals Modeling of geogenic radon in Switzerland based on ordered logistic regression

2017 ◽  
Vol 166 ◽  
pp. 376-381 ◽  
Author(s):  
Georg Kropat ◽  
François Bochud ◽  
Christophe Murith ◽  
Martha Palacios (Gruson) ◽  
Sébastien Baechler
Keyword(s):  
Logistic Regression ◽  
Ordered Logistic Regression
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