Characteristics of New Zealand dividend omissions and resumptions

2019 ◽  
Vol 46 (1) ◽  
pp. 40-55
Author(s):  
Nicholas Kraiger ◽  
Warwick Anderson
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
New Zealand ◽  
Logistic Regression Analysis ◽  
Multinomial Logistic Regression ◽  
Abnormal Returns ◽  
Market Value ◽  
Firm Characteristics ◽  
Content Type ◽  
Dividend Omissions

Purpose For firms listed on the New Zealand Stock Exchange, which is a relatively thinly traded market, the purpose of this paper is to examine the nature of stock returns associated with a dividend omission announcement when computations specifically address thin trading, and whether specific firm characteristics affect the likelihood and nature of a dividend omission. Design/methodology/approach First, event study analysis is used to check if dividend omissions actually do impact share prices in terms of short-term abnormal returns and longer-term cumulative abnormal returns (CARs) in a thinly traded market. Second, binomial logistic regression analysis is used to determine what, if any, company characteristics are associated with the decision to omit a dividend. Third, multinomial logistic regression analysis is employed to determine what firm characteristics are associated with continuing (or ending) a phase of no dividends before a dividend resumption. Findings Dividend omissions generate immediate negative abnormal returns, and there is a longer-term persistence of negative CARs. The size and duration of these abnormal returns are smaller, but still significant, when thin-market-specific methodology is employed. With respect to firm characteristic, smaller firms, firms with decreased earnings, a higher level of extraordinary charges, greater leverage and firms with a higher book-to-market value are associated with a greater likelihood of making an omission. With respect to the length of time between an omission and resumption of dividend payments, earnings decreases, a higher book-to-market value, a higher level of extraordinary charges and a decrease in firm debt level become significant. Originality/value This paper adds value in two dimensions. First, it considers dividend omissions in three different, but inter-connected ways. Second, the use of multinomial logistic regression to examine an aspect of the non-payment hiatus breaks new ground.

scholarly journals Attitudes towards the New Zealand Government’s Smokefree 2025 goal associated with smoking and vaping in university students aged 18 to 24 years: results of a 2018 national cross-sectional survey

BMJ Open ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. e037362
Author(s):  
Ben Wamamili ◽  
Mark Wallace-Bell ◽  
Ann Richardson ◽  
Randolph C Grace ◽  
Pat Coope
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
New Zealand ◽  
University Students ◽  
Confidence Intervals ◽  
Logistic Regression Analysis ◽  
Smoking Prevalence ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Lower Odds

ObjectiveIn March 2011, New Zealand (NZ) launched an aspirational goal to reduce smoking prevalence to 5% or less by 2025 (Smokefree 2025 goal). Little is known about university students’ awareness of, support for and perceptions about this goal. We sought to narrow the knowledge gap.SettingUniversity students in NZ.MethodsWe analysed data from a 2018 cross-sectional survey of university students across NZ. Logistic regression analysis examined the associations between responses about the Smokefree goal with smoking and vaping, while controlling for age, sex and ethnicity. Confidence intervals (95% CI) were reported where appropriate.ParticipantsThe sample comprised 1476 students: 919 (62.3%) aged 18 to 20 and 557 (37.7%) aged 21 to 24 years; 569 (38.6%) male and 907 (61.4%) female; 117 (7.9%) Māori and 1359 (92.1%) non-Māori. Of these, 10.5% currently smoked (ie, smoked at least monthly) and 6.1% currently vaped (ie, used an e-cigarette or vaped at least once a month).ResultsOverall awareness of the Smokefree goal was 47.5% (95% CI: 44.9 to 50.1); support 96.9% (95% CI: 95.8 to 97.8); belief that it can be achieved 88.8% (95% CI: 86.8 to 90.7) and belief that e-cigarettes/vaping can help achieve it 88.1% (95% CI: 86.0 to 89.9).Dual users of tobacco cigarettes and e-cigarettes had greater odds of being aware of the Smokefree goal (OR=3.07, 95% CI: 1.19 to 7.92), current smokers had lower odds of supporting it (OR=0.13, 95% CI: 0.06 to 0.27) and of believing that it can be achieved (OR=0.15, 95% CI: 0.09 to 0.24) and current vapers had greater odds of believing that e-cigarettes/vaping can help to achieve it (OR=8.57, 95% CI: 1.18 to 62.52) compared with non-users.ConclusionsThe results suggest strong overall support for the Smokefree goal and belief that it can be achieved and that e-cigarettes/vaping can help achieve it. Smoking and vaping were associated with high awareness of the Smokefree goal, but lower support and optimism that it can be achieved.

Trust in police as an influencing factor on trust in government: 2SLS analysis using perception of safety

2020 ◽  
Vol 43 (4) ◽  
pp. 541-558
Author(s):  
Jisu Jeong ◽  
Seunghui Han
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Trust In Government ◽  
Content Type ◽  
Perception Of Safety ◽  
Ordered Logistic Regression ◽  
The Impact ◽  
The Relationship ◽  
Trust In Police

PurposeCitizen trust in police is important in terms of citizen consent to government policies and of police achieving their organizational goals. In the previous study, improvements in police policy, organizational operation and policing activities were developed to clarify which factors influence trust in police and how trust can be improved. This research raises the question, would changes in trust in police have an impact on trust in government? In this paper, this research question is discussed theoretically and the causal relationship analyzed empirically by applying OLS, ordered logistic, 2SLS and logistic regressions.Design/methodology/approachThe basic analysis methods are to apply the OLS and the ordered logistic regression. OLS regression analysis is an analytical method that minimizes an error range of a regression line. The assumptions for OLS are: linearity, independence, equilibrium, extrapolation and multicollinearity issues. These problems were statistically verified and analyzed, in order to confirm the robustness of the analysis results by comparing the results of the ordered logistic regression because of the sequence characteristic of the dependent variable. The data to be used in this study is the Asia Barometer Survey in 2013.FindingsTrust in police and citizen perception of safety are analyzed as important factors to increase trust in the government. The effects of trust in police are more significant than the effects of control variables, and the direction and strength of the results are stable. The effect of trust in police on trust in government is strengthened by the perception of safety (IV). In addition, OLS, ordered logistic regression analysis, which analyzed trust in central government and local government, and logistic regression analysis categorized by trust and distrust show the stability.Research limitations/implicationsThis paper has implications in terms of theoretical and empirical analysis of the relationship between trust in police and trust in government. In addition, the impact of perception of safety on trust in police can be provided to police officers, policymakers and governors who are seeking to increase trust in government. This paper is also meaningful in that it is the microscopic research based on the citizens' survey. One of the limitations of macroscopic research is that it does not consider the individual perceptions of citizens.Practical implicationsThe results of this paper can confirm the relationship of the virtuous cycle, which is perception of safety – trust in police – trust in government. The police will need to provide security services to improve citizens' perception of safety and make great efforts to create safer communities and society. Trust in police formed through this process can be an important component of trust in government. By making citizens feel safer and achieving trust in police, ultimately, trust in government will be improved.Originality/valueThe police perform one of the essential roles of government and are one of the major components of trust in government, but the police sector has been neglected compared to the roles of the economic and political sectors. These influences of macro factors are too abstract to allow specific policy directions to be suggested. If we consider trust in police, and factors that can improve trust in government, we can suggest practical policy alternatives.

A study of equality of educational opportunity in Nepal using logistic regression analysis

2020 ◽  
Vol 22 (4) ◽  
pp. 249-262
Author(s):  
Naruho Ezaki
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Private Schools ◽  
Logistic Regression Analysis ◽  
Educational Opportunity ◽  
Quality Education ◽  
High Quality ◽  
Content Type ◽  
High Quality Education ◽  
Equality Of Educational Opportunity

PurposeWhile privatisation in education is expanding, the number of children transferring from public to private schools seeking high-quality education has increased. This study examined equality of educational opportunity, focussing on the attributes of individual children and their familial backgrounds. The target country is Nepal, which has been facing an educational disparity problem between public and private schools.Design/methodology/approachThis study performed a logistic regression analysis with the objective variable as the binary capability to attend a private school and analysed the differences between children who attended public versus private schools. Semi-structured interviews with subjects and teachers and home-visit surveys were conducted to collect and confirm data.FindingsThis study revealed that particular children were excluded from seeking high-quality education in form of attending private schools. These children's characteristics correspond to lower economic status, illiterate mothers, being only children and female. Moreover, the study observed changes in awareness due to the modernisation and globalisation of Nepali society and growing enthusiasm for education, amongst others.Originality/valueResearch on privatisation and access to quality education, which has attracted scholarly attention in recent years, requires a broader scope regarding target countries and more in-depth analyses. This study focussed on Nepal since, in the country, the phenomenon of children leaving public for private schools is prominent and little research has been conducted on this context. Additionally, since the study gathered extensive data on individual children and did not rely on secondary data, it was possible to perform an in-depth analysis and accurately portray the real situation faced by Nepali children.

The benchmarking of the use of toolkit for mass customization in the automobile industry

2017 ◽  
Vol 24 (6) ◽  
pp. 1767-1783 ◽  
Author(s):  
Diego Castro Fettermann ◽  
Márcia Elisa Soares Echeveste ◽  
Guilherme Luz Tortorella
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Automobile Industry ◽  
Mass Customization ◽  
Design Methodology ◽  
Market Conditions ◽  
Content Type ◽  
Corporate Brands ◽  
The Relationship

Purpose The purpose of this paper is to examine the relation between the utilization of the customization strategy and the availability of the online toolkit and its features with the commercial variables of businesses. Design/methodology/approach The sample used in this paper consists of 134 cases of corporate brands in the automobile industry; their sales correspond to 49.12 percent of vehicles produced in 2012. The logistic regression analysis was then applied to the sample. Findings This paper confirmed the relationship between the use of toolkits for customization and business variables, like vehicle sales. Originality/value The generated model allows the prediction of market conditions which recommended to provide the toolkit for customization, and if implemented, what combination of features it must have.

scholarly journals PERBANDINGAN REGRESI LOGISTIK MULTINOMINAL DAN ANALISIS DISKRIMINAN

2021 ◽  
Vol 1 (2) ◽  
pp. 135-150
Author(s):  
Rifda Nabila ◽  
Risdiana Himmati ◽  
Rendra Erdkhadifa
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Discriminant Analysis ◽  
Logistic Regression Analysis ◽  
Multinomial Logistic Regression ◽  
Regression Method ◽  
Destination Image ◽  
Tourism Destination ◽  
Multinomial Logistic Regression Analysis ◽  
Logistic Regression Method

Abstrak: Tujuan dari penelitian ini adalah untuk membandingkan analisis regresi logistik multinomial dan analisis diskriminan untuk mengelompokkan keputusan kunjungan wisata halal di Jawa Tengah berdasarkan ketepatan pengelompokan. Analisis statistik yang digunakan adalah regresi logistik multinomial dan analisis diskriminan. Kedua analisis tersebut dapat digunakan sebagai metode pengelompokan objek, sehingga keduanya dapat dibandingkan berdasarkan ketepatan pengelompokkannya. Penelitian ini membandingkan analisis regresi logistik multinomial dan analisis diskriminan dalam pengelompokan keputusan kunjungan wisata halal. Data yang digunakan adalah worship facilities, halalness, general Islamic mortality, dan tourism destination image. Hasil analisis menggunakan metode regresi logistik multinomial menunjukkan faktor-faktor yang secara signifikan mempengaruhi pengelompokan keputusan kunjungan wisata halal adalah variabel tourism destination image, variabel halalness, dan variabel general Islamic morality. Sedangkan dengan analisis diskriminan menunjukkan bahwa semua variabel prediktor yakni worship facilities, halalness, general Islamic mortality, dan tourism destination image memberikan pengaruh secara signifikan terhadap pengklasifikasian keputusan mengunjungi destinasi wisata halal. Penelitian ini menunjukkan bahwa metode regresi logistik multinomial lebih baik untuk pengelompokkan keputusan kunjungan wisata halal dibandingan metode analisis diskriminan, dengan presetnase ketepatan pengelompokkan pada metode regresi logit multinomial sebesar 59,5%  dan analisis diskriminan sebesar 53,5%. Analisis regresi logistik multinominal lebih mudah digunakan dalam proses pengelompokan keputusan kunjuangan wisata halal karena tidak mempertimbangkan asumsi yang harus dipenuhi. Kata Kunci: Analisis Diskriminan; Regresi Logistik Multinominal; Keputusan Mengunjungi   Abstract: The purpose of this study is to compare multinomial logistic regression analysis and discriminant analysis to classify decisions on halal tourism visits in Central Java based on grouping accuracy. Statistical analysis used is multinomial logistic regression and discriminant analysis. The two analyzes can be used as a method of grouping objects, so that they can be compared based on the accuracy of the grouping. This study compares multinomial logistic regression analysis and discriminant analysis in grouping decisions for halal tourism visits. The data used are worship facilities, halalness, general Islamic mortality, and tourism destination image. The results of the analysis using the multinomial logistic regression method show that the factors that significantly influence the grouping of decisions for halal tourism visits are the tourism destination image variable, the halalness variable, and the general Islamic morality variable. Meanwhile, discriminant analysis shows that all predictor variables namely worship facilities, halalness, general Islamic mortality, and tourism destination image have a significant influence on the classification of decisions to visit halal tourist destinations. This study shows that the multinomial logistic regression method is better for grouping decisions on halal tourist visits than the discriminant analysis method, with a preset percentage of grouping accuracy in the multinomial logit regression method of 59.5% and discriminant analysis of 53.5%. Multinominal logistic regression analysis is easier to use in the process of grouping halal tourism travel decisions because it does not consider the assumptions that must be met. Keywords: Discriminant Analysis; Multinomial Logistic Regression; Visiting decision.

scholarly journals Comparative analysis of the elements of attack and defence in men’s and women’s games in the Estonian volleyball highest league

2016 ◽  
Vol 25 (1) ◽  
pp. 37 ◽  
Author(s):  
Raini Stamm ◽  
Meelis Stamm ◽  
Doris Torilo ◽  
Kaivo Thomson ◽  
Alexander Jairus
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Comparative Analysis ◽  
Logistic Regression Analysis ◽  
Multinomial Logistic Regression ◽  
Block Type ◽  
Multinomial Logistic Regression Analysis ◽  
Expert Assessments ◽  
Attack Type

The aim of this study was to analyse the differences between men’s and women’s teams of the Estonian highest league in attack, serve, block, defence and serve reception. The sample consisted of 5 men’s and 5 women’s teams of the Estonian volleyball highest league in the 2014/2015 season. To collect data, two game videos of each team were watched; from them tempo of attack, type of attack, block and serve, and the results of defence and cover were registered. In addition, statistics created by the Data Volley and Volleysoft 6–3 programs on the basis of expert assessments were used to estimate the efficiency of volleyball elements and results of reception. SPSS Statistics 23 version for Windows was used to construct frequency tables and multinomial logistic regression analysis was applied to find the probable frequencies of the activities analysed. The results revealed that in Estonian men’s highest league games quick tempo 1 attacks were used statistically significantly more often than in women’s games. Men were more proficient at attack and used a vigorous spike more often than women. For both genders, double block was the most often used block type. Broken double block was more common to men than to women. The serve type most often used by men was the power jump serve, followed by the tactical float serve. Women most often used the standing serve and, as second, the jump float serve. Men made more serve errors than women did. The percentage of ace serves was also higher in women than in men.In defence, the percentage of the ball remaining in play was higher in women than in men, and women’s defence cover was more efficient than men’s. As a result of attack cover, the ball remained in play nearly by half more frequently in women’s than in men’s games. Nonetheless, women scored fewer points as a result of attack cover. Serve reception in the Estonian highest league was better in men, and men made statistically significantly fewer errors in reception than women did.

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