Unobserved Time-invariant Factors Research Articles

STUDY ON THE RELATIONSHIP BETWEEN FIRMS’ PERFORMANCE AND STOCK MARKET RETURNS IN SELECT NSE LISTED COMPANIES

Purpose: An investor considers lot of factors while investing his money into the Stocks. Money is majorly invested in BSE or NSE in India. BSE is established in the year 1875 and NSE established in the year 1992. Apart from this some stocks are traded in local exchange market in each city. Earlier we had manual trading. However, it is more organized and digitalized now. Every investor does some survey prior to investing their hard-earned money. The reason behind investment is to earn profits over the invested money. The returns over the stock market are dependent on various micro and macro-economic factors. Panel data analysis was conducted using data from the top 50 companies listed on the National Stock Exchange (NSE) over a 10-year period. The analysis explored the impact of various financial ratios on stock market returns, considering individual-specific effects and time variations. The study found that certain financial ratios, including Earnings per Share (EPS), Earning Yield, Debt to Equity ratio, and Market Capitalization to Sales ratio, significantly influenced stock market returns.
 
 Method: Panel data analysis, also known as longitudinal data analysis or panel regression, is a statistical method used to analyze data collected from a group of individuals, entities, or subjects over time. In panel data analysis, observations are made on the same subjects or entities repeatedly at multiple time points, creating a panel or panel dataset. Panel data analysis is particularly useful in social sciences, economics, and other fields where researchers are interested in studying the dynamics of individual units over time and accounting for both cross-sectional and time-series variations.
 
 Results and Conclusion: The findings from this study provide valuable guidance for individual investors, financial advisors, and policymakers in optimizing investment strategies. However, it is essential to acknowledge the limitations of this research, including the static nature of data collection and the focus on the Indian stock market. Future research should explore longitudinal effects and consider macroeconomic factors to deepen our understanding of the complex relationship between financial ratios, risks, and stock returns. The random effects model shows that the independent variables have a significant relationship with the dependent variable, meaning they are related to each other. The regression models confirm that certain financial ratios, like EPS, Price_To_Cash_Flow, and Cash_Flow_TO_Assets, have a significant impact on stock returns. The model considers the influence of time-specific factors, and the fixed effects model better captures the differences between entities, suggesting that each entity behaves differently in the analysis. In conclusion, this study highlights the multifaceted nature of the Indian stock market and the diverse factors that influence investors' decision-making processes. Enhancing financial literacy, promoting risk management, and understanding investor sentiment are crucial for building a robust and informed investor community. By addressing these aspects, investors and policymakers can contribute to the overall growth, stability, and efficiency of the Indian stock market.
 
 Implications of research: The key advantage of panel data analysis is that it allows researchers to control for individual heterogeneity and unobserved time-invariant factors, which can lead to more accurate and efficient estimates of the relationships between variables. By incorporating both within-unit and between-unit variations, panel data analysis provides a more comprehensive understanding of the data and can help identify causal relationships. Originality/value: the current paper aims to study the relationship between firms’ performance and stock market returns in select NSE listed companies.

Class size and teacher effects on non-cognitive outcomes in grades K-3: a fixed effects analysis of ECLS-K:2011 data

This study examines the association between class size, teacher characteristics and five non-cognitive student outcomes (i.e., self-control, interpersonal skills, approaches to learning, externalizing and internalizing problem behaviors) in grades K-3. Individual fixed-effects, that control for observed and unobserved time-invariant factors, including student and school time-constant variables, are employed to analyze national data from the Early Childhood Longitudinal Study, Kindergarten Class of 2010–11 (ECLS-K:2011). Results suggest a significant linear association between reducing class size and interpersonal skills. Teacher experience is saliently, positively and significantly related with student self-control, interpersonal skills, and approaches to learning, and negatively associated with externalizing problem behaviors. Teacher education and certification were not associated with any of the five non-cognitive outcomes. Changing schools had a negative effect on student’s self-control.

Tackling dynamic prediction of death in patients with recurrent cardiovascular events.

In the field of cardiovascular disease, recurrent events such as stroke or myocardial infarction (MI) are often encountered, leading to an increase in the risk of death. Accurately evaluating the prognosis of patients and dynamically predicting the risk of death by considering the historical recurrent events can improve medical decisions and lead to better health care outcomes. Recently proposed joint modeling approaches within the Bayesian framework have inspired the development of a dynamic prediction tool, which can be applied for subject-level prediction of death with implementation in software packages. The prediction model incorporates subject heterogeneity with subject-level random effects that account for unobserved time-invariant factors and an extra copula function capturing the part caused by unmeasured time-dependent factors. Thereafter, given the prespecified landmark time , the survival probability for a prediction horizon time of interest can be estimated for each individual. The prediction accuracy is assessed by time-dependent receiving operating characteristic curve and the area under the curve and the Brier score with calibration plots is compared to traditional joint frailty models. Finally, the tool is applied to patients with multiple attacks of stroke or MI in the Cardiovascular Health study and the Atherosclerosis Risk in Communities study for illustration.

Associations of Changes in Organizational Justice with Job Attitudes and Health-Findings from a Prospective Study Using a Matching-Based Difference-in-Difference Approach.

Ample evidence indicates that unfairness at the workplace (organizational injustice) is associated with both job attitudes and health of employees. Several factors that influence these associations have been identified: e.g., personality traits, such as the Big Five traits, justice sensitivity, type of occupation (e.g., white-collar), and unobserved time-invariant factors. Previous studies only addressed parts of these issues, and the ideal research design to mitigate biases-an experiment with random assignment to a treatment and control group-is not feasible. This study therefore mimics a randomized experiment using two statistical techniques. First, matching was implemented to balance the treatment and control group in confounding factors (demographics and personality) in two prospective waves (2012-2014) of observational data (4522 white-collar, 2984 blue-collar) taken from the Linked Personnel Panel, which is an employee survey representative for German private sector companies with more than 50 employees. Second, a difference-in-difference approach excludes unobserved time-invariant factors by estimating associations of changes in organizational justice (distributive, procedural, interactional) with job attitudes (job satisfaction, turnover intention) and health (general and mental) in these groups, separate for white- and blue-collar employees. A decrease in perceived justice was associated with lower job attitudes (less job satisfaction and higher turnover intentions), while an increase was associated with higher values. This pattern was found for white- and blue-collar workers and also for health indicators, with the latter, however, being less pronounced. Increased fairness at the workplace is related to better job attitudes and health for white- and blue-collar employees, independent of personality traits and unobserved time-invariant factors.

Mental health, interpersonal trust and subjective well-being in a high violence context.

This paper assesses whether two factors of wellbeing, social capital (interpersonal trust and social networks) and subjective well-being are associated with frequent mental distress and if there are any mediating effects by gender in a city of high urban violence. This paper relies on data that comes from a sample of over 1300 people representative by gender, race/ethnicity, and socioeconomic breakdown of the city of Cali in Colombia, which was collected in 2017 through face-to-face surveys.Our study uses logistic regression with fixed-effects at the district level to control for unobserved time-invariant factors. At the individual level, our analyses account for social and demographic context variables. The dependent variable is mental distress, defined as having 14 or more days feeling mentally ill in the previous 30-day period. Independent variables of interest are “interpersonal trust in unknown people” measured in a scale 0–10 and, social networks measured using the number of family members and close friends and subjective well-being through a question about life satisfaction in a scale 0–10. We find risk factors for mental health distress were low trust in unknown people, low life satisfaction, high levels of depression, living in cohabitation, being female, not having children, and living in middle socio-economic status. The odds of feeling mentally ill decreased as trust in unknown people increased by each unit in the trust scale (OR: 0.92). There were gender differences, with women's mental health being less likely to be affected by lack of interpersonal trust (OR: 0.94) than men (OR: 0.76).Our study suggests that actions aimed at fostering interpersonal trust in unknown people could positively affect mental health distress for both males and females. In the context of high urban violence, our study shows that men are more likely to benefit from such actions.

Homotypic and heterotypic continuity of symptoms of psychiatric disorders from age 4 to 10years: a dynamic panel model.

Childhood psychiatric disorders and their symptoms evince both within-disorder (homotypic) and between-disorder (heterotypic) continuities. These continuities may be due to earlier symptoms causing later symptoms or, alternatively, that the same (unknown) causes (e.g., genetics) are operating across time. Applying a novel data analytic approach, we disentangle these two explanations. Participants in a Norwegian community study were assessed biennially from 4 to 10years of age with clinical interviews (n=1,042). Prospective reciprocal relations between symptoms of disorders were analyzed with a dynamic panel model within a structural equationframework, adjusting for all unmeasured time-invariant confounders and time-varying negative life-events. Homotypic continuities in symptoms characterized all disorders; strongest for attention-deficit/hyperactivity disorder (ADHD) (r=.32-.62), moderate for behavioral disorders (r=.31-.48) and for anxiety and depression (r=.15-.40), and stronger between 8 and 10 than between 4 and 6years. Heterotypic continuity also characterized all disorders. A dynamic panel model showed that most continuities were due to unmeasured time-invariant factors rather than effects of earlier symptoms on later symptoms, although symptoms of behavioral disorders, which evinced two-year homotypic continuity (B=.14, 95% CI: .04, .25), did influence later symptoms of ADHD (B=.13, CI: .03, .23), and earlier ADHD symptoms influenced later anxiety disorder symptoms (B=.07, CI: .01, .12). Homotypic and heterotypic continuities of symptoms of childhood psychiatric disorders are mostly due to unobserved time-invariant factors. Nonetheless, symptoms of earlier behavioral disorders may affect later symptoms of such disorders and of ADHD, and ADHD may increase the risk of later anxiety. Thus, even if interventions do not alter basic etiological factors, symptom reduction may itself cause later symptom reduction.

Evaluating the role of income, state dependence and individual specific heterogeneity in the determination of subjective health assessments

This paper investigates the role of various determinants of an individual's subjective self-assessment of own health. While the economics literature has focused primarily on the role of income on these assessments, we include an examination of the role of state dependence and unobserved individual specific time invariant heterogeneity. We employ a dynamic fixed effects ordered choice model to examine the responses of Australian residents. We find no statistically significant relationship between transitory income and health responses. We also find that while there is evidence of state dependence, this does not appear to be responsible for the distribution of responses. Our results suggest that the variation in the individual specific effects, comprising both observed and unobserved time invariant factors, is primarily responsible for the variation across individuals’ responses.

Continuity of cannabis use and violent offending over the life course.

Although the association between cannabis use and violence has been reported in the literature, the precise nature of this relationship, especially the directionality of the association, is unclear. Young males from the Cambridge Study of Delinquent Development (n = 411) were followed up between the ages of 8 and 56 years to prospectively investigate the association between cannabis use and violence. A multi-wave (eight assessments, T1-T8) follow-up design was employed that allowed temporal sequencing of the variables of interest and the analysis of violent outcome measures obtained from two sources: (i) criminal records (violent conviction); and (ii) self-reports. A combination of analytic approaches allowing inferences as to the directionality of associations was employed, including multivariate logistic regression analysis, fixed-effects analysis and cross-lagged modelling. Multivariable logistic regression revealed that compared with never-users, continued exposure to cannabis (use at age 18, 32 and 48 years) was associated with a higher risk of subsequent violent behaviour, as indexed by convictions [odds ratio (OR) 7.1, 95% confidence interval (CI) 2.19-23.59] or self-reports (OR 8.9, 95% CI 2.37-46.21). This effect persisted after controlling for other putative risk factors for violence. In predicting violence, fixed-effects analysis and cross-lagged modelling further indicated that this effect could not be explained by other unobserved time-invariant factors. Furthermore, these analyses uncovered a bi-directional relationship between cannabis use and violence. Together, these results provide strong indication that cannabis use predicts subsequent violent offending, suggesting a possible causal effect, and provide empirical evidence that may have implications for public policy.

Income inequality and social capital, are they negatively related?: European cross-country analyses 2006-2012

Theoretical notions in the literature suggest the existence of a negative relationship between earnings inequality and social capital as measured by interpersonal trust. In a number of crosscountry studies this negative relationship has been confirmed. However, in later cross country-studies that control for per capita wealth and several characteristics of the population and analyse one year or shifts over longer periods find no relationship between inequality and trust. In our study we take into account that socio-cultural factors may obscure this relationship. Our main focus is on the role of a country’s welfare regime. Four regimes are distinguished: social democratic regime, conservative regime, liberal regime and transition country. We further examine the impact on interpersonal trust of per capita GDP and the societal indicators percent of residents with tertiary education, percent urbanization, government spending as a percent of GDP. We use data over four points of time from 17 European countries. Besides cross-section OLS regression models using averaged data, fixed-effects models are estimated to control for unobserved time-invariant factors. We find the hypothesised negative relationship between earnings inequality and interpersonal trust not confirmed by our data. Our findings do suggest associations between interpersonal trust and welfare regime. With regard to the welfare regime, we found in particular that a conservative regime, a liberal regime and a transition regime are all associated with a much lower level of interpersonal trust than a social democratic regime. The difference in the level of interpersonal trust from countries with a social democratic regime is largest in countries in transition and smallest in countries with a liberal regime. For the development of institutions that can raise the transition countries to higher levels of social capital and economic development, those from the social democratic welfare regime appear to offer the best perspective. The social democratic welfare regime not only pays more attention to the socially vulnerable in society by paying their benefits, but – in addition to that – by investing in strengthening their productive capabilities to improve their chances on the labour market.

Socioeconomic inequality in health in the British household panel: Tests of the social causation, health selection and the indirect selection hypothesis using dynamic fixed effects panel models

Despite social inequality in health being well documented, it is still debated which causal mechanism best explains the negative association between socioeconomic position (SEP) and health. This paper is concerned with testing the explanatory power of three widely proposed causal explanations for social inequality in health in adulthood: the social causation hypothesis (SEP determines health), the health selection hypothesis (health determines SEP) and the indirect selection hypothesis (no causal relationship). We employ dynamic data of respondents aged 30 to 60 from the last nine waves of the British Household Panel Survey. Household income and location on the Cambridge Scale is included as measures of different dimensions of SEP and health is measured as a latent factor score. The causal hypotheses are tested using a time-based Granger approach by estimating dynamic fixed effects panel regression models following the method suggested by Anderson and Hsiao. We propose using this method to estimate the associations over time since it allows one to control for all unobserved time-invariant factors and hence lower the chances of biased estimates due to unobserved heterogeneity. The results showed no proof of the social causation hypothesis over a one to five year period and limited support for the health selection hypothesis was seen only for men in relation to HH income. These findings were robust in multiple sensitivity analysis. We conclude that the indirect selection hypothesis may be the most important in explaining social inequality in health in adulthood, indicating that the well-known cross-sectional correlations between health and SEP in adulthood seem not to be driven by a causal relationship, but instead by dynamics and influences in place before the respondents turn 30 years old that affect both their health and SEP onwards. The conclusion is limited in that we do not consider the effect of specific diseases and causal relationships in adulthood may be present over a longer timespan than 5 years.

Evaluating the Role of Individual Specific Heterogeneity in the Relationship between Subjective Health Assessments and Income

This paper investigates the impact of income on an individual's subjective self-assessment of own health. We employ recently developed methods in the non linear panel data literature to account for the endogeneity of income and the presence of individual heterogeneity. We examine a panel data set of individuals living in Australia and find no statistically significant relationship between income and health responses. Moreover, the evidence suggests that the variation in the individual specific effects, comprising both observed and unobserved time invariant factors, is primarily responsible for the variation across individuals' responses.