Info5060 Data Analytics And Business Assessment Answers

Utilise various analytics tools and techniques to provide insights about the data. Analyse different sets of data for insight, and to report the findings in effective manner. 

Answer:

Introduction

Sustainability of the aging population has become a global concern nowadays. This is the concern which in turn have compelled the governments to consider the possibility of incrementing the retirement age of the population. This decision taken by the government may enhance the labor market although health is also needed to be considered which could make this extra force more effective and thereby improve the economic productivity. This is the underlying reason for investigating the intricacy of the relationship between employment and health (Gauthier and Bartova, 2015). On the other hand, it is also important to the policy makers to develop an understanding of the impact if employment over the health stature of the people so that they can effectively implement certain more effective policy frameworks. This is also expected to improve the health condition of the people of the labor market through the implementation of new employment policies. It has been a widely argued fact that the stature of employment or the standard of job can impact severely over the mental and physical health of the individual employees. For instance Goodman (2015) have argued that it is more likely that if a person is employed in the elite sector it is more likely that the person would lead a more healthy life. The aim of this research is thus to investigate the impact of the employment standard over the health condition of people. In order to substantiate the aim of this research a set of key objectives have also been designed in accord, achieving which is expected to lead the researcher towards the expected research outcomes. The broader objectives of the research are, to develop a proper understanding of the term job stature and to determine how the stature or standard of job may affect the health condition of the employees. In the era of globalization and advancements the level of competition in the labor market is increasing rapidly and hence the governments of the respective countries are certainly needed to take care of their labor force so as to sustain the extreme competition. Hence this research work is expected to provide the government of the country to evaluate how the employment stature can affect the heath condition of the employees. This in turn would enable the government to design and implement certain strategic framework which in turn would make the employee better off through proper health policies and their performance would also improve due to this.

Conceptual Framework

The relationship or association between employment standard and health has been a widely discussed factor and the researchers concerned in this field have focused mostly on the impact of employment on health (Benach et al., 2014). That is they have considered employment or the standard of employment as the independent variable while the health condition is identified as the dependent variable determined by the job standard. The literature have substantiated the fact that there is a positive relationship between health and employment, which signifies the fact that the better the health of an employee would be the better would be his or her performance. On the other hand, Gebel and Voßemer, (2014), have stated that health limitations in turn increases the non-employment hazards by 58% in the context of men and 39% in the context of women. Moreover, the critical decision for joining or leaving the labor force intricately depends on the health status of the individuals, because the people who are unhealthy may decide to stay unemployed because of their health status or they can lose the job because of the lower level of productivity (Clement et al., 2015).

It is also a widely discussed fact that the impact of employment on health is also positive. Schultz et al., (2016), have substantiated the fact that employed people generally depicts a better health condition in comparison to the people who are not employed. For example it can be traced out from the research work of Chaumet-Riffaud et al., (2017), that people who are full time employed with a fixed contract in Germany are 42% more likely to report poor health condition than those people who possesses permanent work contracts. However, it has also been observed that the relationship between employment and health is more complicated or complex that the one way relationship as stated above. There may exist a double causality relationship between these two variables which signifies there may be a two way relationship between these two (Benach et al., 2016). However, it is also a matter of fact there is not so many studies which have investigated this two way relationship. This research work will shed light on investigating the relationship between these two variables and will also determining to what extent changing the employment would affect the health condition of the individuals. The designed hypothesis for the research work can be stated as follows,

Null Hypothesis: There is a positive relationship between the employment stature and health condition of people.

Alternative Hypothesis: There is not a positive relationship between the employment stature and health condition of people.

Methodology

Positivism research approach have been followed strictly while carrying out the research work, which signifies that it has made use of relevant graphs, charts and data available in this regard. Secondary data have been collected and used for this research work, the relevant data have been collected from World Value Survey and is analytically represented with the help of SPSS. The advantage of using secondary data is that it is less time consuming and reduces the cost of the research as well. Furthermore, secondary data have also been collected in the form of journal articles, company annual reports, case studies from the trusted sources which in turn ensured that there is no discrepancy in the secondary data. The Wave 5 of the World Value Survey has been utilized in the context of this specific research work. As the data presented the responses in terms of Likert Scale, relevant dummy variables have been constructed for effectively carrying out the research. In this case the health condition have been considered as the dependent variable and hence a single dummy has been created for this variable for the people with excellent health condition. On the other hand, in the context of employment standards relevant dummy variables have been constructed on the basis of the need which effectively represents the variable. Furthermore logistic regression have been conducted because binary values cannot regressed ordinarily. On the other hand, descriptive statistics have also been used for developing a crisp idea about the variables which are considered in the research work.

Data Analysis (600)

Descriptive Statistics
	N	Minimum	Maximum	Mean	Std. Deviation
State_of_Health_Dummy	1041	.00	1.00	.3314	.47095
Fulltime_Dummy	1041	.00	1.00	.3189	.46628
Self_Employed_Dummy	1041	.00	1.00	.0711	.25709
Unemployed_Dummy	1041	.00	1.00	.0768	.26648
Job_Manager_Dummy	1041	.00	1.00	.0893	.28537
Job_Supervisor_Dummy	1041	.00	1.00	.0663	.24889
Job_EliteWorker_Dummy	1041	.00	1.00	.1575	.36449
Job_Farmer_Dummy	1041	.00	1.00	.0029	.05363
Valid N (listwise)	1041

The descriptive statistics signifies that the value of the considered variables are centrally aligned and the occurrence of each of them is equally likely. On the other hand the standard deviation of the variables also depicts that these could not be regarded as a non-significant variable. Hence the descriptive statistics of the dummy variables depict significant results.

Logistic Regression

Case Processing Summary
Unweighted Casesa		N	Percent
Selected Cases	Included in Analysis	1041	100.0
	Missing Cases	0	.0
	Total	1041	100.0
Unselected Cases		0	.0
Total		1041	100.0

 

a. If weight is in effect, see classification table for the total number of cases.

 

Dependent Variable Encoding
Original Value	Internal Value
Others	0
Excellent	1

 

Categorical Variables Codings
		Frequency	Parameter coding
			(1)
Job_Farmer_Dummy	No	1038	1.000
	Yes	3	.000
Self_Employed_Dummy	No	967	1.000
	Yes	74	.000
Unemployed_Dummy	No	961	1.000
	Yes	80	.000
Job_Manager_Dummy	No	948	1.000
	Yes	93	.000
Job_Supervisor_Dummy	No	972	1.000
	Yes	69	.000
Job_EliteWorker_Dummy	No	877	1.000
	Yes	164	.000
Fulltime_Dummy	Not full Time	709	1.000
	Full Time	332	.000

Block 0: Beginning Block

Classification Tablea,b
	Observed		Predicted
			State_of_Health_Dummy		Percentage Correct
			Others	Excellent
Step 0	State_of_Health_Dummy	Others	696	0	100.0
		Excellent	345	0	.0
	Overall Percentage				66.9

 

a. Constant is included in the model.

b. The cut value is .500

 

Variables in the Equation
		B	S.E.	Wald	df	Sig.	Exp(B)
Step 0	Constant	-.702	.066	113.608	1	.000	.496

The table above depicts that the research work has taken into consideration a total of 1041 observations and hence it can be regarded as a large sample on which the logistic regression has been performed. The standard error can be considered as quite low which is about 6.6% as a whole and hence the research work is valid. The results are meaningful

Variables not in the Equation
			Score	df	Sig.
Step 0	Variables	Fulltime_Dummy(1)	5.091	1	.024
		Self_Employed_Dummy(1)	2.753	1	.097
		Unemployed_Dummy(1)	4.429	1	.035
		Job_Manager_Dummy(1)	2.034	1	.154
		Job_Supervisor_Dummy(1)	.319	1	.572
		Job_EliteWorker_Dummy(1)	3.041	1	.081
		Job_Farmer_Dummy(1)	1.526	1	.217
	Overall Statistics		18.342	7	.011

Block 1: Method = Enter

Omnibus Tests of Model Coefficients
		Chi-square	df	Sig.
Step 1	Step	18.304	7	.011
	Block	18.304	7	.011
	Model	18.304	7	.011

 

Model Summary
Step	-2 Log likelihood	Cox & Snell R Square	Nagelkerke R Square
1	1304.129a	.017	.024

 

a. Estimation terminated at iteration number 4 because parameter estimates changed by less than .001.

Finally the Cox and Snell R square value signifies the fact that goodness of fit of the model is good however the Nagelkerke R square value signifies a way better goodness of fit. Hence it can be stated that the model can be accepted and the Null Hypothesis should be substantiated by the model.

Classification Tablea
	Observed		Predicted
			State_of_Health_Dummy		Percentage Correct
			Others	Excellent
Step 1	State_of_Health_Dummy	Others	695	1	99.9
		Excellent	343	2	.6
	Overall Percentage				67.0

 

a. The cut value is .500

 

Variables in the Equation
		B	S.E.	Wald	df	Sig.	Exp(B)
Step 1a	Fulltime_Dummy(1)	-.302	.147	4.201	1	.040	.739
	Self_Employed_Dummy(1)	-.525	.255	4.236	1	.040	.591
	Unemployed_Dummy(1)	.333	.286	1.357	1	.244	1.395
	Job_Manager_Dummy(1)	-.369	.230	2.568	1	.109	.691
	Job_Supervisor_Dummy(1)	-.247	.266	.862	1	.353	.781
	Job_EliteWorker_Dummy(1)	-.304	.182	2.777	1	.096	.738
	Job_Farmer_Dummy(1)	-1.618	1.229	1.732	1	.188	.198
	Constant	2.107	1.399	2.268	1	.132	8.227

 

a. Variable(s) entered on step 1: Fulltime_Dummy, Self_Employed_Dummy, Unemployed_Dummy, Job_Manager_Dummy, Job_Supervisor_Dummy, Job_EliteWorker_Dummy, Job_Farmer_Dummy.

As the variable summary suggests on the basis of the probability and level of significant the null hypothesis is accepted and the alternative hypothesis is rejected. Hence it can be stated that the employment standard possesses a positive impact over the health condition of the employees.

Conclusion

On a concluding note, it can be stated that the research work has successfully evaluated and examined the impact of employment standards over the health conditions of the employees. It has been observed after thorough research work and data analysis that the employment standard possesses a positive and significant impact of the health condition of the employees. The better the employment is the better the health condition of the individual. Furthermore, it is also necessary to mention that the research work have been conducted through following the appropriate research ethics any academic malpractice have not been performed by the researchers. All the data have been collected from trusted sources following appropriate techniques.

Reference List

Benach, J., Vives, A., Amable, M., Vanroelen, C., Tarafa, G. and Muntaner, C., 2014. Precarious employment: understanding an emerging social determinant of health. Annual review of public health, 35.

Benach, J., Vives, A., Tarafa, G., Delclos, C. and Muntaner, C., 2016. What should we know about precarious employment and health in 2025? Framing the agenda for the next decade of research. International journal of epidemiology, 45(1), pp.232-238.

Chaumet-Riffaud, A.E., Chaumet-Riffaud, P., Cariou, A., Devisme, C., Audo, I., Sahel, J.A. and Mohand-Said, S., 2017. Impact of Retinitis Pigmentosa on Quality of Life, Mental Health, and Employment Among Young Adults. American journal of ophthalmology, 177, pp.169-174.

Clement, S., Schauman, O., Graham, T., Maggioni, F., Evans-Lacko, S., Bezborodovs, N., Morgan, C., Rüsch, N., Brown, J.S.L. and Thornicroft, G., 2015. What is the impact of mental health-related stigma on help-seeking? A systematic review of quantitative and qualitative studies. Psychological medicine, 45(1), pp.11-27.

Gauthier, A.H. and Bartova, A., 2015. The impact of leave arrangements on employment, fertility and health: a review of the literature.

Gebel, M. and Voßemer, J., 2014. The impact of employment transitions on health in Germany. A difference-in-differences propensity score matching approach. Social science & medicine, 108, pp.128-136.

Goodman, N., 2015. The Impact of Employment on the Health Status and Health Care Costs of Working-age People with Disabilities. Lead Center Policy Brief.

Schultz, R., Owen, G., Anton, M., Bloomgren Jr, B. and Gaugler, J., 2016, November. IMPACT OF EMPLOYMENT STATUS ON HEALTH, STRESS, AND ANXIETY OF EMPLOYED FAMILY CAREGIVERS. In GERONTOLOGIST(Vol. 56, pp. 152-152). JOURNALS DEPT, 2001 EVANS RD, CARY, NC 27513 USA: OXFORD UNIV PRESS INC.