Relationship between States Children's Health Insurance for Persons and Income - Speech or Presentation Example

Analysis of Relationship between s’ Childrens Health Insurance for Persons and Income, Poverty Rate and Region Introduction: s provide various welfare measures to its citizens. This is to fulfill various needs of population and provide social security to them. However, many people feel that there is more to it than meets to eye. To them these measures have more to compensate for the higher cost of leaving than mere on humanitarian nicety. This may be topic of debate. But some people have tried to prove their point by hard statistical data and analysis rather than just keeping it in the realm of discussion. In their last book Bob Stoker and Laura Wilson-Gentry have claimed that the welfare measures of states are an instrument to compensate for the higher cost of living in that state rather than being focused on the need of the population. This claim of the authors can be checked by suitable statistical analysis. This paper proposes to check by t-test if the claims of the Bob Stoker and Laura-Wilson-Gentry are correct or not. Student’s T-test is a method by which one can check whether or not there is statistically significant difference between means of a pair of data. What one does in this test is to calculate the t-statistics for a pair of data from sample mean, sample standard deviation and sample size. This value is then compares with the critical value of the t-statistics for a chosen significance level and degree of freedom (depends on the sample size). If the t-statistics is more than the t-critical then it means that there is statistically significant difference between means of the two data pairs otherwise the difference is considered statistically insignificant. One of the important welfare measures of states is to provide “children’s health insurance for persons (CHIP)”. Some states provide this benefit to persons above 250% of the poverty level while others do not. This is certainly a very generous welfare measure and cannot be termed need based. It should be interesting to see if there exists statistically significant difference between median income levels of the states providing CHIP to those above 250% of the poverty level. Therefore, if statistically significant difference exists between median incomes of those states providing CHIP to those above 250% of the poverty level it can be seen as a compensatory measure towards higher cost of living in those states as higher median income is certainly an indicator of the higher cost of living. If the difference is statistically insignificant then one can say that cost of living has no implication on states providing CHIP to those above 250% of the poverty level. Poverty rate is an indicator of the needs of population. Higher poverty rate will mean there is a need of more welfare measures from the state side. Therefore, if indeed the welfare measures are need based then the states with higher poverty rate should be providing CHIP to more people including those above 250% above the poverty level. In other words Student’s T-test should show statistically significant difference between poverty level of the states providing CHIP to those above 250% of the poverty level and those not providing CHIP to those 250% above the poverty level. F this difference is not significant then it will mean that state’s welfare measures are not need based. This paper analyses if provision of CHIP to those above 250% of the poverty level is related to median income level and poverty rate of the states. It has also been examined whether region has an impact on the provision of CHIP to those above 250% of the poverty level. Key Points Children’s Health Insurance for Persons Median Income Level Poverty Rate Region Student’s T-test Methodology Data on poverty rate, median income level and provisions of CHIP for those above 250% of the poverty level was collected for 50 states in the five regions of USA. This data was recorded in MS Office Excel. The states having provisions for CHIP for those above 250% of the poverty level were assigned ‘1’ and those not having such provision were assigned ‘0’. The data was sorted on the basis of CHIP above 250 to make two pairs of data for income level. One column contained median income of states with CHIP above 250 and the other contained median income of state without CHIP with 250. Student’s T-test was performed to examine if there is statistically significant difference between the median incomes of the states in the two groups. This analysis was performed to examine if there exists statistically significant difference in the poverty rate of the sates in the two categories. Further the data was sorted on the basis of region. Then % of states with provision of CHIP above 250 was calculated for each region to see if region has any impact on the provision of CHIP above 250. The analysis is presented in the subsequent sections. Income Level and Provision of CHIP above 250 Student’s T-test was performed to ascertain whether or not there exists statistically significant difference between the median income of states with provision of CHIP above 250 and without this provision. This test was performed using MS Office Excel at significance level of 0.05 and output of the test is presented in Table 2, in the Appendix. This test is performed in the following manner. Let there be n1 and n2 data in column 1 and 2 respectively and 1 and 2 be means of data and 21 and 22 be the variance of the data in column 1 and column 2 respectively. Then t-statistics is defined as where Now there is a critical value of t-statistics corresponding to chosen level of significance and degree of freedom (=) that determines whether the difference between the two means is statistically significant or not. If the t-statistics is more than t-critical then the difference is statistically significant else it is not. In the present case as can be seen from Table 2 in the appendix that the difference between median incomes of the states with provisions of CHIP above 250 and those without this provision is statistically significant. In fact the states with provision of CHIP above 250 have higher median income. This means the provision of CHIP above 250 cannot be seen as state nicety rather it is a compensatory measure against higher cost of living in these states. Poverty Level and Provision of CHIP above 250 Results of Student’s T-test performed using MS Office Excel at 0.05 significance level is presented in Table 3. This test demonstrates that the difference between poverty rates in the states with provision of CHIP above 250 and those without this is not statistically significant. This implies that the provision of CHIP above 250 is not dependent on poverty rates of the states. In other words the state welfare measure above 250 is not need based as the state welfare measures are claimed to be. Prevalence of CHIP above 250 in Different Regions Table 1 in the appendix shows that states in region 1, 2 and 4 are highly likely to have the provision of CHIP above 250; while states in region 3 and 5 are less likely to have this provision. This information is pictorially represented in Fig. 1 using a bar chart. Therefore, the theory that region plays a role in determining the provision of CHIP above 250 appears to have strong basis. Discussions: While there is no denying that states with provision of CHIP above 250 have higher median income based on the t-test. But it remains a matter of debate if this can be taken as a confirmation that this measure is just a compensatory measure against the higher cost of living as the researchers have claimed. It worth pointing here that the states with higher median income are more likely to be rich states and therefore can afford to give welfare measures to more people and therefore, it cannot be seen as just a compensatory measure against the higher cost of living; rather there is an angle of state’s nicety in this measure. Coming to this provision of CHIP above 250 being independent of the state’s poverty rate cannot be taken as a confirmation that state ignores the need angle while determining the welfare measures. One needs to look at the number of people at lower income levels. If that number is large then state will be justified in having the CHIP provision for those rather that to have this provision for people above 250. Therefore, while statistical analysis does its job; one should be careful in drawing conclusions without getting into the underlying logic. Conclusions Based on the findings of the statistical analysis it can be claimed that the states with provision of CHIP above 250 have higher income than the states without this provision. Also, there is no statistically significant difference between the poverty rates in the two types of states. Finally region has significant bearing on whether or not a state has the provision of CHIP above 250. APPENDIX Table 1: Income Level and Poverty Rate of States with CHIP above 250 and without it Median Income ($) Poverty Rate (%) No Chip above 250 Chip above 250 No Chip above 250 Chip above 250 Region %of States with CHIP above 250 40232 55864 20 19 1 83.3 60124 62893 12 13 2 80 47750 63164 20 16 3 28.6 39279 51320 20 15 4 66.7 57333 46407 13 15 5 23.1 54310 49262 15 13 46142 46659 17 15 49387 39461 18 23 47876 65124 13 14 39678 58286 20 16 47160 57815 13 12 46394 45834 16 15 35971 63942 27 9 41852 65933 15 14 49861 49546 13 20 53008 43035 14 19 42295 47750 21 17 44743 49155 13 15 41046 54009 19 14 48521 41632 17 20 42561 51566 18 12 46321 56049 12 13 44861 40103 22 19 55974 50619 13 13 57679 13 48205 13 Table 2: Student’s T-test on Income of States Providing CHIP above 250 and Not Providing the Same   CHIP above 250 No CHIP above 250 Mean 52309.5 47252.4 Variance 64580611.9 39046451.7 Observations 24 26 Hypothesized Mean Difference 0 df 43 t Stat 2.469764203 P(T Read More