How Educational Attainment and Age Affect the Relationship - Essay Example

AN INVESTIGATION OF THE RELATIONSHIP BETWEEN PERCEIVED LEVELS OF CORRUPTION IN GOVERNMENT AND SATISFACTION LEVELS OF BAHRAINIS: HOW EDUCATIONAL ATTAINMENT AND AGE AFFECT THE RELATIONSHIP By Presented to Introduction This research investigated the relationship between the satisfaction levels of Bahrain nationals aged above 18 years of age and how they perceive corruption to be deeply or lightly rooted in the government. Age and highest education levels attained by individual respondents to the survey were introduced to seek their abilities to moderate the relationship. It has been established that corruption is a hindrance to quality service delivery, and that once the populations learns about its true levels (especially when it is considerably high), they tend to be apathetic towards their administration (Porumbescu and Im, 2013). In the real sense, corruption affects the general physical infrastructure of a country/ region, including construction of roads, schools, health facilities, and conservation of the environment (Radin, 2013; Ionescu, Lazaroiu and Iosif, 2012). Certain variables either mediate or moderate the relationship between these two perceptions. For instance, more mature people (those in relatively more advanced ages) tend to have better understanding of corruption and its effects, and may consequently tend to rate corruption significantly higher than younger persons. Explaining this observation, Porumbescu and Im (2013) further noted that ‘more educated’ individuals are more conscious of corruption in society, and can relate its effects to service delivery more easily than the less educated. Based on these established discussions, the present analysis attempted to conceptualize how perceptions on corruption could be related to the perceived impediments to quality service delivery, including provision of high standard infrastructure. Respondents’ satisfaction with eight items that constitute infrastructural wellbeing was assessed. These include public transport systems, roads and highways, schools, quality of air, quality of water, quality of health care, quality of housing, and the beauty or physical setting of the localities within which the respondents live. Again, based on the findings in the mentioned research articles, the researcher hypothesized that higher perceived levels of corruption in government are significantly related to lower levels of satisfaction with service delivery. Similarly, age and educational level are estimated to relate with the perceived level of satisfaction such that as either increases, the level of satisfaction decreases. Age and educational attainment are also theorised to have a linear relationship with the perceived level of corruption, implying that as either of the variables increases, the perceived level of corruption increases. Methods Data used for the present analysis was downloaded from the World Values Survey website. The data was collected in 2014, and comprised a sample of 1200 Bahrainis who responded to a wide number of survey questions. For the purposes of this analysis, only 11 variables were (representing 11 questions in the survey) were picked. Besides satisfaction with public transport systems, roads and highways, schools, quality of air, quality of water, quality of health care, quality of housing, and the beauty or physical setting, the age, level of educational attainment, and perceived level of corruption within government were used. The first eight were reconstructed to comprise subscales of the ‘satisfaction’ scale. The subscales were used to determine the inclusion and exclusion criteria for individuals in the final analysis. A method of determining how to deal with respondents’ failure to express their level of satisfaction across varying number of questions complicated the search for a way to use data from these individuals without compromising on the overall outcome. In the end, data from all those respondents who failed in this respect was struck off, remaining with data from 1191 participants. The eight subscale scores were summed up to form a common satisfaction score representing every individual. The highest score an ‘extremely satisfied’ participant could provide for any unique question was 4, while the most dissatisfied could give a score of 1. The scores were initially reported in an inverted manner, meaning a score of 1 corresponded to highest level of satisfaction as 4 corresponded to the highest level of dissatisfaction. All 8 subscales of satisfaction were reconstructed to the form indicated earlier. As such, the highest score expected of an individual was 32 (for a respondent who was ‘extremely satisfied’ with all 8 facilities represented in the subscales) while the lowest was 8. Summation satisfaction scores above 16 were considered to represent ‘satisfaction’ while those below the threshold represented ‘dissatisfaction’. Similarly, on a scale of 1 to 10, ratings above 5 were taken to represent ‘high rate of perceived corruption’ while those between 1 and 5 represented ‘low level of corruption’. This classification was necessary for contingency and chi square analysis. Participants who had not attained a primary school education (those who never attended and those who dropped before graduating at the level) were reclassified together. This clustering was continued for participants who had not completed high school and those who had not completed university education. Age was split up into four categories representing the relatively youthful (18 – 36 years), mature adults (37 – 54 years), and the relatively aged (55 – 72 years). Regression and chi square analysis were used to provide insight into the data. Analysis and Discussion Univariate Analysis Descriptive analysis was performed to provide insight into the general characteristics of the response variable, satisfaction with service delivery and physical amenities. Table 1 and Figure 1 below indicate the general characteristics of the variable. Table 1. Descriptive statistics for the overall satisfaction score. N Min. Max. Mean Std. Deviation Skewness Kurtosis Overall satisfaction score 1191 8.0 32.0 23.94 6.88 -0.575 -0.373 Valid N (list-wise) 1191 Based on the above table, the minimum level of satisfaction was 8. This indicates that for the particular respondents replying this way, they only awarded a mark to each question. They were simply ‘extremely dissatisfied’ with every aspect of service delivery. By contrast, there were respondents indicating that they were ‘absolutely satisfied’ with the level of service delivery at every point of consideration. Generally, the average level of satisfaction was above average (mean = 23.94, std. dev. = 6.88). Notably, the average level of satisfaction was quite close to 75% ((23.94/32)*100 = 74.81%), which can be considered to be relatively high. The level of skewness (-0.575) indicates that the data is slightly but not abnormally skewed to the left. This indicates that more values lie to the left of the mean value, creating a left tail as shown in the histogram below. The data can be described as bimodal, with frequencies peaking at both 24 and 32. These are the overall satisfaction scores that had the largest number of respondents each. Again, we notice that they both lie on the side of the ‘above average satisfaction rate’. Such scores could have had a significant positive influence on the outcome of the average score. Figure 1. Histogram of the overall satisfaction scores for respondents. Bivariate Analysis Bivariate analysis of variables was performed to determine the nature of associations between the independent variable, perception of level of corruption, and the dependent, overall satisfaction scores. The results of the cross-tabulation are shown in Table 2 below. Table 2. Crosstabulation: Total satisfaction recoded into either low or high * Corruption recoded into either low or high. Count Corruption recoded into either low or high Total Low Corruption Levels High Corruption Levels Total satisfaction recoded into either low or high Low Satisfaction Levels 94 146 240 High Satisfaction Levels 348 603 951 Total 442 749 1191 In line with the earlier observed position of most values closer to the mean, the table shows that the frequencies for respondents who indicated they had above average (total scores above 16) levels of satisfaction was higher for both groups of respondents who indicated that there was either high or low corruption levels in government. 348 of those indicating corruption levels were low (rating 5 and below) had satisfaction levels higher than average while 603 who indicated corruption was high in government recorded above average satisfaction levels with service delivery. In total 951 (79.85%) out of the 1191 reported above average satisfaction scores.94 of respondents who returned low satisfaction scores indicated that corruption levels were low while 146 indicated that corruption within government was high. Looked at from another dimension, more respondents (749, comprising 62.89%) indicated that corruption was high in government while 442 (37.11%) believed the vice was lowly practised. There is an element of contrast in the results; despite more respondents reporting that corruption was high in government (62.89%), an even higher percentage (79.85%) was generally satisfied with the level of service delivery by the government. In other words, they could not relate corruption to impediments to service delivery. This can be attested to using the chi square results in Table 3 below. Table 3. Chi-Square results for the association between total satisfaction and corruption levels. Value df Asymp. Sig. (2-sided) Exact Sig. (2-sided) Exact Sig. (1-sided) Pearson Chi-Square 0.544a 1 0.461 Continuity Correctionb 0.439 1 0.508 Likelihood Ratio 0.541 1 0.462 Fishers Exact Test 0.501 0.253 Linear-by-Linear Association 0.543 1 0.461 N of Valid Cases 1191 a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 89.07. b. Computed only for a 2x2 table. Based on the Pearson’s chi square value (χ2 = 0.544, df = 1, p = 0.461), the rows and columns of the table are not statistically independent. The earlier found link between the high satisfaction scores and high corruption perception levels could imply that the data is not interdependent; however, this seeming relationship can only be attributed to chance: there is no statistical evidence to show that the relationships actually exist. This demystifies any suppositions that could come with wrongly insinuated relationships between the cells (and the variables they represent). The relationship was further tested using linear regression. The results are presented in Table 4 below. Table 4. ANOVA table for the regression analysis. Model Sum of Squares df Mean Square F Sig. 1 Regression 267.962 1 267.962 5.676 .017b Residual 56131.685 1189 47.209 Total 56399.647 1190 a. Dependent Variable: Summation of the 8 satisfaction scales b. Predictors: (Constant), How widespread: Corruption is within the government in your country The regression results indicate there is a significant (F = 5.676, p = 0.017) relationship between satisfaction and levels of corruption. In essence, the significance level of this test indicates that the regression coefficient is not equals to zero (0); if it was, the hypothesized linear relationship would not be existing. This result is further supported by the results in Table 5 below. Indeed, the coefficient (-0.243) indicates that the two variables have an inverse relationship: a higher level of satisfaction corresponds to a lower level of perceived corruption in government. Table 5. Table of coefficientsa. Model Unstd. coeff. Std. Coeff. t Sig. 95% CI for B B S.E. Beta L.B. U.B. 1 (Constant) 25.415 0.651 39.065 0.000 24.139 26.692 How widespread: Corruption is within the government -0.243 0.102 -0.069 -2.382 0.017 -0.443 -0.043 a. Dependent Variable: Summation of the 8 satisfaction scales Multivariate Analysis This section of the analysis provides insights into further relationships between the above used variables (dependent: satisfaction score, and the independent: perceived level of corruption in government). The age and education elements were introduced to investigate how they mediate the relationship between the dependent and independent variables. Tables 6 and 7 provide a glimpse into the interdependence between the mediating variables and satisfaction scores. Table 6. Crosstabulation: satisfaction versus age groups. Age Groups Total 18-36 37-54 55-72 Total satisfaction recoded into either low or high Low Satisfaction Levels 100 102 38 240 High Satisfaction Levels 451 322 178 951 Total 551 424 216 1191 Of those who reported above average levels of satisfaction, 451 were between 18 and 36 years, 322 between 37 and 54 years, and 178 between 55 and 72 years of age. Based on this and earlier analysis, this category (based on satisfaction levels) captured the views of a larger number of respondents. Among those indicating they were satisfied below average, 100 were between 18 and 36 years, 102 between 37 and 54 years, and 38 between 55 and 72 years. The chi square test showed that the values in the rows and the columns are dependent of each other; they are interrelated (χ2 = 6.271, df = 2, p = 0.043). Therefore, the ratings were influenced by the ages of participants. A higher ratio of those between 55 and 72 years was satisfied with the infrastructural amenities than were respondents from other age groups. Table 7. Crosstabulation: satisfaction versus highest level of education attained. Education levels based on highest verifiable certificates Total None Primary High School University Total satisfaction recoded into either low or high Low Satisfaction Levels 52 89 76 23 240 High Satisfaction Levels 120 333 388 110 951 Total 172 422 464 133 1191 Based on Table 7, the number of highly satisfied respondents without any formal educational certificates was 120. Those with primary school certificates were 333, 388 had high school certificates, and 110 had university degrees. Of those who reported below average level of satisfaction, 52 had not attained any educational certificates, 89 had primary school certificates, 76 had high school certificates and 23 university degrees. Satisfaction levels and educational attainment were dependent of each other (χ2 = 15.873, df = 3, p = 0.001). Based on the results, the more educated groups of respondents tend to have higher levels of satisfaction than the lowly educated/ uneducated ones. This is unlike the initially anticipated hypothetical relationship that the more educated people within a group point out instances of corruption more easily since they have higher understanding of what it entails. The results show the opposite: however, it is baseless to indicate that the more educated persons in the survey are blind to corruption; rather, it is likely that the level of it being said to exist does not match its real extent on the ground. Therefore, as the less educated fail to identify whether the claims are indeed true, the more educated fail to find a basis for the claims, and remain optimistic about the ability of the government to deliver quality services and infrastructural projects. Regression analysis was undertaken to further understand the relationship between the two main variables and how the moderating variables affect the relationship. The results are shown in Tables 8 and 9 below. Table 8. ANOVAa for the mediated relationship. Model Sum of Squares df Mean Square F Sig. 1 Regression 985.407 3 328.469 7.036 .000b Residual 55414.240 1187 46.684 Total 56399.647 1190 a. Dependent Variable: Summation of the 8 satisfaction scales b. Predictors: (Constant), Highest educational level attained, How widespread: Corruption is within the government in your country, Age Table 9. Coefficientsa for the mediated relationship. Model Unstd. Coeff. Std. Coeff. t Sig. 95.0% C.I. for B B S.E. Beta L.B. U.B. 1 (Constant) 26.37 .987 26.72 .000 24.43 28.31 How widespread: Corruption is within the government -.260 .102 -.074 -2.55 .011 -.459 -.060 Age -.045 .014 -.091 -3.12 .002 -.073 -.017 Highest educational level attained .163 .083 .057 1.967 .049 .000 .325 a. Dependent Variable: Summation of the 8 satisfaction scales Age (β = -0.045, p = 0.002) and educational attainment (β = 0.163, p = 0.049) were both significant predictors of the satisfaction levels of respondents. This implies that both variables can be further tested for mediating effect on the satisfaction scores. The significance of the mediating effects were calculated using the formula: where seab equals: For age: zab = [-0.260*-0.045]/ {(-0.2602*0.000196) + (0.002025*0.010404)}1/2 = 1.997. This value is greater than the conventional 1.96 below which the z-score would be considered not significant. Therefore, age is a significant mediating factor for the relationship between satisfaction levels and perceived levels of corruption. Using a similar approach, educational attainment had a z-score of -1.556. In its absolute form, this value is not statistically significant. Therefore, educational attainment is not a significant mediating factor for the relationship between satisfaction levels and perceived levels of corruption. Age has been determined as the only significant mediating factor for the relationship. The relationship is shown in Figure 2 below. -0.243 -0.010 -0.045 References Ionescu, L., Lazaroiu, G. and Iosif, G. 2012. Corruption and bureaucracy in public services. Amfiteatru Economic. XIV (6): 665-679. Porumbescu, G. and Im, T. 2013. Does transparency improve citizens’ perceptions of government performance? Evidence from Seoul, South Korea. Seoul National University. Radin, D. 2013. Does corruption undermine trust in health care? Results from public opinion polls in Croatia. Social Science & Medicine. 98: 46-53. Worldvaluessurvey.org. 2015. WVS Wave 6 (2010 – 2014) – Bahrein 2014. [Online]. http://www.worldvaluessurvey.org/WVSDocumentationWV6.jsp. Read More