Interpretación de datos en un contexto organizacional completo

For a stable society, health education must become a major component of the educational curriculum. In order to achieve MDG health targets, the need for an improved balance between primary, secondary and tertiary health care expenditure cannot be overemphasized, as poor people derive more benefits from primary healthcare supply them from extended care services for hospitals. Also, understanding the sensitivity of age dynamics in this regard would be beneficial to the system. To further bridge the observed inequities, female education needs to be on the front burner of policy implementation to support better health outcomes for households.

Table 5.1.5: Error Correction Model – Health and Population Dynamics

Dependent Variable: D(HEALTH) Method: Least Squares

Date: 01/23/14 Time: 12:58 Sample(adjusted): 1981 2010

Included observations: 30 after adjusting endpoints

Variable Coefficient Std. Error t-Statistic Prob. C 5141.510 3240.944 1.586424 0.1276 D(POP5) 0.130388 0.039670 3.286837 0.0035 D(POP6T11) -0.021580 0.028845 -0.748125 0.4627 D(POP12T17) -0.024472 0.008869 -2.759166 0.0118 D(POP25T34) -0.512859 0.149074 -3.440299 0.0025 D(POP35T44) -0.239544 0.101659 -2.356354 0.0282 D(POP45T54) 1.192868 0.338085 3.528307 0.0020 D(POP65T74) 0.105624 0.188681 0.559805 0.5815 RESHLTH(-1) -1.511103 0.193848 -7.795312 0.0000 R-squared 0.773501 Mean dependent var 5614.298 Adjusted R-squared 0.687215 S.D. dependent var 18889.37 S.E. of regression 10564.29 Akaike info criterion 21.61167 Sum squared resid 2.34E+09 Schwarz criterion 22.03203 Log likelihood -315.1751 F-statistic 8.964446 Durbin-Watson stat 1.956674 Prob(F-statistic) 0.000027

The model above showed robustness and indicated a good fit. Durbin-Watson value of 1.956 showed evidence of no First Autocorrelation amongst the variables. Also, the F statistic and probability indicated a good fit at the 1 percent significance level. Furthermore, the adjusted R squared value of 0.773501 indicates a good fit between the behavioral information and independent variables.

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Public spending in the health sector, which takes into cognizance the changing age structure of the country’s population in the short run would, however, yield significant long term benefits. The speed of adjustment coefficient of -1.511 shows the annual rate of adjustment required in health spending to bring about equilibrium in health spending and population dynamics. The above results implies that health spending should be increased by 1.511 units annually for every 1 unit of change in population to support the dynamics of demographic changes.

Population between the age below 5, 12 – 17 years, 25 – 34 years and 45-54 years had coefficients 0.130, -0.024, -0.512 and 1.192 respectively. These values showed a significant relationship with spending on the health sector. Results indicate that as the Pop 5 and below increases, expenditure in this category increases but not too significantly. This scenario suggests an indication of some sort of commitment to child health care programmes28. This would support positive, non-governmental sector to engage with the sector for populations less than 5 years of age, would support the governments compulsory primary health programme.

The following population groups show a negative relationship with public spending on health services: 6 - 11, 12 – 17, 25 – 34 and 35 – 44. The statistical results suggest that as the population within these age group increases, public spending on health services decreases. This negative relationship between the variables, further indicates the impossibility of meeting MDG Goals 4, 5 and 6 focused on Child Mortality, Maternal health and Combating Diseases respectively.

In-addition, the population within age 45–64 and 65-74 shows a positive relationship with public spending on health spending. This implies that rising population within this group has been met with increasing public spending. However, the model showed a high probability that there would not be, any impact of expenditure on those in the age bracket (65-74). This would obviously put enormous pressure to the working class, thereby worsening welfare conditions

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generally. The elderly and aged should normally get support from the government on health and economic related issues for a sustainable development path.

Results show a structural defect in the system that needs to be addressed for MDG targets to be achievable and sustainable. The child age bearing group (12-117/25- 34) and active working age group (35-44) has a negative relationship with health sector spending. This pattern negates the principle of Maternal Mortality Ratio Target of MDG Goal Five (5).

Figure 5.0.4 Vector Autoregressive Model – Health Sector and Population Dynamics

Source: Derived from the Estimated VAR Model

Inverse Roots (Autoregressive Model) stability test shows that the model passed the minimum requirement because most of the plots lie within the circle.

Health spending in Nigeria as a proportion of total federal government spending has been fluctuating from 2.7 percent to 6.2 percent between 1999 and 2012, which is lower than 2012 allocations in Ghana (57.1 percent), Gabon (51.2 percent), Cameroon (33.5 percent) and Niger (39.7 percent) respectively (WHO National Health Account Database). These countries are smaller than Nigeria in terms of population and they spend higher relatively on total public spending on health than Nigeria (Abiola, 2011). Our analysis are in tandem with FMOH (2005) position that annual budgetary allocations to the health sector are misaligned because of poor framework, bureaucracies and other institutional factors, which frequently results to a haphazard implementation The insignificant health spending could also explain why Nigeria ranks 187 among the 191 signatory member states by the World Health Organization (WHO) in 2000

-1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5

Inverse Roots of AR Characteristic Polynomial

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(National Health Policy, 2004) and 142 out of 169 countries with 48.4 years in life expectancy at birth in 2009 ( HDI UNDP Report, 2010). The infant mortality rate (91 per 1000 live births) is among the highest in the world (Obansa and Orimisan, 2013). These scenarios raise concern on the attainment of MDG targets’ by 2015.

Generally, well being (health) involves many dimensions both for the individual and society in general. For health benefits to reach all, expenditure on the sector should be targeted and specific to the social and cultural dynamics of each age cohort. The health system needs to be integrated into the overall development strategy of the government and would further address existing inequities in the system. Thus, health care service could be readily available with benefits accruing to those who need it.. Emphasis should be placed on improving social conditions of women and children and in addition developing social safety nets. In-addition, restructuring the vertical and horizontal imbalance in the distribution of resources would support attainment of MGD goals on Health. Furthermore, measuring MDG health goals and understanding health problems would benefit the poor and disadvantaged.