Dependent and Control Variables

The primary dependent variable in the statistical tests is Life Expectancy. Life Expectancy can be viewed as an indicator of public health since it is a measure of “the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same

throughout its life.”50 As such, it is a long-term measure which projection over time of the health conditions facing citizens in the current period, indicating how the current environment would impact individuals over time. Data for Life Expectancy come from the United Nation’s

Human Development Reports.51

I also utilize a second measure of public health as a robustness test, Unlike Life

Expectancy, Infant Mortality, which represents the number of infants dying before age one (per

1,000 live births), is a more immediate measure of public health. Ross (2006) argues that infant mortality is highest among the poor, making it a good measure of the health issues facing those who may lack the financial resources to provide for their own healthcare needs and thus would be in greatest need of humanitarian assistance. Furthermore, infant mortality is also “a sensitive measure of many other conditions – including access to clean water and sanitation…prenatal and neonatal health services, caloric intake, [and] disease” (Ross 2006, 861), making it a good measure of overall health and access to needed health infrastructure which aid organizations can help provide. Information for infant mortality rates comes from the World Bank’s WDI.52

The limited time period available for analysis is the motivation for using Life Expectancy as the primary indicator and Infant Mortality as a secondary measure of health. It is possible that aid activities may have both long-run and short-run effects. With only a four-year sample, however, there is a limited window available to assess these effects by varying the temporal relationship between the delivery of aid and the corresponding health outcome. Using Life

Expectancy, even though it is calculated in a specific year within the sample, allows for greater

consideration of systemic level factors which may influence long-run trends in health than would

50

Description taken from the “Notes” section of the World Bank’s WDI, accessed April 4, 2011. 51

http://hdr.undp.org/en/statistics/data/. Accessed June 23, 2011. 52 _{Accessed April 4, 2011.}

the more immediate measure of Infant Mortality. In other words, Life Expectancy should encompass a broader range of health inputs and reflect how they would impact individuals over time than would Infant Mortality, and it is therefore a better measure of the broad set of direct and indirect ways in which aid is argued to impact health detailed in Chapter 3.0 , including through crisis.53

Additional regressors are drawn from other studies examining the relationship between civil conflict and public health, specifically Iqbal (2010) and Ghoborah et al. (2003).54 These variables can be loosely group in one of the three following categories: economic, demographic, and political.

The first of the economic variables is the level of economic development, which is measured here with GDP per capita in constant 2000 U.S. dollars, using data taken from the World Bank’s World Development Indicators (WDI), from which GDP Growth, the yearly percentage increase in GDP, is also taken. In addition to level of development, the openness of a country’s economy to international trade has also been shown to affect health (Owen and Wu 2007; Rudra and Tirone 2011). Therefore, in line with Iqbal (2010) a measure of the country’s openness to international trade, Openness, is included. Openness measures the level of imports and exports as a percentage of GDP in constant terms with data from the Penn World Tables (Heston, Summers, and Aten 2011). This variable is also interacted with GDP per capita to create GDP per capita X Openness. Finally, to capture the domestic government’s commitment

53 _{Infant Mortality is customarily one of the measures accounted for in the calculation of Life Expectancy,} so the latter is also a reflection of the short term dynamics affecting the infant mortality rate.

54

I adopt this model specification, in line with the studies cited, due to the ways in which the theory suggests aid should affect health. In the theory the externalities of aid are not primarily medical, but rather operate through various societal channels. Therefore, it is these social channels which are most likely to be correlated with both aid and health and would induce bias if omitted. This would be different if I were testing specific medical practices or intervention strategies. In those cases, a specification which was closer to epidemiological testing, for example, would be appropriate. In the absence of data which are so finely differentiated, and in light of the aid- social phenomena-health nexus which is the focus of the theory, this specification is more statistically appropriate.

to health and available resources, Public Health Expenditures measures government spending on health as a percentage of all government expenditures. Data for Public Health Expenditures come from the World Bank’s WDI.55

Two demographic measures are also included. The first is Population (logged), which is the natural log of the population and comes from the World Bank’s WDI.56 Additionally, as Ghoborah, Russett and Huth (2003, 191) argue, “a more knowledgeable population is likely to be more knowledgeable of health risk factors, to support greater investments and expenditures, and to utilize health-care services.” As such, Education, a measure of the expected number of years of education a citizen will receive, is also included, with data from the United Nation’s Human

Development Reports.57

A number of studies have also highlighted the relationship between a country’s regime type and health (As an example, see Ross 2006; Rudra and Tirone 2011). Therefore, the Polity IV project’s Polity measure, the 21-point scale running from -10 to 10, with lower values indicating greater levels of autocracy and higher values greater democracy, is also included (Marshall and Jaggers 2002).58

Table 4-1 provides descriptive statistics for the primary variables utilized in the analysis.

55 _{Accessed June 16, 2011.} 56

Accessed June 16, 2011. 57

http://hdr.undp.org/en/statistics/data/. Accessed June 23, 2011.

Table 4-1 Descriptive Statistics, 2004-2007

N Mean Min Max

Life Expectancy 676 66.44 41.28 82.18 Infant Mortality 503 38.72 1.40 139.80 ICRC Aid 734 5119.88 0 160,381.90 MSF Aid 734 2048.62 0 61,843.30 Oxfam Aid 770 2286.79 0 50,611.02 Conflict (Current) 766 0.11 0 1 Conflict (Prior) 766 0.19 0 1

Civil Conflict (Current) 766 0.09 0 1

Civil Conflict (Prior) 766 0.18 0 1

Civil War (Current) 766 0.09 0 1

Civil War (Prior) 766 0.14 0 1

Disasters (Current) 766 1.64 0 37.00

Disasters (Prior) 763 4.61 0 91.00

GDP Growth 666 6.14 -6.47 46.50

GDP per capita 655 5976.53 85.82 106,466.10

Openness 659 95.55 1.77 441.22

Public Health Expenditures 652 10.61 0.77 41.66

Population (logged) 727 8.09 2.35 14.09

Polity 542 2.40 -10.00 10.00