Official development assistance, income per capita and health outcomes in developing countries: Is Africa different?

Figures & data

Table 1. Descriptive statistics

	(1)	(2)	(3)	(4)	(5)
VARIABLES	N	mean	sd	Min	Max
ODA	405	34.01	70.22	−0.400	819.9
GDPPC	405	2,616	2,907	126.5	15,690
HIV	405	2.453	4.919	0.100	28.04
IMM	405	81.63	16.85	20.60	99
U5MR	405	65.34	52.02	5.500	254.3
CO2	405	1.627	2.039	0.0183	15.03
LE	405	64.82	9.444	36.60	79.77
Number of CROSSID	81	81	81	81	81

Source: Authors computation

Table 2. Correlation matrix

	LE	U5MR	ODA	GDPPC	HIV	HIV	IMM
LE	1.0000
U5MR	−0.9283	1.0000
ODA	−0.5206	0.5573	1.0000
GDPPC	0.5973	−0.5720	−0.3278	1.0000
HIV	−0.4899	0.2783	0.0961	−0.0911	1.0000
CO2	0.4895	−0.5064	−0.2855	0.5833	−0.1670	1.0000
IMM	0.7006	−0.7732	−0.2803	0.4010	−0.0832	0.4214	1.0000

Source: Authors computation

Table 3. Result of two-step-system-GMM

VARIABLES	LE (1)	LE (2)	LE (3)	LE (4)	LE (5)
L.LE	0.563***	0.568***	0.605***	0.595***	0.627***
	[0.0702]	[0.0635]	[0.0512]	[0.0536]	[0.0588]
ODA	−0.0134**	−0.00815***	−0.00769***	−0.00809**	0.0461*
	[0.00534]	[0.00252]	[0.00264]	[0.00339]	[0.0239]
GDPPC	0.000529***	0.000317***	0.000324***	0.000345***	0.000405***
	[0.000152]	[0.0000924]	[0.000078]	[0.0000966]	[0.000101]
HIV		−0.341***	−0.343***	−0.346***	−0.341***
		[0.069]	[0.0576]	[0.0601]	[0.0602]
CO2		−0.0629	0.0256	0.0205	0.0807
		[0.192]	[0.213]	[0.226]	[0.235]
IMM		0.123***	0.143***	0.140***	0.148***
		[0.0223]	[0.0238]	[0.0252]	[0.0242]
SSA			2.333	2.273	3.947**
			[1.534]	[1.799]	[1.875]
GDPPC_SSA				−0.00024
				[0.000373]
ODA_SSA					−0.0559**
					[0.0252]
Constant	29.02***	19.26***	14.22***	15.23***	11.19**
	[4.421]	[3.012]	[3.924]	[4.005]	[4.41]
Observations	324	324	324	324	324
No. of CROSSID	81	81	81	81	81
Hansen_test	4.843	4.165	4.475	4.213	3.236
Hansen Prob	0.184	0.244	0.107	0.122	0.198
AR(1)_test	2.752	2.05	2.097	2.079	2.278
AR(1)_P-value	0.00592	0.0403	0.036	0.0376	0.0228
AR(2)_test	−0.739	−1.189	−1.492	−1.529	−1.9
AR(2)_P-value	0.46	0.234	0.136	0.126	0.0574
No. of Instrum.	7	10	10	11	11

Robust standard errors in parentheses, *** p < 0.01, ** p < 0.05, * p < 0.1

This table reports the regression result from two-step System GMM for life expectancy. LE(1) only considered ODA, and GDPPC, LE(2) included other control variables like the prevalence of HIV, CO2 emission, and immunization. LE(3) included a dummy of SSA, to establish if life expectancy is significantly different between SSA and non-SSA countries. LE(4) included the interaction effect (GDPPC_SSA) to find out if the effect of GDPPC on life expectancy for SSA countries is significantly different from that of non-SSA countries. LE(5) included the interaction term (ODA_SSA) to find out if the effect of ODA on life expectancy rate for SSA countries is significantly different from that of non-SSA countries.

Source: Authors computation

Table 4. System GMM result based on under-5-mortality

VARIABLES	Model 1	Model 2	Model 3	Model 4	Model 5
L.U5MR	0.746***	0.651***	0.714***	0.728***	0.716***
	(0.0351)	(0.0429)	(0.0461)	(0.0473)	(0.0427)
ODA	0.0352***	0.0401***	0.0426***	0.0444***	−0.194**
	(0.0121)	(0.0101)	(0.00860)	(0.00862)	(0.0894)
GDPPC	−0.000444**	−0.000382**	−0.000374*	−0.000481*	−0.000684**
	(0.000222)	(0.000188)	(0.000213)	(0.000250)	(0.000282)
HIV		0.465***	0.744***	0.579***	0.781***
		(0.117)	(0.180)	(0.185)	(0.191)
CO2		−0.205	−0.634	−0.594	−0.835*
		(0.215)	(0.401)	(0.392)	(0.483)
IMM		−0.482***	−0.548***	−0.510***	−0.554***
		(0.0939)	(0.112)	(0.108)	(0.102)
SSA			−14.39***	−16.10***	−18.93***
			(3.790)	(4.911)	(5.094)
GDPPC_SSA				0.00185
				(0.00124)
ODA_SSA					0.246***
					(0.0929)
Constant	5.892**	51.75***	58.50***	54.66***	63.08***
	(2.595)	(10.71)	(12.93)	(12.37)	(12.63)
Observations	324	324	324	324	324
No. of CROSSID	81	81	81	81	81
firm effect	YES	YES	YES	YES	YES
year effect	NO	NO	NO	NO	NO
Hansen_test	15.63	12.81	7.128	8.076	8.045
Hansen Prob	0.00135	0.00507	0.0283	0.0176	0.0179
Sargan_test	70.79	45.08	8.858	11.42	8.375
Sargan Prob	0	8.88e-10	0.0119	0.00331	0.0152
AR(1)_test	−0.0342	−0.200	−0.309	−0.172	−0.754
AR(1)_P-value	0.973	0.841	0.757	0.864	0.451
AR(2)_test	−3.058	−2.405	−2.143	−2.164	−2.143
AR(2)_P-value	0.00223	0.0162	0.0321	0.0304	0.0321
No. of Instruments	7	10	10	11	11

Robust standard errors in parentheses, *** p < 0.01, ** p < 0.05, * p < 0.1

This table reports the regression result from two-step System GMM for under-5-mortality. Model 1 only considered the ODA, and GDPPC, Model 2 included other control variables like the prevalence of HIV, CO2 emission, and immunization. Model 3 included a dummy of SSA, to establish if the under-5-mortality rate in SSA is significantly different from non-SSA countries. Model 4 included the interaction effect (GDPPC_SSA) to find out if the effect of GDPPC on the under-5-mortality rate for SSA countries is significantly different from that of non-SSA countries. Model 5 included the interaction term (ODA_SSA) to find out if the effect of ODA on the under-5-mortality rate for SSA countries is significantly different from that of non-SSA countries.

Source: Authors computation

Table

Variable	Description	Source
ODA	Net official development assistance (ODA) per capita consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients; and is calculated by dividing net ODA received by the midyear population estimate. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent)	World Bank Database
GDP per capital (GDPPC)	GDP per capital (GDPPC) which represents income is considered to be very relevant to health outcome since a high level of income increases ability to pay for quality goods and services (quality medical services), provides access to quality housing, and better nutrition. “GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. Data are in current U.S. dollars	World Bank Database
Prevalence of HIV	“Prevalence of HIV refers to the percentage of people ages 15–49 who are infected with HIV”.	World Bank Database
Immunization	Child immunization, measles, measures the percentage of children ages 12–23 months who received the measles vaccination before 12 months or at any time before the survey. A child is considered adequately immunized against measles after receiving one dose of vaccine”.	World Bank Database
Under-5-mortality rate (U5MR)	Under-5-mortality rate (U5MR), is one of the proxies for health outcomes used in this study. It is “the number of death among infants before the ages of 5 years, per 1,000 live births, in a given year. We adopted this measure of health outcome because it is more susceptible to change given changes in our main variables and other socioeconomic variables under considerations”. The under-five mortality rate is the probability per 1,000 that a newborn baby will die before reaching age five, if subject to age-specific mortality rates of the specified year.	World Bank Database
CO2	Carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement. They include carbon dioxide produced during consumption of solid, liquid, and gas fuels and gas flaring”.	World Bank Database
Life expectancy at birth (LE)	Life expectancy at birth (LE) “indicates 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”.	World Bank Database

Table

List of Developing Countries understudy
Albania	Congo, Dem. Rep.	Jamaica	Pakistan
Algeria	Congo, Rep.	Kazakhstan	Panama
Argentina	Costa Rica	Kenya	Paraguay
Armenia	Cote d’Ivoire	Kyrgyz Republic	Peru
Azerbaijan	Cuba	Lebanon	Philippines
Bangladesh	Dominican Republic	Macedonia, FYR	Rwanda
Belize	Ecuador	Madagascar	Senegal
Benin	Egypt, Arab Rep.	Malawi	Sierra Leone
Bolivia	El Salvador	Malaysia	Sri Lanka
Botswana	Gabon	Mali	Sudan
Brazil	Georgia	Mauritania	Eswatini
Burkina Faso	Ghana	Mexico	Tajikistan
Burundi	Guatemala	Mongolia	Tanzania
Cambodia	Guinea	Morocco	Thailand
Cameroon	Guinea-Bissau	Mozambique	Togo
Central African Republic	Guyana	Namibia	Tunisia
Chad	Haiti	Nepal	Uganda
Chile	Honduras	Nicaragua	Uruguay
Colombia	India	Niger	Uzbekistan
Comoros	Iran, Islamic Rep.	Nigeria	Vietnam
			Zimbabwe

Table

	(1)	(2)	(3)	(4)	(5)
VARIABLES	SGMM1	SGMM2	SGMM3	SGMM4	SGMM5
L.LE	0.330**	0.365***	0.565***	0.554***	0.575***
	(0.152)	(0.127)	(0.0591)	(0.0602)	(0.0650)
ODA	−0.0275***	−0.0149***	−0.0113***	−0.0129***	0.0484**
	(0.0103)	(0.00471)	(0.00359)	(0.00479)	(0.0233)
GDPPC	0.000852***	0.000544***	0.000411***	0.000462***	0.000481***
	(0.000248)	(0.000144)	(9.06e-05)	(0.000114)	(0.000106)
HIV		−0.474***	−0.396***	−0.379***	−0.404***
		(0.0920)	(0.0684)	(0.0643)	(0.0746)
CO2		−0.0348	0.0682	0.0704	0.129
		(0.201)	(0.188)	(0.204)	(0.211)
IMM		0.173***	0.156***	0.158***	0.158***
		(0.0350)	(0.0237)	(0.0263)	(0.0242)
SSA			2.926**	3.454*	4.257**
			(1.417)	(1.870)	(1.763)
GDPPC_SSA				−0.000415
				(0.000372)
ODA_SSA					−0.0620**
					(0.0248)
Constant	42.93***	27.95***	15.37***	15.74***	13.42***
	(9.160)	(5.535)	(3.840)	(3.816)	(4.309)
Observations	324	324	324	324	324
Number of CROSSID	81	81	81	81	81
Hansen_test	4.843	4.165	4.475	4.213	3.236
Hansen Prob	0.184	0.244	0.107	0.122	0.198
AR(1)_test	2.312	1.642	2.098	2.178	2.184
AR(1)_P-value	0.0208	0.101	0.0359	0.0294	0.0289
AR(2)_test	0.159	−0.896	−1.539	−1.575	−2.025
AR(2)_P-value	0.874	0.370	0.124	0.115	0.0429
No. of Instruments	7	10	10	11	11

Robust standard errors in parentheses

*** p < 0.01, ** p < 0.05, * p < 0.1

SGMM1 to SGMM5 denote One-Step system GMM model1 to model5.

One Step System GMM for Under-5-Morterlity rate

Table

	(1)	(2)	(3)	(4)	(5)
VARIABLES	SGMM1	SGMM2	SGMM3	SGMM4	SGMM5
L.U5MR	0.783***	0.679***	0.679***	0.686***	0.701***
	(0.0446)	(0.0585)	(0.0537)	(0.0560)	(0.0504)
ODA	0.0431***	0.0495***	0.0484***	0.0481***	−0.169*
	(0.0136)	(0.0111)	(0.00849)	(0.00870)	(0.0984)
GDPPC	−0.000135	−0.000182	−0.000401	−0.000402	−0.000620*
	(0.000226)	(0.000241)	(0.000263)	(0.000299)	(0.000331)
HIV		0.358*	0.877***	0.789***	0.880***
		(0.182)	(0.244)	(0.242)	(0.285)
CO2		−0.239	−0.589	−0.478	−0.732
		(0.203)	(0.409)	(0.372)	(0.495)
IMM		−0.429***	−0.614***	−0.575***	−0.573***
		(0.127)	(0.141)	(0.138)	(0.125)
SSA			−12.71***	−12.02**	−16.53***
			(4.460)	(5.330)	(5.822)
GDPPC_SSA				0.000864
				(0.00125)
ODA_SSA					0.217**
					(0.102)
Constant	2.090	44.95***	65.43***	60.89***	64.18***
	(2.678)	(14.56)	(16.32)	(15.85)	(15.53)
Observations	324	324	324	324	324
Number of CROSSID	81	81	81	81	81
Hansen_test	15.63	12.81	7.128	8.076	8.045
Hansen Prob	0.00135	0.00507	0.0283	0.0176	0.0179
Sargan_test	70.79	45.08	8.858	11.42	8.375
Sargan Prob	0	8.88e-10	0.0119	0.00331	0.0152
AR(1)_test	−0.155	−0.248	−0.334	−0.282	−0.724
AR(1)_P-value	0.877	0.804	0.738	0.778	0.469
AR(2)_test	−2.668	−2.140	−2.136	−2.114	−2.092
AR(2)_P-value	0.00763	0.0324	0.0326	0.0345	0.0364
No. of Instruments	7	10	10	11	11

Standard errors in parentheses

*** p < 0.01, ** p < 0.05, * p < 0.1

SGMM1 to SGMM5 denote One-Step system GMM model1 to model5.