Eur J Health Econ DOI 10.1007/s10198-015-0697-6

ORIGINAL PAPER

Effects of food price inflation on infant and child mortality in developing countries Hyun-Hoon Lee1 • Suejin A. Lee2 • Jae-Young Lim3 • Cyn-Young Park4

Received: 26 January 2015 / Accepted: 11 May 2015  Springer-Verlag Berlin Heidelberg 2015

Abstract Background After a historic low level in the early 2000s, global food prices surged upwards to bring about the global food crisis of 2008. High and increasing food prices can generate an immediate threat to the security of a household’s food supply, thereby undermining population health. This paper aims to assess the precise effects of food price inflation on child health in developing countries. Methods This paper employs a panel dataset covering 95 developing countries for the period 2001–2011 to make a comprehensive assessment of the effects of food price inflation on child health as measured in terms of infant mortality rate and child mortality rate. Results Focusing on any departure of health indicators from their respective trends, we find that rising food prices

& Jae-Young Lim [email protected]

have a significant detrimental effect on nourishment and consequently lead to higher levels of both infant and child mortality in developing countries, and especially in least developed countries (LDCs). Discussion High food price inflation rates are also found to cause an increase in undernourishment only in LDCs and thus leading to an increase in infant and child mortality in these poorest countries. This result is consistent with the observation that, in lower-income countries, food has a higher share in household expenditures and LDCs are likely to be net food importing countries. Conclusions Hence, there should be increased efforts by both LDC governments and the international community to alleviate the detrimental link between food price inflation and undernourishment and also the link between undernourishment and infant mortality. Keywords Food prices  Infant mortality  Child mortality  Undernourishment  Food security JEL Classification

I15  I18  I19  Q18

Hyun-Hoon Lee [email protected] Suejin A. Lee [email protected]

Introduction

Cyn-Young Park [email protected]

From the early 1970s, prices of food commodities traded in the global market declined substantially, to reach a historic low level in the early 2000s [1]. After this period, however, global food prices began to increase gradually, and from 2006 they surged upwards to bring about the global food crisis of 2008. Following a brief decline from the second half of 2008 to the first half of 2009, global food prices again began to increase rapidly so as to surpass the 2008 level in August 2012 (see Fig. 1).

1

Department of International Trade and Business, Kangwon National University, Chuncheon 200-701, Republic of Korea

2

Field of Economics, Cornell University, Ithaca, NY 14853, USA

3

Department of Food and Resource Economics, Korea University, Seoul 136-701, Republic of Korea

4

Economics and Research Department, Asian Development Bank, Mandaluyong 1550, The Philippines

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H.-H. Lee et al. 80.0

300.0 Food Price Index (Le Scale)

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-40.0 1/2001 4/2001 7/2001 10/2001 1/2002 4/2002 7/2002 10/2002 1/2003 4/2003 7/2003 10/2003 1/2004 4/2004 7/2004 10/2004 1/2005 4/2005 7/2005 10/2005 1/2006 4/2006 7/2006 10/2006 1/2007 4/2007 7/2007 10/2007 1/2008 4/2008 7/2008 10/2008 1/2009 4/2009 7/2009 10/2009 1/2010 4/2010 7/2010 10/2010 1/2011 4/2011 7/2011 10/2011 1/2012 4/2012 7/2012 10/2012 1/2013 4/2013 7/2013 10/2013 1/2014

Fig. 1 Trend of food price index and inflation rates. Source: authors’ calculations using statistics division of the FAO (FAOSTAT) database

The sudden increases of global food commodity prices were transmitted to national food price inflation.1 The high prices of food commodities in the global market and the consequent increases in national food prices led to increased concern over global food security because high and increasing food prices may result in an increased probability of starvation and reduced household consumption of nutritious foods; such a situation can both undermine population health and increase mortality. Some studies have examined the impact of the recent global food crisis in combination with the global financial crisis on nutrition and health status [2–4]. Brinkman et al. [2] assess the potential effect of high food prices combined with the global financial crisis on food consumption, nutrition, and health by examining various transmission channels. They show that a food consumption score, a measure of diet frequency and diversity, was negatively correlated with food prices in Haiti, Nepal, and Niger, and argue that a large number of vulnerable households in developing countries reduced the quality and quantity of food consumption and faced a risk of malnutrition as a result of high food prices and the global financial crisis. Drawing on experience from previous crises, Christian [3] identifies and elaborates upon a number of nutritional channels by which the recent economic crisis and accompanying increases in food prices may affect infant and child mortality. Darnton-Hill and Cogill [4] also review past food price shocks and their known impact on nutrition and

emphasize that these shocks initially compromise maternal and child nutrition, mainly through a reduction in dietary quality and an increase in micronutrient deficiencies as well as concomitant increases in infectious disease morbidity and mortality.2 Brinkman et al. [2] warn that high and increasing food prices run the risk of undoing much of the progress made toward achieving Millennium Development Goals (MDGs),3 which call for a reduction in under-5 child mortality (and infant mortality) by two-thirds between 1990 and 2015 (Goal 4). As agricultural commodity prices in real terms are likely to remain on a higher plateau during the next decade compared to the previous decade [7], understanding the effect of food price inflation on child and infant mortality is critical for the development of public policies and social programs to help the vulnerable countries and groups. In particular, an accurate assessment is needed to help target the assistance, monitor the progress, and evaluate the effect of such policies and programs. To the best of our knowledge, this is the first study that attempts to assess the precise effects of food price inflation on child health in developing countries. We undertake a systematic regression analysis by employing a comprehensive panel dataset comprising infant (and child) mortality rate, food price inflation, and other control variables for 95 developing countries during the period 2001–2011.4 Specifically, we assess the effects of food price inflation on 2

1

Using panel data for 72 developing countries from 2000 to 2011, Lee and Park [5] found that domestic food price inflation in developing countries was strongly associated with the 1-year-lagged value of global food price inflation (measured using the FAO food price index). Durevall et al. [6] also found that world food prices determined the long-run evolution of domestic food prices in Ethiopia, particularly during the global food crisis.

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Bloem et al. [8] summarize a series of papers that explore the relationships between crises and their cumulative impact among vulnerable populations, particularly through hidden hunger. 3 Millennium Development Goals (MDGs) are eight international development goals with specific targets and means of measurement that were officially established following the Millennium Summit of the United Nations in 2000. 4 Ninety-five countries are chosen on the basis of data availability.

Effects of food price inflation…

the short-term fluctuations of infant and child mortality rates around their long-term trends. Thus, in contrast to the literature on the long-term determinants of child health,5 this paper is in line with the literature investigating shortterm fluctuations of infant and child mortality rates.6 The remainder of this paper is organized as follows. The ‘‘Background’’ section offers a brief overview of trends of child health and national food price inflation rates during the period 2001–2011. The ‘‘Methods’’ section is an empirical model to assess the effects of food price inflation on health conditions, specifically infant mortality and child mortality. ‘‘Results’’ presents empirical results and ‘‘Discussion’’ provides explanations for our findings. Finally, the ‘‘Conclusions’’ section concludes the paper with a summary of empirical findings and a discussion on policy implications.

Background Infant and child mortality in developing countries MDG 4 aims at reducing child mortality rates (CMR) and infant mortality rates (IMR) by two-thirds between 1990 and 2015. IMR is the number of deaths of children\1 year of age per 1000 live births and CMR is the number of deaths of children before their fifth birthday per 1000 live births. IMR has been criticized as a measure of population health because it is narrowly based and is often constructed using projections and/or interpolations [24].7 Criticism has also been raised that IMR can be underestimated, depending on a particular country’s live birth criterion, vital registration system, and reporting practices [25]. Despite the contentious issues related to the measurement of IMR and CMR, we still use these as measures of child health because (1) data on infant mortality are available for a large number of countries and are more reliable than other indicators such as life mortality; (2) infant mortality is

5 For example, see Preston [9, 10]; Evans [11]; Houweling et al. [12]; Cutler et al. [13]; Lazarova [14]; Moore et al. [15]; Shell et al. [16]; Sores [17]; Mishra and Newhouse [18]; Kaufmann et al. [19]; Muldoon et al. [20]; and Pamuk, et al [21]. The main findings of these papers are utilized in our choice of control variables in ‘‘Methods’’. 6 For example, see Gerdtham and Ruhm [22] on the short-term effects of changes in unemployment on short-term changes in infant mortality. See also Baird et al. [23] on the effects of short-term fluctuations in aggregate income on short-term changes in infant mortality. 7 More comprehensive measures such as disability-adjusted life expectancy (DALE) have been suggested as alternatives. However, these more comprehensive measures of population health are harder to measure precisely and are, in fact, highly correlated with infant mortality rate [26].

more sensitive than life expectancy to changes in economic conditions [18]. This paper focuses on the period from 2001 to 2011, during which the world experienced rapidly increasing food commodity prices after a historic low level, as seen in Fig. 1. During this period, both mortality rates decreased in LDCs8 and other developing countries included in our sample, as seen in Fig. 2, although they still remained at substantially high levels, particularly in LDCs.9 Specifically, IMR (CMR) of LDCs in our sample decreased from 83.8 (136.5) in 2001 to 57.9 (86.5) in 2011, while the corresponding figures for other developing countries decreased from 32.2 (42.6) to 21.0 (28.2). Among the individual countries included in the sample, Sierra Leone (140.9), Angola (119.8), Mali (113.1), Nigeria (109.3), Central African Republic (108.0), and Mozambique (106.9) are the six countries that reported the greatest figures for IMR in 2001. In 2011, Sierra Leone (120.1), Angola (102.2), Central African Republic (92.8), Chad (91.3), and Mali (81.4) were the top five countries in terms of IMR. The Appendix Table 6 lists all of the developing countries in our sample together with their annualized reduction rates of IMR for the period 2001–2011. It is well known that long-term reduction in mortality has been driven mainly by improvements in nutrition, education, particularly female education, and social infrastructure such as water and sanitation, as well as medical technology [10, 13]. We are more interested in short-term fluctuations of infant and child mortality rates and their possible association with food price inflation. Figure 3 shows the yearly rates of change in infant and child mortality. It is interesting to note that while the annual reduction rates of infant and child mortality of other developing countries were gradually decreasing, the annual reduction rates for LDCs were increasing until 2007 and then they decreased until 2010 (IMR) or 2011 (CMR). It is not convincing to argue that the slowdown of reduction in infant and child mortality in LDCs in the late 2000s was due to a deceleration of improvement of medical technology, as the trend of the reduction rate of mortality in 8

Least developed countries are the countries recognized by the United Nations using the following three criteria: income, human resources (indicators of nutrition, health, school enrolment, and literacy), and economic vulnerability ((indicators of natural and traderelated shocks, physical and economic exposure to shocks, and smallness and remoteness). (http://unctad.org/en/Pages/ALDC/ Least%20Developed%20Countries/UN-list-of-Least-DevelopedCountries.aspx). Following the practice of the United Nations, this paper uses LDCs as the acronym for least developed countries. In our sample, there are 30 LDCs and 65 other developing countries determined by the United Nations as of 2011. 9 Infant and child mortality rates are taken from the United Nations MDGs Indicators Database (http://mdgs.un.org/unsd/mdg/default. aspx).

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H.-H. Lee et al. Fig. 2 Trend of infant and child mortality rates for LDCs and other developing countries. Source: authors’ calculations using United Nations MDGs indicators database

160 IMR, LDCs

IMR, non-LDCs

CMR, LDCs

CMR, non-LDCs

140 120 100 80 60 40 20 0

Fig. 3 Trend of annual reduction rates of infant and child mortality rates for LDCs and other developing countries. Source: authors’ calculations using United Nations MDGs indicators database

2001

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-3 -3.5 -4 -4.5 -5 -5.5 -6

other developing countries does not appear to show a similar pattern during the same period. Rather, this slowdown may be largely due to the global food price hikes in the late 2000s, as shown in Fig. 1. This paper aims to provide empirical evidence in support of this supposition. Food prices As surveyed in the introductory section, one of the critical factors influencing food security comprises high and rising food prices because they increase hunger, malnutrition, and mortality among infants and children of poor families. Many studies such as FAO [27] and ADB [28] show that high food prices have indeed increased world hunger and in particular hit hardest many poor households in poor countries. This paper aims to assess the extent to which food price inflation impacted infant and child mortality in 95

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developing countries during the period 2001–2011. Annual food price inflation is calculated as the annual growth rate of the domestic food Consumer Price Index (CPI) for each developing country, and the data for this are drawn from the FAO (FAOSTAT; http://faostat.fao.org/).10 The baseline year of food CPI is the year 2000 for most of the countries, but some countries report different baseline years.11 Figure 4 illustrates the trend of the calculated annual food price inflation rates for LDCs and other developing 10

It should be noted that most countries report food CPI at the national level, but some countries report food CPI only for urban households (22 countries in our sample). As a robustness check, we also conducted our empirical analysis after dropping the nations which report only urban food CPI, and found similar results. 11 Because food price inflation rates are calculated using the growth rate of the indices, different base years do not generate any problem in our analysis.

Effects of food price inflation… Fig. 4 Trend of food price inflation rates in LDCs and other developing countries. Source: authors’ calculations using statistics division of the FAO (FAOSTAT) database

20 LDCs

Non-LDCs

18 16 14 12 10 8 6 4 2 0 2001

2002

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2011

countries in our sample. Inflation rates remained relatively stable within the range from 6 to 12 % until the mid-2000s. Following this, their trend shows an increase in 2007–2008 and then a decrease in 2009 before rising again in 2010. Thus, the national food price inflation rates reflect the hikes of global food commodity prices in the late 2000s. It is also noted that food price inflation is generally higher in LDCs than in other developing countries. One interesting observation is that the rise of national food prices in the late 2000s appears in parallel with the slowdown of reduction in infant and child mortality rates for LDCs, as noted above. The next section presents an empirical model that can capture the effects of food price inflation on infant and child mortality rates in developing countries.

inflation rate is stationary. That is, it stays around a given rate, tending back to that rate when it is either higher or lower. As seen in the previous section, both infant and child mortality rates show very persistent decreasing trends throughout the period 2001–2011. If these indices are not stationary, the partial correlation between either one of these indices and the food price inflation rate can be spurious. Infant and child mortality rates, however, are likely to follow a stationary process because logically they must hit a lower bound of zero at some point. Younger [29] shows that the formal tests reject the null of a unit root in IMR or its log. Therefore, in a similar way to Gerdtham and Ruhm [22], as a benchmark specification we use the log of IMR (or CMR) as a dependent variable and run regressions as a function of food price inflation and other policy variables as well as country-specific time trends:

Methods

MRit ¼ b0 þ b1 FPit þ b02 CVit þ c0i fi ðtÞ þ ht þ eit

Model specification

where MRit is the log of IMR (or CMR) in country i and in year t. FP is annual food price inflation rate and CV is a vector of control variables,12 while year fixed effects ht control for global changes in the same year and eit is a mean-zero error term. Given that our focus is on highfrequency changes in infant and child mortality (in terms of any departure of mortality rates from trends), we include a vector of country-specific time trends, fi(t), to allow for the possibility that factors such as improvements in nutrition and education as well as the adoption of medical

In order to empirically assess the effects of food price inflation on child health, we construct a panel dataset covering 95 developing countries with observations over a period of 11 years from 2001 to 2011. One point to note is that we want to estimate short-run fluctuations of child health that are driven by food price inflation, not long-run structural determinants of child health; thus, we will detrend the series of infant and child mortality rates in a variety of ways. In our analysis, IMR will be used as the main dependent variable and then, as a robustness check, it will be replaced with the CMR rate as both are included in Goal 4 of the MDGs. It seems logical to assume that the food price

ð1Þ

12

We also attempted to control for time-invariant differences among regions and found similar results. Regions are East Asia and Pacific, South Asia, Sub-Saharan Africa, Middle East and North Africa, Latin America and Caribbean, and Europe and Central Asia. The list of countries within each region is presented in the Appendix Table 2.

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technology over time vary across countries [10, 13].13 We report the results with three different specifications of country-specific time trends: linear, quadratic, and cubic. Although the benchmark specification is less likely to suffer from a risk of spurious regression in the sense of Granger and Newbold [30] because both infant (child) mortality rate and food price inflation are stationary, there is still a risk that including country-specific time trends in a regression does not allow for different time trends for different variables. This point seems important because while food price inflation rates are stationary, all control variables are also very persistent over time, as will be discussed in the next sub-section. Therefore, as a second specification, we conduct two-stage regressions. In the first stage, we obtain the short-term fluctuations of infant and child mortality rates around their long-term trends, which are the residuals from regressing the log of infant (child) mortality rate on a flexible formulation of country-specific deterministic trends:14 MRit ¼ c0i fi ðtÞ þ ht þ eit :

ð3Þ

In both equations, a linear, quadratic, or cubic countryspecific time trend was used. It should be noted that food price inflation rates are not de-trended because they are stationary, as noted above.15 In the second stage, the de-trended component of infant (child) mortality is regressed on food price inflation rates and other de-trended control variables as follows: 0

MRit ¼ b0 þ b1 FPit þ b2 CVit þ ht þ eit :

The main objective of this paper is to capture the effects of food price inflation on child health in developing countries, but there is no doubt that various other factors also influence health conditions in those countries. Therefore, the regression analysis also includes various control variables that may affect infant mortality and child mortality. In this sub-section, we explain our control variables included in Eqs. (1) and (4). 1.

ð2Þ

We also obtain the residuals from regressing countryspecific time trends on each control variable: CVit ¼ c0i fi ðtÞ þ ht þ eit :

Control variables

2.

3.

ð4Þ

where MR*it is the de-trended component of IMR or CMR and CV* is a vector of de-trended control variables. Thus, we estimate the effects of food price inflation on the fluctuations of infant and child mortality rates around their long-term trends.16 13

See also Jamison et al. [31] who show that differing rates of technical progress are the principal source of the cross-country variation in reduction rate of infant mortality rate. 14 This specification is also used by Baird et al. [23] in their study on the effects of short-term fluctuations in aggregate income on shortterm changes in infant mortality. 15 Thus, we assume that not only the dependent variable but also all of our control variables do not follow a random walk or are integrated of order 1. 16 It also seems reasonable to say that not only high inflation rates of food prices but also high food price levels affect infant and child mortality. Because we are concerned with fluctuations of infant and child mortality rates around their long-term trends, we only use food price inflation rates (i.e., changes in price levels). Besides, food price levels are not comparable across countries because different countries use different base years in calculating commodity price indices.

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4.

17

Log of per capita GDP, PPP (constant 2005 international $): This is to capture the effects of short-term fluctuations in aggregate income on short-term fluctuations of infant and child mortality rates. Studies such as Baird et al. [23] find that economic downturns in terms of per capita GDP are associated with increases in infant mortality. Lower income due to economic downturns should translate into lower expenditure on food and health at household level [32].17 Source: World Bank, World Development Indicators (WDI). Log of per capita government expenditure on health, PPP (constant 2005 international $): This variable is to capture short-term effects of fluctuations in government health expenditure on child health. The argument for the role of public health is examined by many studies [9–13, 16, 20]. Source: World Health Organization, Global Health Observatory Database. Log of proportion of the population using an improved sanitation facility: This variable is included as a control variable because the provision of sanitation is seen as an essential complement to the availability of food in preventing child malnutrition. Even if the food supply for children is sufficient, diarrhea hampers the intake of calories and micro-nutrients and thereby prevents adequate nutritional outcomes and increases the likelihood of mortality [16, 20]. Source: United Nations, Millennium Development Goals Indicators Database. Political stability and absence of violence/terrorism: This variable is included also as a control variable because political instability or violence may incur human casualties including children [15]. Political instability may also hinder both international and

From the longer-term perspective, the role of economic development in health improvement in developing countries has been controversial. Although income brings so many things—better nutrition, better housing, the ability to pay for health care, as well as the means for the public provision of clean water and sanitation, cross-country evidence does not suggest that economic development will improve health without deliberate public action [13, 33]. There have also been studies investigating the impact of decline in child mortality on economic growth [34].

Effects of food price inflation…

5.

6.

government assistance in maternal and infant health. This is an index for governance performance, which reflects the perceptions of the likelihood that the government will be destabilized or overthrown by unconstitutional or violent means, including politically-motivated violence and terrorism. This index ranges from -2.5 (weak governance) to 2.5 (strong governance). Source: World Bank, Worldwide Governance Indicators (http://data.worldbank.org/data-catalog/world wide-governance-indicators). Government effectiveness: this is also an index for governance performance, which reflects perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government’s commitment to such policies. We include this index as a control variable because many studies suggest that government effectiveness promotes child health conditions in developing countries [14, 19]. This index ranges from -2.5 (weak governance) to 2.5 (strong governance). Source: World Bank, Worldwide Governance Indicators (http://data.worldbank.org/datacatalog/worldwide-governance-indicators). Log of youth population, age 0–14 (% of total). This variable is included as a control variable because a high share of youth population in total population is expected to result in a smaller amount of assistance for infant health per infant.18 Source: World Bank, World Development Indicators (WDI).

Variables on female/male education and economic inequality have also been suggested as determinants of child health in the literature [13, 16, 35]. However, these variables are excluded from the regression because annual data for these variables are not available for developing countries.19

Results We report not only the results for all of the developing countries included in our analysis but also the results estimated separately for LDCs and other developing countries, so as to assess whether and to what extent the impact of food prices on child health may be more severe in LDCs, 18 Following Muldoon et al. [20] and Mishra and Newhouse [18], we also used fertility rate as an alternative and found similar results. 19 We also initially included, as control variables, cereal import dependency ratio, percent of arable land equipped for irrigation, value of food imports in total merchandise exports, and natural disasters. However, these variables did not show any significant results and inclusion of these variables did not have any significant effect on the results for our key variables.

as many studies reveal that the poorest countries were most severely affected during the recent world food crisis [1, 36]. Table 1 reports the estimated results for a benchmark equation, which includes country-specific time trends, which are assumed to be linear, quadratic, or cubic. Regardless of the type of country-specific time trend applied, food price inflation rates carry positive and significant coefficients in the equations for all developing countries. When we split the sample into LDCs and other developing countries, however, food price inflation rates are significant only in the equations for LDCs, regardless of the type of country-specific time trend. Specifically, according to the results in columns four and five, a 10-percentage-point increase in food price inflation rate in a particular year results in an increase of IMR by 2.3 % in the same year, ceteris paribus. That is, a 10-percentage-point-higher food price inflation rate in 2001 would have resulted in an increase of 1.48 infant deaths per 1000 live births.20 It should also be noted that per-capita GDP is negatively associated with infant mortality in LDCs but not in other developing countries. Thus, during economic downturns and high food price inflation, child health is likely to be hit hardest in LDCs. The results obtained when applying all specifications also reveal that a greater amount of government health expenditure per capita appears to decrease infant mortality in developing countries (particularly in other developing countries). Infant mortality in other developing countries also appears to decrease with improved sanitation facilities. In contrast, our benchmark specification appears to reveal only a limited role for political stability and government effectiveness in decreasing infant mortality. Lastly, infant mortality both in LDCs and in other developing countries appears to increase with a greater share of youth population. As noted in the previous section, our benchmark results are free from the risk of spurious regression, but the inclusion of country-specific time trends in the regression equation does not allow for different time trends applicable to different variables. Therefore, we report the results with a specification using two-stage regressions (our preferred specification). In the first stage, we remove the countryspecific trends by regressing log of IMR (and all explanatory variables except food price inflation rates) on a flexible formulation of time trends; in the second stage, we regress the de-trended component of infant mortality on food price inflation rates and other de-trended control variables. The estimated results are summarized in Table 2.

20

1.48 is obtained by multiplying 0.023 by 64.55, which is the average IMR of LDCs in the period 2006–2010, during which the world witnessed food price hikes.

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123 -0.162 (0.105) -0.137* (0.076) -0.309*** (0.078) -0.039 (0.040) -0.060 (0.097) 0.669*** (0.184) 4.272*** (1.004) 909 0.959

Log of GDP per capita, PPP

Log of government health expenditure per capita

Log of improved sanitation facilities

Political stability and absence of violence

Government effectiveness

Log of youth population share

Constant

Number of observations

R2

0.987

909

3.843*** (1.099)

0.745*** (0.207)

0.014 (0.074)

-0.055* (0.031)

-0.299*** (0.084)

-0.132** (0.066)

-0.174 (0.111)

0.0025** (0.0011)

0.995

909

3.703*** (1.215)

0.790*** (0.221)

-0.039 (0.066)

-0.032 (0.028)

-0.266*** (0.089)

-0.098* (0.058)

-0.203* (0.113)

0.0015* (0.0008)

0.924

297

0.873 (2.174)

1.413*** (0.492)

-0.183** (0.086)

-0.016 (0.044)

-0.136 (0.087)

0.006 (0.064)

-0.224* (0.116)

0.0023* (0.0013)

0.974

297

1.413 (2.029)

1.362*** (0.463)

-0.039 (0.055)

-0.051 (0.044)

-0.152 (0.104)

-0.013 (0.051)

-0.247** (0.112)

0.0023** (0.0009)

Quadratic (5)

0.990

297

0.819 (2.184)

1.439*** (0.515)

-0.085 (0.058)

-0.038 (0.040)

-0.122 (0.104)

0.013 (0.041)

-0.252** (0.122)

0.0017*** (0.0007)

Cubic (6)

0.937

612

4.718*** (1.401)

0.467** (0.186)

-0.059 (0.127)

-0.055 (0.054)

-0.539*** (0.155)

-0.200** (0.091)

0.019 (0.139)

0.0015 (0.0018)

Linear (7)

Non-LDCs

0.980

612

4.837*** (1.540)

0.564*** (0.216)

-0.006 (0.106)

-0.048 (0.044)

-0.475*** (0.169)

-0.203** (0.086)

-0.000 (0.151)

0.0012 (0.0013)

Quadratic (8)

0.993

612

4.143*** (1.590)

0.581*** (0.223)

-0.062 (0.080)

-0.014 (0.036)

-0.465** (0.181)

-0.178** (0.071)

-0.032 (0.146)

0.0006 (0.0010)

Cubic (9)

All regression equations include linear, quadratic, and cubic country-specific time trend, respectively. Country-clustered standard errors are in parenthesis. Year dummies are included but not shown for the sake of brevity. *** p \ 0.01, ** p \ 0.05, * p \ 0.1

0.0034** (0.0017)

Food inflation rate

Linear (4)

Cubic (3)

Linear (1)

Quadratic (2)

LDCs

All developing countries

Dependent variable: log of infant mortality rate

Table 1 Effects of food price inflation on infant mortality: a benchmark specification

H.-H. Lee et al.

-0.181** (0.091) -0.118* (0.067) -0.292*** (0.070) -0.030 (0.039) -0.102 (0.094) 0.682*** (0.182) 0.071 (0.054) 909 0.846

Log of GDP per capita, PPP

Log of government health expenditure per capita

Log of improved sanitation facilities

Political stability and absence of violence

Government effectiveness

Log of youth population share

Constant

Number of observations

R2

0.867

909

0.080** (0.039)

0.803*** (0.189)

-0.000 (0.066)

-0.056** (0.028)

-0.261*** (0.068)

-0.250*** (0.080)

-0.091* (0.048)

0.0016** (0.0007)

0.862

909

0.048* (0.027)

0.868*** (0.186)

-0.037 (0.053)

-0.038* (0.023)

-0.215*** (0.064)

-0.290*** (0.070)

-0.062* (0.035)

0.0011*** (0.0003)

0.953

297

0.068 (0.333)

1.431*** (0.473)

-0.202** (0.080)

-0.013 (0.041)

-0.130 (0.079)

0.015 (0.057)

-0.229** (0.114)

0.0017 0.0012)

0.967

297

0.092 (0.238)

1.362*** (0.430)

-0.059 (0.052)

-0.053 (0.038)

-0.147* (0.089)

-0.249** (0.108)

-0.005 (0.038)

0.0016*** (0.0005)

Quadratic (5)

0.962

297

0.077 (0.176)

1.399*** (0.445)

-0.089* (0.051)

-0.040 (0.034)

-0.117 (0.082)

-0.260** (0.118)

0.019 (0.027)

0.0009*** (0.0002)

Cubic (6)

0.695

612

0.118* (0.064)

0.497*** (0.186)

-0.103 (0.123)

-0.044 (0.052)

-0.526*** (0.146)

-0.188** (0.082)

-0.005 (0.126)

0.0018 (0.0015)

Linear (7)

Non-LDCs

0.705

612

0.113** (0.048)

0.629*** (0.198)

-0.004 (0.094)

-0.055 (0.039)

-0.440*** (0.146)

-0.087 (0.119)

-0.167** (0.068)

0.0008 (0.0009)

Quadratic (8)

0.701

612

0.067** (0.031)

0.696*** (0.192)

-0.046 (0.066)

-0.023 (0.029)

-0.396*** (0.142)

-0.158 (0.098)

-0.131*** (0.051)

0.0008 (0.0005)

Cubic (9)

Except for food price inflation rate, all dependent and explanatory variables are de-trended in the first stage, using linear, quadratic, and cubic country-specific time trend, respectively. Countryclustered standard errors are in parenthesis. Year dummies are included but not shown for the sake of brevity. *** p \ 0.01, ** p \ 0.05, * p \ 0.1

0.0030** (0.0014)

Food inflation rate

Linear (4)

Cubic (3)

Linear (1)

Quadratic (2)

LDCs

All developing countries

Dependent variable: log of infant mortality rate

Table 2 Effects of food price inflation on infant mortality—second stage estimation using de-trended variables

Effects of food price inflation…

123

H.-H. Lee et al.

In a similar way to the results obtained from the first specification, food price inflation rate is positively and significantly associated (at the 1 % level in both quadratic and cubic de-trended specifications) with the de-trended component of IMR in LDCs. Specifically, according to the results obtained on using a de-trended measure with a quadratic time trend as reported in column five, a 10-percentage-point increase in food price inflation rate in a particular year results in an increase of IMR by 1.6 % in the same year. That is, a 10-percentage-point higher food price inflation rate in 2001 would have resulted in an increase of 1.03 infant deaths per 1000 live births.21 This is smaller than the figure that we obtained from the benchmark specification but is nevertheless relatively large, since the average number of live births per year in LDCs was 27.8 million during the period 2006–2010.22 The estimated effect of a 10-percentage-point increase of food prices in LDCs translates to 28,608 more infant deaths per year in LDCs. Thus, we present strong empirical evidence that rising food prices have a serious detrimental impact on infant health in LDCs and thus supports the findings of many previous studies [1, 36], revealing that the poorest countries were most severely affected during the recent world food crisis. This result is consistent with the observation that, in lower-income countries, food accounts for a higher share of household expenditures. Besides, LDCs are likely to be net food importing countries. For example, Valde´s [37] report that during 2005–2009, all of the 35 low-income countries were net food importing, while of 51 lowmiddle income countries, 37 countries were net food importing and 14 countries were net food exporting. Hence, there should be increased efforts by both LDC governments and the international community to alleviate the detrimental link between food price inflation and infant mortality. Economic downturns also appear to increase infant mortality in most of the developing world (LDCs in a linear de-trended specification and other developing countries in both quadratic and cubic de-trended specifications). This finding is consistent with Baird et al. [23], who also found that infant mortality increases during periods of economic downturn in developing countries because economic downturns may result in reduced household consumption of nutritious foods. The results for food price inflation and per-capita GDP suggest that the global economic and food crises of the late 21

1.03 is obtained by multiplying 0.016 by 64.55, which is the average IMR of LDCs in 2006-2010, during which period the world witnessed food price hikes. 22 United Nations Population Division, World Population Prospects: The 2012 Revision, United Nations.

123

2000s would have had a serious detrimental impact on the health condition of infants (and, more generally, the entire population) in developing countries, and in particular the poorest countries. Thus, policies that protect the health status of infants in developing countries may become especially important during periods of concurrent economic downturn and high food price inflation. Our results also show that infant mortality in both LDCs and other developing countries may decrease with increased government health expenditure and improved sanitation facilities. Thus, governments’ strong commitment to public health as evidenced by increasing health expenditure and improving sanitation facilities is crucial in improving child health in developing countries. Once again, the results obtained on applying all of the specifications reveal that infant mortality in both LDCs and other developing countries increases with a greater share of youth population. This suggests that an increase in the share of youth population in total population increases infant mortality rates because with a greater share of youth population each infant on average is expected to receive a smaller amount of health assistance. In contrast, political stability and government effectiveness appear to contribute only to a limited extent to a reduction in infant mortality in both LDCs and other developing countries. It should be noted, however, that by de-trending IMR and other control variables, we are trying to capture the effects of food price inflation and other control variables on short-term fluctuations of IMR around their long-term trends. Therefore, our results do not necessarily suggest that political stability and government effectiveness do not contribute to lower IMRs in developing countries in the long run. CMR is equally important in monitoring child health conditions in developing countries. Therefore, we re-estimated the figures by applying all of the specifications after replacing IMR with CMR as the dependent variable. The results obtained by the two-stage regressions, constituting our preferred specification, are reported in Table 3. These results are very similar to those outlined above: child mortality is also detrimentally influenced by food price inflation, especially in LDCs. Also, economic downturns appear to increase child mortality in LDCs.

Discussion As noted in the introductory section, the adverse effect of high and rising food prices on infant and child mortality can be realized through malnutrition and under-nutrition [38–40]. Having reviewed the impact of past food price shocks on nutrition, Darnton-Hill and Cogill [4] conclude that the shocks initially compromise maternal and child nutrition, mainly through a reduction in dietary quality and

Effects of food price inflation… Table 3 Effects of food price inflation on child mortality—second stage estimation using de-trended variables Dependent variable: log of child mortality rate LDCs

Non-LDCs

Linear (1)

Quadratic (2)

Cubic (3)

Linear (4)

Quadratic (5)

Cubic (6)

Food inflation rate

0.0015 (0.0014)

0.0018*** (0.0006)

0.0011*** (0.0002)

0.0023 (0.0017)

0.0011 (0.0010)

0.0010* (0.0006)

Log of GDP per capita, PPP

-0.244* (0.126)

-0.253** (0.117)

-0.287** (0.129)

-0.006 (0.138)

-0.092 (0.133)

-0.166 (0.112)

Log of government health expenditure per capita

-0.022 (0.067)

-0.039 (0.047)

0.017 (0.035)

-0.184** (0.089)

-0.168** (0.072)

-0.137** (0.054)

Log of improved sanitation facilities

-0.137 (0.096)

-0.168 (0.105)

-0.142 (0.096)

-0.703*** (0.174)

-0.595*** (0.172)

-0.539*** (0.164)

Political stability and absence of violence

0.032 (0.047)

-0.023 (0.045)

-0.016 (0.039)

-0.040 (0.057)

-0.056 (0.041)

-0.026 (0.031)

Government effectiveness

-0.227** (0.099)

-0.073 (0.062)

-0.134** (0.068)

-0.109 (0.129)

0.005 (0.099)

-0.040 (0.069)

Log of youth population share

2.899*** (0.640)

2.742*** (0.576)

2.572*** (0.560)

0.572*** (0.205)

0.718*** (0.218)

0.785*** (0.213)

Constant

-0.362 (0.399)

-0.204 (0.285)

-0.098 (0.209)

0.088 (0.073)

0.090* (0.055)

0.047 (0.036)

Number of observations

297

297

297

612

612

612

R2

0.946

0.958

0.947

0.695

0.698

0.694

Except for the food price inflation rate, all dependent and explanatory variables are de-trended in the first stage, using linear, quadratic, and cubic country-specific time trend, respectively. Country clustered standard errors are in parenthesis. Year dummies are included but not shown for the sake of brevity. *** p \ 0.01, ** p \ 0.05, * p \ 0.1. Authors’ calculations using Statistics Division of the FAO (FAOSTAT) database

Fig. 5 Nutritional pathways by which the economic crisis and increase in food prices may affect child mortality. Source: Fig. 1 in [3]

an increase in micronutrient deficiencies. Christian [3] also elucidates numerous nutritional pathways by which childhood mortality can increase as a result of food price increases (see Fig. 5). These include increased prevalence of maternal undernutrition, micronutrient deficiency, and childhood undernutrition.

In order to test the above proposition, we estimate two different sets of equations. First, in order to investigate the linkage between nutrition and mortality of infants and children, we regress de-trended components of infant and child mortality rates on the de-trended component of prevalence of undernourishment. Second, where in the first

123

123

All dependent and explanatory variables are de-trended in the first stage, using linear, quadratic, and cubic country-specific time trend, respectively. Country-clustered standard errors are in parenthesis. Year dummies are included but not shown for the sake of brevity. *** p \ 0.01, ** p \ 0.05, * p \ 0.1

0.442 0.434 0.359 0.927 0.936 0.941 0.504 0.488 0.416 0.954 0.958

0.951

503 503 503 337 337 337 503 503 503 337 337

Number of observations R2

337

0.271*** (0.045) 0.382*** (0.064) 0.479*** (0.081) 0.730*** (0.051) 1.023*** (0.072) 1.293*** (0.082) 0.267*** (0.038) 0.374*** (0.054) 0.472*** (0.069) 0.625*** (0.040) 1.107*** (0.065) Constant

0.879*** (0.057)

0.525*** (0.165) 0.523*** (0.157) 0.442*** (0.161) 0.261** (0.103) 0.263** (0.114) 0.252*** (0.094) 0.420*** (0.142) 0.412*** (0.137) 0.352** (0.139) 0.261*** (0.086) 0.248*** (0.090) 0.253*** (0.076)

Quadratic (8) Linear (7) Cubic (6) Quadratic (5) Cubic (3) Quadratic (2)

Log of undernourishment

Quadratic (11) Linear (10) Linear (4) Linear (1)

Cubic (9) LDCs Non-LDCs LDCs

Non-LDCs

Dependent variable: log of child mortality rate

MDG 1 calls for halving the proportion of people who suffer from hunger as its third target and the prevalence of undernourishment is an indicator for this target. This refers to the proportion of the population below the minimum level of dietary energy consumption. This variable is taken from the United Nations MDGs Indicators Database (http://mdgs.un.org/unsd/mdg/default.aspx). Note that UNICEF, WHO, and the World Bank [41] report estimates of child malnutrition that is potentially more closely related to infant and child mortality, but these data are available only for a limited number of years for most countries. 24 Among the control variables, government health expenditure, a measure of improved sanitation facilities, and youth population share are less likely to be associated with undernourishment. However, we report the results with the inclusion of these variables for the sake of comparison. In different regressions, we removed these variables and found that the results for other variables remained almost unchanged.

Dependent variable: log of infant mortality rate

23

Table 4 Effects of undernourishment on infant and child mortality—second stage estimation using de-trended variables

stage we find a positive influence of undernourishment on mortality rates, we investigate the linkage between nutrition and food price inflation by regressing the de-trended component of under-nourishment on food price inflation and de-trended components of various control variables used in the equations for infant and child mortality. Table 4 reports the results for the linkage between undernourishment and mortality rates of infants and children in LDCs and other developing countries, respectively.23 In all equations using various de-trended measures, we find that in both LDCs and other developing countries alike, short-term increases in undernourishment result in shortterm increases in infant and child mortality rates. Having found that undernourishment leads to an increase in infant and child mortality in the developing world, we next examine the nexus between food price inflation and under-nourishment by regressing de-trended components of prevalence of undernourishment on food price inflation rate and other de-trended components of the control variables used in the equations for IMR and CMR.24 The results are reported in Table 5. It is striking to observe that only in LDCs do higher food price inflation rates cause an upward deviation of undernourishment from its long-term trend. Thus, having combined all of the results that we obtained from various regressions, we can conclude that high food price inflation rates cause an increase in undernourishment only in LDCs and this in turn leads to an increase in infant and child mortality in these poorest countries. The question then remains as to how the prevalence of undernourishment can be effectively controlled, especially when food price inflation is high in LDCs. It is reasonable to suppose that this question can be answered by examining the results for the relevant control variables. Interestingly, per-capita income, political stability, and government effectiveness all carry negative and significant coefficients only in the sample for LDCs, suggesting that not only business cycles but also short-term changes in political stability and government effectiveness may

Cubic (12)

H.-H. Lee et al.

Effects of food price inflation… Table 5 Effects of food price inflation on prevalence of undernourishment—second stage estimation using de-trended variables Dependent variable: log of under-nourishment LDCs

Non-LDCs

Linear (1)

Quadratic (2)

Cubic (3)

Linear (4)

Quadratic (5)

Cubic (6)

Food inflation rate

0.0028** (0.0012)

0.0016** (0.0007)

0.0005 (0.0005)

-0.0035 (0.0029)

-0.0013 (0.0012)

-0.0004 (0.0006)

Log of GDP per capita, PPP

-0.257* (0.154)

-0.282* (0.169)

-0.350** (0.170)

-0.188 (0.216)

-0.179 (0.160)

-0.096 (0.146)

Log of government health expenditure per capita

0.047 (0.095)

0.071 (0.056)

0.085* (0.050)

0.052 (0.123)

0.048 (0.081)

-0.006 (0.051)

Log of improved sanitation facilities

-0.007 (0.071)

0.048 (0.076)

0.038 (0.086)

-0.180 (0.147)

-0.102 (0.153)

-0.076 (0.155)

Political stability and absence of violence

-0.108** (0.045)

-0.103*** (0.038)

-0.125*** (0.039)

-0.026 (0.066)

-0.030 (0.060)

0.010 (0.051)

Government effectiveness

-0.428*** (0.112)

-0.330*** (0.101)

-0.208*** (0.074)

0.086 (0.176)

0.062 (0.141)

-0.005 (0.104)

Log of youth population share

1.266 (0.958)

0.747 (0.821)

0.630 (0.828)

0.430 (0.404)

0.458 (0.454)

0.523 (0.479)

Constant

-0.900** (0.413)

-0.439 (0.273)

-0.303 (0.212)

-0.240** (0.106)

-0.184** (0.077)

-0.148*** (0.054)

Number of observations

276

276

276

383

383

383

R2

0.673

0.669

0.548

0.205

0.224

0.202

Except for food price inflation rate, all dependent and explanatory variables are de-trended in the first stage, using linear, quadratic, and cubic country-specific time trend, respectively. Country-clustered standard errors are in parenthesis. Year dummies are included but not shown for the sake of brevity. *** p \ 0.01, ** p \ 0.05, * p \ 0.1

impact the status of nourishment in LDCs. Thus, with improved political stability and government effectiveness, the expectation arises that the adverse effect of food price inflation on nourishment in LDCs can be mitigated.25

Conclusions High and increasing food prices can generate an immediate threat to the security of a household’s food supply, thereby undermining population health, retarding human development, and lowering labor productivity for the economy in the long term. Understanding the effect of a food crisis on nutrition and health is therefore critical for the development of public policies and social programs to help the vulnerable groups of individuals, households, and countries alike. In particular, an accurate assessment is needed to help target the assistance, monitor the progress, and evaluate the effects of the policies and programs. 25

It should be noted that this finding does not necessarily mean that the adverse effect of food price inflation on nourishment can become weaker in the countries with better political stability and government effectiveness. We tested this possibility by adding inflation rates interacting with the measures of political stability and government effectiveness, respectively, but we found no significant results for the interaction terms.

Using a panel dataset covering 95 developing countries for the period of 2001–2011, this paper provides a comprehensive assessment of the short-term effects of food price inflation on nutrition and child health as measured in terms of infant mortality rate and child mortality rate. On applying any particular one of various specifications adopted to control for any country-specific deterministic trend, we have found that rising food prices have a significant detrimental effect on nourishment and consequently raise the levels of both infant and child mortality in developing countries, and especially in LDCs. We have also found that economic downturns increase infant and child mortality in most of the developing world. Thus, policies that protect the health status of infants and children in developing countries may become especially important during periods of concurrent economic downturn and high food price inflation. In this regard, international community’s enhanced efforts to provide food and health aid to these countries are in great need during these difficult periods.26 For all of the specifications employed, government health expenditure per capita has a negative relationship with infant and child mortality. The results also show that 26

For recent discussions on food and health aid allocation, the reader is referred to Fielding [42], and Lee and Lim [43].

123

H.-H. Lee et al.

infant mortality in both LDCs and other developing countries may decrease with improved sanitation facilities. Thus, governments’ strong commitment to public health as evidenced by increasing health expenditure and improving sanitation facilities is crucial in improving child health in developing countries. We acknowledge that differences should be expected among LDCs regarding the extent of the influence of food prices on child health. We also acknowledge that within each LDC there should be differences among households. In fact, FAO [32] reports an empirical investigation yielding the result that the vast majority of poor households are hit hardest by higher food prices. Also, Neha and Quisumbing [44] provide empirical evidence that in

rural Ethiopia the impact of the 2007–2008 food price crisis was greater for female-headed households. Accordingly, it would be useful to undertake micro-level investigations of the effect of food price inflation on mortality of infants and children in developing countries, and especially in LDCs. Acknowledgments This study was supported by 2014 Research Grant from Kangwon National University (No. C1010781-01-01).

Appendix See Table 6.

Table 6 Appendix table: list of countries and summary statistics Country group

LDCs

123

No.

1

Country

Angola

Infant mortality (per 1000)

Annual reduction rate of infant mortality (%)

Food price inflation rate (%)

2001

2011

Average

Average

119.8

102.2

-1.6

29.5

2

Bangladesh

61.5

35.2

-5.5

7.4

3 4

Benin Bhutan

88.5 56.9

60.4 36.9

-3.7 -4.2

3.8 6.1

5

Burkina Faso

95.2

67.7

-3.2

4.5

6

Burundi

91.1

68.9

-2.7

8.9

7

Cambodia

75.9

35.5

-7.3

5.2

8

Central African Republic

108

92.8

-1.5

4.5

9

Chad

104.3

91.3

-1.4

4.8 14.8

10

Ethiopia

86.6

48.6

-5.5

11

Gambia

61.1

49.9

-2.0

7.8

12

Haiti

73

57.7

-2.4

12.4

13

Lao People’s Democratic Republic

81.9

56

-3.8

8.6

14

Lesotho

81

72.7

-0.6

7.9

15

Madagascar

66

42.2

-4.4

10.1

16

Malawi

96.5

49.2

-6.7

10.8

17

Mali

113.1

81.4

-3.2

3.5

18 19

Mauritania Mozambique

74.4 106.9

65.8 67.2

-1.2 -4.8

6.1 12.1

20

Nepal

57.4

34.9

-4.9

8.3

21

Niger

97.7

64.8

-4.0

4.9

22

Rwanda

100.6

40.8

-8.5

8.7

23

Samoa

17.8

15.4

-1.5

6.5 16.8

24

Sao Tome and Principe

54.9

39

-3.3

25

Senegal

67.7

46.2

-3.6

3.8

26

Sierra Leone

140.9

120.1

-1.6

13.7

27

Uganda

85.4

48.9

-5.6

8.8

28

United Republic of Tanzania

75.4

39.3

-6.3

9.1

29

Yemen

67.4

47.7

-3.4

12.8

30

Zambia

95.3

58.7

-4.7

12.1

Effects of food price inflation… Table 6 continued Country group

Non-LDCs

No.

Country

Infant mortality (per 1000)

Annual reduction rate of infant mortality (%)

Food price inflation rate (%)

2001

2011

Average

Average

31

Albania

24

15.6

-4.4

2.8

32

Algeria

28.2

17.8

-4.6

5.3

33 34

Argentina Armenia

17.6 25.3

13 15.4

-2.9 -4.9

10.7 5.6

35

Azerbaijan

55.7

32

-5.4

9.1

-8.9

16.8

36

Belarus

10.2

37

Bolivia (Plurinational State of)

54.7

34

4.3

-4.7

5.6

38

Bosnia and Herzegovina

8.4

6

-3.5

4.2

39

Botswana

54.5

42.9

-2.4

8.9

40

Brazil

27.1

13.6

-6.8

7.6

41

Bulgaria

17.1

10.9

-4.4

4.5

42

Cameroon

89.4

63

-3.4

3.8

43

Cape Verde

29.1

19.5

-4.1

4.7

44

China

28.3

12.9

-7.6

5.6

45

Colombia

20.7

15.6

-2.9

6.2

46

Congo

74.6

63.9

-1.5

4.4

47

Costa Rica

10.6

8.8

-2.2

9.2

48 49

Dominican Republic Ecuador

31.4 27.2

23.4 20.4

-2.9 -2.9

10.6 6.3

50

Egypt

33.8

18.7

-5.8

10.5

51

El Salvador

25

14.2

-5.5

3.3

52

Fiji

20.1

19.2

-0.6

4.7

53

Georgia

27.9

18.5

-4.3

8.3 12.0

54

Ghana

64.8

49.9

-2.6

55

Grenada

13.1

11.7

-1.3

3.7

56

Guatemala

38.4

27.4

-3.4

8.4

57

Honduras

29.8

20.1

-3.9

6.3

58

Hungary

9.1

5.5

-5.1

6.1

59

Indonesia

39.5

26.7

-3.9

8.4 17.2

60

Iran (Islamic Republic of)

27

15.7

-5.3

61

Iraq

35.2

29

-1.9

4.3

62

Jamaica

19.4

14.9

-2.7

11.6

63

Jordan

22.6

16.8

-2.9

5.3

64 65

Kazakhstan Kenya

36.3 67.2

18.1 49.8

-6.9 -2.8

9.8 12.8

66

Kyrgyzstan

40.4

25.1

-4.9

3.9

67

Malaysia

8.1

7.3

-1.5

3.1

68

Maldives

32.5

10

-11.6

9.4

69

Mauritius

15

12.8

-1.9

7.3

70

Mexico

20.3

14.3

-3.6

5.6

71

Mongolia

45.4

24

-6.2

11.1

72

Morocco

40.6

27.7

-3.8

2.8

73

Namibia

47.9

29.2

-4.4

6.7

74

Nicaragua

31

21.3

-3.8

9.3

75

Nigeria

109.3

80.1

-3.1

12.4

76

Pakistan

85.8

70.7

-2.0

10.1

123

H.-H. Lee et al. Table 6 continued Country group

No.

Country

Infant mortality (per 1000)

Annual reduction rate of infant mortality (%)

Food price inflation rate (%)

2001

Average

Average

2011

77

Panama

21.3

16.3

-2.6

4.3

78

Paraguay

26.3

19.4

-3.0

9.0

79 80

Peru Philippines

28.4 29.9

14.8 24.1

-6.4 -2.1

3.3 4.7

81

Republic of Moldova

23.9

15.6

-4.3

7.7

82

Romania

22.1

11.2

-6.3

7.8

83

Saint Lucia

15

15.2

-0.1

3.9

84

Seychelles

11.9

11.5

-0.5

7.9

85

South Africa

52.3

34.2

-3.6

7.0

86

Suriname

27.6

19.1

-3.7

10.3

87

Swaziland

80.7

57

-3.0

11.5 10.4

88

Syrian Arab Republic

19.2

12.6

-4.1

89

Thailand

18.3

11.8

-4.3

4.8

90

The former Yugoslav Republic of Macedonia

13.4

7.5

-6.5

2.5

91

Tonga

15.1

11.4

-2.8

7.2

92

Tunisia

23.6

14.4

-4.9

4.4

93

Turkey

28.3

12.9

-7.6

15.5

94 95

Ukraine Vietnam

15.1 23.8

9.7 18.6

-4.6 -2.4

7.5 10.5

Listed countries are included in the analysis

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