The effect of formal education on food security in Togo: evidence from the food insecurity experience scale

doi:10.21203/rs.3.rs-2479183/v1

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The effect of formal education on food security in Togo: evidence from the food insecurity experience scale

https://doi.org/10.21203/rs.3.rs-2479183/v1

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The objective of this paper is to analyze the effect of formal education level on food security status at the individual level in Togo. The Food and Agriculture Organization of the United Nations' Food Insecurity Experience Scale (FIES) measure is the basis of the analysis. Using the Chi-square test and probit model, we found that there is a significant difference between the individual's education level and food security status. In addition, the probability that the individual is food secure increases with his or her education level. Finally, the study shows the existence of significant heterogeneity in the determinants of food security according to the gender of the individual. To this end, any policy aimed at investing in the education of the Togolese population while favoring vulnerable groups is desirable.

JEL code: Q18; I2

education

food security

food insecurity experience scale

Togo

The problem of food security remains acute in both developed and developing countries due to the restriction caused by the Coved 19 pandemic (Rudin-Rush et al., 2022). According to the Food and Agriculture Organization of the United Nations, food security exists when all people, at all times, have physical and economic access to sufficient, safe, and nutritious food to meet their energy needs and food preferences for an active and healthy life (Upton et al., 2016). Food insecurity, on the other hand, exists when members of a household have inadequate food for part or all of the year or face the possibility of inadequate food in the future (Maxwell et al., 2014). It can occur as a result of unavailability, lack of social or economic access, and/or misuse of food. The economic literature highlights the importance of several factors in improving the level of food security (Lecoutere and al., 2009) including the education received by the individual. Indeed, education plays a fundamental role in the food security of poor households in both developing and developed countries (Mutisya et al., 2016).

Education is thus recognized as the main policy instrument for economic growth, development, social mobility and individual fulfillment (Mutisya et al., 2016). In addition, food security is recognized as a basic right at the household and individual levels (Cordero-Ahiman et al., 2020). However, in 2020, approximately 30.4% of the world's population is still food insecure, including 11.9% in a serious situation (FAO, 2021). Globally, food insecurity has been growing since 2014 (22.4–30.4%), but it hides geographical disparities. Africa has the highest rate of undernourishment (nearly four tenths) with a projection of more than half (51.5%) in 2030 and more than half of its population is already food insecure in 2020 (an increase from 47.3–59.6% between 2014 and 2020). In Togo, the situation also seems to be worrying. This is reflected in the ranking of the hunger index (GHI) in the world where Togo is still in the zone of severe hunger with a score of 23.9 (ACTED, 2019) but also the fact that 30.5% of the Togolese population live in prevalence of severe food insecurity in 2016. Moreover, between 2016 and 2018, 68.1% (32.2% severe vs. 35.9% moderate) vs. 66.9% between 2014 and 2016 of the population was food insecure (FAO, 2019). Finally, 15.7% of female-headed households are food insecure compared to 10.3% of male-headed households (Kofi & al., 2010).

According to Caire, (1967), human capital is considered as a stock of productive resources embodied in the individuals themselves. It consists of various elements such as education, training and work experience, health status or knowledge of the economic system. Human capital has been identified as a means of increasing agricultural productivity and income, thereby enhancing food security (Schultz, 1971). It has been shown that food security and human development are intimately linked, and that significant progress on one cannot be sustained without concomitant progress on the other (Conceição and al., 2011). Thus, low education levels reduce the opportunities for households to engage in high-income paid jobs. For example, estimates from Patrinos, (2016) have shown that each additional year of education increases hourly earnings by 10 percent overall. Low education limits households to low-income jobs (menial jobs), which prevents them from acquiring the resources to purchase food for consumption, thereby increasing the level of household food insecurity ménages (Bashir and al., 2013 ; Kara & Kithu, 2020).

Many studies focus a priori on the analysis of household food security (Carletto et al., 2013; Halam and al., 2017 ; Agidew & Singh, 2018) due to the lack of data at the individual level (Broussard, 2019). In Togo, the national education system has undergone numerous reforms in recent years, notably the implementation of the 2020–2030 education sector plan (UNESCO, 2020), free primary school fees since 2008 (AFD, 2008), free secondary school registration and tuition fees for the year 2021–2022, and most recently the adoption of the National Agency for Quality Assurance in Higher Education (UL, 2022). However, studies on household food security lack information on its relationship with the level of education (Kofi & al., 2010). Also, the mechanisms by which education affects household food security vary according to different household characteristics, including gender. Moreover, achieving food security is one of the fundamental pillars of the Sustainable Development Goals (SDGs) which can only be achieved through the harmonious development of human capital, in this case individual education.

In this light, this paper aims to answer the following main question: does improving the level of education improve food security status at the individual level in Togo? Thus, this study examines the effect of formal education on food security status at the individual level while analyzing by gender. To do this, we have applied the chi-square test and probit model to data from the 2018 Gallup Global Polling survey (GWP, 2018). We found that there is a significant difference between the individual's education level and their food security status. Furthermore, the likelihood of the individual being food secure increases with their level of education.

The remainder of this paper is organized as follows: the next section presents the theoretical and empirical framework of the study. Section three highlights the methodology of the study. The results and interpretations are discussed in section four. Finally, the last section presents the conclusion and policy implications.

2.1 Theoretical elements of analysis.

Human capital is defined as "the knowledge, skills, competencies and other personal qualities possessed by an individual that are relevant to economic activity" (Weiss, 2015). Human capital is therefore a material asset that can advance and sustain productivity, innovation and employability and hence food security. It is widely recognized that education is a critical factor in food security (Mutisya, 2016). Through education, individuals gain greater capacity to engage in sustainable agricultural activities that contribute to household food security, especially in rural areas where agriculture is the main economic activity (De Moro and Burch, 2007). Education also ensures employment opportunities, improves diet and nutrition, access to markets, health, and decision making, all of which are critical to household food security.

This purely economic approach (Becker, 1962; Psacharopoulos, 1994; Schultz, 1971) of the effect of human capital is widely criticized (Seen, 1997; Woodhull 2001; Robins, 2006). Indeed, according to the capability approach, education can have an effect on food security through social change. Education thus plays a key role in providing access to public information, particularly on health, nutrition and hygiene, as it "can open people's minds" (Mukudi, 2003, p. 200; Robeyns, 2006). Acquiring knowledge about how to avoid and cope with disease is essential, as people with diseases need more calories to be food secure. In addition, it is well known that economic agents need to have, as much as possible, an adequate and diversified diet in order to strengthen their immune system and avoid morbidity and mortality. On the other hand, low or inadequate education reduces the opportunities for households to engage in high-income paying jobs. It limits households to low-income jobs (menial jobs), which prevents them from acquiring the resources needed to purchase food for consumption, thus increasing the level of household food insecurity (Headey, 2011). Household food security is not only explained by the level of education of the farmer, but also by the farmer's experience in agricultural activity. This experience is often captured by the age of the head of the household. Thus, authors such as Babatunde and al., (2008) and Bogale & Shimelis, (2009) have shown that the socio-demographic characteristics of the head of the household significantly influence household food security. Indeed, small-scale producers with a low level of experience could not master the new technology unless they are accompanied. This could affect their productivity and consequently food security. Thus, based on the literature, the following conceptual framework presents the different channels through which human capital influences household food security.

2.2 Elements of empirical analysis

The effect of education on food security has been the subject of several studies in both developing and developed countries. However, the results remain mixed because of the contradiction of the expected signs (positive effect). Indeed, while some authors have found a significant positive effect of human capital on household food security (Faye et al., 2011), others find a significant negative effect (Amali, 2012). Still others find no significant effect of education on food security (Garrett & Ruel, 1999).

In Bangladesh, Tauseef, (2022) has shown that education positively affects the level of household food security. The same is true for Akbar and al., (2020) Pakistan, who instead focused on parental education. Mutisya and al., (2016) in the case of Kenya, studied the link between education and food security of the urban poor in two slums. Using longitudinal data collected between 2007 and 2012 in Kenya and using a generalized random-effects ordered probit model, the authors arrived at the results that there is a significant positive relationship between education and household food security. The probability of being food insecure decreased by 0.019 for a unit increase in the average number of years of education of the members of a given household.

The impact of education on food security and economic growth in Bangladesh was the focus of Islam, (2020). Engel-Granger integration is applied to determine the long-run and short-run relationships between the variables over the period 1998–2017. The integration results confirm the existence of positive short- and long-run relationships between education spending and economic growth. Also, they show that education has a direct link with food security, particularly on the food access dimension.. Halam and al., (2017) examined the role of education and income in determining household living standards and food security. The results revealed that education and income contribute significantly and positively to household living standards and food security.

On the other hand, based on the human capital index constructed using principal component analysis, Obayelu and al., (2019) showed a negative relationship between food insecurity and the human capital index in Nigeria and an absence of a bidirectional relationship between the two variables. In the case of Pakistan, Iftikhar and al., (2015) it is rather the literacy rate that is considered for production and food security in Punjab province. The study by Adegbola, (2019) concluded that the level of primary and secondary education negatively affects the food security status of farm households in Benin. The similar result was also found in the study of Amali, (2012) in Nigeria.

In Nigeria, Mukaila and al., (2020), reveal that there is no significant relationship between education and household food security in vegetable farming. Similarly, Njura et al, (2020) suggest that there is a statistically insignificant relationship between educational approaches and food security in Kenya. The same finding between food production and farmers' level of education is also observed in the study of Oguh, (2020). In Ghana, Acheampong et al., (2022) also found no significant effect of education as a determinant of food insecurity at the farm household level.

This review of the literature shows that the impact of education on food security is mixed, not only because of the opposing results, but also because the link between education and food security is not direct but the result of several other factors. Moreover, this impact has not been sufficiently studied for the case of African countries in general and Togo in particular. The present study fills this gap for the case of Togo by focusing on individual analysis as in (Broussard, 2019).

3.1 Theoretical framework.

Households in developing countries are mostly consumers and producers at the same time. In this context, the utility model of the agricultural household (Strauss et al., 1986) is generally applied to analyze the determinants of their food security (van Wijk et al., 2014; Ogundari,2017).

In this framework, the analysis model is presented as follows:

$Max U\left\{\left[\left({C}_{of} ,{C}_{fp}\right)\right.\right., {\beta }_{nf}\left.)\right], {l}_{i }\left( {x}_{i}\right)$ }

$$S/C$$

$${P}_{fp}{C}_{fp}+{P}_{nf}{B}_{nf}+{P}_{of}{C}_{of}+El={P}_{of}{Q}_{of}+TE+nfinc-Ul$$

With U a twice differentiable and strictly quasi-concave utility function, ${C}_{of}$ own production or home production, ${C}_{fp}$ good purchased on the market, 𝛽𝑛f non-food good, 𝑙𝑖 the demand for leisure and 𝑥𝑖 is a vector of socio-demographic characteristics including education level. The equation on the left of the equality represents the individual's expenditures and the one on the right represents income. Expenditures include the value of market purchases of food consumed ${P}_{fp}{C}_{fp}$, the value of non-food expenditures (𝑃𝑛f𝐵𝑛f), the value of purchasing one's own farm produced good ${P}_{of}{C}_{of}$ and $El$ the expenditures on leisure. The individual's income includes the value of farm products ${P}_{of}{Q}_{of}$, the value of the time endowment $TE$, the value of labor used and $nfinc$ is non-farm income.

The maximization by the method of Lagrange under constraint, allowed to obtain the optimal

value of the food consumption of the individual:

$${Id}_{a}=\left[{P}_{of},{P}_{fp}, {P}_{nf}, S, {\text{i}\text{n}\text{c}}^{* }\left(Pof, w,{L}^{0}, {C}^{0}, N\right), {x}_{i}\right] \left(2\right)$$

Where ${P}_{of}$, ${ P}_{fp}$and ${P}_{nf}$are respectively the price of the food produced by the individual, the price of the food good purchased on the market, and the price of the non-food good ; $w$ is the wage rate in the economy; ${\text{i}\text{n}\text{c}}^{* }$the total income of the individual on the basis of which consumption decisions are made; ${L}^{0}$ the fixed quantity of land; ${C}^{0}$is the fixed stock of capital; According to Ogundari, (2017), individual food demand (${Id}_{a}$) can be considered as a measure of individual food security (IFS) and is written as follows:

$${Id}_{a}=IFS=\left[SCA ,IP, IDA, FIES\dots \right] \left(3\right)$$

IFS is a vector of various indicators (food consumption score, production index, Food Insecurity Scale, food diversity index or food expenditure) of the individual's food security (Smith & Subandoro, 2007 ; Lokosang and al., 2011; Obayelu, 2013 ; Broussard, 2019).

3.2 Empirical model specification and data

3.2.1 Empirical specification of the model

The objective was to determine the effect of education on food insecurity in the Togolese population. To do this, we then re-scaled the relationship between food security and its determinants using a reduced form of Eq. (2) in consideration with Eq. (3) as follows:

$${FIES}_{i}=\left[{inc}_{i}^{*},{educ}_{i},{z}_{i}|\alpha \beta \right]+{\epsilon }_{i} \left(4\right)$$

With FIES, Food Insecurity Experience Scale; 𝑒𝑑𝑢𝑐𝑖respondent's level of education; and 𝑧𝑖 other characteristics of the respondent; 𝛼 𝑒𝑡 𝛽 the parameters to be estimated and 𝜀𝑖 the error term.

The parameters of Eq. (4) can be generated using a binary Probit or Logit model. The Probit model assumes a normal distribution of the stochastic term, while the Logit assumes a logistic distribution. These are linear probability models using maximum likelihood estimation. Consequently, the dichotomous model is written as follows:

$${p}_{i}=prob\left({y}_{i}=1/x\right)=F\left({educ}_{i},{z}_{i}|\alpha \beta \right), {\forall }_{i} =1\dots N \left(5\right)$$

Pi is the probability that individual $i$ is food insecure, ${y}_{i}$ is the dichotomous dependent variable which is 1 if the individual is food secure and 0 otherwise, and F is the distribution function. Based on the lowest AIC and BIC information criteria (see appendix table 1), we used the probit model to facilitate the calculation of marginal effects. The econometric model can be specified as follows:

$${F}IESi= {\beta }_{0}+ {\beta }_{1}.{Educ}_{i}+{\beta }_{2}.{income}_{i}+{\beta }_{3}.{place}_{i}+{\beta }_{4}{.sex}_{i}+{\beta }_{5}.{age}_{i}+{\beta }_{6}.{adult}_{i}+ {\beta }_{7}{.child}_{i}+ {\epsilon }_{i} \left(6\right)$$

Where $i$ refers to the individual, FIES the explained variable being 1 if the individual is food secure and 0 otherwise. The vector of explanatory variables is composed of education (Educe), respondent's income quintile (Income), place of residence (Place), sex (Sex), age (Age), number of individuals aged fifteen and over in the respondent's household (Adult) and the number of individuals under fifteen (Child).

3.2.2 Data source and variable definition

The data used in this study, comes from the 2018 wave of Gallup Global Polling (GWP). Each year since 2005, a random sample of approximately 1,000 people in 147 countries is selected to participate in the GWP. The samples are nationally representative of the resident population aged 15 and older in each country. Interviews are conducted either face-to-face or by telephone. Surveys are conducted by telephone in the country with more than 80 percent telephone coverage and face-to-face otherwise.

In 2014, the Food and Agriculture Organization of the United Nations (FAO) commissioned Gallup World Poll to collect the Food Insecurity Experience Scale (FIES) data on behalf of the FAO, as part of the Voices of the Hungry (VoH) project. The FIES measure is based on respondents' self-assessment of difficulty in obtaining adequate food and is a direct measure of food access. The questions were tested and validated, using item response theory, to be comparable across cultures (Smith and al., 2017). Data on food security, as well as demographic characteristics and other indices of well-being, are available in the GWP for 147 countries around the world.

In the case of our study, the analysis is conducted using data from the 2018 wave of the GWP for Togo. The total sample size is 1000 adults and the data relate to the respondent's income quintile, education level, area of residence, gender, age as well as the individuals in the household (child under 15 years and adults over 15 years). The questions that are asked during data collection to construct the Food Insecurity Experience Scale (FIES) are presented in Table 2. The data used in this study were obtained at the authors' request in April 2020 from the Gallup website. Variable definitions and statistics are reported in Table 3.

Table 2

Food Insecurity Experience Scale questions.
Now I would like to ask you some questions about your food consumption in the last 12 months. During the last 12 months, was there a time when:
Q1. You were worried you would run out of food because of a lack of money or other resources? Q2. You were unable to eat healthy and nutritious food because of a lack of money or other resources? Q3. You ate only a few kinds of foods because of a lack of money or other resources? Q4. You had to skip a meal because there was not enough money or other resources to get food? Q5. You ate less than you thought you should because of a lack of money or other resources? Q6. Your household ran out of food because of a lack of money or other resources? Q7. You were hungry but did not eat because there was not enough money or other resources for food? Q8. You went without eating for a whole day because of a lack of money or other resources?
Source: authors from Cafiero et al., (2018)

Table 3

*Definition of variables and descriptive statistics*.
Qualitative variables	Definition			Modality				Proportion (%)
Binary FIES	food security index			1 = Food security (FS)				36,00
	food security index			0 = Food insecurity (FI)				64,00
Educ	Education level of the individual			0 = primary				30,10
				1 = college				61,90
				2 = high school				8,00
Income	Incomes quintiles			1st quintile 2nd quintile 3rd quintile 4th quintile 5th quintile				15,90 15,50 18,40 22,40 27,80
Place	Respondent’s place of residence			0 = urban 1 = rural				23,00 77,00
Sex	Gender of the respondent			1 = Male 0 = Female				57,90 42,10
Quantitative variables		Mean	Standard deviation		Minimum	Maximum
Age of respondent		30,56	13,43		15		100
Number of adults		2,91	1,45		1		9
Number children		3,22	1,87		1		11
Observation			1000

Source: authors using data from GWP, 2018.

3.3 Measuring food safety.

Food security is a complex concept to define. It includes four dimensions: availability, accessibility, utilization and sustainability. Thus, more than 200 indicators are used in the literature to capture food security (Maxwell et al., 2008). An indicator that is more appropriate to best capture this phenomenon is the Food Insecurity Experience Scale (FIES) index implemented by the FAO in 2014. This index is estimated from the affirmative responses to the eight questions in Table 2 using the Rasch model (Cafiero and al., 2018; Saint Ville and al., 2019). The thresholds for the different levels of food security are set at less than − 0.51598 for food security, less than 3.05227 for mild food insecurity, and more than 3.05227 for severe food insecurity at the country level (Sheikomar et al., 2021). In order to split the sample in two, the 3.05227 threshold was used in this study to have the food secure individuals from the food insecure ones; this allows us to obtain the binary FIES.

4.1 Descriptive statistics on the effect of education on food security

4.1.1 Food security in Togo

The analysis of Fig. 2 shows that 36% of respondents are food secure in Togo. However, 49.20% are moderately food insecure and 14.80% are severely food insecure. This measure hides disparities according to the gender of the respondent. In fact, 31.43% of men are food secure compared to 51.64% and 16.93% respectively who are moderately and severely food insecure. Among women, 42.28% are food secure compared to 45.84% who are moderately food insecure and 11.88% who are severely food insecure. This means that in Togo there is a gender effect in terms of food insecurity.

Figure 3 shows the marginal predicted effect of food security status by individual's education level, with other covariates held at their mean values. The probability of being food secure increases significantly with increasing education level. In contrast, the probability of being moderately and severely food insecure decreases significantly with increasing education level of the individual.

Finally, Fig. 4 shows the marginal effect of the interaction between education and gender. The analysis of this figure shows that, for the same level of education, women have a lower probability of being food insecure in Togo than men. For example, when both individuals have primary school education, the probability that the female is food insecure is 76.20% for men compared to 65.89% for women. When they all have high school education, the probability of being food insecure increases to 58.94% for men and 46.94% for women.

4.1.2 Food security and education in Togo: application of Chi-square test.

The level of education plays a crucial role in the level of food security of respondents. This is confirmed by the chi-square test between the level of food security and the level of education of the individual. It can be seen that according to the level of education, 26.91% of the respondents in food security have a primary level; 38.61% have the college level against 50.00% who have the high school level (Table 4). The proportion of food secure individuals increase with the level of education of the respondent. The opposite finding is observed for individuals who are moderately or severely food insecure with the level of education of the individual. This confirms the first finding: the higher the level of education, the less food insecure the individual is in Togo.

Other characteristics of the individuals surveyed also have a significant effect at the 1% level on food insecurity. These are characteristics such as the respondent's gender and income. This difference in gender confirms the finding in Fig. 4. Also, according to the income quintile, the richest people are food insecure, since this proportion decreases as the level of wealth of the respondents increase.

Table 4

food security and education level: chi2 test
Variables	Food security status
Variables	N	FS (%) (n = 360)	MFI (%) (n = 492)	SFI (%) (n = 148)
Total	1000	36.00	49.20	14.80
Educ: primary	301	26.91	55.15	17.94	19,95***
College	619	38.61	47.50	13.89
High school	80	50.00	40.00	10.00
Sex: Male	579	31.43	51.64	16.93	13,83***
Female	421	42.28	45.84	11.88
Place: urban Rural	230 770	36.96 36.71	46.96 49.87	16.09 14.42	0,699
Income	159 155 184 224 278	20.75 34.84 33.70 33.48 48.92	60.38 46.45 52.72 51.79 39.93	18.87 18.71 13.59 14.73 11.15	39,85***

Notes: FS, food security; MFI, moderate food insecurity; SFI, severe food insecurity.

Source: authors using data from GWP, 2018.

4.2 Econometric analysis of the effect of education on food security in Togo.

The previous analysis shows that there is a difference according to the level of education in terms of food insecurity at the individual level in Togo, but it does not allow us to appreciate the nature of the relationship between the two variables. To do this, the probit model is estimated, the results of which for all and by gender are recorded in Table 4. Before interpreting these results, it is necessary to conduct preliminary tests to ensure the significance of the model.

4.2.1 Hosmer and specificity tests of probit model.

The validity of the probit regression of the effect of education on respondent food security is tested using the test of Hosmer & Lemesbow, (1980) and specificity tests. The Hosmer test with chi2 (941) = 964.66 is significant at the 1% level (Appendix Table 5) showing that the model fits reasonably well. In addition, the result of the sensitivity and specificity test suggests that the percentage of good prediction is 65.90% (Appendix Table 5). This means that the overall rate of correct classification (De Caigny et al., 2018). Finally, the ROC curve (Appendix Fig. 6) shows that the area under the curve is 65.84 stipulating that the model has acceptable predictive power (Dorfman & Alf Jr, 1969). The following Fig. 7 shows the sensitivity and specificity as a function of the cut-off probability.

Moreover, the Wald test of joint significance (64.84) shows us that at least one of the variables introduced into the model is significantly different from zero (prob = 0.000) at the 1% threshold. Moreover, this test carried out individually confirms that the coefficient of level of education is significantly different from zero. Also, to account for possible heteroscedasticity problems, we estimated the model with heteroscedasticity correction. The following section presents and analyzes the effect of education and the other control variables on food security in Togo.

4.2.2 Analysis and discussion of results

In the probit model, the coefficients are not directly interpretable. They only give an idea of how the independent variables affect the dependent one. For this purpose, only the marginal effects are presented in Table 4. The coefficients of the probit and logit models as well as the marginal effects of the latter are reported in Table 6 in the appendix. The dependent variable is food security. A positive effect means, an increase in the probability of being food secure. On the other hand, a negative effect means a decrease in the probability of being food secure. Finally, given the gender effect that is generally found in the education sector, we have estimated and reported in the same table (column 1 and 2) the estimates by gender to see if the effects differ by gender with respect to the effect of education on food security in Togo.

Table 4 shows that regardless of the respondent's education level, a positive effect is found on the respondent's food security (column1). This means that the probability that the individual is food secure increases if he or she has a higher level of education. In fact, compared to respondents with primary education, having a college degree increases the probability of the respondent being food insecure by 10.3%. This probability increases by 17.9% when the respondent has the high school education level. This result can be explained by several channels. First, education may allow the individual to access food and nutrition information necessary for the individual to be food secure. Second, education can enable the individual to access well-paid jobs. Also, education helps the individual to be more productive; this is a crucial link for the individual to be food secure if he/she lives especially in rural areas: this is the productivity effect. Finally, education allows the individual to have a solid social capital. This constitutes the last resort for the individual and therefore allows him to escape from food insecurity.

Table 4

Marginal effects estimation of the probit model.
	(1)	(2)	(3)
Variables	Total	Male	Female
Income
2nd quintile	0.138***	0.0796	0.218***
	(0.0499)	(0.0645)	(0.0766)
3rd quintile	0.125***	0.0883	0.186**
	(0.0483)	(0.0627)	(0.0753)
4th quintile	0.130***	0.0662	0.225***
	(0.0479)	(0.0607)	(0.0773)
5th quintile	0.274***	0.230***	0.346***
	(0.0507)	(0.0663)	(0.0788)
Age	0.00104	-0.00135	0.00640***
	(0.00118)	(0.00138)	(0.00209)
Sex: Male	0.112***
	(0.0307)
Education: primary
College	0.103***	0.0966**	0.0764
	(0.0338)	(0.0440)	(0.0528)
High school	0.179***	0.142*	0.231**
	(0.0624)	(0.0745)	(0.110)
Place: urban	-0.0359	-0.0499	-0.0100
	(0.0343)	(0.0443)	(0.0537)
Adult	-0.0196*	-0.0187	-0.0190
	(0.0105)	(0.0140)	(0.0161)
Child	-0.00118	-0.00239	0.00117
	(0.00917)	(0.0118)	(0.0145)
Observations	1000	580	420

Standard deviations are in parentheses; *** p < 0.01, ** p < 0.05, * p < 0.1

Source: authors using data from GWP, 2018.

This result is consistent with the work of Akbar and al., (2020) in Pakistan; Gallegos and al., (2022) in Australia and Mutisya and al., (2016) in Kenya, which showed that the education of the household head positively influences household food security in Kenya. It is also consistent with the capability theory of Sen (Lanzi, 2007)which emphasizes a fundamental role of education in food security but also the human capital theory (Becker, 1962) which showed the importance of investment in human capital for the well-being of an individual and his nation. But our result is in contradiction with some studies. For example, no significant effect is found between education level and food security in the work of Kahsay and al., (2020) in Ethiopia.

The effect of education is not the same on the level of household food security when we refer to columns 2 and 3. Indeed, for women, only the high school education level has a statistically significant effect on food security. However, the probability of being food secure for women remains higher than for men with the same level of education (in this case high school). This probability is 23.1% for women versus 14.2% for men. If we look only at men, we see that this probability increases significantly with the level of education (0.97% for colleague compared to 14.1% for high school).

To analyze the effect of education on individuals' food security, other variables were also introduced into the model as control variables. The regression results show that the income of individuals have a significant positive effect on the food security status of respondents. It is noted that the probability for respondents to be food secure increases from 13.8–24.8% for individuals in the first income quintile and the second income quintile respectively. This means that the wealthiest are more likely to be food secure than the poorest. Indeed, income would allow households to access food in quantity and quality and thus improve their food security status. This result is consistent with the work of Ndobo & Sekhampu, (2013) in South Africa and in particular the thesis of Sen & Sen, (1982) who considers that the problem of food insecurity is a phenomenon of the lack of purchasing power of the poor to access food goods. However, this result contradicts the work of de Feleke and al., (2005) who found no significant effect. In contrast, the observed mixed effect of education on the food and nutrition security status of households in Mozambique (Garrett & Ruel, 1999). Moreover, the income effect is more pronounced for women than for men (columns 2 and 3).

The gender of the individual also plays a crucial role in the level of food security of individuals. Indeed, it is found in our analysis that gender has a significant positive effect at the 1% level on the food security status of respondents. This means that compared to women, being male increases the respondent's probability of being food secure by 11.2%, all other things being equal. This shows the existence of a gender effect in food security in Togo. This result can be explained by the fact that in our developing countries, women are often marginalized in the sharing of economic and natural resources. It corroborates the results of Obayelu, (2012) in Nigeria and Tibesigwa & Visser, (2016) in South Africa which showed that the male head of household is more likely to be food secure. The result is also consistent with the work of Broussard, (2019) which showed that women are 2.7% less likely to be food secure than men in 146 countries around the world. However, our result does not corroborate that of Zoyem and al., (2008) in Burundi, which did not find a statistically significant effect of gender on food security status.

Finally, the result shows that when the number of individuals aged 15 and over increases by one unit, all else being equal, the probability of being food secure decreases by 1.96%. Although counter-intuitive, this can be explained by the additional burden that these individuals create for the respondent, especially in the context of our developing countries. This result is contradictory to the work of Garrett & Ruel, (1999) which found a positive effect of household size on household food security status and the thesis defended by natalists that population growth can be seen as an innovation. However, it is consistent with Malthusian theory (Heinsohn & Steiger, 1980). However, no significant effect is reported by gender of the respondent.

Education is an essential link in the development of an economy. Its development improves the agricultural productivity of rural households, creates economic opportunities for both urban and rural. As a result, it contributes to the strengthening of the level of food security of the individual and the nation. Also, education is a key tool as highlighted in the World Development Report 2018: schooling is not synonymous with learning, but it is crucial to invest wisely and effectively in the education of people in order to develop human capital (World Bank, 2018). Based on this, this paper proposes to analyze the effect of formal education on food security status at the individual level in Togo. The data used in the analysis are from the 2018 Gallup Global Survey conducted among a sample of one thousand (1000) individuals in Togo. Descriptive and econometric analyses are conducted in this study. Chi-square test and probit model are used.

The results of the study show that about 36% of the respondents were food secure; 49% were moderately food insecure and 14% were severely food insecure. There is also a difference in terms of food insecurity according to the respondent's level of formal education. The analysis of the effect of education on food security status shows that the respondent's level of education positively affects the respondent's food security status in Togo. However, the effect of education on food security is more pronounced among men than women. To address the problem of food security, it would be wise to promote investment in the education of the Togolese population, with particular emphasis on the education of women. The study also recommends improving the income (financial factor) of the population and gender equality policies to improve the level of food security of the Togolese population.

Data available on request from the authors

The data that support the findings of this study are available from GWP at [email protected], upon reasonable request.

Conflict of interest

The authors declared that they have no conflict of interest.

Funding Statement

This research received no specific grant from any funding agency, commercial or not-for-profit sectors.

Acknowledgements

An earlier version of this paper was presented at the symposium organised by FASEG of the University of Lomé (Togo) in April 2022 and benefited from constructive comments by symposium participants. The authors would like to thank GWP for making the data available for this research. We also thank PARESI for its full assistance in the development of this research. Finally, authors thank Professor Ega Akoété AGBODJI, Esso-Hanam ATAKE and Mr. Koffi Géraud TOZO for their contributions.

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The effect of formal education on food security in Togo: evidence from the food insecurity experience scale

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Abstract

Figures

1 Introduction

2 Link Between Education And Food Security

2.1 Theoretical elements of analysis.

2.2 Elements of empirical analysis

3 Research Methodology

3.1 Theoretical framework.

3.2 Empirical model specification and data

3.2.1 Empirical specification of the model

3.2.2 Data source and variable definition

3.3 Measuring food safety.

4 Analysis And Discussion Of Results

4.1 Descriptive statistics on the effect of education on food security

4.1.1 Food security in Togo

4.1.2 Food security and education in Togo: application of Chi-square test.

4.2 Econometric analysis of the effect of education on food security in Togo.

4.2.1 Hosmer and specificity tests of probit model.

4.2.2 Analysis and discussion of results

Conclusion

Declarations

References

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