Open access peer-reviewed chapter - ONLINE FIRST

Economic Perspectives on Analysis of Ensuring Cereal Production and Consumption Security

By Ryusuke Oishi

Submitted: November 9th 2020Reviewed: February 3rd 2021Published: March 4th 2021

DOI: 10.5772/intechopen.96377

Downloaded: 50

Abstract

Cereals are essential for human nutrition. However, the ever-increasing world population makes it difficult to maintain the cereal production and consumption security. It is essential to overcome this situation by increasing cereal yield. An additional issue is the fact that while some countries suffer from hunger, a significant amount of food is discarded in others. This study analyses both production and consumption of cereals with the goal of ensuring food security. On the production side, many developing countries lack production capacity in contrast to developed countries. This is mainly due to a lack of capital, technology and human resources skills. In this study, we first theoretically demonstrated a cereal production gap between developing and developed countries. Second, we performed an empirical analysis to confirm the theoretical demonstration. On the consumption side, we focused on the cause of food loss and waste. We apply economic theories to demonstrate the situation where food loss and waste are occurring in the market. Then we introduced the related data to interpret the current world situation. Finally, we discussed the potential measures to improve cereal production and consumption.

Keywords

  • cereals
  • rice
  • wheat
  • maise
  • production
  • yield

1. Introduction

Cereals are essential for human nutrition. However, the ever-increasing world population makes it difficult to maintain the security of this food source. It is essential to overcome this situation by increasing cereal yield. An additional issue is the fact that while some countries suffer from hunger, a significant amount of food is discarded in others. This study analyses both production and consumption of cereals with the goal of ensuring food security.

On the production side, many developing countries lack production efficiency mainly due to a lack of capital and human resources skills. First, we theoretically demonstrated a cereal production gap between developing and developed countries. Second, we performed empirical analysis to confirm the theoretical demonstration. We also clarified how the production and consumption status of three typical cereals (wheat, rice and maize—or corn in United States English) are related to the regional food cultures.

On the consumption side, we investigated the cause of food loss and waste. We applied economic theories to demonstrate the market situation where food loss and waste are occurring. We then introduced the data relating to food loss and waste in G20 and the least developed countries in the world to interpret the current world situation. In addition, we also considered some cases of macroeconomic impacts on cereal productions (i.e. weather extremes and changes in commodity prices).

The remainder of this chapter is organised as follows. Section 2 provides the formal definition of food security. Section 3 provides both the theoretical and empirical analysis of cereal production. Section 4 analyses the causes of food loss and waste. Section 5 interprets the additional issues of cereal production (i.e. the macroeconomic impacts) and Section 6 concludes the chapter.

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2. Food security

According to the Food and Agriculture Organisation of the United Nations (FAO), food security exists when all people—at all times—have physical, social and economic access to sufficient, safe and nutritious food that meets their dietary needs and food preferences for an active and healthy life [1]. The issue of food security has been raised as a major agenda at the United Nations (for example, Goal 2 of the Sustainable Development Goals: End Hunger, Achieve Food Security and Improved Nutrition and Promote Sustainable Agriculture) [2].

The above agenda is mainly due to the expected increase in the world population potentially make it difficult to ensure food security with the current level of food production. Overcoming this situation will require increasing the production capacity of nutritious foods for human consumption (especially wheat, rice and maize). However, the cereal production capacity varies across countries. In particular, there is more room for improvement in the crop yield in developing countries than in developed countries. Moreover, a significant amount of edible food is being discarded without being consumed in many developed countries whereas some developing countries concern food shortages. Eliminating such consumption waste can contribute to food security as much as increasing production capacity.

3. Cereal production

3.1 Theoretical analysis

In this section, we used a simple economic model to illustrate the problems of cereal production in developing countries and the methods for its improvement1. In order to highlight the problem of cereal production in developing countries, we comparatively analysed developing and developed countries. A farmer produces a product (i.e. cereals) by using labour and capital as demonstrated in Eq. (1).

Yi=LiαiKi1αiE1

Eq. (1) takes the form of a Cobb–Douglas production function, where Yiis an output of cereals. iis a subscript that informs on whether the farmer lives in a developed or developing country (i.e. i=R,i=Pfor developed and developing countries, respectively); Lidenotes the labour in country iand Kidenotes the capital used to produce cereals (e.g. machinery). The degree of contribution of Liin producing cereals is measured by αi. We assume that αR>αP. Because capital is often exported from industrialised countries to the rest of the world, we assume that there is no significant difference in performance of capital between developing and developed countries. In this case, the degree of αiis determined by the production capacity of Lirelative to the performance of Ki. By considering its relationship to Ki, labourers in developing countries are often under trained and less productive than in developed countries.

Next, we investigated the relationship between labour and capital in production for further details. Specifically, by fixing the production of cereals at a certain level (i.e.Y¯i), the marginal rate of technical substitution of i(MRTSi) is derived as Eq. (2).2

MRTSi=LiKi=1αiαiY¯iKi1αiE2

According to Eq. (2), MRTSPis larger than MRTSR. This indicates that, as compared to developed countries, introducing one unit of capital can replace a larger number of labourers to produce a given amount of cereal in developing countries. This is because, as compared to when there is enough farming machinery, productivity is more likely be improved by introducing one machine when there is a shortage of farming machinery.

Next, we set the farmer’s budget constraints. To use labour and capital, wages and purchase/maintenance costs for capital resources were incurred, and the farmers are supposed to cover them out of their budgets. Eq. (3) shows the farmer’s budget constraints.

Bi=LiIi+KiCE3

Biis a farmer’s budget in country i, Iiis an income of Liand Cis the cost of purchasing and maintaining Ki. We assumed that BR>BPand IR>IPbecause, in most cases, the income level in developed countries is higher than in developing countries. In contrast, we did not distinguish Cin terms of subscript i. This is because capital is often exported from industrialised countries around the world, and hence its prices do not differ largely between countries.

By using Eqs. (1)-(3), we demonstrate the farmer’s cereal production regarding to its first-order conditions. The first-order condition is derived by solving the problem with a Lagrange multiplier (Eq. (4)).

LFi=LiαiKi1αi+λiBiLiIiKiCE4

where LFiis the dependant variable of the Lagrange function in country iand λiis a Lagrange multiplier of the problem in country i, respectively.

To solve the problem, we first differentiate LFiwith respect to Li, Kiand λishown in Eqs. (5)-(7), respectively.

LFiLi=αiLiαi1Ki1αiλiIiE5
LFiKi=1αiLiαiKiαiλiCE6
LFiλi=BiLiIiKiCE7

By using the first-order conditions of Eqs. (5)-(7), we can derive the optimal level of Li(Li) and Ki(Ki) as follows:

Li=αiBiIiE8
Ki=1αiBiCE9

Eq. (8) specifies the optimal number of labourers to produce cereals in country i. By assuming that the difference between Biand Iiin developing and developed countries is the same (i.e.BRIR=BPIP), the optimal number of labourers in developing countries is smaller than in developed countries.

Eq. (9) specifies the optimal amount of capital resources to produce cereals in country i. Due to the comparison of Biand αibetween developing and developed countries, we are unable to comparatively conclude the size of KRand KP.

The optimal set of inputs LRKRand LPKPare illustrated in Figures 1 and 2 , respectively.

Figure 1.

Optimal Set of Imputs in Developed Countries.

Figure 2.

Optimal Set of Imputs in Developing Countries.

The figures are two-dimensional, with the number of labourers in country i(Li) on the vertical axis and the quantity of capital in country i(Ki) on the horizontal axis. The negative slope straight line in each figure illustrates the farmers’ budget constraints in country i(Bi).3 The curves illustrate the farmers’ production in country i(Y¯i).4 In this situation, the farmers’ best option is to produce a certain amount of cereals by minimising the cost, which is reflected by the points where the production curve touches the budget constraint.

As illustrated in Figures 1 and 2 , due to the small budget, the optimal amount of both inputs in developing countries is less than in their developed counterparts.5 However, closer inspection reveals that the optimal amount of capital is relatively larger than the number of labourers in developing countries. This is due to the lack of skilled labourers and the fact that there is more room for productivity improvements through capital in the case of developing countries.6 Even though this is the optimum input situation based on the model, the situation in reality differs. In many developing countries, development support has not sufficiently progressed, and agriculture is often carried out manually.

3.2 Empirical analysis

Although we theoretically demonstrate the optimal input of cereal production in developing and developed countries, it does not reflect the actual situation. In this section, we investigate the empirical data to identify the discrepancies between the optimality condition (Liand Ki) demonstrated in 3.1 and reality.

3.2.1 Data source

The data employed for the empirical analysis was extracted from FAOSTAT.7 Specifically, the production quantity (Element code: 5511) and domestic supply quantity (Element code: 5301) of wheat (Item code: 2511), rice (Item Code: 2805) and maize (Item code: 2514) in the group of 20 (G20) countries and the least developed countries in 2018 (Year code: 2018) are extracted from a domain of new food balance (Domain code: FBS).8 The number of tractors (Element code: 5116 and Item code: 2455009) in the G20 and least developed countries in 2006 (Year code: 2006) is extracted from a domain of machinery (Domain code: RM).9 The population (Element code: 511 and Item code: 3010) in the G20 and least developed countries in year 2018 were extracted from a domain of annual population (Domain code: OA). The food losses (Element Code: 5123) of wheat, rice and maize in the G20 countries and the least developed countries in 2018 are extracted from the domain of new food balance. 10

3.2.2 Data description

Tables 1 and 2 in the Appendix show the domestic production quantity and the production quantity of wheat, rice and maize, the number of tractors used for agriculture and the population in the world’s least developed countries and the G20 countries. Close inspection of the tables reveals the problems related to cereal production and food security in developing countries.

CountryWheatRiceMaizeTractorsPopulation
ProductDomestic SupplyProductDomestic SupplyProductDomestic Supply
Afghanistan3613699535262610716571137171.92
Angola31111107252765299630809.79
Bangladesh10996885544165641532884841161376.7
Benin018645921311510141511485.04
Burkina Faso02771615231700161619751.47
Cambodia046106471000660469216249.79
Central Africa05111190864666.368
Chad27526025743842215477.73
Djibouti033914424104958.923
Ethiopia450063945444183508255109224.4
Gambia084234021439422280.094
Guinea0420171352781980612414.29
Haiti027818373526028811123.18
Laos024358534369827377061.507
Lesotho959258191002922108.328
Liberia0734030598014818.973
Madagascar6365112477421522226262.31
Malawi114531681182698273618143.22
Mali2934123230273625322619077.75
Mauritania755113429516234403.313
Mozambique216912757411011250131529496
Myanmar1165605152261761984155910275053708.32
Nepal1958196110257002473261628095.71
Niger566120309306037522442.82
Rwanda1115876314841020712301.97
Senegal0682920205126464515854.32
Sierra Leone0913159523257650.15
Sudan595275487125456341801.53
Togo01441452228879057889.093
Uganda236472463742773250042729.04
Tanzania57984222021346273520656313.44
Yemen106365007814368728498.68
Zambia11416043562395285917351.71

Table 1.

Production of cereals, number of tractors and population in the world’s least developed countries.

Note: Table 1 is provided by the author based on the data extracted from FAOSTAT. Product and domestic supply of wheat, rice and maize are in 1,000 tonnes. Population is in 1,000 people.

CountryWheatRiceMaizeTractorsPopulation
ProductDomestic productProductDomestic productProductDomestic product
Argentina1853955961368753434621923744361.15
Australia20941871663545338738224898.15
Brazil54221253011749122738228864173209469.3
Canada3221679400533138851421573318237074.56
China1316901272482140792069192573492770321459378
France35798195217365912667842864990.51
Germany202641628904053344671479870083124.42
India997009542217258014268827820234021352642
Indonesia0986883037738053025431380267670.5
Italy693311136151269961791203460627.29
Japan7666700972811232015819127202.2
Mexico2943621728413522717040514126190.8
Korea26466351956688781003751171.71
Russia721363241610381175114196447439600145734
Saudi Arabia51836670188245316033702.76
South Africa1900359331406125101051057792.52
Turkey2000019134940135957007071103738382340.09
The UK135551636406060206767141.68
The US5139833837101535504364262292878327096.3

Table 2.

Production of cereals, number of tractors and population in G20 countries.

Note: Table 2 is provided by the author based on the data extracted from FAOSTAT. Product and domestic supply of wheat, rice and maize are in 1,000 tonnes. Population is in 1,000 people.

First, in many developing countries, both the quantity of production and the domestic production of cereals are far below those of the G20, which indicates that developing countries lack cereal production capacity. Moreover, many G20 countries’ production exceeds its domestic supply, indicating that those countries import cereals to cover shortages in their national consumptions. However, the opposite is true in the case of the least developed countries. A low level of production is indicative of threatened food security.

Second, although based on scarce information, the number of tractors in the G20 countries is significantly higher than in developing countries. As demonstrated in the theoretical analysis, abundant machinery contributes to the production of cereals. The lack of machinery likely causes the difference in the productivity between developed and developing countries.

Third, the production of wheat, rice and maize varies according to the country’s region. For example, wheat production in many countries in Table 1 is lower than that in countries in Table 2 . This is because many developed countries are Western countries whose staple food is wheat (i.e. bread). On the contrary, many countries in Table 1 produce more rice. This is because rice is often consumed in Asia and Africa, and those regions include many countries in Table 1 . Unlike the other two cereals, maize is actively produced in the countries listed in both Tables 1 and 2 . This is because maize is often consumed in Africa as well as in Western countries.

3.2.3 Empirical analysis

To make the discussion in 3.2.2 more reliable, we performed regression analyses. We confirmed the first (as compared to developed countries, developing countries lack cereal production capacity) and third argument (i.e. the production of wheat, rice and maize varies according to the country’s region).11

Cerealcit=βc0+βc1G20i+βc2Africai+βc3Asiai+βc4Americai+βc5Europei+t=20152018Yeart+εitE10

In Eq. (10), the dependent variable Cerealcitrepresents the domestic supply quantity of cereal cin country iat year t.12 Subscript cdistinguishes three types of cereals (i.e. wheat, rice and maize). Subscript tspecifies the year in the sample period.13 The explanatory variable G20iis a dummy variable that takes the value of 1 if countryiis a member of G20, and 0 otherwise. Africai,Asiai,AmericaiandEuropeiare dummies that take the value of 1 if country iis in that region and 0 otherwise.14 βc0,βc1,βc2,βc3,βc4andβc5are a constant term, the coefficients for G20i,Africai,Asiai,AmericaiandEuropeiin the case of regressing for cereal c, respectively. t=20152018Yeartis the sum of the dummies between 2015 and 2018 for capturing the year fixed effect.15 εitis an error term for country iat year t.16

Table 3 presents the descriptive statistics for the data employed for the regression analysis of Eq. (10). As mentioned earlier, the G20 production of all cereals far exceeds that of the developing countries. The difference is particularly noticeable in maize production and smallest of the three (wheat, rice and maize) in rice production. This is because there are many countries that have rice as their staple food in poor regions such as Southeast Asia.

WheatRiceMaize
The Least
Developed
Countries
G20 CountriesThe Least
Developed
Countries
G20 CountriesThe Least Developed CountriesG20 Countries
Observation165951659516595
Mean1056.66722955.143775.12124536.861343.52142863.25
Standard Deviation1862.21830904.3410106.5454650.721704.47983273.31
Minimum Value52735−423751346
Maximum Value7617127248564152069198255343651

Table 3.

Descriptive statistics for Cerealcit.

Note: Table 3 is provided by the author based on the data extracted from FAOSTAT. Cerealcitis in 1,000 tonnes.

Table 4 shows the estimation results of Eq. (10). Close inspection of the estimation results reveals some features that are consistent with the argument in 3.2.2. First, the estimated coefficients of G20iβ̂c1in the case of all three cereal types are positively estimated with strong significance, indicating that G20 countries produce larger amounts of all three cereals than the least developed countries. Second, by looking at the estimation result of the regional dummies, differences in cereal production by region can be found. For example, in case of CerealRiceit, the size of the estimated coefficient for Asiaiβ̂Rice3is significantly larger than those for other regions. This finding makes sense given that rice is the staple food for people in Asian countries. Similarly, in the case of CerealMaizeit, the size of the estimated coefficient for Americaiβ̂Maize4is much larger than those for other regions. This is also understandable because people in the United States consume many foods made from maize. In case of CerealWheatit, estimation of the regional dummies is different from our expectation. Given that wheat-based foods are mainly consumed in Europe, the estimated coefficient for Europeiβ̂Wheat5was expected to be larger than for other regions. However, β̂Wheat3is larger than that of β̂Wheat5. This might be due to China’s wheat production, that surpassed that in European countries. Finally, the low R2 value in all three cases indicates that the explanatory ability of these estimation results is not high. This is because all the explanatory variables (except the constant) are dummy variables.

Independent VariableDependent Variable
CerealWheatit
Dependent Variable
CerealRiceit
Dependent Variable
CerealMaizeit
Estimated CoefficientEstimated CoefficientEstimated Coefficient
G20i24978.12***
(0.000)
32732.82***
(0.001)
45346.42***
(0.000)
Africai17217.26***
(0.002)
31947.7***
(0.001)
44958.31***
(0.000)
Americai7068.021***
(0.001)
8418.469***
(0.001)
80329.6***
(0.000)
Asiai24711.49***
(0.000)
54529.34***
(0.000)
46233.9***
(0.000)
Europei13487.44***
(0.000)
254.84***
(0.002)
7352.68***
(0.000)
Constant−17861.62***
(0.003)
−32457.05***
(0.002)
−46880.16***
(0.000)
Number of Observations260260260
Prob > F0.0000.0000.000
R20.3120.3090.247

Table 4.

Estimation results of Eq. (10).

Note: This table shows estimation results for Eq. (10). P-values are presented in parentheses. The estimation is conducted with robust standard errors. Superscripts ***, ** and * indicate statistical significance at 1%, 5% and 10%, respectively.

In order to comparatively analyse cereal production in the developed and developing countries in greater detail, in addition to Eq. (10), we conducted another estimation procedure. The production of cereals in a country depends on its population. By using per capita productivity, we can exclude the impact of the population. In order to reveal the latter issue, we set Eq. (11) as follows:

CerealPerCapitacit=βc6+βc7G20i+βc8Africai+βc9Asiai+βc10Americai+βc11Europei+t=20152018Yeart+εitE11

Eq. (11) is different from Eq. (10) in that it uses CerealPerCapitacitas a dependant variable. This variable was obtained by dividing Cerealcitby population of country i.17

Table 5 shows the descriptive statistics for CerealPerCapitacit. Information in Table 5is significantly different from Table 3 . Specifically, as compared from the developed country, the mean value of CerealPerCapitaRiceitis higher in the least developing countries. This is probably because the large populations in developed countries used as a denominator value of CerealPerCapitaRiceitlowered their value of CerealPerCapitaRiceit.

WheatRiceMaize
The Least
Developed
Countries
G20
Countries
The Least
Developed
Countries
G20
Countries
The Least
Developed
Countries
G20
Countries
Observation165951659516595
Mean0.05025360.14826610.12702910.05402630.05836970.20179
Standard Deviation0.10624250.09390060.1623050.06773630.05509030.2146537
Minimum Value0.00107150.0291697−0.00194420.00456240.00020750.0146632
Maximum Value0.85011590.35576840.616450.27573080.23659341.063882

Table 5.

Descriptive statistics for CerealPerCapitacit

Note: Table 5 is provided by the author based on the data extracted from FAOSTAT.

Table 6 shows the estimation results of Eq. (11); the interpretation of these results requires careful consideration. In the case of wheat and maize, the coefficients of G20i(β̂Wheat7andβ̂Maize7) are positively significant, indicating that even if the effects of the population are eliminated, G20 countries are more productive than the least developed countries, which is consistent with our view. In contrast, in the case of rice, surprisingly, the estimation of G20i(β̂Rice7) is negatively significant. This is probably because G20 countries with rice food cultures include populous countries (i.e. China and Indonesia).

Independent VariableDependent Variable
CerealPerCapitaWheatit
Dependent Variable
CerealPerCapitaRiceit
Dependent Variable
CerealPerCapitaMaizeit
Estimated CoefficientEstimated CoefficientEstimated Coefficient
G20i0.0388***
(0.001)
−0.150***
(0.000)
0.132***
(0.000)
Africai−0.225***
(0.000)
−0.090***
(0.002)
0.177***
(0.000)
Americai−0.211***
(0.000)
−0.014
(0.103)
0.399***
(0.000)
Asiai−0.209***
(0.000)
0.123***
(0.000)
0.132***
(0.000)
Europei−0.066***
(0.000)
−0.011***
(0.000)
0.087***
(0.000)
Constant0.270***
(0.000)
0.169***
(0.000)
−0.119***
(0.000)
Number of Observations260260260
Prob > F0.0000.0000.000
R20.3400.4030.530

Table 6.

Estimation results of Eq. (11).

Note: This table shows estimation results for Eq. (11). P-values are presented in the parentheses. The estimation is conducted with robust standard errors. Superscripts ***, ** and * indicate statistical significance at 1%, 5% and 10%, respectively.

In the case of rice, looking at the estimated result of the regional dummies shows that only Asiai(β̂Rice9) is positively significant. This confirms that Asia stands out in terms of rice productivity. Similarly, in the case of maize, the estimated coefficient of Americai(β̂Rice10)is significantly larger than those of other regions, indicating that maize productivity in the American region is higher than in other regions. One unexpected observation is that, in the case of wheat, all regional dummies are estimated to be negative. Because the estimated coefficient for Europei(β̂Wheat11)has the smallest negative value, we can argue that the per capita production of wheat in Europe is the largest; however, the reason for this is not clear.

Compared to Table 4 , all the R2 values are slightly higher in Table 6 . Therefore, the explanatory power of the estimation results improved slightly in Table 6 .

4. Cereal consumption

In Section 3, we describe both the theoretical and empirical analyses of the cereal supply. In this section, we identify the problems with and the methods for improving the consumption of cereals as food security issues. One might think that the only issue regarding food security is the improvement of production capacity; however, management of consumption is also important. Among many problems relating to cereal consumption, we focused on food loss and waste.

The food situation differs from country to country. While some countries suffer from poverty and lack of food, others have excessive food supply in their markets and dispose of consumable foods.

Table 7 shows the amount of food lost in the least developed and G20 countries.18 Not surprisingly, as compared to that in the least developed countries, the larger amount of food loss is reported in the G20 countries. Considering the larger production volume and the population, the loss in the G20 can be understood as a natural consequence of its food consumption. However, the developing countries are not completely devoid of food loss; although small comparatively, food loss is also reported in the least developed countries. However, reasons for food loss are different between the G20 and the least developed countries. In the case of the G20 countries, the cause of food loss is overstocking. For example, in Japan, consumers strongly demand food safety and quality [3]. As a result, foods that are not sold by the expiration date are discarded [3]. Moreover, consumable foods with slight scratches or incompatible size are discarded [3]. Another issue is that the main concern of business food suppliers is to make profit. When such economic agents compete with each other to form a market is a basis of capitalism. However, in order to make profits, they sometimes make decisions that are detrimental to society. For example, convenience stores in Japan often overstock foods, because they do not want to lose customers due to out of food stock [3].

The Least Developed CountriesG20
WheatRiceMaizeWheatRiceMaize
Afghanistan5422516Argentina31653633
Angola00307Australia20962
Bangladesh2383104250Brazil24711818321
Benin0115378China2901862411806
Chad01036France3263112
Ethiopia1683252India598746542785
Madagascar040310Italy493411
Malawi05529Japan1631904
Mali21127218Mexico197534571
Mauritania2271Korea23481205
Mozambique1575Russia43321115
Myanmar2486190Saudi Arabia35092
Nepal195486248South Africa850569
Niger041Turkey213330202
Rwanda0349The US233439817864
Senegal63033
Sierra Leone01201
Sudan4824
Uganda205175
Tanzania330738
Zambia3272

Table 7.

The amount of food loss in the least developed and G20 countries.

Note: Table 7 is provided by the author based on the data extracted from FAOSTAT. Food loss of wheat, rice and maize in the least developed and G20 countries are in 1,000 tonnes.

In the case of developing countries, due to a lack of sufficient capital for processing and preserving food, some foods are rarely delivered to consumers while fresh. For example, in developing countries, most of the postharvest grains are stored in traditional storage structures, which cannot prevent insect infestation and mould during storage [4].

Figure 3 illustrates an excess supply of food (caused by overstocking) in developed countries.19 According to economic theory, if goods are traded at their market equilibrium (i.e. the intersection of the demand and supply curves), production and consumption match and no goods will be left unsold. However, as shown in Figure 3 , if the price of goods deviates from its equilibrium, supply and demand of goods do not match, and some goods are not sold.

Figure 3.

The Market with Oversupply of Food.

Figure 4 illustrates a food shortage situation in poor countries.20 Unlike in Figure 3 , the supply curve in Figure 4 becomes vertical at a certain quantity (QS). This shows supplier’s limit of cereal production capacity. Due to the limited production capacity in poor countries, once the supply reaches its limit, the quantity does not increase regardless of the price. Moreover, in this situation, the price of the goods deviates downward from its equilibrium. The discrepancy between supply and demand becomes the shortage.

Figure 4.

The Market with Shortage of Food.

In theory, eliminating oversupply of food and the assurance of food security in developing countries is mutually achievable. For example, transferring food surplus from developed countries to developing countries to combat the shortages would provide a solution to both problems.

5. Measures to ensure world food security

As discussed in Sections 3 and 4, there are the challenges to ensuring world food security both in food supply and consumption. On the supply side, the main reason for food insecurity is the lack of capital and training of human resources in developing countries. However, due to lack of funds, increasing capital and training human resources are hardly be achieved. Therefore, loans and assistance from international organisations and developed countries are required. Additionally, investment projects (i.e. foreign direct investment) are also effective in raising funds for developing countries. Furthermore, to gain an understanding of the outcome of such investments is larger in developing countries than in developed countries will be important21.

There are other points that need improvement. First, improvement in seed breeding is effective for sustainable agricultural production [5]. Second, in many cases, as compared to farmers with large operations, smallholder farmers are disadvantaged in accessing market; therefore, farming should be re-invented as an attractive local business opportunity for smallholder families [6]. Third, in the agri-food system, a few large international firms dominate the market share, and smallholders mainly trade on local short-supply chains [7]. Fourth, in recent years, production and consumption of rice in many parts of Asia has been steadily declining, whereas the opposite is true in Africa [8]. Fifth, due to economic development, the demand for maize to feed livestock has increased [9]. Six, the problem of food self-sufficiency does not apply only to developing countries. In Japan, due to the ageing population and the lack of young people willing to engage in agriculture, the self-sufficiency rate is low [10]. As a result, Japan imports a substantial amount of food from abroad (i.e. China) to cover their shortages [10].

Stabilisation of markets to protect suppliers from macroeconomic shocks is also important. For example, in 2020, the global economy was greatly affected by the spread of COVID-19. Because the main transmission route of COVID-19 is droplets from infected people, people stopped eating out. In Japan, food manufacturing and service businesses were severely damaged by people’s restraints and many food manufacturers and restaurants went bankrupt [11]. This was mainly because in Japan many restaurants are small and medium-sized enterprises that lack corporate strength to withstand severe economic adversities [12]. As a result, a significant amount of ingredients that were to be delivered to restaurants went left unsold. In addition, a sharp drop in the demand for restaurant food has spurred the overstock of food, leading to the collapse of the prices of some foods. If the situation does not improve, farmers will not be able to make sufficient profits and will be forced out of business. This will lead to a decline in food production capacity and will worsen food insecurity.

In addition, inflation and instability of agricultural prices will put pressure mainly on the world’s low-income group of people and an increase in labour productivity will be necessary to overcome the problem [13]. The effect of extreme weather is also a major issue for cereal production. Weather extremes in the United States in 2012 caused a sharp increase in the world maize price, and the poor countries with high maize import dependency were the most seriously affected [14].

On the consumption side, the main challenge is to reduce food loss in the developed countries. One measure to correct such market failure is government intervention in the market to internalise negative externalities. Additionally, transferring food surpluses from developed countries to developing countries to combat food shortages may improve the situation. Food banks are one of the potential measures for recycling food within a country [15]. If such food banks could be internationalised, food security in developed countries may be ensured in a way that is close to our idea. However, there are many difficulties with this potential solution. For example, some foods do not last long and are not suitable for long-distance transportation. Moreover, as discussed before, due to regional variances in food culture, some foods may be hard to replenish.22 Many countries also impose tariffs on imported products because large amounts of imported food may adversely affect local farmers’ businesses.

Additionally, food loss also occurs in developing countries, where food security is not ensured. The main cause of food loss here is lack of capital for storage; therefore, as in the supply side discussion, increasing capital through investment and assistance is the effective measure23.

In this section, we examined measures to improve food security. Although the authors’ proposed methods have the potential to improve food security, there are many challenges. In order to achieve these improvements, in addition to international efforts (i.e. international organisations and governments), changing the mindset of each economic entity (i.e. supplier and consumer) will be necessary.

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6. Conclusion

Cereals are essential for human nutrition. However, the ever-increasing world population makes it difficult to maintain food security. It is necessary to consider various factors related to production and consumption of cereals to ensure food security. This study considers the food security issues for cereals in terms of both supply and consumption.

On the supply side, we proposed that cereal food security can be improved by increasing production capacity in developing countries. The optimal condition of our theoretical model specifies that, as compared to the case of developed countries, farmers in developing countries should more actively utilise capital resources. However, reality largely differs from theory. As shown by the data, the use of farming machinery in developing countries is lower than in developing countries. Additionally, our regression result confirms that the production of cereals (i.e. wheat, rice and maize) in G20 countries surpasses that in the least developed countries. Furthermore, our empirical analysis also confirms that the type of cereals produced vary significantly regarding the region.

On the consumption side, we emphasised the problem of food loss. Although some countries in the world suffer from food insecurity, others discard large amounts of food. Reducing such waste can contribute to global food security. However, the causes of food loss differ between developing and developed countries. In the case of the former, the lack of capital means that food rots before it is consumed. In the case of the latter, foods are oversupplied to the market due to excessive competition between firms.

In order to mitigate these problems, we proposed the following measures. In order to increase production in developing countries, their capital resources need to increased; this requires significant investment and assistance. On the other hand, one way to prevent food loss in developed countries is to mitigate excessive competition among firms through government market intervention. It may also be effective to transport surplus food from developed countries to developing countries to fill shortages. However, there are many challenges to implementing these measures. To truly improve the global food situation, in addition to international efforts (i.e. international organisations and governments), each of us needs to change our consciousness.

Acknowledgments

We are deeply grateful for the editor, Dr. Aakash Goyal. We are also grateful to IntechOpen and Meikai University, which supported our research in various ways.

Notes

  • Because many readers of this paper are not expected to be specialised in economics, we will deal with a simple model that can easily be understood.
  • The MRTS i measures the number of L i to be replaced by increasing one unit of K i to maintain a certain level of production (i.e. Y ¯ i ).
  • The farmers are only able to purchase the set of inputs allocated inside (lower left) of the budget constraints.
  • The curve of Y ¯ i illustrates the sets of L i and K i to maintain the fixed amount of the farmer’s production in country i . Moreover, slope of the curve is reflected by size of MRTS i (without the negative sign). Because MRTS P is larger than MRTS R , slope of the curve in Figure 2 is steeper than Figure 1.
  • In this case, it is assumed that the difference in B i is larger than the difference in α i between the countries.
  • However, as the country develops, the optimal input of labour and capital changes. As the country develops, labourers acquire higher skills. Moreover, capital accumulation leaves less room for marginal productivity gains. Hence, the developing country’s optimal condition converges toward that of developed countries.
  • FAOSTAT (http://www.fao.org/faostat/en/#data).
  • The production quantity is a value that considers import / export and change in stocks from domestic production quantity.
  • Due to a small data availability, the author decided to show the number of tractors in 2006, which reports more data than other years.
  • The author identifies G20 countries in the ‘countries’ and the least developed countries in the ‘special group: Least Developed Countries > List) in the domains of the items (i.e. new food balance, machinery and annual population). We excluded the European Union (EU) from G20 because the latter is not a single nation.
  • Due to the small amount of available data, we did not perform the regression analysis on the second argument (i.e. the number of tractors in the G20 countries is significantly higher than that in developing countries).
  • We separately regressed Eq. (10) for the three cereals types (i.e. Cereal Wheat i t , Cereal Rice i t and Cereal Maize i t ). Although i is used to distinguish developed or developing country (i.e. i = R , i = P ) in subsection 3.1, in this subsection, i is used to distinguish the countries in the dataset (i.e. i = the US , i = the UK , etc … ).
  • Although Tables 1 and 2 only show the 2018 data for each country, we decided to use the 2014–2018 data for the estimation. This is because a larger data size helps to perform a more significant quantitative analysis.
  • To deal with collinearity, we dropped Oceania i from the regression equation.
  • To deal with collinearity, we dropped Year 2014 from the regression equation.
  • The data employed in subsection 3.2.3 are extracted from the source introduced in 3.2.1. The dummies were created by the author. The regional dummies Africa i , Asia i , America i , Europe i and Oceania i were created by using FAOSTAT information: Regions (Africa > (List), Asia > (List), Americas > (List), Europe > (List), Oceania > (List)).
  • The regression of Eq. (11) additionally uses population data of the countries in 3.2.1 (in the period between 2014 and 2018) to the data employed for the regression of Eq. (10). To distinguish from the coefficients in Eq. (10), the constant, coefficient of G 20 i , Africa i , Asia i , America i and Europe i in Eq. (11) are expressed as β c 6 , β c 7 , β c 8 , β c 9 , β c 10 and β c 11 , respectively.
  • Because the food loss data is reported from a limited number of countries, the countries with no data were deleted from Table 7 .
  • S, D, P, Q, Q S and Q D in Figures 3 and 4 represent supply, demand, price, quantity, quantity supplied and quantity demanded for a product in the market.
  • Here, in order to focus on the issue of food security in developing countries, we ignored food loss in the developing countries.
  • This is because countries with small capital grow faster by capital investment than countries with large capital. However, on the other hand, we cannot ignore that investment in developing countries often involves higher risk than that in developing countries.
  • South Asia, where rice is the staple food, is one of the most densely populated regions and the second poorest region in the world [16]. In order to guarantee its food security, self-sufficiency is important [16].
  • Installation of evaporative coolers can be considered as one of the realistic measures to reduce food loss and waste [15].

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Ryusuke Oishi (March 4th 2021). Economic Perspectives on Analysis of Ensuring Cereal Production and Consumption Security [Online First], IntechOpen, DOI: 10.5772/intechopen.96377. Available from:

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