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European Journal of Applied Sciences – Vol. 10, No. 3

Publication Date: June 25, 2022

DOI:10.14738/aivp.103.12204. Adegnika, M. (2022). Causality Test on Panel Data: An Application to the Study of the Causality Between Agricultural Growth and

Demographic Burst in the Uemoa Area. European Journal of Applied Sciences, 10(3). 281-299.

Services for Science and Education – United Kingdom

Causality Test on Panel Data: An Application to the Study of the

Causality Between Agricultural Growth and Demographic Burst

in the Uemoa Area

ADEGNIKA Moutairou

Teacher-Researcher at the National School of Applied Economics and

Management (ENEAM) of the University of Abomey-Calavi

ABSTRACT

This article aims to analyze the main lines of the modern theoretical debate around

the interactions between demographic growth and agricultural growth in the

WAEMU space. It identifies the (none) causalities between certain demographic and

agricultural growth variables focused on an autonomous and intermediate

research field between the corpora of demography and agricultural growth theory.

The results of the application of the approach of Konya (2006) based on a test of

(none) causality in the sense of Granger (1969), show that the econometric results

obtained are ambiguous to the theoretical corpus which was constituted between

the strong population growth and weak agricultural growth in the WAEMU space.

According to the results of the various (no) tests, the causality between the

population surge and agricultural growth is far from being retroactive in certain

countries (Benin and Mali) unlike other countries in the area where we note the

existence of feedback between population growth and agricultural growth. Almost

all the countries of the UEMOA space seem to be part of the logic of the

populationists. Population growth in WAEMU countries remains a determining

factor for agricultural growth. It is the main lever of agriculture. This result

confirms the thesis of Jean Bodin (1530-1596).

Keywords: Population growth-Agricultural growth-(None) Causality-UEMOA space- Panel

JEL: C23, O41, O53, O55

INTRODUCTION

Population growth is still rapid in many parts of the WAEMU region. This population growth

seems to induce recurring problems of regional or local agricultural growth. The social,

economic and political issues in the WAEMU space are associated with the various demographic

trajectories whose adverse effects vary from one State to another in this space. This divergence

in the effects of population growth on agricultural growth is explained by the capacity of each

member country of the space to satisfy these basic food security and nutrition needs on the one

hand, but also by agricultural policy (crops cash crops/ and or food crops). Meeting food needs

and politics should be driven by strong health and education policies. In the UEOMA countries,

do the agrarian systems of the space reduce the food and nutritional insecurity affecting the

population, in both urban and rural areas? It is also about the capacity of the Member States of

the UEMOA space and local authorities to draw up and implement effective policies with a view

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to sustainable development (preserving the environment, preventing conflicts, ensuring

security goods and people, equipping and managing a growing number of agglomerations and

supporting the emergence of dynamic urban economies, etc.).

In the WAEMU area, the problems of population growth and agricultural growth are

particularly acute. The population growth rate is high there, 2.3% on average over the past ten

years. In addition, the current growth in foodstuffs is about 30% lower than in 1967. Low yields

and the scarcity of land is widespread there. These obstacles to the growth of agricultural

production are further reinforced by the fragmentation of agricultural holdings, poor land

management, a lack of technical and organizational progress in agriculture, and inappropriate

agricultural and economic policies. The food situation in WAEMU countries is particularly

delicate. It has deteriorated over the years despite some progress in agriculture, and the

demographic outlook suggests growing difficulties if significant agricultural policy measures

are not taken (Benson, 2004; Bruinsma, 2002; IFPRI, 2004; Paillard, 2010; Rosegrant, 2003).

In this alarming situation how to solve the resulting food security problem in this space. Several

methods are considered in this perspective, but it is clear that they have remained ineffective.

The first method advocated is to increase food production by 300% to provide barely adequate

diets for their projected 2 billion people by 2050.

The WAEMU space seems to be characterized by large-scale poverty and malnutrition, large

food deficits are observed in some countries in the space, a high and growing dependence on

the import of food products and aid dealer. Food products still represent around 70% of the

total value of agricultural production in this area, and it is estimated that demand in this area

will double by 2020.

Generalized population growth also concerns the agricultural labor force, but with variable

rates that contribute to widening the differences between countries in terms of the ratio of

dependents to labor force. The number of people to feed per worker, which was between 1.7

and 2.8 at the start of the period, increased from 2.3 to 5.4 forty years later. This corresponds

to different rates of urbanization and agricultural exodus. The group of Sahelian countries

(Mali, Niger, Burkina Faso) remained very rural and agricultural. Conversely, for the coastal

countries (Benin, Togo and Côte d'Ivoire) the relative place of agriculture in employment has

regressed and the number of people to feed per worker has increased from less than 3 to more

than 4. Senegal and Guinea Bissau followed intermediate trajectories, close to the overall

average Benoit-Cattin et al (2011). This amounts to an additional need of around 50 billion

dollars per year (at current prices). With a low level and stagnation of per capita income, large- scale poverty, the demand in the WAEMU space for high-value food products remains low.

Moreover, the area is experiencing fairly high demographic growth, around 3% on average. The

rural population represents more than half of the population in the space; it too is growing at

an average rate of 2%. This rural population constitutes the majority of the mass considered as

poor according to the criteria defined by the organizations of the United Nations. Agriculture is

its main economic activity in this space.

The different trends in GDP and population growth have led to even more contrasting trends in

per capita GDP by country, particularly for the most recent period considered by Maddison

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Adegnika, M. (2022). Causality Test on Panel Data: An Application to the Study of the Causality Between Agricultural Growth and Demographic

Burst in the Uemoa Area. European Journal of Applied Sciences, 10(3). 281-299.

URL: http://dx.doi.org/10.14738/aivp.103.12204

1973-2001. In the developing countries, only the Asian countries as a whole continued to

record strong growth in their GDP per capita during the period 1973-2001: 3.6% per year on

average, against 0. 9%per year for all Latin American countries, and +0.2% for all of Africa. The

insignificant growth of agricultural GDP per capita in this area between 1973 and 2001 is

attributable to several factors, among which we can cite: an international economic

environment less favorable to this area than in the previous period. The annual data available

between 1960 and 2013 for the major regions of the world confirm the negative impact of

strong demographic growth in sub-Saharan Africa on the increase in its average agricultural

GDP per capita, despite the recent recovery in the economic growth of the region. Agricultural

growth in the area was 6.5% in 2008 against an average of 4.4% during the period 2003-2007

and 3.2% in the 1990s. More than half of the countries in the region have reached the CAADP

target of 6% in 2008. These are Senegal (14.2%), Mali (10%), Burkina Faso and Niger (8.6%).

Given its weight (approximately 70% in agricultural value added), the crop production sub- sector remains the main driver of agricultural growth. With growth of 35.7% in Senegal, 15.7%

in Burkina Faso (11.6%), 81% in Niger, 84% in Benin. This performance recorded in 2008 is

attributable to measures to boost food production following the crisis of soaring food prices

and to the good distribution of rainfall in time and space during the agricultural campaign

2008/2009. However, there was a decline in agricultural growth in 2009. It stood at 4.8% in

2009 at the regional level. A third of the countries were able to achieve the 6% CAADP growth

target (compared to more than half in 2008).

Data on health, education, sanitation and other areas are not so good. Thus, the data available

at the WAEMU level on HIV/AIDS infections show a high prevalence in the countries of the

coastal region. These HIV infections are progressing thanks to the precariousness of social

conditions caused by the war and the appearance of refugee camps, particularly in Côte d'Ivoire,

accentuating promiscuity and prostitution. The movements of combatants, often accompanied

by rape and prostitution, are also likely to favor the progression of the prevalence rate. Indeed,

the prevalence rate is about 10.8% in Côte d'Ivoire and 7.2% in Burkina Faso. Senegal, Mali and

Niger have a prevalence rate of less than 2%, the lowest in the sub-region. The illiteracy rate

remains high in this part of Africa. In Niger it reached 84%. Mali, Burkina, Senegal and Benin

also have very high rates (between 60 and 80%). These rates are generally higher in rural areas

and for women. Statistics show a strong inequality between nations. For example, in 1999,

infant mortality varied from 50 in Mali to 252 in Niger. For a few rare countries, the infant

mortality rate increased between 1990 and 1999. This is the case of Côte d'Ivoire. Maternal

mortality remains a concern. The increase in the majority of cases of health expenditure

expressed in relation to GDP shows that the States are not indifferent to the health situation in

the sub-region. Life expectancy at birth increases very timidly in most cases. However, Ivory

Coast, Mali, Togo and Burkina are falling behind in terms of longevity. This situation can be

explained, among other things, by the economic crisis during the 1990s, and especially by the

persistence of diseases such as AIDS and malaria. Access to health services is high in Niger,

Senegal and Burkina with rates above 90% on the other hand, this rate is low in Benin (18%).

The latter even experienced a regression between 90-93 and 2000. Niger experienced the

greatest progress in this area because in 1990-93, only 30% of the Nigerien population had

access to health care. Access to sanitation remains a crucial problem for the entire sub-region

given the low rates observed, half of the countries being below 50%. Among the countries in

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this area, some have steadily increased the share of public resources earmarked for agriculture.

The Maputo ratio rose to 8% in 2008 in Togo. For the rest of the countries, we note a drop in

the ratio in Benin (from 8.2% between 1996 and 2000 to 6% over the period 2005-2008) and

its stagnation around 2% in Côte d'Ivoire. The work of Taondyandé et al (2012) indicates that

cereal production increased by 12.6% in 2008 in the West African region against an average

increase of 5.2% over the period 2000-2007. Its increase in 2008 is well above the trend

observed since the beginning of the decade in most countries. The largest increases were

recorded in Senegal where it almost doubled (99.3%), followed by Burkina Faso (41.1%), Niger

(25.8%) and Benin (9.4%). At the regional level, this increase in cereal production results from

the almost balanced increase in the supply of rice (13.9%), maize (13.5%) and millet/sorghum

(11.6%). However, when Nigeria is excluded, maize recorded the largest increase (28.3%),

followed by millet/sorghum (22.4%) and finally rice (19.8%). While the region is globally self- sufficient for maize, millet and sorghum, it remains structurally in deficit for rice, where the

rate of coverage of needs is approximately 35% in West African countries. In terms of

productivity, rice is the cereal speculation that recorded the most significant increase in yield

in 2008. In fact, the efforts made by the countries to increase the supply of rice following the

increase in its prices on the international market allowed an increase in its productivity

compared to its level of 2000-2007. With the exception of Côte d'Ivoire where it fell by 8.6%,

rice yield increased from 8% in Togo to 34% in Benin.

For cereal speculation that did not benefit from specific measures, yields also increased in some

countries. However, the climatic factor would be the main determinant of this increase. The

ReSAKSS-AO statistics (Annual Report on Agricultural Sector Trends and Prospects) in 2010

show that the supply of roots and tubers has also progressed beyond its recent trend. It

increased by 9% in the region against an average increase of 5.2% over the period 2001-2007.

This increase in production is the result of efforts to diversify the food supply of certain Sahelian

countries. Indeed, the increase in the production of roots and tubers in the region remains

lower than the regional trend in the main producing countries with the exception of Benin

where it increased by 54% compared to 2007. On the other hand, it tripled in Senegal

(+198.7%) and increased by 42.8% in Burkina Faso. The extension of cultivated areas entirely

explains the increase in supply in the main cassava-producing countries insofar as its yield fell

by 4.7% in Côte d'Ivoire, 1.6% in Togo and 0. 6% and remained constant in Benin. The increase

in plantings also explains the increase in yam production in producing countries with the

exception of Benin where its yield increased respectively by 4.3% compared to 2007.

The results recorded in 2009/2010 are globally below those of 2008. Cereal production at the

regional level remained almost constant (an increase of only 0.8%). It suffered a decline in 6

countries of the region. These are Niger (-27%), Burkina Faso (-17%), Senegal (-2%). The

supply of roots and tubers in the region increased by 5.3% in 2009 against 9% in 2008. The fall

in production in Côte d'Ivoire by 10.6% explains the decline in the rate of increase in regional

production compared to 2008. After having increased by 17% in 2008, the supply of legumes

(peanuts, dry beans, soybeans) in the area fell slightly by 0.1% in 2009 due to the drop in

production in Niger (-45.2% ), in Burkina Faso (-11.3%). It recorded an increase in Senegal

(+30.1%).

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Adegnika, M. (2022). Causality Test on Panel Data: An Application to the Study of the Causality Between Agricultural Growth and Demographic

Burst in the Uemoa Area. European Journal of Applied Sciences, 10(3). 281-299.

URL: http://dx.doi.org/10.14738/aivp.103.12204

Inflation is relatively low in WAEMU member countries. Over the 2000-2007 periods, it

remained below the regional convergence criterion of 3%. Currency instability could be the

cause. In 2008, there was a significant increase in the prices of agricultural products in all the

countries of the region. It oscillated between 8% in Côte d'Ivoire and Senegal to 28% in Togo.

This inflation is attributable to the transmission of higher international prices to local markets.

On average, the terms of trade were balanced over the 2000/2007 period in the region. In 2008,

despite the rise in the prices of local products, given the degradation of terms in most countries

of the region. The rise in producer prices did not make it possible to compensate for the loss of

purchasing power of farmers linked to the inflationary spiral of 2008. The current trend

between agricultural growth and population growth in the WAEMU space, achieve the second

goal of the SDGs? (Ending Hunger; Ensuring Food Security; Improving Nutrition and Promoting

Sustainable Agriculture). The challenges of reviving the agricultural sector in the face of

demographic growth in this space are stalling, insofar as in the WAEMU space, the budgets

allocated to agriculture remain low and below the Maputo agreements.

Faced with the multiple unexplained and unmetered constraints in the agricultural sectors of

the member countries of the space, the second objective of the SDGs seems to be mortgaged.

Among the constraints: agrarian and land reforms, the adoption of agricultural technical

innovations, water control, the perception of climate change with its adverse effects on

agricultural production, the impoverishment of infertile land and training agricultural

producers. Despite this precarious situation to achieve the second objective of the SDGs,

demographic growth and urbanization continue to increase at a high rate. Agricultural growth

and the various methods recommended to increase production and productivity remain

ineffective insofar as the strict causalities between agricultural growth and population growth

are not determined in an alarming and recurrent context. It is imperative in a context of

sustainable food security, to study the causality between agricultural growth and rural

population growth on the one hand, and agricultural growth and active population growth on

the other hand. Is there a retroactive causality between agricultural growth and population

growth in the WAEMU space?

Do rural and active demographic surges in the WAEMU space have recurring impacts on the

causality between agricultural growth and demographic surge? What is the relationship

between population growth and agricultural growth in the WAEMU space? How does

demographic growth affect agricultural growth in the WAEMU region? How does the

demographic transition theory apply to the current trends observed in the WAEMU space?

What is the criterion for comparing the neo-Malthusian thesis considering population growth

as a major problem for humanity, and the thesis which considers population growth as a neutral

or even positive factor for agricultural growth? How would you assess the relative urgency of

demographic concerns in the WAEMU space? This article therefore answers these multiple

questions which are real solutions to remedy and to confirm or invalidate the neo-Malthusian

and anti-Malthusian theses.

THEORETICAL AND EMPIRICAL LITERATURE REVIEW

For twenty-five years, the literature on the subject has increased steadily, without it being clear

where it begins or where it ends. It is true that the issue is broad; that more and more scientific

disciplines are involved in it and that above all there is growing agreement on the

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interrelationships between demographic phenomena and agricultural growth. Population

growth affects the degradation of agricultural resources. In most cases, the relationship

between these two elements is centered on the major scientific “theories”. In this situation,

what are the predominant doctrinal positions in the major international development

agencies? What does scientific field research confirm or invalidate, in well-specified contexts

and societies? The problem is more complex than it first appears. A school debate perhaps, but

above all an ideological conflict based on a different vision of the world (fear of the South, for

example) and which could lead to opposing political priorities: one would be based on family

planning, the other on development. If the positions of each side were clearly affirmed in the

1960s and 1970s, they are relativized today, but the root of the problem remains. Thus, the

pure and hard neo-Malthusian model, with its leader, Malthus (1978) explains the negative

impact of population growth on agricultural production. This concept of Malthus (1978) has

been globally and “logically” extended to the environment. With the finite world assumption,

the earth's physical and biological limits are the ultimate constraints to population growth and

socio-economic change.

In other words, it is the increase in populations (in the South, since those in the North are almost

stagnating) that is at the origin of the problems, which is the threat of tomorrow for the whole

world. For Ramade (1987), the major catastrophe that affects humanity and from which stems

most of the evils from which it already suffers or which threatens it is of intrinsic origin: it

comes from its anarchic reproduction with the consequence of an exponential increase in the

number of 'men. The Brundtland Report (1988) is more nuanced: "Poverty is both the effect

and the cause of global environmental problems", emphasizing inequalities, the relationship

between economic development and the environment, the responsibility of political national

and global economic system even if "the population explosion is a threat". The recent report of

the South Commission (1990) recognizes that "the rapid growth of the countries of the South

accentuates the pressure on natural resources, to varying degrees, depending on the

availability of cultivable land and land tenure systems", but the demographic pressure is only

one of seven factors affecting the environment, the others being land tenure, the type of

agricultural development, economic pressure from the North, the imperative of

industrialization and growth, the adoption of consumption habits using a lot of energy and

finally the exodus of rural populations towards the north. "There is a compelling need for action

to moderate population growth...because, although it may not always be the ultimate cause of

poverty, it can radically undermine a country's ability to value its human capital. For Brown

(1986), the extension of the population leads to a reduction in cultivable land per inhabitant,

overexploitation of the soil leading to its erosion, to a drop in its productivity and to a reduction

in food production. As demand increases, supply decreases. With the addition of droughts, as

in the Sahel in 1973-1974 and 1983-1984, we can end up with famine and an increase in

mortality.

In this same perspective, Hogan (1991) shows that the ongoing desertification is not the direct

consequence of population growth; it is the product of climatic accidents occurring in societies

with strong social inequalities which remove any alternative to the peasants. Authors such as

Paul and Anne Ehrlich (1968) have constantly repeated since the end of the 1960s that

humanity runs the risk of a collision with the natural world with the growth of the human

population could outweigh all the benefits of economic growth and the progress of modern

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Adegnika, M. (2022). Causality Test on Panel Data: An Application to the Study of the Causality Between Agricultural Growth and Demographic

Burst in the Uemoa Area. European Journal of Applied Sciences, 10(3). 281-299.

URL: http://dx.doi.org/10.14738/aivp.103.12204

science, resulting in the general ruin and devastation of the Planet. This neo-Malthusian

perspective has attracted much attention and provided the starting point for contemporary

debate on population growth. For the anti-Malthusianism, from the ambient pessimism of the

two previous models into a kind of optimism: by simplifying, man has always shown himself

capable of facing external threats and problems as he did yesterday. He has a great capacity for

adaptation and innovation. The population is only a completely secondary, sometimes even

favorable factor; the real factors are elsewhere: poverty, inequalities, inadequacy of

technologies, agricultural policies (priority to cash crops), land ownership, urban bias, wars,

and political regimes.

It is a position recalling that there are other emergencies than just family planning; it is also a

position that can justify any policy of non-intervention in fertility matters. The extreme

populationist thesis, defended in particular by Simon (1981), according to which there is no

population problem, almost denying environmental problems. There is no need to fear a

shortage of resources, because the larger a population, the greater its capacity for invention and

technological innovation (of substitute products). Demographic growth in the Third World can

be a factor of economic development in the long term, even if it is recognized that in the short

term it is a constraint. According to Boserup's (1965, 1981) thesis on agricultural development,

population growth or pressure is a stimulus, or even a necessary precondition for progress in

agriculture. The increase in rural densities, the progressive scarcity of land in relation to the

population lead to a more intensive use of land, requiring more work, resulting in increases in

productivity and a general evolution of the structures of production and power. . In a way, the

equation is reversed: it is under (demographic) constraint that technological progress can

occur. This “anti-Malthusian” argument, recognizing a positive role for the population, is

perhaps suitable for Western history or temperate countries, but does not seem generalizable

to the whole of the contemporary world. For example, a study (Pingali et al, 1984) covering 52

areas in Africa showed the importance of soil quality, rainfall and financial resources to make

the investments required for crop intensification following population pressure. . On the other

hand, in some regions (Nicoll, 1984), rural density: has increased without any subsequent

intensification of cultivation. Simplifying, on the one hand, one sacrifices sustainability or the

long term for maximum and immediate profit and pleasure, on the other hand, one overexploits

available natural resources in order to survive.

However, it is important not to rush the reasoning, by attributing in a privileged way, to use the

terminology of Shaw (1989), to an immediate and aggravating factor (the growth of the

population) what comes from basic factors (economic model, poverty, North-South

inequalities) which will be difficult and long to change. Commoner (1988) relativized the

importance of the demographic factor. The evolution of pollution (in different forms) in the

United States between 1950 and 1970 is to be attributed first to the technology used, then only

to the increase in consumption per capita and to that of the population. In an analysis this time

focusing on 65 developing countries between 1970 and 1980 and on three types of production

(cars, electricity, fertilizers and pesticides), he also arrives at a similar result: the weight of

demography, even if it is not negligible, is two to three times less than that of the technology

used. There is no close correlation between population growth rate and environmental

degradation. In summary, the theory attributing to population growth a primordial role in the

quality of agricultural growth is not confirmed by these quantitative studies. Cruse (1994)

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Adegnika, M. (2022). Causality Test on Panel Data: An Application to the Study of the Causality Between Agricultural Growth and Demographic

Burst in the Uemoa Area. European Journal of Applied Sciences, 10(3). 281-299.

URL: http://dx.doi.org/10.14738/aivp.103.12204

increase in the index corruption are major bottlenecks. Vimard et al (2011) examine the

relationships between demography, economic growth and social development in Africa. They

explain the main lines of demographic dynamics and show the specificity of the continent in the

general panorama of demographic transitions on a global scale. The authors place the debates

on population and development policies in the African context. They then analyze the general

relationships in Africa between population growth and development, highlighting the

specificity of the Maghreb and the role of the improvement of human capital in demographic

changes. On this basis, they then propose three possible demo-economic trajectories in the

medium term. In conclusion, emphasis is placed on the need to give development policies a

regional specificity. Kevin (2011) points out that Population growth has a proven influence on

food availability in Africa. This impact can be all the more detrimental as the population of

Africa will reach the figure of 2 billion people in 2050. It also notifies that in the areas of West

Africa, East and of the center will experience a demographic growth of 20% per year. He further

pointed out that among the fastest growing countries in the world are 10 African countries.

Over the next four decades the poorest people in Africa will be in the rural world. This

demographic growth will have its impact on the use of natural resources. These natural

resources will be depleted leading to more constraints for food production. Amadou SY (2014)

shows that in Mali, population growth has no significant short-term positive impact on

economic growth; it even contributes to increased food insecurity. Population growth could

have significant positive effects on economic growth since the investments will have the effect

of stimulating the production of companies leading to the demand for additional labor and

therefore the acceleration of economic growth and reduction of unemployment.

The work of Luc et al (2019) explains that the need to reduce the birth rate has been put

forward as the only possible population policy to fight against poverty. They showed that

population growth has a negative effect on food security. Their work also uses that the increase

in population densities has resulted in a double process of intensification of agriculture and

continuation of extensive practices. Similarly, the work of Putri et al (2019) showed that

demographic pressure on certain land carrying capacities. They analyze the correlation

between land pressure and food sufficiency in West Kalimantan. Their results confirm that land

pressure in West Kalimantan is mostly classified as safe, except for the city of Pontianak whose

population pressure is the most among all cities so that land carrying capacity is classified as

low. Factors of demographic growth and main activities of certain regions which affect land use

and consequently the environment. Adam et al (2019) use a farm household simulation model

to show that the interplay between human population growth and crop yields presents

challenges for agricultural production and farm household incomes in sub-Saharan Africa. They

note that increasing yield potential from more efficient use of livestock manure is one approach

to improving agricultural production and incomes in the face of impending population

pressures.

Our results suggest that, even without taking climate change into account, expected changes in

population density and crop prices in 2050 mean that crop production and income per person

could fall by 21% from 2013 values. if return potential and return spreads remain constant.

However, agricultural production and income per person could increase in 2050 by 8%

compared to 2013 values if (1) growth rates of potential yield increase by 1.13% each year and

for pulses increase by at least 0.4% each year, and (2) farmers use livestock manure more

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efficiently. Our prospective approach aimed at considering agricultural production at the scale

of agricultural household’s complements large-scale analyzes of the production dimension of

food security. Similarly, recent work by Mamy et al (2020) has shown that population growth

implies needs for access to food and nutritional security, health, education and employment for

newcomers. Their results reveal the existence of population growth above the country's

average but unevenly distributed a gradual increase in the quantity of cereals (maize, millet and

sorghum) per inhabitant linked to a faster increase in agricultural production population and

significant progress in terms of physical access to health and education infrastructure. They

explain that population growth poses new challenges related to food security and nutrition.

Akpan et al (2021) examine the relationship between total agricultural land use and population

growth rate from 1961 to 2018 in Nigeria. Their results revealed that agricultural and arable

crops experienced an increase in the rate of 0.62% and 0.72%, respectively per year, while the

growth rate of the total population was at 2.57%. In addition, urban and rural populations grew

at a rate of 4.75% and 1.67%, respectively. Moreover, agriculture and arable land use rates had

a significant positive correlation. From they reveal that rural population growth is lower than

urban growth rate, implying that rural population is deteriorating with its likely negative effect

on agricultural labor.

ANALYSIS METHOD AND TOOLS

The approaches of the econometric literature concerning the tests of (none) causality on panel

data do not yet present a great diversity. Nevertheless, the literature provides some approaches

or methods to test causality between two or more variables. Among these approaches we have:

Granger (1969-1980), Konya (2006), Dumitrescu and Hurlin (2011), Haugh-Pierce (1976-

1977) and Sims (1972). The basis of Granger's definition is the dynamic relationship between

variables. As noted, it is stated in terms of improving the predictability of a variable. In Granger,

temporal succession is central and one cannot discuss causality without taking time into

consideration (Sekkat, 1989). Causality is introduced into econometric analysis by Wiener

(1956) and Granger (1969). Originally, we find the formalization of the notion of causality in

physics, in particular in the work of Isaac Newton on the driving force (cause) and the change

of movement (effect). In this case, the notion of causality translates a principle according to

which if a phenomenon is the cause of another phenomenon, called "effect", then the latter

cannot precede the cause. However, its conceptual definition goes back to the speeches of

Aristotle or David Hume. Transposed into economics, the notion of causality takes on a specific

technical connotation. Indeed, if one variable caused another variable, then necessarily the two

variables must be correlated. Conversely, it is not enough for two variables to be correlated for

it to have causality (correlation is not causality). In this work, we are interested in the non- causality tests of David and Colin (2003), Hurlin and Venet (2001), Konya (2006) and

Dumitrescu and Hurlin (2011). Indeed, we present an econometric study of (non) causality in

the sense of Granger (1969) in a heterogeneous panel, based on the approaches of Konya

(2006); Dumitrescu and Hurlin (2011). This approach is used to test the existence of a causal

relationship between agricultural growth (Agricultural GDP), demographic pressure (rural

population) and the active population in the 8 WAEMU member countries. Our work takes into

consideration the approach of Konya (2006) to test the (non) causality between these two

variables. Also, since it is important to do preliminary tests (specification test, selection of lags,

stationary test) before performing a causality test, we implement some of these tests associated

with panel data, which are different from those considered in the case of time series. With

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European Journal of Applied Sciences (EJAS) Vol. 10, Issue 3, June-2022

Services for Science and Education – United Kingdom

=

�.: �!,+,$ = 0 ∀� = 1,2 ... ... �, �. � �+,# �� ����� ��� �+,# ����� ������� (1969)

�!: �!,+,$ ≠ 0 ∀� = 1,2 ... ... �, �. � �+,# ����� �+,# ����� ������� (1969)

Data source and specification of variables

The data used in this article comes from the FAO. The most widely used were those of the United

Nations Population Division, the World Bank and DHS and MICS Measurement (for

Demographic and Health Surveys, and Multiple Indicator Cluster Surveys). These data range

from 1960 to 2015. They concern the demography at the center of development trajectories in

the eight WAEMU countries (Benin, Burkina-Faso, Côte d'Ivoire, Guinea-Bissau, Mali, Niger,

Senegal, and Togo). These data obtained make it possible to measure the extent of population

growth on the agricultural growth achieved in this area. But this analysis also makes it possible

to understand the extent of the efforts that remain to be made, in the agricultural sector, to

really achieve the optimal agricultural growth covered by the demographic projections of this

WAEMU space. The results of the various causality tests and discussion.

Preliminary tests

First, we use the procedure of Hsiao (1986) to test the panel structure (homogeneous or

heterogeneous) underlying the data. This procedure is based on a general drafting of the panel

template, as follows:

�+# = �+ + �+�+,# + �+,# � = 1,2 ... ... . �, �� � = 1,2, ... ... �

Where: �+ denotes a vector of individual effects of dimension N, �+ denotes a regression

parameter vector of dimension (K, 1), with K the number of rectifiers in the model. �+,# are

independently and identically distributed, such that, �4�+,#6 = 0 , �4�+,#

) 6 = �0

) ∀ � =

1, ... �.i=1,...N.

First, we test the hypothesis of the global homogeneity of the parameters, which is written as

follows:

The Global Homogeneity Hypothesis =

�.: � = �+ �� � = �+ ∀ � = 1,2 ... ... �,

�!: ∃ �+ ≠ �, 12 3( 4 3) ���� �,� = 1,2, ... ... �.

(4)

If we cannot reject the hypothesis of global homogeneity, the model considered is written as

follows:

�+# = � + �5

�+,# + �+,# � = 1,2 ... ... . �, �� � = 1,2, ... ... � (5)

On the other hand, in case of rejection of the null hypothesis, we seek the source of the

heterogeneity by carrying out a second test of the homogeneity, but this time only for the

regression parameters( �+), the hypothesis is then worded as follows:

The hypothesis of the homogeneity of the regression parameters

=

�.: � = �+ ∀ � = 1,2 ... ... �,

�!: ∃ �+ ≠ �, ��� �,� = 1,2, ... ... �.

(6)

Page 13 of 19

293

Adegnika, M. (2022). Causality Test on Panel Data: An Application to the Study of the Causality Between Agricultural Growth and Demographic

Burst in the Uemoa Area. European Journal of Applied Sciences, 10(3). 281-299.

URL: http://dx.doi.org/10.14738/aivp.103.12204

If we cannot reject the null hypothesis, the model this time can be written as follows:

�+# = �+ + �5

�+,# + �+,# � = 1,2 ... ... . �, ��� � = 1,2, ... ... � (7)

On the other hand, if we can reject the null hypothesis, we test the homogeneity of the individual

effects, by considering the following hypothesis:

The hypothesis of the homogeneity of the regression parameters

=

�.: � = �+ ∀ � = 1,2 ... ... �,

�!: ∃ �+ ≠ �, ��� �,� = 1,2, ... ... �.

(8)

If we cannot reject the null hypothesis, then the model is written as follows:

�+# = � + �5

�+,# + �+,# � = 1,2 ... ... . �, �� � = 1,2, ... ... � (9)

On the other hand, if we can still reject the null hypothesis, then the model is globally

heterogeneous. The application of this procedure to the data of our study indicates the

following results:

Table 1: Results of the homogeneity test

Types of tests Related Fisher statistics P value

H0: Homogeneity of individual effects and

regression parameters

8.20 0.00264

H0: Homogeneity of regression parameters 1614,85 0,00000

H0: Homogeneity of individual effects 65,0552 6,55426e-064

Source : Results of our 2021 estimates

Based on these results in Table 1, we can reject all null hypotheses of homogeneity, which tells

us that the panel model associated with the data is heterogeneous and in the form of an

individual effect model. As Konya (2006) in his approach considered a heterogeneous panel,

we continue to apply this approach. In this case, the SUR system (Seemingly Unrelated

Regression), for the approach of Konya (2006), can be written as follows from a trivariate

model with two lags

(10)

⎧ �������!,# = �6,!# +X �6,!,$�������!#7$ +X �6+,$������!#7$ + X �6+,$������+#7$ +

$()

$(!

�6,+#

$()

$(!

$()

$(!

�������8,# = �6,+# +X �6,8,$�������8#7$ +X �68,$������8#7$ +X �68,$������8#7$ +

$()

$(!

�6,8#

$()

$(!

$()

$(!

��

(11)

⎧ ������!,# = �9,+# +X �9,!,$�������!#7$ + X �9!,$������8#7$ +X �9,8,$������8#7$ +

$()

$(!

�9,8#

$()

$(!

$()

$(!

������8,# = �9,8# + X �9,8,$�������8#7$ + X �9,8,$������8#7$ + X �9,8,$������8#7$ +

$()

$(!

�9,8#

$()

$(!

$()

$(!

Page 15 of 19

295

Adegnika, M. (2022). Causality Test on Panel Data: An Application to the Study of the Causality Between Agricultural Growth and Demographic

Burst in the Uemoa Area. European Journal of Applied Sciences, 10(3). 281-299.

URL: http://dx.doi.org/10.14738/aivp.103.12204

According to the results of this table 3, all the variables of our panel are stationary in level, so

we can now pass to the test of (non) causality by applying the approach of Konya, (2006) as

developed above by the method OLS. This test developed in Konya (2006) to analyze the causal

link between exports and the GDP of 27 countries has had several applications among the

authors. This is how authors like Khalil (2014) applied this test to analyze the causal

relationship between financial development and economic growth in developing countries. For

the case of this article, this test is applied by estimating an individual fixed-effect model (by

country) with two lags on the three explanatory variables (agricultural GDP, rural population,

active population) and performing for each estimated model by country, a test of nullity of the

parameters of the causal variables. Initially, agricultural GDP is regressed as a function of the

explanatory variables (agricultural GDP, rural population, active population, with two lags) and

using a Wald statistic, we test the nullity of the parameters of the lagged rural population and

labor force variables. In a second step, we resume the process while taking as explained variable

the rural population variable. The results of these various tests are presented in the following

table:

Table 4: Hypothesis test of (no) causality of the population push towards agricultural growth

Ho: Population growth does not cause agricultural growth in the sense of Granger

Country Stat. du test p. critique

Benin 28,92 0,000***

Burkina Faso 19,55 0,0001***

Ivory Coast 5,37 0,0244**

Guinea-Bissau 4,20 0,0203 **

Mali 25,02 0,000 ***

Niger 15,91 0,0002 ***

Senegal 9,12 0,0039 ***

Togo 19,39 0,0001 ***

Source: Our analysis results; Note that ***, **, *, respectively indicate significance at the 1%,

5%, 10% thresholds

According to the results of the test of non-causality of the population push towards agricultural

growth, we note that we can reject the hypothesis of non-causality at the threshold of 1% for

countries such as Benin, Burkina-Faso, Mali, Niger, Senegal and Togo and at the 5% threshold

for the Ivory Coast and Guinea-Bissau. Consequently, the population growth has influenced

agricultural growth in the countries of the study area over the period from 1960 to 2015. This

result indicates a strong influence of population growth on agricultural growth in the countries

of the WAEMU zone. This phenomenon is represented by the following graph, below.

This graph shows us the dynamics of the evolution of agricultural GDP and population in each

of the 8 WAEMU member countries. An analysis of this graph shows that agricultural GDP and

the population measurement variables (rural population and active population) evolve in

almost the same direction, but it is surprising to see that agricultural GDP evolves at a faster

rate than that of other population variables. This result is truly paradoxical because it fiercely

contradicts the Malthusian theory. But it should be remembered that in the context of this

article, the population is represented by the rural population and the active population and not

the population as a whole.