THE EFFECTS OF GLOBALIZATION ON SOCIAL DEVELOPMENT OF FRANC ZONE’S COUNTRIES

Dongmo Tsobjio Franklin¹⁺ --- Ngouhouo Nji Ibrahim² --- Fomba Kamga Benjamin³

¹PhD Student, Faculty of Economics and Management, Department of Analysis and Economic Policy, University of Dschang, Cameroon.
²Professor, Faculty of Economics and Management, Department of Analysis and Economic Policy, University of Dschang, Cameroon.
³Professor, Faculty of Economics and Management, Department of Analysis and Economic Policy, University of Yaoundé II, Soa, Cameroon.

Keywords:Globalization, Franc zone, Unemployment rate, CEMAC Zone, UEMOA Zone.

JEL Classification: F60, F66, F69, E24.

ARTICLE HISTORY: Received: 10 March 2020, Revised: 13 April 2020, Accepted: 15 May 2020, Published: 4 June 2020

Contribution/Originality: This work aims to bring out the effects of economic and financial globalization on the unemployment rate evolution in the franc zone.

1. INTRODUCTION

The social development of all countries or groups of countries (economic zone or space) in the world depends on their economic and social policies, the implementation of such policies, their feasibility and their realism. But the trend of the world towards a global village thanks to the phenomenon of globalization which involves, a higher migratory phenomenon, the increase in international trade and the increase of the capital flow which influences the implementation of such policies. Globalization can thus not only be beneficial for populations, but also may be a source of inequality. The evolution of inequalities is considered to be an indicator of the structural effects of a lag between growth and social development because, even if there is a relationship between growth and poverty reduction, this correlation is not systematic (Guénard & Dubois, 2001).

Gross domestic product (GDP) per capita has long been used as the ultimate indicator for measuring well-being. But increasingly, other indicators are being put forward to capture social well-being. Recent scientific research integrates other social factors for measuring the social development of populations such as autonomy (reduction in the unemployment rate), equity, health and social cohesion (OECD, 2005). Since the GDP is the result of the total production of a country at a given time, there is a good chance that there is not a fair redistribution of income because we can witness a high concentration of income. This is why the economic policies of all the world countries aim to create more jobs in order to reduce the unemployment rate as much as possible, and finally improve the social level of individual households.

In this research, we will evaluate the level of social development by the level of the evolution of unemployment rate in the countries of the franc zone to show that the autonomy of the human being makes it possible to determine his level of social satisfaction. Thus, this research aims to examine the question of: What are the effects of economic and financial globalization on the social development in the countries of the franc zone. The purpose of this paper is to assess the effects of economic and financial globalization on the evolution of the unemployment rate in franc zone's countries. To conduct this study, we will first elaborate a literature review, then describe the methodology used to conduct this research, after we will present and discuss the results obtained and end our work of research.

2. LITERATURE REVIEW ON GLOBALIZATION AND SOCIAL DEVELOPMENT

2.1. Evolution of Theoretical Works

According to the World Bank, Social development focuses on the need to put people at the forefront of development processes. This has two main implications, namely improving the well-being and the quality of life of individuals; and bringing  social changes in norms and institutions, making development more equitable and inclusive for all members of society (Davis, 2004). For the Canadian government, "social development is about improving the well-being of everyone in society so that they can reach their full potential." Thus, our work will be more oriented towards the first dimension indicated above.

Understanding social development, in a context of globalization, implies knowing the operating mechanisms of economies and societies. If the aim of economic and financial globalization as defined is to allow and facilitate foreign investment through the deregulation of markets, then its direct consequence would be to increase the development of enterprises in the host country and improve the competitiveness of the economy. Thus, by indicating that globalization is certainly an instrument of economic development, Senarclens (2000) also thinks that globalization causes at the same time, a greater polarization in social relations; it makes national economies weak, even more vulnerable to capital movements. Rodríguez and Rodrik (1999) suggest by comparing the cost of World Trade Organization (WTO) membership for a country (about 150 million dollars per year) against the income from investments up to the same amount each year on the education of the population that, for developing countries, integration into the world economy should not be considered as always the best development policy. Despite the fact that globalization endangers the social models of countries by placing workers in competition at international level, they indicate that the sum of the goods made from globalization dominates the sum of misdeeds; which encourages international openness. In terms of international trade, Krugman (1995) explains by taking the case of the United States of America (USA) that the Added Value (AV) of this State is 2/3 made up of non-exportable goods and services, and that employment depends on short term of solvent demand and long-term structural factors such as technical progress and productivity. According to Ayoub (1998) unhindered international trade is a source of long-term factor price convergence. Thus, an increase of trade between developed countries and countries on their ways to be developed should logically provoke, in the long term, an increase of the remuneration of labor in the latter and a relative fall in the industrialized countries, leading at the same time, the convergence of incomes between states (Held, McGrew, Goldblatt, & Perraton, 1999).

According to Huwart and Verdier (2012) many have benefited from economic dynamism and job creation from international trade, the diffusion of technology, skills and knowledge at a sustained pace because the opening of borders to trade is nevertheless advanced with the growth of the middle classes across the planet, despite the fact that globalization sometimes accentuates inequalities. This is why, for Bolduc and Ayoub (2000) a large part of the population believes that globalization rhymes with job losses, exploitation of workers by large companies and rising inequalities.

However, Krugman (1998) denounces the idea that globalization leads an increase of inequalities. For him, "globalization is not guilty" as much as it shows that we must not see in globalization the origin of mass unemployment. Unemployment depends on growth, which is directly influenced by interest rates and innovation. But he nuances his position by showing, of course, that technical progress will first of all have an impact on less qualified jobs with the consequence of increasing inequalities; secondly, the accelerated development of technical progress risks negatively impacting skilled jobs because of the ability of machines, in particular the computer, to perform complex tasks and could thus replace executives in companies. He believes that technical progress, the engine of the spread and popularization of globalization, is an advantage for skilled workers, since it considerably increases the productivity of skilled workers at the expense of unskilled workers.

2.2. Evolution of the Empirical Work of Globalization on Social Development

For Plihon (2013) globalization covers a wide variety of processes. Firstly, it corresponds to the opening of national economies to international transactions and the development of exchanges of goods and services (international dimension) and, secondly, to the international mobility of factors' production, and more particularly capital, which is referred to as financial globalization. The most important vector of this movement is constituted by the international movements of capital, and in particular by foreign direct investments (FDI), carried out by multinational firms. Van Huffel (2001) in his study on the problems and challenges of FDI in the countries of the South and East of the Mediterranean, he shows that the expected positive effects of the multinational firms on the economies of the host countries take into account policies and strategies adopted by them. For him, the benefits of FDI relate to the creation of employment, the growth of the domestic supply, the transfer of technology and the improvement of the balance of payments.

While Mottaleb and Sonobe (2011) show at the end of a study carried out in Bangladesh that the level of employees education and the performance of companies are closely linked; Borensztein, De Gregorio, and Lee (1998) and Feldstein (2000) shows that the gains provided by FDI to developing countries lie in the transfer of technology under the form of new types of fixed capital inputs and contribute to the development of human resources. Thus, as the World Bank cites, FDI helps create jobs in all sectors and allows the host country to reduce the unemployment rate (Klein, Aaron, & Hadjimichael, 2001). But, Kabaka (2012) drawing inspiration from Laïdi (2000) establishes in a study on, the impact of globalization on unemployment in France: study of the relocation of firms, that globalization negatively influences employment in France because it is the source of mass unemployment, which unemployment is due to relocations which are controlled by the concern for profitability and lower labor costs borne by companies. Similarly, Fitoussi (1997) shows in his research that financial globalization increases structural inequalities because unemployment and poverty increase among rich countries among workers without or low skills, while the latter see their lot improved in emerging countries. Dynamic inequality increases in rich countries and decreases in emerging countries.

Hugon has also shown at the end of his work that trade liberalization associated with high interest rates increases unemployment and poverty, that liberalization of financial markets are not associated with appropriate regulation increases economic instability or Privatization without stimulating competition and without monitoring abuses of monopoly power can lead to higher prices (Sapir, 2002). But Terfous (2006) has shown that the intensification of globalization has enabled the rise of countries like China and a reduction of poverty in developing countries; while at the same time, the low-skilled labor force of the industrialized countries is competing with that of the developing countries, one notes in the developed countries a deterioration of the relative situation of the low-skilled workers, which has manifested itself by more unemployment or a rise in wage inequality. Globalization is therefore often held responsible for social plans and layoffs, rising unemployment and inequality.

However, Small and Soete (1999) show that the economies forming part of the Triad benefit much more from globalization than the underdeveloped countries which remain on the fringes of the massive flows of all kinds which characterize globalization. Thus, even as combined with technology, globalization has certainly countered the problem of scarcity, but it has not managed to distribute wealth rationally and equitably (Valaskakis, 1999). Also, the International Monetary Fund (IMF) economists, in particular (Furceri & Loungani, 2015) by conducting a study on financial globalization and inequalities, manage to conclude that any country which opens its economy to global finance will see its social inequalities increase.

Liberalization of capital movements is generally more beneficial and less risky if countries have reached certain levels or thresholds of financial and institutional development. This is why Cartapanis and Artus (2008) estimate that the process of globalization can be accompanied by a resumption of financial instability and even stimulate the triggering of exchange or financial crises, but they associate these instabilities with an application too fast or insufficiently mastered the liberalization of financial markets on a planetary scale and insists that this would not put back its advantages in terms of growth. For Nicolas (2001) the responsibility for the crisis therefore partly stems from the inability of developing economies to cope with the constraints imposed by globalization. For example, according to Huwart and Verdier (2012) African countries that practice mono-export of raw materials with oil are at the mercy of falling prices and are exposed to unstable incomes. It is therefore appropriate to proceed with liberalization gradually so as not only to try to measure the risks, but also to seek to control the crises which are the source of instability.

In the literature, we found that social development has been studied by using more indicators such as GDP per capita, life expectancy at birth, education, health and coming out the social inequalities. There are many indicators that contribute to social development. The promotion of each indicator of social development is ensured by financial resources both at the macroeconomic and microeconomic level; hence the place of choice occupied by the distribution of income to the population because when the economic agents are unemployed, they can neither afford quality training nor treat themselves adequately, nor eat adequately, in short they cannot not ensure their well-being. The vast majority of poor and developing countries have high job insecurity and still high unemployment. Noting this void in the literature, we conducted this research using the unemployment rate as an effective measure of social development. There is also a debate about the effects of globalization on the evolution of the social level in developed and developing countries. It is in this sense that (Krugman, 1995) showed that, one of the causes of reduction of employment is in the technological changes, and not the international trade, which are at the base of the changes in the world of work, this is because they reduce the demand for the least qualified workforce in all spheres of the economy.

3. RESEARCH METHODOLOGY

3.1. Data Collection Method

The data used in this work are from secondary sources. They are collected in the World Bank (WB) database. Because the data used come from the databases of franc zone countries, and whose realities or economic conditions on the structural level is not identical from one country to another, leads us to recommend the application of a panel data analysis in this research.

3.2. Presentation of the Model: the Choice of Variables

Our study will be done using panel data analysis with a log-type linear regression model. Indeed, the panel data have a two-dimensional character: a spatial dimension because the population studied is not located in the same geographic space (or individual dimension), and a temporal dimension because the observations are made over time. The model uses a set of 6 exogenous variables which make it possible to capture the social development which is the dependent variable in this work. Social development will be measured by the unemployment rate (Z). The exogenous variables consist of: foreign direct investment (FDI), Money supply (MS), External debt (ED), Trade balance (TB), investment rate (IR), prices index (PI).

3.3. Choice and Specification of the Model

The study will be done using panel data analysis. Indeed, in panel data models, it is often interesting to identify the effect associated with each individual (an effect which does not vary over time, but which varies from one individual to another). This effect can be fixed or random. Building of research already done on the relationship between financial integration or globalization and an economic magnitude, such as those of Mankiw, Romer, and Weil (1992); Akilou (2006) and Cordella, Ricci, and Arranz (2005) the theoretical econometric model used is specified as follows:

Where Zi,t is the explained variable representing the unemployment rate.

The matrix of explanatory variables is made up of the 6 variables retained (IR, MS, ED, TB, PI and FDI) which explain the value that Zi,t and β take to measure the effect of its variables. i = {1, ..., N} is the number of individuals in the sample and t = {1, ..., T} represents the periods in which the data were observed.

This model specified in panel, and by expressing the variables in logarithm, will be presented in the following form:

Log (Zit) = αi + δ1IRit + δ2MSit + δ3EDit + δ4TBit + δ5PIit + δ6FDIit + µi+ Ɛit

This panel provides information on the socio-economic behavior of countries in two currency areas over time. The panel brings together fourteen countries. The data were collected over 22 years from 1991 to 2013. The data panel is highly balanced, which leads to a good analysis concerning the countries of two monetary zones. The regressions will be made at the global level with all the countries of the franc zone on the one hand and at the level of the Central African Economic and Monetary Community (CEMAC) zone and the West African Economic and Monetary Union (UEMOA) zone on the other hand.

3.4. Statistical Tests

As part of this work, we will do several statistical tests. We are going to proceed to Hausman's specification tests. It is a specification test which determines whether the coefficients of the two estimates (fixed and random) are statistically different. When the probability of this test is lower than the selected threshold, the fixed effects model is preferred. Otherwise, we use the random effects model and in this case the generalized least square (GLS) method is adopted. Then we will do the stationarity tests of variables in the model (unit roots test) for the countries of the franc zone using the Im-Pesaran-Shin tests over 1991-2013 estimation periods. The choice of the chosen model is made from the results presented following this work in Table 1.

4. PRESENTATION OF RESULTS

4.1. Results of Test for the Choice of the Suitable Model

The tests were carried out using STATA software. The statistics of the panel models include three variations or three models. The test results obtained from the three models are listed in the Table 1.

Table-1. Test results of the three regression models.

	Naïve model	Fixed effect model	Random effect model
P-value	0.0000	0.9798	0.9800
R2	0.2422	0.0038	0.0661

The values ​​of P-value show that of these three models, it is the naive or simple regression that guides the choice of the final model because its P-value is zero (P-value = 0.0000). Thus, the adequate model to retain in the modeling of this research is the naive or simple model.

4.2. The Stationarity Tests of Variables: Im-Pesaran-Shin Tests

The stationarity test used in this work is the Im-Pesaran-Shin (IPS) test carried out with the STATA software. The results of this test are collated in the Table 2.

Table-2. Results of overall stationarity test of the variables.

Variable	Significance: P-value	Results
Unemployment rate (Z)	0.0000	Stationary
Investment rate (IR)	0.0000	Stationary
Money supply (MS)	0.0211	Stationary in trend
External debts (ED)	0.0274	Stationary
Trade balance (TB)	0.0000	Stationary in trend
Price index (PI)	0.0000	Stationary
Foreign direct investment (FDI)	0.0001	Stationary

The Im-Pesaran-Shin (IPS) tests carried out with the STATA software and presented in Table 2 show that the stationarity of all variables.

4.3. Results of Model Estimation

These are the results taken as a whole without specifying the economic area. The specific analyzes by zone will be done further after this presentation and the analysis of results at global level.

Table-3. Model results of unemployment rate estimation.

Linear regression					Number of obs    =      318
					P(6, 311)               =      9.43
					prob   >    F           =      0.0000
					R-squared             =      0.2422
					Root MSE              =      3.7244
Unemployment rate	Coef.	Robust Std. Rerr.	t	P  >  |t|	[95% Conf.    Interval]
IR	.06035	.0209146	2.89	0.004	.0191981	.1015019
MS	.018837	.0221714	0.85	0.396	.-.024788	.062462
ED	.0110789	.0021136	5.24	0.000	.0069202	.0152376
TB	.0017837	.0003855	4.63	0.000	.0010251	.0025423
PI	-.0483841	.0388757	-1.24	0.214	-.1248767	.0281085
FDI	-.0406191	.0205314	-1.98	0.049	-.0810171	-.0002211
_cons	4.17347	.7151776	5.84	0.000	2.766271	5.580668

Note: The level of significance used is 5%.

4.4. Economic Interpretation of Variables and Discussions

These results in Table 3 generally show the effects of each independent variable on the unemployment rate. These results are not globally all those expected except those of the FDI variable. Then we have the following relationships:

4.4.1. Unemployment Rate and Investment Rate

It appears from the results obtained Table 3 that the investment rate positively and significantly influences the unemployment rate throughout the franc zone. This means that increasing the domestic investment rate in the countries of the franc zone by one, increases the unemployment rate by 0.06.

This result is contrary to that expected as much as one of the consequences of the investment is job creation; and the creation of employment contributes to the fall of unemployment rate and not to its increase. However, this last correlation is only true if the number of jobs (employment rate) created by domestic investment changes more than in proportion to the number of unemployed per year, because the job market is very dynamic with new applicants of work that enter each year to add to those who were already looking for work. Thus, investments would not always favor the reduction of unemployment rate because they do not always absorb enough unemployed people since the number is constantly increasing with on the one hand, new job seekers especially in a context of training-job mismatch and of underdevelopment, and secondly those who lose their previous jobs at the same time.

4.4.2. Money Supply and Unemployment Rate

The money supply is the data which makes it possible to apprehend the effects of monetary policy starting from the money supply or quite simply from the policy of "Open Market". The results Table 3 of this work show that the money supply has a positive and insignificant effect on the unemployment rate in the franc zone. This reflects a negative effect of monetary policy on the evolution of unemployment rate because the variation (fluctuations in the money supply in all the countries of the franc zone with a tendency to the stability of the money supply in all these countries) of money supply contributes to the increase of unemployment rate. It can thus be concluded that a restrictive policy of the money supply does not favor the improvement of unemployment rate in the franc zone.

In the literature, research results [for example those found by Romer (1986); King (2000) and Ekobena (2013) relating monetary policy to economic growth are divergent because we find negative and positive relations between the money supply and economic growth. Thus, the negative influence of monetary policy on economic growth does not favor in a development perspective the reduction of unemployment rate because the fall of level of growth does not lead to stagnation of employment and more to a fall of employment if the stunting continues in the medium and long term.

4.4.3. Externaldebts and Unemployment Rate

External debts positively and significantly influence the level of unemployment in the franc zone. This result of Table 3, allows us to note that not only the countries of the franc zone do not control their indebtedness but also the debts contracted do not seem to be invested in the real economy so as to positively impact economic growth; for example through the injection of these debts into investments which have direct consequences: the creation of direct and indirect jobs, the improvement of the living standards of the populations. The increase of unemployment rate through external debts leads us to conclude that the countries of the franc zone do not seem to optimize their external debts by investing in the productive sectors which really stimulate employment; thus these debts do not seem sustainable.

This result is supported by the results of the work of Niang (2018) which show in a study of the impact of public debt on investment in Niger, that indebtedness acts negatively on both total investment and on the rate of private investment. In the short term, its impact is significant only in the case of private investment. In the long term when the public debt or publicly guaranteed debt ratio increases by 1%, the total investment rate drops by 0.15%. They concluded that there was a heavy debt burden which reduced the country's incentive to invest. The reduction in the incentive for investment slowed down and blocked the creation of employment and therefore led to a stagnation of employment and above all an increase of unemployment rate.

4.4.4. Trade Balance and Unemployment Rate

The opening up of trade between countries enables the economy to be boosted through trade (imports-exports). Foreign trade can positively or negatively affect the economic growth of countries. The result Table 3 of our work shows that the trade balance has a positive and significant influence on the unemployment rate in the franc zone. This reflects the fact that foreign trade increases the unemployment rate in French-speaking Africa, especially in the franc zone instead of contributing to its decline as we would have liked. In foreign trade, exports have a greater influence on the national economy as a whole than imports. But for exports to be competitive there must be a deep industrialization of the economy and specialization in order to allow the production in large quantities of products intended for export to compete with imports and avoid the deficit of the trade balance; industrialization will increase demand for both skilled and unskilled labor.

In a perspective of the economy industrialization, the productivity gainsinfluence the level of employment. The acceleration of productivity gains brought about by trade mainly affects industry, which is much more open to trade than services. It therefore favors the spilling of jobs from industry to services. As the average skill level of the workforce is higher in services, this contributes to the increase the average skill level of labor demand in the economy. This effect is addition to the direct impact of trade on qualification within each industrial sector. When the labor supply does not adapt sufficiently, this results is none fitly between the skills offered and demanded; and therefore an increase of structural unemployment rate (Cortes & Jean, 1997). Thus, it is certain that the globalization of economies through trade opening is not without consequence on employment: in a context of successful industrialization with a good policy of specialization in export products, the opening trade cannot be a source of poverty or ill-being and therefore an increase of economic and social inequalities; so in a context of weak industrialization and above all of dependence on imports of most products of all kinds, this can contribute to the increase of poverty of populations and social inequalities. This result can be justified here because the policy of countries colonized by France, particularly in Black Africa, remains essentially turned towards imports because of the neocolonialism which appeared to aftermath of independence. The economies countries of the Franc zone remain very little industrialized and draw most of their products from abroad, which worsens the deficit of trade balance implying not only the loss of foreign currencies but also a difficult access to products with the permanent risks of disruption and price increase. The price index (PI) also has a negative impact on the unemployment rate.

4.4.5. Foreign Direct Investment and Unemployment Rate

The results Table 3 of this work show that foreign direct investment (FDI) has a negative and significant effect on the unemployment rate. An increase of one FDI leads to a decrease of unemployment rate of 0.040 times. This result can be explained by the attraction of FDI by developing countries because the investment opportunities are numerous; thus FDI constitutes a factor which is at the heart of the world economy with the mobility of capital; they are means of external financing which encourage the circulation of foreign capital through direct investments in the economy of host country. FDI are at the same time, the catalyst and the vector of transfers of technology, wealth, knowledge (education and training) etc. from one country to another. As a catalyst and vector for transmitting a certain number of factors, FDI contributes to encouraging growth in the beneficiary countries, with the consequence of increasing the level of development of countries concerned and therefore improving social conditions of populations. Thus, it appears that FDI has a leverage effect on the social development of host country. Our results coincide with most of results found in the literature; which show a positive link between FDI and reduced unemployment.

A study carried out in the United States of America on FDI outflows and taken up by Anima (2010) shows that "between 1977 and 1997, the share of production by United States parent companies fell from 65 to 55 % and their share of jobs fell from 60 to 46%. Subsidiaries of foreign companies in the United States recovered most of this reduction in production (from 3.5 to 12.5%) and jobs (from 3 to 12%). One part was obviously relocated, through a subsidiary abroad or outsourcing to third parties”. Thus, it seems to appear that there is a loss of jobs in the countries of departure of FDI and a creation of employment in the host country. Similarly, Anima (2010) notes in its study that FDI creates few direct jobs; it therefore shows that host countries must optimize the indirect effects of FDI, in particular in terms of job creation among clients, suppliers and partners of the investor. However, the majority of research on FDI, especially that of Klein et al. (2001) and Jalilian and Weiss (2002) find that FDI has a positive impact on economic growth; with growth which has a positive impact on poverty reduction. Mainguy (2004) finds the same result when he shows that in Asia, it seems that rapid growth has been associated with a reduction of poverty thanks to the rise of level of employment and therefore the reduction of unemployment and the development of social infrastructure (education, health, etc.). It shows that in Vietnam, poverty fell from 58 to 37% between 1993 and 1998.

FDI is also carried out through the establishment of multinational firms, the direct consequence of which is the creation of direct and indirect jobs. These are companies which in terms of remuneration ensure good social treatment of employees. Similarly, Velde and Morrissey (2001) show that multinational firms pay workers better, who are generally more skilled, but they create few unskilled jobs other than in textiles and are therefore unlikely to directly reduce poverty. Such conclusion lowers the positive impact of the establishment of multinational firms. But this conclusion of Velde and Morrissey seems to us limited as much as beyond the direct jobs which are better remunerated (the remuneration being the crucial element of development or social well-being), they lead to numerous indirect jobs without forgetting the lack of unskilled employment and calls for the formation of better human capital.

From our various results and from those found in the economic literature, it appears that FDI allows a favorable effect on the social development of countries in general and countries of the Franc zone in particular; because in all cases, FDI contributes to the reduction of  level of unemployment through the creation of direct and indirect jobs.

5. THE EFFECTS OF ECONOMIC AND FINANCIAL GLOBALIZATION ON THE EVOLUTION OF UNEMPLOYMENT RATE: COMPARATIVE ANALYSIS BETWEEN CEMAC AND UEMOA ZONES

In a context of economies globalization, the divergences of economic and social characteristics between two zones which form the franc zone militate with the need for a comparative analysis within the framework of this study in order to observe the evolution of unemployment rate of each area. After the statistical tests presented above, the regressions were made in each zone.

5.1. Case of the CEMAC Zone

In the CEMAC Zone, the study of the stationarity test of independent variables shows that all the variables were found to be stationary without trend and with trend. The choice of the final model to be used depends on the characteristics of three models tested. On the basis of the p-values ​​of simple model (P-Value = 0.0000), of fixed effects model (P- value = 0.4748) and of random effects model (P-value = 0.0000), we cannot conclude from the model to remember. This leads us to two tests of Breusch-Pagan and Hausman. The results ofHausman test show that the p-value = -58.15; which leads to the conclusion that there are fixed effects (we accept H1). But we note that in the fixed effect model, the p-value = 0.4748 is greater than 0. The model used here is therefore the simple model.

The results of this regression model are presented in the Table 4:

Table-4. Results of the evolution of unemployment rate in the CEMAC Zone.

Regess unemployment rate IR MS ED TB PI FDI in 1/138
Source	Ss	df	MS		Number of obs     =      135
Model	821.64028	6	136.940047		P(6, 128)              =      7.74
Residual	2264.10178	128	17.6882952		prob   >    F         =    0.0000
Total	3085.74206	134	23.0279258		R-squared            =    0.2663
					Adj R-squared     =    0.2319
					Root MSE            =    4.2057
Unemployment rate	Coef.	Std. Rerr.	t	P  >  |t|		[95% Conf.    Interval]
IR	.0250689	.0302544	0.83	0.409		.-.0347946	.0849325
MS	.2023752	.0735201	2.75	0.007		.0569031	.3478472
ED	.0177168	.0048509	3.65	0.000		.0081186	.0273151
TB	.0016073	.0003109	5.17	0.000		.0009922	.0022224
PI	-.0374811	.0473102	-0.79	0.430		-.1310924	.0561303
FDI	-.0280014	.0287618	-0.97	0.332		-.0849115	.0289087
_cons	2.726012	1.538706	1.77	0.079		-.3185803	5.770604

5.2. Case of the UEMOA Zone

Analysis of the stationarity test of the variables in the UEMOA Zone reveals that the variables are stationary. From the P-values ​​of simple models (0.0000), of fixed effects model (0.2165) and of random effects model (0.2858); the simple model seems the best. However, the probability of the Breusch-Pagan test is 0, which means that we accept the hypothesis of the presence of a random effect. However, Hausman's specification test (p-value = -3.55) allows us to reject the hypothesis H0 of presence of the random effect. But the probability of the fixed effects model is 0.2165, therefore greater than 0. Thus the model chosen is the simple model.

The regression results of this model are presented in the Table 5.

Table-5. Results of the evolution of unemployment rate in the UEMOA Zone.

Regess unemployment rate IR MS ED TB PI FDI in 139/322
Source	ss	df	MS		Number of obs     =      183
Model	292.952841	6	48.8254734		P(6, 176)              =      5.75
Residual	1494.27891	176	8.4902211		prob   >    F         =      0.0000
Total	1787.23175	182	9.8199547		R-squared            =      0.1639
					Adj R-squared     =      0.1354
					Root MSE           =      2.9138
Unemployment rate	Coef.	Std. Rerr.	t	P  >  |t|	[95% Conf.    Interval]
IR	.0352615	.0414914	0.85	0.397	.-.0466231	.1171462
MS	.0900768	.0269721	3.34	0.001	.0368464	.1433072
ED	.0082064	.0025758	3.19	0.002	.0031229	.0132899
TB	.0012992	.0004346	2.99	0.003	.0004415	.002157
PI	-.0526429	.0418227	.-.1.26	0.210	-.1351815	.0298957
FDI	.042083	.0935244	0.45	.0653	-.1424907	.2266567
_cons	2.066319	.9907732	2.09	0.038	.1109936	4.021644

5.3. Interpretation of the Results of the Comparative Analysis of the Effects of Economic and Financial Globalization on the Evolution of the Unemployment Rate between the CEMAC and UEMOA Zones

On the basis of the variables used in this work, the study of the effects of globalization on the unemployment rate in the different areas taken individually makes it possible to note differences and similarities.

This comparative analysis Table 4; Table 5 shows that IR has a positive influence in both the CEMAC and UEMOA zones on the unemployment rate; as well as the price index (PI) shows a negative influence on the unemployment rate in the two zones. Furthermore, the variables MS, ED and TB have positive and all significant effects at the threshold of 1% on the level of unemployment in the two zones; which means that monetary, debt, trade and investment policies must be restructured in order to make them socially beneficial in the Franc zone because, in their current state, they seem to curb the social development of each area. Compared to the results of global model, the effects seem to be the same except for those of the variables IR and MS which in the global model had respectively a positive and significant impact on the one hand, and a positive influence on the other hand.

However, it appears from this same analysis that the impact of FDI on the unemployment rate is positive and not significant in the UEMOA Zone, but negative and not significant in the CEMAC Zone; which shows that in taking both zones in isolation, FDI could not significantly destroy jobs in the UEMOA Zone, while they do not significantly reduce the unemployment rate in the CEMAC Zone. Otherwise, the global regression without distinction of economic zone Table 3, shows us a negative and significant relationship between the unemployment rate and FDI. It is clear that a single governance policy or the complete integration of the two spaces would allow better administration and a convergence of economic and social policies. Thus, overall, FDI contributes to the reduction of the unemployment rate in the countries of the Franc Zone.

Appreciating these results of the comparative analysis between the CEMAC and UEMOA Zones compared to some of our research on the effects of globalization on economic growth in the franc zone, it follows that the effects of globalization on growth economic seem to continue on the social level in particular on the evolution of unemployment rate with some exceptions. Indeed, our results show that external debt, the trade balance and monetary policy negatively influence economic growth in both the CEMAC and UEMOA Zones; which calls the leaders of these economic zones to review the policies and strategies to be deployed in order to reverse this trend. This revision of economic policies is necessary and essential since the repercussions are also perceived at the level of social development because they contribute to the increase the level of unemployment in these economic and monetary spaces.

6. CONCLUSION

Social development can be understood by several types of variables. In this work, because the autonomy (employment) of each individual is an objective sought by all populations and above all an economic policy objective of any State, we have used in this work the unemployment rate to measure the level of social development in the countries of the franc zone.

The econometric analysis in panel data was made on the basis of the globalization variables which were retained. After the results of the statistical tests which made it possible to choose the simple or naive model for the regression at the level of all countries of the franc zone, the result obtained at this overall level shows that foreign direct investment (FDI) has a negative influence and significantly the unemployment rate; just as the price index negatively influences the unemployment rate. These results indicate that FDI contributes to lowering the unemployment rate in all the countries of the franc zone. The trade balance, external debts and the investment rate have a positive and significant effect on the unemployment rate, while the money supply has a positive and not significant appearance on the unemployment rate. Thus, these variables participate in increasing the unemployment rate in the franc zone.

The comparative analysis between the CEMAC and UEMOA Zones using a simple or naïve regression model made it possible to identify the divergences and convergences of results between these two zones taken separately. We noted that in the case of CEMAC, the FDI and PI variables had a negative appearance on the unemployment rate and the other variables had a positive and significant effect on the unemployment rate outside the variable IR. In the UEMOA Zone, only the variable IP negatively influenced the unemployment rate and the other variables had a positive and significant effect on the unemployment rate except the variables FDI and IR which do not have significant effects.

Funding: This study received no specific financial support.

Competing Interests: The authors declare that they have no competing interests.

Acknowledgement: All authors contributed equally to the conception and design of the study.

REFERENCES

Akilou, A. (2006). Trade liberalization and economic growth in the countries of the West African economic and monetary union. Paper presented at the Communication-9th Annual Conference on Global Economic Analysis. Ethiopia.

Anima. (2010). The impact of FDI on the economic development of countries. State of the art and application to the MED region. ANIMA Investment Network, Concept Note. Working paper /22/12/2010. France. Retrieved from: http://www.animaweb.org/sites/default/files/ain_impactide-d_veloppement_22-12-2010.pdf .

Ayoub, A. (1998). Liberalization of energy markets: Utopia, theories and pragmatism. Energy Review, 499, 477-484.

Bolduc, D., & Ayoub, G. A. (2000). Globalization and its effects: Review of the literature: The National Documentation Center (NDC) (pp. 109). Canada: Laval-Quebec University.

Borensztein, E., De Gregorio, J., & Lee, J. W. (1998). How does foreign direct investment affect economic growth? Journal of International Economics, 45(1), 115-135.Available at: https://doi.org/10.1016/S0022-1996(97)00033-0.

Cartapanis, A., & Artus, P. (2008). Financial globalization and growth in emerging economies: The underestimation of the induced macroeconomic constraints. Economic Review, 59(6), 1145-1158.

Cordella, T., Ricci, A., & Arranz, R. (2005). Debt overhang or debt irrelevance? Revisiting the debt-growth link. IMF Working Paper, No. WP/05/223. Washington, DC: International Monetary Fund.

Cortes, O., & Jean, S. (1997). What is the impact of foreign trade on productivity and employment? A comparative analysis of the cases of France, Germany and the United States. CEPII, Study Document No. 97-08.

Davis, G. (2004). A history of the social development network in The World Bank, 1973- 2002. Social Protection Discussion Paper Series; No. 56. Washington, DC: World Bank.

Ekobena, F. S. Y. (2013). Monetary policy and economic growth in the CEMAC zone: A panel data approach. Munich Personal RePEc Archive. MPRA Paper No. 40923.

Feldstein, M. (2000). Aspects of global economic integration: Outlook for the future. NBER Working Paper No. 7899. Cambridge: National Bureau of Economic Research.

Fitoussi, J. P. (1997). Globalization leaves us no choice: Globalization and inequalities. In Confiscated Thought (pp. 238-254). Paris: The Discovery.

Furceri, D., & Loungani, P. (2015). Capital account liberalization and inequality. IMF Working Paper No. 15/243. Washington, DC: International Monetary Fund.

Guénard, C., & Dubois, J. L. (2001). Inequalities, growth and poverty in Sub-Saharan Africa (pp. 41-56). Paris: IRD; Karthala.

Held, D., McGrew, G., Goldblatt, D., & Perraton, J. (1999). Global transformations: Politics, economics and culture, political studies association yearbook series (pp. 14-24). London: Palgrave Macmillan.

Huwart, J.-Y., & Verdier, L. (2012). Economic globalization: Origins and consequences, OECD Essentials, OECD Publishing. Retrieved from: http://dx.doi.org/10.1787/9789264111929-fr .

Jalilian, H., & Weiss, J. (2002). Foreign direct investment and poverty in the ASEAN region. ASEAN Economic Bulletin, 19(3), 231-254.Available at: https://doi.org/10.1355/ae19-3a.

Kabaka, I. P. (2012). Impact of globalization on unemployment in France: Study of industrial offshoring. Retrieved from: https://hal.archives-ouvertes.fr/hal-01257206.

King, R. G. (2000). The new IS-LM model: Language, logic, and limits. FRB Richmond Economic Quarterly, 86(3), 45-104.

Klein, M., Aaron, C., & Hadjimichael, B. (2001). Foreign direct investment and poverty reduction: Policy research working papers (Vol. 44): The Worlk Bank eLibrary. Available at: https://doi.org/10.1596/1813-9450-2613.

Krugman, P. (1995). Unemployed Europe, penniless America. Futuribles Review, 201(2), 58.

Krugman, P. (1998). Globalization is not guilty (Vol. 228). Paris: The Discovery.

Laïdi, Z. (2000). Globalization as a phenomenology of the world. Revue Projet, 262, 41-48.

Mainguy, C. (2004). The impact of foreign direct investment on developing economies. Regional and Development Review, 20, 67-89.

Mankiw, N. G., Romer, D., & Weil, D. N. (1992). A contribution to the empirics of economic growth. The Quaterly Journal of Economics, 107(2), 407-437.Available at: https://doi.org/10.2307/2118477.

Mottaleb, K. A., & Sonobe, T. (2011). An inquiry into the rapid growth of the garment industry in Bangladesh. Economic Development and Cultural Change, 60(1), 67-89.Available at: https://doi.org/10.1086/661218.

Niang, B. B. (2018). Public debt sustainability, in: The race to the next income border: How Senegal and other low-income countries can cross the finish line. International Monetary Fund. IMF eLibrary. 183-194. Available at: http://dx.doi.org/110.5089/9781484373606.9781484373071 .

Nicolas, F. (2001). Developing countries facing globalization. Paris: RAMSES, Dunod.

OECD. (2005). Improving everyone's chances for an active social policy for the benefit of all. Paris: Editions OCDE.

Plihon, D. (2013). Financial globalization. In: The challenges of globalization: The great economic and social questions III (pp. 23-40). Paris: Discovery.

Rodríguez, F., & Rodrik, D. (1999). Trade policy and economic growth: A Skeptic’s guide to the cross-national literature. NBER/Macroeconomics Annual. NBER Working Paper n° 7081, 15(1), 261-325.

Romer, C. (1986). Spurious volatility in historical unemployment data. Journal of Political Economy, 94(1), 1-37.Available at: https://doi.org/10.1086/261361.

Sapir, J. (2002). Joseph Stiglitz, the great disillusionment. East-West Comparative Studies Review, 33(1), 229-232.

Senarclens, D. P. (2000). Humanitarian and globalization. International Review of the Red Cross, 838(82), 311-325.Available at: https://doi.org/10.1017/S1560775500175510.

Small, P., & Soete, L. (1999). Globalization in search of a future: A challenge to national policies. International Social Science Journal, 160, 189-206.

Terfous, N. (2006). Globalization and the labor market in developed countries. Economy & Forecasting, 172(1), 117-124.Available at: https://doi.org/10.3917/ecop.172.0117.

Valaskakis, K. (1999). The theater of globalization: The scene, the cast and the plot of the play have changed. International Social Science Journal, 51(2), 153-164.

Van Huffel, C. (2001). FDI: Problems and challenges for the countries of the South and East of the Mediterranean. Regional and Development Review, 13, 195-216.

Velde, T. D. W., & Morrissey, O. (2001). Foreign ownership and wage: Evidence from five African countries. CREDIT Reseacher Paper, 01/19. University of Nottingham.

Views and opinions expressed in this article are the views and opinions of the author(s), Asian Journal of Economic Modelling shall not be responsible or answerable for any loss, damage or liability etc. caused in relation to/arising out of the use of the content.