Our research focuses on the impact of government spending on economic growth in the countries of the Economic Community of West African States (ECOWAS). It draws on new theories of endogenous growth, and more specifically on Rajhi model. After the tests of specification, an ARDL model was estimated for each of the countries which have cointegration relationships. For those whose cointegration relationship does not exist, a VAR estimate was made. So according to estimates, Total Public Spending in most of the countries of ECOWAS has not positive influence on the economic growth as well in the short term as in the long term. Also in most of the countries, Public Consumption did not positively affect economic growth as well in the long run as in the short run. Regarding Public Investment, we have the same results; it does not positively affects economic growth in most of the ECOWAS countries. Burkina Faso, Guinea and Ivory Coast are the three excepted countries where Total Public Spending has a positive effect on GDP growth in the long term but not in the short run. For further analysis we looked at Public Consumption and Public Investment. It is only in four out of ten countries of the sample that, we found that Public Consumption expenditures positively affect economic growth in the short term while the impact generally is negative in the long term. Regarding Public investment, it is only in three out of ten countries (Burkina Faso, Cote d’Ivoire, Ghana), that it was found determinant to economic growth in the long term.
The role of government spending in recent models of endogenous growth is reconsidered with vigor, especially with the work of Barro [
Later, other works [
Moreover, the effect of government spending on economic growth is still an unresolved issue theoretically as well as empirically. Although the theoretical positions on the subject are quite diverse, the conventional wisdom is that a large government spending is a source of economic instability or stagnation. Empirical research, however, does not conclusively support the conventional wisdom. A few studies report positive and significant relation between government spending and economic growth while several others find significantly negative or no relation between an increase in government spending and growth in real output. Few studies have been done for Sub Saharan African countries; so this one is a contribution to fill the gap.
The main objective of our paper is to look at the effectiveness of public spending in the ECOWAS countries. Indeed, these countries that plan to create a single common currency must strive to implement effective budgetary policies insofar as they will have lost their individual monetary sovereignty. This study is a contribution to the debate on the conditions for the creation of a single currency in ECOWAS. Indeed, we consider that if ECOWAS countries want to create a monetary zone, they must not only converge on fiscal policies, but also make the fiscal policies effective on economic growth
The effectiveness of public spending is measured here by the positive impact on the GDP growth. Thus, through an endogenous growth model that takes into account some of the control variables, we will see if public expenditure variables have a positive or negative impact on GDP.
We also have two specific objectives that are: looking at the impact of public investment on economic growth and at the effect of public consumption on growth.
So, the article is organized as follows: The first part is a review of the empirical literature on the relationship between public spending and economic growth. The second step sets out the methodology of the study. Finally the third part presents the econometric results and their analysis.
From an empirical point of view, several authors have highlighted the link between public spending and economic growth both in developed countries and in developing countries.
In an empirical study on 98 countries to appreciate his endogenous growth model augmented by public expenditures, Barro [
Dia [
Keho [
N’guessan [
Ales Kuhar et al. [
Okoro A. S. [
Ali Sulieman [
Akonji, R. D et al. [
This study relies on the empirical literature and the Rajhi model [
Owing to the endogenous growth models of some authors as Romer [
h t = B ( 1 − u t ) h t , 0 < μ t < 1 (1)
Furthermore, the technology used in consumption goods sector is represented by a continuously twice differentiable function of production which has the three above-mentioned inputs. The Production per head is then represented by the following function:
Y t = f ( k t ; h t ; u t ; g t ) (2)
with fk, fh, fg > 0, the partial derivatives of the yt function with respect to kt, ht and gt respectively.
To obtain the analytical results comparable to those of Lucas [
Y t = f ( k t ; h t ; u t ; g t ) = A t k t β ( u t h t ) ( 1 − β ) g t γ (3)
with 0 < γ < β < 1 and At represents the technical progress. Applying the logarithm in Equation (3), we find the following expression that corresponds to the basic theoretical model:
ln Y t = ln A t + β ln k t + ( 1 − β ) ln ( μ t h t ) + γ g t (4)
Several authors [
A t = A 0 e ∑ i = 1 k a i X i t (5)
| Variables | |
|---|---|
| Pibh Fbcf Dep Fbcfpub depcons Credit Aide Primaire Inflation IDE Labor | Gross domestic product per capita Fixed gross capital formation (in % of GDP) Public spending (in % of GDP) Gross fixed capital formation (in % of GDP) i.e. Public investment Public consumption (in % of GDP) Domestic credit to private sector (in % of GDP) Public aid to development (in % GDP) Continuation of studies up to the end of primary cycle (% of cohort ) Inflation Foreign direct investment Labor force |
By replacing (5) in (4) and noting h t * = u t h t as the level of human capital used directly in production, we get the following general model for estimation purposes:
ln Y t = ln A 0 + ∑ i = 1 k a i X i t + β ln k t + λ ln ( μ t h t ) + γ g t (6)
where Xit is a variable standing for institutions, demography, technology, business climate, etc., at time t and λ = 1 − β. This Equation (6) can be rewritten in detailed form by introducing, in addition to the variable of interest (Government spending), other variables such as the primary completion rate to capture human capital, the foreign direct investment (FDI) to capture the business climate, the credit granted to the private sector, the public development aid and the inflation rate to understand the economic environment [
ln p i b r i t = λ 0 + λ 1 ln d e p b r u t i t + λ 2 ln f b c f i t + λ 3 ln p r i m a i r e i t + λ 4 ln c r e d i t i t + λ 5 ln i n f l a t i o n i t + λ 6 ln a i d e i t + λ 7 I D E i t + μ i t (7)
where μ i t represents the error term. Finally, this model (7) is to be estimated.
All the data used come from the World Bank data, and they concern 10 countries of ECOWAS (Benin, Côte d’Ivoire, Burkina Faso, Ghana, Nigeria, Niger, Senegal, Guinea Conakry, Togo and Mali) over the period 1990-2015.
In parenthesis are the p-values. There is a negative and significant relationship between government spending variables. Moreover, the coefficients of correlation between explanatory variables are low, even if they are significant for some of the relationships, which implies a weak risk of multi-collinearity (
| Variable | Observation | Mean | Std. Dev. | Min | Max |
|---|---|---|---|---|---|
| lpibhbt | 312 | 6.630537 | 0.5865463 | 5.775017 | 8.072391 |
| lfbcf | 312 | 2.861692 | 0.4347634 | 1.51787 | 3.660878 |
| llabor | 312 | 4.19826 | 0.1576008 | 3.892126 | 4.426104 |
| laide | 312 | 1.833439 | 0.9809856 | −0.9816778 | 3.423393 |
| ldep | 312 | 4.679455 | 0.0950564 | 4.218328 | 4.886409 |
| lcredit | 312 | 2.591606 | 0.6517952 | 1.137447 | 4.271626 |
This test helps to decide on the application of a panel model when we are in the presence of data for several individuals during several periods. Also, it allows seeing whether the data generating process is homogeneous or heterogeneous. Econometrically speaking, Hsiao tests the equality of the coefficients of the model studied in its individual dimension. From an economic point of view, this test leads to decide on the nature of the chosen model. In other words, it allows seeing if the template in question can be considered to be identical for all individuals or not [
The specification test of Hsiao is summarized in
From the above table, Hsiao test results do not allow to accept at 5% threshold the null hypothesis as well at the first step as at the second. A panel estimate is not justified for the countries studied. So, the estimate will be done country by country.
The test of stationarity is very important in Econometrics of time series. Studies have shown that a linear regression on non-stationary variables is often misleading as the distribution of the parameters follows more a Brownian movement rather than a Student law. The Stationarity of the series also plays an important role to make a good prediction. Studying the Stationarity of panel data allows to increase the size of the sample in a big way so that that to reduce the probability of dealing with structural breaks and to better address the problem of low power when testing small sample [
There are several methods to test the stationarity of panel data. But in this analysis, we will focus on four (4) methods including IPS, Hadri, Phillips Perron, LLC, and Breitung tests to ensure the robustness of the results.
After testing, it is apparent that all the variables are integrated of order 1 with the exception of public spending, inflation, IDEs (FDI) and public development aid which are stationary (
| F-stat | P-value | Décision | |
|---|---|---|---|
| 1st step | 1.519 | 0.000 | We reject H0 |
| 2 nd step | 1.328 | 0.057 | We reject H0 |
Source: Calculation of the author.
The study of cointegration between variables allows checking the existence of long-term relationships. Several approaches have been proposed including those of Pedroni [
The use of this model allows introducing of lagged explained and explanatory variables to capture the dynamic effects. In addition, it can be applied regardless of the fact that the explanatory variables are I (0) or I (1) or mutually cointegrated. Just make sure that the order of integration of the explanatory variables is less than or equal to one (1), and especially that the variable of interest is integrated of order one (1). The threshold test procedure used by Pesaran et al. is more robust for the study of small samples [
Results show the existence of a cointegration relationship in Benin, Burkina Faso, Côte d’Ivoire, Guinea, Mali and Niger. For Ghana, Nigeria, Senegal and Togo i.e. the test does not reject the null hypothesis of absence of cointegration. Therefore, an error correction model will be estimated for each of the countries where there is presence of cointegration while for other countries, we will estimate for each of them a VAR (pi) model, where p is the optimal lag of country i . The method of generalized moments will be used to estimate the VAR models and to address the endogeneity problem that can result from the presence of the endogenous variable among the explanatory variables. In the first case, the specification of the model is presented as follows:
• Long-term relationship
l p i b h b t i t = ϑ i 1 l d e p i t + ϑ i 2 l f b c f i t + ϑ i 3 l l a b o r i t
| 10% | 5% | 2.50% | 1% | ||||
|---|---|---|---|---|---|---|---|
| low | High | low | high | low high | low | high | |
| 2.72 | 3.77 | 3.23 | 4.35 | 3.69 | 4.89 | 4.29 | 5.61 |
| Pays | BEN | BFA | CIV | GHA | GIN | MAR | MLI | NGA | NER | SEN | TOG |
|---|---|---|---|---|---|---|---|---|---|---|---|
| F-stat computed | 197.808 | 9.173 | 55.99 | 0.853 | 75.512 | 8.742 | 5.23 | 3.261 | 7.382 | 0.521 | 0.557 |
| ARDL optimal | (3, 3, 3, 3) | (1, 3, 2, 3) | (3, 3, 3, 3) | (1, 1, 1, 1) | (3, 2, 2, 3) | (3, 3, 2, 3) | (3, 3, 3, 2) | (3, 3, 3, 2) | (3, 2, 2, 2) | (1, 1, 1, 1) | (1, 2, 3, 3) |
Source: Author calculations.
Avec ϑ 0 = − α 0 α 1 ; ϑ 1 = − α 2 α 1 ; ϑ 2 = − α 3 α 1 ; ϑ 3 = − α 4 α 1
For the long term we assume, l p i b h b t i t = l p i b h b t i t − j ; l d e p i t = l d e p i t − j ; l f b c f i t = l f b c f i t − j ; l l a b o r i t = l l a b o r i t − j
• Short term relationship
Δ l p i b h b t i t = α i + λ i E C M i t − 1 + ∑ j = 1 p − 1 β i j Δ l p i b h b t i t − j + ∑ j = 0 q 1 − 1 γ j Δ l d e p i t − j + ∑ j = 0 q 2 − 1 δ j Δ l f b c f i t − j + ∑ j = 0 q 3 − 1 μ j Δ l l a b o r i t − j + τ i t
where λ i E C M i t − 1 is the adjustment of the dependent variable to its long run equilibrium. For the model to be valid and significant, the coefficient λ i as the adjustment speed measure must be negative and less than 1 in absolute value. To this model, we add other exogenous variables as mentioned above in the methodology; variables which are likely to influence the economic growth of ECOWAS countries. Finally, the short term model can be written as follows:
Δ l p i b h b t i t = α i + λ i E C M i t − 1 + ∑ j = 1 p − 1 β i j Δ l p i b h b t i t − j + ∑ j = 0 q 1 − 1 γ j Δ l d e p i t − j + ∑ j = 0 q 2 − 1 δ j Δ f b c f i t − j ∑ j = 0 q 3 − 1 μ j Δ l l a b o r i t − j + δ i 1 l a i d e i t + δ i 2 i n f l i t + δ i 3 i d e i t + δ i 4 Δ l c r e d i t i t + δ i 4 Δ p r i m i t + τ i t
In the second case, the VAR model (pi) is written as:
{ Δ l p i b h b t i t = α i + ∑ j = 1 p β i j Δ l p i b h b t i t − j + ∑ j = 0 q i γ j Δ l d e p i t − j + ∑ j = 0 q i δ j Δ f b c f i t − j + ∑ j = 0 q i μ j Δ l l a b o r i t − j + δ i 1 l a i d e i t + δ i 2 i n f l i t + δ i 3 i d e i t + δ i 4 Δ l c r e d i t i t + δ i 4 Δ p r i m i t + τ 1 i t Δ l d e p i t = α i + ∑ j = 1 p β i j Δ l p i b h b t i t − j + ∑ j = 1 q i γ j Δ l d e p i t − j + ∑ j = 1 q i δ j Δ l f b c f i t − j + ∑ j = 1 q i μ j Δ l l a b o r i t − j + δ i 1 l a i d e i t + δ i 2 i n f l i t + δ i 3 i d e i t + δ i 4 Δ l c r e d i t i t + δ i 4 Δ p r i m i t + τ 2 i t Δ l f b c f i t = α i + ∑ j = 1 q i β i j Δ l p i b h b t i t − j + ∑ j = 1 q i γ j Δ l d e p i t − j + ∑ j = 1 q i δ j Δ l f b c f i t − j + ∑ j = 1 q i μ j Δ l l a b o r i t − j + δ i 1 l a i d e i t + δ i 2 i n f l i t + δ i 3 i d e i t + δ i 4 Δ l c r e d i t i t + δ i 4 Δ p r i m i t + τ 3 i t Δ l l a b o r i t = α i + ∑ j = 1 q i β i j Δ l p i b h b t i t − j + ∑ j = 1 q 1 γ j Δ l d e p i t − j + ∑ j = 1 q i δ j Δ l f b c f i t − j + ∑ j = 1 q i μ j Δ l l a b o r i t − j + δ i 1 l a i d e i t + δ i 2 i n f l i t + δ i 3 i d e i t + δ i 4 Δ l c r e d i t i t + δ i 4 Δ p r i m i t + τ 4 i t
The results show the presence of an error correction mechanism in 6 out of 11 cases. All the coefficients of adjustments are negative and significantly lower than 1 in absolute value with a slight overflow of 0.2 point for Niger. This result assumes for these countries, that the variables have a same trend in the long term. The estimated value of the coefficient of the error correction term (ECM) informs about the speed of the adjustment process to the long run equilibrium after a short-term shock. In Benin, this coefficient is equal to 0.333; that means that approximately 33% of disequilibrium due to a shock is corrected one year after. In other words, a deviation from the long run following a short term shock is corrected approximately by 33% a year after. This coefficient is respectively 0,299; 0,779; 0.234 and 0.79 for Burkina Faso, Côte d’Ivoire, Guinea, and Mali.
| BEN | BFA | CIV | GHA | GIN | MLI | NGA | NER | SEN | TOG | |
|---|---|---|---|---|---|---|---|---|---|---|
| Coef | Coef | Coef | Coef | Coef | Coef | Coef | Coef | Coef | Coef | |
| ce | −0.333** | −0.299*** | −0.779** | −0.075 | −0.234** | −0.791** | 0.444 | −1.248** | −0.155 | −0.528 |
| LONG TERM | ||||||||||
| ldept | −1.425** | 5.801** | 1.328*** | −0.774 | 2.161** | −3.000*** | −3.155 | −2.38** | 0.547 | 0.785 |
| lfbcft | 0.233** | −1.03*** | 0.337** | 0.813 | 1.024** | 0.213 | 0.107 | 0.502** | 0.109 | −0.062 |
| llabort | −4.758** | 293.625*** | −19.499*** | −1.536 | 7.025*** | 1.111** | −5.208 | −1.064 | −0.796 | −6.152 |
| SHORT TERM | ||||||||||
| dlppibhbtt-1 | −0.257** | - | 0.096 | - | 0.057 | 0.816* | 1.906 | 0.14 | - | 0.918 |
| dlppibhbtt-2 | 0.98*** | - | −0.69** | - | 0.136* | 0.374 | −0.342 | −0.492 | - | - |
| dldept | −0.367** | −1.306* | −0.572* | - | −0.495*** | 2.215** | −1.132** | 1.402* | - | −0.444 |
| dldept-1 | 0.558** | −0.443 | −0.319* | - | −0.756*** | 1.983** | −0.979** | 1.626* | - | −2.125 |
| dldept-2 | 0.992*** | −1.069 | 0.087 | - | - | 1.568** | −0.625* | - | - | - |
| dlfbcft | 0.0345 | 0.146** | −0.175** | - | −0.112*** | −0.301* | 0.222 | −0.422** | - | 0.079 |
| dlfbcft-1 | −0.056* | 0.092** | −0.106** | - | −0.15*** | −0.147 | −0.198* | −0.25* | - | 0.249 |
| dlfbcft-2 | −0.174*** | - | 0.039** | - | - | −0.181 | −0.129 | - | - | 0.264 |
| dllabort | −10.899*** | −133.048*** | −12.44** | - | −2.767*** | *−1.787 | −114.519** | 43.736* | - | −54.066 |
| dllabort-1 | 16.694*** | −100.909*** | −3.11 | - | −4.076*** | −1.135 | 67.464* | −17.001 | - | 115.782 |
| dllabort-2 | −3.903** | −45.795** | 29.6** | - | −3.654*** | - | - | - | −84.514* | |
| IDEt | 0.012*** | −0.001 | −0.031** | −0.001 | 0.003*** | −0.001 | 0.014 | −0.0001 | 0.002 | 0.0019 |
| laidet | 0.012 | −0.093*** | −0.003 | −0.044 | 0.049*** | 0.129 | 0.108* | 0.046 | 0.006 | −0.016 |
| Inf_pibt | −0.002*** | 0.002 | −0.0001 | −0.001 | −0.001*** | −0.002 | 0.002 | −0.001 | −0.002* | −0.002 |
| dprim | 0.007*** | −0.003 | −0.001* | 0.003 | 0.002*** | 0.026** | −0.011* | −0.001 | 0.0002 | −0.0116 |
| dlcreditt | 0.034** | −0.119** | 0.0189 | −0.118 | 0.013* | −0.115 | 0.073 | −0.042 | −0.054 | −0.319 |
| cons | 10.919* | −394.084*** | 64.166** | 1.259 | −8.636*** | 11.891** | −18.909 | 24.826** | 1.101 | 15.763 |
Source: author estimations.
1) Analysis of the Long-Term Relationship
In the long-term, the Total Government Spending negatively impacts the economic growth in Benin, Mali and Niger while this impact is rather positive in Burkina Faso, Ivory Coast and Guinea.
On the other hand, economic growth is positively impacted by physical capital (GFCF) in the short term for the majority of the countries except Burkina Faso where the relationship between the two variables is negative in the long run while it is positive in the short term.
Labor factor is also a determinant factor on which policy-makers must rely on to set up sustained economic growth. The results show that there is a positive relationship between labor factor and economic growth in Burkina Faso, Mali and Guinea, while this relationship is rather negative for Benin and Ivory Coast.
2) Analysis of the Short-Term Relationship
In the short term, the Total Government Spending negatively influences economic growth in Benin, Burkina Faso, Côte d’Ivoire and Guinea Conakry. However, this relationship is positive for Mali and Niger. These results again draw attention to the controversy that exists around the causality between governments spending and economic growth, causality which varies according to the specificities of the studied countries.
Furthermore, the analysis shows that Foreign Direct Investment has a positive effect in the growth of Benin and Guinea while this effect is negative in Côte d’Ivoire. However, the effect of the FDI seems to be not significant in Burkina Faso, Mali and Niger.
This negative relationship of FDI on the economic growth can be explained by the absence of enough skilled labor force to attract foreign investors and boost the economic growth in the countries of the sample. Actually, with the exception of Niger, labor factor has a negative and significant effect on economic growth.
In Benin and Guinea, the economic growth is influenced negatively by inflation while in other countries, the effect is not significant. Regarding international aid variable, the results confirm what is generally found in the literature. Indeed, this variable has a negative effect on economic growth of Burkina Faso and the Niger. On the other hand, in Guinea, international aid has a positive and significant effect on economic performance while this effect is not significant in Benin, Ivory Coast to Mali and the Niger. In fact, according to Burnside & Dollar (2000), international aid is not in itself a negative factor for economic growth but, it would be effective and positively impact economic growth in countries with “good” institutions and sound economic policies.
The Negative Impact of Total Government Spending on Economic Growth in Togo, Nigeria, Senegal and Ghana
The hypothesis of absence of cointegration is not rejected for Togo, Senegal, Nigeria and Ghana. So, a VAR model was estimated with the GMM method to address the problem of endogeneity that results from the dependent variable which also stands as one of the explanatory variables. The VAR stationarity tests show that the variables are stationary for each of the four (4) countries, since all unit roots are lower than the unit in module (or are contained in the unit circle).
The influence of public spending in Togo, Senegal and Ghana is highlighted through a VAR model (
The gross fixed capital formation is a factor on which Togo and Senegal can rely in the short term to boost their economic growth. Labor factor also plays a positive and significant role in Togo and Ghana, but it requires a better quality to ensure sustained economic growth. In addition, a favorable environment for business and proper financial institutions are needed to allocate beneficial loans to the private sector and to attract FDIs.
Moreover, inflation has a negative effect on the economic growth of the countries of the sample. This highlights the interest to control inflation to ensure a sound economic growth.
1) Owing to the Long Term Model Public Consumption Spending Negatively Influences Economic Growth in Most of the Countries
In the long run, government expenditures have a negative impact in Niger and Guinea while they have a positive and significant effect in Ivory Coast. In the other remaining countries, the effect is not significant.
However, investment represented here by the Gross Fixed Capital Formation (GFCF) usually influences economic growth in a positive way in the long term. Indeed, among 7 selected countries, 2 are positively impacted by the GFCF (Côte d’Ivoire and Guinea) and only 1 (Burkina Faso) is negatively impacted. This can be explained by the fact that this country is so far dealing with a socio-political crisis and has been experiencing terrorist threats that have created a unfavorable climate for FDIs. As pointed out by several authors, as long as there is no socio-political and economic stability and good institutions, investment and international aid efforts cannot positively impacts the economy.
2) In the Short Term Government Consumption Is a Stimulating Factor of Economic Growth
In the short term, public consumption generally boosts the economy, which confirms the Keynesian thesis that explains government spending and budget deficit have a positive effect on GDP growth. Indeed, in four (4) countries (Benin, Côte d’Ivoire, Guinea and Niger) where the effect is significant, only Ivory Coast is negatively impacted in the short run, while in the long run public spending has a positive effect in this country. This can be explained by the fact that Ivory Coast has just went through a decade of social and political unrest that undermined its economy. But this country is doing so much investment to repair the damages created by the civil war in order to put the economy in a sustainable growth path.
| BEN | BFA | CIV | GIN | MAR | MLI | NER | |
|---|---|---|---|---|---|---|---|
| Coef | Coef | Coef | Coef | Coef | Coef | Coef | |
| ce | −0.769** | −0.139** | −1.003*** | −0.274** | −0.285** | −0.411* | −0.663* |
| Long term | |||||||
| ldepconst | 0.009 | 0.045 | 0.115*** | −0.238* | −0.585 | −0.204 | −0.419* |
| lfbcft | 0.112 | −1.435** | 0.335*** | 1.459* | 1.673* | −0.533 | 0.004 |
| llabort | −6.42** | 300.381*** | −14.390*** | 10.149** | 0.111 | 1.876** | −3.709** |
| Short term | |||||||
| dlpibhbtt-1 | 0.508 | - | 0.275 | - | −0.353 | 1.418** | −1.071** |
| dlpibhbtt-2 | - | - | - | −0.495 | 0.818** | −0.084 | |
| dldepconst | 0.054** | - | −0.084*** | 0.057*** | −0.233 | 0.033 | 0.217*** |
| dldepconst-1 | 0.021 | - | −0.066*** | 0.045*** | −0.202 | 0.02 | 0.137** |
| dldepconst-2 | - | −0.037*** | − | −0.109 | −0.018 | 0.069** | |
| dlfbcft | 0.008 | 0.064 | −0.126** | −0.231*** | −0.056 | 0.218 | −0.104 |
| dlfbcft-1 | 0.079 | 0.079* | −0.071** | −0.258*** | −0.446 | 0.144 | 0.036 |
| dlfbcft-2 | −0.031 | - | −0.046 | - | −0.075 | 0.152* | |
| dllabort | −4.166 | −82.639*** | −24.080** | −4.942*** | 0.277 | 1.048 | −31.993 |
| dllabort-1 | 7.511* | −58.232** | −0.135 | −4.196*** | 0.316 | −1.541 | 28.005 |
| dllabort-2 | −19.806 | 25.246** | −4.089*** | 1.31 | −1.224* | −27.493* | |
| IDEt | 0.005 | −0.009* | −0.005 | −0.005*** | 0.017** | −0.017** | −0.009** |
| laidet | −0.037 | −0.052** | 0.006 | 0.037*** | −0.034 | −0.063 | −0.167** |
| Inf_pibt | −0.002*** | 0.001 | −0.002*** | −0.002*** | −0.012** | −0.001 | 0.004** |
| dprim | 0.004** | 0.001 | 0.0002 | 0.001** | −0.002 | 0.015** | 0.002 |
| dlcreditt | −0.032** | −0.029 | 0.0189 | −0.031 | −0.279** | −0.09 | −0.012 |
| cons | 25.988** | −183.268** | 66.535** | −10.923*** | 1.463 | −0.679 | 15.988 |
Source: author calculations.
The VAR analysis reveals the existence of a positive and significant relationship between Public Consumption Spending and economic growth in Togo and Senegal (
In this part, the analysis only covers 8 out of 15 countries due to the lack of data. Cointegration tests show the existence of a long-term relationship between investment and growth in Burkina Faso, Ivory Coast and Ghana, which allows us to estimate an ARDL model for each of these countries. However, for countries like Benin, Niger, Guinea, Senegal and Togo there is no long-term relationship. So, a VAR model will be estimated for these countries.
Estimation results of the ARDL model presented in
1) Long Term Relationship: Positive Impact of Public Investment on Economic Growth
In the long run, the results show a positive and highly significant public investment (fbcfpub) impact on economic growth of Burkina Faso, Ivory Coast and Ghana. However, the effect is more important in Côte d’Ivoire (0.316) compared to Ghana (0.211) and Burkina Faso (0.065).
2) Short term Relationship: Negative Impact of Public Investment on Economic Growth
In the short term, public investment adversely affects economic growth. This can be caused by the fact that investment at a time t accuses a slight delay before producing positive effects. The negative effect in the short term can also results from the fact that public investment requires additional public expenditure that can negatively affect the government budget balance, and then the all economy. One would wait a few years for getting positive effect on economic growth.
1) Estimation Results for Benin, Guinea, Niger, Senegal and Togo
Public investment did not significantly influence economic growth in Benin, Guinea, the Niger, Senegal and Togo (
2) Shock on Total Government Spending and Economic Growth in Togo, Senegal, Ghana and Nigeria
Analysis of impulse response function shows that following a shock on Total Public Spending, there is a slowdown in economic growth in Ghana, Nigeria and Senegal in the first year while in Togo, a shock on the public spending has a positive short-term effect. Note that from the second year, there is a strong GDP growth in Nigeria while this trend is less pronounced in other countries (
| BFA | CIV | GHA | |
|---|---|---|---|
| Coef | Coef | Coef | |
| ce | −0.213*** | −0.591** | −0.463*** |
| Long term | |||
| ldepconst | 0.431 | 0.037 | 0.016 |
| lfbcfpubt | 0.065*** | 0.316** | 0.211*** |
| llabort | 170.989*** | −23.774** | 2.615*** |
| Short term | |||
| dlppibhbtt-1 | 0.377** | - | - |
| dlppibhbtt-2 | 0.287* | - | - |
| dldepconst | - | - | 0.007 |
| dldepconst-1 | - | - | - |
| dldepconst-2 | - | - | - |
| dlfbcfpubt | −0.008 | −0.138*** | −0.087*** |
| dlfbcfpubt-1 | - | −0.087*** | −0.039*** |
| dlfbcfpubt-2 | - | −0.018 | −0.017** |
| dllabort | −62.024*** | 31.898* | −2.248 |
| dllabort-1 | - | −10.379 | - |
| dllabort-2 | - | 71.677** | - |
| IDEt | −0.132*** | −0.035 | 0.001 |
| laidet | −0.052** | 0.023 | −0.063* |
| Inf_pibt | 0.001 | 0.002 | 0.001* |
| dprim | 0.002 | −0.0001 | 0.001** |
| dlouvert | −0.079 | −0.353** | −0.145** |
| cons | −160.858*** | 62.381** | −2.274* |
Source: author calculations.
(Yes = positive impact on economic growth)
The cells in gray indicate either the absence of long term relationship for the country in question or the fact that the country has been excluded from the analysis due to the lack of data. The empty white cell means that the coefficient of the variable is not significant.
The introduction of government spending in endogenous growth models is a topic of great importance for public economics. We analyzed the impact of government spending on economic growth in 10 countries in West Africa using an endogenous growth model augmented of government expenditure and developed by Rajhi (1996).
After the stationarity and cointegration tests, either an ARDL error correction model or a VAR model has been estimated, by using the estimation method that best fits the econometric analysis of each country.
Results give evidence that Total Government Spending does not positively affect economic growth in most of the countries of the sample as well in the short term as in the long term. Burkina Faso, Guinea and Ivory Coast are the three excepted countries in which Total Public Spending has a positive effect on GDP growth in the long term. For further analysis we looked at Public Consumption and Public Investment.
It is only in four out of ten countries of the sample we found that Public Consumption expenditures positively affect economic growth in the short term while the impact generally is negative in the long term.
Regarding Public investment, it is only in three out of ten countries (Burkina Faso, Côte d’Ivoire, Ghana), that it was found determinant to economic growth in the long term.
These results show that the ECOWAS countries are facing a problem of economic inefficiency in public spending. Social and political instability, bad governance, corruption, lack of transparency in the management of public procurement are the main factors of inefficiency in public spending. That’s why we will give the following recommendations:
- First of all, we must strengthen the rule of law and democracy to create an environment and institutions that ensure the effectiveness of public action in general and fiscal policies in particular. It is a prerequisite for any effective economic policy.
- To rationalize public spending by priority choices and an efficient management of resources. Public policies must set out quantitative and qualitative objectives.
- To create a favorable business environment for public investment to attract national and foreign private investment.
- To ensure transparency in the allocation and implementation of public procurement according to the rules of competition. Indeed, because of the corruption, in most of the time, real values of expenditures are substantially lower than their nominal amounts in the budget.
- To avoid the excessive public deficit and unsustainable debt, this could result in the cause of socio-economic instability and crisis.
Like any study, this one has its limits related especially to the non-availability of data for all ECOWAS countries. Moreover, taking into account institutional quality variables would shed more light.
The author declares no conflicts of interest regarding the publication of this paper.
Ndiaye, A. (2018) Public Spending and Growth in the Countries of the Economic Community of West African States. Modern Economy, 9, 1949-1975. https://doi.org/10.4236/me.2018.911122
| lpibhbt | Lfbcf | llabor | laide | ldep | lcredit | dprim | Inf_pib | IDE | |
|---|---|---|---|---|---|---|---|---|---|
| lpibhbt | 1 | ||||||||
| Lfbcf | 0.0509 | 1 | |||||||
| (0.3699) | |||||||||
| llabor | −0.5371 | −0.0261 | 1 | ||||||
| (0.000) | (0.6463) | ||||||||
| Laide | −0.7323 | 0.2029 | 0.4302 | 1 | |||||
| (0.000) | (0.0003) | (0.000) | |||||||
| Ldep | −0.4256 | 0.5844 | 0.3107 | 0.5285 | 1 | ||||
| (0.000) | (0.000) | (0.000) | (0.000) | ||||||
| lcredit | 0.6179 | 0.3151 | −0.3145 | −0.3467 | 0.0555 | 1 | |||
| (0.000) | (0.000) | (0.000) | (0.000) | (0.3282) | |||||
| dprim | −0.0947 | 0.0935 | 0.0618 | 0.0894 | 0.1231 | −0.0104 | 1 | ||
| (0.1015) | (0.1059) | (0.2861) | (0.1222) | (0.033) | (0.858) | ||||
| Inf_pib | 0.0908 | −0.0813 | 0.0125 | −0.0885 | −0.1891 | −0.2226 | −0.1064 | 1 | |
| (0.1094) | (0.1519) | (0.8256) | (0.1188) | (0.0008) | (0.0001) | (0.0658) | |||
| IDE | −0.0176 | 0.1898 | 0.0889 | −0.0706 | 0.2365 | 0.0684 | 0.0551 | 0.0913 | 1 |
| 0.7565 | 0.0008 | 0.1171 | 0.2134 | 0 | 0.228 | 0.3415 | 0.1075 |
Source: calcul de l’auteur.
| LLC | Hadri | Philpps Perron | IPS | Breitung | Conclusion | |
|---|---|---|---|---|---|---|
| lpibhbt | I(1) | I(2) | I(1) | I(1) | I(1) | I(1) |
| lfbcf | I(1) | I(1) | I(1) | I(1) | I(1) | I(1) |
| Main d’œuvre | I(1) | I(1) | I(1) | I(1) | I(1) | I(1) |
| laide | I(0) | I(1) | I(0) | I(1) | I(0) | I(0) |
| ldep | I(0) | I(1) | I(0) | I(0) | I(0) | I(0) |
| primaire | I(1) | I(1) | I(1) | I(1) | I(1) | I(1) |
| lcredit | I(1) | I(2) | I(1) | I(1) | I(1) | I(1) |
| louvert | I(1) | I(1) | I(0) | I(1) | I(1) | I(1) |
| IDE | I(0) | I(1) | I(0) | I(0) | I(0) | I(0) |
| Inf_pib | I(0) | I(0) | I(0) | I(0) | I(0) | I(0) |
Source: author calculations.
| Togo | |||||
|---|---|---|---|---|---|
| dlpibhbt | dldept | dlfbcft | dllabort | ||
| coef | coef | coef | coef | ||
| dlpibhbt-1 | 0.496*** | 0.586*** | 2.209*** | 0.006** | |
| dlpibhbt-2 | −0.122 | 0.04 | 0.787 | −0.00004 | |
| dldept-1 | −1.667*** | −0.976*** | −5.259*** | −0.012** | |
| dldept-2 | −0.329 | −0.664*** | −1.607 | −0.001 | |
| dlfbcft-1 | 0.254*** | 0.032 | −0.572** | −0.0001 | |
| dlfbcft-2 | 0.217*** | 0.043 | 0.127 | 0.0004 | |
| dllabort-1 | 81.611*** | 38.155*** | 159.242** | 1.403*** | |
| dllabort-2 | −78.209*** | −35.548*** | −190.81** | −0.409* | |
| IDE | −0.002* | 0.002 | 0.001 | 0.00004* | |
| laide | 0.008 | −0.012 | −0.089 | 0.0003 | |
| Inf_pib | 0.004*** | −0.002** | 0.007 | −0.0001*** | |
| dprim | −0.009*** | −0.006*** | −0.006 | −0.0001** | |
| dlcredit | −0.113** | −0.118*** | −0.255 | −0.004*** | |
| _cons | 0.012 | 0.051** | 0.339** | −0.0002 | |
| Sénégal | |||||
| dlpibhbt | dldept | dlfbcft | dllabort | ||
| coef | coef | coef | coef | ||
| dlpibhbt-1 | −0.022 | −0.206 | 2.533*** | −0.177 | |
| dlpibhbt-2 | 0.226 | 0.122 | −1.682* | 0.1 | |
| dldept-1 | −0.323* | −0.031 | 0.201 | −0.102 | |
| dldept-2 | −0.221 | −0.393** | −0.9 | −0.019 | |
| dlfbcft-1 | 0.098 | 0.019 | −0.275 | 0.019 | |
| dlfbcft-2 | 0.161* | 0.046 | 0.018 | 0.089** | |
| dllabort-1 | −0.395 | −0.775 | −3.058* | 0.201 | |
| dllabort-2 | 0.317 | −0.111 | 1.178 | 0.573** | |
| IDE | 0.007 | 0.003 | 0.015 | 0.006*** | |
| laide | 0.024 | −0.033 | −0.213** | −0.004 | |
| Inf_pib | −0.002** | 0.002** | 0.006* | 0.0004 | |
| dprim | 0.004* | 0.003 | 0.005 | **0.003 | |
| dlcredit | −0.051 | 0.126** | −0.236 | 0.023 | |
| _cons | −0.053 | 0.054 | 0.409* | −0.009 | |
| Ghana | ||||
|---|---|---|---|---|
| dlpibhbt | dldept | dlfbcft | dllabort | |
| coef | coef | coef | coef | |
| dlpibhbt-1 | 0.205 | 0.031 | 2.214 | 0.032 |
| dlpibhbt-2 | −0.557** | 0.672 | 2.863 | −0.026 |
| dldept-1 | −0.144* | −0.402** | 0.363 | −0.016 |
| dldept-2 | −0.185** | 0.108 | 0.835 | 0.024 |
| dlfbcft-1 | 0.022 | −0.065 | −0.633*** | −0.003 |
| dlfbcft-2 | 0.009 | −0.118** | −0.417* | −0.011 |
| dllabort-1 | 1.118** | 2.224** | 14.275** | 0.669*** |
| dllabort-2 | −0.982** | −1.13 | −4.717 | 0.072 |
| IDE | −0.008** | −0.016** | −0.045 | −0.0003 |
| laide | −0.061*** | −0.008 | 0.218 | −0.005 |
| Inf_pib | −0.001*** | −0.001 | −0.004 | 2.00E-04 |
| dprim | 0.002* | 0.004 | 0.019 | 0.002** |
| dlcredit | −0.173*** | −0.021 | −0.531 | 2.10E−02 |
| _cons | 0.233*** | 0.085 | −0.25 | 2.00E−03 |
| Nigéria | ||||
| dlpibhbt | Dldept | dlfbcft | dllabort | |
| coef | Coef | coef | coef | |
| dlpibhbt-1 | −0.042 | −1.387 | −1.896 | 0.028*** |
| dlpibhbt-2 | 0.53 | 3.031* | 8.011** | −0.007 |
| dldept-1 | −0.106 | −0.339* | −0.101 | 0.0002 |
| dldept-2 | −0.005 | −0.112 | 0.366 | 0.0001 |
| dlfbcft-1 | 0.057 | 0.149 | 0.09 | −0.002*** |
| dlfbcft-2 | −0.106 | −0.312** | −0.863*** | 0.001 |
| dllabort-1 | −12.416 | −131.495** | −180.859* | 1.025*** |
| dllabort-2 | 2.257 | 148.749** | 212.178** | 0.028 |
| IDEt | 0.003 | −0.002 | 0.025 | −0.00004 |
| laidet | −0.002 | 0.105 | −0.025 | 0.001* |
| Inf_pibt | −0.001* | −0.0004 | −0.002 | 7.98E−06 |
| dprimt | −0.007** | 0.012** | 0.015 | 2.10E−05 |
| dlcredit | −0.112** | 0.151 | −0.138 | 4.00E−04 |
| _cons | 0.011 | 0.061 | −0.132 | −1.00E−04 |
Source: author calculations.
| GHANA | ||||
|---|---|---|---|---|
| dlpibhbt | dldepconst | dlfbcft | dllabort | |
| coef | coef | coef | coef | |
| dlpibhbt-1 | 0.233 | 7.87 | 2.875* | 0.038 |
| dlpibhbt-2 | −0.444* | −33.946** | 3.431 | −0.024 |
| dldepconst-1 | −0.001 | −0.601*** | −0.068*** | −0.001 |
| dldepconst-2 | 0.002 | −0.32 | −0.043 | 0.002 |
| dlfbcft-1 | 0.01 | 0.638 | −0.554*** | 0.004 |
| dlfbcft-2 | −0.014 | −0.447 | −0.205 | −0.004 |
| dllabort-1 | 1.308*** | 10.562 | 10.765** | 0.604*** |
| dllabort-2 | −0.829* | 9.32 | −2.525 | 0.171 |
| IDE | −0.009*** | −0.540** | −0.045 | 0.0001* |
| laide | −0.057*** | −3.552** | 0.212 | −0.002 |
| Inf_pib | −0.001** | −0.081** | −0.004 | −0.0003** |
| dprim | 0.004** | 0.031 | 0.018 | 0.002*** |
| dlcredit | −0.113** | −9.175*** | 0.09 | 0.031** |
| _cons | 0.213 | 12.721*** | −0.276 | −0.011 |
| NIGERIA | ||||
| dlpibhbt | dldepconst | dlfbcft | dllabort | |
| coef | coef | coef | coef | |
| dlpibhbt-1 | 0.313 | −6.203 | −2.743 | 0.029*** |
| dlpibhbt-2 | −0.458 | 6.596 | 8.428** | −0.001 |
| dldepconst-1 | −0.0002 | −0.765*** | −0.012 | 0.0001* |
| dldepconst-2 | −0.01 | −0.25 | 0.009 | 0.0001 |
| dlfbcft-1 | 0.055 | 4.404*** | 0.084 | -0.003*** |
| dlfbcft-2 | −0.039 | 2.911 | −0.807** | −0.0002 |
| dllabort-1 | 19.038 | −203.566 | −217.304* | 0.881** |
| dllabort-2 | −30.037 | 187.118 | 250.556* | 0.188 |
| IDE | −0.001 | −0.055 | 0.017 | 0.00003 |
| laide | −0.014 | 0.003 | 0.05 | 0.001 |
| Inf_pib | −0.001 | −0.027** | −003* | 7.00E-06 |
| dprim | −0.007** | 0.229*** | 0.017 | 5.00E-06 |
| dlcredit | −0.107* | -2.828** | −0.16 | 0.0004 |
| _cons | 0.03 | 1.043 | −0.037 | −0.001 |
| Sénégal | ||||
|---|---|---|---|---|
| dlpibhbt | dldepconst | dlfbcft | dllabort | |
| coef | coef | coef | coef | |
| dlpibhbt-1 | 0.462 | 0.791 | 2.311* | −0.395** |
| dlpibhbt-2 | −0.326 | −0.533 | −1.961* | 0.164 |
| dldepconst-1 | 0.105** | −1*** | −0.036 | −0.03 |
| dldepconst-2 | 0.005 | −0.009 | 0.09 | 0.003 |
| dlfbcft-1 | 0.139** | −0.968* | −0.31 | −0.029 |
| dlfbcft-2 | 0.108* | −1.102** | −0.222 | 0.051* |
| dllabort-1 | −0.239 | −2.525 | −3.023 | 0.194 |
| dllabort-2 | 0.362 | −0.421 | 0.301 | 0.413 |
| IDE | 0.001 | 0.07* | 0.008 | 0.007*** |
| laide | 0.061** | -0.694** | −0.260** | −0.019 |
| Inf_pib | −0.004*** | 0.011 | 0.009** | 0.001* |
| dprim | 0.004* | −0.03 | −0.001 | 2.00E-03 |
| dlcredit | −0.154** | 0.858 | −0.044 | 0.066* |
| _cons | −0.114* | 1.344** | 0.514** | 0.021 |
| TOGO | ||||
| dlpibhbt | dldepconst | dlfbcft | dllabort | |
| coef | coef | coef | coef | |
| dlpibhbt-1 | 0.179 | −8.876 | 0.711 | 0.004** |
| dlpibhbt-2 | −0.177* | 5.67 | 0.327 | −0.001 |
| dldepconst-1 | 0.019*** | −0.942*** | 0.021 | 4.00E−05 |
| dldepconst-2 | 0.007** | −0.697*** | 0.011 | -5.00E−05 |
| dlfbcft-1 | 0.294*** | −0.184 | −0.408 | −3.00E−04 |
| dlfbcft-2 | 0.105** | −0.731 | −0.05 | −5.00E−04 |
| dllabort-1 | 49.447*** | −1702.936*** | 15.177 | 1.134*** |
| dllabort-2 | −52.224*** | 1713.633*** | −57.584 | −0.203 |
| IDE | -0.005*** | 0.005 | −0.005 | 2.00E−05 |
| laide | 0.006 | −0.687 | −0.056 | 2.00E−04 |
| Inf_pib | 0.006*** | 0.068 | 0.011* | −0.0001*** |
| dprim | −0.003** | 0.108 | 0.013 | −4.00E-05 |
| dlcredit | −0.028 | 5.488*** | 0.106 | −0.003*** |
| _cons | 0.005 | 0.283 | 0.205 | −1.00E−04 |
Source: author estimations.
| BENIN | ||||
|---|---|---|---|---|
| dlpibhbt | dldepconst | dlfbcfpubt | dllabort | |
| coef | coef | coef | coef | |
| dlpibhbt-1 | −0.003 | −2.769 | −0.741 | 0.169 |
| dlpibhbt-2 | 0.216 | 26.860** | −1.852* | 0.204 |
| dldepconst-1 | 4.85E−04 | −0.459 | −0.073 | −1.00E−02 |
| dldepconst−2 | −3.07E−04 | 0.009 | −0.105 | −0.048** |
| dlfbcfpubt-1 | 0.011 | 0.564 | −0.258 | −0.141** |
| dlfbcfpubt-2 | 0.024* | −0.572 | −0.059 | −1.40E−02 |
| dllabort-1 | −0.3 | −4.148 | 2.497 | 1.243** |
| dllabort-2 | −0.300*** | 1.688 | −1.22** | −0.026 |
| IDE | 0.001 | 0.067 | −0.008* | −1.00E−03 |
| laide | 0.011 | 2.02** | 0.051 | 0.054** |
| Inf_pib | −0.001** | 0.009 | −0.006*** | −0.00007 |
| dprim | −9.05E-05 | 0.027 | 0.004 | 1.00E-03 |
| dlouvert | 0.056*** | 0.901 | 0.097 | −0.005 |
| _cons | −0.064 | −4.532 | 1.964 | 0.124* |
| Guinée Conakry | ||||
| dlpibhbt | dldepconst | dlfbcfpubt | dllabort | |
| coef | coef | coef | coef | |
| dlpibhbt-1 | −0.258 | 10.247*** | −2.093** | −0.002 |
| dlpibhbt-2 | −0.054 | 3.319 | −0.817 | 0.007 |
| dldepconst-1 | 7.00E−03 | −0.28 | 0.094 | −3.83E−04 |
| dldepconst-2 | −0.033** | 0.149 | 0.001 | −3.46E−04 |
| dlfbcfpubt-1 | −0.037 | −1.167 | 1.266*** | −1.00E−03 |
| dlfbcfpubt-2 | 0.058 | 0.292 | −0.038 | −1.00E−03 |
| dllabort-1 | −5.699 | 2.597 | 25.971 | 1.155*** |
| dllabort-2 | 0.457 | 14.022 | −16.999 | −0.131 |
| IDE | −0.001 | 0.019 | −0.001 | 7.93E-06 |
| laide | −0.026 | 1.676** | −0.244 | −0.001 |
| Inf_pib | 0.003 | −0.022 | 0.013** | 5.21E−05 |
| dprim | −3.00E−03 | 0.027 | 0.036** | −5.06E−05 |
| dlouvert | −0.233** | −0.155 | −1.64E-01 | 1.00E−03 |
| _cons | 0.075 | −3.034 | 0.096 | 0.007 |
| Niger | ||||||
|---|---|---|---|---|---|---|
| dlpibhbt | dldepconst | dlfbcfpubt | dllabort | |||
| coef | coef | coef | coef | |||
| dlpibhbt-1 | −0.258 | 10.247*** | −2.093*** | −0.002 | ||
| dlpibhbt-2 | −0.054 | 3.319 | −0.817 | 0.008 | ||
| dldepconst-1 | 0.007 | −0.28 | 0.094 | −0.0003 | ||
| dldepconst-2 | −0.033** | 0.149 | 0.001 | −0.0003 | ||
| dlfbcfpubt-1 | −0.038 | −1.167 | 1.266 | −0.001 | ||
| dlfbcfpubt-2 | 0.057 | 0.292 | −0.038 | −0.001 | ||
| dllabort-1 | −5.699 | 2.597 | 25.971 | 1.155*** | ||
| dllabort-2 | 0.457 | 14.023 | −16.999 | −0.131 | ||
| IDE | −0.001 | 0.019 | −0.001 | 7.93E-06 | ||
| laide | −0.026 | 1.676*** | −0.244 | 0.001 | ||
| Inf_pib | 0.003 | −0.022 | 0.007 | −5.21E-05 | ||
| dprim | −0.003 | −0.016 | 0.036*** | −5.06E-05 | ||
| dlouvert | −0.233 | −0.155 | −0.164 | 0.001 | ||
| _cons | 0.075 | −3.034 | 0.096 | 0.007 | ||
| Senegal | ||||||
| dlpibhbt | dldepconst | dlfbcfconst | dllabort | |||
| coef | coef | coef | coef | |||
| dlpibhbt-1 | −0.291 | 3.172 | 0.24 | −0.332*** | ||
| dlpibhbt-2 | −0.188 | −3.783 | −205 | −0.139 | ||
| dldepconst-1 | 0.013 | −0.479* | −0.052 | −0.015 | ||
| dldepconst-2 | −0.004 | −0.497** | −0.012 | −0.028** | ||
| dlfbcfconst-1 | −0.001 | 1.243 | 0.271 | 0.335*** | ||
| dlfbcfconst-2 | 0.208 | 2.930* | 0.226 | 0.104 | ||
| dllabort-1 | −0.464 | −10.789** | −0.673 | 0.023 | ||
| dllabort-2 | −0.268 | 7.334* | 0.714 | 0.289 | ||
| IDE | 0.002 | 0.045 | 0.024*** | 2.00E-03 | ||
| laide | 0.032 | −0.151 | −0.051 | 0.271 | ||
| Inf_pib | −0.002* | −0.008 | −0.001 | 0.001* | ||
| dprim | 0.001 | 0.014 | −0.003 | 0.003*** | ||
| dlouvert | 0.023 | −0.998 | −0.066 | −0.066* | ||
| _cons | 0.381 | −6.326 | 0.063 | −0.754*** | ||
| TOGO | ||||
|---|---|---|---|---|
| dlpibhbt | dldepconst | dlfbcfpubt | dllabort | |
| coef | coef | coef | coef | |
| dlpibhbt-1 | 0.441** | −4.156 | −1.426 | −0.002 |
| dlpibhbt-2 | 0.077 | −3.717 | 2.485* | 0.002 |
| dldepconst-1 | 0.014*** | −0.730*** | 0.049 | −3.00E−05 |
| dldepconst-2 | 0.006 | −0.679*** | 0.051 | −3.72E−05 |
| dlfbcfpubt-1 | 0.022 | 0.568 | 0.403* | −3.90E−04 |
| dlfbcfpubt-2 | −0.025 | −0.469 | −0.442** | −2.38E−05 |
| dllabort-1 | 52.311** | 1086.908 | −344.305* | 0.754*** |
| dllabort-2 | −62.021*** | −1088.406 | 234.555 | 0.194 |
| IDE | −0.005* | 0.210** | −0.025 | 1.33E−05 |
| laide | −0.008 | 0.346 | 0.412** | 2.88E−04 |
| Inf_pib | 0.005*** | −0.041 | 0.014 | −2.97E−06 |
| dprim | −0.003 | 0.001 | 0.059** | 4.66E−05 |
| dlouvert | 0.147 | −3.442 | −0.041 | 0.001 |
| _cons | 0.063 | −0.989 | 0.673 | −0.0003 |
Source: author estimations.