The trade openness is one of the most important determinants of a country’s relative level of economic health. It plays a vital role for most free market economies in the world. This research is an attempt to investigate, particularly, the impact of the trade openness on the economic growth in Niger; and generally, the relationship between all the variables under study. Four (4) variables namely real economic growth rate represented by real gross domestic product growth rate (GDPGR), trade openness (TRDOP), real exchange rate (REEXR) and foreign direct investment (FDI) have been considered in the model. The paper used time series data covering the period from 1980 to 2013 as well as time series methods for the econometric analyses. The results show that there exists a long term relationship between all the variables; the independent variables affects the economic growth in the short-run; only the trade openness and the real exchange rate influence economic growth unidirectionally; except foreign direct investment (FDI), all the variables have explanatory power on economic growth in Niger. The implication of this study is that the trade openness has been efficient to spur the economic growth in Niger over the period of study. Therefore, it is a key indicator which the government should care about.
International trade, also called foreign trade occurs when goods and services are exchanged across national boundaries. Nowadays, it goes beyond this scope of definition, it includes some cross border activities such as overseas investment and contracted projects.
Whether and how trade openness influences economic growth has for long been an interesting point of research for development economists. However, the abundant literature concerning this issue still remains controversial. Although, the tendency is that good international trade policies are in favor of spurring economic growth; nevertheless, it is not a sufficient condition for economic growth and development. Alfred Marshall stated that “The causes which determine the economic progress of nations belong to the study of international trade”. Moreover, trade openness, by increasing the size of the market, allows economies to better capture the potential benefits from increasing returns to scale and exploit economies of specialization (See, e.g., [
In order to promote the world trade that is expected to enhance the economic growth, the world trade organization (WTO) was established in 1993 which replaced the general agreement on tariffs and trade (GATT) established in 1947. Therefore, it is clear that trade is a key determinant in improving the welfare (growth) of economies. In this era of globalization and trade liberalization, Niger joined many regional and international trade agreements such as West African economic and monetary union (WAEMU), economic community of West African states (ECOWAS), world trade organization (WTO), etc…, having an objective to create free trade zones by removing trade barriers. The policy response of such economic partnership agreements on trade policy is to remove trade barriers, reduce tariffs and embark on outward oriented trade policies which foster economic growth and alleviate poverty. For many years, improvements toward trade and investment policies are being observed in Niger and empirical works concerning the existing link between trade openness and economic growth on the specific case of the country are scarce; hence, in light of the preceding information, it is necessary to explore the trade openness and economic growth nexus in Niger, justifying our interest for this research.
The main objectives of this study are: to investigate the relationship between trade openness and economic growth; then to find the direction of the relationship; and finally to what extent, if it does, trade openness influences economic growth?
The remaining content of this paper is divided into four (4) sections. The second section covers the review of previous works; that is the literature review. The data, methodology as well as the econometric analyses are discussed in the third section. Finally, the fourth section comprises the conclusion while the last part concerns the recommendations and limitations of the research.
The link between trade openness and economic growth is a highly debated topic in the growth and development literature; but still, it is far from being resolved.
The theory of comparative advantage developed by David Ricardo can be considered as the root and the traditional explanations of how trade promotes economic growth. Further, other famous theories such as Hechsher- Ohlin’s theory of factor proportions, Stolper-Samuelson and Rybzsnski effects, “trade is the engine of economic growth” theory of D. H. Robertson Morrison arose to enlighten this issue of interest. In fact, all these trade theories predict that an economy will tend to be relatively effective at producing goods that are intensive in the factors with which the country is relatively well endowed. In other words, comparative advantage provides that when nations specialize, they become more efficient in producing a product (a service), and thus if they can trade for their other needs, they and the world will benefit.
As the theoretical literature which could not provide a clear picture on the trade openness―economic growth nexus, the empirical literature is also still an open question. In order to determine the potential relationship and, direction of causality if any, between trade openness and economic growth, an extensive range of research has surfaced.
In his investigation of the relationship between globalization and growth, Uwatt [
Furthermore, in their paper aimed to identify, in the context of the relationship between openness and growth, factors that can account for the poor growth performance of Sub-Saharan African (SSA) countries, Mbabazi J., et al. [
An empirical work to examine the relationship between financial development, trade openness and economic growth in Japan using data from 1960 to 2003 is made by Soukhakian [
To investigate the long-term nexus between exports and domestic economic growth in Saudi Arabia for the period 1970-2005, Hassan (2007) used Vector Auto-Regression (VAR), Impulse Response Function (IFR) and Granger-causality test. The results indicated that the export sector had a significant impact on the economic growth and a positive effect on other economic activities in the long run. Using VAR and VECM, Mustafa [
Rodiguez and Rodrik [
Dudley and Karski [
Time series data on four key macroeconomic variables, namely, real gross domestic product growth rate (GDPGR), trade openness (TRDOP), real effective exchange rate (REEXR) and foreign direct investment (FDI) are used to carry out the analyses. The data are collected on annual basis covering the period from 1980 to 2013 and are extracted from the United Nations Conference on trade and Development (UNCTAD) data base [
A model based on the four (4) variables previously mentioned, is built in order to assess the link between them. It assumed GDPGR as a function of TRDOP, REEXR and FDI.
The model is expressed as follows:
GDPGRt = F[TRDOPt, REEXRt, FDIt], where t denotes the time. (1)
To estimate properly the parameters and facilitate the interpretation, a logarithmic transformation is made to the variables which do not contain negative and/or zero values, precisely TRDOP and REEXR. Thus, the final model is:
Then, the following methods are applied:
The Augmented Dickey-Fuller test (ADF) [
A time series variable, Yt, is stationary if:
1. The expected value of Yt, E (Yt) is the same for all values of t;
2. The variance of Yt, Var (Yt) is finite and the same for all values of t;
3. Cov (Yt, Yt−s) depends only on s, but not on t.
These concepts capture the ideas that the basic statistical properties of the model (i.e. means, variances, and covariances) do not change over time.
There are many unit root tests but here we used the Augmented Dickey-Fuller test. It performs the test that a variable follows a unit-root process. The null hypothesis is that the variable contains a unit root. So, if the P-value of the coefficient of a variable is less than 5% level of significance (P-value < 0.05), we reject the null hypothesis and conclude that the variable is stationary otherwise we accept it.
The Johansen Cointegration test: to check the existence of a long-run relationship between the variables by determining the presence and the number of cointegrating equations;
The Johansen’s trace statistics method for determining r, the number of cointegrating equations used here can be interpreted as being an estimator
The Vector Error Correction Model: to characterize the long-run and short-run dynamics;
The VECM consists to observe long-term and short-term relationships among all variables.
In order to characterize the long-run dynamics, we use the following Vector Error correction model:
With xt = [GDPGRt TRDOPt REEXRt FDIt], Where t stands for the time and the remaining variables are as defined above.
The Granger causality test [
It established the sense of causality between dependent and independent variables. Performing Granger causality test requires that all the variables are stationary. So, for this reason we transformed the variables to the first order difference before running the test. The hypotheses to test are:
H0: the independent variable does not granger cause the dependent variable
H1: the independent variable does granger cause the dependent variable
The variable x is said to Granger “cause” y if we reject H0.
The output of this test indicates that, only GDPGR and FDI are stationary at level; but after the first difference, all the variables become stationary (since P-values < 0.05). The results are summarized in
Variables | ADF Test Statistic | 5% Critical Value of ADF Test Statistic | P-Values (5% Level of Significance) | Order of Remarks Integration | |
---|---|---|---|---|---|
DGDPGR | −5.920115 | −2.963972 | 0.0000* | I(1) 1st order Difference stationary | |
DLnTRDOP | −6.130508 | −2.957110 | 0.0000* | I(1) 1st order Difference stationary | |
DLnREEXR | −6.010155 | −2.957110 | 0.0000* | I(1) 1st order Difference stationary | |
DFDI | −4.121626 | −2.963972 | 0.0033* | I(1) 1st order Difference stationary |
*Stationary at 5% level of significance.
Estimating a co integrating rank necessitates knowing how many lags should be used. For this reason we performed a lag selection-order criteria and the output is presented in
Johansen’s multivariate cointegration test results, based on trace statistic and maximum Eigen value statistic, both reveal the existence of one cointegrating equation among the variables (since “At most 1” is the first value for which the trace statistic 26.40397 is less than its 5% critical value of 29.79707). Since the variables are found to be cointegrated, thus, we conclude that there exists a long-run relationship between GDPGR, lnTRDOP, lnREEXR and FDI. See
The above cointegration tables indicate that all the variables have long run relationship.
It investigated the sense of causality between all the different pairs of variables. The results are presented in
Since we previously found that our variables are cointegrated and the R-Square (0.628416) is less than the Durbin-Watson statistic (2.765477) in
The information in
Confirming the theory, the degree of trade openness has a positive effect on the economic growth. An increase of the TRDOP, on average, by 1% increases the economic growth by 16.73851%, ceteris paribus .This means that as long as Niger was opening more to international trade during the period of study, its economy was likely to grow, in other words the openness to trade enhanced the economic growth in Niger. This early stage increase in output growth as a result of trade openness can be attributed to the deployed efforts by government to develop some infrastructures during the uranium boom period of the 1970’s and early 1980’s.
As expected, the results showed that REEXR has a positive effect on economic growth meaning that when the REEXR increases (depreciates) economic growth also increases and when REEXR decreases (appreciates), economic growth decreases. The depreciation of the real exchange rate of the FCFA, in the long-run increases the economic growth rate, holding the other variables constant. The change in the economic growth rate increases by 8.981520% for one percent increase in real effective exchange rate.
59.84143 is the constant and represent the value of the growth rate when all the variables are zero.
Surprisingly, the coefficient FDI has a negative impact on economic growth and is insignificant. This insignificance may be due to the fact that; in Niger more than 70% of the amount of money invested as FDI are not spent in the country.
Therefore, in this study, it follows that TRDOP and REEXR are the key variables affecting GDPGR.
Lag | LogL | LR | FPE | AIC | SC | HQ |
---|---|---|---|---|---|---|
0 | −283.5895 | NA | 1343.108 | 18.55416 | 18.73919 | 18.61448 |
1 | −194.6823 | 149.1346 | 12.30901 | 13.85047 | 14.77563* | 14.15205* |
2 | −175.2224 | 27.62055* | 10.42817 | 13.62725 | 15.29253 | 14.17009 |
3 | −156.2736 | 22.00503 | 10.03353* | 13.43701* | 15.84241 | 14.22111 |
*indicates lag order selected by the criterion; LR: Sequential modified LR test statistic (each test at 5% level); FPE: Final prediction error; AIC: Akaike information criterion; SC: Schwarz information criterion; HQ: Hannan-Quinn information criterion.
Hypothesized | Trace | 0.05 | ||
---|---|---|---|---|
No. of CE(s) | Eigenvalue | Statistic | Critical Value | Prob.** |
None* | 0.649200 | 57.83017 | 47.85613 | 0.0044 |
At most 1 | 0.478957 | 26.40397 | 29.79707 | 0.1171 |
At most 2 | 0.129168 | 6.846289 | 15.49471 | 0.5956 |
At most 3 | 0.085981 | 2.697117 | 3.841466 | 0.1005 |
Trace test indicates 1 cointegrating eqn(s) at the 0.05 level; *denotes rejection of the hypothesis at the 0.05 level; **MacKinnon-Haug-Michelis (1999) P-values.
Hypothesized | Max-Eigen | 0.05 | ||
---|---|---|---|---|
No. of CE(s) | Eigenvalue | Statistic | Critical Value | Prob.** |
None* | 0.649200 | 31.42621 | 27.58434 | 0.0152 |
At most 1 | 0.478957 | 19.55768 | 21.13162 | 0.0818 |
At most 2 | 0.129168 | 4.149172 | 14.26460 | 0.8433 |
At most 3 | 0.085981 | 2.697117 | 3.841466 | 0.1005 |
Max-eigenvalue test indicates 1 cointegrating eqn(s) at the 0.05 level; *denotes rejection of the hypothesis at the 0.05 level; **MacKinnon-Haug-Mi- chelis (1999) P-values.
Null Hypothesis: | Obs | F-Statistic | Prob. |
---|---|---|---|
LNTRDOP does not Granger Cause GDPGR | 28 | 2.87345 | 0.0455* |
GDPGR does not Granger Cause LNTRDOP | 1.69796 | 0.1896 | |
LNREEXR does not Granger Cause GDPGR | 28 | 1.07141 | 0.0421* |
GDPGR does not Granger Cause LNREEXR | 0.98417 | 0.4696 | |
FDI does not Granger Cause GDPGR | 28 | 1.36864 | 0.2891 |
GDPGR does not Granger Cause FDI | 0.71118 | 0.6462 | |
LNREEXR does not Granger Cause LNTRDOP | 28 | 0.51722 | 0.7864 |
LNTRDOP does not Granger Cause LNREEXR | 1.02348 | 0.4475 | |
FDI does not Granger Cause LNTRDOP | 28 | 0.75071 | 0.6185 |
LNTRDOP does not Granger Cause FDI | 0.99952 | 0.4609 | |
FDI does not Granger Cause LNREEXR | 28 | 0.40062 | 0.8672 |
LNREEXR does not Granger Cause FDI | 0.54179 | 0.7687 |
*Significant at 5% level of significance.
Independent variables and the constant | Coefficients | P-values | Significant or not? |
---|---|---|---|
DLnTRDOP | 16.73851 | 0.0099 | Significant |
DLnREEXR | 8.981520 | 0.0021 | Significant |
DFDI | −0.006490 | 0.2791 | Not Significant |
C | 59.84143 | 0.0036 | Significant |
R-Square: 0.628416; Durbin-Watson statistic: 2.765477.
All the remaining coefficients on C2, C3, C4, C5, C6, C7, C8, C9, C10, C11, C12 and C13 of the variables are short run coefficients; and C14 is the _cons (constant). However, before confirming the results of the VECM, we should test the validity of its residuals.
The
Therefore, all the performed tests show that we have no doubt to validate our model.
Finally, we run Wald test to check whether the coefficients of the different independent variables and their lags jointly have short run effects on the GDPGR. The null hypotheses are: C2 = C3 = C4 = 0; C5 = C6 = C7 = 0; C8 = C9 = C10 = 0 and C11 = C12 = C13 = 0. The outputs in Tables A4-A7 (Appendix) show that none of the variables appears to be significantly affecting the GDPGR (since their Chi-square P-values 0.1247, 0.8620, 0.2994 and 0.6872 respectively are greater than 0.05).
The nexus between trade openness and economic growth in Niger is the main focus in this paper. A four variables model was built in order to investigate our main objectives’ hypotheses with GDPGR as the dependent, TRDOP the independent variable and, REEXR and FDI considered as control variables.
The results of the econometric analyses reveal that:
There is a long-run relationship between the variables under study;
Only TRDOP and REEXR granger cause GDPGR;
None of the explanatory variables influences economic growth in the short-run;
Conclusively, in Niger, it appeared that TRDOP and REEXR are crucial factors to be considered with very much attention as far as the country wants to enjoy a long-run economic growth.
In light of the findings, this study recommends the following policies:
The government should emphasize on the provision of adequate infrastructures to help in reducing the high cost of transportation, providing sufficient electricity and others which constitute big obstacles for the welfare of trade activities in Niger. For instance, the revenue rose from the exports of uranium and oil can be used to develop required infrastructures.
The adoption of a better exchange rate mechanism: a flexible exchange rate favorable to export expansion and consistent with Niger as a small open economy will be better than the actual fixed exchange rate with the Euro.
Better fiscal policies toward enhancing trade and investment should be considered in Niger because of its large dependence on foreign aid and its unfavorable geographical position (landlocked country).
Illegal trade activities like smuggling, drug trafficking, etc… are some major problems being faced by Niger across the borders and even within the country. Therefore, the government needs to reduce import tariffs and secure more the borders in order to discourage or prevent these underground activities.
Good new oriented investments’ policies are needed in order to boost the exports of manufactured products instead of relying only on raw materials specifically uranium and the recently discovered oil because Niger’s economy suffered a lot from international shocks such as recession and inflation due to its high dependence on the trade of these raw materials.
Diversification of trade partners is another key aspect to be considered in order to gain more from trade.
Agriculture accounts much in the GDP of Niger, so encouraging agricultural production through subsidies or tax reduction will be of great interest for the country.
In spite of the much attention given to this study, we noted, however, that it has not been left without some limitations.
We well know that, the determinants of economic growth are many but due to the unavailability of the data, we could not enlarge the research using other important variables.
Also, Future research should use more advanced econometric tools for deeper analyses.
We would like to thank the NSFC 41272362 for all its supports in carrying out this study.