5.1 Research methodology

This study investigates the possible effects of Guinea’s Import  in relation to economic growth. The study adopts measurable indicators of instruments of trade and economic growth as suggested by literature. According to literature, import substitution industrialisation policy is primed on the use of instruments of import trade policy such as tax (on the demand side) and subsidy. These variables are adopted in this study with some degree of modification. The modification is largely due to availability of suitable data and the challenges of finding accurate proxies.

According to previous studies, the importance of import trade openness to economic growth is substantial (Kandiero & Chitiga 2003; Klasra 2009). According to these authors, economic openness helps a country to leverage its comparative advantage by specialising in the production of goods and services that yield comparative advantage, while it imports those goods and services that yield comparative disadvantage. Stiglitz (2002) as well as Hill (2014) also buttress this asseveration. However, a few other studies found inconclusive evidence as regards the impact of import trade openness on economic growth (Wheeler & Mody, 1992; Ponce, 2006). By definition, economic openness depicts the extent to which an economy is opened to foreign competition, through its active participation in trade and investment. This relationship is largely captured through import/export nexus.

In this research, economic openness is proxied by tariff on all imported products from China (ALTAR). Tariff barrier is chosen as a proxy for economic openness in this study because the application of tariffs is one of the cardinal Launchpad of ISI, especially on imported manufactured products. Our choice of tariff barrier (on the demand side) also necessitated the inclusion of subsidy (on the supply side) to the estimation (SUBSY). Subsidy is proxied by total subsidy for all exports. We also introduced trade balance (TRDBAL), which is taken as a nominal value of balance of trade account. Other variables used in this study include employment in agricultural sector (AGRICEM), which is taken as a percentage of total employment. We use consumer price index to proxy inflation (INFLTN), and total government reserve (TTRESV) is used as a proxy for current account balance. This variable is also used to measure government policy on budget deficit (or surplus). Manufacturing value added (MANVADD) is used in this study to gauge the extent of material beneficiation during the periods covered in the study as a way of measuring the contributions of ISI to the industrialisation process of Guinea

Furthermore, literature suggests that various measures can be used to measure economic growth. For example, Hicks (1969) as well as other recent scholars (Allen & Ndikumana, 2000; Asiedu, 2002; Chakrabarti, 2003; Asheghian, 2004; Adams, 2009) have used real Gross Domestic Product (GDP) to proxy economic growth. However, Sen (1999) view economic growth from humanity perspective. According to Sen, economic growth is best measured through improvement in human capital development, household poverty reduction, social freedom, political opportunity, population growth and so on. In this study, real GDP is used as a measure of economic growth as the most convenient proxy.

5.2 Estimation technique

The data used in this study come from World Development Indicators (WDI), a branch of the World Bank. The dataset is for the period 1960 to 2016 (a 57 year period). The time range of the data is informed by the availability of usable data. However, there are missing data between the scopes of the study, but interpolation and extrapolation techniques were used to account for the missing data. This observation is reinforced by the fact that the macroeconomic policy framework, like the impact of trade on economic growth, normally takes a long time before its effects on macroeconomic fundamentals become evident (Root, 1994, Rodriguez and Rodrick, 2000). ).

The theoretical expectation is that there should be a positive and negative relationship between the response variable and the explanatory variables. The literature survey supports this hypothesis, as variations in macroeconomic fundamentals that are explanatory variable proxies are expected to affect Guinea ‘s economic growth based on considerations. In addition, economic growth should be positively correlated with total national reserves, as economies are expected to grow as export capacity increases more than imports. The next section deals with the specification of the model, the data analysis and the concluding remarks.

The econometric equation represents real growth as a response variable. As such, the following model is proposed for estimation:

GDPPPit=αi+β1TRDBALit+β2AGRICEMit+β3SUBSYit+β4INFLATIONit+β5TTRESVit+β6MANVADDit+β7ALTARit+eit

The estimation is conducted with fixed and random effect methods but Hausman test suggested the appropriate method. The study further estimated generalized method of moments (GMM) and system generalized method of moments (SGMM) to control for endogeneity.

5.2.1 Variables used in the model

GDPPP: Proxy for economic growth

TRDBAL: Trade balance

AGRICEM: Employement in agricultural sector

SUBSY: total subsidy for all export

INFLATION: Consumer price index

TTRESV: Total government reserve

MANVADD: tariff on all imported product from china

FDI: Chinese foreign direct investment

5.3 Data analysis

This study investigates the relationship between the measurable indicators of the impact of import on economic growth in time series. In the estimation, t depicts time and i depict country. The analysis begins with unit root test to determine stationarity of the times series data, which is a precursor for cointegration test; and closely followed by cointegration test, causality test, fixed and random effect methods estimation and generalized method of moments estimations.

Table 1 shows the stationarity test of the time series for this study. The study employed Levin, Lin and Chu (LLC), Im, Pesaran and Shin (IPS), Fisher-ADF, Fisher-PP and Breitung unit root detection techniques to establish existence of non-stationarity in the time series. The tests were conducted at none, only drift, drift and trend at levels for real Gross Domestic Product (GDPPPP) proxy for economic growth, trade balance (TRDBAL), employment in agricultural sector (AGRICEM), total subsidy for all exports (SUBSY), consumer price index (INFLATION), total government reserve (TTRESV), manufacturing value added (MANVADD) and tariff on all imported products

 

Series	Model	LLC	IPS	Fisher-ADF	Fisher-PP	Breitung
GDPPPP	None	3.29965 (0.9995)		0.81980 (0.9999)	0.54654 (1.0000)
	Constant	7.29908 (1.0000)	5.19415 (1.0000)	5.90698 (0.8230)	4.47550 (0.9234)
	Constant and trend	5.27847 (1.0000)	5.75999 (1.0000)	3.49940 (0.9671)	2.20169 (0.9945)	5.46066 (1.0000)
TRDBAL	None	-3.25927 (0.0006)***		29.8640 (0.0009)***	24.4340 (0.0065)***
	Constant	-0.49333 (0.3109)	-1.17539 (0.1199)	17.4146 (0.0657)*	13.6747 (0.1884)
	Constant and trend	-1.58761 (0.0562)	-1.57686 (0.0574)*	16.9419 (0.0757)*	12.3004 (0.2655)	-0.89240 (0.1861)
AGRICEM	None	-5.12480 (0.0000)***		52.7788 (0.0000)***	152.243 (0.0000)***
	Constant	-1.30676 (0.0956)*	-0.48333 (0.3144)	14.5473 (0.1495)	36.8959 (0.0001)***
	Constant and trend	-2.46955 (0.0068)***	-3.52006 (0.0002)***	29.7776 (0.0009)***	73.1319 (0.0000)***	-2.15951 (0.0154)**
SUBSY	None	0.03949 (0.5158)		20.2150 (0.0273)**	19.4534 (0.0349)
	Constant	-0.82244 (0.2054)	0.30383 (0.6194)	16.0940 (0.0970)*	9.59429 (0.4768)
	Constant and trend	0.45529 (0.6755)	-0.55338 (0.2900)	38.9620 (0.0000)***	50.9475 (0.0000)***	3.27901 (0.9995)
INFLATION	None	4.55982 (1.0000)		2.11047 (0.9954)	1.62007 (0.9985)
	Constant	7.17135 (1.0000)	7.73708 (1.0000)	0.77843 (0.9999)	0.62692 (1.0000)
	Constant and trend	1.70677 (0.9561)	5.00646 (1.0000)	1.92566 (0.9969)	0.87679 (0.9999)	7.13527 (1.0000)
TTRESV	None	-0.80208 (0.2113)		28.1538 (0.0017)***	21.6518 (0.0170)**
	Constant	0.80421 (0.7894)	1.64600 (0.9501)	15.9671 (0.1006)*	11.6742 (0.3075)
	Constant and trend	-1.13564 (0.1281)	1.53380 (0.9375)	7.70726 (0.6574)	2.77841 (0.9862)	4.45328 (1.0000)
MANVADD	None	-1.31781 (0.0938)*		10.8439 (0.3698)	9.66888 (0.4700)
	Constant	1.35488 (0.9123)	1.24330 (0.8931)	6.98164 (0.7272)	7.85756 (0.6427)
	Constant and trend	-0.50277 (0.3076)	0.65722 (0.7445)	6.47252 (0.7741)	5.76989 (0.8342)	0.85086 (0.8026)

Table 4- 1. 
Panel unit root test results.

Notes: Null: Unit root (assumes common unit root process): Levin, Lin & Chu (t*) and Breitung (t-stat)

Null: Unit root (assumes individual unit root process): Im, Pesaran and Shin (W-stat), ADF – Fisher (Chi-square) and PP – Fisher (Chi-square)

***, ** and * are 1%, 5% and 10% significance level respectively

Trace test				Maximum Eigenvalue test
H0	H1	λ-trace statistic	p-value	H0	H1	λ-max statistic	p-value
GDPPPP, AGRICEM, ALTAR, INFLATION, MANVADD, SUBSY, TRDBAL and TTRESV
r=0	r≥1	255.6	0.0000*	r=0	r≥1	117.8	0.0000*
r≤1	r≥2	148.7	0.0000*	r≤1	r≥2	89.32	0.0000*
r≤2	r≥3	69.90	0.0000*	r≤2	r≥3	34.80	0.0001*
r≤3	r≥4	40.18	0.0000*	r≤3	r≥4	18.71	0.0442*
r≤4	r≥5	25.95	0.0038*	r≤4	r≥5	12.22	0.2705
r≤5	r≥6	18.96	0.0408*	r≤5	r≥6	9.028	0.5295
r≤6	r≥7	14.68	0.1442	r≤6	r≥7	11.49	0.3205
r≤7	r≥8	9.837	0.4549	r≤7	r≥8	9.837	0.4549

Table 4-2. Panel cointegration test result

Notes:Probabilities are computed using asymptotic Chi-square distribution.

• Rejection of the null hypothesis of no cointegration at least at the 10% level of significance.

Model	Null hypothesis	w-statistic	zbar-statistic	p-value	Direction of relationship observed
A	AGRICEM does not homogeneously cause GDPPPP	3.25963	1.21098	0.2259	No Causality
	GDPPPP does not homogeneously cause AGRICEM	3.52554	1.48473	0.1376
B	ALTAR does not homogeneously cause GDPPPP	4.64402	2.63619	0.0084***	ALTARGDPPPP
	GDPPPP does not homogeneously cause ALTAR	7.75242	5.83624	0.0000***
C	INFLATION does not homogeneously cause GDPPPP	10.0154	8.16592	0.0000***	INFLTNGDPPPP
	GDPPPP does not homogeneously cause INFLATION	3.59908	1.56044	0.1187
D	MANVADD does not homogeneously cause GDPPPP	8.13984	6.23508	0.0000***	MANVADDGDPPPP
	GDPPPP does not homogeneously cause MANVADD	4.96792	2.96964	0.0030***
E	SUBSY does not homogeneously cause GDPPPP	4.12593	2.10283	0.0355**	SUBSYGDPPPP
	GDPPPP does not homogeneously cause SUBSY	5.44210	3.45780	0.0005***
F	TRDBAL does not homogeneously cause GDPPPP	7.48152	5.55736	0.0000***	TRDBALGDPPPP
	GDPPPP does not homogeneously cause TRDBAL	6.88867	4.94703	0.0000***
G	TTRESV does not homogeneously cause GDPPPP	8.22896	6.32683	0.0000***	TTRESVGDPPPP
	GDPPPP does not homogeneously cause TTRESV	3.89573	1.86584	0.0621*

Table 4-3. Panel causality test results.

Notes: ***, ** and * are 1%, 5% and 10% significance level respectively.

(ALTAR). We adopted a series of unit root tests to establish a method that would increase deficiency in the other.

Unit root tests reveal that real GDP is not stationary at the level of

Shin (IPS), Fisher-ADF, Fisher-PP and Breitung unit root tests, without drift or trend, with drift and trend with drift estimation. These results suggest that we need to make a first estimate of the differences for real GDP series in Guinea. Unit root tests also reveal that most import indicators such as the trade balance (TRDBAL), employment in the agricultural sector (AGRICEM), total subsidy for all exports (SUBSY), consumer price (INFLATION), a strong order of integration, given that a Levin, Lin and Chu (LLC), Im, Pesaran and Government Reserve (TTRESV), Manufacturing Value Added (MANVADD) and Customs Duties on All Imported Products (OPEN) in Guina are not stationary at the level using the unit root tests of Levin, Lin and Chu (LLC), Im, Pesaran and Shin (IPS), Fisher-ADF, Fisher-PP and Breitung. These unit root test results suggest the need for a cointegration test for a long – term relationship between economic growth on import and import  Estimators on Guinea (Table 2).

In this study, we performed a Johansen-Fisher co-integration test in which the null hypothesis is not co- integration. The Johansen-Fisher cointegration test is superior to other residual-based one-way cointegration tests because it generates results for the entire time series. The estimate follows autoregressive process vector (VAR) for the combination of the time series using Fisher-Trace and Fisher-maximum tests at eigenvalues. The series results from cointegration tests show that six tests of trace value statistics are in favour of the existence of cointegration in the series and four tests of the maximum value of eigenvalue statistics show the presence of cointegration in Series. Thus, at least ten vectors of the cointegration equations have presence of cointegration series. This indicates that there is a long-term relationship between economic growth (GDPPPP) and measurable indicators of the ISI – trade balance (TRDBAL), employment in the agricultural sector (AGRICEM), total subsidy for all exports (SUBSY), consumer price index (INFLATION), total government reserve (TTRESV), manufacturing value added (MANVADD) and tariffs on all imported products (ALTAR)). The direction of the relationship between the combined variables is then assessed through the Dumitrescu – Hurlin causality test (2012).

The Dumitrescu – Hurlin causality test is adopted because of its superiority over other methods of causality (Geweke , 1984). The causality test is performed to determine the causality between the variables considered – economic growth (GDPPPP), trade balance (TRDBAL), employment in the agricultural sector (AGRICEM), total subsidy for all exports (SUBSY), price index to consumption (INFLATION) , total government reserve (TTRESV), manufacturing value added (MANVADD) and tariffs on all imported products (ALTAR) in Guinea. The study conducted a univariate causality test in which the causal effect of ISI indicators and economic growth are introduced into the system separately – one after the other. Null hypotheses are not “homogeneous cause” and if not, the study rejects null hypotheses.

The empirical results in Table 3 show that there is no causal relationship between economic growth (GDPPPP) and employment in agriculture (AGRICEM) in Guinea, but there is a one-way causal relationship of the price index to the consumption (INFLATION) to economic growth (GDPPPP). And the remaining indicators (duties on all imported products (ALTAR), manufacturing value added (MANVADD), total subsidy for all exports (SUBSY), trade balance (TRDBAL) and total government reserve (TTRESV)) have a causal relationship bidirectional with growth (PIBPPP) in Guinea countries. Once this is done, it is considered important to determine the properties of the effects of the model for the estimation (Table 4).

The Hausman test is used to determine the appropriate serial model (fixed or random effect) for the estimation of economic growth in Guinea Country S The result of the Hausman test for the economic growth model in Guinea shows that the chi-square is 120,31 and the probability value is 0.0000. The study rejects the null hypothesis (H0) since the p value of the chi squared is less than 1% of the significance level (ie 0.0000 o 0.01), so the fixed-effect model is considered appropriate for the estimate of economic growth in Guinean countries. However, fixed-effects modelling can be expensive in terms of degrees of freedom if there are multiple cross-sectional units (Baltagi and Levin 1992, Gujarati and Porter 2009). However, since the Hausman test favoured the fixed effects model, the study used a fixed effects model to estimate the effects of the ISI variables on economic growth in the Guinea countries.

Hausman test
	Economic growth model
chi-square	10,120.31***
p-value	0.0000

 

Table 4-4. Model specification test.

 

Notes: H₀: Random effect model is appropriate, H₁: Fixed effect model is appropriate

***, ** and * are 1%, 5% and 10% significance level respectively.

Independent variables	Fixed effect	Random effect
Constant	6.626733***	7.832581***
	[13.32]	{12.86}
	(0.000)	(0.000)
TRDBAL	2.79000***	2.72000**
	[3.49]	{1.97}
	(0.001)	(0.049)
AGRICEM	-0.0338484***	-0.2187492***
	[-3.13]	{-23.26}
	(0.002)	(0.000)
SUBSY	-0.001031	0.0147716***
	[-0.29]	{2.80}
	(0.768)	(0.005)
INFLATION	0.016875***	0.0035558
	[7.25]	{1.03}
	(0.000)	(0.302)
TTRESV	0.4582848***	0.137965
	[4.35]	{0.79}
	(0.000)	(0.431)
MANVADD	-0.0824531***	-0.0373277*
	[-4.66]	{-1.89}
	(0.000)	(0.058)
ALTAR	-0.0065146	0.0230409***
	[-1.24]	{2.77}
	(0.214)	(0.006)
Total panel observations	285	285
R-square	0.6080	0.3393
F-statistic	60.49***	–
	(0.0000)

Table 4-5. FEM and REM result analysis for economic growth in BRICS countries (Dependent variable: GDPPPP).

Notes: Values in parentheses [], { } and () are t-statistic, z-statistic and p-value.

***, ** and * are 1%, 5% and 10% significance level respectively

The combined empirical results for economic growth using fixed and random effects models are presented in Table 5. The exact model for this study is the fixed effects model as suggested by the Hausman test but the random effects model is also estimated. The fixed-effect model revealed that the trade balance has a significant positive impact on economic growth at the 99 percent level of confidence in Guinea countries, and the consumer price index has a positive impact on growth. with 1 per cent the level of statistical significance in Guinea. The empirical results further revealed that the total government reserve has a positive impact on economic growth with a statistical significance of 1% in Guinea.

Employment in the agricultural sector and manufacturing value added are negatively related to economic growth, but statistically significant at a level of significance of 1% in Guinea. But the total subsidy for all exports and all tariffs on all imported products has a negative impact on economic growth and is statistically insignificant for the economy.

Independent variable	One-step estimation
	GMM	SGMM
Constant	0.0312701	-0.2046154**
	[0.27]	[-2.33]
	(0.791)	(0.020)
GDPPPP (-1)	0.9760463***	0.9904788***
	[88.63]	[141.91]
	(0.000)	(0.000)
TRDBAL	5.5000***	5.06000***
	[3.85]	[4.59]
	(0.000)	(0.000)
AGRICEM	0.0025036	0.0029819*
	[1.25]	[1.79]
	(0.210)	(0.073)
SUBSY	0.0004308	0.0006391
	[0.69]	[1.21]
	(0.490)	(0.226)
INFLATION	0.0010046**	0.0012778***
	[2.23]	[3.52]
	(0.026)	(0.000)
TTRESV	0.1044181***	0.0984164***
	[5.18]	[5.66]
	(0.000)	(0.000)
MANVADD	0.0004414	0.0062897**
	[0.13]	[2.29]
	(0.895)	(0.022)
ALTAR	0.0042075***	0.0057792***
	[4.12]	[6.63]
	(0.000)	(0.000)
Number of observations	275	280
Number of groups	5	5
Observations per group	55	56
Number of instruments	273	328
Wald χ2	20,795.30***	48,087.78 ***
	(0.0000)	(0.0000)

Table 4-6. GMM and SGMM result analysis for economic growth (Dependent variable: GDPPPP).

Notes: Values in parentheses [] and () are z-statistic and p-value.

***, ** and * are 1%, 5% and 10% significance level respectively

GMM: Arellano-Bond dynamic panel-data estimation

SGMM: Arellano-Bover/Blundell-Bond system dynamic panel-data estimation

growth in Guinea at least at the level of 10% significance. The results imply that an increase of 1 unit in the trade balance, the consumer price index and the total government reserve increases economic growth in Guinea; but 1 unit of decrease in employment in the agricultural sector, total subsidy for all exports, value added manufacturing and tariffs on all imported products increase the level of economic growth in Guinea.

The random effects model shows that the trade balance, employment in the agricultural sector, total subsidy for all exports, manufacturing value added and tariffs on all imported products are statistically significant for economic growth. are statistically insignificant for economic growth at least at a level of 10% significance in Guinea. The overall importance of the regressors (trade balance, employment in the agricultural sector, total subsidy for all exports, consumer price index, total government reserve, manufacturing value added and tariffs on all imported products) is evaluated. by the F statistic. The F statistic is 60.49 with a probability value of 0.0000; and since the probability value is less than 1% (0.0000-0.01), it is suggested that the explanatory variables are statistically significant for economic growth in Guinea.

The R-squared shows the rate of change in economic growth caused by the exact components (trade balance, employment in the agricultural sector, total subsidy for all exports, consumer price index, total government reserve, manufacturing value added and tariffs on all imported products) of the model. The result shows that R-squared is 0.6080, which implies that the exact components of the model caused 60.8% of variation in economic growth, but that the random terms caused 39.2% variation in economic growth in Guinea.

Empirical results of the effect of economic growth retardation, the trade balance, employment in the agricultural sector, total subsidies for all exports, the consumer price index, total government reserves, of manufacturing value added and customs duties 6, in which the one-step generalized method of moments (GMM) technique and the generalized system moments method (SGMM) were used.

The GMM dynamic time series estimation Arellano-Bond and Arellano-Bover / Blundell-Bond dynamic time series estimation were used to estimate the short-run coefficients of lag of economic growth, trade balance, employment in the agricultural sector, total subsidy for all exports, consumer price index, total government reserve, manufacturing value added and customs duties on all products imported into Guinea. The study also estimated the Generalized Moment Method (MGM) and Generalized System Moment Method (SGMM) to control any endogeneity that may exist in the fixed effects model.

The empirical results of the generalized method of a step of moments (GMM) estimation of the Arellano – Bond dynamic series show that the lag of economic growth, the trade balance, the consumer price index, the total government reserve and tariffs on all imported products are statistically significant at economic rights growth in Guinea at least at a level of significance of 5%. But, employment in the agricultural sector, total subsidy for all exports and manufacturing value added are statistically insignificant for economic growth in Guinea at least at the 10% level of significance.

The overall common importance of the delay in economic growth, the trade balance, employment in the agricultural sector, total exports, the consumer price index, the total government Value added manufacturing and customs duties Wald Chi square test. The chi square of Wald is 20.795.30 with the probability value of 0.0000. This implies that the lag of economic growth, the trade balance, employment in the agricultural sector, total subsidy for all exports, the consumer price index, the total government reserves, the value added manufacturing and tariff on all imported products are jointly significant to economic growth in Guinea.

Test	Economic growth model
	GMM	SGMM
Sargan test of overidentifying restrictions	chi2(264) = 467.92	chi2(319) = 749.7142
	prob. > chi2 = 0.0000	prob. > chi2 = 0.0000

Table 4-7. Diagnostic test for one-step estimations.

Note: Sargan test of overidentifying restrictions: H₀: overidentifying restrictions are valid

The results of the Arellano-Bover / Blundell-Bond dynamic time series generalized moments method (SGMM) system shows that the lag of economic growth, the trade balance, employment in the agricultural sector, the index consumer prices, total government reserve, manufacturing value added and tariffs on all imported products are statistically significant for economic growth in Guinea at least at the 10% level of significance. The common meaning of lagging economic growth, trade balance, employment in the agricultural sector, total subsidy for all exports, consumer price index, total government reserve, manufacturing value added and tariffs Customs on all imported products to economic growth in Guinea is validated by Wald Chi Square of 48,087.78 with a probability value of 0.0000 in SGMM estimate.

The results of GMM and SGMM show that the economic stunting, trade balance, employment in the agricultural sector, the total subsidy for all exports, the consumer price index, the total government reserve, the value manufacturing and short-term tariffs, but the impact of the explanatory variables on economic growth is mixed in the long run, as shown by the fixed-effects model (FEM) in Guinea. The mixed results suggest the need for additional robustness control, which has led to the use of the Sargan test to establish the validity of the instruments.

Following the estimates, Table 7 presents the results of the diagnostic tests of the dynamic economic growth model. It is important to emphasize that the validity of the generalized momentum methods (MGM) and the generalized system-wide methods (SGMM) is strictly dependent on the Sargan test diagnostic tests of the overidentified restrictions for the instrumental variables. Dynamic time series models (GMM and SGMM) do not assume normality and allow for heteroscedasticity that can be controlled by valid instrumentation (Baltagi , 2008). Thus, the study used the Sargan test of overidentifying restrictions to validate the instruments of the models estimated in this study.

Sargan’s tests evaluate all the instruments for identifying models. The results for the economic growth model show that chi-square statistics and p-values ​​are, GMM: chi2 1/4 467.92 with p-value 1/4 0.0000; and SGMM: chi2 1/4 749.7142 with p-value 1/4 0.0000. As such, the study rejects the null hypothesis and concludes that the restrictions on identification are not fully valid. This implies that some of the model’s instruments are not valid but that the power properties of the model are sufficient for policy making since Wald’s chi square confirms the joint importance of the key instruments in the estimation, namely the balance. trade, employment in the agricultural sector, subsidy for all exports, consumer price index, total government reserve, manufacturing value added and tariffs on all products imported for economic growth in Guinea.

We also examine the resilience of instruments to innovation shocks to determine their response model and speed. This is done by the impulse response analysis, which we build on the vector error correction model (not reported). The result of the impulse response is shown in FIG. 1:

The results in Figure 1 show the response of economic growth to Cholesky: a standard deviation / innovation shock in the trade balance, employment in the agricultural sector, total subsidy for all exports, index of consumer price, the total government reserve, all products imported into Guinea. The impulse response measures the shock of the unit applied to each series and its effect on the VAR system. The essence of this is to detect the time path of various shocks and how the VAR system responded to shocks.

Fig. 4-1. : Cholesky one standard deviation/innovation shocks in growth model.

The series (a) in Figure 1 revealed that economic growth has responded positively to a standard deviation / innovation both in the short and long term. In the beginning, the positive reaction of economic growth to own shocks is a growing trend in period 10 but began to collapse in the 11th period up to the 57th period in Guinea. Trade balance shocks have little or no effect on Guinea’s economic growth in both the short and long run, as shown by the series (b) in Figure 1, the trend in the standard deviation of the trade balance is around zero.

In addition, economic growth in Guinea has responded to negative agricultural employment shocks both in the short run and long as shown in series (c) of Figure. 1. Tariff shocks on all imported products also have a positive reaction to short-term economic growth in Guinea, but series (d) in Figure 1 shows a decreasing reaction to long-term economic growth. The series (e) in Figure 1 shows that total subsidy shocks for all exports hamper economic growth in Europe. Guinea with a negative response in the short and long term. The series (f) in Figure 1 shows that economic growth in Guinea reacted positively to innovations in the consumer price index in the short and long run, but peaked in the 22nd. The innovations in the total government reserve have positive reactions to economic growth in Guinea both in the short term and long revealed by the series (g) in the figure. 1. Although, economic growth reacted to innovations in negative short-term manufacturing value added, but in period 22, economic growth started a positive reaction to shocks in the value-added manufacturing sector until the 57th period.

5.4 Tests in time series

5.4.1 Heteroskadacity test

In order to check if our residualare Homoscedastic or Heteroskedastic we perform this test we settle the hypothesis.

H0: The residual are Homoskedastic

H1: The residual are Heteroskedastic

Hederoskedasticity Test: Breusch-Pagan-Godfrey
F-statistic	0.907213	Prob. F(3,25)	0.4516
Obs*R-squared	2.847144	Prob.Chi-Square(3)	0.4158
Scaled explained SS	1．144876	Prob. Chi-Square(3)	0.7663

图4-8 Breusch-pagangodfrey 异方差检验

Figure 4‑8 Heteroskedasticity Test Breusch-pagangodfrey

The probability is Prob = 0.4156>0.05(the critical value) we fail to reject the null hypotheses and conclude that the residual are Homoskedacity.

5.4.2 Serial correlation test

To check if there are serial correlation in our model we shall perform a serial correlation test our starting point is settle hypothesis. Which is good for our model.

H0: There is no serial correlation in the residual

H1: There is serial correlation in the residual

Breush-Godfrey Serial Correlation LM Test:
F-statistic	0.259452	Prob. F(2,22)	0.7738
Obs*R-squared	0.668247	Prob. Xhi-Square(2)	0.7160

图4-9 Breusch-Godfrey自相关检验

Figure 4‑9 Breusch-Godfrey Serial Coration LM Test

The probability is Prob= 0.716>0.05(the critical value) we fail to reject the null hypotheses and conclude that there is no serial correlation in the residual. Which good for our model

5.5 Regression results

After using Ordinary Least Squared method, the result are as followed

Dependent Variable: GDP

Method: Least squares

Date:04/03/18 Time 12:12

Sample (adjusted) 1986 2015

Included observations: 30 after adjustments

Convergence achieved after 40 iterations

Variables	Coefficient	Std. Error	T-Statistic	Prob.
IMPRT	1.887439	0.397040	4.753782	0.0001
EXPRT	0.399015	0.498661	0.800172	0.4311
FDI	-0.923998	0.437885	-2.110141	0.0450
INFL	-31723342	6889450.	-4.604626	0.00001
C	2.05E+09	2.05E+08	9.998190	0.00000
R-squared	0.926169	Mean Dependent Var		3.76E+09
Adjusted R-squared	0.914355	S.D. dependent var		1.27E+09
S.E. of regression	3.71E+08	Akaike info criterion		42.45486
Sum squared resid	3.45E+18	Schwarz criterion		42.68839
Log likelihood	-631.8228	Hannan-Quinn Criter.		42.52956
F-statistic	78.40222	Durbin-watson stat		1.512287
Prob(F-statistic)	00.000000

图4-10普通最小二乘法回归结果

Figure 4‑10 Ordinary Least Squared Results

GDP = 2.28E+09+1.956*IMPRT  – 1.057*FDI –  2124073*INFL

S.E      3.08 E+08            0.2548             0.430          8449953

T-stat     7.4023                7.677                2.454            2.513

R-square 93%                                                                 D.W 1.9488

The variables Import (Importation), FDI (Foreign Direct Investment), INFL (Inflation rate) are all significant variables. Import, Inflation is significant at 1% level but the variable FDI is significant at 5% level.

The variables Import, has a positive impact on GDP while FDI and inflation have a negative impact on GDP.

The Importation of Guinea import from china has a positive impact on Guinea’s economy indeed an increase of one unite of Guinea’s importation from China will lead to an increase of 1.95 unite of its economy ceteris parabus .This is because China being Guinea first Import partner , the majors part of Guinea’s import from China is Machinery. Importing machinery mean import of technology us Cobb-Douglas production function have demonstrate technology has a positive impact on economic growth.

Foreign direct investment to Guinea has a negative impact on Guinea‘s economy. Indeed an increase of one unite of Foreign Direct Investment to Guinea will decrease Guinea economy by 1.05 unite ceteris parabus. Inflation by the same way has a negative impact on Guinea’s economy an increase of inflation rate by one unite will lead to a decrease of 212407031unite.

6 CONCLUSION AND SUGGESTIONS

6.1 Conclusion

China has become an important player in the global economy and is impacting almost every country in the world. Guinea has maintained steady diplomatic ties with China since 1958 just after Guinean Independence. Economic interactions are evolving rapidly, and providing Guinea with alternative sources of finance and helping to diversify its market outlets. These interactions are engendering both winners and losers among the two Countries and the relevant stakeholders in Guinea. The implication is for authorities to device means of enhancing the gains while addressing the losses, rather than relying on the rhetoric of win-win partnership and reciprocal benefits frequently proclaimed by the Chinese leadership.

Import with China has increased considerably over the past few years. This has however been due to a surge in Machinery and Textile imports from China. Imports from China are providing cheap and diverse consumption and capital goods, though issues of quality abound. The Imports are made up of a large variety of essentially manufactured goods. This raises the risk of undermining the industrial sector and locking Guinea in primary activities.

Since 2007, China have become Guinea’s major trading partner, supplying on average about 20.4% of its imports. China’s share of imports increased from 2.7 to 5% between 2001 and 2005, while those of the traditionally trade partner (Europen country) stayed the same during the same period. China then moved from the 5% in 2005 to become Guinean’s first import source.

An assessment of the impact of trade with China has revealed both winning and losing stakeholders in Guinea. As concerns the welfare impact on consumers, many Guinean are sensitive to the origin of goods they consume and a large proportion of them consume Chinese goods, though acknowledging that they are of lower quality compared to European or US goods.

Chinese imported Machinery like telephone are substantially complementing the telecommunication and have contributed to the Growth of that sector from 100% to 150% since 2007. This have led to the increase of Telecommunication Services, the creation of many jobs, many out of poverty, and increased government revenue; though there are concerns related to Quality problems. Also in the the import of electric transformers and Portable Electric Lamp have Improve the electricity problems in Rural areas that helping the creation of an amount of small and middle enterprises the last years.

There is a need for the two countries to sort out ways to the language, financial, and quality problems that facing their bilateral Trade relationship, also there is need for Guinea to sort out ways of releasing some of the competitive pressures on the local industry, measures need to be taken to effectively downsize the fraudulent entry of Chinese goods into the country so as to compete fairly with local firms.

The literature review laid the conceptual foundation for the relevance and adequacy of imports from China as a growth engine in Guinea economic growth at the beginning of the last 50 years. Reference was made to the important roles played by the macroeconomic and import trade policy framework put in place by Guinea during that period. Clearly, the desirability of this political intervention by Guinea to catalyze the process of industrialization was justified by the fact that all the now developed economies have adopted import substitution industrialization at some point in their trade history before adopting economic liberalization when they reach a certain threshold of industrial development.

The results of the empirical analyzes were numerous. In the first case, the cointegration tests show a long-term relationship between the variables considered. It has been established that there is a significant relationship between the dependent variable (real growth) and the measurable indicators of Guinea import from China substitution industrialization policy framework. The causal tests that follow suggest a strong causal relationship between the variables. The strong bidirectional causal relationship between growth and tariffs on all imported products is particularly interesting. This result suggests that the reduction of all imported products could slow down growth. The result clearly indicates that prudent but prudent management of the tariff regime is important to stimulate growth. The same can be said of all the other variables, except for employment in the agricultural sector (AGRICEM), which has no causal link with growth, and inflation, which shows a unidirectional causal relationship with growth – strongly moving from inflation to growth. The overall conclusion of this result is a strong indication that most of the measurable indicators of Guinea import from China influence growth.

In addition, the result of the relationship between growth and Import from China measurable indicators, using both GMM and SGMM, as well as one-step estimates in GMM and SGMM suggest a strong relationship between growth and import measurable indicators. The close relationship between growth and the trade balance is particularly interesting, suggesting that an improvement in the trade balance, which is the prime macroeconomic objective of the import substitution industrialisation, will enhance growth. The analysis also suggests that a reduction in primary sector employment (agriculture) will fuel growth, in the same vein, as a reduction in the export promotion-oriented subsidy would help galvanize growth. In addition, the analysis shows that the creation of manufacturing value added will galvanize growth, mainly because of inflationary pressure on growth. The conclusion also indicates that import tariffs should be managed with caution because of their negative effects on growth, particularly in the case of fixed-effect GMMs. This may imply that most imports are made from manufacturing materials and machinery.

Concluding the analyzes, the analysis of the impulse response suggests that the economy to grow responds to imports from China to the unit over the period considered, while the reaction to the subsidy was negative, but slightly more resilient than the employment in the agricultural sector. This result indicates that any shock on these two variables (AGRICEM and SUBSY) will negatively and significantly hamper growth. This strongly supports the underlying principles of the ISI and gives credibility to the strategic importance of restrictive import trade instruments on the effective implementation of the ISI, especially in the short term. In addition, the response of growth to innovation shocks stimulates growth, which then slowly rebounds towards decline, as opposed to the innovation shock on manufacturing value added that triggered a significant and spontaneous decline in long term growth.

The analyzes contained in this study clearly demonstrate the strategic importance of macroeconomic import policy which has been a catalyst for catapulting the Guinean economy from dependence on industrialization that could ultimately help to build export capacity. The analyzes confirm short – and long – run relationships between growth and import from measurable indicators in China, in a chronological manner that supports short – term import substitution and long – term export promotion. This confirms the prodigiousness of Mill’s concomitant method of variation, not only in the application of political initiatives, but also in the outcome of such policies.

A conclusion can therefore be drawn from both literature and econometric estimates that China ‘s macroeconomic import policy defies the self – defeating prophecy thrown at it by the consensus institutions of Washington and other adversaries. Essentially the criticisms that the policy stimulates economic discouragement, delays growth and kills competition in the domestic industrial sector – all that has been established in this study is inadequate and somewhat inappropriate. It is therefore suggested that Guinea and developing economies, particularly the least industrialized ones, consider short-term import substitution and long-term export promotion as the country develops sufficient production capacity to stimulate the growth of exports.

6.2 Suggestions

As we now know that Guinea’s imports from China have a positive effect on the Guinean economy, it is important to find ways to improve them.

Thus, in order to improve the impact of imports, it will be important to make some suggestions.

Taking into account that the official commercial language of Guinea is French and that the Chinese language is Mandarin and English. It would be important for both countries to set up training centers in Chinese, English, and French. The Guinean traders can learn Chinese or English and Chinese traders will learn English or French. This could enable them to take advantage of trade opportunities between the two countries.

Concerns about insecurity and the environment are worrying. Policy makers should implement a policy that would reduce imports of very poor quality products. This could push the Guinean importers to stop buying products of very poor quality at low prices to resell them expensive in Guinea. This will reduce the quality problems faced by Guinean consumers. And at the same time, it can also change the stereotypes that all Chinese products are of poor quality.

On the financial side, officials should encourage Chinese and Guinean financial institutions to collaborate and improve the problems of the Guinean bank’s payment system. This could facilitate the problems of financial transactions.

As noted, no country in the world seems to have developed or modernized its economy in a sustainable way without structurally transforming its agriculture to the point of take-off as a way forward. We believe that Guinea now has the opportunity to transform its agricultural account of price measurement by the Guinean Commercial Policies on the agriculture sector and to benefit from the Chinese growth through trade, the two countries as organizer of the Fair Trade between the two countries on agricultural product and technology.

To free some of the competitive pressures on local industry, steps must be taken to effectively reduce the fraudulent entry of Chinese products into the country in order to compete fairly with local businesses. The government could also protect certain strategic sectors by interacting with China for a voluntary restriction on certain exports. Guinea can not negotiate any unilateral trade agreement with China, given its obligations as a member of the ECOWAS sub region.

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Appendix 1 

The impact of Chinese investment in Guinea

There is no hesitation that Chinese private investors have brought some welfares to the Guinean economy. They increased the stock of capital goods to the detriment of imports of cheap capital from China. They have also increased the manufacture of goods and services at lower cost such as the construction of the road in Conakry which has significantly improved traffic in this area. The local workforce gains from some of the job opportunities created by Chinese companies, especially as assistants in Chinese hotels and clinics, but also in Chinese yards and restaurants.

These are jobs that do not require specific, low-paying, short-term skills (some are dismissed as soon as the Chinese can communicate in local language – French or English) and workers do not have an employment contract with their employers Chinese. Local labor also loses as workers are laid off or wages reduced as local firms adjust or collapse due to Chinese competition. Even worse, Chinese companies import most of their workforce, even the unskilled. Overall, the local labor force could have been better if Chinese investors hired most of their labor force locally. It can also be said that the local labor force also benefits from a certain spill of skills by working with the Chinese, even if only inadvertently.

One particular case is the recent phenomenon of Guineans practicing traditional Chinese medicine. They claim to have studied in China, but many are understood to have acquired some minimal knowledge working in Chinese clinics in Guinea. The level of skill transfer of Chinese enterprises is certainly l