Regional financial integration, financial development and industrial sector growth in ECOWAS: Does institution matter?

Figures & data

Figure 1. Comparison of industry value-added of selected regions in the world in current US$.

Source: Author’s Sketch using data from World development indicators (2021)

Table 1. Variable definition and measurement

Variable	Definition	Measurement	App. exp.	Data source
cc	Control of corruption	Country’s score in units of standard normal distribution, ranging from −2.5 to 2.5 with 2.5 free from corruption	+	Kaufmann et al. (2010)
rq	Regulatory quality	Country’s score in units of standard normal distribution, ranging from −2.5 to 2.5 with 2.5 as the highest with respect to regulatory quality	+	Kaufmann et al. (2010)
instone insttwo instthree instfour	Government effectiveness) Political stability and absence of violence/terrorism Rule of law Voice and accountability	Country’s score in units of standard normal distribution, ranging from −2.5 to 2.5 with 2.5 highly effective; best politically stable; best with respect to rule of law; highest with respect to voice and accountability respectively	UFE in PCA	Kaufmann et al. (2010)
Ind	Industry value added	Values in constant 2010 US dollars	DV	World Development Indicator (2021)
fdm	Financial development measure by M2	Broad money as a percentage of GDP	+	World Development Indicator (2021)
fdp	Financial development in credit to the private sector	Domestic credit to private sector as a percentage of GDP	+	World Development Indicator (2021)
inf	Inflation rate	Inflation, GDP deflator (annual %)	+	World Development Indicator (2021)
lab	Labour force	People ages 15 and older who supply labor for the production of goods and services during a specified period	+	World Development Indicator (2021)
cap	Investment in capital	Gross fixed capital formation in constant 2010 US dollars	+	World Development Indicator (2021)
exch	Exchange rate	Official exchange rate, local currency unit per US$, period average	+	World Development Indicator (2021)
insq	Institutional quality	An index from principal component analysis using cc, rq, instone, insttwo, instthree, instfour	+	Estimated from equation (4)(4) $\begin{array}{rl}& inston{e}_{it}=t_1{P}_{1it}^T+t_2{P}_{2it}^T+t_3{P}_{3it}^T+\dots +t_A{P}_{Ait}^T+E\\ & insttw{o}_{it}=t_1{P}_{1it}^T+t_2{P}_{2it}^T+t_3{P}_{3it}^T+\dots +t_A{P}_{Ait}^T+E\\ & insthre{e}_{it}=t_1{P}_{1it}^T+t_2{P}_{2it}^T+t_3{P}_{3it}^T+\dots +t_A{P}_{Ait}^T+E\\ & instfou{r}_{it}=t_1{P}_{1it}^T+t_2{P}_{2it}^T+t_3{P}_{3it}^T+\dots +t_A{P}_{Ait}^T+E\\ & r{q}_{it}=t_1{P}_{1it}^T+t_2{P}_{2it}^T+t_3{P}_{3it}^T+\dots +t_A{P}_{Ait}^T+E\\ & c{c}_{it}=t_1{P}_{1it}^T+t_2{P}_{2it}^T+t_3{P}_{3it}^T+\dots +t_A{P}_{Ait}^T+E\end{array}$(4)
rinteg	Regional integration	Quadratic difference between a country’s interest rate spread and an equally weighted average spread for countries in the region	+	Estimated from equation (2)(2) $rinte{g}_{it}={\left(ir{s}_t^i-\frac{\sum _{i=1}^{N}ir{s}_t^j}{N}\right)}^2\left(N=15\right)$(2)
irs	Interest rate spread	lending rate minus deposit rate, %	UFE	World Development Indicator (2021)

Note: Data are all for country i at time t; PCA implies that the variables were used in the principal component analysis; DV implies the dependent variable and UFE implies variable used for estimation

Table 2. Descriptive statistics of variables employed

Variables	count	Mean	Sd	min	max	Sum
cc	315	−.61	.53	−1.70	1.14	−193.09
rq	315	−.62	.40	−2.02	.13	−195.39
ind (US $)	322	8.41 billion	23.3 billion	18.4 million	111 billion	2.71 trillion
fdm (%)	350	27.35	17.50	5.14	104.63	9571.90
fdp (%)	349	14.86	12.25	0.00	65.74	5185.33
inf (%)	355	7.25	12.57	−7.90	100.66	2573.36
lab	360	6.66 million	11.8 million	131,118	63.2 million	2.40 billion
cap (US $)	295	6.42 billion	15.9 billion	−37.4 million	78.2 billion	1.89 trillion
exch	360	883.63	1627.84	.16	9183.88	318,105
rinteg	360	40.12	34.84	.06	234.59	14,443.25
insq	314	−2.42e-10	1.00	−2.08	3.01	−7.59e-08

Source: Author’s computation using data from world development indicators (2021)

Table 3. Principal component eigen values & proportion for institutional quality index

Component	Eigenvalue	Difference	Proportion	Cumulative
Comp1	4.734	4.240	0.789	0.789
Comp2	0.494	0.112	0.082	0.871
Comp3	0.383	0.188	0.064	0.935
Comp4	0.194	0.076	0.032	0.968
Comp5	0.119	0.042	0.020	0.987
Comp6	0.076	-	0.013	1.000

Source: Computed with STATA 16 using data from world development indicators (2021)

Table 4. Correlation matrix of variables employed

Variables	(cc)	(rq)	(ind)	(fdm)	(fdp)	(inf)	(lab)	(cap)	(exch)	(rinteg)	(insq)
Cc	1.00
Rq	0.75***	1.00
Ind	−0.05	0.05	1.00
Fdm	0.70***	0.39***	−0.14**	1.00
Fdp	0.71***	0.48***	−0.09	0.90***	1.00
Inf	−0.06	−0.01	0.11**	−0.18***	−0.24***	1.00
Lab	−0.06	0.08	0.99***	−0.18***	−0.10*	0.12**	1.00
Cap	−0.002	0.07	0.99***	−0.13**	−0.05	0.11*	0.98***	1.00
Exch	−0.34***	−0.37***	−0.14**	−0.14***	−0.24***	0.09*	−0.13**	−0.14**	1.00
Rinteg	−0.20***	−0.25***	−0.24***	−0.18***	−0.28***	0.05	−0.25***	−0.27***	0.15***	1.00
Insq	1.00***	0.76***	−0.04	0.69***	0.71***	−0.05	−0.05	−0.00	−0.34***	−0.2***	1.00
*** p < 0.01 and significant at 1%, ** p < 0.05 and significant at 5%, * p < 0.1 and significant at 10%

Source: Author’s computation using data from world development indicators (2021)

Table 5. Hausman test result for models

Decision information	Model one	Model two	Model three	Model four
Hausman ${\chi }_{statistics}^2$ statistic = (b-B)’[(V_b-V_B)^(−1)](b-B)	30.38***	31.19***	27.27***	21.42**
Probability of chi2	0.0001	0.0003	0.0006	0.0293

*** p < 0.01 and significant at 1%, ** p < 0.05 and significant at 5%, * p < 0.1 and significant at 10%

Source: Author’s computation using data from world development indicators (2021)

Table 6. Cross-sectional dependence test

Method	Model one	Model two	Model three	Model four
M. H. Pesaran (2004) statistics	−2.791***	−1.313	−2.042**	−2.125**
Pesaran Pr.	0.0052	0.1891	0.0411	0.0336
Frees (2004) statistics	2.761***	2.223***	1.814***	2.171***
Critical values from Frees’ Q distribution
alpha = 0.10	0.4892	0.4892	0.4892	0.4892
alpha = 0.05	0.6860	0.6860	0.6860	0.6860
alpha = 0.01	1.1046	1.1046	1.1046	1.1046

*** p < 0.01 and significant at 1%, ** p < 0.05 and significant at 5%, * p < 0.1 and significant at 10%

Source: Author’s computation using data from world development indicators (2021)

Table 7. Panel unit root test by Pesaran

Variables	At level			At first difference
	Obs.	Z[t-bar]	P–value	Obs.	Z[t-bar]	P–value
lnind	292	1.375	0.915	277	−3.972***	0.000
fdm	314	0.254	0.600	297	−3.116***	0.001
fdp	313	−0.845	0.199	296	−3.932***	0.000
rinteg	330	0.798	0.788	315	−4.544***	0.000
inf	325	−6.143***	0.000
lnlab	330	−1.407*	0.080
lncap	263	1.368	0.914	248	−2.729***	0.003
lnexch	330	−2.257**	0.012
insq	240	0.393	0.653	225	−1.943**	0.026
rq	240	−1.532*	0.063	225	−5.960***	0.000

*** p < 0.01 and significant at 1%, ** p < 0.05 and significant at 5%, * p < 0.1 and significant at 10%

Source: Author’s computation using data from world development indicators (2021)

Table 8. Kao test for cointegration

Measure	Model one		Model two		Model three
Number of panels	15		15		15
Avg. number of periods	16.8		13.5		13.5
Modified Dickey–Fuller t statistics	−2.044**	0.020	−2.715***	0.003	−2.025**	0.021
Dickey–Fuller t statistics	−3.486***	0.000	−3.714***	0.000	−2.868**	0.002
Augmented Dickey–Fuller t statistics	−3.0648***	0.001	−2.837***	0.002	−2.286***	0.011

Using the Newey–West lags selection

*** p < 0.01 and significant at 1%, ** p < 0.05 and significant at 5%, * p < 0.1 and significant at 10%

Source: Author’s computation using data from world development indicators (2021)

Table 9. Long-run fixed effect panel regression result with Driscoll and Kraay efficient standard errors and quantile regression

	Model 1	Long-run Model 2	Model 3	Model 4	Quantile Regression
Variables	Fin. Dev	Institution	Index	Interaction	Q1 Reg.	Q2 Reg.	Q3 Reg.
Fdm	−0.004	−0.005	−0.005	−0.006	0.009	0.005	0.007
	(0.004)	(0.003)	(0.003)	(0.003)	(0.006)	(0.006)	(0.004)
Fdp	0.010	0.006	0.008	0.010	−0.027***	−0.021***	−0.027***
	(0.010)	(0.009)	(0.009)	(0.010)	(0.007)	(0.007)	(0.007)
Rinteg	−0.002	−0.001	−0.001*	−0.001	−0.000	−0.002**	−0.002***
	(0.001)	(0.001)	(0.001)	(0.001)	(0.001)	(0.001)	(0.001)
Inf	−0.001	−0.002*	−0.002	−0.002*	−0.003	0.000	−0.001
	(0.001)	(0.001)	(0.001)	(0.001)	(0.004)	(0.004)	(0.003)
Lnlab	0.984***	0.803**	0.616	0.597	0.609***	0.551***	0.534***
	(0.327)	(0.314)	(0.361)	(0.367)	(0.110)	(0.072)	(0.029)
Lncap	0.282**	0.378***	0.450***	0.429***	0.763***	0.706***	0.686***
	(0.044)	(0.090)	(0.112)	(0.110)	(0.079)	(0.047)	(0.022)
Lnexch	0.132*	0.129	0.169**	0.144**	0.020	−0.021	−0.021**
	(0.071)	(0.085)	(0.077)	(0.079)	(0.035)	(0.024)	(0.010)
Insq	-	-	0.008	-	-	-	-
	-	-	(0.076)	-	-	-	-
fdm*insq	-	-	-	−0.004	−0.026***	−0.019**	−0.007***
	-	-	-	(0.003)	(0.007)	(0.008)	(0.003)
fdp*insq	-	-	-	0.001	0.043***	0.032***	0.016***
	-	-	-	(0.004)	(0.010)	(0.011)	(0.005)
rinteg*insq	-	-	-	0.003*	0.007***	0.005***	0.002**
	-	-	-	(0.002)	(0.001)	(0.001)	(0.001)
Cc	-	−0.094	-	-	-	-	-
	-	(0.146)	-	-	-	-	-
Rq	-	0.363**	-	-	-	-	-
	-	(0.133)	-	-	-	-	-
Constant	−0.470	0.446	1.374	2.258	−4.420***	−1.716***	−0.824**
	(3.024)	(3.270)	(3.560)	(3.773)	(0.643)	(0.441)	(0.340)
Obs.	287	262	262	262	262	262	262
R-squared	0.679	0.700	0.687	0.699	-	-	-
Pseudo R^2	-	-	-	-	0.77	0.79	0.81
No of ct.	15	15	15	15	-	-	-
F—stat	634.6***	374.6***	542.7***	721.2***	-	-	-

*** p < 0.01 and significant at 1%, ** p < 0.05 and significant at 5%, * p < 0.1 and significant at 10%

Test for equality of Q1, Q2 and Q3 estimated coefficients: for fdm*insq, f-stat = 5.07***; for fdp*insq, f-stat = 4.82***; for rinteg*insq, f-stat = 2.07

Source: Author’s computation using data from world development indicators (2021)

Table 10. Short run dynamic fixed effect regression result

Variables	Model one	Model two	Model three
ECT	−0.237***	−0.340***	−0.315***
	(0.035)	(0.045)	(0.043)
Δfdm	−0.006*	−0.010**	−0.009**
	(0.004)	(0.004)	(0.004)
Δfdp	−0.003	−0.005	−0.004
	(0.005)	(0.006)	(0.006)
Δrinteg	0.001**	0.001*	0.001*
	(0.001)	(0.001)	(0.001)
Δinf	−0.001	−0.001	−0.001
	(0.001)	(0.001)	(0.001)
Δlnlab	−2.020*	−1.637	−2.150*
	(1.135)	(1.262)	(1.226)
Δlncap	−0.018	−0.036	−0.044
	(0.030)	(0.056)	(0.056)
Δlnexch	−0.069	−0.036	−0.028
	(0.073)	(0.130)	(0.129)
Δcc	-	−0.046	-
	-	(0.099)	-
Δrq	-	−0.100	-
	-	(0.120)	-
Δinsq	-	-	−0.051
	-	-	(0.049)

*** p < 0.01 and significant at 1%, ** p < 0.05 and significant at 5%, * p < 0.1 and significant at 10%

Source: Author’s computation using data from world development indicators (2021)

Kaufmann, D., Kraay, A., & Mastruzzi, M. (2010). . World Bank Policy Research Working Paper No. 5430 (Word Bank Group), http://papers.ssrn.com/sol3/papers.cfm?Abstract_id=1682130.

 Google Scholar

World Development Indicator. (2021). 2021 world development indicators. from https://databank.worldbank.org/source/world-development-indicators#

 Google Scholar

Pesaran, M. H. (2004). General diagnostic tests for cross section dependence in panels. Cambridge Working Papers in Economics No. 0435, University of Cambridge, Faculty of Economics

 Google Scholar

Frees, E. W. (2004). Longitudinal and panel data: Analysis and applications in the social sciences. Cambridge University Press.

 Google Scholar