#19. Financial Development, Trade Costs and Bilateral Trade:

Connecting the Nexus in ECOWAS

By

John T. Odebiyi, Ph.D Candidate

Dept. of Economics and Development Studies, Covenant University, Ota, Nigeria

(john.odebiyi@covenantuniversity.edu.ng; jtpeter2001@yahoo.co.uk)

&

Evans S. OSABUOHIEN, Ph.D

 Dept. of Economics and Development Studies, Covenant University, Ota, Nigeria

(evans.osabuohien@cu.edu.ng; pecos4eva@gmail.com)

Work-in-Progress Submitted for ACRIA 6

Introduction

Some studies (e.g.  Kletzer and Bardhan, 1987; Do and Levchenko (2004 etc) have shown that financial development could be a source of comparative advantage for trading economies or trade partners; and, hence an important determining factor for trade flows. This appears to be logical, considering the importance of finance for the advancement of several economic activities.  Financial development (FD) entails as the set of policies and drivers of such policies, intermingling together within and in the global community to foster economic growth and development. It denotes the ability of the financial sector to actively play its intermediating role to enhance economic growth and development (Olayiwola et al, 2012). FD in both exporting and importing countries would be required to fund production and consumption respectively. FD could also determine the extent to which trade finance is available for financing exports and imports in partner countries.

Main Objectives and Scope

This study utilises the augmented gravity model of trade to empirically examine the effect of financial development on bilateral trade flows in Economic Community of West African States (ECOWAS). It focuses on the period 2006–2013 due to data availability. The ECOWAS countries selected include: Benin, Burkina Faso, Cape Verde, Cote d’voire, Gambia, Ghana, Guinea, Guinea Bissau, Liberia, Mali, Niger, Nigeria, Senegal, Sierra Leone, and Togo

 

Model Specification

The following model is specified and being estimated in this study:

Where:

 

 

 

 

 

 

Measurement, Estimation Techniques

In this study, financial development (FD), which is the main variable of interest is proxied by one of its general indicative measures; notably, Financial depth (defined as credit to the private sector as percentage of GDP). The estimation of the model started with panel-OLS, which is complemented with Poisson Pseudo-maximum likelihood (PPML) and GMM techniques.

 

Preliminary Findings and Implications

The preliminary findings (see Tables below) of the gravity model inform that the financial development of both exporting and importing countries are significant determinants of bilateral trade flows. The implications of this preliminary finding from the study is that where there is more credit available to the private sector, it provides a significant boost to trade.  This could be likened to the availability of finance for trade. Policies could therefore be put in place to favour the development of the financial sectors of the exporting countries and importing countries. This would in turn enhance the flow of credit to the firms that are heavily involved in international trading activities (intensive sectors of the economy).

 

 


Table 1:  Results from Panel-OLS Estimation

 

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

VARIABLES

OLS

OLS

OLS

OLS

OLS

OLS

OLS

OLS

 

 

 

 

 

 

 

 

 

ln_gdp_exp

0.591***

0.593***

0.593***

0.580***

0.584***

0.299***

0.299***

4.927*

 

(0.0759)

(0.0780)

(0.0780)

(0.0765)

(0.0785)

(0.0581)

(0.0580)

(2.906)

ln_gdp_imp

0.245***

0.246***

0.246***

0.211***

0.210***

0.215***

0.215***

-1.624

 

(0.0764)

(0.0772)

(0.0772)

(0.0784)

(0.0791)

(0.0562)

(0.0561)

(2.889)

ln_distance

-0.831***

-0.815***

-0.815***

-0.845***

-0.826***

-0.436***

-0.438***

-3.232***

 

(0.213)

(0.215)

(0.215)

(0.214)

(0.216)

(0.161)

(0.124)

(0.549)

comlang_off

0.305

0.314

0.314

0.316

0.325

0.946**

0.946**

0.809**

 

(0.576)

(0.578)

(0.578)

(0.577)

(0.578)

(0.378)

(0.377)

(0.368)

comcol

1.066*

1.069*

1.069*

1.064*

1.069*

-0.218

-0.216

-0.102

 

(0.596)

(0.599)

(0.599)

(0.597)

(0.599)

(0.386)

(0.378)

(0.369)

ln_trade_cost

 

 

 

 

 

0.122***

0.122***

0.194***

 

 

 

 

 

 

(0.0212)

(0.0212)

(0.0249)

ln_fd_imp

 

 

 

0.227**

0.246**

-0.0865

-0.0867

-0.349**

 

 

 

 

(0.113)

(0.115)

(0.137)

(0.137)

(0.143)

ln_fd_exp

 

-0.0390

-0.0390

 

-0.0615

-0.0368

-0.0370

-0.327**

 

 

(0.113)

(0.113)

 

(0.115)

(0.155)

(0.154)

(0.161)

ln_rem2_exp

 

 

 

 

 

 

 

1.835

 

 

 

 

 

 

 

 

(2.890)

ln_rem2_imp

 

 

 

 

 

 

 

-4.628

 

 

 

 

 

 

 

 

(2.906)

contig

-0.263

-0.255

-0.255

-0.243

-0.232

0.00400

 

 

 

(0.337)

(0.340)

(0.340)

(0.338)

(0.340)

(0.219)

 

 

Constant

3.380**

3.331**

3.331**

3.233*

3.168*

3.938***

3.952***

-29.15***

 

(1.674)

(1.686)

(1.686)

(1.678)

(1.687)

(1.431)

(1.211)

(6.460)

 

 

 

 

 

 

 

 

 

Observations

1,529

1,499

1,499

1,511

1,481

802

802

802

Number of pairid

210

208

208

210

208

134

134

134

Standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1

 

 

 

TABLE 2 with the Poisson Pseudo-Maximum Likelihood (PPML) estimates of Gravity Model in column (9)

 

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

VARIABLES

OLS

OLS

OLS

OLS

OLS

OLS

OLS

OLS

PPML

 

 

 

 

 

 

 

 

 

 

ln_gdp_exp

0.591***

0.593***

0.593***

0.580***

0.584***

0.299***

0.299***

4.927*

0.898

 

(0.0759)

(0.0780)

(0.0780)

(0.0765)

(0.0785)

(0.0581)

(0.0580)

(2.906)

(0.610)

ln_gdp_imp

0.245***

0.246***

0.246***

0.211***

0.210***

0.215***

0.215***

-1.624

-0.186

 

(0.0764)

(0.0772)

(0.0772)

(0.0784)

(0.0791)

(0.0562)

(0.0561)

(2.889)

(0.606)

ln_distance

-0.831***

-0.815***

-0.815***

-0.845***

-0.826***

-0.436***

-0.438***

-3.232***

-0.695***

 

(0.213)

(0.215)

(0.215)

(0.214)

(0.216)

(0.161)

(0.124)

(0.549)

(0.121)

comlang_off

0.305

0.314

0.314

0.316

0.325

0.946**

0.946**

0.809**

0.137***

 

(0.576)

(0.578)

(0.578)

(0.577)

(0.578)

(0.378)

(0.377)

(0.368)

(0.0331)

comcol

1.066*

1.069*

1.069*

1.064*

1.069*

-0.218

-0.216

-0.102

-0.00922

 

(0.596)

(0.599)

(0.599)

(0.597)

(0.599)

(0.386)

(0.378)

(0.369)

(0.0279)

ln_trade_cost

 

 

 

 

 

0.122***

0.122***

0.194***

0.0475***

 

 

 

 

 

 

(0.0212)

(0.0212)

(0.0249)

(0.00618)

ln_fd_imp

 

 

 

0.227**

0.246**

-0.0865

-0.0867

-0.349**

-0.0792***

 

 

 

 

(0.113)

(0.115)

(0.137)

(0.137)

(0.143)

(0.0273)

ln_fd_exp

 

-0.0390

-0.0390

 

-0.0615

-0.0368

-0.0370

-0.327**

-0.0846***

 

 

(0.113)

(0.113)

 

(0.115)

(0.155)

(0.154)

(0.161)

(0.0199)

ln_rem2_exp

 

 

 

 

 

 

 

1.835

0.226

 

 

 

 

 

 

 

 

(2.890)

(0.605)

ln_rem2_imp

 

 

 

 

 

 

 

-4.628

-0.842

 

 

 

 

 

 

 

 

(2.906)

(0.609)

contig

-0.263

-0.255

-0.255

-0.243

-0.232

0.00400

 

 

 

 

(0.337)

(0.340)

(0.340)

(0.338)

(0.340)

(0.219)

 

 

 

Constant

3.380**

3.331**

3.331**

3.233*

3.168*

3.938***

3.952***

-29.15***

-5.906***

 

(1.674)

(1.686)

(1.686)

(1.678)

(1.687)

(1.431)

(1.211)

(6.460)

(1.458)

 

 

 

 

 

 

 

 

 

 

Observations

1,529

1,499

1,499

1,511

1,481

802

802

802

802

R-squared

 

 

 

 

 

 

 

 

0.230

Number of pairid

210

208

208

210

208

134

134

134

 

Standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1

 


Table 3: Dynamic Model GMM Results

 

(1)

(2)

VARIABLES

GMM

GMM

 

 

 

ln_L1trade

-0.173

-0.126

 

(0.108)

(0.0799)

ln_distance

0.00833

-0.226

 

(1.034)

(0.826)

comcol

0.199

-2.640

 

(2.154)

(2.364)

comlang_off

2.002

4.327

 

(2.864)

(2.858)

contig

-2.697

-0.101

 

(2.372)

(1.895)

ln_gdp_exp

0.108

0.296*

 

(0.170)

(0.173)

ln_gdp_imp

0.186

0.407***

 

(0.147)

(0.147)

ln_fd_imp

-0.470*

-0.110

 

(0.242)

(0.181)

ln_fd_exp

-0.663**

-0.0646

 

(0.265)

(0.193)

ln_trade_cost

0.0935***

0.0459**

 

(0.0342)

(0.0206)

yr_dum_3

0.267***

 

 

(0.0865)

 

yr_dum_4

0.436***

 

 

(0.117)

 

yr_dum_5

0.346***

 

 

(0.134)

 

yr_dum_6

0.533***

 

 

(0.172)

 

yr_dum_7

-3.142***

 

 

(0.709)

 

Constant

6.633

1.498

 

(8.074)

(6.523)

 

 

 

Observations

668

668

Number of pairid

134

134

Year Dummy

YES

NO

Standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1

 

 

 

 

 

References (under compilation)

Olayiwola, W., Osabuohien, E., & Efobi, U., (2012). Inflation and Financial Development in Nigeria. In O. Olaniyan, A.O. Lawson, & B. Alayande (Eds.) Financial Sector Issues and Economic Development in Nigeria (Vol. 2, pp.49-67). Ibadan: University Press.


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