The Impact of Trade Liberalisation on Tax Revenue in Ghana: A Co-Integration Analysis.

AFRICA DEVELOPMENT AND RESOURCES RESEARCH INSTITUTE (ADRRI) JOURNAL

ADRRI JOURNAL (www.adrri.org)

pISSN: 2343-6662 ISSN-L: 2343-6662 VOL. 3 ,No.3, pp 1-19,December, 2013

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The Impact of Trade Liberalisation on Tax Revenue in Ghana: A Co-Integration

Analysis.

Mustapha Immurana1, Abdul Mumin Abdul Rahman

2 and Abdul-Aziz Iddrisu

3

1Department of Accounting Studies Education, University of Education Winneba, Kumasi-

Ghana. Tel: +233-246110693 Email: [email protected]

2 Department of International Development, London School of Economics and Political

Science, E-mail:[email protected]

3Lecturer, Department of Accountancy and Accounting Information Systems, Kumasi

Polytechnic, Kumasi-Ghana. E-mail: [email protected]

Correspondence: Mustapha Immurana, Department of Accounting Studies Education,

University of Education Winneba, Kumasi-Ghana. Tel: +233-246110693

Email: [email protected]

Received: 4th

November, 2013 Accepted: 30th

November, 2013 Published Online: 1st December, 2013

URL: http://www.adrri.org/journal

Abstract

There is ambiguity in the literature on the impact of trade liberalization on tax revenue and this tends to be one

of the major concerns of developing countries in opening up their economies. This paper therefore explored how

the trade liberalisation policy agenda is consistent with meeting the revenue objective of developing countries

using Ghana as a case study. It used the Autoregressive distributed lag (ARDL) model to find the impact of

trade liberalisation on total tax revenue in Ghana using time series data from 1980 to 2010. It found that trade

liberalisation had positive significant impact on tax revenue in Ghana. The study concluded that trade

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mailto:[email protected]

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liberalization increased tax revenue and that developing countries should open their economies without any fear

of losing tax revenue.

Keywords: Ghana, Tax revenue, Trade liberalization, Cointegration, ARDL

INTRODUCTION

Domestic resource mobilisation has been an important factor in the development strategies of

low income countries. The volatility of foreign assistance and the downward trends of aid,

make domestic resource and taxation necessary for sustainable funding in social programs,

improving institutional capacity and enhancing public investment for sustainable growth and

development (Di John, 2005). The West African Economic and Monetary Union (WAMU)

for instance, is committed to raise tax revenue to 17 per cent of GDP among its member

states as convergence strategy (Keen and Baunsgaard, 2005, 3). Achieving the Millennium

development goals requires 4 percentage points increment in the Tax-GDP ratio of low –

income countries (UN 2005; IMF 2011).

Another important development policy initiative for developing countries is trade

liberalisation. Developing countries, under Structural Adjustment Policies by the IMF, are

demanded to liberalise their market to enhance domestic competition, facilitate technology

diffusion, increase efficiency and ultimately foster economic growth and development

(Dornbush, 1992). The implementation of these policies is sometimes conditioned in

International Financial Institution’s loans to developing countries. Trade liberalisation often

entails the reduction and unification of tariffs and the relaxation and elimination of

quantitative barriers, and may be accompanied by currency devaluation and domestic tax

reform (Agbeyegbe et al 2004;3). It is generally believed that increased in market access for

agriculture and labour-intensive exports, would provide the basis for growth and poverty

reduction for developing countries. According to the World Bank (2002), trade liberalisation

accelerates growth; enhance productivity through specialisation, and leads to high

employment and poverty reduction (Bhasin and Obeng 2007; 2).

However, the effect of trade liberalisation on growth and development both in theory and

empirical evidence has attracted debates in the academic literature, but less attention has been

given to its effect on tax revenue. One major concern of developing countries’ further




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liberalisation of trade through regional, bilateral and multilateral agreements by tariff

reduction under the current DOHA round, is the potential adverse fiscal consequence (Keen

and Baunsgaard 2005; 3). There is an ambiguous relationship between trade liberalisation and

trade tax revenue in both theory and empirical evidence (Gabriel and Obeng, 2008, 1). Trade

liberalisation in the form of converting quantitative restrictions to tariffs can initially lead to

an increase in trade tax revenue. Further liberalisation in the form of tariffs cut can cause

trade tax revenue loss on one hand, but can also amount to an increase in the volume of

imports, and hence the tax base and revenue. The net effect of trade liberalisation depends on

many factors, including the structure of liberalisation and the elasticity of demand for imports

(Gabriel and Obeng 2008; 1).

The fear of the effect of trade liberalisation on international trade tax is even substantial in

low income countries because it constitutes an average of 26 per cent total tax revenue

(Pelzman 2004 cited in Pupongsak 2009; 130). The ambiguity of the relationship between

trade liberalisation and total tax revenue in the literature creates a knowledge gap, which is

worth probing empirically.

This paper looked at the effect of trade liberalisation on total tax revenue using Ghana as a

case study. Ghana has been described as a country that has gone deep structural adjustment

reform from the 1980s. Trade liberalisation has formed one of the key reform programs in

Ghana since its implementation of Structural Adjustment policies in 1983. Its liberalisation

policies were not gradual from relaxation and elimination of quantitative restrictions to tariff

cuts but proceeded with simultaneous elimination of quotas and reduction in the range and

level of tariffs at the same time (Gabriel and Obeng 2008; 1). The aim of this paper was to

look at whether liberalisation policies advanced by the International Financial Institutions are

consistent with effective state formation and the achievement of the Millennium

Development Goals through the meeting of the revenue objectives since its actual effect on

tax revenue is ambiguous in the literature. This is vital for policy makers in the design of

policies for further liberalisation and subsequent tax reforms.

The remainder of this paper was structured as follows: Section 2 dealt with the literature

review, section 3 covered data sources and methodology and section 4 covered the analysis of

results and discussion and the final section (section 5) dealt with conclusion and policy

implication.




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LITERATURE REVIEW

Brief theoretical literature

In theory the direction of changes in revenue to trade liberalisation is ambiguous as it

depends on the tax structure and the revenue productivity (Suliman 2005; 6). Theoretically,

trade liberalisation in the form of tariff cuts and unification can lead to loss in direct trade tax

revenue on one hand, but on the other hand, can also result to increase in volume of imports

and hence the tax base and revenue (Gabriel and Obeng 2008; 1). The net effect on revenue

will therefore depend on the form of liberalisation as well as the elasticity of demand for

imports. Considering trade liberalisation as stages, the first stage of trade policy reform-

elimination of prohibitive tariffs and quantitative restrictions, unification of tariffs,

elimination of exemptions- may lead to increase in trade tax revenue. Further liberalisation

towards a free trade or freer trade in tariff cuts can however have negative fiscal consequence

(Keen and Baunsgaard 2005; 3).

Furthermore, trade liberalisation exerts indirect effect on profit and corporate income tax.

Privatisation, restructuration and automation accompanying trade liberalisation could lead to

job loss, wage cuts resulting in the contraction in the base of personal income tax as well as

decline in personal income tax revenue (Pupongsak 2009; 8). This effect is however

dependent on the growth effect of trade liberalisation, country specific factors and conditions

and some other underlining contingent factors (Pupongsak 2009; 8). Real exchange rate

depreciation associated with trade liberalisation also affects the profitability of corporate

firms through changes in the relative prices of imported inputs as well as exports (Pupongsak

2009; 9). This affects the corporate tax base and revenue, but the net effect on corporate tax

revenue is ambiguous and depends on the growth effect of trade liberalisation as argued by

Agbeyegbe et al (2004).

Empirical literature

The empirical evidence on the relationship between the share of tax revenue and trade

liberalisation is largely based on cross-country analysis. Ebrill et al (1999), based on a panel

of 27 countries from Africa, Asia and Western Hemisphere for the period 1980-1992 and a

panel of 105 countries for 1980-1995, examined two complementary models of the

determinants of import and international trade tax revenue. They concluded that using a




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fixed-effect and instrumental regression framework, tariff reform does not necessarily lead to

loss in trade tax revenue. In contrast, Khattry and Mohan Rao (2002), using a similar fixed-

effect regression framework for a panel of 84 countries from developing and industrialised

countries covering 1970-1998, found trade liberalisation in developing countries particularly

low and upper middle-income countries, to be associated with declining tax revenues as a

result of falling income and trade tax revenue. This findings support Rao (1999) study on the

effect of changes in openness and changes in the tax base on overall tax revenue, which

concluded that there is a trade-off for Sub-Saharan African countries between reduced

protection and reduced revenues from liberalisation.

Adam et al (2001), using a difference General Method of Moments (GMM), examined the

relationship between tax revenues, exchange rate and trade liberalisation. They found that

trade liberalisation with an openness variable as a proxy, raises tax revenue in CFA Franc

countries but little effect on non-CFA franc countries. Longoni (2009), using General Method

of Moment Regression on panel-data of large number of African countries from the period

1970-2000, taking into account macroeconomic features of African economies as well as

their political capacity in undertaking trade policy reforms, found a large trade-off between

the degree of openness to international trade and the revenue from import and export

taxation. The paper also detected the existence of ‘Laffer effect’, in which further tariff

reduction will lead to further reduction in trade tax revenue in these African countries.

In a study by Pupongsak (2009), using a traditional tax effort model with a panel data of 134

countries covering the period of 1980-2003 and employing the two way fixed-effect

approach, found trade liberalisation (with share of trade to GDP, average tariff rates and the

number of free trade agreements as proxies) to have positive effect on both international trade

tax and domestic taxes for 30 low income countries. The result is highly inconsistent with

Khattry and Rao (2002) findings on low income countries.

Keen and Baunsgaard (2005), using a panel data of 111 countries over 25 years, studied the

extent to which countries have recovered revenue loss resulting from trade liberalisation.

They found advanced countries to have successfully overcome the fiscal impacts of trade

liberalisation through other domestic taxation. Middle income countries recovery has been in

the order of 45-60cents for each dollar loss from trade tax revenue. Low income countries, on

the other hand, were far from revenue recovery. Their recovery is at best 30 cents for each




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dollar lost. These findings are consistent with that of Khattry and Rao (2002), but both

studies ignored the possible effect on other domestic taxes of trade liberalisation. Suliman

(2000) examined the buoyancy and elasticity of the Sudanese tax system with particular

attention to the impact of trade liberalisation reforms of 1992 on revenue mobilisation and the

stabilisation role of the fiscal sector over 1970-2002. The study found an improvement in tax

yield from import duties over the liberalisation period. Zafar (2005) study of the revenue and

fiscal impact of trade liberalisation in Niger from 1983-2003, found that, tariff reductions

during the 1980s and 1990s in the context of Structural Adjustment and West African

Regional integration initiatives, had negative effect on trade tax revenue. It however revealed

that, the increase in the volume of imports after 1994 following trade liberalisation succeeded

in partially offsetting the revenue losses.

Oduro (2000) based on descriptive analysis of tax revenue variations, finds trade

liberalisation to be fiscally incompatible in Ghana in the 1990s. This method does not

however provide an exact impact of trade liberalisation on total tax revenue (Gabriel and

Obeng, 2008, 1). A similar study on Ghana, by Gabriel and Obeng (2008), used regression

analysis to examine the impact of import liberalisation on tariff revenue. Comparing post-

liberalisation period (post-1983) with pre-reform period (pre-1983), the study found trade

liberalisation to be in conflict with revenue objectives of economic reforms. This study

however differed from the previous two papers on Ghana. It looked at how trade

liberalisation has affected total tax revenue in general. It recognises, as in the study of

Agbeyegbe et al (2004), the direct and indirect effect on other domestic taxes of trade

liberalisation.

METHODOLOGY

Data

The empirical investigation of this paper was based on annual time-series data on Ghana

taken over the period 1980-2010. 1983 marked the year for the implementation of Structural

Adjustment policies with trade liberalisation as one of the main policy initiatives. Data was

drawn from the Ghana Revenue Authority (GRA), Ministry of Finance and Economic

Planning (MoFEP), the World Development Indicators (WDI, World Bank 2011), African

Development Indicators (ADI, World Bank 2011) and the International financial Statistics

(IFS, IMF 2012)).




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Method

The explanatory variables widely used as the determinants of tax revenue include the level of

real income per capital, sectoral shares in GDP, real effective exchange rate, terms of trade

and indices of trade liberalisation (Obeng et al 2011). These variables were used in Adam et

al (2001), Khattry and Rao (2002), Agbeyegbe et al (2004), Suliman (2005), among others.

Other variables used in some of these papers included the net aid, and quality of governance

indicators.

Based on the literature, data availability, cointegration, diagnostics and stability test, the

study derived a simple tax revenue model for Ghana as follows:

lnTR/GDP t =β1 + β

2ln(OPEN)t + β

3ln(TRADE)t + β

4lnAGRICt + β

5lnINDt + β

6ln(SER)t +

β7ln(RER)t + β

8ln(ODA)t + Ԑt...........................(1)

Where; TR/GDP is tax revenue as a share of GDP, Log (OPEN) is an index for openness

implying the collected tariff rate (the ratio of import duties to the value of imports); Log

(TRADE) is a measure of trade liberalization which is import + exports/ GDP, AGRIC is

agriculture share to GDP, IND is Industry share to GDP, SER is services’ share of GDP, RER

is the real exchange rate, ODA is the net transfers of aid and Ԑ is the error term and t is time

in years.

Tax Revenue as a percentage of GDP (TR/GDP) was the Dependent variable and data was

calculated using Tax revenue on Ghana from the MoFEP & Ghana Revenue Authority and

GDP data from the WDI (2011).

Trade Liberalization proxies: According to Rodrik and Rodrigues (1999), the effective rate

of trade taxation and the collected tariff rate are the two main indices for trade liberalisation

used in empirical works (cited in Longoni 2009; 8). The effective rate of taxation is the ratio

of international trade tax to the volume of international trade. This measure has been used by

among other authors by Khattry and Rao (2002) and Longoni (2009), where a drop in the

ratio indicates greater liberalisation, while a rise in the index shows a country is becoming

more restrictive or closed relative to its trade volumes. It has been argued that this index

ignores the Laffer effect on revenue by extremely tax rate and ignores tax evasion through

smuggling and other practices (Kattry and Rao, 2002). But it gives an idea of ‘’realised’’




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tariff as it is based on actual tariff collected (Longoni 2009; 8). The collected tariff rate

measure is the ratio of import duties to the value of imports, where a decline in the ratio

represents greater liberalisation (Agbeyegbe et al 2004; 12). Ebrill (1999) and Agbeyegbe et

al (2004) employed this measure.

This study therefore employed the share of trade to GDP (TRADE) and the collected tariff

rate (OPEN) as the measures of trade liberalization. The unavailability of data does not

permit the use of the effective rate of trade taxation, and given the small share of export tax in

trade tax, it is not likely to affect the results. Data on the share of trade to GDP (TRADE) was

calculated from the WDI (2011) and data on the collected tariff rate (OPEN) was calculated

using import duties data from the MoFEP & Ghana Revenue Authority and data on the value

of imports from the WDI (2011). The impact of trade liberalization as has been stated already

is not certain thus it can be negative or positive.

Sectors (Agriculture, Industry and Service) share to GDP; A higher agriculture share to

GDP is expected to be associated with lower revenue because of difficulty in taxing

agricultural activities as it is less monetized and largely informal and hence Agriculture as a

share of GDP is expected to have a negative impact on tax revenue. A larger share of industry

and service to GDP is expected to be positively related to tax revenue. Data on Sectors

(Agriculture, Industry and Service) share to GDP were obtained from the WDI (2011).

Real exchange rate; trade reforms are usually accompanied by exchange rate reforms which

include domestic currency devaluation. In the short-run, the aggregate elasticity of import

demand might be quite inelastic, but could lead to increase in revenue if the valuation effect

(the effect due to higher domestic currency value of imports) dominates the volume effect

(the negative effect on trade revenue due to the fall in imports) (Longoni 2009; 10). Data

calculated from the IFS (May, 2012, IMF).

Net aid; the relationship between net aid and tax revenue is also uncertain. There is some

evidence that net aid reduces tax effort and administrative capacity and efficiency in tax

mobilisation, but these results might depend on the nature of aid and other factors

(Agbeyegbe et al 2004; 21). So the impact of Net aid could be either positive or negative.

Data was obtained from the ADI (2011).




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Empirical methodology

Unit Root Tests

It was important to verify the stationarity properties of the variables used for the study in

order to avoid the risk of spurious regression since literature has shown that most time series

variables have stochastic trends, thus their variances and unconditional means are non-

stationary. This study adopted the standard test for unit root developed by Dickey-Fuller

(1979) known as the Augmented Dickey-Fuller (ADF) test to examine the order of

integration of the variables used in the model.

Co-integration test

The Ordinary Least Square (OLS) estimator becomes inappropriate since literature has shown

that most time series variables are mostly non-stationary. Therefore to curb the issue of

spurious regression associated with non-stationary variables; this paper adopted the co-

integration technique. Co-integration simply means although it is possible that single series or

variables may not be stationary, their linear combinations with other variables may generate

stationarity. Thus if co-integration is established, it means a stationary co-integrating

relationship is established between the variables and hence the problem of spurious

regression can be avoided. This study used the Autoregressive Distributed Lag (ARDL)

model approach to co-integration to estimate the impact of trade liberalisation on total tax

revenue. The ARDL model was used as it is suitable for small sample size as it is in the case

of this study. It also allows for co-integration to be performed curbing the problem of

spurious correlation from non-stationarity of variables associated with time-series data.

The ARDL model

Following Pesaran et al (2001), the study therefore adopted the ARDL model which involved

three steps.

In step 1, equation (1) was estimated by the ordinary least square (OLS) in order to test for

the existence of a level or a long-run relationship among the variables. This was done by

conducting an F-test for the joint significance of the coefficients of lagged levels of the

variables.




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The hypothesis would be:

H0: β

1= β

2 = β

3 = β

4 = β

5= β

6 = β

7 = β

8 = 0 (No long run relationship or co-integration)

H1: β

1= β

2 = β

3 = β

4 = β

5= β

6 = β

7 = β

8 ≠ 0 (There is a long run relationship or co-integration)

So if the F-statistic is above the upper critical value, the null hypothesis of no long-run

relationship is rejected regardless of the orders of the variables. Also, if the F-statistic, falls

below the lower critical value, the null hypothesis is accepted, implying that there is no long-

run relationship among the series. Lastly, if the F-statistic falls between the lower and the

upper critical values, the result is inconclusive. When the existence of co-integration (long

run relationship) was established, the study proceeded to the second step to run the long-run

model for . Finally, the third step in the ARDL bounds approach involved

estimating an Error Correction Model (ECM) to capture the short-run dynamics of the model.

The ECM provides the means of reconciling the short-run behaviour of an economic variable

with its long-run behaviour.

ANALYSIS AND DISCUSSION

Here the Unit root test was done using EVIEWS 7 and the ARDL model was run using

Microfit 5.0.

Analysis of Time Series Properties

Results for Unit Root Test

In order to find out the impact of trade liberalization (measured by the collected tariff rate and

trade) on Tax revenue as a percentage of GDP in Ghana, the stationarity status of all the

variables in the model specified for the study was tested. This was done to ensure that the

variables were not integrated of order two (I(2)) so as to avoid spurious results.




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Table 1.0 Results of the Unit Root Test

Variables Augmented Dickey Fuller – Test

lnTR/GDP -1.827429 -5.270035***

LnOPEN -2.476902 -8.122838***

LnTRADE -1.454554 -4.852030***

LnAGRIC -1.363277 -5.479209***

LnIND -1.443409 -4.613640**

LnSER -1.012922 -5.685564***

LnRER -1.615355 -4.415467***

LnODA -2.080984 -5.917258***

Legend: *** (**) denotes the rejection of the null hypothesis of unit root or no-stationarity at

1% (5%).

As can be seen from Table 1.0, when the regression was estimated at the log level (with

intercept), none of the variables becomes stationary. But using the first difference, all the

variables become stationary. Hence, the null hypothesis of non-stationarity is rejected and the

alternative hypothesis of stationarity accepted. Thus, the first differences of the variables

were stationary.

Results for Cointegration test

After establishing stationarity among the variables, the study now proceeded with the co-

integration test and the results can be seen in Table 1.1 below:

Table 1.1 Bounds Test for Long Run Relationship or Co-integration

Critical Values

F-statistics 5.1306

Lower Bound I(0) Upper Bound I(1)

5% 2.9476 4.5130

10% 2.4002 3.7804




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Since the F-statistic (5.1306) was above the upper bounds (4.5130), it means the null

hypothesis of no level relationship is rejected and hence there is co-integration. Based on this,

we therefore run our ARDL model.

Diagnostic and Stability Test

The diagnostic and stability test was done to find out the robustness of the model. The result

as seen in appendix I showed that, the null hypotheses of no normal distribution, the

existence of autocorrelation, incorrect functional form and heteroscedasticity in the model

could not be accepted at the 5% level. The stability test was also done using the Cumulative

sum and the Cumulative sum of squares of recursive residuals and it showed the non-

existence of structural break and the results can be found in graph 1.0 and 1.1 below.

Graph 1.0

Graph 1.1

Long Run Impact of Trade Liberalisation on Total Tax revenue

-20

-10

0

10

20

1981 1988 1995 2002 2009

The straight lines represent critical bounds at 5% signif icance level

Plot of Cumulative Sum of Recursive Residuals

-0 .4

-0 .2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1981 1988 1995 2002 2009

The straight lines represent critical bounds at 5% signif icance level

Plot of Cumulative Sum of Squares of Recursive Residuals




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The long run impact on the share of tax revenue to GDP estimated from the ARDL (1, 1, 0, 1,

0, 0, 0, 0) model based on the Schwarz Bayesian Criterion (SBC) can be seen in Table 1.2

below:

Table 1.2 Estimated Long run model for the selected ARDL (1, 1, 0, 1, 0, 0, 0, 0) based

on Schwarz Bayesian Criterion. Dependent Variable: lnTR/GDP

Variable Coefficient Std. Error T-Statistic Prob.

LnOPEN .47732 .098406 4.8505 .000***

LnTRADE .39032 .11128 3.5074 .003 ***

LnAGRIC -.65698 .47974 -1.3695 .188

LnIND .78143 .19825 3.9416 .001***

LnSER .26361 .37798 .69742 .494

LnRER -.26999 .10423 -2.5903 .018**

LnODA .31526 .080257 3.9282 .001***

C .65919 3.5934 .18344 .856

*** (**)* significant at 1% (5%) 10%

From Table 1.2 above, both measures of trade liberalisation had positive and significant

impacts on tax revenue in the long run, with tax revenue being much sensitive to the collected

tariff proxy (lnOPEN) than the share of trade to GDP index (lnTRADE). A percentage

increase in each of the indices led to an approximate 0.4 – 0.5 per cent increase in tax

revenue. These findings contrast that of Khattry and Mao (2002) and Agbeyegbe et al (2004)

but consistent with that of Pupongsak (2009). The result could suggest a high elasticity of

demand for imports where the increase in the volume of imports resulting from openness

exceed the magnitude of tariff cuts resulting in positive fiscal impact. It can also be argued

that, the tax reforms in Ghana following trade liberalisation such as the introduction of the

VAT in 1998; have succeeded in replacing reliance on international trade tax by domestic

taxation. The positive effect of trade liberalisation on total tax revenue can also be as a result

of increase in corporate profit as a result changes in the profitability of import and exports for

companies.

The share of industry had a positive and significant effect on tax revenue as argued in

literature. The positive and significance effect of the share of industry also suggests a higher

tax base for domestic taxes such as corporate and profit tax, and income tax. Surprisingly, the

share of Agriculture, although had a negative impact on tax revenue as predicted by literature,




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but was statistically insignificant. The share of Service also had a positive but statistically

insignificant effect on tax revenue.

Furthermore, real exchange rate had a negative impact on total tax revenue at a 5 per cent

level of significance. This result is consistent with Agbeyegbe et al (2004) findings and also

confirms Tanzi’s (1989) hypotheses that, there is an inverse relationship between a country’s

real exchange rate and its tax revenue. Thus in Ghana, the high demand for foreign exchange

has kept the real exchange rate in upward trend resulting in negative effect on tax revenue as

the result shows.

Also, official aid had a positive and significant impact on tax revenue, indicating that the

receipt of official external assistance in Ghana is not as a result of its weak domestic revenue

generating capacity as aid is not used as a substitute for domestic revenue mobilisation.

Short run Impact of Trade Liberalisation on Total Tax Revenue- the Error Correction

Model or the Short run model.

Since co-integration was established in the Tax revenue as a percentage of GDP model, it

means that from the ARDL model, there is an error correction model that captures the short

run dynamics of the Tax revenue as a percentage of GDP model. The error correction model

enables us to estimate coefficients that tell us the speed at which the variables adjust to their

long run equilibria following any shock in the short run. The results of the short run dynamics

or the error correction model from the ARDL (1, 1, 0, 1, 0, 0, 0, 0) model based on the

Schwarz Bayesian Criterion (SBC) are given in table 1.3 below:

Table 1.3 Error Correction Representation for the selected ARDL (1, 1, 0, 1, 0, 0, 0,0)

based on Schwarz Bayesian Criterion. Dependent Variable: dlnTR/GDP.

Variable Coefficient Std. Error T-Statistic Prob.

DlnOPEN .22922 .063163 3.6291 .002***

DlnTRADE .32701 .10342 3.1620 .005 ***

DlnAGRIC .059816 .45267 .13214 .896

DlnIND .65468 .15538 4.2134 .000***

DlnSER .22085 .31514 .70082 .491

DlnRER -.22620 .093806 -2.4113 .026**

DlnODA .26413 .077111 3.4253 .003***

Ecm(-1) -.83780 .073672 -11.3720 .000

*** (**)* significant at 1% (5%) 10%




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From Table 1.3 above, the two indices of trade liberalisation had positive and significant

impact on tax revenue. That is, the positive effect on total tax revenue by trade liberalisation

is not sensitive on the proxy being used or on the time period of analysis. Given the nature of

trade liberalisation in Ghana, which proceeded with simultaneous elimination of quantitative

restrictions and reduction and unification of tariff levels, one would expect it to have adverse

fiscal consequence at least in the short run before any tax reforms, but the results showed

otherwise. The results suggest a high elasticity of demand for imports resulting in higher

demand for imports for any marginal reduction in tariff levels. That is, the increase in tax

revenue from a rise in the volume of imports as a result of any tariff cut more than offset the

possible revenue loss from decrease in the value of imports.

Also, in the short run, the ratio of agriculture to GDP (AGRIC) had a positive coefficient

which was different from its long run negative coefficient but was still not significant as it

was in the long run. The share of industry to GDP, the share of service to GDP and Official

foreign aid, all had positive and significant impact on Tax revenue in the short run as in the

long run. Real exchange rate also had a negative significant impact on total tax revenue in the

short run as in the long run.

Additionally, the error correction (ECM) term had a negative coefficient of (-.83780) with a

p-value of .000 which means that it is highly significant at 1% level. This result met the

expectation of econometric theory. The coefficient of the ECM measures the alacrity with

which the Tax revenue as a percentage of GDP model adjusts to changes in the independent

variables in the model. Thus the ECM coefficient of -.83780 shows a high speed of

adjustment to equilibrium after a shock and means approximately more than 84% of

disequilibria from the previous year’s shock converges back to the long-run equilibrium in

the current year.

Combining the short run and long run effect on tax revenue of trade liberalisation in Ghana,

this paper argues that, the positive effect of trade liberalisation indices on tax revenue can be

explained by both the high elasticity of demand for imports as well as the subsequent tax

reforms especially the introduction and implementation of the VAT in the late 1990s.

CONCLUSION AND RECOMMENDATION

The relationship between trade liberalisation and total tax revenue is ambiguous. Policy

makers in devising trade policies are challenged by ascertaining their fiscal impacts.




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The endeavour to unravel the ambiguity in the relationship between trade liberalisation and

total tax revenue was undertaken by this paper, using the ARDL regression model based on

country case study of Ghana for the period 1980-2010. The results showed trade liberalisation

to have a positive and significant effect on total tax revenue both in the short run and in the

long run. The paper can conclude that, the observed positive effect on total tax revenue by

trade liberalisation in the short run is due to the high elasticity of demand for import in the

Ghanaian economy, and this high elasticity is complemented by the subsequent tax reforms

for the observed relationship to persist in the long run. This result has a serious policy

implication as it suggests the reluctance of developing countries in further opening up their

national economies on the basis of diminishing tax revenue has no basis and the paper would

recommend that they should open up their economies and institute important domestic taxes

in order to raise tax revenue.

This paper addresses the effect on total tax (in aggregate) of trade liberalisation. It does not

decompose the components of total tax revenue to analyse the impact on each component of

trade liberalisation. The paper does not also estimate the exact elasticity of import demand

following trade liberalisation that it argues to be one of the factors driving the results. These

limitations raise queries for further research.

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ACRONYMS

ARDL- Autoregressive Distributed Lag VAT-Value Added Tax

ADF- Augmented Dickey-Fuller WAMU-West African Monetary Union

ADI- African Development Indicators WB- World Bank

CEPS- Custom Excise and Preventive Service WDI- World Development Indicators

CPIA- Country Policy and Institutional Assessment

ECM- Error Correction Model

EOWAS- Economic Community of West African States

http://www.ieo-imf.org/external/np/res/seminars/2005/macro/pdf/sulima.pdf

http://www.ieo-imf.org/external/np/res/seminars/2005/macro/pdf/sulima.pdf

http://www.wto.org/english/tratop_e/tpr_e/tp157_e.htm

http://www.wto.org/english/tratop_e/tpr_e/tp294_e.htm




19

ERP- Economic Recovery Programme

GDP- Gross Domestic Product

GMM- General Method of Moments

GRA- Ghana Revenue Authority

IFS- International Financial Statistics

IMF- International Monetary Fund

MoFEP- Ministry of Finance and Economic Planning

OECD- Organisation of Economic Co-operation and Development

OLS- Ordinary Least Squares

SAP- Structural Adjustment Program

UN- United Nations

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The Impact of Trade Liberalisation on Tax Revenue in Ghana: A Co-Integration Analysis.

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