The Advantage of Being a Small Country on Economic Growth

Spillovers: A Review on Spain and Portugal with ARDL Approach

MURAT EMİKÖNEL*

Faculty of Economic and Administrative Science, Economics Department,

University of Kocaeli, Turkey

ORCID: 0000-0002-8415-0510

DANIEL MEYER

College of Business and Economics, University of Johannesburg

PO Box 524, Auckland Park

SOUTH AFRICA

AYHAN ORHAN

Faculty of Economic and Administrative Science, Economics Department,

University of Kocaeli, Turkey

ORCID: 0000-0002-8109-4306

GUALTER COUTO

School of Business and Economics and CEEAplA

University of Azores

9500-321 Ponta Delgada, Portugal

PORTUGAL

ORCID: https://orcid.org/0000-0001-5560-5101

RUI ALEXANDRE CASTANHO

Faculty of Applied Sciences, WSB University

41-300 Dabrowa Górnicza

POLAND

and

College of Business and Economics, University of Johannesburg

PO Box 524, Auckland Park

SOUTH AFRICA

Abstract This study investigates Spain's role in Portugal’s economic development and analyzes the assumption

that Spain’s import from Portugal is the factor that increases Portugal’s per capita income the most. Apart from

these reasons, there are several other motivations to focus on foreign trade between Spain and Portugal. The

first is to examine the impact on Portugal of the increases in GDP, exports and imports of Spain, which is the

major country and borders Portugal. Second, this study aims to test the growth spread. According to the test

results, the economic growth of Spain positively affects the growth of Portugal in the long and short term. In

addition, it was concluded that the share of imports has more positive effects than exports in the long run. It

shows that the deviation in the variables according to the error correction term result converges to only 85

percent in the t period. The findings are also consistent with previous research supporting the economic

integration arguments that emerged as a result of trade relations. In addition, in this direction, the economic and

political meetings to be held between the two countries and the actions to be taken as a result of these meetings

can create an environment where both countries can win.

Key-Words: - Economic Growth Spillovers, Economic Growth and Development, International Trade, Export

and Import, Small Country, Spain-Portugal, ARDL Bounds Test.

Received: July 24, 2021. Revised: December 30, 2021. Accepted: January 15, 2022. Published: January 16, 2022.

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1 Introduction

The Spanish economy has undergone major changes

over the past forty years. With these changes, the

country is vital for the EU in tourism, agriculture,

and industry [1]. Considering its economic size, it is

the fifth-largest economy in the EU and fourteenth

in the world. Spain is a modern knowledge-based

economy represented by the services sector,

equalling 75% of its business operations. It has a

highly competitive, young, highly skilled, and

highly motivated population in Western Europe [2].

The most important sectors of the Spanish economy

are wholesale and retail trade, transportation,

accommodation and food services (23.4%), public

administration, defense, education, human health

and social work activities (18.9%), and industry

(17.8%). [3].

Portugal, which could be described as a poor

economy in Europe until the 1990s, grew more

compared to the economies of similar countries by

the 2000s [4]. Between 2001-10, GDP growth fell

an average of 0.6%, and unemployment tripled.

Correction of macroeconomic and financial

imbalances started seriously in 2011. Despite

significant losses in foreign trade, the current

account deficit was narrowed significantly due to

both the decrease in import volume and strong

export performance [5]. As one of the most income-

generating mushroom producers in the world today,

Portugal is in the high-income group [6]. Portuguese

economy primarily exports motor vehicle parts,

electrical machinery, petroleum and mineral fuels,

industrial machinery, and plastics, respectively. The

most imported products are motor vehicle parts,

petroleum and mineral fuels, industrial machinery,

electrical machinery, and plastics, respectively [7].

Historically on the southern border of Europe, the

two countries with a less developed economy than

their northern partners have a rich national history.

Spain and Portugal were in limited relations with

Europe until they became a member of the European

economic community. After membership, the two

entered deeper economic ties between themselves

and Europe [8]. They work with similar views

within the EU for stronger relations with the

Mediterranean and Latin American countries [9]. As

a result of increased relations, Spain ranked first in

exports and imports for the Portuguese economy

[10]. In this context, export and import shares,

which are included in the analysis part of the study,

are given in Figure 1.

Fig. 1: Trade Share

Source: The data was compiled by the authors from World Bank.

When Figure 1 is analyzed, it is seen that the rate of

Spain’s exports to Portugal is 2.6 times higher than

the imports. The striking point in the figure is that

while the share of imports increases regularly, the

percentage of exports fluctuates. After the global

economic crisis in 2008, Portugal’s share in Spain’s

exports increased after this year even though it was

at the bottom level in 2012. As of 2017, this rate

approached the figures back in 2012 but increased

again in the following year. Several factors have

been affecting the economic performance of Spain

and Portugal recently and changing its economy,

and these factors can be examined under four

headings. The first is the oil crisis in the early

1970s, the second is the process of connecting to

the community that goes back to the end of 1985,

the third is the period until the introduction of the

euro, and the last one is the period that includes the

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effects of the major economic and financial crisis

triggered by the American mortgage market crisis.

In general, both Spain and Portugal adapt to

European economic dynamism. When Europe loses

its economic dynamism, both Portugal and Spain

lose dynamism accordingly. However, Portugal is

more affected by negative consequences [11].

The close relationship in both the historical and

economic relations of the two countries is reflected

in the per capita income. When Figure 2 is

analyzed, it is seen that Spain and Portugal’s per

capita income move together. However, the same

proportionality increases in favor of Spain during

the enlargement periods.

Fig. 2: Comparative Per Capita Income of Countries

Source: The data was compiled by the authors from the World Bank.

This study focused on the Spanish-Portuguese

couple for three reasons. The primary reason is to

examine the impact on Portugal of the increase in

Spain's share of exports and imports from Portugal,

in addition to the increase in Spain's GDP.

Although some studies in the literature research the

economic relationship between Spain and Portugal,

there is no study examining this relationship in this

relevant respect. Second, this study tests growth

spread rather than macroeconomic links, unlike

other studies. Thirdly, it is expected that countries

are economically interdependent as they are close

neighbors. In this context, considering Spain and

Portugal’s close commercial and economic

relations, the study analyzes the effect of Spain’s

per capita income and increase in export and import

shares on the Portuguese economy with the ARDL

border test approach for long and short terms.

2 Literature Review

There are studies in the literature that focus on

Export-Led Growth and Import-Led Growth.

Studies aiming to confirm the positive impact of

exports on economic growth were conducted by

Findlay [12], Krueger [13], and Darrat [14], which

test for cointegration using the rank correlation.

Furthermore, Balassa [15], and Ram [16] estimated

regression equations for GDP (GNP) where the

export is considered as the independent variable

besides other variables, such as capital and labor.

Furthermore, Michaely [17], Feder [18], Marin

[19], and Thornton [20] has found that countries

that export the majority of their final goods grow

more quickly. The increase in exports also

encourages exports by providing technological

spillovers and other externalities in the economy.

Models by Grossman and Helpman [21], Rivera-

Batiz and Romer [22], and Romer [23] assume that

expanded international trade increases the number

of specialized inputs, increasing growth rates as

economies become open to international trade.

Buffie [24] evaluates the impact of shocks in

exports on export-led growth. According to

Bhagwati [25], increased trade results in more

income (increased GDP) and more income further

increases trade. Ramos [26] conducted a Granger

causality analysis for the Portuguese economy

based on the Johansen cointegration and error

correction model. As a result, the cointegration

between export growth and economic growth

suggests long and short-term bidirectional causality

relationships. However, no correlation between

import and export growth was detected. Awokuse

[27] tested the link between exports, imports, and

GDP growth through an augmented production

function. The Granger causality test provided

evidence for ELG and Growth-Led Export (GLE)

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for Bulgaria. However, for the Czech Republic, a

unidirectional relationship from exports and

imports to GDP growth was identified. For Poland,

only ILG was validated.

For China, Mah [28], tested ELG using the ARDL

model for the statistic of Pesaran and Shin [29].

The results were in favor of a long-term

bidirectional relationship between real GDP growth

and export growth. The same finding was also

obtained by Shan and Sun [30].

Hye and Boubaker [31] investigated the

relationship between exports, imports, and

economic growth for Tunisia between 1960 and

2008 by applying the ARDL test to determine the

direction of causality in the long term. The analysis

results found a unidirectional causality between

exports and economic growth and bilateral

causality between imports and economic growth.

They also noted that the growth based on exports

and imports was valid in Tunisia. Mendonça [11]

researched the economic performance of Spain,

Portugal, and Europe in his study. The two

countries’ economies are shaped by various shocks

that profoundly affect the internal and external

dynamics. Spain was more successful than Portugal

in complying with European Union regulations.

While the Spanish economy became stronger in the

European Union process, the sensitivity of the

Portuguese economy increased. Lastly, Kalai and

Zghidi [32] addressed the relationship between

foreign investment, international trade, and

economic growth for the 15 countries in the MENA

region between 1999 and 2012 with the ARDL test

and vector error correction model. According to the

analysis results, they concluded that the main factor

affecting economic growth in the long run in

MENA countries is foreign direct investments.

Kumar [33], in addition to the impact of physical

capital and foreign direct investment on growth,

India examines the dynamic spillover of China's

bilateral trade using the ARDL method. The results

of the analysis indicated that bilateral trade has a

significant long-term effect on the growth rate of

the two countries as measured by GDP per capita.

Kumar [34] examined the exports and imports of

India, the largest economy in the South Asian

Regional Cooperation Association, to/from South

Asia and its contribution to these countries. In his

study, which he analyzed with the ARDL bounds

test using data from 1990-2016, he concluded that

India's economic growth and regional trade have

short- and long-term spillovers on the economic

growth of Bangladesh, Sri Lanka, Nepal and

Bhutan.

3 Data and Methodology

The ARDL procedure is superior to the other

cointegration tests since it allows to overcome the

problem of endogeneity caused by the Granger

procedure and allows for long-run relationship

testing. In addition to this, the ARDL test for the

long-run relationship has no restriction on the

integration order of the variables, i.e., variables

with different order of integration, nonintegrated,

or fractionally cointegrated can be used. Moreover,

the ARDL technique can be performed on a small-

sized sample [31]. With these superior features, the

study measures the effect of Spain on the

Portuguese economy using the ARDL method.

Since Spain is larger than Portugal in terms of

population and GDP, per capita income is used as a

variable in the analysis. Accordingly, the effect of a

change (increase) in Spain’s per capita income on

growth spread in Portugal’s per capita income is

examined. The study is carried out using annual

data covering 1989-2018. Four variables are used

in the model. Portugal’s per capita income is an

independent variable obtained from the World

Bank database. There are three dependent

variables: the per capita income of Spain, the share

of Spain’s exports to Portugal in its total exports,

and the share of Spain’s imports from Portugal in

total imports. Spain’s per capita income is also

taken from the World Bank database, and export

and import shares from the World Integrated Trade

Solution online database. and represent the

dependent country’s GDP growth rate and the

independent country’s GDP growth rate to show

economic growth, respectively. represents the

share of Spain’s exports to Portugal in total exports,

and represents the share of imports from

Portugal in total imports. The relationship between

the variables is given in equation 1.

= + + + + (1)

denotes dependent country per capita GDP

denotes independent country per capita GDP

denotes the share of Spain’s exports to

Portugal in its total exports.

denotes the share of Spain’s imports from

Portugal in total imports.

denotes error term.

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4. Empirical Findings

4.1 Unit Root Test Results

For the data analysis in the study, firstly, stationary

properties are examined. Stationary is decided

based on whether the stochastic process varies

depending on time in time series analysis. If the

nature of the probabilistic process changes over

time, it means that the series is not stationary. As a

result of the fact that the series is not stationary, the

problem of false regression arises [35]. In such a

situation, the real relationship between the series

cannot be measured. In this context, the series to be

examined were analyzed with the Augmented

Dickey-Fuller [36] unit root test developed by

Dickey-Fuller in 1981 to obtain consistent and

reliable analysis results. The test results are

presented in Table 1.

Table 1. ADF Unit Root Test Results (Level and first difference)

GDP

EXPORT

IMPORT

Level

First difference

Level

First difference

Level

First difference

Without

Constant Trend

Without

Constant-Trend

Without

Constant-Trend

Without

Constant-Trend

Without

Constant-Trend

Without

Constant-Trend

Country

Spain

1.0367

0.9170

-2.0638

0.0394**

Portugal

1.3853

0.9548

-2.5727

0.0121**

0.2175

0.7423

-4.6533

0.0000***

-3.4890

0.0595*

-7.7206

0.0000***

Note: ***, **, and * indicate significance at 1%, 5%, and 10% significance levels, respectively.

Looking at Table 1, the GDP variable is stationary

at the first difference for Spain and Portugal and is

statistically significant at the 5% level. The share of

Spain's exports to Portugal is stationary at the first

difference and statistically significant at the 1%

level. The share of Spain's imports from Portugal is

stationary both in level and in the first difference,

but the statistical significance levels are 10% and

1%, respectively. Table 1 shows that the ARDL

bounds test can be performed in the study because

the series is stationary at different levels, and it

does not need to be stationary at the same level

compared to the Johansen-Juselius and Engle-

Granger [37] cointegration tests. The assumption

that the Johansen-Juselius [38] and Engle-Granger

cointegration tests are evenly stationary as the

prerequisite is the weakness of these tests.

However, Pesaran et al. [29] and then Pesaran et al.

In the ARDL bounds test developed by (2001), the

lack of a condition requiring the series to be

stationary at the same level provides convenience

in the studies [39]. Additionally, the ARDL bounds

test can be used in a small observation dataset [40].

The ARDL bounds test consists of two stages. The

first step is to determine the existence of a long-

term relationship between the variables. After the

existence of a long-term relationship is detected in

the first stage, the long-term and short-term

causality relationship is estimated in the second

stage within the framework of the error correction

term (ECT).

This study adapted the form of the model presented

in equation 2 to determine the existence of a long-

term relationship between the variables:

= + + +

+ + +

+ +

+ (2)

where is the constant term, is the error term,

are first difference of the series, are long-

run multipliers, and a, b, c, and d represent the lag

length of the variables.

The test of the existence of cointegration in the

ARDL model is based on the F statistic. With

calculated F statistics

: = = = = 0 (No cointegration.)

: ≠ ≠ ≠ ≠ 0 (Cointegrated.)

hypotheses are tested. Based on the F statistics

results obtained from the test results, it is decided

whether the hypothesis can be rejected or not. If

the result of the F statistic is above the limit, is

rejected, and there is a cointegration result. If the F

statistic result is below the limit, cannot be

rejected, and it is concluded that there is no

cointegration. If the result is between the lower

limit and the upper limit, no interpretation can be

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made [39]. The ARDL limit and diagnostic test results of the study are presented in table 2.

Table 2. The ARDL Bounds Test and Diagnostic Tests

ARDL

Tests

statistics

Diagnostic tests

Remarks

Normality

Heteroscedasticity

Serial

Correlation

Ramsey

Reset Tests

F (PRT/ESP)

1,4,5,5

7.038591

0.268086

(0.874552)

0.025007

(0.8743)

1.842590

(0.1746)

1.214656

(0.3206)

Cointegrated

Significance

Level

Critical values T:35

F (PRT/ESP)

Lower bounds I(0)

Upper bounds I(1)

5.333

3.71

3.008

7.063

5.018

4.15

10%

Considering the results of F statistics given in

Table 2, it is concluded that there is a long-term

cointegration at the five percent level. According to

the diagnostic test results, it was determined that

there was no variance, autocorrelation problem, and

model building error in the model, and the model

showed a normal distribution. In other words, the

model is not set up incorrectly and the reliability of

the information obtained as a result of the

established model is based on solid foundations.

After long-term cointegration is determined among

the variables, the long and short-term coefficients

of the variables can be calculated. The relationship

of variables in the short run is determined by the

error correction model. The error correction model

equation includes the first differences of the

variables and the one-time delayed errors of the

cointegration regression. The advantage of using an

error correction model is that it reveals short- and

long-term causality and determines the imbalance

between the variables, besides fixing them [41].

The adapted form of the error correction model is

presented in equation 3.

= + +

+ + +

+ (3)

shows a time-lagged value of the series of

error terms derived from the long-term relationship.

coefficient shows the rate of adaptation of the

system to long-term balance after shocks occurring

in the short term [42]. Error correction term (ECT)

coefficient should be negative and statistically

significant. It is also expected to be between 0 and -

1 [42]. However, if it is between -1 and -2, the

variables provide convergence with decreasing

fluctuation each time [43].

4.2 Long and Short-Run Test Results

After determining that there is cointegration in the

variables taken for Spain and Portugal, the ARDL

test was applied within the framework of error

correction (ECT) to determine the variables’ long

and short term coefficients. Long and short term

test results of Portugal are given in Table 3.

According to the test results, the economic growth

of Spain positively affects the growth of Portugal in

the long run. In the short term, it affects positively

in the current period and in the three delay periods,

while it affects negatively in one delayed and two

delayed periods. The share of exports affects

positively in the long and short term. While the

share of imports has more positive effects than

exports in the long run, it has a negative effect in

the short run. The error correction term was found

to be -0.85. This result indicates that the deviation

in the variables in the t-1 period converged only 85

percent in the t period.

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Table 3. Short- and Long-Run Relationship for Portugal

Long-run relationship

Short-run relationship

Variable

Coefficient

Variable

Coefficient

Export

544.8157

(0.0014)***

ΔExport

285.3311

(0.0025)***

Import

2241.793

(0.0016)***

ΔExport (-1)

52.18409

(0.4437)

0.409388

(0.0004)***

ΔExport (-2)

119.8903

(0.0948)*

ΔExport (-3)

348.7434

(0.0010)***

ΔExport (-4)

168.8244

(0.0438)**

ΔImport

-631.5739

(0.0114)**

ΔImport (-1)

-2508.944

(0.0004)***

ΔImport (-2)

-2074.591

(0.0015)***

ΔImport (-3)

-1900.858

(0.0009)***

ΔImport (-4)

-883.2378

(0.0072)***

ΔX

0.415465

(0.0003)***

ΔX(-1)

-0.132181

(0.0804)*

ΔX(-2)

-0.112378

(0.1475)

ΔX(-3)

0.130222

(0.0585)*

ECT(-1)

-0.850467

(0.0006) ***

Note: ***, **, and * indicate significance at 1%, 5%, and 10% significance levels, respectively.

Considering the figure 1 above, although Spain's

export share to Portugal has fluctuated over the

years, its share in 2018 is at a point equivalent to

the initial year. However, the share of imports has

followed an increasing course over the years. As

seen in our results, the share of imports is more

influential than the share of exports. When we look

at the products imported by Spain to Portugal, the

first five rows are vehicles other than railway or

tramway wagons and their parts and components;

Machinery, mechanical devices, nuclear reactors,

boilers, parts thereof; Plastics and articles thereof;

Mineral fuels, mineral oils and their distillation

products, bituminous substances, mineral; Iron and

steel products are included. The share of these

products in their trade is 12%, 8%, 7%, 5%, and

4.6%, respectively. When we look at the products

exported by Spain from Portugal, the first five

ranks are "Vehicles other than railway or tramway

wagons and their parts and parts; Machinery,

mechanical devices, nuclear reactors, boilers, their

parts and parts; Electrical machinery and

equipment and their parts; Plastics. and goods;

Mineral fuels, mineral oils and products obtained

from their distillation, bituminous substances,

mineral" products. The share of these products in

their trade is 8.3%, 7.9%, 7.4%, 5.5% and 4.5%,

respectively. Although four of the groups of goods

it exports and imports are the same products,

Portugal is a net exporter of these products against

Spain. As of 2020, Portugal's net trade surplus

value against Spain is approximately 10.3 billion

dollars.

Spain’s per capita income, the effect of changes in

export and import shares on Portugal’s per capita

income are collectively presented in Figure 3. The

cumulative sum (CUSUM) tests of the study are

given in Annex 1.

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Long Run Spillovers Short Run Spillovers

Fig. 3: The Impact of Spain’s Gdp, Export Share, and Import Share on Portugal

5. Conclusions and Recommendations

Spain and Portugal, which joined the European

Community in 1986, have rich historical and

economic relations. Based on this close economic

relationship, the effect of Spanish trade data and

economy on the Portuguese economy was examined

in the study. While the studies in the literature

analyze bilateral trade, they sometimes consist of

studies to find the factors that can be effective in the

trade between the two countries. Sometimes, the

effects on bilateral trade are analyzed directly by the

amount of exports and imports or the monetary

values of these amounts. The feature that

distinguishes this study from other studies is that it

measures the economic growth performance of the

partner country for bilateral foreign trade, taking

into account the export of the big country to the

partner country and the share of imports from it in

all exports and imports. The results reveal that

Spain’s exports, imports, and economic growth

significantly increase Portugal’s economic growth.

As a result, the increase in Spain’s per capita

income positively affects Portugal’s per capita

income in the long run. In the short term, the

increase in Spain’s per capita income in the current

period and the three lagged periods positively

affects Portugal’s per capita income, while in one

lagged period, it affects negatively. The share of

exports affects positively in the long- and short-

term. While the share of imports has more positive

effects than exports in the long run, it has a negative

effect in the short run. This is because Spain has a

25 percent share in Portugal’s total exports.

Additionally, the fact that Portugal prefers imported

products from Spain causes external reflection in

trade, which therefore increases the export of

Portugal. The findings are also consistent with

previous research supporting the economic

integration arguments that emerged as a result of

trade relations. Based on these results, Portugal can

increase its market share in the region by increasing

its exports to Spain in the long term and positively

affecting its economy. However, a contraction in the

Spanish economy in the future could affect Portugal

more negatively. Hence, Portugal needs to focus on

market and product diversification. In addition, in

this direction, the economic and political meetings

to be held between the two countries and the actions

to be taken as a result of these meetings can create

an environment where both countries can win. This

study investigated the data of Spain and Portugal.

With the addition of different countries to the

analysis in future studies, results can be diversified.

Consequently, evaluations can be made by

analyzing different variables for these two countries.

Acknowledgements:

This research was partially funded by the program

of the Minister of Science and Higher Education

titled “Regional Initiative of Excellence” in 2019-

2022, project number 018/RID/2018/19, the amount

of funding PLN 10 788 423,16. Moreover, our

thanks also to the Portuguese national funds through

FCT—Fundação para a Ciência e a Tecnologia, I.P.,

project number UIDB/00685/2020.

ESP

GDP

Export

Import

port

PRT

ESP

GDP

Export

Import

port

PRT

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_US

Annex 1

-8

-6

-4

-2

2013 2014 2015 2016 2017 2018

CUSUM 5% Significance

-0.4

0.0

0.4

0.8

1.2

1.6

2013 2014 2015 2016 2017 2018

CUSUM of Squares 5% Significance

WSEAS TRANSACTIONS on BUSINESS and ECONOMICS

DOI: 10.37394/23207.2022.19.33

Murat Emi

könel, Daniel Meyer,

Ayhan Orhan, Gualter Couto,

Rui Alexandre Castanho

E-ISSN: 2224-2899

385

Volume 19, 2022