New Kids on the Bloc
Theory and practice; is the fear for the expansion of trading blocs justified?
MSc International Business & Management Faculty of Economics and Business
University of Groningen 21st of June 2017
By
Miriam Wapstra s1967681
Supervisor: V.E. Kunst
Co-Assessor: Dr. H.J. Drogendijk
Abstract
This paper analyzes the effect of trade bloc expansion of original bloc member welfare, as well as aspiring member welfare moderated by corruption level distance and cultural distance. I hypothesize that the expansion will have a positive effect of welfare. Furthermore, I expect that this effect will be more pronounced when corruption distance and cultural distance are small. To analyze these relationships a series of OLS regressions was performed on data for the four major trading blocs in the world (i.e. ASEAN, EU, MERCOSUR, NAFTA). I conclude that the effect of expansion is indeed positive on welfare. However, the influence of corruption and culture cannot be confirmed by the results.
1. Introduction
Recently, there have been several events worldwide that are creating a widespread feeling of concern among the different members of global trading blocs (e.g. Boffey, 2017; Casey and Zarate, 2017; Ellis, 2017; Holodny, 2017; Hunt and Wheeler, 2017; Kossen, 2016). In the EU there is the United Kingdom that has voted to exit the European Union (EU) (Hunt and Wheeler, 2017), The Netherlands who voted against an association agreement between the EU and Ukraine (Kossen, 2016), a new corruption decree that caused uproars in Romania (Ellis, 2017) and meanwhile anti-EU or Eurosceptic parties are gathering strength (Boffey, 2017). The North American Free Trade Agreement (NAFTA) bloc has also fallen on hard times. The new president of the United States of America, Donald J. Trump, announced that he wants to quit several trade deals and renegotiate the NAFTA, which he called “the worst trade deal in the history of the country” (Holodny, 2017). Additionally, the South American trading bloc The Common Market of the South (MERCOSUR) is dealing with recent corruption scandals in both Brazil and Venezuela (Casey and Zarate, 2017), causing people to fear for their jobs and security.
“The previous examples are induced by negativity in the media or negative remarks by powerful individuals. However, in scientific literature trading blocs, and more specifically their expansions, are predominantly viewed as positive. For instance, Panagariya and Findlay state in their 1994 paper that the more partners there are in a customs union, the more likely it is that welfare is improved for the member countries. This is underlined by Bond and Syropoulos (1999), who mention that there is an incentive for blocs to add members and for countries to want to enter large blocs. If this is true, than trading bloc expansion should not only be welfare creating for bloc members, but also for aspiring members. Yi (2000) posits that the formation of a free-trade area can indeed make non-members better off as long as the members do not exploit their joint power to change terms of trade.
Secondly, there have been analyses of specific trading blocs such as Kwan and Qiu (2010) looking at FDI in the ASEAN+3 trading bloc, and Panagariya (1996) who looks at the free trade area in the Americas and its effect on Latin America. Thirdly, culture, or more specifically, the differences has been taken into account in previous studies. Or more specifically, the differences between countries that are forming an alliance with one another. These differences in cultural dimensions may act as a barrier between countries that want or try to form a trading bloc (Kwan and Qiu, 2010). Other research in cultural differences has focused on their effect on foreign entry (Barkema et al., 1996), strategic alliances (Steensma et al., 2000), and mergers and acquisitions (Stahl and Voigt, 2008).
However, little attention has been paid to the effect of culture on trading bloc expansion, while this can be seen as a sort of merger, but on a larger scale. Therefore, this paper will aim to shed light on the expansion of trading blocs by answering the question: How is country welfare affected by trading bloc expansion? I do this by looking at the four largest trading blocs in existence today (i.e. NAFTA, EU, ASEAN, and MERCOSUR). Additionally, I examine the possible moderating effects of corruption and cultural differences on this relationship.
To this purpose, the effect of bloc extension on the welfare of current bloc members and aspiring members is analyzed. I contribute to current literature in the following ways: this paper investigates the effect on the business community using data for multiple trading blocs, while also scaling countries according to their corruption level (Bayesian Corruption Index) and their culture (Hofstede, 1980). This will help to identify past effects on welfare in these trading blocs as a whole and as a means to forecast effects of expanding trading blocs in the future.
2. Theoretical framework and conceptual model
2.1 Trading blocs
According to Schott (1991), a trading bloc is an association of countries that aims to reduce or even eliminate regional barriers to promote the trade in goods, services, investments and capital. The regional arrangements organized among developed countries, especially in Western Europe, are widely viewed as trade-creating institutions that also contributed to political cooperation (Mansfield and Milner, 1999; Eichengreen and Frankel, 1995; Frankel and Wei 1998). Taifeng (2009) states that countries form such an alliance to realize trade liberalization and to strengthen and regulate economic and technical cooperation within the region.
Today, most countries in the world are members of the World Trade Organization (WTO), which limits import/export tariffs in certain ways but does not eliminate them entirely (World Trade Organization, 2016a). Most countries are also members of regional free trade areas that lower trade barriers among participating countries. Depending on the level of economic integration, trade blocs can fall into different categories of preferential/regional trading arrangements (PTAs/RTAs), such as customs unions (CUs), which eliminate internal trade barriers and impose a common external tariff (CET); free trade areas (or agreements) (FTAs), which eliminate internal trade barriers, but do not establish a CET; and common markets (CMs), which allow the free movement of factors of production and finished products across national borders (Mansfield and Milner, 1999).
As Kwan and Qiu (2010) observed, there have been more than 240 RTAs, a large portion of which are regional FTAs, since the inception of the General Agreements on Tariffs and Trade (GATT) on the 1st of January 1948 (GATT, 1986). Data from the World Trade Organization
shows that there are currently 433 RTAs in force (as notified to the WTO), while many others are still being negotiated (World Trade Organization, 2016c). This indicates the popularity of trade agreements worldwide, but gives no clear answer as to how successful they are in creating world welfare.
Nowak-Lehmann, 2003; Egger, 2004), corruption (Damania, Fredriksson, and List, 2003; Meunier and Nicolaïdis, 2006), and welfare (Panagariya, 1996; Bond et al., 2004; Li and Whalley, 2014; Joshua, 2017). In fact, the results of several studies (Yi, 2000; Panagariya and Krishna, 2002; Bond et al., 2004) show that the formation of an FTA improves the terms of trade and welfare on nonmember countries because it creates an incentive for members to reduce external tariffs. This is underlined by Park (2009), who explains that, in the context of North-East Asia and the Asian Free Trade Association (AFTA), RTAs would benefit the East-Asian economies as well as the global economy.
2.2 Trade bloc expansion and welfare
Moving forward with this concept of benefit and welfare, an impressive amount of papers have studied welfare growth and diversion, but at the same time very few give a clear definition or any definition at all. Their goal has not been to conceptualize welfare, but rather to test the validity of theoretical models (Kolberg, 1992, p. 103). However, a definition is needed here to be able to understand how welfare can be affected. Trotignon (2009) gives a simple but effective explanation. According to him, country welfare is generated when trade creation exceeds trade diversion. In the trading bloc aspect, this means that the positive effects of being part of a trading bloc (trade creation) outweigh the negative effects (trade diversion).
On the one hand, blocs might increase their external barriers to trade to limit the market access of non-member countries, benefitting only at a national level (Bond and Syropoulos, 1999). The terms of trade between member states and the rest of the world (ROW) will deteriorate, which is welfare reducing (Bond et al., 2004). Additionally, members might exploit their joint power to change terms of trade to benefit only themselves (Yi, 2000). On the other hand, regional trading blocs could function as stepping-stones to global free trade, because they are likely to make tariff reductions with non-members easier to negotiate (Bond and Syropoulos, 1999). This is also indicated in the results of the study by Bond et al. (2004), who find that the formation of an FTA improves the terms of trade and welfare of non-members, because it creates an incentive for members to reduce their external tariffs. This liberalization of internal trade will cause intra-union trade to expand, which is welfare improving (Bond et al., 2004).
Bond et al., 2004). However, the effect of the expansion of trading blocs on welfare is somewhat underexposed. I build on the work by Trotignon (2009) who analyzes trading blocs to determine if they are building blocks, or stumbling blocks. He finds that integration stimulates the intra-bloc trade as well as extra-bloc exports and imports. Thus highlighting the positive effect of expansion on welfare (i.e. trade creation). Panagariya and Findlay (1994) make a political-economy analysis looking at FTAs and CUs. They conclude that the more partners there are in a CU, the more likely it is that welfare is improved for the member countries. According to the authors, this is explained by the fact that under a CU, the tariff available to one country becomes available to all countries in the CU. When tariffs are lowered, this will lead to lower prices and trade creation will occur. This switch to lower cost producers in other countries will lead to an increase in consumer surplus and economic welfare (Pettinger, 2012).
Thus, as the free-trade area expands the optimal individual external tariff of the member country decreases (Yi, 2000). As long as the member countries’ collective size is sufficiently large, the welfare improving effect will dominate, benefiting all members (Bond et al., 2004). Consequently, there is an incentive for blocs to add members and for countries to want to enter large blocs. However, this is only true if the members do not exploit their joint power to change terms of trade Yi (2000). In this scenario, the expansion of the free trade area also makes nonmembers better off. In fact, practice shows that since the end of the 1980s, the formation or consolidation of large regional groups has not only been of benefit to their internal trade flows, but has also been a generator of multilateral trade Trotignon (2009).
As trading blocs form and expand, tariffs are reduced, allowing countries to trade and improve welfare for both. Therefore, I expect that the expansion of trading blocs by allowing new countries to become a member will have a positive effect on welfare for countries that are a part of this trading bloc as well as on aspiring member countries.
Hypothesis 1: The expansion of trading blocs will have a positive effect on original member
country welfare.
Hypothesis 2: The expansion of trading blocs will have a positive effect on new member
2.3 Corruption
Both economic and societal development is affected by the ever-present corruption in various parts of our society and economy (Dimant and Tosato, 2017). Corruption, most commonly described as the abuse of public power for private gain (Morris, 1991), can be a compromising factor when economies expand and/or mix. This makes it an important element to consider when it comes to trading bloc expansion. Corruption has a negative effect on welfare, not because money changes hands, but because it makes people unwilling or unable to increase public welfare (Lambsdorff, 2001). Furthermore, corruption affects welfare not only indirectly through GDP, but also directly through the time and effort required to cope with corrupt behavior (Welsch, 2008).
Ideally, business will try to avoid having to spend this time and effort when selecting new trading partners. A similar or closer market reduces uncertainty and learning costs about the host country (Qian et al. 2012). Although it might be easy to conceive that the difference in corruption level between two countries is more problematic for investors coming from a less corrupt environment than those from a more corrupt one, it is still a "distance" that both types of investors will have to overcome (Habib and Zurawicki, 2002).
In practice, for example Croatia (who joined the EU in 2013), corruption has a negative effect on development and needs to be stopped in order for welfare to be able to grow (Budak, 2006). And that is only an example on a national level, internationally the difference will probably be bigger. Consequently, the corruption distance between countries negatively affects the volume of FDI to be invested in a host country (Qian et al., 2012). This adverse effect of corruption on international trade is also highlighted by Wei (2000). As increased inter-country trade is a large part of trading blocs and their expansion, I expect that a high corruption distance will weaken the positive welfare effects for the current trading bloc members.
This corruption distance goes both ways, for both original members and for aspiring members it will be more beneficial to have a smaller corruption distance rather than a larger corruption distance. Therefore, I formulate the following two hypotheses:
Hypothesis 3: The positive relation between the expansion of trading blocs and original
Hypothesis 4: The positive relation between the expansion of trading blocs and new country
welfare will be negatively moderated by corruption distance.
2.4 Cultural distance
When examining multiple countries working and trading with one another one of the most obvious obstacles is their different ways of thinking or cultural differences. This is especially true for the expansion of trade blocs where different cultures become partners in a shared alliance. In fact, in the business perspective it is easier to work with and for people who share the same cultural values (Hofstede, 1980).
Joshua (2017) mentions the complementarity between China and members of the trading blocs of which China is part as a driver for trade links to be expanded and to facilitate the creation of new trade. Thus, when countries are culturally close this can help to assist trade creation within the trading bloc. Alternatively, these cultural dimensions may act as a barrier between countries who want or try to form a trading bloc but are culturally distant from each other (Kwan and Qiu, 2010).
In his paper, Neumann (1998) takes an anthropological view at trading bloc expansion in the EU context. He mentions the failed application of Morocco to become a member of the EU in 1986 that was swiftly dealt with in contrast to the usually long bureaucratic procedures that follow an application. Neumann (1998) states that Morocco was even denied the negotiation process of entering because it was marked as “clearly Non-European” as it is located in Africa. Nonetheless, Cyprus (or at least the Greek part) was allowed to enter the EU in 2004 (The Guardian, 2004) although, according to the UN (2014), Cyprus is a part of Asia and not of Europe.
Juncker has already stated that if the Turkish President continues with these plans all EU admission talks will be stopped (Kroet, 2017).
This anecdote clearly underlines how the differences between culturally different countries creates conflict. In fact, governments and businesses working with different cultures already consider this when deciding what countries to allow into a trading bloc or what entry strategy to use. Additionally, data from several studies (Hofstede, 1980; Kwan and Qiu, 2010; Joshua, 2017) suggest that cultural differences between new member countries and the trading bloc will negatively influence the success of trading bloc expansion. This leads me to the final hypotheses:
Hypothesis 5: The positive relation between the expansion of FTAs and country welfare will
be negatively moderated by the cultural distance between a member of a trade bloc and the bloc average.
Hypothesis 6: The positive relation between the expansion of FTAs and new country welfare
will be negatively moderated by the cultural distance between a member of a trade bloc and the bloc average.
As a result of hypotheses 1, 3, and 5, the following conceptual (1) model is proposed:
For the effect of trading bloc expansion on new member countries with hypotheses 2, 4, and 6, conceptual model (2) was added.
Figure 2: Conceptual model (2)
3. Methodology
3.1 Sample
This paper will look at the formation of the four major trade groups in the world as mentioned by several sources (Duina, 2006; WTO, 2016b; Bacchus, 2017; BBC, 2017) namely the North American Free Trade Agreement (NAFTA), the European Union (EU), the Common Market of the South (Mercosur), and the Association of Southeast Asian Nations (ASEAN), see also the red squares in figure 3. To look at the effect of the formation of these trading blocs, I look at data from 1963 to 2013, starting 10 year before the first expansion. Most of these trade blocs have been preceded by smaller alliances that were the
foundation of the current four trading blocs. However, for simplicity I will use the foundation of the current trading blocs as our benchmarks. Trade was already present and encouraged before the official formation, but the larger agreements have only come into play with the signing of the current trade agreements.
NAFTA
NAFTA is known as North American Free Trade Agreement and was established in 1994 (Floudas and Rojas, 2000). The aim of NAFTA is to eliminate the trade barriers among the member countries, increase the investment opportunities, promoting the conditions for free trade and protecting the intellectual property rights. This bloc included only Canada and the United States, under the Canada-US Trade Agreement of 1988 and expanded in 1994 to include Mexico. The implementation of NAFTA brought the immediate elimination of tariffs on more than one-half of Mexico's exports to the U.S. and more than one-third of U.S. exports to Mexico (Floudas and Rojas, 2000).
EU
A precursor of the European Union (EU) was founded in 1957 when the Treaty of Rome was signed (Schott, 1991), with the aim of developing a regional free trade association, developing the economic and executive connection and healthy relationship among the member states. Currently, there are 27 member countries associated with the European Union including (for a complete list, see appendix 1). In fact, Meunier and Nicolaïdis (2006) state that the European Union is the most powerful trading bloc in the world. Research by Kwan and Qiu (2010) points out the EU bloc as the most integrated trading bloc with an intra-regional trade share of almost 63%.
MERCOSUR
In South America, the Common Market of the South, created in 1991 with the treaty of Asunción, is a customs union between Argentina, Brazil, Paraguay, Uruguay, and Venezuela (Meunier and Nicolaïdis, 2006). The aim of the MERCOSUR trade bloc is to integrate the member state for the purpose of accelerating the sustained economic development depending on the social justice, combating poverty and environmental protection.
ASEAN
worldwide. The main goal of this trade bloc is to promote the regional peace, stability, cultural development and social progress among the nations (Bacchus, 2017).
3.2 Research design
Although Egger (2004) uses panel econometric techniques to estimated trading bloc effects, he states that most estimates are based on OLS regressions. This research also uses OLS regressions to analyze the data.
3.3 Measurements
The QoG Standard Database has specified a welfare category in their codebook. This category includes indicators on government expenditure related to social welfare (pension, sickness coverage and accidents). However, the QoG standard database only has data for 2012-2015; this gives us too little evidence for the formation of the trading blocs I look at, as they occurred before this time interval. A country’s welfare can be influenced by a multitude of factors. Most commonly this is measured by looking at a country’s Gross Domestic Product (GDP). As welfare is highly correlated with GDP (correlation of 0.98 in Jones and Klenow, 2016), this does seem logical.
Therefore, I have opted to measure the dependent variable original member welfare by combining GDP per capita, Unemployment percentage, and Trade (as a percentage of GDP) per year. The GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products (The World Bank Group, 2015). Data are in current U.S. dollars and is gathered from the Worldbank. Trade is the sum of exports and imports of goods and services measured as a share of gross domestic product by the World Bank (2016) World Development Indicators. Data for trade is gathered from the QoG Standard Database and is measured as a percentage of GDP. Unemployment data is gathered from the QoG Standard Database, where it is measured as a percentage of the total labor force.
Trade=0.902, Unemployment=-0.718). This resulted in the new variable Average Bloc Welfare (for years 1991-2013). I did the same for the new member countries. Here I also performed a Principal Component Analysis to check if the number of variables can be reduced. The results show that the variables can be combined into one component explaining 62.330% of the variance with all coefficients above an absolute value of 0.5 (i.e. GDP=0.782, Trade=0.798, Unemployment=-0.788). This resulted in the new variable Average New Welfare (for years 1963-2013).
The independent variable Trade bloc expansion is measured by looking at the country level per year. This is a binary variable. 0 = no new country added to bloc, 1 = new country added to bloc. For example, Brunei entered the ASEAN bloc in 1984. Therefore, the cases 1983 and lower have a 0 in the Extension variable, and all cases 1984 and above have a 1 for this variable.
The independent variable Corruption Distance was measured by using the Bayesian Corruption Index (with data available from 1984 – 2014). Given the hidden nature of corruption, direct measures are hard to come by, or inherently flawed (Standaert, 2015). Instead, in the Bayesian Corruption Index, Standaert (2015) combines the opinion on the level of corruption from inhabitants of the country, companies operating there, NGOs, and officials working both in governmental and supra-governmental organizations. According to Dimant and Tosato (2017), the empirical research on corruption has advanced due to the more convenient and better availability of data although it has only recently become a focus area for the economic field.
With data available for all countries in our sample, I created a yearly average for the countries who were the original bloc members. I then subtracted the corruption scores per country per year from the bloc average for that year to create the variable Corruption Distance.
The independent variable Cultural Distance was measured by applying the Kogut and Singh (1988) measure of cultural distance based on Hofstede’s (1980) four-dimensional framework. Here I created bloc averages for each of the four trading blocs and used the Kogut and Singh formula to calculate the cultural distance of a country to the bloc average (see formula 1).
(1) 𝐶𝐷𝑗 =∑{(𝐼𝑖𝑗− 𝐼𝑖𝐴𝑆𝐸𝐴𝑁) 2 4
𝑖=1
/ 𝑉𝑖 } / 4
- Iij is country j’s score on the ith cultural dimension - IiAEAN is the score of ASEAN on this dimension - Vi is the variance of the score of the dimension
The scores for the bloc averages and distances per bloc are presented in annex 2-6.
Because I now have two variables measured at different scales they do not contribute equally to the analysis (BioMedware, 2002). For example, if one variable has a scale that ranges from 0 to 1 and another variable has a range of 0 to 100 the latter variable will have a larger weight in the analysis. I have therefore rescaled the culture and corruption variables with the z-score formula in SPSS, giving them a mean of 0 and a standard deviation of 1.
Furthermore, I used three dummy variables as controls. I used year dummies (1963-2013), one for each year. These are binary variables with a zero for cases that are not for that specific year and a one for cases in that year. Additionally, I created four bloc dummies, one per bloc. With zero for cases that are not member of a trading bloc in that year and one for cases where a country is a member of that trading bloc.
4. Analysis and results
In order to test hypotheses one, three, and five, a linear regression was conducted five times. A significant positive effect was found (F(54, 619)= 16.983, p <0.01), with an R2 of 0.597
supporting hypothesis one that the expansion of trading blocs will positively affect member country welfare. With respect to the expected negative effect of corruption and the interaction effect with bloc extension, I found bloc extension to significantly affect bloc member welfare
(F(35, 431)= 21.915, p <0.01), with an R2 of 0.640. The sign for corruption distance and the
interaction term are both found to be positive and both are not significant. The negative moderating effect of corruption distance and the positive relation between the expansion of trading blocs and original member country welfare is not confirmed by the interaction term (see annex 7 for a plot of the interaction effect). I thus reject hypothesis three. When checking for the expected interaction effect of cultural distance I found (F(56, 566)= 15.715, p <0.01), with an R2 of 0.609. Bloc expansion, cultural distance, and the interaction term are not
significant (see annex 8 for a plot of the interaction effect). However, the interaction term does have the expected negative sign. I therefore cannot confirm that the positive relation between the expansion of FTAs and original member welfare is negatively moderated by the cultural distance and therefore reject hypothesis five. The final model includes all variables and interaction terms. No significant negative effect was found for bloc extension (F(37, 399)=
20.321, p <0.01), with an R2 of 0.653. Corruption distance and the interaction term of bloc
Correlations Mean Deviation Std. N 1 2 3 4 5 6 7 8 9 10 1. Average Bloc Welfare -0,239 0,953 437 1,00 2. Bloc extension 0,934 0,249 437 -0,07 1,00 3. ZCultural Distance -0,768 0,474 437 -0,32 0,21 1,00 4. Extension* Culture -0,693 0,496 437 -0,26 -0,37 0,82 1,00 5. ZCorruption Distance 0,452 0,899 437 0,02 -0,04 0,25 0,26 1,00 6. Extension* Corruption 0,412 0,889 437 0,01 0,12 0,28 0,20 0,97 1,00 7. ASEAN dummy 0,263 0,441 437 0,26 0,16 0,24 0,14 -0,04 -0,02 1,00 8. EU dummy 0,394 0,489 437 -0,62 0,21 0,41 0,27 -0,06 -0,02 -0,48 1,00 9. Mercosur dummy 0,206 0,405 437 0,12 -0,34 -0,29 -0,10 0,14 0,08 -0,30 -0,41 1,00 10. NAFTA dummy 0,137 0,345 437 0,41 -0,11 -0,56 -0,44 -0,03 -0,03 -0,24 -0,32 -0,20 1,00
extension and cultural distance show the expected negative sign, though none of the variables is significant. In table 2, the results of the OLS regressions are presented.
In order to test hypotheses two, four, six, the same linear regression was conducted five times. Although the sign is positive, no significant negative effect was found (F(54, 1179)= 39.788, p
<0.01), with an R2 of 0.646. I therefore reject hypothesis two that the expansion of trading blocs
will positively affect new country welfare. With respect to the expected interaction effect of corruption, I did not found bloc extension to significantly affect bloc member welfare (F(35,
720)= 45.140, p <0.01), with an R2 of 0.687. However, the sign for bloc extension is again
positive. The sign for corruption distance is also found to be negative, while the interaction term is positive, both are not significant (see annex 9 for a plot of the interaction effect). The negative moderating effect of corruption distance and the positive relation between the
expansion of trading blocs and new member country welfare is not confirmed by the interaction term. Thus, hypothesis four is rejected. When checking for the expected interaction effect of cultural distance I found (F(56, 947)= 22.082, p <0.01), with an R2 of 0.566. Bloc
Controls H1 H3 H5 All Constant 0.175 -1.674* -2.543* -0.993* -0.692 Independent variables Bloc Extension 0.853* (0.101) 1.188* (0.161) 0.644 (0.473) 0.588 (0.911) Corruption Distance -1.999E-11 (0.134) -0.024 (0.181) Bloc extension * Corruption distance 2.105E-11 (0.137) 0.022 (0.184) Cultural Distance (0.392) 0.174 (0.746) 0.534 Bloc extension * Cultural distance -0.173 (0.386) -0.523 (0.742) Controls
Year yes yes yes yes yes
ASEAN dummy (0.079) 0.333* (0.075) 1.328* (0.074) 1.323* (0.097) 0.134 - EU dummy -0.801* (0.060) - - -1.193* (0.095) -1.324* (0.074) Mercosur dummy - 1.207* (0.075) 1.199* (0.077) - -0.129 (0.101) NAFTA dummy 0.688* (0.076) 1.845* (0.082) 1.831* (0.090) 0.674* (0.113) 0.538* (0.125) R² 0.551 0.597 0.640 0.609 0.653 N 674 674 467 623 437 F 14.338 16.983 21.915 15.715 20.321
Standard errors are listed in parentheses. * denotes significance at 5% level.
expansion is positive, but not significant. Cultural distance and the interaction term with bloc extension are both not significant. However, the interaction term of cultural distance with bloc extension does have the expected negative sign (see annex 10 for a plot of the interaction effect). I therefore cannot confirm that the positive relation between the expansion of FTAs and new member welfare is negatively moderated by the cultural distance and reject hypothesis six. The final model includes all variables and interaction terms. A significant negative effect was found for bloc extension (F(37, 571)= 21.821, p <0.01), with an R2 of 0.586. Corruption
distance and cultural distance show the expected negative sign. However, none of the variables apart from bloc extension is significant. In table 3, the results of the OLS regressions are presented. Controls H2 H4 H6 All Constant -1.155* -1.163* -1.078* -1.104* -1.232* Independent variables Bloc Extension 0.033 (0.034) 0.024 (0.47) 0.057 (0.43) 0.088 (0.058) Corruption Distance (0.034) -0.002 (0.039) -0.007 Bloc extension * Corruption distance 0.001 (0.040) 0.000 (0.046) Cultural Distance 0.012 (0.019) 0.041 (0.036) Bloc extension * Cultural distance -0.034 (0.030) -0.064 (0.043) Controls
Year yes yes yes yes yes
ASEAN dummy 1,315* (0.043) 1.310* (0.043) 1.361* (0.047) 1.286* (0.101) 1.284* (0.106) EU dummy - - - - - Mercosur dummy 0.702* (0.061) 0.712* (0.062) 0.724* (0.084) 0.715* (0.067) 0.739* (0.091) NAFTA dummy (0.045) 1.213* (0.045) 1.210* (0.060) 1.192* (0.049) 1.205* (0.067) 1.167* R² 0.645 0.646 0.687 0.566 0.586 N 1234 1234 756 1004 609 F 40.523 39.788 45.140 22.082 21.821
Standard errors are listed in parentheses. * denotes significance at 5% level.
5. Discussion and conclusion
This study investigates the relation between the expansion of trading blocs on member country welfare and entering country welfare with the possible moderating effects of corruption and cultural distance. The results of my study demonstrate that the expansion of trading blocs positively affects original member country welfare. However, I did not find evidence to support this statement for entering countries Additionally, in both cases the negatively moderating effects of cultural and corruption distance cannot be confirmed by this research.
5.1 Theoretical implications
Building on the works of Bond and Syropoulos (1999), and Bond et al. (2004) I expected that the expansion of trading blocs would have a positive effect on member country welfare. This assumption is confirmed by the results from our OLS regressions. Furthermore, I hypothesized that this effect is negatively moderated by corruption distance and cultural distance for both member countries as new members. However, in both tests this does not seem to be the case. In fact, there appears to be a counterintuitive positive effect of corruption distance on the relationship between trade bloc expansion and welfare. This might may explained by the difficulty to measure corruption, so that we did not fully caught the effect in this study. Another possible explanation is that the model might be more complicated than was tested in this paper. For the cultural distance interaction term, we do see the expected negative sign, although it is not significant in both cases. Further research might look into this while including a broader measure of culture to see if this changes the effect.
5.2 Practical implications
Alternatively, this paper measures economic welfare, although people might not express their own welfare in terms of wealth. Another concern might be that multinationals get too much power, while smaller businesses and the environment are overlooked.
5.3 Contributions
The aim of this paper was to answer the research question: How is country welfare affected by
trading bloc expansion? I hypothesized that the expansion would have a positive effect on
country welfare, and also that this relation would be negatively moderated by corruption and cultural distance. As it was elaborated in the literature review blocs are continuously expanding and the inhabitants are openly hesitant about adding new members to a bloc their country is a part of. With this research the opponents of expansion can be reassured with the knowledge that trade bloc expansion does not have a negative influence on country welfare. I can also add that in this specific research there was no negative effect of corruption distance and cultural distance. Alternatively, I did find a negative effect on welfare for new member co untries. However, this study does not incorporate the long-term effects for new members, so this effect might be counterbalanced later on or by other benefits from entering the trade bloc.
5.4 Limitations
The effect of a new country entering can already start before a country has actually become a member. Due to starting negotiations and arrangement, people may already start to trade more, therefore skewing the timeline. Another way that this study is limited is in the cultural distance measure. Shenkar (2001) critiques, among others, the illusion of causality of this measure. He states that distance is a multidimensional construct and should be studied not in isolation but together with geographic distance, institutional distance.
5.5 Conclusion
This paper has examined the effect of trading bloc expansion on member country welfare and aspiring country welfare with a possible moderating role for corruption and culture. Looking at the results, I conclude that the expansion of trading blocs does indeed have a significantly positive effect on country welfare. With respect to the moderating effect, I found that these were not significant. There remains much work to be done in the field of trading bloc expansion and the many effects it causes, but we can conclude that We are only as strong as we are united,
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Annex
Annex 1: Bloc members (original in color)
ASEAN EU NAFTA MERCOSUR
Malaysia Belgium Mexico Brazil
Philippines Bulgaria United States Uruguay
Singapore Czech Replublic Venezuela
Thailand Denmark Vietnam Estonia Finland France Germany Greece Hungary Ireland Italy Latvia Lithuania Luxembourg Malta Netherlands Poland Portugal Romania Slovakia Slovenia Spain Sweden United Kingdom Annex 2: Average bloc culture scores
PDI IDV MAS UAI
ASEAN 82,80 22,40 48,40 40,00
EU 49,33 71,50 49,50 73,83
NAFTA 39,50 85,50 57,00 47,00
MERCOSUR 59,67 40,00 47,67 87,33
Annex 3: Distance to ASEAN bloc
ASEAN average
PDI IDV MAS UAI
Annex 4: Distance to EU bloc
EU average
PDI IDV MAS UAI
49.3 71.5 49.5 73.8 K=4 Country Distance Austria 51.3 Belgium 26.2 Bulgaria 48.6 Czech Republic 20.2 Denmark 68.5 Estonia 28.1 Finland 33.3 France 23.2 Germany 24.0 Greece 54.4 Hungary 40.4 Ireland 48.0 Italy 21.0 Luxembourg 15.3 Malta 26.4 Netherlands 43.5 Poland 32.5 Portugal 58.5 Romania 60.8 Slovakia 86.9 Slovenia 59.8 Spain 26.1 Sweden 65.8 United Kingdom 47.9
Annex 5: Distance to Mercosur bloc
Mercosur average
PDI IDV MAS UAI
Annex 6: Distance to NAFTA bloc
NAFTA average
PDI IDV MAS UAI
39.5 85.5 57.0 47.0 K=4 Country Distance Canada 7.5 Mexico 78.6 United States 7.5
Annex 7: Plotted Interaction effect Corruption Distance * Bloc extension
-4 -3,5 -3 -2,5 -2 -1,5 -1 -0,5 0 A ve rage B loc W elf ar e
No bloc extension Bloc extension
Low Corruption distance
Annex 8: Plotted Interaction effect Cultural Distance * Bloc extension
Annex 9: Plotted Interaction effect Corruption Distance * Bloc extension
-2,5 -2 -1,5 -1 -0,5 0 A ve rage B loc W elf ar e
No bloc extension Bloc extension
Low Cultural distance High Cultural distance -2,5 -2 -1,5 -1 -0,5 0 0,5 A ve rage Ne w M em b er W elf ar e
No bloc extension Bloc extension
Low Corruption distance
Annex 10: Plotted Interaction effect Cultural Distance * Bloc extension -1,25 -1,2 -1,15 -1,1 -1,05 -1 -0,95 -0,9 A ve rage Ne w M em b er W elf ar e
No bloc extension Bloc extension
