Globalization has swept the world as the flow and spread of goods and services, people, capital, and even culture reaches every corner of the globe. This increasingly powerful force has led countries to be more interconnected than ever before. One result of the economic side of globalization has been the opening up to international trade and the implementation of trade liberalization policies. These policies resulting from the influence of globalization have the ability to drastically change a country’s economy and impact its people. Some see globalization as the only means by which developing countries can overcome poverty, while others argue that globalization is one of the causes of global poverty. A debate with such conflicting arguments proves to be very complex, and the means of globalization and the measures of economic growth can vary. There is also the importance of judging the short run and long run impacts. With globalization being such a powerful force reaching every corner of the globe, it is important to assess whether it has been beneficial to all countries and their people, or if some have been hurt or left behind.
From a Western perspective, globalization is generally seen as a positive force on economies because it expands trade and allows for more opportunities of growth. However, many developing countries have seen mixed results from implementing policies based on the principles of globalization. For example, developing countries in Asia have seen much more significant amounts of economic growth than their counterparts in Africa and Latin America (Dollar, 1992). The extent of this growth, and if there is any growth at all, will be examined in my research, to determine whether trade liberalization and more open economies lead to higher economic growth and an increase in wealth of a country’s population.
This paper will first compare several studies and articles that have examined the links between globalization, economic growth, and poverty. It will examine their theories, research methods, and findings. Next, the theory and hypothesis will be discussed and the research design, including data collection, will be laid out. Following, will be the results from the research and an analysis of them. Lastly will be the conclusion of this research, including its limitations and the broader meaning the results can have on the world.
The economic growth of developing countries is a topic of immense research and debate. Data collection and research began in the 1960s and has continued ever since. One of the first studies testing the link between an open economy and growth, and still one of the most cited, is David Dollar’s 1992 research. The main conclusion from his work is that trade liberalization will dramatically improve growth performance in developing countries (Dollar, 1992). Later studies by Frankel and Romer, 1999, Harrison, 1996, Rodriguez and Rodrik, 2000, Santos-Paulino and Thirlwall, 2004, and Waciarg and Welsh, 2008, echo these findings and continue on the research with more modern data. However, there are many other complexities of this question, which are examined within these studies.
The macroeconomic level is where most scholars measure general economic growth of the country. On this level many agree that trade liberalization does improve the economic performance of developing countries (Dollar, 1992; Harrison, 1996; Rodriguez & Rodrik, 2000; Santos-Paulino & Thirlwall, 2004; Wacziarg & Welch, 2008). But just how significant this growth is, or if it can even be attributed to policies of globalization are still disputed (Bigman, 2002). There is also the argument that trade liberalization alone is not enough to significantly improve economic growth (Harrison, 1996; Goldin & Reinert, 2012). Dollar argues that only when trade liberalization is paired with the devaluation of the real exchange rate and maintains a stable exchange rate will it greatly improve economic performance in developing countries. Similarly, Harrison, as well as Goldin and Reinert, are skeptical that liberalized trade policies alone are enough to cause significant economic growth. Several studies argue that trade liberalization is one of several indicators of openness, which weighs lightly in the result of economic growth (Winters & McCulloch & McKay, 2004; Harrison, 1996; Rodriguez & Rodrik, 2000). Frankel and Romer’s study concludes that the relationship between trade and economic growth may be greatly influenced by geographic location than the trade policies themselves. Wacziarg and Welch offer a different perspective in their conclusion. This study is one of the only cited that discusses outside factors, other than geography, that affect the impacts of trade reforms on the growth of economies. They argue that countries will experience negative or no effects on growth when they undergo either political instability, the adoption of contractionary macroeconomic policy after trade reforms, or enact policy to shield domestic sectors.
When analyzing the impact of globalization on the microeconomic level, there is much more disagreement among scholars and various conflicting evidence. Some studies suggest that after trade liberalization policies take effect, certain sectors of the labor force will see a reduction in wages (Arbache & Dickerson & Green, 2004; Winters & McCulloch & McKay, 2004; Bigman, 2002). The research so far offers a few explanations for this observation. Some argue that when economies are more open and trade more, workers in the import-competing sectors are likely to see a reduction in wages or a decrease in employment (Winters & McCulloch & McKay, 2004). There is also the theory that the growth in labor resulting from liberalization will occur mainly in the sectors of highly educated workers due to a higher demand for them. As a result, the unskilled workers that often make up the majority of the labor force in developing countries see a reduction in wages (Arbache & Dickerson & Green, 2004).
While all the previous research cited uses valid methods of research and uses strong evidence such as widely accepted theories and previous studies to support their arguments, their results may be outdated for the 21st century and a larger sample size may better reflect the impact of globalization on developing countries. The research by Wacziarg and Welsh consisted of a study of only 24 countries. From this study, the authors found that after trade liberalization thirteen countries experienced significant economic growth, six experienced negative effects, and the remaining five saw no effects. However, these results may not reflect trade liberalization outcomes of all developing countries because it is such a small sample. Similarly, Harrison’s study included data for only 23 countries, and conclusions made by Arbache, Dickerson, and Green were done so after examining a case study of Brazil. The largest sample of countries analyzed was Dollar’s study of 95 countries. However this data was collected from 1976 to 1985, which means the conclusions may be outdated. More recent data and data collected from a greater number of countries may provide a more accurate explanation of how globalization affects countries in the new era of globalization.
Just as there are many similar themes and findings within previous research, there are also similar methods used. Most of the previous studies used regression analyses to test the same variables that will be tested in this study. While the literature cited does provide a solid foundation to understanding the impact that globalization may have on the developing world, more recent research is needed on the issue. One of the most widely cited cases from Dollar was published in 1992, but uses data from 1976 to 1985. Harrison uses data from 1971 to 2000 in her research. Even though globalization is a fairly new phenomenon developing in the last century, it is such an important issue that it requires the most up to date research.
Furthermore, the cited literature falls short in assessing the long term impacts of trade liberalization. Globalization has been a studied phenomenon for a few decades but has only begun to transform developed countries more recently. The previous research on this topic was conducted when trade liberalization was just beginning in the developing world. In order to be able to understand its long term effects, more recent research is required.
The orthodox liberal assessment of the impact of globalization on development suggests that states that have integrated the most deeply into the global economy through trade liberalization have seen the most economic growth (Baylis, Smith, & Owens, 2014). The reason for this is that having more trade partners, exporting more goods, and importing more will cause an increase in GDP. Because economic size is most often measured by GDP, many would say the country has experienced economic growth. This relationship is the same when a country experiences more investment from foreign countries. Greater investment creates a larger economy, showing economic growth. Using this theory, it is presumed that increased trade and development will have positive effects on a country’s GDP.
Based on the literature, it is expected in this research that trade liberalization will have no effect on the population of developing countries. This is because some scholars argue that the labor force in the trade competing sectors see a reduction in wages when economies open up to trade (Arbache & Dickerson & Green, 2004; Santos-Paulino & Thirlwall, 2004; Winters & McCulloch & McKay, 2004). However, these studies also show that trade liberalization can grow new sectors of an economy and the workers in those sectors will see an increase in wages. I expect that the growth in certain sectors benefiting from more open trade will balance out the losses in the trade competing sectors to show no effect.
After reviewing previous research on economic openness and growth, there are a few hypotheses that can be made. Since there are studies that find trade liberalization improves the growth of economies, my first hypothesis is that an economy with more liberal trade policies will see higher economic growth on the macroeconomic level in terms of GDP.
However, there is also research to suggest that the microeconomic effects of trade liberalization can be mixed. The second hypothesis is that increased openness to trade will have no effect on the population of developing countries in terms of Human Development Index, and GDP per capita.
To test the hypothesis the dependent variable, the growth of the developing country, will be measured as increases in GDP, the Human Development Index, and income per capita. GDP and income per capita are common measures of economic growth that were often used in the previous literature. The Human Development Index measure is useful in determining the economic impact of individuals of developing countries rather than the economy as a whole. The GDP variable will give a broader picture of the economy while the per capita and Human Development Index variables show a more narrow point of view. The data on GDP was collected from the World Bank as the annual percentage of GDP growth per year. Data on the Human
Development Index data was collected from the United Nations Development Report for each year. Data on the GDP per capita was collected from the World Bank in US dollars.
The independent variable, openness of economies in terms of their liberal trade policies, will be measured quantitatively, as the amount of investment within a country as well as trade to and from the country. These factors are viable measures of the economic impact of globalization because as a country is more impacted by globalization, the economy will be more open and experience more trade and more investment. Data on foreign investment as a percentage of GDP was collected from the World Bank. Data on trade was also collected from the World Bank as trade to and from each country as a percentage of GDP.
Data was collected for this research on 138 developing countries* from the years 1995 to 2019. The hypothesis was tested through a linear regression analysis for each dependent variable for the years 2019, 2009, and 1999. The independent variables were tested as investment and trade from the years 2018, 2008, and 1998. Data for the independent variables was collected from the year before the dependent variable data because effects of trade policy are not immediately shown and are better reflected in the following year. A linear regression test was most appropriate for this research because it is used to determine if there is a relationship between an independent variable and a dependent variable. If there is a relationship, this type of analysis can also determine how changes in each independent variable are related to changes in the dependent variable.
The results from each regression analysis are shown in Table 1, 2, and 3. The standard error is listed in parentheses. An asterisk (*) indicates a p value less than .05. GDP stands for gross domestic product. HDI stands for Human Development Index score. GDPPC stands for GDP per capita.
Table 1: 2019 Data
|GDP 2019||HDI 2019||GDPPC 2019|
|Investment 2018 (% of GDP)||.003||.004||-169.411|
|Trade 2018 (% of GDP)||.004||.009||53.726*|
Table 2: 2009 Data
|GDP 2009||HDI 2009||GDPPC 2009|
|Investment 2008 (% of GDP)||-.185*||-.166||-50.728|
|Trade 2008 (% of GDP)||-.022||-.022||46.480*|
Table 3: 1999 Data
|GDP 1999||HDI 1999||GDPPC 1999|
|Investment 1998 (% of GDP)||.031||.027||-37.611|
|Trade 1998 (% of GDP)||.005||.006||29.284*|
Table 1 reports the regression for the dependent variables of the year 2019 and the independent variables for the year 2018. The asterisk (*) in the table indicates a p value of less than .05, which is interpreted as a significant relationship between the independent and dependent variables. The negative symbol (-) indicates that the independent variable has a negative relationship with the dependent variable. The results indicate that the only significant relationship was between GDP per capita in 2019 and trade in 2018. A significant relationship means that the independent variable, in this case trade, does positively affect the dependent variable, GDP per capita.
Table 2 reports the regression for the dependent variables of the year 2009 and the independent variables for the year 2008. Based on the results in this table, there are two significant relationships. The first is between investment in 2008 and overall GDP in 2009. The second is between trade in 2008 and GDP per capita in 2009. The negative symbol (-) in the cell for the investment and GDP regression shows that investment in 2008 had a negative influence on GDP in 2009. Because there is no negative symbol (-) for the second significant relationship, it can be interpreted that trade in 2008 positively influenced GDP per capita in 2009.
Table 3 reports the regression for the dependent variables of the year 1999 and the independent variables for the year 1998. The only statistically significant relationship is shown to be between GDP per capita in 1999 and trade in 1998. This means that trade from 1998 positively affected GDP per capita in 1999.
Based on these results, both hypotheses were incorrect. In terms of the first hypothesis, that openness would positively influence economic growth; investment and trade did not have significant impacts on GDP. Investment in 2008 actually had a significant negative influence on GDP. The second hypothesis, that openness would have no effect on HDI or GDP per capita was partially proven in the results. There were no significant relationships between either of the independent variables and HDI. However, consistently for each of the analyses, trade had a significant effect on GDP per capita. This disproves the second hypothesis.
Although the hypotheses were incorrect, the literature suggests that these results are to be expected. If the majority of the countries in the analysis enacted liberal trade policies but did not accompany them with the devaluation of the real exchange rate or maintained a stable exchange rate, the growth potential may be stunted and the variables would not show as significant in the analysis (Dollar, 1992). Also, trade liberalization is only one of several indicators of openness, so it may weigh lightly in the result of economic growth (Winters & McCulloch & McKay, 2004; Harrison, 1996; Rodriguez & Rodrik, 2000). Perhaps there are other measures of economic openness that should be considered in order to find a significant relationship, or several indicators of openness should be analyzed together in order to be significant. Using trade and investment alone in separate analyses may not be a comprehensive enough measure to show significance in affecting economic growth.
These results could also be compared to the “trickle down” approach that was attempted in certain developing countries which produced results very similar to the findings in these analyses. Although there were found to be impressive rates on growth of GDP per capita in some developing countries, the success was not reflected in the societies in terms of overall GDP or the HDI (Baylis & Smith & Owens, 2014). Although there may be a small portion of the population that becomes substantially wealthier from economic liberalization, shown in the significant rise in GDP per capita, the rest of the population and most of the economic sectors see no significant change, reflected in overall GDP (Baylis & Smith & Owens, 2014).
The real world implications of this research are quite eye opening and can change the way that economic liberalization is handled in developing countries. While policies of trade openness may bring extreme wealth to some in developing countries, these gains are only for a very small portion of the population and perhaps even for a short period of time. The rest of the population and the sectors of the economy that are left out of the traded sectors may actually see a worsening of their economic well being, thus exacerbating income inequality (Arbache & Dickerson & Green, 2004; Winters & McCulloch & McKay, 2004; Bigman, 2002). In order to keep economic inequality within developing nations from growing larger, policies should be put into place that empower local communities and ensure a better distribution of income (Baylis & Smith & Owens, 2014).
This research may also offer a possible explanation to the long term effects of trade liberalization that were not able to be addressed in the previous literature. Beginning in the 1960s and in the few decades following, developing countries began to implement liberal trade policies and most saw significant economic growth on the macroeconomic level (Dollar, 1992; Frankel & Romer, 1999; Harrison, 1996; Rodriguez & Rodrik, 2000; Santos-Paulino & Thirlwall, 2004; Wacziarg & Welsh, 2008). However, this research suggests that overtime, after these policies have been in place and encouraged a quick boost of growth, the effects are not long lasting. Over time, the high levels of economic growth due to these policies may fizzle out and its effects become insignificant. Even more concerning is that in later decades even though overtime economic growth slows, income inequality continues to worsen and the gap widens.
One result that is a bit more difficult to explain is the significant relationship between investment in 2008 and GDP in 2009. This is not consistent with all three analyses, so it seems to be an anomaly of significance. In order to know more about investment and GDP in the developing world around this time more analyses should be conducted. This significance may be a deviation in 2009, or it may be a trend in the early 2000s that investment was hurting the economic growth of developing countries. It is not a reality that had been considered in the hypotheses but would certainly be important to study further. However, it does not seem to be a continuing hindrance to economic growth because it was not significant in the analysis of the most recent data from 2019.
Further research could include case studies of specific countries to analyze the individual factors of the country at the time of liberalization, including some of the factors mentioned in the previous literature such as, devaluation of the real exchange rate, maintaining a stable exchange rate, political instability, or the adoption of contractionary macroeconomic policy after trade reforms (Dollar, 1992; Wacziarg & Welsh, 2008). Having a smaller sample would allow the researcher to better understand the conditions surrounding each economy and how they impact growth and trade. It is almost impossible to factor in all of the economic and political circumstances that affect growth of all 138 countries. While this research was able to determine if trade and investment alone are significant in affecting growth, it may be valuable to study whether trade and investment along with the other factors has more of an impact on growth.
Beyond this research there are still questions that remain unanswered regarding the topic of globalization and economic growth. For example, why in this research is trade liberalization not continually significant in affecting the GDP of developing countries like it was shown to be in previous studies? For what reason did investment in 2008 negatively influence GDP in 2009? Also, if trade liberalization can be effective in producing high levels of economic growth, what other factors and policies must accompany trade liberalization to be significant? Although globalization has had such a positive impact on growing the economies of certain nations such as China, Japan, and the United States, the fact that there is still a categorization of developing countries which have low GDP and GDP per capita numbers and extreme poverty should be of great concern. There should be more research to find the most effective routes to economic growth that benefit all sectors of the population. It may not be a one size fits all solution, and may not even include any policies of trade liberalization. But if developing countries are seeing a trend towards economic stagnation and increasing income inequality that has been suggested by this research, there may need to be a very different approach.
*Upon further investigation the editors were unable to determine the exact countries analyzed for the study
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