The impending U.S. military build-up on the island of Guam, a U.S. territory located in Western Pacific, is expected to drastically change the island's socio-economic landscape. There is concern about who would gain and who would lose on the road to economic development. The consensus in the literature that the economic development process could be designed so that it would have an equalizing effect on income distribution suggests a role for deliberate policymaking and economic planning.
This paper will look at the issue of income distribution in general and in the context of Guam in particular. It will present a review of literature on the relationship between economic development and income distribution, followed by a section on the measures of income distribution and available data on Guam, where attempts are made to explain changes in Guam's income distribution over time
Based on our review of existing literature on Guam's income distribution, this paper is the first attempt to analyze existing data on this issue. As such, it not only contributes to the academic literature but also fills in the serious gaps in both the availability and analysis of reliable, current and relevant economic data on Guam. It is hoped that this paper will provide policymakers, businesses and communities, both local and international, with an effective tool to plan for future decisions and courses of actions that will aid in Guam's economic development.
Guam is at a critical juncture in its economic history. The impending military build-up on the island is expected to drastically change its socio-economic landscape. Since the planned move of the Marines from the base in Okinawa, Japan to Guam was first announced in October 2005, policymakers and the private sectors have engaged in discussions on how best to harness this major event into one that will enhance the island's economic development prospects.
As in other economies that faced a similar opportunity to increase its level of economic development, there is concern about how the resulting economic development will affect the local population. Who gains and who loses on the road to economic development?
One concern in particular is how economic development will affect the way in which incomes (or more broadly, resources) are shared by or distributed among the local population. Although the literature presents mixed evidence on the relationship between income distribution and economic growth, there appears to be a consensus on the statement that "it is the character of economic growth (how it is achieved, who participates, which sectors are given priority, what institutional arrangements are designed and emphasized, etc.), not economic growth per se, that matters (Todaro, 2000, p. 179). In other words, the economic development process could be designed so that it would have an equalizing effect on income distribution. This clearly points to a role for deliberate policymaking and economic planning.
Furthermore, there is no evidence to suggest that a more equitable income distribution would be possible only at the expense of rapid economic growth. As Todaro (2000) notes, "rapid economic growth and more equitable distribution of income are not necessarily incompatible as development objectives." (page 179)
This paper will look at the issue of income distribution in general and in the context of Guam in particular. The paper is organized in the following section: a review of literature on the relationship between economic development and income distribution and measures of income distribution and data on Guam, with attempts to explain changes in Guam's income distribution over time.
Based on our review of existing literature on Guam's income distribution, this paper is the first attempt to analyze existing data. As such, it not only contributes to the academic literature but also fills in the serious gaps in both the availability and analysis of reliable, current and relevant economic data on Guam. It is hoped that this paper will provide policymakers, businesses and communities, both local and international, with an effective tool to plan for future decisions and courses of actions that will aid in Guam's economic development.
THE RELATIONSHIP BETWEEN ECONOMIC DEVELOPMENT AND INCOME DISTRIBUTION: A REVIEW OF LITERATURE
The literature on the relationship between economic development and income distribution presents the possibility of the causal relationship running in both directions, that is, that economic development can have an impact on income distribution, and vice versa, that income distribution can affect the economic development process. Throughout the section, the term "economic growth" and "economic development" will be used interchangeable, although it is recognized that the two concepts are not identical. However, with deliberate policies, the economic growth can be made consistent with economic development. Consistent with the points just made, this section is then presented by first reviewing the literature on the effect of economic growth and development on income distribution, followed by the effect of income distribution on economic growth and development, keeping in mind the words of Meier and Rauch (2000) that "it is theoretically possible, of course, that development has no impact on income distribution." (page 375)
Effect of Economic Growth and Development on Income Distribution
Todaro (2000) asks "Does the pursuit of economic growth along traditional GNP-maximizing lines tend to improve, worsen or have no necessary effect on the distribution of income?" (page 176)
The question of how economic growth and development might affect income distribution has become synonymous with the "Inverted-U" hypothesis by Kuznets (1 955). As the name suggests, the hypothesis puts forth a non-linear relationship between the level of economic development (usually measured as per capita real income) and the level of income inequality (originally measured by distribution of household incomes by quintiles). The hypothesis states that, as economic development takes place and per capita income increases, income inequality will first increase then later decrease (equivalently, income distribution will first worsen then later improve). Kuznets attributed the increased income inequality to industrialization and urbanization, that is, the economy's transition from being predominantly agriculture-based to one with a more significant industrial sector. The decrease in income inequality that occurs later is due to "a decline in inequality within urban areas caused by better adaptation of the children or rural-urban migrants to city economic life and growing political power of urban lower-income groups to enact legislative favoring their interests." (Meier and Rauch, 2000, page 376).
Unfortunately, Kuznets' intriguing hypothesis and the compelling explanations do not subject themselves readily to empirical testing. For one, the availability, quality and comparability of data on income distribution present a challenge. In addition, as Kuznets noted, empirical testing would require long periods of data, spanning about one generation. Given this challenge, later scholars used one of two approaches to test Kuznets' hypothesis using contemporary data: using cross-section, cross-country data on per capita real income and a measure of income inequality (Ahluwalia, 1974) or time-series data on developing and developed countries to see if income inequality increases for former and decreases for the latter (Fields, 1991). Empirical studies provide mixed evidence on Kuznets' hypothesis.
Some interpreted the lack of evidence to support Kuznets' hypothesis as challenging the argument, usually rooted among classical economists, that income distribution is functional. In particular, a worsening of in the income distribution can be viewed as desirable as it serves the function of allowing capital owners, who save and invest, the larger share of the nation's income. Referred to as "traditional arguments" in Todaro (2000), it prescribes that "highly unequal distributions are a necessary condition for generating rapid economic growth" (page 181). As there is no clear evidence to support the Kuznets' hypothesis, Todaro (2000) continues to say that "the growth strategy based on sizable and growing income inequality may in reality be nothing more than an opportunistic myth designed to perpetuate the vested interests and maintain the status quo of the economic and political elites of Third World nations, often at the expense of the great majority of the general population." (page 183). Similarly, Perkins et al. (2001) says that "we no longer can argue with confidence that rising inequality can be tolerated because it is temporary and can be counted on to reverse itself in a later stage of development." (page 130). In addition, Meier and Rauch (2000) point to the East Asian Miracle as an example of how economies with relatively equal income distribution can achieve rapid economic growth, (page 377)
Effect of Income Distribution on Economic Growth and Development
Unlike the classical/traditional argument that suggests that an unequal income distribution has a positive effect on economic growth and development, "it is now more commonly believed that the impact of inequality on development is negative rather than positive." (Meier and Rauch, 2000, page 377). Examples of work that look into the negative impact of income inequality on economic growth include Alesina and Rodrik (1994) and Alesina and Perotti (1996), with the latter focusing on the mechanism that brings about this negative relationship, in this case, political instability. In addition to the finding that higher income inequality reduces economic growth, Alesina and Rodrik (1994) also found that this relationship applies equally to democratic and non-democratic economies, and that wealth redistribution (land reform, for example) enhances economic growth.
In the second study, Alesina and Perotti (1996) asked two questions: "Does income inequality increase political instability?" and "Does political instability reduce investment (and hence economic growth)?". Based on data from 71 countries over the period 1960-85 and constructed variables ("middle class" and "socio-political instability index"), they answered both questions in the affirmative.
Although there is no consensus on the literature, our review reveals that both direction of causation are possible, that is, economic development can affect income distribution, and that income distribution can affect economic growth and development. However, there seems to be weak evidence, if any, on the traditional/classical argument that a faster economic growth and development are possible only as a result of a deterioration of income distribution, in this case, higher income inequality will enhance economic growth and development. The evidence suggests the opposite: that higher income inequality will stifle economic growth and development.
Up to now, none was said about these issues in the context of Guam nor were attempts made to cast these issues in the context of Guam. This is planned for the subsequent part of this paper. However, as noted earlier, based on our review of existing literature on income distribution, we believe this paper to be the first attempt to analyze existing income distribution data for Guam.
MEASURES OF INCOME DISTRIBUTION
In this paper, we will use the Gini index (also, Gini coefficient) as the measure of income distribution. This measure will later be calculated using data from Guam during the period 1981-2005.
In calculating our Gini index for Guam, we are mindful of the suggestions made by Kuznets (1955) in making sure that resulting Gini indexes are as accurate a measure of Guam's income distribution as is possible. Hence, we used the following assumptions on our data and calculations.
Income is measured by household, not be individuals . On this, Kuznets' recommended unit of income is household income per capita, found by taking the total income of the household and dividing by number of people in the household. Note that this is not the same as individual or personal income.
Household income data must include all households in the country (or island, in the case of Guam). We believe the Guam data satisfies this requirement.
Given the structure of households on Guam, not all household members are family members or relatives.
Household incomes are pre-tax money receipts of all residents over the age of 15 are combined-should really be post-tax. Most of these receipts are in the form of wages and salaries (before withholding and other taxes), but many other forms of income, such as unemployment insurance, disability, child support, etc., are included as well. In contrast, Kuznets would recommend the use of post-tax income and would make sure receipts "in kind" are also included.
Other of Kuznets' data specifications that are not specifically addressed in this study are the following: consider income generated from full-time, full-fledged employment; income groups categorized by secular (long-term) income, where the cyclical and transient movements in income data are smoothed out; separate new migrants to the urban areas from "residents". The last factor will be of particular interest when studying Guam, especially during the military build-up, where there are predictions of a substantial increase in temporary residents in the form of military personnel and their family as well as temporary workers.
Using the Gini index, which is derived from the Lorenz curve, inequality is measured by the extent to which the actual distribution of income, consumption expenditure, or a related variable, differs from a hypothetical distribution in which each person receives an identical share. This is why the Gini index varies between zero and one, where a Gini index of zero represents "perfect equality" in how incomes are distributed among households in a country or island and a Gini index of one represents "perfect inequality". Based on Figure 1, the Gini index is then calculated as the area labeled "Gini index" as a proportion of the area of the triangle (made up of the areas above and below the Lorenz curve).
Using data on the Gini index as a measure of income inequality for 127 countries (United Nations Development Program, 2008) and graphing each country's Gini index against its per capita income (measured in 2005 US$ PPP), we see in Figure 2 that there is an inverse slightly non-linear relationship between income inequality and economic development. The correlation coefficient between these two variables is -0.41. Since correlation does not imply causation, we are unsure whether it is the increase in per capita income that makes income distribution more equal or the worsening income distribution that decreases per capita income. Assuming it is the first causal relation, the graph below does not appear to support Kuznets' hypothesis, at least in the way the empirical tests have been performed in the literature using cross-section, cross-country analysis.
INCOME DISTRIBUTION ON GUAM
Data on household income on Guam are available by different income groupings on an annual basis from 1981 to 2005. Figure 3 below presents a graph of these income data. For comparison, corresponding data from the mainland United States are also presented for comparison. Based on Figure 3, the following observations can be made. First, estimates of the Gini index for Guam have greater variability than those for the U.S. largely reflecting Guam's greater exposure to natural disasters such as typhoons and earthquakes. Another observation is that, since 1989, Guam's Gini index estimates have been lower than those forthe U.S., thus suggesting a more equal distribution of household incomes on Guam than in the U.S.
Explaining Changes in Guam's Income Distribution
Just looking at Guam data alone, it is tempting to make a statement that describes the overall trend in income distribution as one where it was first improving, with the Gini index decreasing from 1 985 to 1 992, and then deteriorating after that (disregarding the large drop in the index in 2005). One would then look at factors that affect Guam's economy during this period such as those presented in Figure 3.
One approach to understanding changes in Guam's income distribution data might be to divide the 1981-2005 period into two sub-periods: from 1981 to 1992 and from 1992 onwards. By doing this, we recognize that the yearly movements in the Guam's Gini index might not be as meaningful as what appeared to be an improvement on Guam's income distribution up through 1992, followed by a deterioration afterwards. The earlier period, which is associated with an improvement in Guam's income distribution, was a period of a huge boost in the tourism industry and a strong economic period in the East Asian region. Note that during this period, Japan's economy was first strong until the late 1 980s when the economic bubble burst, followed by a long period of stagnation. In contrast, the latter sub-period from 1992 to 2005 was a period of Guam's economic history marred by natural and mamnade disasters (four typhoons, two supertyphoons, two earthquakes and SARS outbreak in Asia). Other aggravating factors during the same sub-period include the Asian financial crisis and crash of Korean Airliner, both occurring in 1 997, September 1 1 terrorist attacks, and the U.S. military response to terrorism, which deployed a proportionately higher proportion of service personnel from Guam. See Figure 4 for details.
Although we attempted to offer explanations for both the longer-run trend on Guam's Gini index over the two sub-periods 198 1-1 992 and 1992-2005 as well as the shorter timeframes of a year or two years, we believe that conclusions from such exercise should be taken with caution. Recall that Kuznets stated that income distribution is a long-period, secular concept, spanning a generation or around 25 years.
Neither the academic literature in general nor the empirical data on Guam gives a definite answer as to the causal relation between economic growth and income distribution on Guam but existing data show a strong correlation. In particular, data show that income distribution on Guam improved during the sub-period 1981-1992, which was a period associated with stronger economic growth. In contrast, the sub-period 1992-2005 saw a deterioration in the income distribution on Guam at the same time that many natural and manmade factors slowed Guam's economic growth.
Nonetheless, the presence of a positive correlation between income distribution and economic growth in Guam's experience makes one thing clear: an economy that grows is better than one that does not grow. This conclusion casts in positive light the impending military build-up on Guam. What this means is that, although the military build-up per se will not necessarily bring about sustainable and equitable economic development on Guam, it however presents an opportunity for Guam's economy to grow. The rest is up to the people of Guam and its policymakers who should continue to engage in constant dialogue and careful evaluation of possible scenarios for Guam's economic future. By doing so, the growth opportunity presented by the military build-up can be harnessed to bring about a sustainable and participatory economic development for the island of Guam and its people.
We acknowledge the assistance provided by Mr. Evan Carpenter, Mr. Vincent Duenas and Mr. Egbert Mabel at the data gathering and organizing stage of this paper. Dr. Ruane is also grateful for the financial support of the University of Guam-Pacific Center for Economic Initiatives.
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Maria Claret M Ruane, University of Guam
Ning Li, University of Guam…