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HomePublicationsCatalogAssessing Socioeconomic Impacts of Transport Infrastructure Projects in the Greater Mekong SubregionInfrastructure and Development in the GMS

Infrastructure and Development in the GMS

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Almost 320 million people live in the GMS, which bridges South, Southeast, and East Asia. While ADB (2010) believes that “the Mekong region has the potential to be one of the world's fastest growing areas,” economic development continues to elude some member countries and alleviating poverty remains a significant challenge. Infrastructure development has been shown to be an important mechanism to facilitate growth and development.2 With this in mind, the GMS has pursued an agenda of comprehensive infrastructure improvement.

Table 1 [ PDF 22.1KB | 1 page ] presents summary data for the GMS. Populations range from just over 6 million people in the Lao PDR to over 90 million in the combined Yunnan/Guangxi region of the PRC. Likewise the economies range widely in size, with the value of gross domestic product (GDP) in the Lao PDR around US$5.5 billion while Thailand's GDP is almost 50 times as large, at over US$270 billion. GDP per capita ranges from under US$900 in Cambodia, Lao PDR, and Myanmar to over US$4,000 in Thailand. While there is variation across the GMS, overall it remains a relatively poor region, as shown by the World Bank poverty estimates in Table 1.

As economies develop, they generally experience a structural shift away from a relative dependence on the agricultural sector and a movement into higher-valued areas of production. This shift can be observed in many of the GMS economies. For example, agriculture contributed approximately 39% of Viet Nam's GDP in 1990 but this had fallen to around 22% by 2008 (World Bank 2010). Despite this, GMS economies continue to rely relatively heavily on the agriculture sector; this is particularly the case in the lower-income countries, where the contribution of agriculture to the economy is much greater—almost 50% of GDP in the case of Myanmar (final column of Table 1). While the contribution of agriculture to output in the economy tends to decline over time, this does not undermine the importance of the agricultural sector for economic development. Binswanger and Lutz (2000) argue that because almost all nonfarm activities in rural areas are linked to agriculture, growth in agricultural demand is a necessary condition for rural growth. They suggest that rural regions cannot achieve sustained growth in agricultural demand unless they trade. Thus, improved transportation infrastructure, allowing rural regions to access export markets, can make an important contribution to agricultural trade and rural poverty reduction. Many agricultural products are produced by poor rural farmers who need access to roads in order to market their products effectively, particularly as products may deteriorate during transportation.

Poverty is multi-dimensional, and a range of different measures can reduce it;3 however, regardless of the measure used, it remains predominantly a rural problem for most poor countries, including in the GMS. Worldwide, over two thirds of the poor in developing countries live in rural areas, where poverty tends to be more acute in terms of income and nutritional status than in urban areas (e.g., Binswanger and Lutz 2000). The predominantly rural nature of poverty in the GMS is striking (Strutt and Lim 2005). Table 2 [ PDF 21.4KB | 1 page ] shows that for each GMS country, the rural population is more than 57% of the total population, with rural dwellers comprising almost 80% of the population in Cambodia. Given the importance of rural communities, a range of studies suggest that rural road investments are likely to bring particularly strong benefits for economic growth and poverty reduction (Jones 2006; Straub, Vellutini, and Warlters 2008). Connecting economic activities to the logistical hubs of the urban area is an important task for development.

In terms of population density and land area, Table 2 indicates significant variation among GMS countries, with land area ranging from under 180 thousand square kilometers in the case of Cambodia to over 650 thousand square kilometers for Myanmar. Population density ranges from 27 people per square kilometer in the Lao PDR to over ten times this density in Viet Nam, at 278 people per square kilometer. It is notable that the poorest countries of Cambodia, Lao PDR, and Myanmar all have particularly limited road networks, with less than 15% of roads paved. These are also countries with relatively low population densities and limited resources to provide rural populations with access to markets and the accompanying opportunities.

Looking more specifically at land area and road coverage, the kilometers of road per square kilometer of land can be used as an indication of road density. For comparison, we present road density along with population density and include the United States (US), Japan, and the Euro Area. Results are shown in Figure 1 [ PDF 43.4KB | 1 page ], with the bars referring to road density and the line to population density. As the figure indicates, the population density for all GMS countries is well above road density (the exception being the Lao PDR). While the US and Viet Nam have very similar road density figures (49 kilometers per square kilometer of land for Vietnam and 68 for the US), their population densities per square kilometer are very different (278 for Viet Nam and 33 for the US). If one assumes that the developed regions shown have a roughly appropriate level of road networks, the substantial differences between the level of service in the GMS countries and the US, Japan, and the Euro Area provide some indication of the great need to expand transport networks within the GMS.

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    The views expressed in this paper are the views of the authors and do not necessarily reflect the views or policies of the Asian Development Bank Institute (ADBI), the Asian Development Bank (ADB), its Board of Directors, or the governments they represent. ADBI does not guarantee the accuracy of the data included in this paper and accepts no responsibility for any consequences of their use. Terminology used may not necessarily be consistent with ADB official terms.

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