Results and Discussion

In this section, we present results of the simulation described above, followed by detailed analysis of the poverty implications.

5.1 Impacts of Transport Improvements on the GMS

The results for this scenario are reported in Table 9 [ PDF 23KB | 1 page ]. The table shows projected changes for each GMS economy at the aggregate level, including real output, exports, and economic welfare. These results suggest that changes in real GDP are highest for those countries with relatively large transport costs—namely Cambodia and the Lao PDR. The projected changes in real GDP for the region total over US$5,500 million (over US$4,300 million excluding gains accruing to the PRC). All of the GMS economies experience increases in GDP of between 1.1% and 8.3%, with the highest percentage increase in Cambodia, followed by Lao PDR, Myanmar, Viet Nam, and Thailand. Since only a relatively small part of the PRC is included in the GMS, the gains for PRC, in percentage terms, are relatively small. As shown in the third row of Table 9, the exclusion of the impact of improved infrastructure and trade facilitation with the PRC affects the GMS economies to varying extents. For Viet Nam and Thailand, the impact of improved transportation for trade with the PRC appears to be an important driver of the GDP results; Viet Nam's GDP gains are significantly lower in the absence of transportation and trade facilitation cost reductions with the PRC and Thailand's gains are eroded by over 36%. Other GMS economies appear much less reliant on gains from improved transportation for trade with the PRC. For Myanmar, the impact on GDP would be a reduction of less than 13%, about 7% for Cambodia, and less than 3% for the Lao PDR.

For all GMS economies with improved infrastructure, the change in economic welfare, as measured using equivalent variation in income, is positive. The total change in welfare for the region is US$7,915 million, however, this would be reduced if there were no reduction of costs between the PRC and other GMS countries (see row 7 in Table 9). For all GMS economies, allocative efficiency improves with better transportation facilitating the movement of resources into more productive activities. This impact is particularly strong for Thailand, contributing almost 17% of the increase in welfare. Terms of trade improvements are experienced by all GMS economies, again leading to increased welfare. This impact is primarily due to an increase in the regional export prices, while regions outside the GMS tend to experience a decline in their regional export prices. This relative change, however, does not dampen the export performance of the region, with the exception of the Lao PDR, which experiences a small decline in total exports. However, as will be discussed below, the Lao PDR's intra-regional export growth is over 80%, implying large potential gains as the GMS market grows.

The direct contribution to economic welfare of improved land transportation productivity is shown in Table 9 to be small but significant, with the exception of Cambodia. The final row of Table 9 reports the contribution from improved trade facilitation and this contributes the bulk of the welfare gains in the region. These gains are made by effectively lowering import prices through reductions associated with improvements in the institutional and regulatory “software” accompanying the transportation “hardware.” This result illustrates the great potential impact of measures that facilitate the efficient movement of goods across borders once the physical infrastructure is in place.

While Table 9 indicates that total exports are expected to increase for GMS countries (except for the Lao PDR), the impact on intra-GMS exports is perhaps of even greater interest. Table 10 [ PDF 19.8KB | 1 page ] presents details of changes in the value of intra-regional export flows. All of the economies increase exports within the region between almost US$150 million and almost US$10,000 million. For all of the countries, with the exception of Cambodia, the largest increases in bilateral exports are to Thailand. This underscores the importance of lower land transportation and trade facilitation costs with Thailand for most of the GMS countries. In the case of Cambodia, it is exports to Viet Nam that are expected to increase by the most, at over US$272 million. For Thailand, increases in exports are spread between all GMS countries, with the largest dollar increases in exports to Viet Nam and the PRC.

5.2 Impacts on Poverty

Turning now to the poverty impacts of the scenario modeled, we begin with the poverty drivers reported in Table 11 [ PDF 21.9KB | 1 page ]. These real earnings changes suggest that, in nearly all cases, factor earnings are rising relative to the cost of living at the poverty line. While the total nominal factor earnings for both groups of poor (US$1 per day and US$2 per day) are the same, their cost of living differs, so the entries in the top section of Table 11 (US$1 per day) differ from those in the bottom section (US$2 per day) by a common factor (the difference in cost of living at the different poverty lines). From Table 11, we see that the largest earnings increases are for the non-agricultural factors—particularly skilled labor. This may be driven by the increase in output in the electronics and other manufacturing sectors experienced by these economies. Land generally experiences a most modest rise in real earnings, and real land rents actually decline in the case of Thailand.

Applying the stratum-specific poverty elasticities to the real earnings changes in Table 11 gives the percentage changes in poverty headcount by stratum in Table 12 [ PDF 21.4KB | 1 page ]. The changes are relatively even across many strata within each country. However, the small change in poverty headcount in households that depend on payment transfers in Cambodia and the Lao PDR is notable. This follows from relatively low poverty elasticities, suggesting a low density of the transfer-dependent households around the poverty line in those countries. Also notable is the extremely large reduction in poverty for the wage labor households in Viet Nam, where the poverty elasticity is very large.

Table 13 [ PDF 23.2KB | 1 page ] converts these percentage changes into number of individuals. Here, we see that for the GMS-4 total (Cambodia, Lao PDR, Thailand, and Viet Nam combined), more than 400,000 people are moved out of extreme poverty, with another 1.75 million being lifted above the US$2 per day poverty line. The largest share (about half) of the extreme poverty alleviation is in Cambodia. This reflects Cambodia's large share in US$1 per day poverty in the region. On the other hand, Viet Nam dominates the US$2 per day poverty reduction in the region, as it dominates the poverty headcount at this higher level of income. At the stratum level, across the GMS-4, the bulk of the poverty reduction comes in the rural areas, with rural diversified households accounting for around one half of the poverty reduction at both poverty levels. This provides strong evidence that road improvements and improved connectivity benefit the rural poor in the region.

5.3 Mitigating Factors

We should emphasize that our results report the anticipated gains, given the set of assumptions made. If the necessary policy and institutional environment that will allow GMS economies to adapt and exploit new opportunities is absent, these gains are far from assured.

The gains from improvements in transport and trade facilitation presented above must also be tempered by the potential negative impacts of enhanced transport networks in the region. For example, as transit countries, the Lao PDR and Cambodia, having fewer resources and lower economic competitiveness, may suffer from worsening traffic safety. Traffic accidents are a concern across the developing world. An ADB (2005b) study provided estimates of annual economic loss from road accidents for GMS countries to be over US$4.7 billion or over 2% of annual GDP. This value is substantiated by EU estimates that road accidents cost approximately 1% to 3% of GDP in India (ERTICO 2008). Lost time, damaged cargo and vehicles, lack of insurance, injuries, and even death all add to the high costs of traffic accidents. There are also concerns about deterioration of the natural environment as a result of growing flows of transit cargo and there is a concern among residents that only foreign multinational companies will reap the benefits of cross-border trade expansion (JICA 2007).

Adverse human health impacts may also accompany improved infrastructure. For example, the spread of HIV and AIDS has been known to closely follow the progress of economic integration in the GMS. For instance, the number of HIV-positive persons and AIDS patients was reported to rise sharply in Savannakhet while the Second Mekong Bridge was under construction (JICA 2007).

Furthermore, concern exists that improved infrastructure may accentuate problems of human trafficking and illegal trade in narcotics. These issues are deeply rooted in the problem of poverty. According to a report on villages in the Lao PDR, those who wanted to work outside their own countries were often victimized (ADB 2006), with a third given false information about their earnings or forced to work in a job different from the initial promise (often prostitution in the case of women).

This brief discussion of possible adverse impacts is far from complete, and further case studies that explore these issues and more (including environmental damage) are needed. However, potential negative impacts need to be viewed in the context of further positive effects that may occur within the region. The increased exposure to new businesses that comes with greater connectivity increases the opportunities for improved technological adaptation. Indeed, it has been shown that improving connectivity has been shown to raise productivity and land values for poor farmers (Iimi and Smith 2007). Evidence has shown that improved transport has increased school attendance (Levy 2004), increased maternal and natal care (Ishimori 2003), improved working conditions and wage levels (Singh and Mitra 2006), and increased levels of FDI (Luanglatbandith 2007). None of these dynamic, positive effects have been explicitly considered in this study. Thus, the net outcome of the dynamic interaction between the negative and the positive potential impacts is very difficult to assess.

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