The Greater Mekong Subregion Economic Cooperation Program: Regional Cooperation and Integration in the GMS for Global Success

Outline
Team
  • Expected start date:
    2019•07•01
    Expected end date:
    2020•12•31
    Institute:
    UNU-MERIT
    Project Status:
    Ongoing
    Project Type:
    Research
    Project Manager :
    Neil Foster-mcgregor

    Introduction

    Since its inception in 1992 the GMS program has been successful in fostering regional cooperation. The program has implemented numerous projects to encourage and improve regional integration and regional infrastructure (examples including sub-regional road, rail and airport improvements, hydropower projects, tourism infrastructure development and communicable disease control), with the ultimate aim of enhancing economic growth and reducing poverty. As we look forward to the fourth decade of the GMS project, it is time to take stock of its achievements, identify areas for improvement and future challenges, and to set out an agenda to help this region achieve the goals of sustained economic growth and poverty reduction.

    What follows sets out a series of areas for research that seek to achieve the goals set out above and that seek to contribute to outlining the foundations for the GMS Strategy 2030. The underlying and implicit questions that we seek to provide answers to are: (i) what would this region look like in 20-25 years?; and (ii) what role can regional cooperation play to achieve the GMS goals ? These questions are broad in nature, with the more specific theme that we intend to contribute in this part of the project being: “Regional Cooperation and Integration in the GMS for Global Success”. This theme follows from the idea that while the form of regional integration that GMS promotes can be an important source of growth and development, success will require a broader strategy that enables these countries to effectively compete and integrate into the global market. A successful strategy will involve access to rich world markets, access to advanced technologies, and the exploitation of economies of scale and scope, amongst other things. The future direction of the GMS project can be an important factor in helping to achieve this access.

    The analysis that we describe below will: (i) provide a mapping of the current situation in the region in terms of both regional and global integration – the successes and the challenges; (ii) provide a set of objectives that the region will need to achieve in order to succeed in moving up the global income distribution; (iii) provide potential pathways for upgrading and diversifying the economies of the GMS regions; and (iv) provide a mapping of the use of Industry 4.0 technologies in the region. The analysis focusses heavily on the use of trade data and takes both a regional and global dimension. The approach thus complements other components of the broader project, and in particular those that focus on the structure and dynamics of regional integration using alternative data, such as patents, occupations, and industry level data (see Research Proposal 2). The analysis in this part of the project will therefore feed into and receive inputs from other components of the project. For example, the analysis in this part of the report will provide insights into potential diversification and upgrading strategies for the GMS region. To further understand the impact of different paths at the regional, national and sub-national levels will, however, require the types of analysis that are conducted elsewhere in the project. Combined, these approaches provide policy inputs for national strategies for diversification and upgrading, as well as an understanding of how regional and sub-national policies could be developed to maximize the extent of gains from such upgrading paths and to ensure that the gains are broadly shared.

    Research Plan

    Based upon the above discussion, the research plan is as follows:

    Task 1 – A Stocktake of the Current Situation in the GMS Region

    In this initial – albeit extensive – exercise we will describe and map the current situation in the GMS region with respect to: (i) their current levels of regional integration; and (ii) their current levels of integration into the world economy. In particular, we will proceed by undertaking the following sub-tasks

    Sub-Task 1.1: Existing Integration into the Global Economy

    In this first sub-task, we will use detailed bilateral trade data to map the involvement of the GMS countries in global trade. In a comparative perspective, we will consider how integrated into the global economy the GMS countries are, by looking at their exports and imports to and from different regions of the world. A comparison will be made between the GMS countries, but also with other comparator countries from the broader Asian region. An important question that we want to address in this initial descriptive analysis is the extent to which these countries rely on regional (i.e., intra-GMS) trade, and whether some or all of the countries have been able to integrate more broadly into the Asian and world markets.

    Sub-Task 1.2: Existing Specialisation Patterns of GMS Countries

    In this sub-task, we will again make use of detailed trade data to identify the sets of products in which these countries (and the region as a whole) are able to compete successfully. In particular, we will make use of the concept of Revealed Comparative Advantage (RCA) to identify these sets of products and to consider how the specialisation patterns of the GMS countries have evolved over time. Extending this analysis, we will combine the information on specialization patterns with data on product complexity to examine the relative complexity of these countries’ export baskets, both with respect to each other, but also with respect to other third countries. [1],[2]

    In this sub-task we will further consider the regional dimension of production capabilities, assessing the extent to which specialisation patterns of GMS countries are dependent upon the specialisation patterns of their neighbours.[3] Given that knowledge tends to diffuse more easily across relatively short distances, there is an expectation that countries that are geographically close may share similar levels of capabilities and that as a result they may end up producing similar goods. Such an outcome presents opportunities and threats. On the one hand, a lack of capabilities in neighbours can limit opportunities for upgrading and diversification, but, on the other hand, improvements in the capabilities of neighbours can present opportunities for upgrading and diversification. Such arguments may also support the need for coordinated regional policies to develop capabilities and comparative advantage.

    Sub-Task 1.3: Positioning within Global Value Chains

    Participation in Global Value Chains (GVCs) has been a prerequisite for the recent development experience of China, as well as other countries including, for example, Cambodia and Thailand It is generally thought that to succeed in GVCs requires countries to upgrade within GVCs.[4] As such, the aim of this sub-task will be to both describe quantitatively the level of participation of GMS countries in GVCs, as well as to identify the positioning of these countries within GVCs (e.g. to identify whether they contribute in low or high value-added segments of GVCs). The standard approach here will be to use global input-output tables, and to the extent that they are available this is the approach that we will take. A drawback of the input-output approach is the relatively aggregated nature of the data. The approach remains an important means of identifying the positioning of countries in the global economy however. In the case of a lack of data availability, alternative approaches will be considered including the possibility of particular case studies (e.g. the participation in GVCs of particular firms or sectors in the GMS countries), as well as the use of detailed trade data or existing firm-level datasets.

    Sub-Task 1.4: Trade Potential of GMS Countries

    In this sub-task, we will build upon the results of sub-task 1 and examine whether the GMS countries are reaching their potential in terms of both intra-regional and global trade. Bilateral trade flows are usually considered to depend upon trade costs – both policy induced (e.g., tariffs) and natural (e.g., geographic distance) and the size of the market in which trade takes place. Under these assumptions it is possible to estimate the expected flows of trade between countries using the familiar gravity model of trade, with these estimates reflecting the trade potential between two countries. Differences between actual trade flows and those estimated from the gravity model can then be used to estimate whether countries are meeting or exceeding their trade potential. Of particular interest to us is whether the set of GMS countries are meeting their trade potential with each other, but also whether they are meeting their potential with other regions of the world (e.g., the richer regions of the world). A finding that countries are not reaching their trade potential has policy implications, and may be an important explanation for differences in the complexity of production that will be identified in sub-task 1.2.[5] While the gravity model is commonly used to model trade at the aggregate level, it may be possible to augment the model to allow for an estimation of trade potential at the sectoral level. In addition to identifying whether these countries reach their trade potential (in certain sectors), the analysis will also enable one to consider the set of countries with which these countries are achieving their potential and those countries where possibilities to further exploit opportunities are available. In other words, the approach can provide information on both the sectoral and geographical trade potential of this set of countries, leading to policy relevant implications for both regional and global trade integration. A potential extension of this approach would be to try and identify the factors that limit countries reaching their trade potential, with trade policy (i.e. preferential trade agreements) being one obvious candidate.

    Task 2: Identifying the Benefits and Opportunities for Regional Integration in the GMS

    The outcome of the above analysis will provide a comprehensive overview of the involvement of the GMS countries in the global economy. It should also provide insights into questions related to whether this set of countries has a complementary set of capabilities that could be further exploited through increased regional cooperation and integration. Under the assumption that future success is dependent upon engaging in the global economy, the second task will take a forward-looking perspective on the development of the countries and regions in the GMS. This work will start from the basic idea that structural change is a major force of development, and that structural change follows a path-dependent pattern. In this context, path dependency means that what a country’s productive system can produce and export in the future depends on what it produces and exports today. In other words, changes in productive capabilities are gradual and context-dependent and will therefore likely differ between countries in the GMS.

    This will be operationalised using data on exports and imports, and the comparative advantages that can be derived from these data. The work will start by using this global trade database to determine how specific products relate to productive capabilities. This will yield a complexity score for each product in the database (there are approximately 5,000 products), with more complex products relating to more advanced production capabilities.

    In the next step, the current export structure of the countries in the GMS will be assessed in terms of “complexity” (i.e., how diverse and unique it is). Whether this can be done for the Chinese regions will depend on whether export data is available for these regions. This analysis will likely yield fairly large differences between the countries in the GMS.

    The path-dependent nature of specialization patterns and production capabilities will be measured using correlations between specialisation patterns of countries. This will yield insights into how products are compared in broader specialisation patterns at the country level, for example in the form of statements like “if a country is specialized in product X, it also tends to be specialized in product Y”. We will include exports in these calculations as a measure of productive capabilities, and imports, especially imports of intermediate products, as a measure of involvement in global value chains (GVCs).[6]

    Using this correlation structure, we will construct likely “upgrade paths” for each country in the GMS. The “upgrade” nature of these paths is defined by average product complexity, i.e., we will search for the paths that increase the average complexity of the export portfolio of a country. In practical terms, this means that we will look for products that a country is likely to be able to diversify into, given its current export structure. We will do this in a dynamic multi-stage way, i.e., we will find the products a country can diversify into from the current export structure, then products that it can diversify into in a second stage, third stage, etc. This will then yield an upgrade path from wherever the country stands now, up to a complexity level comparable with the most advanced economies in today’s global economy. In addition to looking at upgrade paths that increase complexity levels in a general sense, we will also look for specific paths that lead to the GMS region becoming competitive in Industry 4.0 products.

    We will present these upgrade paths as possible scenarios (of which there will be more than one for each country) and discuss the similarities or differences between countries in the GMS, which may then guide discussions about the future form that regional integration should take.

    The approach adopted in this part of the analysis is in many ways similar to the approach adopted in other parts of the project (Research Proposal 2) but focuses on the national level using international trade data, rather than at the sub-national level using patent, occupation and industry data. These two strands of analysis are quite complementary, however. While the approach adopted in this part of the project will allow for an understanding of the export structure of countries in the GMS region and present potential upgrading paths, it will not address the question of which sub-national regions will likely benefit from such an upgrading path, or address the question of how further regional integration and improved connectivity between sub-national regions may help drive a particular upgrading path. Here the approach in Research Proposal 2 will provide crucial additional evidence on understanding the intra-regional dynamics that will allow the GMS countries to successfully upgrade and integrate both locally and globally.

     

    Task 3: Industry 4.0 Readiness in the GMS

    A potentially important factor in future development patterns, and in the role of GVCs – and trade more generally – in development is the introduction of new technologies (in particular, AI, robots, machine learning, nano-technology, etc.). These may provide important opportunities for countries to integrate into GVCs, by enabling countries and firms to leapfrog to a new stage of manufacturing development, but also risk destroying GVCs as a development path by encouraging reshoring and removing developing countries main comparative advantage (i.e. low-skilled and low-wage labour). Given these expected developments, it is important to understand the extent to which the GMS region is currently using these technologies, or more generally, the extent to which the region is active in becoming Industry 4.0 ready (both at the national and firm level).

    One approach to address this issue is to consider disaggregated trade data that allows for an overview of the development, production and use of these technologies. Highly disaggregated trade data can allow for the identification of trade (i.e., imports and exports) in particular types of Industry 4.0 technologies (e.g., robots), although in many cases such a distinction between Industry 4.0 and Industry 3.0 and earlier technologies may not be clearly demarcated. Similarly, patent data allows for a mapping of the development of Industry 4.0 technologies, as well as the use of these technologies (i.e. captured by the locations in which patents for these types of technologies are taken out). In this task, we will combine information on disaggregated trade data and detailed patent information to provide a mapping of the development, production and use of Industry 4.0 technologies, and in particular to identify the positioning of the GMS countries in these technologies. In the case of trade data, it is also of interest to look to identify the specialisation patterns or capabilities that are associated with increased usage (i.e. imports) of Industry 4.0 technologies. The analysis in Task 2 can be adopted to address this question. Once again, the analysis conducted here will be at the national rather than sub-national level.

    Task 4: What does the future landscape of the GMS look like?

    Policy Recommendations

    An important component of this Proposal will be to present general policy recommendations, both for the individual countries and for the GMS region as a whole. On a general level, the analysis described above will provide an overview of where the region has been successful and less successful in integrating – both locally and globally – which will provide inputs into the discussion of the policies required for further and more appropriate integration. Recommendations here may refer to global integration (e.g., within GVCs), regional integration, but also to sectoral interventions. The latter part of the analysis will further identify potential upgrading and diversification paths for development, which will generate important policy insights related to the targeting of policy interventions for the purposes of upgrading. An important aspect of this task will be to propose recommendations that are applicable to the GMS as a whole and to the interaction and spillover effects of different policies that may create a need for coordinated action across the region. To develop this coherent policy analysis will require coordination and a linking of the different parts of the overall project.

    [1] See for example, Hidalgo, C. and R. Hausmann, 2009. The building blocks of economic complexity. Proceedings of. the National Academy of Sciences of the United States of America, 106, 10570-10575.

    [2] Note, that this analysis could be combined with the results from sub-task 1 to consider regional specialisation patterns.

    [3] We will adopt the approach of Bahar et al. (2014) in this part of the analysis. Bahar, D., Hausmann, R. and C. Hidalgo, 2014. Neighbors and the evolution of the comparative advantage of nations: Evidence of international knowledge diffusion. Journal of International Economics, 92, 111-123.

    [4] Upgrading can mean many things, from moving from low to high value-added production stages within specific GVCs to moving activities to new – more complex – value chains.

    [5] An example of such an approach can be found here: https://www.tandfonline.com/doi/abs/10.1080/12265080600888090?src=recsys…

    [6] This approach bears similarities to the approach of identifying ‘relatedness’ in the project component conducted in Research Proposal 2.