Assessing the Benefits to Developing Countries of Liberalisation in Services Trade
Notice bibliographique
Résumé
This paper discusses the potential impacts of services trade liberalisation on developing countries and reviews existing quantitative studies. Its purpose is to distill themes from current literature rather than to advocate specific policy changes. The picture emerging is one of valiant attempts to quantify in the presence of formidable analytical and data problems yielding only a clouded image of likely impacts on trade, consumption, production and welfare emerging to the point that the policy implications of results are not always clear. A central intuition would seem to be that with genuine two‐sided (OECD/non‐OECD) liberalisation in services that are seemingly considerably labour‐intensive in delivery, the potential should be there for significant developing country gains from global liberalisation allowing full cross‐border delivery. However, this picture is neither fully endorsed by available studies, neither is it explicitly contradicted. This seems to be the case for a number of reasons. One difficulty with the studies is that the conceptual underpinnings of what determines trade in services and how this trade differs analytically from that of trade in goods (if at all) is an issue prior to assessments of impacts of liberalisation of trade in services on developing countries being discussed. Key issues here are the treatment of mobility for service providers (both firms and workers), and the differing analytical structures needed to analyse individual service items (banking, insurance, telecoms, etc.). Some recent analytical work suggests that liber‐alisation in some service items, such as banking, need not always yield gains, and this contrasts with quantitative studies where analytical structures mirror conventional trade in goods treatments. The discussion and measurement of barriers to service trade in both developed and developing countries is also problematic. One is talking of domestic regulation, entry barriers, portability of providers, competition policy regimes more so than only barriers at national borders, as with tariffs. Both representing and quantifying such barriers raise major difficulties, and these are also spelled out in the paper. Which barriers actually restrict trade, and which do not because they are redundant is one issue, for instance. It is also often misleading to represent barriers in simple ad valorem equivalent form. As a result, numerical modelling work on the effects of service trade barriers which is based on ad valorem equivalent modelling is often not fully convincing. In addition, individual country results vary considerably across studies in ways that it is frequently hard for outsiders to understand. Studies do, however, point towards a tentative conclusion that effects are small and positive for developed and most developing countries if FDI flow changes accompanying service trade liberalisation are excluded from the analysis, but much larger and more variable across countries if they are present. This could be taken to suggest that mode 3 GATS liberalisation (roughly captured in some studies) might be important for developing countries; but mode 4 GATS liberalisation could be even more important given large barriers to labour flows across countries. Thus, if service trade liberalisation is thought of primarily as a surrogate for improved functioning of global factor markets in which more capital flows to developing countries and more labour flows from them to developed countries, then developing countries could benefit in a major way from genuine two‐sided (OECD/non‐OECD) liberalisation. Developing countries fear, however, that in global negotiations on services liberalisation where there is an asymmetry of power that largely one‐sided liberalisation may be the outcome, and their gains will be correspondingly limited. The paper concludes by evaluating econometric studies on linkage between services liberalisation and country growth rules, and briefly discusses some key sectoral issues in health services and transportation.
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Prédiction machine sur la base complète
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,004 | 0,008 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,000 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
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Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».