The Critical Needs to Address Gaps in Trade Data for Developing Economies
Mohamad Abou Hamia, Chief Economist and Researcher. August 2024
Millions around the globe have been suffering from chronically and persistently high rates of unemployment and poverty for decades. The task team on the post-2015 UN development agenda attributes these high rates to the inability of developing countries to sustain their economic growth. The neoclassical growth theory specifies two kinds of growth with different long run sustainability implications in the long run. The extensive growth is an increase in the production of goods and services due to increases in labor, capital, and land.
On the contrary, intensive growth is an increase in the production of goods and services due to increases in productivity or the total factor productivity (TFP). The TFP represents the stock of knowledge utilized by labor and capital to produce goods and services in the most efficient way. Economic growth cannot be sustained indefinitely by increasing labor, capital, or land due to the law of diminishing returns. Nevertheless, an increase in TFP indefinitely induces sustained economic growth in the long run due to the law of increasing returns.
The knowledge infrastructure in developing countries is alarmingly fragile, often crumbling under the weight of inadequate resources and systemic neglect. As an alternative to address the severe knowledge deficit, emerging markets have systematically transferred knowledge and technology from abroad, adapting these resources to local needs before developing domestic knowledge capabilities. International trade—both imports and exports—serves as one of the most critical channels for this knowledge transfer, enabling developing countries to access cutting-edge technologies and innovations that can be integrated and scaled domestically.
Imports play a crucial role in transferring international knowledge and technology to developing countries. The goods imported are not just products but carriers of embedded expertise, innovation, and advanced processes. By importing sophisticated machinery, electronics, or even consumer goods, developing countries gain access to the underlying know-how and technological advancements. Local firms and researchers can study, reverse-engineer, and adapt these imported products to enhance domestic capabilities. This process of decoding embedded knowledge accelerates industrial learning, supports local innovation, and drives broader economic development.
Exports are essential for bridging the knowledge gap in developing countries, as they provide invaluable learning experiences and exposure to global markets. Engaging in international trade allows businesses to encounter diverse standards, innovative practices, and competitive environments, driving them to integrate advanced technologies and refine their processes. This exposure not only boosts operational efficiency but also facilitates the transfer of global expertise, enabling firms to adopt best practices from around the world. By competing in international markets, exporters gain insights into new market demands and cutting-edge technologies, which enrich their knowledge base and foster continuous improvement.
To activate the international trade channel in transferring international knowledge, developing countries need to develop their external sectors. This requires international trade data to design, implement, and monitor long run strategies and policies. The widely measured and used international trade data are the imports and exports. These indicators are crucial indicators in international trade, but they have significant shortcomings. First, they are limited in scope, primarily focusing on goods while overlooking services, digital trade, and intangible assets like intellectual property.
Valuation issues, such as discrepancies between FOB and CIF prices, exchange rate fluctuations, and the impact of tariffs, can distort the economic value of these figures. Additionally, data collection lags, inaccuracies in classification, and differences in reporting practices across countries lead to inconsistencies. Moreover, traditional trade data fail to capture the complexity of global value chains, where intermediate goods cross multiple borders before final assembly, and they often exclude informal or unreported cross-border trade, particularly in developing regions.
Reliability issues also differ between import and export data. Import data are generally more reliable since countries rigorously monitor incoming goods for tariff collection and regulatory purposes. In contrast, export data tend to be less accurate, as there are fewer incentives for exporters to report comprehensively, and some countries lack the resources to track exports as thoroughly. Informal trade, smuggling, and underreporting are more common with exports, leading to gaps in the data. Consequently, analysts often rely more on import data, considering them a more trustworthy indicator, especially when cross-checking against export records from partner countries.
normalized trade balance, and export/import coverage indices.. major export partners, major import partners, trade intensity, and trade entropy indices. Regional Hirschman index, sectoral Hirschman index, competitiveness index, major export categories, major import categories, export diversification, revealed comparative advantage, trade complementarity, export similarity, and trade overlap indices. average applied/bound tariffs, weighted average tariffs, and dispersion of tariffs.
While imports and exports are commonly highlighted in international trade analysis, a range of lesser-known yet critical trade indicators can provide deeper insights for developing countries seeking to enhance their external sectors and integrate into global markets. These include normalized trade balance, export/import coverage indices, major export and import partners, trade intensity index, trade entropy index, regional Hirschman index, sectoral Hirschman index, competitiveness index, major export and import categories, export diversification index, revealed comparative advantage, trade complementarity index, export similarity index, trade overlap index, average applied/bound tariffs, weighted average tariffs, and dispersion of tariffs.
These indicators offer critical insights into the complexities of trade relationships and dynamics that go beyond basic import and export metrics. For instance, the normalized trade balance and export/import coverage indices provide a more refined view of trade balance sustainability by factoring in a country’s economic scale and trade volume. Understanding major export and import partners helps in identifying strategic relationships and opportunities for trade diversification, while the trade intensity and trade entropy indices measure the concentration or spread of trade across multiple markets, indicating potential vulnerabilities or strengths in external engagement.
Additionally, the Hirschman indices—both regional and sectoral—measure the concentration of trade across markets and industries, revealing a country’s exposure to specific risks or dependencies. The competitiveness index and revealed comparative advantage highlight areas where a country may have competitive strengths, guiding policy strategies that focus on boosting those sectors. On the other hand, the export diversification index and trade complementarity index help in assessing how diverse and compatible a country’s export basket is with global demand, which is crucial for long-term trade sustainability.
Moreover, tariff-related indicators like average applied/bound tariffs, weighted average tariffs, and tariff dispersion provide a nuanced understanding of market access conditions and the barriers facing both imports and exports. They allow policymakers to evaluate the effectiveness of trade agreements and identify sectors that may benefit from lower trade costs.
Incorporating these comprehensive trade indicators into policy frameworks enables developing countries to better design, implement, and monitor strategies for external sector development and global market integration. By using these advanced tools, policymakers can address gaps often overlooked by traditional trade data, enhancing their ability to create effective, data-driven policies that foster economic growth and resilience in an increasingly interconnected global economy.
In conclusion, our global trade hub is committed to bridging gaps and addressing limitations in current trade data. We strive to offer a more comprehensive view of international trade dynamics by systematically measuring and publishing a range of critical, yet often overlooked, trade indicators. Our commitment goes beyond mere data provision; we aim to empower policymakers with actionable intelligence to design more effective trade policies, foster sustainable economic growth, and ultimately alleviate poverty. Through rigorous measurement, publication, and advocacy, we seek to elevate the importance of these crucial indicators, ensuring they play a central role in shaping the future of international trade and development.