China Transactional Trade and Investment Data (CTTID)

The goal of my China Transactional Trade and Investment Data (CTTID) project is to compile a variety of micro-data from different sources in order to observe the trade, investment and production “links” in Chinese supply chains which bridge the intersection of China’s domestic economy and the international economy. Using theories of complexity, these data offer new insights into emergent structures in markets and technology. CTTID consists of several data sources:

1) a searchable database of every import and export transaction conducted by a Chinese firm (several hundred million trade transactions);

2) Chinese firm-level data drawn from national enterprise surveys (over 2 million records);

3) US Customs transactional trade data, broadly similar to the Chinese transactional trade database;

4) 4-digit Chinese industry data.

5) Digital mapping linked with Chinese population and industrial census data.

Thus far, I have primarily examined these transactional and firm-level data through the lens of particular broad industry sectors (e.g. textile-garments, electronics, automobiles, etc.), and their interlinked intra-industry sub-sectors, such as upstream sectors (various textiles, electronic components, auto parts, etc.) and downstream sectors (garments, electronics and auto assembly, etc.).
Intra-industry sectors can be narrowed down to the 4-digit level of China’s industrial classification system, (e.g. semiconductors or cotton printing/dyeing).

By contrast, the transactional trade data are much more refined, with sub-classifications to the 8-digit trade level, based on the Harmonized Trade System classification. One challenge is to create valid concordances between these different data sources.

By breaking industries up along their chain of production, it becomes possible to examine the organization of the linkages that connect global and Chinese industries, including East Asian regional and trans-regional (e.g. US-East Asia) production, investment and trade networks.

I am also using these data to explore the contributions of qualitative research methods, and concept formation and measurement, to big data analysis.

Please contact me if you would like more information about my CTTID Project (