Methods of Analysis

To test our two main hypotheses, we estimated a standard gravity model using the processing trade data described in the previous section. The dependent variable in the model is the natural log of processing exports from a PRC province i to a destination economy j in year t (lnEXijt). We included three independent distance variables in our analysis: the natural logs of export distance, import distance, and internal distance. We measured export distance (ExDistij) as the arc distance between the PRC port closest to province i and the destination economy j. To measure import distance (ImDistij), we needed to take into account that multiple inputs from various economies are used in the production of a specific export good. As a consequence, we measured import distance using the following formula:

where IMijt is province i's imports from economy j in period t; and ExDistij is the arc distance between the PRC port closest to province i and source economy j. Finally, we followed Feenstra, Hanson, and Lin (2004) by measuring internal distance (IDisti) as the distance between a province and its closest major PRC port, where distance is given by train time between the two destinations.

To investigate whether the PRC's processing exports to East Asian economies are more sensitive to export distance and less sensitive to import distance than its processing exports to Western countries, we introduced a dummy variable, Eastj, that equals 1 if the economy of destination is an East Asian one and 0 if the destination market is a non-Asian OECD country. We then introduced interaction terms between Eastj and our two distance variables lnExDistij and lnImDistit as independent variables in our model.

Finally, we added a number of standard control variables that may affect the relationship between distance and processing exports. Specifically, we used data from, respectively, the China Statistical Yearbook and from the World Bank's World Development Indicator database to include controls for GDP per capita (GDPpcit) and population size (Popit) for PRC provinces and destination markets. We also used data from the China Statistical Yearbook to add a control for PRC provincial wages (wageit).

In summary, we estimated the following equation:

where EXijt is the volume of exports from province i to economy j in period t; cGDPpcit and cPopit are the GDP per capita and population of province i in period t; GDPpcjt and POPjt are the GDP per capita and population of the target economy j in period t; Wageit is province i's wage in period t; ExDistij is export distance between province i and economy j; IDisti is internal distance; ImDistit is the weighted import distance for province i in period t; Eastj is a dummy variable that equals 1 if the destination economy is an East Asian one, and is 0 otherwise; λt is the time effect; and μijt is a white noise disturbance term.

Hypothesis 1 will be confirmed if lnExDistij and lnImDistit both have a negative effect on processing exports. Hypothesis 2 will be validated if (i) the coefficient on the interaction term between Eastj and lnExDistij is significantly negative and (ii) the coefficient on the interaction term between Eastj and lnImDistit is significantly positive.

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