usually large, directly participate in international trade (e.g., Bernard, et al., 2007).<sup>7</sup> The standard argument is that exporting is usually associated with high fixed costs and only large (productive) firms can make sufficiently high export revenue to amortize them. However, many non-exporters may engage in international trade indirectly, through wholesalers and other intermediaries, as well as by providing intermediate inputs and services to exporters of all sizes, particularly large multinationals. While the first channel has received a lot of attention in the recent literature (e.g., Bernard et al., 2010 and Ahn et al., 2012), the second channel has not received the deserved attention, partly due to the lack of data on inter-firm transactions within a country.<sup>8</sup> Our paper provides a methodology that combine firm-level and industry-level data to quantify the volume of indirect exports, and through which channel “non-exporters” export indirectly.

Finally, our paper relates to the large literature on the role of SOEs in shaping the Chinese economy (e.g., Brandt et al, 2012; Zhu, 2012). As discussed before, the conventional view is that the Chinese government has been reducing the share of SOEs in the economy. Privatization of SOEs is often attributed to China’s sharp productivity growth and industrial transformation. Little has been done about the effects of the sequential privatization observed in China. Notable exceptions include the recent theoretical work by Song et al. (2011) and Wang et al. (2012), who both highlight and rationalize the high profitability of SOEs.<sup>9</sup> Our papers focus on quantifying the export patterns of SOEs themselves and how they affect other types of exporters. Our estimation can be used to examine some of the specific predictions in these theoretical models.

The rest of this paper is organized as follows. Section 2 develops our conceptual model and estimation methods. Section 3 explains our data. Section 4 analyzes our estimation results. Section 5 concludes, with discussions on potential policy implications and future research.

# **2. Conceptual Model and Estimation Method**

This section first develops a model to split a conventional IO table into sub-accounts that record domestic transactions between different firm types across sectors. It then describes how we use constrained optimization techniques along with various adding-up conditions to estimate those transactions. Readers

> 7 As Bernard et al. (2007) described “engaging in international trade is an exceedingly rare activity: of the 5.5 million firms operating in the United States in 2000, just 4 percent were exporters. Among these exporting firms, the top 10 percent accounted for 96 percent of total U.S. exports.”

> 8 A notable exception is the report by the USITC (2010), who also uses the constrained optimization methodology to estimate the contribution of small and medium enterprise (SMEs) to US exports. The report finds that SMEs’ total contribution to U.S. exports increased from less than 28% to 41% in 2007, when the value of intermediates supplied by SMEs to exporting firms is taken into account.

> 9 Song et al. (2011) further uses the unique feature of SOEs in China to explain several macro outcomes, such as huge saving and current account surplus.

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