Chinese Firms' Entry to Export Markets: The Role of Foreign Export Spillovers

There is evidence that most of the recent growth in Chinese exports is due to foreign firms. Several studies also argue that foreign firms, which are typically engaged in processing trade activities, drive the skill content upgrading of China's manufacturing exports (Amiti and Freund 2010; Xu and Lu 2009). Moreover, estimations of growth equations indicate that the income gains from export performance and export upgrading are confined to the improvements made by domestic firms. Jarreau and Poncet (2012) find that the positive association between GDP per capita growth and export sophistication at the province level is limited to ordinary export activities undertaken by domestic firms. These results, together with the results emphasized by Amiti and Freund (2010), suggest that the export activities of foreign firms in China do not matter for the economic growth of Chinese provinces once domestic exports have been controlled for. However, although there are no direct gains from the export upgrading of foreign firms in terms of GDP per capita, there may be room for foreign firms to indirectly affect domestic firms through export spillovers. There are two channels through which export spillovers can act. Foreign firms can provide specific information on export markets that can help domestic firms to reduce their fixed export costs (e.g., information about the tastes of foreign consumers or distribution networks abroad). Foreign export spillovers can also be linked to the mutualization of fixed or variable export costs (participation in international fares, marketing, transport costs). Thus, it is worth investigating whether foreign firms in China act as export catalysts that foster the creation of new export transactions by domestic firms.

Using panel data from Chinese customs that record provincial export flows for the period 1997–2007 by product, destination country, type of firm, and type of trade, this paper shows that the capacity of Chinese domestic firms to begin exporting new products to new markets responds positively to the export activity of neighboring foreign firms. These export spillovers are found to be very specific both in terms of activity and in terms of the geography of exports. Furthermore, the effect of these export spillovers exhibits a spatial decay consistent with the spillover interpretation and is primarily limited to ordinary trade activities. Endogeneity issues are carefully addressed by introducing relevant controls and fixed effects in the benchmark regression. The estimated impact is robust to more demanding specifications in terms of fixed effects, and it resists an instrumental variable approach that uses the presence of export promotion zones interacting with product-country demand shocks as an instrument for multinational firms' exports. From a quantitative point of view, the size of the effect is not negligible. The marginal impact of the product-country-specific foreign export spillovers is five times as large as a 10 percent increase in the demand for the product in the destination country.

Beyond a mere empirical quantification, the study of export spillovers is a relevant topic from both an academic and a policy viewpoint. Indeed, with the globalization of exchanges, export performance has become an increasingly important dimension of a country's economic success. However, not all firms export, and understanding both theoretically and empirically what determines entry into export markets is a prerequisite to the design of adequate policies aimed at stimulating exports. Moreover, for a country that is very open to FDI, such as China, analyzing the role of foreign firms in the development of domestic export capabilities is crucial.

Hence, our work contributes to several strands of the literature. This work first participates in the literature on the role of the local environment in firm-level export performance. Many theoretical and empirical papers show that exporting firms represent a small fraction of active firms. Fixed and variable export costs generate selection mechanisms in export markets (e.g., Melitz 2003; Bernard and Jensen 2004; Melitz and Ottaviano 2008; Mayer and Ottaviano 2008). These costs are partly explained by the necessity of finding a distributor in the destination country, adapting products to foreign consumers' tastes, or discovering new sources of demand. Domestic firms might benefit from the experience of multinationals in this respect; the possible spillover channels are information externalities, cost-sharing opportunities, and mutualized actions on export markets. Krautheim (2012) provides one of the few theoretical works on export spillovers, in which proximity to other exporters is assumed to reduce the fixed export cost due to the endogenous formation of informational networks between exporting firms. Most of the literature on this topic is empirical. In a pioneering work, Aitken et al. (1997) show that the export decisions of local firms in Mexico is positively influenced by their proximity to multinational exporters. This result has been confirmed by Kneller and Pisu (2007) for UK data and by Kemme et al. (2009) for India. In contrast, Barrios et al. (2003) do not find clear evidence for these export spillovers from foreign firms in Spain, whereas Ruane and Sutherland (2005) find that the export intensity of foreign-owned enterprises is negatively correlated with the export decision and export intensity of domestic firms in Irish manufacturing, suggesting that no (and even negative) export spillovers derive from third-country export-platform FDI. This prediction bodes ill for China, where foreign firms are primarily engaged in the processing trade (i.e., the assembly of imported inputs, which are then re-exported as a final product). In the context of China, three studies investigate export spillovers emanating from foreign firms (Ma 2006; Swenson 2008; Chen and Swenson forthcoming). These papers relate the probability of exporting (or the number of new export transactions at the city or province level) to the presence of multinational firms. They find evidence of positive foreign export spillovers at the two-digit industry level (approximately 100 SITC or HS sectors).

This paper goes further in developing an understanding of the mechanisms at play in foreign export spillovers in China by exploiting data at a finer level, both in terms of the geography of exports and in terms of activities. In particular, Krautheim (2012) argues in his theoretical paper that the relevant information might be destination specific. For example, technical regulations or specific consumer tastes vary across countries. Koenig (2009) finds evidence of export spillovers from French data only when the destination dimension is taken into account. Export spillovers might also occur at a fine product category level that is more detailed than the HS2 categories, which might be highly heterogeneous. For example, in the French case, Koenig et al. (2010) show that export spillovers are magnified when they are product and destination specific (products defined at the 4-digit level). By showing that foreign export spillovers in China are product-country specific and primarily limited to ordinary trade activities, this paper opens the “black box” of these spillovers. This research is also valuable for policy-makers who are interested in tailoring fine-tuned export promotion policies based on spillovers between domestic and foreign firms. The types of actions that public authorities should favor and the type of actors upon which they should rely to promote externalities might differ depending on whether the export spillovers are specific to the exported product or to the destination country, for example.

This paper also complements existing studies on the role of foreign firms in the evolution of Chinese exports. Beyond foreign firms' activities per se, this paper highlights the externalities that foreign firms can exert on domestic firms by stimulating the extensive margin of trade through the creation of new export transactions.

Finally, this paper contributes to the literature on the determinants of growth in China and, more generally, in countries that are very open to FDI. By showing that export externalities primarily apply to ordinary trade activities, this paper points to the limited role of export-platform activities for the promotion of Chinese firms' export performance. This result may indicate that Chinese domestic firms are less likely to internalize benefits from a foreign presence when multinationals' activities are limited to the mere assembly of previously imported inputs.

The rest of the paper is organized as follows. Section 2 describes the data, our empirical approach, and our measure of export spillovers. Section 3 presents and discusses our baseline results, and Section 4 concludes the paper.

I. Data and Indicators

Trade Data Sources

The data used in this study come from Chinese Customs and provide export flows aggregated by province, year, product, and destination country over the 1997-2007 period.¹ We reaggregate the original eight-digit-level data into HS4-level data (more than 1,200 product lines). An interesting feature of this dataset is that it allows us to identify whether the export flows emanate from domestic or foreign firms² and whether they correspond to processing trade or to ordinary trade.³ The processing trade includes all trade flows by firms operating in the assembly sector; that is, firms that import and process inputs in China and then re-export the final products abroad. Firms engaged in this type of activity might be less embedded in their local environment and might consequently generate fewer (and possibly benefit less from) externalities.

Explained Variable: Creation of New Export Linkages

The creation of a new export transaction is measured by a dummy that takes the value 1 if the domestic firms in province i begin exporting product k to country j at time t + 1 and 0 otherwise. A specific database is constructed that incorporates the set of alternatives faced by each province. For a given province, these alternatives are defined as the product-country pairs for which at least one export start is observed over the 1997–2007 period.

For these province-product-country triads, the dataset is originally a balanced panel from 1997 to 2007 covering 211 countries and 1213 HS4 products. The dataset includes 1,050,516 observations each year, resulting in a total of 11,551,716 (province/product/country/year) observations over the 1997-2007 period. Approximately 11 percent of the observations from the entire database correspond to domestic starts, that is, to provinces where domestic firms do not export product k to country j at time t but do export k to j at time t + 1.

These domestic starts are the trade flows to be explained. As in Koenig et al. (2010), ceasing and continuing export flows are not included in the study. Given the time span, for a given province-product-country triad, several starts might be observed. For example, the subsequent export statuses 00011001111 become .001..01… in our sample, with 1 denoting positive exports, 0 denoting no exports, and . denoting a missing value. By definition, all of the observations are missing for 1997, the first year in the sample, because the export statuses in 1996 are not observed. Continuing export flows (a 1 preceded by another 1) and ceasing export flows (a 0 preceded by a 1) are also coded as a dot because they are excluded from the analysis.

Because the estimations will include province-product-country fixed effects, taking into account a broader definition of the possible exported products or the destination countries would not change the final sample used for the estimations. The behavior of the province-product-country triads for which we observe positive export flows or null export flows every year of the period would be explained by the fixed effect.

Unreported results, available upon request, show that the conclusions are very much the same when the sample is restricted to durable starts, defined as export starts leading to positive export values for at least two consecutive years. This finding suggests that the foreign export spillovers captured by the entire sample are not driven by short-lived transactions.⁴

Empirical Approach

Using a conditional logit estimation, all regressions are estimated including fixed effects at the province-product-destination country level η_ikj. This allows for the consideration of all time-invariant characteristics that can explain the export activities for product k to country j of both domestic and foreign firms in province i. Indeed, inward FDI might be attracted to particular provinces due to the presence of local specific advantages for exporting a given product and/or to a given destination. In this case, the estimation would suffer from a reverse causality issue. In particular, the transport infrastructure and endowments of province i, the variables that explain the business relationships between province i and country j (distance, migrant networks) and the local comparative advantage of province i for product k are taken into account by η_ikj as long as they are fixed over time. The year fixed effects μ_t+1 are also added to control for aggregate shocks to the Chinese export activities. Given this estimation strategy, foreign export spillovers are identified based on the within (time) dimension of the data. Hence, the time-varying determinants of domestic and foreign firms' exports Z must also be considered.

The conditioning set Z is composed of three categories of variables. First, following the gravity literature, the demand-side determinants of new export linkages are controlled for by the destination country's import value, defined at the four-digit product level taken from the BACI world trade dataset⁵ and the GDP per capita of the importing country.⁶ Second, supply-side determinants are taken into account by introducing proxies for provincial and Chinese comparative advantages and export intensity. In the absence of firm-level data, these controls are crucial to account for the time-varying ability of different provinces to export different products to different countries. Hence, the log of the province total export sales, the province-product export sales, and the China-product export sales in year t are introduced. Because the regression also includes year fixed effects, which account for the evolution of total Chinese exports, controlling for these variables amounts to introducing the elements of a Balassa index of “revealed comparative advantage” at the province-product level. The total bilateral exports from province i to country j and the total Chinese bilateral exports to country j are also introduced to control for specific relationships between the province/China and the destination country. This step is important given the use of business and trade agreements by the Chinese authorities to manage their diplomacy. Finally, the province GDP per capita is used to take into account the supply-side determinants of exports such as workers' skills.⁷ Third, to ensure that the decision of domestic firms to start exporting does not capture the intrinsic dynamics of exports at the product level or at the country level, the lag values of Chinese and province i's exports at the product level and at the destination country level are included, as well as the lag of foreign demand, to control for specific dynamics on the demand side.

Finally, the other export activities undertaken by the domestic firms of province i in year t are controlled for. By construction, because only newly created linkages at the product-country level are considered, there is no export activity by the domestic firms of the province in the previous year for the considered product-country pair. However, the export activities in other products for the same country, in other countries for the same product, and in other products and other countries must be taken into account. Considering these controls ensures that the coefficient for foreign export spillovers will not proxy for spillovers between different domestic firms or for scope economies within the same firm.

Below, the empirical results obtained using this type of specification are shown to hold when controlling for potential remaining endogeneity, by including more demanding fixed effects or using instrumental variables.

Regarding export spillovers, two different proxies are proposed. First, the value of foreign exports is used. However, in only 4.2 percent of the final sample observations do we observe positive exports for the product-country specific spillover variables. Foreign export activities are then decomposed into the mere presence of foreign exporters for a given product-country pair, as measured by a dummy, and the value of their exports. By doing so, it becomes possible to assess whether foreign export spillovers are due to a switch in foreign export activities (from no export to positive exports) or to changes in the scale of exports realized by foreign firms. Disentangling what is due to the scale of foreign export activities from the more general impact of the presence of foreign exporters⁸ is important when the share of observations in which positive foreign export flows are observed is small.

Descriptive Statistics

Province-product-country triads for which at least one export start is observed over the period are used in the estimation. For these province-product-country triads, the observations originally constitute a balanced panel from 1997 to 2007, covering 211 countries and 1213 HS4 products. As reported in Table 1, the data include 1,050,516 observations each year, resulting in a total of 11,551,716 (province/product/country/year) observations over the 1997-2007 period. Approximately 32 percent of the observations correspond to strictly positive export flows from domestic firms. As emphasized in Table 2, 1,268,768 observations of the 11,551,716 observations of the entire database correspond to domestic starts, that is, to provinces where domestic firms do not export product k to country j at time t but do export at time t + 1.

As shown in Table 1, 11.5 percent of the observations in this balanced sample have non-null product-country-specific foreign export flows. The share rises to 26 percent if the sample is restricted to the observations for which domestic firms report positive exports. As emphasized in Table 2, 7.5 percent of domestic starts occurred when foreign firms in the province were exporting the same product to the same country the year before. As indicated in Table A-1 in the Appendix, the proportion is 69.8 percent when considering foreign exports of the same product to other countries and 88.6 percent when considering foreign exports of other products to the same country.

The geographic and sectoral distributions of the new trade linkages established by Chinese domestic firms over the period are described in Table 3. The export starts are quite diversified in terms of destinations. The US is the main destination for new trade linkages over the period, but it only represents 1.8 percent of overall export starts, followed by Hong Kong, South Korea, and Japan, with between 1.6 percent and 1.7 percent of all export starts. However, new transactions are more concentrated in terms of the province of origin, the most dynamic exporters being, not surprisingly, Guangdong (8.5 percent) and Zhejiang (7.5 percent). The export starts are also more concentrated from a sectoral viewpoint: “Nuclear reactors, machinery etc.” account for 10.5 percent of new transactions over the period in comparison with 6.6 percent for “Electrical machinery etc.” and 4.4 percent for “Articles of iron and steel”.

II. Estimation of Foreign Export Spillovers

Following Koenig et al. (2010), different types of spillovers are considered. Depending on the type of information needed to successfully enter export markets, the export spillovers could be destination specific, product specific, or both. For a given triad province-product-destination country ikj, the spillovers are thus decomposed into four non-overlapping components: product-(HS4) and destination-country-specific (foreign exports from province i of product k to country j), country-specific (foreign exports from province i of products other than k to country j), product-specific (foreign exports of product k to countries other than j), and general spillovers (foreign exports of products other than k to countries other than j).

The coefficients for the various spillover variables capture the net effect of the positive externalities described above and some possible negative effects, such as the pressure exerted by foreign firms on local labor markets, which might increase wages (as highlighted by Hale and Long, 2011, for skilled workers in China) or congestion effects linked to the saturation of transport infrastructures.

Nature of Foreign Export Spillovers

In this section, the value of exports realized by foreign firms is used as a proxy for foreign export spillovers. Because Moulton (1990) has shown that regressing individual variables on aggregate variables can induce a downward bias in the estimation of standard errors, all regressions presented in the paper are clustered at the province level.

When relying on the most aggregated measure of local foreign export activity (all products-all destinations), a negative and weakly significant effect is detected (column 1 of Table 4). This effect might be due to crowding-out effects or to an accounting issue; because total exports in province i in year t are also controlled for, the higher the share of foreign firms in these exports, the less probable the entry of domestic firms into foreign markets the following year. The country-specific (all products-same destination) and product-specific (same product-all destinations) spillover variables also show a negative sign, but the coefficient is very close to zero and not significant (columns 2 and 3 of Table 4). This is not the case for the most precise measure of foreign spillovers (same product-same destination). Interestingly, the product-country specific spillover variable is positive and significant at the 1 percent confidence level (column 4 of Table 4), indicating that the entry of domestic firms into the export markets for product k and country j in year t + 1 is positively influenced by the export activities of foreign firms for product k and country j in year t.

To further assess the specificity of export spillovers for a given province-product-destination country triad ikj, the overall export value of foreign firms from province i is decomposed in column 5 into its four complementary components: exports of the same product k to the same country j, exports of the same product k to other countries, exports of other products to the same country j, and exports of other products to other countries. The dynamics of the demand-side and supply-side determinants of entry into the export markets is also controlled for by introducing the relevant controls in t − 1. With this specification, the product-country specific spillover measure is the only measure that is positive and significant. When the past export performance of domestic firms in province i is added to neutralize export spillovers between domestic firms and/or scope economies in domestic export activities, the main result holds: the coefficient of foreign product-country specific export spillovers slightly increases to reach 0.023 (column 6 of Table 4).

A series of robustness checks are presented in Table A-2 in the appendix. Excluding successively agricultural products and mining products or focusing exclusively on the manufacturing sector does not affect the results (columns 2 to 4 of Table A-2), suggesting that the previous findings do not simply reflect weather conditions or local natural endowments that could jointly determine foreign and domestic export performance. Dropping the product-country pairs for which China is the main supplier of the destination country (45 percent and 85 percent of the total imports of product k by country j) also leaves the results unchanged (columns 5 and 6).⁹ The top three exporting provinces (Guangdong, Shanghai, and Jiangsu) do not drive the results (column 7). A similar conclusion is obtained when dropping the clothing, textile, and footwear sectors that benefited from dramatic trade liberalization over the period (column 8). Finally, excluding the greater China destinations (Hong Kong, Macao, and Taiwan) to account for round-tripping and the well-known outward-oriented province of Guangdong does not change the conclusions (columns 9 and 10). The results are remarkably stable across samples; foreign export spillovers do not appear to be driven by specific products or specific locations in China.

Endogeneity Issues

So far, the estimations control for province-product-country fixed effects and for different time-varying dimensions of export performance for domestic and foreign firms in the two years preceding the observation. However, if some shocks affect the capacity of both domestic and foreign firms from province i to export product k to country j and if foreign firms take this new opportunity before domestic firms, our estimation strategy does not completely correct for endogeneity. Three types of shocks can be considered.

Productivity shocks: It might be the case that both foreign and domestic firms from province i at some point experience a productivity shock specific to product k but do not enter the export markets at exactly the same time. This situation would bias the estimation of spillovers. However, this unobserved change in the ability of the foreign and domestic firms of province i to produce and export product k should affect the domestic starts regardless of the destination country. These productivity shocks can thus be controlled for by adding an HS4-province-year fixed effect to the baseline regression. Foreign export spillovers are then identified using heterogeneity across destinations within a given HS4-province-year.

Demand shocks: The preferences of consumers from country j for product k across the different importing sources might evolve differently over time. Controlling for the total imports of product k by country j at time t and t−1 does not account for the heterogeneous dynamics of demand in the destination country. If German consumers begin consuming increasing amounts of Chinese trousers at the expense of Vietnamese ones, this shift is not captured by our specification. However, if these types of preference dynamics are at play, it is unlikely that they would differ across Chinese provinces; consumers know whether products are produced in China, but they do not know in which province the products are produced. Consequently, if the preferences of consumers from country j for product k that is produced in China evolve over time, they should do so homogeneously across provinces. The destination country-HS4-year fixed effects should thus control for these demand shocks. Foreign export spillovers would then be estimated by comparing, for a given HS4-destination country-year, the timing of the domestic starts across Chinese provinces.

Province-destination country shocks: In the case of bilateral shocks affecting the economic relationships between a province and a destination country (changes in the location of provincial diasporas abroad, province-country economic agreements), the HS4-province-year and the HS4-destination country-year fixed effects will not be sufficient to purge the estimation of export spillovers from endogeneity. The inclusion of province-destination country-year dummies can address this issue.

Province-product-country-year shocks: Finally, it could be the case that unobserved shocks specific to province i, product k, country j, and time t + 1 bias our results. The addition of the three types of fixed effects proposed earlier would not solve the problem. However, it is not possible to introduce HS4-province-destination country-year fixed effects because such fixed effects would be in the same dimension as the export spillovers. The instrumentation of the spillover variable is thus the only solution. To instrument the exports of product k to country j by foreign firms in province i at time t, variables must be identified that can explain foreign exports at time t without being directly correlated with domestic exports at time t + 1. Good candidates for this purpose are the province-specific FDI policies that are likely to modulate, across Chinese provinces, the consequences of demand shocks that are specific to product k and country j. In particular, the Export Processing Zones (EPZ) have been one of the most important components of China's strategy to attract multinationals. Since 1980, the central government has opened a number of these zones, which offer specific incentives to foreign investors (Fu and Gao 2007). Another manifestation of the efforts of Chinese authorities to attract multinational firms, specifically those producing higher-end variety products, is the proliferation of government-sponsored high-tech zones (Wang and Wei 2010).¹⁰ Both types of zones are thus likely to favor exports by foreign firms without directly affecting exports by Chinese firms. Our instrumentation strategy thus relies on the hypothesis that international demand conditions affect foreign firms' exports differently across provinces depending on the presence of these zones. In particular, the impact of a positive demand shock for product k in country j on the foreign firms in province i will be stronger when the number of EPZ and high-tech zones in province i is high. Concretely, the variable used to instrument the export value of foreign firms in province i for a given product-country-year triad kjt is the interaction between demand conditions (import value from the rest of the world) for that country-product-year triad and the number of zones in the province. We use two instruments that rely on the number of EPZs and the number of high-tech zones by province and year, taken from Wang and Wei (2010). Because EPZ and high-tech zones should not directly affect exports by domestic firms and because the total imports of product k by country j at time t are also introduced as an independent regressor, the instruments proposed are likely to be exogenous.

It is not possible to include the various above-mentioned additional fixed effects or to apply our instrumentation strategy in a conditional logit model. Hence, a linear probability model with adequate fixed effects is used in this section. Our benchmark results (column 6 of Table 4) are first replicated and do not differ significantly in terms of sign, significance, and magnitude between using a conditional logit (column 1 of Table 5) or a linear probability model (column 2 of Table 5). In column 2, the coefficients can be interpreted as marginal effects. A 10 percent increase in the value of exports of product k to country j by foreign firms located in province i at time t increases the probability that the domestic firms in the same province will begin exporting product k to country j at time t + 1 by 0.07 percentage points. This result is reassuringly close to the result from a conditional logit estimation (0.05 percentage points).¹¹ It thus appears reasonable to believe that the results obtained by adding controls or using IV in the linear probability model would provide a similar result if it were possible to use them in a conditional logit specification. The inclusion of province-HS4-year, destination country-HS4-year fixed effects, or province-destination country-year fixed effects does not change the results (columns 3 to 5): the significance and the magnitude of the product and the destination country-specific foreign export spillovers remain unaffected. The ranking of the different types of spillovers also remains qualitatively the same. These results suggest that specific productivity shocks, demand shocks, or province-country shocks do not drive the results. The IV estimates are also reassuring (column 6). The first-stage results suggest, as expected, that positive demand shocks result in greater foreign exports in provinces with many EPZs (column 7). The interaction with the number of high-tech zones, however, fails to be significant. The F-test statistic for the inclusion of additional instruments in the first-stage regressions is above the rule of thumb value of 10, suggesting that the instruments are correlated with the endogenous variables and that there is no weak instrument problem (Staiger and Stock 1997). The Hansen test indicates that the overidentifying restriction is not rejected, supporting the validity of the instruments. In the second stage, the coefficient of interest on the spillover variable appears to be greatly increased. However, the standard error also increases, and the Hausman test for the difference between our benchmark and the two-stage least-squares estimates suggests that the exogeneity of the spillover variable in column 2 cannot be rejected. Hence, all of these results show that our benchmark specification does not suffer from a major endogeneity issue. For this reason, the conditional logit specification with province-product-country fixed effects is maintained as the preferred specification for the remainder of the paper.

Specification of Spillovers

In this subsection, the appropriate method of modeling foreign export spillovers and the role of spatial proximity are discussed.

Two strategies are adopted to address the high number of zero foreign trade flows in our sample.

First, the sample is restricted to observations with a non-zero foreign presence for product k and country j in year t (column 2 of Table 6). In this subsample, the average probability of new linkage creation by domestic firms increases from 21.9 percent to 38 percent (as reported at the bottom of the columns). Furthermore, the size of the coefficient increases and is now equal to 0.043, compared to the benchmark results (column 1 of Table 6). In column 3, the sample is restricted to province/product/country triads for which positive foreign exports are observed in 1997, the first year of the sample). Overall, despite the reduction in the number of observations (100,442 in column 2 and 66,585 in column 3), the positive and significant impact of the product-country specific spillover variable is confirmed.