metadata: authors: 0: author: Amiti, Mary
1: author: Freund, Caroline
count: China
docna: 0: docna: The anatomy of China's export growth
docty: Policy Research Working Paper
subtopic: Private Sector Economics,Construction Industry,Common Carriers Industry,Food & Beverage Industry,General Manufacturing,Pulp & Paper Industry,Plastics & Rubber Industry,Private Sector Development Law,International Trade and Trade Rules,Food Security,Marketing,Business Cycles and Stabilization Policies,Transport Services
teratopic: Macroeconomics and Economic Growth,Finance and Financial Sector Development,Private Sector Development,International Economics and Trade
abstracts: cdata!: Decomposing China's real export
            growth, of over 500 percent since 1992, reveals a number of
            interesting findings. First, China's export structure
            changed dramatically, with growing export shares in
            electronics and machinery and a decline in agriculture and
            apparel. Second, despite the shift into these more
            sophisticated products, the skill content of China's
            manufacturing exports remained unchanged, once processing
            trade is excluded. Third, export growth was accompanied by
            increasing specialization and was mainly accounted for by
            high export growth of existing products (the intensive
            margin) rather than in new varieties (the extensive margin).
            Fourth, consistent with an increased world supply of
            existing varieties, China's export prices to the United
            States fell by an average of 1.5 percent per year between
            1997 and 2005, while export prices of these products from
            the rest of the world to the United States increased by 0.4
            percent annually over the same period.
geo_reg_key: 80475,80451,80460
repnme: repnme: The anatomy of China's export growth
display_title: The anatomy of China's export growth
listing_relative_url: /research/2008/05/9473019/anatomy-chinas-export-growth
topicv3: Private Sector Development m1326060 1921,Agriculture and Food Security m1326205 435,Manufacturing Sectors m1326521 1281,Transport m1326661 135,Trade m1326924 698
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: Macroeconomics and Economic Growth,Finance and Financial Sector Development,Private Sector Development,International Economics and Trade
no_of_pages: 29
author_keys: 0: author_key: NA
1: author_key: NA
model_extractions: WPS4628 Policy ReseaRch WoRking PaPeR 4628 The Anatomy of China’s Export Growth _Mary Amiti Caroline Freund_ The World Bank Development Research Group Trade Team May 2008
Policy ReseaRch WoRking PaPeR 4628

# **Abstract**

Decomposing China's real export growth, of over 500 percent since 1992, reveals a number of interesting findings. First, China's export structure changed dramatically, with growing export shares in electronics and machinery and a decline in agriculture and apparel. Second, despite the shift into these more sophisticated products, the skill content of China's manufacturing exports remained unchanged, once processing trade is excluded. Third, export growth was accompanied by increasing specialization and was mainly accounted for by high export growth of existing products (the intensive margin) rather than in new varieties (the extensive margin). Fourth, consistent with an increased world supply of existing varieties, China's export prices to the United States fell by an average of 1.5 percent per year between 1997 and 2005, while export prices of these products from the rest of the world to the United States increased by 0.4 percent annually over the same period.

This paper—a product of the Trade Team, Development Research Group—is part of a larger effort in the department to understand how exports grow. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at cfreund@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **The Anatomy of China’s Export Growth**

Mary Amiti Federal Reserve Bank of New York & CEPR Caroline Freund World Bank _Keywords: Extensive Margin, Intensive Margin, Processing Trade, Specialization JEL Codes: F14_ ______________________________________ Amiti, International Research, Federal Reserve Bank of New York, email: mary.amiti@ny.frb.org; Freund, Research Department, World Bank, 1818 H Street, NW, Washington DC, 20433, Ph 1-202-458-8250, Fax 1-202-589-7767 , email cfreund@imf.org. We would like to thank Jin Hongman of Customs, China for providing us with the data. Prepared for NBER conference. We are grateful to Rob Feenstra for extended comments and discussions, and to David Weinstein, Shang-Jin Wei, Chong Xiang, Bin Xu, and participants at the NBER pre-conference and the IMF for many useful suggestions. The views expressed in this Working Paper are those of the authors and do not necessarily represent those of the World Bank or the Federal Reserve Bank of New York.
# 1. Introduction

China’s real exports increased by more than 500 percent over the last 15 years. As a result, in 2004, China overtook Japan as the world’s third largest exporter, just behind Germany and the United States. This paper decomposes this stunning export growth along various dimensions. In particular, how has China’s export structure changed? Has the export sector become more specialized, focusing on particular types of goods, or has it diversi fi ed as it has grown? Are China’s exports becoming more skill intensive? How important are new goods in export growth? The answers to these questions have important implications for the global welfare consequences of China’s export expansion and for future growth of China’s export sectors.

Our analysis shows that China’s export structure has transformed dramatically since 1992. There has been a signi fi cant decline in the share of agriculture and soft manufactures, such as textiles and apparel, with growing shares in hard manufactures, such as consumer electronics, appliances, and computers. However, a large component of this export growth in machinery has largely been due to growth in processing trade - the practice of assembling duty free intermediate inputs. These inputs are generally of high skill content, originating in countries such as the United Sates and Japan (see Dean, Fung and Wang, 2007). Thus on the surface it appears that China is dramatically changing its comparative advantage yet a closer examination reveals that it is continuing to specialize in labor intensive goods. We fi nd that the labor intensity of China’s exports remains unchanged once we account for processing trade. Further, exports remained highly concentrated in a small fraction of goods–though the particular goods have changed. These patterns are consistent with traditional trade theories, which place specialization and comparative advantage at the center of trade growth.

More recent trade theories emphasize the gains from trade as importing countries access new product varieties. For example, Broda and Weinstein (2006) fi nd that 30 percent of US import growth between 1972 and 2001 was in new varieties (the extensive margin), and that 2
China was the largest contributor to growth in these U.S. varieties; however, most of this growth was in the earlier period from 1972 to 1988. Other papers highlight a strong positive correlation between the number of export varieties a country produces and its living standard (see Funke and Ruhwedel, 2001). Hummels and Klenow (2005) fi nd that larger and richer countries export more varieties of goods, using data for 1995. This fi nding is suggestive that a large portion of China’s export growth would be associated with exports of new varieties. However, our analysis of China’s export growth patterns between 1997 and 2005 shows that most of its export growth was actually in existing varieties (the intensive margin). This large growth in the intensive margin is also supportive of predictions consistent with traditional theories with an important role for terms of trade e ff ects, where the welfare gains for importing countries arise through lower import prices. As China increases its supply of existing varieties on world markets, this is likely to exert downward pressure on world prices of these goods. Indeed, between 1997 and 2005, average prices of goods exported from China to the US fell by an average of 1.5 percent per year whereas the average prices of these products from the rest of the world to the US increased on average by 0.4 percent per year.<sup>1</sup> The rest of the paper is organized as follows. Section 2 describes the data. Section 3 examines the reallocation of exports across industries. Section 4 looks at the skill intensity of exports. Section 5 examines whether there has been increased diversi fi cation or specialization as exports have grown. Section 6 decomposes export growth into the intensive and extensive margins. Section 7 compares China’s export prices to the United States to those from the rest of the world. Section 8 concludes.

# 2. Data

The most disaggregated export data available for China is at the HS 8-digit level, from China Customs Beijing, which includes 8,900 product codes. The trade data are in current

> 1 This is a Tornqvist chain weighted price index using HS 10-digit goods that China exported during this period.

3
US dollars, which we de fl ate by the U.S. CPI to generate a constant dollar series. Summary statistics for China’s exports are presented in Table 1, showing that China’s real exports to the world increased by 500 percent between 1992 and 2005, from US$84.94 billion to US$525.48 billion. Its share of exports to the US increased from 10 percent to 21 percent over the sample period. To check for the accuracy of the China export data, we also use data on US imports from China, from the US Bureau of the Census, Foreign Trade Division. This data also has the advantage of being available at an even higher level of aggregation, at the HS 10-digit, which includes 18,600 product categories.

As there were major reclassi fi cations in the international HS 6-digit classi fi cations in 1996 and 2002, in some cases we aggregate the data up to HS 6-digit codes and convert them to the same HS 6-digit classi fi cations used in 1992 to avoid problems related to reclassi fi cation of codes. This reduces the number of product codes for China’s world exports to 5,000 products. To examine broader export patterns we divide the data into SITC 1-digit codes, which include agriculture (SITC 1 to 4), chemicals (SITC 4), manufactured materials (SITC 5), manufactured materials (SITC 6), machinery (SITC 7) and miscellaneous manufactures (SITC8).

# 3. Reallocation across Industries

China has experienced big changes in its export composition. It has moved from the fi rst stage of agriculture and apparel to more sophisticated manufactured goods. Figure 1 shows this by plotting the export share of each one-digit SITC sector in 1992 and 2005. Rapid export growth has been associated with a move out of agriculture and apparel into the machinery and transport sectors. In Figure 2, we focus on changes within the manufacturing sector. In particular, we look at how trade shares have adjusted in all major 2-digit SITC sectors, where major is de fi ned as accounting for at least 3 percent of exports in 1992 and/or 2005. There is a notable move out of apparel, textiles, footwear, and toys and into electrical machinery, telecom, o ffi ce machines, and to a lesser extent metals.

4
The strongest overall export growth has been in machinery (SITC 7), and within this broad category it is telecoms, electrical machinery and o ffi ce machines that have experienced the highest growth and make up the largest shares within machinery. The question arises whether China is producing most of the value-added of these capital intensive goods or is it just assembling duty-free imported inputs for export? This practice is known as processing trade and does account for an increasingly large share of China’s exports, from 47 percent in 1992 to 55 percent in 2005. According to Dean, Fung and Wang (2007), imported inputs account for between 52 to 76 percent of the value of processing exports. Figure 3 graphs total exports of 2-digit machinery categories as a share of total manufacturing exports, in descending order for 2005, and the lighter bars show the portion that is classi fi ed as processing trade by China Customs. This fi gure reveals that most of the high export growth in machinery is indeed processing trade, thus only a small share of this growth is likely to be due to high value added production in machinery in China.

# 4. Skill Content of Export Growth

China’s export bundle is very di ff erent now from what it was in the early 1990s. Rodrik (2006) and Schott (2006) highlight the increasing sophistication of China’s exports, as demonstrated by an export pattern that more closely resembles high income countries than would be expected given its income level. To see whether this increased sophistication has been associated with an increase in the overall skill content of its exports, we rank industries from low to high skill intensity on the horizontal axis of Figure 4, and plot the cumulative export share on the vertical axis. Because industry skill level data for China were unavailable we based the skill intensity ranking on information from Indonesia, another emerging market that is likely to have similar technologies.<sup>2</sup> The skill intensity is measured as the ratio of non-production workers to total employment from the Indonesian manufacturing census at

> 2 Zhu and Tre fl er (2005) measure changes in the skill content of exports for all countries using U.S. industry level skill data to rank the skill intensity of industries, assuming no factor intensity reversals. Our results also hold using U.S. skill data.

5
the 5 digit ISIC level for 1992. In Figure 4, the shift of the curve to the right indicates that the skill content of China’s exports has increased over the sample period. For example, in 1992, 20 percent of the least skill-intensive industries produced 55 percent of China’s export share. By 2005, the export share that these industries produced fell to 32 percent.<sup>3</sup> However, given the high share of processing trade in China, an increase in the skill content of China’s exports could be due to China importing intermediate inputs with higher skill content that it then assembles for exporting. We assess this possibility by plotting the cumulative of export shares against the skill intensity with non-processing manufacturing exports only. That is, we exclude any exports that have been classi fi ed as processing trade. From Figure 5, we see that there is hardly any shift in the curve indicating no change in the skill content of China’s non-processing exports.

Processing exports make up a large share of China’s manufacturing exports and by excluding processing exports we are excluding around 54 percent of China’s manufacturing exports (see Table 1). Although imported inputs account for a large share of the value of processing exports, there still remains a signi fi cant amount of value added in China in processing exports and there could be a shift in the skill content within that portion. To examine this possibility, we compare the change in the skill content of imported manufacturing inputs for processing trade to the skill content of imported inputs for non-processing trade in Figures 6 and 7. Using US industry skill data to rank the skill intensity of imports, we fi nd a much larger increase in the skill content of processed imports than of non-processing imports. Of course this rise in the skill-content of processing imports does not rule out the possibility that the Chinese value-added has become more skill-intensive too.

> 3 This approach only gives an indication of shifts between industries, thus we cannot say if there has been any skill upgrading within an industry.

6
# 5. Diversi fi cation versus Specialization

We have seen that snapshots of China’s export sector taken in 1992 and 2005 look very different, with the increased churning from agriculture and textiles into machinery, electronics and assembly. As a result of this transformation, China’s exports may have become more specialized or more diversi fi ed. Traditional trade theory highlights the combination of increased trade and specialization as a key factor in promoting higher living standards. Imbs and Warziarg (2003), however, fi nd that countries tend to diversify production as they grow from low levels of income, and that they only begin to specialize once they reach a relatively high level of income. This is consistent with countries moving from exploiting natural resources to developing new industrial sectors as they grow. Hausmann and Rodrik (2003) argue that in the early stage of development, more entrepreneurship and potentially greater diversi fi cation may help producers identify the sectors in which it is a competitive producer.

We examine whether China’s exports display increased or decreased specialization in Figure 8, by plotting the inverse cumulative export shares for all products at the HS 6- digit level. A shift to the left of the curve would indicate increased specialization. Looking across all products, it appears from Figure 8 that there is hardly any change in the degree of specialization. Yet, when we magnify the image of Figure 8 in Figure 9, showing the cumulative trade shares when we keep only the largest 500 categories by value, which account for nearly 80 percent of total exports in either of the years, there is a noticeable downward shift in the curve suggesting there has been an increase in specialization. The pattern is very similar, with a slightly greater increase in specialization, if we only include manufacturing exports.

This fi nding is con fi rmed using the Gini coe ffi cient, which is an alternative way to measure changes in specialization, by measuring export equality in each period. It is de fi ned as where there are n products, i is a product’s rank (1 is smallest and n is largest), and csharei 7
is the cumulative share of exports of the ith product. The Gini coe ffi cient uses the trapezoid approximation to calculate the area between a 45 degree line and the cumulative distribution, weighting each industry as an equal share of the population of industries (1/n). A Gini coe ffi cient of zero indicates that export shares are equally distributed across all industry groups; an increase in the Gini coe ffi cient implies an increase in specialization.

Table 2 reports the Gini coe ffi cient for 1992 and 2005 for the whole sample of products and some sub-samples. The Gini coe ffi cient remained unchanged over the sample period at 0.85 when all products are included. However, when a sub-sample of the largest goods accounting for 70 percent of exports are included, the Gini coe ffi cient increases from 0.46 to 0.55. Similarly, when we only include the top 100 products, which account for 45 percent of exports in 1992 period and nearly 50 percent in 2005, the Gini coe ffi cient increased from 0.35 to 0.50. Thus, over the period we see enhanced specialization - a smaller number of products account for an increased size of China’s exports - though the bundle of goods exported has changed.

# 6. Intensive vs. Extensive Margin

Has the large export growth mainly been in new product varieties or existing varieties? A new variety is generally de fi ned as the export of a new product code, that is, a product code for which there are positive exports one period and zero exports in an earlier period. One of the main problems using this de fi nition is that there have been major reclassi fi cations in the trade data in 1996 and 2002 at the HS 6-digit level, thus a product might be classi fi ed as a new variety just because there has been a new product code or previous codes were split. For example, in one year cherry tomatoes were reclassi fi ed into a new product code rather than being part of the tomatoes category. In this case, cherry tomatoes would appear to be counted as a new variety even though they were exported in previous periods. In contrast, at screen televisions received a new classi cation and these are in fact new varieties.

8
# 6.1. Export shares

There have been various approaches developed to address these reclassi fi cation issues. One approach is to use HS 6-digit data concorded to the same 1992 product codes, but in general these categories might be too aggregated to be able to identify new products: by 1992, China was exporting in over 90 percent of these categories. To examine whether export growth is mainly from new goods with this aggregate data we follow Kehoe and Rhul (2005) by splitting exports into deciles by value in 1992 and calculate their share of exports in 2005. If export growth is mainly from new goods, we would expect rapid growth in the bottom deciles, where trade was negligible in 1992. Figure 10 shows the share of exports in 2005 that is accounted for by the products falling into each decile. The categories that accounted for the bottom twenty percent of trade by value more than doubled between 1992 and 2005, while the categories in the other deciles contracted or remained constant.<sup>4</sup> This points to a sizeable role for the extensive margin, as the least traded goods grew the fastest.

One problem with this method is that exports tend to be concentrated in a small number of categories. This can be clearly seen in Figure 11, where we divide exports into deciles according to the number of categories of trade in 1992. For example, the tenth decile is the top ten percent of product categories when products are ranked by value. The distribution in 1992 is highly skewed, re fl ecting that only 10 percent of categories accounted for nearly 80 percent of trade. The decline in the share of the top decile shows that there was a sizeable reallocation of trade, but it was not the bottom 50 percent of products that gained. Instead, gains in the trade share were in the four deciles just below the top.

In sum, the results imply that there was a signi fi cant reorientation in exports, and that the reshu ffl ing of export products during the expansion was mainly in the mid-upper rank products. These are products that were in the bottom 20 percent by value but in the midto-high range by product rank.<sup>5</sup> Taken with the previous results on specialization, this

> 4 Arkolakis (2006) develops a model consistent with this fi nding.

> 5 These fi gures and the estimates of the extensive and intensive margin are very similar if we use only manufacturing trade.

9
implies that there was a sizeable compositional shift over time that led to a more skewed distribution of trade in 2005 as compared with 1992.

# 6.2. Variety growth

To utilize the more disaggregated trade data at the 8- and 10-digit levels, we examine the contribution of new varieties to export growth using two complementary methods. The fi rst is the Feenstra index of net export variety growth which provides an indication of the importance of new varieties in trade. The second is a decomposition of export growth into new, disappearing, and existing varieties and o ff ers more information on the magnitude of export creation and destruction. We present the de fi nitions and discuss the strengths and weaknesses of each measure below.

Feenstra’s (1994) seminal work on measuring import prices incorporating new goods leads to a natural index of variety growth that has been widely used in the literature. Denoting I as the set of varieties available in both periods, I ⊆ (It ∩ It − 1), the Feenstra index of net variety growth is de fi ned as the fraction of expenditure in period t-1 on the goods i ⊂ I relative to the entire set i ⊂ It − 1 as a ratio of the fraction of expenditure in period t on the goods i � I relative to the entire set i � It, minus one.<sup>6</sup> Let Vti be the value of trade at time t in product i (Vti = ptiqti ), then The index will be equal to zero if there is no growth in varieties relative to the base period and positive if the number of varieties has grown. This measure has the nice feature that if HS trade classi fi cations are split, and their share of total trade remains unchanged, the index remains unchanged. However, if growth classi fi cations are split (or reclassi fi ed) to a greater extent than shrinking classi fi cations are merged, the index will tend to overstate the extensive margin. A disadvantage of the index for measuring the relative importance of new varieties in export growth is that if there is a lot of churning, with an equal amount of export

> 6 From Feenstra (1994) this is the inverse of the lambda ratio minus one.

10
creation and destruction, it will report net variety growth of nil. To an importer, theory suggests that welfare increases with the number of varieties available, so it is net variety growth that is relevant. To an exporter, however, gross variety changes may be of interest as they provide an indication of how important new goods are to export growth. From the exporter’s perspective, the Feenstra index could understate the importance of new goods in export growth if there is a lot of creation and destruction.

To get an idea of how important churning is, we also calculate the shares of trade growth due to new, disappearing, and existing goods. The decomposition of trade growth is as follows: where It<sup>D</sup> − 1<sup>isthesetofproductsthatdisappearedbetweent−1andt,andI</sup> t<sup>N</sup> is the set of new products available in year t. This is an identity where total growth in trade relative to the base period is decomposed into three parts: (i) the growth in products that were exported in both periods, the intensive margin; (ii) the reduction in export growth due to products no longer exported, disappearing goods; and (iii) the increase in export growth due to the export of new products. The share of trade growth due to the extensive margin is de fi ned as the new-goods share less the disappearing-goods. This decomposition provides an estimate of the extent of churning, but it is less robust to reclassi fi cations than the Feenstra index because growth from products that are reclassi fi ed for any reason will be attributed to the extensive margin. We report the share of total export growth of each term on the right hand side of Equation 6.1, hence by construction the intensive and extensive margins sum to one.<sup>7</sup> Figure 12 plots the Feenstra index of net variety growth and the share of trade growth

> 7 Note that there is a direct relationship between the Feenstra index of net variety growth and the decomposition in Equation 6.1. λ t − 1 = 1 − share disappearing *export growth and λ t = 1 − share new*export growth/(Vt/Vt − 1). This highlights how the Feenstra index of net variety growth essentially combines disappearing trade and new trade into one index.

11
attributed to the extensive margin on an annual basis for China’s exports to the US at the 10-digit level from 1993 to 2005. What is striking about this fi gure is the large peak in the growth in the extensive margin around 1996, where there were major reclassi fi cations, and in the following year there is a big fall in variety growth using both measures. This likely re fl ects that some new classi fi cations were used in the middle of 1996 and old classi fi cations were not retired until the following year. Although the size of the reclassi fi cation e ff ect is smaller using the Feenstra index, reclassi fi cations still clearly play an important role in calculations of the extensive margin using both measures.

To measure growth in the extensive margin, it is more insightful to consider changes over a longer horizon since the value of exports in new product codes are generally small when they are fi rst introduced. But if one just compares year to year changes they would no longer be grouped in the new goods category. In order to minimize the reclassi fi cation issues, we report the growth in extensive margin from 1997 to 2005 in Table 3. Using an earlier period as a base yields wide variations in measures, and comparable US and China data give vastly di ff erent results. Panel A of Table 3 shows calculations using China’s 8-digit data. In the fi rst row, where we use data on China’s exports to the world from 1997-2005 in all 8-digit categories, we see moderate net variety growth of 10 percent, with the extensive margin accounting for 26 percent of total export growth. Recalculating the extensive margin with exports only to the United States, in the second row, we see that the magnitudes of the extensive and intensive margins are roughly the same as with total exports. In order to eliminate the potential problem associated with reclassi fi cations that take place from year to year in China’s HS 8-digit data, we also calculate the margins for product codes that existed over the whole period. In this case, we fi nd that the growth in exports to the United States accounted for by new varieties falls markedly, to just 2 percent. This implies that part of the large variety growth found with the full sample is likely a result of reclassi fi cations pushing up the extensive margin. The existing products codes are likely not to be a random sample since entirely new products—such as a digital camera—will by de fi nition require a new code, 12
thus this can be taken as a lower bound of the extensive margin.

Panel B of Table 3 reports the extensive margin using U.S. data at the 10-digit level. The data have more than twice as many codes (over 14,000 for U.S. China trade), allowing the extensive margin to be larger. Using all of the 10-digit exports from China to the U.S., net variety growth is negative and the extensive margin share of trade growth is 17 percent. The smaller value for the extensive margin in the U.S. data, as compared with the China data, is likely a result of there being fewer reclassi fi cation in the United States (81% of codes are permanent as compared with 76% in the China data). Including only codes that exist between 1997 and 2005, the net variety growth and the extensive margin’s share of trade growth are similar, at around 3 percent, and larger than measured using permanent 8-digit codes from the China data. Note that there is still signi fi cant growth in the number of new export variety categories, which increased by more than 40 percent but these new varieties account for a small share of export growth.

Compared to other non-OECD countries, China’s growth in the extensive margin has been small. Based on the HS 10-digit export data to the U.S. with all codes included, China ranks 80th out of a total of 133 non-OECD countries using the Feenstra net index of variety measure and 100th using the extensive margin measure.

All of these measures of the extensive margin should be interpreted with caution given that the magnitudes vary considerably depending on whether all product codes are used and whether the base period is before or after the major reclassi fi cations that took place in 1996. The calculations with the more disaggregated U.S. data from 1997 onwards indicate that a large portion of China’s export growth took place along its intensive margin.

# 7. Export Prices

The large increase in export growth along the intensive margin suggests that China’s export growth is likely to put downward pressure on world prices of these goods. Taking the subset of HS 10-digit goods that China exported to the US between 1997 and 2005, we construct an 13
average export price index using a chain weighted Tornqvist index for manufactured goods, de ned as follows: and pit is the unit value, de fi ned as the ratio of the export value from China to the United States of product i at time t to the quantity exported. Note that we only construct export price indices to the United States rather than to exports to the world because it is important to have highly disaggregated product level data to ensure that the units of measurement of quantities are the same within the HS codes. Using more aggregated data, say, at the HS 6- digit level runs the risk of having aggregated quantities across di ff erent units of measurement. Even at the HS 10-digit level the quantity data is quite noisy, thus we clean the data by deleting products with price change of more than 200 percent over this period. After cleaning the data and ensuring that China and the rest of the world export this same subset of products, we are left with 3,800 HS 10-digit product codes within manufacturing. The export price index for China is weighted by the export value of each of these product codes from China to the US as a ratio of the total value of these exports, and the export price index from the rest of the world to the U.S. is weighted by the export value of each of these same product codes products from the rest of the world to the U.S. as a ratio of total export value of these products.

The Tornqvist export price index (Tindex) for China between 1997 and 2005 is 0.88, indicating a fall of 12 percent over the period. In contrast, the Tindex for exports of these same HS 10-digit codes from the rest of the world to the United States is 1.03, indicating a 3 percent increase in prices over this period.<sup>8</sup> The export price decline in China is consistent with a negative terms-of-trade e ff ect, with increased exports pushing down export prices. However, it could also be related to improved productivity in China, declining pro fi t margins or exchange rate movements.

> 8 The Fisher price index, which is the square root of the Laspeyres index (that uses base period weights) and the Paasche index (that uses current period weights) gives the same result as the Tindex.

14
# 8. Conclusions

This chapter decomposes China’s spectacular export growth, of over 500 percent since 1992, along various dimensions. A number of interesting fi ndings emerge. First, churning among di ff erent products was signi fi cant. China’s export structure changed dramatically, with growing export shares in electronics and machinery and a decline in agriculture and apparel. The strongest overall export growth has been in machinery, and within this broad category telecoms, electrical machinery and o ffi ce machines have experienced the highest growth and make up the largest shares within machinery.

Second, despite the shift into these more sophisticated products, the skill content of China’s manufacturing exports remained unchanged once processing trade is excluded. When examining the skill content of China’s total manufacturing exports, it looks like there has been an increase over the sample period. However, it turns out that this is mainly due — to the increased skill content of imported inputs that are then assembled for export a practice known as processing trade. This result has implications for other studies that have emphasized the sophistication of China’s exports as a potential conduit of China’s rapid income growth. We highlight processing trade as the mechanism behind this special feature of China’s exports. Of course, there still may be something special about processing trade, perhaps through learning externalities or more growth opportunities in export processing.

Third, export growth was accompanied by increasing specialization. This fi nding casts some doubt on the notion that export diversi fi cation is a key element in export growth. The literature argues that diversi fi cation could promote export growth if it makes export discoveries more likely, and that it helps alleviate risks associated with shocks to particular sectors. Indeed, traditional thinking highlights trade and specialization, where market forces work to attract resources into the main sectors where relative cost advantages are the greatest.

Fourth, export growth was mainly accounted for by high export growth of existing products (the intensive margin) rather than in new varieties (the extensive margin). Consistent 15
with an increased world supply of existing varieties, we fi nd that China’s export prices to the US fell by an average of 1.5 percent per year between 1997 and 2005, while export prices of these products from the rest of the world to the US increased by 0.4 percent annually over the same period. Importers have gained from lower prices, and from the abundance of products now available in markets around the globe.

# References

- [1] Arkolakis, C. (2006). “Market Access Costs and the New Consumers Margin in International Trade” University of Minnesota, unpublished mimeo.

- [2] Broda, C. and D. Weinstein (2006). “Globalization and the Gains from Variety” Quarterly Journal of Economics, 541-585.

- [3] Dean, Judy, K.C. Fung and Zhi Wang (2007) “Measuring the Vertical Specialization on Chinese Trade”, unpublished mimeo.

- [4] Debaere, P. and S. Mostashari (2006?) “Do Tari ff s Matter for the Extensive Margin of International Trade? An Empirical Analysis” Mimeo University of Texas, Austin.

- [5] Feenstra, R. (1994) “New Product Varieties and the Measurement of International Prices”, American Economic Review, LXXXIV, 157-77.

- [6] Feenstra, R. and H.L. Kee (2006) “Trade Liberalization and Export Variety: A Comparison of Mexico and China”. Mimeo World Bank.

- [7] Hillberry, R. and C. McDaniel (2002) “A Decomposition of North American Trade Growth Since NAFTA”, ITC Working Paper 2002-12-A.

- [8] Hummels, D. and P. Klenow (2005). “The Variety and Quality of a Nation’s Exports” American Economic Review, 95, 704-723.

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- [9] Imbs, J and R. Warziarg (2003) "Stages of Diversi fi cation" American Economic Review, 93(1): 63-86.

- [10] Kehoe, T. and K. Ruhl (2002) “How Important is the New Goods Margin in International Trade?” Federal Reserve Bank of Minnesota.

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- [12] Rodrik, D. (2006) "What’s So Special About China’s Exports?"NBER Working Paper 11947.

- [13] Schott, P. (2006) "The Relative Sophistication of China’s Exports" NBER Working Paper 12173.

- [14] Zhu Chun, S. and D. Tre fl er (2005). “Trade and Inequality in Developing Countries: A General Equilibrium Analysis", Journal of International Economics 65, 21-48.

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# **Table 1:  Summary Statistics**

|**Trade Data**|
|---|

|||1992|1995|1997|1999|2001|2003|2005|
|---|---|---|---|---|---|---|---|---|
|China's Total Exports|$USbil|84.94|136.50|160.34|163.81|211.19|334.53|525.49|
|China's Total Processing Exports|$USbil|39.92|67.92|87.59|93.23|117.04|184.56|287.24|
||share (%)|0.47|0.50|0.55|0.57|0.55|0.55|0.55|
|China's Exports to US (Chinese Data)|$USbil|8.59|22.67|28.70|35.25|43.08|70.59|112.34|
||share (%)|0.10|0.17|0.18|0.22|0.20|0.21|0.21|
|China's Exports to US(US Data)|$USbil|25.73|41.79|54.87|68.73|81.17|116.32|167.91|

# **Table 2: Gini Coefficient for China's Exports**

|**Period**|**All**|**Top 70%**|**Top 100**|
|---|---|---|---|
|1992|0.85|0.46|0.35|
|2005|0.86|0.55|0.50|

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# **Table 3: Variety Growth in China’s Exports, 1997-2005**

|**A: Extensive Margin using 8-digit China Data**|
|---|

||**Number**<br>**of Codes**|**Type **|**Partner**|**Feenstra**|**Shar**<br>**Intensive**|**e of Total**<br>**New**|**Export Growth f**<br>**Disappearing**|**rom:**<br>**Extensive**|**Total**<br>**Export**<br>**Growth %**|
|---|---|---|---|---|---|---|---|---|---|
|1|7951|All|World|0.10|0.74<br>[5501]|0.33<br>[1624]|0.07<br>[826]|0.26|187|
|2|6357|All|US|0.11|0.76<br>[3641]|0.29<br>[1980]|0.05<br>[736]|0.25|243|
|3|4826|Exist|US|0.01|0.98|0.02|0.00|0.02|212|
||76% of<br>codes||||[3641]|[935]|[250]|||

## **B: Extensive Margin using 10-digit U.S.  Data**

||**Number**<br>**of Codes**|**Type **|**Partner**|**Feenstra**|**Shar**<br>**Intensive**|**e of Total**<br>**New**|**Export Growth f**<br>**Disappearing**|**rom:**<br>**Extensive**|**Total**<br>**Export**<br>**Growth %**|
|---|---|---|---|---|---|---|---|---|---|
|1|14169|All|US|-0.03|0.83|0.29|0.12|0.17|168|
||||||[7576]|[5122]|[1471]|||
|2|11444|Exist|US|0.02|0.97|0.03|0.00|0.03|182|
||81% of<br>codes||||[7576]|[3506]|[362]|||

*Notes: the extensive and intensive margin may not sum exactly to one because of rounding error.

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# **Figure 1: Reallocation of Exports Across SITC One-Digit Industries**

<!-- Start of picture text --> Agriculture and Raw Mat. Misc Manuf Manuf Materials Machinery Chemicals<br>(SITC 1-4) (SITC 8) (SITC 6) (SITC 7) (SITC 5)<br>1992 2005<br>.4<br>.3<br>.2<br>Share of Total Exports<br>.1<br>0<br><!-- End of picture text -->

# Note: Column headings include the following industries:

- SITC 1-4: Beverages, tobacco, raw materials, mineral fuels, oils and fats.

- SITC 5: Chemicals, dyes, pharmaceuticals, and perfumes.

- SITC 6: Leather, rubber, cork and wood products, textiles, metallic and non-metallic manufactures.

- SITC 7: Industrial machinery, office machinery, telecommunications equipment, electrical machinery, transportation equipment.

- SITC 8: Prefabricated buildings, furniture, travel goods, clothing, footwear, professional and scientific equipment.

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**Figure 2: The Reallocation of Manufacturing Exports Across Major Two-digit Sectors***

<!-- Start of picture text --> Apparel Textiles Misc. Man. Footwear Electric. Machinery Metals Telecom Machinery Office Macnines<br>(SITC 84) (SITC 65) (SITC 89) (SITC 85) (SITC 77) (SITC 69) (SITC 76) (SITC 74) (SITC 75)<br>1992 2005<br>.3<br>.2<br>Share of Total Exports<br>.1<br>0<br><!-- End of picture text -->

* A sector is defined as major if the sector’s share of total trade is above 3% in 1992 and/or 2005.  These sectors account for about 70 percent of manufacturing exports.

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# **Figure 3: Machinery Exports and Processing Trade**

<!-- Start of picture text --> Telecom Electric Office Machinery Road Vehicles Power Gen. Specialized Transport Metalworking<br>(SITC 76) (SITC 77) (SITC 75) (SITC 74) (SITC 78) (SITC 71) (SITC 72) (SITC 79) (SITC 73)<br>2005 - All Exports 2005 - Processing Exports<br>.15<br>.1<br>Share of Total Exports<br>.05<br>0<br><!-- End of picture text -->

# Note: Column headings include the following industries:

- SITC 71: Boilers, turbines, internal combustion engines, and power generating machinery. SITC 72: Agricultural machinery, civil engineering and contractors’ equipment, printing and bookbinding machinery, and textile and leather machinery.

- SITC 73: Lathes, machines for finishing and polishing metal, soldering equipment, metal forging equipment, and metal foundry equipment.

- SITC 74: Heating and cooling equipment, pumps, ball bearings, valves for pipes, and nonelectrical machines.

- SITC 75: Typewriters, photocopiers, and data processing machines.

- SITC 76: Television receivers, radio receivers, and sound recorders.

- SITC 77: Equipment for distributing electricity, electro-diagnostic apparatus, and semiconductors.

SITC 78: Automobiles, trucks, trailers, and motorcycles.

SITC 79: Railroad equipment, aircraft, ships, boats, and floating structures.

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# **Figure 4: Skill Intensity of China’s Manufacturing Exports**

<!-- Start of picture text --> 0 .2 .4 .6 .8 1<br>Skill Intensity<br>Cumulative Export Share, 1992<br>Cumulative Export Share, 2005<br>Note: Data uses HS 6-digit classifications. The skill intensity is measured as the ratio<br>of non-production workers to total employment from the Indonesian manufacturing census<br>at the 5 digit ISIC level for 1992.<br>100<br>80<br>60<br>40<br>Cumulative Export share 20<br>0<br><!-- End of picture text -->

# **Figure 5: Skill Intensity of China’s Manufacturing Exports Excluding Processing Trade**

<!-- Start of picture text --> 0 .2 .4 .6 .8 1<br>Skill Intensity<br>Cumulative Export Share, 1992<br>Cumulative Export Share, 2005<br>Note: Data uses HS 6-digit classifications. The skill intensity is measured as the ratio<br>of non-production workers to total employment from the Indonesian manufacturing census<br>at the 5 digit ISIC level for 1992.<br>100<br>80<br>60<br>40<br>20<br>Cumulative Export share - np<br>0<br><!-- End of picture text --> 22
# **Figure 6: Cumulative Import Share and Skill Intensity Processing Trade**

<!-- Start of picture text --> 0 .2 .4 .6 .8 1<br>Skill Intensity<br>Cumulative Import Share , 1992<br>Cumulative Import Share, 2005<br>Note: Data uses HS 6-digit classifications. The skill intensity is measured as the ratio<br>of non-production workers to total employment for US 4 digit SIC industries in 1992.<br>100<br>80<br>60<br>40<br>Cumulative Import share 20<br>0<br><!-- End of picture text -->

**Figure 7: Cumulative Import Share and Skill Intensity Non-Processing Trade**

<!-- Start of picture text --> 0 .2 .4 .6 .8 1<br>Skill Intensity<br>Cumulative Import Share , 1992<br>Cumulative Import Share, 2005<br>Note: Data uses HS 6-digit classifications. The skill intensity is measured as the ratio<br>of non-production workers to total employment for US 4 digit SIC industries in 1992.<br>100<br>80<br>60<br>40<br>Cumulative Import share 20<br>0<br><!-- End of picture text --> 23
**Figure 8: Cumulative Share of Exports by Rank**

<!-- Start of picture text --> 0 1000 2000 3000 4000 5000<br>Rank of Product<br>Cumulative share of trade, 1992<br>Cumulative share of trade, 2005<br>Note: Data uses HS 6-digit classifications. Rank is largest to smallest by value.<br>100<br>80<br>60<br>40<br>Cululative Share of Trade 20<br>0<br><!-- End of picture text -->

**Figure 9: Cumulative Share of Exports by Rank, Top 500 Products**

<!-- Start of picture text --> 0 100 200 300 400 500<br>Rank of Product<br>Cumulative share of trade, 1992<br>Cumulative share of trade, 2005<br>Note: Data uses HS 6-digit classifications. Rank is largest to smallest by value.<br>100<br>80<br>60<br>40<br>Cululative Share of Trade<br>20<br><!-- End of picture text --> 24
**Figure 10: Reallocation of Exports by Value**

<!-- Start of picture text --> 1 2 3 4 5 6 7 8 9 10<br>Decile by value, 1992<br>Note: Data uses HS 6-digit classifications.<br>.25<br>.2<br>.15<br>.1<br>Share of total value in 2005<br>.05<br>0<br><!-- End of picture text -->

**Figure 11: Reallocation of Exports by Product Shares**

<!-- Start of picture text --> 1 2 3 4 5 6 7 8 9 10<br>Decile by number of products, 1992<br>Share of total value, 1992<br>Share of total value, 2005<br>Note: Data uses HS 6-digit classifications.<br>.8<br>.6<br>.4<br>Share of total value<br>.2<br>0<br><!-- End of picture text --> 25
# **Figure 12: Growth in Extensive Margin of US Imports from China, 1992-2005**

<!-- Start of picture text --> 50<br>40<br>30<br>20<br>10<br>0<br>-10<br>-20<br>-30<br>-40<br>1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005<br>Feenstra index of net variety<br>Extensive margin share of export growth<br>Percent<br><!-- End of picture text --> Note: HS 10-digit US imports from China.

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