Category Archives: Firms

What share of US manufacturing firms export?

What share of US manufacturing firms export? That’s a simple question. But my answer recently changed by quite a lot. While updating one of my class slides that is titled “very few firms export”, I noticed a pretty stark contrast between the old and new statistics I was displaying. In the table below, the 2002 numbers are from Table 2 of Bernard, Jensen, Redding, and Schott (JEP 2007), which reports that 18% of US manufacturing firms were exporters in 2002. The 2007 numbers are from Table 1 of Bernard, Jensen, Redding, and Schott (JEL 2018), which reports that 35% of US manufacturing firms were exporters in 2007.

NAICS Description Share of firms Exporting firm share Export sales share of exporters
2002 2007 2002 2007 2002 2007
311 Food Manufacturing 6.8 6.8 12 23 15 21
312 Beverage and Tobacco Product 0.7 0.9 23 30 7 30
313 Textile Mills 1.0 0.8 25 57 13 39
314 Textile Product Mills 1.9 2.7 12 19 12 12
315 Apparel Manufacturing 3.2 3.6 8 22 14 16
316 Leather and Allied Product 0.4 0.3 24 56 13 19
321 Wood Product Manufacturing 5.5 4.8 8 21 19 09
322 Paper Manufacturing 1.4 1.5 24 48 9 06
323 Printing and Related Support 11.9 11.1 5 15 14 10
324 Petroleum and Coal Products 0.4 0.5 18 34 12 13
325 Chemical Manufacturing 3.1 3.3 36 65 14 23
326 Plastics and Rubber Products 4.4 3.9 28 59 10 11
327 Nonmetallic Mineral Product 4.0 4.3 9 19 12 09
331 Primary Metal Manufacturing 1.5 1.5 30 58 10 31
332 Fabricated Metal Product 19.9 20.6 14 30 12 09
333 Machinery Manufacturing 9.0 8.7 33 61 16 15
334 Computer and Electronic Product 4.5 3.9 38 75 21 28
335 Electrical Equipment, Appliance 1.7 1.7 38 70 13 47
336 Transportation Equipment 3.4 3.4 28 57 13 16
337 Furniture and Related Product 6.4 6.5 7 16 10 14
339 Miscellaneous Manufacturing 9.1 9.3 2 32 15 16
Aggregate manufacturing 100 100 18 35 14 17

 

Did a huge shift occur between 2002 and 2007? No. The difference between these two tables is due to a change in the data source used to identify whether a firm exports. In their 2007 JEP article, BJRS used a question about export sales in the Census of Manufactures (CM). In their 2018 JEL article, BJRS used customs records from the Longitudinal Firm Trade Transactions database (LFTTD) that they built. Footnote 23 of the latter article notes that “the customs records from LFTTD imply that exporting is more prevalent than would be concluded based on the export question in the Census of Manufactures.”

This is a bit of an understatement: only about half of firms that export in customs records say that they export when asked about it in the Census of Manufactures! [This comparison is inexact because the share of exporting firms may have really increased from 2002 to 2007, but BJRS (2018) say that they “find a relatively similar pattern of results for 2007 as for 2002” when they use the CM question for both years.] The typical three-digit NAICS industry has the share of firms that export roughly double when using customs data rather than the Census of Manufactures survey response. Who knows what happened in “Miscellaneous Manufacturing” (NAICS 339), which had 2% in the 2002 CM and 35% in the 2007 LFTTD.

I presume that the customs records are more reliable than the CM question. More firms are exporters than I previously thought!

Melitz and Redding on heterogeneous firms and gains from trade

In a recent VoxEU column, Marc Melitz and Stephen Redding describe the logic of Melitz (Ecma, 2003) and Arkolakis, Costinot, and Rodriguez-Clare (AER, 2012). Those should be familiar to Trade Diversion readers (e.g. ACR 2010 wp, Ossa 2012 wp). They then explain their new paper:

In Melitz and Redding (2013b), we show that firm-level responses to trade that generate higher productivity do in fact represent a new source of gains from trade.

  • We start with a model with heterogeneous firms, then compare it to a variant where we eliminate firm differences in productivity while keeping overall industry productivity constant.

We also keep all other model parameters (such as those governing trade costs and demand conditions) constant.

  • This ‘straw man’ model has no reallocations across firms as a result of trade and hence features no productivity response to trade.

Yet it is constructed so as to deliver the same welfare prior to trade liberalisation. We then show that, for any given reduction in trade costs, the model with firm heterogeneity generates higher aggregate welfare gains from trade because it features an additional adjustment margin (the productivity response to trade via reallocations). We also show that these differences are quantitatively substantial, representing up to a few percentage points of GDP. We thus conclude that firm-level responses to trade and the associated productivity changes have important consequences for the aggregate welfare gains from trade.

How can these findings be reconciled with the results obtained by Arkolakis, Costinot, and Rodriguez-Clare (2012)? Their approach compares models that are calibrated to deliver the same domestic trade share and trade elasticity (the sensitivity of aggregate trade to changes in trade costs). In so doing, this approach implicitly makes different assumptions about demand and trade costs conditions across the models that are under comparison (Simonovska and Waugh 2012). By assuming different levels of product differentiation across the models, and assuming different levels of trade costs, it is possible to have the different models predict the same gains from trade – even though they feature different firm-level responses. In contrast, our approach keeps all these ‘structural’ demand and cost conditions constant, and changes only the degree of firm heterogeneity (Melitz and Redding 2013b). This leads to different predictions for the welfare gains from trade.

One potential criticism of our approach is that one can estimate the trade elasticity (the sensitivity of aggregate trade to changes in trade costs) using aggregate trade data only – without requiring any specific assumptions about the firm-level responses to trade. Whatever assumptions are made about those firm-level responses (and the demand and trade-cost conditions), they should then be constructed so as to match that estimated aggregate elasticity. However, recent empirical work has shown that those underlying assumptions radically affect the measurement of the aggregate trade elasticity, and that this trade elasticity varies widely across sectors, countries, and the nature of the change in trade costs (see for example Helpman et al. 2008, Ossa 2012, and Simonovska and Waugh 2012). There is thus no single empirical trade-elasticity parameter that can be held constant across those different models.

Given the lack of a touchstone set of elasticities, we favour our approach to measuring the gains from trade arising from different models; one that maintains the same assumptions about demand and trade costs conditions across those models.

The Chinese government didn’t allocate its MFA quotas efficiently

Amit Khandelwal, Pete Schott, and Shang-Jin Wei have a nice VoxEU column describing their forthcoming AER article on Chinese textile exports under the Multifibre Arrangementquotas. In short, inefficiently implemented policy can substantially amplify the economic distortions introduced by trade barriers:

If trade barriers are managed by inefficient institutions, trade liberalization can lead to greater-than-expected gains. We examine Chinese textile and clothing exports before and after the elimination of externally imposed export quotas. Both the surge in export volume and the decline in export prices following quota removal are driven by net entry. This outcome is inconsistent with a model in which quotas are allocated based on firm productivity, implying misallocation of resources. Removing this misallocation accounts for a substantial share of the overall gain in productivity associated with quota removal.

Melitz & Trefler – Gains from Trade when Firms Matter (JEP 2012)

The Spring 2012 JEP has a symposium on international trade. I already mentioned the great article on the Ricardian model by Eaton and Kortum. Another very nice contribution to the symposium is a piece by Marc Melitz and Daniel Trefler on the “Gains from Trade when Firms Matter” (pdf).

Today, we focus on three sources of gains from trade: 1) love- of-variety gains associated with intra-industry trade; 2) allocative efficiency gains associated with shifting labor and capital out of small, less-productive firms and into large, more-productive firms; and 3) productive efficiency gains associated with trade-induced innovation.

This survey distills a very large body of literature. It belongs on your syllabi.

Peru’s “Easy Export” program

Here’s how the World Development Report 2009 summarized a Peruvian trade-facilitation project:

BOX 8.9 Exporting by mail in Peru—connecting small producers to markets

In many countries small enterprises are often excluded from export chains because they operate in villages or small towns or do not have the needed information to export. In Peru a trade-facilitation program called “Easy Export” connects small producers to markets. The key to this program is the most basic of transport networks—the national postal service.

How does it work? An individual or firm takes a package to the nearest post office, which provides free packaging. The sender fills out an export declaration form, and the post office weighs the package and scans the export declaration form. The sender pays the fee for the type of service desired. Goods with values of $2,000 or less can be exported. The main benefit is that the exporter does not need to use a customs agent, logistics agent, or freight forwarder or to consolidate the merchandise; even the packaging is provided. Firms or individuals need only to go to a post office with a scale and a paper scanner and to use the Internet to complete the export declaration for the tax agency.

Has it made a difference? Within six months of inception, more than 300 firms shipped goods totaling more than $300,000. Most users are new exporters—microentrepreneurs and small firms, producing jewelry, alpaca and cotton garments, food supplements (natural products), cosmetics, wood art and crafts, shoes and leather, and processed food. And many of them are in the poorest areas of the country.

Export pioneers

In a NBER working paper, Artopoulos, Friel, and Hallak describe how firms in Argentina learned to successfully export to high-income markets:

Several developing countries feature weak performances as exporters of differentiated goods to developed countries. This paper builds a conceptual framework to explain the obstacles that prevent producers of differentiated products from establishing a consistent presence in the developed world and the process through which those obstacles may be overcome. We build our framework based on case studies of export emergence in four Argentine industries: motorboats, television programs, wines, and wooden furniture. We find that exporting consistently to developed countries requires drastic changes in how business is conceived and conducted relative to the practices that prevail among domestically-oriented firms. Attempts by these firms to export often do not succeed because they approach foreign markets the same way that they approach the domestic one. Their failure to change the business approach stems from their inability to access critical (tacit) knowledge about differences in consumption patterns and business practices in developed countries. In three of the sectors we study, an export pioneer is the first to implement the necessary changes to established practices. His actions set a benchmark, unleashing a diffusion process that fosters export emergence in the sector. The most salient feature of export pioneers is their knowledge advantage about foreign markets stemming from their embeddedness in the business community of their industry in a developed country.

Surveying the Asian noodle bowl

An ADB report summarizes surveys of firms about their preference utilization under Asian PTAs:

ADB conducted firm-level surveys in six countries, the results of which are published in the book Asia’s Free Trade Agreements: How is Business Responding? Experts in the region looked at the issues using firm surveys in Japan, China, Korea, Singapore, Thailand and the Philippines.

This book asks four important questions concerning the spread of FTAs and the Asian noodle bowl: Are FTA preferences being used by firms? What are their costs and benefits? Are multiple ROOs a burden to business? Is there enough business support for firms to use FTAs?

[HT: LWS]

Matched transaction-level trade data

An interesting line of ongoing research pairs transaction-level trade data across countries to provide detailed descriptions of importers, exporters, and their transactional relations. Eaton, Eslava, Krizan, Kugler, and Tybout (in a project titled “A Search and Learning Model of Export Dynamics”, there are various versions, here’s May 2010) have combined 13 years of Colombian export data with US import data, generating many new interesting findings about buyer-seller matches (e.g. “Roughly 80 percent of matches are monogamous in the sense that the buyer deals with only one Colombian exporter and the exporter ships to only one buyer in the United States”). Blum, Claro, and Horstmann have used the other side of the Colombian trade data, studying Chilean-exporter-Colombian-importer pairs. There are also theoretical predictions about international transactional matching that could be tested using such paired data.

In short, this is an exciting new avenue in trade empirics.

Trade-induced learning

The review of trade-induced learning on pages F324 to F332 of this new article by Ronald Mendoza seems like a pretty good introduction to the topic. He covers the empirical literature on firm-level productivity (selection vs learning by exporting), the roles of quality and variety in importing and exporting, the importance of export destinations’ characteristics, and the product space. As with any survey, you’ll have to turn to the underlying papers to get into the methodological issues and strategies.

[HT: Jim]