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2021 | OriginalPaper | Buchkapitel

3. Exports, Productivity, and Credit Constraints

verfasst von : Miaojie Yu

Erschienen in: Exchange Rate, Credit Constraints and China’s International Trade

Verlag: Springer Singapore

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Abstract

Recent Melitz-type (2003) intra-industry heterogenous trade models argue that a firm’s productivity has significant effects on the firm’s exports. This chapter examines how a firm’s credit constraints as well as its productivity affect its export decisions. We imbed the firm’s credit constraints into a Melitz-type general-equilibrium model by endogenizing the probability of the success of firm-specific projects. We show that, all else equal, it is easier for firms to enter the export market if (1) the probability of the success of their project is higher and consequently they have easier access to external finance from financial intermediaries; or (2) they have alternative sources, other than from financial intermediaries, to obtain funds. We test these theoretical hypotheses using firm-level data from Chinese manufacturing industries and find strong evidence supporting the predictions of the model.

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Vorheriges Kapitel Revaluation of the Chinese Yuan and Triad Trade: A Gravity Assessment

Nächstes Kapitel Exports and Credit Constraints under Incomplete Information

Nur mit Berechtigung zugänglich

Héricourt and Poncet (2009) show that inward foreign direct investment in China plays an important role in alleviating the domestic firms’ credit constraints. Similar evidence is provided by Harrison and McMillan (2003) using data from the Ivory Coast.

For example, setting up a distribution network in foreign country requires foreign labor.

The assumption that the probability of success is a function of productivity is only for the sake of theoretical simplicity. In reality, the probability of success of a project might be related to other variables.

An implicit assumption is that a firm’s productivity leads to exports. That is, good firms export, which is a common assumption for all Melitz-type (2003) models.

Notice that exporting firms sell in the foreign market and thus the foreign price level (P^∗), rather than the domestic price level, is present in the solutions.

See the Appendix for details.

See the Appendix.

Of course, in reality, a firm’s capability of raising funds externally may be affected by other factors such as automatic customer insolvency, bad debts, overdue accounts, commercial risks, and even political risks. However, the key lesson is that firms that are capable of obtaining external loans will be able to export.

This setup also enjoys an extra advantage that we do not need to worry about the reverse causality of exports and productivity in the estimations.

Indeed, aggregated data on the industrial sector in the annual China’s Statistical Yearbook by the Natural Bureau of Statistics (NBS) are compiled from this data set.

Following Levinsohn and Petrin (2003), plants were treated as firms. In this chapter, we do not capture scope economics due to their multi-plant nature. This remains a topic for future research.

Holz (2004) offers careful scrutiny on possible measurement problems in Chinese data, especially on the aggregated level.

Levinsohn and Petrin (2003) suggest covering all Chilean plants with at least 10 workers. Here, we follow their criterion.

Specifically, FIEs include the following firms: foreign-invested joint-stock corporations (code: 310), foreign-invested joint venture enterprises (320), fully foreign-invested enterprise (330), foreign-invested limited corporations (340), H/M/T/ joint-stock corporations (code: 210), H/M/T joint venture enterprises (220), fully H/M/T-invested enterprises (230), and H/M/T-invested limited corporations (340).

By definition, SOEs include firms such as domestic SOEs (code: 110); state-owned joint venture enterprises (141); state-owned and collective joint venture enterprises (143); and state-owned limited corporations.

Including small- and medium-sized SOEs whose scales are lower than the threshold would increase our sample to 1,401,569, which accounts for around 73.8% of the original size of the data set.

Firm data before 2002 were clustered into industrial data by adopting the old industrial classification. We concord such data so that they are consistent with data after 2002.

The five industries dropped include extraction of petroleum and natural gas (7), mining of other ores (11), processing of food from agricultural products (12), and recycling and disposal of waste (43).

Chinese yuan was revalued against the US dollar by around 20% during 2005–2007.

The IV approach is a good way to control for endogeneity issues. Wooldridge (2002, Chapter 5) provided a careful scrutiny of this topic.

For robustness, we construct an alternative indicator using a firm scale, relative to the total economy, as a weight of the monetary supply. The results are similar.

One may worry that monetary expansion might not affect the external financing of small-sized firms in China, because they might not have any access to formal financial intermediaries whatsoever. However, this is not a severe problem for two reasons. First, monetary expansion stimulates investments from informal financial intermediaries as well. Small-sized firms would have easier external financing from these intermediaries following a monetary expansion. Second, all observation used in the default sample are “above-scale” firms, which usually have access to formal financial intermediaries. We will include small- and medium-sized firms later for robustness check.

The reason for using industrial weight and not national weight (l_it − 1/∑_il_it − 1) is that, in China, the competition to borrow from banks is usually stronger in the same industry. However, using a national weight to construct the IV also delivers very similar findings, which are not reported here to save space but available upon request.

Note that the Cragg and Donald (1993) F-statistic is no longer valid since it only works under the i.i.d. assumption.

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Titel: Exports, Productivity, and Credit Constraints
verfasst von: Miaojie Yu
Verlag: Springer Singapore
Buch: Exchange Rate, Credit Constraints and China’s International Trade
Print ISBN: 978-981-15-7521-1

Electronic ISBN: 978-981-15-7522-8

Copyright-Jahr: 2021
DOI: https://doi.org/10.1007/978-981-15-7522-8_3