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Lower prices or higher quality? Firms’ response to increased competition following trade liberalization

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Abstract

This paper investigates the impact of increased competition at the product-market level on firms’ strategic price decisions. We analyse this issue in a context of trade liberalization where only some firms benefit from the input tariff cuts. We focus on China which is characterized by a unique dual trade regime, where some imports of intermediate goods are subject to tariff (i.e., the ordinary status) whereas other (i.e., the processing status) have been exempted of tariffs for the last 30 years. The recent Chinese trade liberalization allowed ordinary importers to improve their competitiveness relative to processing firms. Facing stronger pressures in their export markets, processing firms must adjust their strategy. We find that ordinary firms took advantage of the Chinese’ input trade liberalization to improve the quality of their exported products and processing firms respond to this quality sorting by decreasing their export prices and markups. This finding is more pronounced for lower-end product sold in in advanced economies, where the quality sorting of competitors is more relevant.

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Fig. 1
Fig. 2
Fig. 3

Source Bas and Strauss-Kahn (2015) using unweighted average tariff rates from WITS

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Notes

  1. Note that the Chinese WTO accession may affect processing firms in many ways (e.g., availability and price of inputs, change in trade and competition policy abroad). Such changes would however be common to ordinary and processing firms. We account for this global changes by including product-destination-year fixed effects in the main specification.

  2. De Loecker et al., 2016 for India, Brandt and Morrow, 2017 and Lu and Linhui, 2015 for China and Bas and Paunov, 2021a for Ecuador show evidence of markups adjustment while (Fernandes and Paunov, 2013; Amiti and Khandelwal, 2013; Iacovone, 2012) and Bas and Paunov, 2021a find quality upgrading.

  3. Of course, higher input quality increases unit costs (as in the models of Verhoogen (2008) and Kugler and Verhoogen (2012).

  4. De Loecker et al., 2016; Brandt et al., 2019; Lu and Linhui, 2015 and Fan et al., 2018 show that firms increase markups with input tariff cuts.

  5. Data will be further details in Sect. 4.1.

  6. Recall that in all our empirical analysis, we keep firms that import all their intermediate inputs through one trade regime only over the full period, that is, we exclude switchers.

  7. In Figs. 1 and 2, outliers at the top and bottom 1st percentiles are excluded from the database. Alternative trimming and no trimming at all provide similar results, which are available upon request.

  8. t-tests confirm the significant differences in averages within processing firms export prices and within ordinary export prices and product quality between 2000 and 2006.

  9. The tariff data that support the findings of this study are openly available in WITS at https://wits.worldbank.org. The Chinese transaction data are proprietary. They could be purchased from the General Administration of Customs of China. They have been used in several recent papers (e.g., Manova and Zhang 2012). A transformed version of the data could be made available from the corresponding author upon reasonable request.

  10. Within HS6 codes, HS8 products may be measured in different units (e.g., kilograms or meters). In order to avoid measurement errors, we drop HS8 products that differ in units from the rest of the HS6 category (i.e., less than 0.77% of the sample). Finally, as the HS classification changed over time, we convert older classifications (i.e., HS1-1996 and HS2-2002) into HS0-1988/1992 classification using WITS conversion tables.

  11. The distinction between these two regimes of processing trade relies on whether the firm has to cover foreign exchange payments (in “processing and assembly trade”, the imported materials and parts are supplied by the foreign party. The Chinese processing firm only charges the foreign party a processing fee). This distinction is not relevant for our analysis, we thus consider both processing regimes.

  12. Ordinary and processing trade represent 76% (96%) of total manufacturing imports (exports) on average over the period. Note that the processing trade regime is distinct from the “warehousing trade” and “entrepot trade” regimes. We exclude from our sample intermediary firms as defined in Ahn et al. (2011): Firms that include in their name Chinese characters with English-equivalent meaning of importer, exporter, and trading are considered intermediary.

  13. Processing firm must show proofs of a contractual agreement with a foreign buyer to whom it will export the good in order to obtain the exemption on input tariffs.

  14. The database used in this paper is similar to the one of Bas and Strauss-Kahn (2015). We refer the reader to this paper for a detailed presentation of the data and the Chinese custom regimes.

  15. Previous studies (e.g., Schor, 2004; Goldberg et al., 2010; Topalova and Khandelwal, 2011) used Input–Output (IO) tables in order to compute firm-level input tariff measures. Such tariffs are constructed using aggregate data (IO tables are not usually more disaggregated than the HS3 level) and generate industry-level input tariffs which are then matched to the firm’s sector of activity. In this paper, as in Bas and Strauss-Kahn, 2015, tariffs are generated from the firm’s effective use of a specific imported input, we thus obtain a more precise measure of input tariffs computed at the firm level. All our results are robust to the use of IO tariffs. The results of this alternative measure of input tariffs are available upon request.

  16. The average input tariff decreased by 16.2% between 2002 and 2003, and by 19.8% between 2003 and 2004.

  17. Results in this paper use the average of input tariffs. Other weights, accounting for firms size, have been considered. Results are unchanged and are available upon requests.

  18. In Sect. 6, we present a robustness tests using export prices of ordinary firms competing with processing firms in the same product-market, instrumented by this input tariff faced by ordinary firms, as explanatory variables.

  19. The NBSC collects yearly data from all state-owned firms as well as from firms with other ownership types and annual sales above 5 million RMB. The database includes about 163,000 firms for 2000 and accounts for 95% of total industrial output value. In order to compile our database, we rely on firm’s name and address which are reported both in the (CCTS) custom-transaction and the (NBSC) firm-level databases.

  20. Note that tariffs in 2000 might be extremely high reaching 90% to 120% in agricultural products or certain categories of Motors cars and other vehicles or 57.5% for Natural Rubber.

  21. In order to account for the multi-product aspect of the firms, we also computed similar shares defining a firm’s main export sector at the HS4 and HS3 levels. The figures obtained are similar to the ones presented here.

  22. The decrease in Chinese output tariffs raises the competitive pressure on domestic producers but has no direct effect on competition abroad (i.e., it should not directly affect export prices). In contrast, a change in foreign market trade and competition policy would affect ordinary and processing firms’ prices. In Sect. 6.2, we verify that our results are robust to the inclusion of export markets output tariffs and imports from others countries in the estimation.

  23. Using Khandelwal et al. (2013)’s measure of quality, as explained in Sect. 5.2, we confirm that imported input quality depends on the country of origin. The average quality of products sourced in developed economies (DC) is 60 percent higher than the average quality of products sourced in developing economies (LDC).

  24. Increased import competition due to output tariff cuts (i.e., the pro-competitive effect) may also result in higher ordinary prices and measured quality (see for e.g., Brandt and Morrow (2017)). This is controlled for by our destination market-HS6-year fixed effect. Our specification captures the impact of input tariffs cuts on prices and thus confirms (as in Bas and Strauss-Kahn (2015)) the sourcing effect.

  25. The country-time fixed effect \(\gamma _{ct}\) controls for price index and income at destination, while the product fixed effect \(\gamma _{k}\) controls for variation across products.

  26. Note that observations are reduced relative to the baseline sample due to the lack of values of the elasticity of substitution for some sectors. Moreover, the quality estimation is done by sector for those HS2 sectors with more than 700 observations.

  27. Manova and Yu (2017) indeed shows that in case of quality sorting firms sell at higher prices both because of higher marginal cost (higher priced quality inputs) and bigger markups.

  28. Note that destination country-HS6-year fixed effects cannot be added to this specification as they would be fully collinear with the tariff computed for processing firms, which captures ordinary firm competitiveness and varies at the product-destination market-year level.

  29. Foreign imports data are constructed using the BACI database developed by the CEPII. BACI provides data on bilateral trade flows for 200 countries at the HS6 product level (see Gaulier and Zignago 2010).

  30. The sample size is reduced in columns (3) and (4) since output tariffs in destination markets at the HS6 level are not available for all destination countries of our database.

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Authors and Affiliations

  1. University of Paris 1 and CES, Paris, France

    Maria Bas

  2. ESCP Business School, 79 av de la Republique, 75011, Paris, France

    Vanessa Strauss-Kahn

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  1. Maria Bas
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  2. Vanessa Strauss-Kahn
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Correspondence to Vanessa Strauss-Kahn.

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All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript. Financial support was received from ESCP Business School in order to aquire the data.

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We have benefited from discussions in previous version of the paper with Celine Carrere, Matthieu Crozet, Swati Dhingra, Juan Carlos Hallak, Sebastien Jean, Philippe Martin, Thierry Mayer, Florian Mayneris, John Morrow, Sandra Poncet and Frederic Warzynski. We are responsible for any remaining errors.

Appendix

Appendix

The left panel of Fig. 4 shows that HS6 products with the highest initial tariffs experienced the highest reduction over the period while the right panel displays the decrease in HS6-tariffs mean and standard deviation over the 2000–2006 period (See Table 11).

Fig. 4
figure 4

Source Bas and Strauss-Kahn (2015). Author’s calculation using unweighted average tariff rates from WITS at hs6 level. The left panel presents tariffs change between 2000 and 2006 relative to initial tariffs in 2000 at the hs6 product level. The right panel reports the evolution of the mean and standard deviation of hs6 tariffs over the period

Tariff changes between 2000 and 2006.

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Table 11 Descriptive evidence of the sample (average over the period 2000-2006)
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Bas, M., Strauss-Kahn, V. Lower prices or higher quality? Firms’ response to increased competition following trade liberalization. Rev World Econ (2023). https://doi.org/10.1007/s10290-023-00503-7

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