The impact of Chinese technical barriers to trade on its manufacturing imports when exporters are heterogeneous


In the past few decades, China has put substantial efforts into liberalising its trade and economy that accelerated after its accession to the World Trade Organisation (WTO) in December 2001. In this period, China has significantly reduced its tariffs on manufacturing imports. However, the proliferation of non-tariff measures imposed by China has made it the country notifying the second largest number of technical barriers to trade (TBTs) to the WTO after the USA. Nevertheless, there has been no case in the dispute settlement mechanism of the WTO against China violating the TBT agreement. This paper investigates the heterogeneous impact of Chinese TBTs on the imports of manufacturing products at the 6-digit level of the Harmonised System during 2002–2015. Heterogeneity of exporting firms, sample selection bias, multilateral resistances, and endogeneity bias are controlled for according to the recent strands of gravity modelling. Using the disaggregated data and controlling for these problematic issues in the estimations, paper finds no significantly overall impact of Chinese TBT on imports in comparison with earlier studies in the literature. However, the impact differentiated across exporting countries hints at prohibitive effects against few exporters. The impact on traded prices and quantities provide more insights on how these TBTs affect different exporters. The imposed standards and regulations embedded in these trade policy measures allowed the Chinese economy to gain better access to larger exporters from the more developed economies who could easily comply with TBTs without increasing prices but substituting those exporters who did not comply with TBTs, leading to an overall insignificant net impact on imports values to China.

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Fig. 1

Source: Author’s calculation, UN Comtrade

Fig. 2

Source: Author’s calculation, UN Comtrade, TRAINS, WTO IDB

Fig. 3

Source: Author’s calculations, I-TIP, Comtrade

Disclosure of data and computer code availability

The data that support the findings of this study are available from various sources elaborated in Sect. 3.3. Instructions for how other researchers can obtain the data, and all the information needed to proceed from the raw data to the results of the paper (including code) are, however, available from the author upon reasonable.


  1. 1.

    In another study by Bao and Qiu (2012), they use total number of TBTs, which does not suffer from the aforementioned measurement error as their applied TBT measure is not product-specific but rather a total number of applied TBT by each WTO member. However, their analysis covers bilateral aggregate trade flows across more than one hundred countries globally while this paper is focused on only China’s imports differentiated by exporting countries, which requires another methodology and data.

  2. 2.

    Refer to Head and Mayer (2014) for a detailed discussion on gravity modelling.

  3. 3.

    Baltagi et al. (2003) use the distance of relative factor endowment in absolute terms, which omits the important information whether the trading partner has higher or lower factor endowments relative to China. Moreover, using the absolute terms gives inconsistent estimates of some variables. For instance, the coefficient of tariffs becomes positive or the coefficient of the summation of GDP becomes negative when absolute terms are included. The estimation results including the distance of relative factor endowments in absolute terms are available upon request.

  4. 4.

    The reason to opt for this methodology of controlling for zero trade flows instead of Poisson estimation is that the instrumental variable generalised method of moments (GMM) would not be feasible using Poisson regression. However, the empirical strategy used here is based on the econometrics model proposed by Semykina and Wooldridge (2010), which was also used in other empirical studies on trade flows such as that by Kee et al. (2008) and Essaji (2008).

  5. 5.

    IMR is the ratio of the probability density function to the cumulative distribution function of the estimated probability of exports.

  6. 6.

    Another source of endogeneity bias is the measurement error in the main explanatory variable. As shortly explained before, coverage ratio (CR) and frequency index (FI) of TBTs could suffer from these measurement errors, as a prohibitive TBT halting trade would be excluded from the explanatory variable. However, running a similar specification as that in Bao and Qiu (2010) with both CR and FI of Chinese TBT at the HS 2-digit level would give similar results to the results presented here, i.e. positive impact of Chinese TBT on manufacturing imports. Those robustness checks are presented upon request.

  7. 7.

  8. 8.

    Classification on economic development of countries is borrowed from Upadhyaya (2013).

  9. 9.

    However, if model M2 is used for this purpose, Korean and Malaysian exports values are also positively and statistically significantly associated with Chinese TBTs.


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I am obliged to two anonymous referees and the coordinating editor of the journal of Empirical Economics, Robert M. Kunst and to my colleague Robert Stehrer (wiiw) for their reviews and constructive comments to the work. Thanks should also go to the participants of the 10th FIW Research Conference on International Economics in Vienna, and the participants of the workshop at the Institute for Management and Planning Studies in Tehran (

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Correspondence to Mahdi Ghodsi.

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Ghodsi, M. The impact of Chinese technical barriers to trade on its manufacturing imports when exporters are heterogeneous. Empir Econ 59, 1667–1698 (2020).

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  • World Trade Organisation
  • Trade liberalisation
  • Trade policy
  • Technical barriers to trade

JEL Classification

  • F13
  • F14