Table 6: The effect of NTMS on prices, quality and quality adjusted prices

||All sec|tors||Agricult|ure||Manufa|cturing||
|---|---|---|---|---|---|---|---|---|---|
|_Outcome:_|UV|Qual|QAP|UV|Qual|QAP|UV|Qual|QAP|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|
|log _NTMpcdt_|_−_0.020|_−_0.007|_−_0.013|_−_0.076<sup>_∗∗∗_</sup>|0.010|_−_0.086<sup>_∗∗∗_</sup>|0.044|_−_0.054|0.098<sup>_∗_</sup>|
||(0.017)|(0.017)|(0.021)|(0.027)|(0.022)|(0.030)|(0.043)|(0.049)|(0.051)|
|log _Tari f fpcdt_|0.003|_−_0.005|0.007|_−_0.010|0.005|_−_0.016|0.008|_−_0.010|0.018<sup>_∗_</sup>|
||(0.006)|(0.006)|(0.007)|(0.009)|(0.008)|(0.011)|(0.007)|(0.009)|(0.009)|
|Observations<br>|69,701|69,701|69,701|31,555|31,555|31,555|38,013|38,013|38,013|
|Adjusted _R_<sup>2</sup>|0.823|0.312|0.825|0.834|0.250|0.814|0.816|0.336|0.838|

Notes: The dependent variable is the product _p_ imports of firm _f_ from origin _o_ in year _t_ . _p_ values are in parentheses. ***, ** and * denote significance at 1%, 5%, and 10%. Intercepts included but not reported. Standard errors are clustered at the firm-product-year level.

also sector such as fish and fish products, and fruits and vegetables. We define a firm’s initial product quality as the estimated quality of the product that the firm exported to a particular destination in the first year of exporting to that destination within the sample period. We then use the median of the quality distribution as a breakpoint to define two groups of high- and low-quality products. We consider products _≤_ to the median quality value as low quality. These products display very little product differentiation. Products _>_ the median quality value displays a lot of vertical product differentiation and fall into the high-quality product category. We then introduce an interaction term of high initial product quality ( _PQipcd_ ) and the NTM variable into our baseline specification. The findings are reported in Table 7. We find that initial product quality moderates the trade-reducing effects of NTMs. Specifically, our findings reveal that the trade-reducing effect of NTMs at the intensive margin is reversed for firms with higher initial product quality in the manufacturing sector, and is less pronounced for firms with relatively high initial product quality in the agriculture sector. These findings are in line with Disdier et al. (2023), who found that NTMs boost the export sales of high product quality firms while diminishing those of lower product quality firms.

# **5.4 Robustness checks**

In this section, we subject our main findings to a series of sensitivity analyses to check the robustness of our main findings. We begin by estimating the effects of NTMs on the intensive margin of trade using the PPML estimator (Santos Silva and Tenreyro, 2006). The estimator’s log-linear objective function allows us to specify the gravity equation in its multiplicative form without log-transforming the dependent variable and is consistent under heteroskedasticity (see Appendix A2 for a discussion of the properties of the estimator and the model specification). The results presented in Table A2 support our main findings. The effects are, however, estimated with a higher level of precision at the 1% significant level and the magnitudes of the estimated effects are larger than those from our baseline model with the OLS.

In the preceding sections, we make use of the logarithm of the number of NTMs imposed on a product _p_ , from origin _c_ if we consider just the presence of NTMs? To answer this question, we define a dummy variable ( _NTMpcdt_ ) that takes the value 1 if the count of NTMs 19