Table 7: The effect of non-tariff measures on firm-level export margins by initial product quality

||Extensive|margins|||||Intensive|margin||
|---|---|---|---|---|---|---|---|---|---|
|_Outcome:_|Export E|ntry Dumm|y|Export Ex|it Dummy||Export V|alue (logs)||
||All|Agric.|Manuf.|All|Agric.|Manuf.|All|Agric.|Manuf.|
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|
|log _NTMpcdt_|_−_0.003<sup>_∗∗∗_</sup>|_−_0.003|_−_0.003|_−_0.003<sup>_∗∗∗_</sup>|_−_0.001|_−_0.003|_−_0.730<sup>_∗∗∗_</sup>|_−_0.817<sup>_∗∗∗_</sup>|_−_0.711<sup>_∗∗∗_</sup>|
||(0.001)|(0.002)|(0.002)|(0.001)|(0.002)|(0.002)|(0.055)|(0.102)|(0.102)|
|log _NTMpcdt_ x _PQipcd_|0.006<sup>_∗∗∗_</sup>|0.006<sup>_∗∗∗_</sup>|0.009<sup>_∗∗∗_</sup>|0.004<sup>_∗∗∗_</sup>|0.003<sup>_∗∗∗_</sup>|0.007<sup>_∗∗∗_</sup>|0.801<sup>_∗∗∗_</sup>|0.805<sup>_∗∗∗_</sup>|0.788<sup>_∗∗∗_</sup>|
||(0.001)|(0.001)|(0.001)|(0.001)|(0.001)|(0.001)|(0.038)|(0.041)|(0.076)|
|log _Tari f fpcdt_|_−_0.000|0.000|_−_0.001|_−_0.001<sup>_∗∗_</sup>|0.000|_−_0.001<sup>_∗∗∗_</sup>|0.031|0.062|_−_0.010|
||(0.000)|(0.001)|(0.000)|(0.000)|(0.000)|(0.000)|(0.020)|(0.039)|(0.019)|
|Observations<br>|813,227|287,893|525,158|859,069|304,406|554,477|79,742|34,514|44,971|
|Adjusted _R_<sup>2</sup>|0.222|0.215|0.230|0.207|0.195|0.216|0.624|0.536|0.636|

Notes: “All” denotes all sectors, “Agric.” denotes the agriculture and food sectors, while “Manuf.” indicates the manufacturing sector. Robust standard errors clustered at the origin-destination-product level are in parentheses. ***, ** and * denote significance at 1%, 5%, and 10%. All models include controls for firm-origin-product, firm-product-year and destination-year fixed effects, which are excluded from the table for brevity.

_>_ 1 within a country-product pair in year _t_ , and 0 otherwise. We then replace the log of the count of NTMs with this dummy variable in Equation 4.1. The results which we present in Table A3 have, in most cases, the expected signs with magnitudes that are very small and also statistically insignificant. It is more intuitive to believe that the compliance cost increases with the number of NTMs (cumulative burden), as such what matters is not just the presence of NTMs but how many.

In the final robustness check, we re-estimate Equation 4.1 using an alternative fixed effect by replacing the firm-origin-product fixed effect with (1) firm-origin-destination fixed effect, which accounts for all time-invariant bilateral trade costs, and (2) firm fixed effect. In the first (second) case, our coefficient of interest is identified by exploiting the within firm-originproduct (firm level) changes in export values due to the variation in the number of NTMs imposed by the importing country on HS6-digit product _p_ from origin _c_ over time _t_ . The results reported in Table A4, are qualitative similar to our baseline estimates (Table 2), although they are less precisely estimated. We note, however, that these estimates are not directly comparable to our main one as they are identified based on a different source of variation.

# **6 Conclusions**

Despite sustained tariff concessions, African countries continue to play a marginal role in global trade. While tariffs have traditionally been a major focus of trade policy, NTMs, particularly standards and technical regulations, have emerged as a growing concern for policy makers, exporters, and importers alike. Despite their importance, relatively little is known about the impact of NTMs on firm-level exports in Africa, particularly in comparison to other regions. Hence, we bridge this gap in the literature by examining how NTMs influence firms’ export strategies in Africa, utilizing data from selected African countries.

We explore the effect of non-tariff measures, specifically standards and technical regulations, which are fast replacing tariffs as the main trade policy tool, on the export margins of 20