inspections are much less likely to induce delays; but delays, once induced, have much larger impacts on trade flows.

The findings in Table 5 rely on inference based on standard errors robust to heteroskedasticity. While there is no natural clustering level to consider for our specifications, we check the robustness of our findings to a variety of clustering structures: at the firm-product-country (to account for potential serial correlation), the firm, the firm-product, and the firm-country levels but also the product-country level. The significance of the effect of customs time on imports is maintained in all cases. We also note that while we drop import declarations taking longer than 18 days to clear customs from the raw data set before aggregating it to the firm-HS 6-digit product-origin country-year level, the estimation results are robust to including those declarations.<sup>40</sup>

**Table 5. Effect of customs clearance time on imports**

|||<br>_Cleara_|<br>_nce time mea_|Depende<br>_sured in days_|nt variable is<br>_‐ 2007‐2012 p_<br>|first‐diff. in l<br>_eriod_<br>|og import valu|e at firm‐H|S6 product‐orig<br>_Cleara_<br>|in country‐ye<br>_nce time mea_<br>|ar level<br>_sured in hours_|<br>_‐ 2010‐2012_|<br>_period_||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|||OLS estimation|||IV esti|mation|||OLS estimation|||IV esti|mation||
||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|(10)|(11)|(12)|(13)|(14)|
|First‐diff. in median clearance time<br>|‐0.067***|‐0.076***|‐0.081***|‐0.654***|‐0.789***|‐0.970***||‐0.004***|‐0.004***|‐0.005***|‐0.018***|‐0.021***|‐0.023***||
||(0.005)|(0.005)|(0.006)|(0.104)|(0.106)|(0.149)||(0.000)|0.000|0.000|(0.005)|(0.006)|(0.008)||
|First‐diff. in log median clearance|||||||||||||||
|time|||||||‐1.899***|||||||‐0.096***|
||||||||(0.283)|||||||(0.031)|
|Firm*year fixed effects||Yes|Yes||Yes|Yes|Yes||Yes|Yes||Yes|Yes|Yes|
|HS6 product*origin country*year<br>fixed effects|||Yes|||Yes|Yes|||Yes|||Yes|Yes|
|Observations|200,281|200,281|200,281|200,281|200,281|200,281|200,281|84,298|84,298|84,298|84,298|84,298|84,298|84,298|
|R‐squared|0.001|0.149|0.466|‐0.104|0.032|0.370|0.406|0.002|0.138|0.462|‐0.029|0.106|0.440|0.460|
|F‐statistic from first‐stage regression||||311|422|405|600||||211|260|267|3268|
|First‐stage coefficient on first‐diff.|||||||||||||||
|in median allocation to red channel||||0.071***|0.077***|0.070***|0.036***||||2.092***|2.133***|1.987***|0.481***|
|||||(0.004)|(0.004)|(0.003)|(0.001)||||(0.144)|(0.132)|(0.122)|(0.008)|

Notes: Robust standard errors in parentheses. *** indicates significance at the 1% confidence level.

# **5.2 Economic Interpretation**

Because the identification strategy we employ calculates effects at the intensive margin of trade (and because the two stages in the analysis can complicate interpretation) it is useful to offer some back-of-the-envelope calculations that illustrate the economic magnitude of the estimates in Table 5. Focusing on our preferred specification in column (6), the first-stage regression

> 40 The results using different clustering of standard errors and those including outlier declarations in the sample are available from the authors upon request.

24