that exports follow the booms and busts in the destinations, as captured by the destination fixed effects in the regression. The difference can be explained if small, land-locked countries are more limited in their choice of trade partners than other countries. The fact that this process of following booms and busts is not taking place on the same scale in the land-locked countries could simply mean they have less freedom of choice. Therefore, exporting to attractive countries is not a survival-related choice by the firm but rather a natural constraint: exporters in landlocked countries, facing high trade facilitation costs, are stuck with exporting to their neighbors. However, to really judge the effects of this “landlocked hypothesis” with any degree of certainty, one would need this type of firm-product-destination data from more countries.

**Table 9:** Surviving past the first year (probit – marginal effects) excluding garment or footwear products

||**(1)**|**(2)**|**(3)**|**(4)**|**(5)**|
|---|---|---|---|---|---|
|**Attractiveness**<br>|**0.141**|**0.0675**|**0.0659**|**0.0458**|**0.0799**|
|**Agglomeration**|**0.217*****|**0.158*****|**0.185*****|**0.159*****|**0.174*****|
|**Exp. w. product**<br>|**1.050*****|**0.936*****|**0.952*****|**0.951*****|**1.085*****|
|**Exp. w. destination**<br>|**0.153*****|**0.180*****|**0.177*****|**0.212**|**0.377*****|
|**Initial $ value**<br>||**0.160*****|**0.159*****|**0.199*****|**0.157*****|
|**Has RCA**|||**-0.260****|**-0.0663**|**-0.264****|
|**Firm div. (products)**||||**-0.0805**||
|**Firm div. (destinations)**||||**-0.0273**||
|**Firm div. (P-D)**|||||**-0.292****|
|**Firm div. (sectors)**|||||**0.00838**|
|**N**|**2151**|**2151**|**2149**|**1281**|**2149**|
||*** p<0.10**|**** p<0.05**|***** p<0.01**|||

_Source:_ Authors‟ calculation based on Lao PDR customs data Finally, as a robustness check on these results, we ran the regressions in Table 7 and Table 8 on a couple of sub-samples. First we dropped all transactions of firms that had exported copper at one point or another, which we refer to as “the copper industry”. There is a concern, outlined earlier, that this industry has a significant number of extraordinary exports of machinery, which is, most probably, just sent abroad for repairs. This concerns ~300 of the ~5,000 FPD triplets, singular events which would inflate the creation and destruction of FPD flows, and induce a bias. We find that the results, not shown here, are remarkably similar to Table 7 and Table 8. Furthermore, Table 9 shows the same survival regressions on a sample from which all products with an HS classification as garment or footwear were excluded (~2,000 FPDs). Again, this industry is special in that there are a few large firms, established before the expiration of the Multi Fiber Agreement specifically for the export markets and enjoying some special tax exemptions. We see that the results are again, remarkably similar, with the same signs and magnitudes but a few drops in statistical significance due to higher variance. This analysis confirms the fact that grouping transactions into FPDs is a useful way to filter out some of the noise inherent in the data and therefore produce robust, statistically significant and meaningful results.

# **5 CONCLUSIONS**

We have outlined in this paper the results of an export survival analysis based on a novel dataset from the Lao PDR Customs Department that contains firm-level transactions and covers a period _Exporting from a small landlocked economy_ _22_