is negative and significant at the 1 percent level, regardless of the specification – a very puzzling result. To explain it, one could argue for a selection bias, whereby RCA sectors, mostly garments and resource-based, are “popular” with businesses and attract a large number of firms, a sizable share of them being unfit for export, whereas only the high performers try their hand at the nonRCA sectors and hence enjoy a higher rate of success.

**Table 8:** Initial value of exports (OLS)

||**(1)**|**(2)**|**(3)**|**(4)**|
|---|---|---|---|---|
|**Attractiveness**|**-0.127**|**-1.564*****|**0.111**|**0.144**|
|**Agglomeration**|**0.373*****|**0.367*****|**0.352*****|**0.343*****|
|**Exp. w. product**|**0.552*****|**0.550*****|**0.397*****|**0.453*****|
|**Exp. w. destination**|**-0.0985*****|**-0.0866****|**0.319*****|**0.375*****|
|**Has RCA**||**0.125**|**0.00621**|**0.0287**|
|**Firm div. (products)**|||**-0.615*****|**-0.264****|
|**Firm div. (destinations)**|||**0.385*****|**0.387*****|
|**Firm div. (P-D)**||||**-0.224***|
|**Firm div. (sectors)**||||**-0.439*****|
|**N**|**5042**|**5038**|**2858**|**2858**|
||*** p<0.10**|**** p<0.05**|***** p<0.01**||

_Source:_ Authors‟ calculation based on Lao PDR Customs data The inclusion of the diversification effects in the survival analysis (Table 7) produces only two significant coefficients, both negative. Exporting many products hurts a firm‟s chances of sustaining its export links past the first year. The specification including all factors (5) reduces the level of significance, indicating a possible endogeneity among our diversity proxies, but the coefficient for the number of product-destination pairs remains negative and significant. In effect, this proxy is presumably closest to our notion of lack of focus – equivalent to a firm that is basically “shooting in the dark” and trying out many such combinations with high failure rates. There is a potential for multicollinearity between this proxy and those for “experience”, as they are closely related count measures (their correlation is ~0.7). In fact, in regressions that have only “lack of focus” and no “experience” variables (not shown) its coefficient becomes positive and significant. But when both are included, as in (5) and other combinations of explanatory variables, it is the only “focus” variable that retains significance and is negative, whereas “experience” is positive and significant.

When it comes to the initial value in models (3) and (4) of Table 8, diversification coefficients are all statistically significant. All are negative but for the coefficient of the number of destinations. This could mean that firms which are exporting to many destinations have indeed built up the necessary savoir-faire, which in turn gives them the confidence to start exporting at high values. Alternatively, this could mean that they face multiplied entry-costs which they can only recover through high volume exporting.

There is a possible land-locked effect appearing in the analysis: the coefficient of the attractiveness variable is positive, quite small and not statistically significant, a situation similar to Mali and Malawi but not Tanzania and Senegal (Cadot, et al. 2010). In the case of the latter two, both larger and with sea access, this coefficient is negative and significant, which implies _Exporting from a small landlocked economy_ _21_