Table 7: An alternative horse race across transmission channels

||(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|(9)|
|---|---|---|---|---|---|---|---|---|---|
|Dep. var.: Survival|1y|5y|10y|1y|5y|10y|1y|5y|10y|
|investment needs _×_ banks|0.002|0.044|0.064<sup>_b_</sup>|||||||
||(0.047)|(0.033)|(0.027)|||||||
|liquidity needs _×_ banks|0.103<sup>_a_</sup>|0.083<sup>_a_</sup>|0.052<sup>_b_</sup>|||||||
||(0.039)|(0.029)|(0.022)|||||||
|asset intangibility _×_ banks|0.063|0.065|0.038|||||||
||(0.056)|(0.043)|(0.032)|||||||
|investment needs _×_ stock markets||||0.054|0.076<sup>_a_</sup>|0.062<sup>_a_</sup>||||
|||||(0.040)|(0.026)|(0.019)||||
|liquidity needs _×_ stock markets||||0.128<sup>_a_</sup>|0.053<sup>_b_</sup>|-0.007||||
|||||(0.026)|(0.024)|(0.020)||||
|asset intangibility _×_ stock markets||||0.215<sup>_a_</sup>|0.184<sup>_a_</sup>|0.090<sup>_a_</sup>||||
|||||(0.039)|(0.030)|(0.028)||||
|investment needs _×_ stock market turnover|||||||0.055|0.021|0.035<sup>_c_</sup>|
||||||||(0.036)|(0.027)|(0.019)|
|liquidity needs _×_ stock market turnover|||||||0.097<sup>_a_</sup>|0.070<sup>_a_</sup>|0.046<sup>_a_</sup>|
||||||||(0.025)|(0.021)|(0.015)|
|asset intangibility _×_ stock market turnover|||||||0.111<sup>_a_</sup>|0.083<sup>_a_</sup>|0.047<sup>_a_</sup>|
||||||||(0.034)|(0.027)|(0.017)|
|Observations|252,147|252,147|252,147|243,509|243,509|243,509|240,981|240,981|240,981|
|R-squared|0.264|0.546|0.692|0.255|0.547|0.695|0.255|0.549|0.697|
|Country-Time FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Product FE|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|Full set of controls included|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|Yes|

Dependent variable is the probability of export survival of product _k_ from industrial sector (industry) _i_ exported by country _c_ to the USA. Export survival probability is measured _l_ years after the beginning of export spell, with _l_ = 1 in columns (1), (4) and (7), _l_ = 5 in columns (2), (5) and (8), and _l_ = 10 in columns (3), (6) and (9). The regressions are estimated by OLS and contain a full set of fixed effects at the product level and the (exporting country)*time level, with time referring to the beginning of a given export spell. Each specification controls for interaction terms of the three measures of financial vulnerability with GDP per capita and with real exchange rate. All variables are described in Table 2, Table 3, and Table 4. The full set of controls also includes initial export, total export, number of suppliers, multiple spell, and interaction terms between physical and human capital endowments of country _c_ and the corresponding capital intensities at the industry level. All time-varying explanatory variables are measured at the beginning of the export spell. Robust standard errors are clustered at the (exporting country)*time level, with time referring to the beginning of a given export spell. _a_ , _b_ , _c_ denote statistical significance at the 1%, 5%, and 10% level, respectively.

In columns (4) to (6) of Table 7, we interact the three financial vulnerability proxies with the size dimension of stock market development. At all the time horizons, the positive impact of large stock markets on export survival manifests itself especially through alleviating the financial vulnerability arising from the presence of intangible assets. Large stock markets also promote products with high investment needs, especially when it comes to export survival at longer time horizons. When it comes to products with high liquidity needs, the size of stock markets matters in particular for the short-term export survival.

In columns (7) to (10) of Table 7, we interact our proxies of financial vulnerability with the activity of a given stock market. Similarly to large stock markets explored in the previous three columns, the active stock markets play an important role in promoting the export survival of products whose manufacturing process requires a high share of intangible assets. However, the other two transmission channels operate differently in the case 30