sectors would greatly help to resist to the strong international competitions and reinforce the export orientation of the two countries.

**Table 7. Estimation Results: Common Model with Aggregated** **_IC_ Variables** _<u>(Dependant Variable: Value Added)</u>_

|**_Independent_**<br>**_Variables_**|**Textile**|**Leather**|**Garment**|**Agro**<br>**Industry**|**Metal &**<br>**Machinery**<br>**Products**|**Chemic**<br>**&Pharm**<br>**Products**|**Wood**<br>**&**<br>**Furniture**|**Non Metal**<br>**& Plastic**<br>**Materials**|
|---|---|---|---|---|---|---|---|---|
|**_ln(l )_**|0.637<br>_(16.01)***_|0.778<br>_(27.90)***_|0.879<br>_(15.19)***_|0.551<br>_(12.54)***_|0.885<br>_(25.26)***_|0.578<br>_(11.84)***_|0.836<br>_(17.87)***_|0.923<br>_(15.50)***_|
|**_ln(k)_**|0.337<br>_(15.06)***_|0.252<br>_(16.57)***_|0.196<br>_(7.40)***_|0.397<br>_(24.54)***_|0.258<br>_(13.11)***_|0.447<br>_(20.05)***_|0.248<br>_(11.91)***_|0.254<br>_(9.31)***_|
|**_Intercept_**|1.081<br>_(2.01)**_|2.149<br>_(5.93)***_|1.326<br>_(4.62)***_|4.302<br>_(5.77)***_|1.883<br>_(5.90)***_|2.868<br>_(4.26)***_|1.738<br>_(4.54)***_|1.223<br>_(2.78)***_|
|**_Size_**|-0.809|-0.333|-0.037|-0.212|-0.159|-0.198|-0.490|0.273|
||_(1.54)_|_(1.77)*_|_(0.33)_|_(2.75)***_|_(0.22)_|_(1.99)**_|_(2.22)**_|_(1.10)_|
|**_Foreign_**|-0.426<br>_(0.90)_|-0.006<br>_(0.76)_|-0.014<br>_(0.50)_|-0.005<br>_(3.48)***_|-0.541<br>_(1.05)_|-0.006<br>_(1.72)*_|0.004<br>_(0.54)_|-0.019<br>_(1.28)_|
|**_Export_**|-0.016<br>_(0.81)_|-0.020<br>_(1.95)*_|-0.078<br>_(1.81)*_|-0.001<br>_(1.14)_|-0.114<br>_(1.04)_|-0.008<br>_(1.49)_|-0.017<br>_(1.53)_|-0.186<br>_(1.08)_|
|**_RegInfra_**|0.762<br>_(2.52)**_|-0.079<br>_(0.66)_|-0.057<br>_(0.95)_|0.014<br>_(0.27)_|0.833<br>_(1.83)*_|0.204<br>_(2.35)**_|0.262<br>_(1.71)*_|0.318<br>_(2.32)**_|
|**_H_**|-0.716<br>_(1.76)*_|-0.138<br>_(0.79)_|-0.116<br>_(1.08)_|-0.253<br>_(5.03)***_|-1.174<br>_(1.52)_|-0.147<br>_(1.71)*_|-0.488<br>_(2.33)**_|-0.768<br>_(2.24)**_|
|**_,_**<sup>**_RegGov_**</sup>|-0.259<br>_(1.21)_|-0.072<br>_(0.72)_|0.185<br>_(2.48)**_|-0.047<br>_(1.48)_|0.706<br>_(1.70)*_|-0.068<br>_(1.39)_|-0.060<br>_(0.54)_|0.136<br>_(0.86)_|
|**_Fin_**|0.778<br>_(2.40)**_|0.219<br>_(1.68)*_|0.035<br>_(0.50)_|0.124<br>_(3.86)***_|0.257<br>_(0.54)_|0.148<br>_(2.67)***_|0.330<br>_(2.36)**_|-0.208<br>_(1.26)_|
|**Constant**|-0.961<br>_(0.95)_|0.162<br>_(0.19)_|0.506<br>_(1.84)*_|3.243<br>_(4.82)***_|-6.121<br>_(2.83)***_|1.508<br>_(2.32)**_|0.703<br>_(1.04)_|-0.522<br>_(0.71)_|
|**Obs**|929|433|1555|1481|826|741|750|461|
|**sigma_u**|1.31|1.11|0.25|0.91|1.98|0.70|1.10|0.56|
|**sigma_v**|0.86|0.60|0.73|0.37|0.65|0.56|0.53|0.75|
|**Wald chi2**|1579.56|2375.90|925.66|1343.79|3117.04|1010.55|1490.81|893.91|
|**Prob> chi2**<br>_Notes_<br>:The one|0.00<br>step procedure|0.00<br>explains firm-|0.00<br>level ineffici|0.00<br>ency. The ex|0.00<br>ected sign of t|0.00<br>he_IC_ aggreg|0.00<br>ated variables|0.00<br>is positive for|

_<u>Notes</u>_ <u>: The one step procedure explains firm-level inefficiency. The expected sign of the</u> _IC_ aggregated variables is positive for _RegInfra_ , _RegGov_ and _Fin,_ and negative for H (see definition of variables in section 5). Variables _Size_ , _Foreign_ and _Export_ are also expected with a negative coefficient. All regressions contain country-dummy variables when estimating the production function. * Significant at 10%; ** significant at 5%; *** significant at 1%. Absolute value of z statistics are in parentheses. _<u>Source</u>_ <u>. Authors’ estimations</u> By using our _IC_ aggregate indicators, however, we don’t always better explain productivity. This is somehow the case of _Metal & Machinery Products_ and _Agro-Processing_ , but essentially of _Garment_ for which a very few aspects of the investment climate seem to help firms to perform better<sup>43</sup> . No improvement is seen, either, in _Leather_ , which is again poorly explained by the model. This fact is, however, largely compensated by the tremendous gain of information through the large set of _IC_ variables now explaining firm-level productive performances, as well as by the validation of another variable of interest: the GovernmentBusiness Relation ( _Gov_ )<sup>44</sup> . We will also show in the next section that Garment is better explained by the data, when dealing with small and medium domestic firms.

Another addition of the model consists in validating the role of more plants characteristics in explaining firm-level Technical Efficiency ( _TE_ ). This is true for the variable _Size_ , which justify scales economies in four industries instead of two previously: _Wood & Furniture_ and _Leather_ in addition to _Agro-Processing_ and _Chemicals & Pharmaceutical Products_ . This constitutes an interesting result that would justify a policy of concentration of small enterprises, which importance in developing countries is well documented. Concentration 22