import intensity has an even higher coefficient than the dichotomous variable (cfr.
column 4 and 5) which confirms the results of Hasan and Raturi (2003).
The coefficient on the foreign ownership variable is never statistically different from
zero while it seems that the capital and technology variables are positively correlated to
the export decision and negatively to the import decision. The first case is in line with
the findings of the literature while in the second case there it seems to be a substitution
effect between firm’s capital and technology and the capital and technology embodied in
the imported inputs.
Table 3. Export and Import decision: Probit estimations
|
Dep V |
ariable | |||||
|
EXP |
IMP |
EXP |
EXP |
IMP |
IMP | |
|
(1) |
(2) |
(3) |
(4) |
(5) |
(6) | |
|
IMP |
0.962 | |||||
|
[0.191]*** | ||||||
|
Import share |
1.314 | |||||
|
[0.380]*** | ||||||
|
EXP |
0.980 | |||||
|
[0.187]*** | ||||||
|
Export Share |
0.483 | |||||
|
[0.206]** | ||||||
|
Share of FO |
1.782 |
0.185 |
1.288 |
1.451 |
-0.064 |
-0.078 |
|
[1.430] |
[0.714] |
[1.066] |
[1.241] |
[0.719] |
[0.724] | |
|
Capital Intensity (t-1) |
0.120 |
0.012 |
0.122 |
0.125 |
-0.022 |
0.006 |
|
[0.042]*** |
[0.043] |
[0.044]*** |
[0.043]*** |
[0.045] |
[0.043] | |
|
Skill Intensity |
0.028 |
0.236 |
-0.024 |
-0.002 |
0.236 |
0.232 |
|
[0.060] |
[0.062]*** |
[0.063] |
[0.062] |
[0.065]*** |
[0.063]*** | |
|
Age of machineries |
-0.217 |
0.083 |
-0.246 |
-0.251 |
0.114 |
0.121 |
|
[0.116]* |
[0.123] |
[0.122]** |
[0.121]** |
[0.127] |
[0.124] | |
|
Employment (t-1) |
0.354 |
0.326 |
0.277 |
0.305 |
0.251 |
0.305 |
|
[0.070]*** |
[0.071]*** |
[0.075]*** |
[0.072]*** |
[0.075]*** |
[0.073]*** | |
|
Age of the firm |
0.295 |
-0.135 |
0.326 |
0.317 |
-0.195 |
-0.154 |
|
[0.095]*** |
[0.102] |
[0.099]*** |
[0.099]*** |
[0.106]* |
[0.103] | |
|
Average wage (t-1) |
0.092 |
0.116 |
0.066 |
0.072 |
0.109 |
0.123 |
|
[0.055]* |
[0.055]** |
[0.057] |
[0.056] |
[0.057]* |
[0.055]** | |
|
Constant |
-4.104 |
-3.120 |
-3.319 |
-3.388 |
-2.920 |
-3.144 |
|
[0.563]*** |
[0.555]*** |
[0.559]*** |
[0.553]*** |
[0.574]*** |
[0.560]*** | |
|
Observations |
501 |
"487 |
"487 |
"487 |
"487 |
"487 |
|
Log likelihood |
-236.29 |
-205.53 |
-219.75 |
-226.07 |
-190.86 |
-202.79 |
|
Pseudo R2__________ |
0.3152 |
0.2986 |
0.3460 |
0.3265 |
0.3487 |
0.3080 |
Notes:
Robust Standard errors in brackets
Sector and year dummies included in all the equations
* significant at 10%; ** significant at 5%; *** significant at 1%
Naturally, considering import and export we are referring to different decisions
nonetheless our analysis shows that there is a linkage between the two. The reasons for
10
More intriguing information
1. Cyber-pharmacies and emerging concerns on marketing drugs Online2. A Brief Introduction to the Guidance Theory of Representation
3. Cross-Country Evidence on the Link between the Level of Infrastructure and Capital Inflows
4. The Distribution of Income of Self-employed, Entrepreneurs and Professions as Revealed from Micro Income Tax Statistics in Germany
5. Dynamiques des Entreprises Agroalimentaires (EAA) du Languedoc-Roussillon : évolutions 1998-2003. Programme de recherche PSDR 2001-2006 financé par l'Inra et la Région Languedoc-Roussillon
6. EMU: some unanswered questions
7. Human Development and Regional Disparities in Iran:A Policy Model
8. The changing face of Chicago: demographic trends in the 1990s
9. Structural Influences on Participation Rates: A Canada-U.S. Comparison
10. Partner Selection Criteria in Strategic Alliances When to Ally with Weak Partners