The role of digital intermediation platforms in opening up international markets
Annex C. Regression analysis: Regulatory barriers to digitally enabled services trade
Copy link to Annex C. Regression analysis: Regulatory barriers to digitally enabled services tradeTable A C.1. Regulations to digitally enabled services trade and DIPs diffusion: Total traffic
Copy link to Table A C.1. Regulations to digitally enabled services trade and DIPs diffusion: Total trafficBy DIP type and sector, 2014-2024
|
Log of Total Traffic |
||||
|
Travel & Accommodation Booking |
Ride-Hailing & Carpooling |
X2C Online Marketplace |
||
|
DIP type |
Pure |
Pure |
Pure |
Pure & Hybrid |
|
DSTRI score |
0.5946 (1.0493) |
1.4604 (2.1130) |
1.7977 (2.2120) |
2.2889 (2.5557) |
|
Observations |
346 |
346 |
346 |
346 |
|
R-squared |
0.8876 |
0.7703 |
0.8201 |
0.8872 |
|
Highest VIF |
3.2694 |
3.2694 |
3.2694 |
3.6567 |
|
Infrastructure & connectivity |
0.0495 (1.1933) |
2.2291 (2.0861) |
0.8609 (2.2979) |
2.0166 (1.3636) |
|
Observations |
346 |
346 |
346 |
346 |
|
R-squared |
0.8873 |
0.7718 |
0.8185 |
0.8865 |
|
Highest VIF |
3.1743 |
3.1743 |
3.1743 |
3.5989 |
|
Electronic transactions |
2.7026 (4.4610) |
-6.7563 (11.4469) |
10.1394 (8.3887) |
1.0994 (6.7688) |
|
Observations |
346 |
346 |
346 |
346 |
|
R-squared |
0.8877 |
0.7706 |
0.8220 |
0.8840 |
|
Highest VIF |
3.1813 |
3.1813 |
3.1813 |
3.5912 |
|
Payment systems |
1.0906 (6.7652) |
-5.9411 (17.4127) |
-2.2483 (12.7559) |
-13.7098 (14.5029) |
|
Observations |
346 |
346 |
346 |
346 |
|
R-squared |
0.8873 |
0.7696 |
0.8181 |
0.8863 |
|
Highest VIF |
3.1814 |
3.1814 |
3.1814 |
3.7808 |
|
Intellectual property rights |
-8.0818** (3.8484) |
-5.0628 (34.5847) |
12.8054 (21.4491) |
-4.5191 (13.7841) |
|
Observations |
346 |
346 |
346 |
346 |
|
R-squared |
0.8876 |
0.7693 |
0.8186 |
0.8840 |
|
Highest VIF |
3.1753 |
3.1753 |
3.1753 |
3.5910 |
|
Other barriers |
4.9418 (3.0679) |
-3.6298 (6.9620) |
3.0975 (8.1134) |
6.7720 (5.8192) |
|
Observations |
346 |
346 |
346 |
346 |
|
R-squared |
0.8891 |
0.7697 |
0.8185 |
0.8860 |
|
Highest VIF |
3.8347 |
3.8347 |
3.8347 |
4.6202 |
|
Cost to enforce contracts (%) |
0.0198 (0.0192) |
-0.0186 (0.0226) |
-0.0123 (0.0201) |
-0.0237 (0.0162) |
|
Observations |
346 |
346 |
346 |
346 |
|
R-squared |
0.8914 |
0.7712 |
0.8191 |
0.8876 |
|
Highest VIF |
3.2962 |
3.2962 |
3.2962 |
3.8810 |
|
PMR (Index, 0-6) |
-0.3364* (0.1711) |
-0.3485 (0.3361) |
-0.8733*** (0.3071) |
-0.1977 (0.2365) |
|
Observations |
346 |
346 |
346 |
346 |
|
R-squared |
0.8909 |
0.7713 |
0.8350 |
0.8848 |
|
Highest VIF |
3.1846 |
3.1846 |
3.1846 |
3.5910 |
Notes: All specifications include the country characteristics set out in Annex A as well as time fixed effects, using equation (1). VIF (Variance Inflation Factor) measures multicollinearity among variables. Values below 5 indicate low collinearity; above 10 suggest problematic collinearity. Robust standard errors are in parentheses.
Sources: Author’s elaboration based on data from Semrush and Crunchbase.
Table A C.2. Regulations to digitally enabled services trade and DIPs diffusion: Foreign firms’ traffic
Copy link to Table A C.2. Regulations to digitally enabled services trade and DIPs diffusion: Foreign firms’ trafficBy DIP type and sector, 2014-2024
|
Log of Foreign Firms Traffic |
||||||||
|---|---|---|---|---|---|---|---|---|
|
Controlling for domestic market competition: Yes |
Controlling for domestic market competition: No |
|||||||
|
Travel & Accommodation Booking |
Ride-Hailing & Carpooling |
X2C Online Marketplace |
Travel & Accommodation Booking |
Ride-Hailing & Carpooling |
X2C Online Marketplace |
|||
|
DIP type |
Pure |
Pure |
Pure |
Pure & Hybrid |
Pure |
Pure |
Pure |
Pure & Hybrid |
|
DSTRI score |
0.1841 (2.2788) |
4.9905 (3.7901) |
6.7302 (4.5447) |
1.9891 (3.9948) |
-0.2630 (2.3742) |
1.7965 (3.7274) |
8.8870 (6.8987) |
2.7625 (4.7854) |
|
Observations |
243 |
226 |
231 |
269 |
243 |
226 |
231 |
269 |
|
R-squared |
0.7322 |
0.7053 |
0.5800 |
0.6190 |
0.7171 |
0.6741 |
0.5648 |
0.5830 |
|
Highest VIF |
3.3397 |
3.8348 |
3.1155 |
3.3269 |
3.3049 |
3.7442 |
3.1091 |
3.3130 |
|
Infrastructure & connectivity |
0.4775 (2.7436) |
4.2263 (3.6104) |
4.9723 (8.1191) |
0.9872 (3.9279) |
0.3870 (2.8668) |
2.7972 (3.8665) |
6.5848 (5.2671) |
2.2402 (4.7315) |
|
Observations |
243 |
226 |
231 |
269 |
243 |
226 |
231 |
269 |
|
R-squared |
0.7324 |
0.7038 |
0.6009 |
0.6179 |
0.7172 |
0.6761 |
0.5949 |
0.5824 |
|
Highest VIF |
3.1540 |
3.8350 |
2.7615 |
3.2031 |
3.1462 |
3.7434 |
2.7583 |
3.1891 |
|
Electronic transactions |
-7.1687 (10.7226) |
-5.7638 (19.3695) |
20.0144 (25.4872) |
14.9301 (16.7133) |
-10.7053 (10.5840) |
-9.5452 (20.3275) |
13.0188 (25.7595) |
16.0477 (19.2727) |
|
Observations |
243 |
226 |
231 |
269 |
243 |
226 |
231 |
269 |
|
R-squared |
0.7360 |
0.6974 |
0.5763 |
0.6260 |
0.7265 |
0.6755 |
0.5496 |
0.5898 |
|
Highest VIF |
3.1140 |
3.8839 |
2.7076 |
3.2030 |
3.1025 |
3.7831 |
2.6850 |
3.1877 |
|
Payment systems |
-4.7607 (13.7048) |
3.2514 (27.1784) |
-73.7321** (32.4131) |
-10.7300 (27.3043) |
-4.1602 (14.7529) |
-1.0809 (28.0138) |
-78.8191** (31.8610) |
-22.4783 (28.1633) |
|
Observations |
243 |
226 |
231 |
269 |
243 |
226 |
231 |
269 |
|
R-squared |
0.7329 |
0.6966 |
0.6400 |
0.6189 |
0.7176 |
0.6728 |
0.6333 |
0.5867 |
|
Highest VIF |
3.1315 |
3.8451 |
2.6995 |
3.2744 |
3.1257 |
3.7653 |
2.6785 |
3.2709 |
|
Intellectual property rights |
-22.0417** (8.1545) |
-64.5058** (27.6337) |
N/A |
15.6858 (12.8321) |
-24.1740*** (8.3864) |
-34.2818** (15.4755) |
N/A |
36.3531 (27.5385) |
|
Observations |
243 |
226 |
N/A |
269 |
243 |
226 |
N/A |
269 |
|
R-squared |
0.7362 |
0.7003 |
N/A |
0.6204 |
0.7219 |
0.6739 |
N/A |
0.5988 |
|
Highest VIF |
3.1043 |
3.8426 |
N/A |
3.2269 |
3.0977 |
3.7754 |
N/A |
3.2047 |
|
Other barriers |
3.7528 (5.3556) |
7.7176 (10.4630) |
-27.3026* (14.7886) |
-5.0289 (12.7025) |
2.8990 (5.9288) |
-3.2773 (10.8420) |
-31.5702** (14.5017) |
-11.2028 (12.7461) |
|
Observations |
235 |
226 |
231 |
269 |
243 |
226 |
231 |
269 |
|
R-squared |
0.7339 |
0.6983 |
0.5930 |
0.6184 |
0.7180 |
0.6732 |
0.5822 |
0.5852 |
|
Highest VIF |
3.6798 |
3.8652 |
3.5349 |
4.4530 |
3.6486 |
4.1197 |
3.3815 |
4.4280 |
|
Cost to enforce contracts (%) |
-0.0081 (0.0260) |
0.0708 (0.0358) |
0.0624 (0.0624) |
-0.0057 (0.0645) |
-0.0114 (0.0274) |
0.0853** (0.0386) |
0.0676 (0.0649) |
0.0005 (0.0687) |
|
Observations |
243 |
226 |
231 |
269 |
243 |
226 |
231 |
269 |
|
R-squared |
0.7330 |
0.7185 |
0.5941 |
0.6177 |
0.7188 |
0.7076 |
0.5775 |
0.5799 |
|
Highest VIF |
3.1015 |
3.9891 |
2.8936 |
3.5095 |
3.0954 |
3.9453 |
2.7325 |
3.5024 |
|
PMR (Index, 0-6) |
-0.5780 (0.3746) |
-1.4504*** (0.4021) |
-1.6443*** (0.4932) |
-0.5282 (0.3760) |
-0.6019 (0.4056) |
-1.4902*** (0.3950) |
-1.3890*** (0.4778) |
-0.5038 (0.4860) |
|
Observations |
243 |
226 |
231 |
269 |
243 |
226 |
231 |
269 |
|
R-squared |
0.7429 |
0.7290 |
0.6073 |
0.6238 |
0.7287 |
0.7072 |
0.5751 |
0.5857 |
|
Highest VIF |
3.1124 |
3.9632 |
2.7267 |
3.2067 |
3.1056 |
3.8810 |
2.7191 |
3.1920 |
Notes: All specifications include the country characteristic set out in Annex A. as well as time fixed effects, using equation (1). VIF (Variance Inflation Factor) measures multicollinearity among variables. Values below 5 indicate low collinearity; above 10 suggest problematic collinearity. Robust standard errors are in parentheses. Please refer to the endnotes for missing coefficients (N/A).
Sources: Author’s elaboration based on data from Semrush and Crunchbase.
Table A C.3. Regulations to digitally enabled services trade and DIPs diffusion: Share of foreign firms’ traffic
Copy link to Table A C.3. Regulations to digitally enabled services trade and DIPs diffusion: Share of foreign firms’ trafficBy DIP type and sector, 2014-2024
|
Share of Foreign Firms’ Traffic |
||||
|---|---|---|---|---|
|
Travel & Accommodation Booking |
Ride-Hailing & Carpooling |
X2C Online Marketplace |
||
|
DIP type |
Pure |
Pure |
Pure |
Pure & Hybrid |
|
DSTRI score |
0.0694 (0.0796) |
0.0978 (0.3092) |
0.0817 (0.2138) |
-0.1132 (0.1560) |
|
Observations |
346 |
346 |
346 |
346 |
|
R-squared |
0.3467 |
0.1991 |
0.2325 |
0.1047 |
|
Highest VIF |
3.2694 |
3.2694 |
3.2694 |
3.2694 |
|
Infrastructure & connectivity |
0.0834 (0.0714) |
-0.1834 (0.3095) |
0.3375 (0.2554) |
-0.0414 (0.1812) |
|
Observations |
346 |
346 |
346 |
346 |
|
R-squared |
0.3528 |
0.2009 |
0.2640 |
0.1288 |
|
Highest VIF |
3.1743 |
3.1743 |
3.1743 |
3.1743 |
|
Electronic transactions |
-0.3813 (0.3471) |
1.8575 (2.4863) |
-0.4912 (0.8215) |
0.1298 (0.6653) |
|
Observations |
346 |
346 |
346 |
346 |
|
R-squared |
0.3566 |
0.2133 |
0.2347 |
0.1283 |
|
Highest VIF |
3.1813 |
3.1813 |
3.1813 |
3.1813 |
|
Payment systems |
0.0836 (0.4900) |
2.2815 (2.0278) |
-3.9974* (1.9917) |
-0.5049 (1.2946) |
|
Observations |
346 |
346 |
346 |
346 |
|
R-squared |
0.3354 |
0.2074 |
0.3405 |
0.1312 |
|
Highest VIF |
3.1814 |
3.1814 |
3.1814 |
3.1814 |
|
Intellectual property rights |
-0.2700 (0.5102) |
1.8569 (1.5088) |
2.7771 (2.1577) |
-0.3015 (0.9769) |
|
Observations |
346 |
346 |
346 |
346 |
|
R-squared |
0.3361 |
0.1999 |
0.2436 |
0.1443 |
|
Highest VIF |
3.1753 |
3.1753 |
3.1753 |
3.1753 |
|
Other barriers |
0.0575 (0.2232) |
1.3562 (1.2627) |
-1.9975*** (0.7264) |
-1.1289** (0.4693) |
|
Observations |
346 |
346 |
346 |
346 |
|
R-squared |
0.3357 |
0.2089 |
0.3205 |
0.1924 |
|
Highest VIF |
3.8347 |
3.8347 |
3.8347 |
3.8347 |
|
Cost to enforce contracts (%) |
-0.0006 (0.0006) |
-0.0031 (0.0065) |
0.0035 (0.0036) |
0.0014 (0.0027) |
|
Observations |
346 |
346 |
346 |
346 |
|
R-squared |
0.3456 |
0.2063 |
0.2699 |
0.1416 |
|
Highest VIF |
3.2962 |
3.2962 |
3.2962 |
3.2962 |
|
PMR (Index, 0-6) |
-0.0083 (0.0108) |
-0.1033* (0.0604) |
0.0196 (0.0361) |
-0.0056 (0.0261) |
|
Observations |
346 |
346 |
346 |
346 |
|
R-squared |
0.3409 |
0.2246 |
0.2344 |
0.1284 |
|
Highest VIF |
3.1846 |
3.1846 |
3.1846 |
3.1846 |
Notes: All specifications include the country characteristic set out in Annex A. as well as time fixed effects, using equation (1). Values below 5 indicate low collinearity; above 10 suggest problematic collinearity. Robust standard errors are in parentheses.
Sources: Author’s elaboration based on data from Semrush and Crunchbase.