I am working on my Ms.thesis. the topic related to DETERMINANTS AND POTENTIAL TRADE OF 25 BIGGEST COFFEE EXPORTERS. (25 exporters, 196 importers, 2001-2019)I have tried to use many methods to estimate the gravity model and the results as in the table bellow
For the linear estimator: I use the Ftest; Breusch and Pagan Lagrangian; Hausman test =>FEM is appreciated, but the H0 of RESET test is not rejected, so there is heteroskedasticity, the predicted values also not good ( the values of some countries is too big). Then I use the PPML model with 3 fixed effects Time-Exporter; Time-Importer and Time-Exporter-Importer
my question is:
- Can I use the Ramsey test to select the appreciated model? (for estimating potential (GAP between predict and actual)
- Can I use the coefficient to estimate the potential trade for an individual country to its importer? (EX: calculate the gap between prediction and actual of Vietnam to all the importers)
thank you so much
OLS | FEM | REM | TOBIT | PPML Importer fixed effect | PPML Importer, exporter fixed effect | PPML Importer, exporter, time fixed effect | |
VARIABLES | ln(EX+0.0001) | ln(EX+0.0001) | ln(EX+0.0001) | ln(EX+1) | EX | EX | EX |
log_GDPex | 0.0970*** | 0.322*** | 0.364*** | 0.464*** | 1.621*** | 1.041*** | -0.181 |
(0.00920) | (0.0764) | (0.0279) | (0.106) | (0.118) | (0.0790) | (0.119) | |
log_GDPim | 0.0666*** | 2.516*** | 0.651*** | 3.115*** | -0.00761 | 2.273*** | 0.994*** |
(0.00902) | (0.0695) | (0.0282) | (0.101) | (0.00806) | (0.152) | (0.153) | |
log_prodpercap_ex2 | -0.0180*** | 0.0205*** | 0.0123*** | 0.0222*** | 0.0284*** | 0.0131*** | 0.0104*** |
(0.00120) | (0.00210) | (0.00184) | (0.00276) | (0.00422) | (0.00205) | (0.00312) | |
log_prodpercap_im2 | -0.150*** | -0.0108*** | -0.0515*** | -0.00881** | -0.0417*** | -0.000655 | -0.00206 |
(0.00134) | (0.00284) | (0.00245) | (0.00380) | (0.00193) | (0.00320) | (0.00331) | |
log_pop_ex | 0.505*** | 0.854 | 0.0593 | 1.683 | 5.761 | 4.574* | 1.375 |
(0.0193) | (1.204) | (0.0668) | (1.833) | (5.197) | (2.386) | (1.802) | |
log_pop_im | 1.056*** | -0.765** | 0.294*** | -0.754 | 0.738*** | 2.087** | -1.261** |
(0.0145) | (0.308) | (0.0473) | (0.462) | (0.0177) | (0.951) | (0.574) | |
log_dist | -2.045*** | -2.756*** | -1.312*** | -0.929*** | -0.610*** | -0.614*** | |
(0.0302) | (0.103) | (0.0261) | (0.0395) | (0.0257) | (0.0247) | ||
contig | 3.185*** | 2.271*** | 1.303*** | 0.626*** | 1.023*** | 1.022*** | |
(0.159) | (0.566) | (0.106) | (0.0908) | (0.0683) | (0.0655) | ||
comlang_off | 0.241*** | -0.0647 | 1.668*** | -0.0870 | -0.305*** | -0.308*** | |
(0.0594) | (0.210) | (0.0553) | (0.0623) | (0.0578) | (0.0569) | ||
landlock_ex | -0.419*** | -1.179*** | -3.689 | 4.584 | 2.070 | -1.540 | |
(0.0674) | (0.232) | (2.902) | (3.285) | (1.512) | (1.152) | ||
landlock_im | -4.061*** | -4.056*** | -3.189 | -0.873*** | -33.51*** | -5.646** | |
(0.0524) | (0.188) | (2.302) | (0.0610) | (4.098) | (2.774) | ||
both_rta | 2.952*** | -0.351 | 0.942*** | -0.268 | 3.644*** | 0.692** | 0.745*** |
(0.215) | (0.243) | (0.233) | (0.272) | (0.232) | (0.269) | (0.263) | |
one_rta | 0.943*** | -0.262 | 0.322 | -0.194 | 1.890*** | 0.343 | 0.419* |
(0.215) | (0.232) | (0.225) | (0.225) | (0.222) | (0.247) | (0.243) | |
religion | 0.836*** | 0.182 | 0.103 | -0.568*** | -0.395*** | -0.390*** | |
(0.0643) | (0.228) | (0.0716) | (0.0783) | (0.0585) | (0.0566) | ||
Constant | -19.66*** | -83.03*** | -13.72*** | -94.87*** | -155.5 | -181.5*** | -19.17 |
(0.503) | (21.24) | (1.494) | (34.96) | (99.45) | (46.55) | (35.27) | |
Observations | 87,839 | 87,839 | 87,839 | 87,839 | 87,839 | 87,839 | 87,839 |
R-squared | 0.341 | 0.034 | 0.155 | 0.668 | 0.702 | ||
RESET p-values | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.0000 | 0.1341 | 0.0003 |
Ftest | 0.0000 | ||||||
Breusch and Pagan Lagrangian | 0.0000 | ||||||
Hausman test | 0.0000 | 0.0000 | |||||
Number of pairid | 4,736 | 4,736 | |||||
Standard errors in parentheses | |||||||
*** p<0.01, ** p<0.05, * p<0.1 |
0 Response to estimate gravity model to calculate potential trade by uisng OLS, REM, FEM, TOBIT and PPLM
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