[Joao Santos Silva]

You want the origin and destination fixed effects to vary by year. So, the right way to include the fixed effects is

 
 ppmlhdfe FDIflow lnvreer lnreer lngdp_o lngdp_d lngdpcap_o lngdpcap_d, absorb(isonum_o##year isonum_d##year pair_id) cluster(pair_id)

[Ronan Moore]

Dear Joao,

Thank you for your quick reply.

When I type the code

ppmlhdfe FDIflow lnvreer lnreer lngdp_o lngdp_d lngdpcap_o lngdpcap_d, absorb(isonum_o##year isonum_d##year pair_id) cluster(pair_id)

it omits all of the variables in my model.



How should I proceed?

[Joao Santos Silva]

Then you need to rethink the specification of your model and think about which fixed effects you need to include.

[Ronan Moore]

Dear Dr Santos Silva,

I am wondering whether there are any standard diagnostic tests I should run before gravity modelling.

I know with OLS regressions, researchers usually test for heteroscedasticity, but the PPML estimator is robust to this, and can work with zeroes in the data too. Are there any other tests that should be run before I can trust my model? I am just using the PPML estimator, hence I do not believe a RESET test is appropriate. Please see below for my regression inputs for my main model.

ppmlhdfe FDIflow lnvreer lnreer lngdp_o lngdp_d lngdpcap_o lngdpcap_d, absorb(pair_id year) cluster(pair_id)

I am using the same regressors as before, but I am including country-pair/dyadic fixed effects to capture unobserved heterogeneity, as suggested by Baier, 2020 (from "Foreign Direct Investment and Tax: OECD Gravity Modelling in a World with International Financial Institutions"). My supervisor says this is appropriate.

Please see attached for my regression outputs. My r squared is high, and GDP and GDP per capita coefficients conform to what other researchers have found (economic mass increases FDI, GDP per capita decreases FDI possibly due to wages making costs higher, albeit these are not statistically significant), so I feel somewhat confident in my results.

Any help would be much appreciated.

Best,

Ronan

[Joao Santos Silva]

Dear Ronan Moore,

You can use the RESET; that is a functional form test can can always be used. It is not a test to choose between estimators.

Please ignore the value of the psueudo-R2 reported by reghdfe; it is meaningless and will change if you change the scale of your data!

Best wishes,

Joao

[Ronan Moore]

Thank you for your response Joao Santos Silva.

Firstly, is the RESET test then the only test I would need before running the regressions?

Secondly, is this the correct way to conduct the RESET test:

ppmlhdfe FDIflow lnvreer lnreer lngdp_o lngdp_d lngdpcap_o lngdpcap_d, absorb(pair_id year) cluster(pair_id)

predict fit, xb

gen fit2 = fit^2

ppmlhdfe FDIflow lnvreer lnreer lngdp_o lngdp_d lngdpcap_o lngdpcap_d fit2, absorb(pair_id year) cluster(pair_id)

test fit2

I don't know if using the ppmlhdfe command changes how the RESET test is performed.

I appreciate all your help, and many thanks,

Ronan

[Joao Santos Silva]

Dear Ronan Moore,

The RESET test is the only test I would use and that is the way to do it (notice that you are excluding the fixed effects from the fitter values, as you probably should).

Best wishes,

Joao

[Ronan Moore]

Dear Joao Santos Silva,

Thanks for your help, it has been invaluable.

All the best,

Ronan

[Rethabile Molapo]

How to create a panel dataset for many countries

Today, 05:57
Good day Joao Santos Silva
I am trying to consolidate data such that it includes a panel for 167 countries spanning over 10 years. Currently my dataset looks like this: It is a cross- section from 2022 and now I want to add more years.

COUNTRY	EXPORTS in Rands	GDP	COMMON LANGUAGE	DISTANCE	COMMON TRADE AGREEMENT
Albania	18033154	18882095518	0	7508.121	0
Algeria	311870645	1.91913E+11	0	7433.072	1
Andorra	984554	3352032737	0	8066.814	0
Angola	7103356514	1.06714E+11	0	2457.726	1
Antigua And Barbuda	73310741	1757603704	1	10827.07	0
Argentina	2661167090	6.3277E+11	0	8128.39	1
Australia	13556646697	1.67542E+12	0	10819.277	1
Austria	1553215967	4.714E+11	0	8307.222	1
Azerbaijan	22763093	78721058824	0	7692.677	0
Bahamas	128302349	12897400000	1	12949.423	0
Bahrain	454140280	44390820479	0	6257.082	0
Bangladesh	3257978709	4.60201E+11	0	8660.339	0
Barbados	48084586	5637914515	1	10419.534	0
Belarus	30394551	72793457588	0	8863.57	1
Belgium	64095660699	5.78604E+11	0	8830.881	1
Belize	49764521	2824081836	1	13482.016	0
Benin	306942294	17401746309	0	4526.227	0
Bermuda	4003905	7550500000	1	11758.822	0
Bolivia, Plurinational State Of	71640241	43068885673	0	9763.319	0
Bosnia And Herzegovina	17198620	24527507288	0	7803.429	0
Botswana	76162711968	20352322157	1	259.274	1
Brazil	8265838262	1.9201E+12	0	7890.824	1
Brunei Darussalam	11294520	16681531646	0	9921.892	0
Bulgaria	864372616	89040398406	0	7628.001	0
Burkina Faso	586496839	18884619613	0	5319.844	1
Burundi	136030478	3073414678	1	2488.34	1
Cambodia	143461086	29956769529	0	9266.818	0
Cameroon	969011758	44341646509	1	3750.24	1
Canada	7463645422	2.13984E+12	1	13779.723	0
Cape Verde	65188074	2314816792	0	7192.549	1
Central African Republic	19232657	2382618615	0	3559.658	1
Chad	77490224	12704149842	0	4442.685	1
Chile	1051933757	3.01025E+11	0	9213.617	0
China	1.88588E+11	1.79632E+13	0	11662.891	1
Colombia	763971622	3.43939E+11	0	11460.697	0
Comoros	46925887	1242519407	0	2221.312	1
Congo	1812787119	14615532210	0	2750.109	0
Costa Rica	168820118	68380838316	0	12708.63	0
Côte D'ivoire	2193355868	70018715017	0	5194.605	1
Croatia	753011351	70964606465	0	8050.302	0
Cyprus	138108157	28439052741	0	6794.942	1
Czech Republic	7824643394	2.90924E+11	0	8540.823	1
Democratic Republic Of Congo	23639342872	58065953573	0	2750.109	1
Denmark	5885909709	3.95404E+11	1	9174.017	1
Djibouti	793271495	3515109075	0	4467.681	1
Dominica	5602207	612048148.1	1	10697.733	0
Dominican Republic	244097425	1.13642E+11	0	11667.747	0
Ecuador	257248673	1.15049E+11	0	11664.704	0
Egypt	1651230434	4.76748E+11	0	6213.199	1
El Salvador	15087753	32488720000	0	14413.854	0
Equatorial Guinea	25406898	11813908448	0	3890.369	1
Estonia	218675194	38100812959	0	9476.956	1
Eswatini	25411428723	4854167638	1	301.844	1
Ethiopia	501417810	1.26783E+11	0	4027.01	1
Fiji	43029581	4943248200	1	15080.706	0
Finland	1890736376	2.80826E+11	0	9557.583	1
France	13152259652	2.78291E+12	0	8683.484	1
Gabon	793206497	21071739228	0	3534.033	1
Gambia	72185041	2273060863	1	6516.727	1
Georgia	122257832	24605375420	0	7691.117	0
Germany	1.62875E+11	4.07219E+12	0	8820.487	1
Ghana	6815726226	72838798788	1	4635.802	1
Greece	1462110378	2.19066E+11	0	7100.949	1
Grenada	130715243	1256413185	1	10579.587	0
Guatemala	182813499	95003333381	0	13554.371	0
Guinea	1000393586	21227749389	0	5990.452	1
Guinea-Bissau	11356488	1633559092	0	6318.17	0
Guyana	339935396	15357537068	1	9678.316	0
Haiti	65228961	20253551885	0	12820.991	0
Honduras	278810075	31717700115	0	13199.127	0
Hungary	920738213	1.78789E+11	1	8195.468	1
Iceland	38675699	27841648044	1	10893.743	1
India	89547581942	3.38509E+12	1	7998.458	1
Indonesia	9259694519	1.3191E+12	1	8570.944	0
Iraq	844158776	2.64182E+11	0	6786.955	0
Ireland	2671510353	5.29245E+11	1	9401.419	1
Israel	5952168184	5.22033E+11	1	6438.362	0
Italy	28183121000	2.01043E+12	0	7692.556	1
Jamaica	109847800	17097760745	1	12323.241	0
Japan	1.39338E+11	4.23114E+12	0	13514.04	0
Jordan	715323339	47451499859	1	6466.504	0
Kazakhstan	368073794	2.20623E+11	1	9543.059	1
Kenya	8763707335	1.1342E+11	1	2872.888	1
Kiribati	1393878	223352943.2	1	15387.563	0
Kuwait	1721955690	1.84558E+11	1	6482.127	0
Latvia	1686151075	41153912663	0	9202.588	1
Lesotho	23577537659	2553459763	1	400.891	1
Liberia	707931072	4001047150	1	5513.672	0
Libya	68285395	45752336036	0	6709.932	0
Lithuania	296933128	70334299008	0	8947.966	1
Luxembourg	331856561	82274812251	1	8658.623	1
Madagascar	4883846640	14954967604	0	2636.045	1
Malawi	7593809571	13164667627	1	1431.91	1
Malaysia	12694094439	4.06306E+11	0	8520.317	0
Maldives	234855290	6189865408	1	5907.455	0
Mali	1422869499	18827176532	0	13504.013	0
Malta	660806275	17765270015	1	16946.106	1
Marshall Islands	378660751	279667900	0	15570.338	0
Mauritania	411701565	10375460680	0	6843.529	1
Mauritius	10420086889	12898307089	1	3056.779	1
Mexico	5593750222	1.41419E+12	0	14594.201	0
Moldova, Republic Of	7753004	14420947884	0	8090.761	0
Mongolia	30134848	16810883361	0	11318.706	0
Montenegro	29353319	6095978868	0	7638.997	0
Morocco	6607700799	1.34182E+11	1	6949.209	1
Mozambique	95334516809	17851491428	0	440.203	1
Namibia	56690962106	12607436976	1	1180.197	1
Nepal	17127595	40828247302	0	8522.878	0
Netherlands	97202444927	9.91115E+11	0	8976.722	1
New Zealand	1316062702	2.47234E+11	1	11804.102	0
Nicaragua	52298379	15671583878	1	13023.733	0
Niger	203098231	13969605583	0	5198.525	1
Nigeria	7669460504	4.77386E+11	1	4470.849	1
Norway	3198992231	5.79267E+11	0	9657.164	1
Oman	829265584	1.14667E+11	1	6389.123	0
Pakistan	12143720136	3.76533E+11	0	7954.77	0
Panama	712923356	76522511781	1	12206.933	0
Papua New Guinea	221874265	30633444295	1	12349.272	0
Paraguay	122997796	41722295362	0	9315.469	1
Peru	557327118	2.42632E+11	0	10904.626	0
Philippines	866798367	4.04284E+11	0	10977.222	0
Poland	7844820757	6.88177E+11	0	8698.244	1
Portugal	3411928655	2.51945E+11	0	8150.507	1
Puerto Rico	30041951	1.13435E+11	1	11300.015	0
Qatar	1555367778	2.37296E+11	1	6203.228	0
Romania	1837330405	3.01262E+11	0	7807.76	1
Russian Federation	4620441232	2.24042E+12	1	9106.279	1
Rwanda	487418604	13312796765	1	2653.019	1
Samoa	4955051	832421565.4	1	15112.584	0
Sao Tome And Principe	20228769	546680341.6	0	3703.394	1
Saudi Arabia	6599010139	1.10815E+12	0	5948.835	0
Senegal	2804438657	27684430244	0	6681.492	1
Serbia	30263449	63501748652	0	7883.528	0
Seychelles	1093579861	1588406479	1	3734.108	1
Sierra Leone	1081709447	3970343852	1	5877.625	1
Singapore	10178784069	4.66789E+11	1	8638.189	0
Sint Maarten (Dutch Part)	4224751	1571564246	1	10984.599	0
Slovakia	46392889	1.15469E+11	0	8290.479	1
Slovenia	2221693879	62117768015	0	8102.122	1
Solomon Islands	10577947	1595710784	1	13495.838	0
Somalia	164906705	8126105600	0	3602.215	0
Spain	22745164258	1.39751E+12	0	8061.795	1
Sri Lanka	4067384155	74403578363	1	6654.737	0
Sudan	269777992	51662241775	1	4621.266	0
Suriname	75883561	3620655116	1	9627.073	0
Sweden	2306887563	5.85939E+11	0	9505.625	1
Switzerland	8948072361	8.07706E+11	1	8347.091	0
Tajikistan	12190106	10492123388	0	8305.449	0
Tanzania	8835266790	75709289056	1	2227.793	1
Thailand	6656361251	4.95341E+11	1	8967.648	0
Timor-Leste	160000	3163324631	0	10323.734	0
Togo	1069901485	8126439481	0	4586.043	1
Trinidad And Tobago	62686761	27899082337	1	10486.582	0
Tunisia	228203226	46664948952	0	7205.417	1
Turks And Caicos Islands	748956	1138808881	1	11913.599	0
Tuvalu	3112498	60349391.1	1	15080.706	0
Uganda	1797996554	45559202049	1	2935.536	1
Ukraine	465776155	1.60503E+11	0	8475.71	0
United Arab Emirates	40930706404	5.07535E+11	0	6253.514	0
United Kingdom	1.02427E+11	3.07067E+12	1	9024.146	1
United States	1.77895E+11	2.54627E+13	1	12821.458	1
Uruguay	565458783	71177146197	0	8572.563	1
Uzbekistan	12366231	80391853885	0	8572.563	0
Vanuatu	10234329	983582864.6	1	13536.572	0
Viet Nam	5260492606	4.08802E+11	1	9854.74	0
Zambia	44313062268	29784454056	1	1148.828	1
Zimbabwe	52473837750	20678055598	1	929.143	1

[Joao Santos Silva]

Dear Rethabile Molapo,

I am afraid I do not understand your question and, in any case, I am not the best person to advise you on data manipulation issues.

Best wishes,

Joao