Dear Statalisters,

For my MSc dissertation I am studying panel data of bilateral FDI flows, with 30 sending countries over 2001-2012. My question of interest is whether a characteristic of the sending countries (changes over time), moderates the relation between FDI and labor rights (changes over time) in the receiving country. I have reviewed quite some papers and answers on this fora, and the PPML method Santos

Ive taken the following steps after creating the database (in long format)

- creating fixed effects:

egen origin = group(iso3n_o)

qui tab iso3n_o, g(origin_dum_)

egen destination = group(iso3n_d)

qui tab iso3n_d, g(destination_dum_)

- changed negative fdi flows into "1"s (Folfas, 2001)

recode fdi_outflow (-60000/-1 = 1), generate (fdi_outflow_pos)

- generated my interaction term

generate codet_int = worker*codetermination

Then I ran the following:

ppml fdi_outflow_pos ldistw lgdp_o lgdp_d worker contig comlang_off colony comcur ores fuel codet_int codetermination origin_dum_* destination_dum_*, cluster(distw)

This leads to the following results (Ive attached a picture of the results table)

Number of parameters: 186

Number of observations: 17074

Pseudo log-likelihood: -7719799.4

R-squared: .41231141

Option strict is: off

After this I ran the RESET test, this test was insignificant at the 0.05 level, but very close (0.0684) which worries me a bit.

It would be of great help, if anyone could help me with the following:

1. is this generally a correct way of specifying the model?

and more specifically:

2. does PPML account for multilateral resistance terms or should I add these separately?

3. is clustering by distance in this case right?

4. how can I account for the time dimension (I have looked at Tom Zylkin's "ppml_panel_sg", but this does not allow variables like GDP)

Id be very happy if someone could help me out here, I'll gladly provide more information.

Hester

For my MSc dissertation I am studying panel data of bilateral FDI flows, with 30 sending countries over 2001-2012. My question of interest is whether a characteristic of the sending countries (changes over time), moderates the relation between FDI and labor rights (changes over time) in the receiving country. I have reviewed quite some papers and answers on this fora, and the PPML method Santos

*Silva*and*Tenreyro*(2006) seems appropriate in this case (also since I have quite some zero FDI flows). I have used Stata before, but Im not very familiar with analyzing panel data so I was wondering if anyone on the forum could answer some of my questions? (apologies in advance if i should have included other information to assess this)Ive taken the following steps after creating the database (in long format)

- creating fixed effects:

egen origin = group(iso3n_o)

qui tab iso3n_o, g(origin_dum_)

egen destination = group(iso3n_d)

qui tab iso3n_d, g(destination_dum_)

- changed negative fdi flows into "1"s (Folfas, 2001)

recode fdi_outflow (-60000/-1 = 1), generate (fdi_outflow_pos)

- generated my interaction term

generate codet_int = worker*codetermination

Then I ran the following:

ppml fdi_outflow_pos ldistw lgdp_o lgdp_d worker contig comlang_off colony comcur ores fuel codet_int codetermination origin_dum_* destination_dum_*, cluster(distw)

This leads to the following results (Ive attached a picture of the results table)

Number of parameters: 186

Number of observations: 17074

Pseudo log-likelihood: -7719799.4

R-squared: .41231141

Option strict is: off

After this I ran the RESET test, this test was insignificant at the 0.05 level, but very close (0.0684) which worries me a bit.

It would be of great help, if anyone could help me with the following:

1. is this generally a correct way of specifying the model?

and more specifically:

2. does PPML account for multilateral resistance terms or should I add these separately?

3. is clustering by distance in this case right?

4. how can I account for the time dimension (I have looked at Tom Zylkin's "ppml_panel_sg", but this does not allow variables like GDP)

Id be very happy if someone could help me out here, I'll gladly provide more information.

Hester

## Comment