Hi,
The code below corresponds to an LPM on the probability of commune, with the first panel corresponding to centuries before and after church exposure and the second panel corresponding to centuries before and after start of extended prohibition.
Exporting the results using esttab produces a disorganised table including all the year and category fixed effects.
I want to save the results in a matrix and export using frmttable or esttab to produce a table which does not need as much mannual cleaning.
Could anyone please help me with the code in producing this I? I don't have a lot of experience in the frmttable command or matrices in stata.
Many Thanks in advance, my code is below
*Table 3, Panel 1
preserve
keep if sample10K==1
local v bo_commune exposure
eststo: xi: areg `v' bo_plundered i.year, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered i.year bo_seariver_*, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered i.year caloric_suit_100_*, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered i.year bo_roman_*, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered i.year Europe_*, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered BandAB i.year bo_ever_bishop_*, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered bo_citypop_le10_ bo_citypop_le10_lag i.year, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered i.year bo_seariver_* caloric_suit_100_* bo_roman_* Europe_* BandAB bo_ever_bishop_* bo_citypop_le10_ bo_citypop_le10_lag, absorb(cellID) cluster(cellID)
esttab using tables\Table3_Panel_1.rtf, replace star(* 0.10 ** 0.05 *** 0.01) se cells(b(star fmt(3)) se(par fmt(3))) scalars(r2)
eststo clear
restore
* Table 3, Panel 2
preserve
keep if sample10K==1
local v bo_commune exposure exposure_eb
eststo: xi: areg `v' bo_plundered i.year, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered i.year bo_seariver_*, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered i.year caloric_suit_100_*, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered i.year bo_roman_*, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered i.year Europe_*, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered BandAB i.year bo_ever_bishop_*, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered bo_citypop_le10_ bo_citypop_le10_lag i.year, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered i.year bo_seariver_* caloric_suit_100_* bo_roman_* Europe_* BandAB bo_ever_bishop_* bo_citypop_le10_ bo_citypop_le10_lag, absorb(cellID) cluster(cellID)
esttab using tables\Table3_Panel_2.rtf, replace star(* 0.10 ** 0.05 *** 0.01) se cells(b(star fmt(3)) se(par fmt(3))) scalars(r2)
eststo clear
restore
The code below corresponds to an LPM on the probability of commune, with the first panel corresponding to centuries before and after church exposure and the second panel corresponding to centuries before and after start of extended prohibition.
Exporting the results using esttab produces a disorganised table including all the year and category fixed effects.
I want to save the results in a matrix and export using frmttable or esttab to produce a table which does not need as much mannual cleaning.
Could anyone please help me with the code in producing this I? I don't have a lot of experience in the frmttable command or matrices in stata.
Many Thanks in advance, my code is below
*Table 3, Panel 1
preserve
keep if sample10K==1
local v bo_commune exposure
eststo: xi: areg `v' bo_plundered i.year, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered i.year bo_seariver_*, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered i.year caloric_suit_100_*, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered i.year bo_roman_*, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered i.year Europe_*, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered BandAB i.year bo_ever_bishop_*, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered bo_citypop_le10_ bo_citypop_le10_lag i.year, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered i.year bo_seariver_* caloric_suit_100_* bo_roman_* Europe_* BandAB bo_ever_bishop_* bo_citypop_le10_ bo_citypop_le10_lag, absorb(cellID) cluster(cellID)
esttab using tables\Table3_Panel_1.rtf, replace star(* 0.10 ** 0.05 *** 0.01) se cells(b(star fmt(3)) se(par fmt(3))) scalars(r2)
eststo clear
restore
* Table 3, Panel 2
preserve
keep if sample10K==1
local v bo_commune exposure exposure_eb
eststo: xi: areg `v' bo_plundered i.year, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered i.year bo_seariver_*, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered i.year caloric_suit_100_*, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered i.year bo_roman_*, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered i.year Europe_*, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered BandAB i.year bo_ever_bishop_*, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered bo_citypop_le10_ bo_citypop_le10_lag i.year, absorb(cellID) cluster(cellID)
eststo: xi: areg `v' bo_plundered i.year bo_seariver_* caloric_suit_100_* bo_roman_* Europe_* BandAB bo_ever_bishop_* bo_citypop_le10_ bo_citypop_le10_lag, absorb(cellID) cluster(cellID)
esttab using tables\Table3_Panel_2.rtf, replace star(* 0.10 ** 0.05 *** 0.01) se cells(b(star fmt(3)) se(par fmt(3))) scalars(r2)
eststo clear
restore
