A new database is available that compiles 46 variables for 243 countries from 110 sources. Overall, that’s a very nice public good. A ton of thanks to the authors. Their website is available and their GitHub too. The database is available by using the following Stata script, if you want to download all the series. The file for replicating this blog is available on my own GitHub:
**# First tests of the Global Macroeconomic Database by
*Müller, Xu, Lehbib, and Chen (2025)
**# Start of Program
cd C:\Users\jamel\Dropbox\stata\gmd
capture log close _all
log using GDM_Jan25.log, name(GDM_Jan25) text replace
clear
net install GMD, from(http://www.globalmacrodata.com/package)
global CS1 "nGDP rGDP rGDP_pc inv inv_GDP finv finv_GDP rcons cons cons_GDP imports imports_GDP exports CA CA_GDP pop govexp govexp_GDP govrev govrev_GDP govtax govtax_GDP govdef govdef_GDP govdebt govdebt_GDP CPI HPI deflator infl unemp USDfx REER strate ltrate cbrate M0 M1 M2 M3 M4 BankingCrisis CurrencyCrisis SovDebtCrisis"
GMD $CS1, country() version(2025_01)
des
encode ISO3, generate(cn)
xtset cn year
tsfill, full
order cn, first
decode cn, generate(iso3c)
order cn iso3c, first
kountry iso3c, from(iso3c)
rename NAMES_STD country
order cn iso3c country, first
drop countryname ISO3
xtdescribe
summ $CS1
tabstat $CS1, stat(count)
tabstat $CS1, stat(count) by(cn) save
return list
putexcel set "tabstat", replace sheet(Stats)
putexcel set "tabstat", modify sheet(Stats)
forvalues v=1(1)243 {
putexcel (A`v') = (r(name`v'))
putexcel (B`v') = matrix(r(Stat`v'))
}
*https://www.statalist.org/forums/forum/general-stata-discussion/general/1473382-exporting-variable-label-with-putexcel
putexcel set filename, replace
local row = 1
foreach x of varlist $CS1 {
describe `x'
local varlabel : var label `x'
putexcel A`row' = ("`varlabel'")
local row = `row'+1
}
log close _all
exit
**# End of Program for the Local Projections The descriptive statistics are the following:
Variable | Obs Mean Std. dev. Min Max
-------------+---------------------------------------------------------
nGDP | 19,477 1.98e+08 8.17e+09 1.01e-13 7.17e+11
rGDP | 20,974 6.63e+07 7.29e+08 3.045606 1.94e+10
rGDP_pc | 20,538 1.99e+07 1.22e+08 2.127904 1.86e+09
inv | 15,336 9.09e+07 3.43e+09 -301546.2 2.64e+11
inv_GDP | 15,259 23.22189 14.84143 -908.1306 255.037
-------------+---------------------------------------------------------
finv | 14,015 2.03e+07 4.75e+08 -20231 3.84e+10
finv_GDP | 13,953 21.90447 10.34467 -4.968716 157.8736
rcons | 14,175 4.89e+07 4.73e+08 1.64e-06 1.03e+10
cons | 12,760 5.23e+07 1.15e+09 1.96e-10 9.04e+10
cons_GDP | 12,696 82.59445 22.5204 8.835807 298.3758
-------------+---------------------------------------------------------
imports | 24,470 2.46e+07 6.50e+08 9.65e-15 4.00e+10
imports_GDP | 15,100 42.57324 40.63606 2.03e-11 624.5701
exports | 25,150 2.66e+07 7.72e+08 8.48e-15 4.65e+10
CA | 12,980 6753149 3.01e+08 -7.62e+08 2.15e+10
CA_GDP | 12,986 -2.419042 12.60792 -242.188 314.906
-------------+---------------------------------------------------------
pop | 51,930 13.32227 67.98541 3.77e-06 1523.385
govexp | 19,557 3.11e+07 1.18e+09 3.81e-15 1.02e+11
govexp_GDP | 14,907 25.77256 22.46286 1.23e-06 594.77
govrev | 20,547 2.47e+07 9.45e+08 5.45e-22 8.55e+10
govrev_GDP | 14,667 22.77117 15.32084 .0034447 164.054
-------------+---------------------------------------------------------
govtax | 14,138 3622758 5.33e+07 6.48e-14 2.15e+09
govtax_GDP | 9,472 14.57864 8.539338 .0000628 152.6961
govdef | 13,624 -7402894 2.56e+08 -1.67e+10 6.45e+07
govdef_GDP | 13,674 -1.937165 10.52888 -557.499 125.135
govdebt | 13,945 1.03e+08 3.42e+09 0 2.55e+11
-------------+---------------------------------------------------------
govdebt_GDP | 14,689 52.45973 51.31307 0 2092.92
CPI | 18,659 3.04e+09 2.45e+11 1.73e-15 2.75e+13
HPI | 3,517 57.18159 94.8863 2.56e-12 3093.807
deflator | 17,474 919.081 27368 2.27e-15 1676309
infl | 19,692 5655028 7.54e+08 -99.97137 1.06e+11
-------------+---------------------------------------------------------
unemp | 7,645 7.686186 6.259881 0 70
USDfx | 23,109 189.5223 1478.73 3.49e-16 42000
REER | 11,525 242.8519 3548.467 0 279940.5
strate | 7,383 9.706535 83.74483 -.8191667 6404.965
ltrate | 7,747 7.201801 5.928785 -.5238333 209.6
-------------+---------------------------------------------------------
cbrate | 8,730 23.13453 1110.963 -.75 103484.2
M0 | 14,443 6.41e+12 7.70e+14 -27.7 9.26e+16
M1 | 10,989 1.11e+07 1.38e+08 5.92e-18 4.83e+09
M2 | 10,509 4.78e+12 4.90e+14 5.27e-18 5.02e+16
M3 | 3,143 5.07e+07 4.10e+08 1.90e-10 7.94e+09
-------------+---------------------------------------------------------
M4 | 288 635671 1975027 .022 1.49e+07
BankingCri~s | 19,933 .0181608 .1335362 0 1
CurrencyCr~s | 19,596 .0279139 .1647303 0 1
SovDebtCri~s | 19,069 .0145786 .1198618 0 1
You can also have the coverage per country in this Excel file:
I made a small regression for the current account reaction to the exchange rate and to the GDP per capita:
gen LREER=log(REER)
gen LrGDP_pc=log(rGDP_pc)
areg CA_GDP L5.LREER L5.LrGDP_pc, absorb(cn year) rob
And, for sub-Saharan African countries:
