n?u=RePEc:ais:wpaper:1603&r=his

controlling for the population and the size of the regions, the constructed trade share
contributes significant explanatory power to actual trade.
The predicted values are then used as instruments for the observed trade shares in
the regressions of GDP per capita of region i on the trade share, the logarithm of
population, the logarithm of size, and the area dummies for eastern Länder
(Germany) and for southern regions (Italy):
(A3)
Equation (A3) is estimated separately for Germany and for Italy both by OLS and by
IV, and the regression results are reported in Table 4 (without the area dummies) and in
Table 5 (with the area dummies).
In order to validate the separate estimation of GDP per capita in Germany and in Italy,
Table A3 presents the results of a pooled regression for the regions of the two countries.
Columns (1) and (2) present the results of estimation by OLS, and columns (3) and (4)
the estimation by IV. Columns (2) and (4) contain the coefficients of the variables
interacted with a dummy variable which takes the value 1 for all the regions in East
Germany. The null hypothesis that the coefficients on the variables are the same for
Germany and Italy is rejected both when the equation is estimated by OLS (F(6,24) =
2.70) and when it is estimated by IV (Chi2(6) = 32,48).
Data sources: Regional accounts were obtained from the official German and Italian
statistical sites (Statistische Ämter des Bundes und der Länder, Volkswirtschaftliche
Gesamtrechnung der Länder; ISTAT, Conti e aggregati economici territoriali). Foreign
trade data for Germany come from the Statistisches Bundesamt, GENESIS-Online data
bank; for Italy from ISTAT’s Coeweb data bank. Distances between the various
national and regional capitals come from the DistanceFromTo website. Whether
countries or regions were landlocked or had common borders was subjectively decided
by looking at an atlas.