13.06.2016 Views

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

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

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

SHOW MORE
SHOW LESS

Create successful ePaper yourself

Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.

Table 2 – Regressions for evolution of per capita output gap between the “poor”<br />

and the “rich” region.<br />

Germany<br />

Italy<br />

(1992-2014) (1991-2014)<br />

Dependent variable: GDP per capita (“poor”)/GDP per capita (“rich”) (in const. prices)<br />

Const. 15.922*** 40.326<br />

(4.835) (24.163)<br />

GDPgapt-1 0.618*** 0.723*<br />

(0.064) (0.379)<br />

Invgap t-1 10.402*** 1.254<br />

(2.909) (1.644)<br />

ULC -0.105* -0.255**<br />

(0.054) (0.081)<br />

Dummy 2002/1996 4.985*** 1.777*<br />

(0.192) (1.035)<br />

SE of regression 0.763 0.541<br />

R̅2 0.982 0.837<br />

Note: Heteroskedasticity-robust standard errors in brackets.<br />

GDPgap = Ratio of “poor” region’s GDP per capita to “rich” region’s GDP per capita.<br />

Invgap = Ratio of investment in machinery and equipment/GDP in “poor” region to<br />

investment in machinery and equipment/GDP in “rich” region.<br />

ULC = Ratio of manufacturing unit labour costs in “poor” region to manufacturing labour<br />

costs in “rich” region.<br />

* Significant at 10%.<br />

** Significant at 5%.<br />

*** Significant at 1%.

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!