This document presents an empirical analysis of economic relationships between core and peripheral eurozone countries. It introduces the topic, reviews relevant literature, and outlines a theoretical model. The empirical section uses panel vector autoregression (PVAR) models to analyze the data, examining impulse response functions and variance decompositions. The conclusion summarizes the main findings. Tables and figures present economic indicator data and results of the PVAR analyses.

2. 


4. 1 INTRODUCTION ......................................................................................................................... 6
................................. 6
2 DATA & STYLIZED FACTS ........................................................................................................ 8
3 LITERATURE REVIEW ............................................................................................................. 18
..................................... 18
... 20
............................................................................................. 21
4 THEORY.................................................................................................................................. 25
........ 25
................................................................................................................................ 35
5 EMPIRICAL SECTION ............................................................................................................... 39
.............................................. 39
.................................................................................................. 40
.................................................................................................. 41
....................................................................................... 42
........................................................................................... 45
6 CONCLUSION .......................................................................................................................... 50
7 APPENDIX ............................................................................................................................... 52
8 BIBLIOGRAPHY ....................................................................................................................... 64

10. -8
-6
-4
-2
0
2
4
6
1980 1985 1990 1995 2000 2005 2010 2015
CORE PERIPHERY
-15
-10
-5
0
5
10
1980 1985 1990 1995 2000 2005 2010 2015
GERMANY
-15
-10
-5
0
5
10
1980 1985 1990 1995 2000 2005 2010 2015
SPAIN
-15
-10
-5
0
5
10
1980 1985 1990 1995 2000 2005 2010 2015
GREECE
-15
-10
-5
0
5
10
1980 1985 1990 1995 2000 2005 2010 2015
PORTUGAL
6

11. -2
0
2
4
6
8
10
12
1980 1985 1990 1995 2000 2005 2010 2015
PERIPHERY CORE
-1.0
-0.5
0.0
0.5
1.0
1.5
2000 2002 2004 2006 2008 2010 2012 2014
7
8

12. -2
0
2
4
6
8
10
12
1980 1985 1990 1995 2000 2005 2010 2015 2020
GERMANY SPAIN GREECE
0.8
0.9
1.0
1.1
1.2
1980 1985 1990 1995 2000 2005 2010 2015
GERMANY GREECE SPAIN
9
10

13. -4
0
4
8
12
1975 1980 1985 1990 1995 2000 2005 2010 2015
GERMANY
-4
0
4
8
12
1975 1980 1985 1990 1995 2000 2005 2010 2015
ITALY
-4
0
4
8
12
1975 1980 1985 1990 1995 2000 2005 2010 2015
SPAIN
-4
0
4
8
12
1975 1980 1985 1990 1995 2000 2005 2010 2015
GREECE
-4
0
4
8
12
1975 1980 1985 1990 1995 2000 2005 2010 2015
PORTUGAL
-4
0
4
8
12
1975 1980 1985 1990 1995 2000 2005 2010 2015
IRELAND

14. 0.9
1.0
1.1
1.2
1.3
1.4
1.5
1.6
94 96 98 00 02 04 06 08 10 12 14
CORE PERIPHERY

15. .040
.045
.050
.055
.060
.065
.070
.075
.080
92 94 96 98 00 02 04 06 08 10 12 14
CORE PERIPHERY

16. .00
.02
.04
.06
.08
.10
.12
92 94 96 98 00 02 04 06 08 10 12 14
Germany
.00
.02
.04
.06
.08
.10
.12
92 94 96 98 00 02 04 06 08 10 12 14
Greece
.00
.02
.04
.06
.08
.10
.12
92 94 96 98 00 02 04 06 08 10 12 14
Spain
.00
.02
.04
.06
.08
.10
.12
92 94 96 98 00 02 04 06 08 10 12 14
Italy
.00
.02
.04
.06
.08
.10
.12
92 94 96 98 00 02 04 06 08 10 12 14
Portugal
.00
.02
.04
.06
.08
.10
.12
92 94 96 98 00 02 04 06 08 10 12 14
Ireland

33. λ λ λ
λ λ

46. ≤ ≤ ≤

48. -.0008
-.0006
-.0004
-.0002
0
0 5 10
95% CI IRF
step
impulse : response
0
.01
.02
.03
0 5 10
95% CI IRF
step
impulse : response
-.002
-.001
0
0 5 10
95% CI IRF
step
impulse : response

54. ≠

55. //Enable Stata to access the pvar programme by setting the System Directory
//to the file with the programme has been saved.
sysdir set PERSONAL
ad.ucl.ac.ukhomeuctpbboDocumentsDissertationStataPVAR
// Import the data from excel.
import excel "N:DocumentsDissertationDataData for VAR.xlsx",
sheet("Tabelle1") firstrow
//Tell Stata that the data is panel and set an identifying variable
//for the cross-section and the time variable.
xtset C Year
//Execute the regression with three endogenous variable and one exogenous
//variable.

56. pvar drridws drswlag dhpsl if Year >= 1977 & Year <= 2011, exog (dgns)
// Generate an impulse response function based on 200 Monte Carlo draw and
with 95% confidence bands.
pvarirf, impulse(drswlag) response(drridws) mc(200) level(95)

64. ‐