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No blessing, no curse? On the benefits of being aresource-rich southern region of Italy
Research in Economics, forthcoming. DOI: 10.1016/j.rie.2015.03.003
Roberto Iacono
NTNU & HiST
Oxford, 22.08.2015
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 1 / 32
Historical background
“Call your men back, let them return from wherever they migrated to, andtell them that finally there will be jobs for them, here.”E.Mattei, 27.10.1962.
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 2 / 32
The research question
Has intensive exploitation of oil fields and greater resource revenues inBasilicata, all else equal, led to a higher degree of regional economicdevelopment?
010
2030
4050
Barre
ls o
f oil
per c
apita
1980 1990 2000 2010Year
Source: UNMIG
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 3 / 32
Basilicata and the rest of Mezzogiorno
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 4 / 32
Contribution
1 Estimate the economic effect of oil in the region of Basilicata duringthe period 1980− 2009, compared to control regions.
Synthetic Control Method (SCM) (Abadie et al. 2014): weight controlregions to construct a counterfactual that replicates the treated regionbefore treatment.
2 Discussion about channels.
Control rights; Organized crime; Sectoral effects; Labor migration.
3 Results: null aggregate effects; significant sectoral effects.
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 5 / 32
Contribution
1 Estimate the economic effect of oil in the region of Basilicata duringthe period 1980− 2009, compared to control regions.
Synthetic Control Method (SCM) (Abadie et al. 2014): weight controlregions to construct a counterfactual that replicates the treated regionbefore treatment.
2 Discussion about channels.
Control rights; Organized crime; Sectoral effects; Labor migration.
3 Results: null aggregate effects; significant sectoral effects.
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 5 / 32
Contribution
1 Estimate the economic effect of oil in the region of Basilicata duringthe period 1980− 2009, compared to control regions.
Synthetic Control Method (SCM) (Abadie et al. 2014): weight controlregions to construct a counterfactual that replicates the treated regionbefore treatment.
2 Discussion about channels.
Control rights; Organized crime; Sectoral effects; Labor migration.
3 Results: null aggregate effects; significant sectoral effects.
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 5 / 32
Contribution
1 Estimate the economic effect of oil in the region of Basilicata duringthe period 1980− 2009, compared to control regions.
Synthetic Control Method (SCM) (Abadie et al. 2014): weight controlregions to construct a counterfactual that replicates the treated regionbefore treatment.
2 Discussion about channels.
Control rights; Organized crime; Sectoral effects; Labor migration.
3 Results: null aggregate effects; significant sectoral effects.
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 5 / 32
Contribution
1 Estimate the economic effect of oil in the region of Basilicata duringthe period 1980− 2009, compared to control regions.
Synthetic Control Method (SCM) (Abadie et al. 2014): weight controlregions to construct a counterfactual that replicates the treated regionbefore treatment.
2 Discussion about channels.
Control rights; Organized crime; Sectoral effects; Labor migration.
3 Results: null aggregate effects; significant sectoral effects.
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 5 / 32
Empirical Strategy
Identification strategy: exploit the fact that Basilicata producedthroughout the period of analysis a fraction close to unity of oilextracted in the 5+ 1 southern Italian regions.
.4.6
.81
Oil
extra
cted
(ton
s): B
asili
cata
/Tot
. DP
regi
ons
1980 1990 2000 2010Year
Source: UNMIG
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 6 / 32
Institutional agreement and royalties
Variable Location Net value based royaltiesOil production Onshore 7%
Offshore 4%Gas production Onshore 7%
Offshore 7%Revenue’s benefiter State (30%); Region (70%)
Law 140/1999: southern regions are entitled to 100% of royaltyrevenues. Q: still too low?
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 7 / 32
Empirical Literature
1 Sub-national economic effects of resource revenues:
Caselli and Michaels (2013); Borge et al. (2013); Kan et al. (2014);Papyrakis and Raveh (2014).
2 Comparative Case Studies using SCM:
Abadie et al. (2014); Pinotti (2012).
3 On the case of Basilicata:
Percoco (2012).
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 8 / 32
Empirical Literature
1 Sub-national economic effects of resource revenues:
Caselli and Michaels (2013); Borge et al. (2013); Kan et al. (2014);Papyrakis and Raveh (2014).
2 Comparative Case Studies using SCM:
Abadie et al. (2014); Pinotti (2012).
3 On the case of Basilicata:
Percoco (2012).
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 8 / 32
Empirical Literature
1 Sub-national economic effects of resource revenues:
Caselli and Michaels (2013); Borge et al. (2013); Kan et al. (2014);Papyrakis and Raveh (2014).
2 Comparative Case Studies using SCM:
Abadie et al. (2014); Pinotti (2012).
3 On the case of Basilicata:
Percoco (2012).
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 8 / 32
Empirical Literature
1 Sub-national economic effects of resource revenues:
Caselli and Michaels (2013); Borge et al. (2013); Kan et al. (2014);Papyrakis and Raveh (2014).
2 Comparative Case Studies using SCM:
Abadie et al. (2014); Pinotti (2012).
3 On the case of Basilicata:
Percoco (2012).
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 8 / 32
Empirical Literature
1 Sub-national economic effects of resource revenues:
Caselli and Michaels (2013); Borge et al. (2013); Kan et al. (2014);Papyrakis and Raveh (2014).
2 Comparative Case Studies using SCM:
Abadie et al. (2014); Pinotti (2012).
3 On the case of Basilicata:
Percoco (2012).
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 8 / 32
Empirical Literature
1 Sub-national economic effects of resource revenues:
Caselli and Michaels (2013); Borge et al. (2013); Kan et al. (2014);Papyrakis and Raveh (2014).
2 Comparative Case Studies using SCM:
Abadie et al. (2014); Pinotti (2012).
3 On the case of Basilicata:
Percoco (2012).
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 8 / 32
Implementing the SCM: choosing the DP
1 Choosing the Donor Pool (DP).
Donor Pool, 5 southern Italian regions: Campania, Molise, Puglia,Sardegna, Calabria.Choice informed as well by a study of European regional economiesfrom the Bank of Italy (2012).
2 Generating weights for units in the DP.3 Estimating Impact on the Economy of Basilicata.
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 9 / 32
Implementing the SCM: choosing the DP
1 Choosing the Donor Pool (DP).
Donor Pool, 5 southern Italian regions: Campania, Molise, Puglia,Sardegna, Calabria.
Choice informed as well by a study of European regional economiesfrom the Bank of Italy (2012).
2 Generating weights for units in the DP.3 Estimating Impact on the Economy of Basilicata.
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 9 / 32
Implementing the SCM: choosing the DP
1 Choosing the Donor Pool (DP).
Donor Pool, 5 southern Italian regions: Campania, Molise, Puglia,Sardegna, Calabria.Choice informed as well by a study of European regional economiesfrom the Bank of Italy (2012).
2 Generating weights for units in the DP.3 Estimating Impact on the Economy of Basilicata.
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 9 / 32
Implementing the SCM: choosing the DP
1 Choosing the Donor Pool (DP).
Donor Pool, 5 southern Italian regions: Campania, Molise, Puglia,Sardegna, Calabria.Choice informed as well by a study of European regional economiesfrom the Bank of Italy (2012).
2 Generating weights for units in the DP.
3 Estimating Impact on the Economy of Basilicata.
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 9 / 32
Implementing the SCM: choosing the DP
1 Choosing the Donor Pool (DP).
Donor Pool, 5 southern Italian regions: Campania, Molise, Puglia,Sardegna, Calabria.Choice informed as well by a study of European regional economiesfrom the Bank of Italy (2012).
2 Generating weights for units in the DP.3 Estimating Impact on the Economy of Basilicata.
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 9 / 32
Implementing the SCM: generating weights
SCM Algorithm: define GDP per capita as Y and its determinants X,such as:
Population, Labor Force, Gross Fixed Investment, Pop. shares byeducation level, Value Added shares of GDP by Industry.
Matching period (1980− 1998): Y pre0 and X0 in DP; Ypre1 and X1 in
treated unit.
Post-treatment (1999− 2009): Y post0 in DP; Y post1 in treated unit.
SC unit is given by the vector of weights W ∗ = (w1, ...,w5) (withw1 + ...+ w5 = 1) chosen as W that minimizes
k
∑m=1
vm(X1m − X0mW )2
in which vm are weights assigned to the m− th determinant.Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 10 / 32
Implementing the SCM: generating weights
SCM Algorithm: define GDP per capita as Y and its determinants X,such as:
Population, Labor Force, Gross Fixed Investment, Pop. shares byeducation level, Value Added shares of GDP by Industry.
Matching period (1980− 1998): Y pre0 and X0 in DP; Ypre1 and X1 in
treated unit.
Post-treatment (1999− 2009): Y post0 in DP; Y post1 in treated unit.
SC unit is given by the vector of weights W ∗ = (w1, ...,w5) (withw1 + ...+ w5 = 1) chosen as W that minimizes
k
∑m=1
vm(X1m − X0mW )2
in which vm are weights assigned to the m− th determinant.Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 10 / 32
Implementing the SCM: generating weights
SCM Algorithm: define GDP per capita as Y and its determinants X,such as:
Population, Labor Force, Gross Fixed Investment, Pop. shares byeducation level, Value Added shares of GDP by Industry.
Matching period (1980− 1998): Y pre0 and X0 in DP; Ypre1 and X1 in
treated unit.
Post-treatment (1999− 2009): Y post0 in DP; Y post1 in treated unit.
SC unit is given by the vector of weights W ∗ = (w1, ...,w5) (withw1 + ...+ w5 = 1) chosen as W that minimizes
k
∑m=1
vm(X1m − X0mW )2
in which vm are weights assigned to the m− th determinant.Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 10 / 32
Implementing the SCM: generating weights
SCM Algorithm: define GDP per capita as Y and its determinants X,such as:
Population, Labor Force, Gross Fixed Investment, Pop. shares byeducation level, Value Added shares of GDP by Industry.
Matching period (1980− 1998): Y pre0 and X0 in DP; Ypre1 and X1 in
treated unit.
Post-treatment (1999− 2009): Y post0 in DP; Y post1 in treated unit.
SC unit is given by the vector of weights W ∗ = (w1, ...,w5) (withw1 + ...+ w5 = 1) chosen as W that minimizes
k
∑m=1
vm(X1m − X0mW )2
in which vm are weights assigned to the m− th determinant.Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 10 / 32
Implementing the SCM: generating weights
Region Synthetic weights W ∗
Campania 0Molise .354Apulia .106Sardinia 0Calabria .54
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 11 / 32
Implementing the SCM: estimating impact
SCM Algorithm: generate synthetic Basilicata using assigned weights;compare actual and synthetic Basilicata.
Y1t −6∑j=2w ∗j Yjt
a) Real GDP per capita as dependent variable.
Matching period
050
0010
000
1500
020
000
GD
P p
er c
apita
, con
stan
t pric
es
1980 1990 2000 2010Year
Treated unit Synthetic control unit
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 12 / 32
Time-placebo tests - Treatment 1992 (left)
Real GDP per capita
Matching period
050
0010
000
1500
020
000
GD
P p
er c
apita
, co
nsta
nt p
rices
1980 1990 2000 2010Year
Treated unit Synthetic control unit
Matching period
050
0010
000
1500
020
000
GD
P p
er c
apita
, co
nsta
nt p
rices
1980 1990 2000 2010Year
Treated unit Synthetic control unit
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 13 / 32
Implementing the SCM: estimating impact
b) Employment rate (total) as dependent variable.
Region Synthetic weights W ∗
Campania 0Molise .139Apulia .657Sardinia .204Calabria 0
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 14 / 32
Implementing the SCM: estimating impact
b) Employment rate (total) as dependent variable.
Matching period36
3840
4244
46E
mpl
oym
ent r
ate,
tota
l
1980 1990 2000 2010Year
Treated unit Synthetic control unit
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 15 / 32
Time-placebo tests - Treatment 1992 (left)
Employment rate
Matching period
3638
4042
4446
Em
ploy
men
t ra
te,
tota
l
1980 1990 2000 2010Year
Treated unit Synthetic control unit
Matching period
3638
4042
4446
Em
ploy
men
t ra
te,
tota
l1980 1990 2000 2010
Year
Treated unit Synthetic control unit
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 16 / 32
Implementing the SCM: estimating impact
c) Gross Fixed Inv. as dependent variable.
Region Synthetic weights W ∗
Campania 0Molise .83Apulia 0Sardinia .009Calabria .161
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 17 / 32
Implementing the SCM: estimating impact
c) Gross Fixed Inv. as dependent variable.
Matching period50
010
0015
0020
0025
0030
00G
ross
fixe
d in
vest
men
t, co
nsta
nt p
rices
1980 1990 2000 2010Year
Treated unit Synthetic control unit
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 18 / 32
Time-placebo tests - Treatment 1992 (left)
Gross fixed investment
Matching period
500
1000
1500
2000
2500
3000
Gro
ss f
ixed
inve
stm
ent,
mill.
Eur
o
1980 1990 2000 2010Year
Treated unit Synthetic control unit
Matching period
500
1000
1500
2000
2500
3000
Gro
ss f
ixed
inve
stem
ent,
mill.
Eur
o1980 1990 2000 2010
Year
Treated unit Synthetic control unit
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 19 / 32
Robustness main results
Yi ,t = γi + δt + λTi ,t + X′i ,tβ+ εi ,t
with
Yi ,t = outcome of interest for region i , year t.
γi = region fixed effects.
δt = time fixed effects.
Ti ,t = dummy for the treated region in the post-treatment period.
X′i ,t = a set of covariates.
εi ,t = clustered error term.
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 20 / 32
Robustness main results
Table (1) (2) (3)GDP per capita, Employment Gross fixed inv.constant prices rate, total constant prices
Diff-in-diff -352.8* -0.646 -1,404**(179.1) (0.786) (651.9)
Fixed eff. YES YES YESObservations 180 180 180R-squared 0.995 0.529 0.827Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1
Note: standard errors adjusted for clusters.
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 21 / 32
Discussion about channels
1 Control rights structure.2 The plague of organized crime.3 Sectoral effects.4 Labor migration.
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 22 / 32
Control rights structure
Brunnschweiler and Valente (2013): Int’l Partnership is linked tohigher GDP levels than Domestic/Foreign Control, regardless ofpolitical regime type.
Brunnschweiler and Valente (2013)’s coding of Italy: Foreign1930− 1956 and 1995− 2008, Partnership in between.
Q: would have Italy (and Basilicata)’s GDP benefited fromPartnership?
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 23 / 32
The plague of organized crime
Pinotti (2012): exposure to mafia activity (proxied by increase inmurders) after 1970s lowered GDP per capita by 16% in the treatedunit (Basilicata-Apulia), as compared to control group.
Q: can we rule out that public royalty revenues in Basilicatarepresented a profit opportunity for criminal organizations?
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 24 / 32
Sectoral effects
VAi ,t = γi + δt + λTi ,t + X′i ,tβ+ εi ,t
with
VAi ,t = value added (% of GDP) for sector (..) in region i , year t.
γi = region fixed effects.
δt = time fixed effects.
Ti ,t = dummy for the treated region in the post-treatment period.
X′i ,t = a set of covariates.
εi ,t = clustered error term.
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 25 / 32
Sectoral effects
Dependent variable Industry, % of GDP(1) (2) (3)
Diff-in-diff 2.886*** 4.730*** 5.306***(0.720) (0.620) (1.010)
Real GDP per capita 0.000246(0.000276)
Gross fixed inv. -0.000365***(7.83e-05)
Constant 15.60*** 18.51*** 18.56***(0.253) (0.610) (0.818)
Region fixed effects NO YES YESTime fixed effects NO YES YESObservations 180 180 180R-squared 0.044 0.560 0.662
Robust standard errors in parentheses.Asterisks denote significance levels: *** p<0.01, ** p<0.05, * p<0.1Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 26 / 32
Sectoral effects: SCM for industry
1416
1820
22S
hare
of
valu
e ad
ded,
Ind
ustr
y
1980 1990 2000 2010Year
Treated unit Synthetic control unit
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 27 / 32
Sectoral effects
Dependent variable Constructions, % of GDP(1) (2) (3)
Diff-in-diff -0.755* -1.577*** -0.524(0.428) (0.358) (0.329)
Real GDP per capita 0.000416***(0.000151)
Gross fixed inv. 0.000327***(4.29e-05)
Constant 8.397*** 12.67*** 11.38***(0.197) (0.352) (0.448)
Region fixed effects NO YES YESTime fixed effects NO YES YESObservations 180 180 180R-squared 0.005 0.883 0.919Asterisks denote significance levels: *** p<0.01, ** p<0.05, * p<0.1
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 28 / 32
Sectoral effects: SCM for constructions
68
1012
1416
Con
stru
ctio
ns, s
hare
of G
DP
1980 1990 2000 2010Year
T reated unit Synthetic control unit
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 29 / 32
Labor migration
5906
0161
2229
Bas
ilica
ta
1980 1990 2000 2010
1812
4557
1893
0968
Tot
al D
P re
gion
s
1980 1990 2000 2010Year
Source: ISTAT
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 30 / 32
Concluding remarks
Null hypothesis of aggregate positive economic effects: rejected.
Sectoral effects: positive for industry.
No blessing, no curse?
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 31 / 32
Concluding remarks
Null hypothesis of aggregate positive economic effects: rejected.
Sectoral effects: positive for industry.
No blessing, no curse?
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 31 / 32
Concluding remarks
Null hypothesis of aggregate positive economic effects: rejected.
Sectoral effects: positive for industry.
No blessing, no curse?
Roberto Iacono (Institute) No blessing, no curse? Oxford, 22.08.2015 31 / 32
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