No blessing from oil? Impact on Basilicata's economy

No blessing, no curse? On the bene…ts of being a
resource-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, and
tell them that …nally there will be jobs for them, here.”
E.Mattei, 27.10.1962.

The research question
Has intensive exploitation of oil …elds and greater resource revenues in
Basilicata, all else equal, led to a higher degree of regional economic
development?
01020304050
Barrelsofoilpercapita
1980 1990 2000 2010
Year
Source: UNMIG

Basilicata and the rest of Mezzogiorno

Contribution
1 Estimate the economic e¤ect of oil in the region of Basilicata during
the period 1980 2009, compared to control regions.

Contribution
Synthetic Control Method (SCM) (Abadie et al. 2014): weight control
regions to construct a counterfactual that replicates the treated region
before treatment.

Contribution
before treatment.
2 Discussion about channels.

Contribution
before treatment.
Control rights; Organized crime; Sectoral e¤ects; Labor migration.

Contribution
before treatment.
Control rights; Organized crime; Sectoral e¤ects; Labor migration.
3 Results: null aggregate e¤ects; signi…cant sectoral e¤ects.

Empirical Strategy
Identi…cation strategy: exploit the fact that Basilicata produced
throughout the period of analysis a fraction close to unity of oil
extracted in the 5 + 1 southern Italian regions.
.4.6.81
Oilextracted(tons):Basilicata/Tot.DPregions
1980 1990 2000 2010
Year
Source: UNMIG

Institutional agreement and royalties
Variable Location Net value based royalties
Oil production Onshore 7%
O¤shore 4%
Gas production Onshore 7%
O¤shore 7%
Revenue’s bene…ter State (30%); Region (70%)
Law 140/1999: southern regions are entitled to 100% of royalty
revenues. Q: still too low?

Empirical Literature
1 Sub-national economic e¤ects 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:

3 On the case of Basilicata:
Percoco (2012).

Implementing the SCM: choosing the DP
1 Choosing the Donor Pool (DP).

Donor Pool, 5 southern Italian regions: Campania, Molise, Puglia,
Sardegna, Calabria.

Sardegna, Calabria.
Choice informed as well by a study of European regional economies
from the Bank of Italy (2012).

Sardegna, Calabria.
2 Generating weights for units in the DP.

Sardegna, Calabria.
2 Generating weights for units in the DP.
3 Estimating Impact on the Economy of Basilicata.

Implementing the SCM: generating weights
SCM Algorithm: de…ne GDP per capita as Y and its determinants X,
such as:
Population, Labor Force, Gross Fixed Investment, Pop. shares by
education level, Value Added shares of GDP by Industry.
in which vm are weights assigned to the m th determinant.

such as:
Matching period (1980 1998): Y pre
0 and X0 in DP; Y pre
1 and X1 in
treated unit.

such as:
1 and X1 in
treated unit.
Post-treatment (1999 2009): Y post
0 in DP; Y post
1 in treated unit.

such as:
1 and X1 in
treated unit.
Post-treatment (1999 2009): Y post
0 in DP; Y post
1 in treated unit.
SC unit is given by the vector of weights W = (w1, ..., w5) (with
w1 + ... + w5 = 1) chosen as W that minimizes
k
∑
m=1
vm(X1m X0mW )2

Region Synthetic weights W
Campania 0
Molise .354
Apulia .106
Sardinia 0
Calabria .54

Implementing the SCM: estimating impact
SCM Algorithm: generate synthetic Basilicata using assigned weights;
compare actual and synthetic Basilicata.
Y1t
6
∑
j=2
wj Yjt
a) Real GDP per capita as dependent variable.
Matching period
05000100001500020000
GDPpercapita,constantprices
1980 1990 2000 2010
Year
Treated unit Synthetic control unit

Time-placebo tests - Treatment 1992 (left)
Real GDP per capita
Matching period
05000100001500020000
GDPpercapita,constantprices
1980 1990 2000 2010
Year
Matching period
05000100001500020000
GDPpercapita,constantprices 1980 1990 2000 2010
Year

b) Employment rate (total) as dependent variable.
Campania 0
Molise .139
Apulia .657
Sardinia .204
Calabria 0

b) Employment rate (total) as dependent variable.
Matching period363840424446
Employmentrate,total
1980 1990 2000 2010
Year

Employment rate
Matching period
363840424446
Employmentrate,total
1980 1990 2000 2010
Year
Matching period
363840424446
Employmentrate,total 1980 1990 2000 2010
Year

c) Gross Fixed Inv. as dependent variable.
Campania 0
Molise .83
Apulia 0
Sardinia .009
Calabria .161

c) Gross Fixed Inv. as dependent variable.
Matching period
50010001500200025003000
Grossfixedinvestment,constantprices
1980 1990 2000 2010
Year

Gross …xed investment
Matching period
50010001500200025003000
Grossfixedinvestment,mill.Euro
1980 1990 2000 2010
Year
Treatedunit Synthetic control unit
Matching period
50010001500200025003000
Grossfixedinvestement,mill.Euro
1980 1990 2000 2010
Year

Robustness main results
Yi,t = γi + δt + λTi,t + X
0
i,t β + i,t
with
Yi,t = outcome of interest for region i, year t.
γi = region …xed e¤ects.
δt = time …xed e¤ects.
Ti,t = dummy for the treated region in the post-treatment period.
X
0
i,t = a set of covariates.
i,t = clustered error term.

Robustness main results
Table (1) (2) (3)
GDP per capita, Employment Gross …xed inv.
constant prices rate, total constant prices
Di¤-in-di¤ -352.8* -0.646 -1,404**
(179.1) (0.786) (651.9)
Fixed e¤. YES YES YES
Observations 180 180 180
R-squared 0.995 0.529 0.827
Robust standard errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1
Note: standard errors adjusted for clusters.

Discussion about channels
1 Control rights structure.
2 The plague of organized crime.
3 Sectoral e¤ects.
4 Labor migration.

Control rights structure
Brunnschweiler and Valente (2013): Int’l Partnership is linked to
higher GDP levels than Domestic/Foreign Control, regardless of
political regime type.
Brunnschweiler and Valente (2013)’s coding of Italy: Foreign
1930 1956 and 1995 2008, Partnership in between.
Q: would have Italy (and Basilicata)’s GDP bene…ted from
Partnership?

The plague of organized crime
Pinotti (2012): exposure to ma…a activity (proxied by increase in
murders) after 1970s lowered GDP per capita by 16% in the treated
unit (Basilicata-Apulia), as compared to control group.
Q: can we rule out that public royalty revenues in Basilicata
represented a pro…t opportunity for criminal organizations?

Sectoral e¤ects
VAi,t = γi + δt + λTi,t + X
0
i,t β + i,t
with
VAi,t = value added (% of GDP) for sector (..) in region i, year t.
γi = region …xed e¤ects.
δt = time …xed e¤ects.
Ti,t = dummy for the treated region in the post-treatment period.
X
0
i,t = a set of covariates.
i,t = clustered error term.

Sectoral e¤ects
Dependent variable Industry, % of GDP
(1) (2) (3)
Di¤-in-di¤ 2.886*** 4.730*** 5.306***
(0.720) (0.620) (1.010)
Real GDP per capita 0.000246
(0.000276)
Gross …xed inv. -0.000365***
(7.83e-05)
Constant 15.60*** 18.51*** 18.56***
(0.253) (0.610) (0.818)
Region …xed e¤ects NO YES YES
Time …xed e¤ects NO YES YES
R-squared 0.044 0.560 0.662
Robust standard errors in parentheses.
Asterisks denote signi…cance levels: *** p<0.01, ** p<0.05, * p<0.1

Sectoral e¤ects: SCM for industry
1416182022
Shareofvalueadded,Industry
1980 1990 2000 2010
Year

Sectoral e¤ects
Dependent variable Constructions, % of GDP
(1) (2) (3)
Di¤-in-di¤ -0.755* -1.577*** -0.524
(0.428) (0.358) (0.329)
Real GDP per capita 0.000416***
(0.000151)
Gross …xed inv. 0.000327***
(4.29e-05)
Constant 8.397*** 12.67*** 11.38***
(0.197) (0.352) (0.448)
Region …xed e¤ects NO YES YES
Time …xed e¤ects NO YES YES
R-squared 0.005 0.883 0.919
Asterisks denote signi…cance levels: *** p<0.01, ** p<0.05, * p<0.1

Sectoral e¤ects: SCM for constructions
6810121416
Constructions,shareofGDP
1980 1990 2000 2010
Year

Labor migration
590601612229
Basilicata
1980 1990 2000 2010
1812455718930968
TotalDPregions
1980 1990 2000 2010
Year
Source: ISTAT

Concluding remarks
Null hypothesis of aggregate positive economic e¤ects: rejected.

Concluding remarks
Sectoral e¤ects: positive for industry.

Concluding remarks
Sectoral e¤ects: positive for industry.
No blessing, no curse?

Thanks for attention!
Cite this article as: Roberto Iacono, No blessing, no curse? On the
bene…ts of being a resource-rich southern region of italy, Research in
Economics, http://dx.doi.org/10.1016/j.rie.2015.03.003

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