CrimeandregionalgrowthinItaly Lanzafame,Matteo MunichPersonalRePEcArchive

Munich Personal RePEc Archive

Crime and regional growth in Italy

Lanzafame, Matteo

Università degli Studi di Messina, Dipartimento SEAM

February 2013

Online at https://mpra.ub.uni-muenchen.de/44343/

MPRA Paper No. 44343, posted 13 Feb 2013 14:56 UTC

Crime and regional growth in Italy

Abstract

!

"

Keywords: #

JEL Classifications: #$% &' ( '

$

Crime and regional growth in Italy

1. Introduction

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$''* $' '4 $''54 6 6 **78

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3

# 2 $''98

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: !

3 8 # 2

2 !

3 ;

%

8 !

- /

2

! 3

8 <

2 !

. = #

:

! " "

2 1

2

1

1 ) 3$' '8 > *7*

/ $''$ !

3 8 ")6 - ! 2

6 3$''&8 *+ **

3 8

")6 <

2 ? , 36 **%8

6

3$''&8 !

@ # 3$''78

&

!

-

*5% **+ 6 "

36 "8 6 3 ***8 - 6 " !

!

")6 )

3$' 8 3:) 8 '%

$''$ $''5 - 2

@ 3A /8

: " /@ 3:" /8 - A /

!

:) :) 1 6 3$''&8

6 3$' $8 !

/ 1

*7' !

# 6 3$' $8 1 ,

, B

*7' 5 ")6

!

:

(

!

+

2 A

! 2

1

/ @ 3 ! 8

2

36 / **+8

2 - 2

36 $''58

/ 2

3 "8 36 / **+8

0 ?# # = " ,

3##= "8 6 3$''58 ?1 " , 31 "8

@ = - 3$' $ 8 - "

##= " 1 "

1

-

2 ##= " 1 "

5

: = - 3$' $ 8

? , 3 8 "

- / $

/ %

-

"

/ & / +

/ 5

2. Data and preliminary analysis

- 3 8

*7' $''+ A

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3 8

-

!

3 ) $' '4 # $''78

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- $'

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3 # $''78D A :

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$: ? , ? ,

%1 6 3$''&8 6 3$' $8 !

: @

7

?# . / = ( , 3#(=. /8

. / 3 /-1-8

/-1- ?# $ , 3 ?# / ,8

B

Figure 1. Descriptive statistics

−20246

1970 1980 1990 2000 2010

Labour productivity, % growth rate Crime rate Mean regional values

CAL

SIC CAM

PUG SAR

LIG

BAS LAZ PIELOM

MOL TAA ABR EMR FVG VEN TOS UMB MAR

051015Crime rate

Mean values, 1970−2005

−.15−.1−.050.05.1Labour productivity, % growth rate −1 0 1 2 3

Log of crime rate

/

; 3 6 1

# 8 .

@ 3

# $' 8 - 2 3

8

&

#(=. / B E # E / - #(=. /

D;; ; ;

+ ,

/-1- ?# , - B

B

9

: -

")6 A

$ & 3 8 '' ''' *7'

& 5$ $''+

**' - 2

$7

3 1(8 * # 3#1 8 !

!

. A 3 "8

: :

- B

3. Model and empirical methodology

-

3 8

3-:68 -

% = # 3 8

$&

ω λ

= + 3$8

*

$ '

= 3 8 = $ ( %

# $& !

3 8 '' ''' -

-:6 3 8

=@ 3$8

! ( ) ^{ω : 3 8 3$8}

@

$&

ω λ

= + 3%8

:

1 ) 31() 8

3%8

F

' '

)

* * + +

* +

$&

ω ρ

λ

= =

= + ∑ + ∑ + ^3&8

3.1. Estimation framework

2 =

- 3$' $ $' $ 8 -

3&8 = $ ' = $ (

'

$&

ω λ ′

= + + = φ ′ ! + ε 3+8

$& = π ϕ + ′ + ϑ ! + ϑ ! + υ 358

! = ο ′ !

+ ς = κ ′

+ ς 378

!

⊂ !

! φ - ε

σ

- $& !

! -

! 3 ο = κ = 8

$& $&

$& ! .

3+8 378 3 8 ( ^$& )

6 ' (

!

!

1 !

-

0 " 3 "8 6 / 3 **+8

- "

φ ′ ! 1

-

2 6 3$''58 ?#

# = , 3##=8

- ##=

! !

: 6 3$''58

3+8

( )

! = φ

− − ω λ ′ $& − ε 398

'

φ '

φ

=

= ∑ ^{4 '}

=

= ∑ ^{4 ω '}

^ω

=

= ∑ ^{4 λ '}

^λ

=

= ∑ ^{$& '}

^$&

=

= ∑

'

ε '

ε

=

= ∑ ^{: ' → ∞ φ ≠ ' ε = '}

3+8

$&

$&

ω λ ^′ ε

= + + + + 3*8

- # # = " 3##= "8 "

3*8 - ##= "

$

G

G

$$ ,

'

λ

λ

=

= ∑

^{. ##=}

! ! φ -

##=

##=

. 3*8

= - 3$' $ 8

1 " 31 "8

? , - 1 "

D

$ (

$&

λ

=

= ′ + ∑ + ^{⇒ G ≡ G}

^{3 '8}

$& G

ω λ ′

= + + + + 3 8

- / 3 '8

( − - 3 8

G

? ,

!

3 '8

( −

5A

3*8 # # = 6 3##=68

7- ? , ! ! !! 3

8

%

3 G

8 !

3 8

G

1 '

G

!

- ##= 1 "

- ! G

G

- : 6 3-:68

-:6

1 " ##= "

1 "

G

G

,

'

λ

λ

=

= ∑ ^{= 1 "}

- #

= 3$''*8 G

λ !

1 " ##= "

##= " 1 "

;

- !

9( ? , 36 *9&8 =

- 3$' $ 8 . 3$''98

B ( '; →' -

= 3$''*8 1 "

* 2 1 " = - 3$' $ 8

##=

&

3.2. Estimation results

A " 1() 3&8 @

'

:

3 ( $''58

1 /

# 3/ #8 1() 3 '8

2 -

/

2 ( ^$& )

3 $' $8 A

( ^$& ) ^-

$&

$&

- " - /

< 3 ** 8

:

'1 $& 1

) 2 : 31):8 3) 2 : *7*8 - 1): - 1 1 ! B

A

1() 3 '8

+

< + 5

1

" 2

- 2

3#)8 6 3$''&8

Table 1. Standard MG estimations and CD test

= " " " "

)

− ' ' ' ' '9'H ' ''+ ' '7$H

$& ' ''+II ' ''$II

$& ' ' +II ' ' 'II

' '%$II ' '%+II ' '%+II ' '%*II

J

'K + 5

#) $+ 55 $+ $+ $5 '7 $+ &&

' ''' ' ''' ' ''' ' '''

. D II H K 'K 6

< 3 ** 8

- #)

( )

$

+ + +

$ (

' '

ρ

= = +

  

=    −     ∑ ∑ ^⌢   ^{3 $8}

ρ ^⌢

(

+ : (

> % '

5

( ) ^'

$ ∼ ' ^#)

2

E " #)

- 1

B 1

" 2

- ##= " 1 "

Table 2. CCEMG and AMG estimations: Model specifications with $&

= ##= " ##= " 1 " 1 " 1 " 1 "

)

−

−

− ' $5I ' &'I ' $*5II ' %'7II ' %%%II ' %$+II

$& ' ''$I ' ''%II ' '' ' ''$H ' '' ' ''$H

# ' 99%II ' 9*$II

' ''$ ' ''+ ' '&+II ' '&5II ' '&7II ' '&9II J

'K % % %

. D II I H K +K 'K 6

< 3 ** 8

Table 3. CCEMG and AMG estimations: Model specifications with $&

= ##= " ##= " 1 " 1 " 1 " 1 "

)

−

−

− ' &H ' $ I ' $99II ' $*$II ' %$+II ' % +II

$& ' ''*II ' ' 'II ' ''5I ' ''*II ' ''& ' ' 'II

# ' 99% ' 999II

' ''$ ' ''+ ' ''5H ' ''9 ' ''$ ' ''7H

J

'K $ % $

. D II I H K +K 'K 6

< 3 ** 8

7

- $ ##= " 1 " $& -

##= "

!

1 " $& 3 ' 8

1 " -

- % $&

!

$& ' ''$

$&

' ' '

!

4. Extensions and robustness of the results

- !

2 2

$& $& < !

3&8

/ 2 3

/ **&4 # $''%8 : 2 3 **$8

D

( )

% = . /

#

3 %8

9

$ '

= = $ ( % #

-:6 . / 2

α δ

1 -:6 @ 3$8 = ω λ + $&

@

$& 0

γ ζ α δ

= + + + 3 &8

( )

γ = ω − α δ − ^{ζ = λ} ( ^{− α δ −} ) ⁰

$& A 3&8 3 &8

2 <

- 2

) 2

. 3

# $''%4 # $''+8D

( )

. = 1 + − .

3 +8

*

1 !

' '5

1 -

3$''&8 @ D

/# =

3 58

/#

7 π = ' '7

- 1

##= " 1 " 2

<

@

3 &8 ;

= - 3$' $ 8 !

@ "

4.1. Panel Granger causality tests

: " 3 *5*8 % ?" ,

2 % 2

$: # 3$''+8 2 ._' 1'

(

)

%A / ) - 3$''&8

&

1 # 3$''%8 # 3$''+8

7 =#) 3 L $'''8

$'

: " 2

% % " 2 B %

B

"

!

3 1 $'''4

. ( A $'' 4 LM $''58 1

+

-

< = 2 3 *998

" 3C1(8

2 ω β 2

δ %

= =

= + ∑ + ∑ + ^{3 78}

$ '

= = $ ( ω 3 8 !

2 3 78

'

D

'

' ' '

/ '

δ '

δ '

δ

= = =

= = =

∑ ∑ ∑ ^{3 98}

- % " 2 3 D % → 2 8 -

3 98 "

+1 3 '8 B 1):

3 &8 0 0 ;

!

$

" 1 "

5

)

!

= $ 1

;

1 - & " 1 " "

<

B

Table 4. Panel Granger Causality Tests

Estimator

Null hypothesis MG MG AMG AMG

→$& ' + ' *% & ' % &*

$& → 9 7$II * +9II ' 97 & 7%H

→0 ' $$ ' %7 ' ' ' $%

0 → 9 77I 7 59II 7 '+I 7 ''I

→ $+ 7$II 9 +7II 5 *7I & $

→ + $5H ' +% 55 ' %9

( . N . N

. D I H +K 'K F→F ? " ,

/ < 3 ** 8

5A 1 " ##= "

1 ##= @

D " @

" 2 2 1 " ##= "

$$

2

0

" : "

2 $& 1 "

2

! !

3 &8

4.2. Extended model results

- ##= " 1 " 3 &8 - + 5

" 0 $& 3 $& 8 !

9

-

? , -

' '' $& ' ''7 $&

- + 5 -

3 0 8

%% %9 0 9

7- #) 36 $''&8 "

3 8 - "

9- - + 5 A

D -

$%

Table 5. CCEMG and AMG extended model estimations: Specifications with $&

= ##= " ##= " 1 " 1 " 1 " 1 "

)

−

−

$& ' '' I ' '' I ' '' H ' ''$H ' '' II ' ''$I

0 ' %5%II ' %+9II ' %79II ' %7$II ' %%%II ' %%$II

' $' ' 5% ' 'I ' +I ' $ I ' %H

# ' **+II ' **$II

' '' ' '' ' '$*II ' '$*II ' '$9II ' '$9II

J

'K ' '

. D II I H K +K 'K 6

< 3 ** 8

Table 6. CCEMG and AMG extended model estimations: Specifications with $&

= ##= " ##= " 1 " 1 " 1 " 1 "

)

−

−

$& ' ''7II ' ''9II ' ''7II ' ''*II ' ''7II ' ''*II

0 ' %7' ' %5&II ' %9&II ' %75II ' %%7II ' %%9II

' 9$ ' 77 ' & I ' & I ' +$I ' %7I

# ' **9II ' **&II

' ''' ' ''$ ' ''% ' ''% ' ''$ ' ''&II

J

'K ' '

. D II I K +K 6

< 3 ** 8

3 &8

*

*A 3 &8 ₋ -

- 1$ 1% 1 ! - + 5

$&

5. Discussion of the results

-

, 1

!

B

! /

*7' $''+ *

@

$&

( )

I

= − ζ G $& − $& $& (

$&

=

= ∑

- + ζ G = − ' '' A

33#4 8

( )

I

G

3#4 = − = − ζ $& − $& 3 *8

' 3#4 >

$& = $&

: $ 3#4

A ! .

$+

-

$ $ 6 7 0 7 +' C : C

" = ( - E * %

3#4 + 9

# 3#4 *7' $''+ $*

' 9 -

/ 7 7 ' + $ 5 ' %+

#

Figure 2. PLOSS by region: Models with CR_it, ζ = 30.001

−.20.2.4.6.8 Average annual loss

−100102030Cumulative loss

PIE LOM TAA VEN FVG LIG EMR TOS UMB MAR LAZ ABR MOL CAM PUG BAS CAL SIC SAR Cumulative loss Average annual loss

- B

@ $&

$& 2 2

-

: $ 2

$': - 1& 1 !

$5

@

6. Conclusions

- :

!

2

# !

2 3 "8 36 / **+8

6 3$''58 = -

3$' $ 8 0 ?# # = " , 3##= "8

?1 " , 31 "8 : = - 3$' $ 8

? , "

1

! *7' $''+ /

' %+ ' 9

1

! !

$7 - 2

References

1 6 6 / 1= 3$'''8 / D

& 5 ! 9$D 9$0$

> . / 3$''98 ) : 1 6 (

%D 9* 5%

> / 3 **&8 - D =

) ! 7 %&D &%0 7%

6 # / 3$''%8 - D 1 8 0 3

7 $D % $'5

6 6 6 3$' $8 ) O ) !

D ' ;B +&$ &77& $' $ ' '9+ !

2 6 > L $''' P) / # " OQ

& 5 *'D 5'09%

/( = 3$''*8 # / ) . 6 D 1 .

= 6(1 6 . 797'

6 3$''*8 . 2 D =

! & 5 $9D 7

# : 3$' 8 A O

, $ $D & 5*

$9

# : 3$''+8 1 / 0 ! , 5

31 ) 8 . <

# 2 > 3$''98 = D D

/

) C E 3$' 8 @ :) D 1

) ! 3 7 $7D %$ &$

) # = 3$' '8 ) # = " O .70 5%D %%' %&+

) 2 )1 : A1 3 *7*8 ) = 1 - /

E ( ) ! 7&D &$7 &%

= 3$' $8 = 6 - / < /

) $D 5 7

= - : 3$' $ 8 . - D / < 1

6 1 4-! 8 ! D ' ;B &59

''9& $' $ ''7$' !

= - : 3$' $ 8 6 1 " 6

= / A 2 6 + + ) = E !

" #A> 3 *5*8

%7D &$&0&%9

< # 3 ** 8 < ( ( ( O ( 8 $D $ $5

< = 2 ) . A ( </ 3 *998 =

+5D %7 0 %*+

LM 3$''58 =! D " =#)

$%D *790**$

3$''*8 O & &%D '' ' %

3$' '8 - %*D 977

9*+

$*

. ( ( 3$''58 : ) : : " ) !

7 $ 8 0 %9D '+ '75

3$''58 # 89 9

) ! ( 5 0&%

2 ." ( ) A ). 3 **$8 1

7 ) ! '7D &'7 &%7

# " 3$''78 1 & 5 !

D &+'0&5$

. ( E A ) 3$'' 8 # D 2 :)

4-! 8 !

5%D +%0 7

6 ( 6 : 3 **78 / D

$ 7 9 $*70% 9

6 1 3 *9&8 = 1 ( " (

1 & 5 $+D $$ $&7

6 " 3$''&8 / D

*+ 0 ** ( &D 0%&

6 < 3$''&8 " ) - # / ) 6 R1

) 6 / )6 . $&'

6 < 3$''58 =

7&D *570 ' $

6 < / N / ( 3 ***8 6 " = ) <

6 ) ! *&D 5$ 5%&

6 < / ( 3 **+8 = ( ) <

6 ) ! 59D 7*0 %

%'

6 6 3$' $8 - D 2

A 2 6 . 959

6 ( 3 **%8 2 ) 2 6 E 6 6 .>

- - 1 ) / 3$''&8 - 2

E / ) / = / A 2 6 .

% &$

% Appendix

Table A1. ADF unit root tests on $&

( $ # (

6 6 = ' & 5II

' % +99I

- 1 1 -11 ' & &++II

C C=. ' + $5%II

: C " :C" ' & %5*II

" ' % 9$+I

= ( = ( ' + $+%II

- - / ' $ 9''

E E % 5$5

1( ' 7 7%II

1R ' & +7$II

1 1 ( ' + &+II

$ & %*&II

# #1 $ % %+H

1 6E" ' $ $%%

1/ & % +%$I

# #1 % 7$*I

/ / # ' &&&

/ /1( ' & 5+'II

. D - C ,1 6 36 =8 II I H

K +K 'K 1 1):

@ . 6 3 **+8

Table A2. CCEMG and AMG extended model estimations: Specifications with $&

= ##= " ##= " 1 " 1 " 1 " 1 "

)

−

−

− ' & I ' 5*II ' %'+II ' % 5II ' %& II ' %%9II

$& ' ''$II ' ''$I ' '' ' ''$I ' ''' ' ''$I

0 ' %$9II ' %$%II ' '%&7II ' %%+II ' %$'II ' %'*II

' $'% ' *' ' '*$ ' '*% ' ' ' '99

# ' 9**II ' *'+II

' ''% ' ''+ ' '%7II ' '%7II ' '%9II ' '%9II

J

'K ' ' '

. D II I K +K 6

< 3 ** 8

%$

Table A3. CCEMG and AMG extended model estimations: Specifications with $&

= ##= " ##= " 1 " 1 " 1 " 1 "

)

−

−

− ' %9I ' &%I ' $**II ' %'7II ' %%5II ' %$5II

$& ' ''7II ' ''9II ' ''+H ' ''7I ' ''& ' ''9I

0 ' %%+II ' %%$II ' %+'II ' %%5II ' % *II ' %'*II

' 5+ ' +9 ' $ H ' *H ' %5H ' 5

# ' 9*7II ' *'%II

' ''% ' ''+ ' '' ' '' ' ''+ ' ''&

J

'K

$

. D II I H K +K 'K 6

< 3 ** 8

Table A4. PLOSS by region: Models with CR_it, ζ = 30.001

( $ # 3#4 1 3#4

6 6 = $ 9 ' '5

% ' '*

- 1 1 -11 5 57 ' *

C C=. 7 & ' $

: C " :C" 7 %' ' $'

" 75 ' '+

= ( = ( 5 9* ' *

- - / 7 &5 ' $

E E 7 +7 ' $

1( * %$ ' $5

1R *7 ' '+

1 1 ( 5 7' ' *

+ 75 ' 5

# #1 $ +9 ' %+

1 6E" 7 &9 ' $

1/ ' *+ ' '%

# #1 $9 ** ' 9

/ / # 7 57 ' &*

/ /1( & 9' ' %