Geographic sorting and aversion to breaking rules · 2020. 11. 2. · Geographic sorting and aversion to breaking rules Massimo Anelli 1 Tommaso Colussi 2 Andrea Ichino3 1Bocconi,

Geographic sorting andaversion to breaking rules

Massimo Anelli 1 Tommaso Colussi 2 Andrea Ichino3

1Bocconi, CESifo, IZA

2Catholic University of Milan, IZA

3European University Institute, University of Bologna, CEPR, CESifo, and IZA

Princeton UniversityNovember 2, 2020

Motivation

Aversion to breaking rules (ABR) is heterogeneous across localitiesaround the world and sorting based on ABR may be a reason.

In this paper we:

1 document a new measure of rule breaking that can be observed forthe entire census population;

2 we determine under which conditions measures of rule breaking areactually informative about ABR;

3 show that Italians sort across localities on the basis of ABR;

4 and that this geographic sorting has important consequences foreconomic outcomes in different localities.

Our work relates to papers like Fisman and Miguel (JPE 2007) andLowes et al. (Econometrica 2017).

2

“January Birthdate” (JBD) cheating: North and South50

150

250

350

450

Birt

hs ('

000)

1 July

1-5 Ja

n

30 Ju

ne

Day of birth

North

5015

025

035

045

0

1 July

1-5 Ja

n

30 Ju

ne

Day of birth

South

Note: restricted Census 1991 data with precise birth date on 1920-1970 cohorts.

cohorts 2005-10

3

“17 Birthdate” (17BD) cheating: North and South10

020

030

040

050

060

070

080

0B

irths

('00

0)

1 17 31Day of birth

North

100

200

300

400

500

600

700

800

1 17 31Day of birth

South

Note: restricted Census 1991 data with precise birth date on 1920-1970 cohorts

La disgrazia

4

Definition of North and South

JBD cheating

below p55p65p75p95

17BD cheating

below p65p65p75p95

We define South as the provinces ruled by the “Regno delle due Sicilie” until 1861.

5

Plausible reasons for BD cheating

For 17BD cheating:

• superstition• number 17 in the “Tombola napoletana” La disgrazia

For JBD cheating:

• Allows child to be physically more developed than mates;• analogy with “red shirting”;• relevant in school, sports, army.

• Makes the child available to help at home for a longer time:• If child is male, military service starts one year later;• if child is female, there is more time to find a husband.

Census information does not allow us to nail down the specific reasonsfor JBD cheating, but we can rule out some irrelevant reasons.

6

Reasons for BD cheating that we can exclude

In principle, BD cheating could have nothing to do with ABR.

However, we can exclude many of the “irrelevant” interpretations.

Specifically, BD cheating is not related to:

• Misreporting birth dates in the Census Cross-cohort variation

• Office closures around Xmas time. Easter holidays

• Observables of the child like gender and education. Link

• The census year. JBD 2001 JBD 2011 17 - 2001 17 - 20117

Alternative interpreation: sloppiness

A possible alternative interpretation is that JBD cheating measures thepropensity to be sloppy, not ABR:

• There exist private benefits to sloppiness.

• Sloppiness may react to deterrence.

• Sorting based on sloppiness is plausible.

However:

• Following rules is often costly, sloppiness is a symptom of low ABR

• Our “donut” robustness checks suggest that this interpretation isunlikely.

8

Advantages of BD cheating for researchers

Irrespective of the motive, BD cheating is a rule breaking that can be:

1 estimated using Census data for the entire population;

2 computed for small groups in the population at different points intime during the 20th century, and specifically for:

• migrants out of a given locality and• remainers in the same locality;

3 it correlates closely across cities with more traditional indicators ofcheating; Correlations

4 traditional cheating indicators cannot be observed for migrants andremainers within the same locality at different points in time;

5 Theory, which will come next, suggests a test of informativeness.

9

A caveat: intergenerational transmission

BD cheating is choice of parents at the time of birth of their children.

Migration is observed by comparing the place of birth and the place ofresidence of children in the 1991 census.

No information about age at (internal) migration in the Census.

Therefore the migration decision may be a decision:

• of the parents who moved with their children.

• of the children who left home alone when adults.

In the second case some degree of intergenerational transmission ofABR is needed.(Tabellini, 2008; Algan and Cahuc, 2010 Zilibotti et al. 2017)

Internal Migration

10

Road map

• Preliminary evidence on BD cheating indicators.

• A model of ABR, probability of cheating and deterrence.

• Geographic sorting on the basis of ABR.

• The 1926 Fascist reforms: a shock to deterrence for BD cheating.

• The economic consequences of geographic sorting based on ABR.

11

A model of ABR, probability of cheating and deterrence

A rule is broken (cheating) if C = 1, otherwise C = 0.

B ∼ F (B) is the utility benefit of cheating.

D is deterrence, i.e. the expected public penalty for cheating.

A is the individual private Aversion to Breaking Rules (ABR).

The decision process that leads to cheating is lexicographic:

if B ≤ A ⇒ C = 0

if B > A ⇒

and B ≤ D ⇒ C = 0

and B > D ⇒ C = 1

12

Levels of Aversion to Breaking Rules and deterrence

Consider a population divided in two types

• with different ABR, AH > AL• but facing the same deterrence D.

Suppose that:

• Pr(A = AH) = GH : frequency of individuals with high ABR;• Pr(A = AL) = 1− GH : frequency of individuals with low ABR.

Three interesting cases depend on how D, AL and AH are ordered:

Low deterrence: D < AL < AH

Medium deterrence: AL < D < AH

High deterrence: AL < AH < D13

Probability of cheating under Medium Deterrence

AL < D < AH

Πmed = [1− F (D)](1− GH) + [1− F (AH)](GH)

1 Less cheating with higher ABR (GH)

∂Πmed∂GH

= [1− F (AH)]− [1− F (D)] < 0

2 Less cheating with more deterrence (D)

∂Πmed∂D

= −f (D)[1− GH ] < 0

3 The reaction to deterrence is smaller with higher ABR (GH)

∂∣∣∣∂Πmed∂D ∣∣∣∂GH

= −f (D)14

Probability of cheating under High Deterrence

AL < AH < D

Πhigh = [1− F (D)]

1 Cheating does not change with ABR (GH)

∂Πhigh∂GH

= 0

2 Less cheating with more deterrence (D)

∂Πhigh∂D

= −f (D)

3 The reaction to deterrence does not change with ABR (GH)

∂∣∣∣∂Πhigh∂D ∣∣∣∂GH

= 015

Probability of cheating under Low Deterrence

D < AL < AH

Πlow = [1− F (AL)](1− GH) + [1− F (AH)](GH)

1 Less cheating with more ABR (GH)

∂Πlow∂GH

= [1− F (AH)]− [1− F (AL)] < 0

2 Cheating does not react to an increase of deterrence (D)

∂Πlow∂D

= 0

3 The reaction to deterrence does not change with ABR (GH)

∂∣∣∣∂Πlow∂D ∣∣∣∂GH

= 016

Predictions of the model for Migrants and Remainers

A migrant is someone born in the South and observed in the North atthe Census time, or viceversa.

Let:

• πmlt be the share of JBD cheaters among Migrants from locality land born at time t

• πrlt be the share of JBD cheaters among Remainers in locality l andborn at time t.

In each locality (municipality or local labor markets/commuting zones),both Migrants and Remainers are likely to be:

• exposed to the same deterrence;

• have the same distribution of cheating benefits.

Observed cheating in the two groups is informative about their ABR.

Michaeli et al.

17

Summary of the main predictions

A) If Dmlt = Drlt , Bmlt = Brlt and

πmlt < πrlt

then[GH ]mlt > [GH ]rlt

i.e., higher cheating of remainers implies a higher frequency of

high-ABR types among migrants

B) If Dmlt = Drlt , Bmlt = Brlt and[∂∣∣ ∂Π∂D

∣∣∂GH

]mlt

<

[∂∣∣ ∂Π∂D

∣∣∂GH

]rlt

then[GH ]mlt > [GH ]rlt

i.e., higher reaction to deterrence of remainers implies a higherfrequency of high-ABR types among migrants.

Other Predictions18

Road map






19

A measure of JBD for group g in year t

Let:

• ρ+gt be the number of births between January 1 and 5 of year t + 1• ρ−gt be the number of births between December 27 and 31 of year t.

Then the index:

πgt =ρ+gt −

ρ+gt+ρ−gt

2

ρ+gt+ρ−gt

2

=ρ+gt

ρ+gt+ρ−gt

2

− 1

captures the share of JBD cheating families,

- i.e., with real birth before Dec. 31, and a false birth after Dec. 31.

• πgt = 0 if no family cheats• πgt = 1 if all families with births before December 31 cheat• πgt = 12 if half of the families with births before December 31 cheat

20

Geographic sorting on the basis of ABR (Hp1)

.15

.2.2

5.3

.35

.4Π

gt fo

r JD

B ch

eatin

g

Remainers Migrants

North

.6.6

5.7

Remainers Migrants

South

Appendix

21

JBD cheating of migrants from South to North and viceversa

πg = β1 +β2Southg +β3Migrantg ∗Northg +β4Migrantg ∗Southg + �gΠg = JBD Cheating

(1) (2) (3) (4)

Migrant∗South (β4) -0.024** -0.017*** -0.014*** -0.022***(Mig.S-Rem.S) (0.011) (0.004) (0.003) (0.005)Migrant∗North (β3) 0.136*** 0.070*** 0.062*** 0.068***(Mig.N-Rem.N) (0.030) (0.019) (0.015) (0.017)South (β2) 0.520*** 0.141**(Remainers,South) (0.027) (0.054)β1 0.175*** 0.354*** 0.425*** 1.574***(Remainers,North) (0.018) (0.025) (0.000) (0.502)

Observations 1,508 1,508 1,454 1,424Province FE No Yes No NoLLM FE No No Yes YesControls No No No Yes

Note: Observations for all Italian local labor markets in the period 1920-1955.

Controls are average demographic characteristics of local labor markets.

Appendix - municipalities Appendix - donut measure22

Road map






23

Fascism and deterrence of BD cheating

In 1926 the regime suddenly implements a wide set of reforms.

• Introduction of the “Podestà” in each city to increase control of thecentral state on the daily life of citizens.

• Pro-natality policies to compensate for the economic autarky planand to increase the size of a potential army.

- Creation of the ONMI “Opera Nazionale Maternita’ e Infanzia”:

- an institution aimed (among other goals) at rapidly reducing the highinfant mortality by providing obstetricians’ help during births at home;

- new census of infant mortality occurring within 1 or 6 days from birth.

- Introduction of subsidies to fertility and marriages.

- Introduction of taxes on singles.

24

Evolution of JBD cheating in the North and in the South

0.2

.4.6

.8Π

gt fo

r JD

B ch

eatin

g

1920 1930 1940 1950 1960Year of Birth

North South

17BD Cheating Back25

Interpretation

Since we cannot assume that North and South have

• the same starting level of deterrence D∗,• the same distribution of cheating benefits,we cannot make claims on the ABR of northerners and southerners.

However, the sudden drop of JBD cheating shows that:

• the 1926 fascist reform must have implied an increase of deterrence,• which was large enough to induce a reaction in the population• and therefore JBD cheating is informative about ABR .

The absence of a drop for 17BD cheating shows that:

• the 1926 reform did not care about superstition (D < AL < AH),• or that “one day” cheating was hard to detect,• 17BD cheating is less informative for our purposes.

26

The effect of deterrence on southern Migrants and Remainers

.55

.6.6

5.7

.75

.8Π

gt fo

r JDB

che

atin

g

1921 1923 1925 1927 1929 1931 1933 1935 1937 1939 1941 1943 1945 1947 1949 1951 1953Year of Birth

Migrants Remainers

South

Details

27

The effect of deterrence on Southern Migrants and Remainers

πg ,t = β1+β2Migrantg ,t+β3Fascismg ,t+β4Migrantg ,t∗Fascismg ,t+�g ,t

Πg ,t = JBD Cheating(1) (2) (3) (4)

Fascism ∗ Migrant (β4) 0.018** 0.023** 0.024*** 0.021**(R.NF. -R.F.)-(M.NF.-M.F.) (0.009) (0.009) (0.009) (0.008)Fascism (β3) -0.201*** -0.196*** -0.194*** -0.200***(Rem Fascism-Rem No Fascism) (0.009) (0.009) (0.009) (0.009)Migrant (β2) -0.032*** -0.026*** -0.023*** -0.027***(Mig-Rem, No Fascism) (0.007) (0.004) (0.004) (0.004)β1 0.773*** 0.770*** 0.768*** 0.830***(Remainers,No Fascism) (0.013) (0.004) (0.003) (0.018)


Note: Southern local labor market in the period 1921-1954

28

The effect of deterrence on northern Migrants and Remainers

.1.1

5.2

.25

.3Π

gt fo

r JDB

che

atin

g

1921 1923 1925 1927 1929 1931 1933 1935 1937 1939 1941 1943 1945 1947 1949 1951 1953Year of Birth

Migrants Remainers

North

Details

29

The effect of deterrence on Northern Migrants and Remainers

πg ,t = β1+β2Migrantg ,t+β3Fascismg ,t+β4Migrantg ,t∗Fascismg ,t+�g ,t

Πg ,t = JBD Cheating(1) (2) (3) (4)

Fascism ∗ Migrant (β4) -0.058* -0.054 -0.057* -0.060*(R.NF. -R.F.)-(M.NF.-M.F.) (0.035) (0.035) (0.034) (0.034)Fascism (β3) -0.085*** -0.082*** -0.081*** -0.093***(Rem Fascism-Rem No Fascism) (0.006) (0.006) (0.006) (0.008)Migrant (β2) 0.163*** 0.089*** 0.084*** 0.106***(Mig-Rem, No Fascism) (0.032) (0.019) (0.018) (0.018)β1 0.216*** 0.216*** 0.215*** 0.189***

(0.015) (0.004) (0.002) (0.019)


Note: Northern local labor market in the period 1921-1954

30

Interpretation of the effects of the deterrence shock (Hp2)

Among Migrants from South to North

• the baseline share of cheaters is lower than for Remainers,• cheating reduction during Fascism is smaller than for Remainers,

Among Migrants from North to South

• the baseline share of cheaters is higher than for Remainers,• cheating reduction during Fascism is larger than for Remainers,

and therefore

• ABR share is higher among Migrants from South vs Remainers.• ABR share is higher among Migrants from North vs Remainers.• There is geographic sorting based on ABR.

31

Road map






32

ABR drain across Italian LLM, due to migrations

In each locality l (LLM) wemeasure JBD cheating of

• “born” in l : πlb(emigrants and remainers)

• “remainers” in l in 1991 : πlr(born who remain)

The ABR drain due to emigrants is:

δl = πlr − πlbgain mingain p25p50=0drain p75drain p95

33

Anatomy of the ABR drain δl

δl = πlr − πlb = (1− F (D∗l ))(abrlb − abrlr )Let Ng be the number of agents in group g ∈ {lb, lr , lm}.Then, the emigration rate in l is

ηl =NlmNlb

and the fraction of ABR agents born in l is:

abrlb = (1− ηl)abrlr + ηlabrlm

Thereforeδl = ηl(1− F (D∗l ))(abrlm − abrlr )

and the ABR drain is positive if the fraction of ABR agents is largeramong migrants than among remainers:

δl ≥ 0 ⇐⇒ abrlm − abrlr ≥ 0

The size of δl depends also on (1− F (D∗l )) and on ηl .34

Economic consequences of ABR drain

To assess the economic consequences of the drain we estimate thefollowing equation:

Yl = a + b δl + c πl ,20 + g Xl + λr + �l

where:

• Yl is a current economic outcome in locality l• δl is the ABR drain measured between 1927 and 1955• πl ,20 is JBD cheating in locality l measured in 1920-26• Xl is a set of locality controls measured around 1920• λr is a set of regional fixed effects

In general b does not have a casual interpretation, but it is asuggestive controlled correlation.

35

The indicators of performance

1 Vote counting productivity (Ilzetsky Simonelli, 2019)

- Ballot counting time in a crucial Italian referendum on constitutionalamendment in 2016

- Labor intensive task uniform over the entire country

- No capital involved

- Ballot is exactly the same for the entire country

- Opportunity cost is controlled for

- Accounts for more than half of the north-south productivity gap in ItalyMap

- Captures the impact of reciprocal trust on group-task productivity

2 Firm value added per worker

- Bureau van Dijk firm data covering 80% of all Italian employment

- We control for capital contribution in a total factor productivityframework

36

Vote counting productivity (Ilzetsky Simonelli, 2019)Log(Vote Counting Productivity) - Referendum 2016 December

(1) (2) (3) (4) (5) (6)

ABR Drain (Standardized) -0.052*** -0.026*** -0.020*** -0.014** -0.015** -0.018**(0.014) (0.009) (0.007) (0.007) (0.007) (0.007)

JBD Generation 1920 -0.472*** -0.172*** -0.107** -0.103* -0.121**(0.041) (0.054) (0.053) (0.053) (0.054)

Employment Rate 1936 -0.374 -0.387 -0.369(0.308) (0.305) (0.310)

Agriculture Emp. Share 1936 0.586*** 0.654*** 0.670***(0.118) (0.140) (0.141)

Manufacture Emp. Share 1936 0.610*** 0.666*** 0.673***(0.163) (0.175) (0.175)

Literacy 1921 -0.152 -0.198(0.114) (0.121)

Brain Drain -1.382**(0.557)

Constant 5.388*** 5.617*** 5.469*** 5.130*** 5.134*** 5.164***(0.026) (0.025) (0.031) (0.164) (0.164) (0.165)

Observations 779 779 779 775 775 723R-squared 0.020 0.438 0.529 0.586 0.587 0.595Region FE No No Yes Yes Yes YesDrain mean -0.000 -0.000 -0.000 -0.000 -0.000 -0.000Drain S.D. 0.017 0.017 0.017 0.017 0.017 0.018Outcome Levels Mean 237.137 237.137 237.137 236.845 236.845 233.707Outcome Levels S.D. 66.770 66.770 66.770 66.795 66.795 64.963

Reducing ABR Drain by 1 S.D. would reduce South-North gap (-71 votes counted per hour, -38%) by 4 votes (6%)

37

Value added per workerFirm value added per worker

(1) (2) (3) (4) (5) (6) (7) (8)

ABR Drain (Standardized) -0.004* -0.007*** -0.006*** -0.005** -0.005*** -0.005*** -0.005*** -0.005***(0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002) (0.002)

JBD Generation 1920 -0.316*** 0.013 0.038 0.032 0.033 0.000(0.028) (0.041) (0.035) (0.035) (0.035) (0.033)

Employment Rate 1936 -0.006 -0.006 0.039(0.131) (0.132) (0.133)

Agriculture Emp. Share 1936 -0.395*** -0.389*** -0.384**(0.145) (0.147) (0.155)

Manufacture Emp. Share 1936 -0.296* -0.292* -0.283(0.166) (0.166) (0.174)

Literacy 1921 -0.020 -0.025(0.083) (0.089)

Brain Drain -0.553(0.362)

Log of capital per worker 0.124*** 0.120*** 0.116*** 0.106*** 0.107*** 0.107*** 0.107***(0.004) (0.004) (0.004) (0.003) (0.003) (0.003) (0.003)

Years of educ. in SLL 1.092*** 0.686*** 0.120 0.384*** 0.058 0.051 0.115(0.143) (0.136) (0.134) (0.105) (0.130) (0.122) (0.124)

Constant 3.088*** -0.452 0.602** 1.735*** 1.242*** 2.262*** 2.279*** 2.129***(0.025) (0.317) (0.300) (0.295) (0.223) (0.376) (0.362) (0.378)

Observations 650,541 650,541 650,541 650,541 650,518 649,419 649,419 643,115R-squared 0.000 0.114 0.131 0.145 0.313 0.314 0.314 0.314Region FE No No No Yes Yes Yes Yes YesIndustry FE No No No No Yes Yes Yes YesDrain mean 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001Drain S.D. 0.007 0.007 0.007 0.007 0.007 0.007 0.007 0.007Outcome Levels Mean 30.927 30.927 30.927 30.927 30.927 30.928 30.928 30.907Outcome Levels S.D. 22.766 22.766 22.766 22.766 22.766 22.770 22.770 22.767

Reducing ABR Drain by 1 S.D. would reduce North-South productivity gap (23%) by 2.1%

38

Conclusions

In this paper we have studied the historical tendency of Italians toregister a false date of birth if they are born:

• near the end of the year, shifting the date to early January;

• on the 17th of each month, shifting the date before or after.

Specifically we have shown that:

1 these measures of cheating can be constructed for migrants andremainers at the city/time level in Italy;

2 JBD Cheating is informative about ABR because it reacts to the1926 Fascist reforms that increased deterrence;

3 Italians sort across geographic areas on the basis of their ABR;

4 in local labor markets affected by one standard deviation more ABRdrain, firms have on average 0.5 percent lower valued added.

39

17 - La disgrazia

Back

40

17 - La disgrazia

Back

41

North-South differences in JBD cheating - 2001 Census50

150

250

350

450

Birth

s ('0

00)

1 July

1-5 Ja

n

30 Ju

ne

Day of birth

North

5015

025

035

045

0

1 July

1-5 Ja

n

30 Ju

ne

Day of birth

South

Note: restricted Census 2001 data with precise birth date Back

42

North-South differences in JBD cheating - 2011 Census50

150

250

350

450

Birth

s ('0

00)

1 July

1-5 Ja

n

30 Ju

ne

Day of birth

North

5015

025

035

045

0

1 July

1-5 Ja

n

30 Ju

ne

Day of birth

South

Note: restricted Census 2011 data with precise birth date Back

43

North-South differences in JBD cheating - Cohorts 2005-20100

5000

0Bi

rths

('000

)

1 July

1-5 Ja

n

30 Ju

ne

Day of birth

North

050

000

Birth

s ('0

00)

1 July

1-5 Ja

n

30 Ju

ne

Day of birth

South

Note: Pupils enrolled in elementary school in academic year 2015/16Back

44

North-South differences in 17BD cheating - 2001 Census10

020

030

040

050

060

070

080

0Bi

rths

('000

)

1 17 31Day of birth

North

100

200

300

400

500

600

700

800

1 17 31

Day of birth

South

Note: restricted Census 2001 data with precise birth dateBack

45

North-South differences in 17BD cheating - 2011 Census10

020

030

040

050

060

070

080

0Bi

rths

('000

)

1 17 31Day of birth

North

100

200

300

400

500

600

700

800

1 17 31

Day of birth

South

Note: restricted Census 2011 data with precise birth dateBack

46

JDB and gender of the child50

150

250

350

450

Birth

s ('0

00)

1 July

1-5 Ja

n

30 Ju

ne

Day of birth

Male

5015

025

035

045

0Bi

rths

('000

)1 J

uly

1-5 Ja

n

30 Ju

ne

Day of birth

Female

47

17DB and gender of the child10

020

030

040

050

060

070

080

0Bi

rths

('000

)

1 17 31Day of birth

Male

100

200

300

400

500

600

700

800

1 17 31Day of birth

Female

48

JDB and education of the child50

150

250

350

450

Birth

s ('0

00)

1 July

1-5 Ja

n

30 Ju

ne

Day of birth

Primary

5015

025

035

045

0Bi

rths

('000

)1 J

uly

1-5 Ja

n

30 Ju

ne

Day of birth

Secondary & Tertiary

49

17DB and education of the child10

020

030

040

050

060

070

080

0Bi

rths

('000

)

1 17 31Day of birth

Primary

100

200

300

400

500

600

700

800

1 17 31Day of birth

Secondary & Tertiary

Back

50

Easter day cheating

3040

5060

70Bi

rths

('000

)

-60 Easter 60

North South

Back

51

Definition of North and South (Asymmetric 20-daywindow)

JBD cheating

below p55p65p75p95

17BD cheating

below p65p65p75p95

We define South as the provinces ruled by the “Regno delle due Sicilie” until 1861.

52

Correlation between cheating measures across cities

JBD Invalsi Invalsi Absenteism Ghost 17BDmath literacy buildings

JBD 1

Invalsi math 0.8238 1Angrist et al. (2017)

Invalsi literacy 0.8336 0.9577 1Angrist et al. (2017)

Absenteism 0.3586 0.3095 0.299 1Ichino, Maggi (2000)

Ghost buildings 0.6142 0.4752 0.4642 0.5898 1Casaburi, Troiano (2015)

17BD 0.5811 0.6487 0.609 0.2687 0.4106 1

Principle Component Back

53

JBD cheating and PCA of other cheating indicators

Cheating Cheating Cheating CheatingJanuary 1 17 January 1 17

PC PBR .151*** .061*** .45*** .024***(.003) (.002) (.003) (.002)

Kingdom=1 .44*** .150***(.007) (.005)

Obs 3381 3381 3381 3381R2 0.43 0.3 0.7 0.44

Back

54

Net Internal Migration in thousands

Source: ISTATBack

55

Why could there be sorting based on ABR?

A model is proposed by Michaeli et al. (2018):

• Localities in two regions – South and North - in which citizens playa public good game with mandatory contributions.

• Two types of citizens:- the Civic who always contribute because this is what one ought to do;- the Uncivic who contribute only if convenient given enforcement.

• The cost of enforcement decreases in the fraction of contributors.

• Good equilibrium in the North, with enforcement (all contributes),because the fraction of Civic is historically high to begin with.

• The South could be in both equilibria, but given the low initialfraction of Civic is in a bad equilibrium.

• This setting generates a civicness drain from South to North- due to better enforcement of civic behavior in the North,- which makes migration more attractive for the Southern Civic.

Back

56

Geographic sorting on the basis of ABR (Hp1).1

5.2

.25

.3.3

5.4

.45

.5.5

5.6

.65

.7Π

gt fo

r JD

B ch

eatin

g

Remainers Migrants

North

.15

.2.2

5.3

.35

.4.4

5.5

.55

.6.6

5.7

Remainers Migrants

South

Back

57

Other predictions

C) Cheating decreases with deterrence unless deterrence is low.

D) If prediction A holds it must be that deterrence is not too high.

E) If prediction B holds it must be that deterrence is medium.

Back

58

Geographic sorting on the basis of ABR (Hp1)

Asymmetric 20-day window.1

.15

.2.2

5.3

Πgt fo

r JD

B ch

eatin

g

Remainers Migrants

North

.5.5

5.6

Remainers Migrants

South

59


πg = β1 + β2Southg + β3Migrantg + β4Migrantg ∗ Southg + �g

πg = JBD Cheating

Migrant∗South (β4) -.1525*** -.167*** -.097*** -.0652***(Mig.S-Rem.S)-(Mig.N-Rem.N) [.032] [.037] [.018] [.016]Migrant (β3) .1283*** .1275*** .0698*** .0467***(Mig.N-Rem.N) [.003] [.003] [.018] [.015]South (β2) .5185*** .4961*** .1065*(Rem.S-Rem.N) [.027] [.025] [.061]β1 .1764*** .6001*** .6375*** .6796***(Remainers,North) [.033] [.187] [.100] [.076]

Observations 11615 11615 11615 7106Controls N Y Y YProvince FE N N Y YMunicipality FE N N N Y

Note: Observations for all Italian municipalities in the period 1920-1955. Controls

are average demographic characteristics of localities. Back

60


Asymmetric window around Jan 1Πgt = JBD Cheating

(1) (2) (3) (4)

Migrant X Southern -0.134*** -0.126*** -0.073*** -0.075***(0.027) (0.040) (0.023) (0.015)

Migrant 0.111*** 0.088** 0.049** 0.057***(0.024) (0.038) (0.021) (0.013)

Southern 0.443*** 0.397*** 0.094*(0.026) (0.020) (0.053)

Constant 0.130*** 1.934*** 1.141*** 0.979***(0.014) (0.417) (0.324) (0.356)

Observations 1,539 1,510 1,510 1,458Controls No Yes Yes YesProvince FE No No Yes NoLLM FE No No No Yes


Controls are average demographic characteristics of local labor markets.

61

JBD cheating of migrants from South to North and viceversa - donut

measure

Πgt = JBD Cheating(1) (2) (3)

Migrant X Southern -0.015* -0.020*** -0.024***(0.008) (0.006) (0.007)

Migrant 0.049*** 0.050*** 0.051***(0.007) (0.006) (0.006)

Southern 0.064*** 0.020*(0.007) (0.011)

Constant 0.252*** 0.273*** 0.282***(0.005) (0.005) (0.000)

Observations 1,539 1,539 1,516Controls No No NoProvince FE No Yes YesLLM FE No No Yes


Controls are average demographic characteristics of local labor markets. Back

62

Evolution of JBD cheating in the North and in the South

Asymmetric Window around Jan 10

.2.4

.6.8

Πgt fo

r JD

B ch

eatin

g

1920 1930 1940 1950 1960Year of Birth

North South

63

Evolution of 17BD cheating in the North and in the South

0.0

5.1

.15

.2.2

5Π

gt fo

r 17D

B ch

eatin

g

1920 1930 1940 1950 1960Year of Birth

North South

Back

64

Testing the effect of deterrence on Migrants and Remainers

In the following graph we plot:

• the change of the average share of JBD cheaters computed overintervals τ of two consecutive years,

• for Migrants out of the South,

πmsτ+1 − πmsτ

• and for Remainers in the South,

πrsτ+1 − πrsτ

• between the periods immediately before and after the 1926 reforms.Back

65

The effect of deterrence on Southern Migrants and Remainers

Asymmetric Window around Jan 1(1) (2) (3) (4)

VARIABLES

Migrant X I(27-28) 0.021 0.024* 0.025* 0.027*(0.014) (0.013) (0.013) (0.014)

Migrant -0.023* -0.044*** -0.014 0.005(0.013) (0.013) (0.012) (0.014)

I(27-38) -0.167*** -0.169*** -0.171*** -0.171***(0.023) (0.022) (0.022) (0.022)

Constant 0.687*** 4.098*** 1.459** -1.289(0.028) (0.806) (0.572) (1.132)

Observations 1,290 1,290 1,290 1,290R-squared 0.153 0.309 0.484 0.691Controls No Yes Yes YesProvince FE No No Yes YesLLM FE No No No Yes

Note: Southern local labor market in the period 1925-192866

ABR drain across Italian LLMs, due to migrations

Asymmetric Window around Jan 1

In each locality l (LLM) wemeasure JBD cheating of




δl = πlr − πlbgain mingain p25p50=0drain p75drain p95

67

ABR drain across Italian Provinces, due to migrations

In each locality l (province) wemeasure JBD cheating of




δl = πlr − πlb(0.006,0.108](0.000,0.006](-0.001,0.000](-0.006,-0.001][-0.133,-0.006]

68

Vote counting rate and value added

Source: Ilzetsky Simonelli, 2019 Back

69

Preliminary EvidenceModelGeographic SortingFascism and DeterrenceABR DrainEconomic ConsequencesAppendix

Documents

Geographic sorting and aversion to breaking rules · 2020. 11. 2. · Geographic sorting and aversion to breaking rules Massimo Anelli 1 Tommaso Colussi 2 Andrea Ichino3 1Bocconi,