bank non-secrecy: taxation and ﬁnancial service use in … · permitido inscribir a unos 21,023...

Bank non-secrecy: taxation andfinancial service use in Mexico

Pierre Bachas (UC Berkeley) & Anders Jensen (LSE)

October 11, 2015

Bachas & Jensen Bank non-secrecy: taxation and financial service use in Mexico 1/54

Financial information

• Financial information could be key for effective taxation– On extensive margin: detect unregistered taxpayers– On intensive margin: estimate revenue and assets

• Financial information trail leveraged to detect varioustypes of income

– Multinational tax avoidance and wealthy individuals(Zucman 2014) Big debate in OECD countries (e.g. USIRS and Swiss banks)

– Domestic tax avoidance/evasion (Gordon & Li 2009)Particularly important in the absence of other info trails?

• Increasing pressure to end bank secrecy but still stronginstitution in developing countries.


Financial information

Table : Tax administration access to bank information in L.A.

Judge authorization Specific cases (audit) Direct access

Argentina (AFIP) xBolivia (SIN) xBrasil (RFB) xChile (SII) xColombia (DIAN) xCosta Rica (DGT) xEcuador (SRI) xEl Salvador (DGII) xGuatemala (SAT) xHonduras (DEI) xMexico (SAT) xNicaragua (DGI) xPanama (DGI) xParaguay (SET) xPeru (SUNAT) xRep. Dominicana (DGI) xUruguay (DGI) x

Source: Inter American Center for Tax administration (CIAT) 2012


Bank secrecy L.A. vs OECD

0.1

.2.3

.4.5

Re

gio

n−

sh

are

of

co

un

trie

s

Latin America (N=17) OECD (\MEX, N=29)

Court order Tax audit investigation Direct access

Source: (CIAT, 2012) (OECD, 2004)


Financial services taxes

• Many countries have taxed financial services -Sometimes with an “information trail” logic. (L.A. , India,Pakistan). What characterizes these policies:

– Taxing basic transactions (deposits and withdrawals) -often cash specific.

– Fill urgent budgetary needs - initially collects a lot ofrevenue (Coehlo et al 2009)

– Short-lived, justified as repealed once having served itsinformation-collection purpose. Could also be becausebehavioural responses→ zero revenue in medium-run

• But no micro-evidence on behavioral responses:– Distortions could be large in countries developing

financial inclusion.


What this study does

• Study a policy motivated by leveraging the financialinformation trail and fighting tax evasion in Mexico

– Large informal sector and low tax/gdp ratio– Low financial inclusion given gdp

• Show important behavioral responses:– Policy led to restriction in cash deposits– Large share can be explained by substitution to other

deposits types. → Limitted loss of total deposits

• New puzzle: technology disadoption?


Outline

• Present IDE

• Theory (Very simple)

• EmpiricsI Distribution over time of cash depositsI Distributions of non-cash and total depositsI Focus on “bunchers” behaviorI Some heteorgeneity and correlations

• Welfare (Discussion and next steps)


IDE

• Base = monthly cash deposits above threshold

• Non-cash deposits are not taxed

• Control tax: fully deductible against any other tax liability

• Financial institutions are liable for tax collection andinforming their clients (Transaction costs incurred).


IDE quotes

• El Economista, June 2009“Superando lo esperado, el Impuesto a los Depositos en Efectivo (IDE) cumple hoy

un ano. Por un lado, dejo al descubierto a casi 2 millones de posibles evasores queahora el fisco tendra que ir a buscar. Esta cifra equivale al numero de personasreportadas por los bancos al SAT, que nunca declararon el pago del Impuesto.”

• Jose Gonzalez Anaya, revenue subsecretary, July 2011:“El IDE ha sido fundamental para afinar la fiscalizacion en el pais, pues ha

permitido inscribir a unos 21,023 contribuyentes solo en el 2010 y ha permitidocorregir el Registro Federal de Contribuyentes (RFC) de otros 384,000 causantes,”

• Forum, Financial Red ”Como funciona IDE”, January 2012“Lo que deberiamos hacer todos es guardar el dinero en cajas fuertes, en casa, enun colchon, que se yo. pero sacarlo del banco”

• “Al igual que todos odio este maldito impuesto, pero he sabido de algunos tips sobretodo a los comerciantes pequenos, les recomiendo que el pago a sus probedoressea por deposito a cuentas de ellos generalmente son grandes empresas y el ide noles afecta por que lo deducen, paguen cuanto mas servicios y productos se puedaen efectivo, y solo depositen lo que verdaderamente es su utilidad ... Ni un pesomas de impuestos”


IDE cumulative revenue

01

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20

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05

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Cu

mu

lative

re

ve

nu

e (

Mil

pe

so

s)

jan−

07

july−08

jan−

10

jan−

14

jan−

15

Cumulative IDE revenue over time


Macro environment

11

.52

2.5

Se

mi−

an

nu

al va

lue

in

de

xe

d (

1st

ha

lf 2

00

5=

=1

)

1st H

−2005

1st H

−2006

1st H

−2007

1st H

−2008

1st H

−2009

1st H

−2010

1st H

−2011

1st H

−2012

1st H

−2013

1st H

−2014

GDP Total deposits Tax revenue


Macro picture

• IDE directly collected revenue only in first 2 years:I Delays in deduction and learning about IDE?I Formalization so everyone deducts?I Financial disintermediation?

• Macro levelI Tax revenue and total deposits grow faster than GDP

over period.I However cash economy and informality on the rise over

period (INEGI, OECD)I Polarization of informal and formal sector?

• Go to micro level to look deeper


Theory: set-up

• Agent generates revenue flow Fit , which she has tostore. Three storage technologies:

– Store flow at home, c– Deposit flow at bank under cash format, d– Deposit flow at bank under non-cash format, e

• Relative gains and losses– Gain of financial usage (d , e) over cash at home c:

Safety, access to loans, bank relation, etc.– Gain of non-cash e over cash financial use d : more

efficient services, improved credit conditions (?)– Loss from non-cash e: technology adoption cost f


Theory: introduction and repeal of IDE

• Agent maximizes: Vit = cit + βitdit + γiteit − f .1(eit > 0)

• Pre-IDE: financial usage dominates cash-economy ifmin(γit − f , βit) > 1if γit − f > βit , then adopt non-cash financial technology• IDE introduction: βi ↓ if dit > Threshold

– Decrease in d , can switches to c or e

• IDE repeal with tax reform: γt ↓ , βtγt↑ , βt unclear

– Increase in d ; some agents switch from e to d (butpotentially not complete reversal from pre-IDE).

– Assumptions on fixed cost f : incurred every period oronce?


Theory: basic predictions and extensions

• Basic prediction: IDE-introduction leads to ↓ d , switch toc or e is governed by agent-heterogeneity in thetwo-dimensional space (βi , γi)

– Corollary of basic set-up: bunching dit = Threshold isoptimal strategy for subset of agents

• Dynamic extension: forward-looking choices– If agent faces Fit >> Threshold , possibly optimal to

repeatedly bunch d in periods t , t + 1, t + 2, ...– Agent will weigh net present value of dynamic bunching

relative to one-off net gain from switching to e: foragents with high Fit , repeated bunching is too costly


Data

• Panel of accounts from large Mexican bank (300,000clients)

– Current focus on balanced panel of self-employed(N=82,000), most responsive to policy.

– All Deposits and withdrawals at monthly level bytransaction method

– Other financial products (e.g loans and credit cards)– Socio-demographics (locality, occupation, gender, age)

• Continuous monthly panel starting April 2011 untilOctober 2014.

• Main data issue: hard to study all effects of 2008 and2010 reforms as only have month of December of 2006,08, 09, 10.


Empirics preview

Focus on Repeal of IDE, part of 2014 Fiscal Reform:

1. Distribution over time of cash deposits:→ large reaction of cash to the reform.

2. Distributions of non-cash and total deposits:→ Substitution from non-cash to cash deposits.→ Limitted evidence of change in total deposits.

3. Study the behavior of subgroup (“bunchers”) that arerevealed preference constrained in their cash deposits.

4. Heteorgeneity and correlations with other factors


Empirics preview







Cash deposit distributions0

50

01

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01

50

02

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02

50

03

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0N

um

be

r d

ep

osits

5000 15000 25000 35000 45000Sum of Cash deposits (Pesos)

IDE introduction, July 2008

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Nu

mb

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Threshold change, Jan 2010

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30

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Nu

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Pre Reform

Post Reform

IDE repeal, Jan 2014


Repeal of IDE: Bunching over time


Repeal of IDE: large cash deposits


Bunching disapearance

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cash

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Apr−Sept 13

Apr−Sept 14

IDE repeal − Below 50k


Replaced by excess mass

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20

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Nu

mb

er

cash

de

po

sits

50000 60000 70000 80000 90000 100000Sum of Cash deposits (Pesos)

Apr−Sept 13

Apr−Sept 14

IDE repeal − Above 50k


Zero cash deposits: slowdown in growth rate

.42

.44

.46

.48

.5.5

2P

erc

en

tag

e a

t ze

ro

jan−12

jan−13

jan−14

Oct

−14

Cash deposits at zero over time


Large cash deposits: increase

.06

.07

.08

.09

.1.1

1P

erc

en

tag

e a

bo

ve 1

00

,00

0 p

eso

s

jan−12

jan−13

jan−14

Oct

−14

Large cash deposits over time


Beyond cash deposits

• Clear evidence that IDE repeal (and tax reform?)encouraged use of cash deposit:

– Reduced frequency of small cash deposits (5-25k) anddisapreance of excess mass at threshold (15k)

– Increased frequency of medium (30-100k) andespecially of large ( > 100k ) cd.

• Substitution away from non-cash deposits or increase intotal deposits?Look at:

1. Checks, electronic, cards which are non taxable.2. Total deposits. Ex-ante effect is ambiguous:

IDE repeal ↑, Fiscal reform ↓3. Buncher’s deposit behavior post reform


Empirics preview







Zero non-cash deposits increase

.18

.19

.2.2

1.2

2P

erce

ntag

e at

zer

o

jan−12

jan−13

jan−14

Oct−14

Non cash deposits at zero over time


Large non-cash deposits drop

.34

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.38

.4.4

2.4

4P

erce

ntag

e ab

ove

100,

000

peso

s

jan−12

jan−13

jan−14

Oct−14

Large non−cash deposits over time


Zero total deposits: constant growth rate

.08

.1.1

2.1

4.1

6P

erc

en

tag

e a

t ze

ro

jan−12

jan−13

jan−14

Oct

−14

Total deposits at zero over time


Large deposits: constant level

.4.4

2.4

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8.5

Pe

rce

nta

ge

ab

ove

10

0,0

00

pe

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jan−12

jan−13

jan−14

Oct

−14

Large total deposits over time


Substitution and total effect

• Focus ont two moments: % deposits at 0 and %deposits above $100,000

• Slowdown in growth rate of 0 cash deposits mirrors dropin 0 non-cash deposits.

• Increase of large cash dep from 7 to 11% correspondsto drop in large non-cash dep from 40 to 36%→ Substitution across deposit technologies.

• Substitution seems to explain total deposits behavior.→ No change in total dep?


Empirics preview




3. Study the behavior of subgroup (“bunchers”) thatare revealed preference constrained in their cashdeposits.



Bunchers

• Focus on group particularly affected by IDE reform:“bunchers”

– Defined as having deposited in the 13-15k c.d. -¿ Half ofthose firms constrained.

– Threshold potentially represented binding constraint.– Can think of intensity of treatment (regularility of c.d

bunching) and different comparison groups (note: nevera clean “control” group)

• Look at their behavior:– “Event studies” around reform: look at average deposits

in subsequent month following bunching month.– Regression analysis: compare bunchers to smaller

depositors and within bunchers number of timesbunching


Event studies: buncher cash deposit12000

14000

16000

18000

20000

22000

24000

Ave

rage c

ash

deposi

t

−5 0 5months compared to bunching

Bunchers June

12000

14000

16000

18000

20000

22000

24000

Ave

rage c

ash

deposi

t


Bunchers August

12000

14000

16000

18000

20000

22000

24000

Ave

rage c

ash

deposi

t


Bunchers October

12000

14000

16000

18000

20000

22000

24000

Ave

rage c

ash

deposi

t

−5 0 5Months compared to bunching

Bunchers December


Event studies: buncher non-cash deposit60000

70000

80000

90000

100000

Ave

rage n

on−

cash

deposi

t


Bunchers June

60000

70000

80000

90000

100000

Ave

rage n

on−

cash

deposi

t


Bunchers August

60000

70000

80000

90000

100000

Ave

rage n

on−

cash

deposi

t


Bunchers October

60000

70000

80000

90000

100000

Ave

rage n

on−

cash

deposi

t


Bunchers December


Event studies: buncher total deposit80000

90000

100000

110000

Ave

rage d

eposi

t


Bunchers June

80000

90000

100000

110000

Ave

rage d

eposi

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Bunchers August

80000

90000

100000

110000

Ave

rage d

eposi

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Bunchers October

80000

90000

100000

110000

Ave

rage d

eposi

t


Bunchers December


Regression: Bunchers vs 10-12k

yit = α+ β.Postt + γ.Treati + δ.Postt .Treati + εit

Cash dep Noncash dep Total Dep

2013-14Post 4,724∗∗ -5,644∗∗ -916

(348) (743) (807)Post-Treat 2,153∗∗ -1,490 663

(474) (962) (1043)constant 12,934 82,845 95,779obs 368,148 368,148 368,148

2012-13Post -439∗ -1,212 -1,651∗

(209) (730) (760)Post-Treat -112 764 652

(278) (954) (999)constant 14,334 83,406 97,740obs 408,936 408,936 408,936

Note: DinD regression. Treat is defined as at least once in 13-15k in pre period. Control isat least once in 10-12k and only observations not appearing on both groups are kept.


Regression: Bunchers intensity

yit = α+ β.Postt + γ.Intensityi + δ.Postt .Intensityi + εit

Cash dep Noncash dep Total Dep

2013-14Post 3905∗∗ -6,234∗∗ -2,328∗∗

(415) (749) (806)Post-Intensity 1,763∗∗ -453 1,309∗∗

(206) (285) (313)constant 13,334 81,469 94,804obs 343,794 343,794 343,794

2012-13Post -1,401∗∗ 604 -796

(173) (582) (608)Post-Intensity 243∗∗ 337 581∗

(66) (214) (225)constant 14,334 80260 96,530obs 375,048 375,048 375,048

Note: Regression within bunchers, where intensity is the number of month in the pre yearduring which cash deposits were in the 13-15k bin.


Buncher summary

• Large increase of bunchers c.d post reform:→ bunchers were c.d constrained

• Avg $10,000 increase in c.d. explained by $10,000 dropin non-cash deposits.

• Total deposit effect seems again limitted:– Bunchers did not increase total dep by more than

smaller depositors despite increasing c.d. by more.– Only subgroup of regular bunchers increased total

deposits.


Summary and technology

• IDE repeal:– ↑ cash deposit which substitute non-cash deposits– Limitted effect on total deposits. IDE repeal cancelled by

increased information component of fiscal reform?– Bunchers were c.d constrained

• Seems IDE encouraged other deposit technologywithout a significant disintermediation effect?

• Technology puzzle: non-cash technology dis-adoptedfast after IDE repeal. → Against standard technologyadoption models.


Substitution

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.5.5

2perc

eta

nge o

f cl

ients

0 10 20 30 40

Cash Deposit

.76

.77

.78

.79

.8perc

eta

nge o

f cl

ients

0 10 20 30 40

Non−cash Deposits


Which technology?.3

6.3

8.4

.42

.44

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tan

ge

of

clie

nts

0 10 20 30 40

Cash Windows − Firm services

.4.4

2.4

4.4

6p

erc

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ng

e o

f cl

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ts0 10 20 30 40

Internet

.24

.26

.28

.3.3

2p

erc

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ng

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f cl

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ts

0 10 20 30 40

Cheques

.1.1

1.1

2.1

3.1

4p

erc

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ng

e o

f cl

ien

ts

0 10 20 30 40

Electronic

.3.3

5.4

.45

pe

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0 10 20 30 40

Other

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5.1

4.1

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.15

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0 10 20 30 40

Punto de Ventas


Welfare and discussion

• Welfare evalution of IDE balances revenue gains againstreform-induced distortions• Clear evidence that IDE distorted the financial behaviour

of bank-clients– IDE repeal ↑ cash deposits and substitute away from

non-cash deposit types– But not clear if IDE had any effect on total deposits→

limitted financial disintermediation?– Difficult to study 2008 and 2010 reform: clients

disintermediated then and in 2014 reform only observebehavior of substituters?

– Are there costs to the bank from changing deposittypes? Second round effects on credit?

– Bank and clients incurred transaction and liquidity costs


Empirics preview







Heterogeneous responses

• Expect heterogeneity in response to IDE– by legal type/industry: technological variation in ability to

trade in cash?– by state/size of informal sector: variation in prevalence

of cash-economy?

• Use bunching from the 2008 introduction of IDE– Bunching intensity summary measure: number of

monthly cash deposits in bin 22.5-25k, relative tonumber of cash deposits in 25-30k bin


Account types bunching 2008 reform

05

00

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20

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25

00

Density

5000 15000 25000 35000 45000Cash deposits (Pesos)

Individuals

05

00

10

00

15

00

20

00

25

00

Density


Self_employed

05

00

10

00

15

00

20

00

25

00

Density


Firms

IDE Introduction by client type


Industry bunching 2008 reform

0.5

11

.5[#

de

p:

22

.5−

25

k]/

[# d

ep

: 2

5−

30

k]

GAS S

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CHEM

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State level bunching 2008 reform

(1.2,1.6](1.15,1.2](1.1,1.15](1.08,1.1](1,1.08](.92,1][.4,.92]


Bunching & informality

40

50

60

70

Info

rma

l sh

are

of

no

n−

ag

r a

ctiv

e p

op

ula

tion

, %

.5 1 1.5[# dep: 22.5−25k]/[# dep: 25−30k]

State−2008 Fitted values

INEGI, ENOE survey. Labor-force share of non-registered workers; paiddomestic service


Bunching & SS registrations

.1.2

.3.4

.5.6

IMS

S r

eg

iste

red

sh

are

of

active

po

p,

%

.5 1 1.5[# dep: 22.5−25k]/[# dep: 25−30k]


Source: INEGI Sistema Estatal for IMSSBachas & Jensen Bank non-secrecy: taxation and financial service use in Mexico 51/54

Bunching & organized crime

0.0

0005

.000

1.0

0015

Org

aniz

ed c

rime

cour

t cas

es p

er c

apita

.5 1 1.5[# dep: 22.5−25k]/[# dep: 25−30k]


Source: INEGI Sistema Estatal en materia penal. Cases are sentencesBachas & Jensen Bank non-secrecy: taxation and financial service use in Mexico 52/54

Bunching & narcotics

0.0

01.0

02.0

03N

arco

tics−

rela

ted

cour

t cas

es p

er c

apita

.5 1 1.5[# dep: 22.5−25k]/[# dep: 25−30k]


Source: INEGI Sistema Estatal en materia penal. Cases are sentencesBachas & Jensen Bank non-secrecy: taxation and financial service use in Mexico 53/54

THANK YOU

I Contact: [email protected]


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