Bank non-secrecy: taxation and financial service use in … · permitido inscribir a unos 21,023...
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Bank non-secrecy: taxation andfinancial service use in Mexico
Pierre Bachas (UC Berkeley) & Anders Jensen (LSE)
October 11, 2015
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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.
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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
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Bank secrecy L.A. vs OECD
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.2.3
.4.5
Re
gio
n−
sh
are
of
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un
trie
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Latin America (N=17) OECD (\MEX, N=29)
Court order Tax audit investigation Direct access
Source: (CIAT, 2012) (OECD, 2004)
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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– Short-lived, justified as repealed once having served itsinformation-collection purpose.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.
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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?
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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)
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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).
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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”
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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”
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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”
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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”
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IDE cumulative revenue
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Mil
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jan−
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july−08
jan−
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jan−
14
jan−
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Cumulative IDE revenue over time
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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
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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
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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
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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?
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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
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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.
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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
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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
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Cash deposit distributions0
50
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0N
um
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ep
osits
5000 15000 25000 35000 45000Sum of Cash deposits (Pesos)
IDE introduction, July 2008
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Nu
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5000 15000 25000 35000 45000Sum of Cash deposits (Pesos)
Threshold change, Jan 2010
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Nu
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5000 15000 25000 35000 45000Sum of Cash deposits (Pesos)
Pre Reform
Post Reform
IDE repeal, Jan 2014
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Repeal of IDE: Bunching over time
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Repeal of IDE: large cash deposits
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Bunching disapearance
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5000 15000 25000 35000 45000Sum of Cash deposits (Pesos)
Apr−Sept 13
Apr−Sept 14
IDE repeal − Below 50k
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Replaced by excess mass
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50000 60000 70000 80000 90000 100000Sum of Cash deposits (Pesos)
Apr−Sept 13
Apr−Sept 14
IDE repeal − Above 50k
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Zero cash deposits: slowdown in growth rate
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.44
.46
.48
.5.5
2P
erc
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tag
e a
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ro
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jan−13
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Oct
−14
Cash deposits at zero over time
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Large cash deposits: increase
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.07
.08
.09
.1.1
1P
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ve 1
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0 p
eso
s
jan−12
jan−13
jan−14
Oct
−14
Large cash deposits over time
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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
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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
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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
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Large non-cash deposits drop
.34
.36
.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
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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
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Large deposits: constant level
.4.4
2.4
4.4
6.4
8.5
Pe
rce
nta
ge
ab
ove
10
0,0
00
pe
sos
jan−12
jan−13
jan−14
Oct
−14
Large total deposits over time
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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?
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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”) thatare revealed preference constrained in their cashdeposits.
4. Heteorgeneity and correlations with other factors
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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
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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
−5 0 5months compared to bunching
Bunchers August
12000
14000
16000
18000
20000
22000
24000
Ave
rage c
ash
deposi
t
−5 0 5months compared to bunching
Bunchers October
12000
14000
16000
18000
20000
22000
24000
Ave
rage c
ash
deposi
t
−5 0 5Months compared to bunching
Bunchers December
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Event studies: buncher non-cash deposit60000
70000
80000
90000
100000
Ave
rage n
on−
cash
deposi
t
−5 0 5Months compared to bunching
Bunchers June
60000
70000
80000
90000
100000
Ave
rage n
on−
cash
deposi
t
−5 0 5Months compared to bunching
Bunchers August
60000
70000
80000
90000
100000
Ave
rage n
on−
cash
deposi
t
−5 0 5Months compared to bunching
Bunchers October
60000
70000
80000
90000
100000
Ave
rage n
on−
cash
deposi
t
−5 0 5Months compared to bunching
Bunchers December
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Event studies: buncher total deposit80000
90000
100000
110000
Ave
rage d
eposi
t
−5 0 5Months compared to bunching
Bunchers June
80000
90000
100000
110000
Ave
rage d
eposi
t
−5 0 5Months compared to bunching
Bunchers August
80000
90000
100000
110000
Ave
rage d
eposi
t
−5 0 5Months compared to bunching
Bunchers October
80000
90000
100000
110000
Ave
rage d
eposi
t
−5 0 5Months compared to bunching
Bunchers December
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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.
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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.
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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.
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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.
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Substitution
.44
.46
.48
.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
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Which technology?.3
6.3
8.4
.42
.44
pe
rce
tan
ge
of
clie
nts
0 10 20 30 40
Cash Windows − Firm services
.4.4
2.4
4.4
6p
erc
eta
ng
e o
f cl
ien
ts0 10 20 30 40
Internet
.24
.26
.28
.3.3
2p
erc
eta
ng
e o
f cl
ien
ts
0 10 20 30 40
Cheques
.1.1
1.1
2.1
3.1
4p
erc
eta
ng
e o
f cl
ien
ts
0 10 20 30 40
Electronic
.3.3
5.4
.45
pe
rce
tan
ge
of
clie
nts
0 10 20 30 40
Other
.13
5.1
4.1
45
.15
pe
rce
tan
ge
of
clie
nts
0 10 20 30 40
Punto de Ventas
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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
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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
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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
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Account types bunching 2008 reform
05
00
10
00
15
00
20
00
25
00
Density
5000 15000 25000 35000 45000Cash deposits (Pesos)
Individuals
05
00
10
00
15
00
20
00
25
00
Density
5000 15000 25000 35000 45000Cash deposits (Pesos)
Self_employed
05
00
10
00
15
00
20
00
25
00
Density
5000 15000 25000 35000 45000Cash deposits (Pesos)
Firms
IDE Introduction by client type
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Industry bunching 2008 reform
0.5
11
.5[#
de
p:
22
.5−
25
k]/
[# d
ep
: 2
5−
30
k]
GAS S
TATION
GRO
CER
Y STO
RE
AGRIC
SHO
PPING
PRO
FESSIONAL
SERV
EDUC S
ERV
RESTAU
RAN
T
MED
ICAL
SERV
REN
TAL
GO
VERNM
ENT
VIVIE
NDA
METAL
PRO
CESSIN
G .
NO
VIV
IENDA
AUTO
FINAN
SER
V
SUPPLI
ES, STATIO
NER
Y
LEIS
URE P
ARKS
OTH
ER IN
DUS
TRAN
SPORT
MIN
ING
TEXTILE
CHEM
ICALS
ELECTR
ICIT
Y
PAPER
HO
TELS
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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]
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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
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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]
State−2008 Fitted values
Source: INEGI Sistema Estatal for IMSSBachas & Jensen Bank non-secrecy: taxation and financial service use in Mexico 51/54
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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]
State−2008 Fitted values
Source: INEGI Sistema Estatal en materia penal. Cases are sentencesBachas & Jensen Bank non-secrecy: taxation and financial service use in Mexico 52/54
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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]
State−2008 Fitted values
Source: INEGI Sistema Estatal en materia penal. Cases are sentencesBachas & Jensen Bank non-secrecy: taxation and financial service use in Mexico 53/54
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THANK YOU
I Contact: [email protected]
Bachas & Jensen Bank non-secrecy: taxation and financial service use in Mexico 54/54