econ 230b { graduate public economics taxation in developing...
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Econ 230B – Graduate Public Economics
Taxation in developing countries
Gabriel Zucman
1
Roadmap
1. Taxes over the path of development
2. The structure of taxation in developing countries
3. Tax base elasticities and investment in tax capacity
2
ALB ARG
ARM
AUS
AUT
AZE
BGD
BLR
BEL
BEN
BOL
BIH
BRABGR
BFAKHM
CMR
CAN
CAFTCD
CHLCHNCOL
COD
CRI
CIV
HRV
CUB
CZE
DNK
DOMECUSLV
EST
ETH
FINFRA
GMB
DEU
GHA
GRC
GTMGIN
GNB
HTI
HND
HKG
HUN
IND
IDN
IRN
IRL
ISR
ITA
JAM
JPN
JOR
KAZ
KEN
KOR
LAO
LVA
LBNLBR
LTUMKD
MDG
MWI MYSMLIMRT
MUSMEX
MDA
MNG
MAR
MOZ
MMR
NAM
NPL
NLDNZL
NICNER
NOR
PAK
PAN
PNG
PRY
PER
PHL
POLPRT
ROU
RWA
SEN
SLE
SGP
SVK
SVN
ZAF
ESP
LKA
SDN
SWE
CHE
SYR
TJK
TZA
THA
TGO
TTOTUN TUR
UGA
UKRGBR
USAURYUZB
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are
of T
axes
in G
DP
6 7 8 9 10 11 12Log GDP per capita
3
Key question in taxation & development: how does a gov. gofrom raising 10% of GDP in taxes to raising around 40%? Two views:
• Pessimistic view: it takes mass-mobilization wars or revolutions(e.g., Scheve & Stasavage 2012; Scheidel 2017)
• Optimistic view: as countries develop, easier to collect taxes (e.g.,tax enforcement simpler as businesses grow bigger & more formal)
• To shed light on this debate, useful to study how today’sdeveloped countries have achieved high tax rates
• And important to study recent trends in developing countries
4
1 Taxes over the path of development
• During 20th century, big rise of tax revenues in today’s richcountries: from 10% to 30-50% of national income
• Part of this jump happens during and just after World Wars
• Previous wars had seen some increase in gov. size (Tilly 1975:“war made the State and the State made war”), but not persistent
• Specificity of mass-mobilization wars: led to development of majornew institutions (public pensions, Welfare State) → ratchet effect
5
20%
30%
40%
50%
60%
Tota
l tax
reve
nues
(% n
atio
nal i
ncom
e)
Figure 13.1. Tax revenues in rich countries, 1870-2010
Sweden
France
U.K.
U.S.,
0%
10%
1870 1890 1910 1930 1950 1970 1990 2010
Tota
l tax
reve
nues
(% n
atio
nal i
ncom
e)
Total tax revenues were less than 10% of national income in rich countries until 1900-1910; they represent between 30% and 55% of national income in 2000-2010. Sources and series: see piketty.pse.ens.fr/capital21c.
Source: Piketty (2014)
6
Rise of taxes during 20th century corresponds to change in the formof taxation:
• Before 20th century: mostly archaic indirect taxes
• First half of twentieth century: birth of progressive income andwealth taxation
• Largely as a response to world wars, communist revolution, highinequality
• Second half: broad-based VAT and Social Security contributions tofund welfare State (education, health & means-tested transfers)
7
Archaic indirect taxes
Key source of revenue since the Roman Empire. Two main forms:
1. Taxes on trade: for using roads, crossing bridges, arriving inharbor...
2. Taxes on consumption: on goods sold, on salt, on slaves...
Middle-Ages: role of trade fairs where exchanges are concentrated →makes it easier for governments to impose sales taxes
Indirect taxes still very high up to late 19th century: 60% of taxrevenue in France just before World War I
8
The birth of progressive taxation
• Three forms of progressive taxes: progressive income taxes,progressive inheritance taxes, progressive estate taxes
• Before WW1: no or very limited progressive taxation
• Very high top marginal tax rates = a US invention in the late1910s-1920s. Two motivations:
– Confiscate excess profits from war (so as to discouragewarmongering)
– But also fear of becoming as unequal as Europe (Fisher, 1919)9
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Top
Mar
gina
l Tax
Rat
e
Top marginal income tax rates, 1900-2013
U.S.
U.K.
Germany
France
10
The invention of the VAT
• Invented by French civil servant Maurice Laure in the 1950s
• Introduced in France in 1954, then Denmark (1967), Germany(1968), Sweden (1969)...
• About 160 countries in total today have a VAT (exceptions: USA,Iraq, Saudi Arabia, Syria, etc.)
• Key property: firms can offset VAT on their purchases againstliability on their sales → paper trail → low evasion
11
Figure 4: Historical Evolution of fiscal capacity
around 10% in national income to around 25% in the sample as a whole.
Equally striking is the increasing reliance on income taxation which only
made up about 5% of revenues in 1900 but about 50% by the end of the last
century. The hikes of the income tax share during the two world wars, and
the ratchet effect associated with them, also stand out in the picture.However, the narrow sample in Figures 4 and 5 ignores many of the poorer
countries in the world. We would also like to use the model in this chapter to
understand how fiscal capacity varies over countries. A first salient featureof the data is that richer countries tend to raise more tax revenue as a share
of national income than poorer countries. This is illustrated in Figure 6.
The left panel plots the overall tax take as a share of GDP from Baunsgaard
and Keen (2005) against the log of GDP per capita from the Penn World
Tables, both measured around the year 2000, and distinguishes observations
by income. The right panel looks at the same relationship instead using
the time-series data on our sample of 18 countries from Mitchell (2007) to
plot five-year averages of the tax share over the twentieth century againstnational income from Maddison’s data, and distinguishing observations by
10
Source: Besley and Persson (2013)
12
Self-enforcing nature of VAT: Pomeranz (AER 2015)
• Randomized experiment with 445,000 firms in Chile: threat ofVAT audit letters sent to sub-sample of businesses
• Significant effect of letters on VAT collection
• Smaller impact on reported transactions that already have a papertrail (intermediate sales) than on those that don’t (final sales)
• Effect of random audit announcement is transmitted up the VATchain, increasing compliance by firms’ suppliers
13
2558 THE AMERICAN ECONOMIC REVIEW AUGUST 2015
I compare the impact of the deterrence letter to the tax morale and placebo letters to determine whether deterrence drives the effect. Panels B and C of Figure 2 show that in contrast to the deterrence letter, no marked increase is visible at the time of the mailing. The apparent first increase in Panel B happens before mailing, and the second increase almost a year later is very unlikely to be due to the letter. The variance is larger due to the smaller sample size. This comparison shows that it is the content of the deterrence letter that drives the response, not simply the fact of receiving mail from the tax authority.
Table 4 shows the same result in regressions for the mean, median, probability of declaring more than in the same month of the previous year, probability of declaring more than predicted, and probability of declaring any positive amount. All specifi-cations confirm a highly significant impact of the deterrence message, except for the
Mailing of letters−5
0
5
10
Per
cent
diff
eren
ce in
med
ian
VA
T
−18 −12 −6 0 6 12
Month
Panel B. Motivational versus control (median)
Mailing of letters
−5
0
5
10P
erce
nt d
iffer
ence
in m
edia
n V
AT
−18 −12 −6 0 6 12
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Panel A. Deterrence versus control (median)
Mailing of letters
−5
0
5
10
Per
cent
diff
eren
ce in
med
ian
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T
−18 −12 −6 0 6 12
Month
Panel C. Placebo versus control (median)
Figure 2. Impact of the Three Types of Letters
Notes: This figure plots the monthly percent difference between the medians of the treatment and the control group for each type of letter: (median VAT treatment group—median VAT control group)/(median VAT control group), normalizing the average of pretreatment months percent difference to zero. The y-axis indicates time, with monthly observations, and zero indicates the last month before the mailing of the letters. The vertical line marks mailing of the letters. The figure shows the first wave of mailing. For the second (much smaller) wave of mailing, see online Appendix Figure A2.
Source: Pomeranz (2015)
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2559POMERANZ: NO TAXATION WITHOUT INFORMATION VOL. 105 NO. 8
regression using mean VAT, which as expected does not provide statistically signif-icant results.38 The deterrence letter led to a 1,326 peso increase in the median VAT per month, a 7.6 percent increase compared to the baseline median. The probability of declaring more than in the same month of the previous year increased by 1.4 per-centage points, the probability of declaring more than predicted by 1.42 percentage points, and the probability of declaring any positive amount by 0.53 percentage points. All estimates are significant at the 1 percent level.
For robustness, I also report estimates from alternative estimation strategies for the nonlinear models in online Appendix Table A2: Athey and Imbens (2006) for the changes-in-changes estimation on the median VAT and Blundell and Dias (2009) for a nonlinear difference-in-differences estimate of the probability of an increase in VAT compared to the previous year. The results remain qualitatively the same. Finally, online Appendix Table A3, column 1 shows a robustness check that includes the carryovers from previous declarations and also finds a very similar effect.
38 The tax morale letter only has a significant effect on the margin of declaring a positive amount. In line with this, quantile results not shown here find no significant effects overall, except for an increase by those with very low or negative declared VAT. For these firms, receiving a letter about high compliance by others may have a deterrence effect, as it may suggest that the tax authority suspects them of evasion.
Table 4—Letter Message Experiment: Intent-to-Treat Effects on VAT Payments by Type of Letter
MeanVAT
MedianVAT
Percent VAT > previous year
PercentVAT > predicted
PercentVAT > zero
(1) (2) (3) (4) (5)Deterrence letter × post −1,114 1,326*** 1.40*** 1.42*** 0.53***
(2,804) (316) (0.12) (0.10) (0.09)Tax morale letter × post −1,840 262 0.40 0.30 0.44**
(6,082) (666) (0.25) (0.22) (0.20)Placebo letter × post 835 383 −0.11 −0.19 −0.14(6,243) (687) (0.26) (0.23) (0.20)Constant 268,810*** 17,518*** 47.50*** 48.27*** 67.30***
(1,799) (112) (0.07) (0.07) (0.06)Month fixed effects Yes Yes Yes Yes YesFirm fixed effects Yes No Yes Yes YesTreatment assignment No Yes No No No
Observations 7,892,076 1,221,828 7,892,076 7,892,076 7,892,076Number of firms 445,734 445,734 445,734 445,734 445,734Adjusted R 2 0.40 0.14 0.28 0.47
Notes: Column 1 shows a regression of the mean declared VAT on treatment dummies, winsorized at the top and bottom 0.1 percent to deal with extreme outliers. Column 2 shows a median regression of average VAT before treat-ment and in four months after each treatment wave. Columns 3–5 show linear probability regressions of the proba-bility of an increase in declared VAT compared to the same month in the previous year, the probability of declaring more than predicted and the probability of declaring any positive amount. Observations are monthly in columns 1 and 3–5 for ten months prior to treatment and four months after each wave of mailing. The four months after the second wave excludes firms treated in the first. Coefficients and standard errors of the linear probability regressions are multiplied by 100 to express effects in percent. Monetary amounts are in Chilean pesos, with 500 Chilean pesos approximately equivalent to $1. Standard errors in parentheses, robust and clustered at the firm level for columns 1 and 3–5.
*** Significant at the 1 percent level. ** Significant at the 5 percent level. * Significant at the 10 percent level.
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2563POMERANZ: NO TAXATION WITHOUT INFORMATION VOL. 105 NO. 8
Table 6—Interaction of Firm Size and Share of Sales to Final Consumers
Percent VAT > previous year
(1) (2) (3) (4) (5)Panel A Deterrence letter × final sales share 1.61*** 1.48*** 1.43***
(0.26) (0.27) (0.26) Deterrence letter × size category −0.17*** −0.10***(0.04) (0.04) Deterrence letter × log employees −0.45*** −0.29**(0.11) (0.12)Deterrence letter 0.68*** 2.63*** 1.66*** 1.49*** 0.92***
(0.16) (0.29) (0.13) (0.35) (0.19)Constant 47.53*** 48.87*** 47.50*** 48.89*** 47.53***
(0.08) (0.08) (0.08) (0.08) (0.08) Final sales share × post Yes No No Yes Yes Size measure × post No Yes Yes Yes YesFirm fixed effects Yes Yes Yes Yes YesMonth dummies Yes Yes Yes Yes Yes
Observations 7,308,631 7,116,590 7,340,994 7,084,823 7,308,631Number of firms 406,834 396,135 408,636 394,367 406,834Adjusted R 2 0.14 0.14 0.14 0.14 0.14
Percent VAT > predicted
(1) (2) (3) (4) (5)Panel B Deterrence letter × final sales share 1.51*** 1.51*** 1.44***
(0.23) (0.25) (0.24) Deterrence letter × size category −0.10*** −0.03(0.03) (0.04) Deterrence letter × log employees −0.28*** −0.11(0.10) (0.11)Deterrence letter 0.74*** 2.15*** 1.57*** 1.00*** 0.83***
(0.14) (0.26) (0.12) (0.32) (0.16)Constant 48.48*** 49.79*** 48.26*** 50.01*** 48.48***
(0.08) (0.08) (0.08) (0.08) (0.08) Final sales share × post Yes No No Yes Yes Size measure × post No Yes Yes Yes YesFirm fixed effects Yes Yes Yes Yes YesMonth fixed effects Yes Yes Yes Yes Yes
Observations 7,308,631 7,116,590 7,340,994 7,084,823 7,308,631Number of firms 406,834 396,135 408,636 394,367 406,834Adjusted R 2 0.28 0.26 0.29 0.26 0.28
Notes: Regression of the probability of monthly declared VAT being higher than in the same month of the previous year (panel A) and on being higher than predicted (panel B). Coefficients and standard errors are multiplied by 100 to express effects in percent. Sample includes all firms in the deterrence treatment and in the control group. The four months after the second wave excludes firms treated in the first. Number of observations vary due to missing obser-vations for some variables. Final sales share is not defined for firms with zero sales in preceding year, size category is not available for new firms. Robust standard errors in parentheses, clustered at the firm level.
*** Significant at the 1 percent level. ** Significant at the 5 percent level. * Significant at the 10 percent level.
Source: Pomeranz (2015)
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2565POMERANZ: NO TAXATION WITHOUT INFORMATION VOL. 105 NO. 8
The findings remain robust even after inclusion of the control variables, indicating that it is not the different nature of supplier and client firms, but rather their position in the VAT chain that seems to be driving the result.47 Online Appendix Figure A5 shows graphical evidence of the impact of the preannouncement on VAT payments by trading partners.
The findings of the Spillover Experiment provide several insights. First, as pre-dicted by the self-enforcement hypothesis, the built-in paper trail of the VAT leads to spillovers of enforcement up the production chain. Monitoring a firm increases tax payments by its suppliers. Second, this indicates that when taking the whole network of firms into account, the paper trail globally acts as a complement to the audit probability: it augments the effectiveness of an increase in the audit probabil-ity of one firm, by increasing VAT payments by others.
Third, the mere existence of information through the paper trail—not surpris-ingly—is not by itself self-enforcing in an environment where the risk of cross-checks
47 Online Appendix Table A3 shows a robustness check including carryovers from previous VAT declarations. As expected, this introduces more noise, since the firms in the Spillover Experiment had large carryovers from the pretreatment period. The results on the differential spillover effects are robust, though less significant.
Table 7—Spillover Effects on Trading Partners’ VAT Payments
Percent VAT> previousyear
PercentVAT> predicted
Percent VAT> previous year
PercentVAT> predicted
Percent VAT> previous year
PercentVAT> predicted
(1) (2) (3) (4) (5) (6) Audit announcement 2.41** 2.03* × post (1.14) (1.11) Audit announcement 4.28*** 3.92*** 4.14*** 3.83*** × supplier × post (1.54) (1.50) (1.52) (1.52) Audit announcement −0.26 −0.28 −0.14 −0.28 × client × post (1.64) (1.51) (1.67) (1.55) Supplier × post −0.64 0.34 −1.11 0.60
(1.62) (1.59) (1.67) (1.64)Constant 52.07*** 49.06*** 52.07*** 49.06*** 52.75*** 50.11***
(0.95) (0.94) (0.95) (0.94) (0.96) (0.96) Controls × post No No No No Yes Yes Controls × audit No No No No Yes Yes announcement × post
Month fixed effects Yes Yes Yes Yes Yes YesFirm fixed effects Yes Yes Yes Yes Yes Yes
Observations 45,264 45,264 45,264 45,264 44,288 44,288Number of firms 2,829 2,829 2,829 2,829 2,768 2,768Adjusted R 2 0.05 0.11 0.05 0.11 0.05 0.10
Notes: Regressions for trading partners of audited firms. Columns 1, 3, and 5 show the probability of an increase in declared VAT since the previous year, columns 2, 4, and 6 show the probability of declaring more than predicted. The controls in columns 5 and 6 are firm sales, sales/input-ratio, share of sales going to final consumers, and indus-try categorized as “hard-to-monitor.” Observations are monthly for ten months prior to treatment and six months after the audit announcements were mailed. Coefficients and standard errors are multiplied by 100 to express effects in percent. Robust standard errors in parentheses, clustered at the level of the audited firm.
*** Significant at the 1 percent level. ** Significant at the 5 percent level. * Significant at the 10 percent level.
17
Why does third-party reporting work?
• In theory, employer and employee could collude to evade taxes
• In practice, such collusion is fragile in modern companies because
– Accounting and payroll records are widely used within the firm
– Whistleblowing: a single employee can denounce collusionbetween employer and employees.
• Kleven, Kreiner & Saez (2016): taxes can be enforced even withlow penalties and low audit rates
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2 The structure of taxation in developing countries
• Tax/GDP ratio has slightly increased in recent decades, consistentwith “optimistic view” of evolution of tax capacity
• Two important qualifiers:
– Substantial heterogeneity across countries
– Increase in tax/GDP ratios mostly driven by rise in consumptiontaxes, not (progressive) income taxation
→ does not seem to have substantially mitigated rise ofpre-tax-and-transfer inequality
19
010
2030
% o
f GD
P
HICs UMICs LMICs LICs19
95s20
00s20
05s20
10s
1995
s20
00s20
05s20
10s
1995
s20
00s20
05s20
10s
1995
s20
00s20
05s20
10s
Sample contains an avg 115 obs per year. It excludes countries with missing observations for a fullhalf decade in indirect and total tax revenue between 1995-2013; countries who are resource rich; andcountries who have low populations. Total tax rev includes social contributions, not resource rev.Observations are aweighted by population.Indirect: Sum of taxes on G&S, trade, and other taxes (without resource revenue).
ICTD Half Decade Weighted Central Sample from 1995-2013Trends in Weighted Indirect versus Total Tax Revenue
Total Tax Revenue Indirect Tax Revenue
20
0%
5%
10%
15%
20%
25%
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
Government tax revenue in China (% of national income)
Source: Piketty, Yang, Zucman (2017)
21
10%
15%
20%
25%
30%
35%
40%
45%
50%
1978 1982 1986 1990 1994 1998 2002 2006 2010 2014
Figure 10. Income inequality in China, 1978-2015: corrected estimates
Top 10%
Middle 40%
Bottom 50%
Distribution of pretax national income (before taxes and transfers, except pensions and unempl. insurance) among adults. Corrected estimates (combining survey, fiscal, wealth and national accounts data). Equal-split-adults series (income of married couples divided by two).
Source: Piketty, Yang, Zucman (2017)
22
2%3%4%5%6%7%8%9%
10%11%12%13%14%15%16%
1978 1982 1986 1990 1994 1998 2002 2006 2010 2014
Figure 12. Top 1% income share in China : corrected vs raw estimates
Top 1% (corrected)
Top 1% (raw)
Distribution of pretax national income (before taxes and transfers, except pensions and unempl. insurance) among adults. Corrected estimates combine survey, fiscal, wealth and national accounts data. Raw estimates rely only on self-reported survey data. Equal-split-adults series (income of married couples divided by two).
Source: Piketty, Yang, Zucman (2017)
23
25%
30%
35%
40%
45%
50%
1978 1982 1986 1990 1994 1998 2002 2006 2010 2014
Figure 21. Top 10% income share: China vs rich countries
China
USA
France
Distribution of pretax national income (before taxes and transfers, except pensions and unempl. insurance) among adults. Corrected estimates (combining survey, fiscal, wealth and national accounts data). Equal-split-adults series (income of married couples divided by two).
Source: Piketty, Yang, Zucman (2017)
24
Vanishing trade revenue: Cage and Gadenne (2016)
• Analyze 140 episodes of trade liberalization (during which tradetaxes fall by more than 3% GDP) since 1970s
• Leads to larger and longer-lived decreases in total tax revenuesthan in rich countries in the 19th and early 20th centuries.
• Half the developing countries experience a fall in total tax revenuesthat lasts more than ten years after an episode
→ fiscal cost of trade liberalization = decreases in trade tax revenuesnegatively affect governments’ capacity to provide public services
25
Figure 2: Definition of trade liberalization episodes and fiscal recovery: example ofGuatemala
05
10R
even
ues
as a
sha
re o
f GD
P (%
)
1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004Year
Smoothed trade tax revenues Smoothed tax revenuesTrade tax revenues Tax revenues
Notes: The figure illustrates our method for constructing episodes of trade liberalization and the fiscal recovery variable.The vertical red line shows the start of the episode, the blue line its end and the green line the year of recovery. See thetext for a description of the dataset used.
25
26
3 Tax base elasticities and investment in tax capacity
Why do developing countries rely so much on indirect taxes?
• Standard economic explanation: high elasticity of taxable incomedue to informality (Gordon and Li, 2009)
•Making the tax base less elastic requires investment in tax capacity(auditing, record-keeping, legal framework, etc.)
•Which begs the question: Why do some countries invest more orless in tax capacity?
27
Tax base elasticity in developing countries
• Developing countries often rely on sub-optimal forms of taxation(e.g., taxes on turnover instead of profits)
• Hard to understand with standard models
• But makes sense if large behavioral responses to standard taxes →growing literature documenting such responses
• E.g., Kleven and Waseem (QJE 2013), Best et al. (JPE 2016),Carillo et al. (AEJ 2017), Bachas and Soto (2016)
28
TAX REVENUES AND TAX STRUCTURESACROSS COUNTRIES (1996-2001)
Revenue�is lower
Share�of�income tax
Shares�of�corporate�income�tax,� Informal�economyis�lower income�tax�is�lower
consumption�taxes,�border�taxesand�seignorage are�higher
yis�larger
Source: Gordon and Li (2009)
29
The elasticity of corporate profits: Bachas & Soto (2016)
• Use notch in tax schedule to estimate elasticity of reported profitsin Costa Rica (see also Kleven and Waseem 2013)
• Very high elasticity (in between 3 and 5), an order of magnitudegreater than in OECD countries
• Elasticity entirely driven by evasion → Costa Rican firms evadetaxes on 70% of their profits when faced with a 30% rate
• Evasion in turn largely driven by cost-deductibility → providessupport for taxing turnover (see also Best et al. 2016 in Pakistan)
30
Source: Bachas and Soto (2016)
31
Investment in fiscal capacity
• Tax base elasticities are not exogenous
• Besley & Perrson (2011, 2013): model of inv. in tax capacity
• Investments in State capacity depend on structural factors, e.g.,:
– Rises with risk of external conflict (higher expected value ofpublic goods)
– Falls with degree of resource dependence
– Rises with degree of political stability32
References
Bachas, Pierre and Mauricio Soto, “Not(ch) Your Average Tax System: Corporate Taxation Under
Weak Enforcement”, 2016
Besley, Tim and Torsten Persson, “State capacity, conflict, and development”, Econometrica 2010
Besley, Timothy and Torsten Persson, “Taxation and Development,” in MartinFeldstein, Alan J. Auerbach, Raj Chetty and Emmanuel Saez, eds., Handbook ofpublic economics, vol. 5, 2013 (web)
Best Michael, Anne Brockmeyer, Henrik Jacobsen Kleven, Johannes Spinnewijn, and Mazhar
Waseem, “Production vs Revenue Efficiency With Limited Tax Capacity: Theory and Evidence From
Pakistan”, JPE 2016
Cage, Julia and Lucie Gadenne, “The fiscal cost of trade liberalization”, working paper 2016
Carillo, Paul, Dina Pomeranz, and Monica Singhal, “Doding the taxman”, American Economic
Journal, 2017
33
Gordon, Roger and Wei Li, “Tax structures in developing countries: Many puzzles and a possible
explanation”, Journal of Public Economics 2009
Kleven, Henrik and Mazhar Waseem, “Using Notches to Uncover Optimization Frictions and
Structural Elasticities: Theory and Evidence from Pakistan”, Quarterly Journal of Economics, 2013
(web)
Kleven, Henrik, Claus Kreiner, and Emmanuel Saez “Why Can Modern Governments Tax So Much?
An Agency Model of Firms as Fiscal Intermediaries”, Economica, 2016 (web)
Pomeranz, Dina “No Taxation without Information”, American Economic Review 2015
Piketty, Thomas, Li Yang and Gabriel Zucman, “Capital Accumulation, Private Property, and
Inequality in China 1978-2015”, NBER working paper 2017
Scheidel, Walter The Great Levelling, 2017
Scheve Kenneth & D. Stasavage, “Democracy, War, and Wealth: Lessons from Two Centuries of
Inheritance Taxation”, American Political Science Review, 2012 (web)
Scheve Kenneth, and David Stasavage, “Taxing the Rich : A History of Fiscal Fairness in the United
States and Europe”, Princeton University Press, 2016
34