Taxpayer Responses over the Cycle: Evidence from Irish Notches Enda - - PowerPoint PPT Presentation

Taxpayer Responses over the Cycle: Evidence from Irish Notches

Enda Patrick Hargaden

Department of Economics University of Michigan

IFS Labour Market Conference March 1, 2016

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Introduction and Motivation

Why would cyclical variation be interesting?

Standard theory shows that the behavioral response optimally determines:

1 Tax rates 2 Extent of redistribution 3 Enforcement levels

Should these vary over the cycle? Some have argued a Keynesian cyclicality story on the expenditure side.

Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 2 / 51

Introduction and Motivation

Why would cyclical variation be interesting?

Standard theory shows that the behavioral response optimally determines:

1 Tax rates 2 Extent of redistribution 3 Enforcement levels

Should these vary over the cycle? Some have argued a Keynesian cyclicality story on the expenditure side.

Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 2 / 51

Introduction and Motivation

Which way does cyclical variation swing?

Arguments for increase in responsiveness during a recession: If firms are struggling to survive, they may search harder for cost savings With income effects, employees may value a euro more during a recession Arguments for decrease: There may be fewer opportunities to hide income when GDP is smaller It is harder to adjust hours during a recession, by e.g. switching jobs Wage rigidity could be a factor in downturns

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Introduction and Motivation

Which way does cyclical variation swing?

Arguments for increase in responsiveness during a recession: If firms are struggling to survive, they may search harder for cost savings With income effects, employees may value a euro more during a recession Arguments for decrease: There may be fewer opportunities to hide income when GDP is smaller It is harder to adjust hours during a recession, by e.g. switching jobs Wage rigidity could be a factor in downturns

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Introduction and Motivation

What does this paper have?

Administrative employee tax return data, and a set of notches Unprecedentedly volatile developed economy Insight into “frictions”, i.e. the determinants of reporting tax disadvantaged incomes Focus on the inter-temporal component of taxpayer response A new method (bunching in differences) to investigate the responsiveness

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Introduction and Motivation

Preview of Results

The evidence of taxpayer response is much weaker during the recession. Pre-2008 ‘treatment effects’ are about three times as large as post-2008. Much of the difference reflects non-random attrition from labor force.

◮ Reduced employment in sectors (e.g. construction) that exhibit

above-average ability to report tax-advantaged incomes creates composition effect/composition bias.

However, it’s more than just a composition effect.

◮ Holding the labor force constant, people are less responsive to the

incentives.

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Introduction and Motivation

Overview of Talk

1 The theory of notches 2 Taxpayer responses and the elasticity of taxable income 3 Data description and introduction to methods 4 Empirical evidence of cyclical variation 5 Determinants of tax avoidance 6 Inverse probability weighting estimates⋆ Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 6 / 51

Theory of Notches

Question: What exactly are notches?

Pre-tax income Post-tax income Y1 Y2

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Theory of Notches

Question: What exactly are notches?

Pre-tax income Post-tax income Y1 Y2

Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 7 / 51

Theory of Notches

Question: What exactly are notches?

Pre-tax income Post-tax income Y1 Y2

Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 7 / 51

Theory of Notches

Question: What exactly are notches?

Pre-tax income Post-tax income Y1 Y2 Yl Yu

Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 7 / 51

Theory of Notches

Question: What exactly are notches?

Pre-tax income Post-tax income Y1 Y2 Yl Yu

Strictly dominated region

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Understanding Taxpayer Responses

Understanding Taxpayer Responses

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Understanding Taxpayer Responses

Taxpayer Response and Taxable Income

Debate over which margin of adjustment: hours, gross income, evasion/avoidance? Feldstein (1995) shifted the focus to taxable income (ETI). Many margins of adjustment, all captured by taxable income. Under certain circumstances, this measures the welfare costs of taxation. Readily available empirical source.

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Understanding Taxpayer Responses

Bunching at notches to identify taxpayer response

Notches provide very strong incentives, and clean tests of ability to avoid taxes. Extent of level-bunching can identify ETI (Saez, 2010). The larger the bunching, the larger the ETI. Chetty et al (2011) and Kleven & Waseem (2013) bunching in Denmark and Pakistan. Almunia & Lopez-Rodriguez (2014), Auten & Carroll (1999), Bastani & Selin (2014), Gruber & Saez (2002), Jenderny (2015), Kopczuk & Munroe (2015), Marx (2012), Onji (2009), Ramnath (2013), Sallee & Slemrod (2012), Slemrod et al (2015), Yelowitz (1995).

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Understanding Taxpayer Responses

Slemrod & Kopczuk: ETI as a policy choice

ETI is not an immutable parameter. For a cost, we can influence it. Dependence on tax system: compare Denmark and Greece. Increased enforcement will lower responsiveness — ETI can be lowered (at a cost). Subtle point: I find a very low responsiveness for Ireland.

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Understanding Taxpayer Responses

Policy and academic implications of the paper

Time-varying responsiveness affects:

1 Optimal enforcement varies with the phase of the cycle: fund HMRC

in good times.

2 Stimulus package identification bias.

Small aside: tax cuts likely less stimulating than hoped.

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Understanding Taxpayer Responses

Policy and academic implications of the paper

Time-varying responsiveness affects:

1 Optimal enforcement varies with the phase of the cycle: fund HMRC

in good times.

2 Stimulus package identification bias.

Small aside: tax cuts likely less stimulating than hoped.

Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 12 / 51

Data Description

Data and Empirics

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Data Description

Sample from Universe of Irish Tax Returns

I have access to an administrative panel of employee tax returns with demographics and details on their employer. Employers must file an income statement for each employee Dataset is a panel (2006–2013) of 10% of all employees, representative of full sample Demographic information on employee (age, sex, nationality) Some business information on employer (legal form, number of employees, detailed sector)

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Data Description Trends in the data

10,000 20,000 30,000 40,000 Frequency 20,000 40,000 60,000 80,000 100,000 Total Annual Pay (€)

Earnings distribution in Ireland, 2006-2013

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Data Description Trends in the data

100 105 110 115 120 Real Output (2005 Q1=100) 2006 2008 2010 2012 2014 Year Ireland USA

Sources: Central Statistics Office, FRED

Irish and US Business Cycles

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Data Description Trends in the data

2.5 5 7.5 10 12.5 15

Unemployment Rate (seasonally adjusted)

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Ireland USA

Sources: Central Statistics Office, BLS

Irish and US Unemployment Rates

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Data Description Trends in the data

40 60 80 100 120

Employment by Sector (2006 Q2 = 100)

2007 2008 2009 2010 2011 2012 2013 2014 Year Total Non-construction Construction

Source: Central Statistics Office/QNHS

Employment in Ireland

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Data Description Trends in the data

Limitation of the data

The notches are not applicable to people who are (i) married; (ii) jointly filing; and (iii) both spouses working. Will attenuate results. Likely becomes less of a problem over time.

Marriage rate Employment rate Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 19 / 51

Data Description Experimental Design

A Tale of Three Notches

Health Levy — earmarked for contribution to public health service, enacted in 1979 Income Levy — enacted by the Financial Emergency Measures in the Public Interest Act, 2009 Universal Social Charge (USC) — enacted in 2011 to replace both the Health and Income Levies.

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Data Description Experimental Design

A Tale of Three Notches

Health Levy — earmarked for contribution to public health service, enacted in 1979 Income Levy — enacted by the Financial Emergency Measures in the Public Interest Act, 2009 Universal Social Charge (USC) — enacted in 2011 to replace both the Health and Income Levies.

Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 20 / 51

Data Description Experimental Design

A Tale of Three Notches

Health Levy — earmarked for contribution to public health service, enacted in 1979 Income Levy — enacted by the Financial Emergency Measures in the Public Interest Act, 2009 Universal Social Charge (USC) — enacted in 2011 to replace both the Health and Income Levies.

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Data Description Experimental Design

A Tale of Three Notches

Health Levy — earmarked for contribution to public health service, enacted in 1979 Income Levy — enacted by the Financial Emergency Measures in the Public Interest Act, 2009 Universal Social Charge (USC) — enacted in 2011 to replace both the Health and Income Levies.

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Data Description Experimental Design

List of Quasi-Experimental Variation

Year Health Levy Income Levy USC Tax Penalty 2005 20,800 (416) 2006 22,880 (458) 2007 24,960 (499) 2008 26,000 (520) 2009 26,000 15,028 (867) (200) 2010 26,000 15,028 (1,040) (301) 2011 4,004 (80) 2012 10,036 (201) 2013 10,036 (201)

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Data Description Experimental Design

Order of the Game

1 December of Year T − 1: government announces annual budget. 2 January 1 of Year T: tax changes take effect. Wages are paid and

100% of taxes are deducted by employers at source.

3 Early in Year T + 1: employers send tax forms to Revenue detailing

total annual pay.

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Bunching Estimates Empirical Design

Estimation

The literature’s standard estimation technique measures excess mass (“bunching”) near the threshold.

1 Plot histogram of earnings near the threshold. 2 Fit high-order polynomial to these data. 3 Compare actual mass to the predicted mass.

Identification requires the level of the income distribution to be flat at the notch threshold.

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Bunching Estimates

An Illustrative Example

100 200 300 400

Frequency

25,490 25,690 25,890 26,090 26,290 26,490

Income

Extent of excess bunching b= 7.5 (0.6)

Bunching (Levels) in 2008

2005 2006 2007 2008 2009 2010 2009 IL 2010 IL 2012 2013 Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 24 / 51

Bunching Estimates

Round-number problem: spurious bunching

300 400 500 600 700 800

Frequency

20,000 21,000 22,000 23,000 24,000 25,000 26,000 27,000 28,000 29,000 30,000

Annual Income

Earnings Distribution, 2006-2007 Clear round-number bunching for multiples of e1,000.

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Bunching Estimates

Changes in bunching as an alternative strategy

Rather than look at the bunching in levels, we can look at the bunching in differences. Identification is valid if the change in the income distribution is flat at the notch threshold.

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Bunching Estimates Difference Bunching

Bunching Clear in Early Years: 2006

50 100 150 200

Frequency

22,370 22,570 22,770 22,970 23,170 23,370

Income

Extent of excess bunching b=72.3 (21.7)

Bunching (Differences) in 2006

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Bunching Estimates Difference Bunching

Bunching Clear in Early Years: 2007

50 100 150 200

Frequency

24,450 24,650 24,850 25,050 25,250 25,450

Income

Extent of excess bunching b=146.5 (24.4)

Bunching (Differences) in 2007

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Bunching Estimates Difference Bunching

Bunching Clear in Early Years: 2008

• 50

50 100 150

Frequency

25,490 25,690 25,890 26,090 26,290 26,490

Income

Extent of excess bunching b=153.6 (18.8)

Bunching (Differences) in 2008

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Bunching Estimates Difference Bunching

No Bunching: 2009

• 50

50 100 150

Frequency

14,520 14,720 14,920 15,120 15,320 15,520

Income

Extent of excess bunching b=15.6 (10.2)

Bunching (Differences) in 2009

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Bunching Estimates Difference Bunching

No Bunching: 2009

• 50

50 100 150

Frequency

25,490 25,690 25,890 26,090 26,290 26,490

Income

Extent of excess bunching b=-20.3 (10.0)

Bunching (Differences) in 2009

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Bunching Estimates Difference Bunching

No Bunching: 2010

• 50

50 100 150

Frequency

14,520 14,720 14,920 15,120 15,320 15,520

Income

Extent of excess bunching b=-2.0 (9.5)

Bunching (Differences) in 2010

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Bunching Estimates Difference Bunching

No Bunching: 2012

• 50

50 100 150

Frequency

9,530 9,730 9,930 10,130 10,330 10,530

Income

Extent of excess bunching b= 9.4 (8.3)

Bunching (Differences) in 2012

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Declining Responsiveness Salience?

Could this be a salience story?

One plausible explanation is that people knew about the tax in the initial years and, in the midst of a recession, lost sight of their personal finances. This seems quite unlikely.

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Declining Responsiveness Salience?

Could this be a salience story?

One plausible explanation is that people knew about the tax in the initial years and, in the midst of a recession, lost sight of their personal finances. This seems quite unlikely.

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Declining Responsiveness Salience?

Public attention of USC

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Declining Responsiveness Salience?

Public attention of USC

Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 35 / 51

Declining Responsiveness Salience?

Public attention of USC

Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 35 / 51

Declining Responsiveness Salience?

Public attention of USC

Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 35 / 51

Declining Responsiveness Salience?

Public attention of USC

Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 35 / 51

Declining Responsiveness Salience?

Public attention of USC

Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 35 / 51

Declining Responsiveness Salience?

Public attention of USC

Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 35 / 51

Declining Responsiveness Salience?

Public attention of USC

Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 35 / 51

Declining Responsiveness Salience?

Public attention of USC

Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 35 / 51

Declining Responsiveness Salience?

Public attention of USC

Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 35 / 51

Determinants of Bunching

Who bunches?

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Determinants of Bunching

Who bunches?

If it’s not a salience story, what sort of people place themselves in the tax-advantaged portion of the income distribution? To address this, consider a dummy variable: Dominated Region =

• 1

if income in dominated region if income ∈ (Threshold-e100, Threshold] This permits estimating probits on the determinants of tax-reporting behavior.

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Determinants of Bunching Regression Results

Self-employed construction workers avoid taxes

Table: Selected determinants of reporting tax-disadvantaged income

• Avg. Marginal Effects

Personal Characteristics Number of Employers 1.9⋆⋆⋆ EU 2004 2.0⋆⋆ Fifty-two weeks

• 3.7⋆⋆⋆

Self-employment

• 16.0⋆⋆⋆

Firm Characteristics Partnership 3.7⋆⋆ Private Limited 5.4⋆⋆⋆ Foreign Branch 10.0⋆⋆⋆ Public Limited 10.2⋆⋆⋆ Firm-size 0.02⋆⋆⋆ Industry Construction

• 3.0⋆⋆⋆

Retail

• 2.0⋆⋆

Hotel & restaurants

• 3.2⋆⋆

Public admin 3.2⋆⋆ Utilities 4.2

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Determinants of Bunching Regression Results

Discussion of regression results

Bunchers share traits. They are younger, are employed primarily in small enterprises, typically for 52 weeks of the year, in certain industries. Perhaps these covariates are changing over time, and this is affecting bunching. What happens when we reweight the pre- and post-recession samples to look like each other?

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Counterfactual Estimation

VAT Notch in Japan

Figure: Onji (JPubEc, 2009)

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Counterfactual Estimation

DiNardo, Fortin, Lemieux approach

.0004 .00045 .0005 .00055

Density

24,500 25,000 25,500

Annual Pay (€) Actual (pre) Actual (post) Counterfactual

Controls: male age irish emp_size legal_form sector fiftytwo

DFL Density Estimates 2006-2007

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Counterfactual Estimation

DiNardo, Fortin, Lemieux approach

.00042 .00044 .00046 .00048 .0005

Density

25,500 26,000 26,500

Annual Pay (€) Actual (pre) Actual (post) Counterfactual

Controls: male age irish emp_size legal_form sector fiftytwo

DFL Density Estimates 2007-2008

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Counterfactual Estimation

DiNardo, Fortin, Lemieux approach

.0004 .00045 .0005 .00055

Density

25,500 26,000 26,500

Annual Pay (€) Actual (pre) Actual (post) Counterfactual

Controls: male age irish emp_size legal_form sector fiftytwo

DFL Density Estimates 2008-2009

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Counterfactual Estimation

DiNardo, Fortin, Lemieux approach

.00038 .0004 .00042 .00044 .00046

Density

14,500 15,000 15,500

Annual Pay (€) Actual (pre) Actual (post) Counterfactual

Controls: male age irish emp_size legal_form sector fiftytwo

DFL Density Estimates 2009-2010

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Controlling for composition

It’s not just composition bias

Table: Changes in wage dynamics for job-stayers

Year Proportion Freezes Proportion Cuts Proportion Increases 2005-06 2.5% 17.2% 80.4% 2006-07 2.5% 17.6% 79.9% 2007-08 2.8% 22.9% 74.2% 2008-09 3.3% 52.7% 44.0% 2009-10 4.4% 55.2% 40.3% 2010-11 6.8% 39.3% 53.9% 2011-12 10.3% 34.2% 55.5% 2012-13 10.0% 34.3% 55.7%

Job-stayers are defined as employees who remain with the same employer over multiple years. Table shows the proportion of job-stayers whose pay was frozen within ±0.1% of previous year’s pay, cut, or increased. Source: Doris et al. (2013)

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Controlling for composition Inverse Probability Weighting

I use weights to match the pre- and post-recession samples

One way to disentangle composition bias from additional constraints on behavior is to use inverse probability weighting (IPW). This calculates the determinants of bunching “as if” the composition of the labor force were unchanged from previous years.

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Controlling for composition Inverse Probability Weighting

Post-matching magnitudes vary

Table: Matched sample determinants

2006 2010 (match) Fifty-two weeks

• 3.18⋆
• 7.58⋆⋆⋆

Firm Size (’000s)

• 0.01

0.05⋆⋆ Self-employment

• 12.66⋆⋆⋆
• 21.33⋆⋆⋆

Number of employers 1.03 2.14 Irish 1.72 0.50 Male

• 0.27

2.58⋆ Table shows selected mean marginal effects from probit regression on the de- terminants of bunching. The first column shows the results for the notch at e22,880 in 2006. The second column shows the results for the 2010 notch, but with the results weighted so the covariates match those of the 2006 sample.

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Controlling for composition Inverse Probability Weighting

Interpretation of recession in potential outcome framework

One interpretation of the results is to consider the recession as a treatment with non-random assignment (e.g. construction). If a recession imposes no additional constraints on behavior, then selection into the treatment should explain the change in outcomes. This is rejected by the data. Regardless of the specification, the change in tax-reporting behavior is not explained by the covariates. People are 4–5pp less likely to respond to these tax incentives post-2008.

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Conclusion

Conclusions and contributions

This paper has three things really going for it:

1 Great variation: several changes in location and severity of notch ◮ Motivation for the difference bunching strategy 2 Great data: third party-reported, administrative panel 3 Huge business cycle volatility Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 49 / 51

Conclusion

Conclusions and contributions

Developed a new bunching strategy with more compelling identification than existing approaches. Tested the response to the ‘treatment’ of notch introduction. Contributed to the literature on what covariates are consistent with avoiding taxes. Decomposed the total response into a labor composition effect, and a change in behavior effect.

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Conclusion

Conclusions and contributions

Clear, unambiguous results in the initial period: people avoid taxes. That evidence disappears. The employer and employee characteristics are determinants of reporting behavior. Changes in the composition of the labor force can explain much of the changes in reporting. . . . . . but composition alone cannot explain the findings. In a model of cyclical responsiveness, optimal tax rate and enforcement vary over the cycle. People are less able to avoid taxes during recessions: fund the tax authorities in good times.

Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 51 / 51

Conclusion

Conclusions and contributions

Clear, unambiguous results in the initial period: people avoid taxes. That evidence disappears. The employer and employee characteristics are determinants of reporting behavior. Changes in the composition of the labor force can explain much of the changes in reporting. . . . . . but composition alone cannot explain the findings. In a model of cyclical responsiveness, optimal tax rate and enforcement vary over the cycle. People are less able to avoid taxes during recessions: fund the tax authorities in good times.

Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 51 / 51

Conclusion

Conclusions and contributions

Clear, unambiguous results in the initial period: people avoid taxes. That evidence disappears. The employer and employee characteristics are determinants of reporting behavior. Changes in the composition of the labor force can explain much of the changes in reporting. . . . . . but composition alone cannot explain the findings. In a model of cyclical responsiveness, optimal tax rate and enforcement vary over the cycle. People are less able to avoid taxes during recessions: fund the tax authorities in good times.

Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 51 / 51

Conclusion

Conclusions and contributions

Clear, unambiguous results in the initial period: people avoid taxes. That evidence disappears. The employer and employee characteristics are determinants of reporting behavior. Changes in the composition of the labor force can explain much of the changes in reporting. . . . . . but composition alone cannot explain the findings. In a model of cyclical responsiveness, optimal tax rate and enforcement vary over the cycle. People are less able to avoid taxes during recessions: fund the tax authorities in good times.

Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 51 / 51

Conclusion

Conclusions and contributions

Clear, unambiguous results in the initial period: people avoid taxes. That evidence disappears. The employer and employee characteristics are determinants of reporting behavior. Changes in the composition of the labor force can explain much of the changes in reporting. . . . . . but composition alone cannot explain the findings. In a model of cyclical responsiveness, optimal tax rate and enforcement vary over the cycle. People are less able to avoid taxes during recessions: fund the tax authorities in good times.

Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 51 / 51

Conclusion

Conclusions and contributions

Clear, unambiguous results in the initial period: people avoid taxes. That evidence disappears. The employer and employee characteristics are determinants of reporting behavior. Changes in the composition of the labor force can explain much of the changes in reporting. . . . . . but composition alone cannot explain the findings. In a model of cyclical responsiveness, optimal tax rate and enforcement vary over the cycle. People are less able to avoid taxes during recessions: fund the tax authorities in good times.

Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 51 / 51

95 100 105 110 115 Employment (2005 Q1=100) 2006 2008 2010 2012 2014 Year Ireland USA

Sources: Central Statistics Office, BLS

Irish and US Employment Levels

Back Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 1 / 12

20 40 60 80 100 120 Weddings (2005=100) 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Year

Source: Central Statistics Office

Weddings Registered in Ireland

Back Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 2 / 12

50 100 150 200 250

Frequency

20,290 20,490 20,690 20,890 21,090 21,290

Income

Extent of excess bunching b= 3.8 (1.2)

Bunching (Levels) in 2005

Back Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 3 / 12

50 100 150 200 250

Frequency

22,370 22,570 22,770 22,970 23,170 23,370

Income

Extent of excess bunching b= 1.9 (0.8)

Bunching (Levels) in 2006

Back Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 4 / 12

100 200 300

Frequency

24,450 24,650 24,850 25,050 25,250 25,450

Income

Extent of excess bunching b= 3.5 (1.0)

Bunching (Levels) in 2007

Back Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 5 / 12

100 200 300 400

Frequency

25,490 25,690 25,890 26,090 26,290 26,490

Income

Extent of excess bunching b= 7.5 (0.6)

Bunching (Levels) in 2008

Back Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 6 / 12

50 100 150

Frequency

14,520 14,720 14,920 15,120 15,320 15,520

Income

Extent of excess bunching b= 4.8 (0.9)

Bunching (Levels) in 2009

Back Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 7 / 12

100 200 300

Frequency

25,490 25,690 25,890 26,090 26,290 26,490

Income

Extent of excess bunching b= 8.2 (1.0)

Bunching (Levels) in 2009

Back Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 8 / 12

50 100 150 200

Frequency

14,520 14,720 14,920 15,120 15,320 15,520

Income

Extent of excess bunching b= 4.4 (0.9)

Bunching (Levels) in 2010

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100 200 300 400

Frequency

25,490 25,690 25,890 26,090 26,290 26,490

Income

Extent of excess bunching b=10.0 (0.9)

Bunching (Levels) in 2010

Back Hargaden (University of Michigan) Irish Tax Notches March 1, 2016 10 / 12

50 100 150 200

Frequency

9,530 9,730 9,930 10,130 10,330 10,530

Income

Extent of excess bunching b= 3.3 (3.7)

Bunching (Levels) in 2012

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50 100 150 200

Frequency

9,530 9,730 9,930 10,130 10,330 10,530

Income

Extent of excess bunching b= 3.2 (5.4)

Bunching (Levels) in 2013

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