Earnings responses to payroll and income taxes Exploiting variation - - PowerPoint PPT Presentation

Introduction Pension Incidence Empirical model Data Results Conclusions

Earnings responses to payroll and income taxes Exploiting variation in Dutch pension rates Nicole Bosch (CPB Netherlands Bureau for Economic Policy Analysis) Casper van Ewijk (University of Amsterdam, CPB, Netspar) Maja Micevska Scharf (University of Amsterdam)

February 2016

Individual earnings responses to taxes Nicole Bosch

Introduction Pension Incidence Empirical model Data Results Conclusions

INTRODUCTION

◮ Payroll taxes amount to 23% and income taxes to 14% of labour costs in the

OECD and the Netherlands in 2014 (OECD, 2014). On top of this, the Dutch pension contributions are among the highest worldwide.

◮ Welfare effects of taxation are driven by both behavioural effects as well as wage

rate effects (incidence). Empirical literature on payroll taxes is scarce (Saez et al., 2012).

◮ Current paper uses panel approach exploiting exogenous tax variation over time

largely resulting from pension contributions.

◮ Goals ◮ Separately estimate responses to payroll taxes and to income taxes ◮ Shed additional light on the issue of incidence of payroll taxes ◮ Empirical analysis closely related to Lehmann, Marical & Rioux (JpuB, 2013). Individual earnings responses to taxes Nicole Bosch

Introduction Pension Incidence Empirical model Data Results Conclusions

Dutch pension system

◮ The Dutch pension system consists of three pillars. Old age pensions,

• ccupational pensions and individual pension savings.

◮ Even without statutory obligation, employers voluntarily offer occupational

• pensions. Once such an agreement exists at an industry level, it is compulsory.

◮ Pension funds are supervised by the Netherlands Bank and are restricted to

regulation (funding ratio, interest rate) but have large discretionary power. Funds invest abroad (not own sector).

◮ There is a clear contribution-benefit linkage, but because of the collective nature,

the system is not actuarially fair. Most are defined benefit schemes, some are defined contribution.

◮ Contributions apply to earnings between a lower limit and - often- an upper limit. ◮ Large up-and-down movements in average and marginal rates (see next Figures). Individual earnings responses to taxes Nicole Bosch

Introduction Pension Incidence Empirical model Data Results Conclusions

Marginal pension rates in 2012

• Individual earnings responses to taxes

Nicole Bosch

Introduction Pension Incidence Empirical model Data Results Conclusions

Variation in marginal pension rates over time

• Individual earnings responses to taxes

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Introduction Pension Incidence Empirical model Data Results Conclusions

Variation in lower limits over time

• Individual earnings responses to taxes

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Introduction Pension Incidence Empirical model Data Results Conclusions

Variation in lower limits over time, including extreme cases

• Individual earnings responses to taxes

Nicole Bosch

Introduction Pension Incidence Empirical model Data Results Conclusions

Are changes in pension rates exogenous? ∆ log wi,t = α + βP ∆ log τ P

i,t + γXi,t−1 + ui,t

(1) where wi,t indicates labour costs for person i in year t and τ P is the net-of-payroll tax rate.

◮ Reversed causality: change in wi,t affects change in τ due to nonlinear tax ◮ Omitted vars: unobs. (pension fund) chars may impact both changes in τ and w

Solutions

◮ Instrument tax rates (Gruber and Saez, 2002; Weber, 2014) ◮ Include pensionfund dummies (e.g. demographics), yeardummies (financial crisis) Individual earnings responses to taxes Nicole Bosch

Introduction Pension Incidence Empirical model Data Results Conclusions

Are changes in pension rates exogenous after including pensionfund and timedummies?

◮ Source of variation in rates due to legal rules (funding ratios, life expectancy)

that do not affect wages directly

◮ Variation in international interest rate impact asset portfolio and may lead to

different rates, but do not have a direct impact on wages.

◮ Pensionfunds have large discretionary power in setting pension rates (lower limit,

division between employer and employee, indexation retirees). Sectoral downturns (construction sector)? Lower wages and higher rates go together? Impact on rates depends foremost on financial position fund. Funds have large discretionary power, and can set different rates even in same financial position.

Individual earnings responses to taxes Nicole Bosch

Introduction Pension Incidence Empirical model Data Results Conclusions

What is incidence?

◮ Statutory incidence: who pays the tax ◮ Economic incidence: who bears the burden (employment and wages) ◮ Invariance of Incidence Proposition: statutory incidence irrelevant ◮ Labour demand and labour supply elasticities determine incidence

In equilibrium, incidence on employee/ full shifting to employee (Gruber, 1997) if:

◮ Elastic demand; ◮ Inelastic supply or ◮ Full tax-benefit linkage Individual earnings responses to taxes Nicole Bosch

Introduction Pension Incidence Empirical model Data Results Conclusions

Complications/ disequilibrium

◮ Institutions (minimum wage, sticky wages, labour unions) ◮ Competitiveness market (small open economy, monopoly, prices)

In the end, it is an empirical question whether costs are shifted to employees. Earlier micro-econometric studies find varying effects:

◮ No shifting to employee because of sticky wages and significant labour supply

effects (Lehmann et al., 2013)

◮ Incidence of higher employee (employer) contributions paid by employee

(employer). Different costs and net wages for new employees (Saez et al. 2012)

◮ Economic incidence equals statutory incidence (Neumann and Mueller, 2014) Individual earnings responses to taxes Nicole Bosch

Introduction Pension Incidence Empirical model Data Results Conclusions

Infer incidence from panel estimates Let’s start from changes in labour costs w = h ∗ W (Lehmann et al., 2013). ∆ log wi,t = α+βP

τ ∆ log τ P i,t+βI τ∆ log τ I i,t+βP ρ ∆ log ¯

ρP

i,t+βI ρ∆ log ¯

ρI

i,t+γXi,t−1+ui,t

(2) marginal net-of-payroll tax τ P and net-of-income tax τ I (substitution effects) average net-of-payroll tax ρP and net-of-income tax ρI (income effects/incidence) (assuming small income effects) Full incidence EE ER on ER EE on EE Full incidence ER Benchmark (el.LD) e.g. Sticky wages Labour cost βP

ρ = βI ρ = 0

βP

ρr = −1; βP ρe = βI ρ = 0

βP

ρr = βP ρe = βI ρ = −1

βI

τ > βP τ ; βI τ > 0

βI

τ > βP τe; βI τ > 0

βI

τ = βP τ = 0

Individual earnings responses to taxes Nicole Bosch

1-atr

Introduction Pension Incidence Empirical model Data Results Conclusions

Hourly wage costs ∆ log( wi,t hi,t ) = α+βP

τ ∆ log τ P i,t+βI τ∆ log τ I i,t+βP ρ ∆ log ¯

ρP

i,t+βI ρ∆ log ¯

ρI

i,t+γXi,t−1+ui,t

(3) marginal net-of-payroll tax τ P and net-of-income tax τ I (marginal incidence) average net-of-payroll tax ρP and net-of-income tax ρI (incidence) (assuming hours is only behavioural effect) Full incidence EE ER on ER,EE on EE Full incidence ER Benchmark (el.LD) e.g. Sticky wages Labour cost/h βP

ρ = βI ρ = 0

βP

ρr = −1; βP ρe = βI ρ = 0

βP

ρr = βP ρe = βI ρ = −1

βI

τ = βP τ = 0

βI

τ = βP τ = 0

βI

τ = βP τ = 0

Individual earnings responses to taxes Nicole Bosch

Introduction Pension Incidence Empirical model Data Results Conclusions

Empirical model First, we estimate changes in labour costs w = h ∗ W (Lehmann et al., 2013). ∆ log wi,t = α+βP

τ ∆ log τ P i,t+βI τ∆ log τ I i,t+βP ρ ∆ log ¯

ρP

i,t+βI ρ∆ log ¯

ρI

i,t+γXi,t−1+ui,t

(4) The vector Xi,t−1 includes demographics, pensionfund dummies, yeardummies and a function of base-year income. We assume ∆ log SSCs = 0. The error term ui,t captures time-varying and unobserved heterogeneity.

◮ βP

ρ = 0 and βP τ > 0 (incidence on EE, lower posted wages and/or lower hours)

◮ βP

ρ = −1 and βP τ = 0 (incidence on ER)

Income versus payroll taxes:

◮ |βP

ρ | > |βI ρ| and βP τ > βI τ > 0 (more salient payroll tax)

◮ |βI

ρ| > |βP ρ | and βI τ > βP τ > 0 (tax-benefit linkage)

Individual earnings responses to taxes Nicole Bosch

Introduction Pension Incidence Empirical model Data Results Conclusions

Hourly labour cost Second, we estimate the following equation where we control for hours: ∆ log( wi,t hi,t ) = α+βP

τ ∆ log τ P i,t+βI τ∆ log τ I i,t+βP ρ ∆ log ¯

ρP

i,t+βI ρ∆ log ¯

ρI

i,t+γXi,t−1+ui,t

(5) Assuming hours is only behavioural response (neglect effort, avoidance), we can interpret coefficient as incidence.

◮ βP

ρ = 0, βI ρ = 0 (full incidence on EE)

◮ βP

ρ = −1 (full incidence on ER)

Individual earnings responses to taxes Nicole Bosch

Introduction Pension Incidence Empirical model Data Results Conclusions

Separating employee and employer taxes Our third estimation separates employer rate ( ¯ ρrP ) from employee pension rate ( ¯ ρeP ). ∆ log wi,t = α+βP

τ ∆ log τ P i,t+βI τ∆ log τ I i,t+βP ρe∆ log ¯

ρeP

i,t+βP ρr∆ log ¯

ρrP

i,t+βI ρ∆ log ¯

ρI

i,t+γXi,t

(6) (assuming small income effects)

◮ βP

ρr = 0 (incidence of ER on EE, full shifting)

◮ βP

ρr = −1 (incidence of ER on ER, e.g. posted wage stickiness)

◮ βP

ρe = 0, βI ρ = 0 (incidence of EE on EE)

◮ βP

ρe = −1, βI ρ = −1 (incidence of EE on ER)

◮ |βP

ρr| > |βP ρe| (less salient employer payroll tax, Iturbe-Ormaetxe, 2015)

Individual earnings responses to taxes Nicole Bosch

Introduction Pension Incidence Empirical model Data Results Conclusions

Analogue to ETI literature, estimating previous equations leads to two problems:

◮ Endogenous (marginal) tax rate –> instrument with synthetic tax rate based on

(lags of) base-year income (Gruber and Saez, 2002; Weber, 2014)

◮ Mean reversion and diverging income trends –> add functions of base-year income ◮ Include income controls can mob up changes in tax rates. Especially if income

controls are close to large changes in tax rates (thresholds).

◮ We include synthetic changes in average tax rate and not actual change in

average tax rates, because they do not depend on labour cost and pension system is not proportional.

Individual earnings responses to taxes Nicole Bosch

Introduction Pension Incidence Empirical model Data Results Conclusions

Data

◮ Dutch Social Statistical Database on Jobs 2006-2012 is a longitudinal dataset for

entire working population.

◮ Containing (uncapped) monthly wage earnings, hours, CLA code, firm code, and

employer and employee SSCs.

◮ Earnings and SSCs are reported by employers to tax administration and are reliable. ◮ Combined with municipality data and a self-constructed database with pension

rates for each collective labour agreement (CLA)

◮ Income rates are simulated by using CPB’s detailed gross-net calculator ◮ Sample selection: age 20-55, balanced panel, same household type, same CLA ◮ This leaves us with 3 mln person-year observations (approx. 700K each year). Individual earnings responses to taxes Nicole Bosch

Introduction Pension Incidence Empirical model Data Results Conclusions

Estimation results: Labour cost ∆ log wi,t = α+βP

τ ∆ log τ P i,t+βI τ∆ log τ I i,t+βP ρ ∆ log ¯

ρP

i,t+βI ρ∆ log ¯

ρI

i,t+γXi,t−1+ui,t

(1) (2) (3) (EE) (ER) βP

τ

0.0281 0.0227 0.0193 >=0 (0.0002) (0.0018) (0.0018) βI

τ

0.0035

• 0.0019
• 0.0021

>=0 (0.0007) (0.0007) (0.0007) βP

ρ

• 0.1770
• 0.1130
• 0.0900
• 1

(0.0023) (0.0023) (0.0023) βI

ρ

• 0.0299
• 0.0230
• 0.0149
• 1

(0.0057) (0.0056) (0.0056) Income control none 10-piece log income

Notes: controls for gender, age and marital status, year and pensionfund dummies, labour costs > 10K. Two-year changes. N=2.93 mln First-stage regressions: strong instruments Individual earnings responses to taxes Nicole Bosch

Introduction Pension Incidence Empirical model Data Results Conclusions

Estimation results: hourly labour costs ∆ log( wi,t hi,t ) = α+βP

τ ∆ log τ P i,t+βI τ∆ log τ I i,t+βP ρ ∆ log ¯

ρP

i,t+βI ρ∆ log ¯

ρI

i,t+γXi,t−1+ui,t

(1) (2) (3) (EE) (ER) βP

τ

0.1410 0.1280 0.1250 >=0 (0.0020) (0.0016) (0.0016) βI

τ

0.0017

• 0.0033
• 0.0038

>=0 (0.0008) (0.0006) (0.0006) βP

ρ

• 0.2400
• 0.1780
• 0.1680
• 1

(0.0025) (0.0020) (0.0020) βI

ρ

0.0414 0.0488 0.0632

• 1

(0.0114) (0.0048) (0.0049) Income control none 10-piece log income

Notes: controls for gender, age and marital status, year and pensionfund dummies, labour costs > 10K. Two-year changes. N=2.93 mln First-stage regressions: strong instruments Individual earnings responses to taxes Nicole Bosch

Introduction Pension Incidence Empirical model Data Results Conclusions

Estimation results Labour costs: separating employer and employee LC Penmr Penpmr Taxmr Taxpmr PenEpar PenRpar Taxp LC 1 Penmr 0.055 1 Penpmr 0.026 0.788 1 Taxmr

• 0.145
• 0.009
• 0.004

1 Taxpmr 0.012 0.014 0.015 0.437 1 PenEpar

• 0.200

0.029 0.043 0.005 0.001 1 PenRpar

• 0.052

0.137 0.166 0.01

• 0.003

0.758 1 Taxpar

• 0.033
• 0.061
• 0.064
• 0.052
• 0.043

0.022 0.048 1

Individual earnings responses to taxes Nicole Bosch

Introduction Pension Incidence Empirical model Data Results Conclusions

Estimation results Labour costs: separating employer and employee ∆ log wi,t = α+βP

τ ∆ log τ P i,t+βI τ∆ log τ I i,t+βP ρe∆ log ¯

ρeP

i,t+βP ρr∆ log ¯

ρrP

i,t+βI ρ∆ log ¯

ρI

i,t+..+u

(1) (2) (3) (EE) (ER) (EE,ER) βP

τ

0.0226 0.0177 0.0137 >=0 >=0 (0.0018) (0.0018) (0.0018) βI

τ

0.0034

• 0.0020
• 0.0022

>=0 >=0 (0.0007) (0.0007) (0.0007) βP

ρe

0.1760 0.1010 0.0622

• 1

(0.0046) (0.0046) (0.0046) βP

ρr

• 0.3730
• 0.2130
• 0.1390
• 1
• 1

(0.0063) (0.0063) (0.0063) βI

ρ

• 0.0328
• 0.0246
• 0.0165
• 1

(0.0057) (0.0056) (0.0056) Income control none 10-piece log income

Notes: controls for gender, age and marital status, year and pensionfund dummies, labour costs > 10K. Two-year

• changes. N=2.93 mln

First-stage regressions: strong instruments Correlation ¯ ρeP i,t, ¯ ρrP i,t = 0.75 Individual earnings responses to taxes Nicole Bosch

Introduction Pension Incidence Empirical model Data Results Conclusions

Sensitivity: labour costs (1) (2) (3) (4) βP

τ

• 0.0590

0.0144 0.2160 0.159 (0.0014) (0.0018) (0.0027) βI

τ

• 0.0002
• 0.0021
• 0.0018
• 0.0020

(0.0058) (0.0009) (0.0037) βP

ρ

• 0.0420
• 0.1190

0.0399

• 0.527

(0.0018) (0.0023) (0.0026) βI

ρ

0.0253

• 0.1040
• 0.0446
• 0.0148

(0.0043) (0.0070) (0.0056)

Notes: (1) splines and difference log(wi,t−1) − log(wi,t−2) , (2) excluding public sector, (3) fully interacted pensionfund and timedum- mies, (4) actual changes in tax rates (instrumented) Individual earnings responses to taxes Nicole Bosch

Introduction Pension Incidence Empirical model Data Results Conclusions

Findings

◮ Small and significant coefficients for marginal tax rates. Zero effect income tax. ◮ Small and negative coefficients for (net-of) average income tax. ◮ Small but sizeable negative coefficients for (net-of) average payroll tax (range of

• 0.1 to -0.2).

◮ Somewhat sensitive to inclusion of income controls. ◮ Employer pension contributions raise labour costs (10% increase leads to 2%

higher costs)

◮ Employee contributions lower labour cost. Contradicting result, implying negative

income effects or more than offsetting incidence.

Individual earnings responses to taxes Nicole Bosch

Introduction Pension Incidence Empirical model Data Results Conclusions

Preliminary conclusions

◮ Pension schedule provides ample opportunity to analyse incidence. ◮ Small variation in income tax rates limits comparison income and payroll tax. ◮ Rich and reliable administrative data. Quality hours needs further exploration. ◮ We find less negative effects of payroll taxes than earlier studies. ◮ This suggests that Dutch wages are flexible or that employees fully value benefits. ◮ We conclude that incidence is on the employee, although not fully. ◮ Tentative results show that employers are less able to shift their contributions to

employees which could be explained by the fact that these are less salient. Overall, more to be done.

Individual earnings responses to taxes Nicole Bosch

Introduction Pension Incidence Empirical model Data Results Conclusions

Future plans

◮ Estimate hours equation and explore reliability hours ◮ Technical issues like rescaling and multiplicative structure ◮ Focus on separate pensionfunds ◮ Alternative instruments: grouping variable (pensionfund*year) ◮ Sample selection (more heterogeneous sample) ◮ Focus on subgroup with income tax reform Individual earnings responses to taxes Nicole Bosch