1. Govt Abstract
1.1 Background to Scottish Earnings Tax
Earnings Tax has been partially devolved to the Scottish Parliament since tax yr 2016 to 2017
From tax yr 2017 to 2018 it has had the facility to set the charges and thresholds for the non-savings and non-dividends (NSND) Earnings Tax paid by Scottish taxpayers (usually often called earned revenue)
For the tax yr 2018 to 2019, the Scottish Authorities launched two new Earnings Tax bands and charges, in addition to growing the charges for 2 of the prevailing bands
This switched Scotland from a three-band system to a five-band system – the tables beneath set out the charges and thresholds for Scottish Earnings Tax and for Earnings Tax in the remainder of the UK (rUK)
Desk 1: Scottish Earnings Tax NSND coverage for the tax yr 2018 to 2019.
Desk 2: rUK NSND Earnings Tax coverage for the tax yr 2018 to 2019.
1.2 Intention of the research and the strategy taken
The modifications to Scottish Earnings Tax offered a singular alternative to raised perceive Scottish taxpayer behaviour in response to Earnings Tax modifications
Whereas we can’t immediately observe behaviour change in relation to the coverage, we now have utilized analytical methods to attempt to estimate it
We had been ready to make use of HMRC’s Self-Evaluation and Actual Time Data (RTI) knowledge to check Scottish taxpayers to a gaggle of comparable taxpayers from rUK – since Earnings Tax charges remained the identical in rUK, any variations in revenue declared are assumed to be because of the introduction of the coverage
Taxpayers had been grouped into ten revenue bands for our evaluation – they align with the five-band system, while additionally accounting for the Taper price (the place a person incomes greater than £100,000 is topic to the next marginal tax price because of the elimination of their Private Allowance)
We additionally break up our Extra and Prime price taxpayers into three revenue bands in keeping with the Scottish Fiscal Fee’s behavioural framework
For every revenue band we estimated the proportion change in taxable revenue declared in Scotland in response to a 1% change within the share of revenue retained after tax (also referred to as the marginal price of retention or MRR) – this share change is named a taxable revenue elasticity or TIE
We excluded people migrating between Scotland and rUK from our research – the estimated TIEs replicate behaviour regarding the quantity of revenue declared relatively than different behaviours resembling migration from Scotland
1.3 What we discovered
General, the outcomes are broadly per the educational literature, offering restricted proof of Scottish taxpayers decreasing their declared revenue in response to growing tax charges (and therefore lowering MRR)
As anticipated, the dimensions of the behavioural response typically elevated with revenue
These findings remained pretty secure when making an attempt completely different methodological approaches
Prime price and Extra price taxpayers
For taxpayers incomes greater than £150,000, we estimate {that a} 1% discount in MRR results in a discount in revenue declared of between 0.52% to 0.77% – that is akin to HMRC’s earlier 2012 estimates of 0.48% and 0.71%, relying on the methodology used, and was additionally in keeping with later estimates from research on UK tax coverage
The estimated share change in revenue for taxpayers within the three separate revenue bands over £150,000 had been rather less secure when making an attempt completely different analytical approaches
Greater price taxpayers
For Scottish taxpayers incomes greater than the Scottish Greater price threshold of £43,431 in 2018 to 2019, we discovered that behaviour was smaller than that of people within the Prime price and usually elevated with revenue
Behaviour for these people was considerably greater than anticipated from the educational literature, starting from a 0.12% to a 0.46% discount in revenue declared in response to a 1% discount within the MRR, in comparison with the 0.11% to 0.27% reductions present in different research
Starter, Fundamental and Intermediate price taxpayers
Initially outcomes for some Scottish taxpayers with taxable revenue beneath £43,431, confirmed a rise of their taxable revenue relative to comparable taxpayers in rUK
Nevertheless, this gave the impression to be largely pushed by greater progress in public sector pay in Scotland relative to the UK as an entire
After we excluded the general public sector from our evaluation, we discovered little to no proof of a behavioural impact at this revenue stage, which is in keeping with expectations from the literature
2. Summary
Our paper estimates the response of Scottish taxpayers to the introduction of 5 marginal Earnings Tax charges in Scotland for the tax yr 2018 to 2019. We apply a propensity rating matching difference-in-differences approach to HMRC’s RTI and Self-Evaluation knowledge utilizing rUK as a management group to estimate TIEs for ten revenue bands. Our outcomes present that there’s little to no behavioural response to the brand new Starter price band of 19% or the Intermediate price band of 21% when accounting for greater public sector pay progress in Scotland. We discover some proof of behaviour throughout the Greater price band of 41% with TIEs of 0.12 to 0.46. We discover even stronger behaviour on the Prime price band of 46% with TIEs of as much as 5.45 for the very best earners and an general TIE of 0.52 to 0.77 for all Prime price taxpayers. Nevertheless, this group was discovered to be notably delicate to our selection of matching methods.
3. Acknowledgements and Disclaimer
The evaluation introduced on this report wouldn’t have been attainable with out the enter of colleagues each inside and out of doors of HMRC. We’re notably grateful for the constructive feedback offered by teachers from each the Fraser of Allander Institute and the College of Westminster. We additionally thank officers from the Scottish Authorities, the Scottish Fiscal Fee, the Welsh Authorities, the Workplace for Finances Accountability and HM Treasury, who’ve offered feedback and constructive problem at numerous levels of the challenge. The views expressed on this report are these of the authors and don’t essentially signify these of HMRC. Any remaining errors are the authors’ personal duty.
Authors: R. Waite; C. White; J. Carr; N. Duncan; and G. McGregor.
4. Introduction
The Scottish Authorities used the powers devolved to them by the Scotland Act 2016 to introduce a brand new five-band construction for Earnings Tax in Scotland for the 2018 to 2019 tax yr. This included a brand new Starter price band of 19%, a Fundamental price band of 20%, an Intermediate price band of 21%, a Greater price band of 41% and a Prime price band of 46%. All taxpayers who’re resident in Scotland for almost all of the tax yr are topic to this technique. In rUK the prevailing three-band system of 20% Fundamental Price, 40% Greater Price and 45% Extra Price was retained.
This produced a singular alternative to review the responsiveness of Scottish taxpayers based mostly on a pure experiment the place one nation throughout the UK modified their Earnings Tax charges in comparison with rUK, and the primary time this has occurred within the UK’s fashionable historical past. Our paper due to this fact seeks to contribute to the literature by being the primary of its sort to review this influence on Scottish taxpayer behaviour in 2018 to 2019 from the five-band coverage. We do that by constructing a brand new multi-year dataset utilizing HMRC’s wealthy knowledge sources and supply precious insights into the rising analysis space of devolved fiscal coverage.
Particularly, our paper seeks to estimate how Scottish taxpayers modified their stage of revenue topic to Earnings Tax, often called their taxable revenue, in response to the change within the tax price utilized to every extra pound of their revenue, often called their marginal tax price. Their taxable revenue consists of earnings from employment, self employment, property revenue and pension revenue.
From this we produce TIEs which present the proportion change in taxable revenue declared in response to a 1% change within the share of revenue retained after tax. The TIEs are estimated for ten revenue bands to permit us to estimate the completely different behaviour of taxpayers at completely different ranges of revenue, which is known as heterogeneous behaviour. These revenue bands are assigned on the pre-policy tax yr of 2017 to 2018 and replicate quite a lot of various factors. They align with the five-band system, while additionally accounting for the Taper price (the place a person incomes greater than £100,000 is topic to the next marginal tax price because of the gradual elimination of their Private Allowance). We additionally break up our Extra and Prime price taxpayers into three revenue bands in keeping with the Scottish Fiscal Fee’s behavioural framework.
The dataset we use to analyse the Scottish and rUK taxpayers in our paper attracts on HMRC’s RTI knowledge submitted by employers at any time when they make a fee to their workers, in addition to theSelf-Evaluation Outturn knowledge used within the manufacturing of the Scottish Earnings Tax Outturn Statistics. Our dataset covers the three tax years 2016 to 2017, 2017 to 2018, and 2018 to 2019 when the five-band coverage got here into impact. It consists of taxpayers current in all three years and excludes any taxpayers who moved from Scotland to rUK in that point, or vice versa.
By selecting this inhabitants, we estimate behaviours resembling tax avoidance actions, altering the variety of hours labored, or deciding whether or not to take a position time in a private enterprise. This kind of behaviour is known as intensive behaviour. Different behaviours that take away people from the workforce utterly resembling retirement, not beginning a enterprise, or migration are known as intensive behaviours and usually are not captured by our evaluation. In most comparable research, intensive behaviours make up nearly all of taxpayer behaviour, with intensive behaviours sometimes being small.
A typical methodology for estimating TIEs can be a difference-in-differences design, whereby the change in taxable incomes for Scottish taxpayers are in contrast with the equal change for rUK taxpayers, and the distinction in how their incomes modified is the coverage response. This system is commonly utilized in comparable research of taxpayer behaviour resembling Brewer, Saez and Shephard (2010) of their research of high incomes throughout the UK.
Nevertheless, this depends upon the idea that revenue progress would have been the identical amongst the remedy group (Scotland) and the management group (rUK) within the absence of the coverage change. We discovered that Scotland and rUK had completely different progress charges in revenue over that point (non-parallel tendencies) which signifies that an ordinary distinction in variations design wouldn’t give us legitimate estimates for the TIEs.
We tried to regulate for this drawback of non-parallel tendencies by adapting our methodology to check Scottish taxpayers with solely rUK taxpayers who’ve comparable traits. These traits are their age, intercourse, sector or business they work in, their logged revenue in 2017 to 2018 (the yr earlier than the coverage was launched) and at last the expansion of their revenue between the tax years 2016 to 2017 and 2017 to 2018.
To seek out appropriate rUK taxpayers who will be matched with our Scottish taxpayers, we apply a method known as propensity rating matching and mix this with distinction in variations. The primary stage is to estimate propensity scores for every person who captures the chance they might be throughout the handled group based mostly on their particular person traits. The second stage makes use of an identical approach to match people throughout the remedy group to people throughout the management group with the closest propensity rating. In essence, this assigns the person rUK taxpayers who’re most much like our Scottish taxpayers. That is known as nearest neighbour one to at least one matching and is the headline matching approach in our paper.
Utilizing this strategy, we estimate the typical share change in taxable revenue for a Scottish taxpayer utilizing the difference-in-differences strategy on our matched taxpayers solely. We assume that the entire distinction within the common share change in taxable revenue between Scottish and matched rUK taxpayers is pushed by coverage variations. Nevertheless, it’s value taking into account that there’ll inevitably be different unobservable elements driving variations between Scottish and rUK taxable revenue progress along with the consequences of the coverage that we can’t management for.
We convert the typical share change in taxable revenue to a TIE by dividing by the proportion change within the taxpayers MRR for the revenue band thought of. The MRR is outlined as take dwelling pay as a proportion of complete pay, also known as their internet of tax price (for instance, if taxed at 40%, a person’s MRR can be 60%).
In addition to going through a unique MRR, Scottish taxpayers can even pay a unique complete quantity of Earnings Tax in comparison with their rUK friends on the identical revenue. Dividing their complete Earnings Tax liabilities by their complete earned revenue produces what’s known as their common or efficient tax price. Our paper focusses on behaviour to modifications within the MRR solely.
The interpretation of a TIE is greatest seen with a labored instance. A TIE of 0.1 signifies that a 1% lower within the given taxpayer group’s MRR (i.e. the tax price has gone up) results in a 0.1% lower of their taxable revenue. Nevertheless, a TIE of -0.1 signifies that the identical 1% lower of their MRR results in a 0.1% improve of their taxable revenue.
Whereas our paper finds some proof of a behavioural response to the five-band coverage, it must be famous that throughout all revenue bands, most of our outcomes usually are not statistically important. For instance, no Greater or Prime price revenue band is critical throughout all of our matching approaches apart from the £43,431 to £80,000 band.
Low incomes taxpayers with incomes between £11,850 and £13,850 paying the brand new Starter price of 19% have a TIE of -0.06. This implies little or no to no response to the autumn of their marginal price. One would possibly count on this end result given the restricted alternatives for this group to change their taxable incomes. The outcomes additionally present that, when accounting for variations in public sector pay progress in Scotland and the rUK, there’s little to no evident behavioural response for people with incomes of lower than £43,430.
Greater earners with incomes between £43,431 and £80,000 paying the brand new Greater price of 41% had a TIE of 0.35. This can be a noticeable lower of their taxable incomes in response to their marginal tax price growing. The TIEs vary from roughly 0.12 to 0.46 throughout the Greater price tax band after we take a look at all matching approaches.
Very excessive earners with incomes above £300,000 and £500,000 have TIEs of two.39 and 5.45 respectively, exhibiting a robust discount of their taxable incomes when confronted with the brand new Prime price of 46%. Nevertheless, we discovered this group to be delicate to each our matching strategy in addition to various approaches for assigning propensity scores which we discover within the robustness checks part of our paper. That is doubtlessly because of the small measurement of the taxpayer inhabitants inside these bands. With any analytical research an estimate based mostly on a small inhabitants measurement will be extra prone to uncertainty and volatility. Our general TIE for taxpayers within the Prime price incomes above £150,000 ranges from 0.54 to 0.77 which has similarities to previous research on UK tax coverage by HMRC (2012) and the IFS (2017).
The rest of our paper continues as follows: our subsequent part appears to be like deeper into the coverage background adopted by reviewing a number of the current TIEs literature; we then think about the info used for our research and current some descriptive statistics on our taxpayer inhabitants; the methodology is then thought of in additional element earlier than outlining the outcomes and exploring their robustness; lastly, we end with a dialogue of the outcomes and provide our conclusions.
5. Background to the Devolved Earnings Tax Powers in Scotland
The ability to set Earnings Tax charges is devolved by the UK Parliament to the Scottish and Welsh Parliaments. Due to this fact, a taxpayer residing within the UK might face a unique Earnings Tax regime relying on the place they dwell. For Scotland, the devolution of powers occurred in three vital levels. These had been the Scotland Acts of 1998, 2012 and 2016.
5.1 The Scotland Acts
The Scotland Act 1998 gave the Scottish Parliament the facility to range the Fundamental price of Earnings Tax by three share factors relative to the UK price. The ability granted beneath this Act was by no means exercised by the Scottish Authorities and was changed by the next Acts of 2012 and 2016.
The Scotland Act 2012 gave the Scottish Parliament the duty for setting the Scottish Price of Earnings Tax (SRIT) ranging from the tax yr 2016 to 2017. This price solely utilized to NSND revenue, which incorporates earnings from employment, self employment, property revenue and pension revenue. Earnings Tax on financial savings and dividends will not be devolved, with charges for the entire of the UK set by the UK Parliament. The Private Allowance threshold (a common reduction from Earnings Tax as much as a sure stage of revenue) can be not devolved.
To coincide with the introduction of SRIT, the UK Authorities diminished the NSND Earnings Tax already collected in Scotland by 10 share factors for all three tax bands (Fundamental, Greater and Extra). For the tax yr 2016 to 2017 the Scottish Authorities then selected to set the Scottish price at 10%. This meant {that a} Scottish taxpayer and a taxpayer from rUK with the identical earnings had the identical complete Earnings Tax liabilities. Nevertheless, in Scotland, 10 pence within the pound went to the Scottish Authorities and 10 pence, 30 pence and 35 pence went to the UK Authorities for the Fundamental, Greater and Extra price tax bands respectively.
Desk 3 beneath exhibits the SRIT and UK Authorities charges for the 2016 to 2017 tax yr. The SRIT powers applied beneath the Scotland Act 2012 had been solely efficient for one yr earlier than they had been changed by the Scotland Act 2016.
Desk 3: Scotland and UK NSND Earnings Tax charges within the tax yr 2016 to 2017.
The Scotland Act 2016 gave the Scottish Parliament full energy over charges and thresholds of NSND Earnings Tax, excluding the Private Allowance, collected in Scotland for the 2017 to 2018 tax yr onwards. This gave the Scottish Parliament the flexibility to set the total Scottish Earnings Tax charges and accumulate all related tax (i.e. the equal UK Authorities charges in Scotland had been eliminated totally). The Act additionally gave the Scottish Parliament the flexibility to create new tax bands in the event that they wished.
For the primary tax yr 2017 to 2018, the Scottish Authorities selected to align the Scottish Earnings Tax charges to the UK Authorities charges within the rUK. Nevertheless, it set the brink at which a taxpayer begins to pay the Greater price at £43,000 in comparison with the UK Authorities threshold of £45,000. The 2 programs had been in any other case equivalent. Desk 4 beneath compares the 2 programs for that yr.
Desk 4: Scotland and rUK NSND Earnings Tax charges within the tax yr 2017 to 2018.
For the tax yr 2018 to 2019 the Scottish Authorities exercised its powers to introduce a brand new five-band coverage which is completely different to the UK Authorities regime. This coverage is roofed in additional element within the subsequent part. Determine 1 beneath summarises the three Acts of UK Parliament described on this part.
Lastly, from the tax yr 2019 to 2020 the Welsh Parliament had been granted their very own Welsh Charges of Earnings Tax (WRIT) beneath the Wales Act 2014. Given our paper focusses on the behavioural response to the Scottish Earnings Tax modifications in 2018 to 2019 earlier than WRIT got here into impact, the rUK can broadly be regarded as England, Wales and Northern Eire all through our paper.
Determine 1: Abstract of the Acts of UK Parliament granting devolved Earnings Tax powers to Scotland.
Determine 1 exhibits a horizontal time axis of 1998 to 2020. There are three spokes alongside the axis which signify the Scotland Acts of 1998, 2012 and 2016 coming into energy. There’s a temporary description of the powers that every Act granted. For an outline of the powers proven on this determine, please confer with ‘The Scotland Acts’ part of the paper above.
5.2 5-band coverage in 2018 to 2019
For the tax yr 2018 to 2019 the Scottish Authorities launched two new Earnings Tax bands and their related charges, in addition to growing the charges for 2 of the prevailing bands. This switched Scotland from a three-band system to a five-band system.
Taxpayers in Scotland due to this fact face 5 completely different marginal tax charges starting with the Starter price of 19%, a Fundamental price of 20%, a brand new Intermediate price of 21%, a Greater price of 41% and a Prime price of 46%. Desk 5 beneath exhibits the brand new Scottish Earnings Tax system for the tax yr 2018 to 2019 and Desk 6 exhibits the rUK system for a similar yr.
Desk 5: Scottish Earnings Tax NSND coverage for the tax yr 2018 to 2019.
Desk 6: rUK NSND Earnings Tax coverage for the tax yr 2018 to 2019.
As will be seen in Tables 5 and 6, a excessive incomes Scottish taxpayer will face the next marginal Earnings Tax price than somebody in rUK with the identical stage of revenue, whereas a low incomes taxpayer will face a decrease marginal price.
Along with the 5 and three-bands in Scotland and the rUK respectively, it’s vital to concentrate on the Taper price. For incomes above £100,000, a taxpayer’s Private Allowance (the primary £11,850 of revenue in 2018 to 2019) is eliminated by the quantity of £1 for each £2 of extra revenue. In impact, which means a Scottish taxpayer faces a marginal price of 61.5% on their earned revenue between £100,000 and £123,700 whereas and a rUK taxpayer faces a marginal price of 60%.
Each teams of taxpayers are topic to the Taper price provided that the Private Allowance will not be devolved, nonetheless the marginal charges over the revenue band are completely different as a result of Scottish taxpayers are shedding their Private Allowance to a Greater price of 41% relative to their rUK friends’ Greater price of 40%.
Determine 2 beneath exhibits the variations within the marginal charges confronted by completely different revenue ranges for each Scottish and rUK taxpayers. For the needs of our research, we’re not analyzing or together with the consequences of Nationwide Insurance coverage Contributions (NICs) which aren’t devolved to the Scottish Parliament, nor are we contemplating some other taxes or deductions to revenue.
Determine 2: Marginal NSND Earnings Tax charges in Scotland and rUK within the tax yr 2018 to 2019.
Determine 2 exhibits taxpayer revenue alongside the x-axis with the related marginal tax price for Scotland and the rUK alongside the y-axis. The marginal charges for Scotland are decrease or equal to the rUK charges from £11,850 to £24,000, earlier than Scotland has greater marginal charges for incomes higher than £24,000.
Tables 5 and 6 coupled with Determine 2 show a Scottish taxpayer incomes lower than £13,850 may have a decrease marginal price in comparison with a rUK taxpayer on the identical revenue. This implies their take dwelling pay for each pound earned in that band, their MRR, can be greater in Scotland. Nevertheless, a taxpayer incomes above £24,000 will face greater marginal charges of Earnings Tax, and due to this fact have a decrease MRR for every pound of revenue they earn above that quantity in Scotland.
This part presents literature on TIE research from quite a lot of completely different tax reforms which have taken place previously. Many of the literature obtainable focuses on reforms in the US of America (USA), however there are current research for tax modifications in different international locations, together with the UK. Word that the literature usually refers to TIEs as “Elasticity of Taxable Earnings” or ETI’s. Elasticities are usually negligible or very small in the beginning of the revenue distribution and improve with revenue.
The literature considers various behaviour by taxpayers that may have an effect on taxable revenue in response to a change within the tax price. Behaviours that cut back taxable revenue progressively are thought of to be ‘intensive’, for instance avoidance, lowering hours, or not investing to increase a private enterprise. Behaviours that take away people from the workforce utterly resembling retirement, not beginning a enterprise, or migration are described as ‘intensive’.
Totally different research will embrace completely different behaviours of their estimated TIEs, however the estimates are nonetheless broadly comparable. Typically talking, intensive results are usually a lot smaller than intensive results. Since our paper solely consists of taxpayers remaining resident as a taxpayer in Scotland or rUK throughout all the interval, we outline our estimated TIEs as capturing behaviour alongside the intensive margin solely.
6.1 UK based mostly literature
Brewer, Saez and Shephard (2010) current a high revenue share evaluation for the UK between 1962 and 2003. There have been two notable tax modifications launched by the UK Authorities on this interval: the highest marginal tax price was minimize from 83% to 60% in 1979 after which diminished to 40% in 1988. They use a difference-in-differences design which depends on the figuring out assumption that revenue progress would have been the identical amongst the remedy and management teams. They take a look at two approaches:
the change in revenue share of the highest 1% of earners; and
the change within the high 1% of earners utilizing the subsequent 4% of earners as a management group.
They discover elasticities across the 1979 reform between 0.34 when contemplating the primary strategy and 0.08 when utilizing the second strategy. The elasticities for the 1988 reform are estimated to be between 0.37 and 0.41 for each approaches respectively. Lastly, when contemplating a full time-series regression from 1973 to 2003, they discovered an elasticity of 0.73 and 0.46 respectively.
HMRC (2012) estimate a TIE utilizing the 2010 to 2011 introduction of the 50% Extra price of Earnings Tax. They used a four-step strategy to estimating a TIE from Self-Evaluation returns. While their estimates for elasticities ranged between 0.48 and 0.71 when various their controls, they counsel a TIE of 0.45 as their central estimate when contemplating the obtainable proof on TIEs.
The Institute for Fiscal Research adopted up on this analysis in 2017. They up to date HMRC’s strategy with an additional yr of information and located an elasticity of 0.31 for the Extra price inhabitants based mostly on the response in 2010 to 2011, and 0.83 based mostly on the response in 2011 to 2012. The IFS assert that HMRC’s methodology for estimating the consequences of stopping on the time was “prone to result in overestimates of how a lot got here from these preliminary publish‑reform years, and therefore underestimate the underlying taxable revenue elasticity”. The IFS due to this fact recommended an alternate methodology which supplies them an elasticity of 0.58 for the response of this inhabitants in 2010 to 2011 and 0.95 in 2011 to 2012.
6.2 Worldwide literature
Feldstein (1995) makes use of a panel of particular person revenue tax reforms to review the 1986 Tax Reform Act within the USA. This reform diminished the highest tax price from 50% to twenty-eight% in 1988. A difference-in-differences technique is used to estimate a spread of elasticities with respect to the net-of-tax price. Feldstein finds TIEs between 1.10 and three.05 for prime revenue people.
These estimates are much like the estimates of Lindsey (1987) who studied the 1981 Financial Restoration Tax Act which offered a 23% discount in tax charges over three years and a direct minimize within the high private price from 70% to 50%. Lindsey used non-panel tax return knowledge to offer estimates with ranges from 1.05 to 2.75, with a lot of the knowledge suggesting a TIE between 1.6 and 1.8.
A research on a panel of USA tax returns that Gruber and Saez (2002) analysed all through the Eighties provides estimates of TIEs in keeping with revenue stage. The highest marginal revenue tax price on the federal stage fell from 70% in 1980 to twenty-eight% by 1988, with a discount from fifteen revenue tax brackets to 4. They estimate the TIE for people incomes between $10,000 and $50,000 to be between 0.180 and 0.284. They estimate a TIE between 0.106 and 0.265 for people with greater earnings within the vary of $50,000 to $100,000. Lastly, they estimate a TIE between 0.484 and 0.567 for people with incomes in extra of $100,000.
Saez (2004) makes use of USA revenue tax knowledge from 1960 to 2000 to analyse behavioural responses to taxation. Saez finds that “solely the highest 1% incomes present proof of behavioural responses to taxation”. This research argues that there was no response to the big high price cuts within the early Nineteen Sixties however there was proof of responses because the Eighties. Saez makes use of a time-series regression to search out elasticity estimates between 0.50 and 0.71 when accounting for time tendencies.
Saez, Slemrod and Giertz (2012) use difference-in-differences to estimate elasticities for the highest 1% and the subsequent 9% of incomes. That is carried out throughout 4 particular person tax modifications in addition to throughout a time collection from 1960 to 2006. Throughout the total time-series regression, they discover an elasticity starting from 1.71 with no time tendencies to 0.58 with time tendencies for the highest 1% of incomes. Against this, the subsequent 9% have coefficients which might be roughly zero which helps the findings of Saez’s 2004 paper.
Research of tax reforms in Nordic international locations by Aarbu and Thoresen (2001) and Kleven and Schultz (2014) discover decrease TIE estimates. Aarbu and Thoresen studied the 1992 tax reform in Norway which elevated the MRR for high-income earners utilizing a distinction‑in-differences strategy. They discover comparatively low elasticities with respect to the net-of-tax price by comparability to USA research, starting from -0.6 and 0.2.
Equally, Kleven and Schultz use Danish inhabitants knowledge starting in 1980 protecting 4 separate reforms, the most important of which occurred in 1987 the place the marginal tax price for prime and center earners was diminished. They discovered that the TIEs throughout all reforms thought of are roughly 0.082 however improve to 0.189 for the 1987 reform.
Desk 7: Abstract desk of literature.
7. Information
7.1 Taxpayer knowledge sources
We’ve drawn upon HMRC’s RTI knowledge for Pay-As-You-Earn (PAYE) taxpayers. This knowledge is submitted to HMRC by employers at any time when they make a fee to their workers. It consists of the sum of money paid to the worker, the Earnings Tax withheld from them on behalf of HMRC and the mandatory info to determine the taxpayer, resembling their nationwide insurance coverage quantity (NINO).
For Self-Evaluation taxpayers, we now have drawn upon the info extracted yearly by HMRC to supply the Scottish Earnings Tax Outturn Statistics. Particularly, our Self-Evaluation dataset is per the established or recognized Scottish Earnings Tax liabilities on the time the outturn was produced. Some liabilities for any given yr will be collected a number of months or years after the fiscal yr has ended. This unestablished quantity is estimated within the Outturn Statistics based mostly on historic knowledge and makes up roughly 1% of all liabilities. For our functions we solely require these taxpayers with confirmed liabilities to have the ability to research their behaviour. We don’t consider the absence of the unestablished quantity will influence our outcomes.
Each our RTI and Self-Evaluation datasets embrace pensioners along with the energetic workforce, since pension revenue is included beneath NSND revenue. The datasets cowl taxpayers from the entire of the UK.
For our research we now have used knowledge from the three tax years of 2016 to 2017, 2017 to 2018 and 2018 to 2019. This allows us to estimate the behavioural response within the last yr when the five-band coverage was launched, often called the remedy yr, in addition to draw upon the tendencies in taxpayer incomes earlier than that yr to make use of in our methodology.
Our dataset solely consists of taxpayers current in all three tax years, often called a balanced panel dataset, and it excludes any taxpayers who moved from Scotland to the rUK throughout that point, or vice versa.
7.2 Earnings variable
NSND revenue is the first variable in our knowledge set. For PAYE, a person’s annual NSND revenue is assumed to be the sum of their month-to-month pay throughout the tax yr. The place they’ve a number of pay quantities per thirty days, for instance somebody who has two or extra employments, these have been summed beneath the identical particular person and included of their complete pay. It is because Earnings Tax liabilities are calculated on an individual’s complete revenue, not on an employment-by-employment foundation resembling beneath the NICs coverage.
Our RTI datasets cowl the total fee submissions reported for workers from April 2016 to March 2017 for the tax yr 2016 to 2017, and the equal time interval for the opposite two tax years.
For SA, a person’s annual NSND revenue is available from the Self-Evaluation outturn knowledge. For the tax yr 2016 to 2017 this consists of all Self-Evaluation returns captured by the submitting deadline of April 2018, and by the equal deadline for the opposite two tax years.
Employed people who paid Earnings Tax through the PAYE assortment methodology and thus seem in RTI may have been required to file a Self-Evaluation return. It is because Self-Evaluation returns usually are not solely for the self-employed. An employed particular person might need to file for a number of causes, together with incomes over £100,000 in any given yr or having an employed revenue and a self-employment revenue.
For people with each an RTI file and a Self-Evaluation file, we now have prioritised their Self-Evaluation revenue over their RTI pay in any given yr. Their Self-Evaluation NSND revenue will seize all types of revenue, together with their employment revenue from RTI. We’ve due to this fact sought to make sure that every particular person taxpayer solely has one revenue file in our dataset.
7.3 Scottish Indicators (s-flags)
The definition of a Scottish taxpayer is predicated on the place a person resides for almost all of a tax yr. Scottish taxpayer standing applies for an entire tax yr – it isn’t attainable to be a Scottish taxpayer for a part of a tax yr. The situation of an individual’s employer will not be related. For instance, somebody who works in Scotland however has their essential dwelling elsewhere within the UK won’t be a Scottish taxpayer. Additional info on who pays Scottish Earnings Tax will be discovered on the GOV.UK web site.
As soon as a Scottish taxpayer has been recognized they’re given a Scottish indicator, also known as an s-flag, which suggests they’ve paid their Earnings Tax liabilities beneath the five-band Scottish regime, not the three-band rUK regime. We use this s-flag variable to determine our Scottish taxpayers within the tax yr 2018 to 2019 in our remedy group.
The s-flags in our dataset for each RTI and Self-Evaluation taxpayers are drawn from, and due to this fact per, the HMRC knowledge used to assemble the Scottish Earnings Tax Outturn Statistics.
7.4 Demographic variables (Age, Intercourse and Sector)
We’ve sourced taxpayer age from HMRC’s RTI knowledge for each RTI and Self-Evaluation taxpayers wherever attainable. That is taken as their age on the finish of the tax yr in query. We’ve additionally sourced taxpayer intercourse from the identical RTI knowledge supply for each RTI and Self-Evaluation taxpayers. This would be the intercourse offered to HMRC by their employer.
For sector and business classification we now have utilized the related Customary Industrial Classification of Financial Actions (SIC) codes from 2007 to our taxpayers wherever attainable and positioned these into the twenty-one sections of business starting from Agriculture, Forestry and Fishing (A) to Actions of additional territorial organisations and our bodies (U). A full checklist of the twenty-one sections of business will be discovered on the Firms Home web site.
For RTI taxpayers we now have sourced a SIC code that’s assigned to every taxpayer based mostly on their employment. For a taxpayer with a number of employments, we now have taken the SIC code hooked up to their employment with the very best quantity of pay in that yr. The exception to that is when an RTI taxpayer’s file is flagged as being from an occupational pension. All RTI information are flagged as both employment pay or occupational pension pay. If flagged because the latter, the RTI taxpayer is classed as a Pensioner and never their business classification.
For Self-Evaluation taxpayers, a taxpayer’s essential supply of revenue is the issue that determines their business classification. For instance, for a Self-Evaluation taxpayer whose essential supply of revenue is classed as employment pay, we now have sourced a SIC code on file based mostly on their employer. For a Self-Evaluation taxpayer whose essential supply of revenue is classed as being a sole dealer, we now have sourced their SIC code on file based mostly on their commerce revenue. For every of those SIC sources, there could also be lacking info for some taxpayers. Desk 8 beneath units out the completely different classifications of SIC code for our Self-Evaluation taxpayers.
Desk 8: SIC code supply for Self-Evaluation taxpayers.
Within the cases the place a taxpayer has each an RTI SIC code and a Self-Evaluation SIC code, we now have prioritised their Self-Evaluation SIC code for all taxpayers with one exception. This being that if they’ve a essential supply classification of employment pay and their Self-Evaluation SIC code is lacking, we now have allowed for his or her RTI SIC code to exchange their lacking Self-Evaluation SIC code. The place it isn’t lacking, their Self-Evaluation SIC code nonetheless takes precedence for any essential supply classifications of employment pay.
Lastly, Desk 9 beneath summarises the sources for our key variables.
Desk 9: Abstract of sources for key variables in our dataset.
8. Descriptive Statistics
8.1 Taxpayer Statistics
The statistics introduced listed below are for the inhabitants utilized in our evaluation. Migrants between Scotland and rUK have been eliminated and the panel is balanced so that every particular person seems in all three tax years. Whereas these figures think about all people inside Scotland and rUK, some people can be omitted by the econometric methodology.
8.2 Variety of taxpayers in every band for 2017 to 2018
Desk 10 presents the variety of taxpayers in every revenue band for 2017 to 2018. We see that almost all of taxpayers thought of have revenue between £11,850 and £43,430 (84%). There are roughly 15.5 million people who’ve revenue beneath the Private Allowance. These people are dropped from the evaluation and usually are not included in some other figures or tables. Numbers are rounded to the closest 500.
Desk 10: Variety of folks in every revenue band for the entire of the UK in 2017 to 2018.
Determine 3: Variety of taxpayers in every revenue band for 2017 to 2018.
This determine exhibits the distribution of taxpayers throughout the revenue bands. There are roughly 2 million people in revenue band 1, which will increase to round 10m in revenue band 2. Past this level, the variety of people falls a small quantity for band 3 adopted by a considerable drop in revenue band 4 and past.
8.3 Taxpayers throughout rUK and Scotland
The distribution of taxpayers throughout the revenue bands is comparatively comparable in rUK and Scotland. There’s a barely smaller proportion of people within the Fundamental price in rUK than in Scotland, and that is mirrored by having a barely bigger proportion of people which might be within the Greater and Extra / Prime price bands.
Determine 4: Distribution of taxpayers in keeping with revenue band in rUK and Scotland.
This determine compares the distribution of incomes throughout rUK and Scotland. General, the shapes of the distributions are comparable, with the most important proportions of people in revenue bands 2 and three. There are very small variations throughout distributions in rUK and Scotland, with Scotland having extra people in revenue bands 2 and three, however fewer within the greater revenue bands.
8.4 Age Distribution
There are some variations within the age distribution for taxpayers in Scotland and rUK. The latter has a higher proportion of individuals between the ages of 20 and 40 years. The figures are comparable for the 40 to 50 yr age group. Scotland then has a bigger proportion of people aged between 50 and 70 years. And eventually, rUK has barely extra people (as a proportion) which might be aged 70 and over.
Determine 5: Age Distribution throughout rUK and Scotland.
This determine describes the distributions throughout Scotland and rUK. rUK has extra people between the ages of 20 to 40 years, whereas Scotland has extra folks between the ages of fifty and 70 years.
8.5 Intercourse Distribution
The next desk captures the intercourse of people for Scotland and rUK. The proportion of individuals which might be male is bigger in rUK than in Scotland for the inhabitants captured inside our evaluation.
Desk 11: Distribution of intercourse throughout rUK and Scotland.
8.6 Sectoral Distribution
The distribution of sectors between rUK and Scotland tends to be pretty comparable as proven by the determine beneath. The dominant sector recorded is the general public sector for each rUK and Scotland and the second most dominant sector is pensions. The general public sector is constructed utilizing a mixture of “Public Administration”, “Schooling” and “Human Well being”. We acknowledge that there could also be people inside these teams which might be within the personal sector and that there could also be people within the public sector not captured in these teams.
Determine 6: Distribution of sectors throughout rUK and Scotland.
This determine compares the distributions of taxpayers throughout sectors inside Scotland and rUK. Nearly all of people are within the public sector, with the second largest sector being pensions. Scotland has a lot bigger proportions of people within the public sector, pensions and mining and quarrying. rUK has bigger proportions inside Wholesale and Retail Commerce, Administrative and Help Service Actions and Manufacturing. All different sectors have roughly equal proportions of people.
8.7 Macroeconomic Developments
8.8 GDP Development
ONS knowledge is used to assemble GDP progress tendencies between Scotland and rUK (Additional-Regio exercise has been eliminated). Sometimes, GDP progress has been stronger in rUK since 2010. The ONS figures of regional GDP progress are broadly much like these produced by the Scottish Authorities, and permit for comparable figures for Scotland and the rUK.
Determine 7: GDP Development throughout Scotland and rUK.
This determine exhibits a comparability of GDP progress between Scotland and rUK from 2010 to 2019. GDP progress in rUK is rather more secure, with progress typically falling since 2014. In Scotland, there’s volatility within the GDP progress price, which repeatedly goes from excessive to low.
8.9 Employment price
Labour Pressure Survey (LFS) knowledge is used to assemble a comparability of employment for Scotland and rUK. The employment price (outlined because the proportion of the inhabitants over 16 in employment) has sometimes been decrease in Scotland.
Determine 8: Employment price tendencies throughout rUK and Scotland.
This determine exhibits the modifications in employment charges over time per tax yr for Scotland and rUK from 2010 to 2011 as much as 2019 to 2020. The employment price in rUK has been steadily growing from round 58% in 2011 to 2012 as much as 62% in 2019 to 2020. In Scotland, there’s a comparable upward pattern till 2014 to 2015. There’s then a divergence, the place employment charges turn out to be flatter and are near 60% as much as 2019 to 2020.
8.10 Pay Development
The next is taken from RTI knowledge, exhibiting the pattern of pay progress for workers between Scotland and rUK. RTI pay has grown sooner by roughly 1 to 2 share factors in rUK in comparison with Scotland because the tax yr 2015 to 2016.
Determine 9: Pay Development Developments.
9. Methodology
We use propensity rating matching and difference-in-differences to estimate the proportion change in taxable revenue for Scottish taxpayers because of the coverage. Our design takes benefit of Earnings Tax modifications in Scotland by evaluating Scottish taxpayers to a matched management group from rUK. We recuperate the Common Therapy Impact on the Handled (ATET), or in different phrases, the influence on NSND revenue declared by Scottish taxpayers going through new Earnings Tax charges in 2018 to 2019.
Our methodology selects a management group from rUK who match Scottish taxpayers in key dimensions, together with historic revenue progress and sector. We distinction the imply log change in revenue between the remedy and management teams to recuperate the coverage impact. Utilizing this strategy, we estimate the typical share change in revenue in Scotland with out specifying a practical kind.
People are grouped into revenue bands reflecting their marginal price to permit estimation of the completely different behaviour of taxpayers at completely different revenue ranges (heterogeneous behaviour). Cross-border migrants are excluded from the evaluation. On this method the recognized parameter displays the intensive behavioural margin, which captures behaviour regarding the quantity of revenue declared relatively than different behaviours resembling migration from Scotland.
9.1 Behavioural Results
To determine the coverage impact, we assume people solely react to modifications of their marginal tax price. Equivalently, as in Saez et al. (2012), we assume revenue results don’t generate behaviours to cut back taxable revenue. This assumption is vital to account for the numerous tax price modifications people face beneath their margin that affect net-of-tax-income.
We outline the MRR as one minus the marginal Earnings Tax price. This variable summarises the behavioural incentives confronted by people. It displays the quantity of revenue obtainable to spend after tax. Our definition excludes NICs, tuition charges, and numerous different deductions.
We break up the inhabitants into ten bands and prohibit the handled teams such that people are solely in comparison with others experiencing the identical proportional change of their MRR. The relative change within the MRR varies throughout tax bands since we calculate the change within the MRR because the distinction in pure logarithms of the publish and pre-policy MRR:
The place τt’ and τt are the marginal tax charges earlier than and after the coverage change respectively. For instance, within the Extra / Prime price a change in MRR from 0.55 to 0.54 imposes a fall of 1.8%, whereas within the Intermediate price a change from 0.8 to 0.79 imposes a fall of only one.3%. In impact, the Extra / Prime price experiences a unique coverage change to the Intermediate price.
We allocate people into ten revenue bands in keeping with their revenue within the 2017 to 2018 tax yr. The ten revenue band construction displays the five-band system, with logical factors for modifications within the MRR such because the Taper price, and is per the Scottish Fiscal Fee’s behavioural framework for splitting up the Extra / Prime price. This permits us to seize heterogeneity in responses.
Desk 12: Earnings bands used for TIEs evaluation.
Cross-border migrants are faraway from the dataset. It’s attainable that the choice emigrate is influenced by tax coverage. Excluding migrants similtaneously the coverage change is a call to exclude a part of the behavioural impact from the recognized parameter. This aligns the recovered estimate of the behavioural impact extra intently to the intensive margin.
9.2 Distinction-in-Variations Matching Mannequin
A difference-in-differences methodology compares the change in revenue earlier than and after the coverage between the handled and management teams. The management group gives us with a counterfactual distinction – the change we’d count on within the absence of a coverage influence. That is legitimate on the idea that, within the absence of the coverage, revenue would change on the identical price, usually known as the ‘parallel’ or ‘widespread’ tendencies assumption. This strategy controls for choice on mounted results, and modifications which might be widespread to each teams.
Scotland and rUK are divergent in key dimensions. Traditionally, revenue grows at considerably completely different charges for the 2 international locations as will be seen by Determine 9 of the descriptive statistics exhibiting RTI pay progress. To aim to regulate for non-parallel tendencies, we choose a management group utilizing propensity rating matching. This system permits us to check Scottish taxpayers with taxpayers from rUK who’re comparable by way of key traits. A propensity rating is the chance of remedy given a vector of observable variables.
We estimate propensity scores utilizing a logistic (logit) regression. Historic revenue progress charges, the log of present revenue, intercourse, sector, and age act as covariates. Historic progress is outlined because the distinction within the log of revenue between 2016 to 2017 and 2017 to 2018.
People are matched on tax yr 2017 to 2018, the yr earlier than the coverage change. Matches are restricted to inside revenue band. By matching on historic progress, we create a re-weighted management group that’s extra prone to be on a parallel pattern throughout the pre-reform intervals within the dataset.
The research presents three various strategies when matching handled people with these within the management group: (1) nearest neighbour with one-to-one matching; (2) nearest neighbour with one-to-two matching; and (3) kernel matching.
The closest neighbour matches are with substitute. For Kernel matching we use an Epanechnikov kernel operate and robotically compute the bandwidth as per Jann (2017). We bootstrap commonplace errors for kernel matching and use Abadie and Imbens (2006) to calculate commonplace errors for nearest neighbour matches.
Our headline estimates are taken from (1) nearest neighbour with one-to-one matching however no single methodology is clearly preferable. Due to this fact, the evaluation presents all three to check the robustness of the noticed remedy results.
The ATET is a weighted common of the distinction in steady progress charges between people within the remedy and the management teams. It’s obtained by estimating the next equation (Lenhart, 2019):
D=1 signifies remedy and D=0 signifies non-treatment, P(X) denotes the propensity rating, Y is revenue for a person the place subscript 0 denotes the untreated state, subscript 1 denotes the handled state, subscript t denotes the post-treatment interval and subscript t’ denotes the pre-treatment interval.
From Heckman et al. (1997), the estimator above identifies the typical remedy impact on the handled if the next assumption holds:
The recovered statistic is the proportion change in revenue brought on by coverage. That is transformed to an elasticity by dividing by the change in MRR. The person is assumed to react to modifications of their headline price of tax, and we don’t account for idiosyncratic elements which may affect a person’s efficient price, resembling switching revenue bands. The system for the conversion is given beneath.
The place the ATET is the remedy impact outlined above, (1-τ) is the MRR, the subscript t denotes the post-treatment interval and the subscript t’ denotes the pre-treatment interval.
10. Outcomes
Our headline estimates are nearest neighbour with one-to-one matching. The ATET captures the typical share change in revenue for a given revenue band because of the tax change in Scotland.
10.1 Proportion Modifications in Earnings
Desk 13: Common remedy impact on the handled throughout all revenue bands.
Customary errors in parentheses. *** p<0.01, ** p<0.05, * p<0.1
10.2 TIEs
This part exhibits the outcomes above as TIEs with respect to the MRR.
Desk 14: Taxable revenue elasticities.
*** p<0.01, ** p<0.05, * p<0.1
11. Robustness Checks
11.1 Balancing Assessments
Standardisation Bias
The standard of matching is assessed by performing exams that examine whether or not the propensity rating adequately balances the traits of the remedy and management teams.
We check the matching high quality by utilizing the standardised bias as recommended by Rosenbaum and Rubin (1985). It’s outlined because the distinction of pattern means within the remedy and matched management subsamples as a share of the sq. root of the typical of pattern variances in each teams for every covariate. The standardised bias after matching is given by:
The place X1 (V1) is the imply (variance) within the remedy group after matching and X0 (V0) is the analogue for the management group. Many empirical research regard a standardisation bias of lower than 5% as enough.
We typically discover that the standardisation bias between the remedy and matched management teams is lower than 5% usually. This holds true for all revenue bands, no matter whether or not we use nearest neighbour or kernel matching.
T-test distinction of means
T-tests are used to examine for the equality of covariate means within the remedy and matched management group. If there’s good steadiness, then there won’t be statistically important variations between the technique of the covariates. We think about these exams on the 5% significance stage.
We discover that usually, there are not any statistically important variations on the 5% stage between the technique of the handled and management teams. These outcomes maintain throughout revenue bands and matching strategies. The t-tests and standardisation bias reinforce the energy of our outcomes and present that there’s typically good steadiness within the propensity rating matching methodology.
11.2 Overlap Situation
An extra examine on propensity rating matching is to confirm the overlap situation. The concept right here is to visually examine the propensity rating distributions for each the remedy and management teams, wanting on the closeness of the overlap. There must be no clear or sizeable variations between the remedy and management teams after the matching course of. All graphs are proven in Annex B (when contemplating nearest neighbour with one‑to-one matching).
Determine 10: Propensity rating overlap earlier than and after matching for revenue band 1, with nearest neighbour one-to-one matching.
Determine 10 exhibits the propensity scores earlier than and after matching for revenue band 1 with nearest neighbour one-to-one matching. On the left, the graph exhibits the density of propensity scores for the handled and management teams earlier than matching, the place we see that there are sizeable variations within the density of propensity scores. On the fitting we see overlap between the handled and matched management teams.
Determine 11: Propensity rating overlap earlier than and after matching for revenue band 10, with nearest neighbour one-to-one matching.
Determine 11 exhibits a comparability of the density of propensity scores earlier than and after matching for revenue band 10, with nearest neighbour one-to-one matching. The left‑hand aspect exhibits the comparability of propensity scores earlier than matching, exhibiting a transparent distinction within the peak of propensity scores for the handled and management teams. The best-hand aspect exhibits the comparability of propensity scores after matching and exhibits that there’s little or no distinction between the densities of propensity scores.
The graphs present how the matching course of improved the overlap of the management group. The left-hand aspect of figures 10 and 11 examine everybody in rUK throughout the respective revenue band within the management group to Scottish taxpayers. Earlier than matching, the form of the densities are comparable, however the peak and vary of propensity scores are a lot greater for the management group. The post-match graphs present how matching has improved the match of propensity scores within the management group to Scotland. In all circumstances throughout all revenue bands, the overlap between handled and management teams is improved by the match.
11.3 Different Specs
We investigated the consequences of adjusting elements of the matching course of and together with migrants. General, there is no such thing as a main distinction to the outcomes when making modifications to the matching course of.
When utilizing a probit regression relatively than a logit regression to estimate the propensity scores (with nearest neighbour one-to-one matching) the magnitude of outcomes is usually decrease in absolute worth. The elasticities generated by utilizing probit regressions comply with the identical sample because the headlines, the place they improve with revenue bands. Essentially the most notable divergences in elasticities happen in revenue bands 9 and 10, the place the elasticities generated utilizing a probit mannequin to estimate propensity scores are a lot smaller than these produced by the logit mannequin.
Desk 15: Comparability of elasticities beneath logit and probit fashions, with nearest neighbour one-to-one matching.
The headline outcomes for nearest neighbour matching enable for substitute, the place one particular person within the management group can be utilized as a match for a number of handled people. Matching may also be carried out with out substitute, the place one particular person within the management group can solely be matched with one particular person within the remedy group. The findings stay constant when not permitting for substitute. There are solely two circumstances the place this makes a big distinction to the elasticity, for revenue bands 7 and eight.
Desk 16: Comparability of elasticities for nearest neighbour with one-to-one matching with and with out substitute.
The headline evaluation removes all people who migrated between Scotland and rUK for the entire interval thought of. When people who migrated between 2016 to 2017 and 2017 to 2018, which consists solely of a small variety of people, we discovered that this didn’t make any important distinction to the outcomes.
The ultimate examine is on completely different mixtures of covariates used for matching. Our headline evaluation makes use of demographic and revenue covariates, however we explored utilizing demographics and revenue alone. We discovered that there have been some bigger variations in outcomes in comparison with our headlines, and that the steadiness of the specs was generally worse after matching than earlier than matching. The strongest outcomes for steadiness got here from utilizing all covariates.
12. Dialogue
The outcomes point out a spread of behavioural results broadly per the literature. For people with revenue above the Scottish Greater price threshold, we discover a divergence in revenue progress between the handled and management teams after the coverage was applied.
This means that above a sure revenue, people in Scotland lowered their taxable revenue in response to the coverage. The scale of the response is believable and usually growing with revenue band. The three matching approaches are per each other, and throughout bands.
Most outcomes usually are not statistically important on the 10% stage utilizing adjusted commonplace errors. Though significance does vary, no Greater or Extra / Prime price revenue band is critical throughout all three matching approaches apart from band 4.
We conclude that there’s little to no proof of a behavioural impact for Starter, Fundamental or Intermediate price taxpayers. The headline outcome does present a divergence in revenue progress between the handled and management teams. Nevertheless, we check this utilizing band 2 as a placebo and discover proof of a confounding issue. We use a proxy to regulate for public sector pay. This instinct displays greater public sector pay progress in Scotland in comparison with the UK as an entire and is noticed in our Fundamental and Intermediate price outcomes.
Evaluating significance and the validity of the outcomes throughout revenue bands is troublesome because the measurement of the handled and management teams range. Bigger pattern sizes sometimes trigger smaller confidence intervals and this makes it extra possible that we see statistically important outcomes. We consider this to be the case in decrease revenue bands, since over 84% of taxpayers have incomes between £11,850 and £43,430.
Inside our dataset there are solely roughly 1,100 handled people in band 10, and only one,800 in band 9. This rises to 10,500 for band 8. Notably, of the Greater price bands, band 4 is essentially the most persistently important and has significantly extra observations at 216,000. With any analytical research, an estimate based mostly on a small inhabitants measurement will be extra prone to uncertainty and volatility.
The outcomes fulfill the important thing exams for validity. They’re balanced, with low standardisation bias and t-tests that aren’t statistically important. The propensity rating overlap between teams present the matching course of was profitable. These outcomes are comparatively invariant to the modelling choices of the PSM design.
12.1 Prime Price and Extra Price Taxpayers
People within the Scottish Prime price see a fall of their MRR of 1.8%. These in band 10 with incomes higher than £500k present the very best potential response, with taxable revenue falling between 5% and 10%. The response falls with revenue band: band 9 has a fall between 1.6% and 4.4%, band 8 has a fall between 0.3% and 1.3%. The next desk exhibits the elasticities for every matching strategy:
Desk 17: TIEs for the Prime and Extra price revenue bands.
We discover a vary of elasticates akin to comparable analysis from the literature throughout all the Prime and Extra price. For comparability, the 2012 HMRC analysis of the 50% Extra price estimated elasticities of 0.48 and 0.71. That is additionally akin to estimates produced by the IFS (2017) and Brewer et al. (2010).
We word that the elasticities produced by revenue bands 9 and 10 seem greater than the estimates given within the literature. These outcomes are restricted of their interpretation, as they’re delicate to the selection of mannequin to estimate propensity scores. When utilizing probit relatively than logit fashions, we see the elasticities beneath nearest neighbour with one-to-one matching fall to 0.74 for revenue band 9 and a pair of.78 for revenue band 10. It’s intuitive that greater revenue bands see a higher response to tax modifications. Nevertheless, the small variety of observations in these teams make the estimation of the elasticity much less exact.
When in comparison with the literature on modifications in USA tax coverage, the elasticities produced are fairly comparable regardless of the variations in fiscal programs. The outcomes are clearly decrease than the estimates produced by Feldstein (1995) and Lindsey (1987) however are rather more akin to the research by Saez (2004) and Saez et al. (2012) the place elasticities had been between 0.5 to 0.7 when accounting for time tendencies within the time-series regressions.
The literature in different international locations suggests decrease elasticities with respect to the MRR. For instance, Aarbu and Thoresen’s 2001 research of the 1992 Norwegian tax reform produced elasticity estimates of between -0.6 and 0.2, that are considerably decrease than the elasticities estimated inside this paper and different research from the USA.
12.2 Greater Price Taxpayers
The tax affairs for these within the Greater price are difficult by the existence of the Private Allowance Taper, the place for each £2 of revenue above £100,000, the Private Allowance falls by £1. For bands 4, 5, and seven the coverage will increase the marginal price from 40% to 41%, leading to a 1.7% fall within the MRR.
Nevertheless, these with revenue falling throughout the Taper price band face an extra marginal change. The Taper price of fifty% signifies that every pound earned on the margin is successfully taxed at 60% earlier than the coverage and 61.5% after the coverage. This corresponds to a fall within the MRR of three.75%. Take into account the elasticities within the desk beneath.
Desk 18: TIEs for the Greater price revenue bands.
Outcomes on the Greater price indicate a decrease behavioural impact than on the Extra / Prime price, as can be anticipated by the literature. These teams have the next variety of observations and are typically extra statistically important.
Nevertheless, band 7 will not be statistically important in any matching strategy and has by far the bottom variety of handled observations of all of the bands within the Greater price group. The outcomes for this band are maybe decrease than anticipated provided that the outcomes for bands 4, 5 and 6 are bigger in magnitude however have a decrease stage of revenue.
The Greater price outcomes for these with incomes beneath £123,700 are extra intuitive and are typically growing with revenue. The magnitudes of the elasticities are affordable (decrease than the Extra / Prime price and better than the Stater, Fundamental and Intermediate charges) and offers proof of a restricted behavioural response.
Earnings band 4 is statistically important on the 1% stage throughout all matching strategies, with nearly equivalent coefficients. Band 4 has the most important variety of observations, with over 200,000 handled people, in comparison with solely roughly 24,000 in band 5, and eight,000 in band 7.
The elasticities are greater than these sometimes discovered within the literature. Analysis on TIEs not often appears to be like at coverage affecting people throughout this revenue bracket. For comparability, Gruber and Saez (2002) USA reforms throughout the Eighties estimate that people with revenue between $50,000 and $100,000 have elasticities starting from 0.106 to 0.265.
12.3 Starter, Fundamental and Intermediate Price Taxpayers
The 2018 to 2019 modifications break up the previous Scottish Fundamental price into three bands. Band 1 noticed their MRR improve by 1.25%, band 2 noticed no change, and band 3 noticed their MRR lower by 1.25%.
People with revenue beneath the Greater price threshold are thought to have restricted alternatives to interact in doubtlessly pricey tax avoidance exercise, and that tax incentives don’t affect the choice on how a lot to take part within the labour market.
Outcomes for band 1 usually are not statistically important. Nevertheless, outcomes for band 3 present a constructive behavioural impact that’s statistically important on the 1% stage throughout all three matching approaches.
This outcome implies that these in band 3 responded to greater tax charges by growing their taxable revenue. This result’s counter-intuitive and contradictory with the literature. To check for confounding elements we use band 2 to run a placebo check.
The propensity rating matching methodology is prolonged to this group utilizing the identical covariates. Since band 2 skilled no change to their marginal tax price, we count on this group to have the identical revenue progress as their matched management. The outcome on the proportion change in revenue from band 2 and band 3 are introduced within the desk beneath for comparability.
Desk 19: Placebo check for share change in revenue for band 2 in contrast with band 3.
Each bands report a statistically important improve in revenue progress relative to the management. This improve is larger in band 2 than in band 3 for all matching strategies. We conclude the presence of a confounding issue.
The Annual Survey of Hours and Earnings (ASHE) knowledge on public sector pay progress signifies that Scottish public sector employees had been awarded will increase in pay that had been greater than the UK as an entire similtaneously the rise in Earnings Tax. Determine 12 is produced by utilizing a Scottish Authorities publication that compares median gross weekly full-time earnings progress within the public sector from the ASHE knowledge.
Determine 12: Public sector median gross weekly full-time earnings progress.
Determine 12 exhibits a comparability of public sector earnings progress between 2012 and 2020. Scottish public sector earnings progress will increase from round 1.2% in 2012 as much as 3% in 2014, earlier than falling to lower than 0.5% in 2015. There’s then a common improve as much as 2018, reaching 3% as soon as extra earlier than falling in 2019 and growing once more in 2020. UK public sector earnings progress follows a unique sample to Scotland. It begins just under 2% in 2012 and falls progressively to 1% in 2014. There’s a rise in 2015, adopted by a fall to round 0.75% in 2016. There’s elevated earnings progress which is usually decrease than that of Scotland as much as 2019, as much as round 3% and falls beneath Scottish progress in 2020 to round 2.5%.
Modifications in public sector pay might clarify the divergence. Public sector employment will not be immediately observable within the knowledge. Nevertheless, a proxy for the general public sector utilizing info on sector is enough to check the idea. The next sectors are excluded from the handled and management teams: ‘Public Administration’, ‘Schooling’, and ‘Human Well being’. To substantiate confounding by public sector pay, the distinction must be nearer to zero.
Desk 20: Proportion change in revenue for band 3 excluding the general public sector.
We convert the outcome within the desk above to get the next vary of elasticities:
Desk 21: TIEs for revenue band 3 excluding the general public sector.
The elasticities inside this revenue band are a lot nearer to zero, and usually not statistically important. The check confirms Scottish taxpayer revenue grew at roughly the identical price as its matched management group in sectors not dominated by the general public sector.
We conclude that the distinction in public sector pay progress in Scotland confounds the outcomes for Intermediate price taxpayers. The share change in revenue is no longer statistically considerably completely different from zero, and damaging throughout two of the matching approaches.
These outcomes match a lot better with expectations that people inside this revenue band have nearly no behavioural results to tax modifications. This concurs with Gruber and Saez’s (2002) findings that people inside an analogous sized revenue band exhibit a small behavioural response. Of their paper, they discover an elasticity of taxable revenue between 0.18 and 0.28 for people with revenue between $10,000 and $50,000.
We due to this fact conclude that after accounting for the change in public sector pay, there’s little to no divergence in revenue progress between the 2 teams, and by inference no fall in taxable revenue because of the coverage throughout the Starter, Fundamental and Intermediate price bands.
13. Conclusion
Our paper has contributed to the literature by offering the primary insights into how Scottish taxpayers responded to the five-band coverage in 2018 to 2019. We took this distinctive alternative to analyse a pure experiment, evaluating Scottish taxpayers to a matched management group of comparable taxpayers from rUK, the place Earnings Tax charges remained the identical.
General, our outcomes had been broadly per the printed literature, offering some restricted proof of Scottish taxpayers decreasing their taxable revenue in response to growing tax charges. As anticipated, the dimensions of the behavioural response typically elevated with growing revenue ranges.
Our outcomes had been additionally comparatively secure beneath completely different methodological approaches. It’s value noting that our research excluded individuals who moved between Scotland and rUK, so the behaviour lined in our paper solely pertains to taxpayers who stay the place they’re and alter the quantity of revenue they declare in response to the coverage. It’s attainable that some taxpayers might as an alternative have moved between Scotland and rUK because of the coverage.
The behavioural results had been largest for taxpayers incomes over the rUK Extra price and Scottish Prime price threshold of £150,000. Our general elasticity for these taxpayers was akin to and considerably bigger than HMRC’s earlier 2012 estimate of 0.45, starting from 0.52 to 0.77 relying on the management group matching methodology used. This result’s extra in keeping with estimates produced by the IFS (2017) and Brewer et al. (2010).
Our estimates for every of the three revenue bands over £150,000 elevated with growing revenue ranges. The outcomes are a bit unstable for this group relying on the matching methodology used and that is possible because of the comparatively small numbers of taxpayers in these bands. With any analytical research, an estimate based mostly on a small inhabitants measurement will be extra prone to uncertainty and volatility. Our outcomes are broadly much like these present in USA research, and better than outcomes present in research from different international locations resembling Norway and Denmark.
For Scottish people with incomes above the 2018 to 2019 Scottish Greater price threshold of £43,431 and beneath £150,000, we discovered proof of a restricted behavioural response, smaller than for these incomes greater than £150,000. For essentially the most half, the behavioural results elevated with revenue (other than an unusually small outcome for incomes above the Private Allowance Taper between £123,701 and £150,000).
Our outcomes for Scottish taxpayers throughout the Scottish Greater price band had been considerably greater than these anticipated from the printed literature on TIEs. Analysis on TIEs tends to focus extra on greater revenue people, as it’s usually assumed that there can be little or no behaviour at decrease revenue ranges. Our outcomes had been a bit bigger than these present in earlier research of behaviour at comparable revenue ranges, starting from 0.12 to 0.46 in comparison with the 0.11 to 0.27 discovered by Gruber and Saez (2002).
We initially discovered some counterintuitive outcomes for Scottish taxpayers with taxable revenue beneath £43,431, the place they appeared to extend their taxable revenue relative to comparable taxpayers in rUK. Nevertheless, we discovered that this was largely pushed by proof of upper progress in public sector pay in Scotland relative to the UK as an entire. When a proxy for the general public sector was excluded, we discovered rather more intuitive outcomes, with little to no proof of any behavioural impact. That is in keeping with expectations from the literature.
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15. Annexes
15.1 Annex A – Data on inhabitants included inside Outcomes Part
The data inside Desk A1 exhibits figures for the variety of handled and untreated people used throughout the propensity rating matching strategy. These apply for the closest neighbour matching approaches.
Desk A1: Variety of people in every revenue band, handled and untreated for nearest neighbour matching.
15.2 Annex B
The figures beneath present the propensity scores earlier than and after matching for every revenue band with nearest neighbour one-to-one matching. On the left, the graph exhibits the density of propensity scores for the handled and management teams earlier than matching, the place we typically see that there are sizeable variations within the density of propensity scores. On the fitting we see important overlap between the handled and matched management teams.
Determine A1: Band 1.
Determine A2: Band 2.
Determine A3: Band 3.
Determine A4: Band 4.
Determine A5: Band 5.
Determine A6: Band 6.
Determine A7: Band 7.
Determine A8: Band 8.
Determine A9: Band 9.
Determine A10: Band 10.
15.3 Annex C – Different Specs
This part presents various strategies of matching and estimating propensity scores as a robustness examine to the primary analysis design. Column three exhibits the closest neighbour with substitute utilizing a probit mannequin to estimate propensity scores. Column 4 exhibits the closest neighbour with out substitute utilizing a logit mannequin to estimate propensity scores.
Desk A2: Outcomes from various specs.
Customary errors in parentheses. *** p < 0.01, ** p<0.05, * p<0.1
15.4 Annex D – Eradicating the Public Sector from Band 2 and Band 3
Desk A3: Proportion change in revenue excluding the general public sector.
Customary errors in parentheses. *** p < 0.01, ** p<0.05, * p<0.1
