SILC confirms the boom in labour income

A previous post looked at the increase in labour versus non-labour income in the CSO’s national accounts statistics.  This week the CSO published the 2017 update for the Survey on Income and Living Conditions and, perhaps unsurprisingly, the income patterns in this granular micro-data reflect what has already been reported in the aggregate macro-data.

Here is a table of weekly average household income since 2012.

The bottom line is that, in nominal terms, weekly net disposable household income is up €136 or 17 per cent since 2012.  And we have to go all the way up to the top to find the item contributing most to this: employee income.  Over the same period, average weekly employee income is up €148 or 27 per cent. 

The figures in the table are averaged across all households so will include households who have no employee income (such as retirees) who will bring the average down.  This can also be seen for “unemployment benefits” under social transfers. 

The average weekly amount here has fallen from €61 in 2012 to €39 in 2017. This is not because payment levels have been reduced but because the number of recipients has fallen.  Many households have moved to have zero in this category and this brings the average down.

But it is not the average, per se, that we are interested in, but the changes in them and we can see that employee income accounts for most of the improvement in household disposable income.

Proportionately, the largest increase has been for gains from self-employment which are up 83 per cent over the period.  The direct income item with the smallest proportionate increase for the period shown is “other”.  From the background notes the CSO tell us that this is:

Other direct income:

• Value of goods produced for own consumption
• Pension from individual private plans
• Income from rental of property or land
• Regular inter-household cash transfers received
• Interests, dividends, profit from capital investments in unincorporated business
• Income received by people aged under 16

This is where the non-labour income that was the focus of the previous post would show up.  The series in the SILC is a bit erratic.  Although it is up 20 per cent compared to 2012, it is actually down slightly compared to 2014 (and going back one year to 2011 would show a 50 per cent increase by 2017). 

Still there is little evidence of non-labour income such as interest, dividends, and most notably, rents outstripping labour income.  At an individual household level, there will be some who are seeing their housing costs rising faster than their income but in aggregate terms employee income is rising by a much greater amount than housing costs.

This table tries to scale up the average weekly amounts shown in the SILC to annual and national terms.  It is very crude.  The weekly amounts are annualised and then multiplied by an estimate of the number of households for each year (based off the 1.7 million figure from Census 2016).

In rough terms, it corresponds to what would expect given what is in the aggregate data. A key difference is that the SILC does not include the imputed rent of owner-occupiers as income.  Here is some work from Eurostat on the distributional impact of imputed rents in the SILC.

The scaled-up figures gave an increase in employee income of €15 billion over the period which is in line with what we have seen elsewhere (though maybe levels could be higher).  The amounts for “other” direct income scales up to between €2.0 billion and €2.5 billion each year. 

The boom is in labour income.

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The continuing remarkable improvement in Ireland’s Net International Investment Position

The Net International Investment Position (NIIP) of a country is the balance of external financial assets and liabilities.  In headline terms, Ireland is a huge debtor nation with a negative NIIP of around €420 billion, or around €90,000 for every person in the country. 

While this can put Ireland at the top (or maybe the bottom) of international tables two factors are worth noting: the impact of the IFSC and MNCs on Ireland’s data.  Both of these contribute significantly to Ireland’s NIIP position but these debts will not fall on the shoulders of Irish people so there inclusion in the €90,000 net debtor position is misleading. 

And if we strip them out we get an entirely different picture.  Here is Ireland’s NIIP excluding the IFSC and the non-financial corporate (NFC) sectors using all available data in the latest series.

It would be nice to see this series extended backwards but it is not a surprise to see that we had a debt position of around €100 billion at the start of 2012.  Since then the turnaround has been remarkable and we have moved to a net creditor position of almost €120 billion.  On a per capita basis we have €25,000 more external financial assets than external financial liabilities.

It could be that stripping out the entire non-financial sector omits some important information.  Stripping out the NFC sector does purge the data of the polluting impact of foreign-owned MNCs but the international position of domestic firms is excluded as well.  However, there is nothing to suggest it would alter the underlying pattern shown above.

It is worth looking at a sectoral breakdown of the above aggregate position.  There are four sectors included in the total shown above:

• General government (public debt)
• Monetary authority (central bank)
• Monetary financial institutions (banks)
• Financial intermediaries (pension and other investment funds)

Here is the contribution of each to the underlying NIIP shown above

The negative NIIP €130 billion for the government sector is unsurprising and, of course, is linked to the c.€200 billion of debt that the government has, and this NIIP position has been largely unchanged for the past few years.

On the other hand, financial intermediaries has seen a sustained improvement in their positive NIIP, rising from €100 billion at the start of 2012 to €200 billion in the latest data.  This largely reflects the value of private pension and investment funds of Irish households.  This increase will be the result of additional contributions but also revaluation effects, reflecting the rising value of various financial assets through the period.

The NIIP of monetary financial institutions has changed little over the period shown.  It was close to zero in 2012 and had edged up to around +€20 billion by the middle of this year.  One reason for this is that the chart excludes the chaos of the 2008 to 2010 period when the banks ran into huge problems and their external liabilities would have been bouncing around.

We know that during this period the banks repaid almost all of their external creditors and did so by drawing down huge amounts of central bank liquidity which reached up to €180 billion at one stage.  This improved the NIIP of the financial sector but merely transferred the external liabilities to the central bank, at least until the banks were able to repay the central bank liquidity they were using.

And this is can be seen.  At the start of 2012, the monetary authority (the Central Bank of Ireland) had a negative NIIP of around €100 billion.  This largely reflected a liability to the Eurosystem in respect of the liquidity provided to Irish banks to allow them to pay their creditors.

Since then, the banks have been reducing the size of their balance sheets but in terms of the NIIP this shows up through the position of the central bank rather than the banks themselves as they have been using the reduction in loans and increase in deposits to reduce their reliance on central bank liquidity, which in turn reduces the central bank’s liabilities to the Eurosystem.  This is the deleveraging we have been going through for the past decade or so.

And the net result is that, if we strip out the IFSC and MNCs, Ireland has a positive international investment position of almost €120 billion.  It has been a remarkable turnaround.

Of course, this aggregate does not reflect the distribution.  The biggest debtor is the general government sector which, in a sense, is all of us, while the biggest creditor are financial intermediaries which reflect the pension and investment savings of a much narrower subset of households.  And it is also the case that some of the improvement in the financial position has been brought about by the sale of real assets.  Still it’s much better to be talking about the distribution of assets than the burden of debt.

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Where’s the boom in non-labour earnings?

One of the most notable features of the Irish recovery in recent years has been the surge in employee earnings.  Compensation of employees received in the first half of 2018 was almost 12 per cent higher than in the equivalent period of 2008 (€40.4 billion to €45.2 billion).  The chart below shows this. It is in nominal terms though relative prices between 2008 and 2018 are not hugely different in overall terms.

But with labour earnings booming it is worth considering what has happened to non-labour income.  The institutional sector accounts allow us to do this. Here is a chart of property income as defined in the institutional sector accounts since 2005.

The pattern here is very different to the pattern shown in the first chart.  There has been no boom in property income and it remains below the levels seen in 2007 and 2008.

There have been some changes within the total.  Interest received is down 70 per cent since 2008.  The distributed income of corporations returned to its 2008 level in 2017 and has grown 70 per cent since 2013.  It would be useful to get a breakdown of the distributed income of corporations into actual dividends received (which is capital income) and withdrawals from quasi-corporations such as large partnerships (which has some links to employment).  The definitions of the investment income linked to insurance policies and pension entitlements is available here.

One thing to note is that the above chart does not include income earned by households as suppliers as services.  This will include the income of independent traders (the self-employed) and the income of households as a supplier of housing services (landlords).  The only rent included in the above chart is rent on natural resources or land.

To complete our look at earned income we must look at mixed income and gross operating surplus.  Mixed income is the income of the self-employed and the operating surplus of the household income is derived from the provision of housing services.

First, mixed income:

This is still way below the previous peak and is only rising slowly.  This is likely linked to the construction sector and the engagement of contractors.

Second, the gross operating surplus of the household sector:

OK, so maybe we have a boom in non-labour income after all.  This is the capital income households earn as suppliers of housing services after the deduction of costs for maintenance, repairs, utility charges and property taxes. 

One important consideration here is as most households own their own home it is an imputed income from the housing services they supply to themselves.  Money doesn’t actually change hands but it is the amount as if owner-occupier households were charging rent to themselves.  This imputed rent is based on market rents.

Of course, there are plenty of instances of those owning housing provided housing services to others and charging actual rents for the supply of these services.  It would be ideal if the gross operating surplus shown above was available for actual and imputed rents but it does not appear to be so.

The CSO do provide a measure of net rent of dwellings (i.e. after depreciation) that is divided into actual and imputed rents so this gives a reasonable idea of what has happened.  The net amount for 2017 is around €3.5 billion below the gross amount shown above which reflects the depreciation set against the capital assets.

We can see that since that imputed rents have contributed significantly to the increase in this item of capital income.  Actual rents received have also increased. 

In net terms, actual rents received for housing have increased from €1.8 billion in 2008 to €3.0 billion in 2018.  In fact, the share of actual rents in the above total has increased from 21 per cent in 2008 to 27 per cent in 2017.

An alternative way of looking at this is, rather than look at income, to look at the amount of rent included as consumption.  This is the aggregate amount of housing services consumed so is before the deduction of costs, charges and depreciation.

The aggregate amount of actual rents in household consumption expenditure has gone from €3.0 billion in 2008 to €4.5 billion in 2017.  It has gone from 19.5 per cent of household rental consumption to 24.5 per cent.

Anyway, the summary is that the boom in labour income has not been matched by a boom in non-labour income, dwelling rentals and in particular the imputed rentals of dwellings excepted.

Here is a table with the past five years of figures for the main items covered above with a further breakdown of employee compensation by the sectors who pay it.

Since 2013, there has been a €16 billion rise in compensation of employees received and a €3.5 billion rise in the imputed rentals of owner-occupier household to themselves.  The incomes of the self-employed (mixed income) have risen around €2 billion.  After that the changes become even smaller.

In percentage term, the distribution income of corporations paid to households is up 70 per cent and actual rentals paid by household are up 40 per cent though these make relatively small contributions to the overall change in the income of the household sector which has primarily been driven by employee, and to a lesser extent, self-employed income.

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The Distribution Impact of Budget Changes

After each budget the ESRI produce excellent analysis on the distributional impact of the announced measures on disposable income.  This tells us whether the budget is regressive or progressive.  The analysis published for Budget 2019 contains the following chart:

It is commonly used to infer the impact the budget had on disposable income.  This is not necessarily true.   The budget did not reduce the disposable income of all households as might be inferred from the above chart.

To understand this it should be noted that these losses shown above are relative to a benchmark scenario, in which welfare payments and tax bands and credits are indexed in line with wage growth.

The chart above shows whether households are better or worse off compared to this benchmark; not relative to their starting position.  In the ESRI benchmark scenario for Budget 2019, wages tax bands and credits and welfare payments are increased by 3.0 per cent.

Let’s try to set up some sample households to see the impact of this.

Example 1
Consider a household with an earned income of 30,000 (and no other income). Assume the single tax rate is 20 per cent and the tax credit is 3,000.

Pre-budget disposable income in 27,000. The benchmark scenario assumes a 3.0 per cent rise in wages and the tax credit. Thus income is assumed to rise to 30,900 and the tax credit becomes 3,090. Disposable income in the benchmark is 27,810 – a rise of 3.0 per cent.

If the budget does nothing to this household (by keeping the tax rate at 20% and the tax credit at 3,000) the distribution analysis will look at the impact of these (non)changes after the assumed 3.0 per cent increase in wages.

Thus, their assumed income of 30,900 will continue to be taxed at 20 per cent with the credit staying at 3,000.  Actual disposable income is expected to rise to 27,720 – a rise of 2.67 per cent

According to the distribution analysis the household is worse off by 0.33 per cent – and that’s even though the budget changed neither the tax rate nor the tax credit they get on their income.

Intuitively we would say the budget has no impact on them, but they are relatively worse off because tax credits did not increase in line with the increase in wages. A greater proportion of their income is now taxed.

The households "effective tax rate" has gone from 10.00 per cent to 10.29 per cent. This is called fiscal drag. They are said to be worse off even though the household disposable income has increased from 27,000 to 27,720. It would have increased to 27,810 if tax credits were increased in line with wage growth. The household are worse off relative to this benchmark by 0.32 per cent but in reality their disposable income has increased by 2.67 per cent (because of the expected wage growth).

Example 2
Consider a household who receive transfer income of 15,600 (and no other income). This one is more straightforward. The benchmark scenario assumes a 3.0 per cent increase in the transfer payment. So the benchmark is a disposable income of 16,068 – a rise of 3.0 per cent.

Let’s assume that the budget sees this family receive am increase in their transfer payments of 6 per week, i.e., an annual gain of 312. This means the household’s disposable income increases to 15,912 – a rise of 2.0 per cent.

According to the distribution analysis this household is worse off by 1.0 per cent – and that’s even though the budget increased their welfare payments by 312. Intuitively we would say that the budget has made them better off but they are relatively worse off because their welfare payment did not increase in line with the increase in wages.

The gap between this household on welfare and a household on wages is now greater (as wages are assumed to have increased by 3.0 per cent). They are said to be worse off even though their disposable income has increased from 15,600 to 15,912.

It should have increased to 16,068 if transfer payments were increased in line with wage growth. The household are worse off relative to this benchmark by 1.0 per cent but their disposable income has actually increased by 2.0 per cent (because of the increased transfer payment).

Distribution Analysis
If our economy is made up of just these two households and we have a budget that does nothing except increase the transfer payment to the household on welfare the distributional analysis where wages are expected to grow by 3.0 per cent is:

• Welfare Household: –1.00%
• Wage Household: -0.33%

The budget is regressive and everyone is worse off. Yet the only thing in the budget was an increase in the transfer payment. The budget gave income to the low-income household and did nothing to the high-income household yet is labelled regressive.

This is because the budget failed to offset the impact of the assumed 3.0 per cent increase in wages. It is because of this that the high-income household is relatively better off compared to the low-income household – not because of any changes in the budget.

Before the budget the high/low income ratio was 27,000/15,600 = 1.73. After the budget the ratio is 27,720/15,912 = 1.74 (based on the assumed increase in wages). 

Inequality has increased and we shout at the minister for introducing a regressive budget. The minister looks down at her notes and wonders what sort of eijits is she dealing with as she is after announcing a budget where the only change is an increase in transfer payments to the low-income household. How could that be regressive? It is regressive because income inequality in the economy has increased.

It is also possible that the same budget could be judged as progressive.  If we put in a wage increase of 1.5 per cent the conclusion changes – assumptions matter.  Here is the distribution impact for our simplified scenario with an assumed 1.5 per cent increase in wages.

• Welfare Household: +0.50%
• Wage Household: -0.17%

The same budget is now progressive.  This is because the income gap narrows.  The wage household is a little worse off because of the budget, again because tax credits were not increased in line with the expected wage growth (which this time is 1.50 per cent).  The “effective tax rate” goes from 10.00 per cent to 10.15 per cent.  The welfare household have gained because of the increase in the transfer payment and have gained even more relative to wage earners.

By working through the numbers it can be seen that the post-budget income ratio here is 27,360/15,912 = 1.72.  Income inequality has been reduced relative to the starting ratio (1.73).  So the same budget can be both regressive and progressive depending on what initial assumptions are put in.

This might seem like a massive complication of what should be a relatively simple concept – what impact did the budget have on household disposable income. However, a budget is not set in isolation. The impact of the dynamics of the economy (wage growth etc.) have to, or least should, be taken into account when the budget is being formulated so it is right that the impact of the budget is compared to some benchmark of what is expected to happen in the economy rather than the way it is now. We do not live a world where things are static.

This makes the analysis of the ESRI a bit more nuanced to interpret. The key thing we can take from it is whether a budget is regressive or progressive in terms of the income gap between households in a changing economy. Hence the simple contrived example above shows a regressive budget even though all the budget did was give a higher transfer payment to the low income household – it should have given them more to keep pace with the assumed 3.0 per cent growth in wages.

Budget 2019 did not make anybody worse off. Just looking at the measures introduced would show that. What the ESRI are saying is that inequality will increase if the assumed wage growth inputted to the analysis materialises. Hence the budget was regressive – or at least it was from decile three up to decile ten.

This does not mean inequality will rise in 2019. This is because the analysis by the ESRI is micro-based. So, yes, the micro analysis points to greater inequality as a result of government policy relative to a scenario where wages rise by 3.0 per cent.  However, the distributional analysis does not reflect macro factors such as employment growth which obviously has a large impact on inequality – and probably a greater one than the budget measures.

A continued increase in employment in 2019 will likely reduce inequality. A priori, the net effect on inequality between the offsetting micro and macro factors is impossible to determine.  For that we need something like the Survey on Incomes and Living Conditions. SILC 2017 is due to be published by the CSO next week.

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