Housing-related taxation receipts

In recent years, the summer period has become a boom time for those with an interest in the public finances. The past few weeks have seen a number of releases in the area including the Government’s Summer Economic Statement and IFAC’s Fiscal Assessment Report. The upcoming National Economic Dialogue will also spur debate in advance of Budget 2017.

With this in mind, readers might be interested in recent work published by myself and Kieran McQuinn (ESRI) in the Journal of European Real Estate Research examining the sustainable nature of housing related taxes in Ireland. Using a 3 pronged modelling approach we quantify the extent of housing related tax windfall gains and losses over a 30 year period as a result of disequilibrium in the housing market. We find that the fiscal position compatible with equilibrium in the housing market has at times diverged greatly from actual outturns both during the boom, the collapse and in the subsequent recovery.

The paper highlights the role played by the housing market in influencing the tax take and above all points to the need for a more granular approach to be taken in tax forecasting within Ireland. A link to the paper can be found here: http://www.emeraldinsight.com/doi/pdfplus/10.1108/JERER-01-2016-0004 with an older working paper version available here: http://www.esri.ie/publications/assessing-the-sustainable-nature-of-housing-related-taxation-receipts-the-case-of-ireland/.

Progressing at Euro 2016

Before Euro 2016 started, John Eakins and I discussed the probability of qualification from the group stages of the tournament given the conditions of the four team round-robin structure. We had previously examined this for Euro 2012. Euro 2016 is more complicated as four of the six third place teams will qualify for the last sixteen. John proceeded to present all possible group outcomes (there are 729 in total) and the probability of qualification associated with each number of points. For example, nine points obviously results in 100% chance of qualification, while one point will see a country occupy 4th spot almost 90% of the time.

Given Ireland’s results to date, we now know the team can achieve a maximum of 4 points from Group E. Assuming (probably naively) Ireland beat Italy, and given the team’s head-to-head record with Belgium, it will be impossible for the Irish to finish ahead of the Red Devils if they manage at least a draw with Sweden. Should Sweden win, Ireland can only finish ahead of the Swedes if they can outscore Zlatan and co. by three goals or more. While the chance of a second place finish is still possible, it’s highly improbable. Scoring goals hasn’t been Ireland’s forte. Wales have now scored twice as many goals at Euro Finals (in the past ten days) than Ireland have (since 1988!).

Much depends on the outcome of the other group games. Group A is finished, with Albania sitting 3rd on three points. Ireland can better this and must hope another group ends with a third place team on 3 points or less. Had England beaten Slovakia, Ireland would now know that a win against Italy would be enough to progress.

Two more chances are presented tonight. A German victory over Northern Ireland or a draw in the Turkey Czech Republic game, will ensure four points guarantees a place in the last sixteen. Are either of these outcomes likely? The econometricians might be able to help us here. In early June Goldman Sachs published The Econometrician’s Take on Euro 2016. Exhibit 2 presents their model’s predicted results in each group game. Germany are predicted to win 2-1 against Northern Ireland tonight. The Turkey Czech Republic game is predicted to finish 1-1. Either will suffice for Ireland.

A word of caution. The model fails to predict a single clean sheet for any country in any group game. Past results shows that roughly one-third of games end with at least one team failing to score. So far, the model has predicted 9 correct match outcomes from the 28 games. Just 5 games have finished in the predicted score line.

It shouldn’t be overly concerning that Ireland’s game with Italy is forecast to finish 1-1. Let’s hope the econometricians are off the mark again.

Geographic inequalities in higher education accessibility

Update: Now open for comments. (Novice error!)

As Leaving Certificate students take their seats this morning to start their final examinations, it is timely to consider how where they live (and often where they were born) can impact on a range of higher education decisions and outcomes and why these might matter for their futures. According to previous research, Ireland has reasonably good overall geographic accessibility to higher education institutions (HEIs) in terms of travel distance, though there are large areas from which an individual would have to travel, say, 75kms or more to their nearest HEI. These areas tend to be more rural with relatively low population densities and with a finite number of HEIs some inequality in access is of course inevitable.

But not all HEIs are the same. If we distinguish by type of HEI, then the pattern of geographic inequality is very different. In particular, if we consider distance to nearest university as another measure of accessibility, then geographic accessibility inequalities are much more pronounced, with relatively poor access in much of the south-east, south-west, west, north-west and along the border.

Such inequalities matter for a number of reasons, particularly in terms of the impact of geographic accessibility on whether school leavers progress to higher education and, if they do so, where and what they choose to study. Indeed, this is the focus of an on-going programme of research I am conducting jointly with Darragh Flannery (UL) and Sharon Walsh (NUI Galway). For example, this paper showed that greater travel distances were associated with lower participation rates for school leavers from lower social classes, all else equal. It also highlighted how these distance effects resulted in differential higher education participation rates across social classes and that the effects of distance were most pronounced for lower-ability students from poorer backgrounds.

Importantly, distance also matters for where and what students study, suggesting possible inefficiencies in matching students to courses. For example, a separate piece of work found that geographic accessibility plays an important role in determining outcomes relating to HEI type, degree level and field of study, with students living further from a university much more likely to study at an institute of technology (IT), all else equal. The paper argues that these decisions are important in terms of future labour market outcomes such as employment rates and earnings for school leavers.

The pursuit of equity in access to higher education is claimed to be central to education policy in Ireland. Although much of the focus has been on narrowing the social class differential in participation, spatial factors are now finally being acknowledged as a potential barrier to access.  In a consultation paper on the development of a National Plan for Equity of Access to Higher Education 2015-2019, the Higher Education Authority highlighted the strong geographic dimension to higher education participation.

At present, one of the main policy responses to address inequities in access is the ‘student grant scheme’, which includes maintenance grants, fee grants and postgraduate contributions. The maintenance grant scheme is a contribution towards a student’s living costs and eligibility is based on meeting certain criteria based on parental income levels and means, as well as travel distance from a student’s chosen HEI.  Thus, the grant system explicitly acknowledges the potential impact that travel distance can have on higher education related decisions.  The current grant eligibility limit for the so-called adjacent (partial) grant is 45kms or less (up from 24kms in 2012), while the non-adjacent (full) grant applies to those living more than 45kms from the approved institution.  Thus, two otherwise comparable students, one living 50kms from her chosen institution, the other living 250kms away, would receive the same financial aid.

The results from our studies suggest that consideration should be given to establishing a more flexible or stepwise higher education grant system, with progressively higher payments for those living further away. As it currently stands with a single distance cut-off of 45kms, the maintenance grant system does not take into account that significantly longer travel times could have important implications for students in terms of financial costs, but also in terms of their available time to engage in paid employment to perhaps support their studies. Of course, any revised system would need to be carefully designed in order to avoid unnecessary transaction costs, as well as imposing perverse incentives for students to travel further than necessary.

Finally, one area of current policy likely to impact on geographic accessibility is the proposed consolidations in the Irish higher education sector, with a number of ITs to be possibly amalgamated into new technological universities. In a paper published last week, we used a variety of techniques and measures to consider the effects of the proposed re-structuring on both the level of, and inequalities in, geographic accessibility to university education.  Overall we found that the north-west and areas of the west, south-west and border are poorly serviced in terms of absolute and relative accessibility to university education both pre- and post-policy reform.  These areas consistently remain in the bottom quintile of each measure of accessibility considered, implying that the impact of the reforms for those regions will be negligible.  On a more positive note, we did find that the percentage of the 17-19 year old cohort (a good proxy for the population of school leavers) who live more than 100kms to their nearest university would fall from 14.5% to 7.9% post-reform.  However, the same analysis showed that there would remain a significant minority living more than 150kms from a university.  Overall we concluded that “the reform will do little to remove geographical impediments to university participation for those that are most disadvantaged [currently] from a spatial standpoint.”  This assertion is also supported by the inequality analysis, which shows little improvement in overall geographic inequality in university accessibility across Ireland as a result of the consolidation reform.

So, as Leaving Certificate students take their seats today, it is worth stressing that the choice set facing many of them in terms of their higher education opportunities is very much a function of where they live. For resource-constrained students in particular, the distance impediment is not adequately addressed through current policies. Unfortunately, changes to the grant system rarely feature in the debate around the financing of higher education. Any move to an alternative financing system would provide an ideal opportunity to address this issue.

Sports Economics Workshop

The 2nd sportseconomics.org Workshop will be held on Friday 22nd of July 2016 at University College Cork. The purpose of this workshop is to discuss and stimulate interdisciplinary research ideas from those working in the areas of economics, sport, coaching, public health, management, and related fields from Ireland and abroad.

The keynote address will be delivered by Rodney Fort, Professor of Sport Management at the University of Michigan.

Other confirmed presenters include Professor Rob Simmons, University of Lancaster and Professor Paul Downward, Loughborough University.

The workshop is free and those interested in attending should register here. The full programme will be available shortly.

This event is kindly funded by the Irish Research Council Government of Ireland “New Foundations” Scheme.

Mortgage term as a credit condition

The aim of this post is to introduce the topic of mortgage term to maturity in an Irish setting. I will outline how mortgage terms were highly pro-cyclical during the pre-2008 expansion, and that they were used by credit-hungry borrowers to make high-leverage strategies more affordable on a monthly basis. It is well established that credit conditions, as measured by Loan to Value ratios (LTV), Loan to Income ratios (LTI) and Debt Service Ratios (DSR, ratio of monthly repayments to net income) reached unsustainable levels in Ireland in the run-up to the 2008 crash.[1]  By contrast terms have received much less attention. Previous work by McCarthy and McQuinn (2013) on Irish credit conditions is the only piece known to me which contains an analysis of mortgage terms. They show that median terms increased rapidly in the 2000-2008 period, and did not decrease after the housing market crash. Further, they show that terms were higher for First Time Buyers, and that longer terms are correlated with an easing in other credit conditions. Today’s post concerns recent analysis carried out by my colleague Edward Gaffney which looks at the distribution of mortgage terms for loans originated between 1997 and 2014.

Why should mortgage terms be of interest to us? Firstly, they can have a huge impact on mortgage affordability. Identical loans, for identical houses, to people with identical incomes, at identical interest rates, can have widely varying monthly repayments driven by varying terms. As a simple example, a loan for €250,000 at an annual rate of 4.5 per cent has a monthly repayment of €1,581 when taken out over 20 years, which falls to €1,183 when that loan is extended to 35 years. A saving not to be sniffed at!

Secondly, they appear to have associations with risk-taking behaviour. Research from Central Bank colleagues[2] has shown that, controlling for a range of factors associated with higher credit risk, mortgages with longer terms are more likely to default, even though a longer term allows for a lower monthly mortgage repayment, all else equal!

Finally, terms also have a big impact on banks’ profitability, as longer term loans will have higher lifetime interest income for the bank. Further, longer terms allow banks to make larger loans while continuing to respect any Debt Service to Income rules that may be in place.

So what can we say about mortgage terms in Ireland? In all that follows, I will focus on the First Time Buyer (FTB) segment of the mortgage market. Our first figure (Fig 1) provides clear evidence from Edward’s work that mortgage terms lengthened significantly during the boom phase in Ireland. Of the 1997 cohort still outstanding in 2014, 60 per cent were originated with terms of 20 years or less, with 90 per cent having terms under 25 years. At the turn of the millennium, the 35 year mortgage was close to non-existent. However, its proliferation through the period of rapid credit growth was quite remarkable, moving to a market share of roughly 50 per cent by 2006-07, with a further 5 per cent of the market taking terms between 35 and 40 years.

While Kelly, McCann and O’Toole (2015) report that credit conditions tightened considerably in the aftermath of the financial crisis, Edward’s chart shows that “credit tightening” in mortgage terms has been much less stark, with 60 per cent of mortgages originated in 2014 still having terms above 30 years.

Fig 1: The distribution of originated mortgage terms per year, First Time Buyer segment 1997 to 2014.

term_line

This evidence of a structural shift towards longer terms begs a number of questions relating to the role of term as a credit condition. Figure 2a from Edward’s work provides conclusive evidence that, during the boom phase, longer terms were associated with higher leverage. In 2007, those taking out 40 year mortgages had an average LTV of over 90, with LTVs of 85, 72, 60 and 50 as we move in five-yearly intervals down to 20 year mortgages. While these LTVs have converged since the crisis, the rank ordering persists. Figure 2b completes the picture by showing that borrowers on different terms have in fact been accessing similarly valued houses, which implies of course that those with longer terms were taking out larger average loans. Taken together, these figures strongly suggest that term was being used by FTBs to mount the property ladder at as high a point as possible for a given down-payment amount, using higher originating LTVs to access valuable housing with small down-payments and large loans, while easing the monthly repayment burden of this high-leverage strategy via longer terms.

Figure 2: Average LTV and property value for mortgages originating at different terms.

(a)    LTV (b)   Average Property Value
 term_ltv  term_val

Our next piece of evidence links borrowers’ incomes to mortgage terms. Figure 3 reports clear differences in originating Loan to Income ratios (LTI) across term groups. Those on 40 year mortgages in 2007 were accessing loans with an average LTI of 5, while the equivalent number was under 3 for those with 20 year mortgages, again providing strong evidence that mortgage terms were used as part of a broad “credit conditions package” by credit-hungry borrowers. Figure 3(b) confirms that this highly-indebted strategy was in fact more common among high-income borrowers in the run-up to 2008, with median incomes falling as terms shorten. The one exception to this rule is the 40-year mortgage, which appears to have been popular among lower-income households with extremely high LTIs during its short existence.

Figure 3: Average LTI and income for mortgages originating at different terms.

(a)    Loan to Income ratios (b)   Incomes (median)
 term_lti  term_inc

So where did this “credit condition package” leave borrowers on a monthly basis? It is unclear from the above whether long terms acted to offset the affordability difficulties brought on by high-leverage strategies. To do this, Edward calculates a monthly repayment to gross income (RTI) ratio for each loan in the data, applying an indicative opening interest rate. The evidence is conclusive: despite the fact that longer terms mechanically improve mortgage affordability by lowering repayments all other things equal, it was still the case up to 2008 that borrowers with longer terms were taking out such large loans that their RTIs were in fact higher than borrowers with shorter terms. This is likely part of the explanation for the finding of Kelly, O’Malley and O’Toole (2015) that longer-term mortgages have higher default probabilities, even after controlling for a range of explanatory factors.

More posts on the mortgage market in Ireland to follow over the coming months.

[1] McCarthy and McQuinn (2013) and Kelly, McCann and O’Toole (2015)

[2] Kelly, O’Malley and O’Toole (2015)