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Starter Home Deposit Loan Scheme - Chief Statistician - Transcript - 18 February 2013

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Corporate Services Scrutiny Panel Starter Home Deposit Loan Scheme Review Hearing with the Chief Statistician

MONDAY, 18th FEBRUARY 2013

Panel:

Senator S.C. Ferguson (Chairman)

Deputy J.G. Reed of St. Ouen (Vice Chairman) Deputy S. Power of St. Brelade

Deputy R.J. Rondel of St. Helier

Witnesses:

Dr. D. Gibaut (Chief Statistician) Ms. K. Falle (Statistical Officer)

[10:01]

Deputy J.G. Reed of St. Ouen (Vice Chairman):

I welcome our members of the public and the media to our hearing. I am sure you are aware of the code of behaviour expected from members of the public and we hope you abide by them. A general welcome as well to Duncan and Katie. It is great to have you with us and we are thankful for you giving us the time to be able to discuss some of the matters around the statistics that are being used to support the starter home deposit loan scheme. I would like to offer the apologies of the Constable of Grouville , Dan Murphy, who is one of our panel members. Unfortunately, he is unable to be with us this morning. Without further ado, I would like to just very briefly go round the

table and we can all introduce ourselves and then we can start.

The Deputy of St. Ouen :

Right, Duncan, we would like to start looking at the development of the proposals and your involvement in providing some of the information that is being used to base the scheme upon. Can you please explain what advice and information you have been asked to provide during the development of this particular deposit loan scheme?

Chief Statistician:

Certainly. The proposition is clearly based on a great deal of information that the Statistics Unit has published over the last year or so, and continues to publish actually, on the housing market in Jersey. So at its simplest level, we publish the quarterly house price index, and clearly that is one of the pieces of information that goes into the proposition. Above the house price index a great deal of analysis was done to look at housing affordability in Jersey by comparing house prices and flat prices, each property type actually, with household income, and not just for the latest year or so but looking back over the last decade or so. So a publication we produced this time last year and we are going to be updating and producing again in the next month or so,  Housing Affordability, again was the second major piece of information that clearly went into the proposition looking at house prices versus household income. There was also, you might recall, an income distribution survey we did in 2009/10, which we can obviously upgrade with earnings indices, which gives us the distribution of income of households in Jersey, overall households but also, and crucially for this proposition, by household type and structure. By that I mean looking at single person households, looking at households with children, couples with children or single parents with children, and also crucially for working households. So the income distribution survey is again a very rich source of information that we can analyse further into the affordability analysis using the house price index, which clearly has all been taken on board into this proposition. So that is all publicly available information, which we have talked to Members about over the last year or so - quarterly for the house price index - we talked to officers from the various departments, whether it be Chief Minister's Department or from scrutiny, we talked to the media about house prices and affordability indices. All that is publicly available. What is not publicly available but clearly does underpin this proposition is some further analysis we were asked to do by officers of the Chief Minister's Department, which I think you have copies of and is summarised on page 4 of P.131, whereby we looked at the potential effect of the States deposit loan scheme on various household types trying to purchase various household property types. That is a 15 per cent deposit; how does that change the affordability of a one-bedroom flat or a 2-bedroom flat and so on for different household types? So that table there on page 4 of the proposition is actually a summary of some analysis that we have done and were asked to do in the Statistics Unit to look at the effect of such a deposit scheme potentially giving access to households of a particular type at the lower quartile of dwelling prices. So this is a summary, this table and this table, of information that is all publicly available and with some further analysis that we were asked to do by the Chief Minister's Department.

The Deputy of St. Ouen :

Sorry, you have clearly said that there are a number of different areas where you gather information from, and clearly there is a wide range of information available. I think that we would like to better understand this further analysis and what particular work you have done - apart from the analysis of figures relative to that table 4 - to support some of the comments and information that is contained in the report.

Chief Statistician:

Well, firstly, I would like to say straight off the bat we do not do analysis to support anybody's proposition. I neither support nor oppose propositions. As a statistician, I am in a very privileged and, to be honest, very easy position of being completely impartial and completely objective. If the information supports a proposition, that is up to the writer of the proposition. If the information is in opposition to a proposition, that is up to the opposers. But as statisticians we sit in an unbiased, impartial position. So I would just like to say that and that applies not just to this but to everything that we do, actually. I think your question is: how good is this information in terms of how it has been used? Well, as I said, underpinning the analysis is the information that goes into the house price index. That is actually very good information that we gather quarterly from every transaction that goes through in the residential property market in Jersey. It is not a sample. I have seen it many times over the years being described by various people as a sample of the property market in Jersey. It is not a sample. It is a census. It is every single freehold and flying freehold that goes through the Royal Court. It is every single share transfer that goes through. We put all that information ... we gather it up each quarter, we being my colleague to my right, and it is incredibly rich. It is a census and it means we can slice and dice it. By that I mean we can look at one- bedroom flats, whether they be share transfers or not, 2-bedroom flats, share transfers or not, 2, 3 and 4-bedroom houses. We do exclude a small number of properties; for example, 3 or more bedroom flats. Very few of those go through and they tend to be non-representative. They tend to be very much upscale type developments. We also do exclude multi-property transactions; for example, a farm dwelling where there may be a main house with several other buildings. So we stick very much to the core residential property market, the one and 2-bed flats and the 2, 3 and 4- bed houses, and we collect the information on all of those properties in terms of their transaction price. So the information underpinning all of these analyses is actually very rich.

Deputy R.J. Rondel:

Just to clarify, on the representing the upper limit of the lower quartile range of properties, a 3- bedroom home you have stated would be about £410,000.

Yes.

Deputy R.J. Rondel:

How reliable is that? Are there any properties that have passed through that may need a large amount spending on them because they are in a dilapidated state?

Chief Statistician:

Clearly, there will be. Now, if I could just say what that means, actually; probably I should have said what is the upper limit of the lower quartile. Basically from the house price index information we get all property. So if we are looking at 3-bedroom houses, we get of order 100 or so every quarter that goes through, and there is a distribution. Of that distribution of prices there is a mean, which people think of as the standard average: add up all the prices, divide it by the number of properties. There is also the median, which is another descriptor used to indicate an average value, and the median is conceptually more straightforward. The median is the middle value property. You line them all up; the median has half above, half below. The lower quartile is the 25th percentile. So if you line everything up from zero to 50 per cent to 100 per cent in terms of their order of pricing, the lower quartile upper limit is the 25th percentile. So by definition 25 per cent of 3-bedroom houses have been transacted at or below the lower quartile. Now, within there, clearly there is going to be a range of property conditions, let us say, and also locations. So there may well be some perhaps properties that do need some work, but clearly there are going to be properties that very much people can just move into straight away. Now, we do some statistical analysis that does allow for and account for, actually, the effect of very, very low property prices but also, and importantly, accounts for very, very high property prices. So we see, for example, the mean average price of a 3-bedroom house over the last few years was above half a million pounds and has come down to slightly below half a million pounds. To get that measure of the mean, we do a statistical technique called winsorisation. Now, where you have a distribution you can top and tail. You can chop the ends off. That is quite a blunt thing to do because you are not actually acknowledging that there was perhaps a transaction of a 3-bedroom house at a million pounds and another transaction of a 3-bedroom house at £150,000. You can exclude those. What winsorisation does is actually take those prices, acknowledge that they were there, those houses, and pull them into the 95th or 90th percentile or the 5th or the 10th percentile. Instead of having several houses out at a million pounds, they get pulled into the 95th percentile, which might be three-quarters of a million, where there is more information.

Deputy S. Power: More data.

Absolutely. The same at the bottom end. At the bottom end, with Deputy Rondel saying: "What if there are some dilapidated properties?" we do see the bottom end of the distribution. Four hundred, 300, there is not much below about a quarter of a million, below 250, of 3-bedroom properties, but every now and again we do see some. So we winsorise, we pull them in. Through doing this - there is a great deal of academic work that goes into that - you basically get a mean that is more robust. By that I mean it is more comparable quarter to quarter to be less sensitive to things in the long tail at the high end or things in the short tail at the low end. So we do acknowledge them, we do see them, but there are not many. But there is by definition a quarter of the whole distribution of 3-bedroom properties or a quarter of any distribution is below the lower quartile.

Deputy R.J. Rondel:

So are you saying that £410,000 is a reliable figure?

Chief Statistician:

Yes, very much, with probably an uncertainty of between £10,000 and £20,000 on there, probably closer to £10,000. So even though it is a census, there will be a statistical uncertainty, but the £410,000 is actually a very good measure of the lower quartile price, as is the mean, as is the median of what they are trying to describe.

Deputy R.J. Rondel:

Okay, but would you accept that if we were building 3-bedroom homes on an open site for first time buyers, for example, that that figure would probably be low?

[10:15]

Chief Statistician:

That is the upper end of the lower quartile. To put it into context, I think we need to go to the housing affordability report, where we actually did analysis not just for the affordability of houses of whatever type to all households in Jersey, but potentially for potential first-time buyers to have access, we call it, at the lower quartile and particularly of first-time buyers who are working and with a working person below age 39. For example, on page 5 of the affordability analysis - and the affordability analysis is, again, extremely rich - the house price index is your base line. The affordability analysis takes those distributions of house and dwelling prices, couples them to earnings distributions and household types, and then looks at what proportion of households particularly cannot access at the lower quartile. Now, it is quite a detailed ... well, it is a very detailed report, but on pages 5 and 6 is basically all you need if you just want a quick cheat sheet.

Five and 6 tells you the headlines and on the bottom of page 5, for example, if you do not mind me reading, in terms of access analysis: "The percentage of young working households - who are potentially your first-time buyers - who could not afford to purchase a starter home at the lower quartile price" actually reduced by more than a third in 2010 to less than a quarter in 2011, but in 2011 ... sorry, I am jumping around a little bit here. A better statistic to answer the Deputy 's question would be that in 2011 more than two-fifths of all working households could not service a mortgage affordably on the purchase price of a property at the lower quartile price, and that is what I was saying was a slight reduction on 2010. So in 2011 more than two-fifths - so that is between 40 per cent and 50 per cent - of working households could not service a mortgage affordably with specifically defined criteria on a lower quartile price. So putting that into context of your question - is £410,000 low or high? - not for me to say, but what I can say is that more than two-fifths of all households could not service a property affordably on a lower quartile price in 2011.

Deputy S. Power:

So the implication from that, Duncan, is that if that statement of bold fact based on the lower figure that you are talking about is the case in 2011, on Richard's interpretation that that figure may be slightly low the situation is actually worse? If one were to go with what Richard is saying, not what you are actually ... you are giving us a snapshot of a statistical analysis of the situation on the Jersey housing affordability index, so at the moment 40 per cent of those cannot afford to buy a house in that £410,000 ...

Chief Statistician:

At the lower quartile prices.

Deputy S. Power:

... at the lower quartile. The question Richard asked, the situation could theoretically be worse than that?

Chief Statistician:

Yes, it probably would be because this is the lower quartile price of all property types, whereas Deputy Rondel was asking about the 3-bedroom properties. So, in principle, it would be worse than that, yes. It would be.

Senator S.C. Ferguson:

When were you actually brought in to provide the sort of statistical background for the proposition?

Gosh, that is a good, tough question. It has always been there. We publish quarterly. We publish annually the affordability measure. We published in late 2012 the housing needs survey, which is very much complementary and does and should inform what went into the proposition. That has always essentially been there. When we actually got asked to do the additional analysis which was summarised into the table in the proposition I would say would be some time in the third, possibly the fourth quarter. Fourth quarter?

Statistical Officer:

I was thinking fourth ...

Chief Statistician:

Fourth quarter of 2012. So it was ... yes, it was. It was the fourth quarter of 2012 because we had a certain amount of house price information available up to a certain quarter and then to make it completely up to date basically we left it ... or we used the most up-to-date information. Yes, thank you for reminding me. It was fourth quarter of 2012 we were asked to do this additional analysis.

Statistical Officer:

I think we started discussing it in the third quarter and then ...

Senator S.C. Ferguson:

The information that was extracted to put in the proposition, are you as a statistician happy with the way your figures have been treated?

Chief Statistician:

It is certainly one way to do it. [Laughter]

Senator S.C. Ferguson:

Is there any significant difference between the figures in the proposition and the figures that you provided?

Chief Statistician:

There is one significant difference, yes. Basically, all the figures in that proposition, in that table, in 3 of the columns are essentially our figures. What is not the Statistics Unit's figures but is derived from them is the minimum income needed. So what we provided to the Chief Minister's Department, the officers thereof, is the detailed spreadsheet that you all have and the questions that we were answering was what households of certain types of certain incomes would be facilitated by this 15 per cent deposit scheme to have access at the lower quartile. So the analysis

that we could do basically gave you a range of incomes. So, for example, if we look at one- bedroom flats, if I just talk you through - and I think it is worth talking through just so we know what is going through this table - one-bedroom flats, lower quartile dwelling price was £171,000. There were almost 70 properties going through in the 4 quarters up until we did this analysis, 66 properties, the 15 per cent deposit value of the £171,000. Now, what we have then is the income distribution survey showing us the incomes of singles and couples with no children. There are about 14,000 households from our census of singles and couples, non-pensioners, with no children, about 14,000 households. Well, before the deposit of 15 per cent is applied, but assuming the affordability criteria that we do into our calculations of these households having a 5 per cent deposit and earnings of a certain level such that at a particular interest rate their mortgage interest payments are no more than 30 per cent of their gross income - so that is the affordability calculations that we do that go into this from the affordability analysis - then from that analysis 2,800 households of this particular type could not afford a one-bedroom flat at the lower quartile price. That is almost 3,000 out of 14,000 households existing in Jersey. With the States deposit proposition scheme adding another 15 per cent that has to be paid back over the term of the mortgage - so we have to factor that into the affordability calculations - we then come up with a number that slightly less than 2,000 such households could not afford a one-bedroom flat at the lower quartile price. So the improvement, that is the reduction in the number of households who could not afford such a property, well, it was 2,800, it went down to about 2,000, so it is between 800 and 900 - 859 sounds very precious but between 800 and 900 [Laughter] - households potentially could have access. The next question is which income band - the income that we collected from the income distribution survey, et cetera, and from the other surveys that we have - which band of incomes are we facilitating? Where do these extra 800 or 900 households come from? Well, they come from the household income band of £29,000 to £34,000. That is our numbers; ours being the Statistics Unit. The proposition then translated that income band into £32,000; that is roughly the middle of that. So potentially of the 800 to 900, if it was spread linearly, uniformly, through that income band, by taking a value in the middle you are potentially assisting half of that 800 or 900. That is one thing, so that number is actually derived from officers to whom we gave this. The second thing to point out, and it is also a very important point, I think, is that these are potential numbers of households who in principle would be assisted by such a scheme. It does not actually tell you how many would actually want to move. This is clearly an in principle upper limit. The question as to how many would actually want to move would require further analysis with respect to what we have in the housing needs survey, where there are sections in there looking at, again, potential first-time buyers. In the housing needs survey, which I have somewhere ... we called it housing assessment because "needs" can be slightly an emotive word. So housing assessment looks at supply and demand and does subtractions and looks at, in principle, shortfalls and surpluses. This is again a very rich complementary analysis. Before I delve into that, is that okay so far in terms of I think the question was how happy I am with ...

Senator S.C. Ferguson:

Are the figures that are in the proposition directly reconcilable with your figures?

Chief Statistician:

Yes, they are. That is one way of doing it.

Senator S.C. Ferguson:

I am not asking you for a political opinion from a statistician.

Deputy S. Power:

She means do you think that they are robust.

Chief Statistician:

In principle, you could do that. We have given an income band of potential households that could be assisted. The proposition developers have actually taken a value in the middle of that income band. They could have taken the lower end, the higher end or something in between.

The Deputy of St. Ouen :

I just have one question before we move on regarding the house price index. You said it is very good information, you capture all properties that are sold.

Chief Statistician: Yes.

The Deputy of St. Ouen :

You say that you can separate different groups from share transfer or not. Where do we find that information or is that something that you do not publish?

Chief Statistician:

We do publish it in the house price index report, which unfortunately I did not bring the latest version along.

Senator S.C. Ferguson:

How do you get the share transfer price?

Chief Statistician:

We get it from the land transaction tax information that came in in 2010 or so from income tax. We have taken the income tax oath, so I can go down and we can collect the share transfer information. In particular, obviously as you know it is mostly one and 2-bedroom flats that actually go through share transfer, what share transfers are mostly relevant for, and so in the house price index for each of the last few years, actually, we have reported on the numbers of share transfer properties that have gone through. Clearly, that proportion has increased quite markedly in the last 2 years. Up until 2009/2010 we saw slightly below half of the flats were share transfers. The other half were flying freeholds. In 2011 and 2012 we have seen almost three-quarters of all flats going through as share transfers and the proportion of one-bedroom flats is actually greater still. In the latest year, the proportion of one-bedroom flats that went through as share transfers was 79 per cent; almost four-fifths of all one-bedroom flats were share transfers and roughly two-thirds of the 2-bedroom flats were share transfers. Overall, roughly almost three-quarters of flats are going through as share transfers in each of the last 2 years.

The Deputy of St. Ouen :

Just following up that, how often do you collect this information?

Chief Statistician: We collect it quarterly.

The Deputy of St. Ouen :

Quarterly, so would it be possible for us to see or for you to be able to provide that information or publish that information on a quarterly basis?

Chief Statistician:

We do. It is in our house price index.

The Deputy of St. Ouen :

The house price index is published quarterly?

Chief Statistician:

Quarterly, yes. We have one coming out on Wednesday.

The Deputy of St. Ouen :

Just to be absolutely clear, not only do you capture those properties that sold by share transfer but you identify whether they are one-bedroom, 2-bedroom or 3-bedroom properties?

Chief Statistician:

Yes, that is crucial to us. Underpinning the house price index we want property type and size. By type I mean house or flat and by size number of bedrooms. So we get that for every property that goes through and that allows us to do the analysis of affordability of one-bedroom flats, like I say, for working households or all households.

The Deputy of St. Ouen :

Does the analysis include capturing those sales in value terms, in bands? In other words, for argument's sake, if it is one-bedroom flats, let us say, you capture the lowest price as - let us call it - £130,000, so you could have £130,000 to £200,000 as one band, £200,000 to £250,000 or £260,000 another band and so on and so forth. Is that the sort of information that you provide in the house index?

[10:30]

Chief Statistician:

What we actually collect is the actual discrete price, the data point. So if a price of a flat went through for £139,999.99, that is what we get.

The Deputy of St. Ouen : So every sale is published?

Chief Statistician:

Every sale is published. Then, of course, at the back of the house price index reports we have started putting in the distributions to show that the mean is a single statistic trying to describe a distribution of prices, 3-bedroom properties we talked about in terms of quarter of a million to half a million to more than a million, a distribution of prices. The mean is a single statistic. The median is another single statistic and the lower quartile is another single statistic. But what is really informative is actually to look at the distributions from one year to the previous year to see how distributions particularly have shifted or may not have shifted with respect to each other over the years. The 3-bedroom houses, we clearly have seen a shift downward. Mean price was £510,000 to £520,000; median price slightly below £500,000. Both of those measures of the average have decreased in the last 2 to 3 years and if you look at the distributions both of those distributions have decreased towards the lower values.

The Deputy of St. Ouen :

One last question, just sticking on the information that you are capturing, you were just talking about 3-bedroom houses. We know that there are category (a) and category (b) housing and there is a significant difference between a first-time buyer home that is quite likely to fall into the £410,000 to £440,000 price range, and the very attractive granite-built 3-bedroom home that you might find in a private development in a rural environment. Can you or are you able to identify the value of category (a) properties separately from category (b)?

Chief Statistician:

Sorry for my ignorance on a Monday morning. Help me with the difference between category (a) and category (b).

The Deputy of St. Ouen : First-time buyer homes.

Chief Statistician:

Yes, so the first-time buyer homes, yes, we do identify and separate out from the full, let us say, distribution of open market properties that we publish. Once a year, though, and particularly in every Q4 for the last few years and in the report that is coming out later this week, actually, we do a separate analysis on first-time buyer properties. We do not publish first-time buyer properties in every quarterly bulletin or every quarterly report because they tend to be coming through a few 10s and then nothing and then a 10 and then nothing. So we publish first-time buyer information as an appendix in every fourth quarter of the house price index, and what we have seen ... and we have been doing that for the last ... gosh, I have been doing it for the last 10 or 11 years or so ... and we publish houses and flats separately for the first-time buyer properties. The first-time buyer mean price of houses was above £200,000 or so at the start of the last decade and became over £400,000 a few years ago and has been consistently between about £410,000-£430,000 for a first- time buyer house for the last 3 to 4 years or so.

Deputy R.J. Rondel:

How do you define first-time buyer?

Chief Statistician:

We see developments and we check with planning and housing departments are these properties actually designated as first-time buyer. It is not us defining it. It is actually us checking with the departments that these are the designated properties. These are designated for first-time buyer schemes as opposed to a person buying a house in Jersey for the first time. The properties that we have are the designated first-time buyer properties.

Deputy R.J. Rondel:

That tracks resales as well?

That tracks resales as well. So what we have in there, absolutely, we see, for example, the flats. When we see Woodville Apartments or waterfront flats coming on from several years ago and they would come on in a few 10s in each quarter, and then we see resales of these, and in some years we see very few, if any, new ones coming through. So that is why we do not publish this information quarterly. We publish it annually and we also name the developments that are actually contributing to. Not every single property that goes through but certainly if a chunk of 10 or 20 come through we will name that in the table; if there are a fair few resales of a certain property development, again. So that is all in the appendices of the fourth quarter of the house price index.

Deputy R.J. Rondel:

Which will be out later this week?

Chief Statistician:

Yes, it is going to be out on Wednesday/Thursday midnight. I will send it to all States Members on Wednesday before lunchtime.

Deputy S. Power:

I wish we could guarantee you that they would all read it. [Laughter] Can I ask a couple of questions here on this?

The Deputy of St. Ouen : Absolutely, sure.

Deputy S. Power:

It is absolutely vital for us to understand, and you have explained it extremely well, that the house price index is a rolling census of activity in the residential property market. So as such it is not a sample, it is not a date, it is an actual census, it is an actual snapshot of all residential activity sales in the market and thus accurate. It has been doing the same database, the same approach, for quite a number of years.

Chief Statistician:

Since 2001, 2002, actually.

Deputy S. Power:

Yes. That is important and we appreciate that. Therefore, you made a very interesting point there and somebody who was with us last week, Peter Seymour of The Mortgage Shop, said the same thing in a different way. The market has changed; the activity levels have changed completely.

Whereas traditionally the market was over 50 per cent, you said, 3-bedroom houses in that area, now two-thirds, 65-66 per cent, are one and 2-bedroom flats.

Chief Statistician:

No, what has actually changed, the numbers that I quoted, the two-thirds were share transfers of the 2-bedroom flats. The actual turnover ...

Deputy S. Power:

In the total market, yes.

Chief Statistician:

Yes, the actual turnover in the total market, 3-bedroom properties are still the dominant property type. They have come down from what was about 50 per cent of the residential property market 10 years or so ago to somewhat closer to 40 per cent. So I do not have the weights. I perhaps should have brought the house price index with me, but the proportion of flats has clearly increased in the last 5 years or so.

Deputy S. Power:

That is a direct correlation of supply? It has to be.

Chief Statistician:

Clearly, yes. Well, for example, the proportion of share transfer flats going up from what was 40 per cent a few years ago towards 50 per cent in 2010 to three-quarters in 2011 and 2012 is clearly an issue of supply of these particular property types. We adjust our weights when we do the calculation to reflect the greater turnover of the flats relative to the houses.

Deputy S. Power:

Just to develop supply, supply would mean to me - and hopefully you will agree or disagree - the creation of that product, that is the one or 2-bedroom flat. The new build is what we are looking at in the marketplace ...

Chief Statistician: Yes.

Deputy S. Power:

... whereas the counterargument might be that we are not seeing such a similar level of activity in the traditional 3-bedroom housing market.

I think that is a very fair summary, actually. We are seeing overall the turnover has reduced by about a sixth or so in the last few years relative to where we were before 2008, before the global economic downturn and obviously the effects it had locally. We saw turnover come down initially by almost a third. It has recovered slightly to about a sixth to a fifth below where we were, but we have seen an increased turnover of flats relative to the houses. So the housing turnover has somewhat declined, whereas the flats turnover has somewhat increased. Clearly, what has been the driving factor in there is the greater availability of the share transfer properties and particularly that has had effects and ramifications for affordability. Analysis that we looked at the affordability of Jersey property over the last decade or so ... and by affordability I mean look at the distributions of the property prices, look at the distributions of earnings, factor in interest rates and household income, do it in a statistically robust, scientific way. We can see that affordability improved marginally in 2011 compared to 2010 and that improvement was because of the availability of the lower priced share transfer properties coming on to the market. So there was a slight improvement in affordability even though our headline was between 2002 and 2011 a working household with mean net income - so think of average income - was not able to service a mortgage affordably on a purchase price of a median-priced house of any size through the last 10 years. So houses were unaffordable to the average working household throughout the last 10 years, but a working household was able to service a mortgage affordably on a median-priced one-bedroom flat over the period and on a 2-bedroom flat for some of the period, particularly from 2009 to 2011, again with share transfer properties coming in, and also some stagnation in prices, but not during 2006 to 2008. But clearly this increased supply or availability of share transfer properties of below £200,000, particularly for one-bedroom flats, did improve the measures of affordability that we saw.

Deputy S. Power:

That is also significant because if one were to state that in a difficult market, in difficult times of recession and a difficult housing market, residential market, with the whole scenario of the mortgage availability thing, that is an even more significant statistic in some ways because had that product not been on the market, the market would have been less active. Would you say that is the case?

Chief Statistician:

Not really for me to say. That is getting more into the economics of things, but in principle the product was there and it was transacting.

Deputy S. Power:

Yes, and it has taken a significant part of the overall level of activity as per your housing price index.

Chief Statistician:

It has and as statisticians we have to change the weights, the effect that these properties go into the overall house price index ... the house price index is a great big pot into which we put everything. More interestingly, I think, are the individual property types, but you want a single measure that is your headline measure, which is the house price index. We can only do that by putting in flats of each type or houses of each type with a certain weight and you have constant weights for a period so that you are not susceptible to fluctuations. However, as the fluctuations over an n-year period suggest that there are more flats transacting than houses, then you have to change the weights, and that is what we have done.

Deputy S. Power:

The value of your reliability of the housing price index is because you have had to adjust the weighting because the market has changed?

Chief Statistician:

Yes, clearly the distribution in particular, if I could direct you to looking at the one-bedroom flats in any house price index over the last year or so or the last 2 years, you can see significant numbers of properties coming in below £200,000, which is driven by your share transfer one bedrooms.

Deputy S. Power:

Almost dominated. You said 79 per cent.

Chief Statistician: Yes, absolutely.

The Deputy of St. Ouen :

Just sticking with property transactions for the minute, what proportion of property transactions can be attributed to non-locals purchasing buy-to-let properties?

Chief Statistician:

The second part of that statement I do not know the purposes for which non-locals ... well, firstly, we have to define what a non-local is. Is it a non-local under employment law, under housing law? Is it what is a (j) category? Is it by person ...

The Deputy of St. Ouen :

Well, I would suggest that a non-local would have to be under the housing category because otherwise anyone that is under the employment category would not be able to necessarily purchase a home unless they were a (j) cat, obviously, an essential employee. What I am trying to identify are people that do not reside in the Island purchasing property to let.

Chief Statistician:

That is incredibly hard for us to assess. One statistic that may help you, (j) categories are locally qualified under housing law and we have looked over the years at proportions of purchasers by (j) category type households of the freehold and flying freehold market. I looked at it several times between the mid-2000s to the mid to late 2000s and it was consistently about 5 to 6 per cent of the residential property market, of freehold and flying freehold, were purchased by (j) categories. I must admit I have not looked at it more recently. It is an incredibly difficult and quite subjective thing to do. It means going to all sorts of population office type information so I have not looked at it for a few years, but when we last did it was about and had been 5 to 6 per cent of the freehold and flying freehold, i.e. not including the share transfers, was purchased by (j) category type households.

The Deputy of St. Ouen :

Why I asked the question is that I was reading February's edition of the Business Brief and in it there was an article written by I think it was the managing director of Skipton International. They make specific comments that the market has been buoyant with regards to the buy-to-let group of individuals that are purchasing property to let. We are well aware that non-locals, people who do not reside on the Island, live elsewhere, are able to purchase property to let.

[10:45]

We are wondering whether or not, first of all, the Minister for Treasury and Resources or other people had asked you ever to identify what impact this may have on affordability and availability of homes for the local residents and, furthermore, the sort of numbers that might be included in that particular category.

Chief Statistician:

It is a jolly good question. No, we have not been asked and it is awfully hard to do. One would have to look at particularly the addresses, I guess, of the purchasers and then make assumptions: are these locals or non-locals? One can have an address that is off-Island but still be a local perhaps returning. One might be purchasing to come and live in Jersey or one might be purchasing as a buy to let. Incredibly subjective, hard to get the information to start with, but we have not done that. We have not been asked to do that and I would say that that would be terribly difficult to do and it would have to involve all sorts of subjective type assumptions even if we had the information, i.e. are these people non-local, i.e. non-Jersey born or non-(j) cat, and why are they purchasing this property? That is not something really the Statistics Unit would get into.

Senator S.C. Ferguson:

It is relatively easy with the share transfer properties to get a feel.

Chief Statistician:

In principle it could be, yes.

The Deputy of St. Ouen :

Are you aware of any other department doing that sort of work?

Chief Statistician:

I am not, but the information is clearly held by the Treasury Department and the information at some level will be informed by the Population Office.

Senator S.C. Ferguson:

I did actually do some work on that a couple of years ago.

Deputy R.J. Rondel:

What information do you have in respect of the supply and demand for housing? Would you have information?

Chief Statistician:

We have a great deal of information. It is the complementary analysis. Everything we have talked about so far has been to do with house prices and distributions and income and distributions and affordability. Another major piece of work that we actually do every 3 years for the last ... since 2000 was the first one - so we did one in 2000, 2004, 2007 ... whatever last year was, 2012, thank you - was the housing needs survey. We reported on it at the end of last year, called it Jersey's housing assessment. This actually goes right to the heart of looking at supply and demand. From a statistical sense, what we do is we have run very large standalone surveys in 2000, 2004 and 2007 where we are asking people: "What are your intentions over the next 3 years - or 5 years in some of the earlier analyses or earlier reports - in terms of moving? Are you intending to move? If so, where to? Into what type of tenure, what type of property, house, flat, size, or off-Island?" From all of that information that we have gathered, which has been very, very rich, we produced these periodic reports every 3 or 4 years or so. Just to point out supply for us is defined as a

household moving from their current dwelling into another dwelling. It is not supply that is coming on stream in terms of being built or approved by planning or developed or anything. It is purely supply by households moving or also properties opening up through death or care. So we look at and do a great deal of analysis in terms of looking at households where perhaps over the next few years what is the statistical probability, what statistical numbers would we expect from households becoming vacant due to occupiers either dying or moving into care. So, all of that constitutes supply, as does also outward migrants, people leaving. So, in this analysis, which I can just point you to - gosh, you are ahead of me already - we do look at different types of supply and it is outlined on page 4 of the latest report: existing households means those are moving, they existed as a whole in a household somewhere in Jersey and are moving somewhere else in Jersey, households leaving and death and care. So that is the supply side of our analysis. The demand side of our analysis is, again, from those existing households. If they are moving in Jersey, they are moving from somewhere, a supply, and demand somewhere else. An important category is concealed households. This is potentially households who are at the moment latent, hidden within an existing household but intending or hoping to move. Perhaps it might be ...

Deputy S. Power: Sofa surfers.

Chief Statistician:

... for example, households newly established, newly forming households, and also in-migrant households, households coming in. So we have on one side supply, one side demand, and we can look at where people are living in terms of their type and size of property and their tenure, owner occupied, social rental, private rental or non-qualified, and do a great big subtraction of these tables.

Deputy R.J. Rondel:

On page 7, is that the conclusion of your supply and demand breakdowns?

Chief Statistician:

Yes, that is the supply and demand breakdowns, absolutely. If I could just head you through, at that stage we are doing it by type and size, which is interesting but it hides really important and much richer features which become apparent from tenure. So the type and size is conceptually the way into this analysis because it is just conceptually simpler, but if you actually do it by tenure and you start in particular looking at ... for example, type and size will give you very large shortfalls of one-bedroom properties but most of those are going to be of a certain tenure. So what you want to do is look at the tenure analysis. So we then repeat on pages 9 and 10 the supply and demand by type and size and tenure. It is again a very rich analysis that we have actually matured

over the years, and the first headline table in this report is table 6 on page 11. Table 6 on page 11 gives you the supply minus demand by tenure.

Deputy S. Power:

That is the difference between the supply table of 10,500 and the demand of 11,980?

Chief Statistician:

Exactly. So what you see from this are anything in brackets is a potential shortfall. This is if everybody's aspirations and intentions came through and the fluid jigsaw did actually take place over the next 3 years. What you would end up with is a potential shortfall of more than 1,000 owner-occupied properties mostly in the 2 and 3-bedroom type properties, a potential shortfall of 400 or more than 400 social housing properties. Now, both of those numbers are different to what we had seen in previous rounds of this survey. The owner occupier shortfall was greater in each of the previous 3 rounds of the survey and the social housing shortfall, there essentially was not a social housing shortfall. This is the first time we have seen through this survey this social housing potential shortfall of this scale.

Deputy R.J. Rondel:

Do you know how that figure relates to the present housing needs figure?

Chief Statistician:

The housing waiting list?

Deputy R.J. Rondel:

Yes, the gateway waiting list.

Chief Statistician:

Yes, that is considerably lower than the housing waiting list. The housing waiting list is about 800, but in principle one could imagine that it would be lower than the housing waiting list because what we have in this survey asked people is are you intending to move and, if so, where to. So they get a choice, if they are moving from social housing into owner occupation or private rental into owner occupation, whereas, of course, the housing waiting list you can perhaps be in private rental and be aspiring to buy. That might be your first choice which we pick up, but you may also sign on the housing waiting list. So you get a second choice and also the non ...

Deputy S. Power:

There is some duplication in the housing ...

Absolutely. So in terms of the demand on social housing, it would probably be somewhere between our 400 and their 800. But that is the first major table to look through and I can only stress look at it by tenure because that is where you get the stories coming through.

Deputy R.J. Rondel:

So we see a minimum shortfall of 1,500?

Chief Statistician: Yes, however ...

Senator S.C. Ferguson: But is that not aspirational?

Chief Statistician:

Absolutely, absolutely. Now, we have tried very hard, and that is why we focus on 3 years, are you intending to move, not do you have a wish to move or anything, but are you really intending to move, but it is still obviously at some level aspirational. So what we can now do for the first time in this analysis is couple it to the affordability analysis that my colleague Katie has developed over the last 2 years and actually apply affordability criteria on people's aspirations. Because not only do we have the methodology, the statistical methodology to do it, but also in the survey we collected the required information. We collected household income and we collected household deposits, potential deposits. So from both of those additional pieces of information we can apply Katie's affordability analysis on people's intentions to move, and if we do that from table 6, applying realistic affordability criteria, you jump to table 10 on page 19. So table 6, much as we could ask people: "Are you intending to move, really intending to move?" that still has not factored in affordability. The minute you put on realistic affordability criteria you end up with table 10. Essentially, your owner-occupied shortfall overall drops to almost nothing, although there are still potential shortfalls of one and 2-bed flats of order 300, a potential surplus of almost 300 4- bedroom properties, and almost breakeven on 3 bed. So, again, it is very important to look at it by tenure, which you are doing here, and also by size. So the overall owner-occupied shortfall is very small with realistic affordability criteria, and there are, nevertheless, shortfalls of one and 2- bedroom properties and a surplus of 4 bedroom. That is in owner occupation. In social housing there is a slightly greater shortfall.

Deputy S. Power: It hardly changes.

It hardly changes, absolutely. Most of the driver for owner occupation is coming from ... if you look on page 12 at figure 5, that tells you where most of the demand or where the demand is coming for  owner occupation. Almost  three-fifths is coming from people  who are already in owner occupation, which can be people perhaps wishing to upscale from one and 2-bedroom properties to 3 or 4; wishing to downsize from perhaps where the concealed households have left the nest so perhaps wanting to downsize; also potentially and importantly perhaps owner occupiers of current share  transfer  properties  wanting  to  upscale.   So,  overall,  three-fifths  of  the  owner-occupier demand is from current owner occupiers, but a very small proportion, only 3 per cent of the demand, is social housing. Hence, as Deputy Power said, if you put affordability criteria on, the social housing shortfall does not ...

Deputy S. Power: It stays constant.

Chief Statistician:

It stays very similar, yes, absolutely, whereas private rental goes from what was a surplus of more than 100 to a shortfall of more than 100 because the private rental there is more than 1,000, i.e. a quarter of the demand for owner occupied households is from private rental. If you put affordability criteria on, then these people, these households, wanting to move into owner occupier now cannot so they stay in a private rental and there is more demand in the private rental also from non- qualified.

Deputy S. Power:

The situation is actually quite serious.

Chief Statistician:

There is a lot going on in this report, yes.

Deputy S. Power:

Well, if you just look at the affordability, it means that irrespective of the tests you apply to the demand excess over supply, it means that the social housing demand there is actually rock solid. That is those are 450 units of accommodation. It is not just one bed, 2 bed or 3 bed and 4 bed, it is actually that is what is needed now.

Chief Statistician:

Absolutely. Could I just show you something else, Deputy Power, before I ...

Deputy S. Power:

Can I just clarify on the demand also the concealed figure? The concealed figure also must ... I cannot use the word "must", but would you not consider that also the concealed figure must or should ... I will start again. The concealed figure has to include multigenerational families?

Chief Statistician:

Yes, it does and there is a whole section, we call it first-time buyers, that unpicks the potential first- time buyers. Are they concealed households or existing households? Certainly, a large proportion are concealed households which may be multigenerational. It may be under 30 year-olds fleeing the nest to purchase. So again I ...

Deputy R.J. Rondel:

Having to stay at home because they do not have that opportunity, they are stuck.

Chief Statistician:

If I could direct you to section 6 of this ... thank you for the opportunity to let me point you to these things. Section 6 really does impact very much and inform, I should say, on the demand of potential first-time buyers. What is the size of it? What is their current tenure? Are they concealed or existing? Very interestingly, also figures 11 and 12 give us the earnings and the deposit available of such potential first-time buyer households. Again, section 6, although it is only 3 pages, is incredibly rich, I think. Also, Deputy Power, if it is all right, the affordability measures, which are the official affordability measures that we produce in terms of looking at prices and income and interest rates and deposits and mortgage interest payments, but you can also get a very quick feel for affordability or lack of affordability by looking at a ratio analysis.

[11:00]

The ratio analysis is much simpler where you just look at house prices, whether it be mean, median or what have you, against earnings. In appendix C on page 28 it is an absolutely horrendous plot but I was pedantic and insisted that it goes in.

Deputy S. Power: Crikey.

Chief Statistician:

Well, if I talk you through it, it is all right. If I talk you through it, I think it is okay. What we are doing with ratios is looking at multipliers. So, for example, on the right-hand side here we are looking at only owner occupiers. You have ratios of 4, 6 and 8. Traditionally, banks in the U.K.

(United Kingdom) and Jersey were ratios of about 4, things crept up towards 6-7 in the boom years and have now changed, clearly. Clearly, the affordability measure is the proper way to do it, but if you just want a quick feel for what is going on, at a ratio of 4 you basically have a surplus of more than 700 owner-occupied properties. That is basically saying if you apply ratios of 4 there is no shortfall. In fact, you have a big surplus. Apply ratios of 6, you still have a surplus. You are above this line here. It is only when you get to ratios of 8 you get small shortfalls. So that is telling you in very much a complementary and a quicker, more accessible way than the truly detailed analysis that if you apply affordability criteria essentially there is no shortfall until you get to very large multipliers. Then Deputy Power's comments about the social housing being rock solid at more than 400 shortfall, i.e. independent of any affordability criteria which he suggested from that table, that is what that line there tells you. Whether it is a ratio of 4, 6 or 8 ...

Deputy S. Power: It is a flat line.

Chief Statistician:

Yes, these are not your customers for owner occupation. These are people that ... this is actually a shortfall of social housing.

Deputy S. Power:

These are people that will never buy. These are people that will always need to have a form of social rented.

Chief Statistician:

Yes, absolutely. What is also quite interesting, I think, is the reason it gets overly complicated, we have actually done this not just with 3 ratios for each tenure but for 3 different migration scenarios. So we have done it for net nil, where the big inflows equal the big outflows. We have done it for current trends, which is actually 700 people per year coming in more than leaving, i.e. more than 300 households coming in per year, and we have done it for an intermediate number. What you can see is that over the short term for this survey, which is the next 3 years, net migration has very little effect on owner occupation, social housing or private rental, i.e. on the qualified tenures, which is what you would expect. These are brand new people coming in in the next 3 years.

Deputy R.J. Rondel:

What about natural births to deaths?

Chief Statistician:

That would also ... well, bear with me, in what sense?

Deputy R.J. Rondel:

Yes, that is a figure ... there are more births than deaths obviously, so surely that figure should be included in this, or not?

Chief Statistician:

Not necessarily. In terms of the numbers of people ...

Deputy S. Power: This is just 3 years.

Chief Statistician:

Yes, this is just 3 years. If you want the change in the population, you have to add ... the current trend is 700-plus of order 300 births and deaths.

The Deputy of St. Ouen : Natural growth.

Chief Statistician:

Natural growth. This is just looking at households coming in who could potentially impact on the housing market. Over the next 3 years the new migrants, yes, there will be some (j) cat type pressure but generally quite small, but the new migrants tend not to affect the qualified tenures but clearly do affect the non-qualified tenures, what goes from current trends of potential large shortfalls to breakeven at intermediate to net nil. So there is a lot going on in that plot but I think what it does back up ...

Deputy S. Power:

What it means, looking at the current migration levels, if that were to be kept at its current level of net inward migration, it is going to cause another problem in the non-qualified and private rental sector very quickly, judging by the bar between 2 and 450, it looks like.

Chief Statistician:

It can do, and also bear in mind that there was a large inflow during the mid-2000s, 2004 through 2008, through E.U. (European Union) accession, enlargement, et cetera. Those households would be qualifying generally after the period of this survey. So perhaps there will be greater pressure on the qualified tenures through the inward migrants that came in in the mid-2000s. So, although the short-term migrants do not affect the shortfalls or surpluses in the qualified tenures over the period of the survey, if one factors in the greater flows coming in in the mid-2000s it will have an impact and we will potentially see that in the next round of this survey. We are clearly seeing it at some level from non-qualified households saying that they will be qualifying and wanting to go into the owner-occupied sector in the next 3 years, so that will be 2015. The next round of this will pick up the waves that came in in 2005 through 2008 and so we will be intending to run this if not next year perhaps the year after. We tended to run it every 3 to 4 years, this survey.

Deputy S. Power:

So to put this in context, if I could just jump to a point that is fresh in my head, having looked at this mass of information that you have here, incredible stuff, looking at the deposit scheme amount which has been proposed of £3 million and if one were to look at the gateway, the eligibility that Senator Ozouf is suggesting, somewhere between £22,000 to £50,000 as a deposit figure, if the average deposits were £30,000 we might get 100 assisted mortgages. If it was £40,000 we might get 75 and if it were £50,000 we might get 60. The point is this is going to have absolutely little or no effect on what you have just shown us apart from possibly accelerating the sale of flats.

Chief Statistician:

Clearly, it will have an effect for those households that do get into the scheme. That is obviously life-changing type assistance. Bear in mind the numbers that we have on this additional analysis where we are looking at potential 900 households being assisted, we do have to ...

Deputy S. Power: Being eligible.

Chief Statistician:

... couple that with ... yes. Well, firstly desire and eligibility, yes.

Deputy S. Power:

Desire and eligibility, the 2 together.

Chief Statistician:

Yes, absolutely. Now, we have not done that ...

Deputy S. Power:

So of a pool of 900 this will affect no more than 10 per cent of that 900 maximum?

Chief Statistician:

Sounds like it from the numbers you just quoted.

Deputy S. Power:

Well, if it is £3 million and you do any kind of multiplication on it, it is going to be under 100 assisted mortgages on a pool of 900. Would you in your expert area as having analysed the house price index and activity and the weightings that have changed or the weightings you have had to put on it because of change, it would appear that given the market activity levels it could be construed or it looks like this will not change patterns in the market at the moment. So a lot of these deposit assistance could go towards one or 2-bedroom flats.

Chief Statistician:

That is where the properties clearly are of that lower quartile. If one takes the lower quartile distribution of all property types, I do not know the details of the scheme, whether or not an assistance would be for a particular property type I do not know, but if one gives an assistance and then the household in question has then access or can buy any property type, then clearly at the lower quartile it is mostly one and 2-bedroom flats.

Deputy S. Power:

That is likely what is going to happen. That is the trend.

Chief Statistician: Yes.

Deputy S. Power:

Trends do not buck overnight, particularly with a small scheme like this.

Chief Statistician:

It is not just the trend; it is just that is where the properties are.

Deputy S. Power:

That is where the activity is.

Chief Statistician:

The population of that lower quartile is one and 2-bedroom flats.

Deputy S. Power:

Yes, so that is not going to buck the trend. Sorry, Vice-Chairman, I just wanted to jump in on that.

The Deputy of St. Ouen :

Yes, I am looking at the time and I am well aware we have overrun. I would just like to ask one last question. How do we reconcile the fact that we are told that 900 households could potentially stand to benefit from this scheme, and yet in table 8, page 17, under section 5, affordability, we are told that there are roughly 3,000 people who are planning to purchase in the owner-occupier sector with a mortgage and another 1,000 people that are planning to buy without a mortgage?

Chief Statistician:

Sorry, Deputy , I am struggling as to which table.

The Deputy of St. Ouen : This is the ...

Chief Statistician:

Oh, housing assessment, sorry, yes. Which page is that, Deputy ?

The Deputy of St. Ouen : Page 17.

Chief Statistician: Yes, I am with you.

The Deputy of St. Ouen :

I want to reconcile those 2 figures because here we have approximately 4,000 people who have said, we are told, that they are planning to purchase in the owner-occupier sector with or without a mortgage over a 3-year period. Yet we are told that there are 900 people that could potentially stand to benefit from the starter homes deposit scheme. How can I reconcile those 2 separate but very different numbers?

Chief Statistician:

Well, one would have to unpick who these people are buying without a mortgage. In principle, again we put this information out there and it is not just something to say: "Here is a fait accompli, off you go". We want people to come to us and ask questions. There is a very good question: who are these 800 or so existing, 1,000 households with the concealed, who are buying without a mortgage? I do not know. We have the information to try to unpick that. What is the overlap of this 1,000 with this 900? I do not know. We would have to look at their incomes, for example, their deposits available, for example. We have all that information. What is the level of overlap between that 900 and this 1,000 is a jolly good question. We have not done that analysis, it is only basically you have brought it up to me, but in principle it could be done.

The Deputy of St. Ouen :

How difficult and how long would it take you to do that analysis?

Chief Statistician:

I think it could be looked at this week, actually.

The Deputy of St. Ouen :

Because why I ask the question is that first of all it seems that if you want to understand who you want to help with this new scheme it is the sort of question that should have been asked perhaps and, more importantly, it would be useful to understand that issue.

Chief Statistician:

Very much. I think also the complementary question is: what is the demand, what is the desire of such 900? This is the potential maximum statistical estimate of the households which in principle would be assisted by this scheme. Put the actual desire to move, I think we can at least explore the data that we have to see what proportion of that actually wish to move and, secondly, Deputy Reed's question as to what proportion of these would then be buying without a mortgage as well.

The Deputy of St. Ouen : You could reconcile it?

Chief Statistician:

It may take more than a week. Yes, we have a few things going on this week, actually. It might be more a month or so, maybe 2 weeks might be pushing it. A month sounds a bit more realistic.

The Deputy of St. Ouen :

Obviously, we are on a time constraint regarding our review. It would be useful if you could give us some overview, an indication of how these 2 interact, even if you do not produce the fully detailed information that necessarily goes with it.

Chief Statistician:

I still think maybe in 2 weeks we could have is it negligible overlap or is it a large population.

The Deputy of St. Ouen : That would be good.

Deputy R.J. Rondel:

Yes, that would be very useful.

Chief Statistician:

A month would be a more definitive number; 2 weeks we could have a look perhaps. I am not getting kicked under the table [Laughter] so I take it that is a yes. My shin bone is still intact.

The Deputy of St. Ouen :

We would be grateful if you were able to do that for us. On that note, thank you very much, Duncan and Katie, for joining us. As I say, I am sorry we have overrun, but it is certainly a very interesting subject and it is certainly something that we want to get a greater understanding on. It is likely that we will have further contact with you in the coming weeks ...

Chief Statistician: Absolutely, please do.

The Deputy of St. Ouen :

... as we explore this matter further. Thank you very much. I thank the members of the public and media for joining us and I declare the meeting closed. Thank you.

Chief Statistician: Thank you.

[11:13]