REINZ has released their January 2020 residential report today, and they reported the busiest January in 4 years. The annual average rise across New Zealand was 7%, with Auckland at 4.4% and other areas up 9.1%. Auckland is actually now among the faster-rising regions. Prices in Canterbury are rising, although to date this has been slower than many other regions.
In January the median number of days to sell a property nationally decreased by 6 days from 48 to 42 when compared to January 2019 – the lowest days to sell for the month of January in 3 years.
Low interest rates and lighter regulation are driving the market. Over 2019, the RBNZ cut the OCR from 1.75 percent to 1 percent and they indicate that the OCR will remain at 1 percent for some time. In response, household debt continues to rise. Lower debt servicing costs enables higher household spending on consumption, although returns from savings will be lower as well.
Over the past year New Zealand construction activity has ramped up substantially while net migration has steadily declined. The cancellation of earlier plans to introduce a capital gains tax has also helped to drive the market.
For New Zealand excluding Auckland, the number of properties sold increased by 0.9% when compared to the same time last year (from 3,279 to 3,308) – also the highest for the month of January in 4 years.
In Auckland, the number of properties sold in January increased by 9.7% year-on-year (from 1,180 to 1,295) – the highest number of residential properties sold in the month of January since January 2016.
Sales in Auckland were the highest for the month of January in four years, with particularly strong uplifts in sales volumes in North Shore City (+29.0%), Waitakere City (+28.6%) and Rodney District (+21.1%).
Regions outside Auckland with the highest percentage increase in annual sales volumes during January were: • Nelson: +42.6% (from 54 to 77 – 23 more houses) • Manawatu/Wanganui: +15.3% (from 281 to 324 – 43 more houses) – the highest for the month of January in 3 years • Bay of Plenty: +11.5% (from 340 to 379 – 39 more houses) – the highest for the month of January in 4 years • Marlborough: +11.3% (from 62 to 69 – 7 more houses). Regions with the largest decrease in annual sales volumes during January were: • Tasman: -29.3% (from 58 to 41 – 17 fewer houses) – the lowest since January 2017 • Southland: -27.2% (from 151 to 110 – 41 fewer houses) – the lowest for the month of January in 6 years • Otago: -17.1% (from 269 to 223 – 46 fewer houses) – the lowest for the month of January in 9 years.
In the recent Reserve Bank NZ Monetary Policy Statement, they indicated that over the medium term, annual house price inflation is expected to slow as net immigration moderates, residential construction activity remains high, and the effects of past lower mortgage rates fade.
However, they expect residential investment growth is expected to pick up over the next six months, in line with recent high levels of residential building consent issuance. That said, residential investment is forecast to decline very gradually as a share of GDP later in the projection period, reflecting ongoing capacity constraints in the construction sector.
In December 2019, the Government announced a substantial investment package of $12bn, equivalent to around 4 percent of annual nominal GDP. The Treasury forecasts that $8.1bn will be spent between June 2020 and June 2024, mainly on infrastructure projects
Which is probably just as well, given that business investment is forecast to fall ahead.
We discuss our submission to the Senate Inquiry into funding for the SME sector. The proposed bill will provide incentives for the big banks, but do little to address the real issues. We offer an alternative approach, using data from our SME surveys.
We are pleased to offer our submission for consideration.
The Bill as proposed will do little to address the underlying SME funding
issues we have in Australia, despite benefitting the incumbent major investors
through their equity shares. It might play well from a “we are doing something
for SME’s” perspective, but in reality, it will do little.
To address the real problem of SME funding, we recommend
a FinTech style structure, as already proven in the UK and elsewhere across
Europe. This would enable the allocated funds to reach more businesses, but
more importantly also facilitate a transformation of lending to the SME sector
in Australia, including driving incumbents to lift their game.
This transformational play would demonstrate the
Governments active support for the SME sector, but also lead to broader and
deeper change, to the benefit of the local economy.
Introduction
Digital Finance Analytics is a boutique research and
advisory firm which curates a rolling 52,000 firm survey each year, with ~4,000
new firms added each month. The survey is a telephone omnibus and is executed
on our behalf by a reputable service bureau. It is statistically accurate
across the country.
We design the questions, and analyse the results using our
Core Market Model. The survey has seen running for more than 15 years. We have
several clients who subscribe to our data services, as well as those to receive
copies of the free summaries. Clients include several financial services
companies, FinTechs and Government agencies, within Australia and beyond.
We hold information about their business structure, banking
relationships and financial profile, as well as their digital behaviour. This
provides a multi-factorial basis for our underlying segmentation[i],
which has proved to be both stable, and insightful over time.
There is tremendous diversity in the SME sector, and as a
result one size certainly does not fit all. We believe strong segmentation is
essential to be able to translate strategy into effectively action. We focus on
what we call “the voice of the customer”.
This enabled us to develop models and descriptors for each
of the clusters. Businesses are placed within the model descriptions in a
best-fit manner. We believe that the results should be judged largely on the
interpretability and usefulness of results, not whether the clusters are “true”
or “false”.
When these stable segments are cross-linked with our
research, we can compare the different needs and opportunities across the
groups, and we can prepare segment specific treatment plans for each.
The custom segmentation we use is well distributed by count
across the business community. Growing business and Cash Strapped Sole Traders
are the two largest groups. As expected, the count of Large Established Firms
is the lowest.
In the light of our research, we have reviewed the
provisions of the proposed legislation and wish to make three major points.
SME’s Are Indeed an Essential Part of Our Economy.
The small and medium business sector (SME) is a critical
growth engine for the economy, with more than 3 million businesses offering
employment for more than 7 million Australians. The characteristics of these
businesses are varied from newly founded part-time entities, through to
businesses employing up to 100 people and with a turnover of up to $10 million
each year. More than 77% have a turnover of less than $500,000 each year. 91.3%
have an annual turnover of less than $2 million each year. So, one size does
not fit all.
The largest industry segment is Construction (17%), followed
by Professional, Scientific and Technical (12.5%) and Rental, Hiring and Real
Estate Services (11.5%). Financial Services (9%) and Agribusiness (8.25%) are
the next two. Note that Mining accounts for only 0.4% of all SME’s.
Nearly half of all businesses have been trading for less
than 4 years. Cash Strapped Sole Traders are most likely to fail (55% in 5
years), followed by Cash Strapped Sole Traders and Stable Subcontractors. The
highest failure rates are found in Transport, Financial Services, Real Estate
and Construction.
Most SME’s are true small businesses and one quarter of
SME’s have a sales turnover off less than $50,000 each year, and more than half
have a turnover of less than $150,000 per annum. Most low turnover businesses
are unincorporated. Those businesses with larger turnovers are more likely to
be formed as a company.
Looking at the state distribution, 60% of businesses are in
NSW and VIC.
Funding Is Indeed A Growing Problem for SME’s.
We have detected an increasing problem where more businesses
are unable obtain suitable finance to enable them to grow and invest in their
businesses. Underlying this is the fact
that demand from households and businesses for services from the SME sector is
waning as the broader economy falters. SME’s are the canary in the economic
coalmine!
For many segments, the need for working capital is the main
issue, and the main cause of this need relates to delayed payments. This is
particularly a concern among some smaller businesses. The average debtor days
is still elevated, with 45% of firms reporting an average settlement time from
invoicing of 50-60 days. There were minor variations across the states. Debts from Large Corporates and Government
entities are both taking longer to settle due to “enhanced” cash flow
management techniques.
The average number of banking relationships varies across
the segments. Larger and more complex businesses are likely to spread their
relationships. Others, in need of funding, will also try to access facilities
from many sources, and so have more complex relationships.
Satisfaction with banking services remains in the doldrums,
with around half of all businesses dissatisfied, or very dissatisfied with
their bank, and only 17% very satisfied.
The satisfaction rating did vary by segment, with more established
firms who do not need to borrow the more satisfied, while newer smaller firms,
seeking to borrow, the least satisfied. For them access to credit was a
significant issue.
Compliance and price were the two most significant causes of
dissatisfaction, though only 5% said obtaining funding was the root cause of
their concerns. When asked about their propensity to switch lenders, 61% said
they would consider moving. However, when we examined their length of time with
existing banking relationships, many are rusted on long term. The inertia, and
the gap between intent to switch and switching is explained by a combination of
time constraints, complexity of switching and lack of available alternatives.
Again, this footprint varies by segment.
We continue to see the rise of FinTech lenders operating in
Australia. Around 23% of SME’s have applied, and a further 10% say they will
apply for funding. Overall awareness is rising, although there are some
concerns about the true costs of borrowing from this source.
Many lenders are reluctant to lend to the sector, require
security (mortgage over property for example) and funding is expensive. Banks
prefer to lend to households as opposed to businesses, partly because of the
relative capital ratio costs and lower risk profiles.
Some businesses are turning to the growing FinTech sector,
where unsecured finance is available, at a price, but getting funding through
these channels can be expensive because of lack of true competition and high
demand.
Finally, we agree with the proposition that Australia
currently lacks a patient capital market for small and medium enterprises. But this is not the main issue blocking the
growth of the sector. Access to straightforward credit is.
But the Proposed Bill Is Targeting the Wrong SME Segments
We understand the fund will invest between $5 million to $15
million in small and medium enterprises that have a turnover of between $2
million and $100 million, where they can demonstrate three years of revenue
growth and a clear vision to expand.
Established Australian businesses will be eligible to apply
for equity capital investments between $5 million and $15 million.
Small-business owners will not have to give up control for this investment.
The Business Growth Fund’s investment stake will range from
10 to 40 per cent, setting a balance between business owners keeping control of
their business and providing enough incentives for investors. Initially, the
Business Growth Fund could support 10 investments per year, with the aim to
increase to 30 per year as the fund develops. Banks and superannuation
contributions could enable the fund to grow to $500 million.
Our research indicates that this particular segment is
small, can already obtain funding for such expansion (many would fit within our
“Business In Transition” segment), and as a result we do not believe many would
be prepared to give up such a large stake in their growing businesses. It seems
this is more orientated to offer investors and the financial sector a return,
than being shaped best to provide support for those small businesses which need
assistance the most. The small number of transactions envisaged will also not
assist many businesses, and the target is clearly not the bulk of those with
real funding needs.
Thus, we cannot support the current proposal (which we also
note is imprecise in terms of the assessment processes, return hurdles and
other matters). Our view is that the current proposal appears rushed, and too
high-level. But our main point is, it is targeting the wrong SME’s.
We Think There Is A Better Option
We believe there is a better option to assist SME’s in their
growth agenda. The truth is there is a dearth of financing available from
existing major players. Their risk and capital ratios mean they prefer to lend
to households for mortgage purposes, then to small business. As interest rates
fall, this pressure is being exacerbated.
We think a better model would be to provide funding via the
emerging Fintech sector, by either providing funding to flow to existing FinTech’s,
or by creating a new Government backed marketplace where FinTech’s and SME’s
can transact.
There are good examples of such models[ii].
For example, in the UK, the main contenders are Tide (focused solely on SMEs,
small or medium-sized companies) and Starling (which has retail accounts as
well). In France, the big player is Qonto. In Germany, there’s Penta and Hufsy
(which is based in Denmark). In Norway, Aprila. For “micro-businesses” of 1-10
people, there’s Holvi in Finland, Coconut, Anna and CountingUp in the UK, and
Shine in France.
Tide now claims over 1.4% of the UK’s SMEs as clients (up
from 1% in December 2018), and is gunning for 8% market share by 2023, aided by
a £60m UK government grant.
Meanwhile, Starling has 46,000 SME members, up from 30,000
in March, with £100m from the same government grant to develop its business
banking offering.
Qonto in France has grown from 15,000 small business
customers to 40,000 in the past year, and is expanding into Germany, Spain and
Italy this year. Finnish startup Holvi, which was bought by Spanish bank BBVA
in 2016, claims 150,000 customers and is expanding into France, Italy, the
Netherlands, Ireland and Belgium.
There is a lot of space for growth because the European
market — with 24.5m SMEs — is still extremely dominated by the big lenders. In
the UK, for example, four big banks have a 90% share of SME banking.
This was an intentional strategy from the UK Government to
disrupt the inadequate SME sector. And in response the incumbents have been
forced to respond and are now upping their game and starting their own
digital-focused business banks as well to compete. In November 2018, NatWest
launched Mettle. Santander’s “start-up” small business bank, Asto, also
launched in the UK late 2018 Meanwhile, HSBC is building its own small business
bank start-up, known internally as Project Iceberg.
In addition, the cost of funding to SME’s has dropped and
the Fintech sector has developed, supported by the core injection of UK
Government funding.
These digital plays cover a wide range of services which
SME’s need, as well as basic payments, transactions and lending. And they are
tending to create a marketplace where businesses and service providers and
lenders can interact. This is transformational.
The SME experience has been significant, with easier access
to funding, faster decisions, and the resultant rebalancing of the industry has
lifted mainstream lenders too. If a similar model was replicate here, the SME
sector would win. Australia would win.
Conclusion
The point to make, is rather than a thin deal flow
targeting larger SME’s which really do not need assistance, a revised strategy
could facilitate transformation of finance to SME sector. Thus, the planned investment
could be made by the Australian Government, but leading to more productive
outcomes. If we were to replicate a UK model, we think it should be the current
inflight Fintech-based approach, rather than one which favours incumbents, and
which does not deal with the core issues Australian SMEs face.
Thus, we recommend that the current proposed Bill is
withdrawn, and the strategy redeveloped to take account of the emerging Fintech
scene
Martin North
Principal
Digital Finance Analytics
9th February 2020
[i] Our
partitional clustering approach means that the segments are defined using multi-factor
cluster analysis and split into non-overlapping tribes, rather than in a
hierarchical tree. To achieve this, we developed a proprietary scoring system
based on Lloyd’s algorithm, (also known as Voronoi iteration) for grouping data
points into a given number of categories. This is often referred to as k-means
clustering. The modelling is iterated sufficiently to enable adequate
separation between clusters, as determined by Lloyds’s algorithm.
We will be running our latest live show tomorrow 20:00 Sydney on 18th February. Join us live, to ask a question, or send one in beforehand via the DFA blog
Economist John Adams and Analyst Martin North reflect on last week’s Canberra visit when John had 14 (yes 14) meetings about the Cash Restrictions Bill. But John also came away with some more disturbing conclusions about our politicians.
The current popular view is that in response to the Covid-19 problem, the central bank will stimulate, and this will support the local, and therefore global economy. One reason why markets are sanguine.
There is just one problem with this. China’s Global Times (one external voice of the Government) headed a piece “China should get ready for belt-tightening following virus outbreak”. Maybe China will not stimulate the economy by rolling out another massive monetary stimulus. This is potentially a game changer.
With the Chinese economy taking a major hit from the outbreak of the novel coronavirus pneumonia (COVID-19), the central government appears to pursue fiscal austerity as part of the efforts to pull through the difficult times.
While it is generally expected that fiscal stimulus and monetary easing will undoubtedly be the two main tools of central authorities for alleviating downward pressure on the economy and for maintaining macroeconomic stability, given the past experience and the financial risks currently facing China, a flood of spending programs seems no longer on the financial regulators’ list of choices for stimulating the economy.
“China will face decreased fiscal revenues and increased expenditures for some time to come, and the fiscal operation will maintain a state of ‘tight balance.’, Chinese Finance Minister Liu Kun wrote in an article published on Qiushi, a magazine affiliated with the Communist Party of China Central Committee. In this situation, it won’t be feasible to adopt a proactive fiscal policy by expanding the fiscal expenditure scale. I, and instead, policies and capital must be used in a more effective, precise and targeted way,” Liu said. Chinese Finance Minister Liu Kun wrote in an article published on Qiushi, a magazine affiliated with the Communist Party of China Central Committee.
Liu’s article sent a clear signal that China would not stimulate the economy by rolling out another massive monetary stimulus.
Due to the major impact of the coronavirus outbreak on businesses across the country, the Ministry of Finance has already made it clear that it would continue to reduce the tax burden on enterprises, which will undoubtedly weigh down the already slowing fiscal income. And a potential decrease in fiscal revenues directly points to the limited room for splashing out on unnecessary programs. China’s fiscal revenues grew 3.8 percent in 2019, the slowest growth since 1987, while fiscal expenditures during the same year gained 8.1 percent compared with the previous year, outpacing economic growth.
Therefore, to maintain a “tight balance,” the Chinese economy will have to tighten its belt by curbing non-essential expenditures while expanding investment in a precise and targeted manner.
There has been a consensus call among economists and economic observers for the fiscal deficit ratio to break the 3 percent GDP mark temporarily so that more space could be given to fiscal expenditures to stabilize the economy amid the epidemic.
However, it should be noted that fiscal space constraint is not the key reason for belt-tightening. Past experience with massive stimulus already showed that a flood of investments could lead to many consequences like high levels of local government debts, and to the detriment of high-quality economic growth.
In 2019, China’s fiscal expenditures reached 23.9 trillion yuan ($3.4 trillion), of which only 3.5 trillion yuan was spent by the central government, and the rest by local governments.
In this sense, governments at all levels should be prepared for belt-tightening in the future to come.
This could have significant consequences for us all!
At first glance, the latest data – which came out on Feb. 7 – look pretty good. They show nominal hourly earnings rose 3.1% in January from a year earlier.
But the operative word here is nominal,
which means not adjusted for changes in the cost of living. Once you
factor in inflation, the picture changes drastically. And far from
representing a “blue collar boom” – as the president put it in his State of the Union address – the real, inflation-adjusted data show most U.S. workers have not benefited from the growing economy.
As an economist who studies wage data, I think it’s paramount that we take a step back and look at what the data really show.
Business journalists and financial markets
tend to focus on the monthly data. These figures are only reported in
nominal or current terms because the inflation data doesn’t come out
until later.
A more complete set of wage and pay data
is reported quarterly. The latest release came out in December for the
third quarter. These figures are not only adjusted for inflation but
also include fringe benefits, which account for just under a third of
total compensation.
At first blush, it makes sense to focus
primarily on the first set. Newer data is, well, newer, and market
participants and companies prefer the latest information when making
decisions about investments, hiring and so on.
But the effect of inflation means that the same US$1 bill buys less stuff over time as prices increase.
From December 2016 to September 2019, nominal wages rose 6.79% from $22.83 to $24.38. But after factoring in inflation, average wages barely budged, climbing just 0.42% in the period.
Incorporating fringe benefits into the picture adds another wrinkle.
The inflation-adjusted or real value of
fringe benefits, which include compensation that comes in the form of
health insurance, retirement and bonuses, declined 1.7% in the
three-year period.
Altogether, that means total real compensation slipped 0.22% from the end of 2016 to September 2019.
Of course, workers in different sectors
have fared differently. The Trump administration has singled out
manufacturing workers – who it says are the main beneficiaries of its
trade war and other policies intended to support the sector – as having
benefited from a “blue collar boom” in wages.
The nominal data for manufacturing workers
hardly support a boom but they do show an increase of 2.22% since
Donald Trump took office.
The adjusted data, however, make it look
more like a bust, with wages plunging 3.88% in the period. And, again,
the situation is worse when we add in fringe benefits, which brings the
decline to 4.33%.
So next time you read a story about a rise in pay, try to see if it reports the wage data in nominal or real terms, and if it includes fringe benefits too. If it’s only nominal wages, the numbers may mean a lot less than they seem.
Author: David Salkever, Professor Emeritus of Public Policy, University of Maryland, Baltimore County
