Don't block the entrance - or the exit

I wrote a while back about the excellent data the Bureau of Labor Statistics in the US produces on the labour market - what they call the JOLTS data (Job Openings and Labor Turnover Survey). You can access it yourself here. The graph below shows the key results from the latest (December '14) reading.

The mechanics of the thing are simple - when hires (the blue line) are greater than separations (essentially layoffs and quits, in red) total employment grows (in green). What's really striking about the US labour market - and indeed most labour markets - is the huge gross flows compared with the much smaller net outcome. In December alone, for example, hires were 5.1 million and separations 4.9 million: for 2014 as a whole, there were 58.3 million hires and 55.4 million separations, for a net gain in employment of 2.9 million.

We don't have the equivalent set of data in New Zealand, though it is on Stats' radar, but we do have some data that shows the same patterns operating here. Here, for example, are the numbers of jobs created at new firms, and the numbers of jobs lost through firms closing - the jobs associated with company 'births' and 'deaths'. The numbers come from Stats' Linked Employer-Employee Database, and again you can find them for yourself at Stats' (free) access site NZ.Stat under the 'Business demography statistics' heading.

This is only a slice of the labour market - the bigger part is the hiring and firing at ongoing firms - but it's interesting nonetheless. Again the gross flows are considerably larger than the net flows.

What's the relevance? It's because most folk (I believe) don't realise this is how the labour market works. I'd guess that most people reckon hiring dries up during a recession, and layoffs dry off in good times. They don't: there are very large numbers of new hires even in bad times, and very large numbers of layoffs even in good times. Rather, the ratio between them changes: hires drop faster than layoffs in bad times, and grow faster than layoffs in better times. But both power along in large volumes all the time, with a high degree of churn or turnover going on. There's a vast amount of matching and rematching going on all the time as both employers and employees look for the best fit. The efficiencies from a process where people are continually looking for the best option for both parties must be very large indeed..

The wrong idea, that layoffs happen only or overwhelmingly in bad times, tends to lead to a well-intentioned but wrong policy prescription: that if we stop the layoffs, we can keep employment up. Unfortunately in some over-regulated markets, 'job protection' measures, that aim to make it harder to lay off people, gummage up both sides of the labour market. Employers can't lay off people when they'd like (or need), and knowing that, they're less inclined to to hire in the first place, or only in unregulated ways (eg with short term contracts that don't accrue the same protection rights). Much of continental Europe is lumbered with high unemployment as a result. Well-meaning but inefficient job protections aren't the only reason for Europe's high unemployment, of course, but they're a part of it, and likely to be a substantial part of it when it comes to youth unemployment or the unemployment of more marginal groups in general.

There's also a school of thought that employees need to be protected, because the employers have the whip hand: there's some kind of market power on the employers' side. That's not true, either. Have a look at this, also from the latest JOLTS data.

In fact, things don't just 'happen' to employees at employers' discretion.  Most of the time, voluntary 'quits' are substantially larger than involuntary layoffs. In a bad recession, more people than usual prefer to sit tight, for obvious reasons. But usually there are substantially more people leaving jobs of their own volition than are leaving them because they've got the pink slip. Again the efficiencies - and personal career and life satisfaction - from a system where people can freely leave and freely find new jobs must be enormous. Anything that throws sand into this process - and it's not just job protection regulation, but could be barriers of other kinds, such as the US system of employer-provided medical insurance, or in New Zealand arguably differences in regional housing costs - risks jeopardising one of the main productivity engines of a modern economy.

Diminishing Marginal Utility

The concept of marginal utility is one of the most fundamental principles of economics. It describes the additional satisfaction an individual gets from consuming one more unit of a good or service. This information is critical for predicting and explaining consumption decisions.

Although actual utility cannot be measured in hard numbers, it is possible to reveal consumer preferences, tendencies, and other relevant aspects that are critical for decision making. However to be able to do this, we must first look at the principle in some more detail. 

Thinking at the margin

First of all, to describe decision making processes accurately it is necessary to think at the margin. Particularly we need to focus on the "next step" and analyze its consequences (e.g. what happens if we buy one more bottle of water, etc.). In other words, to understand decision making processes we have to look at the effects of small (marginal) changes from various states.

The idea behind this is actually quite simple. Rational individuals should always consider costs and benefits associated with every action they take. As long as the additional benefits (i.e. marginal benefits) are greater than the additional costs (i.e. marginal costs), the individual will be better off afterwards and thus take the action. For example, if you have to decide whether or not to buy ice cream you probably trade off your desire for ice cream against its price and only buy it if you feel like you are better off if you do so.

Hence, mathematically speaking marginal utility is the first derivative of total satisfaction (i.e. total utility) at a specific point. This aspect will be relevant once we introduce the law of diminishing marginal utility.

Diminishing marginal utility

The law of diminishing marginal utility states that the additional utility of a good (or service) decreases as its supply increases. This suggests that every additional unit that is consumed has a lower marginal utility than the unit before. At a certain point the additional utility can even become negative for some products. In those cases consuming another unit will actually decrease overall satisfaction. This principle is illustrated in the graph below.

Illustration 1: Diminishing Marginal Utility

The most important thing to note from this graph is that the utility curve (UC) is not linear, but becomes flatter as quantity (Q) increases. As a result the changes in total utility (U) resulting from an increase in Q become smaller as total quantity grows. For example, if quantity increases from q1 to q2, the change in total utility (u2 - u1) is quite significant. However if quantity increases from q3 to q4, there is only a very small increase in total utility (u4 - u3) even though the change in quantity is the same. 

To make this more comprehensible we can look a simple example: the utility of a glass of water. On a hot summer day the satisfaction you get from drinking this glass will most likely be high (especially if you have not had anything to drink for a long time). However if you have just consumed two other glasses of water a minute ago you are probably not that thirsty anymore so the additional satisfaction you get from drinking the additional water will not be that high anymore. At some point if you drink too much you might even get sick and have to vomit, thus marginal utility becomes negative.

Limitations and Exceptions

Although the law of diminishing marginal utility is an important and widely applicable concept there are certain exceptions that need to be considered. Thus for the sake of completeness the most relevant of those limitations are listed below.

• As mentioned before, the law of diminishing marginal utility only applies to rational individuals. If individuals do not act rationally their actions become somewhat erratic which makes it impossible to accurately describe and predict their behavior.
• The law does not account for fashion trends or other changes in taste. If a product comes into fashion its utility increases (irrespective of the quantity consumed), whereas its utility decreases once it goes out of fashion.
• There is no (or limited) diminishing marginal utility for goods that are added to a collection (e.g. stamps, coins, etc.). This is due to the fact that collections generally become more valuable the more extensive they are.
• The law is not applicable for situations that require a specific amount of a good or service to achieve a desired outcome. A common example here is the use of antibiotics. While the right dose might cure an illness, not taking enough pills will leave bacteria with an increased resistance and thus aggravate the illness.

In a nutshell

The concept of marginal utility is one of the most fundamental principles of economics. It describes the additional satisfaction an individual gets from consuming one more unit of a good or service. Most products experience diminishing marginal utility, which means the amount of additional utility decreases as their supply increases. For those goods and services every additional unit that is consumed has a lower marginal utility than the unit before. Even though this concept is widely applicable it is important to note that there are several limitations (i.e. assumption of rational individuals, disregard of fashion trends) and exceptions (i.e. collections, required specific amounts) to it.

More house lending controls to come?

As we all know, the Reserve Bank is in a difficult spot.

It can't easily raise rates. It probably doesn't want to anyway, since (as I've argued before), overall monetary policy conditions are already too tight. But even if it did, the Kiwi dollar would appreciate, or at the very least not fall to the levels the RBNZ would like: "The upward pressure on the TWI reflects several influences but primarily investors have been attracted by the broad strength of the economy and our higher interest rates", as the Governor's speech last week said (it's here as a web page and here as a pdf), and wider interest differentials in NZ's favour would clearly make the fight on the NZ$ front more difficult (as is already the case with the A$/NZ$ cross rate after the Aussies' cut in interest rates).

It can't easily lower rates. There's an argument that the low oil price has lowered any inflation risks, and another (which I'm partial to) that, in hindsight, it overtightened with its latest OCR increases, but cutting rates in the middle of a boom would still be rather odd. "New Zealand is the only country among the advanced economies that has had a positive output gap in the past two years, our unemployment rate is low and falling, net inward migration and labour force participation is at record levels, and business and consumer confidence surveys remain strong", as the Governor said, plus it would make the housing market even more exuberant - "we have already seen some effective easing of credit conditions with declines in fixed-rate mortgages, at a time when we have financial stability concerns about accelerating house prices in Auckland".

So by default it's stuck with leaving interest rates where they are, which means that its financial stability headache over Auckland house prices doesn't go away, or even gets progressively worse - floating mortgage rates stay where they are (or even drop a bit if the banks' marketing wars heat up a bit more), while fixed rates fall as long maturity bond yields remain very low overseas (essentially we're lumbered with importing world bond yields, plus a credit/risk premium).

All of which leads you to think that there may be another round of "macro-prudential" regulation around the corner. We've got the existing regulation - only 10% of new bank lending on houses can have a loan to value ratio (LVR) higher than 80%, or put another way, 90% of new lending must have at least a 20% deposit - but while it's had some impact, it doesn't look as if it's been enough to rein in the Auckland market in particular. Prices in an already expensive market are up another 13% in the year to last December (on the latest REINZ data),

Yes, there's more going on than just easy credit. As the Governor said, Auckland prices reflect a melange of "rising household incomes, falling interest rates on fixed-rate mortgages, strong migration inflows and continued market tightness". But there's still a financial stability issue. When these factors ease, or reverse (eg when housing supply finally come on strong), banks risk being left with big loans on lower priced assets. So you'd reckon the RBNZ must be looking in the cupboard for another macro-prudential stick.

As it happens, there's a brand new model for them to have a look at, and that's the Irish Central Bank's. The Irish had one of the biggest housing market busts of all time - the national house price halved, almost exactly, between the peak in September '07 and the trough in March '13 - and, to put it very mildly, are not keen to see a repeat. With Irish house prices up 16.2% over the year to last December, they've just stepped in with a package that combines LVR ratio limits and loan to income ratios. You can read the whole thing in the Bank's FAQ here: the gist is a 3.5 times income limit for all new loans except loans to buy rental properties, a 20% LVR ratio limit for most mortgages, a 10% first time buyers' LVR limit up to €220,000 (about NZ$340,000), and a 30% LVR limit for rental property loans. There's room for the banks to do some business outside these limits (20% can be outside the income limit, 15% outside the LVR limits).

Interestingly, one of the questions in the FAQ reads, "Has the Central Bank considered that these measures may be discriminatory against people looking to buy in Dublin and the surrounding areas?" The Irish Central Bank preferred to downplay that aspect - it says, yes, but only a bit - but that's exactly the sort of selective impact we'd like to see happening in Auckland.

"We will be talking more about the housing market over the next few months", the Governor said last week. I wonder if they'll be talking with an Irish accent?

Who got what?

The Productivity Commission has just come out this morning with an interesting new Working Paper, "Who benefits from productivity growth? –The labour income share in New Zealand", and if life's too short, there's an accompanying "cut to the chase" summary. The labour income share, by the way, is as it sounds  - "The labour income share (LIS) is the proportion of income generated from production that is spent on labour in the form of wages and associated on-costs" such as employers' super contributions. The rest of the income in the economy is attributed to capital, so the paper is about the split of national income between wages and salaries on the one side, and returns to the owners of capital on the other.

At first sight, the headline finding risks feeding the post-Piketty fears of those who think the working stiff is losing out to the plutocrat: here's a graph (it's Fig 1 in the summary) of GDP and labour's share of it. The labour share's gone down from around 64-65% of GDP to around 56%.

But whether this is a good thing or a bad thing isn't at all obvious: as the paper says (p6), it "depends on the situation and is partly a matter of preference. For example, would New Zealanders prefer to participate in an economy where real wages are increasing strongly but the LIS is falling because productivity growth is even faster, or an economy with weak growth in real wages and productivity so that the LIS is more constant?", and the paper steers clear of making any judgement calls.

One factor in the background is that capital's share will depend on how much capital there is. If there's a lot more capital going into the business of producing GNP then there used to be, and most of us would reckon that's a good thing (lots more equipment at work in the Aussie economy is one of the reasons Australia has been growing faster than us in recent years), then its share will tend to go up and labour's to go down. It's not a given - could be, for example, that wages go up fast enough for labour's share of the total cake to hold up - but it's likely. And as it happens, we have in fact seen the amount of capital in use growing faster than the amount of labour employed. Here are the numbers. 'MS-11' in the title is the 11-industry 'measured sector' that the paper has looked at, and  'MFP' is 'multifactor productivity', or that bit of GDP that isn't explained by increased inputs of labour and capital.

The fall in labour's share is also not a uniquely Kiwi phenomenon, by the way, if you've been thinking deep dark thoughts about the distributional consequences of Rogernomics and its successors*. In a range of OECD countries the labour income share typically rose to a peak in the late '70s or early '80s and declined since as a result of a bunch of things. As the paper notes summarising the research on the whys and wherefores (p10), "Perhaps most importantly, technological advances that have increased the return on capital have led to capital deepening as businesses have substituted capital for more-expensive labour...Other contributing factors include shifts in industry composition towards more capital-intensive industries, increased globalisation that increased the global supply of cheap labour, and institutional developments that have reduced labour’s bargaining power". 

And if you're still nurturing "they're watering the workers' beer" thoughts, the paper shows that there are actually good links between the value that employees bring to their business (the growth in labour productivity) and what they get out of it as a result by way of higher real wages, as these two charts from the summary show. Over time (left hand graph)  and across industries (right hand one), if firms are doing well because the employees are more productive, it turns up in the payroll run.

The paper doesn't have a lot to say about policy, and that's fine, it set out to be more of an analytical piece, but what it does say is sensible: if there are all these trends buffeting labour's share of the goodies, then (from p7)

benefiting from new technology requires investment in the necessary complementary skills. In particular, the education system must be of high quality and sufficiently responsive to provide new and dislocated workers with the skills they need to enter productive and lucrative occupations where they can make the most of new technology. Policy should also work to minimise entry barriers and other frictions, such as excessive occupational licensing, that prevent workers from moving to where they can work most productively. There is also a geographic aspect to this in that cities are one of humankind’s most productive inventions. So restrictions on housing supply that mean low-skilled workers cannot afford to live in economically dynamic places can limit productivity growth and economic resilience to change.

Even if policy is set just right to ensure that the benefits of technology-based growth and globalisation are widely spread, a social safety net may still have to catch people who fall through the cracks. Accordingly, policy must ensure that social services function effectively to deal with the side effects of rapid technological change

It may not be original - much the same policy combo is what has traditionally been prescribed to cope with the impact of freeing up international trade - but it's none the worse for that.

Another thing I liked about this paper is that it's given us a handy summary way of thinking about our recent economic growth, and here it is. You've got the different growth cycles, and their sources, all in one nicely packaged schematic.

As the graph indicates, we had a 'high productivity' phase in the 1990s, when that tricky multi-factor productivity kicked in much more forcefully than it had been doing before, or has since. Australia did, too, as the data below shows (snipped from Table 6.2 of the paper).

And that brings us to the biggest policy questions of all. Where did that surge in productivity come from? Why did it go away? And, most crucially, can we get it back?

*I'd also note that one of the bigger dips in the labour share occurred pre-reforms, in 1982-84, when Muldoon in his Late Anarchy period imposed a wage and price freeze. As the report notes (p39), "In practice, this proved to be more a wage freeze than a price freeze".

Limitations of GDP as an Indicator of Welfare

Gross Domestic Product (GDP) is essentially an indicator of aggregate economic activity. In addition to that it is also frequently used to describe social welfare. The idea behind this is that GDP tends to correlate with consumption, which in turn is commonly used as a proxy for welfare. In other words, the more people consume, the happier they are supposed to be.

Now, this line of argument seems a little too simplistic. Assuming causality based on a simple correlation between GDP and welfare may lead to false conclusions which can be highly problematic especially for policy makers. Hence it is important to look at the limitations of GDP as a welfare indicator and to consider possible alternative approaches. 

Limitations of GDP

There are several limitations of GDP as a welfare indicator. Most of them can be traced back to the fact that in essence GDP is not supposed to measure well-being. As a result the concept does not account for various important factors that influence social welfare. To keep things simple the most relevant limitations are listed below:

• GDP does not incorporate any measures of welfare: This is probably the most obvious issue. As mentioned before, GDP only describes the value of all finished goods produced within an economy over a set period of time. There are multiple ways to calculate and measure GDP, but neither of them includes any indicator of welfare or well-being. Even though this does not necessarily mean GDP cannot be a good indicator of welfare, the fact that it is used as a "proxy of a proxy" should be kept in mind as it significantly affects its validity.
• GDP only includes market transactions: As a result, it does not account for domestic or voluntary work, even though these activities have a considerable positive impact on social welfare, as they complement the market economy and thus improve the standard of living. On the other hand GDP does not include black market transactions or other illegal activities that may have a substantial negative impact on overall social well-being.
• GDP does not describe wealth distribution: If there is a high degree of wealth inequality, the majority of people do not really benefit from an increased economic output because they cannot afford to buy most of the goods and services. Thus to accurately describe social welfare it is essential to consider wealth distribution.
• GDP does not describe what is being produced: Since GDP measures the value of all finished goods and services within an economy, it also includes products that may have negative effects on social welfare. Think of a country with an extremely strong armaments industry that represents most of its GDP. If the arms are sold and used within the country itself, overall social welfare will most likely decrease. Of course this also holds true for other goods and services that may have adverse effects on society.
• GDP ignores externalities: Economic growth usually goes hand in hand with increased exploitation of both renewable and non-renewable resources. Due to this overuse, more and more negative externalities arise (e.g. pollution, overfishing) and social welfare will decrease as a result. This effect is not included in GDP at all.

If we look at these aspects, the major issue with GDP as a welfare indicator becomes quite obvious. It suggests that a higher GDP always increases social well-being. However at one point the positive effects resulting from the increase in consumption opportunities may be outweighed by the negative effects associated with the limitations mentioned above. Hence although GDP may on certain occasions be a good proxy for social welfare, it results in a biased description that may lead to unfavorable conclusions.

Alternative approaches

In view of the shortcomings mentioned above there have been various attempts to develop more accurate and reliable indicators in order to measure social well-being. Among others these alternative approaches include the Human Development Index (HDI), the Gross National Happiness Index (GNH), and the Social Progress Index (SPI).

• Human Development Index: An indicator that focuses specifically on people and their capabilities to assess the development and welfare of a country. In particular, it measures achievements in three critical dimensions: health and life expectancy, education, and standard of living. The latter is measured by gross national income per capita. Thus HDI also includes an indicator of economic activity, but it adds two complementary dimensions which results in a more comprehensive description of social welfare.
• Gross National Happiness Index: An index that takes a holistic and psychology based approach to measuring social welfare. It was developed in Bhutan and builds on four pillars: governance, socio-economic development, cultural preservation, and environmental conservation. These four pillars are further classified into nine areas and measured by 33 specific indicators. The large number of distinct indicators used in this concept allows for a very sophisticated analysis.
• Social Progress Index: An extensive framework that is based on three key dimensions: basic human needs, foundations of well-being , and opportunity. Again, social progress for each of those dimensions is measured by a multitude of indicators. Those include but are not limited to: nutrition, medical care, and safety (basic human needs), education, wellness, and sustainability (foundations of well-being), and personal rights, freedom, and tolerance (opportunity).

All these approaches take into account multiple dimensions to provide a more comprehensive description of social welfare. Although it is not feasible to completely replace GDP as a welfare indicator anytime soon, it could be used in conjunction with these alternative approaches to provide more accurate and profound results.

In a nutshell

Despite several shortcomings GDP is commonly used as an indicator of social welfare. Most of the limitations are due to the fact that in essence the concept is not supposed to measure well-being. As a result, GDP fails to account for non-market transactions, wealth distribution, the effects of externalities, and the types of goods or services that are being produced within the economy. To compensate for these issues, different approaches to measuring welfare have been developed, including the Human Development Index (HDI), the Gross National Happiness Index (GNH), and the Social Progress Index (SPI).

Gross Domestic Product (GDP)

The Gross Domestic Product, also known as GDP, is arguably the most common indicator to describe a country's economic performance. Generally speaking it measures the total value of all goods and services produced in an economy over a set period of time (usually one year). It can be measured in nominal or real terms. 

There are three different approaches to calculating GDP: the value added approach, the income approach, and the expenditure approach. They should technically all lead to the same result, however due to estimation errors and minor inaccuracies that will hardly ever be the case in reality. Therefore it is important to be aware of the differences between the three approaches. We will look at them in more detail below.  

Value added approach

The first approach to calculate GDP is the value added approach (also known as production approach). It is the most direct but also the least efficient method as it measures the output of all economic sectors. In particular, GDP according to the value added approach equals the value of all goods produced in all sectors minus the value of all purchased intermediate goods for production (i.e. intermediate consumption). To calculate this the gross value of output resulting from domestic economic activity (VOGS) has to be estimated first. Afterwards, intermediate consumption (IC) can be determined and subtracted from the gross value to obtain GDP. We can illustrate this with a simple formula:

GDP = VOGS - IC

To give an example, we shall look at an imaginary country that only has two factories (factory A and B) that produce wooden tables. Over the course of a year 1'000 tables were produced in factory A and sold at a price of $100 each. The legs required to assemble the tables were produced by factory B and sold to factory A at a price of $10 each, while the tops were imported from a different country at a price of $20 each. In this case, the value  of goods sold adds up to $140'000 (1'000 x $100 + 4'000 x $10) and intermediate consumption adds up to $60'000 (1'000 x $20 + 4'000 x $10). As a result, GDP amounts to $80'000 ($140'000 - $60'000). Note that the value of the table legs is only counted once (for factory B) where it is actually added.

Income approach

Another approach to measure GDP is the income approach. This method focuses on the sum of primary incomes (from labor, capital, land, and profit) to estimate GDP. The idea behind this is that firms need to hire factors of production to create all goods and services, thus the sum of primary incomes can be used as an indicator of economic output. In particular, all incomes from labor (W), rent (R), and interest (i), as well as remaining profits (P) have to be summed up to receive national income. Adding indirect business taxes (IBT) and depreciation (D) to the calculated national income will finally result in GDP. The formula for this looks as follows:

GDP = W + R + i + P +IBT + D

To illustrate this, we can go back to our imaginary economy. Let's assume the workers of the two factories earn a total of $5'000. The rent for all business facilities adds up to $10'000, and the private households earn a total of $5'000 worth of interest payments for lending their money to factories A and B. After paying these expenses, the factories still earn a total profit of $50'000. In this case national income is $70'000 ($5'000 + $10'000 + $5'000 + $50'000). By adding indirect business taxes of $5'000 and depreciation of $5'000, GDP also amounts to $80'000 ($70'000 + $5'000 + $5'000).

Expenditure approach

The last approach to calculate GDP is called the expenditure approach. It can be seen as the counterpart to the income approach, as it measures total spending on final goods and services (as opposed to earnings from them). At this point it becomes quite obvious why the different approaches should result in the same GDP value: according to the circular flow of income, economic expenditure by one party is ultimately always income for a different party. Thus, to calculate GDP according to the expenditure approach, all economic activities that result in the use of goods or services have to be added up. In particular, that includes private consumption (C), total investment (I), government spending (G), and net exports (exports - imports, NX). Again, we can illustrate this with a simple formula:

GDP = C + I + G + NX

Let's revisit our imaginary country again. We assume that private consumption amounts to $50'000. Total investment shall be $30'000, and the government spends $20'000. Last but not least, net exports are -$20'000, because factory A imports intermediate goods worth $20'000 and there are no exports (0 - $20'000). Thus, Once again GDP amounts to $80'000 ($50'000 + $30'000 + $20'000 - $20'000).

Nominal vs. real GDP

Calculating GDP according to one of the three approaches described above will result in a nominal value. That means it is calculated in historical monetary terms without any further adjustments. At this point it is important to note that comparing annual nominal GDPs can be problematic and lead to false conclusions due to changes in the overall price level (i.e. inflation) that are not taken into account. Therefore we generally use the real GDP to compare economic output over multiple years, because it is adjusted for the effects of price level changes. In other words, real GDP uses the prices of a certain base year as a reference to value economic output and thereby eliminates the effect of inflation (or deflation).

To give an example, if the GDP of an economy increased from $80'000 last year to $81'600 this year, it appears as if the economic output had increased by $1'600 (2%). However, if the economy experienced an inflation of 1% over the year, the value of its output increased by $800 even if there had been no increase in actual (real) output. Thus if we adjust for the effect of inflation, real GDP (measured in the prices of the previous year) will only amount to $80'800.

In a nutshell

Gross Domestic Product (GDP) is an important indicator of economic performance. It measures the total value of all goods and services produced in an economy over a certain period of time. It can be calculated in three different ways: the value added approach (GDP = VOGS - IC), the income approach (GDP = W + R + i + P +IBT + D), and the expenditure approach (GDP = C + I + G + NX). If the indicator is used to compare multiple economic outputs within one year, GDP is usually calculated in nominal terms, whereas to compare annual numbers it is most commonly measured in real terms.

Fancy a spendup?

I really like Bill McBride's Calculated Risk blog, a great guide to what's happening to the US economy. Apart from the obvious coverage of the major macro stats, he's also got the gift of presenting the data well - I blogged before about his really impressive graph of the US labour market, and judging by the pageviews lots of others thought it was pretty neat, too - as well as the knack of finding data series that are somewhat off the beaten track but provide interesting insights into what's happening in America.

Here's his latest find, the Restaurant Performance Index produced by the National Restaurant Association and originally published here (where you can see the methodology of the thing). Bill calls it a "minor indicator", and he's right in the sense that it doesn't move markets or get much headline coverage in the business media, but that said, for me this is one of the best summary indicators of the US economy I've seen in ages.

You can see the GFC 'Great Recession', you can see the prolonged period from 2010-12 where double dips, treble dips and jobless recoveries were all in play, and then you see the more recent strong rise (particularly in 2014) where the US economy finally pulls free and starts to grow more strongly on a sustained basis. The Restaurant Performance Index is very closely aligned indeed with turning points in the overall economy, partly (as Bill notes) because it tracks largely discretionary spending decisions, which you'd expect (and you'd be right) would be highly sensitive to the economic cycle.

All of this got me wondering whether the monthly data Stats collects on electronic card transactions (latest example here) couldn't be turned into a roughly equivalent indicator for New Zealand,. One of the card series is electronic card spending on 'hospitality', which includes "accommodation, bars, cafés and restaurants, and takeaway retailing", which again is heavily discretionary and hopefully cyclically sensitive. It's unlikely to be as good a tracker as the American restaurant index, which is built up from a detailed industry survey, but it might show something interesting.

So I downloaded the series (it starts in October 2002 and at time of writing runs to November '14 - you can access it yourself on Stats' Infoshare, it's in the 'Economic Indicators' bit), ran a simple regression to eliminate the long term time trend, and looked at the residuals as a percentage of each month's hospitality spending. What you get is a graph that shows when spending on 'hospitality' is unusually strong or unusually weak, and it looks like this.

It's not too bad. There are oddities: I'm not sure why there's that cyclical weakness in 2003-05, which may be an artefact of how I've calculated the indicator (by construction there will be similar numbers of 'overs' and 'unders' whereas in real life expansion and contractions aren't the same length). But it catches the GFC and post-GFC weakness, and in particular it shows the strength of the current upswing. As far as the consumer is concerned, this is the best time for a bit of a spendup in the past dozen years.