House price growth to ‘slow sharply’: ANZ

From Investor Daily.

In a housing market update this week, ANZ Research said it expects “prices to slow sharply this year and next” and flagged the potential oversupply of apartments – particularly in Melbourne and Brisbane – as a key concern.

“The twin issues of housing affordability and financial stability are front of mind for governments, the RBA and APRA,” the bank said. “Household debt is at record levels, which increases vulnerability to future shocks.”

According to ANZ, the residential construction cycle has lost momentum with approvals down about 20 per cent from their 2016 peak. The major bank expects another 5-10 per cent fall in the next 6-12 months.

“That said, the solid pipeline of work suggests that the level of residential construction activity will slow only gradually this year. There has been a slight rise in settlement risk which bears close monitoring,” ANZ said.

ANZ believes that the housing market will steadily cool going forward with a combination of further regulation and changes to government policy, tighter borrowing conditions and out-of-cycle mortgage rate increases all expected to weigh on the outlook for prices.

“We anticipate nationwide dwelling prices will rise by 4.5 per cent through 2017, before slowing further to 1.9 per cent 2018 and expect to see continued divergence across regions,” the group said.

While price growth in Sydney and Melbourne is expected to slow to well below historical averages, ANZ said these markets will remain positive as demand and population growth remain elevated.

“On the other hand, prices are expected to ease slightly through 2018 in Brisbane, given the significant volume of supply due to hit that market,” the bank said.

Tightening Is Toxic

From Moody’s.

The FOMC is expected to announce a 25 bp hike in the federal funds rate’s midpoint to 1.125% on Wednesday, June 14. Despite March 14’s 25 bp hiking of fed funds to a 0.875% midpoint, the 10-year Treasury yield fell from March 13’s 2.62% to a recent 2.20%. If the 10-year Treasury yield does not climb higher following June 14’s likely rate hike, the scope for future rate hikes should narrow.

At each of its end-of-quarter meetings, the FOMC updates its median projections for economic activity, inflation, and the federal funds rate. At the March 2017 meeting, the FOMC’s median projections for the year-end federal funds rate were 1.375% for 2017, 2.125% for 2018, and 3.0% for 2019 and beyond. However, the recent 10-year Treasury yield of 2.20% implicitly reflects doubts concerning whether the fed funds rate’s long-run equilibrium will be as high as 3.0%.

Perhaps, the FOMC will supply a lower long-run projection for fed funds. Nevertheless, in order to ward off speculative excess in the equity and corporate credit markets, the FOMC may wisely decide to overestimate the likely path of fed funds. The last thing the FOMC wants to do is help further inflate an already overvalued equity market.

Moreover, equity market overvaluation has pumped up systemic liquidity by enough to narrow high-yield bond spreads to widths that now under-compensate creditors for default risk. According to a multi-variable regression model that explains the high-yield bond spread in terms of (1) the VIX index, (2) the average EDF (expected default frequency) metric of non-investment grade companies, (3) the Chicago Fed’s national activity index, and (4) the three-month trend of nonfarm payrolls, the high-yield spread’s recent projected midpoint of 410 bp exceeds the actual spread of 380 bp. Moreover, after excluding the VIX index from the model, the predicted midpoint widens to 500 bp. The 90 bp jump by the predicted spread after excluding the VIX index is the biggest such difference for a sample that commences in 1996. The considerable downward bias imparted to the predicted high-yield spread by the recent ultra-low VIX of 10.2 points highlights the degree to which a richly priced and highly confident equity market has narrowed the high-yield bond spread. (Figure 1.)

High-yield spreads can narrow amid Fed rate hikes

There is absolutely nothing unusual about financial market conditions easing amid Fed rate hikes. When the fed funds’ midpoint was hiked from 0.125% to 0.375% in December 2015, the high-yield bond spread quickly swelled from a November 2015 average of 697 bp to February 2016’s 839 bp. However, though the midpoint is likely to reach 1.125% at the FOMC’s upcoming meeting of June 14, the high-yield spread has since narrowed to a recent 380 bp. (Figure 2.)

Early on, Fed rate hikes often were followed by thinner corporate bond yield spreads. For example at the start of the first tightening cycle of 1991-2000’s economic upturn, fed funds was hiked from year-end 1993’s 3.0% to 5.5% by year-end 1994. Despite that 2.5 percentage point hiking of fed funds, the high-yield bond spread managed to narrow from Q4-1993’s 439 bp to Q4-1994’s 350 bp. Not until the 10-year Treasury yield dipped under August 1998’s 5.5% fed funds rate did the high-yield spread widen beyond 600 bp.

It’s also worth recalling how the market value of US common stock soared higher by 19.4% annualized, on average, from January 1994 through March 2000 despite a hiking of fed funds from 3.00% to 5.75%. However, once fed funds reached 6.00% in March 2000, a grossly overvalued equity market finally crested and began a descent that would slash the market value of US common stock by a cumulative -43% from March 2000’s top to October 2002’s bottom. (Figure 3.)

The series of Fed rate hikes that occurred during 2002-2007’s recovery told a similar story. Notwithstanding a steep and rapid ascent by fed funds from the 1% of June 2004 to 5.25% by June 2006, the high-yield bond spread averaged an extraordinarily thin 340 bp from July 2004 through July 2007. At the same time, the VIX index averaged a very low 13.2 points despite the span’s 425 bp hiking of fed funds. Moreover, from June 2004 through October 2007, the market value of US common stock advanced by nearly 11% annualized, on average.

 

The Great Lending Rotation Is Upon Us

The bumper edition of ABS data today, just before the long weekend included both the housing finance data and the lending finance data for April. Investor lending is on the turn now, and first time buyers are also retreating. The question now is what will this do to house prices, and the debt burden many households are currently under?

We think this marks a significant point of rotation for the housing market. However, business lending is not accelerating, leaving a significant growth hole in the economy.

Looking at the housing lending, overall lending flows fell 0.4% in trend terms from March, to $32.8 billion. Within that owner occupied loans fell 0.1% to $19.9 billion and investment lending fell 1% to $12.6 billion.

Refinance loans fell significantly, and the proportion of loans for investment purposes also fell.

Looking at the number of commitments, overall this fell by 0.5% to 53,062, with the purchase of new dwellings down 0.7% to 44,443. Purchase of new dwellings was down 0.1% to 2,755 and the construction of dwellings was up 0.6% to 5,864.

Revisions to the data have changed the trends, with owner occupied loans stronger, and investment loans weaker.

Looking at the stock of loans, overall values were higher again.

Owner occupied loans net rose $5.7 billion, or 0.56%, whilst investment loans rose $2.1 billion or 0.39%. Both Building Societies and Credit Unions saw a net loss in portfolio value.

In original terms, the number of first home buyer commitments as a percentage of total owner occupied housing finance commitments rose to 13.9% in April 2017 from 13.5% in March 2017. The number of first home buyer commitments decreased by 17.5% to 6,547 in April from 7,939 in March; the number of non-first home buyer commitments also decreased.

There was a big fall in the number of first time buyer commitments, offsetting the rise in the previous month.

We continue to track momentum in investor first time buyers, another 4,000 joined the ranks this past month.

The ABS says that in this issue, revisions have been made to the original series as a result of improved reporting of survey and administrative data. These revisions have affected the following series:

  • Owner occupied housing for the month of March 2017.
  • Investment housing for the month of March 2017.
  • Housing loan outstandings to households for owner occupation series for the periods January 2017 to March 2017.

 

Securitisation Still Going Sideways

The ABS released their data on Australian securitisers today. At 31 March 2017, total assets of Australian securitisers were $121.6b, up $4.4b (3.8%) on 31 December 2016.

Residential mortgages continue to make up most of the transactions and there was a small overall lift, but in the past year the value of mortgages fell 0.9%. So whilst the securitisation conduits are open, and pricing reasonable (if higher than pre-GFC), overall volumes are still well below their 2007 peaks. This is because other forms of funding are available, including direct investment. Most securitisation instruments are sold to Australian investors.

During the March quarter 2017, the increase in total assets was primarily due to an increase in other loans (up $1.9b, 12.0%), residential mortgage assets (up $1.3b, 1.4%) and cash and deposits (up $1.0b, 27.2%).

At 31 March 2017, total liabilities of Australian securitisers were $121.6b, up $4.4b (3.8%) on 31 December 2016. The increase in total liabilities was due to an increase in long term asset backed securities issued in Australia (up $7.6b, 7.8%). This was partially offset by a decrease in short term asset backed debt securities issued in Australia (down $1.9b, 42.0%) and loans and placements (down $0.6b, 6.4%).

At 31 March 2017, asset backed securities issued in Australia as a proportion of total liabilities increased to 88.6%, up 1.5% on the December quarter 2016 proportion of 87.1%. Asset backed securities issued overseas as a proportion of total liabilities decreased to 3.8%, down 0.3% on the December quarter 2016 proportion of 4.1%.

US Unemployment Rate Was 4.3 Percent in May 2017

From The US Bureau of Labor Statistics.

The US unemployment rate was 4.3 percent in May 2017, down from 4.8 percent in January. Among the unemployed, the number of job losers and persons who completed temporary jobs declined by 211,000 to 3.3 million in May, or 2.1 percent of the total labor force. In comparison, job leavers made up 0.5 percent of the labor force. These are people who quit or voluntarily ended their jobs and began searching for a new job.

Unemployed reentrants to the labor force made up 1.3 percent of the labor force in May 2017. Reentrants are people who previously worked but were out of the labor force before they began their job search. Unemployed new entrants made up 0.4 percent of the labor force in May.

These data are from the Current Population Survey. For more information, see “The Employment Situation — May 2017″

The Economy’s Growing For All The Wrong Reasons

From The New Daily.

The national accounts released on Wednesday paint an alarming picture of a slowing economy that is staying in positive growth territory for all the wrong reasons.

GDP growth of 1.7 per cent over the past year is extremely sluggish, but that’s not the main point of interest.

The contribution of household consumption was the big question, because other sources of growth – government spending, business investment and net exports – aren’t enough to get things moving.

Headline household consumption wasn’t too bad, growing 0.5 per cent in the March quarter or 2.3 per cent over the past 12 months.

However, it’s the kind of consumption that is worrying.

The biggest increases in household spending were in ‘electricity, gas and other fuel’ (up 2.9 per cent) and ‘operation of vehicles’ (1.3 per cent).

The problem with the first category is that it represents ‘price inelastic’ goods. As prices rise, we still use our gas heaters or run our cars a similar amount.

Gas and electricity prices are getting eye-watering, and average unleaded prices have gone up 8 per cent since the December quarter.

So we’re spending more money and boosting ‘growth’, while consuming roughly the same amount of energy and fuel.

As for the ‘operation of vehicles’, that is harder to quantify.

Auto-industry economist Richard Johns tells me a number of factors are at work.

While currency fluctuations are not having much of an impact on car prices, Mr Johns has noticed many Australians opting for higher price-bracket vehicles.

That takes two forms. Firstly, cars are getting better, so even basic models include features such as automatic emergency braking. For some reason, the Australian Bureau of Statistics (ABS) tends to strip out those price components when it measures car-price inflation.

As a result the ABS says car prices have fallen over the past three quarters, whereas Mr Johns’ own research shows prices paid have risen.

The second factor influencing the ‘operating of vehicles’ is that Australians who earn more of their incomes from shares and property are gradually moving into luxury marques, whereas families who rely on wages are not.

That’s not just a function of ageing, but of the inequalities being created by perverse incentives in the tax system.

Savings slide

So household consumption isn’t as rosy as Treasurer Scott Morrison implies. He said on Wednesday that “household spending continues to support the economy, while household savings remain positive.”

Well only just, Mr Treasurer. While households are spending more on gas, electricity, fuel and vehicles, they are cutting back on discretionary items – alcohol spending fell 1 per cent and clothing and footware contracted 0.7 per cent.

More worrying, though, is how all this consumption is being funded.

Shadow Treasurer Chris Bowen noted on Wednesday, “…weak household income growth is meaning that households are dipping into their savings more and more … [that’s] is not a sustainable plan for the Australian economy.”

Mr Bowen’s right, though it’s worse than he says.

Before the global financial crisis, Australians were saving very little – often a ‘negative’ amount during 2003 to 2007 (see chart below).

What that means is that, after putting away 9 per cent of their incomes as super savings, households were not only eroding that saving by racking up debts, but sometimes borrowing more than the 9 per cent.

In the days of rapid house price growth that didn’t matter too much – the ballooning equity in homes offset the low savings rate.

But look at the figures now – we’re putting away a mandatory 9.5 per cent in super, then borrow about 4.8 per cent of our incomes to give an average savings rate of 4.7 per cent.

And this time around, house prices are forecast to remain flat or falling in the near future.

All told, the national accounts show a nation spending more on life’s essentials with less money left for the kind of spending that would buoy key areas, such as the sagging retail sector.

The economy needs stimulus, which the Treasurer obliquely admits. He said at his Wednesday media conference: “We made the right choices in the budget to invest in productivity-boosting public infrastructure and to deliver further support to small businesses to invest in their future.”

All true. These are not a good set of economic figures, but at least with those pragmatic measures in the budget the government is starting to take the problems seriously

Growth Slowed in the March Quarter to 0.3 per cent

Data from the Australian Bureau of Statistics (ABS) shows the pace of growth of the Australian economy slowed in the March quarter to 0.3 per cent in seasonally adjusted chain volume terms. Through the year, GDP grew 1.7 per cent.

Investment in new housing fell by 4.4 per cent in the March Quarter 2017 which brings the sector down from record high investment in December 2016 and back to levels similar to those experienced at the start of 2016.

As Saul Estlake noted in The Conversation today:

It’s now been 103 quarters (25 years and 9 months) since Australia last had consecutive quarters of negative growth in real gross domestic product (GDP), in the March and June quarters of 1991.

Contrary to much-repeated claims, the Netherlands didn’t experience more than a quarter-century of economic growth without consecutive quarters of negative real GDP growth between the early 1980s and the global financial crisis.

The Netherlands’ real GDP declined by 0.3% in the June quarter of 2003, and by 0.01% in the September quarter of that year, according to data published by Statistics Netherlands and, separately, by the OECD. So, at best, the Netherlands went for only 22 years without experiencing a recession. Australia surpassed that benchmark in 2013.

Yes, that second quarterly decline in 2003 was almost imperceptible. But sporting records are delineated by margins as small as one one-hundredth of a second, so we can’t blithely discount a -0.01% fall in real GDP as “not relevant”.

Even if you blinked and missed that tiny second successive decline in real GDP in the September quarter of 2003, the Netherlands still wouldn’t hold the record for the longest run of continuous economic growth. That belongs to Japan – which, according to OECD data, went from the March quarter of 1960 to the March quarter of 1993 without ever registering two or more consecutive quarters of negative growth in real GDP. That’s 133 quarters, or more than 33 years.

Indeed, if Japanese GDP data were available on a quarterly basis earlier than 1960 it’s likely that this run of continuous economic growth would have been even longer, perhaps as long as 38 years, inferring from annual data available back to 1955. So Australia would need to avoid consecutive quarters of negative real GDP growth until at least 2024 if it is truly to be able to claim this “world record” as its own.

Even more importantly, the definition of a technical recession as (two or more consecutive quarters of negative growth in real GDP) is, as former RBA Governor Glenn Stevens said, “not very useful”. It was originally proposed in December 1974 by Julius Shishkin, who at that time was the head of the Economic Research and Analysis Division of the US Census Bureau (now the Bureau of Economic Analysis, which publishes the US national accounts).

It’s not used to identify recessions in the US. It takes no account of differences over time, or as between countries, in the rates of growth of either population or productivity – which are the key determinants of whether a given rate of economic growth is sufficient to prevent a sharp rise in unemployment. This is something which most people (other than economists) would use to delineate a recession.

While Australia has avoided consecutive quarterly contractions in real GDP since the first half of 1991, we’ve had two periods of consecutive quarterly declines in real per capita GDP (in 2000 and 2006). We’ve also had two periods of consecutive quarterly declines in real gross domestic income or GDI, which takes account of income gains or losses accruing from movements in Australia’s terms of trade (in 2008-09, and in 2014). Perhaps most meaningfully of all, Australia has had two episodes where the unemployment rate has risen by one percentage point or more in 12 months or less (in 2001 and 2009).

That’s still a better track record than almost any other advanced economy during the past quarter-century or so – and it reflects well on the quality of economic management (and the nature of our luck) over this period. Nonetheless, we shouldn’t be in the business of awarding ourselves prizes to which we’re not entitled.

And the long term trend also highlights a slowing, so we need new growth engines if we are to keep the growth ball in the air!

Growth was recorded across the economy with 17 out of 20 industries growing during the quarter. Strong growth was observed within the service industries including Finance and Insurance Services, Wholesale Trade, and Health Care and Social Assistance.

Agriculture, Forestry and Fishing decreased after strong growth in the previous two quarters, while Manufacturing decreased for the tenth time in eleven quarters.

Chief Economist for the ABS, Bruce Hockman said; “This broad-based growth was tempered by falls in exports and dwelling investment. Dwelling investment declined in all states, except Victoria, and overall is the largest decline for Australia since June 2009.”

Compensation of employees (COE) increased 1.0 per cent in the March quarter, a pick up from the negative growth recorded in the December quarter, and is consistent with other labour market data. COE is still only 1.5 per cent higher through the year, continuing to contribute to the reduction in the household saving rate. The household saving ratio fell to 4.7 in the March quarter, half the rate it was in March quarter 2013.

Mr Hockman said; “Even though there was a fall in dwelling investment this quarter, levels are still historically high. There was also positive growth in household consumption, albeit in non-discretionary items such as electricity and fuel purchases. The softer growth in household consumption is broadly in line with modest income growth.”

Household Debt Rising Further – RBA

The latest chart pack from the RBA to June 2017 includes the worrisome chart on household debt levels.

No sign of a change in trajectory, despite low wage growth and some lending tightening. The last available data point on household debt to income is 188.7 from December 2016.  The March data should be out soon and will be higher again.

Of course this is an average, and some households are in deep debt strife, right now, as higher mortgage rates hit. See our latest mortgage stress analysis released a couple of days ago.

Understanding the labor productivity and compensation gap

From The US Bureau of Statistics.

Increases in productivity have long been associated with increases in compensation for employees. For several decades beginning in the 1940s, productivity had risen in tandem with employees’ compensation. However, since the 1970s, productivity and compensation have steadily diverged.1 This trend, which will be referred to as the “productivity–compensation gap,” has received much scrutiny from both academics and policymakers alike.

Although research on the productivity–compensation gap has existed for some time, most work in this field has been conducted at the total nonfarm business sector or similar aggregate level.2 However, the Bureau of Labor Statistics (BLS) publishes a wealth of detailed industry-level labor productivity and compensation data. Industry data can be used to look at this topic from a fresh perspective in order to see what is driving trends in the broader economy. This Beyond the Numbers article studies underlying trends over the 1987–2015 period in 183 industries that are driving some of the widening gap between labor productivity and compensation observed in the nonfarm business sector.3 Most of the industries studied had increases in both labor productivity and compensation over the period studied; however, compensation lagged behind productivity in most cases.

Labor productivity, defined as real output per hour worked, is a measure of how efficiently labor is used in producing goods and services. There are many possible factors affecting labor productivity growth, including changes in technology, capital investment, capacity utilization, use of intermediate inputs, improved managerial skills or organization of production, and improved skills of the workforce. In this article, all references to labor productivity are labeled as productivity for ease of reference. In addition, labor compensation, a measure of the cost to the employer for securing the services of labor, is defined as an employee’s base wage and salary plus benefits. All references to labor compensation are on a per-hour basis and are adjusted for price change but are labeled as compensation for ease of reference.4 Measures of hours worked and compensation cover all workers including production, supervisory, self-employed, and unpaid family workers.

The productivity–compensation gap by sector and industry

To understand the productivity–compensation gap at an industry-level, it is helpful to first consider this relationship in different sectors of the economy. Each sector referenced below in chart 1 represents the combined activity of many individual industries that perform a similar type of activity.5

Productivity outpaced compensation for the 1987–2015 period in all sectors with significant industry coverage except for the mining sector. (See chart 1.) Some sectors including information, manufacturing, and retail trade exhibited major gaps between productivity and compensation, while other sectors such as accommodation and food services and other services showed slight differences. Compensation in chart 1 has been adjusted for inflation with the BLS Consumer Price Index (CPI).

As mentioned earlier, there have not been many studies of the productivity–compensation gap at the industry level. BLS industry productivity data allow for a deeper analysis by providing information on industries that make up each sector in the panels of chart 1. When examined at a detailed industry level, the average annual percent change in productivity outpaced compensation in 83 percent of 183 industries studied. (See chart 2.) The distance of each industry (represented by a dot) to the equal growth rates line indicates the size of the productivity–compensation gap. Industries above the equal growth rates line saw productivity outpace compensation and those below saw compensation outpace productivity. The largest differences between productivity and compensation occur in Information Technology- (IT) related industries such as computer and peripheral equipment manufacturing, and semiconductor and other electronic component manufacturing.

Does the type of price adjustment matter?

As mentioned above, compensation is calculated in real terms by adjusting nominal values to exclude changes in prices over time. The price indexes that are used to adjust dollar amounts for changes in prices are referred to as “deflators.”

The Consumer Price Index (CPI) is typically used to adjust compensation as it measures how the prices of a basket of consumer goods change over time. Thus, using the CPI shows how changes in workers’ purchasing power compare to productivity within their respective industries. In most cases, productivity gains did not equate to a proportional rise in workers’ purchasing power of goods and services. (See chart 2.)

However, the CPI might not be the most appropriate deflator to use when comparing compensation to productivity. Workers are compensated based on the value of goods and services produced, not on what they consume. Using an output price deflator, a measure of changes in prices for producers, instead of the CPI is an alternative that better aligns what is produced to the compensation that workers receive. Each industry has its own unique output deflator that matches the goods and services that are produced in that industry.6

If the output deflator is used to adjust compensation, a different story emerges. Chart 3 shows that the compensation workers are receiving is rising more in line with productivity than when CPI deflators are used to adjust compensation. The largest gaps from chart 2 shrink considerably once this adjustment is made. In fact, the size of the gap decreased in 87 percent of industries that previously showed productivity rising faster than compensation.

Charts 2 and 3 show an interesting contrast in employee compensation—employees are both consumers and producers. Using the CPI as a deflator is appropriate for analyzing the purchasing power of employees. However, from a producer perspective, using the output deflator is more appropriate for comparing the compensation workers receive for the goods and services they produce in their industry.

Components of the productivity–compensation gap

The gap between productivity and compensation can be divided into two components: (1) the difference between compensation adjusted by the CPI and by the output deflator, as detailed in the previous section and (2) the change in the labor share of income.7 The labor share of income measures how much revenue is going to workers as opposed to the other components of production—intermediate purchases and capital.8

Using the power generation and supply industry as an illustrative example, chart 4 shows how the overall gap in labor productivity and compensation within an industry can be divided into these two components. In this case, the decline in labor share and the difference in deflators contributed equally to productivity rising faster than compensation over the period studied. The composition of the gap, however, varies by sector and industry. For example, the software publishing industry posted a 42-percent decline in its labor share while the newspaper, periodical, book, and directory publishers industry experienced a 22-percent increase in its labor share. All 183 industries are affected differently by current economic trends, which would explain why the labor share and difference in deflators vary by industry.

Chart 5 shows the composition of the productivity–compensation gap at the sector level, which varied significantly. The difference in deflators contributed to the gap in seven of the sectors and was particularly large in the information, wholesale trade, and retail trade sectors. The change in labor’s share of income also contributed to the gap in seven of the sectors and was most important in explaining the gap in manufacturing. In the mining sector, an increase in the labor share led to hourly compensation growing faster than productivity. Both of these components are important in explaining the widespread existence of productivity–compensation gaps among U.S. industries.

The composition of the productivity—compensation gap at the detailed industry level shows 79 percent of the 183 detailed industries had an output deflator that increased slower than the CPI. This means that the rate of change in the productivity–-compensation gap grew faster when adjusted by the CPI than by an output deflator. This difference in deflators contributed to the overall gap between productivity and compensation. The median difference in growth rates between the output deflator and CPI was -0.6 percent per year.

The labor share of income declined in 77 percent of industries studied. This means that a growing share of income was going to factors of production other than employee compensation over the period studied. Factors of production include labor, capital (e.g. machinery, computers, and software), and intermediate purchases (purchased materials, services and energy that go into producing a final product). The median growth rate in the labor share of income was -0.6 percent per year. The median effect of the change in labor share was the same as that of the difference in deflators.

High productivity—wide compensation gaps

Industries with the largest productivity gains experienced the largest productivity–compensation gaps. (See chart 6.) This group of high productivity industries experienced huge technological advances during the IT boom. All of these industries saw compensation rise much more slowly than productivity over time. This was mainly due to the difference in deflators. The prices of the electronic components used in production for these industries fell substantially over time. This is in contrast to the CPI, which rose steadily over the same period. The change in labor’s share of income was a much smaller contributor to the gap for these industries but still declined in each one.

The strong correlation between productivity and the productivity–compensation gap was primarily due to the difference in deflators. The relationship between productivity and the change in labor share was much weaker, yet it still existed. The difference in deflators was the stronger effect among high productivity industries while the change in labor’s share of income was the stronger effect among most other industries.

What about the 17 percent of industries that saw compensation rise at least as fast as productivity?  These tended to be industries with low productivity growth or even productivity declines. (See chart 7.) The median change in productivity of these industries since 1987 was 0.4 percent per year. In contrast, the median change in productivity of industries that saw compensation rise slower than productivity was 1.9 percent.

Industries in which compensation grew the fastest relative to productivity include the water, sewage, and other systems industry; the golf courses and country clubs industry; and the newspaper, periodical, book, and directory publishers industry. The first industry had a large difference in deflators, the second industry saw a large increase in the labor share, and the third industry had a combination of these two components affecting the gap. All three of these industries had productivity declines over the period.

Why the decline in labor share?

Although the difference in deflators explains much of the gap, as mentioned earlier, the share of income going to workers has declined in 77 percent of industries since 1987.

This raises the question: if not for labor compensation, what were the revenues used for?9 Industries divide their income amongst three broad groups: intermediate purchases, capital, and labor compensation. Relative changes to both intermediate purchases and capital can affect labor compensation. It is likely that numerous factors are responsible for recent changes in the labor share.

Using the information sector as an example, we can see in chart 8 that some industries had significant declines in labor’s share of income while others had modest declines or even increases from 1987 to 2015. The largest declines in labor share were in newer, information technology-related industries such as software publishing and wireless telecommunications carriers, where labor share declined by 23 and 16 percentage points respectively. These industries also saw a large rise in output and productivity in this period. In contrast, labor share increased by 7 percentage points in the more established newspaper, periodical, book, and directory publishing industry, which declined in output and productivity.

It is important to note that the reason for declining labor share will likely vary significantly by industry. Here are some plausible explanations:

Globalization – Some of the income that might have gone to domestic workers is now going to foreign workers due to increased offshoring (i.e. the outsourcing of production and service activities to workers in other countries). This could have caused intermediate purchases to increase and labor compensation to decrease.10

Increased automation – It is possible that increased automation has been leading to an overall drop in the need for labor input. This would cause capital share to increase, relative to labor share as machines replace some workers.11

Faster capital depreciation – It is possible that the capital used by industries is depreciating at a faster rate in recent years than in the past. These assets include items such as computer hardware and software that are upgraded or replaced more frequently than machinery used in prior decades. This faster depreciation could require a higher capital share to cover upgrade and replacement costs.12

Change over time

The American economy is dynamic and changes over time. These changes appear in the productivity–compensation gap and its components. Chart 9 shows the components of the gap in each sector for the 1987–2000 and 2000–2015 periods. These periods roughly divide the data in half and use an important point in the business cycle as a breakpoint. Several observations can be made based on this chart.

First, the average productivity–compensation gap among the sectors grew faster in the first period than in the second. This was mainly due to changes in the utilities and wholesale trade sectors.

Second, the difference in deflators accounted for most of the gap on average in the first period, but had a smaller effect on average in the second period. This was particularly true in the utilities, manufacturing, wholesale trade, and transportation and warehousing sectors.

Third, there are large changes in labor’s share of income happening in the mining and manufacturing sectors during the two periods. The manufacturing sector’s drop in labor share during the 2000–2015 period was the largest decline observed in any sector and time period. Conversely, mining experienced the largest increase in labor share during the 2000–2015 period.

What about changes over time in detailed industries? Chart 10 shows how the components of the gap changed over time in industries with the highest employment in 2015. These 10 industries, ordered by employment, made up about 39 percent of the total employment of the 183 industries studied. The first three industries in the chart had component effects that flipped direction from one period to the next. Other general merchandise stores industry, which includes warehouse clubs and supercenters, had a very large drop in labor’s share of income in the first period and a much more modest drop in the second. Charts 9 and 10 show that the productivity and compensation dynamics of sectors, and the industries within them, are changing over time and will likely continue to do so as the economy evolves.

Choosing the right tools, focusing on industries

Studying the productivity and compensation trends of industries can help us better understand the productivity–compensation gap observed in the broader economy. It can show which industries have the largest gaps and the extent to which gaps are widespread. It is important to choose an appropriate deflator for compensation when comparing to productivity. Failing to do so can exaggerate the gap, especially for high productivity industries. A full 83 percent of industries studied here had productivity–compensation gaps when the same deflator was used for output and compensation. These gaps came from a declining labor share of income. Sectors with the strongest declines in labor share included manufacturing, information, retail trade, and transportation and warehousing. Although the causes of the decline in labor share are still unclear, focusing on industries may help to isolate and understand the causes unique to each industry.

1 See Susan Fleck, John Glaser, and Shawn Sprague, “The compensation–productivity gap: a visual essay,” Monthly Labor Review, January 2011, https://www.bls.gov/opub/mlr/2011/01/art3full.pdf.

2 For example, see Barry Bosworth and George L. Perry, “Productivity and Real Wages: Is There a Puzzle?” Brookings Papers on Economic Activity, 1:1994, https://www.brookings.edu/bpea-articles/productivity-and-real-wages-is-there-a-puzzle/.

3 The detailed industries in this article include all published industries at the 4-digit NAICS level as well as some industries at the 3-, 5-, and 6 digit level for cases where the 4 digit is not published. There is an exception for NAICS industry 71311, which is used in place of NAICS 7131. This was done because NAICS 71311 is published back to 1987 while NAICS 7131 is only published back to 2007 and the more detailed industry makes up most of the 4-digit industry.

4 The measure of real hourly compensation used in this article differs from the labor compensation measure typically published for the industries examined. Measures of labor compensation typically published are not adjusted for inflation or on a per-hour basis. The measures of real hourly compensation calculated here are available upon request.

5 The sectors in this article are 2-digit NAICS sectors. The detailed industries, defined in the third endnote, are components of these sectors.

6 Industry output deflators are mostly based on Producer Price Indexes (PPIs) unique to each industry. PPIs measure price change from the perspective of the seller. Consumer Price Indexes (CPIs) for individual products are used to deflate output in some industries (e.g. industries in retail trade).

7 The rates of change calculated in this article are compound annual growth rates. One must use logarithmic changes for the components of the gap between productivity and real hourly compensation to equal the total gap in all cases. For most industries, the components sum up to the total gap using either method but may differ by 0.1 percent due to rounding.

8 Intermediate purchases include all of the purchased materials, services, and energy that go into producing a final product. Measures of the labor share included in this analysis are not directly comparable with the labor share measures of the nonfarm business sector, business sector, or nonfinancial corporate sector. The difference has to do with how output is measured at the industry and major sector levels. Measures at the industry level exclude intra-industry transactions but include all other intermediate purchases. Output at the major sector level is constructed using a value-added concept and subtracts out all intermediate purchases. Thus, industry output can be divided between labor, capital, and intermediate purchases, whereas major sector output can only be divided between labor and capital.

9 For another BLS discussion of the labor share of income, see Michael D. Giandrea and Shawn A. Sprague, “Estimating the U.S. Labor Share,” Monthly Labor Review, February 2017, https://www.bls.gov/opub/mlr/2017/article/estimating-the-us-labor-share.htm.

10 See Michael W. L. Elsby, Bart Hobijn, and Aysegul Sahin, “The Decline of the U.S. Labor Share,” Brookings Papers on Economic Activity, Fall 2013, https://www.brookings.edu/wp-content/uploads/2016/07/2013b_elsby_labor_share.pdf. A number of possible explanations for the declining labor share were examined. Analysis showed that offshoring of labor-intensive work is a leading potential explanation.

11 See Maya Eden and Paul Gaggl, “On the Welfare Implications of Automation,” Policy Research Working Paper, No. 7487, World Bank Group, November 2015, http://documents.worldbank.org/curated/en/2015/11/25380579/welfare-implications-automation. Some of the decline in labor’s share of income can be linked to an increase in the income share of information and communication technology (ICT). ICT effects may have had a larger impact on the distribution of income among workers.

12 See Dean Baker, “The Productivity to Paycheck Gap: What the Data Show,” Center for Economic and Policy Research, April 2007, http://cepr.net/publications/reports/the-productivity-to-paycheck-gap-what-the-data-show This is one of many articles that documents the fact that a rising share of GDP goes to replace worn-out capital goods. Income going towards replacing these goods should not be expected to raise living standards.

Once Again RBA Holds

The latest from the RBA continues the mixed story, with some better economic indicators, but also higher risks from household debt. As a result they held the cash rate again.

At its meeting today, the Board decided to leave the cash rate unchanged at 1.50 per cent.

The broad-based pick-up in the global economy is continuing. Labour markets have tightened further in many countries and forecasts for global growth have been revised up since last year. Above-trend growth is expected in a number of advanced economies, although uncertainties remain. In China, growth is being supported by increased spending on infrastructure and property construction, with the high level of debt continuing to present a medium-term risk. Commodity prices are generally higher than they were a year ago, providing a boost to Australia’s national income. The prices of iron ore and coal, however, have declined over recent months as expected, unwinding some of the earlier increases.

Headline inflation rates in most countries have moved higher over the past year, partly reflecting the higher commodity prices. Core inflation remains low, as do long-term bond yields. Further increases in US interest rates are expected over the year ahead and there is no longer an expectation of additional monetary easing in other major economies. Financial markets have been functioning effectively.

Domestically, the transition to lower levels of mining investment following the mining investment boom is almost complete. Business conditions have improved and capacity utilisation has increased. Business investment has picked up in those parts of the country not directly affected by the decline in mining investment. Year-ended GDP growth is expected to have slowed in the March quarter, reflecting the quarter-to-quarter variation in the growth figures. Looking forward, economic growth is still expected to increase gradually over the next couple of years to a little above 3 per cent.

Indicators of the labour market remain mixed. Employment growth has been stronger over recent months, although growth in total hours worked remains weak. The various forward-looking indicators point to continued growth in employment over the period ahead. Wage growth remains low and this is likely to continue for a while yet. Inflation is expected to increase gradually as the economy strengthens. Slow growth in real wages is restraining growth in household consumption.

The outlook continues to be supported by the low level of interest rates. The depreciation of the exchange rate since 2013 has also assisted the economy in its transition following the mining investment boom. An appreciating exchange rate would complicate this adjustment.

Conditions in the housing market vary considerably around the country. Prices have been rising briskly in some markets, although there are some signs that these conditions are starting to ease. In other markets, prices are declining. In the eastern capital cities, a considerable additional supply of apartments is scheduled to come on stream over the next couple of years. Rent increases are the slowest for two decades. Growth in housing debt has outpaced the slow growth in household incomes. The recent supervisory measures should help address the risks associated with high and rising levels of indebtedness. Lenders have also announced increases in mortgage rates, particularly those paid by investors and on interest-only loans.

Taking account of the available information, the Board judged that holding the stance of monetary policy unchanged at this meeting would be consistent with sustainable growth in the economy and achieving the inflation target over time.