|One-year inflation rate, 2014-Q4, 10-year z-score, relative to own country's history. Source: FactSet data, gunnmap.herokuapp.com, author's elaboration.|
No time for writing this week, so I'm listing blog posts and articles that caught my eye recently:
1. Liftoff levers
. John Cochrane is doing a fantastic job explaining how the Fed's reverse repo operations are supposed to work. Start with this post
, and then read this other one
2. A "new" working paper
, by Katharina Knoll, Mortiz Schularick, and Thomas Steger, looks at global house prices in the really long run (1870-2012).
From the abstract:
...house prices in most industrial economies stayed constant in real terms from the 19th to the mid-20th century, but rose sharply in recent decades. Land prices, not construction costs, hold the key to understanding the trajectory of house prices in the long-run. Residential land prices have surged in the second half of the 20th century, but did not increase meaningfully before. We argue that before World War II dramatic reductions in transport costs expanded the supply of land and suppressed land prices. Since the mid-20th century, comparably large land-augmenting reductions in transport costs no longer occurred. Increased regulations on land use further inhibited the utilization of additional land...
3. An Icelander goes to Cyprus and tells us why Cypriots keep cash worth 6% of GDP under the mattress
.--Sigrún Davíðsdótti at A Fistful of Euros.
4. China's monetary and exchange rate framework under pressure
4.1 Huge FX inflows turn into small outflows, and the PBoC switches from draining renminbis to injecting them
. To keep base money growing, the central bank has introduced new tools. By Gabriel Wildau for the Financial Times.
4.2 Time to ditch the renminbi-dollar peg
? The Chinese currency has depreciated and is hitting the central bank's target band.
4.3 On the internationalization of the RMB, a colleague forwards several papers and reports
Paths to a reserve currency
, at the Asian Development Bank Institute.
The rise of the redback
, by HSBC.
Yuan is fifth world's payments currency
, at the WSJ.
An important event to keep in mind is that the IMF is reviewing the SDR basket in 2015. China is under pressure to step up the internationalization of the renminbi, ahead of the basket review.
5. Dani Rodrik summarizes
the results of his latest paper on de-industrialization
Premature deindustrialization is not good news for developing nations. It blocks off the main avenue of rapid economic convergence in low‐income settings, the shift of workers from the countryside to urban factories where their productivity tends to be much higher.
Industrialization contributes to growth both because of this reallocation effect and because manufacturing tends to experience relatively stronger productivity growth over the medium to longer term. In fact, organized, formal manufacturing appears to exhibit unconditional convergence (Rodrik 2013), which makes it special and an engine of growth. Since low‐income countries tend to start with small manufacturing sectors, the dynamic within manufacturing initially plays a small role, overshadowed by the reallocation effect. But over time, the within‐manufacturing effect becomes a more potent force as the manufacturing sector becomes larger.Premature deindustrialization throws sand in the wheels of both engines (Rodrik 2013, 2014).
The consequences are already visible in the developing world. In Latin America, as manufacturing has shrunk informality has grown and economy‐wide productivity has suffered. In Africa, urban migrants are crowding into petty services instead of manufacturing, and despite growing Chinese investment there are as yet few signs of a real resurgence in industry. Where growth occurs, it is driven largely by capital inflows, transfers, or commodity booms, raising questions about its sustainability.
In the absence of sizable manufacturing industries, these economies will need to discover new growth models. One possibility is services‐led growth. Many services, such as IT and finance, are high productivity and tradable, and could play the escalator role that manufacturing has traditionally played. However, these service industries are typically highly skill‐intensive, and do not have the capacity to absorb – as manufacturing did – the type of labor that low‐ and middle‐income economies have in abundance. The bulk of other services suffer from two shortcomings. Either they are technologically not very dynamic. Or they are non‐tradable, which means that their ability to expand rapidly is constrained by incomes (and hence productivity) in the rest of the economy.
I couldn't help but tie Rodrik's paper to that other paper by Pritchett and Summers
, the one about regression to the mean of long-term growth rates. Growth is far from a uniform process. It tends to happen in fits and starts. Those who are projecting high growth rates of developing economies, based on past high growth rates, which in turn hinged on industralization, are probably going to be disappointed.
6. The translation industry
.The Economist opines
that translation is very hard for machines. Humans will need to stay involved, but technology will improve productivity.
A different question: Do improvements in translation bode well for language diversity in the world? How about the language learning industry? I see this as a race between technologies that allow machines to translate better, and technologies that allow humans to learn languages faster. The machines are winning, by a long shot. We're clearly on a path to better simultaneous translation capabilities. Soon we'll be able to listen to anything, anywhere in our native tongue, in real time. That means humans won't have to know more than one language. Learning languages will become a hobby, like dancing. (Sorry, parents, but you're wasting your money on Mandarin lessons.)
As for language diversity, I think a more important force than technology is urbanization. The lion's share of the world's languages are spoken by small, rural communities in developing countries. Urbanization increases the usefulness of majority languages, killing the minority languages. And urbanization will happen faster than the spread of cheap, simultaneous translation technology. At some point, however, the trend towards fewer and fewer languages will slow down, as simultaneous translation becomes pervasive.
Hideki Konishi, Kozo Ueda, and Mitsuru Katagiri presented a few months ago a paper titled "Aging and deflation from a fiscal perspective
." Here are the slides
The authors build a model that combines overlapping generations, the fiscal theory of price determination, and political considerations to analyze how the price level changes with fertility and longevity.
The simplified version of the model, in section two of the paper, assumes that taxes are exogenous. This simple version, nevertheless, is enough to produce a key result:
"Aging is deflationary when caused by an increase in longevity, but inflationary when caused by a decline in birth rate."
The reason is political considerations:
"If the birth rate declines, the resultant contraction in the tax base reduces the fiscal surplus. The government is then inclined to maintain its solvency partly by generating inflation at the cost of the older generation's well-being and partly by making the younger generation pay more taxes. In contrast, if the life expectancy increases and older persons survive longer than expected, they might face a shortage of savings for their retirement period. The government then, led by the strengthened political influence of the older generation, attempts to suppress inflation and increase the real value of the government bonds held by the older generation."
Japan has experienced both unexpected declines in fertility and unexpected increases in longevity. The deflationary effect of higher longevity, however, dominated. The authors' simulations of the model show that Japan's aging depressed inflation by 0.6 percentage points annually.
Another key result, which comes from the fiscal theory of price determination, is that our children don't pay for our deficits. The government debt at the beginning of each period is fixed in nominal terms. Today's price level changes to equate the real value of today's debt with the present value of future deficits.
A corollary of this result is that tomorrow's fiscal policy is not constrained by today's level of debt or fiscal policy. Governments are unencumbered by the deficits of their predecessors in office.
A second corollary of the fiscal independence result is that governments don't have an incentive to strategically accumulate debt. In some political economy models of fiscal policy, a government can tie the hands of a successor it dislikes, by raising debt. If the price level, however, adjusts every year to fulfill the government's inter-temporal budget constraint, strategic debt accumulation doesn't happen.
I thought this paper was a refreshing way of looking at the link between deflation and aging.
Other recent papers (post 2000) about this topic, in chronological order:
Lindh, T. and B. Malmberg (2000) “Can age structure forecast inflation trends?”, Journal of Economics and Business, 52, pp 31–49.
The demographic age structure influences the aggregate of individual economic decisions. Standard macroeconomic models imply that inflation pressure will covary with the age distribution unless accommodated by monetary policy. We estimate the relation between inflation and age structure on annual OECD data 1960–1994 for 20 countries. The result is an age pattern of inflation effects consistent with the hypothesis that increases in the population of net savers dampen inflation, whereas especially the younger retirees fan inflation as they start consuming out of accumulated pension claims. This can be explained, for example, with life-cycle saving behavior combined with a cumulative process of inflation, but other mechanisms are also consistent with the results. In any case, the results suggest that demographic projections may be useful for long- and medium-term inflation forecasts. Forecasts from our panel model catch the general downward trend in OECD inflation in the 1990s. However, useful forecasts for individual countries need to incorporate more country-specific information.
Bullard J., C. Garriga and C. J. Walker (2012) “Demographics, Redistribution, and Optimal Inflation” Federal Reserve Bank of St. Louis Review, November/December 2012, 94(6), pp. 419–39.
The authors study the interaction among population demographics, the desire for intergenerational redistribution of resources in the economy, and the optimal inflation rate in a deterministic life cycle economy with capital. Young cohorts initially have no assets and wages are the main source of income; these cohorts prefer relatively low real interest rates, relatively high wages, and relatively high rates of inflation. Older cohorts work less and prefer higher rates of return from their savings, relatively low wages, and relatively low inflation. In the absence of intergenerational redistribution through lump-sum taxes and transfers, the constrained efficient competitive equilibrium requires optimal distortions on relative prices. The authors’ model allows the social planner to use inflation/deflation to try to achieve the optimal distortions. In the model economy, changes in the population structure are interpreted as the ability of a particular cohort to influence the redistributive policy. When older cohorts have more influence on the redistributive policy, the economy has a relatively low steady-state level of capital and a relatively low steady-state rate of inflation. The opposite happens when young cohorts have more control of policy. These results suggest that aging population structures, such as those in Japan, may contribute to observed low rates of inflation or even deflation.
Anderson, D., D. Botman and B. Hunt (2014) ”Is Japan’s Population Aging Deflationary?” IMF Working Paper 14/139, August.
Japan has the most rapidly aging population in the world. This affects growth and fiscal sustainability, but the potential impact on inflation has been studied less. We use the IMF’s Global Integrated Fiscal and Monetary Model (GIMF) and find substantial deflationary pressures from aging, mainly from declining growth and falling land prices. Dissaving by the elderly makes matters worse as it leads to real exchange rate appreciation from the repatriation of foreign assets. The deflationary effects from aging are magnified by the large fiscal consolidation need. Many of these factors will beset other advanced countries as well, but we find that deflation risk from aging is not inevitable as ambitious structural reforms and an aggressive monetary policy reaction can provide the offset.
Yoon, J.-W., J. Kim and J. Lee (2014) “Impact of Demographic Changes on Inflation and the Macroeconomy” IMF Working Paper 14/210 November.
The ongoing demographic changes will bring about a substantial shift in the size and the age composition of the population, which will have significant impact on the global economy. Despite potentially grave consequences, demographic changes usually do not take center stage in many macroeconomic policy discussions or debates. This paper illustrates how demographic variables move over time and analyzes how they influence macroeconomic variables such as economic growth, inflation, savings and investment, and fiscal balances, from an empirical perspective. Based on empirical findings—particularly regarding inflation—we discuss their implications on macroeconomic policies, including monetary policy. We also highlight the need to consider the interactions between population dynamics and macroeconomic variables in macroeconomic policy decisions.
Juselius, M. and Takáts, E. (2015) “Can Demography Affect Inflation and Monetary Policy?” BIS Working Paper 485, February.
Several countries are concurrently experiencing historically low inflation rates and ageing populations. Is there a connection, as recently suggested by some senior central bankers? We undertake a comprehensive test of this hypothesis in a panel of 22 countries over the 1955-2010 period. We find a stable and significant correlation between demography and low-frequency inflation. In particular, a larger share of dependents (ie young and old) is correlated with higher inflation, while a larger share of working age cohorts is correlated with lower inflation. The results are robust to different country samples, time periods, control variables and estimation techniques. We also find a significant, albeit unstable, relationship between demography and monetary policy.
The world might not be "deleveraging," but I wouldn't know just by looking at the debt-to-GDP ratio.
The latest update
to the McKinsey Global Institute's "Debt and deleveraging" report says that
...debt continues to grow. In fact, rather than reducing indebtedness, or deleveraging, all major economies today have higher levels of borrowing relative to GDP than they did in 2007. Global debt in these years has grown by $57 trillion, raising the ratio of debt to GDP by 17 percentage points.
What does a debt-to-GDP ratio of, say, 286% mean? It means that if a country devoted all its income to paying down debt, it would take 2.86 years, at today's income level, to pay it all off. And if the ratio rises to 300% next year, it means the country's debts grew faster than its income.
At first consideration it makes sense to normalize debt levels across countries and over time using GDP. Bigger and wealthier nations should be able to support more debt than smaller or poorer ones. And if income grows over time, a country should have the capacity to borrow more.
The proceeds from borrowing, however, are (often) not consumed, but rather used to buy assets. And if you have more assets you should be able to bear more debt too.
Suppose you make $200k this year. You buy a house that costs $500k, making a $100k downpayment, and getting a $400k mortgage. You have no other assets or debt. Your debt-to-income ratio in year 1 is 2 ($400k / $200k).
Next year you make $200k again, save $100k, and buy another $500k house, with a $400k mortgage and $100 downpayment. The principal on the first mortgage is still $400k. Now your debt-to-income ratio is 4 ($800k / $200k). Your "leverage" is going up fast!
If you measure leverage a different way, however, you will see that debt is not going up at all. Continuing with the example above, the debt-to-equity ratio is 4 at the end of year 1 ($400 / $100), and still 4 at the end of year 2 ($800 / $200). Leverage is stable.
You could question whether servicing an $800k debt is a sane financial decision for somebody with a stagnant $200k income. But a broad discussion about "leverage" shouldn't leave the two houses out of the equation.
"Leverage," measured by the conventional debt-to-GDP ratio, has been going up in a number of countries for decades:
Other than Japan, debt-to-GDP has been generally going up in the long run.
You might think that the world has been on a multi-decade borrowing binge that will be, eventually, corrected. But while we wait for the Big Crash, we could entertain another possibility: the economy's balance sheet is just growing faster than income is.
I don't mean to say there's nothing to worry about. I have no clue whether national assets or equity have gone up in most countries, or whether the increase in the value of assets or equity matches the rise in debt. Besides, asset values can fall just as quickly as they rise. And, crucially, one needs to consider the distribution of assets and debt within the economy to make any assessment of "stability," "risk," or "sustainability."
Nonetheless, looking at rising debt-to-GDP ratios and concluding, as McKinsey does, that leverage is going up, which "poses new risks to financial stability and may undermine global economic growth," is quite a leap, to the say the least. A more complete assessment of "leverage" would be welcome.
P.S. Antonio Fatás
has similar concerns about the McKinsey report.
A recent post
by Antonio Fatás got me curious about the composition of growth between 2007 and 2013. (Beware, however, that the period doesn't comprise a full business cycle, and that some European economies suffered two recessions during that period.)
Antonio shows that, between 2007 and 2013, the growth of productivity -measured as GDP per worker- was strongest in Spain, U.S., and Ireland. (I don't know where his data come from, so I make no attempt to replicate, correct, or comment on his findings.)
I look at data on the decomposition of growth from the Conference Board's Total Economy Database (TED). I start with the (geometric) average growth rate of GDP:
Australia, Switzerland, Canada, and the U.S. posted the fastest growth, whereas the GIPS were the weakest.
How was growth split between the increases in labor quantity and labor productivity?
Once again, the GIPS shed the most labor, whereas Australia, Switzerland, Norway, and Canada added the most. (Notice that three of the top four are commodity economies.) In the U.S. total labor input decreased between 2007 and 2013 (although much less than in the GIPS).
On productivity, Australia is still among the top performers, and so is Canada. But here the news is that two of the GIPS (Ireland and Spain) are near the top, along with the U.S. In Italy and Greece productivity declines sharply, and so does in the U.K. This feature of the U.K. recovery (relatively small job loss, and massive declines in productivity) has been covered several times
by the FT.
Productivity growth can further be decomposed into the contributions of: changes in labor composition (essentially, changes in the education of the employed), capital additions, and "dark matter" (also known as total factor productivity).
Starting with labor composition:
Portugal, Greece, and Spain improved the quality of their employed the most, whereas Italy did so the least. The labor composition didn't make a negative contribution to growth anywhere.
The contribution of capital (the sum of ICT and non-ICT capital) was also positive in every country, and was largest among commodity economies, as well as Ireland. Greece here is number six. Italy is once again last.
Finally, and strikingly, total factor productivity growth was negative almost everywhere:
TFP contributed the most to growth in some of the richest economies (U.S., Japan, Germany, Switzerland) and the least in Greece, Norway, U.K., and Portugal.
To sum up:
1) Output growth was fastest among commodity economies (Australia and Canada), as well as the U.S. and Switzerland, thanks to generally growing labor input (or a small loss, in the U.S.), fast growth of capital, and some growth of TFP in the U.S.
2) Labor composition (the "quality" of labor) added to growth everywhere, whereas total factor productivity was negative everywhere except in the U.S. and Japan.
3) Southern European countries lost the most employment.
4) Productivity shrunk by a massive amount in Greece. Italy, the U.K., and the Netherlands also saw their productivity decline.