But alongside these well known statistics, there are a few lesser viewed numbers worth keeping an eye on to gain a more nuanced picture of the labour market.

Actual hours worked

As it says on the tin, this estimates the actual number of hours worked in the economy, seasonally adjusted. In May, this hit a new high – above the pre-recession peak.

Redundancies

How many people have either been made redundant or taken voluntary redundancy. Though the numbers are down on a year ago, there has been an uptick in the last three months, adding to the picture of a weakening labour market.

Economic inactivity by reason

This looks at those people who are inactive in the job market, but aren’t captured by the unemployment numbers as they have not been seeking work within the last four weeks and/or they are unable to start work within the next two weeks.

This chart is notable as it shows the rise in student numbers from the early 2000s and the decline in the number of people choosing to stay at home – both a direct result of government policies. However bumping along the bottom, almost unchanged, are the “discouraged workers” for whom policy interventions have been much less effective.

Last year I got a call from someone at DWP. The call went roughly as follows:

DWP: We’ve got a story for you. Figures show that the benefit cap is working and it hasn’t even been brought in yet.

Me: Really? How do they do that?

DWP: Well the number of people who have come off benefits since we announced the policy is XXX thousand. [I forget the actual number the person used.]

Me: Right, and how do you know they are coming off because of the cap?

DWP: Well, we don’t know for sure, but there is anecdotal evidence from Job Centres around the country that the threat of the cap is making people decide to go back to work.

Me: But how do you know that that is true for all XXX thousand who have found work in this period?

DWP: We can’t prove it with numbers, but anecdotal evidence….

Me: There is one way to at least suggest it with facts. Can you show the number going into work is much higher than in equivalent periods in previous years?

DWP: I’ll see if we can get that for you.

I didn’t hear from the contact about the story again.

Having had multiple conversations like this with DWP officials, it doesn’t surprise me at all that Iain Duncan Smith has been criticised by the official stats watchdog today for misusing statistics.

The work and pensions secretary claimed just before the cap came in last month:

Already we’ve seen 8,000 people who would have been affected by the cap move into jobs. This clearly demonstrates that the cap is having the desired impact.

But the data simply didn’t support the claim that there was a link between the two. In fact the Job Centre release from which the data was taken said the figures were

not intended to show the additional numbers entering work as a direct result of the contact

In fact, even if DWP had provided me with information showing the numbers coming off benefits had gone up sharply, that wouldn’t necessarily have supported their claim. A much more direct reason, as the Job Centre release originally stated, is the fact that the eligibility criteria had changed. Put simply, fewer people were on benefits because they simply weren’t allowed to be.

Andrew Dilnot, chair of the UK Statistics Authority, says in a letter to the TUC (which first made a complaint about the issue):

We have concluded that the statement attributed to the secretary of state for work and pensions… is unsupported by the official statistics published by the department on 15 April.

In the techy world of government stats, this is pretty brutal criticism.

Professors Reinhart and Rogoff were embarrassed by a spreadsheet gaffe. Now statisticians within the Japanese government are smarting, after a private-sector economist pointed out errors that led them to overstate weakness in the economy during the fourth quarter last year.

In an announcement to the Japanese press club on Tuesday evening, the Cabinet Office said that a miscalculation of the value of trade in services between October and December meant that nominal gross domestic product was reported as shrinking by 0.3 per cent, rather than the true figure of 0.1 per cent.

With Britain’s economy bumping along the bottom and official data prone to large revisions, analysts have been on the lookout for indicators of regional and national recovery.

Until now, no one spotted a good set of figures, quietly collated at the Health and Safety Executive. Cranes puncturing the skyline are the most visible indicator of economic dynamism and have often been used to gauge the heat in economies as diverse as Dubai or China and the torpor of Tokyo.

The HSE started requiring the operators of tower cranes – used for new office buildings, infrastructure, larger residential blocks and big public sector projects – to register their addresses in 2010, providing an invaluable snapshot of the building industry in action.

The results show a remarkable degree of concentration in London and its surrounding counties, signifying a gulf between the optimism about a prosperous future for the capital and pessimism in the rest of the UK.

With London home to only one in eight people in the UK, it has seen more tower cranes notified to the HSE than all the rest of the UK put together. Almost eight in 10 cranes were in London, the southeast and the east of England.

This week may signal a new phase in the eurozone’s continued battle for economic recovery.

Tuesday’s unemployment data will set the tone for Thursday’s European Central Bank interest rate announcement. With unemployment at a record high of 12 per cent, commentators see no early signs of any improvement.

“Companies continue to shed labour at a fast pace,” says Madhur Jha, of HSBC. “Forward-looking indicators show that things are unlikely to improve next month.”

Falling inflation and soft business survey data contribute to the atmosphere of continued weakness.

In the light of this, the ECB is now widely expected to cut interest rates soon. While a rate cut is certainly possible this week, recent indications suggest the ECB may choose to take further non-standard monetary steps first.

“The release of the next ECB projections in June and eurozone first-quarter GDP data in May would make a rate cut in June still more plausible than [this] week,” says Rob Carnell, of ING.

The most likely candidate as an alternative measure would be for the securitisation of loans to small businesses, to ease credit in this area of the economy.

An early indication of the severity of the continued weakness in global spending should come from Korea’s April export figures, out on Wednesday. Last week’s poor China flash manufacturing PMI the Korean data will not be encouraging.

The US Federal Reserve’s Open Market Committee is not expected to make any change to the interest rate on Wednesday, and no early movement is now expected on closing down its asset purchase programme, due to recent softening of key data including labour market indicators. “The FOMC will likely shelve any consideration of scaling back QE, which provides a crumb of comfort to markets that had been fretting about this,” Mr Carnell says.

Consumer confidence and house price data on Tuesday and unemployment figures on Friday will be watched for any further weakness. The US has The US has performed fairly well so far this year but expectations of a slowdown are now beginning to build, fuelled by last week’s disappointing GDP figures.

The UK’s April services PMI, due out on Friday, will be crucial in shaping expectations for the second quarter’s growth. The surprisingly strong 0.3 per cent growth in the first quarter was driven primarily by the services sector, so any sign of weakening here would be cause for concern. Mortgage approvals and consumer credit data are this week expected to document the continued improvement in the housing market, albeit still at low transaction levels.

The upside surprise in the Q1 preliminary GDP figure may push back the timescale for any expansion of the UK’s quantitative easing programme.

Previous expectations of a further tranche of asset purchases in the second half of this year are now beginning to shift towards early 2014. Incoming Bank of England governor Mark Carney will give two speeches in Canada this week in which his intentions may become clearer.

Poland’s central bank may opt for an interest-rate cut in May, as poor data continues to pile up. “We doubt Q2 will show industrial recovery and expect the April PMI to at best stay flat given the poorer business sentiment in the eurozone and Germany in particular,” Mr Carnell says.

Chinese workers’ demands for better conditions and higher pay have been driving manufacturers to seek cheaper alternatives. That has brought many textile firms to Bangladesh, which is reputed to have the lowest textile industry wages in the world – and they have certainly been increasing much more slowly than those in China.

Quite apart from the risk of killing one’s employees through lax safety standards, manufacturers may find that there is a downside to this cheapness: efficiency. Bangladeshi textile workers simply aren’t as efficient as their Chinese counterparts.

So why would garment-makers bother to move?

Look at the difference between relative wages and relative productivity. Bangladeshi workers’ cheapness is more than sufficient to compensate for their lower level of productivity.

Until Bangladeshi workers’ pay rises substantially, or China’s efforts to increase its productivity pays off, Bangladesh will continue to be an attractive option for international clothing manufacturers – despite its terrible safety record.

But the Chancellor shouldn’t feel too relieved; in actuality, we have no idea whether the country grew in the past three months.

The numbers published this morning constitute only the first, preliminary data release for the period. GDP estimates undergo several subsequent revisions to add detail and richness to the data, and this can affect the headline number. Today’s figures put growth at 0.3 per cent but, as the FT’s economics editor Chris Giles has already pointed out, the average revision to initial GDP data releases is 0.4 per cent since 2000.

These are very small numbers – within the margin of subsequent adjustment. Taking a big-picture perspective, the economy is flatlining.

Given the range of possible subsequent adjustments, Britain’s economy could have grown by 0.7 per cent in the first quarter, or shrunk by 0.1 per cent – we just don’t know.

The G20 group represents 79 per cent of global GDP. But when it comes to demographics, you can split its membership into three quite distinct groups.

This shows each country in terms of GDP per capita and median population age, with its economy’s size depicted by the bubble:

• Rich but old. These are wealthy western countries, with GDP per capita around $40,000 and median population age of 40 years
• Poor but young. These are emerging economies, with GDP per capita around $10,000 and median population ages of 25 to 30 years
• Poor and ageing. This group contains just China and Russia, who have GDP per capita around $10,000 but median population ages approaching 40 years

The first group is dominated by its ageing baby boomer population. Historically the over-55s have largely been ignored as a source of demand, but today this generation offers a major new growth opportunity. They will be over a third of the group’s total population by 2030, more than double the percentage in 1950.

The “poor but young” group has a different opportunity. Its populations have successfully escaped from poverty in recent decades, but now need to be supported as they seek to progress up the income ladder towards Western living standards. Sustained growth could therefore come from developing new products and services to meet the emerging needs of this generation, whose incomes currently still average less than $20 a day ($7,300/year).

The final group has a more complex challenge ahead. China’s one-child policy since 1978 means its population risks growing old before it gets rich. Russia’s population is also ageing fast, due to its fertility rates having halved since 1950 whilst life expectancy has hardly changed. Growth prospects in both countries therefore depend on their ability to support demand growth within on their own new poor generations, and move away from their current export-dependency.

The chart shows the urgent need to shift the economic debate away from the current “one size fits all” argument between advocates of stimulus or austerity. A more nuanced approach is instead required, as demographics are now taking demand patterns in completely new directions.

Sustaining future growth thus depends on the G20’s ability to successfully develop and implement new policies, focused on the opportunities offered by the emergence of the New Old and New Poor as major new demand sources for the first time in history.

Paul Hodges is the co-author of Boom, Gloom and the New Normal: How the Western Baby Boomers are Changing Demand Patterns, Again www.new-normal.com

As FT Alphaville has noted, the issue is about one of Reinhart and Rogoff’s most heavily cited papers on the importance of debt. This paper has been accused of being the victim of fat-fingered Excel coding, as well as selective use of data and odd weighting of how different episodes are weighted, which seemed – to the authors – to make little sense. [UPDATE, 14:46 GMT - Pollin and Ash have written a piece for the FT on what they think this all means for austerity here.]

Robin Harding posted Reinhart and Rogoff’s original reply here. Overnight, the authors have worked through the numbers – and have put up a pretty robust defence of their work. They do admit the first error – there was an Excel blunder:

…Herndon, Ash and Pollin accurately point out the coding error that omits several countries from the averages in figure 2. Full stop. HAP are on point. The authors show our accidental omission has a fairly marginal effect on the 0-90% buckets in figure 2. However, it leads to a notable change in the average growth rate for the over 90% debt group.

They are, however, resisting the second issue – the selective use of data.

HAP go on to note some other missing debt data points, which they describe as “selective omissions”. This charge, which permeates through their paper, is one we object to in the strongest terms. The “gaps” are explained by the fact there were still gaps in our public data debt set at the time of this paper.

They also defend the weightings:

Our approach has been followed in many other settings where one does not want to overly weight a small number of countries that may have their own peculiarities

And they stand by their conclusions.

So do where does this leave matters on debt and growth? Do Herndon et al. get dramatically different results on the relatively short post war sample they focus on? Not really. They, too, find lower growth associated with periods when debt is over 90 per cent. Put differently, growth at high debt levels is a little more than half of the growth rate at the lowest levels of debt.

To address that point, here are some tables from Prof Reinhart showing the difference between their work in the American Economic Review in 2010 and the debunking, using data from 1945 to 2009. The new research shows some linkage between debt and growth.

She enclosed another table, with a longer timespan, back to 1800:

Prof Reinhart also pointed out that an article of theirs, published in the Journal of Economic Perspectives in 2012, found countries with a debt ratio of below 90 per cent had average growth rates of 3.5 per cent – compared to 2.4 per cent for those above 90 per cent – for 1800 to 2011.

Their full response is below the fold.

Response to Herndon, Ash and Pollin by Carmen Reinhart and Kenneth Rogoff, April 17, 2012

We are grateful to Herndon et al. for the careful attention to our original Growth in a Time of Debt AER paper and for pointing out an important correction to Figure 2 of that paper. It is sobering that such an error slipped into one of our papers despite our best efforts to be consistently careful. We will redouble our efforts to avoid such errors in the future. We do not, however, believe this regrettable slip affects in any significant way the central message of the paper or that in our subsequent work. But first let us consider the specific points raised by Herndon Ash and Pollin (HAP) in their comment that we were sent yesterday.

The authors point out that there are three problems with our 1945-2009 averages and the paper itself: (i) a coding error that causes the first five countries in the alphabet to be omitted in forming averages for the 1946-2009 period in one figure, (ii) “selective exclusion” of 1946-1950 for New Zealand, and (iii) “unconventional weighting of summary statistics”—the implication being that these omissions are intentionally used to bias the results. They argue that the interaction of three problems magnifies their effects and leads to completely different conclusions, especially when they choose a different weighting scheme.

On the first point, we reiterate that Herndon, Ash and Pollin accurately point out the coding error that omits several countries from the averages in figure 2. Full stop. HAP are on point. The authors show our accidental omission has a fairly marginal effect on the 0-to-90-per-cent buckets in figure 2. However, it leads to a notable change in the average growth rate for the over-90-per-cent debt group. The median growth rate we report is the right order of magnitude.

Our interpretation of the errant data point in figure 2 was fortunately tempered somewhat by the parallel weight given to the median GDP growth rate for the various levels of debt in our discussion, an issue HAP selectively ignore. To quote from our opening paragraph:

“median growth rates for countries with public debt over roughly 90 percent of GDP are about one percent lower than otherwise”

There is also Table 1 which immediately follows figure 2, and does not have the same issues. Table 1 gives all the individual country estimates for all the buckets and over a much longer time period than figure 2, and of course figures importantly in our analysis. We are fortunate that we chose to present our results in several different ways, including means, medians, and individual country averages, in no small part as standard robustness checks. Nevertheless, the mistake in figure 2 resulting from the coding error is a significant lapse on our part.

HAP go on to note some other missing debt data points, which they describe as “selective omissions”. This charge, which permeates through their paper, is one we object to in the strongest terms. The “gaps” are explained by the fact there were still gaps in our public data debt set at the time of this paper, a data set no one else had ever been able to construct before and which we now have filled in much more completely. Many readers of our work have followed this evolution on our data website. For example, at the time the 2010 AER paper was written, there were gaps in the French data for the 1970s that we only filled in later. Other data, including data for New Zealand for the years around WWII, had just been incorporated and we had not vetted the comparability and quality data with data for the more recent period. In effect, HAP only knew we had these data as we sent them the file we had used at that time.

We have no issues with to Herndon, Ash and Pollin for bringing attention to any data question regarding our work. In this regard, we note that we have long since fully integrated the New Zealand data back to the early 1800s, once we were able to process it. Every major high debt episode for advanced countries since 1800 and the underlying data is included in our 2012 Journal of Economic Perspectives paper co-authored with Vincent Reinhart.

But surely the authors do not mean to insinuate that we manipulated the data to exaggerate our results. To what purpose would we “manipulate” the average growth rate for debt above 90 per cent and show an average of -0.1 per cent when in the same AER paper we report the median for 1946-2009 at 1.6 per cent, and over the longer sample 1790-2009, we report and average of 1.7 per cent and a median of 1.9 per cent? (see table below) Why, for that matter, would we provide all the data that we have gathered and used in our research over the years documenting in detail multiple sources to the public domain?

This brings us to the core conceptual issue, which Herndon, Ash and Pollin argue greatly biases our results. They argue that we use an “unconventional weighting of summary statistics.” In particular, for each bucket, we take average growth rates for each country and then take an average of the result. This seems perfectly natural to us, and hardly unconventional. We do not want to excessively weight Greece, for example, which has debt over 90 per cent for 19 years in the 1946-2009 sample. The post-war Advanced Economy experience would quickly reduce to the experiences of Greece and Japan. Our approach has been followed in many other settings where one does not want to overly weight a small number of countries that may have their own peculiarities. Our approach is quite clear from table 1, which also gives the averages for each individual country.

Our 2012 Journal of Economic Perspectives paper, based a much longer time period (1800-2011 versus the 1946-2009 Herndon et al focus on), gives episode-by-episode data for each country, including growth rates and number of years, so the results are quite transparent. The problems with weighting long episodes much more heavily than short episodes, as Herndon et al. suggest, become much more apparent in the longer time series (an earlier version of which was also used in Table 1 of our original AER paper) As we noted in our initial comment yesterday upon just receiving the paper, our JEP paper anticipates most of the aggregation debate and diffuses it by using a case-study approach. That is where this literature is now expanding.

So do where does this leave matters on debt and growth? Do Herndon et al. get dramatically different results on the relatively short post war sample they focus on? Not really. They, too, find lower growth associated with periods when debt is over 90 per cent. Put differently, growth at high debt levels is a little more than half of the growth rate at the lowest levels of debt. They ignore the fact that these results are close to what we get in our Table 1 of our AER paper they critique, and not far from the median results in Figure 2 despite its coding error. And they are not very different from what we report in our 2012 Journal of Economic Perspectives paper with Vincent Reinhart—where the average is 2.4 per cent for high debt versus 3.5 per cent for below 90 per cent . The table below makes the similarity of all these comparisons clear:

There is also the question of whether these growth effects can be economically large. Here it is very misleading to think of 1 oer cent growth differences without recognizing that the typical high debt episode lasts well over a decade (23 years on average in the full sample.)

It is utterly misleading to speak of a 1 per cent growth differential that lasts 10-25 years as small. If a country grows at 1 per cent below trend for 23 years, output will be roughly 25 per cent below trend at the end of the period, with massive cumulative effects.

Looking to the reaction to this comment in blogosphere, we note that this is not the first time our academic work is seen pandering to a political view. What is quite remarkable is that this claim has spanned polar opposites! This time, we are charged with misconstruing analysis to support austerity. Only a few months ago, our findings on slow recoveries from financial crises was accused as providing a rationale for the deep recession and weak economy the Obama administration has faced since 2007.

Herndon, Ash and Pollin have written a useful paper, finding a significant mistake in one of our figures, and helped reconcile why one result is out of line with all the other results in our original paper as well as ones presented in our later research, not to mention those they present in their helpful comment. Clearly more research is needed on debt and growth and we welcome all efforts, it is very exciting area. We now have debt data for a larger number of countries than the original sample and long time periods that allows this research to press forward.