5/3/2014: Who Owns Emerging Market Government Debt: IMF Blog

An interesting breakdown of the ownership distribution of the emerging markets' Government debt via "The Trillion Dollar Question: Who Owns Emerging Market Government Debt" by Serkan Arslanapl and Takahiro Tsuda

Obviously, take a look at Ukraine and Russia. The core difference is that foreign official sector holdings of government debt for Ukraine are well in excess of those for Russia. Foreign non-bank holdings are also larger for Ukraine. Overall, half of Ukraine's Government debt is foreign-held, against around 1/5 for Russia. Last point, private domestic holdings of Government debt of Ukraine are tiny, at around 22-25% against Russia's 75% or so... Ukraine more closely resembles Argentina and Uruguay in this setting...

5/3/2014: Broader Measures of Unemployment in Ireland: QNHS Q4 2013

Completing the coverage of Q4 2013 QNHS results for Ireland.

• First post covering detailed analysis of employment by sectors: http://trueeconomics.blogspot.ie/2014/02/2722014-employment-by-sectors-qnhs-q4.html
• Second post covering employment across broader sectors and categories: http://trueeconomics.blogspot.ie/2014/02/2822014-new-employment-across-broader.html
• Third post covering Participation and Unemployment Rates: http://trueeconomics.blogspot.ie/2014/02/2822014-participation-and-unemployment.html
• Fourth post covering duration of unemployment by age group: http://trueeconomics.blogspot.ie/2014/02/2822014-duration-of-unemployment-qnhs.html

Now, let's take a look at broader measures of unemployment.

Methodology note: CSO reports the following measures of broader unemployment:

• PLS1 indicator is unemployed persons plus discouraged workers as a percentage of the Labour Force plus discouraged workers. This indicator is broadly comparable to the previously published S1 indicator. In the nutshell, PLS1 = unemployed persons plus discouraged workers.
• PLS2 = PLS1 + Potential Additional Labour Force
• PLS3 = PLS2 + others who want a job, not available & not seeking for reasons other than being in Education and training.
• PLS4 = PLS3 + plus underemployed

In addition, I use CSO data from Live Register and emigration to add two more metrics:

• PLS4+STP: PLS4 + State Training Programmes Participant
• PLS4+STPE: PLS4 + State Training Programmes Participants + Emigration

So let's take a look first at labour force. The data is not seasonally-adjusted.

In Q4 2013 there were 2,163,000 people in labour force in Ireland, an increase of 19,600 year on year (+0.9%). A small increase, but a welcome one, suggesting that emigration is not offsetting demographic inflows of workers into the labour force. However, the level of labour force is still below Q4 2011 and is down 137,000 on pre-crisis peak. On average over the entire 2013, levels of labour force were 110,600 behind the pre-crisis period average levels.

As chart above shows, the greater challenge for us is the flat-trending labour force over the period of 2011-2013.

Table and chart below summarise changes in the broader measures of unemployment:

The key takeaway from the above charts and the table is shallower declines in the broadest measures of unemployment officially reported (PLS2-PLS4) compared to PLS1 and the adverse impact of 'sticky' State Training Programmes on the measure. It appears that these programmes are not moving workers out of unemployment fast enough.

Keeping in mind that Emigration is imputed only through April 2013 (we do not have official data beyond that), the PLS4+STP+E measure likely underestimates overall changes in broad unemployment.

Just how bad things are on overall unemployment front? With caveats to data and estimation errors, the above shows that in Q4 2013, 31.7% of Irish potential (including emigrants and state training schemes participants) labour force was either unemployed, underemployed, discouraged from seeking employment, not seeking employment for some reason other than being in education, toiling for free at Job Bridge and other fine 'activation' programmes or 'partying' abroad. Happy times...

That number, incidentally, is down from 32.5% in Q4 2012, but is still above 30.9 in Q4 2011.

4/3/2014: A new Initiative from IMHO

Irish Mortgage Holders Organisation (IMHO) are launching a new programme along with KBC Bank Ireland, aimed at providing independent, consumer-oriented advice and negotiation services to mortgage holders who are currently in arrears or experience difficulties with their mortgages.

Here are the details (click on images to enlarge).

28/2/2014: Duration of Unemployment: QNHS Q4 2013

Continuing with the coverage of Q4 2013 QNHS results for Ireland:
- First post covering detailed analysis of employment by sectors: http://trueeconomics.blogspot.ie/2014/02/2722014-employment-by-sectors-qnhs-q4.html
- Second post covering employment across broader sectors and categories: http://trueeconomics.blogspot.ie/2014/02/2822014-new-employment-across-broader.html
- Third post covering Participation and Unemployment Rates: http://trueeconomics.blogspot.ie/2014/02/2822014-participation-and-unemployment.html

In the current post let us consider changes in duration of unemployment.

The CSO reports two basic duration metrics:
- Less than 1 year,
- 1 year and over
And the data covers different age groups:
- All population 15 years and older
- Population 15-24 years of age,
- Population 25-44 years of age, and
- Population 45 years of age and older.

Here are the charts and quick commentary on these. The data is not seasonally-adjusted, so there is a lot of volatility and I am not going to do q/q analysis here.

For overall population 15 years of age and over:

• Q4 2013 total unemployment declined 14.05% (41,400 in level terms) compared to Q4 2012. In 2012, Q4 y/y decline was -6.1% (-19,300 in level terms). Thus, 2013 numbers are much better compered to 2012 numbers, as one should expect.
• Of these, unemployment numbers for duration less than 1 year have declined 18% (-20,900) in Q4 2013. Te good news - this reversed 2012 y/y rise of 2.0% (+2,300).
• Unemployment with duration over 1 year has fallen as well, in Q4 2013 this was down 11.8% (-20,900) compared to Q4 2012, which is a small gain on decline recorded in Q4 2012 (y/y -10% and -19,700).

So good news here is that numbers are declining for both long-term and short-term unemployed. However, while overall unemployment numbers have now fallen to the levels below those recorded in Q4 2009 (though ahead of those in Q4 2008), long-term unemployed numbers are down to the levels below those recorded in Q4 2010 and are way ahead of those in Q4 2009.

Since the current Government came to power (H1 2011), unemployed numbers for those over the age 15 are down 59,300, of which 36,050 declines came from the ranks of short-term unemployed and 22,050 declines came from the ranks of long-term unemployed.

Given the difficulty of reducing long-term unemployment compared to short-term unemployment, this is still a good record.

However, given that we do not know how many of long-term unemployed are gaining jobs vs how many are dropping out of the labour force (emigration or exits from workforce) we really have little to go in identifying how god the above aggregates really are.

Charts below plot unemployment by duration for different age groups.

Youth unemployment (15-24 years of age) is shrinking. Across total youth unemployment, in Q4 2013 numbers unemployed fell 17.3% y/y (down 10,200 in level terms), building on 12.9% (-8,700) decline in Q4 2012.

Compared to H1 2011, youth unemployment is down 19,950 (-29%) overall, with 11,000 of this decline coming from short-term unemployed figures and 8,450 from long-term unemployed ranks.

The problem with the above numbers is that we do not know the sources for these declines in youth unemployment. These, in addition to people gaining jobs, include demographic transition (entry of new young workers and exists of previously younger workers into the next category of 25-44 year olds), exits to and entries from education and training, including State Training programmes, emigration, including short-term migration on post-education visas and so on).

The weakest performance by age group is in the 45 and over category. Here, in Q4 2013 the numbers unemployed declined only 8.6% y/y (down 6,900 in level terms). The good news is that this reversed the rise in unemployment in this category recorded in 12 months through Q4 2012 (+3.0% and +2,300). Compared to H1 2011, numbers unemployed in this age group are still higher (+2.8% and +2,000). Numbers of long-term unemployed dipped in Q4 2013 only slightly (by 6.7% or -3,700) and compared to H1 2011 long-term unemployment in this age category is still up +11.4% or +5,250.

So overall, these are pretty solid numbers,with core reading showing that total number of unemployed for age 15 and over is currently at the lowest level for any Q4 period since (and including) Q4 2009.

Lastly, on severity of long-term unemployment, consider the chart plotting percentage of long-term unemployed in each age group total unemployment numbers:

This clearly shows that since around H2 2012, the positive trends in overall unemployment are broadly translating into symmetric reductions in unemployment for both short-term and long-term unemployed for all age groups. Again, this is a positive trend in the short run, as long-term unemployment is the hardest (or the stickiest) of all forms of unemployment and we can expect an upward trend in these charts. This was indeed the case in the period prior to H2 2012. Since then, however, we are seeing reductions in unemployment of relatively similar proportions for short-term and long-term unemployed.

28/2/2014: Participation and Unemployment Rates: QNHS Q4 2013

Having covered sectoral and broader aggregates QNHS results for employment levels (see post here for links: http://trueeconomics.blogspot.ie/2014/02/2822014-new-employment-across-broader.html), it is now time to take a look at participation rate and unemployment rate.

At the end of Q4 2013, seasonally-adjusted participation rate stood at 60.4%, up on 60.3% in Q3 2013 and 59.8% in Q4 2012. Compared to H1 2011 average (the period when the current Government came to power), the participation rate is up 0.3 percentage points.

Historical average for the seasonally-adjusted rate is 60.77% so we are just a whisker away from hitting this landmark. At the current rate of adjustment, we should be there around Q2-Q3 2014.

At the end of Q4 2013, official seasonally-adjusted unemployment rate fell to 12.1 from 12.7 in Q3 2013 (a very strong decline),  this marks the second sharpest correction downward in unemployment rate for the entire period of the crisis.

Over the year, seasonally adjusted unemployment rate has fallen full 2.1 percentage points from 14.2 to 12.1, improving on 2.0 percentage points decline y/y in Q3 2013. Compared to H1 2011, unemployment rate is now down 2.5 percentage points.

Q4 2013 marks the fifth consecutive quarter of declines in unemployment rate (q/q terms) and current rate is at the levels comparable with Q2 2009. All of which is very good news, despite all the possible caveats to data arising from potential impact of emigration and state training programmes participation (I will be covering these figures in my analysis of broader measures of unemployment as usual, next).

28/2/2014: New Employment Across Broader Categories: QNHS Q4 2013

In the previous post (http://trueeconomics.blogspot.ie/2014/02/2722014-employment-by-sectors-qnhs-q4.html), I covered detailed breakdowns in employment numbers changes across various sectors of the economy. Here, I will briefly identify sub-trends relating to aggregate data.

A caveat: per my discussion before, I will also report here numbers in employment ex-agriculture. In my view, it is questionable as to how agricultural employment is registered in the first place, since many/some of today's famers used to be construction sector employees or self-employed contractors. How many? We do not know. How many claimed unemployment in the past and now, having run-out of benefits, declared themselves to be farmers or farm employees for the purpose of optimising extraction of subsidies or supports? We do not know. Hence, I will omit farming employment from consideration in one sub-set of the aggregate figures (clearly labeled and identified below). This is done not because all of the employment in this sector is somehow 'bad' or 'unproductive' but because

1. we do not know how much of this employment is real and of what quality, and
2. employment in agriculture is different in nature (and in valued added) to employment in all other sectors of the economy (this is the reason why many other jurisdictions report non-farm employment numbers and/or private non-farm employment numbers).

Definitions for table and chart below:

• Non-agricultural Private Sectors include all sectors, with exception of Agriculture, Forestry & Fishing, and Public & State-controlled Sectors Employment (as defined below)
• Public & State-controlled Sectors Employment covers employment in Public admin & defence, social security (O), Education (P) and Human health & social work (Q). This grouping is not designed to measure public sector employment levels (I will blog on these later separately), but rather identify separately employment in the economy relating to sectors largely controlled by public sector and heavily influenced by state policies on employment and activity.
• High-value added activities employment covers the following sectors: Information and communication (J), Professional, scientific & technical activities (M), Education (P), Human health & social work (Q), Financial, insurance & real estate (K,L)

Table below summarises changes on H1 2011 average and Q4 2013:

The claim is that there were 60,900 jobs added (employment created) in Q4 2013 compared to Q4 2012. Of these, slightly less than half were added in the private non-agricultural employment sectors (29,600), while Public & State-controlled Sectors employment grew by 4,500 and agricultural employment expanded by 26,800. The numbers are strong and positive.

High-value added sectors of employment showed weaker performance, adding only 12,100 new employees in 12 months through Q4 2013. This, of course, comes on foot of strong performance in 2012, as evidenced by the total number in sector employment rising by 23,600 between H1 2011 and Q4 2013.

Although it is unclear if they include any of the State Training Programmes participants (if they do, as we know they are excluded from unemployment counts), then the numbers are less impressive.

Dynamics across the categories are shown in the chart below:

Dynamics across all aggregates are positive, with exception of the Public & State-controlled Sectors where things are moving sideways. Not quite down significantly and not up. Pick up in non-agricultural private sector employment is weak and unconvincing for now, so it would be good to see steady gains over 2014 in this category.

One thing to keep in mind is that the claimed 61,000 new jobs created is a suspect claim for two reasons:

1) It is subject to modification on the basis of quality adjustments (in part, I will do this when I am reviewing full-time vs part-time employment figures; and in part due to agricultural employment issues highlighted above)

2) The impact of the State Training Programmes, which are for now unknown in terms of how they register in the above data

On the other hands, there have been new jobs added in both higher value-added sectors and in non-agricultural private sectors, as detailed above. This, undoubtedly is a good news.

Stay tuned for more analysis of QNHS data tomorrow.

27/2/2014: Employment by Sectors: QNHS Q4 2013

Quarterly National Household Survey is out for Q4 2013. Here is the first post looking at the sectoral jobs distribution and jobs 'creation' or rather employment additions.

The next post will cover aggregate employment levels data.

Key to tables below: red denotes reduced numbers in employment in specific sub-sector/sector, green denotes increases in employment. In the tables, I reference current level of employment on H1 2011 average - the period when the current Government came to power.

Table 1:

As the above shows, there was a massive recorded increase in numbers in employment in agriculture. These numbers are driven by the unknown factors, as they are impacted by revaluations applied by the CSO. CSO detail the issues involved with this data in their notes: http://cso.ie/en/media/csoie/releasespublications/documents/labourmarket/2013/qnhs_q42013.pdf
so there is no need for me to go into deep explanations.

Outside Agriculture, Forestry & Fishing, there were modest y/y gains in Construction sector, totalling just 400 jobs. For all the reported activity in the sector - with investors flocking to our shores and building industry posting alleged revivals, there is preciously little to show here in terms of jobs creation since the current Government came to power. Still, good news is that employment is up y/y. May this be a trend, rather than a blip. Construction sector employment has been trending at around Q4 2013 levels since Q1 2011, showing no serious uplifts.

In contrast, Wholesale & Retail Trade, etc sector saw massive drop off in employment, down 3,000 in a year through Q4 2013. The sector is now at the levels last seen in Q4 2004, and Q2 2013 was the second lowest quarterly reading over the current crisis period.

Transportation & Storage sector is basically showing the same signs as Construction sector, with a small rise in employment of just 600 jobs in Q4 2013 compared to Q4 2012. The sector is still down on H1 2011. Q4 2013 marks the second lowest Q4 on record for the period of the crisis.

Accommodation & Food Services sector is gaining jobs at a nice pace. Employment is up 23,150 since H1 2011 and of this increase, 17,400 came in the twelve months through Q4 2013. This is an unambiguous positive, since the sector is now very close to regaining 2007 highs in employment.

Table 2:

As above shows, things are slipping somewhat in the Information & Communication sector, with employment gains since H1 2011 running at a a strong 7,250 on H1 2011, but employment levels down modest 700 jobs in Q4 2013 compared to Q4 2012. Still, Q4 2012 was the absolute record level for employment in the sector, so some retrenchment, especially mild, is ok. The problem, of course, is that this sector is the focal point of all the talk about Irish economy becoming a haven for ICT services jobs. The technical and specialist jobs in this area go into this category, while business services jobs are absorbed into the next two categories.

The above explains why we are witnessing a significant rise in employment in Professional, Scientific & Technical activities sector, where employment rose 11,500 in Q4 2013 compared to H1 2011, and the rise was even sharper (by 13,000) in 12 months through Q4 2013. Very good signal, of course, is that employment in this sector of activities was on a strong rise now since Q4 2011 and we are now just 2,900 jobs shy of the all-time high posted in Q2 2008.

Things were, however, more mixed in Administrative & Support Services sector, where Q4 2013 employment recorded a decent rise of 1,300 jobs compared to Q4 2012, but still posted a loss of 2,600 jobs compared to H1 2011. We are currently running on flat trend from Q4 2009-Q1 2010 albeit with high volatility in the series.

Public Administration & Defence have been shrinking in employment levels, with employment decline of 1,000 in 12 months through Q4 2013. Over the period from H1 2011, employment in this sector is down 6,800, which sounds impressive, as long as we assume that there was no reclassification of employees from this category to other state-controlled or state-related areas, such as Health and Education, Transport etc. I will blog on public sector employment numbers separately, so stay tuned for more analysis.

Education has returned higher employment in Q4 2013 compared to Q4 2012 - a rise of 1,600, but the levels of employment remain lower (by a very small number of 250) compared to H1 2011. It would be interesting to know if the latest changes are driven by private employment, part-time employment or full-time public employment. Alas, we do not have that information.

Table 3

As with Education, Human Health & Social Work also posted an increase in employment over 12 months through Q4 2013, rising by a very significant 3,900. Despite all the 'cuts' talk, sector employment is now 10,400 ahead of where it was in H1 2011.

The chart below summarises the trends in Human Health & Social Work, Education and Public Administration & Defence:

Back to table 3 above:

Industry employment (excluding Construction) rose strongly, some 6,400 in 12 months through Q4 2013, and employment growth is more moderate, at +4,650 when compared against H1 2011 levels. This is good news and confirms my thesis that we are witnessing some (albeit still fragile) organic recovery in the sector.

Services sectors on the aggregate basis posted a rise of 29,300 jobs in 12 months though Q4 2013 and there was a very similar increase on H1 2011 figures.

However, there was strong contraction in employment in the Financial Services, Insurance & Real Estate sector, with employment down 5,300 on H1 2011 and 5,700 on Q4 2012.

In the next post, I will take a look at the Total Employment, Non-Agricultural Employment, Public Sector and State-Controlled Sectors Employment and other core aggregates.

26/2/2014: IBRC Sale Requires Upfront Clarity on CCMA

Much discussion is ongoing concerning the fate of the IBRC Mortgages which are to be sold in the coming weeks/days. The problem centres on the issue of applicability of the Code of Conduct relating to mortgages arrears. By some reports, the book held by IBRC is 50-70% in arrears.

The Government has reached an agreement with the Special Liquidator on the issue. This is covered here: http://www.finance.gov.ie/news-centre/press-releases/agreement-reached-between-special-liquidator-and-phase-two-bidders-ibrc

The idea behind the agreement is a fine one and the Government objective (ensuring that CCMA applies to IBRC mortgagees) is correct one. The problem is that this agreement is voluntary and not enforceable. Thus, it simply muddies the waters.

Here is my view on this expressed earlier on twitter:

In fact the only way to deal with the #IBRC mortgages sale is by setting clear, legally-binding compliance with the code of conduct requirement. This will give certainty on regulatory constraints to bidders/buyers, reduce their concerns about potential ex-post political interference, as well as provide clear-cut enforcement avenue for regulators & supervisors at the CB. A voluntary compliance system, as advocated currently, will only create confusion on the regulatory side but will still be priced as higher risk (bid discount) by bidders. So proposed voluntary arrangement is a lose-lose for everyone, while compulsory regulatory arrangement is a win-win.

Related background:

• Liquidators for IBRC are proceeding with sales of loans books: http://uk.reuters.com/article/2014/02/26/uk-ireland-anglo-idUKBREA1P0SJ20140226
• IBRC holds 12,702 mortgages accounts of which 10,622 are PDH and 2,080 are BTL accounts
• Credible estimate I have seen is that 50% of IBRC mortgages book are in arrears, compared to about 18% for all banks.
• Total Mortgages book to be sold is around EUR1.8 billion

24/2/2014: A Chart for Thought... Historical CO2 Concentrations

A chart for thought:

via

@PeterGleick

21/2/2014: Homeownership, Negative Equity, Entrepreneurship: Data from France

Over recent years I wrote extensively about the issues of negative equity and the costs of this phenomena to the society and economy at large. Much of the research in this areas focuses on the US data, with some departures for German and Italian data sets. Here is a recent paper using French data and dealing with the issue of housing collateral (house prices-linked borrowing constraints) and entrepreneurship.

"HOUSING COLLATERAL AND ENTREPRENEURSHIP" by Martin C. Schmalz, David A. Sraer, David Thesmar (Working Paper 19680 http://www.nber.org/papers/w19680) provides evidence on whether entrepreneurs "face credit constraints, which restrict firm creation, post-entry growth, and survival, even over the long run. The existing literature documents a strong correlation between entrepreneurial wealth and the propensity to start or keep a business (Evans and Jovanovic, 1989; Evans and Leighton, 1989; Holtz-Eakin et al., 1993)."

The problem is that there is still "a considerable debate …about whether such a correlation constitutes evidence of financial constraints. For instance, individuals who experience a wealth shock, through personal accumulation or inheritance, may also experience an expansion of business opportunities for reasons unrelated to their wealth (Hurst and Lusardi, 2004)."

The authors used "variations in local house prices, combined with micro-level data on home ownership by entrepreneurs. …We compare entrepreneurial outcomes of entrepreneurs owning a house and entrepreneurs renting a house, and compare this difference across geographic regions with different house price dynamics. The comparison between owners and non-owners allows us to filter out local economic shocks that may drive the creation, growth, and survival of local businesses." Do note the important aspect of this data set - by controlling for home ownership v renters, the paper also allows us to look at the potential benefits of the former or the latter in terms of entrepreneurship.

"We investigate both the extensive and intensive margin of entrepreneurship, that is, entry decisions as well as post-entry growth. Our investigation starts with firm growth and survival, conditional on entry. We construct a large cross section of French entrepreneurs starting a businesses in 1998. Combining survey data and administrative data, we are able to observe a variety of personal characteristics, in particular, the home location of the entrepreneurs, as well as their home-ownership status. We match this information to firm-level accounting data of the newly created firms for up to eight years following creation."

Now for the results: 

• "We find that in regions with greater house price growth in the 1990s, firms started by homeowners in 1998 are significantly larger and more likely to survive than firms started by renters." Oops, for the folks saying that homeownership should not be encouraged or incentivised. "In other words, the difference in the size of businesses created by owners and renters is larger in regions in which house prices have appreciated more in the past five years. 
• This effect is robust to controlling for a large set of entrepreneurial characteristics. It is also persistent: in 2005, firms started by entrepreneurs with lower collateral values in 1998 remain significantly smaller in terms of assets, sales, employment, or value added. 
• Finally, this effect is economically large: going from the 25th to the 75th percentile of house price growth in the five years preceding creation allows homeowners to create firms that are 6.5% larger in terms of total assets."
• "We then verify how collateral shocks affect the probability of starting a business, that is, the extensive margin of entrepreneurship. …We find that homeowners located in regions where house prices appreciate more are significantly more likely to create businesses, relative to renters located in the same regions. In other words, the difference between owners and renters in the propensity to start a business is larger in regions in which house prices appreciated more in the past. 
• Again, the effects are economically sizable. Going from the 25th to the 75th percentile of past house price growth increases the probability of firm creation by homeowners, relative to renters, by 9% in our preferred specification."
• More to the above: "We confirm the importance of this result in the aggregate: total firm creation at the regional level is more correlated with house prices in regions where the fraction of homeowners is larger."

As an aside, consider also the following discussion from the paper: The link between funding of start ups and wealth constraints is non-trivial. "Robb and Robinson (2013) document that debt is a large source of financing for start-ups (approximately 44%) and that its availability is related to the scarcity —and therefore the value— of real estate collateral. Hurst and Lusardi (2004) and Adelino et al. (2013) are closest to our paper, because they also investigate the role of housing wealth on firm creation."

However, the latest paper "makes two significant advances relative to these papers:

1. the information on individual homeownership allows us to control for local economic shocks that might create a spurious correlation between entrepreneurial rate and local house prices, and 
2. the nature of our data allows us to track not only firm creation (the extensive margin), but also post-entry growth and survival over a long horizon (the intensive margin)."

"Several earlier papers focus on the role of inheritance shocks to firm quality and survival. Holtz-Eakin et al. (1993) find that firms started after a large inheritance are more likely to survive, a finding they interpret as evidence of credit constraints. By contrast, using Danish data, Andersen and Nielsen (2011) find that businesses started following a large inheritance have lower performance. This finding suggests the relationship between wealth and entrepreneurship may be driven by private benefits of control, or in other words, that business ownership has a luxury-good component (Hurst and Lusardi, 2004). The relation between wealth shocks and post-entry growth/survival thus remains an open discussion."

The latest paper "contributes to this debate by looking at wealth shocks generated by local variations in house prices for homeowners. Arguably, these shocks are much less likely to be correlated with the unobserved heterogeneity in entrepreneurial outcome than inheritance shocks."

"Fracassi et al. (2012) also provide a clean identification on the role credit constraints play small business survival, by exploiting a discontinuity in the attribution of loans to start-ups at a small local bank. In a similar vein, Black and Strahan (2002) find that banking deregulations in U.S. states led to a large increase in firm creations. Whereas these papers focus on the effect credit supply on firm creation and survival, our paper focuses on credit demand via the supply of collateral."

There is an intuitive link between the above forces: "When house prices increase, firms and households have more collateral to pledge, which raises borrowing capacity. On the credit-supply size, banks, balance sheets become stronger, which allows them to lend more. Recent papers have documented the link between house prices and household borrowing and consumption (Mian et al., 2011; Gan, 2010), the link between real estate prices and corporate investment (Gan, 2007a; Chaney et al., 2012), and the link between real estate bubbles and bank lending (Gan, 2007b)."

And the conclusion is: "Our paper shows that entrepreneurial activity also strongly reacts to changes in the value of collateral available to potential entrepreneurs."

So back to that 'negative equity only matters for those who want to move from their current house' meme that Irish economists and policymakers keep pushing around… My suggestion: go back to study economics, folks.

21/2/2014: Fed Transcripts, 2008: Icebergs, Titanic, Violins...

Marketwatch are running a live blog on Fed's release of 2008 transcripts

http://blogs.marketwatch.com/capitolreport/2014/02/21/the-feds-crisis-era-transcripts-of-its-2008-meetings-live-blog/

My comment: Fed transcripts from 2008 show a circus hit by a hurricane drowning in a surge of self-delusion.

Bernanke waffling on, in September 2008, about 'moral hazard' in a virtually academic exercise that is more about him being 'decidedly confused and muddled' shows the extent to which the Fed (and do keep in mind - this is the most competent Central Bank out there) was left completely unprepared for a systemic crisis. Forget the nature of the crisis or specific causes of it. The point is that some 14 months into huge pressure pilling up in the markets, the Fed was utterly unprepared to face a crisis.

Now, observe that having done the deed of acting outside any confidence about the impact of his actions, Bernanke subsequently defends his choices by saying that "I just don't believe that you can allow systemically critical institutions to fail in the middle of financial crises and expect it to be not a problem." Which, of course begs the question: does he believe that he should fail these institutions ex post after the crisis is over? And how the hell does he propose we go about that restoration of 'zero moral hazard' state? By sending in the FBI?..

In short, the man is still out of touch with reality. First, with the one he was thrown into in September 2008, second, with the one he constructed in response to September 2008 events.

Poor Ben... he goes on: "“We did not have—as the Europeans have or as we have FDICIA for banks—a system that was set up to allow a reasonable and responsible orderly resolution of nonbank systemically critical institutions. I think we now have made a lot of progress there. The TARP will provide a good interim solution.”"

Come again? What is that that 'the Europeans' have? "a system ...to allow a reasonable and responsible orderly resolution of nonbank systemically critical institutions"? Dear, oh dear... he needed retirement rest and relaxation back in 2008.

Still, the Fed transcripts show how the Central Bank did move to face the reality, unlike 'the Europeans' who basically used the Mongols' tactic for capturing Beijing - throw bodies against the walls. Even though Fed's 'data' included Yellen's quotes about plastic surgeons reporting customers delaying elective procedures... and she subsequently followed up on this pearl by expressing (in December 2008) concern about rising labour force participation...


In short, the transcripts make us, macroeconomists, look decidedly scientific and impossibly human, compared to the Central Bankers... And this before we get any transcripts from that bastion of surreality in Frankfurt, called the ECB...

20/2/2014: Gold Demand 2013: US Mint Sales

I recently posted on the 2013 demand for gold:

• http://trueeconomics.blogspot.com/2014/02/1822014-gold-demand-trends-2013.html started with highlights of the World Gold Council report and was followed up with 
• http://trueeconomics.blogspot.com/2014/02/1822014-demand-for-gold-netting-out.html covering demand for gold stripping out changes in ETFs holdings.

To complete this analysis, let's take a look at another area of demand.

Sales of gold coins by the US Mint are usually seen as representing more stable, long-only and non-instrumented demand for gold. US Mint coins are first and foremost used by investors interested in a store of value and secondly as long term savings. These are principally non-speculative in nature and do not rely heavily on shorter term volatility in prices (as some o the statistics discussed below show).

The series covered here include American Eagles and American Buffalos. The data we have for both series goes back to the start of 2006.

We shall focus in this post on annual values.

In 2013,

• US Mint sold 1,095,500 oz of gold in the form of coins, marking the third largest demand in the series history. The demand in terms of total weight was up 29.8% y/y, reversing previous 3 consecutive years of annual declines.
• US Mint sold total of 1,697,500 gold coins in 2013, marking the third highest year of sales by coinage, and up 39.1% y/y.
• Average weight of coin sold in 2013 was 0.645oz/coin, down on 0.692oz/coin in 2012. Overall, this was the third lowest annual average oz/coin sold performance.

Correlation between price and weight of gold sold was 0.349, and between price and coins sold 0.450, while correlation between price of gold and oz/coin average weight was 0.137.

Monthly series confirm that there is little sustained correlation between prices and gold sales via US Mint coins:

Looking at longer-range series:

• Average sales of coins by total weight in 2005-2009 was 874,250 oz per annum, against 1,092,250 oz per annum for 2010-2013 period.
• Average sales of coins by total number in 2005-2009 was 1,174,625 coins per annum, against 1,548,625 coins per annum for 2010-2013 period.
• Average sales of coins by average weight per coin sold in 2005-2009 was 0.705 oz/coin, against 0.703 oz/coin for 2010-2013 period.

In conclusion: US Mint sales of gold coins suggest healthy demand for gold, strengthening in 2013 on foot of both - improved affordability and rebounding in the underlying demand toward the 2010-2013 average levels.