20/8/19: Public Spending in the Euro Area: Post-Crisis Austerity?

Given the never-ending repetition of the 'austerity narrative' in European economic analysis, it is virtually impossible to conclusively address the issue of changes in public spending during the crisis and the post-crisis periods and the relationship between fiscal policies and economic growth. Thew reason for this is the lack of singular set metrics that can capture these dimensions of the debate.

However, this lack should not be a reason for not trying.

Here is an interesting chart (based on the IMF WEO data and 2019 forecasts), plotting average Government expenditure as a share of GDP for two periods for euro area economies. The two periods under consideration are: 2000-2007 and 2013-2019. I am also showing two metrics for Ireland: the GDP (a measure of economic activity that vastly overstates the true extent of national economic activity) and GNI* (an official Irish Government metric of national economic activity). Note: using 2014-2019 average paint effectively the same picture.

The picture is worrying. Thirteen out of nineteen euro area economies have witnessed a rise in Government spending as a share of GDP in post-crisis period compared to pre-crisis period, two experienced virtually no change, and four experienced declines. In other words, based on the ratio of Government spending to economic activity, only four states exhibit a clear case of 'austerity'.

Ireland is an interesting outlier to the picture (hence, reporting of GNI* metric): based on GDP measure, Ireland's Government spending as a share of GDP averaged 32.85 percent per annum in 2000-2007, and this fell to 30.32 percent in 2013-2019 - an austerity gap of 2.53 percentage points per annum. But based on GNI* measure, Ireland's Government spending rose from 38.69 percent in pre-crisis years to 45.51 percent in post-crisis period - an expansion gap of 6.82 percentage points.

Overall, using the above metric, top austerity countries in the euro area are:

• Malta (gap of -4.86 percent)
• Ireland (GDP gap of -2.53 percent)
• Germany (gap of -2.227 percent)
• Austria (gap of -1.311 percent)

Top fiscal expansion countries are:

• Finland (7.514 percent)
• Ireland (GNI* gap of 6.822 percent)
• Spain (4.3 percent)
• Estonia (4.26 percent)

19/8/19: Import Zamescheniye: Replacing Imports with Imports in the Age of Trade Wars

Trump trade wars have led to increasing evidence of substitution by Chinese exporters to the U.S. with exports via third countries and supply chain outsourcing from China to other destinations. While direct evidence of these trends is yet to be provided (data lags are substantial for detailed flows of goods across borders) and is never to be treated as fully conclusive (due to differences in trade goods designations), here is some macro-level snapshot of latest data on U.S. imports shares for selective countries:

The chart above shows that based on trends, U.S. imports arrivals from China are down in 2017-2019, and they are up, significantly for Vietnam and Taiwan, with less pronounced evidence of imports substitution from other Asia-Pacific countries.

Given several caveats (listed below), the above chart is a 'messy' one:

1. Supply chain substitution takes time and may not be fully reflected in the 2018 data, or to a lesser extent, in 2019 data to-date; and
2. The above chart is based on monthly frequency data, which is volatilion (e to begin with.

With these caveats in mind, here is a chart based on annualized data:

Now, it is easier to spot the trends:

• China exports to the U.S. are down, sharply, especially considering pre-Trade Wars averages against Trade Wars period 2019 averages;
• Vietnam, Taiwan and Mexico are major channels for trade/import substitution (using Kremlin's term "import zamescheniye").
• Japan and Thailand are smaller-scale winners.
• Malaysia and Indonesia are basically static.

Now, historically, China has been beefing up its corporates' use of Vietnam, Thailand, and Mexico as platforms for supply chain diversification, which is consistent with the data responses to the Trade Wars. Indonesia and Malaysia are two surprises in this, although both experienced uptick in FDI from China in late 2018, so the data might not be showing these investments, yet.

18/8/19: Migration Policy vs the Law of Unintended Consequences

President Trump's policies are a rich field for sowing evidence on the application of the law of unintended consequence in economic policies. Take his Trade War with China that so far resulted in ca USD20 billion in fiscal receipts and USD26 billion payouts in subsidies to U.S. farmers, netting a fiscal loss of USD 6 billion (https://trueeconomics.blogspot.com/2019/06/17619-lose-lose-and-lose-some-more.html), while generating gains for European exporters (https://trueeconomics.blogspot.com/2019/08/15819-winning-trade-wars-round-3.html) and shrinking net real exports for the U.S. economy (https://trueeconomics.blogspot.com/2019/08/1919-losin-spectacularly-trump-trade.html) and driving losses to the U.S. exporters (https://trueeconomics.blogspot.com/2019/07/31719-fed-rate-cut-wont-move-needle-on.html). Another example, the never-ending rhetorical and regulatory war against skilled (and other) migration.

On the latter, we have plenty of evidence drawn from Mr. Trump's predecessors that conclusively shows the costs of severely restrictive application of the skills-based migration quotas. And, thanks to Mayda, A M, F Ortega, G Peri, K Shih, and C Sparber 2017 paper, titled “The Effect of the H-1B Quota on Employment and Selection of Foreign-Born Labor” (NBER Working Paper No. w23902, https://www.nber.org/papers/w23902.pdf), we now have an in-depth analysis of the mechanics by which unintended consequences of restricting skilled migration impose these economic losses on the U.S.

The authors looked at how changes in H-1B policy, enacted over the years, affect the characteristics of migrants entering the U.S. and how these changes alter U.S.-wide productivity and wages.

Per authors, "The economic intuition [behind the study] is simple. Firms across the globe compete to hire highly skilled workers. The strict quota and the lottery allocation generate uncertainty in acquiring the legal right to work in the US even after securing a job offer. Hence, talented foreign nationals might elect to work elsewhere. Similarly, US firms face uncertainty over whether they will be allowed to employ the top job candidates they have identified. Some firms might elect to forgo this uncertainty altogether by turning to alternative labour sources."

"First, we examine H-1B quality. ... ...H-1B restrictions have particularly hindered the employment of the highest ability foreign-born workers. Anyone who believes immigration policy should be designed to attract ‘the best and brightest’ workers to the country should be troubled by the discovery that restrictions to aggregate inflows generate the opposite effect. Quantitatively, the number of new H-1B workers from the highest wage quintile is nearly 50% lower than it would have been in the absence of H-1B restrictions, but the number of new H-1B workers in the median wage quintile is unchanged." In other words, if wages are a proxy for talent, skills and productivity, reducing H1B quotas appears to reduce availability of more skilled, more talented and more productive foreign workers, while having zero impact on availability of mid-range skills, talents and productivity workers.

Worse, reduced H1B quotas also increased concentration of H1B attaining firms (or reduced the pool of employers with a meaningful access to H1B workers). Authors conclude that "It is possible that when faced with the uncertainty and costs of the H-1B hiring process, economies of scale and network externalities arise that favour firms specialising in H-1B employment and workers with specialised knowledge about the legal hiring process." Or put differently, H1B quotas restriction may be fuelling increase in the share of foreign talent brought into the U.S. by outsourcing agencies and a handful of very larger employers. This selection bias does not appear to be linked to higher productivity and is, therefore, welfare reducing as compared to a system where firms that can generate higher productivity increases by employing foreign workers gain better access to H1B via markets.

In summary, "we presume that by reducing the H-1B cap from 195,000 in 2001-2003 to 85,000 today, policymakers intended to reduce new H-1B employment at for-profit firms and possibly increase employment of competing US-born workers. The policy achieved the first but not the second goal. Moreover, the cap restriction also generated consequences that were likely unintended. The policy change has particularly deterred workers with the highest earnings potential from entering the US labour market. Given the potential for productivity-enhancing technological gains generated by H-1B workers, this loss could reverberate throughout the economy. Other important effects are distributional and favour computer-related occupations and firms that use the H-1B programme heavily."

Consequences. A lesson for MAGA crowd from their predecessors.

16/8/19: Post-Millennials and the falling trust in institutions of coercion

A neat chart from Pew Research highlighting shifting demographics behind the changing trends in the U.S. public trust in core institutions:

Source: https://www.people-press.org/2019/07/22/how-americans-see-problems-of-trust/

Overall, the generational shift is in the direction of younger GenZ putting more trust in scientists and academics, as well as journalists, compared to previous generations; and less trust in military, police, religious leaders and business leaders. Notably, elected officials have pretty much low trust across all three key demographics.

16/8/19: U.S. Military Presence Worldwide

Generally, I do not find Politico to be a great source for geopolitical analysis and data, but here is one exception - a handy map of U.S. military bases, smaller deployment platforms and unconfirmed deployment platforms worldwide:

Thirty years after the end of the Cold War, one country remains completely and comprehensively surrounded by the U.S. military deployment platforms (and these exclude non-U.S. Nato platforms): Russia.

The map does not show the U.S. navy and airforce reach zones, nor does it include Nato's non-U.S. troops bases.

Some 'Peace Dividend' this is, especially given the threat rhetoric from Washington. And any wonder, Russian geopolitical stance remains that of a country under the siege?

Source for the chart: https://www.politico.com/magazine/story/2015/06/us-military-bases-around-the-world-119321.

15/8/19: Winning Trade Wars: Round 3

A couple of days ago, Germany's info Institute published two scenarios estimating the impacts of the latest President Trump threats to China, the imposition of a 10% tariff on Chinese exports to the U.S.

Per ifo's Scenario 1: "If the US imposed 10 percent tariffs on additional imports worth USD 300 billion, this would mean additional income of EUR 94 million for Germany, EUR 129 million for France, EUR 183 million for Italy, EUR 25 million for Spain, and EUR 86 million for the United Kingdom. It would amount to EUR 1.5 billion for the EU28 and EUR 1.8 billion for the US. China would see losses of EUR 24.8 billion." Note: the U.S. 'gains' do not account for U.S. agricultural subsidies supports increases announced by the Trump Administration, but include estimated consumer impact. Potential depreciation of yuan was also not accounted for in these estimates.

Summarising Scenario 1, ifo noted that "The additional tariffs on US imports from China threatened by US President Donald Trump would negatively impact China, while giving the US, Europe, and the UK moderate advantages."

"However, Chinese retaliatory tariffs could turn the US advantage into a disadvantage, while somewhat reducing China’s losses," ifo notes in relation to the estimates of the impact under Scenario 2 that includes retaliatory tariffs by China. "These retaliatory measures would lead to even greater advantages for the UK and the EU. ...If China imposes a further 10 percent tariff on US imports, it could see its losses fall to EUR 21.6 billion, while turning profits for the US into losses of EUR 1.5 billion. The UK and the EU would have the last laugh and come off best. Germany would see additional income of EUR 323 million, with EUR 168 million for France, EUR 231 million for Italy, EUR 25 million for Spain, and EUR 58 million for the United Kingdom. The EU28 would benefit to the tune of EUR 1.7 billion."

12/8/19: OECD Tax Plans: Some Bad News

My column for the Cayman Financial Review covering OECD latest tax reforms proposals: https://www.caymanfinancialreview.com/2019/08/02/oecd-led-tax-reforms-a-prescription-for-a-less-competitive-economy/

12/8/19: Russian Markets Risk Assessments 2Q 2019

Euromoney on Russian markets risk performance in 2Q 2019 with comments from myself and others: https://www.euromoney.com/article/b1g9cypjfm97xh/ebri-q2-results-putin-joins-the-party-as-russia-steps-up-a-gear.

10/8/19: Irish Debt Sustainability Miracle(s): ECB and MNCs

As a part of yesterday's discussion about the successes of Irish economic policies since the end of the Eurozone crisis, I posted on Twitter a chart showing two pivotal years in the context of changing fortunes of Irish Government debt sustainability. Here is the chart:

The blue line is the difference between the general Government deficit and the primary Government deficit, which captures net cost of carrying Government debt, in percentages of GDP. In simple terms, ECB QE that started in 2015 has triggered a massive repricing of Eurozone and Irish government bond yields. In 2012-2014 debt costs remained the same through 2015-2019 period, Irish Government spending on debt servicing would have been in the region of EUR 49.98 billion in constant euros over that period. As it stands, thanks to the ECB, this figure is down to EUR 27.94 billion, a saving of some EUR 4.41 billion annually.

Prior to 2015, another key moment in the Irish fiscal sustainability recovery history has been 2014 massive jump in real GDP growth. Over 2010-2013, the economic recovery in Ireland was generating GDP growth of (on average) just 1.772 percent per annum. In 2014, Irish real GDP growth shot up to 8.75 percent and since the start of 2014, growth averaged 6.364 percent per annum even if we are to exclude from the average calculation the bizarre 25 percent growth recorded in 2015. Of course, as I wrote on numerous occasions before, the vast majority of this growth between 2014 and 2019 is accounted for by the tax-optimisation transfer pricing and assets redomiciling by the multinational corporations - activities that have little to do with the real Irish economy.

8/8/19: Irish New Housing Markets Continue to Underperform

New stats for new dwelling completions in Ireland are out today and the reading press releases on the subject starts sounding like things are getting boomier. Year on year, single dwellings completions are up 15.5% in 2Q 2019, scheme units completions up 2.6%, apartments up 55.6% and all units numbers are up 11.8%. Happy times, as some would say. Alas, sayin ain't doin. And there is a lot of the latter left ahead.

Annualised (seasonally-adjusted) data suggests 2019 full year output will be around 18,000-18,050 units, which is below the unambitious (conservative) target of 25,000. And this adds to the already massive shortage of new completions over the last eleven years. Using data from CSO (2011-present), cumulated shortfall of new dwellings completions through December 2018 was 125,800-153,500 units (depending on target for annual completions set, with the first number representing 25K units per annum target, and the second number referencing target of 25K in 2011, rising to 30K in 2016 and staying at 30K through 2019). By the end of this year, based on annualised estimates, the shortfall will be 132,400-162,250 units. Taking occupancy at 2.1 persons per dwelling, this means some 278,000-341,000 people will be shortchanged out of purchasing or renting accommodation at the start of 2020.

Here is a chart summarising the stats:

Let's put the headline numbers into perspective: at the current 'improved' construction supply levels (using annualised 2019 figure), it will take us between 6.3 and 7.7 years to erase the already accumulated gap in demand. If output of new dwellings continues to grow at 11.8% per annum indefinitely, Irish construction sector will be able to close the cumulative gap between supply and demand by around 2029 in case of the targeted output at 25K units per annum, or worse, by 2031 for the output target of 30K units per annum.

8/8/19: Upbeat Jobs Reports Miss Some Real Points

Unemployment claims down, the weekly jobs report seemed to have triggered the usual litany of positive commentary in the business media

But all is not cheerful in the U.S. labor markets, once you start scratching below the surface. Here are two broader metrics of labor markets health: the civilian employment to population ratio and the labor force participation rate, based on monthly data through July:

The above shows that

1. Civilian labor force participation rate is running still below the levels last seen in the late 1970s, and the current recovery period average (close to the latests monthly running rate) is below any recovery period average since the second half 1970s recession end.
2. You have to go back to the mid-1980s to find comparable 'expansion period'-consistent levels of labor force participation rate as we have today. This is dire. Current recovery-period and President Trump's tenure period averages for labor force participation rate sit below all recovery periods' averages from 1984 through 2006. 

So much for upbeat jobs reports.

6/8/19: El Paso and Dayton mark 2019 as the worst year for mass shooting violence in America on record

In the wake of the extremely sad events of the last two weeks, it took me some time to run through the data from the https://www.gunviolencearchive.org/ on mass shootings in the U.S. 2014-2019 (to-date), and the numbers are shocking. The El Paso, TX shooting of August 3, followed by the Dayton, OH incident on August 4  (with combined numbers of those killed or injured at 82 with 30 people dead, may they rest in peace) have shaken the world (see, for example, https://www.nytimes.com/2019/08/06/world/europe/mass-shooting-international-reaction.html). 

Here is a summary table on U.S. mass shootings over the last 5 years and 7 months:

So far, 2019 has been the deadliest year on record in terms of overall number of mass shooting incidents, in terms of the numbers of people killed and injured, in terms of the number of people killed, in terms of the number of people injured, and in terms of the number of incidents with 10 or more people killed and injured.

Here is a summary of the 26 largest mass shootings on record:

There appears to be little in terms of distributional trends, especially given small number of years in data coverage, but so far, data suggests that there can be an ongoing increase in the number and severity of mass shootings over the years, with 2019-to-date reconfirming 2016-2017 dynamics that were partially reversed in 2018.

Two visualisation charts, identifying the Texas mass shooting of August 3rd:

 

As the charts above clearly show, August 3, 2019 shooting in Texas is the fourth largest in terms of people either killed or injured (46) after October 1, 2017 mass shooting in Nevada (500), June 12, 2016 shooting in Florida (103), and November 5, 2017 mass shooting in Texas (47).

Overall, there has been 1,925 mass shootings in the U.S. over 2042 days since the start of 2014, with 2,163 people killed and 8.160 people injured. Since January 1, 2014 through August 4 2019, on average, almost 1.06 persons died and 4 persons were injured in mass shootings per day.

The impact of these horrific incidents is, of course, far deeper-reaching, touching the lives of those close to people killed or injured, as well as those in public vicinity of those directly impacted. There is also an unquantifiable broader impact on the society at large. We need better data to better understand these deeper and broader impacts.

We also need better data to try and decipher any causal links and drivers for these horrific crimes. And we need more analysis of the deeper roots and causes of these.


As a tail end of the post, my deepest sympathies to the families and friends of those taken away by the gunmen in mass shootings, and indeed by all gunmen in all guns-involved violent events, and my best wishes for full and speedy recovery for all those injured by them.