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First review of “Foreign States in Domestic Markets”

Professor Lucia Quaglia has just published in Regulation and Governance the first review of my recent book Foreign States in Domestic Markets (joint with Professor Mark Thatcher and published with Oxford University Press).

It makes a number of interesting points worth reading in full here and is very generous in its positive overall assessment of the book:

“This book is a “must” for scholars of International Political Economy and Comparative Political Economy. It is impressive in terms of analytical rigor, breath of empirical coverage and importance of the findings and how they contribute to the existing literature.”

New book on Foreign States in Domestic Markets is finally out with Oxford University Press!

Political economy debates have focused on the internationalisation of private capital, but foreign states increasingly enter domestic markets as financial investors. How do policy makers in recipient countries react? Do they treat purchases as a threat and impose restrictions or see them as beneficial and welcome them? What are the wider implications for debates about state capacities to govern domestic economies in the face of internationalisation of financial markets?

In response, Foreign States in Domestic Markets have developed the concept of ‘internationalised statism’, where governments welcome the use of foreign state investments to govern their domestic economies. These foreign state investments are applied to the most prominent overseas state investors, Sovereign Wealth Funds (SWFs). Many SWFs are from Asia and the Middle East and their number and size have greatly expanded, reaching $9 trillion by 2020.

This book examines policies towards non-Western SWFs buying company shares in four countries: the US, UK, France, and Germany. Although the US has imposed significant legal restrictions, the others have pursued internationalised statism in ways that are surprising given both popular and political economy classifications. This book argues that the policy patterns found are related to domestic politics, notably the preferences and capacities of the political executive and legislature, rather than solely economic needs or national security risks.

The phenomenon of internationalised statism underlines that overseas state investment provides policy makers in recipient states with new allies and resources. The study of SWFs shows that internationalisation and liberalisation of financial markets offer national policy makers opportunities to govern their domestic economies.

You can order the book at Oxford University Press , Waterstones , or Amazon.

Witness at International Trade Committee

I recently gave evidence as a witness in the inquiry into Inward Foreign Direct Investment organised by the International Trade Committee. Other witnesses included Diego López, Managing Director, Global SWF; Duncan Bonfield, Chief Executive Officer, International Forum of Sovereign Wealth Funds; Nicolai Tangen, Chief Executive Officer, Norges Bank Investment Management; Trond Grande, Deputy Chief Executive Officer, Norges Bank Investment Management; Lord Grimstone, Investment Minister, Department for International Trade / Department for Business, Energy and Industrial Strategy; and Lord Callanan, Minister for Business, Energy and Corporate Responsibility, Department for Business, Energy and Industrial Strategy.

New working paper on Weather and Lockdown Compliance

The effectiveness of containment measures depends on both epidemiological and sociological mechanisms, most notably compliance with national lockdown rules. Yet, there is growing discontent with social distancing rules in many countries, which is expected to intensify further during summer. Using a highly granular dataset on compliance of over 105,000 individuals in the United Kingdom (UK), we find that compliance with lockdown policies tends to be high in the overall population, but that specific segments of society are substantially less compliant. Our findings show that warmer temperatures decrease non-compliance with governmental guidelines of individuals who are male, divorced, part-time employed, and/or parent of more than two children. Thus, as long as heard immunity through vaccination is not achieved and new strains demand containment measures to remain in place, understanding the individual determinants of non-compliance behaviour in different seasons of the year will remain important for policymakers to design effective policies in the future.

Full paper can be accessed at: https://www.researchgate.net/publication/352355506_Weather_and_Lockdown_Compliance

My piece on Pandemic misery index in top 5 most read in LSE EUROPP blog in 2020

To mark the end of 2020, the LSE EUROPP blog compiled a list of top 5 EUROPP articles with the highest readership in 2020 and my recent post introducing a pandemic misery index was ranked 3rd:

1. The implications of Brexit for the UK economy

2. The economic consequences of Covid-19

3. A pandemic ‘misery index’: Ranking countries’ economic and health performance during Covid-19

4. Beating Covid-19: The problem with national lockdowns

5. Thomas Piketty on inequality

Pandemic Misery Index

Ranking countries economic and health performance during Covid19

Tim Vlandas, University of Oxford. This post first appeared on LSE Europe blog

What has been the economic and health performance of different countries since the covid19 crisis began? I propose to rank countries on the basis of how they have fared since the ongoing pandemic began by combining data on two dimensions: a health dimension capturing mortality data; and an economic dimension capturing increases in unemployment.

While the two indicators I select cannot provide an exhaustive picture, they are nevertheless useful in giving us some sense of how countries have fared across two of the dimensions that the covid19 crisis has affected most.

A measure of health costs

The health dimension is based on the so-called p-score. This data is available from the ourworldindata website (data extracted on 14th November 2020) and captures the weekly deviation of current mortality from the 5 years average for that week.

Excess mortality have two advantages over more direct measures of covid19 deaths. First, they do not depend on the testing capacity of the country under consideration, nor are they dependent on definitions of what it means to have died from covid19.

Second, they include the total ‘health cost’ of the pandemic in terms of mortality, i.e. the excess deaths that are the product of both the pandemic and the policy responses to the pandemic.

A measure of economic costs

However, as is well recognised and widely discussed, the pandemic and our policy responses entail significant economic costs. Many economic indicators could be relevant to capture the economic costs. For my purpose, I focus on monthly unemployment rate data, which is extracted from the OECD website.

Partly, this choice is based on data availability constraints, since the alternative to use instead GDP growth data would be hindered by more limited, less recent and less frequent data at the time of writing.

But partly this choice finds inspiration in the so-called misery index which was created following the stagflation in the 1970s. At the time, governments were attempting – and more or less able – to jointly minimise inflation and unemployment.

Adverse unemployment performance can be captured in two distinct ways. The first is simply to look at the average monthly unemployment rate. However, this does not account for the fact that when the pandemic hit, countries started from different relative position. Since the p-score is calculated as a percentage increase from a previous average, I calculate an ‘unemployment score’ as the percentage increase in unemployment from one month to the next.

Country coverage and time period

The following countries are included in my analysis: Austria, Belgium, Canada, Chile, Czech Republic, Denmark, England & Wales, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Israel, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, South Korea, Spain, Sweden, and the United States.

Because ourworldindata.org does not report excess deaths by age groups for the UK as a whole but instead for England&Wales, this is the data I use throughout. For most countries. I have data from January to September 2020 (inclusive). More recent data was not available for all countries at the time of writing so what follows does not capture what has happened since the ‘second wave’.

Excess mortality by age group

I start by showing the weekly evolution of excess mortality by four age groups (Figure 1): 15-64; 65-74; 75-84 and 85+.

The figure reveals the (by now) familiar worse performers, most notably Belgium and England. Note further that English experience is not atypical in the UK given the similar picture for Scotland and to a lesser extent Northern Ireland.  

Other countries that did not fare well include Chile, Spain, Netherlands, Italy; although we can observe differences in the timing of the peak. In all cases, excess mortality is strongly a function of age, as has been well documented elsewhere.

Figure 1: Weekly excess mortality by age group

Economic and health costs over time

If we abstract from the cross-national variation, we can see February was actually below the excess mortality average of the last five years for that time of the year and in March the average for our countries only experienced a mild increase. By contrast, in April most countries experienced very significant rises in their excess mortality (Figure 2).

Figure 2: Monthly excess mortality and unemployment score

Bringing in the labour market deterioration into the picture, the increase in unemployment associated with the lockdown measures many countries introduced is also apparent. From May onwards and well into September, both unemployment and mortality stopped to increase in any substantial way across this sample of countries.

The correlation between the unemployment score and different measures of excess mortality is statistically significant and positive but modest (between 0.13 and 0.15), which suggests that countries’ performance in one dimension does not relate strongly for its performance on the other dimension.

This contrasts with claims about the automatic inevitable adverse effects of addressing pandemic for the economy, but also about the presumed positive effects of addressing the pandemic for the economy.

Finally, the heterogeneity is apparent when it comes to excess mortality by age group (figure 3): while some countries experienced the highest increases in mortality for the very old (85+), in others the figures were worst for the 65 to 84, and we can observe both below and above average excess mortality rates for the 16-64 age group.

Figure 3: Excess mortality by country and age group over whole period (from Febuary 2020 onwards)

Pandemic Misery Index (PMI)

Policy makers are therefore faced with a joint minimisation problem whereby they are trying to minimise both health and economic costs. It is in this respect worth keeping in mind that both are – at least in the medium to long term – intrinsically linked to each one another.

On the one hand, mass health issues end up undermining economic productivity and growth. On the other hand, economic decline, insecurity and deprivation generate health problems while also limiting our ability to fund health interventions.

If we combine our economic and health performance indicators into a single pandemic misery index (PMI), we can see that the peak in April hides significant cross-national variation as captured by the standard deviation, and that as the mean of the PMI falls, so does its standard deviation (Figure 4).

In Figure 5, we plot the cross-national variation in the PMI. In the top worst performers we find three liberal market economies (the UK and the US) and two southern European countries (Spain, Italy and Portugal). Although not in top five worst performers, two small open economies in continental Europe – Belgium and Netherlands – also fared poorly.

Figure 4: Pandemic misery index over time

Note: the standard deviation statistic with weights returns the bias-corrected standard deviation, which is based on the factor sqrt(N_i/(N_i-1)), where N_i is the number of observations.

Figure 5: Pandemic misery index across countries

To assess what’s driving poor performance we can disaggregate the PMI along its two dimensions (Figure 6): the PMI in Spain, Italy and the UK is driven by mortality rates with relatively mild increases in unemployment, compared to the US and to Canada, where the increases in unemployment was much more acute.

Among good performers, we find several central and eastern European countries, including Latvia, Hungary, and Slovakia; and also Nordic countries such as Norway, Denmark and Iceland.

Of course, different countries started with different labour market positions, so plotting average levels (instead of changes) in unemployment rates, reveals a slightly different picture (Figure 7). Greece and Spain now look worsts in terms of unemployment rate over the period, followed by Chile, Canada, US and Italy. Czech Republic, Poland, Netherlands, England and Wales, among others kept a low level of unemployment rate.

Finally, excess mortality among the very old (85+) reveals especially dire numbers for parts of Southern Europe (Figure 8), but contrast Spain and Italy, and to a lesser extent Portugal on one hand, and Greece on the other hand. The US, England and Wales, and Canada score high but are not in the top 6 worst performers, while Iceland, Norway, Hungary, Denmark and Slovakia do especially well.

Figure 6: Disaggregating the pandemic misery index across countries

Figure 7: Disaggregated PMI using levels in average monthly unemployment

Figure 8: Disaggregated PMI using mortality rates for over 85 rather than all ages

CNN article on recent interest in UBI and divisions within UBI coalition

Very good new CNN article by Julia Horowitz on “Job guarantees and free money: ‘Utopian’ ideas tested in Europe as the pandemic gives governments a new role”.

It discusses the recent interest in the Universal Basic Incomes (UBI) and what economic and political factors are driving it.

As this partly touches on research I have been doing on support for UBI across Europe, I had the pleasure of discussing the challenges of a pro-UBI coalition with Julia.

Indeed, as I show in my recent articles, the coalition supporting the idea of a UBI is very heterogenous and it has been shown elsewhere that support also depends on the framing of the question.

Question in the European Social Survey

The 2016 wave of the ESS (ESS,2016) includes a question about the university basic income (UBI). Respondents are asked whether they are “against or in favour of the UBI scheme” being introduced in their respective country, which “some countries are currently talking about”, with the following characteristics:

1. The government pays everyone a monthly income to cover essential living costs;

2. It replaces many other social benefits;

3. The purpose is to guarantee everyone a minimum standard of living;

4. Everyone receives the same amount regardless of whether or not they are working;

5. People also keep the money they earn from work or other sources;

6. This scheme is paid for by taxes.

Support for the Universal Basic Income across countries

I focus on 21 countries in my analysis: Austria, Belgium, Czech Republic, Estonia, Finland, France, Germany, Hungary, Iceland, Ireland, Italy, Lithuania, Netherlands, Norway, Poland, Portugal, Slovenia, Spain, Sweden, Switzerland, and the United Kingdom.

Adding those who are “in favour” or “strongly in favour” of the scheme indicates that a slight majority (51.2%) support a UBI.

The cross-national variation can be observed below (with the bars indicating the uncertainty around the estimated country average). Support tends to be higher in South and Central Eastern Europe, and lower in Scandinavian countries.

Who supports UBI?

My findings are partly consistent with what we know about the drivers of support for other social policies. Younger, low-income, left-leaning individuals and the unemployed are more likely to support a UBI.

Individuals with positive views of benefit recipients and/or high trust in political institutions are also more supportive, while anti-immigration attitudes are associated with lower support.

Trade union membership is not always relevant, perhaps because of contradictory effects: unions typically support new welfare state policies but they also have a key role in many existing welfare state schemes and may worry about individuals’ attachment to the labour market.

Cross-national variation

At the cross-national level, support tends to be higher where unemployment benefit activation is more pronounced and unemployment benefits less generous.

This suggests that countries where welfare state institutions are less developed might be better placed to introduce a UBI.

The paradox of high support

Overall these findings suggest one possible reason why countries with high support for a UBI have not introduced it: the mixed support among the left means a pro-UBI coalition has to draw on right-wing voters who may support it only with lower taxes and/or extensive replacement of welfare state benefits, which in turn may further alienate parts of the left.

In other words, the fact that a UBI can mean different things to different people may explain both the fairly high support for the scheme in some countries and the difficulty in finding a politically viable coalition to support its introduction when the financing of a UBI and its interaction with existing welfare state benefits have to be specified.

Thus, the wide political appeal of the UBI might also be its greatest weakness: because many people support a UBI for very different reasons, the basis of support are politically and ideologically fragmented and may therefore be irreconcilable.

Details about European Social Survey

Reference:

European Social Survey (2017). ESS Round 8 (2016/2017) Technical Report. London: ESS ERIC

Excerpt from ESS website:

“The European Social Survey (ESS) is an academically-driven multi-country survey, which has been administered in over 30 countries to date. Its three aims are, firstly – to monitor and interpret changing public attitudes and values within Europe and to investigate how they interact with Europe’s changing institutions, secondly – to advance and consolidate improved methods of cross-national survey measurement in Europe and beyond, and thirdly – to develop a series of European social indicators, including attitudinal indicators. In the eighth round, the survey covers 23 countries and employs the most rigorous methodologies. From Round 7 it is funded by the Members, Observers and Guests of ESS European Research Infrastructure Consortium (ESS ERIC) who represent national governments. Participating countries directly fund the central coordination costs of the ESS ERIC, as well the costs of fieldwork and national coordination in their own country. The survey involves strict random probability sampling, a minimum target response rate of 70% and rigorous translation protocols. The hour-long face-to-face interview includes questions on a variety of core topics repeated from previous rounds of the survey and also two modules developed for Round 8 covering Public Attitudes to Climate Change, Energy Security, and Energy Preferences and Welfare Attitudes in a Changing Europe (the latter is a partial repeat of a module from Round 4).”

References

Vlandas, T. (2020) “The Political Economy of individual level support for the basic income in Europe” Journal of European Social Policy [PDF]

Vlandas, T. (2019) “The Politics of the Basic Income Guarantee: Analysing individual support in Europe” Basic Income Studies [PDF]