**6. Country cases, indicators, time period, limitations and measurements**

In what follows, we compare the outcomes of different welfare and production regime-types. The list of developed countries in the sample is grouped into four different types of welfare regimes and three different types of varieties of capitalism. Australia, Canada, Ireland, the United Kingdom and the United States are examples of the liberal welfare state and liberal market economy (LWS-LME). Austria, Belgium, Germany and the Netherlands are examples of the conservative-corporatist welfare state and coordinated market economy (CWS-CME). Denmark, Finland and Sweden are examples of the social democratic welfare state and coordinated market economy (SDWS-CME). And Greece, Italy, Portugal and Spain serve as examples of the southern welfare state and Mediterranean economy (SWS-ME) [2, 19].

We use the following nine indicators from the OECD database in order to compare the outcomes of 16 countries (clustered into four regime-types) before and after the recent crisis: *public sector employment* (employees in general government as a percentage of total employment), *direct job creation* (temporary work, and in some cases, regular jobs in the public or non-profit sector, offered to unemployed individuals), *social protection expenditures* (as a percentage of total expenditures), *long term unemployment* (share of unemployed as a percentage of the unemployed population), *involuntary part time work* (share of involuntary part-timers as a percentage of part-time employment, in dependent employment), *marginally attached workers* (those aged 15 and over, neither employed nor actively searching for work, but are willing to take up a job, as share of labor force), *short-term job tenure* (percentage of employees working for their employers for less than 1 year), *trade union density* (the ratio of wage and salary earners who are union members, divided by the total number of wage and salary earners) and *collective bargaining coverage* (number of employees covered by the collective agreement, divided by the total number of wage and salary earners) [35].

These nine indicators [36–44] were chosen for a variety of reasons. First, they were readily available for two points in time—one pre-crisis (2007) and one post-crisis (2017–2018)—for all the selected countries. Second, they are decent measures of socio-economic outcomes as they encompass a range of factors integral to macro-economic stability and social well-being. Third, they are easily accessible to a very broad audience. Fourth, they are measured regularly by the OECD, so they can be periodically updated to show further divergent or convergent trends beyond the most recent year for which data was available. Fifth, the choice of indicators was guided by an interest in processes connected to marginalization and social exclusion, given the type of welfare regime and variety of capitalism is supposed to be consequential for determining the relative inclusion and exclusion of certain groups in society. While some indicators do not capture the socio-economic position of large numbers of people, they are nevertheless important measures of social cohesion, which is an important social policy goal in all welfare and production regimes.

Making cross-country comparisons, however, is complicated by the differential impacts of the global financial and public debt crises. They did not affect all countries to the same extent and policy reactions and recovery processes have been very much unequal. In part, this is because of significant variations in financial

**29**

*The Political Economy of Crisis Recovery DOI: http://dx.doi.org/10.5772/intechopen.92586*

to another (**Table 1**).

therefore be taken before generalizing across cases.

there were small differences in the rates of the CWS-CMEs.

241.54%. Within-regime differences in rates were quite common.

different rates (2.92, 8.37, 16.05 and 22.36%) (**Table 2**).

and trade linkages and the practices and quality of other institutional factors such as exchange rate regimes and capital controls. The debt crises, for example, were prevalent in European countries, especially the Mediterranean region. Different regulatory settings, economic conditions, demographics and political factors all help determine both the level of vulnerability of welfare regimes and market economies to external shocks and the nature, direction and robustness of policy responses. This is one of the reasons why it is difficult to provide a single start date for the crisis or attribute crisis mitigation and recovery processes to the designs and capacities of specific types of welfare states and production models. Care should

The pre- and post-crisis periods can be used as a test case to compare the socioeconomic outcomes of different welfare production systems. For this purpose, several indicators can be utilized to shed light on the extent of cross-national outcome convergence and divergence, which can be measured by comparing the: overall direction of change in the indicators (e.g., numeric outcomes improved or deteriorated), numerical values of the indicators (e.g., values very similar or different to each other), percent changes from one period to another, average country group scores, and average country group percent changes from one period

Public sector employment decreased in 12 out of 15 countries. The share of employment in general government ranged between 10.49 and 28.83% in 2017. In line with divergent expectations, the SDWS-CMEs had the highest rates of public employment (averaging 27.05%), although they all experienced a small decline. Perhaps more surprisingly, the LWS-LMEs, CWS-CMEs and SWS-MEs all had similar rates and group averages, making them somewhat indistinguishable. However,

Direct job creation for the unemployed increased in seven countries, decreased in five countries and remained the same in three countries. Percent change increases ranged from 5.26 to 4100%. Percent change decreases ranged between 6.12 and 100%. While more countries had created public jobs for their vulnerable members since 2007, the 16 country group average in 2017 had declined by a change of 1.48%. Unexpectedly, the group average of the CWS-CMEs had decreased by a change of 52.71% while the group average of the SWS-MEs had increased by a change of

Social protection expenditures increased in 10 out of 15 countries. Percent change increases ranged from 2.72 to 66.76%. The group averages of all regimetypes except the LWS-LMEs increased in 2017. Contrary to expectations, the group averages of the SDWS-CMEs and LWS-LMEs were very similar in 2017 (36.06 and 33.56%), despite these two regime-types representing opposite ends of the social expenditure spectrum in the worlds of welfare literature. Within-regime percentages were very similar among the LWS-LMEs and SDWS-CMEs, with most of them in the early to mid-30% range. However, the rates among the CWS-CMEs varied considerably (ranging from 16.66 to 46.14%). Similarly, the CWS-MEs all had very

The share of individuals out of work for 1 year or more increased in 12 out of 16 countries. Percent change increases ranged between 2.54 and 104.41%. In 2018, the LWS-LMEs and SDWS-CMEs experienced an increase in their long-term unemployment rates and both regimes had very similar group averages (21.98 and 19.5%). While most CWS-CMEs saw their rates decrease in the post-crisis period, their group average (39.25%) was higher than that of the LWS-LMEs and SDWS-CMEs. There were significant within-regime differences in terms of rates among the LWS-LMEs, CWS-CMEs and SWS-MEs, showing once again divergent theories fail

to account for dissimilar outcomes within particular regime-clusters.

#### *The Political Economy of Crisis Recovery DOI: http://dx.doi.org/10.5772/intechopen.92586*

and trade linkages and the practices and quality of other institutional factors such as exchange rate regimes and capital controls. The debt crises, for example, were prevalent in European countries, especially the Mediterranean region. Different regulatory settings, economic conditions, demographics and political factors all help determine both the level of vulnerability of welfare regimes and market economies to external shocks and the nature, direction and robustness of policy responses. This is one of the reasons why it is difficult to provide a single start date for the crisis or attribute crisis mitigation and recovery processes to the designs and capacities of specific types of welfare states and production models. Care should therefore be taken before generalizing across cases.

The pre- and post-crisis periods can be used as a test case to compare the socioeconomic outcomes of different welfare production systems. For this purpose, several indicators can be utilized to shed light on the extent of cross-national outcome convergence and divergence, which can be measured by comparing the: overall direction of change in the indicators (e.g., numeric outcomes improved or deteriorated), numerical values of the indicators (e.g., values very similar or different to each other), percent changes from one period to another, average country group scores, and average country group percent changes from one period to another (**Table 1**).

Public sector employment decreased in 12 out of 15 countries. The share of employment in general government ranged between 10.49 and 28.83% in 2017. In line with divergent expectations, the SDWS-CMEs had the highest rates of public employment (averaging 27.05%), although they all experienced a small decline. Perhaps more surprisingly, the LWS-LMEs, CWS-CMEs and SWS-MEs all had similar rates and group averages, making them somewhat indistinguishable. However, there were small differences in the rates of the CWS-CMEs.

Direct job creation for the unemployed increased in seven countries, decreased in five countries and remained the same in three countries. Percent change increases ranged from 5.26 to 4100%. Percent change decreases ranged between 6.12 and 100%. While more countries had created public jobs for their vulnerable members since 2007, the 16 country group average in 2017 had declined by a change of 1.48%. Unexpectedly, the group average of the CWS-CMEs had decreased by a change of 52.71% while the group average of the SWS-MEs had increased by a change of 241.54%. Within-regime differences in rates were quite common.

Social protection expenditures increased in 10 out of 15 countries. Percent change increases ranged from 2.72 to 66.76%. The group averages of all regimetypes except the LWS-LMEs increased in 2017. Contrary to expectations, the group averages of the SDWS-CMEs and LWS-LMEs were very similar in 2017 (36.06 and 33.56%), despite these two regime-types representing opposite ends of the social expenditure spectrum in the worlds of welfare literature. Within-regime percentages were very similar among the LWS-LMEs and SDWS-CMEs, with most of them in the early to mid-30% range. However, the rates among the CWS-CMEs varied considerably (ranging from 16.66 to 46.14%). Similarly, the CWS-MEs all had very different rates (2.92, 8.37, 16.05 and 22.36%) (**Table 2**).

The share of individuals out of work for 1 year or more increased in 12 out of 16 countries. Percent change increases ranged between 2.54 and 104.41%. In 2018, the LWS-LMEs and SDWS-CMEs experienced an increase in their long-term unemployment rates and both regimes had very similar group averages (21.98 and 19.5%). While most CWS-CMEs saw their rates decrease in the post-crisis period, their group average (39.25%) was higher than that of the LWS-LMEs and SDWS-CMEs. There were significant within-regime differences in terms of rates among the LWS-LMEs, CWS-CMEs and SWS-MEs, showing once again divergent theories fail to account for dissimilar outcomes within particular regime-clusters.


#### **Table 1.**

*Public sector employment (PSE), direct job creation (DJC) and social protection expenditures (SPE) in worlds of welfare and varieties of capitalism.*

The share of involuntary part-timers increased in 7 out of 13 countries. Percent change increases ranged from 19.75 to 157.41%. Consistent with divergent theories, the LWS-LMEs and SWS-MEs had some of the highest rates (23.07 and 64.42%), while the CWS-CMEs and SDWS-CMEs had the lowest (8.48 and 11.25%). The sample group average increased by a change of almost 20%.

The share of marginally attached workers decreased in eight countries, increased in six countries and remained the same in two countries. Country group averages were nearly indistinguishable in 2018, blurring the dividing lines between countries. There were notable differences among the LWS-LMEs, CWS-CMEs and SDWS-CMEs, particularly Australia, the Netherlands and Finland whose rates were more than twice that of their group members (**Table 3**).

The share of employees with less than 1 year job tenure decreased in nine countries and increased in six countries. Percent change decreases ranged between 3 and

**31**

**16 Country Averages**

**Table 2.**

SDWS-CMEs whose rates were similar.

*(MAW) in worlds of welfare and varieties of capitalism.*

*The Political Economy of Crisis Recovery DOI: http://dx.doi.org/10.5772/intechopen.92586*

**2007**

**Liberal Welfare State & Liberal Market Economy (LWS-LME)**

**LTU 2018**

**Conservative Welfare State & Coordinated Market Economy (CWS-CME)**

**Social Democratic Welfare State & Coordinated Market Economy (SDWS-CME)**

**Southern Welfare State & Mediterranean Economy (SWS-ME)**

**IPTW 2007**

Australia 18.5 19.4 23.8 28.5 7.1 5.5 Canada 7.0 10.1 N/A N/A 2.1 1.9 Ireland 30.0 40.8 10.8 27.8 (2017) 0.8 (2008) 3.5 UK 23.8 26.3 9.7 12.9 2.3 (2008) 1.2 US 10.0 13.3 N/A N/A 0.9 0.9 **Averages** 17.86 21.98 14.77 23.07 2.64 2.60

Austria 27.2 28.9 13.0 10.6 3.8 2.5 Belgium 50.4 48.7 15.2 6.8 1.4 1.7 Germany 56.6 41.4 21.6 9.9 1.6 1.3 Netherlands 39.4 38.0 4.6 6.6 3.2 3.0 **Averages** 43.40 39.25 13.60 8.48 2.50 2.12

Denmark 16.1 20.2 13.1 13.1 1.9 1.2 Finland 23.0 22.8 N/A N/A 3.3 4.6 Sweden 12.8 15.5 13.1 9.4 2.1 1.7 **Averages** 17.30 19.5 13.10 11.25 2.43 2.50

Greece 49.7 70.3 61.6 78.6 0.9 2.4 Italy 47.5 59.0 40.8 66.3 3.3 (2010) 3.6 Portugal 47.2 48.4 54.7 53.5 (2017) 1.3 2.5 Spain 20.4 41.7 37.5 59.3 3.6 3.6 **Averages** 41.20 54.85 48.65 64.42 2.27 3.02

29.97 34.05 24.58 29.48 2.47 2.57

**IPTW 2018**

**MAW 2007**

**MAW 2018**

**Indicator year LTU**

22.43%. Percent change increases were from 0.92 to 89.42%. Short-term job tenure rates were similar in the LWS-LMEs and SDWS-CMEs (close to 20% points), contrary to expectations. In the literature, the prevalence of flexible employment is said to be greater in the liberal economies. While short-term job tenure decreased in most places, at least 11 countries from four different regimes had rates between 16 and 22%, meaning nearly one-fifth of all their employees were working for their employers for less than 12 months. These similar rates make the regime-clusters indistinguishable as well. There were also within-regime differences among the CWS-CMEs and SWS-MEs. Trade union density decreased in 15 out of 16 countries. In eight countries, there were percent change decreases ranging between 15 and 30%. Consistent with expectations, the LWS-LMEs and SWS-MEs had the lowest union density figures, with the CWS-CMEs and SDWS-CMEs coming in second and third place respectively. There were considerable outliers in all the regime-types except the

*Long-term unemployment (LTU), involuntary part-time workers (IPTW) and marginally attached workers* 

#### *The Political Economy of Crisis Recovery DOI: http://dx.doi.org/10.5772/intechopen.92586*


#### **Table 2.**

*Long-term unemployment (LTU), involuntary part-time workers (IPTW) and marginally attached workers (MAW) in worlds of welfare and varieties of capitalism.*

22.43%. Percent change increases were from 0.92 to 89.42%. Short-term job tenure rates were similar in the LWS-LMEs and SDWS-CMEs (close to 20% points), contrary to expectations. In the literature, the prevalence of flexible employment is said to be greater in the liberal economies. While short-term job tenure decreased in most places, at least 11 countries from four different regimes had rates between 16 and 22%, meaning nearly one-fifth of all their employees were working for their employers for less than 12 months. These similar rates make the regime-clusters indistinguishable as well. There were also within-regime differences among the CWS-CMEs and SWS-MEs.

Trade union density decreased in 15 out of 16 countries. In eight countries, there were percent change decreases ranging between 15 and 30%. Consistent with expectations, the LWS-LMEs and SWS-MEs had the lowest union density figures, with the CWS-CMEs and SDWS-CMEs coming in second and third place respectively. There were considerable outliers in all the regime-types except the SDWS-CMEs whose rates were similar.


#### **Table 3.**

*Short-term job tenure (STJT), trade union density (TUD) and collective bargaining coverage (CBC) in worlds of welfare and varieties of capitalism.*

Collective bargaining coverage decreased in eight countries, increased in five countries and remained the same in three countries. Group averages in 2017 were consistent with assumptions in the literature, although the SDWS-CMEs, CWS-CMEs and SWS-MEs had very similar averages in 2007. Within-regime differences were notable in all the regime-types except the SDWS-CMEs whose rates were similar.

#### **7. Conclusion**

Overall, there was unidirectional convergence toward negative outcomes in many countries in the post-crisis period. Many countries have not returned to their precrisis levels as several indicators show, including public sector employment (12 out of 15 countries experienced a decrease), direct job creation (decreased in 5 out of 15

**33**

**Author details**

Mohammad Ferdosi

McMaster University, Hamilton, Canada

provided the original work is properly cited.

direction of change and the value of the outcomes.

\*Address all correspondence to: ferdosim@mcmaster.ca

*The Political Economy of Crisis Recovery DOI: http://dx.doi.org/10.5772/intechopen.92586*

countries), social protection expenditures (decreased in 5 out of 15 countries), longterm unemployment (increased in 12 out of 16 countries), involuntary part-time work (increased in 7 out of 13 countries), marginally attached workers (increased in 6 out of 16 countries), short-term job tenure (increased in 6 out of 15 countries), union density (decreased in 15 out of 16 countries) and collective bargaining coverage (decreased in 8 out of 16 countries). Different welfare production systems were therefore not always distinguishable in terms of their impact on the overall direction of change, as many countries were worse off on almost every indicator after the crisis than before it, or the degree of change from 1 year to another, as some of the greatest negative percent changes were reported among the least expected regime-types such as the SDWS-CMEs. It also seems less plausible that the type of welfare or production regime makes as much difference in shaping the value of outcomes as some of the literature seems to suggest. This can be seen in very similar group averages for indicators such as public sector employment (with three regime averages ranging between 14 and 16%), social protection expenditures (with two opposite regimes exhibiting averages between 33 and 36%), long-term unemployment (two regimes had averages between 19 and 21%), marginally attached workers (all four regimes had averages between 2 and 3%), short-term job tenure (two regimes had averages between 19 and 21% and two regimes had 15% averages) and trade union density (two regimes had averages between 19 and 20%). Furthermore, individual countries belonging to the same regime cluster sometimes shared very little in common with their group members in terms of the

However, it is not implausible that the type of welfare or production regime makes some difference. This is most clearly demonstrated in the data by the way different types of welfare and production systems were characterized by different average levels of direct job direction, involuntary part-time workers and collective bargaining coverage. Overall, however, the empirical evidence seems to call into question between

regime differences and within regime similarities as postulated by mainstream theoretical understandings of welfare states and varieties of capitalism. There appears to be more evidence of convergence than divergence in negative outcomes across the four regime clusters, as well as lack of evidence to support within-regime coherence.

© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,

#### *The Political Economy of Crisis Recovery DOI: http://dx.doi.org/10.5772/intechopen.92586*

countries), social protection expenditures (decreased in 5 out of 15 countries), longterm unemployment (increased in 12 out of 16 countries), involuntary part-time work (increased in 7 out of 13 countries), marginally attached workers (increased in 6 out of 16 countries), short-term job tenure (increased in 6 out of 15 countries), union density (decreased in 15 out of 16 countries) and collective bargaining coverage (decreased in 8 out of 16 countries). Different welfare production systems were therefore not always distinguishable in terms of their impact on the overall direction of change, as many countries were worse off on almost every indicator after the crisis than before it, or the degree of change from 1 year to another, as some of the greatest negative percent changes were reported among the least expected regime-types such as the SDWS-CMEs. It also seems less plausible that the type of welfare or production regime makes as much difference in shaping the value of outcomes as some of the literature seems to suggest. This can be seen in very similar group averages for indicators such as public sector employment (with three regime averages ranging between 14 and 16%), social protection expenditures (with two opposite regimes exhibiting averages between 33 and 36%), long-term unemployment (two regimes had averages between 19 and 21%), marginally attached workers (all four regimes had averages between 2 and 3%), short-term job tenure (two regimes had averages between 19 and 21% and two regimes had 15% averages) and trade union density (two regimes had averages between 19 and 20%). Furthermore, individual countries belonging to the same regime cluster sometimes shared very little in common with their group members in terms of the direction of change and the value of the outcomes.

However, it is not implausible that the type of welfare or production regime makes some difference. This is most clearly demonstrated in the data by the way different types of welfare and production systems were characterized by different average levels of direct job direction, involuntary part-time workers and collective bargaining coverage. Overall, however, the empirical evidence seems to call into question between regime differences and within regime similarities as postulated by mainstream theoretical understandings of welfare states and varieties of capitalism. There appears to be more evidence of convergence than divergence in negative outcomes across the four regime clusters, as well as lack of evidence to support within-regime coherence.
