Unit 2 Unemployment, wages, and inequality: Supply-side policies and institutions
2.11 Successes and failures: Germany and Spain
We began this unit with the contrast between high-unemployment Spain and low-unemployment Germany, and how this worked out for Mar, the Spanish woman introduced in Section 2.1. What differences in institutions and policies could account for Spain’s failure to maintain low unemployment and the success of Germany and Denmark? The preceding section showcased the success of Denmark’s flexicurity policies. In this section, we contrast Germany and Spain.
Comparing macroeconomic performance
Among higher-income nations, there are substantial differences in the extent to which their economies successfully deliver low unemployment rates and rising real wages to their populations. In Figure 2.27, Spain’s poor macroeconomic performance—very high unemployment and a decline in real wages—is a clear outlier, but there are major differences among the other countries too. We call the economies that are higher and to the left in the figure—including both Germany and Denmark—‘successes’ because, opposite to Spain, they have the desirable combination of higher real wage growth and lower unemployment.
Above the diagonal line in the figure, the successful countries have different combinations of unemployment and wage growth: citizens may rank the performance of Australia and Japan as similarly good—Australia does very well on wage growth but not so well on unemployment; and vice versa for Japan. To the right of the diagonal line, Belgium and the UK might be ranked by citizens as similarly relatively poor performers. Belgium’s wage growth is better than the UK but its unemployment rate is higher.
Figure 2.27 Macroeconomic performance: Unemployment and wage growth (2010–2019). The red dots are major economies that at the time were members of the European Union.
The WS–PS model tells us where to find clues about the origins of these evident differences between the countries in the extent of structural unemployment and wage growth. To understand why Germany did better than Spain, we need to find factors that shift their price-setting curves up (raising the equilibrium real wage) while maintaining a sufficiently low wage-setting curve to allow high levels of employment (and hence low unemployment).
The level of taxation, pushing the PS curve in Spain down (and explaining the decline in wages there), cannot by itself explain the country’s poor performance; tax rates in Germany were higher (Figure 2.28 at the end of the section).
The factors highlighted in the model that could help explain the Spain–Germany difference include the level of the unemployment benefit as a fraction of wages. This is a bit higher in Spain than in Germany and could result in a higher WS curve in Spain, limiting the level of employment and raising unemployment. The size of trade unions—the fraction of workers covered by a trade union wage contract—is also higher in Spain than in Germany.
The success of Germany compared to Spain is also explained by the following interrelated factors:
- differences in the rate of productivity growth
- the extent of worker–employer cooperation
- the degree of competition in product markets.
Germany: Worker–employer cooperation, competition among firms
Wages in Germany were 30% higher than in Spain (over the same period as covered in Figure 2.27), the result of both a higher level of competition facing German firms (evident in the lower markup) and a level of labour productivity substantially exceeding that of Spain (Figure 2.28). One reason proposed for the higher German level of labour productivity is cooperative relations between employers and workers within firms, which pushes up the PS curve, and keeps the WS curve down. Negotiations about working practices, retraining, and technology occur in works councils consisting of managers and worker representatives (90% of employees in medium and large firms are represented in works councils at firm level, which are separate from unions, which are organized at industry level). For example, the introduction of robots to do the work of employees is typically not opposed by German workers who will often be retained by the firm and reassigned to other tasks.
Read this article to understand what happened to robot-exposed workers in Germany and a comparison with the US. In this article, researchers explain how Germany’s cooperative labour market institutions operated to deliver strong employment outcomes.
Spain: Firms and workers shielded from competition, slow growth in productivity
Spain differs from Germany in this respect. The institutions for cooperative relations between employers and workers at firm level (namely, the works councils in Germany) are missing. Moreover, Spanish employers face legal obstacles and economic costs if they wish to fire a worker (indicated by the difference in the employment protection index in Figure 2.28). This means that they must pay higher wages to motivate employees to work; a shift upwards in the WS curve. Spanish firms also face less competition in the markets for their products, and so mark up their prices above their costs by more (25% compared with 10% in Germany), shifting the PS curve downwards. The result of both shifts is lower wages and also lower employment (more unemployment) in Spain.
| Germany | Spain | Denmark | Sources and notes | |
|---|---|---|---|---|
| Tax share (% of total output) |
38.6 | 34.7 | 46.6 | OECD Global revenue statistics database 2019 |
| Union coverage (%) |
56 | 80.8 | 82 | OECD Trade unions and collective bargaining 2019 |
| Unemployment benefit generosity (%) |
81.6 | 83.2 | 90.1 | Unemployment benefit net replacement ratio (average of 10 categories covering different family types and wage levels) OECD Benefits taxes and wages 2019 |
| Product market competition (1 + markup) |
1.10 | 1.25 | not available | Tommaso Bighelli Marc Melitz, Filippo di Mauro, Matthias Mertens. 2023. JEEA 21 (2): pp. 455–483 Table 2. Equivalent to 1 + µ |
| Labour productivity (output per hour) |
76.8 | 59.6 | 84.5 | OECD.stat Level of output per capita and productivity 2019 |
| Union coordination (index) |
4 | 3 | 4 | OECD/AIAS ICTWSS database 2016 |
| Employment protection index (permanent workers) (higher value, harder to fire workers) |
2.22 | 2.43 | 1.84 | Version 4 OECD/AIAS ICTWSS database 2019 |
| Active labour market policy (% of output) |
0.68 | 0.71 | 1.89 | OECD Public expenditure and participant stocks on Labour Market Programmes 2018 |
| Productivity growth (output per hour, % per annum) |
1.2 | 1.0 | 1.6 | OECD Data set Growth in output per capita, productivity and ULC Extracted 060723 from OECD.Stat 2010–2019 |
Figure 2.28
Indicators for key variables in the WS–PS model: Germany, Spain, and Denmark.
Note: Each country’s total output is measured as its gross domestic product (GDP).
Exercise 2.10 Comparing labour market performance
Figure 2.28 provides statistics for Spain, Germany, and Denmark.
- Using the information in Figure 2.28, suggest how the WS–PS diagram for Denmark would differ from that of Spain and Germany.
Now choose one country from Figure 2.28 and one country from the following list: Belgium, Czech Republic, Finland, France, Italy, Lithuania, the Netherlands, Poland, Portugal, Romania, Slovakia, Sweden, Switzerland.
- For your chosen country, use the links and sources listed in Figure 2.28 to find as many of these variables as you can. Use the same year as in Figure 2.28 or, if that is not possible, use the latest year available. (Note that for ‘Active labour market policy’, the variable to search for in the OECD link is ‘210: Active programmes without employment maintenance incentives (10-70 except 42)’.)
- If your country is not listed in Figure 2.27, calculate the average unemployment rate (2010–2019) from the World Bank database.
- By comparing the supply-side labour market variables for your two chosen countries (one from Figure 2.28 and one from the list) and using the information on the unemployment rate from Figure 2.27 or Question 2, draw a WS–PS diagram that illustrates the differences between their labour markets. Explain your answer.
Exercise 2.11 Unemployment, well-being, and social norms
A group of researchers from the Netherlands used subjective well-being data from various European countries to examine how social norms affect the well-being of people who are unemployed (relative to those who are employed). Read the Introduction and Theory sections of their paper, ‘Employment Status and Subjective Well-Being’, then answer the following questions.
- The researchers considered four groups of people: employed, unemployed, non-working disabled, and retired. How might the social norms about working affect the well-being of these individuals?
- The researchers also considered men’s and women’s well-being separately. How might the effects of unemployment on well-being differ by gender?
Table A1 of their paper (pp. 23–25) contains average well-being, by gender and employment status, for all the countries in their dataset. Countries are grouped according to ‘strong’, ‘medium’, and ‘weak’ work ethic.
- Plot a column chart showing the average well-being (the row titled ‘Average’) for men, by employment status (employed, retired, disabled, unemployed) and work ethic (strong, medium, weak). Plot a separate column chart showing this data for women.
- Comment on how well these charts support the hypotheses from Questions 1 and 2 about the relationship between social norms, employment status, and well-being.
