This Selected Issues paper and Statistical Appendix constructs an index of human capital for the Spanish labor force over 1977–97, and projects it over the next decade on the basis of likely demographic developments. The methodology by which the index is constructed considers both educational attainments resulting from formal schooling and improvements in workers’ productivity resulting from experience, or “learning by doing.” The results suggest that the gains from increases in formal schooling can be large, although they are translated into higher economic growth only gradually.

Abstract

This Selected Issues paper and Statistical Appendix constructs an index of human capital for the Spanish labor force over 1977–97, and projects it over the next decade on the basis of likely demographic developments. The methodology by which the index is constructed considers both educational attainments resulting from formal schooling and improvements in workers’ productivity resulting from experience, or “learning by doing.” The results suggest that the gains from increases in formal schooling can be large, although they are translated into higher economic growth only gradually.

II. The Role of Policy Factors in Job Creation in Spain and Other Countries15

A. Introduction

1. Creating more jobs remains the key policy challenge for many European countries, and especially for Spain, where the unemployment rate currently stands at 17 percent. In the context of the current cyclical upswing, Spain’s employment growth has averaged an impressive 3 percent per annum since 1995. However, it is too early to tell the extent to which this performance reflects cyclical developments or structural change, and it will be important to ensure that the employment growth is sustained through the next cyclical downturn. In an effort to gain insight regarding the policies that might foster sustained employment growth, this chapter provides an analysis of job creation over the past two decades (to abstract from cyclical developments) across the OECD countries, with particular emphasis on the differences within Europe. While many studies have attempted to explain why some countries have had higher unemployment rates than others,16 less attention has been devoted to countries’ relative performance in terms of net employment growth.

2. Shifting the focus to job creation has four advantages. First, employment is easier to measure than unemployment, because it does not depend on subtle distinctions between individuals who are in the labor force and those who are not.17 In the specific case of Spain, there is also a debate whether the unemployment statistics are reliable.18 Second, employment, rather than unemployment, is the key variable determining output and financial pressures on the pensions system. Third, the empirical regularities that have been uncovered by previous studies on aggregate unemployment are not necessarily confirmed in the case of job creation. For example, one of the main findings of this chapter is that while employment protection legislation seems to be unrelated to unemployment, it is significantly associated with low job creation. Fourth, a much richer analysis can be conducted by using employment rather than unemployment as the main variable of interest. In particular, data on unemployment do not ascribe workers to a particular sector or type of contract, whereas the composition of employment by sector and by type of contract is available. This information makes it possible to assess the extent to which, for example, relatively low employment growth in Southern European countries such as Spain resulted from a high initial share of agricultural employment; and to address relevant policy questions such as whether the creation of part-time contracts results in higher overall job creation or merely substitutes for full-time contracts. This last issue is of particular relevance in Spain, in light of recent reform efforts in early 1999, aimed at facilitating the creation of part-time jobs.

3. Net job creation has varied considerably among the OECD countries over the past two decades. In particular, some non-European countries, including the United States, Canada, Australia, and New Zealand, have created far more jobs than a majority of the European countries, notably France, Italy, and some of the Nordic countries. Within Europe, the Netherlands and Ireland clearly outperformed other European countries, and were among the fastest job creators in the OECD especially during the 1990s. Spain’s employment growth has been about average within Europe over the past two decades, but a rapid increase in the participation rate has been mirrored in the sharpest increase in the unemployment rate.

4. Drawing on a variety of data sources this chapter considers, for each country, the sectors, age groups, gender, and type of contracts (part-time versus full-time, and temporary versus permanent) that account for employment growth, and analyzes interactions among these dimensions. Using straightforward shift-share analysis, the chapter finds that the fact that certain countries did especially well in a limited number of sectors (for example, the United States in retail trade) or that they had a favorable initial sectoral composition of employment can only account for a small portion of their better employment performance. By contrast, using regression analysis on aggregate employment data, the chapter shows that a policy package consisting of low dismissal costs and low taxation is significantly associated with more rapid job creation. This accounts almost fully for the different performance of the high-performing non-European countries compared with the European countries. However, with this approach it is somewhat more difficult to account for the different performance of countries within Europe. Regarding that issue, the success of the Netherlands is largely accounted for by the remarkable growth of part-time employment in that country. At the same time, more systematic analysis in a panel of European countries reveals that the substitution of part-time for full-time jobs seems to have been considerable.

5. The chapter is structured as follows. Section B ranks the performance of the various OECD countries in terms of aggregate job creation over the past two decades, taking into account their growth of output, capital, and working age population. Section C studies job creation at the sectoral level, using an international data set with information on employment in agriculture, four industrial sectors, and six service sectors. Section D uses regression analysis to examine the relationship between aggregate job creation and institutional variables including taxation, union density, employment protection legislation, and unemployment benefits. Section E considers job creation within Europe, with a view to understanding the role played by part-time (versus full-time) and temporary (versus permanent) contracts, and their interactions with age and gender characteristics as well as economic sectors. It uses panel regressions to estimate the extent to which part-time jobs have crowded out full-time jobs. Section F discusses the policy implications and concludes.

B. Slow and Fast Job Creators

6. The differences among OECD countries in terms of average job creation over the past two decades are remarkable. Table 1 reports average job creation between 1980 and 1997 for 21 OECD economies.19 It shows that some non-European countries, including Australia, the United States, Canada, and New Zealand, clearly outperformed most Continental European countries, with the exception only of the Netherlands. These non-European countries sustained an average job creation of 1½ percent a year in 1980–97, compared with less than ½ percent a year in Continental Europe. In absolute terms, these differences are very large: for a country the size of Spain, for instance, a 1 percentage point difference in employment growth implies a difference of some 130,000 jobs per year, or more than 2½ million jobs over the past two decades.

Table 1.

Slow and Fast Job Creators in the OECD, 1980–97

article image
Sources: OECD; and Fund staff calculations.

Average employment growth (in percent).

Change in employment-working age population ratio (in percentage points). Average 1995–97 minus average 1980–82.

Average growth of employment to output ratio (in percent).

Average growth of employment to capital ratio (in percent); business sector.

7. In order to obtain clues as to whether a given country’s higher employment growth reflects a better functioning labor market or other factors, it is useful to take into consideration the growth in other variables, including working-age population, output, and the capital stock. To that end, Table 1 also presents the cumulative change (in percentage points) in the employment to working-age population ratio between 1980–82 and 1995–97, the average difference between employment growth and output growth over 1980–97, and the average difference between employment growth and the growth rate of the capital stock over 1980–97. The ranking of most countries remains broadly unchanged when using these alternative indicators. Nevertheless, useful information can be gained by focusing on those countries whose ranking changes considerably.

8. A country’s job creation performance will usually be viewed as positive to the extent that it keeps pace with its working-age population growth, and indeed countries with more rapid working-age population typically end up creating more jobs. From that standpoint, the United States’ experience is confirmed as an “employment miracle,” in that many more jobs were created than would have been required to keep pace with the growth of the working-age population. Over the last 20 years, the United States employment to working-age population ratio increased by more than 7 percentage points. The performance of Australia, Canada, Ireland, and New Zealand seems less striking when considering the change in the employment to working-age population ratio rather than the employment growth rate. Undoubtedly, this is partly due to the fact that these countries were able to attract sizable immigration. Nevertheless, the United States’ labor market clearly outranks these other countries in its ability not only to attract immigrants but also to create more jobs than needed for them. At the same time, the job creation record of countries such as the United Kingdom and Belgium seems more positive when taking into account the fact that their working-age population did not grow very rapidly over the period considered.

9. Job creation is intrinsically linked to output growth. In the limit, if the production function was characterized by a technology with fixed coefficients in labor and capital, output growth and job creation would be the mirror image of each other. Although the difference between employment growth and output growth is nothing other than the inverse of productivity growth, it may still provide clues as to the sources of countries’ employment growth. For example, if a given country were to develop a new product or to become more internationally competitive (including for reasons unrelated to its labor market), the demand for its output would increase substantially, and employment would rise in turn to meet that additional demand. In some sense, this may have been the experience of Ireland, which displayed extremely rapid output growth and could perhaps be characterized not as an employment miracle, but rather as an output growth miracle. At the opposite extreme, in countries such as Greece and Sweden slow employment growth may have reflected low output demand, rather than inefficient labor markets.

10. Finally, over periods of several years, countries with favorable labor market institutions and conditions are more likely to meet the demand for additional output by increasing their labor input rather than their capital stock. Considering the difference between the growth of labor and the growth of the capital stock, it seems that a majority of the continental European economies substituted capital for labor to a greater extent than the high-performing non-European economies. Spain displayed one of the largest increases in the capital/labor ratio (by a cumulative 4 percentage points) in 1980–97. Among the non-European economies,20 Canada also increased its capital stock far more rapidly than the number of its employed workers, which suggests that some potential to create jobs was left unexploited.

11. Focusing only on the 1990s, the performance of some European countries becomes even more impressive, particularly that of Ireland, which displayed the highest average rate of job creation (almost 3 percent in 1990–97) among OECD countries, and of the Netherlands (Table 2). For most other countries, however, the ranking based on 1990–97 is similar to that related to 1980–97. Considering an even shorter sample period, some countries’ job creation performance seems to have changed considerably in recent years. In this regard, Spain is particularly striking, having displayed average employment growth of about 3 percent since 1995. However, as noted, it is still early to tell to what extent this merely reflects cyclical factors.

Table 2.

Slow and Fast Job Creators in the OECD, 1990–97

article image
Sources: OECD; and Fund staff calculations.

Average employment growth (in percent).

Change in employment-working age population ratio (in percentage points). Average 1995–97 minus average 1990–92.

Average growth of employment to output ratio (in percent).

Average growth of employment to capital ratio (in percent); business sector.

12. All in all, these considerations tend to confirm that the United States has displayed an employment miracle, and that a majority of European countries have performed rather poorly in terms of job creation. At the same time, there has been a wide range of experiences within Europe. In particular, Ireland and the Netherlands have been very successful in creating jobs. While Ireland’s success seems to be less closely related to its labor market, the case of the Netherlands seems to have greater potential for policy lessons that might be followed by other countries.

C. Do Sectors Matter?

13. Recent studies have suggested that sectoral effects play a large role in explaining cross-country differences in employment growth. Marimon and Zilibotti (1998) have suggested that the initial sectoral composition of employment is an important determinant of overall job creation. This possibility is supported by Table 3, which shows that, in 1982, several slow job creators (including France and Italy, as well as other Southern European economies not included in the OECD ISDB data set, such as Greece, Portugal, and Spain) had a relatively large share of employment in agriculture and industry, that is, sectors that lost ground in most advanced economies (Table 4).21

Table 3.

Distribution of Employment Across Sectors, 1982

article image
Sources: OECD; ISDB dataset; and Fund staff calculations.

Data refer to 1982–90.

Table 4.

Sectoral Contribution to Average Job Creation, 1982–94

article image
Sources: OECD; ISDB data set; and Fund staff calculations.

Data refer to 1982–90.

14. Using a sample of OECD countries, this chapter finds that although sectoral factors are significant, for most countries they explain only a small portion of aggregate job creation and in any case they do not reverse the various countries’ rankings based upon aggregate employment growth. Straightforward shift-share analysis makes it possible to address Marimon and Zilibotti’s (1998) hypothesis and to quantify the effects of the initial sectoral composition of employment on overall job creation. Specifically, this exercise estimates what each country’s overall job creation would have been if its sectoral composition of employment in 1982 had been the same as the average for the countries in the sample. In other words, each country’s employment growth rate in a given sector is weighted by the average employment share of that sector in the whole sample.22

15. The results show that all slow (fast) job creators suffered (benefited) from adverse (positive) initial conditions (Figure 1), but the countries’ ranking remain broadly unchanged (Table 5) and the cross-country variance of job creation under this exercise is only about a fifth smaller than considering actual employment growth. At the same time, initial conditions appear to have played a significant role in some countries (and the Southern European countries in particular, given their large share in agriculture at the beginning of the sample period). For example, taking this exercise at face value, if Italy’s sectoral distribution of employment had been the same as the sample average in 1982, it would have had at least 1,200,000 more jobs in 1998 and its ranking relative to other countries would have been noticeably better (Table 5).23 Using an expanded data set and a slightly different methodology, Marimon and Zilibotti (1994) find a similar result for Spain as well. The extent to which initial conditions represented an advantage or a disadvantage can be assessed through a similar accounting exercise, which estimates what overall job creation would have been in each country if each of its sectors had grown at the same rate as the average for all the countries in the sample (Table 5).

Figure 1:
Figure 1:

Job Creation and Sectoral Differences: 1982-94

Citation: IMF Staff Country Reports 1999, 081; 10.5089/9781451812022.002.A002

Table 5.

Job Creation and Sectoral Characteristics-Shift-Share Analysis

article image
Sources: OECD; ISDB dataset; and Fund staff calculations.

Average change in employment between 1982 and 1994.

Average job creation based on a common initial distribution.

Average job creation based on a common sectoral growth.

Data refer to 1982–90.

16. A related issue focuses on the role of the retail trade sector. Piketty (1998) has argued that higher job creation in the United States than France can largely be attributed to differences between the two countries in employment growth in the retail trade sector. A considerable part of employment growth in some of the fast job creators has indeed taken place in the retail sector, whose average annual contribution to employment growth amounted to one-half of a percentage point over 1983–94 not only in the United States, but also in Australia and Canada (Table 4). A simple way of testing Piketty’s (1998) hypothesis is to compute countries’ average job creation under the extreme assumption that no jobs were created in the retail trade sector. Even under that assumption, the high-performing non-European countries remain the most rapid job creators, and the overall ranking is unchanged (Table 5).

D. The Role of Labor Market Policies and Institutions

17. A more promising avenue for explaining cross-country differences in job creation is to analyze the relationship between overall employment growth and labor market policies and institutions. Obvious candidates include the level of taxation, union coverage and coordination, unemployment benefits, and employment protection legislation.

18. There are good reasons to expect that these policies and institutions will have an impact on employment growth. Taxation has been shown, both theoretically and empirically, to be linked with unemployment (Daveri and Tabellini, 1997). Policy makers often accept this principle as well. For example, one of the objectives of the 1998 reform of personal income taxes in Spain was to promote job creation by lowering the tax burden. Union participation (and the ensuing heightened wage pressure) and unemployment benefits have been shown to affect equilibrium unemployment (Nickell and Layard, 1998). Empirically, union density appears to increase unemployment, though this effect seems to be mitigated when unions and firms coordinate their bargaining activity. Replacement rates and duration of benefits have also been found to be positively correlated with unemployment.

19. It also seems reasonable to analyze the role of employment protection legislation, although the a-priori case on the effects of this variable is less clear-cut. This variable is particularly relevant in the case of Spain, which (together with Italy) has the highest dismissal costs in the OECD.24 Most theoretical studies predict that dismissal costs should not affect unemployment: since employment protection legislation increases the cost of labor adjustment, the argument goes, both job creation and destruction will be lower, but the effect on average employment will be ambiguous (Bentolila and Bertola, 1990). Consistent with that view, employment protection legislation does not appear to be significant in cross-country regressions that analyze the determinants of unemployment rates. However, Caballero and Hammour (1998) have recently argued that increases in dismissal costs lead entrepreneurs to substitute capital for labor in the medium run. In addition, empirical studies that exploit the time-series information in the data have found a positive relationship between dismissal costs and unemployment (Scarpetta, 1996 and Lazear, 1990).

20. Several empirical relationships identified by existing studies on unemployment are confirmed by the matrix of bivariate correlations between average job creation in 1980–97 and a number of indicators of labor market policies for a sample of 21 OECD countries (Table 6).25 As expected, job creation is negatively correlated with total taxation and union density, and the close link between working-age population growth and job creation is also strongly confirmed. By contrast, the relationship between unemployment benefits and job creation is not statistically significant. More interesting, a negative and significant correlation is found between job creation and a measure of employment protection legislation.26 Figure 2 shows that these bivariate relationships are not driven by any obvious outliers.

Table 6.

Job Creation and Policy Variables: Correlation Matrix

article image
Sources: OECD; and Fund staff calculations.Note: p-values in bold.

JC is average job creation; ΔΠ is average change in inflation; EPL is the index of employment protection legislation; taxes is total taxation as a share of GDP; payroll is payroll taxes as a share of GDP; benefit is unemployment benefits; coord is the index of employer-employee coordination; and wkage is the growth of working age population.

Figure 2:
Figure 2:

Job creation, population growth and institutional variables

Citation: IMF Staff Country Reports 1999, 081; 10.5089/9781451812022.002.A002

21. The robustness of these cross-sectional relationships is confirmed by running a battery of cross-sectional regressions, in the spirit of the extreme bound analysis previously used in cross-country regressions on the determinants of output growth (Levine and Renelt, 1992). First, job creation is regressed against the growth in the working age population, a constant, the variable of interest, and each of the other explanatory variables in turn. Second, the same procedure is repeated using each possible pair of the other explanatory variables. The most robust relationship is found to be that between employment protection legislation (EPL) and job creation: the coefficient on EPL is statistically significant in 24 out of 27 regressions, and it always has a negative sign (Table 7). The estimated value of the coefficient is also very stable. The relationship between job creation and total taxation is also fairly robust, with the coefficient significant in 13 out of 27 regressions. The other relationships are not robust to the inclusion of additional regressors.

Table 7.

Job Creation and Policy Variables: Robustness Checks

article image
Source: OECD; and Fund staff calculations.Note: The left-hand side variable is average job creation for 1980–97. All regressions include a constant and the growth of working age population.

Min (max) is the minimum (maximum) value of the coefficients in the regression.

Number of regressions whose coefficient has a p-value less than 10 percent.

Total number of regressors in each regression.

EPL is the index of employment protection legislation; tot tax is total taxation as a share of GDP; payroll is payroll taxes as a share of GDP; coord is the index of employer-employee coordination; union is the proportion of workers that belong to a trade union; and benefit is unemployment benefits.

22. Small panel regressions are then run relating average job creation to the various institutional measures as well as working-age population growth.27 The average change in inflation is included as an additional explanatory variable, to proxy for business cycle and macroeconomic policy stance effects. Six year (1980–85, 1986–91 and 1992–97) averages are used as the basic data points to smooth out business cycle and other temporary effects. Unfortunately, some of the independent variables, and the measure of EPL in particular, are time invariant owing to data limitations.28 With 21 countries, the total number of observations is 63. The estimation is based on the random effects generalized least square procedure, which is essentially ordinary least squares corrected for the fact that three successive observations for each country cannot be treated as independent random draws.

23. The coefficients on EPL and taxation are significant (Table 8), in both an economic and a statistical sense, and are quantitatively similar to those obtained in the cross-sectional regressions; they are also fairly stable across different panel specifications.29 The coefficient on EPL, however, is marginally less significant in the panel regressions than in the cross sectional regressions, owing in part to the fact that the EPL variable is time invariant. The results suggest that an improvement in the EPL ranking by five positions is associated with an increase in average job creation by 0.1–0.2 percentage point. (Average annual employment growth amounts to 0.6 percent in the sample.) For a country like Spain, this would imply some 15,000–30,000 new jobs per year, or some 300,000–600,000 jobs over 20 years. A reduction in total taxation by 1 percentage point of GDP increases average job creation by some 0.05 percentage point.

Table 8.

Panel Regressions: Institutions and Job Creation

Dependent Variable: Average Job Creation Random Effects GLS regressions 1/

Six year averages: 1980–85; 1986–91; 1992–97

article image
Sources: OECD data; and Fund staff calculations.

z statistics reported below coefficients.

Time dummy for 1986–91 and 1992–97.

Hausman specification test for random effects models. EPL is the index of employment protection legislation; ΔΠ is average change in inflation;

24. This chapter’s result that EPL is negatively associated with job creation seems to be consistent with the hypothesis proposed by Caballero and Hammour (1998). In principle, the result could also be consistent with the traditional view if the 1980–97 period could be seen as a cyclical upswing. In fact, under the traditional view, high job security provisions dampen the fluctuations of employment around its long run average level, and in an upswing the employment increase would tend to be higher in countries with high dismissal costs (e.g., those in continental Europe) than in those with low dismissal costs (e.g., the United States). However, 18 years seem to represent an excessively long horizon to be qualified as a cyclical development.

25. Overall, these small panel regressions fit the data relatively well: the estimated and the actual value of average job creation in the sample of 21 countries, as well as their actual and fitted ranking are fairly similar (Figure 3).30 In particular, the estimated equations account very well for the job creation of the fastest creators, including Australia, Canada, and the United States. However, the fit is somewhat less satisfactory in the case of the European countries. This suggests that further exploration is needed to explain the heterogeneous job creation performance within Europe.

Figure 3:
Figure 3:

Actual and Estimated Job Creation: 1980-97

Citation: IMF Staff Country Reports 1999, 081; 10.5089/9781451812022.002.A002

E. Inside Europe

26. Section D has shown that differences in tax pressure and firing costs may provide a partial explanation for the differences in job creation performance across the OECD countries, most notably between the high-performing non-European countries and the countries of Continental Europe. However, a considerable part of the wide variation in performance among the Continental European countries remains unexplained. This section accounts for differences among the Continental European countries with respect to the composition of job creation by type of contract (part-time or full-time, and temporary or permanent), the broad economic sector in which jobs are created, as well as the age and gender characteristics of the people who fill the new positions. The key finding is that the best European performer, the Netherlands, stands out in that about half of its job creation can be accounted for by part-time jobs taken up by females aged 25–49, typically in the service sector (Figures 4 and 5).

Figure 4:
Figure 4:

Part-Time/Full-Time, Gender and Age: 1982-94

Citation: IMF Staff Country Reports 1999, 081; 10.5089/9781451812022.002.A002

Figure 5:
Figure 5:

Part-Time/Full-Time, Gender and Sector: 1982-94

Citation: IMF Staff Country Reports 1999, 081; 10.5089/9781451812022.002.A002

27. The composition of job creation seems largely to reflect developments in technology or labor supply. In virtually all European Union countries, employment growth was much faster for females than males, mirroring higher growth in labor force participation among women. Developments in youth employment seem to have been determined mostly by changes in schooling age, with declines in youth employment in most countries, but especially in those where the average schooling age rose rapidly, most notably in Portugal. Of course, labor market institutions have also played a role: for example, high firing costs may have made it especially difficult for the young to find employment, as reflected in the large increase in youth unemployment in continental Europe. While job creation among those aged 25–49 was positive in all countries in the sample, job creation performance among those aged 50–64 was more mixed, reflecting in part the tendency toward early retirement in a number of countries. By broad economic sector (also documented in Section C), most countries have experienced net job creation in services and net job destruction in agriculture. The agricultural sector’s negative contribution to overall employment growth has been largest in Italy, Portugal, and Spain, the countries that started off with the highest shares of employment in agriculture sectors at the beginning of the sample. At the same time, Figure 5 confirms that this factor accounts only for a small portion of cross-country differences in overall job creation. These sectoral developments have interacted in an interesting manner with age and gender, notably in the case of rapid employment growth among females aged 25–49 in the service sector.

28. There were also substantial differences among the various European countries with respect to the type of contracts that accounted for job creation. Regarding part-time contracts, the Netherlands clearly stands out, in that half of overall employment creation over the past two decades was accounted for by part-time contracts. The reforms undertaken by the Netherlands in the early 1980s (which, interestingly, were not specifically aimed at promoting part-time contracts) seem to have succeeded in raising overall employment through a sharp increase in part-time employment. In the remaining ten countries for which data are available, the share of part-time jobs increased much more slowly than in the Netherlands, and overall employment growth was also lower (Figure 6).

Figure 6:
Figure 6:

Change in Part-Time Shares and Job Creation: 1985-97

Citation: IMF Staff Country Reports 1999, 081; 10.5089/9781451812022.002.A002

29. The extent to which increases in part-time jobs have been associated with reductions in full-time jobs can be estimated more precisely through panel regressions, which focus on the time-series information in the data. A simple approach is to use part-time and total employment in a particular country in a given year as the basic observations. With 11 countries and the sample period 1984–97, there are 124 observations (allowing for missing values). Overall employment growth is regressed on the increase in the share of part-time jobs in total employment, as well as 10 country dummies and 13 year dummies. The question being addressed is the following: over the sample considered, when 100 part-time jobs were created, what was the total employment creation associated with that increase? Three possible benchmarks seem particularly interesting. First, overall employment also rose by 100 jobs, i.e., there was no crowding out at all of full-time jobs. In that case, the coefficient on the increase in the share of part-time jobs would be 1. Second, there was no net gain or loss of hours worked, that is—given that the average weekly hours of part-time jobs are about half of those of full-time jobs—overall employment rose by 50 jobs. (If two part-time workers could indeed substitute for one full-time worker with no net change in total hours, there would seem to be no fixed costs associated with individual workers.) In that case, the coefficient on the increase in the share of part-time jobs would be 0.5. Third, there was complete crowding out of full-time jobs, i.e., overall employment remained unchanged. In that case, the coefficient on the increase in the share of part-time jobs would be 0.

30. Estimation of the regression described above yields a point estimate of about 0.3, but with a rather high standard error—also 0.3 (Table 9). Nevertheless, it is possible to reject the hull of no crowding out (i.e., that the slope equals 1). Therefore, this approach suggests that increases in part-time employment have typically been associated with some crowding out of full-time jobs, although the exact extent of that crowding out is not estimated very precisely. Robustness tests also suggest that the coefficient is somewhat sensitive to excluding individual years or countries, or to changes in specification of the regression.

Table 9.

Part-time and Aggregate Job Creation, 1984–97

article image
Sources: Eurostat data; and Fund staff calculations.Note: Numbers in italics are p-values of the corresponding null hypothesis.

31. A more detailed approach is to use data on country/sectors (e.g., industry in Spain) as the basic units of analysis. This provides a richer data set, with 3 broad economic sectors for each of the 11 countries, over 1984–97, yielding almost 400 observations. In that case, it is possible to estimate the relationship between increases in the ratio of part-time jobs in a given sector to total employment in the country and the contribution of that sector to overall job creation in the country. In estimating the relationship, both a priori reasons and inspection of the data suggest that it is important to permit the slope coefficient to vary among the three sectors. In fact, the extent to which part-time jobs may substitute for full-time jobs may depend on technological considerations: for example, firm-specific knowledge might be more important in some sectors than others. Moreover, the estimated slope coefficients vary considerably among the three sectors, though formal testing rejects the null hypothesis of slope homogeneity only at the 15 percent level. In agriculture, by far the smallest sector, the point estimate of the slope coefficient amounts to 1, and is significantly different from zero, though not significantly from 0.5. In industry, the point estimate equals 0.4, but is not estimated very precisely. In services, the largest sector, the point estimate is 0.4 and is estimated more precisely, so that it turns out to be significantly different from both 0 and 1. These results suggest that in the services sector increases in part-time employment have been associated with increases in the overall number of jobs but also with partial crowding out of full-time jobs. At the same time, it is not possible to reject formally the null hypothesis that there has been no net change in the number of hours. Again, robustness tests suggest that the coefficient estimates are somewhat sensitive to specification changes and the removal of individual countries or individual years. Overall, it seems clear that β=1 can be rejected, and that β is most likely around 0.5. This suggests that the substitution of part-time jobs for full-time jobs has been only partial, although considerable.

32. Turning to the case of temporary contracts, Spain is the country that stands out over the past two decades, in that its net job creation was entirely accounted for by temporary contracts (Figure 7).31 The reforms of the early 1980s in Spain, which introduced temporary contracts against the background of extremely high dismissal costs, appear to have merely raised the share of temporary employment without affecting overall employment.32 As a result, Spain’s share of temporary employment currently stands at one third, by far the highest in the OECD. Spain has also had (together with Italy) the highest dismissal costs in the OECD. The empirical relationship between high dismissal costs and a higher share of temporary employment or a greater increase in the share of temporary employment is not robust when Spain is excluded from the sample.

Figure 7:
Figure 7:

Temporary/Permanent Employees.

Citation: IMF Staff Country Reports 1999, 081; 10.5089/9781451812022.002.A002

33. All in all, although the systematic cross-country evidence is somewhat mixed, the success of the Netherlands with part-time contracts and the complete substitution of temporary contracts for permanent contracts observed in Spain suggest that part-time contracts may be a more promising avenue of job creation than temporary contracts.

34. There is also considerable evidence that workers tend to be happier with part time contracts than with temporary contracts. About 58 percent of the workers under part time contracts in the European Union in 1997 declared that they did not want a full time job instead, and only 20 percent stated that they would have preferred a full time job if they had been able to find it.33 In the Netherlands, 72 percent of workers under part-time contracts in 1997 declared that they did not want a full time job instead, and only 6 percent stated that they would have preferred a full time job if they had been able to find it.34 By contrast, 7 percent of workers with temporary contracts in the European Union in 1997 declared that they did not want a permanent job instead, and 40 percent stated that they would have preferred a permanent contract if they had been able to find one.35 The proportion of workers with temporary contracts because they could not find permanent jobs amounted to 87 percent in the case of Spain, where the share who did not want permanent jobs was negligible. Unfortunately, a corresponding survey of entrepreneurs is not available, and it seems likely that entrepreneurs would give a more positive view of temporary contracts, although entrepreneurs (notably, in Spain) often state that they also appreciate job stability, because it facilitates the acquisition of firm-specific skills by workers.

F. Concluding Remarks

35. Drawing on a variety of data sources, this chapter has analyzed in a systematic way the job creation performance of 21 OECD economies between 1980 and 1997, focusing on the role of age and gender characteristics, economic sectors, institutions, and types of contract, in the job generation process. There are four main findings. First, the experience of the United States is confirmed as an “employment miracle,” taking into account the growth rate of population, output, and capital. At the same time, although most continental European countries created far fewer jobs than the United States, the case of the Netherlands demonstrates that good job creation performance is possible also in Europe. Second, the fact that certain countries did especially well in a limited number of sectors or that they had a favorable initial sectoral composition of employment can only account for a small portion of the cross-country differences in job creation. In particular, relatively slow employment growth in Southern European countries including Spain over the past two decades can only partially be attributed to their large initial share in agriculture. Third, certain labor market policies and institutions (in particular, a flexible employment protection legislation and a low tax burden) are significantly associated with rapid employment growth, and account for most of the cross-country differences, notably between the high-performing non-European countries and Continental Europe. Fourth, within Europe, the success of the Netherlands is largely accounted for by the creation of part-time jobs for women aged 25–49 in the service sector, which followed the reforms of the early 1980s in that country. Considering also the other European countries in which part-time employment did not rise as rapidly, systematic analysis suggests that substitution of part-time jobs for full-time jobs, while considerable, is only partial. Turning to temporary contracts, the experience of Spain beginning in the mid-1980s suggests that temporary jobs seem to have merely substituted for permanent jobs, a process that may have been exacerbated by Spain’s high dismissal costs.

36. The set of empirical regularities outlined above suggests a number of policy considerations. Although the direction of causality between institutions and labor market outcomes remains to be analyzed, the results are consistent with the view that a policy package including low dismissal costs and a moderate tax burden might foster higher employment growth. Spain’s efforts to reduce the tax burden and dismissal costs go in that direction, though more forceful steps would be desirable.

37. With respect to the role of contracts, Spain’s efforts toward the elimination of remaining obstacles to the use of part-time contracts are also welcome. These contracts have proved to be a popular vehicle to increase female labor force participation (which is still relatively low in Spain) and may help raise overall employment as well.

APPENDIX I Shift-Share Analysis

In what follows, countries are indicated with i=1…‥I, sectors with j=1…‥K, and years with t = 0……T. In this section, I=11, K=11 and t = 0 refers to 1982. Average job creation in country i, git can then be written as

git=Σj=1K(NijtNij0)(T1)Σj=1kNij0

where Nijt is employment in sector j, country i and time t. The contribution to average growth of sector j in country i will be

gijtc=(NijtNij0)(T1)Σj=1kNij0

It follows that the gijtc can be expressed as the product of the growth rate of sector i weighted by its weight in the initial distribution of employment:

gijtc=gijtwi0

where gijt is average job creation in sector i and wij0=Nij0Σj=1kNij0 is the share of sector j in total employment.

The first quantitative exercise carried out in Section C measures average job creation by weighing gijt by the average employment share across countries. More specifically, we indicate with g˜it how a country would have grown if its initial employment share had been the same as the average in the sample:

g˜it=Σj=1kgijw¯j0

where wj0 is the share of sector j in the average country in the sample, and its expression reads

w¯j0=Σi=1INij0Σi=1IΣj=1KNij0

The second accounting exercise carried out in Table 5 measures job creation in each country under the assumption that each sectors had grown uniformly across countries. Defining with prime g˜it ‘ this new measure, its expression reads

g˜it=Σj=1kg¯itwj0

where

g¯ij=Σi=1INjitΣi=1INij0Σi=1INij0

is average job creation in sector j.

APPENDIX II Data Sources And Definition Of The Variables

Section B uses data from the OECD analytical database and the Business Sector Database.

Job creation is simply measured as the average growth in total civilian employment.

Working age population is the number of people between the age of 15 and 64.

Change in the Labor-Capital Ratio is measured from the business sector data set.

Section C uses the ISDB 97, International Sectoral Data Base 97. The ISDB combines a range of data series related primarily to industrial output and primary factor inputs used in 15 OECD member countries. For limited data coverage Finland, Germany (including East Germany), Korea and the United Kingdom are excluded from the sample. The variable used in this chapter is total employment.

The sectoral classification of different countries is not identical. In particular, the International Standard Industrial Classification (ISIC) differs from the General Industrial Classification of all Economic Activities in the European Communities (NACE), which in turn differs from the baseline (ISDB) classification. In order to obtain the cross-country/cross-sector distribution proposed in Section C, the following adjustments were made:

In countries that follow the NACE classification (West Germany, Belgium, and Italy), the subsector Real Estate and Business Sector (RES) which belongs to the sector Financial, Insurance and Real Estate Business (FNI) was included in the sector Other Producer (OPR). Thus, in order to estimate employment in subsector RES for the missing countries, the average proportion of RES within FNI in the other countries is used, and is subtracted from OPR.

Further adjustments had to be made to address country-specific data limitations. In the case of Japan, the subsector HOT (Hotels and Restaurants) was included in the sector SOC (Community Social and Personal Services). In the case of France, PGS (Producer of Government Service) was included in OPR. In both cases, the share was computed as the average in the sample.

Section D uses aggregate data from the following sources:

Average change in inflation is the average change in consumer price inflation (in percentage points) between 1980 and 1997. Data are drawn from the International Financial Statistics of the IMF.

Employment Protection Legislation represents a country’s ranking of overall strictness of protection against dismissals. It is an average ranking of four different subindices related to period 1985–93: Maximum Pay and Notice Period, Strictness of Protection Against Regular and Fixed-Term Contracts, Index of Obstacles to dismissals and the Ranking proposed by Bertola (1990). The index appeared in the OECD Jobs Study (1994) and was compiled by Grubb and Wells (1993).

Overall taxes and payroll taxes are measured as average total taxation and average payroll taxes, respectively, as a share of GDP. The data are drawn from the OECD Revenue Statistics.

Union density measures the proportion of workers that belong to a trade union. Data refer to 1980, 1990 and 1994 and were compiled by the OECD (1997).

Union coordination is an index that measures the extent to which both employers and employees across the economy coordinate in the bargaining process. The index takes values between 1 and 3 and is available for 1980, 1990 and 1994. In was compiled by OECD (1997).

Unemployment benefits measures the average net replacement ratio for an unemployed worker. Information refers to 1981 and 1991 and the data are drawn from the OECD Jobs Study.

Section E uses data from Eurostat’s Labour Force Survey.

References

  • Bentolila, S. and G. Bertola, 1990, “How Bad is Eurosclerosis,” Review of Economic Studies 57, 381402.

  • Bentolila, S. and J. Dolado, 1994, “Labour Flexibility and Wages: Lessons from Spain,” Economic Policy, April 1994, 5399.

  • Bertola, G., 1990, “Job Security, Employment and Wages,” European Economic Review, Vol. 34, 85186.

  • Bertola, G. and A. Ichino, 1995, “Wage Inequality and Unemployment: United States vs. Europe,” NBER Macroeconomic Annual, ed. by B. Bernanke and J. Rotemberg.

    • Search Google Scholar
    • Export Citation
  • Bertola, G. and R. Rogerson, 1997, “Institutions and Labor Reallocation,” European Economic Review, Vol. 41, 114771.

  • Bertola, G., 1998, “Microeconomic Perspective in Aggregate Labor Markets” forthcoming in Handbook of Labor Economics.

  • Bell, B. and S. Nickell, 1997, “Would Cutting Payroll Taxes on the Unskilled Have a Significant Impact on Unemployment?”, ed. by D.J. Snower and G. de la Dehesa, Unemployment Policy: Government Options for the Labour Market, (Cambridge, Massachusetts: University Press).

    • Search Google Scholar
    • Export Citation
  • Bean, C., 1994, “European Unemployment,” Journal of Economic Literature.

  • Blanchard, O., 1997, “The Medium Run,” Brookings Papers on Economic Activity: 2,” 89141.

  • Blanchard, O., 1998, “Employment Protection and Unemployment,” mimeo, Massachusetts Institute of Technology.

  • Blanchard, O. and P. Portugal, 1998, “What Hides Behind the Unemployment Rate?”, NBER Working Paper No. 6636.

  • Boeri, T., 1999, “Enforcement of Employment Security Regulations, On-the-Job Search and Unemployment Duration,” European Economic Review, Vol. 43, No. 1.

    • Search Google Scholar
    • Export Citation
  • Caballero, R. and Hammour, 1998, “Jobless Growth: Appropriability, Factor Substitution and Unemployment,” Carnegie Rochester Conference Series on Public Policy, Vol. 48, 5199.

    • Search Google Scholar
    • Export Citation
  • Daveri, F., and G. Tabellini, 1997, “Unemployment, Growth and Taxation in Industrial Countries,” mimeo, Bocconi University.

  • Davis, S., 1992, “Cross-Country Patterns of Changes in Relative Prices,” NBER Macroeconomic Annual.

  • Davis, J., and J. Haltiwanger, 1998Gross Job Flows,” Handbook of Labor Economics, Volumes 3 and 4, ed. by Orley Ashenfelter and David Card. North Holland, Amsterdam.

    • Search Google Scholar
    • Export Citation
  • Farber, H.S., 1986, “The analysis of union behavior,” ed. by O. Ashenfelter and R. Layard, Handbook of Labor Economics, Vol. II, North Holland, Amsterdam.

    • Search Google Scholar
    • Export Citation
  • Freeman, R. and L. Katz, 1995, “Differences and Changes in Wage Structure,” (Chicago, Illinois: Chicago University Press).

  • Garibaldi, P., 1998, “Job Flow Dynamics and Firing restrictions,” European Economic Review, Vol. 42, No. 2, 245275.

  • Garibaldi, P., J. Konings, and C. Pissarides, 1997, “Gross Job Reallocation and Labour Market Policy,” ed. by D.J. Snower and G. de la Dehesa, Unemployment Policy: Government Options for the Labour Market (Cambridge, Massachusetts: Cambridge University Press).

    • Search Google Scholar
    • Export Citation
  • Grubb, D. and W. Wells, 1993, “Employment Regulation and Patterns of Work in E.C. Countries,” OECD Economic Studies, 21, 758.

  • Krueger, A. and J. Pishcke, 1997, “Observations and Conjectures on the U.S. Employment Miracle,” NBER Working Paper no. 6146.

  • Levine, R. and D. Renelt, 1992, “A Sensitivity Analysis of Cross-Country Growth Regressions,” American Economic Review.

  • Lazear, E., 1990, “Job Security Provisions and Employment,” Quarterly Journal of Economics, Vol. 105, 699726.

  • Marimon, M. and Zilibotti, 1998, “Actual versus virtual employment in Europe: Is Spain different?”, European Economic Review, Vol. 42, No. 1.

    • Search Google Scholar
    • Export Citation
  • Mortensen, D. and C. Pissarides, 1998a, “New Developments in Models of Search in the Labor Market,” forthcoming in Handbook of Labor Economics, North Holland, Amsterdam.

    • Search Google Scholar
    • Export Citation
  • Mortensen, D. and C. Pissarides, 1998b, “Job Reallocation, Employment Fluctuations and Unemployment,” forthcoming in Handbook of Macroeconomics, North Holland, Amsterdam.

    • Search Google Scholar
    • Export Citation
  • Nickell, S., 1997, “Unemployment and Labor Market Rigidities: Europe versus North America,” Journal of Economic Perspectives, Vol. 11, No. 3, pp. 5574.

    • Search Google Scholar
    • Export Citation
  • Nickell, S. and R. Layard, 1998, “Labour Market Institutions and Economic Performance,” forthcoming in Handbook of Labor Economics, North Holland, Amsterdam.

    • Search Google Scholar
    • Export Citation
  • OECD, 1994, “The Jobs Study”.

  • OECD, 1997, “Employment Outlook”.

  • Pissarides, C.A., 1998, “The Impact of Employment Tax Cuts on Unemployment and Wages; The Role of Unemployment Benefits and Tax Structure, European Economic Review, Vol. 42, No. 1, 15583.

    • Search Google Scholar
    • Export Citation
  • Piketty, T., 1998, “Les creations d’emploi en France et aux Etas-Unis: Service de proximite contre petits boulots,” Note de la Fondation Saint-Simon, No. 93.

    • Search Google Scholar
    • Export Citation
  • Scarpetta, S., 1996, “Assessing the Role of Labour Market Policy and Institutional Settings on Unemployment: A Cross-country study,” OECD Economic Studies.

    • Search Google Scholar
    • Export Citation
15

Prepared by Pietro Garibaldi and Paolo Mauro.

16

Recent cross-country studies on the sources of unemployment include Nickell (1997), Scarpetta (1996), and Nickell and Layard (1998) on the empirical side; and Bertola (1998) and Mortensen and Pissarides (1998a,b) on the theoretical side.

17

As is well known, individuals who are not working are recorded as part of the labor force (and therefore as unemployed) only if they are actively looking for a job. However, especially in high unemployment countries such as those of Continental Europe, the low likelihood of finding a job may imply that many people will have stopped actively searching for one (the “discouraged worker” phenomenon); conversely, many people may declare that they are actively searching for a job when in fact their search effort is minimal.

18

See SM/97/76.

19

A sample period spanning almost two decades ensures that cyclical effects will not distort cross-country comparisons.

20

Blanchard (1997) and Caballero and Hammour (1998) have recently argued that heightened demands by the trade unions beginning in the late 1970s led to considerable substitution of capital for labor in Europe.

21

This section analyzes the OECD ISDB data set, which consists of employment data for 11 economic sectors in 11 countries between 1982 and 1994. Although the country coverage is more limited than in Section B, the sample includes rapid job creators both among the high-performing non-European countries (Australia, Canada, and the United States) and in Continental Europe (the Netherlands), as well as the slowest job creators in Europe (such as Italy, France, and Sweden).

22

Appendix I reports the simple formulas used for the accounting exercises carried out in this section.

23

As usual, shift-share analysis needs to be interpreted with caution. In particular, it is not clear which sectors would have been the most successful if their initial geographical distribution had been different.

24

The reform of May 1997 introduced a new type of permanent contract (accessible only to certain groups of workers) with lower dismissal costs, but still above the already high EU average. However, since dismissal costs for existing contracts were not changed, it will take a number of years for average dismissal costs to fall significantly. See SM/98/61.

25

See Appendix II for data sources and variable definitions.

26

Spain is considered to have the second strictest employment protection legislation, following Italy.

27

The methodology is similar to that recently applied by Nickell (1998) and Layard and Nickell (1998) in their studies on unemployment differences across countries. Scarpetta (1996) runs similar regressions on small panel data sets, but adopts a more structural approach.

28

The OECD is currently in the process of updating the EPL ranking used in the present chapter. The new measures, which are not officially available yet, display some variation over time, reflecting reform efforts in some countries, including Spain. Preliminary regressions with the new measure show that the results are very similar to those reported in this section.

29

The only exception is specification 5 in Table 8, which includes payroll taxes instead of total taxes.

30

The fitted values in Figure 3 are based upon the specification in the second column of Table 8.

31

Owing to data limitations, Figure 7 relates to the number of employees, rather than total employment (i.e., it excludes the self-employed). The contribution to employment growth of the self-employed was very low in countries such as Spain and high in countries such as the Netherlands. This may reflect higher social security contributions in Spain than in the Netherlands.

32

Bentolila and Dolado (1994) provide further detail on the impact of the reforms of the early 1980s in Spain.

33

Another 12 percent were in school or suffered from illness, and the remaining 10 percent did not give a reason for having a part-time job.

34

The remaining 21 percent were in school or suffered from illness.

35

Another 29 percent did not give a reason for having a temporary job; and 24 percent were under training contracts or in a probationary period.

Spain: Selected Issues and Statistical Appendix
Author: International Monetary Fund