Youth Unemployment and the Impact of Financial Crises

Transcription

1 Youth Unemployment and the Impact of Financial Crises M.T. Choudhry, E. Marelli ** and M. Signorelli *** Structured Abstract Purpose of this paper The purpose of this paper is to assess the impact of financial crises on the youth unemployment rate. We consider different types of financial crises (systemic banking crises, non-systemic banking crises, currency crises and debt crises) and different groups of countries, according to their income level. Design/methodology/approach After a review of the existing (theoretical and empirical) literature on the determinants of the youth unemployment rate in general and at the occurrence of economic crises, we present empirical estimations on the impact of past financial crises on young workers. We investigate the relationship between financial crises and youth unemployment rate (YUR) by employing fixed effects panel estimation on a large panel of countries (about 70) around the world for the period The "persistence" over time of the impact is also investigated. Finally we estimate the Arellano-Bond dynamic panel, confirming the significance of the results. Findings According to our empirical estimates, two key results are relevant: (i) financial crises have an impact on the YUR that goes beyond the impact resulting from GDP changes; (ii) the effect on the YUR is greater than the effect on overall unemployment. The inclusion of many control variables including in particular GDP growth does not change the sign and significance of the key explanatory variable. Our results suggest that financial crises affect the YUR for five years after the onset of the crises; however the most adverse effects are found in the second and third year after the financial crisis. Research limitations/implications (if applicable) Although we are fully aware of the peculiarities of the last crisis, we believe that our econometric results facilitate a better understanding of the impact of the financial crisis on the youth labour market. Practical implications (if applicable) The main policy implication is that effective ALM (active labour market) policies and better STWT (schoolto-work transition) institutions are particularly needed to reduce the risk of persistence and structural (longterm) unemployment, since young people have been worst affected by the last crisis. What is original/value of paper There are many studies on the characteristics and causes of youth unemployment; considerable research has also been carried out into the labour market impact of financial crises. This paper brings the two strands of literature together, by econometrically investigating the impact of financial crises on YUR. Keywords financial crises, labour impact of economic crises, youth unemployment, panel fixed effects, Arellano-Bond estimates. University of Groningen, Faculty of Economics and Business, The Netherlands; P.O. Box 800, 9700 AV, Groningen, The Netherlands; m.t.choudhry@rug.nl. ** University of Brescia, Full Professor of Economic Policy, Faculty of Economics, Italy; Department of Economics, via San Faustino 74/B, Brescia (Italy); emarelli@eco.unibs.it *** President of the European Association for Comparative Economic Studies (EACES), University of Perugia, Associate Professor of Economic Policy, Faculty of Political Sciences, Italy; Department of Economics, Finance and Statistics, via A. Pascoli, 20, Perugia (Italy); signorel@unipg.it Earlier versions of this paper were presented at the 11th bi-annual EACES Conference (University of Tartu, Estonia, August 26-28, 2010) and at the XXV AIEL Conference (University of Chieti-Pescara, September 9-10, 2010). We thank participants in the above conferences for several useful comments. 1

2 1. Introduction The integration of young people into the labour market is an important objective all over the world and, in particular, it is a key policy issue of the European Employment Strategy. In fact, the European Employment Guidelines stress the need to build employment pathways for young people and to reduce youth unemployment; also the new Europe 2020 plan pays attention to youth labour and education problems, aiming in particular at an increase of human capital. 1 Note that, in Europe, youth unemployment rates are generally more than twice as high as the adult rates, with significant differences across countries and regions 2. Youth unemployment dramatically rose again after the recent global economic crisis. 3 The crisis, which started in as a financial crisis, led to the biggest recession ( ) since the Great Depression of the 30s, with widespread consequences on economic performance, labour productivity and employment in all countries around the world. Note that the real effects of financial crises (on production, income, expenditure, etc.) are always lagged. Considering the labour market consequences of the crisis, the problem is that despite a recovery which has been ongoing (although weak and uncertain) since the Summer of 2009 all the negative effects have not yet been fully revealed, because of even longer lags. The impact has been deeper on the weakest segments of the labour market, especially young people. Can we learn something from past financial crises? The key contribution of this study is the assessment of the impact of past ( ) financial crises on the youth unemployment rate. Of course, we are aware of the peculiarities of the last crisis especially its global nature compared to previous financial crises, concerning in most cases individual countries or specific groups of countries. Nevertheless, we think that some inferences can also be made with respect to the effects of the last crisis 4 and the most appropriate policies to be adopted. We re-estimated our model for sub-samples of high income OECD countries and other economies in the sample. The gender-specific effect of crises on young workers is also investigated. Finally the "persistence" of the impact of financial crises on youth unemployment is also investigated. The structure of the paper is the following. In Section 2, after some empirical evidence on youth unemployment, there is a brief review of the general determinants of youth unemployment and its sensitivity to economic crises, in particular financial crises. Section 3 presents our econometric investigations into the impact of past financial crises on the youth unemployment rate. Section 4 concludes. 2. The youth unemployment problem: empirical evidence and key interpretations 2.1 Empirical evidence on youth unemployment As regards youth labour market analysis, we specify at the outset that, although official statistics tend to focus on the age group, there is considerable debate about the pros and cons of various definitions of youth and their consequences in the study of labour market performance and dynamics 5. In many countries of the world, youth unemployment is much higher than adult unemployment. For the world as a whole, the corresponding figures for the 2010 YUR (youth unemployment rate) are 13.1% vs. 4.8% for adults (see IL0, 2010b). While the lowest values can be found in the Far East, the highest figures apart from North Africa and the Middle East are recorded in Central-South-Eastern Europe & CIS (20.2% vs. 8.2%) and in Developed Economies and the EU (19.1% vs. 7.4%). If we focus our attention on the EU, which is one of the most affected areas in the world, we can analyse the recent evolution of the YUR (for young people in the age group) and disentangle the peculiarities of individual countries. According to Eurostat data, for the EU-27 aggregate over the period (see Table A1 in the appendix), we can see that there was a steady situation until 2005, then an improvement in prior to the global crisis and finally a jump in 2009 to the highest level of the whole decade (19.6%); see also Figure A1 in the appendix. Higher than average figures are shown by different groups of countries: (i) some Mediterranean countries (Spain, Italy, Greece) plus France and Belgium; (ii) many Nordic countries (Sweden, Finland, the Baltic states); (iii) some NMS (Poland, Hungary, 1 The share of year olds having completed tertiary or equivalent education should reach at least 40% at the end of this decade; the school drop-out rates should be reduced to less than 10%. 2 See Quintini et al. (2007), Perugini and Signorelli (2010a and 2010b). 3 See ILO (2010a and 2010b); Arpaia and Curci (2010). 4 A partly similar approach was followed by Verick (2009) who, in order to better investigate the impact of the recent crisis on the labour market (especially on young men and women), also analyses the effects on unemployment of the past Big 5 Crises. 5 See, for example, Lefresne (2003), O Higgins (1997). For a more complete definition of "youth unemployment" and some measurement aspects, see also ILO (2009). 2

3 Slovakia); on the other hand, in Romania and Bulgaria the situation improved over time 6 (and now the two countries are close to or below the EU average). The crisis has caused a serious worsening from 2008 to 2009 in the Baltic states, in Spain and Greece, in Hungary and Slovakia, but also in Sweden, Finland, France and Italy. And the pattern further deteriorated in A possible question that now arises is whether the increased youth unemployment rates reflect the general bad economic situation as shown by the total unemployment rates or instead a peculiar negative movement among young people. If we look at the ratios between YUR and total UR, a first observation is that for the EU as a whole there has been no improvement in the relative position of young people in the last decade despite the European Employment Strategy and the Lisbon Agenda goals, since the ratio has been pretty close to 2 and was slightly deteriorating even before the crisis. In other words, young people are twice as likely to be unemployed compared to the general population. The real figure is probably higher, because the discouraged worker effect 7 is more likely for the young, who can opt to continue their education or simply to live with their families, avoiding implementing robust search efforts if unable to find a job (making up the so-called NEET group). In addition to this overall and EU-wide YUR problem, in particular countries the labour market exhibits even greater problems concerning young people (with youth/total ratios around or close to 3): Italy, Greece, some NMS, Belgium-Luxembourg-France and, rather surprisingly, also Sweden and the UK. On the other hand, the countries that have best coped with the labour market problems, in general, and kept the rise of youth unemployment under control, in particular, are localised in central Europe: Germany, Austria, the Netherlands and Denmark. Is this the revenge of the flexicurity model or, from a different point of view, the success of the attempt to make some labour market institutions more flexible while safeguarding the basic elements of the pre-existing social model (exemplified by the German experiments in recent years)? A final comment about the impact of the recent Global Recession: while the total UR increased in the September 2008/March 2010 period from 7.1% to 9.6% in the EU-27 (from 6.2% to 9.7% in the US), the YUR rose from 15.8% to 20.6% in the EU-27 (from 13.4% to 18.8% in the US), reaching top values above 25% in the following European countries (in descending order): Spain, the Baltic states, Slovakia, Hungary, Greece, Ireland, Italy and also Sweden. The key explanations of the greater impact of economic and financial crises on youth unemployment will be reviewed in section Theories on the Key Determinants of Youth Unemployment As shown in the previous section, the youth unemployment rate is generally much higher than the adult unemployment rate. The main reason for the generally worse youth labour market performance with respect to adults is related to the lower level (and/or different quality) of human capital (and productivity), which ceteris paribus makes employers prefer adults to young people. It has been noticed that among the multiple features characterizing the transition of young people from school to the labour market, the risk of unemployment they face, their performance at work, the quality and stability of their positions human capital is a prominent element. In particular, young people with low human capital and low skills are more exposed to long-term unemployment, unstable and low quality jobs, and perhaps social exclusion (Oecd, 2005). However, the educational level is only the most immediate variable measuring human capital ; in fact, young people lack the other two important components of human capital, namely generic and job-specific work experience 8. As regards the European context, Caroleo and Pastore (2007) argued that the "youth experience gap is the key factor explaining a youth unemployment rate so much higher than the adult unemployment rate. The school-to-work-transition (STWT) institutions are also relevant (Ryan 2001). The links between the institutional framework and policies to counter youth unemployment are discussed in a wide and recent literature (e.g. Brunello et al. 2007; Checchi 2006; European Commission 2008 chapter 5; Perugini and Signorelli, 2010a and 2010b). Many other research studies analyse the role of institutional and policy settings with specific reference to the youth segments, both focusing on specific 6 Also in the Baltic states the situation had improved in the years preceding the crisis, but then worsened sharply; on the contrary youth unemployment in Sweden had been getting worse since the middle of the decade. 7 The complex relationships between unemployment, employment and participation rates have been investigated in depth (see, for example, Perugini and Signorelli, 2007); it should be noted that - especially during and after a crisis - the increase in (youth and total) unemployment rates can undervalue the negative impact if the possible decrease in the (youth and total) participation rates is not adequately considered. The "discouragement effect" is usually more relevant for women and - especially in the case of young people - can partly consist in an extension in the duration of "education. 8 From both a theoretical and an empirical viewpoint, Carmeci and Mauro (2003) have shown that educated youngsters need to acquire firm-specific knowledge by working activities for schooling human capital to become productive. 3

4 aspects such as temporary jobs (e.g. Nunziata and Staffolani 2007) or minimum wage regulation (e.g. Neumark and Wascher 2004; Abowd at al. 1997), or providing a more comprehensive view of the many possible institutional and policy factors directly or indirectly related to the labour market and their interaction (e.g. Kolev and Saget 2005; Bassanini and Duval 2006; OECD, 2006). Quintini et al. (2007) investigate changes in the school-to-work transition process in OECD countries, also highlighting the persisting differences between youth and adult unemployment rates. A growing literature analyses the difficulties in the university-to-work transitions (e.g. Sciulli and Signorelli, 2011). As mentioned above, Clark and Summers (1982) investigate the determinants of the higher flows in and out of unemployment for young people compared with adults, while O'Higgins (2005) examines trends in the youth labour market in developing and transition countries, highlighting the considerable difficulties of integrating young people into "decent work". The persistence of youth unemployment (e.g. Heckman and Borjas 1980; Ryan 2001) has also been investigated. Another possible cause of high youth unemployment and low quality employment low entrance wages, bad-quality jobs, diffusion of non-standard labour contracts has been found in the mismatch between the knowledge acquired through formal education and the skills required by the labour market Literature on the Sensitivity of Youth Unemployment to Economic and Financial Crises Despite the existence of many contributions on the structural determinants of youth unemployment (including the institutional variables) as well as on the impact of macroeconomic shocks, the specific literature on the impact of "financial crises" on youth unemployment is still quite scarce. Of course, overall and youth unemployment depends significantly on macroeconomic cyclical conditions: although the permanent effects, e.g. on potential output, of cyclical downturns can be estimated (see, for instance in the case of the recent global recession, Furceri and Mourougane, 2009, and World Bank, 2010), the economic cycle cannot explain many of the persistent employment difficulties of young people compared to adults. For example, Jimeno and Rodriguez-Palenzuela (2003) although stressing that youth unemployment is more sensitive to macroeconomic shocks than the total unemployment rate investigate the specific role of structural determinants and also of labour market institutions (e.g. the strictness of temporary contracts). A more specific consideration is that the overall and specific impact of a crisis is usually different across (and within) countries depending on many factors, such as: (i) the economic structure, (ii) the institutional framework (including STWT institutions) and (iii) the policymakers response at different levels 9. The previous factors affect, in the first place, the size and the degree of (in)stability of the relationship between economic growth (or output decline) and unemployment rate, i.e. the so-called "Okun's law" 10. However, a decline in aggregate demand - as occurred in in many countries - negatively affects labour demand, with different immediate responses (also as a consequence of labour hoarding practices), various time lags and different degrees of persistence of the effects; moreover, the adverse effects can be partly mitigated by policymaker responses (both general macroeconomic policies and specific measures for the labour market) and the existence of a better institutional framework (including unemployment benefits, social insurance systems, etc.). Considering young people, Scarpetta et al. (2010) highlight that the crises exacerbate a number of structural problems that affect the transition from school to work. In fact, during and after a (financial and/or economic) crisis, the decline in GDP turns - after some months - into a reduction of labour demand: in this situation school-leavers are competing with more jobseekers for fewer vacancies, while the young people already in the labour market are generally among the first to lose their jobs, mainly due to the higher diffusion of temporary contracts 11, with consequent considerable difficulty in getting another one (OECD, 2009). So, the high diffusion of temporary contracts is a key explanation of the higher business-cycle sensitivity of young people in the labour market. However, many authors (e.g. Cockx and Picchio, 2009; 9 In many countries policies are adopted - with different degrees of coordination and autonomy - at more than one level of government (see also Signorelli, 2008). 10 See Okun (1962). For a discussion on the stability (and main direction of causality) of the output-unemployment relationship, see Signorelli (2005). Note that a given output growth (or decline) may impact more on employment or productivity, both in the long run (according to the specific growth models : see Marelli and Signorelli, 2010b) and in the short run (because of different labour hoarding practices, working time adjustments and internal flexibility, EPL and institutional settings, benefit systems, etc.). 11 Also Arpaia and Curci (2010), who carried out an extensive analysis of the labour market adjustments in EU-27 after the recession (in terms of employment, unemployment, hours worked and wages), highlight that workers with weaker employment contracts and lower qualification and experience have borne the brunt of the "great recession". 4

5 Scarpetta et al., 2010) also note that - for many young workers - temporary contracts (especially apprenticeships) are more often a stepping stone to a permanent contract than a "trap" 12. The labour hoarding practices, especially in countries with the highest EPL on "permanent contracts", favour adult segments and can further increase the size and duration of the impact of the crisis on youth unemployment. 13 It should be noted that, generally, "education matters" and the consequences of a crisis are usually more dramatic for low-skilled young people, already in difficulty in good times, since the crisis further increases their risk of long-term inactivity and exclusion. Many authors find that the "scarring" effect of unemployment on young people depends on overall labour market conditions, but it is significantly higher for disadvantaged young people (e.g. Bell and Blanchflower, 2009). In any case, adopting the definitions of Quintini and Manfredi (2009), the crisis is pushing more and more young people, even those who have performed well in good times, into the group of "poorly-integrated new entrants" and possibly into the group of "youth left behind" 14. In particular, Scarpetta et al. (2010) highlight the risk of having a "lost generation" and the need to adopt effective (active and passive) labour policies and STWT institutions to minimise the increase in the number of young people losing effective contact with the labour market and permanently damaging their employment prospects. Considering the specific impact of financial crises, first of all, it should be emphasized that national financial crises (without significant external effects) are obviously very different, in a worldwide perspective, from international financial crises. For example, according to Bordo (2006) and Reinhart and Rogoff (2008a, 2008b, 2009), there have been eight episodes of major international financial crises since As regards the labour market impact of financial crises, Verick (2009) analyses the effects on unemployment of the past Big 5 Crises (Spain 1977, Norway 1987, Finland 1991, Sweden 1991 and Japan 1992) in order to better investigate the impact of the recent crisis on the labour market, especially on young men and women 16. The author argues that data on the five previous financial crises, as well as on the recent one, reveal that young people are hit hardest and the impact persists long after the economy is growing again 17 ; the size and persistence of the impact on youth unemployment depend on: (i) the degree of economic contraction, (ii) the sectoral composition of employment prior to the crisis and (iii) the institutional structures. In particular, Verick (2009) further confirms that - during and after a severe recession - young people find it increasingly difficult both to acquire a job as a new entrant in the labour market, especially as a consequence of hiring freezes, and to remain employed, since they are more likely to be laid off than workers with greater seniority. So, the youth unemployment rates are more sensitive to the business cycle than those witnessed for adults (OECD, 2008). As far as the impact of the last crisis is concerned, it is known that it began as a financial crisis at the end of 2007; its most serious impact on financial markets (with Lehman Brothers default) was in September 2008, when the real effects initially developed (but the biggest fall in production was reached in the first half of 2009) and led to increasing unemployment rates during 2009, although in many countries they continued to rise also in 2010). In fact, the real effects (on product, income, etc.) of financial crises are always lagged and the labour market effects are even more lagged. In the next few years, in addition to a further rise in the 12 The trap effect of temporary contracts seems to be higher in countries with a large difference in the stringency of regulations for permanent contracts (i.e. strict employment protection legislation, EPL) compared to temporary (or other atypical) contracts. 13 This is the most common evidence, but there are some exceptions; e.g. big shocks, such as the crises that hit the transition countries in the 90s, causing mass unemployment, affected adult workers more than the young (see Newell and Pastore, 1999). For a comprehensive analysis of two decades of transition, also regarding many aspects of the labour market structure and dynamics, see Marelli and Signorelli (2010a). 14 According to Scarpetta et al. (2010) the size of the group of "youth left behind" can be proxied by the number of young people who are neither in employment, nor in education or training (NEET). This group represented 11% (on average) of year-olds in the OECD in We briefly recall the dates and countries of origin of the eight "international financial crises": (i) in 1873 German and Austrian stock markets collapsed with effects on the rest of Europe and the Americas; (ii) in 1890 a debt crisis involved Latin America (especially Argentina); (iii) in 1907 a fall in copper prices caused financial panic in the US with effects on Europe, Latin America and Asia; (iv) in 1929 a stock market crash in the US started the well-known "Great Depression"; (v) in a Latin American debt crisis began producing a decade-long debt crisis across developing economies; (vi) in real estate and equity price bubbles burst in Scandinavia and Japan, while in Europe the ERM crisis developed; (vii) in the Asian and Russian crises; (viii) finally, in the worst financial crisis (after 1929) started in the US. For more details, see IMF (2009, p. 128). 16 For an empirical investigation comparing the different impact on regional youth unemployment rates of two major Russian crises, see Demidova and Signorelli (2011). 17 Unlike previous crises, in the last crisis young men have been particular affected, mainly due to the high proportion of young men in heavily impacted sectors. Also from a structural point of view, however, in many developed countries the male unemployment rate is now higher than the female one (see also Pastore, 2011). 5

6 unemployment rates, a certain degree of persistence of the unemployment rate in the subsequent years is also likely, similarly to past crises, due to the phenomenon of "hysteresis" (upward shift in "structural unemployment"). The impact of the crisis has been differentiated not only across countries, but also between the various segments of the labour market. Many studies (e.g. ILO, 2010a and 2010b) have argued that the most exposed segments of the labour market are young people, old workers, vulnerable employment in general and (at least in many world regions) women. Concerning young workers, it should be repeated that a decrease in labour demand implies fewer job openings, so young people are particularly affected; moreover, job destructions are also likely to disproportionately affect young workers, because they tend to work more frequently under temporary contracts (recent evidence confirms that young people have been hardest hit by the crisis: see, for example, O Higgins, 2010). 3. Financial Crises and Youth Unemployment Rate: Some Econometric Investigations In this section we used different econometric methods to estimate on the basis of data concerning past financial crises the relationship between financial crises and the youth unemployment rate in the labour markets Definitions, model and data In order to econometrically estimate the labour market impact especially on young people of past financial crises, in this study we use the definition of "financial crisis" adopted in Honohan and Laeven (2005), that considers financial crisis as the occurrence of either a "systemic banking crisis" or a nonsystemic banking crisis. Systemic crisis is defined as when a country s corporate and financial sector experiences a large number of defaults and financial institutions and corporations face great difficulties repaying contracts on time 18. Non-systemic crisis is a crisis limited to a small number of banks. The authors also consider currency crises and debt crises. In this section we report the econometric results concerning financial crises as a whole. Financial crisis is a variable which takes a value of one if there is a crisis in a country and zero otherwise. As regards unemployment, according to the International Labor Organization (ILO), from which the YUR data were extracted, the unemployed comprise all persons above a specified age who, during the reference period, were: (a) without work; (b) currently available for work; and (c) actively seeking work. So the unemployment rate is defined as the number of unemployed in an age group divided by the labour force for that group. In the case of our YUR, the population for that age group (15-24 years) replaces the labour force as the denominator. The empirical investigation of the relationship between YUR and financial crises is carried out for a sample of more than 70 countries for the period The empirical estimation is done with unbalanced panel data, to fully utilize the available information for our variables of interest. The baseline model for estimation is: YUR it = Crisis it β + Z it µ + ε it (1) where, YUR it represents youth unemployment rate in country i at time t and it is our dependent variable. Crisis it represents our measure of financial crisis: it takes a value of one if there is a crisis in a country and zero otherwise. Z it is a vector of control variables and ε it is the error term. For inclusion of control variables, we take guidance from previous literature (e.g. O Higgins 1997, Jacobsen 1999, Blanchflower and Freeman 2000, Akhtar C. and Shahnaz, 2005). Our control variables include GDP growth, inflation rate, foreign direct investment and openness. Data for our explanatory variables are taken from World Bank Development Indicators (WDI) historical database. Adjusted inflation 19 rate is used as a proxy for the changes in the price level in the country. Detailed explanation of definition and sources of all data used is presented in the Appendix (Table A2). The summary statistics of dependent and independent variables used in empirical estimations is presented in Table A3. Moreover, the correlation matrix of our dependent and main explanatory variables is 18 As a result, non-performing loans increase sharply and all or most of the aggregate banking system capital is exhausted (see Laeven and Valencia (2008)). P / To adjust for extreme movements, we modify the inflation rate (P) as. 1 + ( P /100) 6

7 provided in Table A4: the low correlations of the explanatory and control variables suggest that multicollinearity is not a potential problem in our estimations Impact of financial crises on youth unemployment rate We estimate equation (1) using a fixed effects panel model over the period , for a panel of 75 countries. The fixed effects model was selected on the basis of the Hausman test (see the Hausman test statistic and correspondence p-value in the next table). Results of empirical estimation are presented below in Table 1. In the first model, we simply evaluate the impact of financial crises on the youth unemployment rate (YUR). We observe that the crisis coefficient is positive and statistically significant. The result implies that financial crisis leads to increase in YUR. We then incorporate GDP growth as explanatory variables in Model 2. As expected, the coefficient of this variable is negative and statistically significant for GDP growth; it implies that, as expected, GDP growth in an economy helps to reduce unemployment among young workers. The impact of crisis remains positive and significant for YUR. The significance of the financial crisis variable in the presence of GDP growth implies that this variable is not simply just picking up the effect that the youth unemployment rate is sensitive to current GDP growth 20. We incorporate, in Model 3 to Model 5, the other control variables which may impact the unemployment rate of young workers. Coefficients for Inflation, FDI and Openness variables are negative, which reflect that increase in these variables will promote employment among young workers. Moreover, their inclusion does not change the sign and significance of the key explanatory variable. Finally, in Model 6 we include all variables from Model 1 to Model 5 and find that results remain very consistent. Financial crisis impact remains negative and significant in all specifications 21, suggesting the robustness of our findings 22. Table 1: Impact of financial crises on youth unemployment rate Dependent Variable: Youth Unemployment Rate Variables Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Financial Crises 1.811*** 1.351*** 1.423*** 1.429*** 1.323** 1.492*** GDP growth *** *** *** *** *** Inflation *** *** Foreign Direct Investment Openness Constant *** *** *** *** *** *** Observations Countries Hausman test statistic P-Value R-square Significance of Model 12.96*** *** *** 8.228*** 9.542*** 11.39*** Note: Robust standard errors are reported under the coefficient value. * Significant at 10%, ** significant at 5 %, *** significant at 1 % After estimating the impact of financial crisis on the youth unemployment rate, the question that springs to mind is whether youth workers are more prone to financial crisis than older workers; another interesting issue is whether or not financial crises have a specific effect other than the variation in GDP or other types of crisis. To answer the first question, we estimate the impact of financial crises for the overall unemployment rate. The estimation results are presented in Table We also used lagged value of GDP growth as an explanatory variable. We find negative and significant coefficient. 21 As regards the detailed results concerning the different types of financial crises, we can state that systemic and non-systemic banking crises, as well as currency crises, have significant effects on YUR; only debt crises are not always significant. (Detailed results are available upon request). 22 For further estimations we use the same data sample used for Model 6. We used the sample period for which complete series were available. 7

8 Table 2 : Impact of financial crises on youth unemployment rate and Overall Unemployment Rate Dependent Variable Youth Unemployment Rate Overall Unemployment Rate Model 1 Model 2 Financial Crises 1.492*** 0.651*** GDP growth *** *** Inflation *** *** Foreign Direct Investment *** Openness ** Constant *** *** Observations Countries R-square Note: Robust standard errors are reported under the coefficient value. * Significant at 10%, ** significant at 5 %, *** significant at 1 %. We find that the value of coefficient of crisis variable is higher for the youth unemployment rate than for the aggregate unemployment rate (see Models 1 and 2 in Table 2). For more detailed analysis of the impact of financial crisis on the overall unemployment rate see Choudhry et al. (2010), where results on estimation of the effects on participation rates are also provided. Our findings coincide with the findings of the ILO report (2010b) on youth unemployment, which suggested that youth unemployment is more sensitive to crisis than adult unemployment, supporting the Last in-first out argument. In all such estimates, to evaluate that the financial crisis effect is different from the impact of variation in GDP, we included GDP as an explanatory variable, to make sure that the financial crisis variable is not capturing the effect of economic activity. Our results suggested that this is not the case. As a sensitivity analysis, we have replicated the same exercise for a sample of high income OECD countries and a sample of other countries. According to our results 23, the crisis impact is still negative for YUR, both in high income OECD as well as for other countries. However, it is statistically significant only in the case of high income OECD countries. The value of coefficient is also higher in high income OECD sample countries as compared to other countries. This implies that the impact of financial crises on young workers in high income economies is more severe compared to other countries in the sample. This may be due to the fact that young people in high income economies are working in the formal sector and are mostly employed in non-farm activities; on the contrary, in low income and developing economies young people are mostly working in the informal sector or in the agricultural sector under the category of unpaid family helpers. 3.3 Youth unemployment and crises: persistence of the effects To check the persistence of the adverse effect of crises on YUR, we take the lag value of crisis as an explanatory variable (see Model 2 to Model 7 in Table 3). An important thing to note is that the intensity of the adverse effects of crisis on YUR is high in the second and third year after the financial crisis. The adverse effect of crisis on unemployment disappears five years after the crisis. This finding also confirms the fact that labour market indicators for young workers follow the overall trend in unemployment rate. Choudhry et al. (2010) found that the adverse impact of financial crisis on labour force participation and unemployment rate remain for five years after the crisis. Table 3: Impact of Crisis on Youth Unemployment Rate Dependent variable: Youth Unemployment Rate Variables Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 GDP Coefficient *** *** *** *** *** *** *** Robust SE Available upon request. 8

9 Openness Coefficient *** ** ** Robust SE Foreign Direct Investment Coefficient ** *** ** ** ** * ** Robust SE Inflation Coefficient *** *** *** *** *** *** *** Robust SE Financial Crises Coefficient 1.492*** Robust SE Financial Crisis (-1) Coefficient 2.772*** Robust SE Financial Crisis (-2) Coefficient 2.951*** Robust SE Financial Crisis (-3) Coefficient 2.520*** Robust SE Financial Crisis (-5) Coefficient 1.446*** Robust SE Financial Crisis(-7) Coefficient Robust SE Financial Crisis (-10) Coefficient Robust SE Constant Coefficient *** *** *** *** *** *** *** Robust SE Observations Number of Groups R-Square Significance of Model 24.49*** 33.77*** 31.43*** 21.85*** 12.48*** 18.52*** 29.45*** Note: Robust standard errors are reported under the coefficient value. * Significant at 10%, ** significant at 5 %, *** significant at 1 % 3.4. Youth unemployment and financial crises: a dynamic model To evaluate the short term effect of financial crises on YUR we introduce, in this new model, the lagged dependent variable as an explanatory variable. Thus our model for estimation becomes: YUR it = YUR it(t-1) + Crisis it β + Z it µ + ε it (2) where YUR it represents youth unemployment rate in country i at time t and YUR it(t-1) is the lagged value of the dependent variable. Crisis it represents our measure of financial crisis. Z it is a vector of control variables and ε it is the error term. The main estimation results are presented in Table 4. The coefficient estimates with the lagged dependent variable (in Models 1-6) reflect the short-term effect of explanatory variables on YUR. The coefficient of lagged unemployment rate equals 0.75 to 0.78 and is highly significant, indicating that YUR is highly persistent. This finding is consistent with the literature on unemployment determinants (see Elhorst and Zeilstra, 2007). The impact of financial crisis on YUR is still positive and statistically significant, reflecting the robustness of our findings in the previous section, i.e. that financial crises cause further unemployment among young workers. 24 We have also estimated the empirical model (with lagged dependent variable) from 24 Empirical results imply also that the relationship between unemployment rate and inflation rate is negative and significant. The possible explanation for the negative impact of inflation on unemployment is that if actual price level exceeds the expected price level, real wages are lower than expected during the wage bargaining process and consequently employment increases and unemployment decreases (Nickell, 1998 and Belot and van Ours, 2001). All other explanatory variables have the expected sign and are statistically significant. 9

10 a gender perspective. The findings suggest that unemployment among young female workers is highly persistent and statistically significant. 25 Table 4: Impact of financial crises on youth unemployment rate - Dynamic Model Dependent Variable: Youth Unemployment Rate Variables Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Lagged Youth Unemployment Rate 0.779*** 0.795*** 0.778*** 0.792*** 0.790*** 0.772*** Financial Crises 1.456*** 0.685** 0.708** 0.678*** 0.695** 0.710*** GDP growth ** *** *** *** *** Inflation *** *** Foreign Direct Investment *** *** Openness ** ** Constant 3.376*** 4.445*** 5.095*** 4.606*** 5.775*** 6.198*** Observations Countries R-square Significance of Model *** *** *** *** *** *** Note: Robust standard errors are reported under the coefficient value. * Significant at 10%, ** significant at 5 %, *** significant at 1 %. At this point we should consider that several econometric problems may arise if we estimate the basic model presented in (2) with a simple fixed effects panel estimation. The inclusion of the lagged dependent variable on the right-hand side makes the empirical model dynamic and requires special treatment. The presence of the lagged dependent variable gives rise to autocorrelation; there may be an endogeneity problem and measurement error in some of the explanatory variables. To deal with these issues, we applied the Arellano-Bond (1991) dynamic panel estimation model to analyse the impact of financial crises and lagged dependent variable on YUR. The estimation results are presented in Table We find that both the lagged dependent variable and financial crises are still positive and statistically significant. The Hansen test for over-identifying restriction appears insignificant, suggesting the validity and exogeneity of our instruments. Similarly, the Arellano-Bond test for the first difference autoregressive process appears to be significant and the second difference appears to be insignificant 27. The results confirm once more the robustness of our estimations. Table 5 : Impact of financial crises on youth unemployment rate - Arellano-Bond Dynamic Panel Estimation Dependent Variable Youth Unemployment Rate Lagged Youth Unemployment Rate 0.961*** Financial Crises 3.168*** GDP growth *** Inflation Foreign Direct Investment *** 25 Economic growth, inflation and foreign direct investment reduce the female youth unemployment rate. Results available upon request. 26 We use Roodman (2006) xtabond2 command to apply 2-step GMM system Dynamic Panel Estimation. 27 For consistent estimation of the models, a crucial condition is that the error terms are serially uncorrelated. This can be examined by the Arellano-Bond test for first and second difference autoregressive processes. The test for the first difference autoregressive process appears significant, whereas it is insignificant for the second difference, indicating that the error terms in our models are serially uncorrelated. 10

11 0.010 Openness Constant 1.827* Observations 740 Countries 66 Number of Instruments 25 Arellano-Bond Test for AR(1) 0.00 Arellano-Bond Test for AR(2) 0.59 Hansen Test over identifying restrictions-p value Conclusions This study investigated the effect of financial crises on youth unemployment rates during the period for a large number of countries (about 70). The estimation technique initially used is a fixed effects panel model. The empirical study also focused on the differentiated impact by group of countries, according to their income level. Special attention was paid to the problem of persistence of such effects. The main results of our econometric investigations are the following. Financial crisis impact on the youth unemployment rate is statistically significant and robust; the impact seems more significant for highincome countries. The inclusion of many control variables including in particular GDP growth does not change the sign and significance of the key explanatory variable. Our results also show the persistence of adverse effects for labour markets and suggest that financial crises affect YUR for five years after the onset of the crises; however, the most adverse effects are found in the second and third year after the financial crisis. Moreover, considering the Arellano-Bond dynamic panel estimation model, we found that both the lagged dependent variable and the financial crisis variable have a significant impact on YUR. Thus the two key results of our econometric estimates are that (i) financial crises have an impact on the unemployment rate that goes beyond the impact resulting from GDP changes and (ii) the effect on youth unemployment is greater than the effect on overall unemployment. Although we are fully aware of the peculiarities of the last crisis, its global nature in the first place, we believe that our econometric results facilitate a better understanding of the impact of the financial crisis on the youth labour market. As a matter of fact, recent evidence and forecasts are in accordance with our results; in particular, the impact of the last crisis on the youth labour market has been partly delayed, but unfortunately it will persist for some years (for about five years from the start of the crisis, according to our econometric results concerning past financial crises). Moreover, it is confirmed that the biggest impact occurred on the weakest sections of the labour market and especially young people. It therefore seems appropriate to adopt effective active labour market policies 28, especially in countries where youth performance was poor even before the crisis (in future research we intend to investigate the impact of specific ALMP on youth unemployment). Such policies are fundamental in view of the high risks of persistence and possible transformation of short-term unemployment into structural (longterm) unemployment or inactivity. Better STWT institutions, more efficient educational systems and placement services, more adequate training activities, etc. are particularly needed, otherwise the NEET generation will continue to expand, with serious economic and social consequences. 28 While passive policies as well as macroeconomic policies (such as the fiscal stimuli adopted in many countries in ) were fundamental at the peak of the crisis, ALMP are particularly useful in the recovery period, in order to reduce the risk of long-term unemployment or jobless young people (see also O Higgins, 2010). 11

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14 Appendix Table A1 Unemployment rate of young people (15-24 years) Belgium Bulgaria Czech Republic Denmark Germany Estonia Ireland Greece Spain France Italy Cyprus Latvia Lithuania Luxembourg Hungary Malta Netherlands Austria Poland Portugal Romania Slovenia Slovakia Finland Sweden United Kingdom EU (27 countries) Note: *EU-25 for 1998 and In bold the values higher than the EU average. Source: Eurostat on-line data base Figure A1: Youth Unemployment Rate before and after Crisis Belgium Bulgaria Czech Republic Denmark Germany Estonia Ireland Greece Spain France Italy Cyprus Latria Lithuania Luxembourg Hungary Malta Netherlands Austria Poland Portugal Romania Slovenia Slovakia Finland Sweden United Kingdom EU (27 countries) 14

15 Table A2: Data description and Sources Variable Definition Source Dependent Variables (alternative) Youth Unemployment Rate Youth unemployed labour force/youth labour force Key Indicators of Labour market (KILM) Youth Unemployment Rate Male youth unemployed labour force/ male youth labour force Key Indicators of Labour market (Male) Youth Unemployment Rate (Female) Female youth unemployed labour force/female youth labour force (KILM) Key Indicators of Labour market (KILM) Key Explanatory Variable Financial Crises It is calculated as a sum of systemic banking crises (when a country s corporate and financial sector experiences a large number of defaults and financial institutions and corporations face great difficulties repaying contracts on time; as a result, non-performing loans increase Honohan and Laeven (2005) sharply and all or most of the aggregate banking system capital is exhausted) and non-systemic banking crises (is defined as crises limited to a small number of banks). Control Variables GDP Growth (CSW) Annual GDP growth World Development Indicator Foreign direct Investment (FDI) Net inflow of foreign direct investment as percentage of GDP World Development Indicators Openness (Open) Trade of goods and services as percentage of GDP World Development Indicators Inflation (Inf) Consumer Price Index (P) was adjusted for extreme fluctuations as P/100)/[1+(p/100)] World Development Indicators Table A3: Summary Statistics of Variables Variable Mean Std. Dev. Minimum Maximum Youth Unemployment Youth Unemployment Male Youth Unemployment Female Financial Crisis GDP Growth Openness Foreign Direct Investment Inflation Table A4: Correlation Matrix Variable YUN CRS GDP OPEN FDI INF Youth Unemployment Rate (YUN) 1.00 Financial crises (CRS) GDP Growth (LGDP) Openness (OPEN) Foreign direct Investment(FDI) Inflation (INF)