# A scarred generation ? French evidence on young people entering into a tough labour market

Mathilde Gaini, Aude Leduc, Augustin Vicard

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Direction des Études et Synthèses Économiques

G 2012 / 05

# A scarred generation? French evidence on young people entering into a tough labour market

Mathilde GAINI, Aude LEDUC and Augustin VICARD

Document de travail
INSTITUT NATIONAL DE LA STATISTIQUE ET DES ÉTUDES ÉCONOMIQUES

Série des documents de travail
de la Direction des Études et Synthèses Économiques

G 2012 / 05

A scarred generation? French evidence on young people entering into a tough labour market

Mathilde GAINI*, Aude LEDUC** and Augustin VICARD**

JUIN 2012

We are grateful to Patrick AUBERT, Luc BEHAGEL, Pierre CAHUC, Andrew CLARK, Sandra MCNALLY, Philip OREOPOULOS, Corinne PROST. We also thank the participants at the CREST-LMI seminar (Malakoff, April 2011) and the INSEE-DEEE seminar (Malakoff, December 2011) for their stimulating remarks. All remaining errors are ours. Any opinions expressed here are those of the authors and not of INSEE.

<footnote>* Crest-Insee</footnote>

<footnote>** Département des Études Économiques d'Ensemble - Division « Redistribution et Politiques Sociales »
Timbre G210 - 15, bd Gabriel Péri - BP 100 - 92244 MALAKOFF CEDEX</footnote>
# A scarred generation? French evidence on young people entering into a tough labour market

## Abstract

The late 2000s recession has hit youth very hard, lowering the employment and wage prospects of the entrants into the labour market. In this paper, we address the question of the persistence of these adverse shocks faced by young people who enter into the labour market during an economic downturn, focusing on the French case.

Using the French Labour Force Surveys for the cohorts entering the labour market between 1982 and 2009 (which includes more than two entire business cycles), we find no long term effect on wage or employment of having entered the labour market during an economic crisis. "Unlucky" young people completing their studies during a recession have lower employment rates, are more often part-time and temporary workers, but catch-up with "lucky" one within 3 years.

This fast catch-up contrasts with results for other countries. Potential explanations for those differences are twofold: first, in France a large share of young entrants are paid at the minimum wage and, second, young people unemployment is high in France, so that unemployment at entry on the labour market may be less often used as a screening device by employers.

**Keywords:** Scarring effect, Business cycle, Initial labour market conditions

## Peut-on parler de « générations sacrifiées » ?
Entrer sur le marché du travail dans une période de mauvaise conjoncture économique

## Résumé

La crise économique de la fin des années 2000 a beaucoup touché les jeunes entrants sur le marché du travail, réduisant leurs perspectives d'emploi et de salaire à court terme. Dans cette étude centrée sur la France, nous cherchons à savoir si les jeunes qui font face à une crise au moment d'entrer sur le marché du travail sont aussi pénalisés à long terme. À partir des données des enquêtes Emploi, nous étudions les cohortes sorties du système scolaire entre 1982 et 2009. Cette période comprend plus de deux cycles économiques complets. Après 4 ans, il n'y a pas de différence en termes d'emploi et de salaire entre les cohortes « chanceuses » entrées sur le marché du travail en période de bonne conjoncture économique et les cohortes « malchanceuses » entrées sur le marché du travail en période de crise économique.

Ce rattrapage est plus rapide en France que dans la plupart des autres pays. Deux raisons pourraient l'expliquer. Tout d'abord, les jeunes sont nombreux en France à être payés au salaire minimum quand ils entrent sur le marché du travail. Ensuite, le taux de chômage des jeunes est élevé en France : le temps passé au chômage en début de carrière n'est donc probablement que peu utilisé par les employeurs comme signal de la qualité des candidatures.

**Mots-clés :** Génération sacrifiée, Cycle économique, Conjoncture à l'entrée du marché du travail

**Classification JEL :** J30 - J21
# 1 Introduction

The current crisis has renewed the interest in the impact of business cycle fluctuations on labour markets. There has been a special focus on young people, and among them, on entrants into the labour market, who are hit very strongly by the economic downturns. In France, the unemployment rate of young entrants (1-4 years of experience) rose dramatically by 3.8 percentage points between 2007 and 2010 whereas the unemployment rate of workers with more than 11 years of experience increased by 1.1 percentage points. This raises the question of the effect that economic conditions may have on young entrants into the labour market, that we address in this paper.

More precisely, we wonder if the effects of economic conditions at the entry into the labour market are persistent, or if they disappear after some years. In the literature, the existence of a persistent or very long-lasting effect is often referred to as a *scarring effect*, that we try to measure for the French case. In other words, we try to investigate if "unlucky" young people leaving school during a crisis catch up (in terms of employment and wage levels), after some years, with "lucky" ones, who entered the labour market during a boom.

Theoretical results on long-term effects of leaving school in a bad economy are not conclusive. Economic theory suggests some channels that could cause the adverse economic shock at the entry on the labour market to be persistent. Theoretical arguments are threefold. First, if one assumes that employers face uncertainty about worker productivity, they could use previous unemployment spells as a screening device in their hiring process. Thus, unemployment spells may be a persistent negative point in a career (signal effect theory). Second, skills accumulated by people facing a crisis during their early career may be lower than skills of people facing an economic boom, if we assume that skills deteriorate during a spell of non-employment or job mismatch (human capital theory). Finally, the effects of entering in a bad economy on wages depend on the nature of the wage negotiation. If inter-firm mobility is costly then initial wage will impact all the subsequent wages.

But adverse shocks could be overcome, especially in a flexible labour market. If young people experience unemployment during a crisis and quickly find good jobs when the economy recovers, they may not be stigmatized. Search theory suggests that job changes may be beneficial for wages. Moreover, in the implicit contract theory (Beaudry and DiNardo, 1991), costless mobility induces that, when economic conditions improve, wages must be revised upward to prevent the worker from being bid away by other firms. In addition, the scarring effect of being unemployed during massive unemployment period is not clear-cut on the long-run.
Being unemployed in that period would send a less negative signal to employers than being unemployed during economic boom. In that context, a negative shock on the matching process could be overcome, especially if the labour market is sufficiently flexible and economic cycles quite short.

As theoretical arguments on long-term effects are ambiguous, empirical investiga-
tions can provide useful insights. In this respect, both short and long run effects of
economic conditions at the entry into the labour market have been documented in
numerous countries (Austria, Canada, Germany, Japan, Norway, Sweden and the
U.S., see section 2 for references). Most of these papers find no long-term effect
on unemployment and a longer catch-up process for wages. But this literature
also shows that the existence and the extent of a scarring effect on wages varies
greatly from one country to another. The diversity of national labour markets,
and particularly the integration of school-leaving people into the labour force (see
for example Genda, Kondo, and Ohta, 2010 for a comparison between Japan and
the USA) could explain that variability. In France, only short run effects have
been studied (Fondeur and Minni, 2004). Documenting the French case seems
particularly interesting, because the French labour market greatly differs from the
ones of the USA or other countries where the existing studies have been done. In
particular, the French labour market is characterized by a high level of unemploy-
ment and a minimum wage. Therefore, employment is an important channel for
labour market adjustments.

In this paper, we present estimates of the long run effects of business cycle varia-
tions on both wage and employment profiles of young entrants. We do not find any
evidence of a scarring effect in France. More precisely, our results are the following:
an increase in the unemployment rate when leaving school lowers employment rate
of young entrants during the first 3 years. It also rises the proportion of part-time
and temporary workers. We do not find any significant effect on wages. We do not
find any significant effect on the proportion of managers and professionals even the
first year.<fnref n="1" /> Our results are very similar for men and women. Our results suggest
that entering in a tough labour market and experiencing unemployment during
the first years is not penalizing for the rest of the career. During an economic cri-
sis being unemployed would send a less negative signal to employers as the signal
would be more noisy about intrinsic abilities. Finally potential experience or age
may have a more important effect than real experience in fixing wages as we find
no effect on wages for cohorts having more unemployment spells.

The remainder of this paper is organized as follows. Section 2 summarizes the

<footnote n="1">¹Yet, the negative effect on employment during the first years could entail a positive selection effect in terms of composition of employed people. This could explain why we do not find any negative effect during the first years on wages or occupations.</footnote>
main results of the literature on our subject. Section 3 describes our data, whereas
sections 4 and 5 present the econometric model and our results. Section 6 proceeds
to some robustness checks and Section 7 presents a discussion of our results and
concludes.

2 Literature Review

There is an extensive literature addressing the question of the unemployment persis-
tence or hysteresis, in a general manner (see for instance Arulampalam, Booth,
and Taylor, 2000, Arulampalam, 2001 or Nilsen and Reiso, 2011) or with a specific
focus on young workers (Gregg, 2001, Gregg and Tominey, 2005, Skans, 2010).
Those papers find a high degree of persistence of unemployment: when a young
person experiences a period of unemployment at the beginning of her career, she
would suffer a wage loss for the remaining of her career (results remain even after
using technics - like IV - for controlling for unobserved heterogeneity).

But the focus of these papers is quite different from our own. They compare the
labour market performances of unemployed and employed young people having left
school within the same year while we are interested in comparing young people
having left school at different years, with different economic conditions. A large
body of literature focuses on this latter topic. Our paper is thus mainly related
to this literature which focuses on short and long-term consequences of leaving
school in a bad economy. The results of this last stream of literature are more
contrasted across countries. Previous papers usually do not find persistent effects
on employment while results concerning the persistence of the effect on wages differ
according to the country and the population under scrutiny.

Biewen and Steffes (2010) point out to a potential explanation that reconciles
the two literatures. Using the German Socio-Economic Panel, they show that
the "disadvantage from having been unemployed in the previous period is high
when unemployment is relatively low and low when unemployment is relatively
high. This is consistent with the hypothesis that employers see unemployment as
a stigma and do so especially when the conditions to find a job are relatively good.
On the other hand, if unemployment is relatively high, the stigma connected to it
is lower because it is a more widespread phenomenon".

The remainder of this section presents in details the main conclusions of the lit-
erature devoted to the long-term consequences on wages and employment of the
labour market conditions at entry. We focus here on the notion of catch-up: the
number of years after which young people who faced high unemployment rate
at entry succeed in catching-up (in terms of employment and wage levels) with
young people who entered the labour market facing a low unemployment rate. If
the catch-up process is never completed, even after 15 or 20 years on the labour
market, there is a permanent scarring effect.

## 2.1 An effect on the employment rate generally not persistent

There is a part of literature consistent with an effect of the unemployment rate at entry on future employment rates quickly fading. After three years, some authors find no effect of the business cycle at labour market entry on employment rates (Oreopoulos, von Wachter, and Heisz, 2012 on Canadian male college graduates data between 1982 and 1999; Genda, Kondo, and Ohta, 2010 on the United States between 1986 and 2005).

Yet, some studies find a persistent effect. The catch-up occurs after 6 years accord-
ing to Stevens (2007) on low and medium-skilled male German workers between
1980 and 1995. Genda, Kondo, and Ohta (2010) find a permanent effect on their
analysis period for low-skilled Japanese workers: a 1 percentage point rise in the
unemployment rate at entry reduces the likelihood of employment for low-skilled
Japanese people by 3-4 percentage points for over 12 years. Raaum and Roed
(2006) using Norwegian data from 1993-2000, find a persistent effect on employ-
ment rate of business cycle during adolescence (a 5 percentage point rise in local
unemployment rate between 16 and 19 year old increases the unemployment rate
of 1.5 percentage point during their 25-36 years year old). This effect is not limited
to a particularly disadvantaged group.

## 2.2 A longer catch-up process for wages

The catch-up for wages seems to be longer than for employment, and even never
occur in some countries. Three studies find a catch-up about 6 years after the
labour market entry (Genda, Kondo, and Ohta, 2010 on the United States: after
6 years; Oreopoulos, von Wachter, and Heisz, 2012: between 6 and 10 years ac-
cording to the national or regional specification; Stevens, 2007: between 4 (federal
state model) and 6 (regional planning model) years). Other studies find strong
permanent effects, with a 1 percentage point rise in the national unemployment
rate entailing a permanent wage loss (Mansour, 2009 and Kahn, 2010 on the
NLSY79; Genda, Kondo, and Ohta, 2010 for Japanese men without college edu-
cation; Brunner and Kuhn, 2010 on Austria males data, 1975-2005, IV estimates of 6.5%).

## 2.3 Channels

Oreopoulos, von Wachter, and Heisz (2012) find that the dynamic adjustment process is characterized by an increased mobility across employers and industries and improvements in average firm characteristics. Brunner and Kuhn (2010) find that workers who enter during a recession are initially assigned to lower quality jobs/tasks, and this initial assignment creates wage persistency because part of the human capital accumulated during the initial job is occupation or industry specific. They also find that mechanisms unrelated to productivity, such as downwardly rigid wage contracts, also play an important role in generating persistent wage differences across entry cohorts. Eventually, Kwon, Milgrom, and Hwang (2010) using Swedish data on white collar workers during the period 1970-1990 investigate the explanations of a potential lifetime loss. They find that those who enter the labour market during a crisis get promoted more slowly. Thus, their wage path is less upward sloping.

## 2.4 Studies on French data

In France, effects of downturns seem to be strong on employment in the short run. Between 1990 and 1994, a strong economic slowdown period in France, unemployment rate of young people (15-24) increased from 15.4% to 22.3% whereas the total unemployment rate went up from 8% to 10.8%. Ponthieux (1997) compares mean wage of young entrants of one year of potential experience and mean wage of all French employed in 1991 and 1995. She finds that mean wage of young entrants was 45% lower than mean wage in 1995 whereas it was 35% lower than the mean wage in 1991. Her results are years specific. Fondeur and Minni (2004) find also that both young employment and wages overreacted to crises in France during the 1980s and the 1990s. Yet, effects of business cycle seem to be stronger on employment than on wages.

Ananian and Calavrezo (2012) address the question of potential medium-term effects of entering the labor market in bad economic conditions (up to 5 years after entering into the labor market), for a specific period (1995-2002) and with administrative registers (the "panel DADS"). They find that young people who faced bad economic conditions at their entry into the labor market catch-up within 3 years with those who faced good economic conditions.
In our paper we focus on the first 15 years of potential experience. As far as we know, our paper provides the first contribution to the analysis of long-run effects of business cycle on labour market careers using French data.

# 3 Data and descriptive statistics

## 3.1 Data

### 3.1.1 Business cycle indicator

<figure><img src="image_2.png" /><figcaption>Figure 1: Unemployment rate of young entrants in the labour force, men and women (cohorts: 1982-2009, unemployment rate: 1983-2010)</figcaption></figure>

We use as indicator of economic conditions at entry the unemployment rate of young men/women (15-24 years old) the year following their school-leaving decision (see Figure 1). We do not use unemployment of the school-leaving year since leaving school occurs mainly during the second semester and, entry into the labour market usually occurs during the following Fall and Winter, see Coudin and Beffy (2007). Economic conditions in the year following the school leaving year therefore seem to be a more accurate indicator of the economic conditions at entry.

We focus on cohorts having left school after 1982. Before 1982, total unemployment as well as young entrants unemployment tendancially increased. We prefer to estimate our models on less trended indicators, see Figure 1. Indeed, we focus on scarring effects due to business cycles and not to structural evolutions (*i.e.* structural increase in unemployment between cohorts entering into the labour
<figure><img src="image_3.png" /><figcaption>Figure 2: Autocorrelation of our unemployment indicator</figcaption></figure>

market before and after the 1980s). Furthermore, in most of our regressions, we include year dummies, in order to control for a possible spurious correlation between our variables of interest and unemployment rate due to common temporal pattern.

France experienced 4 major increases in unemployment during our period of interest: 1983-1986, 1993-1999, 2003-2006 and since 2008. The youth unemployment rate varied dramatically between two successive years during certain subperiods, e.g. by more than 5 percentage points between 1992 and 1993, and between 1999 and 2000.

As other countries, France has high unemployment persistence, see Figure 2. Growth rate and unemployment do not exhibit exactly the same patterns although both are obviously correlated, because the productivity cycle in France is quite long. To better capture the situation faced by people entering the labour market, we therefore retain an indicator of the tightness of the latter. We therefore focus on scarring effects of leaving school and facing high unemployment rate, rather than facing negative or very low growth rate.
## 3.2 Labour Force Surveys

We use the French Labour Force Surveys, from 1990 to 2010.<fnref n="2" /> We mainly focus on French young people, with 1 to 15 years of potential experience, and who left school between 1982 and 2009. In this paper, leaving school corresponds to completing its studies or dropping out from school. We differ in this respect from other papers published on the scarring effect in that they consider the year when one gets her first paid job, and not when she leaves school. They usually retain this definition due to the use of administrative data, with no available information on school-leaving year. This provides an arguably very endogenous indicator of the year of entry. We have a better information as we know the school-leaving year of the person. The remaining source of potential endogeneity would be due to changes in school-leaving decisions according to the business cycle. We showed in a companion paper Gaini, Leduc, and Vicard (2012) that only few people remain longer at school during economic downturns and that these changes are not likely to bias our estimations.

Our main variables of interest are the employment status<fnref n="3" /> (employed versus non employed), the monthly wage in logarithm (not corrected by the number of worked hours) and the monthly earned income in logarithm. The earned income equals the monthly wage if the person is working and 0 otherwise.<fnref n="4" />

We begin with graphically comparing wages across cohorts and years as descriptive statistics. We therefore proceed to a normalization to adjust for the evolution of the mean wage. More precisely, we deflate wages by the ratio of the mean wage of the year on the mean wage in 2010.<fnref n="5" />

$$w_{it}^{n} = w_{it} \cdot \frac{\bar{w}_{2010}}{\bar{w}_{t}}$$

<footnote n="2">²Labour Force Surveys were carried out annually in March from 1990 to 2002. Since 2003 they are carried out quarterly. We reweight observations in order to have the same number of individuals each year, and we include year dummies in the different models, which take into account potential breaks in the data. Finally, LFS have a rotative panel design and we only retain the first observation for each interviewee in order to avoid intra-individual correlation.</footnote>

<footnote n="3">³Employment status in the French LFS is the employment status during a referenced week. We extrapolate this employment status to calculate the monthly earned income</footnote>

<footnote n="4">⁴When we focus on earned income, we impute missing wages using the hot-deck method. If not, we would over-weight people with no earned income and bias our estimations. Wages are missing because either the person did not report her wage or she is self-employed. Because earned income can be zero for unemployed people, we also do not use log(earned income), which is not defined, but log(earned income+1) instead.</footnote>

<footnote n="5">⁵Mean wages are computed on our population of interest, i.e. young men or women with 1 to 15 years of potential experience on the labour market.</footnote>
Finally, we need to correct the potential experience variable. Potential experience is computed as the difference between the current year and the school-leaving year. As illustrated in Appendix A.1 the size of a given school-leaving cohort was not the same in the raw data for different levels of potential experience. In the raw data, apprenticeship is considered as a "in studies" period in the 1983-1989 and 2003-2010 surveys whereas it is not in the 1990-2002 surveys. To deal with this, we implement the correction usually applied by the French National Institute of Statistics using the same convention in all surveys. We corrected data so that the school-leaving age takes into account the apprenticeship as a "in studies" period. After correction, the size of a given leaving cohort was approximately the same for different levels of potential experience (Appendix A.1).

## 3.3 Descriptive statistics

We compare employment, wage and earned income trajectories for cohorts entering the labour market in bad economic conditions and cohorts entering in good economic conditions. We firstly compare cohorts entering the labour market at successive years but with very different economic conditions. We then divide our cohort sample (cohorts 1982-2009) in three groups according to the economic conditions the year following graduation or departure from the academic system and we compare the two "extreme" groups: school-leavers when the 15-24 year-old unemployment rate is below 16% for men and school-leavers when it is above 18% for men, and below 20% and above 22% for women, see Figure 1. Finally, we compare cohorts facing persistent economic conditions, i.e. facing 5 years of persistent high or persistent low unemployment at entry.

### 3.3.1 1990-1991 ("good entry") vs 1992-1993 ("bad entry")

Figure 3 displays comparisons for cohorts 1990-1991 ("good entry") versus cohorts 1992-1993 ("bad entry")$^6$. In 1991 and 1992, the youth unemployment was historically low, around 15%. The year 1993 corresponds to an unexpected recession, with a drop of -0,7% of GDP, followed by a quick recovery, but with no decline in the unemployment rate. The unemployment rate remained above its 1991 level until 1999, see Figure 1.

In consequence to this economic environment, male 1990-1991 cohorts have a first year employment rate 8 percentage points higher than men cohorts 1992-1993,

<footnote>$^6$In this paper, standars errors are calculated as if the sample selection was on a simple random sampling</footnote>
whereas the corresponding difference is 5 percentage points for women. Despite
these huge differences, the gap between both cohorts vanishes after 3 years. Be-
tween 8 and 10 years of potential experience, the gap is reversed for men, and,
after 10 years, employment rates are quite similar.

As for wage, there is no visible gap, at short or medium terms. Selection effect
due to unemployment could however overcome a negative effect of the economic
condition for cohorts 1992-1993, at least for the three first years. Earned income
combines employment and wages gaps. Cohorts 1990-1991 have a higher earned
income during the first three years. For men, the gap is reversed between 8 and
10 years of labour market experience and there is no more gap after 10 years. For
women, the gap is reversed between 16 and 17 years of experience.
<figure><img src="image_4.png" /><figcaption>Figure 3: Generations: 1990-1991 ("good entry") vs 1992-1993 ("bad entry")</figcaption></figure>
3.3.2 1997-1998 ("bad entry") vs 1999-2000 ("good entry")

Figure 4 displays comparisons for cohorts 1997-1998 ("bad entry") versus cohorts
1999-2000 ("good entry"). Beginning in 1998, the French economy is booming:
the French growth rate reaches around 3.5% from 1999 to 2001, before a new
slow down takes place from 2002 on. As a consequence, cohorts who entered the
labour market in 1999-2000 have a first year employment rate higher than cohorts
who entered the labour market in 1997-1998 (8 percentage points for men, 10
percentage points for women). But this gap vanishes after 3 years, which is the
sign of a quick catch-up process. The 1999-2000 cohorts also earn a higher wage
than the 1997-1998 cohorts during their first year on the labour market, but this
wage gap vanishes after 4 years for men and after 2 years for women. Earned
income profiles display a similar pattern.
<figure><img src="image_5.png" /><figcaption>Figure 4: Generations: 1997-1998 ("bad entry") vs 1999-2000 ("good entry")</figcaption></figure>
### 3.3.3 "Lucky" vs "unlucky" cohorts of the sample

Until now, we focused on specific cohorts, who entered the labour market during successive years but with very different economic conditions: the problem with such comparisons is that these specific cohorts could be too specific. This section gives a more complete picture, comparing cohorts on the whole period 1982-2009. Figure 5 displays comparisons men/women for cohorts entering the labour market with an unemployment rate higher than 18%/22% ("bad economy") and with an unemployment rate lower than 16%/20% ("good economy"), see Figure 1.

Cohorts entering the labour market in a bad economy have a lower employment rate during the first 4 years. But the catch-up process is quickly completed. For men, from 5 to 12 years on the labour market, unlucky cohorts even have a greater employment rate than lucky ones. This could be easily explained by a business cycle effect: young entrants entering during economic downturns would face an economic boom when they have 8-10 years of potential experience (see figure 2). It is therefore crucial to control for current economic conditions.

There is no systematic difference concerning mean wages. Earned income profiles are therefore similar to employment ones, but differences between cohorts last a little bit longer for women (Figure 5, e and f). Looking at different percentiles of the wage distribution, there is no visible effect on wages for men. For women, there is a small negative effect at the bottom and the median of the wage distribution until 7/8 years of potential experience (Figure 5, g and h). Appendix A.3 displays additional figures, outlining that employment and wage levels 5, 10 and 15 years after school leaving are unrelated to the economic condition when leaving school. The correlation, if any, is positive between unemployment rate when leaving school and employment rate or mean wage after 5, 10 or 15 years.
<figure><img src="image_6.png" /><figcaption>Figure 5: Generations: 1982-2009 "Lucky" vs "unlucky"</figcaption></figure>
3.3.4 1992-1993 ("bad entry") vs 1999-2000 ("good entry")

Finally, we compare cohorts leaving school in 1992-1993 who faced a high unem-
ployment rate at entry and during the following 5/6 years (from 1992 to 1998) with
cohorts 1999-2000 who faced a low unemployment rate at entry and during the fol-
lowing 2/3 years (from 1999 to 2002), see Figure 6. Differences in employment rate,
mean wage and earned income until about 5 years of experience were expected as
we compare cohorts persistently facing different economic conditions during their
first years of experience. Interestingly, even for these cohorts we find no differences
in the long run. One exception is for the female employment rate, probably due to
cohort effects in terms of participation (positive trends in participation over time
and increase in education for cohorts 1999-2000).
<figure><img src="image_7.png" /><figcaption>Figure 6: Generations: 1992-1993 ("bad entry") vs 1999-2000 ("good entry")</figcaption></figure>
# 4 Econometric model

This section presents the econometric model and the main identification assumptions. The model investigates how the initial economic situation impacts on the long-run the labour market situation. The key variables of interest ($y_{c,t}$) are the employment rate$^7$, the monthly wage in logarithm and the monthly earned income in logarithm at a national level. We focus on national specifications because, on the contrary to the United States, regional unemployment rates evolve in France very similarly across regions. Thus a French regional model would not be well identified. Moroever, we do not have the information in the French LFS about the region in which young people were living at the end of their studies.

Our specification includes an interaction of the indicator of economic condition (the unemployment rate the year following the school-leaving year: $UR_c$) with the potential experience ($e$) which characterizes how the initial effect varies with time spent on the labour market (the catch-up process, namely $g(e)$). More precisely, we interact unemployment rate at entry and linear trends of potential experience, allowing for changes in slope at 3, 6, 9 and 12 years of experience.$^8$

$$y_{c,t} = \alpha + \omega_t + f(e) + g(e) \cdot UR_c + X_c \cdot \beta + u_{c,t}$$

$$u_{c,t} = \epsilon_c + \eta_{c,t}$$

$$e = t - c$$

$$e = 1, \dots, 15; c = 1982, \dots, 2009; t = 1990, \dots, 2010$$

$$\begin{aligned} f(e) = & \gamma_1 \cdot e + \gamma_2 \cdot (e-3) \cdot 1[e \ge 3] + \gamma_3 \cdot (e-6) \cdot 1[e \ge 6] \\ & + \gamma_4 \cdot (e-9) \cdot 1[e \ge 9] + \gamma_5 \cdot (e-12) \cdot 1[e \ge 12] \end{aligned} \quad (1)$$

$$\begin{aligned} g(e) = & \delta_0 + \delta_1 \cdot e + \delta_2 \cdot (e-3) \cdot 1[e \ge 3] + \delta_3 \cdot (e-6) \cdot 1[e \ge 6] \\ & + \delta_4 \cdot (e-9) \cdot 1[e \ge 9] + \delta_5 \cdot (e-12) \cdot 1[e \ge 12] \end{aligned}$$

We estimate equation 1 using OLS, on aggregated data at the entry cohort level and separately for men and women. Using an aggregated modelisation emphasizes the source of identification, which basically relies on inter-cohorts variations. We

<footnote>$^7$We also use logarithm of employment rate as dependent variable, it does not change our results.</footnote>

<footnote>$^8$In the literature, less flexible specifications are generally assumed, e.g. linear specification - $g(e) = e$ (Kahn, 2010). Oreopoulos, von Wachter, and Heisz (2012) who uses dummies for experience, is an exception. As Genda, Kondo, and Ohta (2010), we also estimated a model with three years grouped dummies control of potential experienced instead of linear trends with changes in slope. This specification does not change our results.</footnote>
use robust standard errors clustered by cohorts. We therefore authorize correla-
tions between the different observations of one cohort ($\epsilon_c$), in a more flexible way
than expressed in equation 1. We use the Bias Reduced Linearization method to
estimate standard errors since we just have 28 clusters (see Bell and McCaffrey,
2002).

We include a year fixed effects $\omega_t$ in order to control for the economic situation in the current year and for women participation rate increase. Note that this model implicitly assumes that only initial economic conditions can be persistent.

For identification purposes, it is necessary that $E(\epsilon_c|UR_c, e, \omega_t, X_c) = 0$. Therefore, the main identification assumption is that cohorts only differ by the economic conditions at entry into the labour market.<fnref n="9" /> Cohorts entering the labour market between 1985 and 1995 are increasingly qualified (a well-known phenomenon called "démocratisation scolaire" in French) so we also control for average "skill-level" of the cohort ($X_c$) with 6 variables.<fnref n="10" />

The parameters of interest are $\delta_0, \delta_1, \delta_2, \delta_3, \delta_4$ and $\delta_5$: they describe the persistence of the initial shock experienced by young people when they enter the labour market. We expect $\delta_0$ to be negative, reflecting the initial negative employment or wage effect of entering the labour market during a recession (corresponding to a high unemployment level). More precisely, as we regress employment rate between 1 and 15 years of experience on youth unemployment rate at 1 year of experience, $\delta_0$ non negative would indicate a very strong changes in the participation rate the first year after leaving-school. We expect $\delta_1$ to $\delta_5$ to be positive or zero, reflecting the potential catch-up process.

A selection effect could also occur if only the more productive workers leave school
during economic downturns. To explore this potential issue, we first instrumented
the unemployment rate when leaving school by the unemployment rate at 16 years
(note that the mandatory schooling age is 16 in France). Because the unem-
ployment rate when leaving school is crossed with a (piecewise linear) function of
potential experience in our regression, we have 6 potentially endogenous regres-
sors, that we indeed instrument by the unemployment rate at 16 years crossed
with the same (piecewise linear) function of potential experience. They provide
exogeneous intruments, but that are unfortunately weak.<fnref n="11" /> The F-stat of the six

<footnote n="9">⁹More precisely, the key identification hypothesis is that systematic differences between cohorts are not correlated with unemployment rate at the entry into the labour market.</footnote>

<footnote n="10">¹⁰More precisely, we include as control the share of young entrants without degree, with junior high school ("Brevet des collèges"), with basic vocational ("CAP" or "BEP"), with high school or advanced vocational ("Baccalauréat") or with some college ("Baccalauréat + 2 ans") and with university ("Diplôme supérieur").</footnote>

<footnote n="11">¹¹They also provide a very local estimation (comparable to a LATE - local average treatment</footnote>
first-stage equations are usually very low (under 5), and always lower than the usual threshold indicating weak instruments (10), for men as for women, so that we cannot use these instruments. This result is not surprising when one looks at the cyclicality of the unemployment rate (Figure 1). We also restrict our sample to young people who have left school between 16 and 18. <fnref n="12" /> In this case, the F-stat of the six first-stage equations are, as expected, greater than without selection on the school leaving age: between 6 and 11 for men, and between 10 and 15 for women (because the autocorrelation of the unemployment rate is higher for them, see Figure 2). The instruments remain weak, and, consequently, standard errors of our parameter of interest ($\delta_0$ to $\delta_5$) are very large. For these reasons, we do not show the IV estimates, which are available upon request from the authors.

In a companion paper (Gaini, Leduc, and Vicard, 2012), we also directly investigate this potential selection effect due to the endogeneity of the school leaving year to the business cycle. We find a negative significant but very weak effect of the unemployment rate on the probability of leaving school at a given age. A huge crisis, i.e. a 10 percentage points increase in the current young unemployment rate, entails a decrease in the probability to leave school between 0.6 percentage point (for a probability of leaving-school equals to about 20% at age 21) and 2.9 percentage points (for a probability of leaving-school equals to about 30% at age 23).

Finally, another crucial assumption of our econometric model is that the only persistent shock individuals face is the economic conditions at entry. Economic conditions at other moments of the career may have an immediate effect on employment or wage, controlled by the year dummies; but not a persistent effect. We could write a more general model where economic conditions one year and $\tau$ years after the end of the studies may have persistent effect on employment and wages (see equation 2). We tried to estimate such a model for $\tau = 4$ and $\tau = 7$, but the estimates are very imprecise (large standard errors) due to the fact that unemployment at entry into the labour market and 4 or 7 years after are strongly correlated (statistical multicolinearity).

$$y_{c,t} = \alpha + \omega_t + f(e) + g(e) \cdot UR_c^1 + h(e) \cdot UR_c^\tau + X_c \cdot \beta + u_{c,t} \quad (2) \\ e \ge \tau$$

<footnote>effect - in the evaluation literature), because the unemployment rate at 16 is a good predictor of the unemployment rate when leaving school for those young people who anticipate to leave school early, but a bad predictor for those who plan to stay a long-time at school.</footnote>

<footnote n="12">¹²Note however that this selection is potentially endogeneous to the business cycle when the school leaving decision is itself linked to the business cycle.</footnote>
# 5 Results

Table 1 and 2 display coefficient estimates for the regression (1) on men and women with alternatively employment rate, monthly wage and earned income as dependent variable.<fnref n="13" /> Because our coefficients of interest are difficult to interpret on their own, we also graphically illustrate initial entry conditions effects. More precisely, we graph gaps in employment, log wages and log earned income for a 1 percentage point gap in youth unemployment one year after leaving school, see Figures 7, 8, 9 for men and women. Same graphics are available in Appendix (see Figure 19) until 20 years of experience.

<footnote n="13">¹³We also run regressions on other outcomes to measure the quality of the jobs: having a permanent or a full-time contract and being a professional or a manager, see section 5.5.</footnote>
<table><caption>Table 1: OLS results on employment, monthly wage and earned income with 3-years grouped trends (main specification, men)</caption><thead><tr><th></th><th>(1)<br>Employment</th><th>(2)<br>Wage (log)</th><th>(3)<br>Earned income (log)</th></tr></thead><tbody><tr><td>15-24 Unemployment rate - UR(δ<sub>0</sub>)</td><td>-1.439***<br>(0.349)</td><td>-0.00892*<br>(0.00517)</td><td>-0.116**<br>(0.0462)</td></tr><tr><td>UR * Exp. 1 to 15 (δ<sub>1</sub>)</td><td>0.475***<br>(0.147)</td><td>0.00320<br>(0.00231)</td><td>0.0369*<br>(0.0191)</td></tr><tr><td>UR * Exp. 3 to 15 (δ<sub>2</sub>)</td><td>-0.474**<br>(0.215)</td><td>-0.00346<br>(0.00306)</td><td>-0.0427*<br>(0.0237)</td></tr><tr><td>UR * Exp. 6 to 15 (δ<sub>3</sub>)</td><td>0.0534<br>(0.150)</td><td>-0.000841<br>(0.00192)</td><td>0.0177<br>(0.0129)</td></tr><tr><td>UR * Exp. 9 to 15 (δ<sub>4</sub>)</td><td>-0.0960<br>(0.173)</td><td>0.00520**<br>(0.00243)</td><td>-0.00390<br>(0.0165)</td></tr><tr><td>UR * Exp. 12 to 15 (δ<sub>5</sub>)</td><td>0.0677<br>(0.102)</td><td>-0.00339**<br>(0.00145)</td><td>-0.00255<br>(0.0112)</td></tr><tr><td>Education controls</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Experience controls</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Year dummies</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>R<sup>2</sup></td><td>0.8823</td><td>0.9142</td><td>0.9135</td></tr><tr><td>Observations</td><td>286</td><td>286</td><td>286</td></tr></tbody></table>

Standard errors in parentheses (clustered at the cohort level, with a bias-reduced linearization to account for the small number of clusters)

<footnote>* p < 0.10, ** p < 0.05, *** p < 0.01</footnote>
<table><caption>Table 2: OLS results on employment, monthly wage and earned income with 3-years grouped trends (main specification, women)</caption><thead><tr><th></th><th>(1)<br>Employment</th><th>(2)<br>Wage (log)</th><th>(3)<br>Earned income (log)</th></tr></thead><tbody><tr><td>15-24 Unemployment rate - UR(δ<sub>0</sub>)</td><td>-2.081<sup>***</sup><br>(0.387)</td><td>-0.0110<br>(0.00723)</td><td>-0.154<sup>***</sup><br>(0.0272)</td></tr><tr><td>UR * Exp. 1 to 15 (δ<sub>1</sub>)</td><td>0.728<sup>***</sup><br>(0.185)</td><td>0.00191<br>(0.00273)</td><td>0.0526<sup>***</sup><br>(0.0130)</td></tr><tr><td>UR * Exp. 3 to 15 (δ<sub>2</sub>)</td><td>-0.678<sup>**</sup><br>(0.264)</td><td>-0.0000437<br>(0.00413)</td><td>-0.0471<sup>**</sup><br>(0.0193)</td></tr><tr><td>UR * Exp. 6 to 15 (δ<sub>3</sub>)</td><td>-0.246<br>(0.185)</td><td>-0.00316<br>(0.00298)</td><td>-0.0210<br>(0.0147)</td></tr><tr><td>UR * Exp. 9 to 15 (δ<sub>4</sub>)</td><td>0.432<sup>***</sup><br>(0.123)</td><td>0.000467<br>(0.00233)</td><td>0.0314<sup>***</sup><br>(0.00941)</td></tr><tr><td>UR * Exp. 12 to 15 (δ<sub>5</sub>)</td><td>-0.0897<br>(0.179)</td><td>0.00469<sup>*</sup><br>(0.00255)</td><td>-0.00210<br>(0.0128)</td></tr><tr><td>Education controls</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Experience controls</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Year dummies</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>R<sup>2</sup></td><td>0.7760</td><td>0.7966</td><td>0.7840</td></tr><tr><td>Observations</td><td>286</td><td>286</td><td>286</td></tr></tbody></table>

Standard errors in parentheses (clustered at the cohort level, with a bias-reduced linearization to account for the small number of clusters)

* p < 0.10, ** p < 0.05, *** p < 0.01
## 5.1 On employment

Figure 7 displays the employment rate profile for a 1 percentage point difference in youth unemployment. We find that a 1 percentage point increase in youth unemployment entails a decrease in the probability of being employed by about -1.0 percentage point the first year for men and by -1.3 percentage points for women. But the gap quickly decreases and it vanishes within 3 years of potential experience, see Figure 7. For women, we find a positive effect after 12 years of potential experience. This latter could be due to the smaller number of cohorts on which we run the estimation, i.e. 20 cohorts between 1 to 8 years of potential experience vs. 12 to 16 cohorts between 12 to 15 years of potential experience, see Figure A.2.

<figure><img src="image_8.png" /><figcaption>Figure 7: Employment probability gap for a 1 percentage point difference in unemployment - spline specification (generations: 1982-2009; years: 1990-2010)</figcaption></figure>

## 5.2 On monthly wage

Figure 8 displays the log wage gap profile for a 1 percentage point difference in youth unemployment. Until 10 years of potential experience, there is no gap for men in monthly wages due to differences in initial unemployment rate. After 10 years we find a positive and statistically significant gap of about 1% (more exactly 0.01 log point) in favor of people having higher initial unemployment rate. Yet, we have fewer observations for higher potential experiences. For women there is a negative gap until 5 years of potential experience. An increase of 1 percentage point in unemployment entails a decrease in wage at entry of about 1%. This negative effect seems to be a little bit persistent even if not statistically significant. Note
that selection in employment could entail an under-estimation of effects on wages
if only the more productive get employed during economic downturns.<fnref n="14" />

<figure><img src="image_9.png" /><figcaption>Figure 8: Wage percentage gap for a 1 percentage point difference in unemployment - spline specification (generations: 1982-2009; years: 1990-2010)</figcaption></figure>

5.3 On earned income

Figure 9 displays the log earned income gap profile for a 1 percentage point dif-
ference in youth unemployment. A 1 percentage point increase in unemployment
at the entry into the labour market entails a decrease in monthly earned income
the first year of about -7% for men and -10% for women. This represents about
48/69 euros per month for men/women the first year and about 26/39 euros per
month for men/women the second year. But catch-up rapidly occurs and there is
no difference anymore after 3 years of potential experience. During these 3 years,
the average earned income loss for each unemployment point is about 890 euros
for men and 1300 for women. We find again a positive effect for highest levels of
experience.

<footnote n="14">¹⁴We do not correct for the selection in employment due to the lack of good instruments. Anyway, as negative effects on employment vanish in 3 years, selection effects are not likely to bias our results of no persistent effect on wage.</footnote>
<figure><img src="image_10.png" /><figcaption>Figure 9: Earned income percentage gap for a 1 percentage point difference in unemployment - spline specification (generations: 1982-2009; years: 1990-2010)</figcaption></figure>

## 5.4 Relaxing hypothesis of homogenous effect by education level

We estimate our main model on two subsamples depending on level education: low education level vs high education level.<fnref n="15" /> Figures 10, 11, 12 display results. We find also a rapid catch-up and no long-term gap due to differences in initial unemployment rate, whatever the education level is. In the short run, high-educated women seem to be more affected than the other groups by adverse shocks on employment and wages.

<footnote n="15">¹⁵To be accurate, low education level corresponds to no degree, junior high school degree or basic vocational degree and high education level corresponds to some college degree or university degree.</footnote>
<figure><img src="image_11.png" /><figcaption>Figure 10: Effect of a 1 percentage point difference in unemployment on employment rate - different education level subsamples (generations: 1982-2009; years: 1990-2010)</figcaption></figure>
<figure><img src="image_12.png" /><figcaption>Figure 11: Effect of a 1 percentage point difference in unemployment on wage - different education level subsamples (generations: 1982-2009; years: 1990-2010)</figcaption></figure>
<figure><img src="image_13.png" /><figcaption>Figure 12: Effect of a 1 percentage point difference in unemployment on earned income - different education level subsamples (generations: 1982-2009; years: 1990-2010)</figcaption></figure>
5.5 On other outcomes

We run additional regressions to further investigate the effects of leaving school
in a tough labour market. We consider both the probabilities to have a part-
time contract and to have a permanent one, conditionally on being employed, see
graphical results in Figures 13.

We find that men are not more likely to have a part-time contract if they face
adverse conditions at entry. For women, there is a positive effect of about 0.8
percentage point for a 1 percentage point increase in youth unemployment. This
effect vanishes within 5 years of experience. These results are consistent with
a wage penalty only for women. Yet, neither the effect on wages nor the effect
on part-time contracts persists beyond the first 5 years of potential experience.
Concerning permanent contracts, we find that a 1 percentage point increase in
youth unemployment entails a decrease in the probability of having a permanent
contract – conditionally on being employed – of 1.3 percentage points for men
and 0.9 for women. These gaps vanish after 3 years. Bad economic conditions
therefore affect the quality of the jobs during the first years on the labour market.
It seems that these effects are only temporary. This entails that even workers
facing unemployment spells or being under-employed at entry succeed in finding
full-time permanent contracts after few years. Finally, we do not find significant
effects on the probability to be a manager or a professional<fnref n="16" />, see Figure 13 e and f.

<footnote n="16">¹⁶Manager or Professional is "cadre ou profession intellectuelle superieure" or CS=3 in French.</footnote>
<figure><img src="image_14.png" /><figcaption>Figure 13: Effect of a 1 percentage point difference in unemployment on other outcomes - spline specification (generations: 1982-2009; years: 1990-2010)</figcaption></figure>
# 6 Robustness Checks

We run robustness checks for the three main outcomes: employment rate, log wages and log earned income.

## 6.1 Controlling for heterogenous effects of current economic conditions by level of potential experience

Specification 1 can be seen too constrained, since it implies the same effect at all level of experience for current economic conditions. We now estimate a more flexible specification by introducing in our main specification an effect of current economic conditions which depends on the potential experience. More precisely, we replace year dummies by an indicator of current economic conditions (15-24 unemployment rate<fnref n="17" />) and its interaction with potential experience allowing for change in slope at 3, 6, 9 and 12 years of potential experience ($h(e)$ function). Our specification becomes the following:

$$y_{c,t} = \alpha + h(e) \cdot UR_t + f(e) + g(e) \cdot UR_c + X_c \cdot \beta + u_{c,t} \quad (3)$$

Current unemployment rate and year following the school-leaving year unemployment rate are highly correlated for the first years of potential experience because of a high-level of unemployment persistence. Standard-errors are therefore bigger than those in our main specification. We estimate the model for experience between 1 and 15 years and we also graphically represent employment, wage and earned income catch-up from the second potential experience year (see Figure 14). We find no effect on the long-run of unemployment rate the year following the school leaving-year on our interest outcomes. Note that positive effects for the highest levels of experience on wage for women and on employment rate for men are less pronounced. These positive effects in our main specification were probably due to imperfect control of current economic conditions.

<footnote n="17">¹⁷We obtain same results with overall unemployment rate.</footnote>
<figure><img src="image_15.png" /><figcaption>Figure 14: Effect of a 1 percentage point difference in unemployment - current UR control (generations: 1982-2009; years: 1990-2010)</figcaption></figure>
## 6.2 Controlling or not for cohort characteristics: education levels and cohort size

We show that our main results are robust to the exclusion of education and cohort size controls as covariates (tables 3, 5, 7 for men and 4, 6, 8 for women, respectively for employment, wage and earned income in Appendix A.4). More precisely, the main specification includes in the regression the shares of the cohorts having no degree, with junior high school degree, with basic vocational degree, with high school or advanced vocational ("Baccalauréat") degree, with some college degree and with university degree. The education controls are significant, but their exclusion do not change the significativity or magnitude of our coefficients of interest. We also control for the cohort size that turns to be not significant in any of our regressions.

## 6.3 Other robustness checks

In this section, we describe the other robustness checks that we performed. Due to space constraints, we do not report here the regression results. They are available upon request from the authors.

**Sensitivity to the period of observation** First we performed the estimation on different subperiods to check the sensitivity of our results to the period analyzed. We restricted the sample to cohorts entering the labour market between 1982 and 1995 to run the regression on a balanced panel (all cohorts being observed between 8 and 15 years of experience). We also restricted the sample to all cohorts entering between 1990 and 2009 to look at a period following the "démocratisation scolaire". We also performed an estimation of the scarring effect using a longer period of time - 20 years instead of 15 years (see appendix A.5 for the results), although results may be less accurate because of fewer observations to estimate the scarring effect from 15 to 20 years of potential experience (see appendix A.2). Our results of no long term scarring effects remain.

**Alternative indicator for the business cycle** In our main model, we focus on the effects of facing bad economic conditions at entry. Yet, business cycle is viscous and we want to check whether cohorts facing repeated bad economic conditions, i.e. persistent bad/good economic conditions during their first years of experience, do not suffer from persistent scarring effects. Descriptive statistics comparing cohorts 1992-1993 leaving school at the beginning of a persistent downturn and cohorts
1999-2000 leaving school at the beginning of an economic boom of 3 years do not reveal any persistent scarring effect, see Figure 6. To go beyond these descriptive statistics, we run regressions with an alternative indicator for the business cycle taking into account economic conditions during the first years of experience: the unemployment level during the first three years or during the first five years on the labour market (instead of the first year only). We still do not find any scarring effect. We did not use GDP as indicator for the business cycle because it does not precisely reflect the economic conditions on the labour market (e.g. from 1994 to 1998, the unemployment rate remains at a high level, although the GDP growth rate is back to its level before the 1993 crisis).

# 7 Discussion and conclusion

The main finding of this paper is that leaving school in a tough labour market in France has no long-term effect on the labour market performance, whatever the variable considered: employment rate, wage, earned income, proportion of part-time or temporary workers, or proportion of managers and professionals. Workers seem to be able to overcome the short-run adverse shocks in terms of employment, wage or job quality. Furthermore, the catch-up process is completed quite quickly. After 3 years, there is no more difference in labour market performance between different cohorts whatever their initial labour market conditions and the dead-weight loss in terms of earnings is relatively small. French young people therefore seem to manage to overcome adverse shocks more quickly than young people in other countries. In this section, we discuss the theoretical implications of these results and explore some potential explanations to the French pattern.

As noted earlier in the introduction, economic theory suggests two main channels that could entail a persistence of the adverse economic shock at the entry: signal effect theory and human capital theory. Our result of an absence of a scarring effect suggests that neither of these two channels plays a role during crisis.

First, focusing on signal effect theory, our results suggest that employers probably do not use previous unemployment spells as a screening device in their hiring process. Eriksson and Rooth (2011) show with a field experiment in the Swedish labor market that being unemployed immediately after graduation or between two previous jobs has no negative effect on contemporary job search. They also find a clear positive effect of the labor market experience. They conclude that "recruiting employers care more about the job applicants' positive characteristics (i.e. labor market experience) than their negative characteristics (i.e. history of unemployment)". Moreover, being unemployed in a crisis period would send a less
negative signal to employers than being unemployed during an economic boom. As a lot of young people are in the same situation, the signal about "abilities" is potentially noisier. Employers may rely less on it in the hiring process and more on diploma signal for example. In this respect, it seems that facing periods of unemployment during economic downturns is not stigmatizing for young entrants (see also Biewen and Steffes, 2010).

Yet, even if employers are not stigmatizing young people with unemployment spells, entrants facing bad economic conditions could be penalized (at least as fas as wage is concerned) because of lower real experience. The human capital theory suggests that there are both returns to education and to experience. Skills accumulated by people facing a crisis during their early career may be lower than skills of people facing an economic boom for two reasons: skills could deteriorate during a spell of non-employment and people do not accumulate real experience during unemployment spells. Yet, at the beginning of the career, entrants' skills are mainly general skills provided by education which are less likely to deteriorate during a spell of non-employment. Moreover, it could be the duration of the non-employment spell and not being unemployed that really matters. It is well-documented that entrants into the labour market have a higher number of unemployment spells but that they are generally shorter than for other workers. If non-employment spells are quite short, the difference in real experience would not be too large between entrants facing good and bad economic conditions. That could explain the no wage penalty for cohorts having more non-employment spells. Finally, at the beginning of the career, the main determinants of wage could be on one hand education and on the other hand age or potential experience and not the experience accumulated while working.

Furthermore, unemployment rates are high in France even during economic booms. This reinforces the statement of unemployment as a noisy signal for ability during economic downturns. The surplus of unemployment could hit quite randomly young entrants conditionally to their educational attainment. In France the catch-up in terms of employment is as quick as in other countries while it is much quicker in terms of wages: entrants would be more penalized in terms of employment but when they get a job they would not be penalized in terms of wage. The high level of young people paid at the minimum wage in France (35% of the 15-24, see Demailly, 2009) may also explain this difference compared to other countries. Lowering wages of a large part of new entrants is thus not legally possible and this may partly explain why we found no effect on wages. It is worth noting that wage inequalities are lower in France than in the US. Differences between cohorts entering the labour market in contrasted economic conditions would be therefore structurally less pronounced in France. Finally and consistently with our findings, Royer (2012) shows that earning losses for displaced workers between 1995 and
1999 are smaller in France than in the US and that negative effects are stronger on employment than on wages.
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# A Appendix

## A.1 Correction of the school leaving cohorts (Men example)

<figure><img src="image_16.png" /><figcaption>Figure 16: Size of school leaving cohorts by potential experience (after correction)</figcaption></figure>

<figure><img src="image_17.png" /></figure>
## A.2 Number of observations by cohort and potential experience

<figure><img src="image_18.png" /><figcaption>Figure 17: Number of cohorts observed for each potential experience (men and women)</figcaption></figure>
A.3 Mean employment rate and wage by entry conditions, 5, 10 and 15 years after labour market entry

<figure><img src="image_19.png" /><figcaption>Figure 18: Mean employment rate and wage by entry conditions, 5, 10 and 15 years after labour market entry</figcaption></figure>
## A.4 Results of controlling by education levels and cohort size

<table><caption>Table 3: Cohort control variable (education and cohort size): men employment</caption><thead><tr><th></th><th>(1)<br>Main specif.</th><th>(2)<br>W/o education</th><th>(3)<br>With cohort size</th></tr></thead><tbody><tr><td>15-24 Unemployment rate - UR(δ<sub>0</sub>)</td><td>-1.439***<br>(0.349)</td><td>-1.438***<br>(0.342)</td><td>-1.440***<br>(0.350)</td></tr><tr><td>UR * Exp. 1 to 15 (δ<sub>1</sub>)</td><td>0.475***<br>(0.147)</td><td>0.495***<br>(0.139)</td><td>0.475***<br>(0.147)</td></tr><tr><td>UR * Exp. 3 to 15 (δ<sub>2</sub>)</td><td>-0.474**<br>(0.215)</td><td>-0.476**<br>(0.208)</td><td>-0.474**<br>(0.215)</td></tr><tr><td>UR * Exp. 6 to 15 (δ<sub>3</sub>)</td><td>0.0534<br>(0.150)</td><td>0.00745<br>(0.154)</td><td>0.0536<br>(0.151)</td></tr><tr><td>UR * Exp. 9 to 15 (δ<sub>4</sub>)</td><td>-0.0960<br>(0.173)</td><td>-0.0628<br>(0.174)</td><td>-0.0964<br>(0.174)</td></tr><tr><td>UR * Exp. 12 to 15 (δ<sub>5</sub>)</td><td>0.0677<br>(0.102)</td><td>0.0825<br>(0.106)</td><td>0.0675<br>(0.102)</td></tr><tr><td>University</td><td>70.99***<br>(23.98)</td><td></td><td>71.74***<br>(27.17)</td></tr><tr><td>Some college</td><td>47.41**<br>(23.27)</td><td></td><td>48.58**<br>(23.88)</td></tr><tr><td>High school / Advanced vocational</td><td>30.64*<br>(18.49)</td><td></td><td>32.41<br>(28.65)</td></tr><tr><td>Basic vocational</td><td>64.11**<br>(27.90)</td><td></td><td>65.70**<br>(31.94)</td></tr><tr><td>Junior high school</td><td>82.31**<br>(37.59)</td><td></td><td>83.89*<br>(47.39)</td></tr><tr><td>Cohort size</td><td></td><td></td><td>-0.00000152<br>(0.0000197)</td></tr><tr><td>Experience controls</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Year dummies</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>R<sup>2</sup></td><td>0.8823</td><td>0.8792</td><td>0.8823</td></tr><tr><td>Observations</td><td>286</td><td>286</td><td>286</td></tr></tbody></table>

Standard errors in parentheses (clustered at the cohort level, with a bias-reduced linearization to account for the small number of clusters)

<footnote>* *p* < 0.10, ** *p* < 0.05, *** *p* < 0.01</footnote>
<table><caption>Table 4: Cohort control variable (education and cohort size): women employment</caption><thead><tr><th></th><th>(1)<br>Main specif.</th><th>(2)<br>W/o education</th><th>(3)<br>With cohort size</th></tr></thead><tbody><tr><td>15-24 Unemployment rate - UR(δ<sub>0</sub>)</td><td>-2.081<sup>***</sup><br>(0.387)</td><td>-2.065<sup>***</sup><br>(0.361)</td><td>-2.104<sup>***</sup><br>(0.386)</td></tr><tr><td>UR * Exp. 1 to 15 (δ<sub>1</sub>)</td><td>0.728<sup>***</sup><br>(0.185)</td><td>0.716<sup>***</sup><br>(0.186)</td><td>0.725<sup>***</sup><br>(0.185)</td></tr><tr><td>UR * Exp. 3 to 15 (δ<sub>2</sub>)</td><td>-0.678<sup>**</sup><br>(0.264)</td><td>-0.665<sup>**</sup><br>(0.269)</td><td>-0.675<sup>**</sup><br>(0.264)</td></tr><tr><td>UR * Exp. 6 to 15 (δ<sub>3</sub>)</td><td>-0.246<br>(0.185)</td><td>-0.236<br>(0.183)</td><td>-0.241<br>(0.185)</td></tr><tr><td>UR * Exp. 9 to 15 (δ<sub>4</sub>)</td><td>0.432<sup>***</sup><br>(0.123)</td><td>0.394<sup>***</sup><br>(0.132)</td><td>0.437<sup>***</sup><br>(0.124)</td></tr><tr><td>UR * Exp. 12 to 15 (δ<sub>5</sub>)</td><td>-0.0897<br>(0.179)</td><td>-0.0717<br>(0.186)</td><td>-0.101<br>(0.178)</td></tr><tr><td>University</td><td>-25.05<br>(30.49)</td><td></td><td>-4.896<br>(36.94)</td></tr><tr><td>Some college</td><td>-28.71<br>(29.42)</td><td></td><td>-26.60<br>(33.84)</td></tr><tr><td>High school / Advanced vocational</td><td>-47.54<sup>*</sup><br>(26.37)</td><td></td><td>-35.54<br>(30.20)</td></tr><tr><td>Basic vocational</td><td>-42.05<br>(36.05)</td><td></td><td>-38.01<br>(42.56)</td></tr><tr><td>Junior high school</td><td>-31.12<br>(42.77)</td><td></td><td>-21.18<br>(46.59)</td></tr><tr><td>Cohort size</td><td></td><td></td><td>-0.0000245<br>(0.0000224)</td></tr><tr><td>Experience controls</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Year dummies</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>R<sup>2</sup></td><td>0.7760</td><td>0.7725</td><td>0.7773</td></tr><tr><td>Observations</td><td>286</td><td>286</td><td>286</td></tr></tbody></table>

Standard errors in parentheses (clustered at the cohort level, with a bias-reduced linearization to account for the small number of clusters)

<footnote>* p < 0.10, ** p < 0.05, *** p < 0.01</footnote>
<table><caption>Table 5: Cohort control variable (education and cohort size): men wage</caption><thead><tr><th></th><th>(1)<br>Main specif.</th><th>(2)<br>W/o education</th><th>(3)<br>With cohort size</th></tr></thead><tbody><tr><td>15-24 Unemployment rate - UR(δ<sub>0</sub>)</td><td>-0.00892*<br>(0.00517)</td><td>-0.00439<br>(0.00577)</td><td>-0.00890*<br>(0.00522)</td></tr><tr><td>UR * Exp. 1 to 15 (δ<sub>1</sub>)</td><td>0.00320<br>(0.00231)</td><td>0.00221<br>(0.00263)</td><td>0.00318<br>(0.00234)</td></tr><tr><td>UR * Exp. 3 to 15 (δ<sub>2</sub>)</td><td>-0.00346<br>(0.00306)</td><td>-0.00296<br>(0.00334)</td><td>-0.00344<br>(0.00309)</td></tr><tr><td>UR * Exp. 6 to 15 (δ<sub>3</sub>)</td><td>-0.000841<br>(0.00192)</td><td>-0.000612<br>(0.00184)</td><td>-0.000855<br>(0.00193)</td></tr><tr><td>UR * Exp. 9 to 15 (δ<sub>4</sub>)</td><td>0.00520**<br>(0.00243)</td><td>0.00501**<br>(0.00244)</td><td>0.00522**<br>(0.00243)</td></tr><tr><td>UR * Exp. 12 to 15 (δ<sub>5</sub>)</td><td>-0.00339**<br>(0.00145)</td><td>-0.00304**<br>(0.00147)</td><td>-0.00338**<br>(0.00145)</td></tr><tr><td>University</td><td>0.738<br>(0.448)</td><td></td><td>0.691<br>(0.489)</td></tr><tr><td>Some college</td><td>-0.647**<br>(0.325)</td><td></td><td>-0.720*<br>(0.381)</td></tr><tr><td>High school / Advanced vocational</td><td>0.0261<br>(0.392)</td><td></td><td>-0.0848<br>(0.539)</td></tr><tr><td>Basic vocational</td><td>0.0681<br>(0.478)</td><td></td><td>-0.0311<br>(0.579)</td></tr><tr><td>Junior high school</td><td>-0.850*<br>(0.492)</td><td></td><td>-0.949<br>(0.582)</td></tr><tr><td>Cohort size</td><td></td><td></td><td>9.48e-08<br>(0.000000195)</td></tr><tr><td>Experience controls</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Year dummies</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>R<sup>2</sup></td><td>0.9142</td><td>0.9092</td><td>0.9142</td></tr><tr><td>Observations</td><td>286</td><td>286</td><td>286</td></tr></tbody></table>

Standard errors in parentheses (clustered at the cohort level, with a bias-reduced linearization to account for the small number of clusters)

<footnote>* *p* < 0.10, ** *p* < 0.05, *** *p* < 0.01</footnote>
<table><caption>Table 6: Cohort control variable (education and cohort size): women wage</caption><thead><tr><th></th><th>(1)<br>Main specif.</th><th>(2)<br>W/o education</th><th>(3)<br>With cohort size</th></tr></thead><tbody><tr><td>15-24 Unemployment rate - UR(δ<sub>0</sub>)</td><td>-0.0110<br>(0.00723)</td><td>-0.00988<br>(0.00687)</td><td>-0.0109<br>(0.00738)</td></tr><tr><td>UR * Exp. 1 to 15 (δ<sub>1</sub>)</td><td>0.00191<br>(0.00273)</td><td>0.00198<br>(0.00277)</td><td>0.00191<br>(0.00273)</td></tr><tr><td>UR * Exp. 3 to 15 (δ<sub>2</sub>)</td><td>-0.0000437<br>(0.00413)</td><td>-0.000173<br>(0.00411)</td><td>-0.0000457<br>(0.00413)</td></tr><tr><td>UR * Exp. 6 to 15 (δ<sub>3</sub>)</td><td>-0.00316<br>(0.00298)</td><td>-0.00316<br>(0.00295)</td><td>-0.00317<br>(0.00300)</td></tr><tr><td>UR * Exp. 9 to 15 (δ<sub>4</sub>)</td><td>0.000467<br>(0.00233)</td><td>0.000636<br>(0.00234)</td><td>0.000464<br>(0.00231)</td></tr><tr><td>UR * Exp. 12 to 15 (δ<sub>5</sub>)</td><td>0.00469*<br>(0.00255)</td><td>0.00460*<br>(0.00253)</td><td>0.00469*<br>(0.00255)</td></tr><tr><td>University</td><td>0.0526<br>(0.361)</td><td></td><td>0.0404<br>(0.525)</td></tr><tr><td>Some college</td><td>-0.356<br>(0.361)</td><td></td><td>-0.358<br>(0.373)</td></tr><tr><td>High school / Advanced vocational</td><td>-0.131<br>(0.336)</td><td></td><td>-0.138<br>(0.405)</td></tr><tr><td>Basic vocational</td><td>-0.380<br>(0.468)</td><td></td><td>-0.382<br>(0.497)</td></tr><tr><td>Junior high school</td><td>0.0405<br>(0.507)</td><td></td><td>0.0345<br>(0.568)</td></tr><tr><td>Cohort size</td><td></td><td></td><td>1.48e-08<br>(0.000000308)</td></tr><tr><td>Experience controls</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Year dummies</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>R<sup>2</sup></td><td>0.7966</td><td>0.7942</td><td>0.7966</td></tr><tr><td>Observations</td><td>286</td><td>286</td><td>286</td></tr></tbody></table>

Standard errors in parentheses (clustered at the cohort level, with a bias-reduced linearization to account for the small number of clusters)

<footnote>* p < 0.10, ** p < 0.05, *** p < 0.01</footnote>
<table><caption>Table 7: Cohort control variable (education and cohort size): men earned income</caption><thead><tr><th></th><th>(1)<br>Main specif.</th><th>(2)<br>W/o education</th><th>(3)<br>With cohort size</th></tr></thead><tbody><tr><td>15-24 Unemployment rate - UR(δ<sub>0</sub>)</td><td>-0.116**<br>(0.0462)</td><td>-0.0865<br>(0.0558)</td><td>-0.116**<br>(0.0463)</td></tr><tr><td>UR * Exp. 1 to 15 (δ<sub>1</sub>)</td><td>0.0369*<br>(0.0191)</td><td>0.0327<br>(0.0200)</td><td>0.0369*<br>(0.0192)</td></tr><tr><td>UR * Exp. 3 to 15 (δ<sub>2</sub>)</td><td>-0.0427*<br>(0.0237)</td><td>-0.0427*<br>(0.0232)</td><td>-0.0426*<br>(0.0238)</td></tr><tr><td>UR * Exp. 6 to 15 (δ<sub>3</sub>)</td><td>0.0177<br>(0.0129)</td><td>0.0158<br>(0.0144)</td><td>0.0177<br>(0.0130)</td></tr><tr><td>UR * Exp. 9 to 15 (δ<sub>4</sub>)</td><td>-0.00390<br>(0.0165)</td><td>-0.00247<br>(0.0176)</td><td>-0.00386<br>(0.0166)</td></tr><tr><td>UR * Exp. 12 to 15 (δ<sub>5</sub>)</td><td>-0.00255<br>(0.0112)</td><td>0.00382<br>(0.00961)</td><td>-0.00253<br>(0.0112)</td></tr><tr><td>University</td><td>7.356***<br>(2.506)</td><td></td><td>7.289***<br>(2.320)</td></tr><tr><td>Some college</td><td>-0.380<br>(2.045)</td><td></td><td>-0.483<br>(2.287)</td></tr><tr><td>High school / Advanced vocational</td><td>1.441<br>(2.269)</td><td></td><td>1.284<br>(2.305)</td></tr><tr><td>Basic vocational</td><td>5.229*<br>(3.027)</td><td></td><td>5.090*<br>(2.862)</td></tr><tr><td>Junior high school</td><td>7.867*<br>(4.252)</td><td></td><td>7.728*<br>(4.277)</td></tr><tr><td>Cohort size</td><td></td><td></td><td>0.000000134<br>(0.00000168)</td></tr><tr><td>Experience controls</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Year dummies</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>R<sup>2</sup></td><td>0.9135</td><td>0.9009</td><td>0.9135</td></tr><tr><td>Observations</td><td>286</td><td>286</td><td>286</td></tr></tbody></table>

Standard errors in parentheses (clustered at the cohort level, with a bias-reduced linearization to account for the small number of clusters)

<footnote>* *p* < 0.10, ** *p* < 0.05, *** *p* < 0.01</footnote>
<table><caption>Table 8: Cohort control variable (education and cohort size): women earned in-come</caption><thead><tr><th></th><th>(1)<br>Main specif.</th><th>(2)<br>W/o education</th><th>(3)<br>With cohort size</th></tr></thead><tbody><tr><td>15-24 Unemployment rate - UR(δ<sub>0</sub>)</td><td>-0.154***<br>(0.0272)</td><td>-0.150***<br>(0.0245)</td><td>-0.156***<br>(0.0273)</td></tr><tr><td>UR * Exp. 1 to 15 (δ<sub>1</sub>)</td><td>0.0526***<br>(0.0130)</td><td>0.0520***<br>(0.0129)</td><td>0.0524***<br>(0.0130)</td></tr><tr><td>UR * Exp. 3 to 15 (δ<sub>2</sub>)</td><td>-0.0471**<br>(0.0193)</td><td>-0.0471**<br>(0.0196)</td><td>-0.0469**<br>(0.0194)</td></tr><tr><td>UR * Exp. 6 to 15 (δ<sub>3</sub>)</td><td>-0.0210<br>(0.0147)</td><td>-0.0204<br>(0.0147)</td><td>-0.0207<br>(0.0147)</td></tr><tr><td>UR * Exp. 9 to 15 (δ<sub>4</sub>)</td><td>0.0314***<br>(0.00941)</td><td>0.0308***<br>(0.00970)</td><td>0.0318***<br>(0.00946)</td></tr><tr><td>UR * Exp. 12 to 15 (δ<sub>5</sub>)</td><td>-0.00210<br>(0.0128)</td><td>-0.00166<br>(0.0133)</td><td>-0.00281<br>(0.0129)</td></tr><tr><td>University</td><td>-1.752<br>(2.292)</td><td></td><td>-0.499<br>(2.633)</td></tr><tr><td>Some college</td><td>-1.898<br>(2.104)</td><td></td><td>-1.766<br>(2.387)</td></tr><tr><td>High school / Advanced vocational</td><td>-3.184*<br>(1.823)</td><td></td><td>-2.437<br>(2.082)</td></tr><tr><td>Basic vocational</td><td>-3.370<br>(2.551)</td><td></td><td>-3.118<br>(2.960)</td></tr><tr><td>Junior high school</td><td>-2.104<br>(3.007)</td><td></td><td>-1.486<br>(3.248)</td></tr><tr><td>Cohort size</td><td></td><td></td><td>-0.00000152<br>(0.00000153)</td></tr><tr><td>Experience controls</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Year dummies</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>R<sup>2</sup></td><td>0.7840</td><td>0.7822</td><td>0.7849</td></tr><tr><td>Observations</td><td>286</td><td>286</td><td>286</td></tr></tbody></table>

Standard errors in parentheses (clustered at the cohort level, with a bias-reduced linearization to account for the small number of clusters)

<footnote>* p < 0.10, ** p < 0.05, *** p < 0.01</footnote>
## A.5 Main regression for 20 years

<table><caption>Table 9: OLS results on men employment, wage and earned income with 3-years grouped trends</caption><thead><tr><th></th><th>(1)<br>Employment</th><th>(2)<br>Wage</th><th>(3)<br>Earned income</th></tr></thead><tbody><tr><td>15-24 Unemployment rate - UR</td><td>-1.449***<br>(0.337)</td><td>-0.00834<br>(0.00530)</td><td>-0.113**<br>(0.0465)</td></tr><tr><td>UR * Exp. 1 to 15</td><td>0.482***<br>(0.141)</td><td>0.00293<br>(0.00233)</td><td>0.0359*<br>(0.0186)</td></tr><tr><td>UR * Exp. 3 to 15</td><td>-0.481**<br>(0.207)</td><td>-0.00346<br>(0.00312)</td><td>-0.0419*<br>(0.0223)</td></tr><tr><td>UR * Exp. 6 to 15</td><td>0.0534<br>(0.147)</td><td>-0.000138<br>(0.00209)</td><td>0.0184<br>(0.0127)</td></tr><tr><td>UR * Exp. 9 to 15</td><td>-0.102<br>(0.171)</td><td>0.00365<br>(0.00249)</td><td>-0.00944<br>(0.0174)</td></tr><tr><td>UR * Exp. 12 to 15</td><td>0.0797<br>(0.118)</td><td>-0.00191<br>(0.00200)</td><td>0.00373<br>(0.0128)</td></tr><tr><td>UR * Exp. 16 to 20</td><td>-0.0969<br>(0.178)</td><td>-0.00286<br>(0.00270)</td><td>-0.0222<br>(0.0175)</td></tr><tr><td>Experience controls</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Year dummies</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>R<sup>2</sup></td><td>0.8812</td><td>0.9164</td><td>0.9080</td></tr><tr><td>Observations</td><td>341</td><td>341</td><td>341</td></tr></tbody></table>

Standard errors in parentheses (clustered at the cohort level, with a bias-reduced linearization to account for the small number of clusters)

<footnote>* *p* < 0.10, ** *p* < 0.05, *** *p* < 0.01</footnote>
<table><caption>Table 10: OLS results on women employment, wage and earned income with 3-years grouped trends</caption><thead><tr><th></th><th>(1)<br>Employment</th><th>(2)<br>Wage</th><th>(3)<br>Earned income</th></tr></thead><tbody><tr><td>15-24 Unemployment rate - UR</td><td>-2.117***<br>(0.398)</td><td>-0.0107<br>(0.00733)</td><td>-0.157***<br>(0.0278)</td></tr><tr><td>UR * Exp. 1 to 20</td><td>0.700***<br>(0.194)</td><td>0.00127<br>(0.00281)</td><td>0.0503***<br>(0.0136)</td></tr><tr><td>UR * Exp. 3 to 20</td><td>-0.639**<br>(0.273)</td><td>0.000818<br>(0.00426)</td><td>-0.0438**<br>(0.0201)</td></tr><tr><td>UR * Exp. 6 to 20</td><td>-0.198<br>(0.166)</td><td>-0.00262<br>(0.00299)</td><td>-0.0174<br>(0.0134)</td></tr><tr><td>UR * Exp. 9 to 20</td><td>0.304**<br>(0.128)</td><td>-0.00127<br>(0.00225)</td><td>0.0209**<br>(0.00933)</td></tr><tr><td>UR * Exp. 12 to 20</td><td>-0.0480<br>(0.170)</td><td>0.00528**<br>(0.00264)</td><td>0.00230<br>(0.0123)</td></tr><tr><td>UR * Exp. 16 to 20</td><td>-0.316*<br>(0.175)</td><td>-0.00351<br>(0.00284)</td><td>-0.0261*<br>(0.0132)</td></tr><tr><td>Experience controls</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Year dummies</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>R<sup>2</sup></td><td>0.7621</td><td>0.7686</td><td>0.7685</td></tr><tr><td>Observations</td><td>341</td><td>341</td><td>341</td></tr></tbody></table>

Standard errors in parentheses (clustered at the cohort level, with a bias-reduced linearization to account for the small number of clusters)

* p < 0.10, ** p < 0.05, *** p < 0.01
<figure><img src="image_20.png" /><figcaption>Figure 19: Effect of a 1 percentage point difference in unemployment - spline specification (generations: 1982-2009; years: 1990-2010; experience: until 20 years)</figcaption></figure>
<table>
  <tr>
    <td>G 9001</td>
    <td>J. FAYOLLE et M. FLEURBAEY<br>Accumulation, profitabilité et endettement des entreprises</td>
    <td>G 9203</td>
    <td>I. STAPIC<br>Les échanges internationaux de services de la France dans le cadre des négociations multilatérales du GATT<br>Jun 1992 (1ère version)<br>Novembre 1992 (version finale)</td>
    <td>G 9312</td>
    <td>L. BLOCH - B. CŒURÉ<br>Q de Tobin marginal et transmission des chocs financiers</td>
    <td>G 9412</td>
    <td>J. BOURDIEU - B. CŒURÉ -<br>B. COLIN-SEDILLOT<br>Investissement, incertitude et irréversibilité<br>Quelques développements récents de la théorie de l'investissement</td>
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  <tr>
    <td>G 9002</td>
    <td>H. ROUSSE<br>Détection et effets de la multicolinéarité dans les modèles linéaires ordinaires - Un prolongement de la réflexion de BELSLEY, KUH et WELSCH</td>
    <td>G 9204</td>
    <td>P. SEVESTRE<br>L'économétrie sur données individuelles-temporelles. Une note introductive</td>
    <td>G 9313</td>
    <td>Équipes Amadeus (INSEE), Banque de France, Métric (DP)<br>Presentation des propriétés des principaux modèles macroéconomiques du Service Public</td>
    <td>G 9413</td>
    <td>B. DORMONT - M. PAUCHET<br>L'évaluation de l'élasticité emploi-salaire dépend-elle des structures de qualification ?</td>
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  <tr>
    <td>G 9003</td>
    <td>P. RALLE et J. TOUJAS-BERNATE<br>Indexation des salaires : la rupture de 1983</td>
    <td>G 9205</td>
    <td>H. ERKEL-ROUSSE<br>Le commerce extérieur et l'environnement international dans le modèle AMADEUS (réestimation 1992)</td>
    <td>G 9314</td>
    <td>B. CREPON - E. DUGUET<br>Research & Development, competition and innovation</td>
    <td>G 9414</td>
    <td>I. KABLA<br>Le Choix de breveter une invention</td>
  </tr>
  <tr>
    <td>G 9004</td>
    <td>D. GUELLEC et P. RALLE<br>Compétitivité, croissance et innovation de produit</td>
    <td>G 9206</td>
    <td>N. GREENAN et D. GUELLEC<br>Coordination within the firm and endogenous growth</td>
    <td>G 9315</td>
    <td>B. DORMONT<br>Quelle est l'influence du coût du travail sur l'emploi ?</td>
    <td>G 9501</td>
    <td>J. BOURDIEU - B. CŒURÉ - B. SEDILLOT<br>Irreversible Investment and Uncertainty: When is there a Value of Waiting?</td>
  </tr>
  <tr>
    <td>G 9005</td>
    <td>P. RALLE et J. TOUJAS-BERNATE<br>Les conséquences de la désindexation. Analyse dans une maquette prix-salaires</td>
    <td>G 9207</td>
    <td>A. MAGNIER et J. TOUJAS-BERNATE<br>Technology and trade: empirical evidences for the major five industrialized countries</td>
    <td>G 9316</td>
    <td>D. BLANCHET - C. BROUSSE<br>Deux études sur l'âge de la retraite</td>
    <td>G 9502</td>
    <td>L. BLOCH - B. CŒURÉ<br>Imperfections du marché du crédit, investissement des entreprises et cycle économique</td>
  </tr>
  <tr>
    <td>G 9101</td>
    <td>Équipe AMADEUS<br>Le modèle AMADEUS - Première partie - Présentation générale</td>
    <td>G 9208</td>
    <td>B. CREPON, E. DUGUET, D. ENCAOUA et P. MOHNEN<br>Cooperative, non cooperative R & D and optimal patent life</td>
    <td>G 9317</td>
    <td>D. BLANCHET<br>Répartition du travail dans une population hétérogène : deux notes</td>
    <td>G 9503</td>
    <td>D. GOUX - E. MAURIN<br>Les transformations de la demande de travail par qualification en France<br>Une étude sur la période 1970-1993</td>
  </tr>
  <tr>
    <td>G 9102</td>
    <td>J.L. BRILLET<br>Le modèle AMADEUS - Deuxième partie - Propriétés variantielles</td>
    <td>G 9209</td>
    <td>B. CREPON, E. DUGUET<br>Research and development, competition and innovation: an application of pseudo maximum likelihood methods to Poisson models with heterogeneity</td>
    <td>G 9318</td>
    <td>D. EYSSARTIER - N. PONTY<br>AMADEUS - an annual macro-economic model for the medium and long term</td>
    <td>G 9504</td>
    <td>N. GREENAN<br>Technologie, changement organisationnel, qualifications et emploi : une étude empirique sur l'industrie manufacturière</td>
  </tr>
  <tr>
    <td>G 9103</td>
    <td>D. GUELLEC et P. RALLE<br>Endogenous growth and product innovation</td>
    <td>G 9310</td>
    <td>B. CREPON et E. DUGUET<br>Research and development, competition and innovation: an application of pseudo maximum likelihood methods to Poisson models with heterogeneity</td>
    <td>G 9319</td>
    <td>G. CETTE - Ph. CUNÉO - D. EYSSARTIER - J. GAUTIÉ<br>Les effets sur l'emploi d'un abaissement du coût du travail des jeunes</td>
    <td>G 9505</td>
    <td>D. GOUX - E. MAURIN<br>Persistance des hiérarchies sectorielles de salaires: un réexamen sur données françaises</td>
  </tr>
  <tr>
    <td>G 9104</td>
    <td>H. ROUSSE<br>Le modèle AMADEUS - Troisième partie - Le commerce extérieur et l'environnement international</td>
    <td>G 9311</td>
    <td>B. CREPON et E. DUGUET<br>Research and development, competition and innovation: an application of pseudo maximum likelihood methods to Poisson models with heterogeneity</td>
    <td>G 9401</td>
    <td>D. BLANCHET<br>Les structures par âge importent-elles ?</td>
    <td>G 9505<br>Bis</td>
    <td>D. GOUX - E. MAURIN<br>Persistance of inter-industry wages differentials: a reexamination on matched worker-firm panel data</td>
  </tr>
  <tr>
    <td>G 9105</td>
    <td>H. ROUSSE<br>Effets de demande et d'offre dans les résultats du commerce extérieur manufacturé de la France au cours des deux dernières décennies</td>
    <td>G 9312</td>
    <td>J. TOUJAS-BERNATE<br>Commerce international et concurrence impartie : développements récents et implications pour la politique commerciale</td>
    <td>G 9402</td>
    <td>J. GAUTIÉ<br>Le chômage des jeunes en France : problème de formation ou phénomène de file d'attente ?<br>Quelques éléments du débat</td>
    <td>G 9506</td>
    <td>S. JACOBZONE<br>Les liens entre RMI et chômage, une mise en perspective<br>NON PARU - article sorti dans Économie et Prévision n°122 (1996) - pages 95 à 113</td>
  </tr>
  <tr>
    <td>G 9106</td>
    <td>B. CREPON<br>Innovation, taille et concentration : causalités et dynamiques</td>
    <td>G 9303</td>
    <td>Ch. CASES<br>Durées de chômage et comportements d'offre de travail : une revue de la littérature</td>
    <td>G 9403</td>
    <td>P. QUIRION<br>Les déchets en France : éléments statistiques et économiques</td>
    <td>G 9507</td>
    <td>G. CETTE - S. MAHFOUZ<br>Le partage primaire du revenu<br>Constat descriptif sur longue période</td>
  </tr>
  <tr>
    <td>G 9107</td>
    <td>B. AMABLE et D. GUELLEC<br>Un panorama des théories de la croissance endogène</td>
    <td>G 9304</td>
    <td>H. ERKEL-ROUSSE<br>Union économique et monétaire : le débat économique</td>
    <td>G 9404</td>
    <td>D. LADIRAY - M. GRUN-REHOMME<br>Lissage par moyennes mobiles - Le problème des extrémités de série</td>
    <td>G 9601</td>
    <td>Banque de France - CEPREMAP - Direction de la Prévision - Érasme - INSEE - OFCE<br>Structures et propriétés de cinq modèles macro-économiques français</td>
  </tr>
  <tr>
    <td>G 9108</td>
    <td>M. GLAUDE et M. MOUTARDIER<br>Une évaluation du coût direct de l'enfant de 1979 à 1989</td>
    <td>G 9305</td>
    <td>N. GREENAN - D. GUELLEC / G. BROUSSAUDIER - L. MIOTTI<br>Innovation organisationnelle, dynamisme technologique et performances des entreprises</td>
    <td>G 9405</td>
    <td>V. MAILLARD<br>Theorie et pratique de la correction des effets de jours ouvrables</td>
    <td>G 9602</td>
    <td>Rapport d'activité de la DESE de l'année 1995</td>
  </tr>
  <tr>
    <td>G 9109</td>
    <td>P. RALLE et alii<br>France - Allemagne : performances économiques comparées</td>
    <td>G 9306</td>
    <td>P. JAILLARD<br>Le traité de Maastricht : présentation juridique et historique</td>
    <td>G 9406</td>
    <td>F. ROSENWALD<br>La décision d'investir</td>
    <td>G 9603</td>
    <td>J. BOURDIEU - A. DRAZNIEKS<br>L'octroi de crédit aux PME : une analyse à partir d'informations bancaires</td>
  </tr>
  <tr>
    <td>G 9110</td>
    <td>J.L. BRILLET<br>Micro-DMS<br>NON PARU</td>
    <td>G 9307</td>
    <td>J.L. BRILLET<br>Micro-DMS : présentation et propriétés</td>
    <td>G 9407</td>
    <td>S. JACOBZONE<br>Les apports de l'économie industrielle pour définir la stratégie économique de l'hôpital public</td>
    <td>G 9604</td>
    <td>A. TOPIOL-BENSAÏD<br>Les implantations japonaises en France</td>
  </tr>
  <tr>
    <td>G 9111</td>
    <td>A. MAGNIER<br>Effets accélérateur et multiplicateur en France depuis 1970 : quelques résultats empiriques</td>
    <td>G 9308</td>
    <td>J.L. BRILLET<br>Micro-DMS - variantes : les tableaux</td>
    <td>G 9408</td>
    <td>L. BLOCH, J. BOURDIEU, B. COLIN-SEDILLOT<br>Du défaut de paiement au dépôt de bilan : les banquiers face aux PME en difficulté</td>
    <td>G 9605</td>
    <td>P. GENIER - S. JACOBZONE<br>Comportements de prévention, consommation d'alcool et tabagie : peut-on parler d'une gestion globale du capital santé ?<br>Une modélisation microéconométrique empirique</td>
  </tr>
  <tr>
    <td>G 9112</td>
    <td>B. CREPON et G. DUREAU<br>Investissement en recherche-développement : analyse de causalités dans un modèle d'accélérateur généralisé</td>
    <td>G 9309</td>
    <td>S. JACOBZONE<br>Les grands réseaux publics français dans une perspective européenne</td>
    <td>G 9409</td>
    <td>D. EYSSARTIER, P. MAIRE<br>Impacts macro-économiques de mesures d'aide au logement - quelques éléments d'évaluation</td>
    <td>G 9606</td>
    <td>C. DOZ - F. LENGLART<br>Factor analysis and unobserved component models: an application to the study of French business surveys</td>
  </tr>
  <tr>
    <td>G 9113</td>
    <td>J.L. BRILLET, H. ERKEL-ROUSSE, J. TOUJAS-BERNATE<br>"France-Allemagne Couplées" - Deux économies vues par une maquette macro-économétrique</td>
    <td>G 9310</td>
    <td>L. BLOCH - B. CŒURÉ<br>Profitabilité de l'investissement productif et transmission des chocs financiers</td>
    <td>G 9410</td>
    <td>F. ROSENWALD<br>Suivi conjoncturel de l'investissement</td>
    <td>G 9607</td>
    <td>N. GREENAN - D. GUELLEC<br>La théorie coopérative de la firme</td>
  </tr>
  <tr>
    <td>G 9201</td>
    <td>W.J. ADAMS, B. CREPON, D. ENCAOUA<br>Choix technologiques et stratégies de dissuasion d'entrée</td>
    <td>G 9311</td>
    <td>J. BOURDIEU - B. COLIN-SEDILLOT<br>Les théories sur la structure optimale du capital : quelques points de repère</td>
    <td>G 9411</td>
    <td>C. DEFEUILLE - Ph. QUIRION<br>Les déchets d'emballages ménagers : une analyse économique des politiques française et allemande</td>
    <td>G 9607</td>
    <td>N. GREENAN - D. GUELLEC<br>La théorie coopérative de la firme</td>
  </tr>
  <tr>
    <td>G 9202</td>
    <td>J. OLIVEIRA-MARTINS, J. TOUJAS-BERNATE</td>
    <td></td>
    <td>J. BOURDIEU - B. COLIN-SEDILLOT<br>Les décisions de financement des entreprises</td>
    <td></td>
    <td></td>
    <td></td>
    <td></td>
  </tr>
</table>
<table><tr><td>G 9608</td><td>N. GREENAN - D. GUELLEC<br/>Technological innovation and employment<br/>reallocation</td></tr><tr><td>G 9609</td><td>Ph. COUR - F. RUPPRECHT<br/>L'intégration asymétrique au sein du continent<br/>américain : un essai de modélisation</td></tr><tr><td>G 9610</td><td>S. DUCHENE - G. FORGEOT - A. JACQUOT<br/>Analyse des évolutions récentes de la productivité apparente du travail</td></tr><tr><td>G 9611</td><td>X. BONNET - S. MAHFOUZ<br/>The influence of different specifications of<br/>wages-prices spirals on the measure of the<br/>NAIRU: the case of France</td></tr><tr><td>G 9612</td><td>PH. COUR - E. DUBOIS, S. MAHFOUZ,<br/>J. PISANI-FERRY<br/>The cost of fiscal retrenchment revisited: how<br/>strong is the evidence?</td></tr><tr><td>G 9613</td><td>A. JACQUOT<br/>Les flexions des taux d'activité sont-elles seule-<br/>ment conjoncturelles ?</td></tr><tr><td>G 9614</td><td>ZHANG Yingxiang - SONG Xueqing<br/>Lexique macroéconomique Français-Chinois</td></tr><tr><td>G 9701</td><td>J.L. SCHNEIDER<br/>La taxe professionnelle : éléments de cadrage<br/>économique</td></tr><tr><td>G 9702</td><td>J.L. SCHNEIDER<br/>Transition et stabilité politique d'un système<br/>redistributif</td></tr><tr><td>G 9703</td><td>D. GOUX - E. MAURIN<br/>Train or Pay: Does it Reduce Inequalities to En-<br/>courage Firms to Train their Workers?</td></tr><tr><td>G 9704</td><td>P. GENIER<br/>Deux contributions sur dépendance et équité</td></tr><tr><td>G 9705</td><td>E. DUGUET - N. IUNG<br/>R & D Investment, Patent Life and Patent Value<br/>An Econometric Analysis at the Firm Level</td></tr><tr><td>G 9706</td><td>M. HOUBEBINE - A. TOPIOL-BENSAÏD<br/>Les entreprises internationales en France : une<br/>analyse à partir de données individuelles</td></tr><tr><td>G 9707</td><td>M. HOUBEBINE<br/>Polarisation des activités et spécialisation des<br/>départements en France</td></tr><tr><td>G 9708</td><td>E. DUGUET - N. GREENAN<br/>Le biais technologique : une analyse sur don-<br/>nées individuelles</td></tr><tr><td>G 9709</td><td>J.L. BRILLET<br/>Analyzing a small French ECM Model</td></tr><tr><td>G 9710</td><td>J.L. BRILLET<br/>Formalizing the transition process: scenarios for<br/>capital accumulation</td></tr><tr><td>G 9711</td><td>G. FORGEOT - J. GAUTIÉ<br/>Insertion professionnelle des jeunes et proces-<br/>sus de déclassement</td></tr><tr><td>G 9712</td><td>E. DUBOIS<br/>High Real Interest Rates: the Consequence of a<br/>Saving Investment Disequilibrium or of an in-<br/>sufficient Credibility of Monetary Authorities?</td></tr><tr><td>G 9713</td><td>Bilan des activités de la Direction des Études<br/>et Synthèses Économiques - 1996</td></tr></table>

<table><tr><td>G 9714</td><td>F. LEQUILLER<br/>Does the French Consumer Price Index Over-<br/>state Inflation?</td></tr><tr><td>G 9715</td><td>X. BONNET<br/>Peut-on mettre en évidence les rigidités à la<br/>baisse des salaires nominaux ?<br/>Une étude sur quelques grands pays de l'OCDE</td></tr><tr><td>G 9716</td><td>N. IUNG - F. RUPPRECHT<br/>Productivité de la recherche et rendements<br/>d'échelle dans le secteur pharmaceutique<br/>français</td></tr><tr><td>G 9717</td><td>E. DUGUET - I. KABLA<br/>Appropriation strategy and the motivations to use<br/>the patent system in France - An econometric<br/>analysis at the firm level</td></tr><tr><td>G 9718</td><td>L.P. PELÉ - P. RALLE<br/>Âge de la retraite : les aspects incitatifs du ré-<br/>gime général</td></tr><tr><td>G 9719</td><td>ZHANG Yingxiang - SONG Xueqing<br/>Lexique macroéconomique français-chinois,<br/>chinois-français</td></tr><tr><td>G 9720</td><td>M. HOUBEBINE - J.L. SCHNEIDER<br/>Mesurer l'influence de la fiscalité sur la locali-<br/>sation des entreprises</td></tr><tr><td>G 9721</td><td>A. MOUROUGANE<br/>Crédibilité, indépendance et politique monétaire<br/>Une revue de la littérature</td></tr><tr><td>G 9722</td><td>P. AUGERAUD - L. BRIOT<br/>Les données comptables d'entreprises<br/>Le système intermédiaire d'entreprises<br/>Passage des données individuelles aux données<br/>sectorielles</td></tr><tr><td>G 9723</td><td>P. AUGERAUD - J. E. CHAPRON<br/>Using Business Accounts for Compiling National<br/>Accounts: the French Experience</td></tr><tr><td>G 9724</td><td>P. AUGERAUD<br/>Les comptes d'entreprise par activités - Le pas-<br/>sage aux comptes - De la comptabilité<br/>d'entreprise à la comptabilité nationale - A<br/>paraitre</td></tr><tr><td>G 9801</td><td>H. MICHAUDON - C. PRIGENT<br/>Présentation du modèle AMADEUS</td></tr><tr><td>G 9802</td><td>J. ACCARDO<br/>Une étude de comptabilité générationnelle<br/>pour la France en 1996</td></tr><tr><td>G 9803</td><td>X. BONNET - S. DUCHÈNE<br/>Apports et limites de la modélisation<br/>« Real Business Cycles »</td></tr><tr><td>G 9804</td><td>C. BARLET - C. DUGUET -<br/>D. ENCAOUA - J. PRADEL<br/>The Commercial Success of Innovations<br/>An econometric analysis at the firm level in<br/>French manufacturing</td></tr><tr><td>G 9805</td><td>P. CAHUC - Ch. GIANELLA -<br/>D. GOUX - A. ZILBERBERG<br/>Equalizing Wage Differences and Bargaining<br/>Power - Evidence form a Panel of French Firms</td></tr><tr><td>G 9806</td><td>J. ACCARDO - M. JLASSI<br/>La productivité globale des facteurs entre 1975<br/>et 1996</td></tr><tr><td>G 9807</td><td>Bilan des activités de la Direction des Études et<br/>Synthèses Économiques - 1997</td></tr></table>

<table><tr><td>G 9808</td><td>A. MOUROUGANE<br/>Can a Conservative Governor Conduct an Ac-<br/>comodative Monetary Policy?</td></tr><tr><td>G 9809</td><td>X. BONNET - E. DUBOIS - L. FAUVET<br/>Asymétrie des inflations relatives et menus costs<br/>: tests sur l'inflation française</td></tr><tr><td>G 9810</td><td>E. DUGUET - N. IUNG<br/>Sales and Advertising with Spillovers at the firm<br/>level: Estimation of a Dynamic Structural Model<br/>on Panel Data</td></tr><tr><td>G 9811</td><td>J.P. BERTHIER<br/>Congestion urbaine : un modèle de trafic de<br/>pointe à courbe débit-vitesse et demande<br/>élastique</td></tr><tr><td>G 9812</td><td>C. PRIGENT<br/>La part des salaires dans la valeur ajoutée : une<br/>approche macroéconomique</td></tr><tr><td>G 9813</td><td>A.Th. AERTS<br/>L'évolution de la part des salaires dans la valeur<br/>ajoutée en France reflète-t-elle les évolutions<br/>individuelles sur la période 1979-1994 ?</td></tr><tr><td>G 9814</td><td>B. SALANIÉ<br/>Guide pratique des séries non-stationnaires</td></tr><tr><td>G 9901</td><td>S. DUCHÈNE - A. JACQUOT<br/>Une croissance plus riche en emplois depuis le<br/>début de la décennie ? Une analyse en compa-<br/>raison internationale</td></tr><tr><td>G 9902</td><td>Ch. COLIN<br/>Modélisation des carrières dans Destinie</td></tr><tr><td>G 9903</td><td>Ch. COLIN<br/>Évolution de la dispersion des salaires : un essai<br/>de prospective par microsimulation</td></tr><tr><td>G 9904</td><td>B. CREPON - N. IUNG<br/>Innovation, emploi et performances</td></tr><tr><td>G 9905</td><td>B. CREPON - Ch. GIANELLA<br/>Wages inequalities in France 1969-1992<br/>An application of quantile regression techniques</td></tr><tr><td>G 9906</td><td>C. BONNET - R. MAHIEU<br/>Microsimulation techniques applied to inter-<br/>generational transfers - Pensions in a dynamic<br/>framework: the case of France</td></tr><tr><td>G 9907</td><td>F. ROSENWALD<br/>L'impact des contraintes financières dans la dé-<br/>cision d'investissement</td></tr><tr><td>G 9908</td><td>Bilan des activités de la DESE - 1998</td></tr><tr><td>G 9909</td><td>J.P. ZOYEM<br/>Contrat d'insertion et sortie du RMI<br/>Évaluation des effets d'une politique sociale</td></tr><tr><td>G 9910</td><td>Ch. COLIN - FI. LEGROS - R. MAHIEU<br/>Bilans contributifs comparés des régimes de<br/>retraite du secteur privé et de la fonction<br/>publique</td></tr><tr><td>G 9911</td><td>G. LAROQUE - B. SALANIÉ<br/>Une décomposition du non-emploi en France</td></tr><tr><td>G 9912</td><td>B. SALANIÉ<br/>Une maquette analytique de long terme du<br/>marché du travail</td></tr><tr><td>G 9912</td><td>Ch. GIANELLA<br/>Une estimation de l'élasticité de l'emploi peu<br/>qualifié à son coût</td></tr></table>

<table><tr><td>G 9913</td><td>Division « Redistribution et Politiques Sociales »<br/>Le modèle de microsimulation dynamique<br/>DESTINIE</td></tr><tr><td>G 9914</td><td>E. DUGUET<br/>Macro-commandes SAS pour l'économétrie des<br/>panels et des variables qualitatives</td></tr><tr><td>G 9915</td><td>R. DUHAUTOIS<br/>Évolution des flux d'emplois en France entre<br/>1990 et 1996 : une étude empirique à partir du<br/>fichier des bénéfices réels normaux (BRN)</td></tr><tr><td>G 9916</td><td>J.Y. FOURNIER<br/>Extraction du cycle des affaires : la méthode de<br/>Baxter et King</td></tr><tr><td>G 9917</td><td>B. CRÉPON - R. DESPLATZ - J. MAIRESSE<br/>Estimating price cost margins, scale economies<br/>and workers' bargaining power at the firm level</td></tr><tr><td>G 9918</td><td>Ch. GIANELLA - Ph. LAGARDE<br/>Productivity of hours in the aggregate production<br/>function: an evaluation on a panel of French<br/>firms from the manufacturing sector</td></tr><tr><td>G 9919</td><td>S. AUDRIC - P. GIVORD - C. PROST<br/>Évolution de l'emploi et des coûts par quali-<br/>fication entre 1982 et 1996</td></tr><tr><td>G 2000/01</td><td>R. MAHIEU<br/>Les déterminants des dépenses de santé : une<br/>approche macroéconomique</td></tr><tr><td>G 2000/02</td><td>C. ALLARD-PRIGENT - H. GUILMEAU -<br/>A. QUINET<br/>The real exchange rate as the relative price of<br/>nontrables in terms of tradables: theoretical<br/>investigation and empirical study on French data</td></tr><tr><td>G 2000/03</td><td>J.-Y. FOURNIER<br/>L'approximation du filtre passe-bande proposée<br/>par Christiano et Fitzgerald</td></tr><tr><td>G 2000/04</td><td>Bilan des activités de la DESE - 1999</td></tr><tr><td>G 2000/05</td><td>B. CREPON - F. ROSENWALD<br/>Investissement et contraintes de financement : le<br/>poids du cycle<br/>Une estimation sur données françaises</td></tr><tr><td>G 2000/06</td><td>A. FLIPO<br/>Les comportements matrimoniaux de fait</td></tr><tr><td>G 2000/07</td><td>R. MAHIEU - B. SÉDILLOT<br/>Microsimulations of the retirement decision: a<br/>supply side approach</td></tr><tr><td>G 2000/08</td><td>C. AUDENIS - C. PROST<br/>Déficit conjoncturel : une prise en compte des<br/>conjonctures passées</td></tr><tr><td>G 2000/09</td><td>R. MAHIEU - B. SÉDILLOT<br/>Équivalent patrimonial de la rente et souscription<br/>de retraite complémentaire</td></tr><tr><td>G 2000/10</td><td>R. DUHAUTOIS<br/>Ralentissement de l'investissement : petites ou<br/>grandes entreprises ? industrie ou tertiaire ?</td></tr><tr><td>G 2000/11</td><td>G. LAROQUE - B. SALANIÉ<br/>Temps partiel féminin et incitations financières à<br/>l'emploi</td></tr><tr><td>G 2000/12</td><td>Ch. GIANELLA<br/>Local unemployment and wages</td></tr><tr><td>G 2000/13</td><td>B. CREPON - Th. HECKEL<br/>- Informatisation en France : une évaluation à<br/>partir de données individuelles</td></tr></table>
- Computerization in France: an evaluation based on individual company data

G2001/01 F. LEQUILLER
- La nouvelle économie et la mesure de la croissance du PIB

- The new economy and the measurement of GDP growth

G2001/02 S. AUDRIC
La reprise de la croissance de l'emploi profonde-t-elle aussi aux non-diplômés ?

G2001/03 I. BRAUN-LEMAIRE
Évolution et répartition du surplus de productivité

G2001/04 A. BEAUDU - Th. HECKEL
Le canal du crédit fonctionne-t-il en Europe ? Une étude de l'hétérogénéité des comportements d'investissement à partir de données de bilan agrégées

G2001/05 C. AUDENIS - P. BISCOURP - N. FOURCADE - O. LOISEL
Testing the augmented Solow growth model: An empirical reassessment using panel data

G2001/06 R. MAHIEU - B. SÉDILLOT
Départ à la retraite, irréversibilité et incertitude

G2001/07 Bilan des activités de la DESE - 2000

G2001/08 J. Ph. GAUDEMET
Les dispositifs d'acquisition à titre facultatif d'annuités viagères de retraite

G2001/09 B. CRÉPON - Ch. GIANELLA
Fiscalité, coût d'usage du capital et demande de facteurs : une analyse sur données individuelles

G2001/10 B. CRÉPON - R. DESPLATZ
Évaluation des effets des dispositifs d'allégements de charges sociales sur les bas salaires

G2001/11 J.-Y. FOURNIER
Comparaison des salaires des secteurs public et privé

G2001/12 J.-P. BERTHIER - C. JAULENT
R. CONVENEVOLE - S. PISANI
Une méthodologie de comparaison entre consommations intermédiaires de source fiscale et de comptabilité nationale

G2001/13 P. BISCOURP - Ch. GIANELLA
Substitution and complementarity between capital, skilled and less skilled workers: an analysis at the firm level in the French manufacturing industry

G2001/14 I. ROBERT-BOBEE
Modelling demographic behaviours in the French microsimulation model Destinie: An analysis of future change in completed fertility

G2001/15 J.-P. ZOYEM
Diagnostic sur la pauvreté et calendrier de revenus : le cas du "Panel européen des ménages"

G2001/16 J.-Y. FOURNIER - P. GIVORD
La réduction des taux d'activité aux âges extrêmes, une spécificité française ?

G2001/17 C. AUDENIS - P. BISCOURP - N. RIEDINGER
Existe-t-il une asymétrie dans la transmission du prix du brut aux prix des carburants ?

G2002/01 F. MAGNIEN - J.-L. TAVERNIER - D. THESMAR
Les statistiques internationales de PIB par habitant en standard de pouvoir d'achat : une analyse des résultats

G2002/02 Bilan des activités de la DESE - 2001

G2002/03 B. SÉDILLOT - E. WALRAET
La cessation d'activité au sein des couples : y a-t-il interdépendance des choix ?

G2002/04 G. BRILHAULT
- Rétroposition des séries de FBCF et calcul du capital fixe en SEC-95 dans les comptes nationaux français

- Retroposition of the investment series (GFCF) and estimation of fixed capital stocks on the ESA-95 basis for the French balance sheets

G2002/05 P. BISCOURP - B. CRÉPON - T. HECKEL - N. RIEDINGER
How do firms respond to cheaper computers? Microeconomic evidence for France based on a production function approach

G2002/06 C. AUDENIS - J. DEROYON - N. FOURCADE
L'impact des nouvelles technologies de l'information et de la communication sur l'économie française - un bouclage macro-économique

G2002/07 J. BARDAJI - B. SÉDILLOT - E. WALRAET
Évaluation de trois réformes du Régime Général d'assurance vieillesse à l'aide du modèle de microsimulation DESTINIE

G2002/08 J.-P. BERTHIER
Réflexions sur les différentes notions de volume dans les comptes nationaux : comptes aux prix d'une année fixe ou aux prix de l'année précédente, séries chaînées

G2002/09 F. HILD
Les soldes d'opinion résument-ils au mieux les réponses des entreprises aux enquêtes de conjoncture ?

G2002/10 I. ROBERT-BOBÉE
Les comportements démographiques dans le modèle de microsimulation Destinie - Une comparaison des estimations issues des enquêtes Jeunes et Carrières 1997 et Histoire Familielle 1999

G2002/11 J.-P. ZOYEM
La dynamique des bas revenus : une analyse des entrées-sorties de pauvreté

G2002/12 F. HILD
Prévisions d'inflation pour la France

G2002/13 M. LECLAIR
Réduction du temps de travail et tensions sur les facteurs de production

G2002/14 E. WALRAET - A. VINCENT
- Analyse de la redistribution intragénérationnelle dans le système de retraite des salariés du privé - Une approche par microsimulation

- Intragenerational distributional analysis in the french private sector pension scheme - A microsimulation approach

G2002/15 P. CHONE - D. LE BLANC - I. ROBERT-BOBEE
Offre de travail féminine et garde des jeunes enfants

G2002/16 F. MAUREL - S. GREGOIR
Les indices de compétitivité des pays : interprétation et limites

G2003/01 N. RIEDINGER - E. HAUVY
Le coût de dépollution atmosphérique pour les entreprises françaises : Une estimation à partir de données individuelles

G2003/02 P. BISCOURP et F. KRAMARZ
Création d'emplois, destruction d'emplois et internationalisation des entreprises industrielles françaises : une analyse sur la période 1986-1992

G2003/03 Bilan des activités de la DESE - 2002

G2003/04 P.-O. BEFFY - J. DEROYON - N. FOURCADE - S. GREGOIR - N. LAÎB - B. MONFORT
Évolutions démographiques et croissance : une projection macro-économique à l'horizon 2020

G2003/05 P. AUBERT
La situation des salariés de plus de cinquante ans dans le secteur privé

G2003/06 P. AUBERT - B. CRÉPON
Âge, salaire et productivité
La productivité des salariés décline-t-elle en fin de carrière ?

G2003/07 H. BARON - P.O. BEFFY - N. FOURCADE - R. MAHIEU
Le ralentissement de la productivité du travail au cours des années 1990

G2003/08 P.-O. BEFFY - B. MONFORT
Patrimoine des ménages, dynamique d'allocation et comportement de consommation

G2003/09 P. BISCOURP - N. FOURCADE
Peut-on mettre en évidence l'existence de rigidités à la baisse des salaires à partir de données individuelles ? Le cas de la France à la fin des années 90

G2003/10 M. LECLAIR - P. PETIT
Présence syndicale dans les firmes : quel impact sur les inégalités salariales entre les hommes et les femmes ?

G2003/11 P.-O. BEFFY - X. BONNET - M. DARRACQ-PARIES - B. MONFORT
MZE: a small macro-model for the euro area

G2004/01 P. AUBERT - M. LECLAIR
La compétitivité exprimée dans les enquêtes trimestrielles sur la situation et les perspectives dans l'industrie

G2004/02 M. DUÉE - C. REBILLARD
La dépendance des personnes âgées : une projection à long terme

G2004/03 S. RASPILLER - N. RIEDINGER
Régulation environnementale et choix de localisation des groupes français

G2004/04 A. NABOULET - S. RASPILLER
Les déterminants de la décision d'investir : une approche par les perceptions subjectives des firmes

G2004/05 N. RAGACHE
La déclaration des enfants par les couples non mariés est-elle fiscalement optimale ?

G2004/06 M. DUÉE
L'impact du chômage des parents sur le devenir scolaire des enfants

G2004/07 P. AUBERT - E. CAROLI - M. ROGER
New Technologies, Workplace Organisation and the Age Structure of the Workforce: Firm-Level Evidence

G2004/08 E. DUGUET - C. LELARGE
Les brevets accroissent-ils les incitations privées à innover ? Un examen microéconométrique

G2004/09 S. RASPILLER - P. SILLARD
Affiliating versus Subcontracting: the Case of Multinationals

G2004/10 J. BOISSINOT - C. L'ANGEVIN - B. MONFORT
Public Debt Sustainability: Some Results on the French Case

G2004/11 S. ANANIAN - P. AUBERT
Travailleurs âgés, nouvelles technologies et changements organisationnels : un réexamen à partir de l'enquête « REPONSE »

G2004/12 X. BONNET - H. PONCET
Structures de revenus et propensions différentes à consommer - Vers une équation de consommation des ménages plus robuste en prévision pour la France

G2004/13 C. PICART
Évaluer la rentabilité des sociétés non financières

G2004/14 J. BARDAJI - B. SÉDILLOT - E. WALRAET
Les retraites du secteur public : projections à l'horizon 2040 à l'aide du modèle de microsimulation DESTINIE

G2005/01 S. BUFFETEAU - P. GODEFROY
Conditions de départ en retraite selon l'âge de fin d'études : analyse prospective pour les générations 1945 a1974

G2005/02 C. AFSA - S. BUFFETEAU
L'évolution de l'activité féminine en France : une approche par pseudo-panel

G2005/03 P. AUBERT - P. SILLARD
Délocalisations et réductions d'effectifs dans l'industrie française

G2005/04 M. LECLAIR - S. ROUX
Mesure et utilisation des emplois instables dans les entreprises

G2005/05 C. L'ANGEVIN - S. SERRAVALLE
Performances à l'exportation de la France et de l'Allemagne - Une analyse par secteur et destination géographique

G2005/06 Bilan des activités de la Direction des Études et Synthèses Economiques - 2004

G2005/07 S. RASPILLER
La concurrence fiscale : principaux enseignements de l'analyse économique

G2005/08 C. L'ANGEVIN - N. LAÎB
Éducation et croissance en France et dans un panel de 21 pays de l'OCDE

G2005/09 N. FERRARI
Prévoir l'investissement des entreprises
Un indicateur des révisions dans l'enquête de conjoncture sur les investissements dans l'industrie.
G2005/10 P.-O. BEFFY - C. L'ANGEVIN
Chômage et boucle prix-salaires : apport d'un modèle « qualifiés/peu qualifiés »

G2005/11 B. HEITZ
A two-states Markov-switching model of inflation in France and the USA: credible target VS inflation spiral

G2005/12 O. BIAU - H. ERKEL-ROUSSE - N. FERRARI
Réponses individuelles aux enquêtes de conjoncture et prévision macroéconomiques : Exemple de la prévision de la production manufacturière

G2005/13 P. AUBERT - D. BLANCHET - D. BLAU
The labour market after age 50: some elements of a Franco-American comparison

G2005/14 D. BLANCHET - T. DEBRAND - P. DOURGNON - P. POLLET
L'enquête SHARE : présentation et premiers résultats de l'édition française

G2005/15 M. DUÉE
La modélisation des comportements démographiques dans le modèle de microsimulation DESTINE

G2005/16 H. RAOUI - S. ROUX
Étude de simulation sur la participation versée aux salariés par les entreprises

G2006/01 C. BONNET - S. BUFFETEAU - P. GODEFROY
Disparités de retraite de droit direct entre hommes et femmes : quelles évolutions ?

G2006/02 C. PICART
Les gazelles en France

G2006/03 P. AUBERT - B. CRÉPON - P. ZAMORA
Le rendement apparent de la formation continue dans les entreprises : effets sur la productivité et les salaires

G2006/04 J.-F. OUVRARD - R. RATHELOT
Demographic change and unemployment: what do macroeconomic models predict?

G2006/05 D. BLANCHET - J.-F. OUVRARD
Indicateurs d'engagements implicites des systèmes de retraite : chiffrages, propriétés analytiques et réactions à des chocs démographiques types

G2006/06 G. BIAU - O. BIAU - L. ROUVIERE
Nonparametric Forecasting of the Manufacturing Output Growth with Firm-level Survey Data

G2006/07 C. AFSA - P. GIVORD
Le rôle des conditions de travail dans les absences pour maladie

G2006/08 P. SILLARD - C. L'ANGEVIN - S. SERRAVALLE
Performances comparées à l'exportation de la France et de ses principaux partenaires
Une analyse structurelle sur 12 ans

G2006/09 X. BOUTIN - S. QUANTIN
Une méthodologie d'évaluation comptable du coût du capital des entreprises françaises : 1984-2002

G2006/10 C. AFSA
L'estimation d'un coût implicite de la pénibilité du travail chez les travailleurs âgés

G2006/11 C. LELARGE
Les entreprises (industrielles) françaises sont-elles à la frontière technologique ?

G2006/12 O. BIAU - N. FERRARI
Théorie de l'opinion
Faut-il pondérer les réponses individuelles ?

G2006/13 A. KOUBI - S. ROUX
Une réinterprétation de la relation entre productivité et inégalités salariales dans les entreprises

G2006/14 R. RATHELOT - P. SILLARD
The impact of local taxes on plants location decision

G2006/15 L. GONZALEZ - C. PICART
Diversification, centrage et poids des activités de support dans les groupes (1993-2000)

G2007/01 D. SRAER
Allègements de cotisations patronales et dynamique salariale

G2007/02 V. ALBOUY - L. LEQUIEN
Les rendements non monétaires de l'éducation : le cas de la santé

G2007/03 D. BLANCHET - T. DEBRAND
Aspiration à la retraite, santé et satisfaction au travail : une comparaison européenne

G2007/04 M. BARLET - L. CRUSSON
Quel impact des variations du prix du pétrole sur la croissance française ?

G2007/05 C. PICART
Flux d'emploi et de main-d'œuvre en France : un réexamen

G2007/06 V. ALBOUY - C. TAVAN
Massification et démocratisation de l'enseignement supérieur en France

G2007/07 T. LE BARBANCHON
The Changing response to oil price shocks in France: a DSGE type approach

G2007/08 T. CHANEY - D. SRAER - D. THESMAR
Collateral Value and Corporate Investment Evidence from the French Real Estate Market

G2007/09 J. BOISSINOT
Consumption over the Life Cycle: Facts for France

G2007/10 C. AFSA
Interpréter les variables de satisfaction : l'exemple de la durée du travail

G2007/11 R. RATHELOT - P. SILLARD
Zones Franches Urbaines : quels effets sur l'emploi salarié et les créations d'établissements ?

G2007/12 V. ALBOUY - B. CRÉPON
Aléa moral en santé : une évaluation dans le cadre du modèle causal de Rubin

G2008/01 C. PICART
Les PME françaises : rentables mais peu dynamiques

G2008/02 P. BISCOURP - X. BOUTIN - T. VERGÉ
The Effects of Retail Regulations on Prices Evidence form the Loi Galland

G2008/03 Y. BARBESOL - A. BRIANT
Économies d'agglomération et productivité des entreprises : estimation sur données individuelles françaises

G2008/04 D. BLANCHET - F. LE GALLO
Les projections démographiques : principaux mécanismes et retour sur l'expérience française

G2008/05 D. BLANCHET - F. TOUTLEMONDE
Évolutions démographiques et déformation du cycle de vie active : quelles relations ?

G2008/06 M. BARLET - D. BLANCHET - L. CRUSSON
Internationalisation et flux d'emplois : que dit une approche comptable ?

G2008/07 C. LELARGE - D. SRAER - D. THESMAR
Entrepreneurship and Credit Constraints - Evidence from a French Loan Guarantee Program

G2008/08 X. BOUTIN - L. JANIN
Are Prices Really Affected by Mergers?

G2008/09 M. BARLET - A. BRIANT - L. CRUSSON
Concentration géographique dans l'industrie manufacturière et dans les services en France : une approche par un indicateur en continu

G2008/10 M. BEFFY - É. COUDIN - R. RATHELOT
Who is confronted to insecure labor market histories? Some evidence based on the French labor market transition

G2008/11 M. ROGER - E. WALRAET
Social Security and Well-Being of the Elderly: the Case of France

G2008/12 C. AFSA
Analyser les composantes du bien-être et de son évolution
Une approche empirique sur données individuelles

G2008/13 M. BARLET - D. BLANCHET - T. LE BARBANCHON
Microsimplifier le marché du travail : un prototype

G2009/01 P.-A. PIONNIER
Le partage de la valeur ajoutée en France, 1949-2007

G2009/02 Laurent CLAVEL - Christelle MINODIER
A Monthly Indicator of the French Business Climate

G2009/03 H. ERKEL-ROUSSE - C. MINODIER
Do Business Tendency Surveys in Industry and Services Help in Forecasting GDP Growth?
A Real-Time Analysis on French Data

G2009/04 P. GIVORD - L. WILNER
Les contrats temporaires : trappe ou marché-pied vers l'emploi stable ?

G2009/05 G. LALANNE - P.-A. PIONNIER - O. SIMON
Le partage des fruits de la croissance de 1950 à 2008 : une approche par les comptes de surplus

G2009/06 L. DAVEZIES - X. D'HAULTFOEUILLE
Faut-il pondérer ?... Ou l'éternelle question de l'économètre confronté à des données d'enquête

G2009/07 S. QUANTIN - S. RASPILLER - S. SERRAVALLE
Commerce intragroupe, fiscalité et prix de transferts : une analyse sur données françaises

G2009/08 M. CLERC - V. MARCUS
Élasticités-prix des consommations énergétiques des ménages

G2009/09 G. LALANNE - E. POULIQUEN - O. SIMON
Prix du pétrole et croissance potentielle à long terme

G2009/10 D. BLANCHET - J. LE CACHEUX - V. MARCUS
Adjusted net savings and other approaches to sustainability: some theoretical background

G2009/11 V. BELLAMY - G. CONSALES - M. FESSEAU - S. LE LAIDIER - É. RAYNAUD
Une décomposition du compte des ménages de la comptabilité nationale par catégorie de ménage en 2003

G2009/12 J. BARDAJI - F. TALLET
Detecting Economic Regimes in France: a Qualitative Markov-Switching Indicator Using Mixed Frequency Data

G2009/13 R. AEBERHARDT - D. FOUGÈRE - R. RATHELOT
Discrimination à l'embauche : comment exploiter les procédures de testing ?

G2009/14 Y. BARBESOL - P. GIVORD - S. QUANTIN
Partage de la valeur ajoutée, approche par données microéconomiques

G2009/15 I. BUONO - G. LALANNE
The Effect of the Uruguay round on the Intensive and Extensive Margins of Trade

G2010/01 C. MINODIER
Avantages comparés des séries des premières valeurs publiées et des séries des valeurs révisées - Un exercice de prévision en temps réel de la croissance trimestrielle du PIB en France

G2010/02 V. ALBOUY - L. DAVEZIES - T. DEBRAND
Health Expenditure Models: a Comparison of Five Specifications using Panel Data

G2010/03 C. KLEIN - O. SIMON
Le modèle MÉSANGE réestimé en base 2000 Tome 1 – Version avec volumes à prix constants

G2010/04 M.-É. CLERC - É. COUDIN
L'IPC, miroir de l'évolution du coût de la vie en France ? Ce qu'apporte l'analyse des courbes d'Engel

G2010/05 N. CECI-RENAUD - P.-A. CHEVALIER
Les seuils de 10, 20 et 50 salariés : impact sur la taille des entreprises françaises

G2010/06 R. AEBERHARDT - J. POUGET
National Origin Differences in Wages and Hierarchical Positions - Evidence on French Full-Time Male Workers from a matched Employer-Employee Dataset

G2010/07 S. BLASCO - P. GIVORD
Les trajectoires professionnelles en début de vie active : quel impact des contrats temporaires ?

G2010/08 P. GIVORD
Méthodes économétriques pour l'évaluation de politiques publiques

G2010/09 P.-Y. CABANNES - V. LAPÈGUE - E. POULIQUEN - M. BEFFY - M. GAINI
Quelle croissance de moyen terme après la crise ?

G2010/10 I. BUONO - G. LALANNE
La réaction des entreprises françaises à la baisse des tarifs douaniers étrangers
G2010/11 R. RATHELOT - P. SILLARD
L'apport des méthodes à noyaux pour mesurer la concentration géographique - Application à la concentration des immigrés en France de 1968 à 1999

G2010/12 M. BARATON - M. BEFFY - D. FOUGÈRE
Une évaluation de l'effet de la réforme de 2003 sur les départs en retraite - Le cas des enseignants du second degré public

G2010/13 D. BLANCHET - S. BUFFETEAU - E. CRENNER
S. LE MINEZ
Le modèle de microsimulation Destinie 2 : principales caractéristiques et premiers résultats

G2010/14 D. BLANCHET - E. CRENNER
Le bloc retraites du modèle Destinie 2 : guide de l'utilisateur

G2010/15 M. BARLET - L. CRUSSON - S. DUPUCH - F. PUECH
Des services échangés aux services échangeables : une application sur données françaises

G2010/16 M. BEFFY - T. KAMIONKA
Public-private wage gaps: is civil-servant human capital sector-specific?

G2010/17 P.-Y. CABANNES - H. ERKEL-ROUSSE - G. LALANNE - O. MONSO - E. POULIQUEN
Le modèle Mésange réestimé en base 2000
Tome 2 - Version avec volumes à prix chaînés

G2010/18 R. AEBERHARDT - L. DAVEZIES
Conditional Logit with one Binary Covariate: Link between the Static and Dynamic Cases

G2011/01 T. LE BARBANCHON - B. OURLIAC - O. SIMON
Les marchés du travail français et américain face aux chocs conjoncturels des années 1986 à 2007 : une modélisation DSGE

G2011/02 C. MARBOT
Une évaluation de la réduction d'impôt pour l'emploi de salariés à domicile

G2011/03 L. DAVEZIES
Modèles à effets fixes, à effets aléatoires, modèles mixtes ou multi-niveaux : propriétés et mises en œuvre des modélisations de l'hétérogénéité dans le cas de données groupées

G2011/04 M. ROGER - M. WASMER
Heterogeneity matters: labour productivity differentiated by age and skills

G2011/05 J.-C. BRICONGNE - J.-M. FOURNIER
V. LAPÈGUE - O. MONSO
De la crise financière à la crise économique
L'impact des perturbations financières de 2007 et 2008 sur la croissance de sept pays industrialisés

G2011/06 P. CHARNOZ - É. COUDIN - M. GAINI
Wage inequalities in France 1976-2004: a quantile regression analysis

G2011/07 M. CLERC - M. GAINI - D. BLANCHET
Recommendations of the Stiglitz-Sen-Fitoussi Report: A few illustrations

G2011/08 M. BACHELET - M. BEFFY - D. BLANCHET
Projeter l'impact des réformes des retraites sur l'activité des 55 ans et plus : une comparaison de trois modèles

G2011/09 C. LOUVOT-RUNAVOT
L'évaluation de l'activité dissimulée des entre-prises sur la base des contrôles fiscaux et son insertion dans les comptes nationaux

G2011/10 A. SCHREIBER - A. VICARD
La tertiarisation de l'économie française et le ralentissement de la productivité entre 1978 et 2008

G2011/11 M.-É. CLERC - O. MONSO - E. POULIQUEN
Les inégalités entre générations depuis le baby-boom

G2011/12 C. MARBOT et D. ROY
Évaluation de la transformation de la réduction d'impôt en crédit d'impôt pour l'emploi de salariés à domicile en 2007

G2011/13 P. GIVORD - R. RATHELOT - P. SILLARD
Place-based tax exemptions and displacement effects: An evaluation of the Zones Franches Urbaines program

G2011/14 X. D'HAULTFOEUILLE - P. GIVORD - X. BOUTIN
The Environmental Effect of Green Taxation: the Case of the French "Bonus/Malus"

G2011/15 M. BARLET - M. CLERC - M. GARNEO - V. LAPÈGUE - V. MARCUS
La nouvelle version du modèle MZE, modèle macroéconométrique pour la zone euro

G2011/16 R. AEBERHARDT - I. BUONO - H. FADINGER
Learning, Incomplete Contracts and Export Dynamics: theory and Evidence form French Firms

G2011/17 C. KERDRAIN - V. LAPÈGUE
Restrictive Fiscal Policies in Europe: What are the Likely Effects?

G2012/01 P. GIVORD - S. QUANTIN - C. TREVIEN
A Long-Term Evaluation of the First Generation of the French Urban Enterprise Zones

G2012/02 N. CECI-RENAUD - V. COTTET
Politique salariale et performance des entreprises

G2012/03 P. FÉVRIER - L. WILNER
Do Consumers Correctly Expect Price Reductions? Testing Dynamic Behavior

G2012/04 M. GAINI - A. LEDUC - A. VICARD
School as a shelter? School leaving-age and the business cycle in France

G2012/05 M. GAINI - A. LEDUC - A. VICARD
A scarred generation? French evidence on young people entering into a tough labour market