# School as a shelter? School leaving-age and the business cycle in France

Mathilde Gaini, Aude Leduc, Augustin Vicard

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Mathilde Gaini, Aude Leduc, Augustin Vicard. School as a shelter? School leaving-age and the business cycle in France. 2012. hal-05474164

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Direction des Études et Synthèses Économiques

G 2012 / 04

School as a shelter? School leaving-age
and the business cycle in France

Mathilde GAINI, Aude LEDUC et 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 / 04

School as a shelter? School leaving-age
and the business cycle in France

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

MAI 2012

We are grateful to Patrick AUBERT, Luc BEHAGEL, Pierre CAHUC, Sandra MCNALLY, 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>
# School as a shelter?
## School leaving-age and the business cycle in France

### Abstract

This paper examines the impact of the business cycle on school-leaving decisions in France for the period 1983-2009. Business cycle effects are twofold. On the one hand, bad economic conditions reduce the opportunity cost of schooling and may induce higher school participation. On the other hand, it could entail a loss of income for families which may bear no more the cost of their children's education. Using the French Labor Force Surveys, we estimate the effects of current and past unemployment rates on school leaving decisions. We find that some students postpone their entry into the labor market during an economic crisis. Younger students and students from lower social background at a given age are slightly more likely to delay their entry in the labor market. These effects are statistically significant but weak. Our results suggest that most students have an education target level or that only few of them are able to anticipate or postpone their entry to mitigate the effects of the business cycle.

**Keywords:** Business cycle, Endogeneous labour market entry, Initial labour market conditions

### Continuer les études pour laisser passer la crise ?
## L'effet du cycle économique sur l'âge de fin d'études

### Résumé

Ce document étudie l'effet du cycle économique sur la décision de sortie du système scolaire en France, de 1983 à 2009. En théorie, l'impact de la conjoncture est ambigu. Une mauvaise conjoncture réduit les possibilités d'emploi des jeunes et pourrait les inciter à rester plus longtemps dans le système scolaire. Mais, à l'inverse, une situation économique dégradée peut fragiliser la situation financière de certains parents, qui ne pourraient dès lors plus payer le coût des études de leurs enfants. À l'aide des enquêtes Emploi, nous estimons l'effet du chômage courant et passé sur la décision de quitter l'école (avec ou sans diplôme). Nous trouvons que seule une faible part des lycéens et étudiants repoussent leur entrée sur le marché du travail en restant à l'école lors des périodes de mauvaise conjoncture. Les plus jeunes et ceux dont le père est ouvrier ou employé ont légèrement plus tendance à repousser leur sortie d'études. Nos résultats suggèrent que la plupart des étudiants décident une fois pour toutes de leur niveau d'études, ou que seule une faible part d'entre eux sont en mesure d'anticiper ou de repousser leur sortie du système scolaire pour se protéger des effets du cycle économique.

**Mots-clés :** Cycle économique, endogénéité de la date d'entrée sur le marché du travail, conjoncture à l'entrée du marché du travail
# 1 Introduction

A great amount of economic literature is dedicated to understanding the determinants of demand for education. Lot of these determinants have been extensively studied in the empirical literature: returns to education, social background, education supply, etc. By contrast, only few papers focus on the links between the business cycle and the decision to leave school.

Bad economic conditions may have two opposite effects on school participation. On the one hand, they entail reduced job opportunities for school leavers. This reduces the opportunity cost of schooling and may induce higher school participation. Thus, school attendance may be countercyclical: enrollment could rise with unemployment. But, on the other hand, adverse economic conditions generate unemployment. If some families, affected by unemployment, become financially constrained and cannot borrow to invest in education, this would tend to lower the school enrollment rate. This would also be the case if some students finance their studies by working and cannot find appropriate jobs anymore because of bad labor market conditions. When considering both potential effects, it is difficult to predict the direction and the intensity of the impact of unemployment on school enrollment.

In this paper, we empirically investigate this question, using French data over the period 1983-2009. We focus on annual retention rate which is defined as the proportion of a cohort enrolled in school in the previous year that is still enrolled in the current year. The effect of unemployment on the probability of leaving school is statistically significant, but relatively weak. According to our main specification, young students aged 18 have a probability of 9.6% of leaving school when the youth unemployment rises from 18% to 25%, and a probability of 11.3% when unemployment drops from 18% to 15%.<fnref n="1" /> The difference between both probabilities is statistically significant but weak. The effect seems to be larger for young people aged between 16 and 20 years. We also find a larger effect for young people from lower social background at a given age. In comparison, the probability of leaving school at 18 year old decreased by about 10 percentage points between the mid-1980s and the mid-1990s in response to an educational policy. Finally, we do not find any difference between men and women.

Our results contribute to the scarce literature about business cycle effects on school-leaving decisions. As far as the effect of business cycle on demand for education could be country-specific, dependent on the schooling system, collecting results for different countries is important. In particular, France presents several

<footnote n="1">¹During our period of analysis, French youth unemployment ranged from 14% to 24%.</footnote>
peculiarities. For example, tuitions in France are very low compared to tuitions in the U.S.. French students are also less often employed during their studies than in the U.S.. Moreover, before the post-secondary education's reforms in the 2000s, almost every student completing one more year of post-secondary education could earn a new degree ("DEUG" for two years of post-secondary education, "licence" for 3 years, "maîtrise" for four years and "DEA" or "DESS" for five years). Remaining longer at school therefore entailed not only a higher level of schooling but also a higher degree. Yet, our results are in line with most of the papers on other countries. They suggest that most students have an education target level or that only few of them are able to anticipate or postpone their entry to mitigate the effects of the business cycle.

These results are of primary interest for empirical work aiming at measuring the so-called *scarring effect*: i.e., how much income will one lose when she leaves school during an economic crisis? We show that, although school leaving year endogeneity cannot be completely discarded, the bias should remain very small.

This paper is organized as follows. Section 2 summarizes the main results of the (scarce) literature on our subject. Sections 3 and 4 describe our dataset and the econometric model, while sections 5 and 6 present our results and proceed to some robustness checks. Section 7 concludes.

## 2 Literature

The retention phenomenon has been little studied in the literature. Most of the papers we are aware of focus on the U.S. and find a non significant or small positive relationship between unemployment and school enrollment rates. For instance, Betts and McFarland (1995), using US data on community college between the late 1960s and the mid-1980s, find that a 1 percentage point increase in the unemployment rate of recent high school graduates (respectively of adults) is associated with a rise in full-time school attendance of about 0.5% (resp. 4%). Card and Lemieux (2001) use the October CPS files for 1968-1996 and find that a rise in the prime-age male (25-54) unemployment rate from 3.5% to 6.5% is predicted to raise enrollment of seventeen-year-olds by about 1 percentage point. Dellas and Sakellaris (2003), using US data from 1968 to 1988 on college graduates, conclude that a one percentage point increase in unemployment rate is associated with a 2% increase in enrollment rate. Boffy-Ramirez, Hansen, and Mansour (2010) using US data between 1979 and 1994 find that men's odds of enrolling in college increase by 1.2 percentage point following a 1 percentage point increase in the unemployment rate.
Concerning other countries, Messer and Wolter (2010), using Swiss data from 1981 to 2001, and Genda, Kondo, and Ohta (2010) using Japanese data, also find a slightly countercyclical pattern.

Few authors find a negative effect of unemployment on enrollment and underline the role of credit constraints in the demand for education. Using CPS between 1947 and 1974, Edwards (1976) finds that the retention and enrollment rates of teenage girls (16-17-year-olds) vary procyclically, whereas there is no significant relationship for teenage boys. Her explanation focuses on the fact that, after a crisis, the opportunity cost of schooling falls less for girls than for boys because girls' productivity derives for a higher part from home activities. However, these results are at odds with the more recent ones of Card and Lemieux (2001), probably because the opportunity cost of education for young women and the labor market were very different in the fifties and in the eighties. More recently, Christian (2007) using the October school enrollment supplements to the CPS over 1968-2000 finds a slightly positive but insignificant effect of the unemployment rate on enrollment at 18-19 years old and a pro-cyclical effect of business cycle on school participation rate among people in households expected to have lower income.

To sum up, there is a large body of literature consistent with a slightly positive effect of unemployment on school enrollment. One interpretation of this small effect is that the decrease in the opportunity cost of schooling exceeds the potential negative effect on parents' or students' income stemming from credit constraints. Another interpretation, as mentioned before, would be that most students have an education target level and are therefore not influenced by current economic conditions.

Yet, most of the papers focus on the U.S. and the results could depend on the features of educational systems. The French educational system departs from the one of the U.S. on many respects, with a potentially greater effect of the business cycle on schooling decisions. For example, in France students are less often working in a paid job during their studies or more often repeat a grade than in the U.S.. There are also few restrictions in France to high-school and college enrollment. Moreover, before the post-secondary education's reforms in the 2000s, almost each supplementary year of post-secondary education ended by a degree. Remaining longer at school entailed therefore not only a higher level of schooling but also a higher degree. Education costs are also lower in France than in the U.S., which could reduce the cyclicality of schooling decisions. It is therefore interesting to focus on other countries, hereafter on France, to investigate if results are country-specific or not. Finding similar results for countries with very different educational systems would strengthen the education target level hypothesis.
# 3 Data

## 3.1 School trajectory

We use the French Labor force surveys (LFS, called in French "Enquêtes Emploi") from 1983 onwards. We focus on men and women pooled together. Using the variable "school-leaving age", we infer school trajectory since 16 year old, the French compulsory school-leaving age.<fnref n="2" /> We only retain French citizens and we exclude people older than 40 years old in order to circumscribe "memory bias". We mainly focus on people having been or being at school between 1983 and 2009.<fnref n="3" /> People being students at the time of the survey or leaving school the year of the survey are considered as censored information.<fnref n="4" /> We focus on school-leaving age between 16 and 24 years old.<fnref n="5" />

We therefore build an unbalanced panel (age-individual) and a person remains in the dataset until her school-leaving age. We create a variable "leaving-school at age a"<fnref n="6" /> which takes the value 0 for observations before the school-leaving age and the value 1 only for the year of leaving school.

Let us take an example. In LFS 2005, we observe a respondent aged 30 and who left school at 20 in 1995. This respondent corresponds to 5 observations: one for each age from 16 to 20 (and years 1991 to 1995). From 16 to 19 years old, she could have left school but chose not to do so (our variable "leaving school" takes the value 0). At 20 years old, she decided to leave school (our variable "leaving school" takes the value 1). There is no observation for ages higher than 20 for this person.

## 3.2 Business cycle indicator

We choose as indicator of economic conditions the unemployment rate of young people on the labor-market (15-24 years old) in the third quarter of the correspond-

<footnote n="2">²It is indicated to the interviewers that any interruption (resp. for more than one year) in the training is considered as the end of initial training in the 2003-2010 questionnaires (resp. 1982-2002).</footnote>

<footnote n="3">³For robustness checks we also run estimations over the restricted periods 1990-2009 and 1995-2009, see Section 6.</footnote>

<footnote n="4">⁴Note that we retain information from 16 to *age* − 1 because some of them can leave school after the date of the interview.</footnote>

<footnote n="5">⁵We restrict the analysis to ages 16 to 24 because the number of students older than 24 is low compared to the sample rate.</footnote>

<footnote n="6">⁶We retain as definition of age the age reached in the year.</footnote>
ing year, as French young people leave school mostly during the third quarter (see Appendix A).

Figure 1 displays the unemployment rate of young people between 1983 and 2009 and the probability (in %) of staying at least one more year at school for students between 16 and 24, adjusted for trends in educational attainment (see Appendix B for the same figures without any adjustment).<sup>7</sup> It also displays the same figures for each age-group between 16 and 24. The correlation is positive and higher for 16 to 20 years old than for older age-groups.

<figure><img src="image_3.png" /><figcaption>Figure 1: Proportion of students staying at school and current unemployment rate</figcaption></figure>

<footnote n="7"><sup>7</sup>More precisely, we regress the proportion of students staying at school on splines to control for the increase in educational attainment and graph the residuals, see section 4.2.</footnote>
18 years - Men and Women

<figure><img src="image_4.png" /><figcaption>(c) 18 years</figcaption></figure>

19 years - Men and Women

<figure><img src="image_5.png" /><figcaption>(d) 19 years</figcaption></figure>

20 years - Men and Women

<figure><img src="image_6.png" /><figcaption>(e) 20 years</figcaption></figure>

21 years - Men and Women

<figure><img src="image_7.png" /><figcaption>(f) 21 years</figcaption></figure>

22 years - Men and Women

<figure><img src="image_8.png" /><figcaption>(g) 22 years</figcaption></figure>

23 years - Men and Women

<figure><img src="image_9.png" /><figcaption>(h) 23 years</figcaption></figure>
<figure><img src="image_10.png" /><figcaption>(i) 24 years</figcaption></figure>

<figure><img src="image_11.png" /><figcaption>(j) All ages</figcaption></figure>

Note: "residuals" stands for residuals from the logistic regression of the dummy variable "staying at school" on splines.

# 4 Econometric model

## 4.1 Taking into account the rise in educational attainment

Our main period of analysis is from 1983 to 2009. France experienced a huge increase in high-school educational attainment from 1985 to 1993 and an increase in post-secondary educational attainment from 1991 to 1995 (see Durier, 2006). This rise in educational attainment can be related to a political impulse in the educational system aimed at reducing unemployment among youngsters – which had been persistently higher than 20% since 1983. Students positively reacted and remained longer at school. This structural trend could entail spurious correlations and bias our estimations if we do not control for it. For example, the increase in post-secondary educational attainment took place during an economic downturn –1993-1997– which could entail a spurious negative correlation between current unemployment and leaving school in our estimation. Conversely, from 1989 to 1992 unemployment rates were low, around 15% and high-school educational attainment increased, potentially leading to a spurious positive correlation. Moreover, the share of students repeating a grade sharply decreased since the end of the 1990s, entailing a downward trend in the attainment rate during the 2000s. It is therefore necessary to control for these trends in educational attainment to disentangle business cycle effects and structural trends effects.

We therefore retain 1983-2009 for our main analysis to have enough time periods to make robust inference controlling for the increase in school attainment. More
precisely, we include a piecewise linear function of time with one trend break in each regression. The timing of the breaks were determined in order to maximize the BIC of the regressions. We finally perform robustness checks on shorter periods of time (respectively 1990-2009 and 1995-2009), to make sure that our results are robust to changes in the observation windows.

## 4.2 The econometric model

### For all ages - pooled regression

We run a logistic regression of past and current unemployment rates (resp. URt and URt-1) on the instantaneous probability of leaving school L$_{i,t}$. We firstly run a pooled regression, assuming homogenous effects at all ages of the unemployment rates on the instantaneous probability of leaving school. This yields the following model:

$$P(L_{i,t}) = F(\alpha + \beta_0 \cdot UR_t + \beta_1 \cdot UR_{t-1} + \gamma_1 \cdot t + \gamma_2 \cdot (t - \bar{T}) \cdot 1_{t \ge \bar{T}} + \zeta_{16} \cdot 1_{a=16} + \dots + \zeta_{24} \cdot 1_{a=24})$$

More precisely, L$_{i,t}$ is a dummy variable equal to 1 if the student chooses to leave school year t, and to 0 if she chooses to stay at school. We control the regression by piecewise linear function of time with a break at year $\bar{T}$ (year $\bar{T}$ is reported in Table 1) and age dummies.<fnref n="8" /> We choose F as logistic function. This model is clearly "coarse" and we will mainly focus on models age per age hereafter, in order to allow for heterogeneity of unemployment effects according to age. Yet, the pooled regression is useful to illustrate the main features of the model and some robustness checks, since only the intensity of the effects but not the sign vary with age (see Table 1).

We are mainly interested in $\beta_0$, the effect of the current unemployment rate on school leaving decision. We add the past unemployment rate as a regressor in our preferred specification because it explains the school leaving decision and is correlated with the current unemployment rate, so that, if omitted, the estimated coefficient of the current unemployment rate would be potentially biased downward. To understand this, imagine that unemployment was very high last year. If unemployment has an effect, more students than usual will choose to stay at school. But, for most of them, they won't stay as long in the schooling system as would have done usual students who would have stayed at school whatever the unemployment rate: they have a higher probability to leave school one or two years after having decided to stay (one or two more years) at school. For these two

<footnote n="8">⁸The set of age dummies would be equivalent to the baseline hazard function in a proportional hazard model.</footnote>
reasons (past unemployment positively correlated with current unemployment and direct effect of past unemployment on the probability of leaving school), omitting past unemployment could lead us to underestimate the effect of current economic condition on the choice to stay (or to leave) school.<fnref n="9" /> This point is very important, because unemployment shows a high degree of persistence. If students postpone their entry into labor market during economic downturns then we should find that $\beta_0$ is negative and $\beta_1$ positive.<fnref n="10" />

### For each age

We also run separated regressions age per age to allow for heterogenous effects of unemployment according to age.

$$P(L_{i,t}^a) = F(\alpha^a + \beta_0^a \cdot UR_t + \beta_1^a \cdot UR_{t-1} + \gamma_1^a \cdot t + \gamma_2^a \cdot (t - \bar{T})^a) \mathbf{1}_{t \ge \bar{T}^a}$$

$L_{i,t}^a$ is a dummy variable equal to 1 if the student chooses to leave school at age $a$ the year $t$, and to 0 if she chooses to stay at school. We perform a logistic regression of $L_{i,t}^a$ on our variables of interest, current and past unemployment rates at the year of aging $a$. Breaks in trends are age-dependent (years $\bar{T}^a$ are reported in Table 1).

## 4.3 Individual data, weights and cluster

We rely on individual data for our estimations rather than on aggregated ones, even if the main source of identification is the variation of the unemployment rate across years. The probability of leaving school is very low for young pupils or students aged 16 or 17 (see Table 1), particularly after the strong increase in educational attainment between the mid-1980s and the mid-1990s. Using a logistic linking function between the unemployment rate and the probability to leave school seems therefore more accurate than assuming a linear relationship. This logistic regression is close to a least squares regression on aggregated data (see Appendix C). Moreover, we use retrospective information so year-cells corresponding to older

$$P(L_{i,t}) = F(\alpha + (\beta_0 + \beta_1) \cdot UR_t - \beta_1 \cdot (UR_t - UR_{t-1}) + \gamma_1 \cdot t + \gamma_2 \cdot (t - \bar{T}) \mathbf{1}_{t \ge \bar{T}} + \zeta_{16} \cdot \mathbf{1}_{a=16} + \dots + \zeta_{24} \cdot \mathbf{1}_{a=24})$$

Combining the coefficients of our model, one can therefore interpret the model in terms of level and variation of the unemployment rate.

<footnote n="9">⁹We explore the alternative assumption that students can delay for two years, running estimations with two lags of unemployment. We also use the forward of unemployment as robustness checks assuming that students can advance their labor market entry for one year, see Table 3.</footnote>

<footnote n="10">¹⁰More exactly, if students can only postpone one year, then $\beta_1$ is positive, if they postpone either one or two years, then $\beta_1$ would be a "mix" of the effects of $UR_{i,t-1}$ and $UR_{i,t-2}$. Note also that this model is equivalent to the following one:</footnote>
years of analysis are over-represented in our sample. We weight data in order to give the same aggregated weight for each year-age cell i.e. for each unemployment-age cell.

We cluster standard errors at the year level to allow for intra-years correlations.

# 5 Results

We present the odds ratio both for the pooled and for the age per age models, see Table 1.

An odds ratio of 1 indicates that the probability of leaving school does not depend on unemployment. For the pooled regression model (all age-groups) as well as for age per age models, odds ratio of the current unemployment variable are lower than one. The odds ratio are significantly different from 1 at the 1% level for the pooled regression and 17-20 and 22 years old samples. They are significantly different from 1 at the 5% level for 16 and 23 years old samples. It seems therefore that, for each age-groups except for the 21 and 24 years old, when current unemployment increases, the probability of leaving school decreases. Interestingly, students who react the most to business cycle, i.e. younger students, are the more able to remain one more year at school, because there is no restriction for high-school or college enrollment in France.

We also compare the predicted probabilities of leaving school after a dramatic drop of the unemployment rate to 15% and a dramatic rise of the unemployment rate to 25%, in order to illustrate the size of the effect. More precisely, in both cases the past unemployment is set at 18% and the reference year at 2000. We therefore compare the effect of a decrease in unemployment from 18% to 15% and of a rise in unemployment from 18% to 25%. Results are almost identical whatever the baseline level of the unemployment rate.

For instance, 18 years old students have an estimated probability of 9.6% of leaving school when the young entrants unemployment rises to a very high level (25%), and a probability of 11.3% when unemployment drops to a very low level (15%) and the difference is statistically significant at a 1% level. However the effect is relatively weak whatever the age: the difference in probability between the two "extreme" levels of unemployment rate ranges from 1 to 3 percentage points across ages. In comparison, the structural increase in educational attainment between the mid-1980s and the mid-1990s decreased the probability to leave school at 18 years old by about 10 percentage points (see Figure 4 in appendix G).
<table><caption>Table 1: Logistic regression of the choice of leaving school on unemployment</caption><thead><tr><th>Odd-ratio</th><th>16 years</th><th>17 years</th><th>18 years</th><th>19 years</th><th>20 years</th></tr></thead><tbody><tr><td>15-24 years Unemployment</td><td>0.985**<br>(0.006)</td><td>0.968***<br>(0.009)</td><td>0.982***<br>(0.006)</td><td>0.986***<br>(0.005)</td><td>0.982***<br>(0.005)</td></tr><tr><td>Lag of 15-24 years Unemployment</td><td>1.007<br>(0.008)</td><td>1.011<br>(0.010)</td><td>1.010<br>(0.007)</td><td>1.013**<br>(0.006)</td><td>1.017***<br>(0.005)</td></tr><tr><td>trend</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Estimated break</td><td>1992</td><td>1991</td><td>1992</td><td>1993</td><td>1993</td></tr><tr><td>Predicted propor. of school-leavers (%)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>when unemployment rises</td><td>3.868<br>(0.140)</td><td>3.204<br>(0.218)</td><td>9.611<br>(0.315)</td><td>11.240<br>(0.370)</td><td>16.875<br>(0.425)</td></tr><tr><td>from 18% to 25% (1)</td><td>4.456<br>(0.148)</td><td>4.393<br>(0.155)</td><td>11.336<br>(0.289)</td><td>12.775<br>(0.270)</td><td>19.608<br>(0.412)</td></tr><tr><td>when unemployment drops</td><td>0.588**<br>(0.237)</td><td>1.189***<br>(0.322)</td><td>1.725***<br>(0.579)</td><td>1.535***<br>(0.576)</td><td>2.733***<br>(0.715)</td></tr><tr><td>from 18% to 15% (2)</td><td>0.588**<br>(0.237)</td><td>1.189***<br>(0.322)</td><td>1.725***<br>(0.579)</td><td>1.535***<br>(0.576)</td><td>2.733***<br>(0.715)</td></tr><tr><td>Diff. of propor. (2)-(1)</td><td>286270</td><td>260753</td><td>238637</td><td>190524</td><td>152679</td></tr><tr><td>N</td><td>286270</td><td>260753</td><td>238637</td><td>190524</td><td>152679</td></tr><tr><td>Odd-ratio</td><td>21 years</td><td>22 years</td><td>23 years</td><td>24 years</td><td>All ages</td></tr><tr><td>15-24 years Unemployment</td><td>0.996<br>(0.006)</td><td>0.990***<br>(0.003)</td><td>0.987**<br>(0.005)</td><td>0.997<br>(0.007)</td><td>0.987***<br>(0.004)</td></tr><tr><td>Lag of 15-24 years Unemployment</td><td>1.007<br>(0.005)</td><td>1.021***<br>(0.004)</td><td>1.010**<br>(0.005)</td><td>0.998<br>(0.007)</td><td>1.010**<br>(0.004)</td></tr><tr><td>Spline</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Estimated break</td><td>1993</td><td>2003</td><td>1999</td><td>1996</td><td>1991</td></tr><tr><td>Predicted propor. of school-leavers (%)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>when unemployment rises</td><td>19.798<br>(0.639)</td><td>22.889<br>(0.480)</td><td>29.849<br>(0.752)</td><td>37.386<br>(1.100)</td><td></td></tr><tr><td>from 18% to 25% (1)</td><td>20.374<br>(0.424)</td><td>24.751<br>(0.367)</td><td>32.742<br>(0.502)</td><td>38.099<br>(0.768)</td><td></td></tr><tr><td>when unemployment drops</td><td>0.576<br>(0.884)</td><td>1.861***<br>(0.601)</td><td>2.893**<br>(1.115)</td><td>0.714<br>(1.599)</td><td></td></tr><tr><td>from 18% to 15% (2)</td><td>0.576<br>(0.884)</td><td>1.861***<br>(0.601)</td><td>2.893**<br>(1.115)</td><td>0.714<br>(1.599)</td><td></td></tr><tr><td>Diff. of propor. (2)-(1)</td><td>110994</td><td>80598</td><td>55629</td><td>35378</td><td>1411462</td></tr><tr><td>N</td><td>110994</td><td>80598</td><td>55629</td><td>35378</td><td>1411462</td></tr></tbody></table>

Note: standard errors clustered at year-age level are in parenthesis.

Our regression yields another interesting result. The odds ratio of the lag of unemployment are always greater than one (except for 24 years old, non significant) and they are significant at a 5% level for pooled regression and for 19 and 23 years

<footnote>* p<0.10, ** p<0.05, *** p<0.01</footnote>
old and at a 1% level for 20 and 22 years old. An increase in past unemployment
rate therefore increases the probability of leaving school the year after, which is
a result consistent with the existence of a selection effect: people having delayed
their exit in the past are more likely to leave school in the current year.

Men and Women

We run separated regressions on men and women to test if there are differences in
effects between sex. We find no differences, see Appendix E. This suggests that
opportunity costs for men and women are decreasing in the same way for both sex
during economic downturns.

Social background

We estimate our main model on two subsamples depending on father occupation: low social background vs high social background.<fnref n="11" /> We find that students with a low social background react more to changes in unemployment rates, see Appendix F. In introduction, we presented the two potential effects of an increase in unemployment on school leaving decision: (1) decreasing opportunity costs of education entailing a lower school-leaving rate, (2) higher credit constraints entailing a higher school-leaving rate. Our results suggest that the first effect is stronger than the second one for both groups. Moreover, it seems that students with lower social background are more impacted by adverse economic conditions during economic downturns, entailing a higher decrease in opportunity costs of education. These results could be driven for a part by different scholar level and specialization depending on father occupation and correlated with a higher or lower probability to react to changes in unemployment rate. This is also in line with higher effects of business cycle on youngest students, as the unemployment rate of young entrants is stronger for the less educated ones.

6 Robustness checks

In this section, we show that our results are robust across four dimensions: (i) different period of analysis; (ii) the introduction of 0, 1 or 2 lags of unemployment and 0 or 1 forwards of unemployment as covariates; (iii) other unemployment rates as regressors; (iv) different weights and cluster schemes. We only show the results from the pooled regression (16-24 years old). Results for each age groups are qualitatively similar and available upon request from the authors.

<footnote n="11">¹¹To be very accurate, to the attention of French readers, low social background corresponds to "ouvriers" (CS=6) and "employes" (CS=5), whereas high social background corresponds to "professions intermédiaires (CS=4) and "cadres" (CS=3).</footnote>
## 6.1 Different periods of time

We estimate our model on different periods of time, 1983-2009, 1990-2009 and 1995-2009, to show that our results are robust to the way we control for the rise in educational attainment that takes place between 1983 and 1995. Whatever the time period considered, results are qualitatively and quantitatively in line with our main specification: current unemployment has a negative effect on leaving school and past unemployment has a positive effect (Table 2, columns 4 and 5). Mechanically, results from the shorter observation windows are less precise. We now turn to the results on the 1983-2009 period without controlling by time trends or by forcing the time break at 1995, instead of 1991 (Table 2, columns 2 and 3). Current and lagged unemployment estimates have again the same sign as in the main specification (column 1), but insignificant when we do not control for time trends. Results by age-group – not displayed – are similar.

<table><caption>Table 2: Logistic regression of the choice of leaving school on unemployment (various periods, all ages)</caption><thead><tr><th>Odd-ratio</th><th>1983-2009</th><th>1983-2009</th><th>1983-2009</th><th>1990-2009</th><th>1995-2009</th></tr></thead><tbody><tr><td>15-24 years Unemployment</td><td>0.987***<br>(0.004)</td><td>0.990*<br>(0.005)</td><td>0.985<br>(0.015)</td><td>0.983***<br>(0.004)</td><td>0.987***<br>(0.003)</td></tr><tr><td>Lag of 15-24 years Unemployment</td><td>1.010**<br>(0.004)</td><td>1.014**<br>(0.005)</td><td>1.005<br>(0.016)</td><td>1.013**<br>(0.005)</td><td>1.009*<br>(0.005)</td></tr><tr><td>Trend</td><td>Yes</td><td>Yes</td><td>No</td><td>Yes</td><td>Yes</td></tr><tr><td>Break</td><td>1991</td><td>1995</td><td></td><td></td><td></td></tr></tbody></table>

Note: standard errors clustered at the year level are in parenthesis.

## 6.2 Adding lags and forwards of unemployment rate

Table 3 reports the estimates on the pooled sample for different specifications, with more or less lags and forwards of unemployment rate. Adding past unemployment increases the negative effect of current unemployment, confirming the potential downward bias if past unemployment is not included (see column (3) and (4)). When we include the second lag of unemployment (see column (5)), the effect of the first lag is reduced and no more significant and the effect of the second lag is significant at a 5% level. This suggests that some students postpone their entry

<footnote>* p<0.10, ** p<0.05, *** p<0.01</footnote>
by two years.

If students anticipate that economic conditions will remain bad in the future, they could stay at school (see column (1) and (2)). Estimated coefficients are in line with this anticipation effect (lesser than 1 and significant at a 5% level).

<table><caption>Table 3: Logistic regression of the choice of leaving school on unemployment (various lag or forward of unemployment, all ages)</caption><thead><tr><th>Odd-ratio</th><th>1983-2009</th><th>1983-2009</th><th>1983-2009</th><th>1983-2009</th><th>1983-2009</th></tr></thead><tbody><tr><td>Forward of 15-24 years Unemployment</td><td>0.991***<br>(0.002)</td><td>0.994*<br>(0.003)</td><td></td><td></td><td></td></tr><tr><td>15-24 years Unemployment</td><td>0.998<br>(0.002)</td><td>0.992*<br>(0.005)</td><td>0.993**<br>(0.003)</td><td>0.987***<br>(0.004)</td><td>0.989***<br>(0.004)</td></tr><tr><td>Lag of 15-24 years Unemployment</td><td></td><td>1.007<br>(0.005)</td><td></td><td>1.010**<br>(0.004)</td><td>1.005<br>(0.005)</td></tr><tr><td>Lag 2 of 15-24 years Unemployment</td><td></td><td></td><td></td><td></td><td>1.006**<br>(0.003)</td></tr><tr><td>Trend</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Estimated break</td><td>1991</td><td>1991</td><td>1991</td><td>1991</td><td>1991</td></tr></tbody></table>

Note: standard errors clustered at the year level are in parenthesis.

## 6.3 Other unemployment rates

We estimate the same model with different regressors (Table 4). Our principal regressor has the advantage to be close to the labor market conditions of the young entrants but could be endogeneous. In fact, the decision to stay or not at school may influence the 15-24 years unemployment rate. We use the 25-49 years unemployment rate to be sure to have an exogenous regressor with the disadvantage that it is more distant from the labor market entry conditions of young people. We also use the unemployment rate of young entrants<fnref n="12" /> (1-4 experienced year) to be closer to the labor market entry conditions. The three different unemployment indicators yield the same picture, qualitatively and quantitatively. Point

<footnote>* p<0.10, ** p<0.05, *** p<0.01</footnote>

<footnote n="12">¹²The young entrants unemployment rate is not adjusted for the 2003 methodological break in calculating unemployment figures.</footnote>
estimates using 15-24 years and 25-49 years unemployment rate are logically not identical because their scale of variations are not the same: when the 25-49 years unemployment rate increases by 1 point, the 15-24 unemployment rate increases by 3 points. The effects on the probability of leaving school of an increase of 1 point in the 25-49 years unemployment rate and of 3 points in the 15-24 years unemployment rate are indeed very close.

<table><caption>Table 4: Logistic regression of the choice of leaving school on unemployment (various unemployment rate, all ages)</caption><thead><tr><th>Odd-ratio</th><th>UR 15-24 years</th><th>UR Young Entrants</th><th>UR 25-49 years</th></tr></thead><tbody><tr><td>Unemployment</td><td>0.987***<br>(0.004)</td><td>0.990***<br>(0.002)</td><td>0.959***<br>(0.010)</td></tr><tr><td>Lag of Unemployment</td><td>1.010**<br>(0.004)</td><td>1.013***<br>(0.003)</td><td>1.049**<br>(0.013)</td></tr><tr><td>Trend</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Estimated break</td><td>1991</td><td>1991</td><td>1991</td></tr><tr><td>N</td><td>1411462</td><td>1411462</td><td>1411462</td></tr></tbody></table>

Note: standard errors clustered at the year level are in parenthesis.
Analysis period: 1983-2009

## 6.4 Different weighting schemes

We weighted our data at an age-year level in order to give the same weight to each birth cohort in the pooled regression. Without weights, we over-represent age-year cells for older years but if effects are quite homogenous across cohorts, non-weighted estimations should be close to weighted estimations. Results with or without weighted data are very similar, see Appendix D.

<footnote>* p<0.10, ** p<0.05, *** p<0.01</footnote>
# 7 Conclusion

We find that the school-leaving age in France is endogenous to the business cycle, but the negative effect of unemployment on school leaving decision is quite small. Our results are consistent with the literature on other countries. Finding similar results for countries with very different educational system would favor the idea that most students have an education target level.

Our results suggest that many students do not have incentive to stay at school even if unemployment rate is very high. They know their scholar abilities and can anticipate if they will have success the coming year. If they cannot obtain a higher degree or use an additional education year to improve their productivity and their future wage, they will not benefit from staying one more year at school. The opportunity cost of one more education year is too high for them and they will prefer to enter into the labor market even if they are unemployed (because of professionalisation training process or help for job search).

Finally, since students react quite little to changes in economic conditions, comparing cohorts of young people entering into the labor market in different economic conditions without controlling for selection is thus not likely to induce bias in estimations comparing labor market entry cohorts (see Appendix G for more details).
References

BETTS, J. R., AND L. L. McFARLAND (1995): "Safe port in a storm: The impact of labor market conditions on community college enrollments," *The Journal of Human Resources*, 30(4), 741–765.

BOFFY-RAMIREZ, E., B. HANSEN, AND H. MANSOUR (2010): “The effect of business cycles on educational attainment,” Discussion paper.

CARD, D., AND T. LEMIEUX (2001): “Dropout and Enrollment Trends in the Postwar Period: What Went Wrong in the 1970s?,” in *Risky Behavior among Youths: An Economic Analysis*, NBER Chapters, pp. 439–482. National Bureau of Economic Research, Inc.

CHRISTIAN, M. S. (2007): “Liquidity constraints and the cyclicality of college enrollment in the United States,” *Oxford Economic Papers*, 59(1), 141.

DELLAS, H., AND P. SAKELLARIS (2003): “On the cyclicality of schooling: theory and evidence,” *Oxford Economic Papers*, 55(1), 148.

DURIER, S. (2006): “Les progrès de la scolarisation des jeunes de 1985 à 2003,” *Données sociales-La société française*.

EDWARDS, L. N. (1976): “School retention of teenagers over the business cycle,” *The Journal of Human Resources*, 11(2), 200–208.

GENDA, Y., A. KONDO, AND S. OHTA (2010): “Long-Term Effects of a Recession at Labor Market Entry in Japan and the United States,” *The Journal of Human Resources*, 45(1).

MESSER, D., AND S. C. WOLTER (2010): “Time-to-degree and the business cycle,” *Education economics*, 18(1), 111–123.
A Appendix: Most students leave school during the third quarter

<figure><img src="image_12.png" /></figure>

Source: "Generation" Survey Cereq, 1998
B Appendix: Retention rate

<figure><img src="image_13.png" /><figcaption>Figure 2: Probability of completing one more year of schooling</figcaption></figure>
<figure><img src="image_14.png" /><figcaption>22 years - Men and Women</figcaption></figure>

(g) 22 years

<figure><img src="image_15.png" /><figcaption>23 years - Men and Women</figcaption></figure>

(h) 23 years

<figure><img src="image_16.png" /><figcaption>24 years - Men and Women</figcaption></figure>

(i) 24 years

<figure><img src="image_17.png" /><figcaption>All ages - Men and Women</figcaption></figure>

(j) All ages
## C Appendix: Main model with aggregated data

<table><caption>Table 5: OLS regression of the choice of leaving school on unemployment (aggregated data)</caption><thead><tr><th></th><th>16 years</th><th>17 years</th><th>18 years</th><th>19 years</th><th>20 years</th></tr></thead><tbody><tr><td>15-24 years Unemployment</td><td>-0.042<br>(0.038)</td><td>-0.121***<br>(0.041)</td><td>-0.131**<br>(0.063)</td><td>-0.134*<br>(0.068)</td><td>-0.283***<br>(0.084)</td></tr><tr><td>Lag of 15-24 years Unemployment</td><td>0.008<br>(0.039)</td><td>0.019<br>(0.042)</td><td>0.069<br>(0.064)</td><td>0.148**<br>(0.070)</td><td>0.264***<br>(0.086)</td></tr><tr><td>Trend</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Estimated break</td><td>1992</td><td>1991</td><td>1992</td><td>1993</td><td>1993</td></tr><tr><td>Predicted propor.<br>of school-leavers (%)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>when unemployment rises</td><td>4.002<br>(0.253)</td><td>3.141<br>(0.275)</td><td>9.729<br>(0.420)</td><td>11.240<br>(0.459)</td><td>16.778<br>(0.565)</td></tr><tr><td>from 18% to 25% (1)</td><td>4.421<br>(0.174)</td><td>4.354<br>(0.189)</td><td>11.039<br>(0.290)</td><td>12.575<br>(0.318)</td><td>19.608<br>(0.392)</td></tr><tr><td>when unemployment drops</td><td>4.421<br>(0.174)</td><td>4.354<br>(0.189)</td><td>11.039<br>(0.290)</td><td>12.575<br>(0.318)</td><td>19.608<br>(0.392)</td></tr><tr><td>from 18% to 15% (2)</td><td>0.419<br>(0.377)</td><td>1.213***<br>(0.412)</td><td>1.310**<br>(0.627)</td><td>1.335*<br>(0.683)</td><td>2.830***<br>(0.841)</td></tr><tr><td>Diff. of propor. (2)-(1)</td><td>0.419<br>(0.377)</td><td>1.213***<br>(0.412)</td><td>1.310**<br>(0.627)</td><td>1.335*<br>(0.683)</td><td>2.830***<br>(0.841)</td></tr><tr><td>N</td><td>27</td><td>27</td><td>27</td><td>27</td><td>27</td></tr></tbody></table><table><thead><tr><th></th><th>21 years</th><th>22 years</th><th>23 years</th><th>24 years</th><th>All years</th></tr></thead><tbody><tr><td>15-24 years Unemployment</td><td>-0.057<br>(0.099)</td><td>-0.185**<br>(0.089)</td><td>-0.283**<br>(0.121)</td><td>-0.061<br>(0.175)</td><td>-0.184<br>(0.327)</td></tr><tr><td>Lag of 15-24 years Unemployment</td><td>0.124<br>(0.102)</td><td>0.388***<br>(0.089)</td><td>0.204<br>(0.125)</td><td>-0.045<br>(0.182)</td><td>0.144<br>(0.333)</td></tr><tr><td>Trend</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Estimated break</td><td>1993</td><td>2003</td><td>1999</td><td>1996</td><td>1996</td></tr><tr><td>Predicted propor.<br>of school-leavers (%)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>when unemployment rises</td><td>19.792<br>(0.667)</td><td>22.878<br>(0.652)</td><td>29.863<br>(0.924)</td><td>37.376<br>(1.213)</td><td></td></tr><tr><td>from 18% to 25% (1)</td><td>20.361<br>(0.463)</td><td>24.727<br>(0.418)</td><td>32.697<br>(0.605)</td><td>37.984<br>(0.840)</td><td></td></tr><tr><td>when unemployment drops</td><td>20.361<br>(0.463)</td><td>24.727<br>(0.418)</td><td>32.697<br>(0.605)</td><td>37.984<br>(0.840)</td><td></td></tr><tr><td>from 18% to 15% (2)</td><td>0.569<br>(0.993)</td><td>1.849**<br>(0.887)</td><td>2.834**<br>(1.211)</td><td>0.608<br>(1.749)</td><td></td></tr><tr><td>Diff. of propor. (2)-(1)</td><td>0.569<br>(0.993)</td><td>1.849**<br>(0.887)</td><td>2.834**<br>(1.211)</td><td>0.608<br>(1.749)</td><td></td></tr><tr><td>N</td><td>27</td><td>27</td><td>27</td><td>27</td><td>243</td></tr></tbody></table>

<footnote>* p<0.10, ** p<0.05, *** p<0.01</footnote>
## D Appendix: Main model with non-weighted data

<table><caption>Table 6: Logistic regression of the choice of leaving school on unemployment (non-weighted data)</caption><thead><tr><th>Odd-ratio</th><th>16 years</th><th>17 years</th><th>18 years</th><th>19 years</th><th>20 years</th></tr></thead><tbody><tr><td>15-24 years Unemployment</td><td>0.986***<br>(0.005)</td><td>0.977***<br>(0.008)</td><td>0.982***<br>(0.006)</td><td>0.987***<br>(0.005)</td><td>0.982***<br>(0.005)</td></tr><tr><td>Lag of 15-24 years Unemployment</td><td>1.009<br>(0.007)</td><td>1.007<br>(0.008)</td><td>1.012*<br>(0.006)</td><td>1.014***<br>(0.005)</td><td>1.014***<br>(0.005)</td></tr><tr><td>Trend</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Estimated break</td><td>1992</td><td>1991</td><td>1992</td><td>1993</td><td>1993</td></tr><tr><td>Predicted propor.<br>of school-leavers (%)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>when unemployment rises</td><td>3.904</td><td>3.454</td><td>9.620</td><td>11.402</td><td>17.024</td></tr><tr><td>from 18% to 25% (1)</td><td>(0.136)</td><td>(0.193)</td><td>(0.350)</td><td>(0.341)</td><td>(0.482)</td></tr><tr><td>when unemployment drops</td><td>4.482</td><td>4.320</td><td>11.359</td><td>12.812</td><td>19.740</td></tr><tr><td>from 18% to 15% (2)</td><td>(0.141)</td><td>(0.159)</td><td>(0.262)</td><td>(0.252)</td><td>(0.381)</td></tr><tr><td>Diff. of propor. (2)-(1)</td><td>0.578***<br>(0.205)</td><td>0.866***<br>(0.298)</td><td>1.740***<br>(0.558)</td><td>1.410***<br>(0.512)</td><td>2.716***<br>(0.746)</td></tr><tr><td>N</td><td>286270</td><td>260753</td><td>238637</td><td>190524</td><td>152679</td></tr></tbody></table><table><thead><tr><th>Odd-ratio</th><th>21 years</th><th>22 years</th><th>23 years</th><th>24 years</th><th>All ages</th></tr></thead><tbody><tr><td>15-24 years Unemployment</td><td>0.991*<br>(0.005)</td><td>0.992**<br>(0.004)</td><td>0.990**<br>(0.005)</td><td>0.998<br>(0.007)</td><td>0.985***<br>(0.004)</td></tr><tr><td>Lag of 15-24 years Unemployment</td><td>1.011**<br>(0.004)</td><td>1.019***<br>(0.005)</td><td>1.005<br>(0.005)</td><td>0.998<br>(0.007)</td><td>1.009**<br>(0.004)</td></tr><tr><td>Trend</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Estimated break</td><td>1993</td><td>2003</td><td>1999</td><td>1996</td><td>1991</td></tr><tr><td>Predicted propor.<br>of school-leavers (%)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>when unemployment rises</td><td>19.286</td><td>23.146</td><td>30.372</td><td>37.527</td><td></td></tr><tr><td>from 18% to 25% (1)</td><td>(0.528)</td><td>(0.533)</td><td>(0.752)</td><td>(1.104)</td><td></td></tr><tr><td>when unemployment drops</td><td>20.719</td><td>24.657</td><td>32.503</td><td>37.966</td><td></td></tr><tr><td>from 18% to 15% (2)</td><td>(0.391)</td><td>(0.410)</td><td>(0.445)</td><td>(0.761)</td><td></td></tr><tr><td>Diff. of propor. (2)-(1)</td><td>1.434*<br>(0.763)</td><td>1.511**<br>(0.725)</td><td>2.131**<br>(0.998)</td><td>0.440<br>(1.593)</td><td></td></tr><tr><td>N</td><td>110994</td><td>80598</td><td>55629</td><td>35378</td><td>1411462</td></tr></tbody></table>

Note: standard errors clustered at the year level are in parenthesis.

<footnote>* p<0.10, ** p<0.05, *** p<0.01</footnote>
E Appendix: Results by sex

<table><caption>Table 7: Men: Logistic regression of the choice of leaving school on unemployment</caption><thead><tr><th>Odd-ratio</th><th>16 years</th><th>17 years</th><th>18 years</th><th>19 years</th><th>20 years</th></tr></thead><tbody><tr><td>15-24 years Unemployment</td><td>0.985**<br>(0.007)</td><td>0.970***<br>(0.009)</td><td>0.987*<br>(0.007)</td><td>0.988*<br>(0.007)</td><td>0.985***<br>(0.006)</td></tr><tr><td>Lag of 15-24 years Unemployment</td><td>1.010<br>(0.009)</td><td>1.014<br>(0.010)</td><td>1.002<br>(0.007)</td><td>1.009<br>(0.007)</td><td>1.020***<br>(0.005)</td></tr><tr><td>Trend</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Estimated break</td><td>1992</td><td>1991</td><td>1992</td><td>1993</td><td>1993</td></tr><tr><td>Predicted propor. of school-leavers (%)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>when unemployment rises</td><td>4.421</td><td>3.671</td><td>11.734</td><td>12.877</td><td>18.457</td></tr><tr><td>from 18% to 25% (1)</td><td>(0.213)</td><td>(0.246)</td><td>(0.441)</td><td>(0.458)</td><td>(0.601)</td></tr><tr><td>when unemployment drops</td><td>5.129</td><td>4.897</td><td>13.105</td><td>14.262</td><td>20.908</td></tr><tr><td>from 18% to 15% (2)</td><td>(0.186)</td><td>(0.189)</td><td>(0.393)</td><td>(0.410)</td><td>(0.520)</td></tr><tr><td>Diff. of propor. (2)-(1)</td><td>0.708**<br>(0.326)</td><td>1.226***<br>(0.367)</td><td>1.371*<br>(0.750)</td><td>1.385*<br>(0.814)</td><td>2.451***<br>(0.919)</td></tr><tr><td>N</td><td>141215</td><td>127351</td><td>115520</td><td>89850</td><td>71189</td></tr></tbody></table><table><thead><tr><th>Odd-ratio</th><th>21 years</th><th>22 years</th><th>23 years</th><th>24 years</th><th>All ages</th></tr></thead><tbody><tr><td>15-24 years Unemployment</td><td>0.999<br>(0.007)</td><td>0.989<br>(0.007)</td><td>0.985**<br>(0.007)</td><td>1.002<br>(0.010)</td><td>0.989**<br>(0.004)</td></tr><tr><td>Lag of 15-24 years Unemployment</td><td>1.003<br>(0.007)</td><td>1.027***<br>(0.007)</td><td>1.016**<br>(0.008)</td><td>0.989<br>(0.012)</td><td>1.010**<br>(0.004)</td></tr><tr><td>Trend</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Estimated break</td><td>1993</td><td>2003</td><td>1999</td><td>1996</td><td>1991</td></tr><tr><td>Predicted propor. of school-leavers (%)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>when unemployment rises</td><td>20.827</td><td>22.729</td><td>28.729</td><td>37.996</td><td></td></tr><tr><td>from 18% to 25% (1)</td><td>(0.728)</td><td>(1.001)</td><td>(1.133)</td><td>(1.569)</td><td></td></tr><tr><td>when unemployment drops</td><td>21.056</td><td>24.662</td><td>32.031</td><td>37.457</td><td></td></tr><tr><td>from 18% to 15% (2)</td><td>(0.638)</td><td>(0.489)</td><td>(0.643)</td><td>(0.916)</td><td></td></tr><tr><td>Diff. of propor. (2)-(1)</td><td>0.229<br>(1.133)</td><td>1.932<br>(1.271)</td><td>3.301**<br>(1.460)</td><td>-0.539<br>(2.238)</td><td></td></tr><tr><td>N</td><td>51108</td><td>37140</td><td>25945</td><td>16840</td><td>676158</td></tr></tbody></table>

Note: standard errors clustered at the year level are in parenthesis.

<footnote>* p<0.10, ** p<0.05, *** p<0.01</footnote>
<table><caption>Table 8: Women: Logistic regression of the choice of leaving school on unemployment</caption><thead><tr><th>Odd-ratio</th><th>16 years</th><th>17 years</th><th>18 years</th><th>19 years</th><th>20 years</th></tr></thead><tbody><tr><td>15-24 years Unemployment</td><td>0.987**<br>(0.006)</td><td>0.965***<br>(0.010)</td><td>0.974***<br>(0.007)</td><td>0.982**<br>(0.007)</td><td>0.979***<br>(0.007)</td></tr><tr><td>Lag of 15-24 years Unemployment</td><td>1.003<br>(0.008)</td><td>1.008<br>(0.011)</td><td>1.020***<br>(0.008)</td><td>1.017**<br>(0.008)</td><td>1.013**<br>(0.007)</td></tr><tr><td>Trend</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Estimated break</td><td>1992</td><td>1991</td><td>1992</td><td>1993</td><td>1993</td></tr><tr><td>Predicted propor. of school-leavers (%)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>when unemployment rises</td><td>3.311</td><td>2.749</td><td>7.596</td><td>9.729</td><td>15.487</td></tr><tr><td>from 18% to 25% (1)</td><td>(0.116)</td><td>(0.212)</td><td>(0.337)</td><td>(0.493)</td><td>(0.630)</td></tr><tr><td>when unemployment drops</td><td>3.762</td><td>3.888</td><td>9.628</td><td>11.443</td><td>18.452</td></tr><tr><td>from 18% to 15% (2)</td><td>(0.155)</td><td>(0.141)</td><td>(0.287)</td><td>(0.263)</td><td>(0.563)</td></tr><tr><td>Diff. of propor. (2)-(1)</td><td>0.451**<br>(0.225)</td><td>1.139***<br>(0.300)</td><td>2.032***<br>(0.560)</td><td>1.713**<br>(0.645)</td><td>2.965***<br>(1.045)</td></tr><tr><td>N</td><td>145055</td><td>133402</td><td>123117</td><td>100674</td><td>81490</td></tr></tbody></table>

<table><thead><tr><th>Odd-ratio</th><th>21 years</th><th>22 years</th><th>23 years</th><th>24 years</th><th>All ages</th></tr></thead><tbody><tr><td>15-24 years Unemployment</td><td>0.994<br>(0.008)</td><td>0.990<br>(0.009)</td><td>0.989<br>(0.007)</td><td>0.993<br>(0.014)</td><td>0.985***<br>(0.004)</td></tr><tr><td>Lag of 15-24 years Unemployment</td><td>1.011*<br>(0.007)</td><td>1.017*<br>(0.009)</td><td>1.004<br>(0.007)</td><td>1.005<br>(0.013)</td><td>1.010**<br>(0.004)</td></tr><tr><td>Trend</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Estimated break</td><td>1993</td><td>2003</td><td>1999</td><td>1996</td><td>1991</td></tr><tr><td>Predicted propor. of school-leavers (%)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>when unemployment rises</td><td>18.904</td><td>23.025</td><td>30.823</td><td>36.904</td><td></td></tr><tr><td>from 18% to 25% (1)</td><td>(0.933)</td><td>(1.096)</td><td>(1.137)</td><td>(1.964)</td><td></td></tr><tr><td>when unemployment drops</td><td>19.841</td><td>24.839</td><td>33.290</td><td>38.486</td><td></td></tr><tr><td>from 18% to 15% (2)</td><td>(0.465)</td><td>(0.751)</td><td>(0.585)</td><td>(1.561)</td><td></td></tr><tr><td>Diff. of propor. (2)-(1)</td><td>0.937<br>(1.262)</td><td>1.814<br>(1.614)</td><td>2.467<br>(1.526)</td><td>1.583<br>(3.230)</td><td></td></tr><tr><td>N</td><td>59886</td><td>43458</td><td>29684</td><td>18538</td><td>735304</td></tr></tbody></table>

Note: standard errors clustered at the year level are in parenthesis.

<footnote>* p<0.10, ** p<0.05, *** p<0.01</footnote>
# F Appendix: Results by father occupation

<table><caption>Table 9: Father with a low social background: Logistic regression of the choice of leaving school on unemployment</caption><thead><tr><th>Odd-ratio</th><th>16 years</th><th>17 years</th><th>18 years</th><th>19 years</th><th>20 years</th></tr></thead><tbody><tr><td>15-24 years Unemployment</td><td>0.983**<br>(0.008)</td><td>0.959***<br>(0.013)</td><td>0.980***<br>(0.006)</td><td>0.980***<br>(0.008)</td><td>0.982**<br>(0.008)</td></tr><tr><td>Lag of 15-24 years Unemployment</td><td>1.007<br>(0.009)</td><td>1.014<br>(0.012)</td><td>1.010<br>(0.006)</td><td>1.013*<br>(0.008)</td><td>1.017**<br>(0.007)</td></tr><tr><td>Trend</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Estimated break</td><td>1992</td><td>1991</td><td>1992</td><td>1993</td><td>1993</td></tr><tr><td>Predicted propor.</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>of school-leavers (%)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>when unemployment rises</td><td>5.072<br>(0.218)</td><td>4.160<br>(0.459)</td><td>13.307<br>(0.457)</td><td>15.205<br>(0.709)</td><td>22.971<br>(0.962)</td></tr><tr><td>from 18% to 25% (1)</td><td>5.948<br>(0.253)</td><td>6.216<br>(0.254)</td><td>15.760<br>(0.378)</td><td>17.942<br>(0.408)</td><td>26.289<br>(0.623)</td></tr><tr><td>when unemployment drops</td><td>5.948<br>(0.253)</td><td>6.216<br>(0.254)</td><td>15.760<br>(0.378)</td><td>17.942<br>(0.408)</td><td>26.289<br>(0.623)</td></tr><tr><td>from 18% to 15% (2)</td><td>0.876**<br>(0.441)</td><td>2.056***<br>(0.610)</td><td>2.453***<br>(0.779)</td><td>2.737***<br>(1.033)</td><td>3.318**<br>(1.407)</td></tr><tr><td>Diff. of propor. (2)-(1)</td><td>0.876**<br>(0.441)</td><td>2.056***<br>(0.610)</td><td>2.453***<br>(0.779)</td><td>2.737***<br>(1.033)</td><td>3.318**<br>(1.407)</td></tr><tr><td>N</td><td>142085</td><td>126394</td><td>113329</td><td>84431</td><td>63624</td></tr></tbody><thead><tr><th>Odd-ratio</th><th>21 years</th><th>22 years</th><th>23 years</th><th>24 years</th><th>All ages</th></tr></thead><tbody><tr><td>15-24 years Unemployment</td><td>0.994<br>(0.007)</td><td>0.995<br>(0.005)</td><td>0.993<br>(0.008)</td><td>0.974<br>(0.016)</td><td>0.983***<br>(0.004)</td></tr><tr><td>Lag of 15-24 years Unemployment</td><td>1.010<br>(0.006)</td><td>1.017**<br>(0.007)</td><td>0.998<br>(0.008)</td><td>1.022<br>(0.014)</td><td>1.012**<br>(0.005)</td></tr><tr><td>Trend</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Estimated break</td><td>1993</td><td>2003</td><td>1999</td><td>1996</td><td>1991</td></tr><tr><td>Predicted propor.</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>of school-leavers (%)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>when unemployment rises</td><td>26.320<br>(0.936)</td><td>28.740<br>(0.895)</td><td>34.913<br>(1.419)</td><td>35.666<br>(2.298)</td><td></td></tr><tr><td>from 18% to 25% (1)</td><td>27.411<br>(0.689)</td><td>29.863<br>(0.512)</td><td>36.596<br>(0.760)</td><td>41.807<br>(1.760)</td><td></td></tr><tr><td>when unemployment drops</td><td>27.411<br>(0.689)</td><td>29.863<br>(0.512)</td><td>36.596<br>(0.760)</td><td>41.807<br>(1.760)</td><td></td></tr><tr><td>from 18% to 15% (2)</td><td>1.091<br>(1.380)</td><td>1.123<br>(1.116)</td><td>1.683<br>(1.758)</td><td>6.141<br>(3.776)</td><td></td></tr><tr><td>Diff. of propor. (2)-(1)</td><td>1.091<br>(1.380)</td><td>1.123<br>(1.116)</td><td>1.683<br>(1.758)</td><td>6.141<br>(3.776)</td><td></td></tr><tr><td>N</td><td>41772</td><td>27782</td><td>17805</td><td>10813</td><td>628035</td></tr></tbody></table>

Note: standard errors clustered at the year level are in parenthesis.

<footnote>* p<0.10, ** p<0.05, *** p<0.01</footnote>
<table><caption>Table 10: Father with a high social background: Logistic regression of the choice of leaving school on unemployment</caption><thead><tr><th>Odd-ratio</th><th>16 years</th><th>17 years</th><th>18 years</th><th>19 years</th><th>20 years</th></tr></thead><tbody><tr><td>15-24 years Unemployment</td><td>0.993<br>(0.009)</td><td>0.976**<br>(0.011)</td><td>0.990<br>(0.010)</td><td>1.006<br>(0.007)</td><td>0.979***<br>(0.006)</td></tr><tr><td>Lag of 15-24 years Unemployment</td><td>1.009<br>(0.013)</td><td>1.020*<br>(0.012)</td><td>1.005<br>(0.010)</td><td>0.994<br>(0.009)</td><td>1.022***<br>(0.006)</td></tr><tr><td>Trend</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Estimated break</td><td>1992</td><td>1991</td><td>1992</td><td>1993</td><td>1993</td></tr><tr><td>Predicted propor. of school-leavers (%)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>when unemployment rises</td><td>1.165<br>(0.086)</td><td>1.158<br>(0.086)</td><td>4.349<br>(0.345)</td><td>6.268<br>(0.281)</td><td>9.147<br>(0.367)</td></tr><tr><td>from 18% to 25% (1)</td><td>1.249<br>(0.079)</td><td>1.471<br>(0.081)</td><td>4.776<br>(0.135)</td><td>5.951<br>(0.208)</td><td>11.120<br>(0.277)</td></tr><tr><td>when unemployment drops</td><td>1.165<br>(0.086)</td><td>1.158<br>(0.086)</td><td>4.349<br>(0.345)</td><td>6.268<br>(0.281)</td><td>9.147<br>(0.367)</td></tr><tr><td>from 18% to 15% (2)</td><td>1.005<br>(0.005)</td><td>1.023***<br>(0.008)</td><td>1.004<br>(0.008)</td><td>0.993<br>(0.006)</td><td>1.006<br>(0.004)</td></tr><tr><td>Diff. of propor. (2)-(1)</td><td>-0.152<br>(0.465)</td><td>2.027<br>(1.267)</td><td>-0.171<br>(1.314)</td><td>-1.580<br>(1.508)</td><td></td></tr><tr><td>N</td><td>84799</td><td>80137</td><td>75144</td><td>65908</td><td>56652</td></tr></tbody></table><table><thead><tr><th>Odd-ratio</th><th>21 years</th><th>22 years</th><th>23 years</th><th>24 years</th><th>All ages</th></tr></thead><tbody><tr><td>15-24 years Unemployment</td><td>1.001<br>(0.004)</td><td>0.986<br>(0.009)</td><td>1.001<br>(0.007)</td><td>1.007<br>(0.007)</td><td>0.996<br>(0.004)</td></tr><tr><td>Lag of 15-24 years Unemployment</td><td>1.005<br>(0.005)</td><td>1.023***<br>(0.008)</td><td>1.004<br>(0.008)</td><td>0.993<br>(0.006)</td><td>1.006<br>(0.004)</td></tr><tr><td>Trend</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><td>Estimated break</td><td>1993</td><td>2003</td><td>1999</td><td>1996</td><td>1991</td></tr><tr><td>Predicted propor. of school-leavers (%)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>when unemployment rises</td><td>12.315<br>(0.347)</td><td>17.028<br>(0.862)</td><td>28.096<br>(0.898)</td><td>37.211<br>(1.274)</td><td></td></tr><tr><td>from 18% to 25% (1)</td><td>12.163<br>(0.241)</td><td>19.054<br>(0.536)</td><td>27.925<br>(0.718)</td><td>35.632<br>(0.492)</td><td></td></tr><tr><td>when unemployment drops</td><td>12.163<br>(0.241)</td><td>19.054<br>(0.536)</td><td>27.925<br>(0.718)</td><td>35.632<br>(0.492)</td><td></td></tr><tr><td>from 18% to 15% (2)</td><td>-0.152<br>(0.465)</td><td>2.027<br>(1.267)</td><td>-0.171<br>(1.314)</td><td>-1.580<br>(1.508)</td><td></td></tr><tr><td>Diff. of propor. (2)-(1)</td><td>-0.152<br>(0.465)</td><td>2.027<br>(1.267)</td><td>-0.171<br>(1.314)</td><td>-1.580<br>(1.508)</td><td></td></tr><tr><td>N</td><td>45919</td><td>36192</td><td>26634</td><td>17468</td><td>488853</td></tr></tbody></table>

Note: standard errors clustered at the year level are in parenthesis.

<footnote>* p<0.10, ** p<0.05, *** p<0.01</footnote>
# G Appendix: Countercyclical leaving-school decisions and selection in labor market outcomes

We have studied so far the effect of the economic situation (unemployment rate) on the probability of leaving school. We have shown that the probability of leaving school is slightly contra-cyclical. Now we investigate how this cyclical pattern affects the labor market outcomes of a school leaving-year cohort (people who leave school during the same year). This is a main issue for empirical identification strategies relying on labor market comparisons.

Can we compare directly two cohorts of school-leavers who faced different economic conditions at their entry into the labor market? This is of primary interest for empirical work aiming at measuring the so-called *scarring effect: i.e.*, how much income will one lose when she completes a degree during an economic crisis? If the school-leaving age and year are endogenous to business cycle, we cannot directly compare cohorts (and thus employment prospects). If not treated, this endogeneity could lead to an underestimation of the scarring effect but we find that this bias is very low in the French case.

To do so, we use the results of our main model (see Table 2).

We proceed in two steps (see Figure 3):

1. In a first step, we use our estimates to study how the school-leaving age distribution moves with the business cycle, from 1983 to 2009.

2. In a second step, we simulate changes in mean wage entailed by these changes in the school-leaving age distribution (under the assumption that mean wage for a given school leaving age does not vary).

<figure><img src="image_18.png" /><figcaption>Figure 3: Method of the simulation</figcaption></figure>

This method is clearly crude and wages of students anticipating or postponing their school-leaving are likely to be different from wages of other students. Yet, this method gives some hints about the magnitude of the effect. We find that the difference in the wages paths is very weak (not more than 15 euros of monthly wage from one year to the following).
Unemployment therefore affects school-leaving age distribution, which mechani-
cally entails a change in new entrants mean wage path. Yet, as suggested in this
appendix, unemployment effects on school leaving-age distribution are quite small.

G.1 Method

**Probability of leaving school at each age and year** Recall that our main model has the following form ($F(\cdot)$ being the logistic cdf):

$$
P(L_{i,a,t}) = F(\alpha_a + \beta_{0a} \cdot UR_t + \beta_{1a} \cdot UR_{t-1} + \gamma_{1a} \cdot t + \gamma_{2a} \cdot (t - \bar{T}_a) \mathbf{1}_{\{t \ge \bar{T}_a\}})
$$

Let's define $p_a^t$ as the probability of leaving school at age $a$ during the year $t$, netted
out from the effect of the structural evolution of the school leaving age. To do so,
we predict $\hat{p}_a^t$ using unemployment rates of year $t$ and $t-1$ but we fix the year at
2000 for the trend evolutions. The evolution of $\hat{p}_a^t$ over time is thus only driven by
the evolution of the unemployment rate. Formally :

$$
\hat{p}_a^t = F(\hat{\alpha}_a + \hat{\beta}_{0a} \cdot UR_t + \hat{\beta}_{1a} \cdot UR_{t-1} + \hat{\gamma}_{1a} \cdot 2000 + \hat{\gamma}_{2a} \cdot (2000 - \bar{T}_a) \mathbf{1}_{\{2000 \ge \bar{T}_a\}}) \quad (\text{G.1})
$$

**Number of students by age: baseline** We use as baseline for the repartition of students across ages the repartition derived from our main model in 2000, see table 11. We normalize the number of students at age 16 to 100. We note $N_a$ the normalized number of students at age a.

<table><caption>Table 11: Number of students by age, year 2000 (normalized at 100 at age 16)</caption>
  <thead>
    <tr>
      <th>Age</th>
      <th>N</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td>16</td>
      <td>100</td>
    </tr>
    <tr>
      <td>17</td>
      <td>96</td>
    </tr>
    <tr>
      <td>18</td>
      <td>92</td>
    </tr>
    <tr>
      <td>19</td>
      <td>82</td>
    </tr>
    <tr>
      <td>20</td>
      <td>72</td>
    </tr>
    <tr>
      <td>21</td>
      <td>59</td>
    </tr>
    <tr>
      <td>22</td>
      <td>47</td>
    </tr>
    <tr>
      <td>23</td>
      <td>36</td>
    </tr>
    <tr>
      <td>24</td>
      <td>25</td>
    </tr>
  </tbody>
</table>
**School leaving-age distribution** In this simulation, we are interested in the effect of unemployment on the school leaving age distribution. We apply to our baseline distribution of students the predicted probabilities of leaving school for each year and each age ($p_a^t$, $16 \le a \le 24$, $1983 \le t \le 2009$). We obtain the number of students leaving school each year for each age. For each year, we divide the number of students with the same school-leaving age by the total number of students leaving-school that same year. We obtain the share of each age group among the leaving-school students for each year.

$$ \hat{\pi}_a^t = \frac{\hat{p}_a^t \cdot N_a}{\sum_{\alpha} \hat{p}_\alpha^t \cdot N_\alpha} \qquad (G.2) $$

**Wage evolution due to the cyclicality of the school leaving-age** We run a log linear regression to estimate the effect of the school leaving age on earnings, after 1 year and after 5 years of potential experience ($1990 \le t \le 2009$)$^{13}$:

$$ \log(w_{it}^e) = \alpha^e + \beta^e \cdot a_{it} + \eta_t^e + \epsilon_{it}^e \qquad (G.3) $$

We deduce from this regression the mean wage - $\hat{W}_a$ - for each school leaving-age $a$: $\hat{W}_a = \exp(\hat{\alpha} + \hat{\beta} \cdot a) \cdot \exp(\hat{\sigma}^2/2)$ (after 1 or 5 years) with $\hat{\sigma}$ the estimated standard-error of $\epsilon_{it}$.

We then compute the mean wage for the school leavers of year $t$: $\hat{W}_t = \sum_{a=16}^{24} \hat{\pi}_a^t \cdot \hat{W}_a$.

## G.2 Results

We find that changes in the unemployment rate imply very weak variations in the school-leaving age distribution during the period 1983-2009. Figure 4 displays the annual evolution of the share of school-leavers of each age (year 2000). According to our results, the predicted percentage of school leavers aged between 16 and 24 reacts very slightly to the business cycle. For comparison, we represent also the evolution of the percentage of school leavers taking into account the structural trend.

The reasons explaining why this variations are so weak are threefold. First, the estimated effects of unemployment rate on school leaving age are significant but weak. For each age, the current unemployment rate has a weak effect on the predicted probability of leaving school. The effect on the school leaving age distribution is consequently weak. Second, a high unemployment level causes students

<footnote>$^{13}$We use the 1990-2009 period because we do not have wages in our dataset before 1990.</footnote>
to stay at school at every age (although with an heterogeneous intensity), so that the business cycle affects more the number of school leavers than the distribution or mean of the school leaving-age. Third, the current and past unemployment rates play in opposite directions on the probability of leaving school. The viscosity of business cycle therefore causes only a small change in the school leaving age.

<figure><img src="image_19.png" /><figcaption>Figure 4: Simulations: Annual evolutions of the share of each age group among the school leavers and mean school leaving age, French case, year 1983-2009</figcaption></figure>
<figure><img src="image_20.png" /></figure>

Note: confidence intervals are not calculated.

<figure><img src="image_21.png" /><figcaption>Figure 5: Simulations: Annual evolutions of the mean wage due to the impact of unemployment rate on school-leaving age distribution, French case, year 1990-2009</figcaption></figure>

Note: confidence intervals are not calculated. The mean monthly wage is calculated on full-time jobs

Using the school-leaving age distribution we compute the mean wage for one years and five years of potential experience, from 1990 to 2009 and for full-time workers (see Figure 5). We find that the differences in the wages paths are very weak (not more than 15 euros in monthly wage between 2 years, i.e. about 1% of mean wage).
<table><tr><td>G 9001</td><td>J. FAYOLLE et M. FLEURBAEY<br>Accumulation, profitabilité et endettement des entreprises</td></tr><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></tr><tr><td>G 9003</td><td>P. RALLE et J. TOUJAS-BERNATE<br>Indexation des salaires : la rupture de 1983</td></tr><tr><td>G 9004</td><td>D. GUELLEC et P. RALLE<br>Compétitivité, croissance et innovation de produit</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></tr><tr><td>G 9101</td><td>Équipe AMADEUS<br>Le modèle AMADEUS - Première partie - Présentation générale</td></tr><tr><td>G 9102</td><td>J.L. BRILLET<br>Le modèle AMADEUS - Deuxième partie - Propriétés variantielles</td></tr><tr><td>G 9103</td><td>D. GUELLEC et P. RALLE<br>Endogenous growth and product innovation</td></tr><tr><td>G 9104</td><td>H. ROUSSE<br>Le modèle AMADEUS - Troisième partie - Le commerce extérieur et l'environnement international</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></tr><tr><td>G 9106</td><td>B. CREPON<br>Innovation, taille et concentration : causalités et dynamiques</td></tr><tr><td>G 9107</td><td>B. AMABLE et D. GUELLEC<br>Un panorama des théories de la croissance endogène</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></tr><tr><td>G 9109</td><td>P. RALLE et alii<br>France - Allemagne : performances économiques comparées</td></tr><tr><td>G 9110</td><td>J.L. BRILLET<br>Micro-DMS<br>NON PARU</td></tr><tr><td>G 9111</td><td>A. MAGNIER<br>Effets accélérateur et multiplicateur en France depuis 1970 : quelques résultats empiriques</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></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></tr><tr><td>G 9201</td><td>W.J. ADAMS, B. CREPON, D. ENCAOUA<br>Choix technologiques et stratégies de dissuasion d'entrée</td></tr><tr><td>G 9202</td><td>J. OLIVEIRA-MARTINS, J. TOUJAS-BERNATE</td></tr></table>

<table><tr><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>Juin 1992 (1ère version)<br>Novembre 1992 (version finale)</td></tr><tr><td>G 9204</td><td>P. SEVESTRE<br>L'économie sur données individuelles-temporelles. Une note introductive</td></tr><tr><td>G 9205</td><td>H. ERKEL-ROUSSE<br>Le commerce extérieur et l'environnement international dans le modèle AMADEUS (réestimation 1992)</td></tr><tr><td>G 9206</td><td>N. GREENAN et D. GUELLEC<br>Coordination within the firm and endogenous growth</td></tr><tr><td>G 9207</td><td>A. MAGNIER et J. TOUJAS-BERNATE<br>Technology and trade: empirical evidences for the major five industrialized countries</td></tr><tr><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></tr><tr><td>G 9209</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></tr><tr><td>G 9301</td><td>J. TOUJAS-BERNATE<br>Commerce international et concurrence impartie : développements récents et implications pour la politique commerciale</td></tr><tr><td>G 9302</td><td>Ch. CASES<br>Durées de chômage et comportements d'offre de travail : une revue de la littérature</td></tr><tr><td>G 9303</td><td>H. ERKEL-ROUSSE<br>Union économique et monétaire : le débat économique</td></tr><tr><td>G 9304</td><td>N. GREENAN - D. GUELLEC / G. BROUSSAUDIER - L. MIOTTI<br>Innovation organisationnelle, dynamisme technologique et performances des entreprises</td></tr><tr><td>G 9305</td><td>P. JAILLARD<br>Le traité de Maastricht : présentation juridique et historique</td></tr><tr><td>G 9306</td><td>J.L. BRILLET<br>Micro-DMS : présentation et propriétés</td></tr><tr><td>G 9307</td><td>J.L. BRILLET<br>Micro-DMS - variantes : les tableaux</td></tr><tr><td>G 9308</td><td>S. JACOBZONE<br>Les grands réseaux publics français dans une perspective européenne</td></tr><tr><td>G 9309</td><td>L. BLOCH - B. CŒURE<br>Profitabilité de l'investissement productif et transmission des chocs financiers</td></tr><tr><td>G 9310</td><td>J. BOURDIEU - B. COLIN-SEDILLOT<br>Les théories sur la structure optimale du capital : quelques points de repère</td></tr></table>

<table><tr><td>G 9311</td><td>J. BOURDIEU - B. COLIN-SEDILLOT<br>Les décisions de financement des entreprises françaises : une évaluation empirique des théories de la structure optimale du capital</td></tr><tr><td>G 9312</td><td>L. BLOCH - B. CŒURÉ<br>Q de Tobin marginal et transmission des chocs financiers</td></tr><tr><td>G 9313</td><td>Équipes Amadeus (INSEE), Banque de France, Métric (DP)<br>Présentation des propriétés des principaux modèles macroéconomiques du Service Public</td></tr><tr><td>G 9314</td><td>B. CREPON - E. DUGUET<br>Research & Development, competition and innovation</td></tr><tr><td>G 9315</td><td>B. DORMONT<br>Quelle est l'influence du coût du travail sur l'emploi ?</td></tr><tr><td>G 9316</td><td>D. BLANCHET - C. BROUSSE<br>Deux études sur l'âge de la retraite</td></tr><tr><td>G 9317</td><td>D. BLANCHET<br>Répartition du travail dans une population hétérogène : deux notes</td></tr><tr><td>G 9318</td><td>D. EYSSARTIER - N. PONTY<br>AMADEUS - an annual macro-economic model for the medium and long term</td></tr><tr><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></tr><tr><td>G 9401</td><td>D. BLANCHET<br>Les structures par âge importent-elles ?</td></tr><tr><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></tr><tr><td>G 9403</td><td>P. QUIRION<br>Les déchets en France : éléments statistiques et économiques</td></tr><tr><td>G 9404</td><td>D. LADIRAY - M. GRUN-REHOMME<br>Lissage par moyennes mobiles - Le problème des extrémités de série</td></tr><tr><td>G 9405</td><td>V. MAILLARD<br>Theorie et pratique de la correction des effets de jours ouvrables</td></tr><tr><td>G 9406</td><td>F. ROSENWALD<br>La décision d'investir</td></tr><tr><td>G 9407</td><td>S. JACOBZONE<br>Les apports de l'économie industrielle pour définir la stratégie économique de l'hôpital public</td></tr><tr><td>G 9408</td><td>L. BLOCH, J. BOURDIEU, B. COLIN-SEDILLOT, G. LONGUEVILLE<br>Du défaut de paiement au dépôt de bilan : les banquiers face aux PME en difficulté</td></tr><tr><td>G 9409</td><td>D. EYSSARTIER, P. MAIRE<br>Impacts macro-économiques de mesures d'aide au logement - quelques éléments d'évaluation</td></tr><tr><td>G 9410</td><td>F. ROSENWALD<br>Suivi conjoncturel de l'investissement</td></tr><tr><td>G 9411</td><td>C. DEFEUILLEY - Ph. QUIRION<br>Les déchets d'emballages ménagers : une analyse économique des politiques française et allemande</td></tr></table>

<table><tr><td>G 9412</td><td>J. BOURDIEU - B. CŒURÉ - B. COLIN-SEDILLOT<br>Investissement, incertitude et irréversibilité<br>Quelques développements récents de la théorie de l'investissement</td></tr><tr><td>G 9413</td><td>B. DORMONT - M. PAUCHET<br>L'évaluation de l'élasticité emploi-salaire dépend-elle des structures de qualification ?</td></tr><tr><td>G 9414</td><td>I. KABLA<br>Le Choix de breveter une invention</td></tr><tr><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 9502</td><td>L. BLOCH - B. CŒURÉ<br>Imperfections du marché du crédit, investissement des entreprises et cycle économique</td></tr><tr><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 9504</td><td>N. GREENAN<br>Technologie, changement organisationnel, qualifications et emploi : une étude empirique sur l'industrie manufacturière</td></tr><tr><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 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 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 9507</td><td>G. CETTE - S. MAHFOUZ<br>Le partage primaire du revenu<br>Constat descriptif sur longue période</td></tr><tr><td>G 9601</td><td>Banque de France - CEPREMAP - Direction de la Prévision - Érasme - INSEE - OFCE<br>Structures et propriétés de cinq modèles macroéconomiques français</td></tr><tr><td>G 9602</td><td>Rapport d'activité de la DESE de l'année 1995</td></tr><tr><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 9604</td><td>A. TOPIOL-BENSAÏD<br>Les implantations japonaises en France</td></tr><tr><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 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 9607</td><td>N. GREENAN - D. GUELLEC<br>La théorie coopérative de la firme</td></tr></table>
<table>
  <tbody>
    <tr>
      <td>G 9608</td>
      <td>N. GREENAN - D. GUELLEC<br>Technological innovation and employment<br>reallocation</td>
      <td>G 9714</td>
      <td>F. LEQUILLER<br>Does the French Consumer Price Index Over-<br>state Inflation?</td>
      <td>G 9807</td>
      <td>Bilan des activités de la Direction des Études et<br>Synthèses Économiques - 1997</td>
      <td>Bis</td>
      <td>Une estimation de l'élasticité de l'emploi peu<br>qualifié à son coût</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>
      <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>
      <td>G 9808</td>
      <td>A. MOUROUGANE<br>Can a Conservative Governor Conduct an Ac-<br>comodative Monetary Policy?</td>
      <td>G 9913</td>
      <td>Division « Redistribution et Politiques Sociales »<br>Le modèle de microsimulation dynamique<br>DESTINIE</td>
    </tr>
    <tr>
      <td>G 9610</td>
      <td>S. DUCHENE - G. FORGEOT - A. JACQUOT<br>Analyse des évolutions récentes de la producti-<br>vité apparente du travail</td>
      <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>
      <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>
      <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 9611</td>
      <td>X. BONNET - S. MAHFOUZ<br>The influence of different specifications of wages-<br>prices spirals on the measure of the NAIRU: the<br>case of France</td>
      <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>
      <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>
      <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 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>
      <td>G 9718</td>
      <td>L.P. PELÉ - P. RALLE<br>Âge de la retraite : les aspects incitatifs du régime<br>général</td>
      <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>
      <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 9613</td>
      <td>A. JACQUOT<br>Les flexions des taux d'activité sont-elles seule-<br>ment conjoncturelles ?</td>
      <td>G 9719</td>
      <td>ZHANG Yingxiang - SONG Xueqing<br>Lexique macroéconomique français-chinois,<br>chinois-français</td>
      <td>G 9812</td>
      <td>C. PRIGENT<br>La part des salaires dans la valeur ajoutée : une<br>approche macroéconomique</td>
      <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 9614</td>
      <td>ZHANG Yingxiang - SONG Xueqing<br>Lexique macroéconomique Français-Chinois</td>
      <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>
      <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>
      <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 firms<br>from the manufacturing sector</td>
    </tr>
    <tr>
      <td>G 9701</td>
      <td>J.L. SCHNEIDER<br>La taxe professionnelle : éléments de cadrage<br>économique</td>
      <td>G 9721</td>
      <td>A. MOUROUGANE<br>Crédibilité, indépendance et politique monétaire<br>Une revue de la littérature</td>
      <td>G 9814</td>
      <td>B. SALANIÉ<br>Guide pratique des séries non-stationnaires</td>
      <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 9702</td>
      <td>J.L. SCHNEIDER<br>Transition et stabilité politique d'un système<br>redistributif</td>
      <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>
      <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>
      <td>G 2000/01</td>
      <td>R. MAHIEU<br>Les déterminants des dépenses de santé : une<br>approche macroéconomique</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>
      <td>G 9723</td>
      <td>P. AUGERAUD - J.E. CHAPRON<br>Using Business Accounts for Compiling National<br>Accounts: the French Experience</td>
      <td>G 9902</td>
      <td>Ch. COLIN<br>Modélisation des carrières dans Destinie</td>
      <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 9704</td>
      <td>P. GENIER<br>Deux contributions sur dépendance et équité</td>
      <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>
      <td>G 9903</td>
      <td>Ch. COLIN<br>Évolution de la dispersion des salaires : un essai<br>de prospective par microsimulation</td>
      <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 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>
      <td>G 9801</td>
      <td>H. MICHAUDON - C. PRIGENT<br>Présentation du modèle AMADEUS</td>
      <td>G 9904</td>
      <td>B. CREPON - N. IUNG<br>Innovation, emploi et performances</td>
      <td>G 2000/04</td>
      <td>Bilan des activités de la DESE - 1999</td>
    </tr>
    <tr>
      <td>G 9706</td>
      <td>M. HOUBEBINE - A. TOPIOL-BENSAÎD<br>Les entreprises internationales en France : une<br>analyse à partir de données individuelles</td>
      <td>G 9802</td>
      <td>J. ACCARDO<br>Une étude de comptabilité générationnelle<br>pour la France en 1996</td>
      <td>G 9905</td>
      <td>B. CREPON - Ch. GIANELLA<br>Wages inequalities in France 1969-1992<br>An application of quantile regression techniques</td>
      <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 9707</td>
      <td>M. HOUBEBINE<br>Polarisation des activités et spécialisation des<br>départements en France</td>
      <td>G 9803</td>
      <td>X. BONNET - S. DUCHÈNE<br>Apports et limites de la modélisation<br>« Real Business Cycles »</td>
      <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>
      <td>G 2000/06</td>
      <td>A. FLIPO<br>Les comportements matrimoniaux de fait</td>
    </tr>
    <tr>
      <td>G 9708</td>
      <td>E. DUGUET - N. GREENAN<br>Le biais technologique : une analyse sur données<br>individuelles</td>
      <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>
      <td>G 9907</td>
      <td>F. ROSENWALD<br>L'impact des contraintes financières dans la dé-<br>cision d'investissement</td>
      <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 9709</td>
      <td>J.L. BRILLET<br>Analyzing a small French ECM Model</td>
      <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>
      <td>G 9908</td>
      <td>Bilan des activités de la DESE - 1998</td>
      <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 9710</td>
      <td>J.L. BRILLET<br>Formalizing the transition process: scenarios for<br>capital accumulation</td>
      <td>G 9806</td>
      <td>J. ACCARDO - M. JLASSI<br>La productivité globale des facteurs entre 1975 et<br>1996</td>
      <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>
      <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 9711</td>
      <td>G. FORGEOT - J. GAUTIÉ<br>Insertion professionnelle des jeunes et processus<br>de déclassement</td>
      <td>G 9807</td>
      <td>G. LAROQUE - B. SALANIÉ<br>Une décomposition du non-emploi en France</td>
      <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 publique</td>
      <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 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>
      <td>G 9808</td>
      <td>J. ACCARDO - M. JLASSI<br>La productivité globale des facteurs entre 1975 et<br>1996</td>
      <td>G 9911</td>
      <td>G. LAROQUE - B. SALANIÉ<br>Une maquette analytique de long terme du<br>marché du travail</td>
      <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 9713</td>
      <td>Bilan des activités de la Direction des Études<br>et Synthèses Économiques - 1996</td>
      <td>G 9810</td>
      <td>Ch. GIANELLA<br>Ch. GIANELLA</td>
      <td>G 9912</td>
      <td>Ch. GIANELLA<br>Ch. GIANELLA</td>
      <td>G2000/12</td>
      <td>Ch. GIANELLA<br>Local unemployment and wages</td>
    </tr>
  </tbody>
</table>
G2001/13 B. CREPON - Th. HECKEL
- Informatisation en France : une évaluation à partir de données individuelles
- 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 profite-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
- Rétropolation des séries de FBCF et calcul du capital fixe en SEC-95 dans les comptes nationaux français

- Retropolation 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 Familiale 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
Age, 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 microéconomique

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 à 1974

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 Économiques - 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. DUÈE
La modélisation des comportements démographiques dans le modèle de microsimulation
DESTINIE

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 macroeconometric 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 réréprétrétation 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, recentrage 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

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

G2008/13 M. BARLET - D. BLANCHET - T. LE BARBANCHON
A Monthly Indicator of the French Business Climate

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 marchepied 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'économétre 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-prices 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 entreprises sur la base des contrôles fiscaux et son insertion dans les comptes nationaux

G2011/10 A. SCHREIBER - A. VICARD La tertiairisation 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 from 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