# Public-private wage gaps: is civil-servant human capital sector-specific?

Magali Beffy, Thierry Kamionka

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Magali Beffy, Thierry Kamionka. Public-private wage gaps: is civil-servant human capital sector-specific?. 2010. hal-05484693

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Direction des Études et Synthèses Économiques

G 2010 / 16

Public-private wage gaps:
is civil-servant human capital
sector-specific?

Magali BEFFY - Thierry KAMIONKA

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 2010 / 16

Public-private wage gaps:
is civil-servant human capital
sector-specific?

Magali BEFFY* - Thierry KAMIONKA**

SEPTEMBRE 2010

Département des Études Économiques d'Ensemble - Timbre G201 - 15, bd Gabriel Péri - BP 100 - 92244 MALAKOFF CEDEX -
France - Tél. : 33 (1) 41 17 60 68 - Fax : 33 (1) 41 17 60 45 - CEDEX - E-mail : d3e-dg@insee.fr - Site Web Insee :
http://www.insee.fr

Ces documents de travail ne reflètent pas la position de l'Insee et n'engagent que leurs auteurs.
Working papers do not reflect the position of INSEE but only their author's views.

<footnote>* Crest et Insee, Département des Études Économiques d'Ensemble - Division « Redistribution et Politiques Sociales »Timbre G210 - 15, bd Gabriel Péri - BP 100 - 92244 MALAKOFF CEDEX</footnote>

<footnote>** CNRS and Crest</footnote>
# Public-private wage gaps : is civil-servant human capital sector-specific?

## Abstract

What would be the counterfactual wage of civil servants if they were employed in the private sector? Using the French European Household panel, we present a new approach to the wage differential between the public and the private sectors. We estimate a model, which controls both for selection into employment, and for self-selection into the public sector. We also introduce unobserved heterogeneity in the propensity to be employed in either job sector, and in the sector-specific productivity. Evidence based on the counterfactual distributions suggests a large public-private wage premium for low public wages. This conclusion also holds for women but may be explained by a weaker discrimination in the public sector. Unlike women, most male civil servants would earn more in the private sector.

**Keywords:** counterfactual distributions, wage differentials, public and private sector, unobserved heterogeneity

# Les écarts de salaire public-privé : un capital humain spécifique à la fonction publique ?

## Résumé

Quel serait le salaire des fonctionnaires s'ils travaillaient dans le secteur privé ? À l'aide du Panel Européen des Ménages, nous présentons une nouvelle approche au différentiel de salaires entre secteur public et secteur privé. Nous estimons un modèle où nous contrôlons de la double sélection : participation et choix de secteur, et de l'hétérogénéité inobservée dans la propension à être en emploi, dans l'un ou l'autre des secteurs, et dans la productivité spécifique à chaque secteur. Les distributions contrefactuelles estimées permettent de conclure à une prime à l'emploi public pour les bas salaires. La même conclusion tient pour les femmes, mais pour ces dernières, cet « avantage » est dû à une moindre discrimination. À l'inverse, la plupart des hommes en emploi dans le secteur public bénéficieraient de salaires plus élevés dans le secteur privé.

**Mots-clés** : distributions contrefactuelles, différentiel de salaire, secteurs public et privé, hétérogénéité inobservée

**Classification JEL** : J31, J45, J64, C21, C33, C35
# 1. Introduction

There has been an increasing interest in studying public sector employment for more than two decades. This process was initiated by Smith (1977) and this is justified by the large share of public employment in total employment. Over that period of time, this proportion does not decrease for any western country but for UK. For instance, in France, in 2006, this share amounts to one quarter of total employment, and it has been relatively stable since the beginning of the nineties. Providing a study that properly takes into account the factors that can explain differences between public and private wages is therefore an important policy issue.

In this paper, we evaluate the counterfactual wage people currently employed in the public sector, would have in the private sector. We also determine whether public workers benefit from a wage premium along the public wage distribution. To do so, we model private sector and public sector wages, in a panel framework, controlling for the double selection in employment and in sector choices, and we account for unobserved heterogeneity through the use of finite mixture distributions. We derive from this model the unobserved productivity public workers would have in the private sector, and reciprocally.

Hence this paper contributes to the scarce literature dealing with the French case regarding the classical analysis of the public wage gap. Fournier (2001) studies raw public wage premiums. Fougère and Pouget (2003) concentrate on the main determinants of the entry into the public sector. Bargain and Melly (2008) focus on the public sector pay gap using quantile regressions on a short panel data set and compare the quantiles of both distributions. Unlike Bargain and Melly (2008), we observe each individual for 8 years, which ensures convergence properties that can not be ensured when people are surveyed only three times.

This paper also expands some previous approaches: many recent studies rely on cross sectional switching regressions, endogenous or not (see Disney and Gosling (1998) and Gyourko and Tracy (1988) for UK, Dustman and Van Soest (1998) for Germany, Hartog and Oosterbeek (1993) and Van Ophem (1993) for the Netherlands, Fougère and Pouget (2003) for France and Heitmueller (2006) for Scotland). In a different way, Heitmueller (2006) controls for participation and sector selections, but in cross-sectional analysis. In order to overcome these potential biases, Disney and Gosling (2003) uses the natural experiment that happened in the UK in the nineties with the privatization programme. They show that their results are robust to self-selection.

A second set of papers raise close but different issues about wages and mobility between both sectors. Bell, Elliott, and Scott (2005) exploit mobility between both sectors, and study the wage incentives to change sector. They identify the wage premium after a job change. Other studies focus on the link between the wage distribution and mobility. Postel-Vinay and Turon (2007) and Cappellari (2002) focus on earnings dynamics and lifetime values of employment in both sectors. They argue that public and private sectors differ not only in their log wage distribution but also in their income mobility. They conclude, for UK and resp. for Italy, that adopting a life cycle view of earnings matters in the private sector whereas it does not in the public sector.<fnref n="1" />

Our paper is more in line with Dustman and Van Soest (1998) and Heitmueller (2006). We extend their approach by considering a panel framework, controlling for both self selection into employment and into the public sector. Unobserved heterogeneity, modeled by using the method of Heckman and Singer (1984) allows us to control for individual tastes and propensity to be employed in a given sector, and for individual abilities. An individual has a different propensity to earn low or high wages in different sectors.

<footnote n="1">¹Another trend of the literature on public/private differences concerns queue models (Venti (1987), Heywood and Mohanty (1995) and Fougère and Pouget (2003)) and analyzes the individual propensity to seek employment in public sectors. But these models require very detailed information about the supply and demand for public jobs. Furthermore, they are very sensitive to the instruments chosen and it turns out difficult to separately identify the characteristics determining the search for a public job from those determining the access to a public job. Bellante and Link (1981) argue there are more risk adverse workers in the public sector, and Goddeeris (1988) point out a *taste* for public services.</footnote>
We estimate this model with data from the French European Household panel (ECHP) over the period 1994-2001. We obtain a very good model fit in terms of income distribution, employment probability and sector choice. Our results concur with the existing literature, but thanks to the new approach we adopt, we can assess the counterfactual wage civil-servants would get if employed in the private sector. Female are the ones who benefit from a public wage premium since gender discrimination is larger in the private sector. Unlike women, most male civil-servants suffer a public wage penalty. Apart from those at the bottom of the wage distribution, they would get higher wages in the private sector. We also find that mimicking one's father is determinant in the public sector choice whereas the mother status turns out to be non significant. Finally, as it has been already shown in previous papers, the public sector attracts more people when the local labor market is depressed.

We carry out a descriptive analysis of our data in section 2, and the statistical model to be estimated is detailed in section 3. Sections 4 and 5 discuss results and simulations. Finally, Section 6 concludes.

## 2. The data

### 2.1. A brief description

We use data from the waves 1994 to 2001 of the French European Household Survey. We restrict our sample to individuals aged from 16 to 59 years old at the beginning of the panel. We do include female in the sample given their high participation rate in France, and given the fact that we control for participation. We define three sectors of activity or labor force status: nonemployment, employment in the private sector, and employment in the public sector. We consider that individuals work in the public sector when they answer they work for state or local governments. Otherwise, they are said to work in the private sector, namely they are employed by national or private firms, or by their own firm.<fnref n="2" /> Self-employed workers and unpaid workers in a family business are excluded. We also exclude individuals who work, but who do not declare any wage. This leaves us with 5,092 individuals, we follow over 8 years.

Concerning educational level, we consider the highest education degree instead of the number of years of studying. In France, civil-servant exams are indeed conditional on degrees.

The French European Household survey provides annual wage earnings and a monthly description of the occupation, but it does not provide the specific wage of the job occupied during the month of the interview. We thus divide the annual wage earnings by the total number of months employed during the year. In order to get an accurate estimate for this monthly wage, cautiousness is required when people have two jobs or more in a given year, but this is actually the case for less than 5% of the employed people in a given year. Hence, for these people, we divide the annual wage earnings by the number of months they are employed whatever the number of jobs they got throughout the year. Finally, monthly wages are assessed in French francs at 1994 prices.

### 2.2. Some descriptive statistics

The initial sample (without age restriction) contains half nonemployed and half employed people. Logically in the sample restricted to people aged from 16 to 59, employed people are over-represented (see table 1). In the data, the public sector represents one third of employed people.<fnref n="3" />

The proportion of women is traditionally higher in the public than in the private sector, since it is easier to conciliate professional and family lives while employed in the public sector (see table 2). Few foreigners work in the public sector because entrance exams often require French citizenship. Entrance exams also require a minimum degree level, hence the distribution of degrees differs between sectors.

<footnote n="2">²There is no cross-validation of their employment status as in Card (1996) and the different public services cannot be distinguished.</footnote>

<footnote n="3">³In national statistics, the public sector amounts to one fourth of total employment including the self-employed. In this paper we have excluded the self-employed, which explains the higher proportion of public employment we get. This proportion is roughly the same when assessed on the non-balanced panel data.</footnote>
Public jobs require usually more qualification, undergraduates and graduates are thus more represented in the public sector. Unlike skilled workers, the unskilled ones are more present in the private sector. Concerning age, the management of older workers' career differs between sectors and private workers are younger on average than their public sector counterparts.

Finally consider some figures about transitions. The following matrix gives details about transition probabilities between different states over 1994-2001. Very few individuals move from the private to the public sector, while opposite movements are more frequent but still rare. 7% of private workers and 4.7% of public workers become nonemployed in the subsequent period. They may have lost their job or decided to stop working for a while (for instance, women may decide to get out of the labor force to bring up their children).

<table><thead><tr><th></th><th>Nonemployment</th><th>Private</th><th>Public</th></tr></thead><tbody><tr><th>Nonemployment</th><td>87.56</td><td>9.83</td><td>2.62</td></tr><tr><th>Private</th><td>6.95</td><td>92.65</td><td>0.40</td></tr><tr><th>Public</th><td>4.69</td><td>1.26</td><td>94.05</td></tr></tbody></table>

Rows refer to the sector at date $t-1$, and columns to the sector at date $t$.

<table><caption>Table 1 Nonemployment, employment in public and private sectors.</caption><thead><tr><th>Activity status</th><th>1994</th><th>1995</th><th>1996</th><th>1997</th><th>1998</th><th>1999</th><th>2000</th><th>2001</th></tr></thead><tbody><tr><th>Non Employed</th><td>1,692<br>(33%)</td><td>1,653<br>(32%)</td><td>1,663<br>(33%)</td><td>1,671<br>(33%)</td><td>1,655<br>(32%)</td><td>1,637<br>(32%)</td><td>1,692<br>(33%)</td><td>1,740<br>(34%)</td></tr><tr><th>Employed</th><td>3,400<br>(67%)</td><td>3,439<br>(68%)</td><td>3,429<br>(67%)</td><td>3,421<br>(67%)</td><td>3,437<br>(68%)</td><td>3,455<br>(68%)</td><td>3,400<br>(67%)</td><td>3,352<br>(66%)</td></tr><tr><th>Sector</th><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>Public</th><td>1,061<br>(31%)</td><td>1,084<br>(32%)</td><td>1,086<br>(32%)</td><td>1,057<br>(31%)</td><td>1,052<br>(31%)</td><td>1,042<br>(30%)</td><td>1,014<br>(30%)</td><td>993<br>(30%)</td></tr><tr><th>Private</th><td>2,339<br>(69%)</td><td>2,355<br>(68%)</td><td>2,343<br>(68%)</td><td>2,364<br>(69%)</td><td>2,385<br>(69%)</td><td>2,413<br>(70%)</td><td>2,386<br>(70%)</td><td>2,359<br>(70%)</td></tr></tbody></table>

Source: French European Household Survey.

## 2.3. Simple regressions

Table 3 presents the results we get with simple regressions. We first regress the log of the monthly wage on a public sector dummy and a few covariates. The first column of Table 3 shows that the raw public-private gap over 1994-2001 is 22.3 log points (around 25%). Conditioning on more covariates, such as age, a proxy of experience -the age at the end of studies, and degrees (second specification), this public-private pay gap is still significant and amounts to 8.5%. In specification 3, we process 2SLS to take into account that sector selection is endogenous.<fnref n="4" /> In this specification 3, the public wage premium estimate is 24%. In a final specification, we process separate regressions allowing different returns to experience, to degrees in both sectors. And if we evaluate the raw premium as the constant coefficient, it turns out to be 39%, but this measure does not take into account the different returns to covariates between the public and the private sector. Hence it is not certainly the good way to proceed.

<footnote n="4">⁴In the sector choice equation, we include a proxy of the father status, as well as a proxy of the mother status, at the end of the individual's studies. Were the father or the mother civil-servants? The instruments we consider are the gender times the status of one's mother, and the gender times the status of one's father. Finally we also include the unemployment rate to explain the sector choice.</footnote>
<table><caption>Table 2 General descriptive statistics - 1994</caption><thead><tr><th rowspan="2"></th><th colspan="2">Whole Sample</th><th colspan="2">Private Sector</th><th colspan="2">Public Sector</th></tr><tr><th>Number</th><th>Percent</th><th>Number</th><th>Percent</th><th>Number</th><th>Percent</th></tr></thead><tbody><tr><td>Gender</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Women</td><td>2,750</td><td>54.01</td><td>955</td><td>40.83</td><td>628</td><td>59.19</td></tr><tr><td>Men</td><td>2,342</td><td>45.99</td><td>1,384</td><td>59.17</td><td>433</td><td>40.81</td></tr><tr><td>Nationality</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>French</td><td>4,887</td><td>95.97</td><td>2,220</td><td>94.91</td><td>1,053</td><td>99.25</td></tr><tr><td>Not French</td><td>205</td><td>4.03</td><td>119</td><td>5.09</td><td>8</td><td>0.75</td></tr><tr><td>Region</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Paris</td><td>698</td><td>13.71</td><td>351</td><td>15.01</td><td>170</td><td>16.02</td></tr><tr><td>Out of Paris</td><td>4,394</td><td>86.29</td><td>1,988</td><td>84.99</td><td>891</td><td>83.98</td></tr><tr><td>Age</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>16-29</td><td>1,442</td><td>28.32</td><td>555</td><td>23.73</td><td>170</td><td>16.02</td></tr><tr><td>30-39</td><td>1,395</td><td>27.40</td><td>742</td><td>31.72</td><td>340</td><td>32.05</td></tr><tr><td>40-49</td><td>1,378</td><td>27.06</td><td>741</td><td>31.68</td><td>372</td><td>35.06</td></tr><tr><td>50-59</td><td>877</td><td>17.22</td><td>301</td><td>12.87</td><td>179</td><td>16.87</td></tr><tr><td>Highest diploma</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>No secondary degree</td><td>1,838</td><td>36.10</td><td>742</td><td>31.72</td><td>276</td><td>26.01</td></tr><tr><td>Vocational technical school (Basic)</td><td>1,449</td><td>28.46</td><td>851</td><td>36.38</td><td>242</td><td>22.81</td></tr><tr><td>High school degree<br>(general or vocational)</td><td>745</td><td>14.63</td><td>308</td><td>13.17</td><td>143</td><td>13.48</td></tr><tr><td>Technical College, undergraduate<br>university,<br>or Licence, Maitrise</td><td>765</td><td>15.02</td><td>299</td><td>12.78</td><td>270</td><td>25.45</td></tr><tr><td>Graduates</td><td>295</td><td>5.79</td><td>139</td><td>5.94</td><td>130</td><td>12.25</td></tr><tr><td>Part-time</td><td>553</td><td>16.3</td><td>360</td><td>15.4</td><td>181</td><td>17.1</td></tr></tbody></table>

The statistics given above are assessed on the first year 1994.

Source: French European Household Survey.

The differences in the estimation of the public wage gap prompt us to carefully examine our specification, and the way we estimate this premium.

From descriptive statistics the log monthly wage variance is lower in the public sector than in the private one whatever the degree, except for high school dropouts. Internal exams may promote significantly upward mobility for lower degrees, increasing the wage variance of this group. For other degrees, this is consistent with wage compression in the public sector. The log monthly wage mean is also higher in the public sector when degree is not controlled for (see figure 1). Conditional on degree, this still holds except for graduates who seem to be less rewarded in the public than in the private sector. Hence the public sector seems to protect lower degrees from unemployment and lower wages. As descriptive statistics do not control for selectivity, we need to go one step further. The model we propose control for participation selection, and for sector choice, as well as unobserved and observed heterogeneity: age, potential experience,<fnref n="5" /> region, number of children less than 3 years old, between 3 and 6...

<footnote n="5">⁵Experience cannot be precisely measured in the data. Hence we use the age at the end of studies as a proxy of potential experience. It is a proxy for general experience and not for sector-specific experience. We do not introduce potential experience itself in the wage equation to avoid colinearity between potential experience and age.</footnote>
<table><caption>Table 3 Simple regressions on the log of monthly wage</caption><thead><tr><th rowspan="2"></th><th colspan="4">Specification</th><th rowspan="2">Public Sector</th></tr><tr><th>1</th><th>2</th><th>3</th><th>4</th></tr></thead><tbody><tr><td>Constant</td><td>7.165</td><td>5.304</td><td>5.354</td><td>5.262</td><td>5.593</td></tr><tr><td>Public</td><td>-0.010</td><td>0.048</td><td>0.050</td><td>0.058</td><td>0.086</td></tr><tr><td>Gender</td><td>-0.418</td><td>-0.241</td><td>-0.260</td><td>-0.262</td><td>-0.184</td></tr><tr><td>Paris region</td><td>0.007</td><td>0.005</td><td>0.009</td><td>0.007</td><td>0.009</td></tr><tr><td>Age (years/10)</td><td></td><td>0.193</td><td>0.196</td><td>0.238</td><td>0.096</td></tr><tr><td>Age squared (years<sup>2</sup>/10)</td><td></td><td>0.009</td><td>0.009</td><td>0.011</td><td>0.015</td></tr><tr><td>Age squared (years<sup>2</sup>/10)</td><td></td><td>0.661</td><td>0.639</td><td>0.698</td><td>0.581</td></tr><tr><td>Age of end of study (years/10)</td><td></td><td>0.020</td><td>0.022</td><td>0.025</td><td>0.036</td></tr><tr><td>Age of end of study (years<sup>2</sup>/10)</td><td></td><td>-0.063</td><td>-0.062</td><td>-0.069</td><td>-0.052</td></tr><tr><td>Vocational degree</td><td></td><td>0.003</td><td>0.003</td><td>0.003</td><td>0.004</td></tr><tr><td>High School degree</td><td></td><td>0.125</td><td>0.464</td><td>0.129</td><td>0.102</td></tr><tr><td>College and undergraduate</td><td></td><td>0.009</td><td>0.015</td><td>0.010</td><td>0.015</td></tr><tr><td>Graduate</td><td></td><td>0.486</td><td>0.081</td><td>0.465</td><td>0.506</td></tr><tr><td>Part-time</td><td></td><td>0.008</td><td>0.019</td><td>0.011</td><td>0.013</td></tr><tr><td>Part-time</td><td></td><td>0.756</td><td>-0.017</td><td>0.796</td><td>0.714</td></tr><tr><td>Part-time</td><td></td><td>0.011</td><td>0.003</td><td>0.015</td><td>0.016</td></tr><tr><td>Part-time</td><td></td><td>-0.613</td><td>-0.613</td><td>-0.640</td><td>-0.554</td></tr><tr><td>Part-time</td><td></td><td>0.007</td><td>0.007</td><td>0.009</td><td>0.011</td></tr></tbody></table>

Source: French European Household Survey.

We control for time dummies in the wage equation.

Specifications 1 and 2: OLS regressions. Specification 3: 2SLS regression to control for sector choice endogeneity.

Specification 4: OLS regressions for each sector.

# 3. Econometric model and estimation principles

## 3.1. Model

As unobserved heterogeneity is crucial to understand different economic behaviors and unobserved productivity, we add unobserved terms to each equation. Following the method of Heckman and Singer (1984), we model unobserved heterogeneity $\theta$ via a discrete random variable whose distribution has a given number of support points to be estimated. We assume that there are $K$ types of individuals, $\pi_k$ denotes the probability of type $k$. Within this framework, unobserved heterogeneity is type specific such as sector specific. An individual may for instance have a sector specific ability and his unobserved ability may be rewarded differently according to the sector. Hence an individual of type $k$ has a different propensity to earn low or high wages in both sectors, this propensity is captured by $\theta_k^{Pu}$ and $\theta_k^{Pr}$. The propensity to work rather in the public than in the private sector is captured by $\theta_k^Z$, it may represent a particular taste for public services.
In a first equation, we consider the employment status. It describes the fact that the individual works or does not ($y_{it} = 1$ if the individual works, $y_{it} = 0$ otherwise). In a second equation, as the structural model described above confirms it, we consider the sector choice as a binary variable ($z_{it} = 1$ when the individual works in the private sector, $z_{it} = 0$ when he works in the public sector): the nonemployed search for both public and private jobs when $c_{Pu} \le U_{pu}$. And this threshold depends on explanatory variables such as individual covariates and the local unemployment rate. We also include in the explanatory variables the difference of the expected log wages between the public and the private sectors. This difference depends on the type of the individual. Finally we have a switching wage equation: the third (resp. fourth) equation is the log monthly wage in the private sector $w_{it}^{Pr}$ (resp. in the public sector $w_{it}^{Pu}$).<fnref n="6" />

$$y_{it} = \mathbf{1} (X_{it}^{Y} \beta^{Y} + \theta_{k(i)}^{Y} + u_{it}^{Y} > 0) \quad (3.1)$$

And if the individual works,

$$z_{it} = \mathbf{1} (X_{it}^{Z} \beta^{Z} + \gamma \mathbb{E} (w_{it}^{Pr} - w_{it}^{Pu} | k(i)) + \theta_{k(i)}^{Z} + u_{it}^{Z} > 0) \quad (3.2)$$

$$w_{it}^{Pr} = z_{it} (X_{it}^{Pr} \beta^{Pr} + \theta_{k(i)}^{Pr} + u_{it}^{Pr}) \quad (3.3)$$

$$w_{it}^{Pu} = (1 - z_{it}) (X_{it}^{Pu} \beta^{Pu} + \theta_{k(i)}^{Pu} + u_{it}^{Pu}) \quad (3.4)$$

where

$\theta = (\theta^Y, \theta^Z, \theta^{Pr}, \theta^{Pu})$ denotes the vector of the unobserved heterogeneity components,

$k(i)$ denotes the type of the individual $i$,

$X = (X^Y, X^Z, X^{Pr}, X^{Pu})$ denotes the vector of observable characteristics,

$\beta = (\beta^Y, \beta^Z, \beta^{Pr}, \beta^{Pu})$ denotes the vector of parameters,

$u = (u^Y, u^Z, u^{Pr}, u^{Pu})$ denotes the vector of residuals, which are assumed to be independent and normally distributed across time and individuals, with variance $\sigma_{Pr}^2$ (resp. $\sigma_{Pu}^2$).<fnref n="7" />

## 3.2. Identification strategy

The model identification does not only rely on functional assumptions (imposed on the residual distributions), but also on exclusion restrictions. On the one hand, in the nonemployment/employment equation, we include the number of children between 0 and 3, the number of children between 3 and 6, and the spouse income. These variables are crucial for explaining female participation (see Hyslop (1999) and Edon and Kamionka (2008)). And they are excluded from the sector choice and the wage equations. Female may indeed have a higher propensity to choose the public sector when they intend to have children, but their precise number of children may rather influence their participation decision and it does not influence the sector choice.

On the other hand, in the sector choice equation, a proxy of the father status, as well as a proxy of the mother status at the end of the individual's studies, are included. These are known to be determinants of the civil servant status (Audier (2000)). As the true status of the parents' occupation is not directly

<footnote n="6">⁶The model does not include lagged dependent variables. It could be included to capture state dependence. In such a case, the introduction of initial conditions could be solved using the method proposed by Wooldridge (2005) or the one proposed by Heckman (1981). This would entail to compute the likelihood recursively, conditional on the initial conditions.</footnote>

<footnote n="7">⁷The assumption of independence across residuals is not restrictive since we follow Heckman and Singer (1984) to model the unobserved heterogeneity, see also Cameron and Heckman (1998) and Arcidiacono (2005).</footnote>
observed, a proxy is built from the two-digit classification of their occupation. Hence we consider the father (resp. mother) was a civil servant when he (resp. she) was either 'senior civil servants, information professionals or creative and performing artists' or 'middle-level health and teaching workers, middle-level civil servants' or finally 'middle-level civil servants'. These variables are excluded from the rest of the model.<fnref n="8" />

Finally, in order to ensure identification of the unobserved heterogeneity, the intercept is excluded from each equation.

### 3.3. Likelihood and estimation principles

The heterogeneity is modeled by K distinct types $(\theta_1, \theta_2, ..., \theta_K)$ with $\theta_k = (\theta_k^Y, \theta_k^Z, \theta_k^{Pr}, \theta_k^{Pu})'$. Let $\pi_k$ denote the unconditional probability that an individual has the type k. As we consider a discrete distribution for the heterogeneity terms, we rely on the Expectation-Maximization<fnref n="9" /> (EM) algorithm (Dempster, Laird, and Rubin (1977)) to estimate the model.<fnref n="10" />

This algorithm iterates the two following steps until the stability of the log-likelihood (for detailed explanations, see appendix D). At each iteration n of the algorithm, we use the estimated values $\pi_k^n$ and $(\theta_1^n, \theta_2^n, ..., \theta_K^n)$ of the mixture distribution, and the estimated values $(\beta^n, \sigma_{Pu}^{2,n}, \sigma_{Pr}^{2,n})$ of the parameters of interest.

#### E-step

For each type $k = 1, ..., K$ and each individual $i$, the posterior probability of type k is:

$$ \mathbb{P}(T_i = k | \underline{y}_i, \underline{z}_i, \underline{w}_i) = \pi_{ik}^{(n)} = \frac{\pi_k \mathbb{P}(\underline{y}_i, \underline{z}_i, \underline{w}_i | T_i = k)}{\sum_{l=1}^{K} \pi_l \mathbb{P}(\underline{y}_i, \underline{z}_i, \underline{w}_i | T_i = l)}. \quad (3.5) $$

where $T_i$ is the random variable representing the type of the individual $i$. $\pi_{ik}^{(n)}$ denotes the posterior probability for the individual $i$ to be of type k.

#### M-step

The expected completed log likelihood is maximized:

$$ \max_{\substack{\beta, \sigma_{Pu}^2, \sigma_{Pr}^2, \\ (\pi_k)_{k=1,...,K}, \\ (\theta_k)_{k=1,...,K}}} \sum_{i=1}^{N} \sum_{k=1}^{K} \pi_{ik}^{(n)} \ln \left( \underline{y}_i, \underline{z}_i, \underline{w}_i | T_i = k, \beta, \sigma_{Pu}^2, \sigma_{Pr}^2, (\pi_k)_{k=1}^K, (\theta_k)_{k=1}^K \right) \quad (3.6) $$

First $\pi_k^{(n)}$ is updated such that:

$$ \pi_k^{(n+1)} = \frac{\sum_{i=1}^{N} \pi_{ik}^{(n)}}{\sum_{l=1}^{K} \sum_{i=1}^{N} \pi_{il}^{(n)}} \quad (3.7) $$

<footnote n="8">⁸In 1994, among women who work, 13% of them have a father who was civil-servant, and 10.6% a mother who was civil-servant. For men, these percentage are respectively 12.3% and 8.4%.</footnote>

<footnote n="9">⁹We do not use *Simulated Maximum Likelihood* to estimate the model, since it is time consuming and it presents convergence failures. Even with precise and accurate initial conditions, the program fails to converge quickly and it seems to get trapped in some regions.</footnote>

<footnote n="10">¹⁰Standard errors are obtained by parametric bootstrap.</footnote>
Second, due to the partial separability of the conditional completed log-likelihood function (Arcidiacono and Jones (2003)), we get four sequential optimization problems since residuals are assumed to be independent across the four equations (see Appendix D).

Thus, we first maximize the participation equation, then the log-earnings equations. Given the estimates of these two equations, we estimate the parameters of the equation for the sector choice. Although this procedure does not yield full information maximum likelihood estimates, Arcidiacono and Jones (2003) show that this method produces consistent estimates of the parameters. Standard errors estimates are obtained by a parametric bootstrap procedure, instead of a non parametric one, since this last method is unstable when applied to the EM algorithm.<fnref n="11" />

# 4. Results

## 4.1. Parameter estimates

Tables 4 to 6 report the parameter estimates of the four equations.

### Employment

As expected, the gender negatively affects employment, as well as young children do. Women who work may choose to get out of the labor market to bring up their children. They then usually wait for their entrance into nursery or primary school to work again. In France, some children part-time attend nursery school. The marriage also negatively affects the employment decision. The effect of age on employment is assumed to be quadratic: we find that the employment probability first increases, and then decreases with age.

Moreover, the higher the degree, the higher the probability to be employed. Graduate degrees are the most rewarding ones in terms of employment probabilities. High-school degree and vocational degree estimates do not statistically differ.

Individuals who live in the region around Paris or in Paris have a greater probability to be employed because of job offer opportunities. Finally, as expected, the local unemployment rate has a negative effect on the probability to be employed.

### Sector Choice

Our theoretical model teaches us that, given risk aversion, a higher unemployment rate diminishes the cost of searching for a public job when unemployed. The relative return associated to the private sector drops when the unemployment rate rises. This is confirmed by our estimations: the local unemployment rate favors the choice of public sector (Table 5). Fougère and Pouget (2003) also find that the number of candidates for a public job and the macroeconomic cycle go along. Hence the local unemployment rate is a core variable to understand public sector attractiveness.

$$ \bar{\beta}^* = \frac{1}{H} \sum_{h=1}^{H} \beta_h^* \qquad (3.8) $$

$$ \sigma_{\beta^*} = \frac{1}{H-1} \sum_{h=1}^{H} (\beta_h^* - \bar{\beta}^*)^2. \qquad (3.9) $$

<footnote n="11">¹¹The parametric bootstrap consists first in obtaining reliable parameter estimates for the whole set of unknown parameters denoted $\hat{\chi}$. $\hat{\chi}$ is obtained by replicating the previously described EM algorithm with different random initial values for the parameters. The iteration process is necessary to ensure that a global maximum is obtained. Then, given $X$ and $\hat{\chi}$, we generate $H$ vectors of the endogenous variables $(y_i^h, z_i^h, w_i^h)_{h=1...H}$. For each newly generated data set, we estimate the whole set of unknown parameters. Final parameters and standard error estimates are computed as</footnote>
Moreover, the greater the difference between expected log wages, the larger the probability to choose the private sector. Individuals rationally choose the sector where they anticipate the highest wage.

Unlike the mother's position, the father's position has an effect on his children's sector choice. A son tends to prefer public services if his father is a civil-servant. The observation that civil servants' children are over-represented in the public sector (Audier (2000)) is therefore robust to the inclusion of covariates such as degree, local unemployment rate. Unlike men, women whose father is a civil-servant tend to prefer private sector compared to women whose father is not a civil-servant.

Moreover, as expected, women have a higher propensity than men to work in public services. This result will be reenforced by wage analysis. This result is in line with Bell, Elliott, and Scott (2005), who find, for UK, that the gains to staying in the public sector are greater for women than for men, and that women tend to gain by joining the public sector, almost irrespective of their position in the earnings distribution. We find similar results for France (see following sections). Fougère and Pouget (2003) also find that the length of the queue for public sector is longer for female.

Individuals with lower degree tend to work in the private sector unlike individuals with post-secondary education. Two reasons may explain this effect: first, French public jobs are more qualified on the whole than jobs in private sector (teaching, executive...). And many public jobs require to pass an exam which is conditional on a given degree.

## Wages

Standard results are obtained for different variables, such as age, experience, degree... For instance, living around Paris and in Paris gives a positive premium for wages. The comparison between private and public wages is more instructive.

Unlike the descriptive statistics, the residual variance is estimated slightly higher in the public sector (0.109) than in the private one (0.084). For identification reasons, we cannot compute what people usually call "the public raw wage premium". For all degrees, except for graduates, the returns to education are roughly the same in both sectors. But returns to education for graduates are greater in the private sector: the highest wages are observed in the private sector.

Worth to be pointed out is the highest penalty to be a women in the private sector. As Gregory and Borland (1999) underlined, public sector wage inefficiency may counterbalance wage discriminations. That seems to be the case in France as gender is concerned. Nonetheless, to be a woman has also a negative effect on public wages. Indeed women have lower probabilities to be promoted than men with similar characteristics (Bessière and Pouget (2007)). And in public services, wage increases are closely linked to grade promotions. Thus career differences may explain wage differences between men and women in public services.

We give further details on wages in the following section thanks to simulations.

## 4.2. Types

The results are obtained under the assumption that there are four types of individuals within the sample (K = 4, see table 7). The number of heterogeneity components is chosen on the basis of the BIC penalized likelihood criterion: models with K = 3 and K = 2 yield substantially larger BIC values, and a model with five types yields a similar BIC criterion than a model with four types.

In a first step, we compute the individual posterior probability to be of a given type at the initial date 1994. In this subsection, we consider that an individual is of type *k* when the individual posterior probability $P(T_i = k|\underline{y}_i, \underline{z}_i, \underline{w}_i, \underline{X}_i)$ associated to the type *k* is the highest. The results show that a clear
<table><caption>Table 4. Employment equation</caption><thead><tr><th>Variables</th><th>Estimates</th><th>Standard Error</th></tr></thead><tbody><tr><td>Women</td><td>-0.601</td><td>0.049</td></tr><tr><td>Not French</td><td>0.157</td><td>0.044</td></tr><tr><td>Not Married</td><td>0.049</td><td>0.020</td></tr><tr><td>Children under 3</td><td>-0.241</td><td>0.024</td></tr><tr><td>Children between 3 and 6</td><td>-0.268</td><td>0.028</td></tr><tr><td>Age (years/10)</td><td>4.530</td><td>0.204</td></tr><tr><td>Age squared (years<sup>2</sup>/10)</td><td>-0.564</td><td>0.025</td></tr><tr><td>Vocational degree</td><td>0.234</td><td>0.028</td></tr><tr><td>High School degree</td><td>0.284</td><td>0.039</td></tr><tr><td>College and Under Graduate</td><td>0.378</td><td>0.030</td></tr><tr><td>Graduate</td><td>0.726</td><td>0.060</td></tr><tr><td>Paris</td><td>0.174</td><td>0.027</td></tr><tr><td>Local unemployment rate</td><td>-0.010</td><td>0.002</td></tr><tr><td>Log spouse income</td><td>0.026</td><td>0.006</td></tr></tbody></table>

Source: French European Household Survey.

The log spouse income is standardized.

<table><caption>Table 5. Private sector choice</caption><thead><tr><th>Variables</th><th>Estimates</th><th>Standard Error</th></tr></thead><tbody><tr><td>Women</td><td>-0.236</td><td>0.055</td></tr><tr><td>Age (years/10)</td><td>-0.219</td><td>0.177</td></tr><tr><td>Age squared (years<sup>2</sup>/10)</td><td>0.019</td><td>0.021</td></tr><tr><td>Not Married</td><td>0.046</td><td>0.042</td></tr><tr><td>Vocational degree</td><td>0.084</td><td>0.065</td></tr><tr><td>High School degree</td><td>0.092</td><td>0.063</td></tr><tr><td>College and Under Graduate</td><td>-0.114</td><td>0.048</td></tr><tr><td>Graduate</td><td>-0.625</td><td>0.079</td></tr><tr><td>Women times Father civil servant</td><td>0.480</td><td>0.083</td></tr><tr><td>Men times Father civil servant</td><td>-0.266</td><td>0.076</td></tr><tr><td>Women times Mother civil servant</td><td>-0.084</td><td>0.068</td></tr><tr><td>Men times Mother civil servant</td><td>0.043</td><td>0.088</td></tr><tr><td>Local unemployment rate</td><td>-0.037</td><td>0.005</td></tr><tr><td>Difference of expected log wage</td><td>1.665</td><td>0.195</td></tr></tbody></table>

Source: French European Household Survey.

type-partition exists. At the initial date, type-3 people are mainly nonemployed (84.5%) whereas type-1, type-2 and type-4 individuals are mainly employed. These latter groups differ according to the sector choice. 85.5% of type-2 individuals are employed in public services in 1994, whereas 87.9% of type-1 individuals and 75.4% of type-4 individuals are employed in the private sector. Thus employment and sectors distinctly partition individuals in our sample.

Considering the values of unobserved heterogeneity for different types, remark that *type-4* individuals have an unobserved ability similar in both sectors ($\theta^{W_{Pr}} = 4.631$ and $\theta^{W_{Pu}} = 4.700$), whereas type-1 and type-2 individuals would have a different unobserved ability in both sectors. Type-2 individuals, mainly employed in the public sector, clearly have chosen the sector in which they are the most paid
<table><caption>Table 6. Wage equations</caption><thead><tr><th rowspan="2">Variables</th><th colspan="2">Private Sector</th><th colspan="2">Public Sector</th></tr><tr><th>Estimates</th><th>Standard Error</th><th>Estimates</th><th>Standard Error</th></tr></thead><tbody><tr><td>Women</td><td>-0.423</td><td>0.016</td><td>-0.183</td><td>0.008</td></tr><tr><td>Paris</td><td>0.284</td><td>0.010</td><td>0.100</td><td>0.014</td></tr><tr><td>Age (years/10)</td><td>0.889</td><td>0.063</td><td>0.493</td><td>0.030</td></tr><tr><td>Age squared (years<sup>2</sup>/10)</td><td>-0.093</td><td>0.008</td><td>-0.042</td><td>0.003</td></tr><tr><td>Age of end of study (years/10)</td><td>0.190</td><td>0.016</td><td>0.041</td><td>0.027</td></tr><tr><td>Age of end of study squared (years<sup>2</sup>/10)</td><td>-0.018</td><td>0.005</td><td>-0.018</td><td>0.008</td></tr><tr><td>Vocational degree</td><td>0.113</td><td>0.008</td><td>0.065</td><td>0.010</td></tr><tr><td>High School degree</td><td>0.351</td><td>0.013</td><td>0.338</td><td>0.013</td></tr><tr><td>College and undergraduate</td><td>0.453</td><td>0.012</td><td>0.452</td><td>0.012</td></tr><tr><td>Graduate</td><td>0.791</td><td>0.012</td><td>0.667</td><td>0.015</td></tr><tr><td>Part-time</td><td>-0.491</td><td>0.007</td><td>-0.436</td><td>0.012</td></tr><tr><td>Year dummies</td><td></td><td></td><td></td><td></td></tr><tr><td>Year 1995</td><td>-0.044</td><td>0.015</td><td>0.027</td><td>0.016</td></tr><tr><td>Year 1996</td><td>-0.008</td><td>0.012</td><td>0.024</td><td>0.013</td></tr><tr><td>Year 1997</td><td>0.008</td><td>0.013</td><td>0.092</td><td>0.012</td></tr><tr><td>Year 1998</td><td>0.019</td><td>0.014</td><td>0.030</td><td>0.014</td></tr><tr><td>Year 1999</td><td>0.063</td><td>0.013</td><td>0.068</td><td>0.016</td></tr><tr><td>Year 2000</td><td>0.020</td><td>0.012</td><td>0.088</td><td>0.014</td></tr><tr><td>Year 2001</td><td>-0.010</td><td>0.014</td><td>0.047</td><td>0.016</td></tr><tr><td>Variance of residuals</td><td>0.083</td><td>0.014</td><td>0.109</td><td>0.004</td></tr></tbody></table>

Source: French European Household Survey.

($\theta^{WPr} = 4.838$ and $\theta^{WPu} = 5.774$). They may have sorted themselves into the sector that pays them more. For the type-1 individuals, this explanation does not hold. They would have a higher productivity in the public sector.

# 5. Simulations

## 5.1. Model fit

This section presents a brief fit analysis of the statistical model presented above. Table 8 presents the predicted probabilities for nonemployment, public jobs and private jobs.<fnref n="12" /> The frequencies of nonemployment such as those of employment in either sector are well replicated whatever the date considered.

Further the model replicates well the cross sectional distribution. Figure 2 plots the observed and predicted log of monthly wage densities for the two sectors separately, which are quite close.

## 5.2. Counterfactual wage distributions

In this section, we derive the counterfactual wage distribution for the individuals employed in the public sector: we aim at estimating the log of monthly wages of the *public workers* if they were employed in the private sector. This is a crucial issue to understand whether the public sector wages are economically justified, or whether they help to circumvent some discrimination issues, for women for instance.

To estimate these counterfactual distributions at date *t*, we use bootstrapping methods. We draw *H* independent individual replicates, drawn from the empirical distribution of the explanatory variables of

<footnote n="12">¹²We evaluate the predicted probability to be employed at date *t* thanks to: $E(y_t) = E(E(y_t|T)) = \sum_{k=1}^{K} \pi_k E(y_t|T=k)$.</footnote>
<table><caption>Table 7. Unobserved heterogeneity</caption><thead><tr><th>Variables</th><th>Estimates</th><th>Standard Error</th></tr></thead><tbody><tr><td colspan="3">Probability of different types</td></tr><tr><td>Type 1</td><td>0.193</td><td>0.170</td></tr><tr><td>Type 2</td><td>0.223</td><td>0.216</td></tr><tr><td>Type 3</td><td>0.233</td><td>0.233</td></tr><tr><td>Type 4</td><td>0.351</td><td>0.382</td></tr><tr><td colspan="3">Type-specific heterogeneity parameters</td></tr><tr><td></td><td colspan="2">Type 1</td></tr><tr><td>θ<sup>Y</sup></td><td>-6.520</td><td>0.628</td></tr><tr><td>θ<sup>Z</sup></td><td>3.430</td><td>0.902</td></tr><tr><td>θ<sup>W<sub>Pr</sub></sup></td><td>5.121</td><td>0.238</td></tr><tr><td>θ<sup>W<sub>Pu</sub></sup></td><td>5.915</td><td>0.228</td></tr><tr><td></td><td colspan="2">Type 2</td></tr><tr><td>θ<sup>Y</sup></td><td>-6.676</td><td>0.902</td></tr><tr><td>θ<sup>Z</sup></td><td>-0.880</td><td>1.391</td></tr><tr><td>θ<sup>W<sub>Pr</sub></sup></td><td>4.838</td><td>0.299</td></tr><tr><td>θ<sup>W<sub>Pu</sub></sup></td><td>5.774</td><td>0.180</td></tr><tr><td></td><td colspan="2">Type 3</td></tr><tr><td>θ<sup>Y</sup></td><td>-9.138</td><td>1.187</td></tr><tr><td>θ<sup>Z</sup></td><td>2.433</td><td>1.308</td></tr><tr><td>θ<sup>W<sub>Pr</sub></sup></td><td>3.973</td><td>0.421</td></tr><tr><td>θ<sup>W<sub>Pu</sub></sup></td><td>5.216</td><td>0.232</td></tr><tr><td></td><td colspan="2">Type 4</td></tr><tr><td>θ<sup>Y</sup></td><td>-7.301</td><td>0.254</td></tr><tr><td>θ<sup>Z</sup></td><td>2.012</td><td>0.377</td></tr><tr><td>θ<sup>W<sub>Pr</sub></sup></td><td>4.631</td><td>0.160</td></tr><tr><td>θ<sup>W<sub>Pu</sub></sup></td><td>4.700</td><td>0.159</td></tr></tbody></table>

Source: French European Household Survey.

the public sector workers at date $t$ ($y_{it} = 1$ and $z_{it} = 0$). For each individual replicate $h$, we draw his type $t(h)$ in the following posterior distribution

$$ \mathbb{P}(T_h = k | y_{ht} = 1, z_{ht} = 0, X_{ht}) = \frac{\pi_k \mathbb{P}(y_{ht} = 1, z_{ht} = 0 | T_h = k, X_{ht})}{\sum_{l=1}^{K} \pi_l \mathbb{P}(y_{ht} = 1, z_{ht} = 0 | T_h = l, X_{ht})}, \quad (5.10) $$

where $T_h$ is the random variable representing the type of the individual $h$. Then we compute the corresponding fitted value of the log monthly wages in both sectors:

$$ w_{ht}^{s,Pr} = X_{ht} \widehat{\beta^{Pr}} + \widehat{\theta_{t(h)}^{Pr}}, \quad (5.11) $$

$$ w_{ht}^{s,Pu} = X_{ht} \widehat{\beta^{Pu}} + \widehat{\theta_{t(h)}^{Pu}}. \quad (5.12) $$

Finally we add a sector-specific residual term that is i.i.d normally distributed with the estimated sector-specific variance. The results rely on the hypothesis that the 4 types are homogeneous as regards the public and private sector capabilities.

Anyway on the figure 3, we observe that the counterfactual distribution remains close to the log of wage public distribution. But this hides different effects according to gender and degrees (see figure
<table><caption>Table 8. Model Fit</caption><thead><tr><th>Variables</th><th>Year</th><th>Predicted probability<br>%</th><th>Observed probability<br>%</th></tr></thead><tbody><tr><td rowspan="8">Nonemployed</td><td>1994</td><td>34.50</td><td>33.23</td></tr><tr><td>1995</td><td>33.67</td><td>32.46</td></tr><tr><td>1996</td><td>33.32</td><td>32.66</td></tr><tr><td>1997</td><td>33.04</td><td>32.82</td></tr><tr><td>1998</td><td>32.96</td><td>32.50</td></tr><tr><td>1999</td><td>33.08</td><td>32.15</td></tr><tr><td>2000</td><td>33.42</td><td>33.23</td></tr><tr><td>2001</td><td>32.57</td><td>34.17</td></tr><tr><td rowspan="8">Public sector</td><td>1994</td><td>20.08</td><td>20.84</td></tr><tr><td>1995</td><td>20.33</td><td>21.29</td></tr><tr><td>1996</td><td>20.54</td><td>21.33</td></tr><tr><td>1997</td><td>20.57</td><td>20.76</td></tr><tr><td>1998</td><td>20.50</td><td>20.66</td></tr><tr><td>1999</td><td>20.27</td><td>20.46</td></tr><tr><td>2000</td><td>19.96</td><td>19.91</td></tr><tr><td>2001</td><td>20.06</td><td>19.50</td></tr><tr><td rowspan="8">Private sector</td><td>1994</td><td>45.42</td><td>45.94</td></tr><tr><td>1995</td><td>46.00</td><td>46.25</td></tr><tr><td>1996</td><td>46.14</td><td>46.01</td></tr><tr><td>1997</td><td>46.39</td><td>46.43</td></tr><tr><td>1998</td><td>46.55</td><td>46.84</td></tr><tr><td>1999</td><td>46.65</td><td>47.39</td></tr><tr><td>2000</td><td>46.62</td><td>46.86</td></tr><tr><td>2001</td><td>47.37</td><td>46.33</td></tr></tbody></table>

Source: French European Household Survey.

4). The counterfactual distribution for men is rather stable except for the upper tail, whereas the female counterfactual distribution shifts left.

In order to precisely evaluate the public wage premium, let us derive and compare quantiles of the former distributions: the public log of wage distribution and the counterfactual distribution. Further details are given in appendix E. Figures 5 and 6 plot the difference of quantiles between the current and the counterfactual distributions according to gender and degrees. The term "public wage premium" seems to be justified at the bottom of the distribution, whereas it does not hold anymore for the upper tail. But when detailed by degree and gender, we find that the public sector, when compared with the private sector, actually gives a premium to women, whereas men would be better paid in the private sector except for those at the lower tail of the distribution. As expected given previous estimations, male graduates would be far better paid in the private sector. So we find similar results to Disney and Gosling (1998) and Bell, Elliott, and Scott (2005): public sector premium is higher for women than for men, and this premium differs across the pay distribution. The lower part of the distribution gains from staying in the public sector. Does it mean that female public workers are overpaid? It may only suggest that the public sector succeeds in reducing the wage gap between male and female, which is large in the private sector. Finally most male public workers would have the same or a higher wage if they were employed in the private sector...<fnref n="13" />

<footnote n="13">¹³It is essential to control for selection into employment and for selection into sector choice to assess the public wage premium. Naive estimations of this public wage premium given in section 2 cannot be appropriate since they only rely on the</footnote>
# 6. Conclusion

This paper presents a new approach on the public-private pay gap: it evaluates the counterfactual wage distribution of public workers if employed in the private sector.

It estimates sector-specific wage equations controlling both for sector choice and employment selection. Thanks to panel data, it captures unobserved heterogeneity which differs between equations. The unobserved heterogeneity is modeled using the method of Heckman and Singer (1984) via a discrete distribution.

The main results are that the wage public premium is significant at the bottom of the public wage distribution. But it turns out to be negative at the upper tail. This is in line with empirical observations: low-wage civil-servants are weakly mobile, whereas high-wage civil servants move more frequently from the public to the private sector, attracted by higher wages. However these results are mitigated when analyzed by gender. The female public sector workers have a comparative advantage in the public sector. Their counterfactual wages in the private sector would be lower whatever their position in the public wage distribution. Whereas graduated men in the public sector would have higher wages in the private sector, graduated women would have the same one. Could we conclude that the public sector overpays women? It may rather counterbalance wage discrimination (see Gregory and Borland (1999)). Finally, for men employed in the public sector, except at the very bottom of the distribution, they would have the same or higher wages in the private sector.

<footnote>value of the constant covariate.</footnote>
# Acknowledgments

We thank Christian Belzil, Pierre Cahuc, Guy Laroque, Thierry Magnac, Costas Meghir, Corinne Prost, Jean Marc Robin, and seminar and conference participants at D3E-INSEE (Paris), JMA (2009), ESEM (2008), Panel Data Workshop (Bonn, 2009) for very helpful comments.

## A. The Search Model

We derive a continuous time search model in a stationary labor market environment. There are three possible states: employment in the public sector, employment in the private sector and nonemployment. The individuals employed in the private sector can be laid off, and they may search for a private job on the job. Those employed in the public sector do not search for a job and cannot be laid off. In France, a public servant can indeed not be laid off. A public employee can be fired only in very rare cases, the rules of which greatly differ from private-sector ones (disciplinary sanctions in the public sector). Hence firings in the public sector are neglected. Finally the nonemployed may search either for a public or for a private job.

Agents live infinitely. At each point in time, they can be either nonemployed (denoted by $n$ as non employed that is unemployed or out of the labor force), or employed either in the private sector (denoted by $Pr$) or in the public sector (denoted by $Pu$). Unemployment and nonparticipation are assumed to be non distinct labor force states. This assumption is not restrictive since we focus on the choice between the public and the private sector, and the data set is restricted to people under 60 who have a high participation rate, whether male or female. Nonemployed individuals enjoy a real return $b$ and receive job offers at a Poisson rate depending on the sector of research $\lambda_{n,Pr}$ and $\lambda_{n,Pu}$. $b$ may represent non labor incomes. Nonemployed individuals support research costs depending on the type of job they search for: $c_{Pr}$ (resp. $c_{Pu}$) for private jobs (resp. for public jobs). They can decide to restrict their research to private jobs. Agents who decide to search for a job in the public sector can fail to enter public services although they get a public offer since they have to succeed the entrance exam to become a civil servant. $p_S$ denotes the probability to succeed conditional on searching for a job in this sector, and it implicitly depends on individual covariates.

When employed in the private sector, individuals receive a real wage $w$, and they continue to receive private job offers at a Poisson rate $\lambda_{Pr,Pr}$. They are assumed to restrict their job research to the private sector and they face search costs $c$.<fnref n="14" /> Existing private jobs are hit by idiosyncratic (productive) shocks that occur at a Poisson rate $\delta$. This assumption implies that an individual cannot transit directly from the private to the public sector, he has to go through an unemployment period. To ease calculations, the instantaneous discount rate is $\rho$ and the horizon is infinite.

Finally, when employed in the public sector, agents cannot search for a private job. We detail later what are the consequences of this assumption.

$F_{Pr}$ denotes the wage distribution in the private sector on $[0, \bar{w}]$, $F_{Pu}$ in the public sector on $[0, \bar{w}]$. We assume that these distributions are different from one another but that they rely on the same finite support for sake of simplicity. Nevertheless the tails of the distributions can be far different (see the empirical part for some illustration, figure 1).

In the sequel $V$ denotes the value function.

- A worker currently employed in the public sector with starting wage $w$ receives net income $w$ and cannot lose his job. We assume that he receives no external nor internal offer. His value function

<footnote n="14">¹⁴To search for a public job requires a lot of time since entrance exams need preparation.</footnote>
is

$$V_{Pu}(w) = \frac{w \Delta t}{1 + \rho \Delta t} + \frac{V_{Pu}(w)}{1 + \rho \Delta t}, \qquad (A.13)$$

which yields

$$V_{Pu}(w) = \frac{w}{\rho}. \qquad (A.14)$$

– A worker currently employed in the private sector receives a net income $w-c$ and may be forcibly separated from his job with probability $\delta$. He also receives private job offers at rate $\lambda_{Pr,Pr}$ which are accepted when their value exceeds the expected discounted lifetime utility stream in the current job:

$$V_{Pr}(w) = \frac{(w-c)\Delta t}{1 + \rho\Delta t} + \delta \frac{V_n\Delta t}{1 + \rho\Delta t} + (1 - \delta\Delta t - \lambda_{Pr,Pr}\Delta t) \frac{V_{Pr}(w)}{1 + \rho\Delta t} \\ + \frac{\Delta t \lambda_{Pr,Pr}}{1 + \rho\Delta t} \int_{0}^{\bar{w}} \max(V_{Pr}(x), V_{Pr}(w)) dF_{Pr}(x),$$

which can be simplified in

$$V_{Pr}(w)(\rho + \delta) = w - c + \delta V_n \qquad (A.15) \\ + \lambda_{Pr,Pr} \int_{w}^{\bar{w}} (V_{Pr}(x) - V_{Pr}(w)) dF_{Pr}(x).$$

– A currently nonemployed person enjoys a net flow of income $b-c-d_{Pu}c_{Pu}$ depending on her choice to search for a public job ($d_{Pu} = 1$) or not ($d_{Pu} = 0$). We assume that he must search for a private job.

$$V_n^{d_{Pu}} = \frac{(b-c-d_{Pu}c_{Pu})}{1+\rho\Delta t}\Delta t + \frac{\Delta t}{1+\rho\Delta t}\lambda_{n,Pr}\mathbb{E}_{F_{Pr}}(\max(V_n, V_{Pr}(X))) \\ + \frac{\Delta t}{1+\rho\Delta t}\lambda_{n, Pu}d_{Pu}\mathbb{E}_{F_{Pu}}\{\max(V_n, p_S V_{Pu}(X) + (1-p_S)V_n)\} \\ + \frac{1}{1+\rho\Delta t}(1-\lambda_{n,Pr}\Delta t - \lambda_{n, Pu}d_{Pu}\Delta t)V_n. \qquad (A.16)$$

For the nonemployed, the optimal acceptance rule consists in accepting the first job, whatever the sector, that pays more than a reservation wage $w^*$ that is specific to the sector: $w_{Pu}^*$ for the public sector and $w_{Pr}^{*,d_{Pu}}$ for the private sector ($w_{Pr}^{*,d_{Pu}=1}$ denotes the reservation wage when the unemployed search for both public and private jobs, $w_{Pr}^{*,d_{Pu}=0}$ when the unemployed search only for private jobs).

$$d_{Pu} \in \{0, 1\} \qquad \begin{aligned} V_{Pr}(w_{Pr}^{*,d_{Pu}}) &= V_n^{d_{Pu}} \\ V_{Pu}(w_{Pu}^*) &= V_n^{d_{Pu}=1}. \end{aligned}$$

These reservation wages exist and are unique because the private and public value functions are continuous and increasing functions. Therefore the equation (A.16) can be rewritten:<fnref n="15" />

$$\rho V_n^{d_{Pu}} = (b - c - d_{Pu}c_{Pu}) + \lambda_{n,Pr} \int_{w_{Pr}^*}^{\bar{w}} (V_{Pr}(x) - V_n) dF_{Pr}(x) \qquad (A.17)$$

<footnote n="15">¹⁵Note that $\max(x, zp + (1-p)x) = p \max(x, z) + (1-p)x$ with $p \in [0, 1[$</footnote>
$$+\lambda_{n,Pu}d_{Pu}p \int_{w_{Pu}^*}^{\bar{w}} (V_{Pu}(x) - V_n) dF_{Pu}(x).$$

When does a nonemployed worker decide to search for a public job? Searching for a public job is actually costly and risky since individuals are not sure to succeed to enter public services. This cost of searching for a public job is induced by the fact that individuals have to pick up information, to prepare entrance exams. Hence nonemployed will search for a public job when their expected gains, which may depend on individual characteristics and unobserved ability, exceed the searching cost (see figure 7). So $d_{pu} = 1$ when:<fnref n="16" />

$$c_{Pu} \le p_S \frac{\lambda_{n,Pu}}{\rho} \int_{h(w_{d=0}^*)}^{\bar{w}} \bar{F}_{Pu}(x)dx, \quad (A.18)$$

We denote $U_{pu} = p_S \frac{\lambda_{n,Pu}}{\rho} \int_{h(w_{d=0}^*)}^{\bar{w}} \bar{F}_{Pu}(x)dx$ and $h(w_{d=0}^*)$ is a function of $(b, \lambda_{n,Pr}, \lambda_{Pr,Pr}, \bar{w}, \rho, \delta, \bar{F}_{Pr})$. $h(w_{d=0}^*)$ can also be written as

$$h(w_{d=0}^*) = \frac{\lambda_{n,Pr}}{\lambda_{n,Pr} - \lambda_{Pr,Pr}} w_{d=0}^* - c - \frac{\lambda_{Pr,Pr}}{\lambda_{n,Pr} - \lambda_{Pr,Pr}} b \quad (A.19)$$

The probability to search for a public job is $P(c_{Pu} \le U_{pu})$. When the cost of searching for a public job is greater than $U_{pu}$, the nonemployed had rather searched for a private job only. $U_{pu}$ depends on individual characteristics, on the probability of passing the exam and finally, on the reservation wage via $h(w_{d=0}^*)$.

Equation (A.18) entails that the value of the threshold, determining the search for a public job, is lower when the probability to succeed the entrance exams decreases or when the public arrival rate is lower. $U_{pu}$ depends on $\lambda_{n,Pu}$ and $p_S$ in a multiplicative way, since $h(w_{d=0}^*)$ does not depend on these variables.

*Which consequences?* First, the higher the probability to pass the exam ($p_S$), the higher the probability to search for a public job. This feature is empirically illustrated by the fact that the individuals with a higher degree have a higher probability to pass the entrance exams. For instance, in 2006, among individuals who take the "CAPES" exam (entrance exam to become a high-school or secondary-school teacher), 53% had a "licence" degree (L3) and 44% had a "maîtrise" (M1), this latter degree requires an additional year of studies. Considering those who finally pass the exam, 58% had a maîtrise and only 41% had a licence. Similar features hold for other public-sector exams. The higher the degree, the higher the probability to pass the exam.

Second the unemployment rate is captured by the parameter $\delta$, and $h(w_{d=0}^*)$ depends on $\delta$ only by the way of $w_{d=0}^*$. It turns that $w_{d=0}^*$ diminishes when $\delta$ grows (see Appendix B and equation A.19). Hence the probability to search for a public job increases with $\delta$.

*The limits of the model*

This model presents several limits: unemployed and nonparticipants are not distinguished. As the sample is composed of people aged between 16 and 59, largely economically active, this assumption is not very restrictive. Furthermore, the model assumes that public workers cannot search for a private job. This assumption is made for the sake of simplicity but if relaxed, our core results would not be modified. The function value associated to the public sector would be larger, since it is more flexible: the French civil servants could work a few years in the private sector and get

<footnote n="16">¹⁶Details are in appendix B</footnote>
their public job back in the public sector. Henceforth they could not suffer from their private-job experience: even if laid off, they could recover a job in public services. In such a case, their wage would be the wage they had when departing for a private experience.

Finally the model does not take into account possible parental or sabbatic leaves for civil servants. Moreover we do not enable direct transitions from the public to the private sector, and vice versa. These limits would modify both the public and the private function values but the core results would not change.

## B. Structural model

From (A.15), differentiating this latter equation with respect to $w$ yields:

$$ 
\begin{aligned}
\rho V'_{Pr}(x) &= 1 - \delta V'_{Pr}(x) - \lambda_{Pr,Pr} V'_{Pr}(x) \bar{F}(x) \\
\Rightarrow V_{Pr}(x) - V_{Pr}(\bar{w}) &= - \int_{x}^{\bar{w}_{Pr}} \frac{1}{\rho + \delta + \lambda_{Pr,Pr} \bar{F}_{Pr}(y)} dy
\end{aligned}
$$

Let us consider both cases.

* Case 1: $d_{Pu} = 0$

When the individual does not search for a public job, if he receives an offer with a wage $w$ greater than $w_{d=0}^*$, he accepts this offer. The reservation wage $w_{d=0}^*$ checks: $V_n^{d=0} = V_{Pr}(w_{d=0}^*)$. Henceforth:

$$ 
\begin{aligned}
V_n^{d=0} \rho &= (b-c) + \lambda_{n,Pr} \int_{w_{Pr,d=0}^*}^{\bar{w}} (V_{Pr}(x) - V_n) dF_{Pr}(x) \\
&= (b-c) + \lambda_{n,Pr} \int_{w_{Pr,d=0}^*}^{\bar{w}} V'_{Pr}(x) \bar{F}_{Pr}(x) dx \\
\Rightarrow \quad & \left( \begin{array}{l} \rho V_n^{d=0} = (b-c) + \lambda_{n,Pr} \int_{w_{Pr,d=0}^*}^{\bar{w}} V'_{Pr}(x) \bar{F}_{Pr}(x) dx \\ \rho V_n^{d=0} = w_{Pr,d=0}^* - c + \lambda_{Pr,Pr} \int_{w_{Pr,d=0}^*}^{\bar{w}} V'_{Pr}(x) \bar{F}_{Pr}(x) dx \end{array} \right)
\end{aligned}
$$

And:

$$ 
\begin{aligned}
w_{Pr,d=0}^* &= b \qquad (B.20) \\
&\quad + (\lambda_{n,Pr} - \lambda_{Pr,Pr}) \int_{w_{Pr,d=0}^*}^{\bar{w}} \frac{\bar{F}_{Pr}(x)}{\rho + \delta + \lambda_{Pr,Pr} \bar{F}_{Pr}(x)} dx
\end{aligned}
$$

* Case 2: $d_{Pu} = 1$

Let us proceed the same way thus we get:

$$ 
\begin{aligned}
\rho V_n^{d=1} &= (b-c-c_{Pu}) + \lambda_{n,Pr} \int_{w_{Pr,d=1}^*}^{\bar{w}} V'_{Pr}(x) \bar{F}_{Pr}(x) dx \lambda_{n,Pr} \\
&\quad + p \lambda_{n,Pu} \int_{w_{Pu}^*}^{\bar{w}} V'_{Pu}(x) \bar{F}_{Pu}(x) dx
\end{aligned}
$$
$$ \rho V_n^{d=1} = w_{Pr,d=1}^* - c + \lambda_{Pr,Pr} \int_{w_{Pr,d=1}^*}^{\bar{w}} V'_{Pr}(x) \bar{F}_{Pr}(x) dx $$

$$ V_n^{d=1} = V_{Pr}(w_{Pr,d=1}^*) = V_{Pu}(w_{Pu}^*) = \frac{w_{Pu}^*}{\rho} $$

Hence:

$$ w_{Pu}^* = w_{Pr,d=1}^* - c + \lambda_{Pr,Pr} \int_{w_{Pr,d=1}^*}^{\bar{w}} \frac{\bar{F}_{Pr}}{\rho + \delta + \lambda_{Pr,Pr} \bar{F}_{Pr}(x)}(x)dx $$

$$ w_{Pr,d=1}^* = (b - c_{Pu}) + (\lambda_{n,Pr} - \lambda_{Pr,Pr}) \int_{w_{Pr,d=1}^*}^{\bar{w}} \frac{\bar{F}_{Pr}(x)}{\rho + \delta + \lambda_{Pr,Pr} \bar{F}_{Pr}(x)} dx \\ + \frac{\lambda_{n,Pu}p}{\rho} \int_{w_{Pu}^*}^{\bar{w}} \bar{F}_{Pu}(x) dx $$

The values we have to compare to determine whether the individual searches for a public job, are $V_n^{d=0}$ and $V_n^{d=1}$, i.e. $V_{Pr}(w_{Pr,d=0}^*)$ and $V_{Pr}(w_{Pr,d=1}^*)$:

$$ V_{Pr}(w_{Pr,d=1}^*) - V_{Pr}(w_{Pr,d=0}^*) = \int_{w_{Pr,d=0}^*}^{\bar{w}} \frac{1}{\rho + \delta + \lambda_{Pr,Pr} \bar{F}(x)} dx - \int_{w_{Pr,d=1}^*}^{\bar{w}} \frac{1}{\rho + \delta + \lambda_{Pr,Pr} \bar{F}(x)} dx $$

$$ V_{Pr}(w_{Pr,d=1}^*) = V_{Pr}(w_{Pr,d=0}^*) \Leftrightarrow w_{Pr,d=1}^* = w_{Pr,d=0}^* $$

$$ \text{and} \quad V_{Pr}(w_{Pr,d=1}^*) \geq V_{Pr}(w_{Pr,d=0}^*) \Leftrightarrow w_{Pr,d=1}^* \geq w_{Pr,d=0}^* $$

The nonemployed person searches for both public and private jobs when $w_{Pr,d=1}^* \geq w_{Pr,d=0}^*$.

From equations $(w_{Pr,d=0}^*)$, $(w_{Pr,d=1}^*)$ and $(w_{Pu}^*)$, we get:

$$ w_{Pr,d=0}^* = f(w_{Pr,d=0}^*) $$

$$ w_{Pr,d=1}^* = f(w_{Pr,d=1}^*) + g(w_{Pr,d=1}^*) $$

with

$$ f(x) = b + (\lambda_{n,Pr} - \lambda_{Pr,Pr}) \int_{x}^{\bar{w}} \frac{\bar{F}_{Pr}(x)}{\rho + \delta + \lambda_{Pr,Pr} \bar{F}_{Pr}(x)} dx $$

$$ \text{and } g(x) = -c_{Pu} + \frac{\lambda_{n,Pu}p}{\rho} \int_{h(x)}^{\bar{w}} \bar{F}_{Pu}(x) dx $$

$$ \text{and } h(x) = x - c + \lambda_{Pr,Pr} \int_{x}^{\bar{w}} \frac{\bar{F}_{Pr}(x)}{\rho + \delta + \lambda_{Pr,Pr} \bar{F}_{Pr}(x)} dx $$

$h$ is an increasing and bounded function with first derivative:

$$ h'(x) = \frac{\rho + \delta}{\rho + \delta + \lambda_{Pr,Pr} \bar{F}_{Pr}(x)} $$

Hence $g$ is a decreasing and bounded function and three different cases are possible. Indeed, $\forall x \in [0, \bar{w}]$, $0 \geq f'(x) \geq f'(x) + g'(x)$.
• $f(0) + g(0) \le f(0)$: it means that a nonemployed person never searches for a public job for $w_{d=0}^* > w_{d=1}^*$.

• $f(0) + g(0) \ge f(0)$ and $f(\bar{w}) + g(\bar{w}) \ge f(\bar{w})$: it means that a nonemployed person always searches for both public and private jobs.

• $f(0) + g(0) \ge f(0)$ and $f(\bar{w}) + g(\bar{w}) < f(\bar{w})$: it means that a nonemployed person may search for a public job depending on $g(w_{d=0}^*)$. If $g(w_{d=0}^*) \ge 0$ the nonemployed person will search for a public job, whereas she won't.
We show that

$$w_{d=0}^{*} \le w_{d=1}^{*} \Leftrightarrow g(w_{d=0}^{*}) \ge 0$$

Indeed,

◇ On one hand,

$$
\begin{array}{ll}
\text{And} & w_{d=0}^{*} \le w_{d=1}^{*} \Rightarrow f(w_{d=0}^{*}) + g(w_{d=0}^{*}) \ge f(w_{d=1}^{*}) + g(w_{d=1}^{*}) \\
\text{Thus} & w_{d=0}^{*} \le w_{d=1}^{*} \Rightarrow f(w_{d=0}^{*}) \le f(w_{d=1}^{*}) + g(w_{d=1}^{*}) \\
& f(w_{d=0}^{*}) \le f(w_{d=0}^{*}) + g(w_{d=0}^{*}) \Rightarrow g(w_{d=0}^{*}) \ge 0
\end{array}
$$

◇ On the other hand

$$
\begin{array}{ll}
\text{Thus} & g(w_{d=0}^*) \ge 0 \Rightarrow f(w_{d=0}^*) \le f(w_{d=0}^*) + g(w_{d=0}^*) \\
& w_{d=0}^* \le f(w_{d=0}^*) + g(w_{d=0}^*) \\
\text{And} & f(x) + g(x) - x \text{ is a decreasing function such as} \\
& \left\{ \begin{array}{l} f(w_{d=1}^*) + g(w_{d=1}^*) - w_{d=1}^* = 0 \\ f(w_{d=0}^*) + g(w_{d=0}^*) - w_{d=0}^* \ge 0 \end{array} \right\} \\
& \Rightarrow w_{d=1}^* \ge w_{d=0}^*
\end{array}
$$

**Proposition B.1** *Search for a public job*

The nonemployed agent decides to search for both public and private jobs when:

$$c_{Pu} \le p_S \frac{\lambda_{n,Pu}}{\rho} \int_{h(w_{d=0}^*)}^{\bar{w}} \bar{F}_{Pu}(x)dx \quad \text{where } h(w_{d=0}^*) \text{ is a function of } (b, \lambda_{n,Pr}, \lambda_{Pr,Pr}, \bar{w}, \rho, \delta, \bar{F}_{Pr})$$

with:

- $c_{Pu}$ the cost to search for a public job

- $\lambda_{n,Pu}$ the public job offer arrival rate

- $p_S$ the individual probability to succeed public entrance exam

$$- h(w_{d=0}^{*}) = \frac{\lambda_{n,Pr}}{\lambda_{n,Pr}-\lambda_{Pr,Pr}} w_{d=0}^{*} - c - \frac{\lambda_{Pr,Pr}}{\lambda_{n,Pr}-\lambda_{Pr,Pr}} b$$

He only searches for private jobs when:

$$c_{Pu} > p_S \frac{\lambda_{n,Pu}}{\rho} \int_{h(w_{d=0}^*)}^{\bar{w}} \bar{F}_{Pu}(x)dx$$
C. Descriptive Statistics

see figure 8.

D. Implementation

D.1. M-step

In the M-step, we maximize the expected completed log likelihood:

$$
\sum_{i=1}^{N} \sum_{k=1}^{K} \pi_{ik}^{(n)} \ln l \left( \underline{y}_i, \underline{z}_i, \underline{w}_i | T_i = k, \beta, \sigma_{Pu}^2, \sigma_{Pr}^2, (\pi_k)_{k=1}^{K}, (\theta_k)_{k=1}^{K} \right) \quad (D.21)
$$

with $\beta = (\beta^Y, \beta^Z, \beta^{Pr}, \beta^{Pu})$.

$$
\begin{align*}
& l \left( \underline{y}_i, \underline{z}_i, \underline{w}_i \mid T_i = k, \beta, \sigma_{Pu}^2, \sigma_{Pr}^2, (\pi_k)_{k=1}^K, (\theta_k)_{k=1}^K \right) \\
&= \prod_{t=1}^T \left( \mathbb{P} \left( y_{it} = 0 \mid T_i = k, (\theta_k^Y)_k, \beta^Y \right) \right)^{y_{it}=0} \\
&\quad \left( \mathbb{P} \left( y_{it} = 1, z_{it} = 1, w_{it}^{Pr} \mid T_i = k, \beta, \sigma_{Pu}^2, \sigma_{Pr}^2, (\pi_k)_{k=1}^K, (\theta_k)_{k=1}^K \right) \right)^{y_{it}=1, z_{it}=1} \\
&\quad \left( \mathbb{P} \left( y_{it} = 1, z_{it} = 0, w_{it}^{Pu} \mid T_i = k, \beta, \sigma_{Pu}^2, \sigma_{Pr}^2, (\pi_k)_{k=1}^K, (\theta_k)_{k=1}^K \right) \right)^{y_{it}=1, z_{it}=0}
\end{align*}
$$

Since, given the individual type, for a given date, residuals are independent, we have:

$$
\begin{align*}
& l \left( \underline{y}_i, \underline{z}_i, \underline{w}_i | T_i = k \right) \\
&= \prod_{t=1}^{T} \left( \mathbb{P} \left( y_{it} = 0 | T_i = k, (\theta_k^Y)_k, \beta^Y \right) \right)^{y_{it}=0} \left( \mathbb{P} \left( y_{it} = 1 | T_i = k, (\theta_k^Y)_k, \beta^Y \right) \right)^{y_{it}=1} \\
&\quad \prod_{t=1}^{T} \left( \mathbb{P} \left( z_{it} = 1 | T_i = k, (\theta_k^Z)_k, \beta^Z, \gamma, (\theta_k^{Pr})_k, \beta^{Pr}, (\theta_k^{Pu})_k, \beta^{Pu}, \right) \right)^{y_{it}=1, z_{it}=1} \\
&\quad \prod_{t=1}^{T} \left( \mathbb{P} \left( z_{it} = 0 | T_i = k, (\theta_k^Z)_k, \beta^Z, \gamma, (\theta_k^{Pr})_k, \beta^{Pr}, (\theta_k^{Pu})_k, \beta^{Pu}, \right) \right)^{y_{it}=1, z_{it}=0} \\
&\quad \prod_{t=1}^{T} \left( \mathbb{P} \left( w_{it}^{Pu} | T_i = k, (\theta_k^{Pu})_k, \beta^{Pu}, \sigma_{Pu}^2 \right) \right)^{y_{it}=1, z_{it}=0} \\
&\quad \prod_{t=1}^{T} \left( \mathbb{P} \left( w_{it}^{Pr} | T_i = k, (\theta_k^{Pr})_k, \beta^{Pr}, \sigma_{Pr}^2 \right) \right)^{y_{it}=1, z_{it}=1}
\end{align*}
$$

We hence get four sequential optimization problems:

1. Optimization on the employment equation parameters

$$
\max_{\beta^Y, (\theta_k^Y)_K} \sum_{k=1}^{K} \sum_{i=1}^{N} \sum_{t=1}^{T} \left( \begin{aligned}[t]
& \pi_{ik}^{(n)} \mathbb{I}_{y_{it}=0} \ln \Phi(-X_{it}^Y \beta_Y - \theta_k^Y) \\
& + \pi_{ik}^{(n)} \mathbb{I}_{y_{it}=1} \ln \Phi(X_{it}^Y \beta_Y + \theta_k^Y)
\end{aligned} \right),
$$

where $\Phi$ denotes the cumulative distribution function of a standardized gaussian.
## 2. Optimization on the wage equations parameters

$$ \min_{\beta^{Pr}, \sigma_{Pr}, (\theta_k^{Pr})_{k=1}^K} \sum_{k=1}^K \sum_{i=1}^N \sum_{t=1}^T \pi_{ik}^{(n)} \mathbb{I}_{y_{it}=1, z_{it}=1} \ln(\sigma_{Pr}) + \frac{\pi_{ik}^{(n)}}{2\sigma_{Pr}^2} \mathbb{I}_{y_{it}=1, z_{it}=1} (w_{it}^{Pr} - X_{it}^{Pr} \beta_{Pr} - \theta_k^{Pr})^2, $$

and

$$ \min_{\beta^{Pu}, \sigma_{Pu}, (\theta_k^{Pu})_{k=1}^K} \sum_{k=1}^K \sum_{i=1}^N \sum_{t=1}^T \pi_{ik}^{(n)} \mathbb{I}_{y_{it}=1, z_{it}=0} \ln(\sigma_{Pu}) + \frac{\pi_{ik}^{(n)}}{2\sigma_{Pu}^2} \mathbb{I}_{y_{it}=1, z_{it}=1} (w_{it}^{Pu} - X_{it}^{Pu} \beta_{Pu} - \theta_k^{Pu})^2. $$

## 3. Optimization on the sector choice equation parameters

$$ \max_{\gamma, \beta^Z, (\theta_k^Z)_{k=1}^K} \sum_{k=1}^K \sum_{i=1}^N \sum_{t=1}^T \pi_{ik}^{(n)} \mathbb{I}_{y_{it}=1, z_{it}=0} \ln \Phi(-X_{it}^Z \beta_Z - \theta_k^Z - \gamma(X_{it}^{Pr} \beta_{Pr} + \theta_k^{Pr} - X_{it}^{Pr} \beta_{Pu} - \theta_k^{Pu})) + \pi_{ik}^{(n)} \mathbb{I}_{y_{it}=1, z_{it}=1} \ln \Phi(X_{it}^Z \beta_Z + \theta_k^Z + \gamma(X_{it}^{Pr} \beta_{Pr} + \theta_k^{Pr} - X_{it}^{Pr} \beta_{Pu} - \theta_k^{Pu})), $$

# D.2. Monte Carlo Simulation

In order to be sure no mistake were left in the Gauss Code, we run a monte carlo simulation. We simulate 100 samples made up of 700 individuals observed over 3 time periods according to:

$$ y_{it} = \mathbf{1}(X_{it}^Y \beta^Y + \theta_{k(i)}^Y + u_{it}^Y > 0) \quad (D.22) $$

And if $y_{it} = 1$,

$$ z_{it} = \mathbf{1}(X_{it}^Z \beta^Z + \gamma \mathbb{E}(w_{it}^{Pr} - w_{it}^{Pu} | k(i)) + \theta_{k(i)}^Z + u_{it}^Z > 0) \quad (D.23) $$

$$ w_{it}^{Pr} = z_{it} (X_{it}^{Pr} \beta^{Pr} + \theta_{k(i)}^{Pr} + u_{it}^{Pr}) \quad (D.24) $$

$$ w_{it}^{Pu} = (1 - z_{it}) (X_{it}^{Pu} \beta^{Pu} + \theta_{k(i)}^{Pu} + u_{it}^{Pu}) \quad (D.25) $$

where

$$ \theta = (\theta^Y, \theta^Z, \theta^{Pr}, \theta^{Pu}) \text{ denotes the vector of the unobserved heterogeneity components. We use 4 types of unobserved heterogeneity.} $$

$k(i)$ denotes the type of the individual $k$,

$$ X = (X^Y, X^Z, X^{Pr}, X^{Pu}) \text{ denotes the vector of the observable characteristics. Each equation has 3 observed explanatory variables, normally distributed.} $$

$$ \beta = (\beta^Y, \beta^Z, \beta^{Pr}, \beta^{Pu}) \text{ denotes the vector of parameters,} $$

$$ u = (u^Y, u^Z, u^{Pr}, u^{Pu}) \text{ denotes the vector of residuals, which are assumed to be independent and normally distributed across time and individuals, with variance } \sigma_{Pr}^2 \text{ (resp. } \sigma_{Pu}^2). $$

Table D.2 reports the original values and the estimates of the parameters. The results confirm the absence of fatal error in the code.
<table><thead><tr><th>Parameters</th><th>Estimates</th><th>Original Values</th></tr></thead><tbody><tr><td>β<sub>1</sub><sup>Y</sup></td><td>-2.716</td><td>-2.672</td></tr><tr><td>β<sub>2</sub><sup>Y</sup></td><td>0.069</td><td>0.065</td></tr><tr><td>β<sub>3</sub><sup>Y</sup></td><td>-2.967</td><td>-2.914</td></tr><tr><td>β<sub>1</sub><sup>Z</sup></td><td>2.166</td><td>2.152</td></tr><tr><td>β<sub>2</sub><sup>Z</sup></td><td>-3.315</td><td>-3.264</td></tr><tr><td>β<sub>3</sub><sup>Z</sup></td><td>1.130</td><td>1.121</td></tr><tr><td>β<sub>1</sub><sup>Pr</sup></td><td>-5.218</td><td>-5.218</td></tr><tr><td>β<sub>2</sub><sup>Pr</sup></td><td>3.758</td><td>3.755</td></tr><tr><td>β<sub>3</sub><sup>Pr</sup></td><td>1.146</td><td>1.141</td></tr><tr><td>σ<sup>2</sup>,Pr</td><td>0.672</td><td>0.607</td></tr><tr><td>β<sub>1</sub><sup>Pu</sup></td><td>8.930</td><td>8.931</td></tr><tr><td>β<sub>2</sub><sup>Pu</sup></td><td>-0.160</td><td>-0.157</td></tr><tr><td>β<sub>3</sub><sup>Pu</sup></td><td>5.656</td><td>5.658</td></tr><tr><td>σ<sup>2</sup>,Pu</td><td>1.137</td><td>1.105</td></tr><tr><td>π<sub>1</sub></td><td>0.398</td><td>0.400</td></tr><tr><td>π<sub>2</sub></td><td>0.095</td><td>0.100</td></tr><tr><td>π<sub>3</sub></td><td>0.207</td><td>0.200</td></tr><tr><td>π<sub>4</sub></td><td>0.300</td><td>0.300</td></tr><tr><td colspan="3"><strong>Y equation</strong></td></tr><tr><td>θ<sub>k=1</sub><sup>Y</sup></td><td>2.042</td><td>2.000</td></tr><tr><td>θ<sub>k=2</sub><sup>Y</sup></td><td>-5.029</td><td>-5.000</td></tr><tr><td>θ<sub>k=3</sub><sup>Y</sup></td><td>3.914</td><td>4.000</td></tr><tr><td>θ<sub>k=4</sub><sup>Y</sup></td><td>5.110</td><td>5.000</td></tr><tr><td colspan="3"><strong>Z equation</strong></td></tr><tr><td>θ<sub>k=1</sub><sup>Z</sup></td><td>-1.022</td><td>-1.000</td></tr><tr><td>θ<sub>k=2</sub><sup>Z</sup></td><td>-3.010</td><td>-3.000</td></tr><tr><td>θ<sub>k=3</sub><sup>Z</sup></td><td>1.656</td><td>2.000</td></tr><tr><td>θ<sub>k=4</sub><sup>Z</sup></td><td>-2.778</td><td>-3.000</td></tr><tr><td colspan="3"><strong>W<sup>Pr</sup> equation</strong></td></tr><tr><td>θ<sub>k=1</sub><sup>W<sup>Pr</sup></sup></td><td>-3.015</td><td>-3.000</td></tr><tr><td>θ<sub>k=2</sub><sup>W<sup>Pr</sup></sup></td><td>-0.872</td><td>-1.000</td></tr><tr><td>θ<sub>k=3</sub><sup>W<sup>Pr</sup></sup></td><td>3.729</td><td>4.000</td></tr><tr><td>θ<sub>k=4</sub><sup>W<sup>Pr</sup></sup></td><td>2.092</td><td>2.000</td></tr><tr><td colspan="3"><strong>W<sup>Pu</sup> equation</strong></td></tr><tr><td>θ<sub>k=1</sub><sup>W<sup>Pu</sup></sup></td><td>4.975</td><td>5.000</td></tr><tr><td>θ<sub>k=2</sub><sup>W<sup>Pu</sup></sup></td><td>-1.682</td><td>-2.000</td></tr><tr><td>θ<sub>k=3</sub><sup>W<sup>Pu</sup></sup></td><td>-1.797</td><td>-2.000</td></tr><tr><td>θ<sub>k=4</sub><sup>W<sup>Pu</sup></sup></td><td>2.757</td><td>3.000</td></tr></tbody></table>
E. Quantile differences between the public log of wage distributions and the counterfactual distribution

<table><caption>Table 9. Quantile differences between the public log of wage and the counterfactual distributions.</caption><thead><tr><th>Quantiles</th><th>1994</th><th>1995</th><th>1996</th><th>1997</th><th>1998</th><th>1999</th><th>2000</th><th>2001</th></tr><tr><td></td><td colspan="8" style="text-align: center;">Estimates</td></tr><tr><td></td><td colspan="8" style="text-align: center;">Standard Errors</td></tr></thead><tbody><tr><td>0.050</td><td>0.157<br>0.035</td><td>0.170<br>0.031</td><td>0.158<br>0.036</td><td>0.154<br>0.033</td><td>0.155<br>0.032</td><td>0.157<br>0.033</td><td>0.157<br>0.034</td><td>0.168<br>0.036</td></tr><tr><td>0.100</td><td>0.148<br>0.030</td><td>0.161<br>0.029</td><td>0.159<br>0.030</td><td>0.154<br>0.029</td><td>0.157<br>0.027</td><td>0.155<br>0.029</td><td>0.153<br>0.029</td><td>0.158<br>0.031</td></tr><tr><td>0.150</td><td>0.135<br>0.028</td><td>0.147<br>0.027</td><td>0.147<br>0.028</td><td>0.144<br>0.027</td><td>0.148<br>0.026</td><td>0.146<br>0.027</td><td>0.143<br>0.027</td><td>0.145<br>0.028</td></tr><tr><td>0.200</td><td>0.123<br>0.027</td><td>0.133<br>0.026</td><td>0.135<br>0.027</td><td>0.131<br>0.026</td><td>0.137<br>0.025</td><td>0.135<br>0.025</td><td>0.133<br>0.025</td><td>0.134<br>0.026</td></tr><tr><td>0.250</td><td>0.113<br>0.026</td><td>0.121<br>0.025</td><td>0.124<br>0.025</td><td>0.120<br>0.025</td><td>0.126<br>0.024</td><td>0.126<br>0.024</td><td>0.124<br>0.024</td><td>0.123<br>0.025</td></tr><tr><td>0.300</td><td>0.105<br>0.025</td><td>0.111<br>0.025</td><td>0.113<br>0.024</td><td>0.111<br>0.024</td><td>0.116<br>0.024</td><td>0.116<br>0.024</td><td>0.114<br>0.023</td><td>0.114<br>0.024</td></tr><tr><td>0.350</td><td>0.096<br>0.024</td><td>0.102<br>0.024</td><td>0.104<br>0.023</td><td>0.102<br>0.023</td><td>0.107<br>0.023</td><td>0.106<br>0.023</td><td>0.107<br>0.023</td><td>0.105<br>0.023</td></tr><tr><td>0.400</td><td>0.089<br>0.024</td><td>0.093<br>0.023</td><td>0.095<br>0.023</td><td>0.094<br>0.023</td><td>0.099<br>0.023</td><td>0.098<br>0.023</td><td>0.098<br>0.022</td><td>0.097<br>0.022</td></tr><tr><td>0.450</td><td>0.082<br>0.023</td><td>0.085<br>0.023</td><td>0.087<br>0.023</td><td>0.087<br>0.022</td><td>0.090<br>0.023</td><td>0.089<br>0.022</td><td>0.090<br>0.022</td><td>0.089<br>0.022</td></tr><tr><td>0.500</td><td>0.075<br>0.023</td><td>0.078<br>0.022</td><td>0.080<br>0.022</td><td>0.080<br>0.022</td><td>0.082<br>0.023</td><td>0.082<br>0.022</td><td>0.082<br>0.022</td><td>0.082<br>0.022</td></tr><tr><td>0.550</td><td>0.069<br>0.023</td><td>0.071<br>0.022</td><td>0.073<br>0.023</td><td>0.074<br>0.022</td><td>0.075<br>0.023</td><td>0.075<br>0.022</td><td>0.074<br>0.022</td><td>0.075<br>0.021</td></tr><tr><td>0.600</td><td>0.062<br>0.023</td><td>0.065<br>0.022</td><td>0.066<br>0.022</td><td>0.067<br>0.022</td><td>0.067<br>0.023</td><td>0.067<br>0.022</td><td>0.066<br>0.022</td><td>0.068<br>0.021</td></tr><tr><td>0.650</td><td>0.056<br>0.024</td><td>0.058<br>0.022</td><td>0.059<br>0.023</td><td>0.060<br>0.021</td><td>0.060<br>0.023</td><td>0.060<br>0.023</td><td>0.058<br>0.022</td><td>0.060<br>0.022</td></tr><tr><td>0.700</td><td>0.048<br>0.024</td><td>0.050<br>0.023</td><td>0.051<br>0.022</td><td>0.052<br>0.022</td><td>0.051<br>0.023</td><td>0.051<br>0.023</td><td>0.050<br>0.022</td><td>0.052<br>0.022</td></tr><tr><td>0.750</td><td>0.040<br>0.024</td><td>0.042<br>0.023</td><td>0.042<br>0.023</td><td>0.043<br>0.022</td><td>0.041<br>0.023</td><td>0.042<br>0.023</td><td>0.039<br>0.022</td><td>0.042<br>0.022</td></tr><tr><td>0.800</td><td>0.029<br>0.024</td><td>0.031<br>0.023</td><td>0.030<br>0.023</td><td>0.032<br>0.023</td><td>0.030<br>0.024</td><td>0.031<br>0.023</td><td>0.028<br>0.023</td><td>0.031<br>0.023</td></tr><tr><td>0.850</td><td>0.016<br>0.024</td><td>0.017<br>0.024</td><td>0.017<br>0.024</td><td>0.018<br>0.023</td><td>0.016<br>0.025</td><td>0.017<br>0.023</td><td>0.015<br>0.023</td><td>0.017<br>0.024</td></tr><tr><td>0.900</td><td>-0.003<br>0.024</td><td>-0.003<br>0.025</td><td>-0.004<br>0.025</td><td>-0.001<br>0.024</td><td>-0.002<br>0.026</td><td>0.000<br>0.023</td><td>-0.004<br>0.024</td><td>-0.003<br>0.024</td></tr><tr><td>0.950</td><td>-0.037<br>0.023</td><td>-0.040<br>0.025</td><td>-0.039<br>0.026</td><td>-0.035<br>0.025</td><td>-0.033<br>0.027</td><td>-0.030<br>0.025</td><td>-0.032<br>0.026</td><td>-0.032<br>0.025</td></tr></tbody></table>

Source: French European Household Survey.
F. Figures

<figure><img src="image_2.png" /><figcaption>Figure 2 Predicted log of monthly wages - 1994</figcaption></figure>

<figure><img src="image_3.png" /></figure>
<figure><img src="image_4.png" /><figcaption>Figure 3 Counterfactual log of monthly wages for civil servants - 1994</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>Figure 4 Counterfactual log of monthly wages according to degrees</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>Figure 6 Quantile differences between the public log of wage and the counterfactual distributions given sex and degrees.</figcaption></figure>

<figure><img src="image_7.png" /></figure>

<figure><img src="image_8.png" /></figure>

<figure><img src="image_9.png" /></figure>
<figure><img src="image_10.png" /><figcaption>Figure 7 Value function comparison</figcaption></figure>

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JAILLARD<br>Le traité de Maastricht : présentation juridique et historique</td></tr><tr><td>G 9111</td><td>A. MAGNIER<br>Effets accélérateur et multiplicateur en France depuis 1970 : quelques résultats empiriques</td><td>G 9407 J.L. BRILLET<br>Micro-DMS : présentation et propriétés</td></tr><tr><td>G 9112</td><td>B. CREPON et G. DUREAU<br>Investissement en recherche-développement : analyse de causalités dans un modèle d'accélérateur généralisé</td><td>G 9408 J.L. BRILLET<br>Micro-DMS - variantes : les tableaux</td></tr><tr><td>G 9113</td><td>J.L. BRILLET, H. ERKEL-ROUSSE, J. TOUJAS-BERNATE<br>"France-Allemagne Couplées" - Deux économies vues par une maquette macro-économétrique</td><td>G 9409 L. BLOCH - B. CŒURE<br>Les grands réseaux publics français dans une perspective européenne</td></tr><tr><td>G 9201</td><td>W.J. ADAMS, B. CREPON, D. ENCAOUA<br>Choix technologiques et stratégies de dissuasion d'entrée</td><td>G 9410 L. BLOCH - B. CŒURE<br>Profitabilité de l'investissement productif et transmission des chocs financiers</td></tr><tr><td>G 9202</td><td>J. OLIVEIRA-MARTINS, J. TOUJAS-BERNATE</td><td>G 9411 J. BOURDIEU - B. COLIN-SEDILLOT<br>Les théories sur la structure optimal du capital : quelques points de repère</td></tr><tr><td></td><td></td><td>G 9311 J. BOURDIEU - B. COLIN-SEDILLOT<br>Les décisions de financement des entreprises</td></tr></table>

<table><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>Equipes Amadeus (INSEE), Banque de France, Métric (DP)<br>Presentation 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. DEFEUILLE - 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 Bis</td><td>D. GOUX - E. MAURIN<br>Persistance de 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 Economie 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 - Erasme - INSEE - OFCE<br>Structures et propriétés de cinq modèles macro-économiques 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-BENSAÎD<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 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 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 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 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 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>Evolution 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 9611</td>
      <td>X. BONNET - S. MAHFOUZ<br>The influence of different specifications of<br>wages-prices spirals on the measure of the<br>NAIRU : the case of France</td>
      <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 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 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 ré-<br>gime général</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 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 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<br>firms from the manufacturing sector</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 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>Evolution de l'emploi et des coûts par quali-<br>fication entre 1982 et 1996</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 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 2000/1</td>
      <td>R. MAHIEU<br>Les déterminants des dépenses de santé : une<br>approche macroéconomique</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 9902</td>
      <td>Ch. COLIN<br>Modélisation des carrières dans Destinie</td>
      <td>G 2000/2</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 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 9904</td>
      <td>Ch. COLIN<br>Evolution de la dispersion des salaires : un essai<br>de prospective par microsimulation</td>
      <td>G 2000/3</td>
      <td>J.-Y. FOURNIER<br>L'approximation du filtre passe-bande proposée<br>par Christiano et Fitzgerald</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 9905</td>
      <td>B. CREPON - N. IUNG<br>Innovation, emploi et performances</td>
      <td>G 2000/4</td>
      <td>Bilan des activités de la DESE - 1999</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 9907</td>
      <td>B. CREPON - Ch. GIANELLA<br>Wages inequalities in France 1969-1992<br>An application of quantile regression techniques</td>
      <td>G 2000/5</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 9706</td>
      <td>M. HOUBEBINE - A. TOPIOL-BENSAÏD<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 9908</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 2000/6</td>
      <td>A. FLIPO<br>Les comportements matrimoniaux de fait</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 9909</td>
      <td>F. ROSENWALD<br>L'impact des contraintes financières dans la dé-<br>cision d'investissement</td>
      <td>G 2000/7</td>
      <td>R. MAHIEU - B. SÉDILLOT<br>Microsimulations of the retirement decision: a<br>supply side approach</td>
    </tr>
    <tr>
      <td>G 9708</td>
      <td>E. DUGUET - N. GREENAN<br>Le biais technologique : une analyse sur don-<br>nées 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 9910</td>
      <td>Bilan des activités de la DESE - 1998<br>J.P. ZOYEM<br>Contrat d'insertion et sortie du RMI<br>Evaluation des effets d'une politique sociale</td>
      <td>G 2000/8</td>
      <td>C. AUDENIS - C. PROST<br>Déficit conjoncturel : une prise en compte des<br>conjonctures passées</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 9911</td>
      <td>Ch. COLIN - FI. LEGROS - R. MAHIEU<br>Bilans contributifs comparés des régimes de<br>retraite du secteur privé et de la fonction<br>publique</td>
      <td>G 2000/9</td>
      <td>R. MAHIEU - B. SÉDILLOT<br>Equivalent patrimonial de la rente et souscription<br>de retraite complémentaire</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<br>et 1996</td>
      <td>G 9912</td>
      <td>G. LAROQUE - B. SALANIÉ<br>Une décomposition du non-emploi en France</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 9711</td>
      <td>G. FORGEOT - J. GAUTIÉ<br>Insertion professionnelle des jeunes et proces-<br>sus de déclassement</td>
      <td>G 9807</td>
      <td>J. ACCARDO - M. JLASSI<br>La productivité globale des facteurs entre 1975<br>et 1996</td>
      <td>G 9912</td>
      <td>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 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<br>et 1996</td>
      <td>G 9912</td>
      <td>Ch. GIANELLA<br>Une estimation de l'élasticité de l'emploi peu<br>qualifié à son coût</td>
      <td>G 2000/12</td>
      <td>Ch. GIANELLA<br>Local unemployment and wages</td>
    </tr>
    <tr>
      <td>G 9713</td>
      <td>Bilan des activités de la Direction des Etudes<br>et Synthèses Economiques - 1996</td>
      <td>G 9809</td>
      <td>Bilan des activités de la Direction des Etudes et<br>Synthèses Economiques - 1997</td>
      <td>Bis</td>
      <td></td>
      <td>G 2000/13</td>
      <td>B. CREPON - Th. HECKEL<br>- Informatisation en France : une évaluation à<br>partir de données individuelles</td>
    </tr>
  </tbody>
</table>
- Computerization in France: an evaluation based on individual company data

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

- The new economy and the measurement of GDP growth

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

G2001/03 I. BRAUN-LEMAIRE
Evolution 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
Evaluation des effets des dispositifs d'allégements de charges sociales sur les bas salaires

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

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

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

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

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

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

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

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

G2002/02 Bilan des activités de la DESE - 2001

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

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

- Rétroposition 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
Âge, salaire et productivité
La productivité des salariés décline-t-elle en fin de carrière ?

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

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

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

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

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

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

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

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

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

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

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

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

G2004/08 E. DUGUET - C. LELARGE
Les brevets accroissent-ils les incitations privées à innover ? Un examen 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 a1974

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

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

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

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

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

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

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

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

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

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

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

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

G2005/15 M. DUÉE
La modélisation des comportements démographiques dans le modèle de microsimulation 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 réinterprétation de la relation entre productivité et inégalités salariales dans les entreprises

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

G2006/15 L. GONZALEZ - C. PICART
Diversification, 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
Une approche empirique sur données individuelles

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

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

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

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

G2009/04 P. GIVORD - L. WILNER
Les contrats temporaires : trappe ou 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'économètre confronté à des données d'enquête

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

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

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

G2009/10 D. BLANCHET - J. LE CACHEUX - V. MARCUS
Adjusted net savings and other approaches to sustainability: some theroretical 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
Is civil-servant human capital sector-specific?
Public-private wage gap