# Short-term health effects of public transport disruptions: air pollution and viral spread channels

Alexandre Godzinski, Milena Suarez Castillo

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Alexandre Godzinski, Milena Suarez Castillo. Short-term health effects of public transport disruptions: air pollution and viral spread channels. 2019. hal-05399020

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Documents de travail

G2019/03

Mai 2019

# Short-term health effects of public transport disruptions: air pollution and viral spread channels

Alexandre GODZINSKI - Milena SUAREZ CASTILLO
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<figure><img src="image_4.png" /></figure>

Institut national de la statistique et des études économiques

G2019/03

# Short-term health effects of public transport disruptions: air pollution and viral spread channels

Alexandre GODZINSKI*

Milena SUAREZ CASTILLO**

Mai 2019

We are grateful to Geoffrey Barrows, Hubert Holin, Dominique Goux, Lionel Wilner and Sébastien Roux for their suggestions and useful comments. We thank Alireza Banaei, Fatma Kaci, Anne Bataillard, Max Bensadon and Francoise Bourgoin from ATIH for providing us the hospital admission database, Anne Laborie, Gilles Levigoureux and Frédéric Penven from ATMO France and the AASQA for providing us the air pollution datasets, Nick Cohn, Edwin Kools, Elsbeth Schouten and Corinne Vigreux from TomTom for providing us the congestion data, and Nicolas Patin, Almeria Senecat from the French Ministry of Transport and their colleagues from regional structures for providing us the traffic datasets, as well as Nice métropôle. We thank Gisèle Grosz for research assistance.

Département des Études Économiques - Timbre G201

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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>* Faisait partie du Département des études économiques au moment de la rédaction de ce document.</footnote>

<footnote>** Insee-Dese - Département des études économiques - Division « Marchés et entreprises »</footnote>
# Les effets de court terme sur la santé des perturbations dans les transports publics : pollution de l'air et transmission virale

## Résumé

Lorsque les transports publics ne sont pas disponibles, la santé des populations urbaines peut en être affectée. D'abord, la pollution de l'air augmente du fait d'un report vers les véhicules personnels : les pathologies respiratoires peuvent être exacerbées à court terme. Ensuite, des contacts interpersonnels moins nombreux peuvent donner lieu à une moindre propagation virale. Nous mettons en évidence ces deux canaux, par différence de différences, en considérant les grèves dans les transports publics des dix plus grandes aires urbaines françaises sur la période 2010-2015. Les deux jours suivant une grève, les admissions en urgence à l'hôpital pour les grippes, les gastro-entérites et pathologies associées sont moins nombreuses. Malgré l'existence de cet effet de moindre contagion, qui touche aussi des pathologies respiratoires comme la grippe, l'effet néfaste de la pollution de l'air reste substantiel. Un jour de grève, les admissions pour les pathologies aiguës des voies respiratoires supérieures sont plus fréquentes, et le jour suivant, il en est de même pour les anomalies de la respiration. Nos résultats suggèrent que les choix de mode de transport des populations urbaines sont importants puisqu'ils sont responsables d'effets mesurables sur leur santé le jour même et les quelques jours suivants.

**Mots-clés** : Effet dynamique sur la santé, Grève dans les transports, Pollution de l'air, Contagion, différence de différences

# Short-term health effects of public transport disruptions: air pollution and viral spread channels

## Abstract

When public transport supply decreases, urban population health may be strongly affected. First, as ambient air pollution increases, respiratory diseases may be exacerbated during a few days. Second, reduced interpersonal contacts may lead to a slower viral spread, and therefore, after a few incubation days, lower morbidity. We evidence these two channels, using a difference-in-differences strategy, considering public transport strikes in the ten most populated French cities over the 2010-2015 period. On the two days following the strike, we find less emergency hospital admissions for influenza and gastroenteritis. In spite of the existence of this contagion channel, which tends to mitigate the increase of admissions for respiratory diseases, we also evidence a substantial air pollution channel. On the strike day, we find more admissions for acute diseases of the upper respiratory system, while on the following day of the strike, more abnormalities of breathing. Our results suggest that urban population daily transportation choices do matter as they engender dynamic spillovers on health.

**Keywords** : Dynamic health effects, transport strike, air pollution, contagion, difference-in-differences

**Classification JEL** : I12, I18, C23, L91, Q53, R41
# 1 Introduction

For urban populations, public transportation is an essential part of daily life, but the health consequences of a well-functioning public transportation network are not yet fully acknowledged. As it offers an alternative to personal cars, the European commission, among others, "strongly encourages the use of public transport as part of the mix of modes which each person living or working in a city can use".<fnref n="1" /> Indeed, when personal vehicle traffic increases, not only commuters are affected, but also the whole population of the area as air pollution increases (Bauernschuster, Hener and Rainer (2017)). Systematic correlations between mortality and outdoor air pollution are accumulating, but exogenous variations of air pollution are difficult to isolate through crucial in terms of causal evaluation. Therefore, public transport strikes have been considered to gauge the effect of traffic on air pollution (Basagaña et al. (2018), da Silva et al. (2012)). By relying on this variation of air pollution, we could indirectly observe and confirm the causal impact of air pollution on health in relatively moderate pollution levels typical of advanced economy urban pollution. But the health consequences of air pollution following the quasi-experiment triggered by a public transport strike is not that simple to analyze for two reasons. First, an additional channel, contagion, may intervene, due to lower interpersonal contact during a strike event. Second, the dynamic dimension matters as the air pollution shock may not be restricted to the very day of the strike. This quasi-experiment sheds light on the dynamic health consequences of the daily choices of urban transportation, when part of the population divert from public transport toward personal cars.

In this paper, we study emergencies admission rates in the ten most populated urban area in France to evidence two mechanisms. First, following a strike event, air pollution increases which leads to detrimental health effects, especially for frail populations (i.e. young children). Though this effect is documented by a huge epidemiological literature, quasi-experimental evidence is still scarce<fnref n="2" />. Times series analysis are abundant in the medical literature but do not rely on exogenous variation of ambient air pollution. This is a problem for instance if there are avoidance behaviours: when a pollution peak occurs and warnings are broadcasted to the population, fragile persons may spend less time outdoor to protect their health. Secondly, important confounding factors are weather conditions. If most studies take this into account by controlling by weather variables in regressions, they

<footnote n="1">¹European commission policy statement that can be found at https://ec.europa.eu/transport/themes/urban/urbanMobility/urbanMobilityActions/public_transport_en</footnote>

<footnote n="2">²If some papers address this question there are mostly restricted to the study of mortality (e.g. Currie and Neidell (2005), Arceo, Hanna and Oliva (2016) among others). Recent exceptions addressing morbidity are, on a yearly study Filippini, Masiero and Steinbach (2017) or Schlenker and Walker (2015) at daily frequency around airports.</footnote>
must specify a functional form that will be crucial in the estimation. To cope with
these issues, one can ideally rely on exogenous variation triggered by an unrelated
event.<fnref n="3" /> Following Bauernschuster, Hener and Rainer (2017), we argue that a public
transport strike event triggers exogenous variation in ambient air pollution. Nev-
ertheless, we do not assume that ambient air pollution is the only channel through
which respiratory health is affected, nor that the consequences of a strike day are
restricted to the day of the event. As interpersonal contacts may decrease in public
transports themselves, but also by cancellation of trips to work or to school, viral
spread is expected to decelerate. For some pathologies, in particular acute upper
respiratory system diseases<fnref n="4" /> the two channels under study have opposite effects on
health: in this quasi-experimental setting, the delayed negative impact of air pol-
lution is mitigated by less contagion. Our objective is therefore twofold. Firstly,
by evidencing an increase in respiratory emergency admissions on the very day of
the strike, we show the short-term importance of a well-functioning and widely
used day-to-day public transportation network in terms of health. Secondly, we
evidence that the limitations of social interactions likely occurring in these days
may lead to positive health effects, in the spirit of Adda (2016). Acknowledging
this second channel is important in properly interpreting ambient air pollution
delayed effects: when we find evidence of detrimental effects on health, it is most
probably a lower bound. We here contribute to the small but growing literature
linking causally air pollution and morbidity (e.g. Schlenker and Walker (2015),
Filippini, Masiero and Steinbach (2017), Jans, Johansson and Nilsson (forthcom-
ing))<fnref n="5" />, in particular showing that taking into account the dynamics of the effects
over a few days is important: pollution accumulates, has its own dynamics chem-
istry and the body may not react immediately to a pollution shock. One of the
strength of our dataset is to provide a rare perspective on pollution as we monitor
the reaction of six pollutants. It is of importance in the dynamic dimension as
some pollutants are secondary, i.e. not emitted directly but formed from primary
pollutants.

We study separately the impact of a strike on several outcomes of interest, using a difference-in-difference strategy. To this end, we make use of four rich datasets that provide information on hospital emergency admissions, air pollution, traffic and congestion in the ten most populated urban areas in France, over the period 2010-2015. Using 91 one-day strike events staggered over time and cities, we exploit both time and cross-sectional dimensions in order to quantify

<footnote n="3">³ For example Moretti and Neidell (2011) use daily variation in boat traffic and Schlenker and Walker (2015) use excess airplane idling to estimate the impact of respectively ozone and carbon monoxide on local residents respiratory diseases.</footnote>

<footnote n="4">⁴For example influenza, pneumonia: pathologies that are mostly due to a viral infection but also favored by air pollution (See Ciencewicki and Jaspers (2007))</footnote>

<footnote n="5">⁵This literature follows a larger literature linking mortality and air pollution: among others, Currie and Neidell (2005), Arceo, Hanna and Oliva (2016) ..</footnote>
the impact of a strike over traffic, congestion, air pollution and health. We use
a difference-in-difference strategy at the city-date level and first check that cities
affected by a strike show an increase in congestion and in traffic relative to other
cities. Travel times increase by 7% on average in the day. Around 9 a.m., ve-
hicle flows display a significant and large increase: in the morning peak hours,
monitoring stations record an increase by about 20 % of counted vehicles. Air
pollution increases gradually: on the day of the strike, we find an increase in
carbon monoxide concentration, a pollutant whose traffic-related emissions have
been dramatically reduced in recent cars thanks to European norms. Particulate
matters increase by 10% the day following the strike, probably due to a gradual ac-
cumulation. Finally, ozone is of interest as it is a secondary pollutant formed from
traffic-related primary pollutants. As expected from its dynamics, ozone increases
later by 5%, on the second day following the strike. This indirectly confirms that
the primary pollutants increase before secondary ones. Because pollution dynam-
ics is complex, the consequences of an increase in traffic can last severals days.
Secondary pollutants arrive in a second phase and when air does not circulate, an
accumulation of pollutants occurs.

Our results show that the upper respiratory system is affected first, with emer-
gency admissions increasing by 30% on the strike day. This upsurge is borne by
young children (0-4 year-old). The following day, children from 5 to 14 year-old
also show up more than a regular day in emergency rooms for this pathology.
Lagged adverse effect is also observed for abnormality of breathing. However, sur-
prisingly, emergencies for respiratory diseases taken as a whole, i.e. adding most
notably pathologies with chronic origins and influenza seem to be unaffected. We
argue that the delayed effect of ambient air pollution is compensated by a lower
incidence of viral pathology such as influenza and pneumonia that is found across
several age groups but most firmly for 5-14-year-old, on the two days following
the event. This timing is in line with the expected incubation time if contagion
is weakened on the strike day. To assert this interpretation, we show a similar
result for gastroenteritis, which is subject to contagion with a lower incubation
period, but not to air pollution. Despite being in a context where we may un-
derestimate the delayed effect of air pollution, we find a sizeable effect on health,
borne primarily by children.

Finally, we conduct a set of robustness checks. First, we conduct a falsification
test on top emergency causes that we believe are unrelated to the quasi-experiment
of a one day strike: pregnancy and digestive diseases. As could be expected, the
strike do not affect other diseases, unrelated to ambient air pollution and not
caused by a virus. Second, controlling by date fixed effects allows to account for
national level shocks which may be correlated with the event of a strike.<fnref n="6" /> However, it may be possible that in a given city, strikers choose a date where large traffic is expected for some reason unknown to the econometrician.<fnref n="7" /> In this case, the exogeneity of the variation triggered by the strike is undermined. To check that it is most likely not the case, we use the hotel occupancy rate as a proxy for the happening of city-specific events and verify that it is not different from other days.

The remainder of the paper is organized as follow. Section 2 presents the institutional context surrounding strike events and review the main mechanisms under investigation in the literature. Section 3 describe the data sets, section 4 the econometric strategy and section 5 our results. Section 6 provides robustness checks and Section 7 concludes.

## 2 Institutional context and mechanisms

Public transports in France are well developed: aside the well equipped Paris area, other regions count 11 metro lines, 54 tramways and 3691 bus lines in 2012 that respectively account for 133, 589 and 50 695 kilometers (Commis-sariat général au développement durable (2015)). They are an important mode of transportations of urban populations. For instance in the Nantes métropôle, 15% of trips from Monday to Friday are done thanks to the collective transport system. We analyze the ten most populated urban area as listed in Table 1, that all rely on a well developed public transport network. Their geographical position and extent is represented in Figure 1

In this paper, we use behavioral variations caused by public transport pertur-bations in the event of a strike. The International Labour Organisation (ILO) recognizes strike action as a fundamental right of organized labor. In France, it is a constitutional right that has been written in the constitution since 1946. Re-garding French terrestrial transports, a 2007 law provided two guidelines on strike right. First, strikers have to declare at least 48 hours in advance whether they are willing to strike. Second, negotiations between the transport firm and trade unions have to start before the strike. This law does not prohibit strike action, but the first guideline limits its potential impact. It makes easier for the transport firm to redeploy the non-strikers to lessen the effect of strike actions.

<footnote n="6">⁶For example, if strikers choose preferably a day when large departure traffic is expected because of a national bank holiday.</footnote>

<footnote n="7">⁷For example, if strikers choose preferably a day when large traffic is expected because of a city-specific event.</footnote>
<table><caption>Table 1: The ten most populated urban area in France</caption><thead><tr><th rowspan="2">Urban area</th><th colspan="3">Population (in thousands)</th></tr><tr><th>All age</th><th>0-4</th><th>over 70</th></tr></thead><tbody><tr><td>Paris</td><td>12,470</td><td>845</td><td>1,203</td></tr><tr><td>Lyon</td><td>2,259</td><td>152</td><td>249</td></tr><tr><td>Marseille - Aix-en-Provence</td><td>1,744</td><td>103</td><td>231</td></tr><tr><td>Toulouse</td><td>1,312</td><td>81</td><td>137</td></tr><tr><td>Bordeaux</td><td>1,195</td><td>67</td><td>135</td></tr><tr><td>Lille</td><td>1,182</td><td>80</td><td>111</td></tr><tr><td>Nice</td><td>1,006</td><td>52</td><td>171</td></tr><tr><td>Nantes</td><td>934</td><td>61</td><td>97</td></tr><tr><td>Strasbourg</td><td>777</td><td>45</td><td>89</td></tr><tr><td>Rennes</td><td>708</td><td>46</td><td>70</td></tr></tbody></table>

For Lille and Strasbourg urban areas, only the French part is considered.

Source: 2013 census

<figure><img src="image_5.png" /><figcaption>Figure 1: Geographic location of the ten most populated urban areas in France.</figcaption></figure>

Source: Insee, urban areas database, 2010.
## 2.1 Air pollution and health

A large epidemiology literature has consistently linked air pollution to respiratory and cardiovascular diseases, both at long and short term (Seaton et al. (1995)). The wake-up call could be dated to 1952 when a massive smog episode in London provoked an historical number of deaths.<fnref n="8" /> Nevertheless, health effects are not only observed under extraordinary events but as well at pollution levels commonly occurring in developed countries.

Ambient air pollution penetrates into the respiratory system by inhalation. The biological mechanisms are still under active survey, but the highly suspected mechanisms are as follows: air pollution can provoke inflammatory responses at different level of the respiratory system (Ozone, NOx and particulate matters are potent oxidants, Brunekreef and Holgate (2002)). Cells oxidative stress appears as a mediator of the pulmonary inflammatory response. Particulate matter can penetrate into the lower respiratory system. PM2.5 (Particulate matter of less than 2.5 µm) can even penetrate into the gas-exchange region of the lung, irri- tate and corrode the alveolar wall.<fnref n="9" /> Importantly, symptoms may appear several days following an increased exposure level and may persist for several days. In general, studies emphasize distinct effects by age groups. The lung functions of the young child are not completely developed and may be particularly subject to external aggression (Gauderman et al. (2007)). Elderly are subject to reduced lung functions that occur naturally with aging and to increased co-morbidity. We here focus on the short-term effect of ambient air pollution. Long term effects are also of great interest, and represent a huge medical literature, often referred to as "cohort studies". Anderson (2015) and Deryugina et al. (2016) are recent papers addressing this question in the econometric literature.

An important caveat, not addressed here, is that the estimates have to be interpreted cautiously. We can not distinguish what is caused (without pollution, the subject would not have been ill) and what has been exacerbated (without pollution but with another adverse shock, the subject would have been ill as he was in the brink of falling ill). We will only be able to check whether in case of a resurgence of emergency admissions a given day, we observe the converse a few days later (the extreme case where it will only displace admissions that were meant to happen). This hypothesis is referred to the "harvesting hypothesis" when studying mortality.

<footnote n="8">⁸Bell and Davis (2001) estimate that 12,000 excess deaths occurred due to both the acute and persisting effect of the 1952 London smog.</footnote>

<footnote n="9">⁹The alveolar membrane is the gas exchange surface. Carbon dioxide rich blood is pumped from the rest of the body and through the alveolar system released while oxygen is absorbed and afterward directed to the heart.</footnote>
## 2.2 Collectivity exposure and viral diseases spread

Using public transport strikes as a quasi-experiment to infer the health responses to increased ambient air pollution might be dampen by a second channel. On a strike-day, we may expect reduced interpersonal contacts for several reasons: reduced frequentation of public transportation, reduced attendance at school, impossibility to go to one's workplace, choice to take a day off and stay at home... In turn, reduced contact may lead to slower viral spread. This effect has long been recognized in the literature (e.g. Thélot and Bourrillon (1996)) and regained interest recently (e.g. Adda (2016)). Moreover, as ambient air pollution has been pointed as making a favorable ground for contagious diseases such as pneumonia, flu or pharyngitis, we may underestimate the delayed impact of air pollution on health if we do not acknowledge the existence of this channel.

The role of children as primary vector of transmission of influenza has been emphasized: because they have the highest risk factors (Viboud et al. (2004)) there is a high benefit of their vaccination (Weycker et al. (2005)). Therefore, schools closure have been pointed-out as non-pharmaceutical intervention to contain pandemic episode and used for instance by several countries in the 2009 flu pandemic (Cauchemez et al. (2014)). The effect of school holidays on flu transmission has been studied by epidemiologists (Cauchemez et al. (2008)) as well as economists (Adda (2016)) who reach similar conclusions: the effect is the most pregnant for children and there are limited side effects on adults (e.g. parents, grandparents). The short incubation period of influenza<fnref n="10" /> is an important parameter in our context, as it gauges the time between reduced contagion (on a strike day) and reduced morbidity (on strike day plus the incubation time).

Evidence for public transport strike is more scarce. Thélot and Bourrillon (1996) comment the coincidence of an unusually low bronchiolitis episode in Paris region and a multiple weeks public transport strike. The authors interpret this coincidence by lower attendance of young children to daycare. Adda (2016) studies both school closures and railway transport strikes at a weekly frequency in French regions. In the transport strike case, he founds no effect in acute diarrhea<fnref n="11" /> the week of the strike but significant negative effects in flu-like illnesses (measured by visits to general practitioner thanks to the *Réseau Sentinelles* in France). In particular, the strongest reduction is found for children, even though there is some evidence of spillovers on adults.

<footnote n="10">¹⁰According to WHO, 2 days on average and in a range of 1 to 4 days.</footnote>

<footnote n="11">¹¹Whose incubation period is estimated to be short as well: 0-2 days, Adda (2016)</footnote>
<figure><img src="image_6.png" /><figcaption>Figure 2: Causal chain and summary of data sources.</figcaption></figure>
# 3 Data

In this section, we describe the data sources which cover the ten most populated urban areas in France (Table 1) over the 2010-2015 period. Figure 2 represents the causal chain studied in this paper and enumerate the main data sources to monitor the different outcomes. The following section provide more details.

## 3.1 Strikes

We gathered strike events in public transportation services, collecting ourselves the data following a cautious process: every recorded event has to be reported by two distinct media. For each event, we record where and when it occurs, its length and an estimation of the magnitude of the perturbation, in the sense whether newspaper information refers to a perturbation of at least part of the network or whether there was only a negligible perturbation (although a strike was announced). Because we face an heterogeneous phenomenon, with long strike events (the longest strike in our sample lasts 75 days), we restrict the strike events under consideration to one-day strikes. We also withdraw the minor perturbations as we do not expect the shock to be sufficient and to reflect the absence of public transport for part of the users.<fnref n="12" /> To simplify interpretations when considering delayed estimates, when strike episodes are adjacent in a two day window, we exclude the strikes episodes with the two-day window at the city-date level (as we compute delayed effects up to two days).

In the estimation sample, we exclude school holidays when traffic and therefore pollution are not easily captured by our extensive set of fixed effects. Holidays adjacent days are as well excluded as they are characterized by departure and return trips. Our sample is therefore restricted to days within a regular week.

Finally, we are left with 91 one-day strike episodes that occur within an "usual" week and that we use in our estimations. Our baseline sample has 13,500 city-date observations, as long as there is no missing values in the outcome considered (which is the case for congestion and emergency admissions). Our sample is somewhat reduced when considering air pollutants as not all cities record all pollutants at all time, due to physical sensor malfunctions.<fnref n="13" />

<footnote n="12">¹²i.e. we exclude the city-date observations when there is a longer strike or a minor strike event in all our regressions. Adjacent days of strike episodes that we do not consider here are also excluded in the city-date sample.</footnote>

<footnote n="13">¹³Considering a sample where all pollutants are measured at the city-date level entails losing half of the observations and strike events. We nevertheless check that the event of the strike is unrelated to pollutants’ missingness.</footnote>
Table 2 shows the different filters from collected sample to the strike episodes used in our regressions. Figure 3 represents how strikes in the estimation sample are staggered across time and space. The autumn of 2010 was marked by a social movement against pension reforms which raised the non-penalized retirement age for pensions from 65 to 67 and the minimum legal age from age 60 to 62. In the robustness section, we check that excluding 2010 or September do not affect our results.

<table><caption>Table 2: Differences between collected and in-sample strikes: impact of filters (categories from rows (1) to (4) are non-exclusive)</caption><tbody><tr><td rowspan="2">Strike episodes</td><td>Collected</td><td>209</td></tr><tr><td>In estimation sample</td><td>91</td></tr><tr><td rowspan="4">Not considered because</td><td>(1) Occuring in holidays</td><td>34</td></tr><tr><td>(2) Over 1 day duration</td><td>34</td></tr><tr><td>(3) Minor perturbation</td><td>73</td></tr><tr><td>(4) Another strike within a 2 days windows</td><td>38</td></tr></tbody></table>

## 3.2 Congestion

In the causal chain, we first expect a diversion from public transport to personal cars and therefore, more vehicles on the roads and more congested conditions. Congestion is measured by the Tomtom traffic index<fnref n="14" /> which aggregates Tomtom users' individual delays compared to a free flow situation. Tomtom is a worldwide company specialized in navigation device, and provides in particular embedded GPS and navigation assistance in vehicles. We obtained the historic of the daily Tomtom index over 2010-2015 for the ten most populated French urban areas.

The methodology of the index is described in Cohn, Kools and Mieth (2014): starting 2007, GPS speed measurements were collected and mapped to road segments. For each individual road segment $r$, non-congested (free-flow) travel times $T_{0,r}$ are determined based on the shortest travel times of two years of measurements. The overall congestion level value for a city is the weighted average extra travel time experienced by drivers in that city when compared to the free flow travel times i.e. for $r$ a road segment, $100 \times (< \frac{T_r}{T_{0,r}} > -1)$, where travel time is denoted $T$ and $T_0$ under a free-flow situation. The average is weighted by the volume of users on each road segment. Thus, the value of the congestion index may be read as a percentage increase in travel time, with a weighting scheme which allows to over-represent larger volume roads compared to quiet roads.

<footnote n="14">¹⁴https://www.tomtom.com/trafficindex/</footnote>
<figure><img src="image_7.png" /><figcaption>Figure 3: Strike repartition over time and space, among in sample strikes (See Table 2). Source: Authors' collecting, from media reports</figcaption></figure>

Table 3 shows the daily congestion level by city: on average over the period, trips in Paris are 33% longer than under free-flow conditions. The least congested city is Rennes. We might be concerned that active Tomtom customers are not numerous enough for the least populated cities, and that it weakens the aggregate Tomtom traffic index.<fnref n="15" /> However, the right panel of the Table 3 show a quality proxy for the index: the number of vehicles kilometers used to compute the index, or in other words, the number of users times the traveled kilometers. The first decile in Nice, the least congested urban area on average, is 23 000 kilometers per day which seems rather reasonable (it would correspond for example to about 750 persons traveling 30 kilometers to produce a daily measure).

## 3.3 Traffic

An additional source is considered to study traffic conditions on strike days, on top of extra travel time: count of vehicles on main roads. Traffic data were gathered from the regional *Directions Interdépartementale des Routes*<fnref n="16" /> (DIR), decentralized governmental administrations in charge of managing, maintaining and operating roads. As part of their transportation policy, they collect hourly

<footnote n="15">¹⁵Ideally, we would check whether Tomtom customer's travels are representative of urban area's travels, but we have no data to check whether it is the case.</footnote>

<footnote n="16">¹⁶DIR Centre-Est, DIR Ouest, DIR Méditerranée, DIR Est, DIR Atlantique, DIR Nord, DIR Sud-Ouest and DIR Ile-de-France</footnote>
<table><caption>Table 3: Tomtom traffic index over 2010-2015 in the ten most populated urban area in France</caption><thead><tr><th rowspan="2">City</th><th rowspan="2">Mean</th><th colspan="3">Daily congestion level</th><th colspan="3">Daily total vehicle kilometres (/1000)</th></tr><tr><th>D1</th><th>D9</th><th>sd</th><th>Mean</th><th>D1</th><th>D9</th><th>sd</th></tr></thead><tbody><tr><td>Marseille</td><td>36.2</td><td>19.7</td><td>50.1</td><td>11.7</td><td>49</td><td>31</td><td>71</td><td>15</td></tr><tr><td>Paris</td><td>32.9</td><td>16.4</td><td>48.0</td><td>12.0</td><td>2806</td><td>1907</td><td>3899</td><td>738</td></tr><tr><td>Lyon</td><td>24.7</td><td>11.3</td><td>36.0</td><td>9.7</td><td>303</td><td>198</td><td>430</td><td>87</td></tr><tr><td>Nice</td><td>24.7</td><td>13.2</td><td>33.6</td><td>7.9</td><td>37</td><td>23</td><td>52</td><td>12</td></tr><tr><td>Bordeaux</td><td>24.3</td><td>8.4</td><td>37.5</td><td>11.2</td><td>180</td><td>112</td><td>258</td><td>55</td></tr><tr><td>Toulouse</td><td>21.7</td><td>8.5</td><td>35.0</td><td>10.4</td><td>149</td><td>93</td><td>214</td><td>45</td></tr><tr><td>Strasbourg</td><td>21.6</td><td>7.3</td><td>33.6</td><td>10.2</td><td>59</td><td>40</td><td>80</td><td>15</td></tr><tr><td>Nantes</td><td>19.4</td><td>6.8</td><td>30.3</td><td>9.1</td><td>123</td><td>80</td><td>173</td><td>35</td></tr><tr><td>Lille</td><td>18.0</td><td>5.2</td><td>30.5</td><td>10.0</td><td>214</td><td>146</td><td>293</td><td>55</td></tr><tr><td>Rennes</td><td>16.3</td><td>4.9</td><td>26.9</td><td>8.9</td><td>63</td><td>42</td><td>88</td><td>19</td></tr></tbody></table>

Daily congestion level measures the percentage of increased travel time compared to a free flow situation. Vehicle kilometres is the sum of the users' trips in kilometres a given day in the urban area. Source: TomTom

traffic flow (number of vehicles per hour) on their network (state-owned roads) and disclose annual statistics to the public. In general, this network covers correctly the immediate surrounding of the cities and includes ring roads. Except for Nice however, the city center is not covered. Each city data set is provided by a distinct DIR (except for Rennes and Nantes that both depend on the same DIR *Ouest*). One exception is Nice, where the data has been provided by the *Métropôle* (an intercommunal structure, centered on the city of Nice).

Some stations were not constantly operating and we often observed breaks in the times series (possible explanation might be temporary road works on one lane or the dysfunction of a captor). We therefore excluded stations where a break was observed or when a major time period was missing (e.g. more than a year). Maps showing the remaining stations are shown in appendix. In general, monitoring station are well distributed around cities. Then, we applied the following filter: we compute the average daily traffic flow per monitoring station and exclude the observations for that station on days where the daily traffic was under 10% of this value. Table 6 shows summary statistics, and Figure 8 in appendix shows the average hourly traffic pattern.
<table><caption>Table 4: Traffic flow in number of vehicles.</caption><thead><tr><th rowspan="2">City</th><th rowspan="2">Monitors</th><th colspan="3">Hourly traffic flow</th></tr><tr><th>Mean</th><th>D1</th><th>D9</th></tr></thead><tbody><tr><td>Bordeaux</td><td>11</td><td>1861</td><td>219</td><td>3700</td></tr><tr><td>Lille</td><td>12</td><td>1175</td><td>137</td><td>2525</td></tr><tr><td>Lyon</td><td>13</td><td>2109</td><td>282</td><td>4228</td></tr><tr><td>Marseille</td><td>9</td><td>1098</td><td>89</td><td>2620</td></tr><tr><td>Nantes</td><td>20</td><td>1164</td><td>111</td><td>2498</td></tr><tr><td>Nice</td><td>12</td><td>483</td><td>28</td><td>1141</td></tr><tr><td>Paris</td><td>9</td><td>2183</td><td>302</td><td>4383</td></tr><tr><td>Rennes</td><td>15</td><td>1120</td><td>111</td><td>2599</td></tr><tr><td>Strasbourg</td><td>16</td><td>1995</td><td>227</td><td>4312</td></tr><tr><td>Toulouse</td><td>11</td><td>2167</td><td>264</td><td>4344</td></tr></tbody></table>

Note: When there are two measures for the two opposite directions at the same geographical location, we consider that there are two monitors. Source: DIRs, Nice Métropôle

## 3.4 Air pollution

Air pollution in urban areas, closely linked to congestion and vehicles on the roads, is the third outcome expected to be modified by the strike.

Air quality is measured by regional associations called AASQA (*associations agréées de surveillance de la qualité de l'air*), which are grouped in a national federation called ATMO France. They operate numerous air quality measurement stations all over France. We consider the stations located in the 10 most populated urban areas. We focus on a rich set of air pollutants: the 6 pollutants that are widely available on an hourly basis are carbon monoxide (CO), particulate matter of less than 2.5 micrometers (PM2.5), particulate matter of less than 10 micrometers (PM10),<fnref n="17" /> nitrogen dioxide (NO2), ozone (O3) and sulfur dioxide (SO2). We usually have data for several measurement stations per urban area,<fnref n="18" /> which we average at the city and hourly level on a constant set of monitoring stations. For each city and each day (24 observations), we compute three quartiles of air pollutants' concentration.

NO2, O3, CO, particulate matters and SO2 are long recognized to be of critical importance in environmental policies: they cause smog and damage air quality, and anthropogenic emissions are large. The European Commission but also municipalities set threshold values over these pollutants' concentrations used in particular

<footnote n="17">¹⁷In French, PM2.5 and PM10 are called *particules fines*</footnote>

<footnote n="18">¹⁸We have at least one measurement station for each pollution in each urban area.</footnote>
to inform the population in case of pollution peaks. Most are primary pollutants, directly emitted in the atmosphere, except NO2 (quickly formed from NO, a primary pollutant) but most notably O3. Ozone is a secondary pollutant which is formed from a group of precursors pollutants under the action of UV rays. Precursors of ozone are predominantly those emitted during the combustion of fossil fuels, i.e. NOx but also CO. If ozone is not directly emitted by traffic sources, its production is indirectly strongly connected. As for the other pollutants, in 2010, personal vehicle traffic represented 22% of NOx emissions in metropolitan France, 13% of PM10, 11% of PM2.5, 10% of CO emissions but only 0.1% of SO2, which is primarily industrial.<fnref n="19" />

Figure 4 shows how pollution is tightly linked to human week: in light of all the primary pollutants’ concentrations, Sunday is the least polluted day, followed by Saturday. PM, CO and NO2 clearly display an accumulation process throughout the week, while SO2 seem rather constant throughout the business week. O3 dynamics is singular for several reasons: the transformation from precursors is a slow process (NO2+O2 → O3+NO) which needs particular conditions but also, this reaction is inhibited (or reversed) by NO, which is emitted by traffic as well. As a result, O3 is at its peak after a week accumulating precusors pollutants, when other pollutants are at their lowest levels. This explains why ozone is higher in rural areas rather than in urban areas.<fnref n="20" />

## 3.5 Hospital admissions

The first and foremost outcome of interest is health, considered here through hospital emergency admissions.

The data is obtained from the ATIH (Agence Technique de l'Information Hospitalière) that gathers an administrative and exhaustive database which records all admissions in both public and private hospitals. An admission is systematically recorded in case of an overnight stay and a doctor may decide to admit a patient if care is provided within the day or if patient surveillance is necessary.<fnref n="21" /> Its primary use is to compute hospitals’ fundings based on their activity. We were provided the daily count of emergency admissions for each final diagnosis and each urban areas. Further, this information breaks down by age range (0-4, 5-9, up to 75-79 plus over 80). More precisely, an emergency admission is an entrance through the hospital emergency unit that led to an admission from patients coming from

<footnote n="19">¹⁹Inventories of air pollutants’ emissions are realized in France by the CITEPA and transferred to the UE. See https://www.citepa.org/fr/activites/inventaires-des-emissions/secten</footnote>

<footnote n="20">²⁰For a more detailed presentation on the role of road traffic on ground-level ozone, see Munir, Chen and Hopkins (2012).</footnote>

<footnote n="21">²¹Not all persons presenting to emergency units are admitted.</footnote>
<figure><img src="image_8.png" /><figcaption>Figure 4: Pollution concentration along the week. Source: ATMO France</figcaption></figure>

their residence (i.e. not transferred from another hospital) or from public space.<fnref n="22" /> Therefore, elective care, long-term and recurring care are excluded. The diagnosis used here is coded at the end of the patient stay. It accounts for the main diagnosis which gave rise to the highest care resources. When and only when a diagnosis is not reached, the code is relative to the observed symptoms.

We divide the daily count of admissions by the appropriate age range urban area population (Source: Insee, legal population 2013). Our variable of interest is the emergency rate of admission per 100 000 persons. For some diseases and age ranges, admissions are extremely rare. We first restrict our sample to respiratory diseases and symptoms related to the breathing system. To this sample, we add another pathology with viral causes to check on contagious effects: gastroenteritis. We show in Figure 5 the 6 leading causes of emergency admissions. Respiratory diseases ranks first for the youngest children (0-4 year-old). Among these six leading causes of emergency, four might be affected by one-day-strikes (respiratory diseases, cardiovascular diseases, injuries, general symptoms). The last two (pregnancy and digestive admissions) will serve for falsification tests. Figure 5 shows clearly how age is a relevant dimension: more fragile and subjected to comorbidity, elderly people are over represented in emergency admissions. The sharp increase begin around 60. In respiratory diseases and symptoms, children aged from 0 to 4 are over represented. From then on, we define three populations of interest: all,

<footnote n="22">²²When due to hospital organization, emergency room is the main entry point, doctors should not use the code "emergency" systematically (only when the individual situation in the views of the patient, his relatives or his general practitioner is an emergency).</footnote>
0-4 and over 60. For viral contagion, we will also focus on school-aged children from 5 to 14. Table 5 enumerates the pathologies of interest according to the ICD-10 classification.<fnref n="23" />.

<table><caption>Table 5: Daily rate of admission per 100 000 persons and ICD-10 classification.</caption><thead><tr><th rowspan="3">Pathology</th><th rowspan="3">ICD10</th><th colspan="12">Rate of admissions per 100 000 persons</th></tr><tr><th colspan="2">All</th><th colspan="2">0-4</th><th colspan="2">5-14</th><th colspan="2">15-59</th><th colspan="2">Over 60</th></tr><tr><th>Mean</th><th>sd</th><th>Mean</th><th>sd</th><th>Mean</th><th>sd</th><th>Mean</th><th>sd</th><th>Mean</th><th>sd</th></tr></thead><tbody><tr><td>Intestinal infection (e.g. gastroenteritis)</td><td>A08-A09</td><td>0.24</td><td>0.22</td><td>2.24</td><td>2.87</td><td>0.17</td><td>0.37</td><td>0.07</td><td>0.11</td><td>0.15</td><td>0.25</td></tr><tr><td><strong>Diseases of the respiratory system</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>- Acute upper respiratory infections</td><td>J00-J06</td><td>1.37</td><td>0.72</td><td>5.47</td><td>5.65</td><td>0.50</td><td>0.70</td><td>0.49</td><td>0.32</td><td>3.12</td><td>1.67</td></tr><tr><td>- Influenza and Pneumonia</td><td>J09-J18</td><td>0.43</td><td>0.28</td><td>0.70</td><td>1.22</td><td>0.11</td><td>0.29</td><td>0.15</td><td>0.16</td><td>1.33</td><td>0.94</td></tr><tr><td>Abnormalities of breathing</td><td>R06</td><td>0.08</td><td>0.10</td><td>0.12</td><td>0.48</td><td>0.01</td><td>0.08</td><td>0.03</td><td>0.07</td><td>0.23</td><td>0.33</td></tr><tr><td><strong>Pregnancy</strong></td><td>O00-O99</td><td>0.90</td><td>0.83</td><td>&lt; 0.01</td><td>&lt; 0.01</td><td>&lt; 0.01</td><td>0.04</td><td>1.51</td><td>1.36</td><td>&lt; 0.01</td><td>0.01</td></tr><tr><td><strong>Diseases of the digestive system</strong></td><td>K00-K93</td><td>2.79</td><td>0.97</td><td>1.84</td><td>2.53</td><td>1.40</td><td>1.57</td><td>2.18</td><td>0.95</td><td>5.53</td><td>2.41</td></tr></tbody></table>

Sample from 01/01/10 to 31/12/15 in the ten largest urban ares of France. Source: ATIH

Chapters of the ICD-10 are in bold (highest level of classification). Other are subcategories. Mean is < $r_{s,a,t,c}$ > $s,a$ for s a pathology, a an age range, t a given date, c a city, where $r_{s,a,t,c} = \frac{n_{s,a,t,c}}{N_{s,a,c}}$ the ratio of admissions n over population N is our outcome of interest.

## 3.6 Weather

Weather conditions play a key role in human activity (including the decision to travel and the driving behaviour, to some extent) and air pollution formation. We hence consider a full set of weather conditions in our estimations. Data come from Météo France and are available on an hourly basis for our 10 urban areas. We consider seven weather parameters as control variables: temperature, rainfall, wind speed, wind direction, insolation, humidity and vapor pressure. We also consider a day-level dummy coding for presence of snow. Measurement stations are located at nearby airport<fnref n="24" />, except for Paris, where the measurement station is located in a garden in the center of Paris (parc Montsouris).

<footnote n="23">²³International Statistical Classification of Diseases and Related Health Problems (ICD)</footnote>

<footnote n="24">²⁴Specifically for insolation in Lille, we use the measurement station in Lillers, nearby Lille, as this parameter was not available in Lille-Lesquin airport station over the whole studied period.</footnote>
<figure><img src="image_9.png" /><figcaption>Figure 5: The 6 most important pathologies in terms of average daily rate of admissions: rate of admissions per 100 000 persons of a given 5-year age bracket (e.g. 0-4, 5-9, to over 80). The error bars show the first and last decile of observed daily admissions. Symptoms are emergency admissions where no final diagnosis was reached: the doctors described the symptoms rather than a particular disease.</figcaption></figure>

Source: ATIH
# 4 Empirical strategy

We use a difference-in-differences strategy where the control group rotates among urban area for the 91 events used in the estimation. We use the exact same specification for each output variable available on a daily basis: congestion, pollutant concentrations, emergency hospital admissions. For date $t$, city $c$, day-of-the-week $d$, month-of-the-year $m$, and output variable $y_{c,t}$ the specification writes

$$y_{c,t} = \sum_{k=-1}^{k=2} \alpha_k S_{c,t+k} + \beta X_{c,t} + \gamma_{d,c} + \delta_{c,m} + \nu_t + \epsilon_{c,t} \quad (1)$$

where $S_{c,t}$ is a dummy that equals one when a public transport strike is on going in city $c$ at date $t$. We also include two leads and one lag of $S_{c,t}$ so as to explore potential anticipation and delayed effects. To implement a difference-in-difference, we include city and date$^{25}$ fixed effects. Thus, our identification strategy compares, within a given date, cities where a strike is ongoing with cities where there is not. $X_{c,t}$ are weather controls, including temperature, rainfall, humidity, insulation and vapor pressure (for these five variables, we include the day-level mean in a polynomial of order 2). So as to reflect that air pollutants' concentrations are highly dependent on the wind direction and strength, and that the dispersion and the arrival of pollutants depends on city specific topography, we include a polynomial of order 2 in wind speed interacted with wind direction at four times in the day (midnight, 6a.m., noon, 6p.m.), and interacted with cities dummies. We also include a daily dummy for the presence of snow (at least very relevant for traffic outcomes but not only). Finally, we include a day-of-the-week and month-of-the-year interacted with the city to allow for local patterns. Standard errors are clustered at the city level, following Bertrand, Duflo and Mullainathan (2004).

At the hourly level, we adopt for traffic a very similar equation: we adapt the set of fixed effects by including hour-of-the-day and monitoring station fixed effects (when a station records two opposite directions, there is a fixed effect per direction) on top of date dummies, and day-of-the-week and month-of-the-year interacted with the city fixed effects. The weather covariates are taken hourly.$^{26}$ We take into account the variable number of monitoring stations per city by weighting this regression by the inverse of the number of observations in each city.

Finally, depending on air pollutants, concentrations are not always observed, but missingness is unrelated to the event of the strike$^{27}$.

<footnote>$^{25}$We consider each date in the scope from 1 January 2010 to 31 December 2015. To deal with the high number of fixed effects, we use the reghdfe procedure by Correia (2016).</footnote>

<footnote>$^{26}$Keeping the weather covariates at their daily mean instead does not change the results.</footnote>

<footnote>$^{27}$See Table 14 in appendix</footnote>
# 5 Results

We present first our results regarding congestion, traffic and air pollution. Second, we review the results on health.

## 5.1 Congestion, traffic and air pollution

We present in Table 6 the estimates from Equation 1 regarding extra-travel time incurred by drivers. On a strike day, we observe a congestion level superior by about 7.5% compared to a day without strike. Whereas it might seem small, it is likely that the congestion impact is much higher in morning hours. Indeed, hourly traffic estimates in Figure 6 shows that car flow increase by more than 20% vehicles per monitoring stations but that this effect is very localized in the first commuting hours from 8 to 10 a.m..<fnref n="28" /> Between 8 and 9 a.m., there are 300 more vehicles passing by monitoring stations than on a regular day. Even though this effect appears quite strong in morning hours, it is not significant the rest of the day, whereas we might expect a return peak in evening hours. Contrary to congestion which is measured so as to reflect the whole network, traffic data is measured punctually on main axis. In the evening return, some vehicles coming back may divert from the main roads, especially if drivers are learning from the morning difficulties.<fnref n="29" />

As a whole, we observe evidence that traffic is perturbed on a strike day: flow of vehicles passing the main axis increases substantially in the morning peak hours and congestion increases significantly. In what follows, we examine how, with more vehicles and congested conditions, the mix of pollutants is modified in the days following the strike. We focus on the dynamics during several days, as what is suspected to be modified is air pollutants emissions (flows), whereas what we measure is the air pollutants concentration (stocks).

Table 7 shows the results when estimating Equation 1 by air pollutant for the three day-level quartiles.<fnref n="30" /> The first quartile of carbon monoxide increases by 30 µg/m⁻³ on the strike day which is 0.14 of the standard deviation of CO concentration and represents a 10.1% increase. This is in line with the increase of congestion and traffic on that day, and with the fact that CO car emissions are particularly favored by low speed (Ntziachristos and Samaras (2000)). A fleet composition effect may also be at stake. Drivers are more likely to use an older

<footnote n="28">²⁸See Figure 19 in appendix to compare these estimates with those of the adjacent days.</footnote>

<footnote n="29">²⁹Another explanation may be related to cancellation of trips that are not work-related and that can be postponed: Figure 8 in appendix shows the asymmetry of traffic flow suggesting that evening trips are not only returns from work.</footnote>

<footnote n="30">³⁰That is, in linear regression 1, the outcomes are the quartile of air pollutant concentrations over the 24 daily measures.</footnote>
<table><caption>Table 6: Log daily congestion level around strike day S. Estimates from Equation (1)</caption><thead><tr><th></th><th>Log Congestion</th></tr></thead><tbody><tr><td>S-1</td><td>0.00477<br>(0.0242)</td></tr><tr><td>S</td><td>0.0663***<br>(0.0199)</td></tr><tr><td>S+1</td><td>0.0309<br>(0.0369)</td></tr><tr><td>S+2</td><td>0.00426<br>(0.0302)</td></tr><tr><td>Observations</td><td>13541</td></tr><tr><td>R<sup>2</sup></td><td>0.920</td></tr></tbody></table>

Notes: All regressions are run at the date-city level as in Equation (1), and include date fixed effects and city-specific day-of-week, week-of-year fixed effects, and weather controls. Number of 1-day strikes used in estimation sample: 91. Cluster-robust standard errors (robust to the presence of heteroskedasticity) are in parentheses. *: p-value < 0.1,**: p-value < 0.05,***: p-value < 0.01

<figure><img src="image_10.png" /><figcaption>Figure 6: Traffic flow on a one-day strike. Estimates from the hourly regression described in section 3 are reported with their 95% confidence intervals</figcaption></figure>
car that they do not use usually on a strike day. And older cars emit more CO, as European norms have been more and more binding over the last two decades.

Particulate matters increase mainly on the following day of the strike. This result is found for the three quartiles. The three quartile of PM2.5 increase respectively by 10.1%, 12.3% and 12.8%. The first and the third quartile PM10 increase respectively by 7.7% and 8.2%. The delay is rather in line with what Figure 4 suggests on a regular week: particulate matters are subject to an accumulation process, with yesterday's emitted particles being influential on today's concentration. PM2.5 first quartile significantly increases two days after the day, whereas PM10 first quartile does not. This may be explained by the fact that the biggest particulate matters fall more rapidly to the ground, due to their weight.

The daily median of O3 increases two day after the strike. It represents a 4.5% increase. These dynamics are in line with the fact that ozone is a secondary pollutant, formed from precursor pollutants, such as carbon monoxide, non-methane volatile organic compounds and nitrogen oxides, all of them emitted by cars.

Cars emit nitrogen monoxide (NO). Therefore if there are more cars driving at a given speed, the equilibrium $NO2 + O2 \leftrightarrow NO + O3$ tends to shift to the left (a higher NO2 concentration, not observed here). Ozone increases two days after the strike. This indirectly suggests the consumption of the ozone precursors observed here, NO2 and CO, in the reaction producing O3, mitigating their accumulation. The reason why we do not observe an increase in NO2 could also be related to the relation between speed and pollutant emissions. In general, pollutant emissions as a function of speed are U-shaped with a minimum specific to each sources which may range from 40km/h to 80km/h.<fnref n="31" />

Finally, we observe a decrease of the first quartile of SO2 by 36%, emitted mainly by industries, on the day after the strike. We can conjecture that the strike affects plant operations, as not every worker may go to work. This could in turn result in a lower SO2 concentration the following day.

<footnote n="31">³¹A difference between CO and NO2 is related to how their emissions depend on speed. The emissions of nitrogen oxides per unit of distance are a relatively flat U-shaped function of speed (compared to the other precursor), with a minimum at 40km/h (for example decreasing speed from 80 to 40 km/h leads to a decrease in NO2 emissions, and reducing speed below leads to a relatively flat increase), while CO emissions are strongly favored by low speed and increase strongly and constantly when speed is reduced from 80 to below 5 km/h, see (Ntziachristos and Samaras (2000)). On the speed range below 80km/h, the combined effects of more cars on the road and lower speed is therefore unambiguous for CO, but not for NOx.</footnote>
<table><caption>Table 7: Air pollution: daily estimates around a one-day strike</caption><thead><tr><th rowspan="2"></th><th colspan="6">Pollutant concentration (µm/m<sup>-3</sup>)</th></tr><tr><th>CO</th><th>PM2.5</th><th colspan="3">Day first quartile</th><th></th></tr><tr><th></th><th></th><th></th><th>PM10</th><th>NO2</th><th>O3</th><th>SO2</th></tr></thead><tbody><tr><td>S-1</td><td>11.36<br>(21.68)</td><td>0.277<br>(0.567)</td><td>0.328<br>(0.835)</td><td>2.280<br>(1.533)</td><td>-1.546<br>(1.710)</td><td>-0.229<br>(0.174)</td></tr><tr><td>S</td><td>30.37**<br>(12.66)</td><td>0.963<br>(1.031)</td><td>1.216<br>(1.155)</td><td>0.556<br>(1.236)</td><td>0.889<br>(1.537)</td><td>-0.224<br>(0.132)</td></tr><tr><td>S+1</td><td>18.49<br>(18.29)</td><td>1.353**<br>(0.442)</td><td>1.536*<br>(0.695)</td><td>0.216<br>(1.707)</td><td>-0.241<br>(1.736)</td><td>-0.369**<br>(0.139)</td></tr><tr><td>S+2</td><td>-9.072<br>(15.09)</td><td>1.666*<br>(0.862)</td><td>1.219<br>(0.990)</td><td>-0.801<br>(0.529)</td><td>0.531<br>(1.247)</td><td>-0.184<br>(0.110)</td></tr><tr><td>Mean dep. var.</td><td>296.5</td><td>12.9</td><td>19.9</td><td>27.7</td><td>35.1</td><td>0.5</td></tr><tr><td>Observations</td><td>10605</td><td>12458</td><td>11856</td><td>12579</td><td>13052</td><td>11895</td></tr><tr><td>R<sup>2</sup></td><td>0.753</td><td>0.768</td><td>0.745</td><td>0.850</td><td>0.848</td><td>0.437</td></tr><tr><th rowspan="2"></th><th colspan="6">Day median</th></tr><tr><th>CO</th><th>PM2.5</th><th colspan="3">Day third quartile</th><th></th></tr><tr><td>S-1</td><td>6.478<br>(26.11)</td><td>0.834<br>(0.832)</td><td>-0.590<br>(0.839)</td><td>0.758<br>(1.337)</td><td>-1.623<br>(1.548)</td><td>-0.287<br>(0.247)</td></tr><tr><td>S</td><td>15.63<br>(20.62)</td><td>0.685<br>(1.092)</td><td>0.552<br>(1.595)</td><td>-0.380<br>(1.054)</td><td>-0.0839<br>(1.363)</td><td>0.0609<br>(0.343)</td></tr><tr><td>S+1</td><td>35.33<br>(24.21)</td><td>1.977**<br>(0.708)</td><td>1.433<br>(0.782)</td><td>0.625<br>(1.076)</td><td>0.348<br>(1.598)</td><td>-0.216<br>(0.251)</td></tr><tr><td>S+2</td><td>-16.09<br>(22.14)</td><td>1.753<br>(1.288)</td><td>1.807<br>(1.799)</td><td>-0.935<br>(1.000)</td><td>2.759*<br>(1.449)</td><td>-0.269<br>(0.180)</td></tr><tr><td>Mean dep. var.</td><td>417.2</td><td>16.1</td><td>25.4</td><td>38.7</td><td>48.6</td><td>0.9</td></tr><tr><td>Observations</td><td>10605</td><td>12458</td><td>11856</td><td>12579</td><td>13052</td><td>11895</td></tr><tr><td>R<sup>2</sup></td><td>0.807</td><td>0.783</td><td>0.771</td><td>0.876</td><td>0.884</td><td>0.462</td></tr><tr><th rowspan="2"></th><th colspan="6">Day fourth quartile</th></tr><tr><th>CO</th><th>PM2.5</th><th colspan="3">Day fourth quartile</th><th></th></tr><tr><td>S-1</td><td>-8.614<br>(34.71)</td><td>-0.0399<br>(1.032)</td><td>-1.973<br>(1.219)</td><td>1.815<br>(1.741)</td><td>1.464<br>(1.328)</td><td>-0.254<br>(0.304)</td></tr><tr><td>S</td><td>18.27<br>(23.85)</td><td>-0.610<br>(1.306)</td><td>-0.582<br>(2.038)</td><td>-2.333<br>(1.668)</td><td>0.221<br>(1.292)</td><td>0.0250<br>(0.394)</td></tr><tr><td>S+1</td><td>30.18<br>(38.22)</td><td>2.547**<br>(0.926)</td><td>2.578***<br>(0.766)</td><td>0.0792<br>(1.267)</td><td>1.993<br>(2.062)</td><td>0.00792<br>(0.336)</td></tr><tr><td>S+2</td><td>-18.84<br>(27.90)</td><td>1.508<br>(1.268)</td><td>2.564<br>(2.180)</td><td>0.0470<br>(1.747)</td><td>2.811**<br>(1.115)</td><td>-0.422<br>(0.340)</td></tr><tr><td>Mean dep. var.</td><td>543.7</td><td>20</td><td>31.2</td><td>49.7</td><td>62.7</td><td>1.5</td></tr><tr><td>Observations</td><td>10605</td><td>12458</td><td>11856</td><td>12579</td><td>13052</td><td>11895</td></tr><tr><td>R<sup>2</sup></td><td>0.816</td><td>0.784</td><td>0.770</td><td>0.869</td><td>0.901</td><td>0.494</td></tr></tbody></table>

Notes: All regressions are run at the date-city level as in Equation (1), and include date fixed effects and city-specific day-of-week, week-of-year fixed effects, and weather controls. Number of 1-day strikes used in estimation sample respectively by pollutants: 57, 65, 55, 55, 62, 59 (different from 91 due to missing values in the outcomes). Cluster-robust standard errors (robust to the presence of heteroskedasticity) are in parentheses. *: p-value < 0.1,**: p-value < 0.05,***: p-value < 0.01
## 5.2 Health effects

Congestion is higher on strike days and traffic-related air pollutants are higher than usual from that day up to two days after. We now focus on emergency hospital admissions. Due to more air pollution, respiratory diseases are expected to increase. But some respiratory diseases are also caused by infectious agents (mainly viruses). If contagion decreases due to lower interpersonal contact on the strike days, the net effect on respiratory diseases is unclear one or two days after the strike. We show evidence of the existence of these two channels through which health is affected. Table 8 presents our main results on emergency hospital admissions, for respiratory diseases, and for diseases due to an infectious agent with a short incubation period. Influenza and pneumonia belong to both categories. They are respiratory diseases suspected to be favoured by air pollution and are caused by a infectious agent (a virus for influenza, a virus or a bacteria for pneumonia). Consequently, they can be subject to both an air pollution and a contagion channel with opposite effects. As for gastroenteritis, it is not favored by air pollution and only a contagion channel can be at stake.

### Evidence of air pollution impact

Here again, the observed impact is not reduced to the very day of the strike. The first column shows the admissions for abnormalities of breathing, that is persons reporting difficulties in breathing for whom no diagnosis was reached. The day after the strike, there is an increase by about 20% (+0.018 admissions per 100 000 persons in the urban area) of abnormalities of breathing, significant at the 5% level. The second column report admissions for the whole set of diseases of the respiratory system. We observe no significant effects. First, we might want to restrict to pathologies the most likely to be sensitive at short-term to air pollution. When we restrict to acute (as opposed to chronic) diseases that are specific to the upper respiratory system on the third column (i.e. nose, pharynx and larynx who are among other things responsible of the filtering and cleaning of the air we inhale) we evidence an increase by about 38% on the strike day. Second, as argued before, on a strike day people may be less likely to interact and fall ill due to viral causes the following days. As for influenza, the incubation period is very short (from one to four days, with an average at two days) and this channel may lead to underestimate the impact of the air pollution shock triggered by the strike. The fourth column of Table 8 shows that it is indeed the case: on the two days following a strike day, emergency admissions for influenza and pneumonia
are lower than usual by respectively 14 and 18%.<fnref n="32" />

For influenza, the contagion channel is of larger magnitude than the air pollution channel. For acute disease of the upper respiratory system, on the very day of the strike, only the air pollution channel is at work. Afterwards, we may underestimate the delayed air pollution detrimental impact here estimated to be non significant, as pathologies in this category are also subject to infectious agent (e.g. pharyngitis). As far as abnormalities of breathing are concerned, the air pollution channel prevail on the contagion channel, should the second one exist.

On Table 9, we focus on acute respiratory diseases to study the impact by age group.<fnref n="33" /> Two facts emerge. First, the detrimental health impact attributable to air pollution is borne by children. Second, this effect is large, although the marginal increase in air pollution is relatively weak and representative of small variation as opposed to an air pollution peak. On a regular day, a city with 100 000 children between 0 and 4 sees 0.8 admissions, with a standard deviation of 1.2. On a day following a strike, the same city sees on average 0.4 admissions on top. For the 5 to 14 years-old, the impact is almost of the same magnitude than the baseline mean: + 0.07 admissions per 100 000 5-to-14-year-old children.

## Evidence of viral spread

To investigate further the contagion channel, we focus on a disease caused by an infectious agent, but which is not favoured by air pollution : gastroenteritis. The last columns of Table 8 show that there are 19% less admissions two days after the strike compared to a regular day.

We refine results by age group for the two short incubation period diseases. For influenza and pneumonia, the reaction is faster for young children than for teenagers and old people. For gastroenteritis, only the central age group (15-59) is affected, whereas this category was not affected for influenza and pneumonia. Overall, observed delays are in line with what is medically known about average incubation periods of these diseases, which are between one and two days. Taking both infectious pathologies together, decreases are pervasive across age groups and compatible with incubation periods by viruses. For influenza in particular, school-age children are most significantly affected in line with past literature.

<footnote n="32">³²All respiratory diseases (ICD-10 J00-J99) can be split in acute diseases of the upper respiratory system (ICD-10 J00-J06), influenza and pneumonia (ICD-10 J09-J18), and the rest (ICD-10 J20-J99): for the last, not shown here, we provide the estimation in appendix where we find no effects.</footnote>

<footnote n="33">³³Table 16 and 17 complement the results by age groups.</footnote>
<table><caption>Table 8: Emergency hospital admissions for respiratory diseases and diseases with infectious causes (short incubation period)</caption><caption>Rate of admission per 100 000 inhabitants</caption><thead><tr><th rowspan="4">IDC10</th><th colspan="5">Infectious diseases</th></tr><tr><th colspan="4">Related to air pollution</th><th rowspan="3">Unrelated</th></tr><tr><th colspan="4">Diseases of the respiratory system</th></tr><tr><th>Abnormalities of breathing R06</th><th>All pathologies J00-J99</th><th>Acute diseases of the upper respiratory system J00-J06</th><th>Influenza and pneumonia J09-J18</th><th>Gastro-enteritis A08-A09</th></tr></thead><tbody><tr><td>S-1</td><td>0.00438<br>(0.0142)</td><td>0.00719<br>(0.0790)</td><td>0.0204<br>(0.0237)</td><td>0.0134<br>(0.0289)</td><td>0.00345<br>(0.0198)</td></tr><tr><td>S</td><td>0.00972<br>(0.0117)</td><td>0.0668<br>(0.0614)</td><td>0.0309***<br>(0.00448)</td><td>-0.0193<br>(0.0326)</td><td>0.0226<br>(0.0195)</td></tr><tr><td>S+1</td><td>0.0183**<br>(0.00741)</td><td>-0.0917<br>(0.0641)</td><td>0.0175<br>(0.0116)</td><td>-0.0637*<br>(0.0303)</td><td>0.00867<br>(0.0204)</td></tr><tr><td>S+2</td><td>0.00386<br>(0.0129)</td><td>-0.0828<br>(0.0893)</td><td>0.000126<br>(0.0111)</td><td>-0.0802*<br>(0.0367)</td><td>-0.0406*<br>(0.0220)</td></tr><tr><td>Mean dep. var.</td><td>0.08</td><td>1.42</td><td>0.08</td><td>0.44</td><td>0.24</td></tr><tr><td>Obs.</td><td>13547</td><td>13547</td><td>13547</td><td>13547</td><td>13547</td></tr><tr><td>R<sup>2</sup></td><td>0.410</td><td>0.775</td><td>0.429</td><td>0.602</td><td>0.657</td></tr></tbody></table>

Notes: All regressions are run at the date-city level as in Equation (1), and include date fixed effects and city-specific day-of-week, week-of-year fixed effects, and weather controls. 91 one-day strikes are used (no missing values in the outcome). Cluster-robust standard errors (robust to the presence of heteroskedasticity) are in parentheses. * *p* < 0.10, ** *p* < 0.05, *** *p* < 0.01
<table><caption>Table 9: Emergency admissions for acute diseases of the upper respiratory system, by age group</caption><caption>Rate of admission per 100 000 inhabitants of the corresponding age bracket</caption><thead><tr><th rowspan="2">Age group</th><th colspan="4">Acute diseases of the upper respiratory system<br>ICD10 J00-J06</th></tr><tr><th>0-4</th><th>5-14</th><th>15-59</th><th>Over 60</th></tr></thead><tbody><tr><td>S-1</td><td>0.306<br>(0.316)</td><td>0.00337<br>(0.0341)</td><td>0.00227<br>(0.0125)</td><td>0.00267<br>(0.00658)</td></tr><tr><td>S</td><td>0.386***<br>(0.104)</td><td>0.0205<br>(0.0400)</td><td>0.00694<br>(0.00665)</td><td>-0.0000905<br>(0.00662)</td></tr><tr><td>S+1</td><td>0.189<br>(0.145)</td><td>0.0714**<br>(0.0278)</td><td>0.00136<br>(0.00838)</td><td>-0.00953<br>(0.00642)</td></tr><tr><td>S+2</td><td>0.0859<br>(0.188)</td><td>0.00846<br>(0.0280)</td><td>-0.00903<br>(0.0146)</td><td>0.00143<br>(0.0117)</td></tr><tr><td>Mean dep. var.</td><td>0.82</td><td>0.09</td><td>0.03</td><td>0.01</td></tr><tr><td>Observations</td><td>13547</td><td>13547</td><td>13547</td><td>13547</td></tr><tr><td>R<sup>2</sup></td><td>0.422</td><td>0.277</td><td>0.265</td><td>0.235</td></tr></tbody></table>

Notes: All regressions are run at the date-city level as in Equation (1), and include date fixed effects and city-specific day-of-week, week-of-year fixed effects, and weather controls. 91 one-day strikes are used (no missing values in the outcome). Cluster-robust standard errors (robust to the presence of heteroskedasticity) are in parentheses. * $p < 0.10$, ** $p < 0.05$, *** $p < 0.01$
<table><caption>Table 10: Diseases with viral causes, suspected to be exacerbated by air pollution (influenza) or not (gastroenteritis)</caption><thead><tr><th colspan="5">Rate of admission per 100 000 inhabitants of the corresponding age bracket</th></tr><tr><th colspan="5">Influenza and pneumonia<br>ICD10 J09-J18</th></tr><tr><th></th><th>0-4</th><th>5-14</th><th>15-59</th><th>Over 60</th></tr></thead><tbody><tr><td>S-1</td><td>-0.0191<br>(0.0995)</td><td>0.00673<br>(0.0648)</td><td>0.00402<br>(0.0225)</td><td>0.0454<br>(0.0906)</td></tr><tr><td>S</td><td>0.0485<br>(0.165)</td><td>0.0241<br>(0.0745)</td><td>-0.0140<br>(0.0263)</td><td>-0.0700<br>(0.110)</td></tr><tr><td>S+1</td><td>-0.139*<br>(0.0663)</td><td>-0.00835<br>(0.0324)</td><td>-0.0178<br>(0.0239)</td><td>-0.209<br>(0.125)</td></tr><tr><td>S+2</td><td>-0.210<br>(0.159)</td><td>-0.0835**<br>(0.0368)</td><td>-0.0228<br>(0.0171)</td><td>-0.203*<br>(0.105)</td></tr><tr><td>Mean dep. var.</td><td>0.76</td><td>0.12</td><td>0.15</td><td>1.32</td></tr><tr><td>Observations</td><td>13547</td><td>13547</td><td>13547</td><td>13547</td></tr><tr><td>R<sup>2</sup></td><td>0.446</td><td>0.297</td><td>0.365</td><td>0.497</td></tr><tr><th colspan="5">Gastroenteritis<br>ICD10 A08-A09</th></tr><tr><th></th><th>0-4</th><th>5-14</th><th>15-59</th><th>Over 60</th></tr><tr><td>S-1</td><td>-0.0180<br>(0.212)</td><td>0.00459<br>(0.0457)</td><td>0.0140<br>(0.0189)</td><td>-0.0127<br>(0.0474)</td></tr><tr><td>S</td><td>0.309<br>(0.297)</td><td>-0.00877<br>(0.0409)</td><td>0.0116<br>(0.0217)</td><td>-0.000863<br>(0.0411)</td></tr><tr><td>S+1</td><td>0.231<br>(0.281)</td><td>-0.00557<br>(0.0330)</td><td>-0.0299**<br>(0.0113)</td><td>0.0530<br>(0.0538)</td></tr><tr><td>S+2</td><td>-0.436<br>(0.242)</td><td>0.0369<br>(0.0492)</td><td>-0.0223<br>(0.0169)</td><td>-0.0400<br>(0.0550)</td></tr><tr><td>Mean dep. var.</td><td>2.41</td><td>0.17</td><td>0.07</td><td>0.15</td></tr><tr><td>Observations</td><td>13547</td><td>13547</td><td>13547</td><td>13547</td></tr><tr><td>R<sup>2</sup></td><td>0.670</td><td>0.333</td><td>0.294</td><td>0.273</td></tr></tbody></table>

Notes: All regressions are run at the date-city level as in Equation (1), and include date fixed effects and city-specific day-of-week, week-of-year fixed effects, and weather controls. 91 one-day strikes are used (no missing values in the outcome). Cluster-robust standard errors (robust to the presence of heteroskedasticity) are in parentheses. * $p < 0.10$, ** $p < 0.05$, *** $p < 0.01$
# 6 Robustness

## 6.1 Falsification tests with unrelated emergency admissions

As a robustness check, we verify that no effect is found for digestive diseases and pregnancy that are a priori unrelated to the channels we focus on and are among the most frequent admissions in emergency.<fnref n="34" /> As expected, we find no significant effects of the strike neither on the same day nor on adjacent days. Another criticism that these falsification tests weaken is the idea that stress caused by a strike event fragilize health and therefore play a role in emergency admissions. The digestive system is sensitive to stress through a number of nervous connections (Bhatia and Tandon (2005)) while we see no impact on emergency admissions for this pathology.

<table><caption>Table 11: Falsification tests with unrelated emergency admissions</caption><thead><tr><th rowspan="3"></th><th colspan="6">Rate of admission per 100 000 inhabitants<br>of the corresponding age bracket</th></tr><tr><th>Pregnancy<br>O00-O99</th><th colspan="5">Diseases of the digestive system<br>K00-K93</th></tr><tr><th>All</th><th>All</th><th>0-4</th><th>5-14</th><th>15-59</th><th>Over 60</th></tr></thead><tbody><tr><td>S-1</td><td>0.0532<br>(0.0848)</td><td>-0.0732<br>(0.128)</td><td>-0.261<br>(0.425)</td><td>-0.220<br>(0.236)</td><td>-0.164<br>(0.135)</td><td>0.260<br>(0.321)</td></tr><tr><td>S</td><td>0.0581<br>(0.0564)</td><td>-0.00767<br>(0.101)</td><td>0.334<br>(0.383)</td><td>0.0457<br>(0.222)</td><td>-0.0558<br>(0.125)</td><td>-0.0304<br>(0.205)</td></tr><tr><td>S+1</td><td>0.0388<br>(0.0339)</td><td>-0.103<br>(0.110)</td><td>-0.180<br>(0.336)</td><td>-0.191<br>(0.297)</td><td>0.0195<br>(0.133)</td><td>-0.258<br>(0.386)</td></tr><tr><td>S+2</td><td>0.0273<br>(0.0395)</td><td>-0.118<br>(0.141)</td><td>-0.205<br>(0.381)</td><td>-0.315<br>(0.240)</td><td>-0.0409<br>(0.154)</td><td>-0.245<br>(0.346)</td></tr><tr><td>Mean dep. var.</td><td>0.9</td><td>2.83</td><td>1.87</td><td>1.53</td><td>2.21</td><td>5.57</td></tr><tr><td>Observations</td><td>13547</td><td>13547</td><td>13547</td><td>13547</td><td>13547</td><td>13547</td></tr><tr><td>R<sup>2</sup></td><td>0.894</td><td>0.552</td><td>0.356</td><td>0.347</td><td>0.427</td><td>0.396</td></tr></tbody></table>

Notes: All regressions are run at the date-city level as in Equation (1), and include date fixed effects and city-specific day-of-week, week-of-year fixed effects, and weather controls. 91 one-day strikes are used (no missing values in the outcome). Cluster-robust standard errors (robust to the presence of heteroskedasticity) are in parentheses. * $p < 0.10$, ** $p < 0.05$, *** $p < 0.01$

<footnote n="34">³⁴We found no significant impact on other leading causes of emergency admissions that have not been chosen for falsification tests as they could be affected (injury and cardiovascular diseases, see Table 15 in appendix).</footnote>
## 6.2 Do strikers favor days with particular events?

Our empirical strategy would be endangered if strikes coincide with particular events which are by themselves responsible for a higher traffic. By controlling for date fixed effects, we allow strikes to be correlated to national shocks (bank holidays, world cup games etc.). However, we do not control for strikers targeting dates in their city when a particular event takes place, for instance to cause maximal disruption. If the strike has a large impact on users and beyond, it might increase strikers bargaining power as the transport firm may wish a fast conflict resolution. But it may not be a good strategy as it may influence negatively public opinion. To check indirectly whether strikes coincide with particular events, we verify that hotel occupancy is not particularly high on strikes days (or the converse, that hotel occupancy is affected by the strike). We use the responses at the *Enquête mensuelle sur la fréquentation touristique* which corresponds to the number of rooms available and occupied at each date of the years 2010-2015, that we aggregate at the urban area level to compute an occupancy rate (all occupied rooms over all available rooms). As shown by Table 12, the occupancy rate is not modified on the event of a strike. This suggests that although strikes may not be random, they are most probably not happening concomitantly with mass events conditional on our extensive set of control variables and fixed effects.

<table><caption>Table 12: Hotel occupancy around one-day strikes</caption><thead><tr><th></th><th>Occupancy rate</th></tr></thead><tbody><tr><td>S-1</td><td>0.0127<br>(0.00960)</td></tr><tr><td>S</td><td>0.0174<br>(0.0143)</td></tr><tr><td>S+1</td><td>0.000448<br>(0.0115)</td></tr><tr><td>S+2</td><td>-0.00637<br>(0.0105)</td></tr><tr><td>Mean dep. var.</td><td>0.63</td></tr><tr><td>Observations</td><td>13547</td></tr><tr><td>R<sup>2</sup></td><td>0.923</td></tr></tbody></table>

Notes: All regressions are run at the date-city level as in Equation (1), and include date fixed effects and city-specific day-of-week, week-of-year fixed effects, and weather controls. 91 one-day strikes are used (no missing values in the outcome). Cluster-robust standard errors (robust to the presence of heteroskedasticity) are in parentheses. * $p < 0.10$, ** $p < 0.05$, *** $p < 0.01$
<figure><img src="image_11.png" /><figcaption>Figure 7: Pre and post trends. Estimates from Equation (1) modified to includes 10 leads and 10 lags of the strike. 91 one-day strikes are used.</figcaption></figure>

## 6.3 Pre and post trends

In this section, we check on a longer period whether cities are indeed comparable before and after the strike event. This legitimizes a difference-in-difference strategy. Figure 7 shows the daily congestion estimates from the regression (1) on a symmetric window of 10 days. The strike day estimate is the highest coefficient in absolute value and no other coefficient is significant at the 5% level. Figure 19 in appendix shows the hourly estimates from the traffic equation when considering a 5 days window around the strike event. Here as well, the coefficient at 8 a.m. is the highest in absolute value. If some other coefficients are significant at the 5% level, very few are significant both in log and in level (as opposed to the morning peak hours on a strike day) and most are at night time (when traffic is somewhat less stable from one day to the other). We could use a p-value correction for multiple hypothesis testing because we here test 21 and 120 coefficients significances thus false positive are very likely. Because more conservative on detectable effects, it would lead to strengthen how the traffic coefficients on a strike day stand out.<fnref n="35" />

## 6.4 Sample

Finally, we verify what happens to our estimates when dropping particular periods marked by social movements (the year 2010, September months in the 6 years)

<footnote n="35">³⁵Such a procedure applied to our main results (e.g., dividing p-values by 3 in a Bonferroni manner, because we search for strike impact on 3 days) would lead to consider as insignificant the effects found for the contagion channel. But even from this conservative perspective (control of type I error at the type II error expense), the argument for air pollution channel through congestion, particulate matters and acute respiratory diseases estimates, will remain.</footnote>
when a high number of strike events occur, or when we drop the largest urban area of the sample (Paris).

Table 13 provides the main estimates when modifying the sample.<fnref n="36" /> First, across all samples, estimates for both daily congestion level and emergency admissions for acute respiratory diseases are very similar. Dropping Paris reinforces the contagion channel: in particular the influenza admission drop two days after the strike, which was only significant at the 10% level for the whole population, becomes highly significant (1%). Air pollution effects are however less discernible, with significance for PM2.5 increases the day following the strike dropping at 10%. When dropping 2010, on the converse, air pollution effects are reinforced. CO median concentration which was not affected in the baseline (only the first quartile was) is significantly higher on a strike day happening between 2011 and 2015 than on a regular day of the same period. PM2.5 median concentration is significantly affected not only at strike + 1 day but also at strike + 2 days. Over this period however, emergency admissions for abnormalities of breathing seem unaffected. Finally, dropping all September months does not affect the results, except air polutions that is somewhat less significant for CO and PM2.5. However, the effect for PM10 and O3 are not modified compared to using the baseline sample (Table 19). As a whole, these robustness exercises suggest that our conclusions are not driven by a particular city or a particular period.

<footnote n="36">³⁶Tables 18,19,20 in appendix show all estimates for air pollutant concentrations.</footnote>
<table><caption>Table 13: Robustness when dropping the largest urban area (Paris), dropping periods marked by social movement (year 2010, month September) for congestion and health outcomes.</caption><thead><tr><th rowspan="3"></th><th colspan="3">Congestion</th><th colspan="6">Emergency admissions per 100 000 inhabitants</th></tr><tr><th rowspan="2">Log daily<br>congestion</th><th colspan="2">Pollutants<br>median concentration</th><th colspan="3">All</th><th colspan="3">Children (0-4)</th></tr><tr><th>CO</th><th>PM2.5</th><th>Abnorm.<br>of breath.</th><th>Acute<br>resp. dias.</th><th>Influenza</th><th>Diarrhea</th><th>Acute<br>resp. dias.</th><th>Influenza</th></tr><tr><th>Without ...</th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th><th>(7)</th><th>(8)</th><th>(9)</th></tr></thead><tbody><tr><td>... Paris</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>S-1</td><td>0.399<br>(0.941)</td><td>-10.57<br>(28.64)</td><td>0.413<br>(1.150)</td><td>0.0118<br>(0.0158)</td><td>0.0416*<br>(0.0217)</td><td>0.0286<br>(0.0326)</td><td>-0.00116<br>(0.0283)</td><td>0.541<br>(0.323)</td><td>0.0160<br>(0.149)</td></tr><tr><td>S</td><td>1.917**<br>(0.659)</td><td>15.42<br>(29.13)</td><td>0.976<br>(1.659)</td><td>0.00947<br>(0.0141)</td><td>0.0339***<br>(0.00499)</td><td>-0.0236<br>(0.0439)</td><td>0.0184<br>(0.0261)</td><td>0.439***<br>(0.117)</td><td>0.0668<br>(0.234)</td></tr><tr><td>S+1</td><td>1.163<br>(0.938)</td><td>17.94<br>(35.24)</td><td>2.276*<br>(1.089)</td><td>0.0210*<br>(0.0105)</td><td>0.0146<br>(0.0122)</td><td>-0.0721<br>(0.0420)</td><td>0.0181<br>(0.0238)</td><td>0.142<br>(0.150)</td><td>-0.140<br>(0.126)</td></tr><tr><td>S+2</td><td>-0.148<br>(0.817)</td><td>-22.30<br>(34.33)</td><td>1.651<br>(1.896)</td><td>0.0140<br>(0.0128)</td><td>0.00513<br>(0.0131)</td><td>-0.117***<br>(0.0275)</td><td>-0.0546*<br>(0.0270)</td><td>0.178<br>(0.254)</td><td>-0.345**<br>(0.145)</td></tr><tr><td>One-day strikes</td><td>75</td><td>56</td><td>45</td><td>75</td><td>75</td><td>75</td><td>75</td><td>75</td><td>75</td></tr><tr><td>Obs.</td><td>12147</td><td>9317</td><td>11120</td><td>12153</td><td>12153</td><td>12153</td><td>12153</td><td>12153</td><td>12153</td></tr><tr><td>R<sup>2</sup></td><td>0.908</td><td>0.770</td><td>0.773</td><td>0.412</td><td>0.436</td><td>0.598</td><td>0.648</td><td>0.429</td><td>0.451</td></tr><tr><td>... 2010</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>S-1</td><td>0.393<br>(0.712)</td><td>4.633<br>(31.59)</td><td>0.807<br>(0.809)</td><td>0.00572<br>(0.0179)</td><td>0.00876<br>(0.0267)</td><td>0.0293<br>(0.0310)</td><td>0.00863<br>(0.0185)</td><td>0.0367<br>(0.203)</td><td>0.0428<br>(0.163)</td></tr><tr><td>S</td><td>2.234***<br>(0.506)</td><td>40.39**<br>(15.46)</td><td>1.153<br>(0.733)</td><td>0.0168<br>(0.00943)</td><td>0.0428***<br>(0.0130)</td><td>-0.0208<br>(0.0439)</td><td>0.0294<br>(0.0218)</td><td>0.634**<br>(0.204)</td><td>0.0414<br>(0.187)</td></tr><tr><td>S+1</td><td>0.938<br>(1.561)</td><td>35.40<br>(30.65)</td><td>2.186***<br>(0.623)</td><td>0.0227<br>(0.0144)</td><td>0.0391*<br>(0.0198)</td><td>-0.0616<br>(0.0463)</td><td>0.0218<br>(0.0310)</td><td>0.424<br>(0.271)</td><td>-0.150*<br>(0.0752)</td></tr><tr><td>S+2</td><td>-0.0271<br>(0.800)</td><td>-6.353<br>(27.39)</td><td>2.034**<br>(0.661)</td><td>-0.0101<br>(0.0120)</td><td>-0.00503<br>(0.0130)</td><td>-0.0753<br>(0.0566)</td><td>-0.0533*<br>(0.0266)</td><td>0.0323<br>(0.192)</td><td>-0.380<br>(0.309)</td></tr><tr><td>One-day strikes</td><td>38</td><td>23</td><td>25</td><td>38</td><td>38</td><td>38</td><td>38</td><td>38</td><td>38</td></tr><tr><td>Obs.</td><td>11369</td><td>8666</td><td>10586</td><td>11369</td><td>11369</td><td>11369</td><td>11369</td><td>11369</td><td>11369</td></tr><tr><td>R<sup>2</sup></td><td>0.923</td><td>0.829</td><td>0.793</td><td>0.466</td><td>0.447</td><td>0.623</td><td>0.672</td><td>0.443</td><td>0.471</td></tr><tr><td>... Sept.</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>S-1</td><td>0.0772<br>(0.686)</td><td>5.458<br>(30.51)</td><td>1.410<br>(0.814)</td><td>0.00338<br>(0.0145)</td><td>0.0119<br>(0.0215)</td><td>0.00142<br>(0.0293)</td><td>0.0211<br>(0.0240)</td><td>0.142<br>(0.296)</td><td>-0.0315<br>(0.0735)</td></tr><tr><td>S</td><td>1.824***<br>(0.461)</td><td>15.08<br>(21.62)</td><td>1.002<br>(1.196)</td><td>0.00515<br>(0.0132)</td><td>0.0278***<br>(0.00491)</td><td>-0.0237<br>(0.0326)</td><td>0.0242<br>(0.0237)</td><td>0.369***<br>(0.0867)</td><td>0.0259<br>(0.181)</td></tr><tr><td>S+1</td><td>0.234<br>(0.966)</td><td>44.28<br>(26.42)</td><td>1.756*<br>(0.785)</td><td>0.0171**<br>(0.00683)</td><td>0.0144<br>(0.0103)</td><td>-0.0685*<br>(0.0304)</td><td>0.00327<br>(0.0239)</td><td>0.194<br>(0.142)</td><td>-0.161*<br>(0.0788)</td></tr><tr><td>S+2</td><td>-0.197<br>(0.658)</td><td>-20.45<br>(23.33)</td><td>1.719<br>(1.275)</td><td>0.00456<br>(0.0136)</td><td>-0.0104<br>(0.0121)</td><td>-0.0841*<br>(0.0375)</td><td>-0.0305<br>(0.0220)</td><td>-0.0824<br>(0.227)</td><td>-0.176<br>(0.160)</td></tr><tr><td>One-day strikes</td><td>68</td><td>50</td><td>45</td><td>68</td><td>68</td><td>68</td><td>68</td><td>68</td><td>68</td></tr><tr><td>Obs.</td><td>11965</td><td>9400</td><td>11028</td><td>11971</td><td>11971</td><td>11971</td><td>11971</td><td>11971</td><td>11971</td></tr><tr><td>R<sup>2</sup></td><td>0.913</td><td>0.811</td><td>0.792</td><td>0.421</td><td>0.436</td><td>0.609</td><td>0.667</td><td>0.424</td><td>0.458</td></tr></tbody></table>

Notes: All regressions are run at the date-city level as in Equation (1), and include date fixed effects and city-specific day-of-week, week-of-year fixed effects, and weather controls. Cluster-robust standard errors (robust to the presence of heteroskedasticity) are in parentheses.

*: p-value < 0.1,**: p-value < 0.05,***: p-value < 0.01
# 7 Conclusion

In this paper, we exploit the increase in traffic-related air pollution around a one-day public-transport strike event to evidence the detrimental effect of ambient air pollution on health. We scrutinized carefully the causal chain from the one-day strike to emergency admissions and its dynamics, as the effects are not restricted to the strike day. In particular, we evidence the existence of a second channel, contagion, linking the strike event to emergency admissions and conclude that we underestimate the delayed effect of air pollution on health. Using the variations caused by a strike has strong advantages compared to correlations studies, but also its side effects: one limit is that the delayed impact on acute respiratory diseases may be underestimated as evidence of a slower viral spread among children is shown following a strike event. Even though, we find a quite substantial lower bound of the detrimental impact of ambient air pollution on health, borne in priority by children. This study emphasizes that the short-term (within a few days) impact of ambient air pollution on health is sizeable even for moderate shocks and air pollution levels. Indeed, we find evidence of an increase of particulate matters concentration by about 10 to 12%, spread all along the following day of the event. This is comparable with the differential in particulate matters concentration between a Sunday and a Thursday, that is, it is representative of usual, non-remarkable fluctuations. We evidence that the pollution shock caused by a perturbation in public transport and an increase in traffic a given day has delayed effects, due to accumulation but also to the complex chemistry of pollution.

A lot of efforts have been done from a regulatory perspective to limit emissions of new cars and have led to a decreasing trend in main traffic-related pollutants. However, even at modern level of ambient air pollution and for moderate pollution shocks, it is still possible to find negative effects on health in a real-word quasi-experiment. Therefore, by studying a day where public transport are not available, this study indirectly shows the short-term benefit of choosing public transports against polluting alternatives and the importance in terms of dynamic health spill-overs of urban population daily transport choices.
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# Appendices

## A Figures

<figure><img src="image_12.png" /><figcaption>Figure 8: Mean hourly traffic over the estimation sample by hour-of-the-day</figcaption></figure>
<figure><img src="image_13.png" /><figcaption>Figure 9: Traffic monitoring stations in Lyon</figcaption></figure>

<figure><img src="image_14.png" /><figcaption>Figure 10: Traffic monitoring stations in Paris</figcaption></figure>
<figure><img src="image_15.png" /><figcaption>Figure 11: Traffic monitoring stations in Strasbourg</figcaption></figure>

<figure><img src="image_16.png" /><figcaption>Figure 12: Traffic monitoring stations in Rennes</figcaption></figure>
<figure><img src="image_17.png" /><figcaption>Figure 13: Traffic monitoring stations in Toulouse</figcaption></figure>

<figure><img src="image_18.png" /><figcaption>Figure 14: Traffic monitoring stations in Nantes</figcaption></figure>
<figure><img src="image_19.png" /><figcaption>Figure 15: Traffic monitoring stations in Bordeaux</figcaption></figure>

<figure><img src="image_20.png" /><figcaption>Figure 16: Traffic monitoring stations in Marseille</figcaption></figure>
<figure><img src="image_21.png" /><figcaption>Figure 17: Traffic monitoring stations in Nice</figcaption></figure>

<figure><img src="image_22.png" /><figcaption>Figure 18: Traffic monitoring stations in Lille</figcaption></figure>
<figure><img src="image_23.png" /><figcaption>Figure 19: Hourly traffic around the one-day strike. Estimates from the hourly regression described in section 3 are reported at $\alpha = 5\%$ significance level</figcaption></figure>
B Tables

<table><caption>Table 14: Testing whether missing air pollutants concentrations are related to strikes.</caption><thead><tr><th></th><th colspan="6">Dummy =1 if missing</th></tr><tr><th></th><th>PM2.5</th><th>PM10</th><th>CO</th><th>O3</th><th>NO2</th><th>SO2</th></tr></thead><tbody><tr><th>S</th><td>0.0191<br>(0.0279)</td><td>-0.0171<br>(0.0501)</td><td>-0.00121<br>(0.0460)</td><td>0.0259<br>(0.0394)</td><td>-0.0952*<br>(0.0477)</td><td>0.0337<br>(0.0432)</td></tr><tr><th>Observations</th><td>13547</td><td>13547</td><td>13547</td><td>13547</td><td>13547</td><td>13547</td></tr><tr><th>R<sup>2</sup></th><td>0.377</td><td>0.549</td><td>0.614</td><td>0.335</td><td>0.371</td><td>0.415</td></tr></tbody></table>

Notes: All regressions are run at the date-city level as in Equation (1), and include date fixed effects and city-specific day-of-week, week-of-year fixed effects, and weather controls. Cluster-robust standard errors (robust to the presence of heteroskedasticity) are in parentheses. *: p-value < 0.1,**: p-value < 0.05,***: p-value < 0.01
<table><thead><tr><th></th><th colspan="5">Other respiratory diseases<br>ICD10 J20-J99</th></tr><tr><th></th><th>All</th><th>0-4</th><th>5-14</th><th>15-59</th><th>Over 60</th></tr></thead><tbody><tr><th>S-1</th><td>-0.0266<br>(0.0477)</td><td>-0.673<br>(0.396)</td><td>0.101<br>(0.108)</td><td>0.00479<br>(0.0298)</td><td>-0.0305<br>(0.121)</td></tr><tr><th>S</th><td>0.0552<br>(0.0455)</td><td>0.259<br>(0.357)</td><td>0.0129<br>(0.0773)</td><td>0.00381<br>(0.0364)</td><td>0.132<br>(0.0867)</td></tr><tr><th>S+1</th><td>-0.0455<br>(0.0764)</td><td>-0.246<br>(0.650)</td><td>0.000260<br>(0.0628)</td><td>-0.00423<br>(0.0511)</td><td>-0.137<br>(0.172)</td></tr><tr><th>S+2</th><td>-0.00265<br>(0.0645)</td><td>0.219<br>(0.310)</td><td>-0.00157<br>(0.0768)</td><td>-0.0212<br>(0.0501)</td><td>-0.0140<br>(0.154)</td></tr><tr><th>Observations</th><td>13547</td><td>13547</td><td>13547</td><td>13547</td><td>13547</td></tr><tr><th>R<sup>2</sup></th><td>0.724</td><td>0.728</td><td>0.415</td><td>0.396</td><td>0.537</td></tr></tbody></table>

Notes: All regressions are run at the date-city level as in Equation (1), and include date fixed effects and city-specific day-of-week, week-of-year fixed effects, and weather controls. Cluster-robust standard errors (robust to the presence of heteroskedasticity) are in parentheses. *: p-value < 0.1,**: p-value < 0.05,***: p-value < 0.01

<table><caption>Table 15: Other leading admissions</caption><thead><tr><th></th><th colspan="2">Rate of admission per 100 000 inhabitants</th></tr><tr><th></th><th>Cardiovascular diseases<br>ICD10 I00-I99</th><th>Injuries<br>ICD10 S00-T14</th></tr></thead><tbody><tr><th>S-1</th><td>-0.0420<br>(0.0684)</td><td>0.0414<br>(0.128)</td></tr><tr><th>S</th><td>-0.0696<br>(0.0596)</td><td>0.0814<br>(0.124)</td></tr><tr><th>S+1</th><td>0.0413<br>(0.0662)</td><td>-0.103<br>(0.105)</td></tr><tr><th>S+2</th><td>0.0531<br>(0.0521)</td><td>0.101<br>(0.0912)</td></tr><tr><th>Observations</th><td>13547</td><td>13547</td></tr><tr><th>R<sup>2</sup></th><td>0.615</td><td>0.622</td></tr></tbody></table>

Notes: All regressions are run at the date-city level as in Equation (1), and include date fixed effects and city-specific day-of-week, week-of-year fixed effects, and weather controls. Cluster-robust standard errors (robust to the presence of heteroskedasticity) are in parentheses. *: p-value < 0.1,**: p-value < 0.05,***: p-value < 0.01
<table><caption>Table 16: Emergencies admissions by age group: abnormalities of breathing</caption><thead><tr><th rowspan="2">Age group</th><th colspan="4">Abnormalities of breathing</th></tr><tr><th>0-4</th><th>5-14</th><th>15-59</th><th>Over 60</th></tr></thead><tbody><tr><td>S-1</td><td>0.102<br>(0.0682)</td><td>0.00668<br>(0.0122)</td><td>-0.000143<br>(0.00918)</td><td>-0.0191<br>(0.0542)</td></tr><tr><td>S</td><td>0.0107<br>(0.0416)</td><td>-0.0110<br>(0.00816)</td><td>0.0107<br>(0.00736)</td><td>0.0243<br>(0.0493)</td></tr><tr><td>S+1</td><td>-0.0162<br>(0.0673)</td><td>-0.00137<br>(0.00742)</td><td>0.0225**<br>(0.00712)</td><td>0.0299<br>(0.0483)</td></tr><tr><td>S+2</td><td>0.0209<br>(0.0449)</td><td>-0.00764<br>(0.00973)</td><td>-0.00180<br>(0.00998)</td><td>0.0243<br>(0.0337)</td></tr><tr><td>Observations</td><td>13547</td><td>13547</td><td>13547</td><td>13547</td></tr><tr><td>R<sup>2</sup></td><td>0.320</td><td>0.242</td><td>0.308</td><td>0.329</td></tr></tbody><caption>Rate of admission per 100 000 inhabitants of the corresponding age bracket</caption></table>

Notes: All regressions are run at the date-city level as in Equation (1), and include date fixed effects and city-specific day-of-week, week-of-year fixed effects, and weather controls. Cluster-robust standard errors (robust to the presence of heteroskedasticity) are in parentheses. \*: p-value < 0.1, \*: p-value < 0.05, \*: p-value < 0.01
<table><caption>Table 17: Emergencies admissions by age group: diseases of the respiratory system</caption><caption>Rate of admission per 100 000 inhabitants of the corresponding age bracket</caption><thead><tr><th rowspan="2">Age group</th><th colspan="4">Diseases of respiratory system<br>ICD10 J00-J99</th></tr><tr><th>0-4</th><th>5-14</th><th>15-59</th><th>Over 60</th></tr></thead><tbody><tr><td>S-1</td><td>-0.385<br>(0.682)</td><td>0.111<br>(0.138)</td><td>0.0111<br>(0.0447)</td><td>0.0176<br>(0.124)</td></tr><tr><td>S</td><td>0.694*<br>(0.364)</td><td>0.0574<br>(0.153)</td><td>-0.00321<br>(0.0590)</td><td>0.0615<br>(0.170)</td></tr><tr><td>S+1</td><td>-0.197<br>(0.527)</td><td>0.0633<br>(0.0805)</td><td>-0.0206<br>(0.0398)</td><td>-0.355<br>(0.215)</td></tr><tr><td>S+2</td><td>0.0952<br>(0.473)</td><td>-0.0766<br>(0.0789)</td><td>-0.0530<br>(0.0659)</td><td>-0.215<br>(0.196)</td></tr><tr><td>Observations</td><td>13547</td><td>13547</td><td>13547</td><td>13547</td></tr><tr><td>R<sup>2</sup></td><td>0.742</td><td>0.434</td><td>0.461</td><td>0.626</td></tr></tbody></table>

Notes: All regressions are run at the date-city level as in Equation (1), and include date fixed effects and city-specific day-of-week, week-of-year fixed effects, and weather controls. Cluster-robust standard errors (robust to the presence of heteroskedasticity) are in parentheses. *: p-value < 0.1,**: p-value < 0.05,***: p-value < 0.01
<table><caption>Table 18: Robustness when dropping the largest urban area (Paris) for pollutants outcomes.</caption><thead><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr></thead><tbody><tr><td colspan="7" style="text-align: center;">Day first quartile</td></tr><tr><td></td><td>CO</td><td>PM2.5</td><td>PM10</td><td>NO2</td><td>O3</td><td>SO2</td></tr><tr><td>S-1</td><td>8.630<br>(29.55)</td><td>0.0963<br>(0.786)</td><td>0.0418<br>(1.180)</td><td>2.894<br>(1.755)</td><td>-2.630<br>(2.079)</td><td>-0.124<br>(0.136)</td></tr><tr><td>S</td><td>31.94*<br>(17.06)</td><td>1.623<br>(1.393)</td><td>1.072<br>(1.751)</td><td>1.336<br>(1.161)</td><td>0.807<br>(1.931)</td><td>-0.315<br>(0.225)</td></tr><tr><td>S+1</td><td>13.67<br>(27.99)</td><td>1.468<br>(0.830)</td><td>1.421<br>(1.070)</td><td>2.054*<br>(0.933)</td><td>0.592<br>(2.039)</td><td>-0.440**<br>(0.188)</td></tr><tr><td>S+2</td><td>-4.278<br>(22.45)</td><td>1.665<br>(1.252)</td><td>0.793<br>(1.481)</td><td>-0.658<br>(0.686)</td><td>0.579<br>(1.875)</td><td>-0.186<br>(0.156)</td></tr><tr><td>Observations</td><td>9317</td><td>11120</td><td>10476</td><td>11632</td><td>11813</td><td>10551</td></tr><tr><td>R<sup>2</sup></td><td>0.704</td><td>0.761</td><td>0.740</td><td>0.851</td><td>0.852</td><td>0.418</td></tr><tr><td colspan="7" style="text-align: center;">Day median</td></tr><tr><td>S-1</td><td>-10.57<br>(28.64)</td><td>0.413<br>(1.150)</td><td>-1.208<br>(0.992)</td><td>1.615<br>(1.282)</td><td>-2.179<br>(2.100)</td><td>-0.154<br>(0.244)</td></tr><tr><td>S</td><td>15.42<br>(29.13)</td><td>0.976<br>(1.659)</td><td>-0.507<br>(2.090)</td><td>0.134<br>(1.101)</td><td>0.261<br>(1.865)</td><td>-0.385<br>(0.242)</td></tr><tr><td>S+1</td><td>17.94<br>(35.24)</td><td>2.276*<br>(1.089)</td><td>1.602<br>(1.327)</td><td>1.423<br>(1.132)</td><td>-0.0607<br>(2.118)</td><td>-0.254<br>(0.328)</td></tr><tr><td>S+2</td><td>-22.30<br>(34.33)</td><td>1.651<br>(1.896)</td><td>1.171<br>(2.450)</td><td>-1.052<br>(1.280)</td><td>3.342*<br>(1.626)</td><td>-0.396*<br>(0.201)</td></tr><tr><td>Observations</td><td>8666</td><td>10586</td><td>10049</td><td>10678</td><td>11038</td><td>9968</td></tr><tr><td>R<sup>2</sup></td><td>0.829</td><td>0.793</td><td>0.782</td><td>0.881</td><td>0.887</td><td>0.481</td></tr><tr><td colspan="7" style="text-align: center;">Day third quartile</td></tr><tr><td>S-1</td><td>-37.97<br>(34.87)</td><td>-0.316<br>(1.810)</td><td>-2.951*<br>(1.576)</td><td>1.411<br>(1.876)</td><td>1.355<br>(1.739)</td><td>-0.108<br>(0.322)</td></tr><tr><td>S</td><td>11.29<br>(34.81)</td><td>-0.825<br>(1.918)</td><td>-2.145<br>(2.313)</td><td>-0.819<br>(1.380)</td><td>0.297<br>(1.984)</td><td>-0.484<br>(0.286)</td></tr><tr><td>S+1</td><td>-9.660<br>(41.45)</td><td>2.189<br>(1.316)</td><td>2.406*<br>(1.196)</td><td>0.610<br>(1.719)</td><td>1.564<br>(2.962)</td><td>0.171<br>(0.389)</td></tr><tr><td>S+2</td><td>-23.54<br>(45.86)</td><td>1.227<br>(1.936)</td><td>2.250<br>(2.977)</td><td>0.228<br>(2.122)</td><td>2.152*<br>(0.988)</td><td>-0.653<br>(0.422)</td></tr><tr><td>Observations</td><td>9317</td><td>11120</td><td>10476</td><td>11632</td><td>11813</td><td>10551</td></tr><tr><td>R<sup>2</sup></td><td>0.770</td><td>0.773</td><td>0.770</td><td>0.878</td><td>0.886</td><td>0.439</td></tr></tbody></table>

Notes: All regressions are run at the date-city level as in Equation (1), and include date fixed effects and city-specific day-of-week, week-of-year fixed effects, and weather controls. Cluster-robust standard errors (robust to the presence of heteroskedasticity) are in parentheses. \*: p-value < 0.1, \*: p-value < 0.05, \*: p-value < 0.01
<table><caption>Table 19: Robustness when dropping periods marked by social movement (month September) for pollutants outcomes.</caption><thead><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr></thead><tbody><tr><td colspan="7" style="text-align: center;">Day first quartile</td></tr><tr><td></td><td>CO</td><td>PM2.5</td><td>PM10</td><td>NO2</td><td>O3</td><td>SO2</td></tr><tr><td>S-1</td><td>11.09<br>(24.24)</td><td>0.516<br>(0.585)</td><td>0.438<br>(0.846)</td><td>3.173*<br>(1.561)</td><td>-1.106<br>(1.882)</td><td>-0.118<br>(0.198)</td></tr><tr><td>S</td><td>27.03*<br>(14.30)</td><td>1.250<br>(1.238)</td><td>1.578<br>(1.270)</td><td>0.656<br>(1.383)</td><td>1.949<br>(1.906)</td><td>-0.124<br>(0.116)</td></tr><tr><td>S+1</td><td>26.66<br>(20.18)</td><td>1.019*<br>(0.513)</td><td>1.493*<br>(0.775)</td><td>0.519<br>(1.774)</td><td>0.103<br>(1.935)</td><td>-0.352**<br>(0.136)</td></tr><tr><td>S+2</td><td>-10.21<br>(14.97)</td><td>1.641*<br>(0.822)</td><td>1.285<br>(1.143)</td><td>-0.579<br>(0.543)</td><td>0.587<br>(1.292)</td><td>-0.112<br>(0.110)</td></tr><tr><td>Observations</td><td>9400</td><td>11028</td><td>10518</td><td>11118</td><td>11528</td><td>10519</td></tr><tr><td>R<sup>2</sup></td><td>0.758</td><td>0.776</td><td>0.750</td><td>0.855</td><td>0.857</td><td>0.465</td></tr><tr><td colspan="7" style="text-align: center;">Day median</td></tr><tr><td>S-1</td><td>5.458<br>(30.51)</td><td>1.410<br>(0.814)</td><td>-0.298<br>(0.866)</td><td>1.015<br>(1.251)</td><td>-1.110<br>(1.385)</td><td>-0.161<br>(0.291)</td></tr><tr><td>S</td><td>15.08<br>(21.62)</td><td>1.002<br>(1.196)</td><td>1.066<br>(1.647)</td><td>-0.258<br>(1.222)</td><td>0.462<br>(1.804)</td><td>0.219<br>(0.341)</td></tr><tr><td>S+1</td><td>44.28<br>(26.42)</td><td>1.756*<br>(0.785)</td><td>1.231<br>(1.048)</td><td>1.142<br>(1.028)</td><td>0.650<br>(1.686)</td><td>-0.218<br>(0.249)</td></tr><tr><td>S+2</td><td>-20.45<br>(23.33)</td><td>1.719<br>(1.275)</td><td>1.807<br>(2.002)</td><td>-0.857<br>(1.080)</td><td>2.830*<br>(1.483)</td><td>-0.172<br>(0.182)</td></tr><tr><td>Observations</td><td>9400</td><td>11028</td><td>10518</td><td>11118</td><td>11528</td><td>10519</td></tr><tr><td>R<sup>2</sup></td><td>0.811</td><td>0.792</td><td>0.776</td><td>0.881</td><td>0.894</td><td>0.491</td></tr><tr><td colspan="7" style="text-align: center;">Day third quartile</td></tr><tr><td>SS-1</td><td>-23.53<br>(44.88)</td><td>0.609<br>(1.025)</td><td>-1.199<br>(1.120)</td><td>1.936<br>(1.162)</td><td>0.781<br>(1.540)</td><td>-0.101<br>(0.354)</td></tr><tr><td>S</td><td>14.22<br>(29.58)</td><td>-0.354<br>(1.387)</td><td>0.238<br>(1.995)</td><td>-2.364<br>(1.611)</td><td>-0.0149<br>(1.585)</td><td>0.227<br>(0.389)</td></tr><tr><td>S+1</td><td>41.24<br>(39.48)</td><td>2.315*<br>(1.036)</td><td>2.493**<br>(0.886)</td><td>0.802<br>(1.241)</td><td>2.565<br>(2.590)</td><td>0.0478<br>(0.323)</td></tr><tr><td>S+2</td><td>-20.50<br>(30.28)</td><td>1.452<br>(1.223)</td><td>2.814<br>(2.509)</td><td>-0.399<br>(1.830)</td><td>2.892**<br>(1.053)</td><td>-0.312<br>(0.279)</td></tr><tr><td>Observations</td><td>9400</td><td>11028</td><td>10518</td><td>11118</td><td>11528</td><td>10519</td></tr><tr><td>R<sup>2</sup></td><td>0.820</td><td>0.792</td><td>0.776</td><td>0.873</td><td>0.908</td><td>0.530</td></tr></tbody></table>

Notes: All regressions are run at the date-city level as in Equation (1), and include date fixed effects and city-specific day-of-week, week-of-year fixed effects, and weather controls. Cluster-robust standard errors (robust to the presence of heteroskedasticity) are in parentheses. \*: p-value < 0.1,**: p-value < 0.05,**\*: p-value < 0.01
<table><caption>Table 20: Robustness when dropping periods marked by social movement (year 2010) for pollutants outcomes.</caption><thead><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th></tr></thead><tbody><tr><td colspan="7" style="text-align: center;">Day first quartile</td></tr><tr><td></td><td>CO</td><td>PM2.5</td><td>PM10</td><td>NO2</td><td>O3</td><td>SO2</td></tr><tr><td>S-1</td><td>6.438<br>(20.79)</td><td>0.348<br>(0.404)</td><td>0.813<br>(0.696)</td><td>0.800<br>(1.463)</td><td>-0.646<br>(1.245)</td><td>-0.360*<br>(0.169)</td></tr><tr><td>S</td><td>42.60***<br>(11.47)</td><td>1.045<br>(0.639)</td><td>1.944*<br>(0.916)</td><td>-0.828<br>(1.521)</td><td>0.885<br>(1.543)</td><td>-0.207<br>(0.135)</td></tr><tr><td>S+1</td><td>23.64<br>(20.67)</td><td>1.734**<br>(0.549)</td><td>1.508<br>(1.144)</td><td>-1.158<br>(1.667)</td><td>1.599<br>(2.730)</td><td>-0.193<br>(0.176)</td></tr><tr><td>S+2</td><td>13.61<br>(25.89)</td><td>1.988***<br>(0.572)</td><td>2.362***<br>(0.653)</td><td>-1.894**<br>(0.836)</td><td>1.922<br>(2.549)</td><td>-0.0877<br>(0.110)</td></tr><tr><td>Observations</td><td>8666</td><td>10586</td><td>10049</td><td>10678</td><td>11038</td><td>9968</td></tr><tr><td>R<sup>2</sup></td><td>0.778</td><td>0.778</td><td>0.756</td><td>0.855</td><td>0.852</td><td>0.458</td></tr><tr><td colspan="7" style="text-align: center;">Day median</td></tr><tr><td>S-1</td><td>4.633<br>(31.59)</td><td>0.807<br>(0.809)</td><td>0.163<br>(0.928)</td><td>0.116<br>(1.673)</td><td>0.393<br>(1.428)</td><td>-0.419**<br>(0.166)</td></tr><tr><td>S</td><td>40.39**<br>(15.46)</td><td>1.153<br>(0.733)</td><td>1.210<br>(1.684)</td><td>-0.751<br>(1.232)</td><td>0.658<br>(1.709)</td><td>0.272<br>(0.510)</td></tr><tr><td>S+1</td><td>35.40<br>(30.65)</td><td>2.186***<br>(0.623)</td><td>1.355<br>(1.418)</td><td>-0.532<br>(1.330)</td><td>1.814<br>(1.930)</td><td>-0.0465<br>(0.230)</td></tr><tr><td>S+2</td><td>-6.353<br>(27.39)</td><td>2.034**<br>(0.661)</td><td>2.731***<br>(0.817)</td><td>-1.528**<br>(0.646)</td><td>2.364<br>(1.635)</td><td>-0.158<br>(0.148)</td></tr><tr><td>Observations</td><td>8666</td><td>10586</td><td>10049</td><td>10678</td><td>11038</td><td>9968</td></tr><tr><td>R<sup>2</sup></td><td>0.829</td><td>0.793</td><td>0.782</td><td>0.881</td><td>0.887</td><td>0.481</td></tr><tr><td colspan="7" style="text-align: center;">Day third quartile</td></tr><tr><td>S-1</td><td>2.862<br>(39.30)</td><td>0.136<br>(1.230)</td><td>-0.703<br>(1.268)</td><td>2.166<br>(1.659)</td><td>3.124<br>(2.098)</td><td>-0.484**<br>(0.165)</td></tr><tr><td>S</td><td>34.05<br>(19.78)</td><td>0.656<br>(0.824)</td><td>0.150<br>(2.271)</td><td>-3.062<br>(2.060)</td><td>0.335<br>(1.747)</td><td>0.179<br>(0.579)</td></tr><tr><td>S+1</td><td>34.45<br>(55.18)</td><td>2.602***<br>(0.785)</td><td>1.511<br>(1.462)</td><td>-1.631<br>(1.610)</td><td>4.280*<br>(2.037)</td><td>0.101<br>(0.332)</td></tr><tr><td>S+2</td><td>-6.765<br>(30.29)</td><td>1.561**<br>(0.595)</td><td>4.090**<br>(1.673)</td><td>0.218<br>(1.428)</td><td>3.588**<br>(1.372)</td><td>-0.182<br>(0.260)</td></tr><tr><td>Observations</td><td>8666</td><td>10586</td><td>10049</td><td>10678</td><td>11038</td><td>9968</td></tr><tr><td>R<sup>2</sup></td><td>0.837</td><td>0.794</td><td>0.780</td><td>0.874</td><td>0.904</td><td>0.524</td></tr></tbody></table>

Notes: All regressions are run at the date-city level as in Equation (1), and include date fixed effects and city-specific day-of-week, week-of-year fixed effects, and weather controls. Cluster-robust standard errors (robust to the presence of heteroskedasticity) are in parentheses. \*: p-value < 0.1, \*: p-value < 0.05, \*: p-value < 0.01
## Liste des documents de travail de la Direction des Études et Synthèses Économiques

ii

G 9001 J. FAYOLLE et M. FLEURBAEY
Accumulation, profitabilité et endettement des entreprises

G 9020 G. OLIVEIRA-MARTINS, J. TOUJAS-BERNATE
Macro-economic import functions with imperfect competition - An application to the E.C. Trade

G 9002 H. ROUSSE
Détection et effets de la multicolinearité dans les modèles linéaires ordinaires - Un prolongement de la réflexion de BELSLEY, KUH et WELSCH

G 9003 P. RALLE et J. TOUJAS-BERNATE
Indexation des salaires : la rupture de 1983

G 9004 D. GUELLEC et P. RALLE
Compétitivité, croissance et innovation de produit

G 9005 P. RALLE et J. TOUJAS-BERNATE
Les conséquences de la désindexation. Analyse dans une maquette prix-salaires

G 9101 Équipe AMADEUS
Le modèle AMADEUS - Première partie -Présentation générale

G 9102 J.L. BRILLET
Le modèle AMADEUS - Deuxième partie -Propriétés variantielles

G 9103 D. GUELLEC et P. RALLE
Endogenous growth and product innovation

G 9104 H. ROUSSE
Le modèle AMADEUS - Troisième partie - Le commerce extérieur et l'environnement international

G 9105 H. ROUSSE
Effets de demande et d'offre dans les résultats du commerce extérieur manufacturé de la France au cours des deux dernières décennies

G 9106 B. CREPON
Innovation, taille et concentration : causalités et dynamiques

G 9107 B. AMABLE et D. GUELLEC
Un panorama des théories de la croissance endogène

G 9108 M. GLAUDE et M. MOUTARDIER
Une évaluation du coût direct de l'enfant de 1979 à 1989

G 9109 P. RALLE et alii
France - Allemagne : performances économiques comparées

G 9110 J.L. BRILLET
Micro-DMS NON PARU

G 9111 A. MAGNIER
Effets accélérateur et multiplicateur en France depuis 1970 : quelques résultats empiriques

G 9112 B. CREPON et G. DUREAU
Investissement en recherche-développement : analyse de causalités dans un modèle d'accélérateur généralisé

G 9113 J.L. BRILLET, H. ERKEL-ROUSSE, J. TOUJAS-BERNATE
"France-Allemagne Couplées" - Deux économies vues par une maquette macro-économétrique

G 9201 W.J. ADAMS, B. CREPON, D. ENCAOUA
Choix technologiques et stratégies de dissuasion d'entrée

G 9203 I. STAPIC
Les échanges internationaux de services de la France dans le cadre des négociations multila-érales du GATT
Juin 1992 (1ère version)
Novembre 1992 (version finale)

G 9204 P. SEVESTRE
L'économie sur données individuelles-temporelles. Une note introductive

G 9205 H. ERKEL-ROUSSE
Le commerce extérieur et l'environnement international dans le modèle AMADEUS (réestimation 1992)

G 9206 N. GREENAN et D. GUELLEC
Coordination within the firm and endogenous growth

G 9207 A. MAGNIER et J. TOUJAS-BERNATE
Technology and trade: empirical evidences for the major five industrialized countries

G 9208 B. CREPON, E. DUGUET, D. ENCAOUA et P. MOHNEN
Cooperative, non cooperative R & D and optimal patent life

G 9209 B. CREPON et E. DUGUET
Research and development, competition and innovation: an application of pseudo maximum likelihood methods to Poisson models with heterogeneity

G 9301 J. TOUJAS-BERNATE
Commerce international et concurrence impartie : développements récents et implications pour la politique commerciale

G 9302 Ch. CASES
Durées de chômage et comportements d'offre de travail : une revue de la littérature

G 9303 H. ERKEL-ROUSSE
Union économique et monétaire : le débat économique

G 9304 N. GREENAN - D. GUELLEC / G. BROUSSAUDIER - L. MIOTTI
Innovation organisationnelle, dynamisme technologique et performances des entreprises

G 9305 P. JAILLARD
Le traité de Maastricht : présentation juridique et historique

G 9306 J.L. BRILLET
Micro-DMS : présentation et propriétés

G 9307 J.L. BRILLET
Micro-DMS - variantes : les tableaux

G 9308 S. JACOBZONE
Les grands réseaux publics français dans une perspective européenne

G 9309 L. BLOCH - B. CŒURÉ
Profitabilité de l'investissement productif et transmission des chocs financiers

G 9310 J. BOURDIEU - B. COLIN-SEDILLOT
Les théories sur la structure optimale du capital : quelques points de repère

G 9311 J. BOURDIEU - B. COLIN-SEDILLOT
Les décisions de financement des entreprises françaises : une évaluation empirique des théories de la structure optimale du capital

G 9312 L. BLOCH - B. CŒURÉ
Q de Tobin marginal et transmission des chocs financiers

G 9313 Équipes Adameus (INSEE), Banque de France, Métric (DP)
Présentation des propriétés des principaux modèles macroéconomiques du Service Public

G 9314 B. CREPON - E. DUGUET
Research & Development, competition and innovation

G 9315 B. DORMONT
Quelle est l'influence du coût du travail sur l'emploi ?

G 9316 D. BLANCHET - C. BROUSSE
Deux études sur l'âge de la retraite

G 9317 D. BLANCHET
Répartition du travail dans une population hétérogène : deux notes

G 9318 D. EYSSARTIER - N. PONTY
AMADEUS - an annual macro-economic model for the medium and long term

G 9319 G. CETTE - Ph. CUNÉO - D. EYSSARTIER
-J. GAUTIÉ
Les effets sur l'emploi d'un abaissement du coût du travail des jeunes

G 9401 D. BLANCHET
Les structures par âge importent-elles ?

G 9402 J. GAUTIÉ
Le chômage des jeunes en France : problème de formation ou phénomène de file d'attente ? Quelques éléments du débat

G 9403 P. QUIRION
Les déchets en France : éléments statistiques et économiques

G 9404 D. LADIRAY - M. GRUN-REHOMME
Lissage par moyennes mobiles - Le problème des extrémités de série

G 9405 V. MAILLARD
Théorie et pratique de la correction des effets de jours ouvrables

G 9406 F. ROSENWALD
La décision d'investir

G 9407 S. JACOBZONE
Les apports de l'économie industrielle pour définir la stratégie économique de l'hôpital public

G 9408 L. BLOCH, J. BOURDIEU, B. COLIN-SEDILLOT, G. LONGUEVILLE
Du défaut de paiement au dépôt de bilan : les banquiers face aux PME en difficulté

G 9409 D. EYSSARTIER, P. MAIRE
Impacts macro-économiques de mesures d'aide au logement - quelques éléments d'évaluation

G 9410 F. ROSENWALD
Suivi conjoncturel de l'investissement

G 9411 C. DEFEUILLEY - Ph. QUIRION
Les déchets d'emballages ménagers : une analyse économique des politiques française et allemande

G 9412 J. BOURDIEU - B. CŒURÉ - B. COLIN-SEDILLOT
Investissement, incertitude et irréversibilité
Quelques développements récents de la théorie de l'investissement

G 9413 B. DORMONT - M. PAUCHET
L'évaluation de l'elasticité emploi-salaire dépend-elle des structures de qualification ?

G 9414 I. KABLA
Le Choix de breveter une invention

G 9501 J. BOURDIEU - B. CŒURÉ - B. SEDILLOT
Irreversible Investment and Uncertainty: When is there a Value of Waiting?

G 9502 L. BLOCH - B. CŒURÉ
Imperfections du marché du crédit, investisse-ment des entreprises et cycle économique

G 9503 D. GOUX - E. MAURIN
Les transformations de la demande de travail par qualification en France
Une étude sur la période 1970-1993

G 9504 N. GREENAN
Technologie, changement organisationnel, qua-ifications et emploi : une étude empirique sur l'industrie manufacturière

G 9505 D. GOUX - E. MAURIN
Persistence des hiérarchies sectorielles de sa-laires: un réexamen sur données françaises

G 9505 Bis
D. GOUX - E. MAURIN
Persistence of inter-industry wages differentials: a reexamination on matched worker-firm panel data

G 9506 S. JACOBZONE
Les liens entre RMI et chômage, une mise en perspective
NON PARU - article sorti dans Économie et Prévision n° 122 (1996) - pages 95 à 113

G 9507 G. CETTE - S. MAHFOUZ
Le partage primaire du revenu
Constat descriptif sur longue période

G 9601 Banque de France - CEPREMAP - Direction de la Prévision - Érasme - INSEE - OFCE
Structures et propriétés de cinq modèles macro-économiques français

G 9602 Rapport d'activité de la DESE de l'année 1995

G 9603 J. BOURDIEU - A. DRAZNIEKS
L'octroi de crédit aux PME : une analyse à partir d'informations bancaires

G 9604 A. TOPIOL-BENSAÏD
Les implantations japonaises en France

G 9605 P. GENIER - S. JACOBZONE
Comportements de prévention, consommation d'alcool et tabagie : peut-on parler d'une gestion globale du capital santé ?
Une modélisation microéconométrique empirique
<table>
  <tbody>
    <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>
    <tr>
      <td>G 9608</td>
      <td>N. GREENAN - D. GUELLEC<br>Technological innovation and employment reallocation</td>
    </tr>
    <tr>
      <td>G 9609</td>
      <td>Ph. COUR - F. RUPPRECHT<br>L'intégration asymétrique au sein du continent américain : un essai de modélisation</td>
    </tr>
    <tr>
      <td>G 9610</td>
      <td>S. DUCHENE - G. FORGEOT - A. JACQUOT<br>Analyse des évolutions récentes de la productivité apparente du travail</td>
    </tr>
    <tr>
      <td>G 9611</td>
      <td>X. BONNET - S. MAHFOUZ<br>The influence of different specifications of wages-prices spirals on the measure of the NAIRU: the case of France</td>
    </tr>
    <tr>
      <td>G 9612</td>
      <td>PH. COUR - E. DUBOIS, S. MAHFOUZ, J. PISANI-FERRY<br>The cost of fiscal retrenchment revisited: how strong is the evidence?</td>
    </tr>
    <tr>
      <td>G 9613</td>
      <td>A. JACQUOT<br>Les flexions des taux d'activité sont-elles seulement conjoncturelles ?</td>
    </tr>
    <tr>
      <td>G 9614</td>
      <td>ZHANG Yingxiang - SONG Xueqing<br>Lexique macroéconomique Français-Chinois</td>
    </tr>
    <tr>
      <td>G 9617</td>
      <td>J.L. SCHNEIDER<br>La taxe professionnelle : éléments de cadrage économique</td>
    </tr>
    <tr>
      <td>G 9618</td>
      <td>J.L. SCHNEIDER<br>Transition et stabilité politique d'un système redistributif</td>
    </tr>
    <tr>
      <td>G 9619</td>
      <td>D. GOUX - E. MAURIN<br>Train or Pay: Does it Reduce Inequalities to Encourage Firms to Train their Workers?</td>
    </tr>
    <tr>
      <td>G 9620</td>
      <td>P. GENIER<br>Deux contributions sur dépendance et équité</td>
    </tr>
    <tr>
      <td>G 9621</td>
      <td>E. DUGUET - N. IUNG<br>R & D Investment, Patent Life and Patent Value<br>An Econometric Analysis at the Firm Level</td>
    </tr>
    <tr>
      <td>G 9622</td>
      <td>M. HOUDEBINE - A. TOPIOL-BENSAÎD<br>Les entreprises internationales en France : une analyse à partir de données individuelles</td>
    </tr>
    <tr>
      <td>G 9623</td>
      <td>M. HOUDEBINE<br>Polarisation des activités et spécialisation des départements en France</td>
    </tr>
    <tr>
      <td>G 9624</td>
      <td>E. DUGUET - N. GREENAN<br>Le biais technologique : une analyse sur données individuelles</td>
    </tr>
    <tr>
      <td>G 9625</td>
      <td>J.L. BRILLET<br>Analyzing a small French ECM Model</td>
    </tr>
    <tr>
      <td>G 9626</td>
      <td>J.L. BRILLET<br>Formalizing the transition process: scenarios for capital accumulation</td>
    </tr>
    <tr>
      <td>G 9627</td>
      <td>G. FORGEOT - J. GAUTIÉ<br>Insertion professionnelle des jeunes et proces-sus de déclassement</td>
    </tr>
  </tbody>
</table>

<table>
  <tbody>
    <tr>
      <td>G 9712</td>
      <td>E. DUBOIS<br>High Real Interest Rates: the Consequence of a Saving Investment Disequilibrium or of an insufficient Credibility of Monetary Authorities?</td>
    </tr>
    <tr>
      <td>G 9713</td>
      <td>Bilan des activités de la Direction des Études et Synthèses Économiques - 1996</td>
    </tr>
    <tr>
      <td>G 9714</td>
      <td>F. LEQUILLER<br>Does the French Consumer Price Index Overstate Inflation?</td>
    </tr>
    <tr>
      <td>G 9715</td>
      <td>X. BONNET<br>Peut-on mettre en évidence les rigidités à la baisse des salaires nominaux ?<br>Une étude sur quelques grands pays de l'OCDE</td>
    </tr>
    <tr>
      <td>G 9716</td>
      <td>N. IUNG - F. RUPPRECHT<br>Productivité de la recherche et rendements d'échelle dans le secteur pharmaceutique français</td>
    </tr>
    <tr>
      <td>G 9717</td>
      <td>E. DUGUET - I. KABLA<br>Appropriation strategy and the motivations to use the patent system in France - An econometric analysis at the firm level</td>
    </tr>
    <tr>
      <td>G 9718</td>
      <td>L.P. PELÉ - P. RALLE<br>Âge de la retraite : les aspects incitatifs du ré-gime général</td>
    </tr>
    <tr>
      <td>G 9719</td>
      <td>ZHANG Yingxiang - SONG Xueqing<br>Lexique macroéconomique français-chinois, chinois-français</td>
    </tr>
    <tr>
      <td>G 9720</td>
      <td>M. HOUDEBINE - J.L. SCHNEIDER<br>Mesurer l'influence de la fiscalité sur la locali-sation des entreprises</td>
    </tr>
    <tr>
      <td>G 9721</td>
      <td>A. MOUROUGANE<br>Crédibilité, indépendance et politique monétaire<br>Une revue de la littérature</td>
    </tr>
    <tr>
      <td>G 9722</td>
      <td>P. AUGERAUD - L. BRIOT<br>Les données comptables d'entreprises<br>Le système intermédiaire d'entreprises<br>Passage des données individuelles aux données sectorielles</td>
    </tr>
    <tr>
      <td>G 9723</td>
      <td>P. AUGERAUD - J.E. CHAPRON<br>Using Business Accounts for Compiling National Accounts: the French Experience</td>
    </tr>
    <tr>
      <td>G 9724</td>
      <td>P. AUGERAUD<br>Les comptes d'entreprise par activités - Le pas-sage aux comptes - De la comptabilité d'entreprise à la comptabilité nationale - A paraitre</td>
    </tr>
    <tr>
      <td>G 9801</td>
      <td>H. MICHAUDON - C. PRIGENT<br>Présentation du modèle AMADEUS</td>
    </tr>
    <tr>
      <td>G 9802</td>
      <td>J. ACCARDO<br>Une étude de comptabilité générationnelle pour la France en 1996</td>
    </tr>
    <tr>
      <td>G 9803</td>
      <td>X. BONNET - S. DUCHÈNE<br>Apports et limites de la modélisation « Real Business Cycles »</td>
    </tr>
    <tr>
      <td>G 9804</td>
      <td>C. BARLET - C. DUGUET - D. ENCAOUA - J. PRADEL<br>The Commercial Success of Innovations<br>An econometric analysis at the firm level in French manufacturing</td>
    </tr>
  </tbody>
</table>

<table>
  <tbody>
    <tr>
      <td>G 9805</td>
      <td>P. CAHUC - Ch. GIANELLA - D. GOUX - A. ZILBERBERG<br>Equalizing Wage Differences and Bargaining Power - Evidence form a Panel of French Firms</td>
    </tr>
    <tr>
      <td>G 9806</td>
      <td>J. ACCARDO - M. JLASSI<br>La productivité globale des facteurs entre 1975 et 1996</td>
    </tr>
    <tr>
      <td>G 9807</td>
      <td>Bilan des activités de la Direction des Études et Synthèses Économiques - 1997</td>
    </tr>
    <tr>
      <td>G 9808</td>
      <td>A. MOUROUGANE<br>Can a Conservative Governor Conduct an Ac-comodative Monetary Policy?</td>
    </tr>
    <tr>
      <td>G 9809</td>
      <td>X. BONNET - E. DUBOIS - L. FAUVET<br>Asymétrie des inflations relatives et menus costs : tests sur l'inflation française</td>
    </tr>
    <tr>
      <td>G 9810</td>
      <td>E. DUGUET - N. IUNG<br>Sales and Advertising with Spillovers at the firm level: Estimation of a Dynamic Structural Model on Panel Data</td>
    </tr>
    <tr>
      <td>G 9811</td>
      <td>J.P. BERTHIER<br>Congestion urbaine : un modèle de trafic de pointe à courbe débit-vitesse et demande élastique</td>
    </tr>
    <tr>
      <td>G 9812</td>
      <td>C. PRIGENT<br>La part des salaires dans la valeur ajoutée : une approche macroéconomique</td>
    </tr>
    <tr>
      <td>G 9813</td>
      <td>A.Th. AERTS<br>L'évolution de la part des salaires dans la valeur ajoutée en France reflète-t-elle les évolutions individuelles sur la période 1979-1994 ?</td>
    </tr>
    <tr>
      <td>G 9814</td>
      <td>B. SALANIÉ<br>Guide pratique des séries non-stationnaires</td>
    </tr>
    <tr>
      <td>G 9901</td>
      <td>S. DUCHÈNE - A. JACQUOT<br>Une croissance plus riche en emplois depuis le début de la décennie ? Une analyse en compa-raison internationale</td>
    </tr>
    <tr>
      <td>G 9902</td>
      <td>Ch. COLIN<br>Modélisation des carrières dans Destinie</td>
    </tr>
    <tr>
      <td>G 9903</td>
      <td>Ch. COLIN<br>Évolution de la dispersion des salaires : un essai de prospective par microsimulation</td>
    </tr>
    <tr>
      <td>G 9904</td>
      <td>B. CREPON - N. IUNG<br>Innovation, emploi et performances</td>
    </tr>
    <tr>
      <td>G 9905</td>
      <td>B. CREPON - Ch. GIANELLA<br>Wages inequalities in France 1969-1992<br>An application of quantile regression techniques</td>
    </tr>
    <tr>
      <td>G 9906</td>
      <td>C. BONNET - R. MAHIEU<br>Microsimulation techniques applied to inter-generational transfers - Pensions in a dynamic framework: the case of France</td>
    </tr>
    <tr>
      <td>G 9907</td>
      <td>F. ROSENWALD<br>L'impact des contraintes financières dans la décision d'investissement</td>
    </tr>
    <tr>
      <td>G 9908</td>
      <td>Bilan des activités de la DESE - 1998</td>
    </tr>
    <tr>
      <td>G 9909</td>
      <td>J.P. ZOYEM<br>Contrat d'insertion et sortie du RMI<br>Évaluation des effets d'une politique sociale</td>
    </tr>
    <tr>
      <td>G 9910</td>
      <td>Ch. COLIN - FI. LEGROS - R. MAHIEU<br>Bilans contributifs comparés des régimes de</td>
    </tr>
  </tbody>
</table>

<table>
  <tbody>
    <tr>
      <td>G 9911</td>
      <td>G. LAROQUE - B. SALANIÉ<br>Une décomposition du non-emploi en France</td>
    </tr>
    <tr>
      <td>G 9912</td>
      <td>B. SALANIÉ<br>Une maquette analytique de long terme du marché du travail</td>
    </tr>
    <tr>
      <td>G 9912<br>Bis</td>
      <td>Ch. GIANELLA<br>Une estimation de l'élasticité de l'emploi peu qualifié à son coût</td>
    </tr>
    <tr>
      <td>G 9913</td>
      <td>Division « Redistribution et Politiques Sociales »<br>Le modèle de microsimulation dynamique DESTINIE</td>
    </tr>
    <tr>
      <td>G 9914</td>
      <td>E. DUGUET<br>Macro-commandes SAS pour l'économétrie des panels et des variables qualitatives</td>
    </tr>
    <tr>
      <td>G 9915</td>
      <td>R. DUHAUTOIS<br>Évolution des flux d'emplois en France entre 1990 et 1996 : une étude empirique à partir du fichier des bénéfices réels normaux (BRN)</td>
    </tr>
    <tr>
      <td>G 9916</td>
      <td>J.Y. FOURNIER<br>Extraction du cycle des affaires : la méthode de Baxter et King</td>
    </tr>
    <tr>
      <td>G 9917</td>
      <td>B. CRÉPON - R. DESPLATZ - J. MAIRESSE<br>Estimating price cost margins, scale econo mies and workers' bargaining power at the firm level</td>
    </tr>
    <tr>
      <td>G 9918</td>
      <td>Ch. GIANELLA - Ph. LAGARDE<br>Productivity of hours in the aggregate production function: an evaluation on a panel of French firms from the manufacturing sector</td>
    </tr>
    <tr>
      <td>G 9919</td>
      <td>S. AUDRIC - P. GIVORD - C. PROST<br>Évolution de l'emploi et des coûts par qual-fication entre 1982 et 1996</td>
    </tr>
    <tr>
      <td>G 2000/01</td>
      <td>R. MAHIEU<br>Les déterminants des dépenses de santé : une approche macroéconomique</td>
    </tr>
    <tr>
      <td>G 2000/02</td>
      <td>C. ALLARD-PRIGENT - H. GUILMEAU - A. QUINET<br>The real exchange rate as the relative price of nontrables in terms of tradables: theoretical investigation and empirical study on French data</td>
    </tr>
    <tr>
      <td>G 2000/03</td>
      <td>J.-Y. FOURNIER<br>L'approximation du filtre passe-bande proposée par Christiano et Fitzgerald</td>
    </tr>
    <tr>
      <td>G 2000/04</td>
      <td>Bilan des activités de la DESE - 1999</td>
    </tr>
    <tr>
      <td>G 2000/05</td>
      <td>B. CREPON - F. ROSENWALD<br>Investissement et contraintes de financement : le poids du cycle<br>Une estimation sur données françaises</td>
    </tr>
    <tr>
      <td>G 2000/06</td>
      <td>A. FLIPO<br>Les comportements matrimoniaux de fait</td>
    </tr>
    <tr>
      <td>G 2000/07</td>
      <td>R. MAHIEU - B. SÉDILLOT<br>Microsimulations of the retirement decision: a supply side approach</td>
    </tr>
    <tr>
      <td>G 2000/08</td>
      <td>C. AUDENIS - C. PROST<br>Déficit conjoncturel : une prise en compte des conjonctures passées</td>
    </tr>
    <tr>
      <td>G 2000/09</td>
      <td>R. MAHIEU - B. SÉDILLOT<br>Équivalent patrimonial de la rente et souscription de retraite complémentaire</td>
    </tr>
  </tbody>
</table>
G 2000/10 R. DUHAUTOIS
Ralentissement de l'investissement : petites ou grandes entreprises ? industrie ou tertiaire ?

G 2000/11 G. LAROQUE - B. SALANIÉ
Temps partiel féminin et incitations financières à l'emploi

G 2000/12 Ch. GIANELLA
Local unemployment and wages

G 2000/13 B. CREPON - Th. HECKEL
- Informatisation en France : une évaluation à partir de données individuelles
- Computerization in France: an evaluation based on individual company data

G 2001/01 F. LEQUILLER
- La nouvelle économie et la mesure de la croissance du PIB
- The new economy and the measure ment of GDP growth

G 2001/02 S. AUDRIC
La reprise de la croissance de l'emploi profite-t- elle aussi aux non-diplômés ?

G 2001/03 I. BRAUN-LEMAIRE
Évolution et répartition du surplus de productivité

G 2001/04 A. BEAUDU - Th. HECKEL
Le canal du crédit fonctionne-t-il en Europe ? Une étude de l'hétérogénéité des com portements d'investissement à partir de données de bilan agréées

G 2001/05 C. AUDENIS - P. BISCOURP - N. FOURCADE - O. LOISEL
Testing the augmented Solow growth model: An empirical reassessment using panel data

G 2001/06 R. MAHIEU - B. SÉDILLOT
Départ à la retraite, irréversibilité et incertitude

G 2001/07 Bilan des activités de la DESE - 2000

G 2001/08 J. Ph. GAUDEMET
Les dispositifs d'acquisition à titre facultatif d'annuités viagères de retraite

G 2001/09 B. CRÉPON - Ch. GIANELLA
Fiscalité, coût d'usage du capital et demande de facteurs : une analyse sur données individuelles

G 2001/10 B. CRÉPON - R. DESPLATZ
Évaluation des effets des dispositifs d'allégements de charges sociales sur les bas salaires

G 2001/11 J.-Y. FOURNIER
Comparaison des salaires des secteurs public et privé

G 2001/12 J.-P. BERTHIER - C. JAULENT
R. CONVENEVOLE - S. PISANI
Une méthodologie de comparaison entre consommations intermédiaires de source fiscale et de comptabilité nationale

G 2001/13 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

G 2001/14 I. ROBERT-BOBEE
Modelling demographic behaviours in the French

microsimulation model Destinie: An analysis of future change in completed fertility

G 2001/15 J.-P. ZOYEM
Diagnostic sur la pauvreté et calendrier de revenus : le cas du "Panel européen des ménages »

G 2001/16 J.-Y. FOURNIER - P. GIVORD
La réduction des taux d'activité aux âges extrêmes, une spécificité française ?

G 2001/17 C. AUDENIS - P. BISCOURP - N. RIEDINGER
Existe-t-il une asymétrie dans la transmission du prix du brut aux prix des carburants ?

G 2002/01 F. MAGNIEN - J.-L. TAVERNIER - D. THESMAR
Les statistiques internationales de PIB par habitant en standard de pouvoir d'achat : une analyse des résultats

G 2002/02 Bilan des activités de la DESE - 2001

G 2002/03 B. SÉDILLOT - E. WALRAET
La cessation d'activité au sein des couples : y a-t-il interdépendance des choix ?

G 2002/04 G. BRILHAULT
- Rétropolation des séries de FBCF et calcul du capital fixe en SEC-95 dans les comptes nationaux français
- Retropolation of the investment series (GFCF) and estimation of fixed capital stocks on the ESA-95 basis for the French balance sheets

G 2002/05 P. BISCOURP - B. CRÉPON - T. HECKEL - N. RIEDINGER
How do firms respond to cheaper computers? Microeconometric evidence for France based on a production function approach

G 2002/06 C. AUDENIS - J. DER OYON - N. FOURCADE
L'impact des nouvelles technologies de l'information et de la communication sur l'économie française - un bouclage macro-économique

G 2002/07 J. BARDAJI - B. SÉDILLOT - E. WALRAET
Évaluation de trois réformes du Régime Général d'assurance vieillesse à l'aide du modèle de microsimulation DESTINIE

G 2002/08 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

G 2002/09 F. HILD
Les soldes d'opinion résument-ils au mieux les réponses des entreprises aux enquêtes de conjoncture ?

G 2002/10 I. ROBERT-BOBÉE
Les comportements démographiques dans le modèle de microsimulation Destinie - Une comparaison des estimations issues des enquêtes Jeunes et Carrières 1997 et Histoire Familielle 1999

G 2002/11 J.-P. ZOYEM
La dynamique des bas revenus : une analyse des entrées-sorties de pauvreté

G 2002/12 F. HILD
Prévisions d'inflation pour la France

G 2002/13 M. LECLAIR
Réduction du temps de travail et tensions sur les facteurs de production

G 2002/14 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

G 2002/15 P. CHONE - D. LE BLANC - I. ROBERT-BOBEE
Offre de travail féminine et garde des jeunes enfants

G 2002/16 F. MAUREL - S. GREGOIR
Les indices de compétitivité des pays : inter-prétation et limites

G 2003/01 N. RIEDINGER - E. HAUVY
Le coût de dépollution atmosphérique pour les entreprises françaises : Une estimation à partir de données individuelles

G 2003/02 P. BISCOURP et F. KRAMARZ
Création d'emplois, destruction d'emplois et internationalisation des entreprises industrielles françaises : une analyse sur la période 1986-1992

G 2003/03 Bilan des activités de la DESE - 2002

G 2003/04 P.-O. BEFFY - J. DER OYON - N. FOURCADE - S. GREGOIR - N. LAÎB - B. MONFORT
Évolutions démographiques et croissance : une projection macro-économique à l'horizon 2020

G 2003/05 P. AUBERT
La situation des salariés de plus de cinquante ans dans le secteur privé

G 2003/06 P. AUBERT - B. CRÉPON
Age, salaire et productivité
La productivité des salariés décline-t-elle en fin de carrière ?

G 2003/07 H. BARON - P.O. BEFFY - N. FOURCADE - R. MAHIEU
Le ralentissement de la productivité du travail au cours des années 1990

G 2003/08 P.-O. BEFFY - B. MONFORT
Patrimoine des ménages, dynamique d'allocation et comportement de consommation

G 2003/09 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

G 2003/10 M. LECLAIR - P. PETIT
Présence syndicale dans les firmes : quel impact sur les inégalités salariales entre les hommes et les femmes ?

G 2003/11 P.-O. BEFFY - X. BONNET - M. DARRACQ-PARIES - B. MONFORT
MZE: a small macro-model for the euro area

G 2004/01 P. AUBERT - M. LECLAIR
La compétitivité exprimée dans les enquêtes trimestrielles sur la situation et les perspectives dans l'industrie

G 2004/02 M. DUÉE - C. REBILLARD
La dépendance des personnes âgées : une projection à long terme

G 2004/03 S. RASPILLER - N. RIEDINGER
Régulation environnementale et choix de localisation des groupes français

G 2004/04 A. NABOULET - S. RASPILLER
Les déterminants de la décision d'investir : une approche par les perceptions subjectives des firmes

G 2004/05 N. RAGACHE
La déclaration des enfants par les couples non mariés est-elle fiscalement optimale ?

G 2004/06 M. DUÈE
L'impact du chômage des parents sur le devenir scolaire des enfants

G 2004/07 P. AUBERT - E. CAROLI - M. ROGER
New Technologies, Workplace Organisation and the Age Structure of the Workforce: Firm-Level Evidence

G 2004/08 E. DUGUET - C. LELARGE
Les brevets accroissent-ils les incitations privées à innover ? Un examen microéconométrique

G 2004/09 S. RASPILLER - P. SILLARD
Affiliating versus Subcontracting: the Case of Multinationals

G 2004/10 J. BOISSINOT - C. L'ANGEVIN - B. MONFORT
Public Debt Sustainability: Some Results on the French Case

G 2004/11 S. ANANIAN - P. AUBERT
Travailleurs âgés, nouvelles technologies et changements organisationnels : un réexamen à partir de l'enquête « REPONSE »

G 2004/12 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

G 2004/13 C. PICART
Évaluer la rentabilité des sociétés non financières

G 2004/14 J. BARDAJI - B. SÉDILLOT - E. WALRAET
Les retraites du secteur public : projections à l'horizon 2040 à l'aide du modèle de microsimulation DESTINIE

G 2005/01 S. BUFFETEAU - P. GODEFROY
Conditions de départ en retraite selon l'âge de fin d'études : analyse prospective pour les générations 1945 à 1974

G 2005/02 C. AFSA - S. BUFFETEAU
L'évolution de l'activité féminine en France : une approche par pseudo-panel

G 2005/03 P. AUBERT - P. SILLARD
Délocalisations et réductions d'effectifs dans l'industrie française

G 2005/04 M. LECLAIR - S. ROUX
Mesure et utilisation des emplois instables dans les entreprises

G 2005/05 C. L'ANGEVIN - S. SERRAVALLE
Performances à l'exportation de la France
et de l'Allemagne - Une analyse par secteur et
destination géographique

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

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

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

G2005/09 N. FERRARI
Prévoir l'investissement des entreprises
Un indicateur des révisions dans l'enquête de
conjoncture sur les investissements dans
l'industrie

G2005/10 P.-O. BEFFY - C. L'ANGEVIN
Chômage et boucle prix-salaires :
apport d'un modèle « qualifiés/peu qualifiés »

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

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

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

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

G2005/15 M. DUÈE
La modélisation des comportements démographiques dans le modèle de microsimulation
DESTINIE

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

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

G2006/02 C. PICART
Les gazelles en France

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

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

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

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

G2006/07 C. AFSA - P. GIVORD

Le rôle des conditions de travail dans les
absences pour maladie

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

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

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

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

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

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

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

G2006/15 L. GONZALEZ - C. PICART
Diversification, 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 croissance potentielle à long
terme

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

G2009/11 V. BELLAMY - G. CONSALES - M. FESSEAU -
S. LE LAIDIER - É. RAYNAUD

Une décomposition du compte des ménages de
la comptabilité nationale par catégorie de
ménage en 2003

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

G2009/13 R. AEBERHARDT - D. FOUGÈRE -
R. RATHELOT

Discrimination à l'embauche : comment exploiter
les procédures de testing ?

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

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

G2010/01 C. MINODIER
Avantages comparés des séries des premières
valeurs publiées et des séries des valeurs
révisées - Un exercice de prévision en temps
réel

de la croissance trimestrielle du PIB en France

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

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

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

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

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

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

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

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

G2010/10 I. BUONO - G. LALANNE
La réaction des entreprises françaises à la baisse des tarifs douaniers étrangers

G2010/11 R. RATHELOT - P. SILLARD
L'apport des méthodes à noyaux pour mesurer la concentration géographique - Application à la concentration des immigrés en France de 1968 à 1999

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

G2012/06 P. AUBERT - M. BACHELET
Disparités de montant de pension et redistribution dans le système de retraite français

G2012/07 R. AEBERHARDT - P. GIVORD - C. MARBOT
Spillover Effect of the Minimum Wage in France: An Unconditional Quantile Regression Approach

G2012/08 A. EIDELMAN - F. LANGUMIER - A. VICARD
Prélèvements obligatoires reposant sur les ménages : des canaux redistributifs différents en 1990 et 2010

G2012/09 O. BARGAIN - A. VICARD
Le RMI et son successeur le RSA découragent-ils certains jeunes de travailler ? Une analyse sur les jeunes autour de 25 ans

G2012/10 C. MARBOT - D. ROY
Projections du coût de l'APA et des caractéristiques de ses bénéficiaires à l'horizon 2040 à l'aide du modèle Destinie

G2012/11 A. MAUROUX
Le crédit d'impôt dédié au développement durable : une évaluation économique

G2012/12 V. COTTET - S. QUANTIN - V. RÉGNIER
Coût du travail et allègements de charges : une estimation au niveau établissement de 1996 à 2008

G2012/13 X. D'HAULTFOEUILLE - P. FÉVRIER - L. WILNER
Demand Estimation in the Presence of Revenue Management

G2012/14 D. BLANCHET - S. LE MINEZ
Joint macro/micro evaluations of accrued-to-date pension liabilities: an application to French reforms

G2013/01-F1301
T. DEROYON - A. MONTAUT - P-A PIONNIER
Utilisation rétrospective de l'enquête Emploi à une fréquence mensuelle : apport d'une modélisation espace-état

G2013/02-F1302
C. TREVIEN
Habiter en HLM : quel avantage monétaire et quel impact sur les conditions de logement ?

G2013/03 A. POISSONNIER
Temporal disaggregation of stock variables - The Chow-Lin method extended to dynamic models

G2013/04 P. GIVORD - C. MARBOT
Does the cost of child care affect female labor market participation? An evaluation of a French reform of childcare subsidies

G2013/05 G. LAME - M. LEQUIEN - P.-A. PIONNIER
Interpretation and limits of sustainability tests in public finance

G2013/06 C. BELLEGO - V. DORTET-BERNADET
La participation aux pôles de compétitivité : quelle incidence sur les dépenses de R&D et l'activité des PME et ETI ?

G2013/07 P.-Y. CABANNES - A. MONTAUT - P.-A. PIONNIER
Évaluer la productivité globale des facteurs en France : l'apport d'une mesure de la qualité du capital et du travail

G2013/08 R. AEBERHARDT - C. MARBOT
Evolution of Instability on the French Labour Market During the Last Thirty Years

G2013/09 J-B. BERNARD - G. CLÉAUD
Oil price: the nature of the shocks and the impact on the French economy

G2013/10 G. LAME
Was there a « Greenspan Conundrum » in the Euro area?

G2013/11 P. CHONE - F. EVAIN - L. WILNER - E. YILMAZ
Introducing activity-based payment in the hospital industry : Evidence from French data

G2013/12 C. GRISLAIN-LETRÉMY
Natural Disasters: Exposure and Underinsurance

G2013/13 P.-Y. CABANNES - V. COTTET - Y. DUBOIS - C. LELARGE - M. SICSIC
French Firms in the Face of the 2008/2009 Crisis

G2013/14 A. POISSONNIER - D. ROY
Households Satellite Account for France in 2010. Methodological issues on the assessment of domestic production

G2013/15 G. CLÉAUD - M. LEMOINE - P.-A. PIONNIER
Which size and evolution of the government expenditure multiplier in France (1980-2010)?

G2014/01 M. BACHELET - A. LEDUC - A. MARINO
Les biographies du modèle Destinie II : rebasage et projection

G2014/02 B. GARBINTI
L'achat de la résidence principale et la création d'entreprises sont-ils favorisés par les donations et héritages ?

G2014/03 N. CECI-RENAUD - P. CHARNOZ - M. GAINI
Évolution de la volatilité des revenus salariaux du secteur privé en France depuis 1968

G2014/04 P. AUBERT
Modalités d'application des réformes des retraites et prévisibilité du montant de pension

G2014/05 C. GRISLAIN-LETRÉMY - A. KATOSSKY
The Impact of Hazardous Industrial Facilities on Housing Prices: A Comparison of Parametric and Semiparametric Hedonic Price Models

G2014/06 J.-M. DAUSSIN-BENICHOU - A. MAUROUX
Turning the heat up. How sensitive are households to fiscal incentives on energy efficiency investments?

G2014/07 C. LABONNE - G. LAMÉ
Credit Growth and Capital Requirements: Binding or Not?

G2014/08 C. GRISLAIN-LETRÉMY et C. TREVIEN
The Impact of Housing Subsidies on the Rental Sector: the French Example

G2014/09 M. LEQUIEN et A. MONTAUT
Croissance potentielle en France et en zone euro: un tour d'horizon des méthodes d'estimation

G2014/10 B. GARBINTI - P. LAMARCHE
Les hauts revenus épargnent-ils davantage ?

G2014/11 D. AUDENAERT - J. BARDAJI - L. LARDEUX - M. ORAND - M. SICSIC
Wage Resilience in France since the Great Recession
G2014/12 F. ARNAUD - J. BOUSSARD - A. POISSONNIER - H. SOUAL
Computing additive contributions to growth and other issues for chain-linked quarterly aggregates

G2014/13 H. FRAISSE - F. KRAMARZ - C. PROST
Labor Disputes and Job Flows

G2014/14 P. GIVORD - C. GRISLAIN-LETRÉMY - H. NAEGELE
How does fuel taxation impact new car purchases? An evaluation using French consumer-level dataset

G2014/15 P. AUBERT - S. RABATÉ
Durée passée en carrière et durée de vie en retraite : quel partage des gains d'espérance de vie ?

G2015/01 A. POISSONNIER
The walking dead Euler equation
Addressing a challenge to monetary policy models

G2015/02 Y. DUBOIS - A. MARINO
Indicateurs de rendement du système de retraite français

G2015/03 T. MAYER - C. TREVIEN
The impacts of Urban Public Transportation: Evidence from the Paris Region

G2015/04 S.T. LY - A. RIEGERT
Measuring Social Environment Mobility

G2015/05 M. A. BEN HALIMA - V. HYAFIL-SOLELHAC
M. KOUBI - C. REGAERT
Quel est l'impact du système d'indemnisation maladie sur la durée des arrêts de travail pour maladie ?

G2015/06 Y. DUBOIS - A. MARINO
Disparités de rendement du système de retraite dans le secteur privé : approches intergénérationnelle et intragénérationnelle

G2015/07 B. CAMPAGNE - V. ALHENC-GELAS - J.-B. BERNARD
No evidence of financial accelerator in France

G2015/08 Q. LAFFÉTER - M. PAK
Elasticités des recettes fiscales au cycle économique : étude de trois impôts sur la période 1979-2013 en France

G2015/09 J.-M. DAUSSIN-BENICHOU, S. IDMACHICHE, A. LEDUC et E. POULIQUEN
Les déterminants de l'attractivité de la fonction publique de l'État

G2015/10 P. AUBERT
La modulation du montant de pension selon la durée de carrière et l'âge de la retraite : quelles disparités entre assurés ?

G2015/11 V. DORTET-BERNADET - M. SICSIC
Effet des aides publiques sur l'emploi en R&D dans les petites entreprises

G2015/12 S. GEORGES-KOT
Annual and lifetime incidence of the value-added tax in France

G2015/13 M. POULHÈS
Are Enterprise Zones Benefits Capitalized into Commercial Property Values? The French Case

G2015/14 J.-B. BERNARD - Q. LAFFÉTER
Effet de l'activité et des prix sur le revenu salarial des différentes catégories socio-professionnelles

G2015/15 C. GEAY - M. KOUBI - G de LAGASNERIE
Projections des dépenses de soins de ville, construction d'un module pour Destinie

G2015/16 J. BARDAJI - J.-C. BRICONGNE - B. CAMPAGNE - G. GAULIER
Compared performances of French companies on the domestic and foreign markets

G2015/17 C. BELLÉGO - R. DE NIJS
The redistributive effect of online piracy on the box office performance of American movies in foreign markets

G2015/18 J.-B. BERNARD - L. BERTHET
French households financial wealth: which changes in 20 years?

G2015/19 M. POULHÈS
Fenêtre sur Cour ou Chambre avec Vue ?
Les prix hédoniques de l'immobilier parisien

G2016/01 B. GARBINTI - S. GEORGES-KOT
Time to smell the roses? Risk aversion, the timing of inheritance receipt, and retirement

G2016/02 P. CHARNOZ - C. LELARGE - C. TREVIEN
Communication Costs and the Internal Organization of Multi-Plant Businesses: Evidence from the Impact of the French High-Speed Rail

G2016/03 C. BONNET - B. GARBINTI - A. SOLAZ
Gender Inequality after Divorce: The Flip Side of Marital Specialization - Evidence from a French Administrative Database

G2016/04 D. BLANCHET - E. CAROLI - C. PROST - M. ROGER
Health capacity to work at older ages in France

G2016/05 B. CAMPAGNE - A. POISSONNIER
MELEZE: A DSGE model for France within the Euro Area

G2016/06 B. CAMPAGNE - A. POISSONNIER
Laffer curves and fiscal multipliers: lessons from Meléze model

G2016/07 B. CAMPAGNE - A. POISSONNIER
Structural reforms in DSGE models: a case for sensitivity analyses

G2016/08 Y. DUBOIS et M. KOUBI
Relèvement de l'âge de départ à la retraite : quel impact sur l'activité des séniors de la réforme des retraites de 2010 ?

G2016/09 A. NAOUAS - M. ORAND - I. SLIMANI HOUTI
Les entreprises employant des salariés au Smic : quelles caractéristiques et quelle rentabilité ?

G2016/10 T. BLANCHET - Y. DUBOIS - A. MARINO - M. ROGER
Patrimoine privé et retraite en France

G2016/11 M. PAK - A. POISSONNIER
Accounting for technology, trade and final consumption in employment: an Input-Output decomposition

G2017/01 D. FOUGÈRE - E. GAUTIER - S. ROUX
Understanding Wage Floor Setting in Industry-Level Agreements: Evidence from France

G2017/02 Y. DUBOIS - M. KOUBI
Règles d'indexation des pensions et sensibilité des dépenses de retraites à la croissance économique et aux chocs démographiques

G2017/03 A. CAZENAVE-LACROUTZ - F. GODET
L'espérance de vie en retraite sans incapacité sévère des générations nées entre 1960 et 1990 : une projection à partir du modèle Destinie

G2017/04 J. BARDAJI - B. CAMPAGNE - M.-B. KHDER - Q. LAFFÉTER - O. SIMON (Insee)
A.-S. DUFERNEZ - C. ELEZAAR - P. LEBLANC - E. MASSON - H. PARTOUCHE (DG-Trésor)
Le modèle macroéconométique Mésange: réestimation et nouveautés

G2017/05 J. BOUSSARD - B. CAMPAGNE
Fiscal Policy Coordination in a Monetary Union at the Zero-Lower-Bound

G2017/06 A. CAZENAVE-LACROUTZ - A. GODZINSKI
Effects of the one-day waiting period for sick leave on health-related absences in the French central civil service

G2017/07 P. CHARNOZ - M. ORAND
Qualification, progrès technique et marchés du travail locaux en France, 1990-2011

G2017/08 K. MILIN
Modélisation de l'inflation en France par une approche macrosectorielle

G2017/09 C.-M. CHEVALIER - R. LARDEUX
Homeownership and labor market outcomes: disentangling externality and composition effects

G2017/10 P. BEAUMONT
Time is Money: Cash-Flow Risk and Export Market Behavior

G2018/01 S. ROUX - F. SAVIGNAC
SMEs' financing: Divergence across Euro area countries?

G2018/02 C.-M. CHEVALIER - A. LUCIANI
Computerization, labor productivity and employment: impacts across industries vary with technological level

G2018/03 R. MONIN - M. SUAREZ CASTILLO
L'effet du CICE sur les prix : une double analyse sur données sectorielles et individuelles

G2018/04 R. LARDEUX
Who Understands The French Income Tax? Bunching Where Tax Liabilities Start

G2018/05 C.-M. CHEVALIER
Financial constraints of innovative firms and sectoral growth

G2018/06 R. S.-H. LEE - M. PAK
Pro-competitive effects of globalisation on prices, productivity and markups: Evidence in the Euro Area

G2018/07 C.-M. CHEVALIER
Consumption inequality in France between 1995 and 2011

G2018/08 A. BAUER - B. GARBINTI - S. GEORGES-KOT
Financial Constraints and Self-Employment in France, 1945-2014

G2018/09 P. BEAUMONT - A. LUCIANI
Prime à l'embauche dans les PME : évaluation à partir des déclarations d'embauche

G2018/10 C. BELLÉGO - V. DORTET-BERNADET - M. TÉPAUT
Comparaison de deux dispositifs d'aide à la R&D collaborative public-privé

G2018/11 R. MONIN - M. SUAREZ CASTILLO
Récplication et rapprochement des travaux d'évaluation de l'effet du CICE sur l'emploi en 2013 et 2014

G2018/12 A. CAZENAVE-LACROUTZ - F. GODET - V. LIN
L'introduction d'un gradient social dans la mortalité au sein du modèle Destinie 2

G2019/01 M. ANDRÉ - A.-L. BIOTTEAU
F1901
Effets de moyen terme d'une hausse de TVA sur le niveau de vie et les inégalités: une approche par microsimulation

G2019/02 A. BOURGEOIS - A. BRIAND
Le modèle Avionic : la modélisation Input/Output des comptes nationaux

G2019/03 A. GODZINSKI - M. SUAREZ CASTILLO
Short-term health effects of public transport disruptions: air pollution and viral spread channels