# A Welfare Based Estimate of “Real Feel GDP” for Europe and the USA

Jean-Marc GERMAIN
<figure><img src="image_1.png" /></figure>
G2020/03

# A Welfare Based Estimate of “Real Feel GDP” for Europe and the USA

Jean-Marc GERMAIN*

Août 2020

Département des Études Économiques - Timbre G201

88, avenue Verdier - CS 70058 - 92541 MONTROUGE CEDEX - France

Tél. : 33 (1) 87 69 59 54 - E-mail : d3e-dg@insee.fr - Site Web Insee : http://www.insee.fr

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

<footnote>* Insee-Dese - Département des études économiques</footnote>

<footnote>This work benefited from usefull discussions with Didier Blanchet and Sebastien Roux. I also thank Lionel Wilner for providing me with proper french SRCV micro data derived from his own works on life satisfaction, and Martine Durand for facilitated access to OECD databasis on income distribution and life satisfaction.</footnote>
# Au-delà du PIB, une estimation PIB ressenti en Europe et aux Etats-Unis

## Résumé

L'article tente de définir et de calculer un «PIB ressenti», par analogie avec la température ressentie utilisée par les météorologues. C'est en ces termes que nous interprétons une fonction standard de bien-être social de Kolm-Atkinson, estimée avec les micro-données de satisfaction dans la vie rapportées dans les enquêtes Euro-SILC. En utilisant les données longues de distribution de revenu du World Inequality Lab, nous mettons en évidence, aux États-Unis, une stagnation au cours des 40 dernières années du PIB ressenti ainsi défini, signifiant que la croissance économique n'y a pas entraîné un meilleur bien-être monétaire global. Dans l'intervalle, dans la plupart des pays européens, sauf au cours des dernières années, le PIB ressenti et le PIB ont évolué de manière similaire. Nous montrons également que les ralentissements économiques ont duré beaucoup plus longtemps, en terme de bien-être monétaire, que mesurés par le PIB. En effet, le PIB réel des États-Unis a mis 10 ans pour retrouver son niveau d'avant la crise après le deuxième choc pétrolier; près de 10 ans après le ralentissement de 2008, le PIB réel européen n'avait pas encore retrouvé son niveau d'avant la crise.

**Mots-clés** : indicateur économique, économie du bien-être, inégalités, redistribution, au-delà du PIB

# A Welfare Based Estimate of “Real Feel GDP” for Europe and the USA

## Abstract

This paper attempts to define and compute a “Real Feel GDP”, by analogy with meteorologist’s Real Feel Temperature. It is in such terms that we interpret a standard Kolm-Atkinson social welfare function, estimated with life-satisfaction micro data reported in Euro-SILC surveys. Using long run World Inequality Lab distributional data, we find that USA haven’t seen any improvement of our Real Feel GDP for the past 40 years, meaning that economic growth did not result in a better aggregate monetary well-being. In the meantime, in most European countries, except over the recent years, Real Feel GDP and GDP evolved similarly. We also find that economic downturns have lasted much longer than measured by GDP. Indeed, US Real Feel GDP took 10 years to recover its pre-crisis level after the second petrol shock; almost 10 years after the 2008 downturn, European Real Feel GDP had not yet recovered its pre-crisis level.

**Keywords:** economic indicator, welfare economics, inequality, distribution, beyond GDP

**Classification JEL** : D63, E01, O57
Nobody ignores that temperature feels like colder when the wind is blowing. The feeling has physical groundings. A surface loses heat through conduction, evaporation, convection and radiation. The rate of heat transfer depends on both the difference in temperature between the surface and the atmosphere or water surrounding, and the velocity of that fluid with respect to the surface. In a word, you feel colder because your body is actually getting colder more rapidly. For extreme temperature, being aware of this wind chill effect is a matter of survival. The first wind chill effect formulas where developed in the first part of XX's century for Antarctic expeditions by Siple and Passel (1945), and, in the 1970's, made available to the public by Canadian and North American Weather Services<fnref n="1" />. For example, a temperature of minus 10°C with a 30km/h wind “feels like” a temperature of -20°C without wind.

Conversely, high humidity rate reduce the radiation heat transfers from the body to the atmosphere, making it more difficult to support high temperature<fnref n="2" />. With the climate change, and the multiplication of extreme temperature episodes even in temperate countries, the use of feels like<fnref n="3" /> temperature is becoming more and more popular, and useful for example for local authorities to protect more exposed population, such as opening extra shelter for homeless people or distribution water bottle in retirement houses.

This paper attempts to define and compute a Real Feel GDP that could be the equivalent of meteorologist real feel temperature<fnref n="4" />. As temperature is an imperfect proxy for the real health impact of the weather, it has been well documented, notably by the Stiglitz Commission Report (Stiglitz, Sen, Fitoussi 2009), that some major factors affecting living standard are incorporated imperfectly, if at all, in GDP. The Commission addressed a very clear warning: because of exaggerate or misused of indicator like GDP, “those attempting to guide the economy and our societies are like pilots trying to steering a course without a reliable compass”. The Stiglitz Commission Report calls for a switch of the statistical systems center of gravity from GDP to the welfare of actual and future generation.

There have been numerous attempts to build GDP alternative index of the economic performance (See Fleurbaey and Blanchet (2013) for a full literature review on Measuring Welfare). The most widely used, and to date the only one that resisted to time, is undoubtedly the United Nation's Human Development Index, inspired by Amartya Sen (1994) and which mixes, with equal weights, life expectancy, education

<footnote n="1">¹ The formula for low temperature (<10°C) and medium to high wind (>4,8kmph) is $T_R = 13,12 + 0,6215 T_A + (0,3965T_A - 11,37) \times V^{0,16}$.</footnote>

<footnote n="2">²To account for humidity effect, the Canada National Weather Service started to issue, during the 60's, a temperature index, called Humidex, whose current formula was developed by J. M. Masterton and F. A. Richardson of Canada's Atmospheric Environment Service in 1979: $Humidex = T_A + 0,555 \times [\exp(1,530 \times T_H/(273 + T_H)) - 10]$ where $T_A$ is the actual temperature in Farenheit degrees and $T_H$ the dew point. The United States use another index, the HeathIndex which was developed in 1978 by George Winterling as the "humiture" and was adopted by the US's National Weather Service a year later. The formula is as follows : $HI = -0,42 + 2,05T_A + 10,1H - 0,22T_AH - 6,8 \times 10^{-3}T_A^2 - 5,5 \times 10^{-2}H^2 + 1,3 \times 10^{-3}T_A^2H + 8,5 \times 10^{-4}T_AH^2 - 2,0 \times 10^{-6}T_A^3H^2$ where $T_A$ is the temperature in Farenheit degrees and H the humidity rate (percentage between 0 and 100).</footnote>

<footnote n="3">³ Feels like temperature is the denomination used by the National Weather Service for the UK.</footnote>

<footnote n="4">⁴ The denomination "RealFeel Temperature" is a patented concept created in the 1990's (see Myers et alii (2004). The authors claim it as the "first temperature" to take account multiple factors -including humidity, cloud cover, winds, sun intensity and angle of the sun- to determine how hot and cold one feels. Their index is published by AccuWeather.com.</footnote>
and GDP. In this tradition, the OECD (2011) developed a “Better Life Index” based on eleven aspects of well-being ranging from security, housing, income, education, quality of job, to trust in government (see also Durand (2015)). More recently, pushing the logic to the extreme, Sachs (2017) proposed a SDG-Index based upon a mix of the seventeen UNO Sustainable Development Goals, themselves relying on a subset of 230 indicators. The supporters of these indexes justify the equal weightings as reflecting equal importance of underlying objectives or policies, whereas opponents, as Ravallion (2010) who speaks of “mashup indexes” criticize them for their lack of theoretical groundings.

The second set of indicators comes from the literature on the measurement of economic welfare, initiated by Nordhaus and Tobin (1973). The key idea is to monetize non-monetary elements of well-being such as leisure activities or domestic work. They also reconsider health and education as investments to account for the sustainability of living standards. Later, in the same spirit, Cobb and Daly (1989) introduced environmental degradation costs, paving the way for a new generation of indicators qualified by Cobb and Cobb (1994) as green GDPs, such as the Genuine Progress Indicator. This second branch could be qualified as semi theoretical, since it relies on economic theory for the principles, but does not mobilize it further for practical implementation.

The third branch is explicitly grounded on economic theory and was made possible by the development in the 2000s of data on subjective well-being. The idea is to monetize, from a utility function, non-monetary elements of well-being. Becker, Philipson, and Soares (2005) use a utility function to combine income and life expectancy into a full income measure. Boarini, Johansson, Mira d'Ercole (2006) account for unemployment, health and inequality for the largest OECD countries. Fleurbaey and Gaulier (2009) incorporate life expectancy, leisure and inequality to compute a full-income measure for 24 OECD countries. Jones and Klenow (2016) also include leisure and inequality, focus on consumption instead of income, and report results for countries at different stages of development, namely United States, France, Italy, United Kingdom, Spain, but also China, India, Russia, Brazil, Indonesia and South Africa.

Here, we focus on monetary well-being. We will not attempt to assess global welfare, and thus not include non-monetary determinants of welfare. Not that we think they would be less important. Simply they are out of the scope that we assign to this paper: seek for the best measure of welfare procured by national income. Indeed, to carry further the metaphor, real feel temperature does not intend to describe the entirety of how the individual will feel the weather of the day: this overall assessment would also include how he feels such facts as the presence of sun rather than clouds or rain. It focuses on the temperature aspect of the weather report, and intends from temperature to derive a better measure of heat gains or losses for the human body, accounting for wind and humidity. We are here in the same register.

Such an analogy with weather reporting is also used by Blanchet and Fleurbaey (2020). They use it to argue in favor of parsimonious but eclectic dashboards of economic progress, combining objective income measures with measures of subjective perceptions. However, their idea implicitly applies to subjective data directly collected through surveys. What is considered here are model-based
reconstructions of these perceptions, exactly as the real feel temperature of weather forecasts is not an information directly collected from individuals but reconstructed from models that rely on objective data. The rationale for using modelled versions of average perceptions is that they provide a higher level of control over what is really quantified.

We organized the rest of the paper as follows. In Section I, we define real feel GDP as equivalent income derived from an additive utility function of income. Section II is dedicated to the estimation of a welfare utility function using both micro and cross country-aggregated data. We then use World Inequality Lab income distribution data to compute Real Feel GDP for European Countries and the United States, and we discuss the usefulness of the index with regard to past trends of GDP and Real Feel GDP (Section III). Section IV examines an augmented version of Real Feel GDP taking into account unemployment as a proxy of future income uncertainty. Section V is dealing with robustness issues and Section VI concludes.

# I. Theoretical groundings

In this section, we define Real Feel GDP (here on RFGDP) as the Atkinson-Kolm<fnref n="5" /> income-equivalent derived from the welfare procured by income. Let denote $r_{i,j}(t)$ the income of individual i, in country j, at time t, $S_j(r_{i,j}(t))$ the satisfaction procured to individual i by its income. We assume from now on that $S_j(.)$ is an increasing and concave function of r. As our data estimates will show, this functional form translates the idea that the higher the income, the higher the satisfaction but the lower the satisfaction gains from income gains. We also allow, though index j, for country specific effects independent of r<fnref n="6" />. Whereas “growth” between two periods t and $t_0$ is usually computed as $(R_j(t) - R_j(t_0))/R_j(t_0)$, with $R_j(t) = \sum_{i=1}^{n_j} r_{i,j}(t)$, a natural candidate for “real feel growth” would be $(W_j(t) - W_j(t_0))/W_j(t_0)$, where :

$$W_j(r_{1,j}(t), r_{2,j}(t), \dots, r_{n_j(t),j}(t)) = \frac{1}{n_j(t)} \sum_{i=1}^{n_j(t)} S_j(r_{i,j}(t)) \quad (E1)$$

is the average satisfaction, $n_j(t)$ being the population of country j at date t. Here we assume additive satisfaction, but the framework fits also to a broader aggregate welfare function. However, here, regarding to our goal of finding corrections to GDP measure to better fit to what people really feel of GDP, accounting directly welfare growth would rise a measurement unit issue. Whereas real feel temperature is, like temperature itself, measured in Celsius degrees, we seek for a monetary measure of welfare, which is precisely the purpose of the equivalent-income framework.

<footnote n="5">⁵ See Atkinson (1970), Kolm (1969).</footnote>

<footnote n="6">⁶ In other word, we capture through r both direct income effect, but also indirect effect such as education, or health which are strongly correlated to income.</footnote>
To express in monetary term the welfare change, the idea is to find by how much should have the $t_0$ income of all individuals to be increased, with the same rate of growth, to reach exactly the current aggregate satisfaction $W_{jt}$. Following the Atkinson-Kolm-Sen income-equivalent framework, let $W_j(\lambda, r_{1,j}(t), r_{2,j}(t), \dots, r_{n_j(t),j}(t))$ denote the aggregate welfare of country j at time t where all individual income are multiplied by $\lambda$, that is $W_j(\lambda, r_{1,j}(t), r_{2,j}(t), \dots, r_{n_j(t),j}(t)) = 1/n_j(t) \sum_{i=1}^{n_j(t)} s_j(\lambda r_{i,j}(t))$. Then the equivalent income index of country j at time t, for base year $t_0$, is the value of the $\lambda_j^{t_0}(t)$ solution of the following equation:

$$W_j(\lambda, r_{1,j}(t_0), r_{2,j}(t_0), \dots, r_{n_j(t_0),j}(t_0)) = W_j(1, r_{1,j}(t), r_{2,j}(t), \dots, r_{n_j(t),j}(t))$$

Note that if $S$ is increasing function of income r, then $\lambda \to W_j(\lambda, \{r_{i,j}(t_0)\})$ also an increasing function and therefore can be inverted, noted $W_{jt_0}^{-1}(\cdot, \{r_{i,j}(t_0)\})$. Hence, our real feel GDP index is set as:

$$\lambda_j^{t_0}(t) = W_{jt_0}^{-1}(W_{jt}(r_1^{jt}, r_2^{jt}, \dots, r_{n_j^{jt}}^{jt}), \{r_{i,j}(t_0)\}) \quad (E2)$$

In the particular case of a constant income elasticity satisfaction function, that is: $S(r) = \alpha/(1 - \tau) r^{1-\tau} + \beta_j$ where $\beta_j$ is a country specific parameter, we have:

$$W_{jt_0}^{-1}(x) = \frac{x^{\frac{1}{1-\tau}}}{\left[1/n_j(t_0) \sum_{i=1}^{n_j(t_0)} r_{i,j}(t_0)^{1-\tau}\right]^{\frac{1}{1-\tau}}}$$

Consequently:

$$\lambda_j^{t_0}(t) = \left[ \frac{1/n_j(t) \sum_{i=1}^{n_j(t)} r_{i,j}(t)^{1-\tau}}{1/n_j(t_0) \sum_{i=1}^{n_j(t_0)} r_{i,j}(t_0)^{1-\tau}} \right]^{\frac{1}{1-\tau}} \quad (E3)$$

The interpretation of $\lambda_j^{t_0}(t)$ is the following : a $\lambda_j^{t_0}(t)$ greater than one mean that welfare is greater at time $t$ than at time $t_0$, and that the welfare increase is equivalent to the one that would be experimented by country j if the incomes of all individuals would have increased by $(\lambda_j^{t_0}(t) - 1)\%$. That is exactly what we would expect from a macroeconomic synthetic index attempting to reflect what people globally feel from a GDP change. Therefore $\lambda_j^{t_0}(t)$ is a very good candidate for a Real Feel GDP Index.
which leads to, with a constant elasticity individual satisfaction function:

$$RFGDP_j(t) = r_j(t_0) \left[ 1/n_j(t) \sum_{i=1}^{n_j(t)} [r_{i,j}(t)/r_j(t)]^{1-\tau} \right]^{\frac{1}{1-\tau}} \quad (E5)$$

We then of course have $\lambda_j^{t_0}(t) = RFGDP_j(t)/RFGDP_j(t_0)$. Absolute $RFGDP_j(t)$ is not only a convenient reference to compute the index. It can also be interpreted as the egalitarian equivalent to the actual distribution of income in country j at time t. It can be easily shown indeed that $W_j(RFGDP_j(t), ..., RFGDP_j(t)) = W_j(r_{1,j}(t), ..., r_{n_j(t),j}(t)) = S_j(RFGDP_j(t))$. For our purpose, egalitarian distribution is of interest not because of its optimal properties under decreasing marginal utility of income, but as a benchmark situation where we will not have to search for an indicator better than per capita GDP to fit with people monetary well-being per capita. Indeed, if all income were equal, the latter would then be an increasing function of the former.

<figure><img src="image_2.png" /><figcaption>Figure 2: From GDP to Real Feel GDP Level</figcaption></figure>

## II. Well-being function estimates

One critical step to compute Real Feel GDP as defined above is to estimate the satisfaction function $S_j(r)$. We first estimate a monetary utility function on French micro data, then we compare our results with cross-country estimates on aggregate data by quintile of income.
A. Welfare income curve with French Microdata

We first work on French micro data from 2013 to 2017, namely the SRCV survey (which is the French part of EURO-SILC<fnref n="7" />), surveying yearly around 15 000 households. It contains various data concerning resources and living conditions; from 2010 on, subjective well-being is also included, globally and regarding specific issues such as housing, leisure or social relationship. More precisely, it is asked “on a scale from 0 (not at all satisfied) to 10 (very satisfied)” to “indicate your own satisfaction concerning your house, your work, your leisure, your relation with family, friends and neighbors, and the life you live at the moment”. Here we will focus on the global appreciation of life satisfaction.

Figure 3A below displays the average income and the average satisfaction in life, for year 2017, by per unit of consumption disposable income vintile until P95 and by income centiles from P95 to P100.

<figure><img src="image_3.png" /><figcaption>Figure 3A: Satisfaction in Life by Income Percentile with French Micro-Data</figcaption></figure>

We then compute $\tau$ through a non-linear estimation of the following relation:

$$S_i = \alpha/(1 - \tau) r_i^{1-\tau} + \beta + \varepsilon_i$$

where $S_i$ is the life satisfaction of individual i, $r_i$ is his disposable income per consumption unit, $\alpha$ and $\beta$ parameters and $\varepsilon_i$ a residual. We use a maximum likelihood estimation based on the assumption of a Gaussian distribution of residuals<fnref n="8" />. The results of the nonlinear estimation are given in table 1A below.

<footnote n="7">⁷ European union-Statistics on income and living conditions</footnote>

<footnote n="8">⁸ SAS proc model.</footnote>
<table><caption>Table 1A: Non-linear Estimation of Satisfaction Function with French Micro Data</caption><thead><tr><th>Parameters</th><th>Estimated value</th><th>Standard error</th><th>60% range</th></tr></thead><tbody><tr><td>τ</td><td>2.097618 ***</td><td>0.1420</td><td>2,0 – 2,2</td></tr><tr><td>α</td><td>0.552135 ***</td><td>0.0379</td><td>0,51 – 0,58</td></tr><tr><td>β</td><td>7.909157 ***</td><td>0.0936</td><td>7,8 – 8,0</td></tr><tr><td>Year</td><td>2017</td><td>Number of obs.</td><td>14753</td></tr></tbody></table>

The satisfaction curve is hence the following:

$$S_i = 0,552^{***} \times \frac{r_i^{1-2,097}}{(1 - 2,097)} + 7,909^{***} + \varepsilon_{it}$$

We will test the robustness of the estimate in section V below with an ordered logistic procedure accounting for the discretionary nature of the satisfaction variable (Cantril ladder from 0 to 10). The satisfaction function is also robust over time. Table 1B report estimates of τ for successive editions of the survey, from 2013 to 2017.

<table><caption>Table 1B: Non-linear estimation of τ parameter</caption><thead><tr><th>Year</th><th>Estimated value</th><th>Standard error</th><th>Obs.</th></tr></thead><tbody><tr><td>2017*</td><td>2.09761***</td><td>0.1420</td><td>14753</td></tr><tr><td>2016*</td><td>1.71136***</td><td>0.1318</td><td>15330</td></tr><tr><td>2015*</td><td>1.57649***</td><td>0.1059</td><td>15172</td></tr><tr><td>2014*</td><td>1.73735***</td><td>0.1065</td><td>15162</td></tr><tr><td>2013*</td><td>1.87778***</td><td>0.1151</td><td>14650</td></tr><tr><td>2013-2017*</td><td>1.79828***</td><td>0.0532</td><td>75067</td></tr><tr><td>2017**</td><td>2.37822***</td><td>0.1387</td><td>14753</td></tr><tr><td>2013-2017**</td><td>2.07492***</td><td>0.0465</td><td>75067</td></tr></tbody></table>

*weight : population **weight : % of disposable income

Year 2017 gives the highest value of τ. The value obtained by merging the five surveys is equal to 1.8. We also run estimates replacing population weights by the share of disposable income represented by each individual in the sample. The rationale for this correction is that, in the end, computing real feel GDP is looking how national income is distributed. More pragmatically, it gives a high weight to upper incomes, and thus a satisfaction curve that better fits the data at the top of the distribution, at the expense of the bottom of the distribution. It results in higher values of : 2.38 for the 2017 survey versus 2.09 with population weights ; and 2.07 versus 1.80 for the pooled sample.
<figure><img src="image_4.png" /><figcaption>Figure 3B: Satisfaction in Life by Income Group from French Micro-Data (SRCV from 2013 to 2017)</figcaption></figure>

## B. Cross country panel estimation for European Union Countries

We then use OECD data issued mainly from the Euro-SILC household Survey, which provide incomes and life satisfaction by quintiles of disposable income per consumption unit for 26 European countries. For France, the source survey for Euro-SILC is the SRCV survey used in the previous section.

<figure><img src="image_5.png" /><figcaption>Figure 4: Life Satisfaction by Quintile of Income for European Union Countries</figcaption></figure>

First, we estimate $\tau$ to estimate the welfare curve. We assume, to begin, that the same curve applies for all country:

$$S_{k,j} = \beta + \alpha (r_{k,j}/\bar{r}_j)^{1-\tau}/(1-\tau) + \varepsilon_{kj}$$

The optimal value of $\tau$ using maximum likelihood estimation with Gaussian residuals is 1.8, with a 60% range of 1.5 to 2.1.
We then run a regression only on wealthiest countries meaning here those with a high Q1⁹. Two reasons lead us to do so: first to check for possible effect of standard of living on risk aversion; second to control for mismeasurement of Q1, due to data, methodology, dissimulated work, intra-family transfers that results to a real Q1 significantly higher than reported in the statistics. It leads (see table 2 below) to a slightly higher τ (1.985) -quite close to our estimate on French Micro Data (2.097)- meaning a higher aversion to inequalities for this group of countries than for the whole sample.

We then divided our panel into five geographical sets of countries namely Northern Europe, Western Europe, Northern Channel (UK, Ireland and Island), Eastern Europe, Southern Europe. The risk aversion parameter is the highest for the Northern and Western European groups, again close to the Micro Data level (respectively 1.934 and 1.885). It is significantly lower for Southern and Eastern European Countries, but also for the Northern Channel group (UK, Ireland, Island).

<table><caption>Table 2 : Cross Country Estimate of Welfare Curve with French Micro Data</caption><thead><tr><th>Country group</th><th>Estimated value of τ</th><th>Standard error</th><th>60% confidence interval</th></tr></thead><tbody><tr><td>All Countries</td><td>1,780***</td><td>0.330</td><td>1,5 - 2,1</td></tr><tr><td>High Q1 Countries (1)</td><td>1.985***</td><td>0.414</td><td>1,6 - 2,4</td></tr><tr><td>Northern Europe (2)</td><td>1.934***</td><td>0.388</td><td>1,5 - 2,3</td></tr><tr><td>Western Europe (3)</td><td>1.885***</td><td>0.494</td><td>1,4 - 2,4</td></tr><tr><td>Northern Channel (4)</td><td>1.367***</td><td>0.120</td><td>1,3 - 1,5</td></tr><tr><td>Eastern Europe (5)</td><td>1.324***</td><td>0.501</td><td>0,8 - 1,8</td></tr><tr><td>Southern Europe (6)</td><td>1.192***</td><td>0.446</td><td>0,8 - 1,6</td></tr></tbody></table>

These differences may be due to different aversion to inequalities. It may also be due to imperfect measurement of the Q1 income (see above). Or it could simply reflect the fact that Southern and Eastern Country are in a development stage with not enough “high” incomes to properly capture the sharp turn point of the curve in the 20 000 / 30 000 dollars income range. In a word, for those countries, satisfaction curve may look like a straight or a slightly bended curve only because most of their individual incomes are in the steep part of the curve.

Cross-countries micro data, comparable to those used for France above, could give the answer. At this stage, we simply note that the latter argument is more than plausible. Indeed, if we now estimate a welfare curve based on absolute income rather than relative, that is:

$$S_{kj} = \beta + \alpha (r_{kj}/\bar{r})^{1-\tau^*}/(1-\tau^*) + \beta_j + \varepsilon_{kj}$$

where $\beta_j$ is a country specific dummy and $\bar{r}$ the average income for the 26 European countries of our cross country panel and $\tau^*$ the value of $\tau$ that we obtain is equal to

<footnote>(1) Q1>10 000€ : AUT, BEL, CHE, DEU, DNK, FIN, FRA, IRL, ISL, LUX, NLD, NOR, SWE, SVN (2) DNK, FIN, NLD, SWE, NOR (3) AUT, BEL, CHE, DEU, FRA, LUX (4) GBR, IRL, ISL (5) CZE, EST, HUN, LTU, LVA, POL, SVN, SVK (6) ESP, GRC, ITA, PRT.</footnote>

<footnote n="9">⁹ Greater than 10 000 euros, which includes the following countries : AUT, BEL, CHE, DEU, DNK, FIN, FRA, IRL, ISL, LUX, NLD, NOR, SWE, SVN.</footnote>
1.985, very close to the one computed for the high Q1 group of countries. The results can be found in table 3.

<table><caption>Table 3: Satisfaction Function with Specific Country Dummies</caption><thead><tr><th>Variables</th><th>Estimated value</th><th>Standard error</th><th>t-test value</th></tr></thead><tbody><tr><td>Intercept (β)</td><td>8.13560***</td><td>0.03336</td><td>243.88</td></tr><tr><td>f(Income) (α) (1)</td><td>0.64613***</td><td>0.02130</td><td>30.34</td></tr><tr><td colspan="4"><strong>Country specific dummies (β<sub>j</sub>)</strong></td></tr><tr><td>Austria</td><td>0.37624***</td><td>0.08721</td><td>4.31</td></tr><tr><td>Belgium</td><td>0.14249*</td><td>0.07974</td><td>1.79</td></tr><tr><td>Switzerland</td><td>0.43850***</td><td>0.07369</td><td>5.95</td></tr><tr><td>Czech-Republic</td><td>-0.17051*</td><td>0.12056</td><td>-1.41</td></tr><tr><td>Denmark</td><td>0.58863***</td><td>0.09382</td><td>6.27</td></tr><tr><td>Spain</td><td>-0.30700***</td><td>0.05198</td><td>-5.91</td></tr><tr><td>Estonia</td><td>-0.43456</td><td>0.34174</td><td>-1.27</td></tr><tr><td>Finland</td><td>0.62249***</td><td>0.10923</td><td>5.70</td></tr><tr><td>France</td><td>-0.25626***</td><td>0.04174</td><td>-6.14</td></tr><tr><td>Germany (ref)</td><td>0,00000</td><td></td><td></td></tr><tr><td>United-Kingdom</td><td>0.00451</td><td>0.04172</td><td>0.11</td></tr><tr><td>Greece</td><td>-0.59687***</td><td>0.11309</td><td>-5.28</td></tr><tr><td>Hungary</td><td>-0.29337**</td><td>0.14589</td><td>-2.01</td></tr><tr><td>Ireland</td><td>0.03578</td><td>0.11412</td><td>0.31</td></tr><tr><td>Iceland</td><td>0.39119***</td><td>0.51090</td><td>0.77</td></tr><tr><td>Italy</td><td>-0.60586</td><td>0.04613</td><td>-13.13</td></tr><tr><td>Lithuania</td><td>0.08653</td><td>0.24691</td><td>0.35</td></tr><tr><td>Luxembourg</td><td>-0.05281</td><td>0.26023</td><td>-0.20</td></tr><tr><td>Latvia</td><td>-0.24425***</td><td>0.32126</td><td>-0.76</td></tr><tr><td>Netherlands</td><td>0.32476***</td><td>0.06224</td><td>5.22</td></tr><tr><td>Norway</td><td>0.29354**</td><td>0.08118</td><td>3.62</td></tr><tr><td>Poland</td><td>0.35805***</td><td>0.07571</td><td>4.73</td></tr><tr><td>Portugal</td><td>-0.74212***</td><td>0.11611</td><td>-6.39</td></tr><tr><td>Slovak Republic</td><td>0.08695</td><td>0.17202</td><td>0.51</td></tr><tr><td>Slovenia</td><td>-0.19468</td><td>0.27575</td><td>-0.71</td></tr><tr><td>Sweden</td><td>0.44339***</td><td>0.07588</td><td>5.84</td></tr><tr><td>F value</td><td>76.51</td><td>R square</td><td>0.9508</td></tr><tr><td>Year</td><td>2016-2017</td><td>Number of obs.</td><td>130 (DF 103)</td></tr></tbody></table>

(1) f(Income) : $(r_{kt}/\bar{r})^{1-1.985/(1-1.985)}$

Not surprisingly given the results of table 2, we find very significant t-test values for the intercept and the income related coefficient $\alpha$. Most country dummies are also significant, the highest negative dummies been found for Southern Europe Countries. The highest country specific effects are observed in Northern Countries. Once corrected by these country specific effects, we find that $\beta + \alpha (r_{kj}/\bar{r})^{1-\tau^*}/(1-\tau^*)$ is a credible candidate to represent an absolute welfare curve for European Countries, as can be seen on figure 5¹⁰.

<footnote n="10">¹⁰ For each quintile $k$ of country $j$, we plot $r_{kj}$ on the X-axis and $S_{kj}-\beta_j$ on the Y axis. The red curve represents $(r_{kj}, \beta + \alpha (r_{kj}/\bar{r})^{1-\tau^*}/(1-\tau^*))$.</footnote>
<figure><img src="image_6.png" /><figcaption>Figure 5: Adjusted Life Satisfaction by Income for 26 European Countries</figcaption></figure>

### III. Real Feel GDP in Europe and the USA

Having estimated the monetary well-being function, we now return to our initial objective of calculating a real feel GDP. From now on, we will consider that the population is divided in K homogenous groups. Mostly, K would be 5 or 10, and groups would be quintiles or deciles of disposable income. The real feel GDP formula is the following:

$$RFGDP_j(t) = (NNI_j(t)/POP_j(t)) \left[ \sum_{k=1}^{K} \pi_{kj} (r_{kj}(t)/r_j(t))^{1-\tau} \right]^{1/(1-\tau)}$$

where $NNI_j(t)$ and $POP_j(t)$ are respectively the net national income and population of country j at date t, and $π_{kj}$ the weight of group k in the overall population<fnref n="11" />. Net national income, and population data are taken from the World Bank database. For income distributions, we use the WID.world database of Distributional National Accounts, which is the most comprehensive database on wealth and income distribution<fnref n="12" />. Indeed, as recommended by the Stiglitz commission, per capita NNI is preferred to per capita GDP, as it is a better proxy for average personal income, since the former is deduced from the latter by subtracting CCF and net flow of income detain by foreign shareholder.

For the US, those income distributions result from the work of Piketty, Saez and Zucman (2017). They combine tax, survey, and national accounts data to estimate pre-

<footnote n="11">¹¹ Note that here we referee to the net national income rather than GDP: as pointed by the Stiglitz commission, the emphasizing on NNP rather than GDP, that is excluding from GDP net foreign income and fixed capital consumption.</footnote>

<footnote n="12">¹² See https://wid.world/fr/world-inequality-lab-fr/</footnote>
tax and post-tax distributions of national income in the United States since 1913. For Europe, the database relies on Blanchet, Chancel and Gethin (2019) who computed income distributions, back to 1980, for most of the European Countries. For France, we use INSEE-ERFS<fnref n="13" /> data from 1996 to 2016, and retropolate back to 1980 with WIL data due to Garbinti et alii (2018) and Bozio et alii (2018). Results are shown in table 4 below.

<table><caption>Table 4: From GDP to Real Feel GDP for Europe and the USA</caption><thead><tr><th>Country</th><th>GDP (2017)</th><th>GDP per capita (2017)</th><th>NNI p. capita (2017)</th><th>Real Feel GDP (2017)</th><th>Real Feel GDP (1980)</th><th>GDP Growth 1980-2017</th><th>Real Feel Growth 1980-2017</th><th>Atkinson Inequality Index (1980)</th><th>Atkinson Inequality Index (2017)</th></tr></thead><tbody><tr><td>USA</td><td>13 086</td><td>47 348</td><td>40 272</td><td>14 650</td><td>13 208</td><td><strong>2,7%</strong></td><td><strong>0,3%</strong></td><td>39,5%</td><td>63,6%</td></tr><tr><td>Europe</td><td>16 704</td><td>32 598</td><td>27 131</td><td>18 638</td><td>11 955</td><td><strong>1,9%</strong></td><td><strong>1,2%</strong></td><td>21,5%</td><td>31,3%</td></tr><tr><td>Austria</td><td>384</td><td>43 651</td><td>35 699</td><td>26 580</td><td>16 595</td><td><strong>2,0%</strong></td><td><strong>1,3%</strong></td><td>19,9%</td><td>25,5%</td></tr><tr><td>Belgium</td><td>466</td><td>40 996</td><td>33 707</td><td>25 222</td><td>15 779</td><td><strong>1,8%</strong></td><td><strong>1,3%</strong></td><td>23,3%</td><td>25,2%</td></tr><tr><td>Denmark</td><td>319</td><td>55 335</td><td>46 373</td><td>33 174</td><td>22 046</td><td><strong>1,8%</strong></td><td><strong>1,1%</strong></td><td>19,5%</td><td>28,5%</td></tr><tr><td>Finland</td><td>232</td><td>42 203</td><td>34 953</td><td>26 965</td><td>14 909</td><td><strong>2,1%</strong></td><td><strong>1,6%</strong></td><td>19,4%</td><td>22,9%</td></tr><tr><td>France</td><td>2 551</td><td>38 151</td><td>32 122</td><td>25 247</td><td>17 372</td><td><strong>1,8%</strong></td><td><strong>1,0%</strong></td><td>15,4%</td><td>21,4%</td></tr><tr><td>Germany</td><td>3 447</td><td>41 696</td><td>35 280</td><td>24 194</td><td>15 403</td><td><strong>1,8%</strong></td><td><strong>1,2%</strong></td><td>22,4%</td><td>31,4%</td></tr><tr><td>Greece</td><td>220</td><td>20 457</td><td>17 148</td><td>11 830</td><td>12 633</td><td><strong>0,8%</strong></td><td><strong>-0,2%</strong></td><td>17,9%</td><td>31,0%</td></tr><tr><td>Ireland</td><td>318</td><td>66 163</td><td>36 490</td><td>26 645</td><td>9 779</td><td><strong>5,0%</strong></td><td><strong>2,7%</strong></td><td>18,8%</td><td>27,0%</td></tr><tr><td>Italy</td><td>1 880</td><td>31 059</td><td>25 746</td><td>17 371</td><td>14 913</td><td><strong>1,2%</strong></td><td><strong>0,4%</strong></td><td>20,6%</td><td>32,5%</td></tr><tr><td>Lux.</td><td>56</td><td>94 524</td><td>53 989</td><td>37 358</td><td>26 580</td><td><strong>3,9%</strong></td><td><strong>0,9%</strong></td><td>20,4%</td><td>30,8%</td></tr><tr><td>Netherlands</td><td>820</td><td>47 848</td><td>40 144</td><td>30 784</td><td>18 872</td><td><strong>2,1%</strong></td><td><strong>1,3%</strong></td><td>18,4%</td><td>23,3%</td></tr><tr><td>Portugal</td><td>212</td><td>20 585</td><td>16 596</td><td>11 125</td><td>7 100</td><td><strong>1,9%</strong></td><td><strong>1,2%</strong></td><td>22,0%</td><td>33,0%</td></tr><tr><td>Spain</td><td>1 340</td><td>28 754</td><td>23 728</td><td>17 628</td><td>9 518</td><td><strong>2,3%</strong></td><td><strong>1,7%</strong></td><td>28,6%</td><td>25,7%</td></tr><tr><td>Sweden</td><td>505</td><td>50 236</td><td>42 692</td><td>33 287</td><td>20 416</td><td><strong>2,2%</strong></td><td><strong>1,3%</strong></td><td>14,5%</td><td>22,0%</td></tr><tr><td>U.-K.</td><td>2 501</td><td>37 865</td><td>32 631</td><td>22 930</td><td>11 927</td><td><strong>2,3%</strong></td><td><strong>1,8%</strong></td><td>27,6%</td><td>29,7%</td></tr></tbody></table>

Let us start with Europe. We find a Real Feel GDP of 18 600 euros per capita, far below per capita GDP (32 600€). The difference is due for 5500 euros to consumption of fixed capital, and the rest (8500€) to the structure of the income distribution. Over the last 37 years, Europe experienced a 1.9% annual GDP growth. In the meantime, real feel growth was much lower, at 1.2%, due mainly (see figure 6 below) to population growth (since real feel GDP is a per capita notion contrary to GDP) and to a sharp rise in inequality, with the Atkinson inequality index jumping from 21.5% in 1980 to 31.3% in 2017.

<footnote n="13">¹³ Enquête sur les revenus fiscaux et sociaux. The French Tax and Social Income Survey aims to analyze incomes according to usual sociodemographic criteria (socio-professional category and age of the persons composing the household, size of the household, activity of each individual, etc.) and to measure the standard of living and the monetary poverty of the people. It compiles data from various sources administrative sources relatives to different types of income and taxes. 1) The individual income received by each member of the household: wages, pensions, pensions, unemployment benefits, agricultural, industrial, commercial and non-commercial benefits. 2) Non-individualizable income: social benefits (family benefits, housing benefits and social benefits) as well as income from assets. 3) Taxes paid by the household (income tax, housing tax and premium for employment).</footnote>
<figure><img src="image_7.png" /><figcaption>Figure 6: From GDP to RealFeel GDP in Europe (1980=100)</figcaption></figure>

Among European countries, with 37 000€ of RFGDP, Luxembourg appears at the top of the ladder in terms of well-being derived from its national income. However, the difference with other European countries is much smaller than per capita GDP would suggest (94 500€), due to a large amount of its production held by foreign shareholders. France and Germany are very close with a RFGDP at around 25 000 euros, despite a slightly greater GDP per capita for the latter country. They experienced almost the same real feel growth until 2008 crisis, with Germany ahead in the 80's and France catching back during the 1996-2001 period (see Figure 7 below).

<figure><img src="image_8.png" /><figcaption>Figure 7: Real Feel GDP for USA, France and Germany (1980=100)</figcaption></figure>

It is for the US that looking at growth through the glasses of Real Feel GDP leads to the most radical changes, compared to the traditional GDP approach. With 47 000€ of gross domestic product per capita, the United States of America appears to be almost 50% richer than European nations (32 500€). In terms of monetary well-being, the situation is reversed. Indeed, the US RFGDP is 14 650 euros, compared as we said before, to 18 600 euros for the European average.

Even more striking is the comparison of growth rates: while GDP average annual growth was of 2.7% from 1980 on, the real feel growth has been close to zero (0,3% on average). This result is due to the very sharp increase in the inequality well documented by Piketty-Saez-Zucman (2017). In particular, they show that the average
income of the bottom 50% of the population has remained flat over the last forty years. Indeed the Atkinson inequality index jumped from 39.5% in 1980 to 63.6% in 2017. What RFGDP says, in addition, is that the consequence of this tremendous inequality increase has been a four decades stagnation in terms of well-being.

<figure><img src="image_9.png" /><figcaption>Figure 8: From GDP to RealFeel GDP in the USA (1970=100)</figcaption></figure>

Interestingly also for economic policy monitoring, economic cycles look very different from a well-being point of view. In this respect, it takes much more time for a country to recover from an economic turndown. Let us examine the double deep after the second oil shock in the United States. Each time it took at most one year to recover the post crisis GDP level; by 1983, US GDP was already 10% above that of 1978; on the contrary, ten years after the oil shock, US RFGDP was still below its 1978 level (see Figure 9 below). The same occurred after the 2007 downturn. By 2016, RFGDP was still below its 2007 level.

<figure><img src="image_10.png" /><figcaption>Figure 9: RealFeelGDP in the US after the 1978 oil shock</figcaption></figure>

As can be seen from Figure 6, the same situation occurred in Europe after the 2008 recession. By 2010, GDP had more or less recovered its pre-crisis level; in terms of real feel growth, the economic downturn lasted seven more years, and the RFGDP recovered only in 2017. The situation was complicated, in terms of economic policies, in the euro zone by the hiatus between French and German situations. While Germany recovered very rapidly, even in terms of RFGDP, helped by its declining demography, French RFGDP went on declining (see Figure 7 and 10 below).
<figure><img src="image_11.png" /><figcaption>Figure 10: From GDP to Real Feel GDP in France (1996=100)</figcaption></figure>

## IV. Accounting for Unemployment: Augmented Real Feel GDP

As mentioned earlier, we do not pretend or even seek to construct a full measure of welfare. On the contrary, we assume to stick as much as possible to the income contribution to welfare. This is the reason not to account for dimensions such as leisure, health or security.

Nonetheless, the exception we may consider is unemployment. Disregards of the social disutility of unemployment, the direct effect of losing his job is to have a sharp decrease in income, more or less important, depending upon how protective are unemployment insurance benefits. In a perfect world, the income loss should be captured by income data; in the real world, they are many good reasons to think that it is not the case. Most surveys rely on ordinary households, and thus exclude a significant part of unemployed persons, particularly among young people.

The second reason to account for unemployment in our effort to measure monetary well-being is to try to incorporate some prospective elements in the evaluation of current monetary well-being. Indeed, well-being is generally defined as the discounted sum of current and future incomes; a higher unemployment rate increases the probability to lose one's job, or the frequency of expected unemployment periods and therefore decreases expected well-being.

Accounting for unemployment implies modifying the utility function as follows:

$$S_j(r_{ij}(t), U_{ij}(t)) = \frac{\alpha}{1 - \tau} r_{ij}(t)^{1-\tau} + \delta U_{ij}(t) + \beta_j$$

where $U_{ij}(t)$ is a dummy equal to 1 if individual $i$ of country $j$ is unemployed at date $t$. An alternative would be, as in Boarini et alii (2006), to calibrate $\tau$, and estimate
satisfaction by income fractile with $\delta$ allowed to be differentiated<fnref n="14" />. Since there is a strong correlation between unemployment status and income, this would lead to lower $\alpha$ and increase $\delta$, leaving the overall result merely unchanged. In addition, whereas they were mainly interested in monetizing none monetary dimensions of well-being, our main goal of computing a real feel GDP, leads us, as discussed before, to focus as much as we can on income effect, unemployment being here only to capture possible income effect we would have otherwise missed.

This new specification has been estimated on the French SRCV survey, setting the parameter $\tau$ at 1.9 as in section III above. The results of the linear estimation are given in table 5 below.

<table><caption>Table 5: Augmented Satisfaction Curve Estimate</caption><thead><tr><th>Variables</th><th>Estimated value</th><th>Standard error</th><th>t-test value</th></tr></thead><tbody><tr><td>Intercept</td><td>β = 8.01540***</td><td>0.03637</td><td>220.40</td></tr><tr><td>r<sub>kt</sub><sup>1-1,9</sup>/(1 - 1,9)</td><td>α = 0.52287***</td><td>0.02503</td><td>20.89</td></tr><tr><td>Unemployment</td><td>δ = -0.70481***</td><td>0.05237</td><td>-13.46</td></tr><tr><td>F value</td><td>381.58</td><td>Root MSE</td><td>98.02454</td></tr><tr><td>R square</td><td>0.0492</td><td>Adjusted R-square</td><td>0.0491</td></tr><tr><td>Year</td><td>2017</td><td>Number of obs.</td><td>14753</td></tr></tbody></table>

We find a very significant effect of unemployment on monetary well-being<fnref n="15" />, losing one's job resulting, everything else being equal, in a 0.7 decrease in life satisfaction.

We then apply these values to estimates of national welfares. The new expression for total welfare of country j at time t is now:

$$W_j(r_{1,j}(t), r_{2,j}(t), \dots, r_{n_j(t),j}(t), UR_j(t)) = \frac{\alpha}{1-\tau} \frac{1}{n_j(t)} \sum_{i=1}^{n_j(t)} r_{i,j}(t)^{1-\tau} + \delta UR_j(t) + \beta_j$$

where $UR_j(t)$ is the unemployment rate of country j at date t. Absolute equivalent income (augRFGDP from now on) is as before defined as the solution of:

$$W_j(r_{1,j}(t), r_{2,j}(t), \dots, r_{n_j(t),j}(t), UR_j(t)) = W_j(\text{augRFGDP}_j(t), \dots, \text{augRFGDP}_j(t), \overline{UR})$$

where $\overline{ur}$ is the unemployment rate assumed to be representative of full employment. One can easily show<fnref n="16" /> that the augmented Real Feel GDP can be derived from RFGDP and the unemployment rate according to:

<footnote n="14">¹⁴ Indeed, they compute, on aggregated cross country distribution data, an equivalent income by quintile using a satisfaction function equal to $S(r_{kj}(t)) = \frac{\alpha_k}{1-\tau} r_{kj}(t)^{1-\tau} + \delta_k U_{kj}(t) + \mu_k H_{kj}(t)$ where $U_{kj}(t)$ and $H_{kj}(t)$ are respectively unemployment rate and life expectancy of quintile k, in country j, at date t</footnote>

<footnote n="15">¹⁵ We certainly also capture purely subjective effect link we unemployment status, which justify a specific denomination for the synthetic index accounting for unemployment.</footnote>

<footnote n="16">¹⁶ $W_j(\{r_{ij}(t), ur_j(t)\}) = W_j(\{\text{augRFGDP}_j(t), \overline{UR}\}) \leftrightarrow \frac{\alpha}{1-\tau}(\text{augRFGDPext}_{jt})^{1-\tau} + \delta \overline{UR} + \beta_j = \frac{\alpha}{1-\tau} \frac{1}{n_j(t)} \sum_{i=1}^{n_j(t)} r_{ijt}^{1-\tau} + \delta UR_j(t) + \beta_j \leftrightarrow \text{augRFGDP}_j(t)^{1-\tau} = \frac{1}{n_j(t)} \sum_{i=1}^{n_j(t)} r_{ij}(t)^{1-\tau} - \frac{\delta}{\alpha}(\tau-1)(UR_j(t) - \overline{UR}) \leftrightarrow \text{augRFGDP}_j(t)^{1-\tau} = \left[ \frac{1}{n_j(t)} \sum_{i=1}^{n_j(t)} r_{ij}(t)^{1-\tau} - \frac{\delta}{\alpha}(\tau-1)(UR_j(t) - \overline{UR}) \right]^{1/(1-\tau)} \leftrightarrow \text{augRFGDP}_j(t) = \left[ \text{RFGDP}_j(t)^{1-\tau} - \frac{\delta}{\alpha}(\tau-1)(UR_j(t) - \overline{UR}) \right]^{1/(1-\tau)}$</footnote>
$$augRFGDP_j(t) = \left[ RFGDP_j(t)^{1-\tau} - \frac{\delta}{\alpha}(\tau-1)(UR_j(t) - \overline{UR}) \right]^{1/(1-\tau)}$$

<figure><img src="image_12.png" /><figcaption>Figure 11: French and German GDP and Real Feel GDP During Post 2008 Recovery</figcaption></figure>

The unemployment effect is far from negligible. For instance, in 2011, three years after the September 2008 downturn, French GDP was already 1.3% above its pre-crisis level, augmented RFGDP at 8% below (see Figure 11 above). Moreover, nine years after the outbreak of the crisis, well-being monetary of France was still 4% below its 2008 level. Real Feel GDP also shows another face of the German recovery during the same period. Take period 2012-2014: while GDP was still growing, Real Feel GDP was falling. On the one hand, a growth that just slowed down, on the other a double deep! By 2015, GDP is 6,2% above 2008's and RFGDP yet 0,5% below.

<figure><img src="image_13.png" /><figcaption>Figure 12: Augmented RealFeelGDP for USA (1970=100)</figcaption></figure>

Figure 12 compares Real Feel GDP and the augmented RDGDP of the USA on a longer period. In terms of well-being loss, unemployment played also an important specific role, additional to the fall of GDP:-4,5% in 1982 and 1983,and -3,3% in
2008. Nevertheless, those effects are mainly cyclical. What happened structurally, during this period, in terms of well-being was played out behind the GDP/unemployment scenes, with the continual and unprecedented rise of inequality.

## V. Robustness

As said before, very critical in our results is the satisfaction function estimate. In the limit, in a world with infinite income substitution elasticity, Real Feel GDP would be equal to GDP, or more precisely to per capita net national product. That is the reason we took great care in estimating the τ parameter, confronting microeconomic data estimates on large samples surveys, and cross-country assessments.

In this section, we examine a question that we have temporarily left out. We have done so far as if the answers to the survey question on life satisfaction was life satisfaction itself. However, the people surveyed are not asked to rate their well-being freely, but to do so in a scale of 0 to 10, 0 meaning as already said, “not at all satisfied”, and 10 “very satisfied”. What happens if one year I answer 10, and that the following year, I feel even more satisfied in life: I would be forced by the questionnaire to answer 10 while I would have liked to spontaneously note my life at 11, 12 or more.

This classical truncation effect could have a particularly damaging effect for our purpose, since it could bring out the monetary well-being function more curved than it really is. To look at this question, we first examine the distribution of life satisfaction for the bottom 10%, the richest 10%, and the richest 1%. Figure 13 suggests that this phenomenon exists, but is not likely to modify in a determining way our results. First, among the 10% at the top of the income ladder, only 8% answer 10. Say otherwise, 92% of them are not constrained by the 10 ceiling of the Cantril ladder. The percentage of 10 increases as income rises, but very slightly, reaching 10% for the 1% richer, while 7% of the 10% poorest also answer to be very satisfied of their life.

<figure><img src="image_14.png" /><figcaption>Figure 13: Life Satisfaction Distribution by Income Group</figcaption></figure>
By the way, these distributions from the French SRCV surveys confirm a standard result concerning the economic determinants of well-being : money does not make happiness, but lacking money makes life more difficult : 40% of the poorest 10% rate their life satisfaction less than or equal to 5 ; the percentage is of 5% for the 10% richest.

The effect of truncation is therefore weak, but it exists, as shown by the slightly bent appearance of the distributions between 9 and 10. We will here estimate the consequences. To do so, we assume here that satisfaction is a continuous variable determined by $s_i = a(1 - \tau)(r_i/\bar{r})^{1-\tau} + b + \varepsilon_i$ where $\varepsilon_i$ is a randomly distributed residual with respectively density f and cumulative density F. We note $R_i(s_i)$ the discrete answer ranking from 0 to 10 of individual i when surveyed on life satisfaction. Individual i is supposed to answer k if $k - 1 + \delta_{k-1} \le s_i < k + \delta_k$ hence :

$$p(R_i = k) = F^{-1}(k + \delta_k - a/(1 - \tau)(r_i/\bar{r})^{1-\tau} - b) - F^{-1}(k - 1 + \delta_{k-1} - a/(1 - \tau)(r_i/\bar{r})^{1-\tau} - b)$$

This implies:

$$F(p(R_i \le k)) = k + \delta_k - a/(1 - \tau)(r_i/\bar{r})^{1-\tau} - b$$

We recognize here the logistic model $g(p(R_i = k)) = \alpha_k + \beta x$ with the link function g equals to F, $x = (r_i/\bar{r})^{1-\tau}$, $\beta = a/(1 - \tau)$, and $\alpha_k = k + \delta_k - b$. We first estimate the parameter $\tau$ with maximum likelihood method.

We used alternatively, as link functions, a cumulative probit or cumulative logit. In both cases, the optimal value is 1.90, a value logically smaller than the one obtained through ordinary least square (1.90 versus 2.097), but, as could also be inferred from the distribution curve of graphic 14 above, the OLS bias is quite low.

<figure><img src="image_15.png" /><figcaption>Figure 14: Maximum Likelihood Estimate of $\tau$ with Logistic Model for Satisfaction</figcaption></figure>

Full results for the logistic case with parameter $\tau$ equal to 1.90 are shown on table 6 below. This table also shows the estimated range of S for each value of the Cantril
ladder ($k - 1 + \delta_{k-1} \le s_i < k + \delta_k$). We would expect at least that $k + \delta_k$ would be lower than $k + 1$, which is generally the case.

The exception is for $R$ equal to 0 and 1: answers are 0 until $S=1,7$ while we would expect a answer of 1 for $S<1$; the shift is much smaller for $R=1$ since the rank here is $1,7<S<2,2$ for an expected bracket of $1<S<2$. Beyond that point, all results are consistent: $R=2$ for $S$ between 2.2 and 2.8 for an expected bracket of $2<S<3$, $R=3$ for $S$ between 2.8 and 3.6...and so on. The three widest ranges are, in decreasing order, for 8, for 7 and for 5, unsurprisingly for 5 and 8 since we already noticed concentration of the distribution on those two values (see figure 14).

<table><caption>Table 6: Estimate of Satisfaction Curve Using Logit Model</caption><thead><tr><th>Variables</th><th>Estimated value</th><th>Standard error</th><th>Estimated Range for S</th><th>Cantril ladder (R(S))</th></tr></thead><tbody><tr><td>r<sub>i</sub><sup>1-1,90</sup>/(1 - 0,90)</td><td>-0.6417***</td><td>0.000462</td><td></td><td></td></tr><tr><td>α<sub>0</sub></td><td>-6.2699***</td><td>0.00212</td><td>-∞ &lt;S&lt;1,7</td><td>0</td></tr><tr><td>α<sub>1</sub></td><td>-5.8030***</td><td>0.00174</td><td>1,7&lt;S&lt;2,2</td><td>1</td></tr><tr><td>α<sub>2</sub></td><td>-5.1580***</td><td>0.00135</td><td>2,2&lt;S&lt;2,8</td><td>2</td></tr><tr><td>α<sub>3</sub></td><td>-4.3444***</td><td>0.00104</td><td>2,8&lt;S&lt;3,6</td><td>3</td></tr><tr><td>α<sub>4</sub></td><td>-3.6909***</td><td>0.000897</td><td>3,6&lt;S&lt;4,3</td><td>4</td></tr><tr><td>α<sub>5</sub></td><td>-2.6344***</td><td>0.000767</td><td>4,3&lt;S&lt;5,3</td><td>5</td></tr><tr><td>α<sub>6</sub></td><td>-1.9204***</td><td>0.000719</td><td>5,3&lt;S&lt;6,0</td><td>6</td></tr><tr><td>α<sub>7</sub></td><td>-0.8882***</td><td>0.000678</td><td>6,0&lt;S&lt;7,1</td><td>7</td></tr><tr><td>α<sub>8</sub></td><td>0.6421***</td><td>0.000683</td><td>7,1&lt;S&lt;8,6</td><td>8</td></tr><tr><td>α<sub>9</sub></td><td>1.8333***</td><td>0.000797</td><td>8,6&lt;S&lt;9,8</td><td>9</td></tr></tbody></table>

All in all, we can retain a constant elasticity function of income, with parameter $\tau$ equal to 2.0, and a margin of error of 0.3, as the best proxy for monetary well-being.

<figure><img src="image_16.png" /><figcaption>Figure 15: Impact of $\tau$ on Real-Feel GDP (USA 1970-2017)</figcaption></figure>

Figure 15 above shows how Real GDP is affected when skipping from bottom (1.7) to the top of the margin of error (2.3).
## VI. Concluding remarks

As recommended by the Stiglitz commission, we attempted to define a synthetic indicator that could help decision makers to better monitor economic policies, in achieving, to use the words of the Stiglitz report, to be a compass that really indicate the direction of well-being improvement.

In the tradition of previous works on equivalent income, we define a monetary measure of the welfare provided by national income. Intending to stick, as best as we can, to monetary aspects of well-being, we focused on the distribution of disposable income. In this respect, the synthetic indicator we try to build is more to be classified as “besides” GDP than “beyond” GDP. Nonetheless, we also account for unemployment as a proxy for future income taking into account the risk of losing one's job.

We call this new indicator real feel GDP in reference of meteorologist real feel temperature. The parallel is not just a question of calling. Whereas real feel temperature measures real heat flows between the inside and outside the body, real feel GDP measures how income is really –or not– distributed to the largest fraction a population’s country. We could just as well have called our indicator “distributed GDP” or “really distributed GDP”.

Since this is critical, we paid much attention to the estimation of the underlying life satisfaction function, using French Micro Data and satisfaction variables from the Euro-SILC surveys. We also controlled for possible truncation effects with Logit and Probit estimates. Using long run WIL word distributional data starting from the 70’s, we find this new indicator sheds new light on the economic histories of Europe and the USA over the last forty years. Indeed, while GDP more than tripled from the 70’s in the US, Real Feel GDP remained absolutely flat, meaning that growth did not increased welfare of the many for the last 40 years.

In the meantime, in France and most European countries, except in the recent years, Real Feel GDP and GDP evolved similarly. We also find that economic downturns lasted much longer than measured by GDP: US Real Feel GDP took 10 years to recover the before crisis level after the second petrol shock ; in 2018, almost 10 years after 2008 downturn, Europe Real Feel GDP has not yet recover pre-crisis level.
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ROSENWALD<br>Investment et contraintes de financement : le poids du cycle</td></tr><tr><td>G 2000/06</td><td>Une estimation sur données françaises<br>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. AUDENS - 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></table>
<table><tr><td>G 2000/10</td><td>R. DUHAUTOIS</td><td>Ralentissement de l'investissement : petites ou grandes entreprises ? industrie ou tertiaire ?</td></tr><tr><td>G 2000/11</td><td>G. LAROQUE - B. SALANIÉ</td><td>Temps partiel féminin et incitatives financières à l'emploi</td></tr><tr><td>G 2000/12</td><td>Ch. GIANELLA</td><td>Local unemployment and wages</td></tr><tr><td>G 2000/13</td><td>B. CREPON - Th. HECKEL</td><td>Informalité en France : une évaluation à partir de données individuelles</td></tr><tr><td>G 2001/01</td><td>F. LEQUILLER</td><td>- La nouvelle économie et la mesure de la croissance du PIB - The new economy and the measure of GDP growth</td></tr><tr><td>G 2001/02</td><td>S. AUDRIC</td><td>La reprise de la croissance de l'emploi profite-t-elle aussi aux non-riploèmes ?</td></tr><tr><td>G 2001/03</td><td>I. BRAJUN-LEMAIRE</td><td>Évolution et répartition du surplus de productivité</td></tr><tr><td>G 2001/04</td><td>A. BEAUDU - Th. HECKEL</td><td>Le canal du crédit fonctionne-t-il en Europe ? Une étude de l'haproférance des comportements d'investissement à partir de données de bilan agrégées</td></tr><tr><td>G 2001/05</td><td>C. AUDENIS - P. BISCOURP - N. FOURCADE - O. LOISEL</td><td>Testing the augmented Solow growth model: An empirical reassessment using panel data</td></tr><tr><td>G 2001/06</td><td>R. MAHIEU - B. SÉDILLOT</td><td>Départ à la retraite, irréversibilité et incertitude</td></tr><tr><td>G 2001/07</td><td>J. Ph. GAUDEMET</td><td>Bilan des activités de la DESE - 2000</td></tr><tr><td>G 2001/08</td><td>B. CRÉPON - Ch. GIANELLA</td><td>Les dispositifs d'acquisition à titre facultatif d'annuïtés viagères de retraite</td></tr><tr><td>G 2001/09</td><td>B. CRÉPON - Ch. GIANELLA</td><td>Fiscalité, coût d'usage du capital et demande de facteurs : une analyse sur données individuelles</td></tr><tr><td>G 2001/10</td><td>B. CRÉPON - R. DESPLATZ</td><td>Évaluation des effets des dispositifs d'alégements</td></tr><tr><td>G 2001/11</td><td>J.-Y. FOURNIER</td><td>Comparaison des salaires des secteurs public et privé</td></tr><tr><td>G 2001/12</td><td>J.-P. BERTHIER - C. JAULENT</td><td>R. CONVENEVOLE - S. PISANI</td></tr><tr><td>G 2001/13</td><td>P. BISCOURP - Ch. GIANELLA</td><td>Substitution and complementarity between capital, skilled and less skilled workers: an analysis at the firm level in the French manufacturing industry</td></tr><tr><td>G 2001/14</td><td>I. ROBERT-BOBEE</td><td>Modelling demographic behaviours in the French</td></tr></table>

<table><tr><td>G2002/13</td><td>M. LECLAIR</td><td>Réduction du temps de travail et tensions sur les facteurs de production</td></tr><tr><td>G2002/14</td><td>E. WALRAET - A. VINCENT</td><td>Évaluation de la redistribution intragénérationnelle dans le système de retraite des salariés du privé - Une approche par microsimulation</td></tr><tr><td>G2002/15</td><td>P. CHONE - D. LE BLANC - I. ROBERT-BOBEE</td><td>Offre de travail féminine et garde des jeunes enfants</td></tr><tr><td>G2002/16</td><td>F. MAUREL - S. GREGOIR</td><td>Les indices de compétitivité des pays : interprétation et limites</td></tr><tr><td>G2003/01</td><td>N. RIEDINGER - E.HAUVY</td><td>Le coût de dépollution atmosphérique pour les entreprises françaises: Une estimation à partir de données individuelles</td></tr><tr><td>G2003/02</td><td>P. BISCOURP et F. KRAMARZ</td><td>Création d'emplois, destruction d'emplois et internationalisation des entreprises industrielles françaises: une analyse sur la période 1986-1992</td></tr><tr><td>G2003/03</td><td>Bilan des activités de la DESE - 2002</td><td></td></tr><tr><td>G2003/04</td><td>P.-O. BEFFY - J. DEROYON - N. FOURCADE - S. GREGOIR - N. LAIB - B. MONFORT</td><td>Évolutions démographiques et croissance : une projection macro-économique à l'horizon 2020</td></tr><tr><td>G2003/05</td><td>P. AUBERT</td><td>La situation des salariés de plus de cinquante ans dans le secteur privé</td></tr><tr><td>G2003/06</td><td>P. AUBERT - B. CRÉPON</td><td>Age, salaire et productivité</td></tr><tr><td>G2003/07</td><td>H. BARON - P.O. BEFFY - N. FOURCADE - R. MAHIEU</td><td>La productivité des salariés décline-t-elle en fin de carrière?</td></tr><tr><td>G2003/08</td><td>P. O. BEFFY - B. MONFORT</td><td>Patrimoine des ménages, dynamique d'allocation et comportement de consommation</td></tr><tr><td>G2003/09</td><td>P. BISCOURP - N. FOURCADE</td><td>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</td></tr><tr><td>G2003/10</td><td>M. LECLAIR - P. PETIT</td><td>Présence syndicale dans les firmes : quel impact sur les inégalités salariales entre les hommes et les femmes?</td></tr><tr><td>G2003/11</td><td>P. O. BEFFY - X. BONNET - M. DARRACO-PARIES - B. MONFORT</td><td>Les comportements démographiques dans le modèle de microsimulation DESTINIE - Une comparaison des estimations issues des enquêtes Jeunes et Carrières 1997 et Histoire Famillelle 1999</td></tr><tr><td>G2003/12</td><td>J.-P. ZOYEM</td><td>La dynamique des bas revenus : une analyse des entrées-sorties de pauvreté</td></tr><tr><td>G2003/13</td><td>F. HILD</td><td>Prévisions d'inflation pour la France</td></tr></table>

<table><tr><td>G2002/13</td><td>M. LECLAIR</td><td>Réduction du temps de travail et tensions sur les facteurs de production</td></tr><tr><td>G2002/14</td><td>E. WALRAET - A. VINCENT</td><td>Évaluation de la redistribution intragénérationnelle dans le système de retraite des salariés du privé - Une approche par microsimulation</td></tr><tr><td>G2002/15</td><td>P. CHONE - D. LE BLANC - I. ROBERT-BOBEE</td><td>Offre de travail féminine et garde des jeunes enfants</td></tr><tr><td>G2002/16</td><td>F. MAUREL - S. GREGOIR</td><td>Les indices de compétitivité des pays : interprétation et limites</td></tr><tr><td>G2003/01</td><td>N. RIEDINGER - E.HAUVY</td><td>Le coût de dépollution atmosphérique pour les entreprises françaises: Une estimation à partir de données individuelles</td></tr><tr><td>G2003/02</td><td>P. BISCOURP et F. KRAMARZ</td><td>Création d'emplois, destruction d'emplois et internationalisation des entreprises industrielles françaises: une analyse sur la période 1986-1992</td></tr><tr><td>G2003/03</td><td>Bilan des activités de la DESE - 2002</td><td></td></tr><tr><td>G2003/04</td><td>P.-O. BEFFY - J. DEROYON - N. FOURCADE - S. GREGOIR - N. LAIB - B. MONFORT</td><td>Évolutions démographiques et croissance : une projection macro-économique à l'horizon 2020</td></tr><tr><td>G2003/05</td><td>P. AUBERT</td><td>La situation des salariés de plus de cinquante ans dans le secteur privé</td></tr><tr><td>G2003/06</td><td>P. AUBERT - B. CRÉPON</td><td>Age, salaire et productivité</td></tr><tr><td>G2003/07</td><td>H. BARON - P.O. BEFFY - N. FOURCADE - R. MAHIEU</td><td>La productivité des salariés décline-t-elle en fin de carrière?</td></tr><tr><td>G2003/08</td><td>P. O. BEFFY - B. MONFORT</td><td>Patrimoine des ménages, dynamique d'allocation et comportement de consommation</td></tr><tr><td>G2003/09</td><td>P. BISCOURP - N. FOURCADE</td><td>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</td></tr><tr><td>G2003/10</td><td>M. LECLAIR - P. PETIT</td><td>Présence syndicale dans les firmes : quel impact sur les inégalités salariales entre les hommes et les femmes?</td></tr><tr><td>G2003/11</td><td>P. O. BEFFY - X. BONNET - M. DARRACO-PARIES - B. MONFORT</td><td>Les comportements démographiques dans le modèle de microsimulation DESTINIE - Une comparaison des estimations issues des enquêtes Jeunes et Carrières 1997 et Histoire Famillelle 1999</td></tr><tr><td>G2003/12</td><td>J.-P. ZOYEM</td><td>La dynamique des bas revenus : une analyse des entrées-sorties de pauvreté</td></tr><tr><td>G2003/13</td><td>F. HILD</td><td>Prévisions d'inflation pour la France</td></tr></table>

<table><tr><td>G2004/02</td><td>M. DUÈE - C. REBILLARD</td><td>La dépendance des personnes âgées : une projection à long terme</td></tr><tr><td>G2004/03</td><td>S. RASPILLER - N. RIEDINGER</td><td>Réglation environnementale et choix de localisation des groupes français</td></tr><tr><td>G2004/04</td><td>A. NABOULET - S. RASPILLER</td><td>Les déterminants de la décision d'investir: une approche par les perceptions subjectives des firmes</td></tr><tr><td>G2004/05</td><td>N. RAGACHE</td><td>La déclaration des enfants par les couples non mariés est-elle fiscalement optimale?</td></tr><tr><td>G2004/06</td><td>M. DUÈE</td><td>L'impact du chômage des parents sur le devenir scolaire des enfants</td></tr><tr><td>G2004/07</td><td>P. AUBERT - E. CAROLI - M. ROGER</td><td>New Technologies, Workplace Organisation and the Age Structure of the Workforce: Firm-Level Evidence</td></tr><tr><td>G2004/08</td><td>E. DUGUET - C. LELARGE</td><td>Les brevets acquis-ils les incitations privées à innover? Un examen microéconomique</td></tr><tr><td>G2004/09</td><td>S. RASPILLER - P. SILLARD</td><td>Affiliating versus Subcontracting: the Case of Multinationals</td></tr><tr><td>G2004/10</td><td>J. BOISSINOT - C. L'ANGEVIN - B. MONFORT</td><td>Public Debt Sustainability: Some Results on the French Case</td></tr><tr><td>G2004/11</td><td>S. ANANIAN - P. AUBERT</td><td>Travailleurs âgés, nouvelles technologies et changements organisationnels: un réexamen à partir de l'enquête «REPONSE»?</td></tr><tr><td>G2004/12</td><td>X. BONNET - H. PONCET</td><td>Structures de revenus et propensions différentes à consommer - Vers une équation de consommation des ménages plus robuste en prévision pour la France</td></tr><tr><td>G2004/13</td><td>C. PICART</td><td>Évaluer la rentabilité des sociétés non financières</td></tr><tr><td>G2004/14</td><td>J. BARDAJI - B. SÉDILLOT - E. WALRAET</td><td>Les retraites du secteur public: projections à l'horizon 2040 à l'aide du modèle de microsimulation DESTINIE</td></tr><tr><td>G2005/01</td><td>S. BUFFETEAU - P. GODEFROY</td><td>Conditions de départ en retraite selon l'âge de fin d'études: analyse prospective pour les générations 1945 à 1974</td></tr><tr><td>G2005/02</td><td>C. AFSA - S. BUFFETEAU</td><td>L'évolution de l'activité féminine en France: une approche par pseudo-panel</td></tr><tr><td>G2005/03</td><td>P. AUBERT - P. SILLARD</td><td>Délocalisations et réductions d'effectifs dans l'industrie française</td></tr><tr><td>G2005/04</td><td>M. LECLAIR - S. ROUX</td><td>Mesure et utilisation des emplois instables dans les entreprises</td></tr><tr><td>G2005/05</td><td>C. L'ANGEVIN - S. SERRAVALLE</td><td>Performances à l'exportation de la France</td></tr></table>
<table>
  <tr>
    <td>G2005/06</td>
    <td>Bilan des activités de la Direction des Études et Synthèses Économiques - 2004</td>
  </tr>
  <tr>
    <td>G2005/07</td>
    <td>S. RASPILLER<br/>La concurrence fiscale : principaux enseignements de l'analyse économique</td>
  </tr>
  <tr>
    <td>G2005/08</td>
    <td>C. L'ANGEVIN - N. LAIB<br/>Éducation et croissance en France et dans un panel de 21 pays de l'OCDE</td>
  </tr>
  <tr>
    <td>G2005/09</td>
    <td>N. FERRARI<br/>Prévoir l'investissement des entreprises<br/>Un indicateur des révisions dans l'enquête de conjoncture sur les investissements dans l'industrie.</td>
  </tr>
  <tr>
    <td>G2005/10</td>
    <td>P.O. BEFFY - C. L'ANGEVIN<br/>Chromage et boucle prix-salaires :<br/>apport d'un modèle « qualifiés/peu qualifiés »</td>
  </tr>
  <tr>
    <td>G2005/11</td>
    <td>B. HEITZ<br/>A two-states Markov-switching model of inflation in France and the USA: credible target VS inflation spiral</td>
  </tr>
  <tr>
    <td>G2005/12</td>
    <td>O. BIAU - H. ERKEL-ROUSSE - N. FERRARI<br/>Réponses individuelles aux enjuvés de conjoncture et prévision macroéconomiques :<br/>Exemple de la prévision de la production<br/>manufacture</td>
  </tr>
  <tr>
    <td>G2005/13</td>
    <td>P. AUBERT - D. BLANCHET - D. BLAU<br/>The labour market after 50: some elements of a Franco-American comparison</td>
  </tr>
  <tr>
    <td>G2005/14</td>
    <td>D. BLANCHET - T. DEBRAND -<br/>P. DOUGRON - P. POLLET<br/>L'enquête SHARE : présentation et premiers résultats de l'édition française</td>
  </tr>
  <tr>
    <td>G2005/15</td>
    <td>M. DUÉE<br/>La modélisation des comportements démographiques dans le modèle de microsimulation<br/>DESTINE</td>
  </tr>
  <tr>
    <td>G2005/16</td>
    <td>H. RAOUI - S. ROUX<br/>Étude de simulation sur la participation versée aux salaires par les entreprises</td>
  </tr>
  <tr>
    <td>G2006/01</td>
    <td>C. BONNET - S. BUFFETEAU - P. GODEFROY<br/>Disparités de retraite de droit direct entre hommes et femmes : quelles évolutions ?</td>
  </tr>
  <tr>
    <td>G2006/02</td>
    <td>C. PICART<br/>Les gazelles en France</td>
  </tr>
  <tr>
    <td>G2006/03</td>
    <td>P. AUBERT - B. CRÉPON - P. ZAMORA<br/>Le rendement apparent de la formation continue dans les entreprises : effets sur la productivité et les salaires</td>
  </tr>
  <tr>
    <td>G2006/04</td>
    <td>J.-F. OUVRARD - R. RATHELOT<br/>Demographic change and unemployment:<br/>what do macroeconomic models predict?</td>
  </tr>
  <tr>
    <td>G2006/05</td>
    <td>D. BLANCHET - J.-F. OUVRARD<br/>Indicateurs d'engagements implicites des systèmes de retraite : chiffrages, propriétés analytiques et réactions à des chocs démographiques types</td>
  </tr>
  <tr>
    <td>G2006/06</td>
    <td>G. BIAU - O. BIAU - L. ROUVIERE<br/>Nonparametric Forecasting of the Manufacturing Output Growth with Firm-level Survey Data</td>
  </tr>
</table>

<table>
  <tr>
    <td>G2006/07</td>
    <td>C. AFSA - P. GIVORD<br/>Le rôle des conditions de travail dans les absences pour maladie</td>
  </tr>
  <tr>
    <td>G2006/08</td>
    <td>P. SILLARD - C. L'ANGEVIN - S. SERRAVALLE<br/>Performances comparées à l'exportation de la France et de ses principaux partenaires<br/>Une analyse structurelle sur 12 ans</td>
  </tr>
  <tr>
    <td>G2006/09</td>
    <td>X. BOUTIN - S. QUANTIN<br/>Une méthodologie d'évaluation comptable du coût du capital des entreprises françaises : 1984-2002</td>
  </tr>
  <tr>
    <td>G2006/10</td>
    <td>C. AFSA<br/>L'estimation d'un coût implicite de la pénibilité du travail chez les travailleurs âgés</td>
  </tr>
  <tr>
    <td>G2006/11</td>
    <td>C. LELARGE<br/>Les entreprises (industrielles) françaises sont-elles à la frontière technologique ?</td>
  </tr>
  <tr>
    <td>G2006/12</td>
    <td>O. BIAU - N. FERRARI<br/>Théorie de l'opinion<br/>Faut-il pondérer les réponses individuelles ?</td>
  </tr>
  <tr>
    <td>G2006/13</td>
    <td>A. KOUBI - S. ROUX<br/>Une réinterprétation de la relation entre productivité et inégalités salariales dans les entreprises</td>
  </tr>
  <tr>
    <td>G2006/14</td>
    <td>R. RATHELOT - P. SILLARD<br/>The impact of local taxes on plants location decision</td>
  </tr>
  <tr>
    <td>G2006/15</td>
    <td>L. GONZALEZ - C. PICART<br/>Diversification, recensement et poids des activités de support dans les groupes (1995-2000)</td>
  </tr>
  <tr>
    <td>G2007/01</td>
    <td>D. SRAER<br/>Allegements de cotisations patronales et dynamique salariale</td>
  </tr>
  <tr>
    <td>G2007/02</td>
    <td>V. ALBOUY - L. LEQUIEN<br/>Les rendements non monotaires de l'éducation :<br/>le cas de la santé</td>
  </tr>
  <tr>
    <td>G2007/03</td>
    <td>D. BLANCHET - T. DEBRAND<br/>Aspiration à la retraite, santé et satisfaction au travail : une comparaison européenne</td>
  </tr>
  <tr>
    <td>G2007/04</td>
    <td>M. BARLET - L. CRUSSON<br/>Quel impact des variations du prix du pétrole sur la croissance française ?</td>
  </tr>
  <tr>
    <td>G2007/05</td>
    <td>C. PICART<br/>Flux d'emploi et de main-d'œuvre en France : un réexamen</td>
  </tr>
  <tr>
    <td>G2007/06</td>
    <td>V. ALBOUY - C. TAVAN<br/>Massification et démocratisation de l'enseignement supérieur en France</td>
  </tr>
  <tr>
    <td>G2007/07</td>
    <td>T. LE BARBANCHON<br/>The Changing response to oil price shocks in France, a DSGE type approach</td>
  </tr>
  <tr>
    <td>G2007/08</td>
    <td>T. CHANEY - D. SRAER - D. THESMAR<br/>Collateral Value and Corporate Investment<br/>Evidence from the French Real Estate Market</td>
  </tr>
  <tr>
    <td>G2007/09</td>
    <td>J. BOISSINOT<br/>Consumption over the Life Cycle: Facts for France</td>
  </tr>
  <tr>
    <td>G2007/10</td>
    <td>C. AFSA<br/>Interpréter les variables de satisfaction :<br/>l'exemple de la durée du travail</td>
  </tr>
</table>

<table>
  <tr>
    <td>G2007/11</td>
    <td>R. RATHELOT - P. SILLARD<br/>Zones Franches Urbaines : quels effets sur l'emploi salarié et les créations d'établissements ?</td>
  </tr>
  <tr>
    <td>G2007/12</td>
    <td>V. ALBOUY - B. CRÉPON<br/>Aléa moral en santé : une évaluation dans le cadre du modèle causal de Rubin</td>
  </tr>
  <tr>
    <td>G2008/01</td>
    <td>C. PICART<br/>Les PME françaises : rentables mais peu dynamiques</td>
  </tr>
  <tr>
    <td>G2008/02</td>
    <td>P. BISCOURP - X. BOUTIN - T. VERGÉ<br/>The Effects of Retail Regulations on Prices<br/>Evidence form the Loi Galland</td>
  </tr>
  <tr>
    <td>G2008/03</td>
    <td>Y. BARBESOL - A. BRIANT<br/>Économies d'agglomération et productivité des entreprises : estimation sur données individuelles françaises</td>
  </tr>
  <tr>
    <td>G2008/04</td>
    <td>D. BLANCHET - F. LE GALLO<br/>Les projections démographiques : principaux mécanismes et retour sur l'expérience française</td>
  </tr>
  <tr>
    <td>G2008/05</td>
    <td>D. BLANCHET - F. TOUTLEMONDE<br/>Évolutions démographiques et deformation du cycle de vie active : quelles relations ?</td>
  </tr>
  <tr>
    <td>G2008/06</td>
    <td>M. BARLET - D. BLANCHET - L. CRUSSON<br/>Internationalisation et flux d'emplois : que d'une approche comptable ?</td>
  </tr>
  <tr>
    <td>G2008/07</td>
    <td>C. LELARGE - D. SRAER - D. THESMAR<br/>Entrepreneurship and Credit Constraints - Evidence from a French Loan Guarantee Program</td>
  </tr>
  <tr>
    <td>G2008/08</td>
    <td>X. BOUTIN - L. JANIN<br/>Are Prices Really Affected by Mergers?</td>
  </tr>
  <tr>
    <td>G2008/09</td>
    <td>M. BARLET - A. BRIANT - L. CRUSSON<br/>Concentration géographique dans l'industrie manufacturière et dans les services en France : une approche par un indicateur en continu</td>
  </tr>
  <tr>
    <td>G2008/10</td>
    <td>M. BEFFY - É. COUDIN - R. RATHELOT<br/>Who is confronted to insecure labor market histories? Some evidence based on the French labor market transition</td>
  </tr>
  <tr>
    <td>G2008/11</td>
    <td>M. ROGER - E. WALRAET<br/>Social Security and Well-Being of the Elderly: the Case of France</td>
  </tr>
  <tr>
    <td>G2008/12</td>
    <td>C. AFSA<br/>Analyser les composantes du bien-être et de son évolution<br/>Une approche empirique sur données individuelles</td>
  </tr>
  <tr>
    <td>G2008/13</td>
    <td>M. BARLET - D. BLANCHET -<br/>T. LE BARBANCHON<br/>Microsimumer le marché du travail : un prototype</td>
  </tr>
  <tr>
    <td>G2009/01</td>
    <td>P.-A. PIONNIER<br/>Le partage de la valeur ajoutée en France, 1949-2007</td>
  </tr>
  <tr>
    <td>G2009/02</td>
    <td>Laurent CLAVEL - Christelle MINODIER<br/>A. Monthly Indicator of the French Business Climate</td>
  </tr>
  <tr>
    <td>G2009/03</td>
    <td>H. ERKEL-ROUSSE - C. MINODIER<br/>Do Business Tendency Surveys in Industry and Services Help in Forecasting GDP Growth?<br/>A Real-Time Analysis on French Data</td>
  </tr>
</table>

<table>
  <tr>
    <td>G2009/04</td>
    <td>P. GIVORD - L. WILNER<br/>Les contrats temporaires : trappe ou marchéied vers l'emploi stable ?</td>
  </tr>
  <tr>
    <td>G2009/05</td>
    <td>G. LALANNE - P.-A. PIONNIER - O. SIMON<br/>Le partage des fruits de la croissance de 1950 à 2008 : une approche par les comptes de surplus</td>
  </tr>
  <tr>
    <td>G2009/06</td>
    <td>L. DAVEZIES - X. D'HAULTFOUEUILLE<br/>Faut-il pondérer ?... Ou l'éternelle question de l'économètre confronté à des données d'enquête</td>
  </tr>
  <tr>
    <td>G2009/07</td>
    <td>S. QUANTIN - S. RASPILLER - S. SERRAVALLE<br/>Commerce intragroupe, fiscalité et prix de transferts : une analyse sur données françaises</td>
  </tr>
  <tr>
    <td>G2009/08</td>
    <td>M. CLERC - V. MARCUS<br/>Élastiques-prix des consommations énergétiques des ménages</td>
  </tr>
  <tr>
    <td>G2009/09</td>
    <td>G. LALANNE - E. POULIQUEN - O. SIMON<br/>Prix du pétrole et croissance potentielle à long terme</td>
  </tr>
  <tr>
    <td>G2009/10</td>
    <td>D. BLANCHET - J. LE CACHEUX - V. MARCUS<br/>Adjusted net savings and other approaches to sustainability: some theoretical background</td>
  </tr>
  <tr>
    <td>G2009/11</td>
    <td>V. BELAMY - G. CONSALES - M. FESSEAU -<br/>S. LE LAIDET - É. RAYNAUD<br/>Une décomposition du compte des ménages de la comptabilité nationale par catégorie de ménage en 2003</td>
  </tr>
  <tr>
    <td>G2009/12</td>
    <td>J. BARDAJI - F. TALLET<br/>Detecting Economic Regimes in France: a Qualitative Markov-Switching Indicator Using Mixed Frequency Data</td>
  </tr>
  <tr>
    <td>G2009/13</td>
    <td>R. AEBERHARDT - D. FOUGÈRE -<br/>R. RATHELOT<br/>Discrimination à l'embauche : comment exploiter les procédures de testing ?</td>
  </tr>
  <tr>
    <td>G2009/14</td>
    <td>Y. BARBESOL - P. GIVORD - S. QUANTIN<br/>Partage de la valeur ajoutée, approche par données microéconomiques</td>
  </tr>
  <tr>
    <td>G2009/15</td>
    <td>I. BUONO - G. LALANNE<br/>The Effect of the Uruguay round on the Intensive and Extensive Margins of Trade</td>
  </tr>
  <tr>
    <td>G2010/01</td>
    <td>C. MINODIER<br/>Avantages comparés des séries des premières valeurs publiées et des séries des valeurs révisées - Un exercice de prévision en temps réel<br/>de la croissance trimestrielle du PIB en France</td>
  </tr>
  <tr>
    <td>G2010/02</td>
    <td>V. ALBOUY - L. DAVEZIES - T. DEBRAND<br/>Health Expenditure Models: a Comparison of Five Specifications using Panel Data</td>
  </tr>
  <tr>
    <td>G2010/03</td>
    <td>C. KLEIN - O. SIMON<br/>Le modèle MÉSANGE réestimé en base 2000<br/>Tome 1 - Version avec volumes à prix constants</td>
  </tr>
  <tr>
    <td>G2010/04</td>
    <td>M. É. CLERC - É. COUDIN<br/>L'IPC, miroir de l'évolution du coût de la vie en France ? Ce qu'apporte l'analyse des courbes d'Engel</td>
  </tr>
  <tr>
    <td>G2010/05</td>
    <td>N. CECH-RENAUD - P.-A. CHEVALIER<br/>Les seuils de 10, 20 et 50 salariés : impact sur la taille des entreprises françaises</td>
  </tr>
</table>
<table><tr><td>G2014/10</td><td>B. GARBINTI - P. LAMARCHE<br/>Les hauts revenus epargnent-ile davantage ?</td></tr><tr><td>G2014/11</td><td>D. AUDENAERT - J. BARDAJI - R. LARDEUX -<br/>M. ORAND - M. SICNIC<br/>Wage Resilience in France since the Great<br/>Recession</td></tr><tr><td>G2014/12</td><td>F. ARNAUD - J. BOUSSARD - A. POISSONNIER -<br/>H. SOAL<br/>Computing additive contributions to growth and<br/>other issues for chain-linked quarterly<br/>aggregates</td></tr><tr><td>G2014/13</td><td>H. FRAISSE - F. KRAMARZ - C. PROST<br/>Labor Disputes and Job Flows</td></tr><tr><td>G2014/14</td><td>P. GIVORD - C. GRISLAIN-LETRÉMY<br/>- H. NAEGELE<br/>How does fuel taxation impact new car<br/>purchases? An evaluation using French<br/>consumer-level dataset</td></tr><tr><td>G2014/15</td><td>P. AUBERT - S. RABATÉ<br/>Durée passée en carrière et durée de vie en<br/>retraite : quel partage des gains d'espérance de<br/>vie ?</td></tr><tr><td>G2015/01</td><td>A. POISSONNIER<br/>The walking dead Euler equation<br/>Addressing a challenge to monetary policy<br/>models</td></tr><tr><td>G2015/02</td><td>Y. DUBOIS - A. MARINO<br/>Indicateurs de rendement du système de retraite<br/>français</td></tr><tr><td>G2015/03</td><td>T. MAYER - C. TREVIEN<br/>The impacts of Urban Public Transportation:<br/>Evidence from the Paris Region</td></tr><tr><td>G2015/04</td><td>S.T. LY - A. RIEGERT<br/>Measuring Social Environment Mobility</td></tr><tr><td>G2015/05</td><td>M. A. BEN HALINA - V. HYAFIL-SOLELHAC<br/>M. KOUBI - C. REGAERT<br/>Quel est l'impact du système d'indemnisation<br/>maladie sur la durée des arrêts de travail pour<br/>maladie ?</td></tr><tr><td>G2015/06</td><td>Y. DUBOIS - A. MARINO<br/>Disparités de rendement du système de retraite<br/>dans le secteur privé : approches intergénéra-<br/>tionnelle et intragénérationnelle</td></tr><tr><td>G2015/07</td><td>B. CAMPAGNE - V. ALHENC-GELAS -<br/>J.-B. BERNARD<br/>No evidence of financial accelerator in France</td></tr><tr><td>G2015/08</td><td>Q. LAFFÉTER - M. PAK<br/>Élasticités des recettes fiscales au cycle<br/>économique : étude de trois impôts sur la<br/>période 1979-2013 en France</td></tr><tr><td>G2015/09</td><td>J.-M. DUASSIN-BENICHOU, S. IDMACHICHE,<br/>A. LEDUC et E. POULIQUEN<br/>Les déterminants de l'attractivité de la fonction<br/>publique de l'État</td></tr><tr><td>G2015/10</td><td>P. AUBERT<br/>La modulation du montant de pension selon la<br/>durée de carrière et l'âge de la retraite : quelles<br/>disparités entre assurés ?</td></tr><tr><td>G2015/11</td><td>V. DORTET-BERNADET - M. SICNIC<br/>Effet des aides publiques sur l'emploi en R&D<br/>dans les petites entreprises</td></tr></table>

<table><tr><td>G2015/12</td><td>S. GEORGES-KOT<br/>Annual and lifetime incidence of the value-added<br/>tax in France</td></tr><tr><td>G2015/13</td><td>M. POULHÉS<br/>Are Enterprise Zones Benefits Capitalized into<br/>Commercial Property Values? The French Case</td></tr><tr><td>G2015/14</td><td>J.-B. BERNARD - Q. LAFFÉTER<br/>Effet d'activité et prix sur le revenu salarial<br/>des différentes catégories socioprofessionnelles</td></tr><tr><td>G2015/15</td><td>C. GEAY - M. KOUBI - G de LAGASNERIE<br/>Projections des dépenses de soins de ville,<br/>construction d'un module pour Destinine</td></tr><tr><td>G2015/16</td><td>J. BARDAJI - J.-C. BRICONGNE -<br/>B. CAMPAGNE - G. GAULIER<br/>Compared performances of French companies<br/>on the domestic and foreign markets</td></tr><tr><td>G2015/17</td><td>C. BELLÉGO - R. DE NUJ<br/>The redistributive effect of online piracy on the<br/>box office performance of American movies in<br/>foreign markets</td></tr><tr><td>G2015/18</td><td>J.-B. BERNARD - L. BERTHET<br/>French households financial wealth: which<br/>changes in 20 years?</td></tr><tr><td>G2015/19</td><td>M. POULHÉS<br/>Fenêtre sur Cour ou Chambre avec Vue ?<br/>Les prix hédoniques de l'immobilier parisien</td></tr><tr><td>G2016/01</td><td>B. GARBINTI - S. GEORGES-KOT<br/>Time to smell the roses? Risk aversion, the<br/>timing of inheritance receipt, and retirement</td></tr><tr><td>G2016/02</td><td>P. CHARNOZ - C. LELARGE - C. TREVIEN<br/>Communication Costs and the Internal<br/>Organization of Multi-Plant Businesses; Evidence<br/>from the Impact of the French High-Speed Rail</td></tr><tr><td>G2016/03</td><td>C. BONNET - B. GARBINTI - A. SOLAZ<br/>Gender inequality after Divorce: The Flip Side of<br/>Marital Specialization - Evidence from a French<br/>Administrative Database</td></tr><tr><td>G2016/04</td><td>D. BLANCHET - E. CAROLI - C. PROST -<br/>M. ROGER<br/>Health capacity to work at older ages in France</td></tr><tr><td>G2016/05</td><td>B. CAMPAGNE - A. POISSONNIER<br/>MELEZE: A DSGE model for France within the<br/>Euro Area</td></tr><tr><td>G2016/06</td><td>B. CAMPAGNE - A. POISSONNIER<br/>Laffer curves and fiscal multipliers: lessons from<br/>Mélèze model</td></tr><tr><td>G2016/07</td><td>B. CAMPAGNE - A. POISSONNIER<br/>Structural reforms in DSGE models: a case for<br/>sensitivity analyses</td></tr><tr><td>G2016/08</td><td>Y. DUBOIS et M. KOUBI<br/>Relevement de l'âge de départ à la retraite : quel<br/>impact sur l'activité des seniors de la réforme des<br/>retraites de 2010 ?</td></tr><tr><td>G2016/09</td><td>A. NAQUAS - M. ORAND - I. SLIMANI HOUTI<br/>Les entreprises employant des salaires au Smic :<br/>quelles caractéristiques et quelle rentabilité ?</td></tr><tr><td>G2016/10</td><td>T. BLANCHET - Y. DUBOIS - A. MARINO -<br/>M. ROGER<br/>Patrimoine privé et retraite en France</td></tr><tr><td>G2016/11</td><td>M. PAK - A. POISSONNIER<br/>Accounting for technology, trade and final</td></tr></table>

<table><tr><td>G2017/01</td><td>D. FOUGÈRE - E. GAUTIER - S. ROUX<br/>Understanding Wage Floor Setting in Industry-<br/>Level Agreements: Evidence from France</td></tr><tr><td>G2017/02</td><td>Y. DUBOIS - M. KOUBI<br/>Règles d'indexation des pensions et sensibilité<br/>des dépenses de retraites à la croissance<br/>économique et aux chocs démographiques</td></tr><tr><td>G2017/03</td><td>A. CAZENAVE-LACROUTZ - F. GODET<br/>L'espérance de vie en retraite sans incapacité<br/>sèvère des générations nées entre 1960 et<br/>1990 : une projection à partir du modèle Destinine</td></tr><tr><td>G2017/04</td><td>J. BARDAJI - B. CAMPAGNE -<br/>M.-B. KHDER - Q. LAFFÉTER - O. SIMON<br/>(Insee)<br/>A-S) DUFERNEZ - C. ELEZAAR -<br/>P. LEBLANC - E. MASSON -<br/>H. PARTOUCHE (DG-Trésor)<br/>Le modèle macroéconométrique Mésange :<br/>réstellung et nouveautés</td></tr><tr><td>G2017/05</td><td>J. BOUSSARD - B. CAMPAGNE<br/>Fiscal Policy Coordination in a Monetary<br/>Union at the Zero-Lower-Bound</td></tr><tr><td>G2017/06</td><td>A. CAZENAVE-LACROUTZ -<br/>A. GODZINSKI<br/>Effects of the one-day waiting period for sick<br/>leave on health-related absences in the<br/>French central civil service</td></tr><tr><td>G2017/07</td><td>P. CHARNOZ - M. ORAND<br/>Qualification, progess technique et marchés<br/>du travail locaux en France, 1990-2011</td></tr><tr><td>G2017/08</td><td>K. MILIN<br/>Modélisation de l'inflation en France par une<br/>approche macrosectorielle</td></tr><tr><td>G2017/09</td><td>C.-M. CHEVALIER - R. LARDEUX<br/>Homeownership and labor market outcomes:<br/>disentangling externality and composition<br/>effects</td></tr><tr><td>G2017/10</td><td>P. BEAUMONT<br/>Time is Money: Cash-Flow Risk and Export<br/>Market Behavior</td></tr><tr><td>G2018/01</td><td>S. ROUX - F. SAVIGNAC<br/>SMES' financing: Divergence across Euro<br/>area countries?</td></tr><tr><td>G2018/02</td><td>C.-M. CHEVALIER - A. LUCIANI<br/>Computerization, labor productivity and<br/>employment: impacts across industries vary<br/>with technological level</td></tr><tr><td>G2018/03</td><td>R. MONIN - M. SUAREZ CASTILLO<br/>L'effet du CICE sur les prix : une double<br/>analyse sur données sectorielles et<br/>individuelles</td></tr><tr><td>G2018/04</td><td>R. LARDEUX<br/>Who Understands The French Income Tax?<br/>Bunching Where Tax Liabilities Start</td></tr></table>

<table><tr><td>G2018/05</td><td>C.-M. CHEVALIER<br/>Financial constraints of innovative firms and<br/>sectoral growth</td></tr><tr><td>G2018/06</td><td>R. S.-H. LEE - M. PAK<br/>Pro-competitive effects of globalisation on<br/>prices, productivity and markups: Evidence<br/>in the Euro Area</td></tr><tr><td>G2018/07</td><td>C.-M. CHEVALIER<br/>Consumption inequality in France between<br/>1995 and 2011</td></tr><tr><td>G2018/08</td><td>A. BAUER - B. GARBINTI -<br/>S. GEORGES-KOT<br/>Financial Constraints and Self-Employment<br/>in France, 1945-2014</td></tr><tr><td>G2018/09</td><td>P. BEAUMONT - A. LUCIANI<br/>Prime à l'embauche dans les PME :<br/>évaluation à partir des déclarations<br/>d'embauche</td></tr><tr><td>G2018/10</td><td>C. BELLÉGO - V. DORTET-BERNADET -<br/>M. TÉPAUT<br/>Collaboration de deux dispositifs d'aide à la<br/>R&D collaborative public-privé</td></tr><tr><td>G2018/11</td><td>R. MONIN - M. SUAREZ CASTILLO<br/>Replication et rapprochement des travaux<br/>d'évaluation de l'affet du CICE sur l'emploi<br/>en 2013 et 2014</td></tr><tr><td>G2018/12</td><td>A. CAZENAVE-LACROUTZ - F. GODET -<br/>V. LIN<br/>L'introduction d'un gradient social dans la<br/>mortalité au sein du modèle Destologie 2</td></tr><tr><td>G2019/01</td><td>M. ANDRÉ - A.-L. BIOTTEAU<br/>Effets de moyen terme d'une hausse de TVA<br/>sur le niveau de vie et les inégalités : une<br/>approche par microsimulation</td></tr><tr><td>G2019/02</td><td>A. BOURGEOIS - A. BRIAND<br/>Le modèle Avionic : la modélisation<br/>Input/Output des comptes nationaux</td></tr><tr><td>G2019/03</td><td>A. GODZINSKI - M. SUAREZ CASTILLO<br/>Short-term health effects of public transport<br/>disruptions: air pollution and viral spread<br/>channels</td></tr><tr><td>G2019/04<br/>F1903</td><td>L. AEBERHARDT - F. HATIER -<br/>M. LECLAIR - B. PENTINAT - J.-D. ZAFAR<br/>L'économie numérique fausse-t-elle le<br/>partage volume-prix du PIB?</td></tr><tr><td>G2019/05</td><td>A. CAZENAVE-LACROUTZ - E. YILMAZ<br/>Dans quelle mesure les incitations tarifaires<br/>et la procédure de mise sous accord<br/>préalable ont-elles contribué au<br/>développement du chirurgie ambulatoire?</td></tr><tr><td>G2019/06</td><td>J.-P. CLING - S. EGHBAL-TEHERANI -<br/>M. ORZONI - C. PLATEAU<br/>The Differences between EU Countries for<br/>Sustainable Development Indicators:<br/>It is (mainly) the Economy!</td></tr><tr><td>G2019/07</td><td>P. CHONÉ - L. WILNER<br/>Competition on Unobserved Attributes: The<br/>Case of the Hospital Industry</td></tr></table>
G2019/08 P. PORA - L. WILNER

Child Penalties and Financial Incentives:
Exploiting Variation along the Wage
Distribution

G2019/09 E. GAUTIER - S. ROUX - M. SUAREZ
CASTILLO

Do Minimum Wages make Wages more
Rigid ? Evidence from French Micro Data

G2019/10 M. ANDRÉ - A. SIREY JOL

Imposition des couples et des familles :
effets budgétaires et redistributifs de l'impôt
sur le revenu

G2019/11 K. MOHKAM - O. SIMON

L'empreinte matière de l'économie
française : une analyse par matiŁre et
catégorie de produits

G2019/12 S. BUNEL - B. HADJIBEYLI

Évaluation du crédit d'impôt innovation

G2019/13 C. BONNET - F. GODET - A. SOLAZ

Gendered economic determinants of couple
formation over 50 in France

G2019/14 P. GIVORD - M. SUAREZ CASTILLO

Excellence for all? Heterogeneity in high
schools' value-added

G2019/15 G. CETTE - L. KOEHL - T. PHILIPPON

Labor Share in Some Advanced Countries

G2020/01 J. SILHOL - B. VENTELOU

Les zones d'intervention prioritaire reflètent-
elles des écarts de pratiques des médecins
généralistes ?

G2020/02 B. BOUCHTENIK - R. LARDEUX

The Take-Up of Unemployment Benefit
Extensions

G2020/03 J-M. GERMAIN

A Welfare Based Estimate of "Real Feel
GDP" for Europe and the USA