French GDP Research Articles

Institutions and Economic Growth in Democratic Europe: France’s 1958 Transition From Fourth to Fifth Republic

This paper studies the impact of France’s 1958 constitutional transition from the French Fourth Republic to the French Fifth Republic. A difference-in-differences regression analysis compared the effect of France’s 1958 institutional change on French economic growth against a control group of 12 democratic European countries in the period 1948 – 1969. The regression analysis conducted suggested that the 1958 French constitutional change contributed an additional 2.73% GDP growth per year to French GDP growth in the period 1959 – 1969. 

Foreign Shocks as Granular Fluctuations

This paper uses a dataset covering the universe of French firm-level sales, imports, and exports over the period 1993-2007 and a quantitative multi-country model to study the international transmission of business cycle shocks at both the micro and the macro levels. The largest firms are both important enough to generate aggregate fluctuations (Gabaix, 2011), and most likely to be internationally connected. This implies that foreign shocks are transmitted to the domestic economy primarily through the largest firms. We first document a novel stylized fact: larger French firms are significantly more sensitive to foreign GDP growth. We then implement a quantitative framework calibrated to the full extent of observed heterogeneity in firm size, exporting, and importing. We simulate the propagation of foreign shocks to the French economy and report one micro and one macro finding. At the micro level heterogeneity across firms predominates: 40 to 85% of the impact of foreign fluctuations on French GDP is accounted for by the “foreign granular residual” — the term capturing the fact that larger firms are more affected by the foreign shocks. At the macro level, firm heterogeneity dampens the impact of foreign shocks, with the GDP responses 10 to 20% larger in a representative firm model compared to the baseline model. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

Foreign Shocks as Granular Fluctuations

This paper uses a data set covering the universe of French firm-level sales, imports, and exports over the period 1993-2007 and a quantitative multi-country model to study the international transmission of business cycle shocks at both the micro and the macro levels. The largest firms are both important enough to generate aggregate fluctuations (Gabaix 2011), and most likely to be internationally connected. This implies that foreign shocks are transmitted to the domestic economy primarily through the largest firms. We first document a novel stylized fact: larger French firms are significantly more sensitive to foreign GDP growth. We then implement a quantitative framework calibrated to the full extent of observed heterogeneity in firm size, exporting, and importing. We simulate the propagation of foreign shocks to the French economy and report one micro and one macro finding. At the micro level, heterogeneity across firms predominates: 40-85 percent of the impact of foreign fluctuations on French GDP is accounted for by the “foreign granular residual”—the term capturing the fact that larger firms are more affected by the foreign shocks. At the macro level, firm heterogeneity dampens the impact of foreign shocks, with the GDP responses 10-20 percent larger in a representative firm model compared to the baseline model.

Prévoir la croissance du PIB en lisant le journal

GDP statistics in France are published on a quarterly basis, 30 days after the end of the quarter. In this article, we consider media content as an additional data source to traditional economic tools to improve short-term forecast / nowcast of French GDP. We use a database of more than a million articles published in the newspaper Le Monde between 1990 and 2017 to create a new synthetic indicator capturing media sentiment about the state of the economy. We compare an autoregressive model augmented by the media sentiment indicator with a simple autoregressive model. We also consider an autoregressive model augmented with the Insee Business Climate indicator. Adding a media indicator improves French GDP forecasts compared to these two reference models. We also test an automated approach using penalised regression, where we use the frequencies at which words or expressions appear in the articles as regressors, rather than aggregated information. Although this approach is easier to implement than the former, its results are less accurate.

Assessing the cost-effectiveness of hepatitis C screening strategies in France

In Europe, hepatitis C virus (HCV) screening still targets people at high risk of infection. We aim to determine the cost-effectiveness of expanded HCV screening in France. A Markov model simulated chronic hepatitis C (CHC) prevalence, incidence of events, quality-adjusted life years (QALYs), costs and incremental cost-effectiveness ratio (ICER) in the French general population, aged 18 to 80 years, undiagnosed for CHC for different strategies: S1 = current strategy targeting the at risk population; S2 = S1 and all men between 18 and 59 years; S3 = S1 and all individuals between 40 and 59 years; S4 = S1 and all individuals between 40 and 80 years; S5 = all individuals between 18 and 80 years (universal screening). Once CHC was diagnosed, treatment was initiated either to patients with fibrosis stage ≥F2 or regardless of fibrosis. Data were extracted from published literature, a national prevalence survey, and a previously published mathematical model. ICER were interpreted based on one or three times French GDP per capita (€32,800). Universal screening led to the lowest prevalence of CHC and incidence of events, regardless of treatment initiation. When considering treatment initiation to patients with fibrosis ≥F2, targeting all people aged 40-80 was the only cost-effective strategy at both thresholds (€26,100/QALY). When we considered treatment for all, although universal screening of all individuals aged 18-80 is associated with the highest costs, it is more effective than targeting all people aged 40-80, and cost-effective at both thresholds (€31,100/QALY). In France, universal screening is the most effective screening strategy for HCV. Universal screening is cost-effective when treatment is initiated regardless of fibrosis stage. From an individual and especially from a societal perspective of HCV eradication, this strategy should be implemented. In the context of highly effective and well tolerated therapies for hepatitis C virus that are now recommended for all patients, a reassessment of hepatitis C screening strategies is needed. An effectiveness and cost-effectiveness study of different strategies targeting either the at-risk population, specific ages or all individuals was performed. In France, universal screening is the most effective strategy and is cost-effective when treatment is initiated regardless of fibrosis stage. From an individual and especially from a societal perspective of hepatitis C virus eradication, this strategy should be implemented.

Management des compétences et évolution du positionnement stratégique sur le marché du bâtiment

Le marché du bâtiment, qui représente 10 % du produit intérieur brut français, n’est pas épargné par la crise. La baisse continue de son activité économique depuis 2008 impacte les entreprises du secteur et notamment les organisations de maîtrise d’œuvre qui se retrouvent contraintes à faire évoluer leur positionnement stratégique sur le marché pour pallier la diminution des commandes. Mais cette évolution subie apparaît souvent en inadéquation avec les compétences internes. Elle renforce les importantes difficultés économiques et sociales de ces structures, mises en évidence par des recherches récentes (Ruat, 2012 ; Zardet, Delattre & Petit, 2012). L’étude a été réalisée à partir d’une méthodologie de recherche-intervention auprès de 23 terrains de recherche. Elle s’attache à identifier comment l’amélioration d’un management des compétences peut aider les organisations de maîtrise d’œuvre à mieux cibler les évolutions de positionnement stratégique à adopter sur le marché du bâtiment afin d’améliorer leur performance économique et sociale.

Trading forward: The Paris Bourse in the nineteenth century

Contrary to what law and finance theory would predict, the Paris Bourse was highly liquid at the turn of the twentieth century: the traded volumes amounted to four times the French GDP. This magnitude was mainly due to forward trading. The Bourse had developed as a forward market, despite a ban on forward transactions. The guild-like body running the Bourse played a key role in legitimizing and legalizing these operations, previously equated with gambling. The 1885 legalizing act initiated a new field of law (‘securities law’) and paved the way for the heyday of the Paris Bourse.

The new MIBA model: Real-time nowcasting of French GDP using the Banque de France's monthly business survey

This paper introduces a new nowcasting model of the French quarterly real GDP growth rate (MIBA), developed at the Banque de France and based on monthly business surveys. The model is designed to target initial announcements of GDP in a mixed-frequency framework. The selected equations for each forecast horizon are consistent with the time frame of real-time nowcasting exercises: the first one includes mainly information on the expected evolution of economic activity, while the second and third equations rely more on information on observed business outcomes. The predictive accuracy of the model increases over the forecast horizon, consistent with the gradual increase in available information. Furthermore, the model outperforms a wide set of alternatives, such as its previous version and MIDAS regressions, although not a specification including also hard data. Further research should evaluate the performance of the MIBA model with respect to promising alternative approaches for nowcasting GDP (e.g. mixed-frequency factor models with targeted predictors), and consider forecast combinations and density forecasts.

Rationality of Announcements, Business Cycle Asymmetry, and Predictabilityof Revisions. The Case of French GDP

We analyze French GDP revisions and we investigate the rationality of preliminary announcements of GDP. We consider nonlinearities, taking the form of business cycle asymmetry and time changes, and their effect on both unconditional moments of revisions and the rationality of announcements. We find that nonlinearity represents an interesting feature of French GDP announcements and revisions. Our results suggest that revisions are unbiased, but announcements are overall inefficient, conditionally on a set of macro-financial indicators. Finally, we investigate the forecastability of GDP revisions in real-time and we find out that total revisions are predictable.

The Prisme Model: Can Disaggregation on the Production Side Help to Forecast GDP?

Although a forecasting model has very good statistical properties and the mean of the residuals equals zero, it can produce systematic errors during a short period. In the case of regular publications, forecasters want to prevent such a persistence of errors over several periods. For this reason, a safeguard model can be used to inform the forecaster when there is a risk that the standard model (i.e. the best specified model on average) leads to persistent errors over several months or quarters. This paper explains why and how such a safeguard model has been built in order to improve the forecasts of French GDP at the current quarter horizon (nowcasts), which are officially published by the French central bank. The official benchmark model for GDP nowcasts is an aggregated model that relies exclusively on survey in the manufacturing industry. In the long run, this model still has the best performances. On the contrary, the safeguard model is a disaggregated model which features equations for the valued added of 6 sectors. From this example, we provide general remarks on the advantages of disaggregation as well as how such safeguard models can be used in practice.

Nowcasting French GDP in real-time with surveys and “blocked” regressions: Combining forecasts or pooling information?

This paper empirically investigates two alternative combination strategies, namely forecast combination and information pooling, in the context of nowcasting French GDP in real time with monthly survey opinions. According to the encompassing paradigm, we claim that the outperformance of the forecast combination strategy reported by recent works may be related to the issues of model selection and misspecification. To address these issues, we promote the blocking modeling approach to allow us to handle mixed frequencies in a linear framework that is compatible with an automatic model selection algorithm. Selected restricted- and pooled-information models are specified and tested for forecast encompassing in order to determine the best combination strategy. The results suggest that the forecast combination strategy dominates as long as no individual (restricted) model encompasses the rivals. However, when a predictive encompassing model is obtained by pooling the information sets, this model outperforms the most accurate forecast combination scheme.

Short-term forecasting of French GDP growth using dynamic factor models

In recent years, central banks and international organisations have been making ever greater use of factor models to forecast macroeconomic variables. We examine the performance of these models in forecasting French GDP growth over short horizons. The factors are extracted from a large data set of around one hundred variables including survey balances and real, financial, and international variables. An out-of-sample pseudo real-time evaluation over the past decade shows that factor models provide a gain in accuracy relative to the usual benchmarks. However, the forecasts remain inaccurate before the start of the quarter. We also show that the inclusion of international and financial variables can improve forecasts at the longest horizons.

Can the new French economic policy be successful?

In early 2013, the French economy, like many other EU economies, faces tough challenges. French GDP is 9 per cent below the level it would have reached had it continued to grow at its pre-crisis trend. France has committed to cut the public deficit to 3 per cent in 2013 and 0 per cent in 2017 which would imply dramatic public spending cuts and fiscal tightening, reducing GDP growth even further. France has to choose between strengthening its specificity, its social model and its State-interventionist tradition, and imitating the best pupils of globalization in the world or in Europe by implementing liberal or social-liberal strategies. The paper deals with the French government strategy since the 2012 presidential elections and tries to assess its chances of success. In many areas – fiscal strategy, social issues, banking and industrial policies – there is a significant risk that the announced proactive strategy will be replaced by policies accepting the constraints imposed by European institutions and financial markets.

Short-Term Forecasts of French GDP: A Dynamic Factor Model with Targeted Predictors

In recent years, factor models have received increasing attention from both econometricians and practitioners in the forecasting of macroeconomic variables. In this context, Bai and Ng (2008) find an improvement in selecting indicators according to the forecast variable prior to factor estimation (targeted predictors). In particular, they propose using the LARS-EN algorithm to remove irrelevant predictors. In this paper, we adapt the Bai and Ng procedure to a setup in which data releases are delayed and staggered. In the pre-selection step, we replace actual data with estimates obtained on the basis of past information, where the structure of the available information replicates the one a forecaster would face in real time. We estimate on the reduced dataset the dynamic factor model of Giannone, Reichlin and Small (2008) and Doz, Giannone and Reichlin (2011), which is particularly suitable for the very short-term forecast of GDP. A pseudo real-time evaluation on French data shows the potential of our approach.

Short‐Term Forecasts of French GDP: A Dynamic Factor Model with Targeted Predictors

ABSTRACTIn recent years, factor models have received increasing attention from both econometricians and practitioners in the forecasting of macroeconomic variables. In this context, Bai and Ng (Journal of Econometrics 2008; 146: 304–317) find an improvement in selecting indicators according to the forecast variable prior to factor estimation (targeted predictors). In particular, they propose using the LARS‐EN algorithm to remove irrelevant predictors. In this paper, we adapt the Bai and Ng procedure to a setup in which data releases are delayed and staggered. In the pre‐selection step, we replace actual data with estimates obtained on the basis of past information, where the structure of the available information replicates the one a forecaster would face in real time. We estimate on the reduced dataset the dynamic factor model of Giannone et al. (Journal of Monetary Economics 2008; 55: 665–676) and Doz et al. (Journal of Econometrics 2011; 164: 188–205), which is particularly suitable for the very short‐term forecast of GDP. A pseudo real‐time evaluation on French data shows the potential of our approach. Copyright © 2013 John Wiley & Sons, Ltd.

France : tenue de rigueur imposée

En moyenne annuelle, l’economie francaise devrait connaitre en 2013 un leger recul de son PIB (-0,2 %) et une modeste reprise en 2014, avec une croissance de 0,6 %. Cette performance particulierement mediocre est tres eloignee du chemin que devrait normalement emprunter une economie en sortie de crise.Quatre ans apres le debut de la crise, le potentiel de rebond de l’economie francaise est important : il aurait du conduire a une croissance spontanee moyenne de pres de 2,6 % l’an au cours des annees 2013 et 2014. Mais cette reprise spontanee est freinee, principalement par la mise en place de plans d’economies budgetaires en France et dans l’ensemble des pays europeens. Afin de tenir son engagement d’un deficit public a 3 % en 2014, le gouvernement francais devrait poursuivre la strategie – adoptee en 2010 – de consolidation budgetaire imposee par la Commission europeenne a l’ensemble des pays de la zone euro. Cette strategie budgetaire devrait amputer de 2,6 points de PIB l’activite en France en 2013 et de 2,0 points de PIB en 2014.En s’etablissant a un rythme eloigne de son potentiel, la situation sur le marche du travail devrait continuer a se degrader. Le taux de chomage augmenterait regulierement pour s’etablir a 11,6 % fin 2014.Seul un changement de cap dans la strategie budgetaire europeenne permettrait d’enrayer la hausse du chomage. Elle supposerait que les impulsions budgetaires negatives se limitent a -0,5 point de PIB au lieu de -1,0 point prevu au total dans la zone euro en 2014. Cet effort budgetaire plus faible pourrait etre repete jusqu’a ce que le deficit public ou la dette publique atteigne un objectif a definir. Par rapport aux plans actuels, parce que l’effort serait plus mesure, le fardeau de l’ajustement peserait de facon plus juste sur les contribuables de chaque pays. Cette nouvelle strategie conduirait certes a une reduction plus lente des deficits publics (-3,4 % en 2014 contre -3,0 % dans notre scenario central) mais egalement et surtout a plus de croissance economique (1,6 % contre 0,6 %). Ce scenario « moins d’austerite » permettrait a l’economie francaise de creer 119 000 emplois en 2014, soit 232 000 de plus que dans notre prevision centrale et le chomage baisserait au lieu de continuer a augmenter.

Nowcasting French GDP in Real-Time from Survey Opinions: Information or Forcast Combinations?

This paper investigates the predictive accuracy of two alternative forecasting strategies, namely the forecast and information combinations. Theoretically, there should be no role for forecast combinations in a world where information sets can be instantaneously and costlessly combined. However, following some recent works which claim that this result holds in population but not necessarily in small samples, our paper questions this postulate empirically in a real-time and mixed-frequency framework. An application to the quarterly growth rate of French GDP reveals that, given a set of predictive models involving coincident indicators, a simple average of individual forecasts outperforms the individual forecasts, as long as no individual model encompasses the others. Furthermore, the simple average of individual forecasts outperforms, or it is statistically equivalent to, more sophisticated forecast combination schemes. However, when a predictive encompassing model is obtained by combining information sets, this model outperforms the most accurate forecast combination strategy.

Prediction of time series by statistical learning: general losses and fast rates

Abstract We establish rates of convergences in statistical learning for time series forecasting. Using the PAC-Bayesian approach, slow rates of convergence √ d/n for the Gibbs estimator under the absolute loss were given in a previous work [7], where n is the sample size and d the dimension of the set of predictors. Under the same weak dependence conditions, we extend this result to any convex Lipschitz loss function. We also identify a condition on the parameter space that ensures similar rates for the classical penalized ERM procedure. We apply this method for quantile forecasting of the French GDP. Under additional conditions on the loss functions (satisfied by the quadratic loss function) and for uniformly mixing processes, we prove that the Gibbs estimator actually achieves fast rates of convergence d/n. We discuss the optimality of these different rates pointing out references to lower bounds when they are available. In particular, these results bring a generalization the results of [29] on sparse regression estimation to some autoregression.

Prévision à court terme de la croissance du PIB français à l’aide de modèles à facteurs dynamiques

Les banques centrales et les organismes internationaux recourent de plus en plus aux modèles à facteurs pour prévoir les grands agrégats macroéconomiques. Nous étudions l’apport de ces modèles à la prévision conjoncturelle du taux de croissance trimestriel du PIB français. Les facteurs sont extraits d’une base constituée d’une centaine de variables comprenant des soldes d’enquêtes et des variables réelles, monétaires, financières et internationales. Une évaluation hors échantillon en quasi temps réel sur la dernière décennie montre que les performances prédictives des modèles à facteurs surpassent celles des modèles de référence usuels. Toutefois, les prévisions effectuées avant le début du trimestre à prévoir restent fragiles. Nous montrons également que l’utilisation de variables internationales et financières permet d’améliorer les prévisions aux horizons les plus lointains.

Monthly Forecasting of French GDP: A Revised Version of the Optim Model

This paper presents a revised version of the model OPTIM, proposed by Irac and Sedillot (2002), used at the Banque de France in order to predict French GDP quarterly growth rate, for the current and next quarters. The model is designed to be used on a monthly basis by integrating monthly economic information through bridge models, for both supply and demand sides of GDP. For each GDP component, bridge equations are specified by using a general-to-specific approach implemented in an automated way by Hoover and Perez (1999) and improved by Krolzig and Hendry (2001). This approach allows to select explanatory variables among a large data set of hard and soft data. The final choice of equations relies on a recursive forecast study, which also helps to assess the forecasting performance of the revised OPTIM model in the prediction of aggregated GDP. This study is based on pseudo real-time forecasts taking publication lags into account . It turns out that the model outperforms benchmark models.