Photo Laurent Ferrara

Laurent Ferrara

Chargé(e) de recherches
  • Email
  • Tél. professionnel 0140977817
  • Bureau à Paris Nanterre (Bât. + num.) G517A
  • Research group

      Macroéconomie Internationale, Banque et Econométrie Financière

  • Theme(s)
    • Econométrie non-linéaire
    • Prévision macroéconomique
    • Cycles économiques
    • Economie internationale

2021-23 "Dating business cycles in France: A reference chronology"

Antonin Aviat, Frédérique Bec, Claude Diebolt, Catherine Doz, Denis Ferrand, Laurent Ferrara, Eric Heyer, Valérie Mignon, Pierre-Alain Pionnier

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Abstract
This paper proposes a reference quarterly chronology for periods of expansion and recession in France since 1970, carried out by the Dating Committee of the French Economic Association (AFSE). The methodology used is based on two pillars: (i) econometric estimations from various key data to identify candidate periods, and (ii) a narrative approach that describes the economic background that prevailed at that time to finalize the dating chronology. Starting from 1970, the Committee has identified four economic recession periods: the two oil shocks 1974-75 and 1980, the investment cycle of 1992-93, and the Great Recession 2008-09 spawned by the Global Financial Crisis. The peak before the Covid-19 recession has been identified in the last quarter of 2019.
Classification-JEL
E32, E37, C24, N14
Mot(s) clé(s)
Business cycles, French economy, Dating, Narrative approach, Econometric modeling
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2021-22 "Les cycles économiques de la France : une datation de référence"

Antonin Aviat, Frédérique Bec, Claude Diebolt, Catherine Doz, Denis Ferrand, Laurent Ferrara, Eric Heyer, Valérie Mignon, Pierre-Alain Pionnier

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Abstract
This article proposes a quarterly dating of recession and expansion periods of the French economy since 1970, carried out by the AFSE (Association Française de Science Economique)’s cycle dating committee. The methodology used is based on two pillars: (i) econometric estimates from a dataset to identify candidate periods, and (ii) a narrative approach that details the economic context of the time to finalize our dating. From 1970 to nowadays, the committee identified four periods of economic recession: the two oil shocks of 1974-75 and 1980, the investment cycle of 1992-93, and the Great Recession of 2008-09 spawned by the global financial crisis. The peak prior to the Covid recession has been dated to the last quarter of 2019.
Classification-JEL
E32, E37, C24, N14
Mot(s) clé(s)
Business cycles, French economy, dating, narrative approach, econometric models
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2020-11 "When are Google data useful to nowcast GDP? An approach via pre-selection and shrinkage"

Laurent Ferrara, Anna Simoni

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Abstract
We analyse whether, and when, a large set of Google search data can be useful to increase GDP nowcasting accuracy once we control for information contained in official variables. We put forward a new approach that combines variable pre-selection and Ridge regularization and we provide theoretical results on the asymptotic behaviour of the estimator. Empirical results on the euro area show that Google data convey useful information for pseudo-real-time nowcasting of GDP growth during the four first weeks of the quarter, when macroeconomic information is lacking. However, as soon as official data become available, their relative nowcasting power vanishes. In addition, a true real-time analysis confirms that Google data constitute a reliable alternative when official data are lacking.
Classification-JEL
C53, C55, E37
Mot(s) clé(s)
Nowcasting, Big data, Google search data, Sure Independence Screening, Ridge Regularization
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2018-2 "Global Financial interconnectedness: A non-linear assessment of the uncertainty channel"

Bertrand Candelon, Laurent Ferrara, Marc Joëts

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Abstract
The role of uncertainty in the global economy is now widely recognized by policy-makers but its effects on the international fi…nancial system are less understood. In this paper we assess the impact of uncertainty on the interconnectedness within the international system of equity prices. In this respect, we extend the measure of connectedness put forward by Diebold and Yilmaz (2009) by allowing for non-linear effects through the estimation of a non-linear Threshold VAR model whose regimes depend on the level on uncertainty. Results clearly show that high uncertainty tends to generate more connectedness among equity indexes of a set of advanced and emerging countries. From an economic policy point of view, this result suggests that in the presence of high uncertainty, an adverse …financial shock in a speci…fic country is likely to propagate more widely and more strongly to the whole fi…nancial system. This result advocates for a close real-time monitoring of uncertainty measures.
Classification-JEL
G15; C31; D84
Mot(s) clé(s)
Financial markets, Network interconnectedness, Uncertainty, Non-linear model
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2015-12 "What Are The Macroeconomic Effects of High-Frequency Uncertainty Shocks?"

Laurent Ferrara, Pierre Guérin

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Abstract
Following the Great Recession, econometric models that better account for un certainty have gained increased attention, and an increasing number of works evaluate the effects of uncertainty shocks. In this paper, we evaluate the impact of high-frequency uncertainty shocks on a set of low-frequency macroeconomic variables representative of the U.S. economy. Rather than estimating models at the same common low-frequency, we use recently developed econometric methodology that allows us to avoid aggregating high-frequency data before estimating models. The impulse response analysis uncovers various salient facts. First, in line with the existing literature, high-frequency uncertainty shocks are associated with a broad-based decline in economic activity. Second, we find that credit and labor market variables react the most to uncertainty shocks. Third, we show that the responses of macroeconomic variables to uncertainty shocks are relatively similar across single-frequency and mixed-frequency data models, suggesting that the temporal aggregation bias is not acute in this context. Finally, we find that some macroeconomic variables exhibit an asymmetric response to uncertainty shocks over the different phases of the business cycle.
Classification-JEL
E32, E44, C32.
Mot(s) clé(s)
MIDAS model, Mixed-frequency VAR, Uncertainty.
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2014-21 "Does the Great Recession imply the end of the Great Moderation? International evidence"

Amélie Charles, Olivier Darné, Laurent Ferrara

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Abstract
After years of low macroeconomic volatility since the early eighties, well documented and referred to as the Great Moderation period in the literature, the 2008-2009 worldwide recession adversely impacted output levels in most of advanced countries. This Great Recession period was characterized by a sharp apparent increase in output volatility. In this paper we evaluate whether this sudden event is likely to be temporary. Whether or not this new volatility regime is likely to persist would have strong macroeconomic effects, especially on business cycles. Based on break detection methods applied to a set of advanced countries, our empirical results do not give evidence to the end of the Great Moderation period but rather that the Great Recession is characterized by a dramatic temporary effect on the output growth but not on its volatility. In addition, we show that neglecting those breaks both in mean and in variance can have large effects on output volatility modelling. Last we empirically show that observed breaks during the Great Recession are to some extent related to uncertainty measures.
Classification-JEL
E32; C22
Mot(s) clé(s)
Great Recession; Great Moderation; breaks; volatility; uncertainty
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2013-19 "Forecasting US growth during the Great Recession: Is the financial volatility the missing ingredient?"

Laurent Ferrara, Clément Marsilli, Juan-Pablo Ortega

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Abstract
The Great Recession endured by the main industrialized countries during the period 2008-2009, in the wake of the financial and banking crisis, has pointed out the major role of the financial sector on macroeconomic fluctuations. In this paper, we reconsider macrofinancial linkages by assessing the leading role of the daily volatility of two major financial variables, namely commodity and stock prices, in their ability to anticipate US GDP growth. For this purpose, an extended MIDAS model is proposedthat allows the forecasting of the quarterly growth rate using exogenous variables sampled at various higher frequencies. Empirical results show that using both daily financial volatilities and monthly industrial production is helpful at the time of predicting quarterly GDP growth over the Great Recession period.
Classification-JEL
C53 E37
Mot(s) clé(s)
GDP forecasting; financial volatility; MIDAS approach
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2013-12 "Post-recession US employment through the lens of a non-linear Okun’s law"

Menzie Chinn, Laurent Ferrara, Valérie Mignon

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Abstract
This paper aims at investigating the relationship between employment and GDP in the United States. We disentangle trend and cyclical employment components by estimating a non-linear Okun’s law based on a smooth transition error-correction model that simultaneously accounts for long-term relationships between growth and employment and short-run instability over the business cycle. Our findings based on out-of-sample conditional forecasts show that, since the exit of the 2008-09 recession, US employment is on average around 1% below the level implied by the long run output-employment relationship, meaning that about 1.2 million of the trend employment loss cannot be attributed to the identified cyclical factors.
Classification-JEL
E24, E32, C22
Mot(s) clé(s)
Okun’s law, trend employment, non‐linear modeling
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2012-19 "Financial variables as leading indicators of GDP growth: Evidence from a MIDAS approach during the Great Recession"

Laurent Ferrara, Clément Marsilli

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Abstract
The global economic recession, referred to as the Great Recession, endured by the main industrialized countries during the period 2008-09, in the wake of the financial and banking crisis, has pointed out the current importance of the financial sector in macroeconomics. In this paper, we evaluate the predictive power of some major financial variables to anticipate GDP growth in euro area countries during this specific period of time. In this respect, we implement a MIDAS-based modeling approach, put forward by Ghysels et al. (2007), that enables to forecast quarterly GDP growth rates using exogenous variables sampled at higher frequencies. Empirical results show that, overall, stock prices help to improve the accuracy of GDP forecasts by comparison with a standard opinion survey variable, while oil prices and term spread appear to be less informative.
Classification-JEL
C2, C5, E3
Mot(s) clé(s)
Great Recession; Forecasting; Financial variables; MIDAS approach
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2011-27 "A new monthly chronology of the US industrial cycles in the prewar economy"

Amélie Charles, Olivier Darné, Claude Diebolt, Laurent Ferrara

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Abstract
This article extends earlier efforts at redating the US industrial cycles for the prewar period (1890–1938) using the methodologies proposed by Bry and Boschan (1971) and Hamilton (1989) and based on the monthly industrial production index constructed by Miron and Romer (1990). The alternative chronology detects 90% of the peaks and troughs identified by the NBER and Romer (1994), but the new dates are consistently dated earlier for more than 50% of them, especially as regards the NBER troughs. The new dates affect the comparison of the average duration of recessions and expansions in both pre-WWI and interwar eras. Whereas the NBER reference dates show an increase in average duration of the expansions between the pre-WWI and interwar periods, the new dates show evidence of shortened length of expansions. However, the new dates confirm the traditional finding that the length of contractions increases between the both eras.
Classification-JEL
C22; E32
Mot(s) clé(s)
Industrial business cycle; Dating chronology
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2010-14 "A factor-augmented probit model for business cycle analysis"

Christophe Bellégo, Laurent Ferrara

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Abstract
Dimension reduction of large data sets has been recently the topic of interest of many research papers dealing with macroeconomic modelling. Especially dynamic factor models have been proved to be useful for GDP nowcasting or short-term forecasting. In this paper, we put forward an innovative factor-augmented probit model in order to analyze the business cycle. Factor estimation is carried either by standard statistical methods or by allowing a richer dynamic behaviour. An application is provided on euro area data in order to point out the ability of the model to detect recessions over the period 1974-2008.
Classification-JEL
Mot(s) clé(s)
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