The Breaks in per Capita Productivity Trends in a Number of Industrial Countries

The purpose of this article is to study the trends in per capita productivity in several major industrialised countries. The analysis is first based on annual data over a long period spanning the entire 20th century for the United States, France and the United Kingdom. Productivity trends are then studied over a shorter period, using quarterly data, for the United States, France, the United Kingdom, Germany, Spain, Japan and the Netherlands. There are already a large number of studies of this kind, but they are too often focused on presenting average productivity growth rates for given periods chosen on an ad hoc basis. In this article, we use a robust statistical method to endogenously identify possible breaks in per capita productivity trends. This method, developed by Bai and Perron (1998), brings out the following salient features: – in the United States, per capita productivity growth accelerated following the trend break at the start of the 1920s, then slowed down at the end of the 1960s. This finding is in line with the “Big Wave” concept developed by Gordon (1999, 2002) to describe the trends in US productivity growth throughout the 20 th century. – French and UK productivity started catching up with that in the United States around the end of the Second World War. – Most of the countries under review recorded slower trend productivity growth in the first half of the 1970s. In the United States, this break occurred in 1966. This finding differs from that of other existing analyses, which point to 1974. – Trend productivity growth in Europe and Japan slowed in the 1990s, whereas US productivity gained momentum over the same period.Productivity trends ; Structural breaks ; Bai and Perron method

Parts de marché et spécialisation commerciale de l’Allemagne, de la France et de l’Italie.

parts de marché, spécialisation commerciale.

OPTIM : un outil de prévision trimestrielle du PIB de la France.

Le modèle OPTIM permet de prévoir, chaque mois, les taux de croissance du PIB de la France et de ses principales composantes, pour le trimestre en cours et le trimestre suivant. Ce modèle mobilise un large éventail de données macro-économiques mensuelles et de données d’enquête, sélectionnées par une procédure statistique automatique.Prévision, taux de croissance du PIB, modèle d’étalonnage, approche “general-to-specific”.

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 Sédillot (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.GDP forecasting ; Bridge models ; General-to-specific approach

OPTIM: a quarterly forecasting tool for French GDP.

The OPTIM model helps to forecast each month the growth rate of French GDP and its main components for the coincident quarter and the quarter ahead. The model uses a wide range of monthly macroeconomic data and survey data, selected by an automatic statistical procedure.GDP forecasting, bridge model, general-to-specifi c approach (Gets).