Fifty years of business confidence surveys on manufacturing sector

In this work the evolution of the Italian Business Confidence Survey on manufacturing sector is presented starting from the preliminary European project for harmonized statistics launched in the late fifties of the last century. Survey changes are described, focusing in particular on the so-called confidence indicator. The continuing increase of statistical accuracy in sampling is recalled, from the initial purposive sample and controls, up to the present state of the art. Specific attention is devoted to the role of administrative archives in the sampling plan. Emphasis is also given to the increasing use of computer simulation in assessing the validity of the estimates. The role of cyclical analysis is finally highlighted with regard to two aspects: (1) the business confidence has not a corresponding variable in the economic system\u2014the validation can only be performed in comparison with correlated variables (e.g. IP, GDP); (2) confidence shows forecasting capability for the economic system

Comparative Economic Cycles

The income cycles that have been experienced by six OECD countries over the past 24 years are analysed. The amplitude of the cycles relative to the level of aggregate income varies amongst the countries, as does the degree of the damping that a®ects the cycles. The study aims to reveal both of these characteristics. It also seeks to determine whether there exists a clear relationship between the degree of damping and the length of the cycles. In order to estimate the parameters of the cycles, the data have been subjected to the processes of detrending, anti-alias ¯ltering and subsampling

Comparative economic cycles

The income cycles that have been experienced by six OECD countries over the past 24 years are analysed. The amplitude of the cycles relative to the level of aggregate income varies amongst the countries, as does the degree of the damping that affects the cycles. The study aims to reveal both of these characteristics. It also seeks to determine whether there exists a clear relationship between the degree of damping and the length of the cycles. In order to estimate the parameters of the cycles, the data have been subjected to the processes of detrending, anti-alias filtering and subsampling