A Harmonized Consumer Confidence Index for Autonomous

The regional use of a CIS survey .Twitter Share on Facebook Share on In Compartment in Google Plus By Álex Costa – Economist. Catalan Association of Regional Science and Vittorio Galletto – Economics Area. Metropolis Institute. Autonomous University of Barcelona. Two and a the Consumer Confidence Index for Barcelona  saying that monitoring the situation is often more interesting from the point of view of demand than of supply, but that, in the territorial economy, demand approximations are complex and scarce.

In this context the ICC-BCN was

Valued as an affordable and also very significant demand indicator, as it refers to the most important concept of aggregate demand: household consumption. What was said . Most of them lack this information, relying only on sectoral indicators. The Regional Accounting of Spain offers data that is structural, and also on  Canada Phone Number Data the supply side. So we understand that it is relevant to have an indicator of the general situation on the demand side. An indicator, furthermore, of zero cost, since it is Consumer Confidence Index of the Autonomous . Communities  let us briefly recall the methodology of these indices. There is no completely .Homogeneous methodology for calculating these indices, and the evaluation of the future of the economy.

The value of the index is determined as an

Arithmetic mean of the indices of three components that are by the survey in three aspects that directly affect the family economy: Balance responses regarding the situation and expectations for the home economy . Balance of responses regarding the situation and expectations of the economy as a whole Balance of responses  Belgium Phone Number List regarding the situation and expectations of the labor market As we are using CIS microdata. The reference economy and labor market are those of the Spanish economy. The use is possible on the basis of two elements: the size of the samples and the population variance. Regarding the size of the sample, the monthly samples have been  order to generate quarterly results that are reliable and  have samples of  . Communities with a smaller sample. Although the samples are quite small. If the population variances are small the results can show high consistency.