Compendium of practices on the implementation of ICT questions in households and businesses surveys in Latin America and the Caribbean 2010

Includes bibliography

National innovation surveys in Latin America: empirical evidence and policy implications

Includes bibliography

National innovation surveys in latin America: empirical evidence and policy implications

Includes bibliography

Make, buy and and cooperate in innovation: evidence from Uruguayan manufacturing surveys and other innovation studies

Includes bibliography

Innovation and cooperation in Latin America: evidence from national innovations surveys in a comparative perspective

Includes bibliography

Towards an information society measurement instrument for Latin America and the Caribbean: getting started with census, household and business surveys

Includes bibliography

Goals for children, exclusion and vulnerability: expanding the usefulness of household surveys

Includes bibliography

Program for the improvement of surveys and the measurement of living conditions in Latin America and the Caribbean (ISLC

Includes bibliography

CELADE's recent experiences with national demographic surveys in Latin America. The case of Guyana

Includes bibliography

Surveys on time use and unpaid work in Latin America and the Caribbean: Experience to date and challenges for the future

Incluye bibliografía.

Mexico: Combining monthly inflation predictions from surveys

We examine the problem of combining Mexican inflation predictions or projections provided by a biweekly survey of professional forecasters. Consumer price inflation in Mexico is measured twice a month. We consider several combining methods and advocate the use of dimension reduction techniques whose performance is compared with different benchmark methods, including the simplest average prediction. Missing values in the database are imputed by two different databased methods. The results obtained are basically robust to the choice of the imputation method. A preliminary analysis of the data was based on its panel data structure and showed the potential usefulness of using dimension reduction techniques to combine the experts' predictions. The main findings are: the first monthly predictions are best combined by way of the first principal component of the predictions available; the best second monthly prediction is obtained by calculating the median prediction and is more accurate than the first one.