Investment forecasting with business survey data
AbstractBusiness investment is a very important variable for short- and medium-term economic analysis, but it is volatile and difficult to predict. Qualitative business survey data are widely used to provide indicators of economic activity ahead of the publication of official data. Traditional indicators exploit only aggregate survey information, namely the proportions of respondents who report “up” and “down”. As a consequence, neither the heterogeneity of individual responses nor the panel dimension of microdata is used. We illustrate the use of a disaggregate panel-based indicator that exploits all information coming from two yearly industrial surveys carried out on the same sample of Italian manufacturing firms. Using the same sample allows us to match exactly investment plans and investment realisations for each firm and so estimate a panel data model linking individual investment realisations to investment intentions. The model generates a one-year-ahead forecast of investment variation that follows the aggregate dynamics with a limited bias.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Bank of Italy, Economic Research and International Relations Area in its series Temi di discussione (Economic working papers) with number 832.
Date of creation: Nov 2011
Date of revision:
investment plans; dynamic panel data model; forecasting;
Find related papers by JEL classification:
- C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
This paper has been announced in the following NEP Reports:
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ().
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.