SINTESI DI TATIANA
CESARONI, MARCO MALGARINI,
GAIA ROCCHETTI
WP N. 50
L’INCHIESTA
ISAE SUGLI INVESTIMENTI DELLE IMPRESE MANIFATTURIERE ED ESTRATTIVE: ASPETTI
METODOLOGICI E RISULTATI
ABSTRACT
The Joint harmonized EU Investment survey, carried out
for Italy by the Institute for Studies and Economic Analysis (ISAE), provides
quantitative information about investment plans and the structure of investment
and qualitative data on the factors influencing firm’ behavior.
As shown in the recent OECD’ Business Tendency Surveys Handbook (OECD, 2003),
in dealing with business surveys a special attention should be devoted to the
control for the reliability of the results and to the appropriate use of
weighting in processing survey’ data. From a methodological standpoint, this is
particularly important for surveys providing quantitative as well as purely
qualitative data, as is the case for the Investment survey. In this respect,
the paper proposes deterministic and statistically-based methods for the
treatment of missing data and outliers, focussing especially on the
quantitative question on investment plans. After a careful deterministic
control, based on the possibility of re-interviewing nonresponding
firms, a fairly simple econometric model is used to estimate “residual” missing
data, based on information on sector, geographical partition and number of
employee of the firm, and its investment plans for the previous years (when
available). The robustness of sample estimates in case of extreme observation
in the tails of the distribution is then tested with the use of the winsorized mean. In processing the results, estimate of
investment plans at industry level is then derived using sample weights, based,
for each stratum, on the ratio between the Universe Population and that of the
sample. Aggregation of qualitative data concerning investment structure and
factors influencing firm’ behaviour is then based on appropriate,
variable-specific, size weights, i.e. the investment plan of the firm itself.
This appears to be a fairly more appropriate choice with respect to the more
usual value added-based weight. A presentation of the resulting data-bank,
together with some consideration on possible future research, concludes the
work.
Key Words: Business surveys; Investment; Missing
data; Outliers; Aggregation.
JEL
Classification: C42; C81; E22