Malgarini, Marco and Margani, Patrizia and Martelli, Bianca Maria (2005): Re-engineering the ISAE manufacturing survey.
Download (373kB) | Preview
The Joint harmonized Manufacturing survey for Italy, carried out by the Institute of Studies and Economic Analysis (ISAE, formerly ISCO), has a long history: it began on a quarterly basis in 1959, becoming monthly in 1962. The survey was then broadly modified in several occasions; in particular, in 1986 it was re-designed in order to provide data also at the regional level, adopting a new stratified random sample, the strata represented by the sector, region and size of the firm. In 1998, the sample was upgraded further, using an optimal allocation of the reporting units to the sample strata (Cochran, 1977). These changes satisfied the demand for more detailed and, at the same time, better harmonized data. However, at this stage, the processing of the results was still based on a very detailed industry grid based on the old NACE1970 classification, re-codified to obtain harmonized data for the Main Industrial Groups and total manufacturing. Size weights were used in the processing of the results, but there were still some differences in the elaboration of the data at the national and regional level, resulting in a not fully-fledged comparability between local and national data. For these reasons, in 2003 ISAE started a re-thinking of the manufacturing survey processing phase. The resulting re-engineering process recently implemented by ISAE is described in this paper. It has reached two main relevant goals: i. The underlying industrial structure for the aggregation of survey results is now based on the NACERev1.1 classification, at the 3-digit level, adapted to take into consideration the structure of Italian economy. ii. The weighting scheme is now based on a coherent system of size weights, based on a four-stage method in which, firstly, the balance Ba,j for question a, firm j, is aggregated in each strata, using the j-firm employees as weights; in the following stages, the result for each strata is progressively aggregated to calculate the Industry total, using value added weights, provided by an external source (i.e., the National Institute for Statistics, ISTAT). The main consequence is that now results at the regional and dimensional level are fully comparable to the ones for the entire industry. Historical data up to 1991 have been recalculated accordingly to the new aggregation scheme and are presented here as a conclusion of the paper.
|Item Type:||MPRA Paper|
|Original Title:||Re-engineering the ISAE manufacturing survey|
|Keywords:||Survey methods, aggregation, weights|
|Subjects:||E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E32 - Business Fluctuations ; Cycles
C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs > C82 - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data ; Data Access
?? C42 ??
|Depositing User:||Patrizia Margani|
|Date Deposited:||06. Nov 2012 11:16|
|Last Modified:||23. Aug 2015 13:55|
Altissimo F., Marchetti D.J. and Oneto G.P. (2000), “The Italian Business Cycle: Coincident and Leading Indicators and Some Stylised Facts”, Temi di Discussione, n. 377, Bank of Italy, Rome.
Bovi M., Lupi C. and Pappalardo C. (2000), “Predicting GDP Components Using ISAE Bridge Equations Econometric Forecasting Model (BEEF)”, ISAE Working Paper n. 13, Istituto di Studi ed Analisi Economica, Rome.
Bruno G. and Lupi C. (2001), “Forecasting Industial Production and the Early Detection of Turning Points”, ISAE Working Paper , n. 20, Istituto di Studi ed Analisi Economica, Rome.
Bruno G. and Lupi C. (2003), Forecasting Euro-Area Industrial Production Using (Mostly) Business Survey Data”, ISAE Working Paper, n. 33, Istituto di Studi ed Analisi Economica, Rome.
Bruno G. and Malgarini M. (2002), An Indicator of Economic Sentiment for Italian Economy, ISAE Working Paper n. 28, Istituto di Studi ed Analisi Economica, Rome.
Bry G. and Boschan C. (1971), “Cyclical Analysis of Time-Series: Selected Procedures and Computer Programs”, NBER Technical Paper, n. 20.
Carlson J. A., Parkin M, (1975), “Inflation Expectations”, Economica, may.
Carnazza P. (2001), “The Role of Short-Term Economic Information in Industrial Firms’ Strategy”, ISAE Working Paper n. 15, Istituto di Studi ed Analisi Economica, Rome.
Carnazza P. and Parigi G. (2003), “Tentative Business Confidence Indicators for the Italian Economy”, Journal of Forecasting, 22 (8), pag. 587-602.
Cicchitelli G., Herzel A., and Montanari G.E. (1992), Il Campionamento Statistico, Il Mulino, Bologna.
Cicconi C., (2004), “A Smooth Survey-Based Indicator Free of End-of-Sample Revisions”, paper presented at the 27th Ciret Conference, Warsaw, 15-18 September.
Chiades P., Gallo M. and Venturini A. (2003), “L’Utilizzo degli Indicatori Compositi nell’Analisi Congiunturale Territoriale: un’Applicazione all’Economia del Veneto”, Temi di Discussione, n. 485, Bank of Italy, Rome.
Cochran, W. G. (1977), Sampling Techniques, 3rd edition, John Wiley and Sons, New York.
Dahl, C.M. and Xia L. (2004), “Quantification of Qualitative Survey Data and Test of Consistent Expectations: A New Likelihood Approach”, Journal of Business Cycle Measurement and Analysis, Ciret and OECD, Paris.
D’Elia, E. (1991), “La Quantificazione dei Risultati dei Sondaggi Congiunturali: Un Confronto Tra Procedure”, Rassegna di Lavori dell’ISCO, ISCO, Rome.
European Commission (1997),”The Joint Harmonized EU Programme of Business and Consumer Surveys”, European Economy, Reports and Studies, n. 6, Bruxelles.
European Commission (2002), “The Joint Harmonized EU Programme of Business and Consumer Surveys”, User Guide 2002, Bruxelles.
Gomez, V. and Maravall, A. (1996), “Programs Tramo and Seats”, Banco de Espana, Servicio de Estudios, Documento de Trabajo, n. 9628.
ISAE (2003), “La Congiuntura Industriale in Italia”, Nota Mensile, Istituto di Studi e Analisi Economica, Rome.
ISCO (1961), “Progetto per un’inchiesta congiunturale Rapida Mensile tra i sei Paesi della Comunità Economica Europea”, Congiuntura Italiana, n. 12, Istituto Nazionale per lo Studio della Congiuntura, Rome.
Martelli B. (1998), Le Inchieste Congiunturali dell’ISCO: Aspetti Metodologici, Rassegna di Lavori dell’ISCO, n. 3, Anno XV, Istituto Nazionale per lo Studio della Congiuntura, Rome.
OECD (2000), System of National Accounts 1993 Glossary, OECD, Paris.
OECD (2003), Business Tendency Surveys: A Handbook, OECD, Paris.
Oppenlander, K.H. and Poser G., eds (1984), “Leading Indicators and Business Cycles Surveys”, paper presented at the 16th Ciret Conference, Washington D.C., 1983, Aldershot.
Oppenlander, K.H. and Poser G., eds (1986), “Business Cycles Surveys in the Assessment of Economic Activity”, paper presented at the 17th Ciret Conference, Vienna, 1985, Aldershot.
Oppenlander, K.H. and Poser G., eds (1988), “Contributions of Business Cycles Surveys to Empirical Economics”, paper presented at the 18th Ciret Conference, Zurich, 1987, Aldershot.
Oppenlander, K.H. and Poser G., eds (1996), “Business Cycles Surveys: Forecasting Issues and Methodological Aspectes”, paper presented at the 22th Ciret Conference, Singapore, 1995, Gower.
Oppenlander, K.H. and Poser G., eds (2000), “Use of Survey Data for Industry Research and Economic Policy”, paper presented at the 24th Ciret Conference, Wellington, New Zealand, Gower.
Oppenlander, K.H., Poser G., and Nerb G., eds (1995), “Application of Business Surveys for Macroeconomic Analysis”, CIRET Studies, n. 49.
Pinca F. (1990), “La Regionalizzazione delle Indagini Congiunturali”, M. Strassoldo (ed.), L’Analisi della Congiuntura Economica Locale: Modelli, Metodi e Basi informative, CEDAM, Padova.
Schafer G. (2001), “Main Industrial Groupings – Common Aggregates for Analysing Business Cycles”, Statistics in Focus, Theme 4, 8/2001, Eurostat, Luxembourg.
The Conference Board (2001), Business Cycle Indicators Handbook, New York, NY.