1. Evaluating Alternative Index Designs for the Texas Manufacturing Outlook Survey
Third Joint European Commission-OECD Workshop on International Development of Business and Consumer Tendency Surveys
Brussels, November 2007
By Fiona Sigalla, Frank Berger, Tom Fomby,
Keith Phillips and Mine Yücel
Federal Reserve Bank of Dallas
The views expressed are the authors and do not necessarily represent those of
the Federal Reserve Bank of Dallas or the Federal Reserve System

2. Weighting of Business Tendency Surveys
Countries using firm size and industry weighting
Belgium Czech Republic Denmark
Finland France Germany
Hong Kong Italy Netherlands
Portugal Slovakia South Africa
Spain Switzerland United Kingdom
Countries using unweighted indexes
Austria China P.R. Hungary
Korea United States
U.S. Regional Federal Reserve Banks

3. The Unweighted Index Gives equal weight to all responding firms.
Responses from large firms and small firms contribute equally to the index.
Can be distorted by participation of firms.
Industries with numerous small firms can be over-represented compared to industries with a few large firms.
Varies with month-to-month response rate of the survey panel.

4. The OECD Weighted Index
Firm weighting
Firms are weighted based on size
assigning more weight to big firms than small firms
Sampling weighting
corrects for firms entering and exiting the sample
corrects for sample not being representative of population
Industry weighting
Industries are weighted based on value added

5. Comparison of Weighted and Unweighted indexes

9. In Search of a Good Dependent Variable
Texas variables
Texas manufacturing employment
Texas manufacturing coincident index
U.S. variables
U.S. manufacturing employment
U.S. industrial production index
Institute of Supply Management Manufacturing Indexes

10. Evaluating Alternative Weighting Schemes
Seasonally adjust survey variables as necessary.
Most dependent variables are in percent changes.
ISM indexes are levels because they are stationary.
Employment used instead of value added for industry weights on employment variable.
OLS with one lag of the dependent variable.

16. Conclusions
Many unweighted and most weighted indexes have significant explanatory power for some important regional and national variables.
Both regional and national indicators:
weighted indexes were superior most of the time.
unweighted seemed to work best for employment and out of sample Texas variables.

17. This research would benefit from testing a longer time series, such as data from an OECD country.