New Proposals for the Quantification of Qualitative Survey Data

In this paper we propose and evaluate two new methods for the quantification of business surveys concerning the qualitative assessment of the state of the economy. The first is a nonparametric method based on the spectral envelope, originally proposed by Stoffer, Tyler and McDougall (Spectral analysis for categorical time series: scaling and the spectral envelope, Biometrika 80: 611-622) to the multivariate time series of the counts in each response category. Secondly, we fit by maximum likelihood a cumulative logit unobserved components models featuring a common cycle. The conditional mean of the cycle, which can be evaluated by importance sampling, offers the required quantification. We assess the validity of the two methods by comparing the results with a standard quantification based on the balance of opinions and with a quantitative economic indicator. Copyright (C) 2010 John Wiley & Sons, Ltd.