Using the results of qualitative surveys in quantitative analysis

The answers to qualitative questions put to economic operators can be integrated in standard macro-economic analysis by using a "quantification" procedure chosen among the probabilistic approach, the regression methods or the latent factor approach. The first one is the most commonly used. It is based on the assumption that the respondents reply that the value of the reference variable x can be described by a certain statement (e.g.: x stays stable) if it lies between two known thresholds (e.g.: ±5% around its initial value). A number of quantified indicators may be derived by assuming a special functional form for the frequency distribution of opinions and expectations of respondents about x. According to the regression approach, the respondents attach to each qualitative answer a reference value of x, which can be estimated by regressing an available quantitative measure of x against the time series (or longitudinal samples) of percentages of people who gave each qualitative answer. Finally, one can assume that every percentage of answers is driven by a single common "latent factor", which can be estimated by applying to the percentages of answers the standard tools of multivariate statistics. All of the three approaches include as a special case the "balance statistic", adopted very often in empirical analyses. Both the theoretical analysis and the empirical evidence on the relative merits of various methods are mixed. In general, no single quantification technique clearly outperforms the others, at least in preliminary analysis. However, when the quantified indicators must be included as explanatory variables in standard econometric models, the regression approach seems the most suitable and natural one. On its turn, the latent factor approach provides a profitable alternative to the regression method in exploratory analyses and when multicollinearity and degrees of freedom of estimates become severe constraints.