Exploring the dynamics of business survey data using Markov models

Business tendency surveys are widely used for monitoring economic activity. They provide timely feedback on the current business conditions and outlook. We identify the unobserved macroeconomic factors behind the distribution of quarterly responses by Austrian firms on the questions concerning the current business climate and production. The aggregate models identify two macroeconomic regimes: upturn and downturn. Their dynamics is modeled using a regime-switching matrix. The micro-founded models envision dependent responses by the firms, so that a favorable or an adverse unobserved common macroeconomic factor increases the frequency of optimistic or pessimistic responses. The corresponding conditional transition probabilities are estimated using a coupling scheme. Extensions address the sector dimension and introduce dynamic common tendencies modeled with a hidden Markov chain.