The Fed's policy rule switches during the different phases of the business cycle. This finding is established using a dynamic mixture model to estimate regime-dependent Taylor-type rules on US quarterly data from 1960 to 2021. Instead of exogenously partitioning the data based on tenures of the...

In several scientific fields, such as finance, economics and bioinformatics, important theoretical and practical issues exist involving multimodal and asymmetric count data distributions due to heterogeneity of the underlying population. For accurate approximation of such distributions we...

Detecting heterogeneity within a population is crucial in many economic and financial applications. Econometrically, this requires a credible determination of multimodality in a given data distribution. We propose a straightforward yet effective technique for mode inference in discrete data...

Multimodal empirical distributions arise in many fields like Astrophysics, Bioinformatics, Climatology and Economics due to the heterogeneity of the underlying populations. Mixture processes are a popular tool for accurate approximation of such distributions and implied mode detection. Using...

In this essay six societal challenges and research opportunities that confront 21st century Bayesian econometricians are briefly discussed using an important feature of modern Bayesian econometrics: conditional probabilities of a wide range of economic events of interest can be evaluated by...