Machine derived contents note: Chapter 1: Decision Theory and Bayesian Inference --
Chapter 2: Bayesian Statistics and Linear Regression --
Chapter 3: Methods of Numerical Integration --
Chapter 4: Prior Densities for the Regression Model --
Chapter 5: Dynamic Regression Models --
Chapter 6: Bayesian Unit Roots --
Chapter 7: Heteroskedasticity and ARCH --
Chapter 8: Nonlinear Tome Series Models --
Chapter 9: Systems of Equations --
Appendix A: Probability Distributions --
Appendix B: Generating Random Numbers.

Offering an up-to-date coverage of the basic principles and tools of Bayesian inference in economics, this textbook then shows how to use Bayesian methods in a range of models suited to the analysis of macroeconomic and financial time series