Risk Econometrics: A Practical Guide to Bayesian and Frequentist Methods serves as a guide to mastering a growing number of applications in network analysis, environmental science and healthcare. By avoiding a focus either on time series or cross-sectional/panel data methods and adopting either Frequentist (Classical) or Bayesian approaches, it trains readers to recognize the most important aspects of applied Frequentist and Bayesian statistics, emphasizing methods, insights, and popular advances widely used during the last ten years. Sections dive deeply into the assumptions and pros and cons of statistical methods. Based on R and Python, and accompanied by both exercises and research projects, this book reinforces a balance between theory and practice that other books, wedded to only one statistical method, cannot match.

Author Biography

Elena Goldman is an Associate Professor at Pace University, where she teaches courses in Financial Econometrics, International Finance and Financial Management. She has published in the Journal of Financial Research, Studies in Nonlinear Dynamics and Econometrics, Empirical Economics, Communications in Statistics, Journal of Trade and Global Markets, Economics Letters, Bayesian Statistics and its Applications volume among other, and she received her Ph.D. from Rutgers University.