Markov chain Monte Carlo methods in corporate finance
Arthur Korteweg


This chapter introduces Markov chain Monte Carlo(MCMC) methods for empirical corporate finance. These methods are very useful for researchers interested in capital structure, investment policy,financial intermediation,corporategovernance,structural models of the firm and other areas of corporate finance. In particular, MCMC can be used to estimate models that are difficult to tackle with standard tools such as OLS, Instrumental Variables regressions and Maximum Likelihood. Starting from simple examples, this chapter exploits the modularity of MCMC to build sophisticated discrete choice, self-selection, panel data and structural models that can be applied to a variety of topics.Emphasis is place on cases for which estimation by MCMC has distinct benefits compared to the standard methods in the field. I conclude with a list of suggested applications.