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Working Paper
A moment-matching method for approximating vector autoregressive processes by finite-state Markov chains
This paper proposes a moment-matching method for approximating vector autoregressions by finite-state Markov chains. The Markov chain is constructed by targeting the conditional moments of the underlying continuous process. The proposed method is more robust to the number of discrete values and tends to outperform the existing methods for approximating multivariate processes over a wide range of the parameter space, especially for highly persistent vector autoregressions with roots near the unit circle.
Working Paper
The Downward Spiral
To analyze the opioid epidemic, we construct a model where individuals, with and without pain, choose whether to misuse opioids knowing the probabilities of addiction and dying. These odds are functions of opioid use. Markov chains are estimated from the US data for the college and non–college educated that summarize the transitions into and out of opioid addiction as well as to a deadly overdose. We construct a structural model that matches the estimated Markov chains. We also examine the epidemic’s drivers and the impact of medical interventions.