## Abstract

This paper employs a spatial Durbin panel data model, an extension of the crosssectional

spatial Durbin model to a panel data framework, to estimate the impact of a set of social

and economic determinants on opioid-induced mortality in the US. The empirical model uses a

pool of US states over six years from 2014 to 2019 and a k=8 neighbor matrix that represents the

topological structure between the states. Calculation of direct (own state) and indirect (cross-state

spillovers) effects estimates – based on Bayesian estimation and inference – reflects a proper

interpretation of the marginal effects for our nonlinear model that involves lags of the dependent

variable vector. The study provides evidence for the existence of spatial effects working through

the dependent variable vector and points to the importance of larger indirect effects of Asian

and Hispanic/Latino minorities on the one side and the population age groups 35-44 years and

65 years and older on the other. This finding echoes the first law of geography that ”everything

is related to everything else, but near things are more related than distant things” (Tobler

1970). Space – largely neglected in previous research – matters for gaining a valid and better understanding

of why and how neighboring states contribute to opioid-induced mortality in the states.

spatial Durbin model to a panel data framework, to estimate the impact of a set of social

and economic determinants on opioid-induced mortality in the US. The empirical model uses a

pool of US states over six years from 2014 to 2019 and a k=8 neighbor matrix that represents the

topological structure between the states. Calculation of direct (own state) and indirect (cross-state

spillovers) effects estimates – based on Bayesian estimation and inference – reflects a proper

interpretation of the marginal effects for our nonlinear model that involves lags of the dependent

variable vector. The study provides evidence for the existence of spatial effects working through

the dependent variable vector and points to the importance of larger indirect effects of Asian

and Hispanic/Latino minorities on the one side and the population age groups 35-44 years and

65 years and older on the other. This finding echoes the first law of geography that ”everything

is related to everything else, but near things are more related than distant things” (Tobler

1970). Space – largely neglected in previous research – matters for gaining a valid and better understanding

of why and how neighboring states contribute to opioid-induced mortality in the states.

Originalsprache | Englisch |
---|---|

Herausgeber | WU Vienna University of Economics and Business |

Publikationsstatus | Veröffentlicht - 1 Aug. 2022 |

### Publikationsreihe

Name | Working Papers in Regional Science |
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Band | 2022/01 |

## WU Working Paper Reihe

- Working Papers in Regional Science

## Schlagwörter

- Bayesian econometrics
- Markov Chain Monte Carlo,
- Spatial Durbin panel data model direct (own state) effects
- indirect (cross-state spatial spillover) effects
- inferential statistics