The Effect of Tax Credit Policy on Electric Vehicle Sales: A Synthetic Control Approach Using Bayesian Structural Time Series

Authors

  • Atia Ferdousee Middle Tennessee State University

DOI:

https://doi.org/10.33423/jabe.v22i13.3912

Keywords:

business, economics, tax credit policy, Bayesian structural time series model, electric vehicle, synthetic control

Abstract

The government is intervening in automobile markets to reduce greenhouse gas emissions in many countries. Several tax incentive programs, at both federal and state level, are being effective for the adoption of environment-friendly vehicles over the past few years. Previous studies in this field focused on discrete choice models analyzing such policies. In this study, however, I employed a Bayesian structural forecasting model to construct a synthetic control to test the effects of state-level tax credit policy in Maryland using a unique time-series data set of vehicle sales records. I observed a significant positive policy effect on electric vehicle sales.

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Published

2020-12-20

How to Cite

Ferdousee, A. (2020). The Effect of Tax Credit Policy on Electric Vehicle Sales: A Synthetic Control Approach Using Bayesian Structural Time Series. Journal of Applied Business and Economics, 22(13). https://doi.org/10.33423/jabe.v22i13.3912

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Section

Articles