Accessible Unlicensed Requires Authentication Published by De Gruyter Oldenbourg April 10, 2018

Using a Bayesian Structural Time–Series Model to Infer the Causal Impact on Cigarette Sales of Partial and Total Bans on Public Smoking

Jaime Pinilla, Miguel Negrín, Beatriz González-López-Valcárcel and Francisco-José Vázquez-Polo

Abstract

The Bayesian structural time series model, used in conjunction with a state–space model, is a novel means of exploring the causal impact of a policy intervention. It extends the widely used difference–in–differences approach to the time series setting and enables several control series to be used to construct the counterfactual. This paper highlights the benefits of using this methodology to estimate the effectiveness of an absolute ban on smoking in public places, compared with a partial ban. In January 2006, the Spanish government enacted a tobacco control law which banned smoking in bars and restaurants, with exceptions depending on the floor space of the premises. In January 2011, further legislation in this area was adopted, removing these exceptions. The data source used for our study was the monthly legal sales of cigarettes in Spain from January 2000 to December 2014. The potential control series were the monthly tourist arrivals from the United Kingdom, the total number of visitors from France, the unemployment rate and the average price of cigarettes. Analysis of the state–space model leads us to conclude that the partial ban was not effective in reducing the tobacco sold in Spain, but that the total ban contributed significantly to reducing cigarette consumption.

JEL Classification: K20; I12; L66; C11; C31

Acknowledgements:

The authors are grateful to two anonymous referees for valuable comments and suggestions on an earlier version of the paper. This research has been partially supported by the Grants ECO2013–47092–P, ECO2017–35755–P and ECO2013–48217–C2–1–R(MINECO, Spain).

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Article note

This article is part of the special issue “Empirical Health Economics” published in the Journal of Economics and Statistics. Access to further articles of this special issue can be obtained at www.degruyter.com/journals/jbnst.

Code and Datasets

The author(s) published code and data associated with this article in the ZBW Journal Data Archive, a storage platform for datasets. See: https://doi.org/10.15456/jbnst.2018303.125442.

Received: 2017-07-05
Revised: 2018-01-26
Accepted: 2018-03-12
Published Online: 2018-04-10
Published in Print: 2018-09-25

© 2018 Oldenbourg Wissenschaftsverlag GmbH, Published by De Gruyter Oldenbourg, Berlin/Boston