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.
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).
References
Abadie, A. (2005), Semiparametric Difference–in–Differences Estimators. Review of Economic Studies 72: 1–19.10.1111/0034-6527.00321Search in Google Scholar
Abadie, A., Diamond A., Hainmueller J. (2010), Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California’s Tobacco Control Program. Journal of the American Statistical Association 105: 493–505.10.1198/jasa.2009.ap08746Search in Google Scholar
Angrist, J. D., Pischke J. (2009), Mostly Harmless Econometrics: An Empiricist’s Companion. Princeton, NJ: Princeton University Press.10.1515/9781400829828Search in Google Scholar
Bertrand, M., Duflo E., Mullainathan S. (2004), How Much Should We Trust Differences–In–Differences Estimates? Quarterly Journal of Economics 119(1): 249–275.10.1162/003355304772839588Search in Google Scholar
Borland R., Yong H. H., Siahpush M., Hyland A., Campbell S., Hastings G., Cummings K. M., Fong G. T. (2006), Support for and Reported Compliance with Smoke-free Restaurants and Bars by Smokers in Four Countries: Findings from the International Tobacco Control (ITC) Four Country Survey. Tobacco Control 15: 34–41.10.1136/tc.2004.008748Search in Google Scholar
Brodersen, K. H., Gallusser F., Koehler J., Remy N., Scott S. L. (2015), Inferring Causal Impact using Bayesian Structural Time–Series Models. The Annals of Applied Statistics 9: 247–274.10.1214/14-AOAS788Search in Google Scholar
Chun J. Y., Seo H. K., Kim M. K., Shin M. J., Kim S. Y., Kim M., Kim C. J., Song K. H., Kim E. S., Lee H., Kim H. B. (2016), Impact of a Hand Hygiene Campaign in a Tertiary Hospital in South Korea on the Rate of Hospital-Onset Methicillin–Resistant Staphylococcus Aureus Bacteremia and Economic Evaluation of the Campaign. American Journal of Infection Control 44: 1486–1491.10.1016/j.ajic.2016.07.009Search in Google Scholar
Centro de Investigaciones Sociológicas (CIS). Barómetro Sanitario. Available online: http://www.msssi.gob.es/estadEstudios/estadisticas/docs/BS2006totalmar.pdf Accessed June 2015).(Search in Google Scholar
Fernández E., Fu M., Pascual J. A., López M. J., Pérez–R&’ios M., Schiaffino A., Mart&’inez–Sánchez J. M., Ariza C., Saltó E., Nebot M. (2009), Impact of the Spanish Smoking Law on Exposure to Second–Hand Smoke and Respiratory Health in Hospitality Workers: A Cohort Study. PLOS ONE 4: 42–44.10.1371/journal.pone.0004244Search in Google Scholar
Galán I., López M. J. (2009), Tres años con Ley de medidas sanitarias frente al tabaquismo: aire más limpio, pero no lo suficiente. Gaceta Sanitaria 23: 87–90.10.1016/j.gaceta.2009.01.003Search in Google Scholar
George, E. I., McCulloch R. E. (1993), Variable Selection via Gibbs Sampling. Journal of the American Statistical Association 88: 881–889.10.1080/01621459.1993.10476353Search in Google Scholar
George, E. I., McCulloch R. E. (1997), Approaches for Bayesian Variable Selection. Statistica Sinica 7: 339–374.Search in Google Scholar
González, R., Hosoda E. B. (2016), Environmental Impact of Aircraft Emissions and Aviation Fuel Tax in Japan. Journal of Air Transport Management 57: 231–240.10.1016/j.jairtraman.2016.08.006Search in Google Scholar
Heckman, J. J., Vytlacil E. J. (2007), Econometric Evaluation of Social Programs, Part I: Causal Models, Structural Models and Econometric Policy Evaluation. 4779–4874 in: Heckman J. J. and Leamer E. E. (eds.), Handbook of Econometrics 6, Part B. Elsevier, Amsterdam.10.1016/S1573-4412(07)06070-9Search in Google Scholar
Hoeting, J.A., Madigan D., Raftery A.E., Volinsky C. T. (1999), Bayesian Model Averaging: A Tutorial. Statistical Science 14: 382–401.Search in Google Scholar
Joossens, L., Raw M. (1995), Smuggling and Cross Border Shopping of Tobacco in Europe. British Medical Journal 310(6991): 1393–1397.10.1136/bmj.310.6991.1393Search in Google Scholar
Kleinberg, S., Hripcsak G. (2011), A Review of Causal Inference for Biomedical Informatics. Journal of Biomedical Informatics 44: 1102–1112.10.1016/j.jbi.2011.07.001Search in Google Scholar
Lakhdar C.B. (2008), Quantitative and Qualitative Estimates of Cross-border Tobacco Shopping and Tobacco Smuggling in France. Tob Control 17: 1216.10.1136/tc.2007.020891Search in Google Scholar
Ley de medidas sanitarias frente al tabaquismo y reguladora de la venta, el suministro, el consumo y la publicidad de los productos del tabaco. L. N. 28/2005 (26 December 2005).Search in Google Scholar
Ley por la que se modifica la Ley 28/2005, de 26 de diciembre, de medidas sanitarias frente al tabaquismo y reguladora de la venta, el suministro, el consumo y la publicidad de los productos del tabaco. L. N. 42/2010 (30 December 2010).Search in Google Scholar
Liang, F., Paulo R., Molina G., Clyde M. A., Berger J. O. (2008), Mixtures of $$g-$$priors for Bayesian Variable Selection. Journal of the American Statistical Association 103: 410–423.10.1198/016214507000001337Search in Google Scholar
López M.J., Nebot M., Schiaffino A., Pérez–R&’ios M., Fu M., Ariza C. G. Muñoz, E. Fernández E (2012), Two–Year Impact of the Spanish Smoking Law on Exposure to Secondhand Smoke: Evidence of the Failure of the “Spanish model”. Tobacco Control 21: 407–411.10.1136/tc.2010.042275Search in Google Scholar
Nagelhout G. E., van den Putte B., Allwright S., Mons U., McNeill A., Guignard R., Beck F., Siahpush M., Joossens L., Fong G. T., de Vries H., Willemsen M. C. (2014), Socioeconomic and Country Variations in Cross-Border cigarette Purchasing as Tobacco Tax Avoidance Strategy. Findings from the ITC Europe Surveys. Tobacco Control 23: 30–38.10.1136/tobaccocontrol-2012-050838Search in Google Scholar
OECD (2015), Daily Smokers (indicator). doi: 10.1787/1ff488c2-en Accessed 12 July 2015).(Search in Google Scholar
Polson, N. G., Scott S. L. (2011), Data Augmentation for Support Vector Machines. Bayesian Analysis 6: 1–23.10.1214/11-BA601Search in Google Scholar
Ranson, M. K., Jha P., Chaloupka F. J., Nguyen S. N. (2002), Global and Regional Estimates of the Effectiveness and Cost-Effectiveness of Price Increases and Other Tobacco Control Policies. Nicotine & Tobacco Research 4: 311–319.10.1080/14622200210141000Search in Google Scholar
Rubin, D. W. (2008), Statistical Inference for Causal Effects, with Emphasis on Applications in Epidemiology and Medical Statistics. in: Miller J. P., Rao C. R., Rao D. C. (eds.),Epidemiology and Medical Statistics. Handbook of Statistics 27: 28–63. Elsevier, Amsterdam.10.1016/S0169-7161(07)27002-6Search in Google Scholar
Scott, J. G., Varian H. R. (2014), Predicting the Present with Bayesian Structural Time Series. International Journal of Mathematical Modeling and Optimization 5: 4–23.10.1504/IJMMNO.2014.059942Search in Google Scholar
Schaap, M. M., Kunst A. E., Leinsalu M., Regidor E., Ekholm O., Dzurova D., Helmert U., Klumbiene J., Santana P., Mackenbach J. P. (2008), Effect of Nationwide Tobacco Control Policies on Smoking Cessation in High and Low Educated Groups in 18 European Countries. Tobacco Control 17: 248–255.10.1136/tc.2007.024265Search in Google Scholar
World Health Organization (2015), WHO Report on the Global Tobacco Epidemic, 2015: Raising Taxes on Tobacco Executive Summary. http://www.who.int/tobacco/global\_report/2015/report/en/ (Accessed 28 July 2015).Search in Google Scholar
Zellner, A. (1986), On Assessing Prior Distributions and Bayesian Regression Analysis with $$g-$$prior Distributions. in: Goel P. K., Zellner A. (eds.), Bayesian Inference and Decision Techniques: Essays in Honor of Bruno de Finetti. Studies in Bayesian Econometrics and Statistics 6: 233–243. North–Holland, Amsterdam.Search in Google Scholar
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.
© 2018 Oldenbourg Wissenschaftsverlag GmbH, Published by De Gruyter Oldenbourg, Berlin/Boston
