SpringerLink
Log in

An empirical assessment of effectiveness of the US tobacco control policies: a smoothed instrumental variables quantile regression approach

  • Published:
Empirical Economics Aims and scope Submit manuscript

Abstract

A sound understanding of the potency of tobacco control policies is key to tobacco prevention. This study exploits a Smoothed Instrumental Variables Quantile Regression estimator to gauge the effectiveness of these policies while addressing major methodological and data limitations plaguing the previous literature. Specifically, smoke-free indoor air laws and tobacco control expenditures are examined in a single framework, which has the promise of accounting for potential complementarities thereof. Further, endogeneity of price (a proxy for tax policy) and other tobacco control policies is addressed through a unique set of instruments while allowing for differential impacts across the conditional distribution of cigarette consumption. Finally, our use of the nationally representative individual-level price and consumption data is essential to precise estimation of price elasticities and policy effects. Results indicate that ignoring price and policy endogeneity leads to inconsistent estimates. Further, tobacco control expenditures appear to be effective only for relatively more addicted smokers. Meanwhile, state-level smoke-free indoor laws, whose primary goal is to reduce exposure to second-hand smoke, do not affect cigarette use among smokers. In contrast, tax policy appears to be most potent for less addicted individuals. Therefore, optimal policy responses should combine tobacco control expenditures with sin taxes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Spain)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Data availability

We are able to share our data and estimation code permanently.

Notes

  1. According to the Guardian (2019): “The phrase “sin tax” is first recorded in 1901, in an article about a young women’s society in the USA that fined its members for using slang. (“My sin tax!” exclaimed one as she paid up.) Its political use, to mean state levies on alcohol, tobacco and gambling, is attributed to Eisenhower’s chief of staff, Sherman Adams, during his previous time as governor of New Hampshire (1948–52).”.

  2. As illustrated by Dhar et al. (2003), Hovhannisyan and Bozic (2017), and Hovhannisyan and Devadoss (2020), unless properly addressed, endogenous regressors can lead to biased estimates of economic effects and erroneous policy recommendations.

  3. SIVQR implements the smoothed estimator of Kaplan and Sun (2017). Despite many similarities to other quantile regression estimators, some of the main advantages of SIVQR are the fast computation and allowance for multiple endogenous variables. For example, compared to Censored Quantile Instrumental Variables (CQIV) estimator derived by Chernozhukov et al. (2019), SIVQR allows for multiple discrete and continuous endogenous variables while handling reverse causality and simultaneity (Kaplan 2022). See Kaplan (2020) and Kaplan (2022) for more detail on how SIVQR compares to the remaining quantile regression estimators such as those implemented by Stata commands IVQREG, IVQREG2, and IVQTE.

  4. It deserves noting that the outcome variable in this setting is the number of cigarettes smoked (i.e., intensive margin). Further, smoke-free indoor laws can still be “optimal” insofar as they reduce second-hand smoke exposure, which is their primary goal (Center for Disease Control and Prevention (CDC) 2021).

  5. Equation (1) does not include an "error term", because it is implied by the randomness of the coefficient vectors \({{\varvec{\upbeta}}}\left( U \right)\) and \({{\varvec{\upalpha}}}\left( U \right)\).

  6. Parameter estimates from the first-stage regressions are not presented because of limited space; however, they are available upon request.

  7. When estimating the SIVQR, in addition to the political ideology-related instruments, we also include state fixed-effects to account for the potential effects of tobacco lobby political influence (as explained earlier). We do not conduct overidentification tests for the SIVQR, as to our knowledge, currently it does not allow for this test. However, Liu (2023) formally introduces an overidentification test for IVQR, which we will use in our future studies.

  8. As our analysis is conditional on smoking, one may wonder about potential bias in estimated policy effects resulting from it. However, our results from a sample containing both smokers and nonsmokers are virtually identical to those based on smokers only.

  9. To our knowledge, this constitutes the first study examining tobacco control expenditures and smoke-free indoor air laws in a single empirical framework.

References

  • Berry WD, Ringquist EJ, Fording RC, Hanson RL (1998) Measuring citizen and government ideology in the American States, 1960–93. Am J Polit Sci 42(1):327–348

    Article  Google Scholar 

  • Bialous SA, Glantz SA (2018) Heated tobacco products: another tobacco industry global strategy to slow progress in tobacco control. Tob Control 27(Suppl 1):s111–s117

    Article  PubMed  Google Scholar 

  • Bottai M, Frongillo EA, Sui X, O’Neill JR, McKeown RE, Burns TL, Liese AD, Blair SN, Pate RR (2014) Use of quantile regression to investigate the longitudinal association between physical activity and body mass index. Obesity (silver Spring) 22(5):E149-156

    Article  PubMed  Google Scholar 

  • Callison K, Kaestner R (2014) Do higher tobacco taxes reduce adult smoking? New evidence of the effect of recent cigarette tax increases on adult smoking. Econ Inq 52(1):155–172

    Article  Google Scholar 

  • Campaign for Tobacco-Free Kids (2021) Broken promises to our children: a state-by-state look at the 1998 tobacco settlement 22 years later. from https://www.tobaccofreekids.org/what-we-do/us/statereport

  • Carroll J (2004) "Smoking." Gullup Polls. Retrieved October 20, 2023, from https://news.gallup.com/poll/14257/smoking.aspx

  • Center for Disease Control and Prevention (CDC) (2021) "Smokefree Policies Reduce Smoking." Retrieved June 17, 2023, from https://www.cdc.gov/tobacco/secondhand-smoke/protection/reduce-smoking.htm

  • Centers for Disease Control and Prevention (2015) National adult tobacco survey. Retrieved April 15, 2016, from http://www.cdc.gov/tobacco/data_statistics/surveys/nats/

  • Centers for Disease Control and Prevention (CDC) (2009) Federal and state cigarette excise taxes - United States, 1995–2009. Morb Mortal Wkly Rep 58(19):524–527

    Google Scholar 

  • Centers for Disease Control and Prevention (CDC) (2021) State tobacco activities tracking and evaluation (STATE) system. Retrieved August 21, 2021, from http://www.cdc.gov/statesystem/

  • Chaloupka F (1991) Rational addictive behavior and cigarette smoking. J Polit Econ 99(4):722–742

    Article  Google Scholar 

  • Chaloupka F, Saffer H (1992) Clean indoor air laws and the demand for cigarettes. Contemp Econ Policy 10(2):72–83

    Article  Google Scholar 

  • Chaloupka F, Warner K (2000) Chapter 29: The economics of smoking. Handbook of Health Economics, Elsevier, 1, pp 1539–1627

  • Chaloupka F, Wechsler H (1997) Price, tobacco control policies and smoking among young adults. J Health Econ 16(3):359–373

    Article  CAS  PubMed  Google Scholar 

  • Chen CM, Chang KL, Lin L (2013) Re-examining the price sensitivity of demand for cigarettes with quantile regression. Addict Behav 38(12):2801–2804

    Article  PubMed  Google Scholar 

  • Chernozhukov V, Fernández-Val I, Han S, Kowalski A (2019) Censored quantile instrumental-variable estimation with Stata. Stand Genomic Sci 19(4):768–781

    Google Scholar 

  • Chernozhukov V, Hansen C (2005) An IV model of quantile treatment effects. Econometrica 73(1):245–261

    Article  MathSciNet  Google Scholar 

  • Cohen JE, Milio N, Rozier RG, Ferrence R, Ashley MJ, Goldstein AO (2000) Political ideology and tobacco control. Tob Control 9(3):263–267

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Colman GJ, Remler DK (2008) Vertical equity consequences of very high cigarette tax increases: if the poor are the ones smoking, how could cigarette tax increases be progressive? J Policy Anal Manage 27(2):376–400

    Article  Google Scholar 

  • Corliss HL, Wadler BM, Jun HJ, Rosario M, Wypij D, Frazier AL, Austin SB (2013) Sexual-orientation disparities in cigarette smoking in a longitudinal cohort study of adolescents. Nicotine Tob Res 15(1):213–222

    Article  PubMed  Google Scholar 

  • DeCicca P, McLeod L (2008) Cigarette taxes and older adult smoking: evidence from recent large tax increases. J Health Econ 27(4):918–929

    Article  PubMed  Google Scholar 

  • Dhar T, Chavas J-P, Gould BW (2003) An empirical assessment of endogeneity issues in demand analysis for differentiated products. Am J Agr Econ 85(3):605–617

    Article  Google Scholar 

  • Duffy M (1996) Econometric studies of advertising, advertising restrictions and cigarette demand: a survey. Int J Advert 15(1):1–23

    Article  Google Scholar 

  • Evans WN, Ringel JS, Stech D (1999) Tobacco taxes and public policy to discourage smoking. Tax Policy and the Economy, Volume 13. J. Poterba. Cambridge, MA, National Bureau of Economic Research

  • Farrelly MC, Loomis BR, Han B, Gfroerer J, Kuiper N, Couzens GL, Dube S, Caraballo RS (2013) A comprehensive examination of the influence of state tobacco control programs and policies on youth smoking. Am J Public Health 103(3):549–555

    Article  PubMed  PubMed Central  Google Scholar 

  • Farrelly MC, Loomis BR, Kuiper N, Han B, Gfroerer J, Caraballo RS, Pechacek TF, Couzens GL (2014) Are tobacco control policies effective in reducing young adult smoking? J Adolesc Health 54(4):481–486

    Article  PubMed  Google Scholar 

  • Farrelly MC, Pechacek TF, Chaloupka FJ (2003) The impact of tobacco control program expenditures on aggregate cigarette sales: 1981–2000. J Health Econ 22(5):843–859

    Article  PubMed  Google Scholar 

  • Farrelly MC, Pechacek TF, Thomas KY, Nelson D (2008) The impact of tobacco control programs on adult smoking. Am J Public Health 98(2):304–309

    Article  PubMed  PubMed Central  Google Scholar 

  • Fatima N, Sen A (2011) Do lower cigarette taxes increase smoking? Evidence from the Canadian national experiment. Can Tax J 59:221–238

    Google Scholar 

  • Gale F, Foreman L, Capehart T (2000) Tobacco and the economy: farms, jobs, and communities. Agricultural Economic Reports 34007, United States Department of Agriculture, Economic Research Service

  • Givel MS, Glantz SA (2001) Tobacco lobby political influence on US state legislatures in the 1990s. Tob Control 10(2):124–134

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Glantz SA (2019) Estimation of 1-year changes in medicaid expenditures associated with reducing cigarette smoking prevalence by 1. JAMA Netw Open 2(4):e192307

    Article  PubMed  PubMed Central  Google Scholar 

  • Glynn TJ (2014) E-cigarettes and the future of tobacco control. CA Cancer J Clin 64(3):164–168

    Article  PubMed  Google Scholar 

  • Goel RK, Ram R (2004) Quantile-regression estimates of cigarette demand elasticities for the United States. J Econ Finance 28(3):413–421

    Article  Google Scholar 

  • Goldin J, Homonoff T (2013) Smoke gets in your eyes: cigarette tax salience and regressivity. Am Econ J Econ Pol 5(1):302–336

    Article  Google Scholar 

  • Haden K (1990) The demand for cigarettes in Japan. Am J Agric Econ 72(2):446–450

    Article  Google Scholar 

  • Hahn EJ (2010) Smokefree legislation: a review of health and economic outcomes research. Am J Prev Med 39(6 Suppl 1):S66-76

    Article  PubMed  Google Scholar 

  • Hao L, Naiman DQ (2007) Quantile regression. Sage Publications, Thousand Oaks

    Book  Google Scholar 

  • Hovhannisyan V, Bozic M (2017) Price endogeneity and food demand in urban China. J Agric Econ 68(2):386–406

    Article  Google Scholar 

  • Hovhannisyan V, Devadoss S (2020) Effects of urbanization on food demand in China. Empir Econ 58:699–721

    Article  Google Scholar 

  • Hsieh C-S, van Kippersluis H (2018) Smoking initiation: peers and personality. Quant Econ 9(2):825–863

    Article  Google Scholar 

  • Imbens GW, Newey WK (2009) Identification and estimation of triangular simultaneous equations models without additivity. Econometrica 77(5):1481–1512

    Article  MathSciNet  Google Scholar 

  • Jarvis MJ (2004) Why people smoke. BMJ 328(7434):277–279

    Article  PubMed  PubMed Central  Google Scholar 

  • Kaplan DM (2020) sivqr: Smoothed IV quantile regression. In: Working papers 2009, Department of Economics, University of Missouri

  • Kaplan DM (2022) Smoothed instrumental variables quantile regression. Stand Genomic Sci 22(2):379–403

    Google Scholar 

  • Kaplan DM, Sun Y (2017) Smoothed estimating equations for instrumental variables quantile regression. Econom Theor 33(1):105–157

    Article  MathSciNet  Google Scholar 

  • Kim HH-S, Chun J (2018) Analyzing multilevel factors underlying adolescent smoking behaviors: the roles of friendship network, family relations, and school environment. J School Health 88(6):434–443

    Article  PubMed  Google Scholar 

  • Koenker R (2005) Quantile regression. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Koenker R, Hallock KF (2001) Quantile regression. J Econ Perspect 15(4):143–156

    Article  Google Scholar 

  • Laporte A, Karimova A, Ferguson B (2010) Quantile regression analysis of the rational addiction model: investigating heterogeneity in forward-looking behavior. Health Econ 19(9):1063–1074

    Article  PubMed  Google Scholar 

  • Larson A, Bovbjerg V, Luck J (2016) State clean indoor air laws and smoking among adults with poor mental health. J Public Health Policy 37(4):453–466

    Article  PubMed  Google Scholar 

  • Lee I, Blackwell AKM, Hobson A, Wiggers D, Hammond D, De-Loyde K, Pilling MA, Hollands GJ, Munafò MR, Marteau TM (2023) Cigarette pack size and consumption: a randomized cross-over trial. Addiction 118(3):489–499

    Article  PubMed  Google Scholar 

  • Liang L, Chaloupka F, Nichter M, Clayton R (2003) Prices, policies and youth smoking, May 2001. Addiction 98(Suppl 1):105–122

    Article  PubMed  Google Scholar 

  • Liu X (2023) Testing in smoothed GMM quantile models with an application to quantile Euler equation. Working paper available at https://xinliu16.github.io/. Washington State University

  • Maclean JC, Kessler AS, Kenkel DS (2016) Cigarette taxes and older adult smoking: evidence from the health and retirement study. Health Econ 25(4):424–438

    Article  PubMed  Google Scholar 

  • Maclean JC, Webber DA, Marti J (2014) An application of unconditional quantile regression to cigarette taxes. J Policy Anal Manage 33(1):188–210

    Article  Google Scholar 

  • Manning WG, Blumberg L, Moulton LH (1995) The demand for alcohol: the differential response to price. J Health Econ 14(2):123–148

    Article  CAS  PubMed  Google Scholar 

  • McKinlay JB, Marceau LD (2000) To boldly go. Am J Public Health 90(1):25–33

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • McLellan DL, Hodgkin D, Fagan P, Reif S, Horgan CM (2012) Unintended consequences of cigarette price changes for alcohol drinking behaviors across age groups: evidence from pooled cross sections. Subst Abuse Treat Prev Policy 7(1):28

    Article  PubMed  PubMed Central  Google Scholar 

  • McLeroy KR, Bibeau D, Steckler A, Glanz K (1988) An ecological perspective on health promotion programs. Health Educ Q 15(4):351–377

    Article  CAS  PubMed  Google Scholar 

  • McMullen KM, Brownson RC, Luke D, Chriqui J (2005) Strength of clean indoor air laws and smoking related outcomes in the USA. Tob Control 14(1):43–48

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Menashe CL, Siegel M (1998) The power of a frame: an analysis of newspaper coverage of tobacco issues—United States, 1985–1996. J Health Commun 3(4):307–325

    Article  CAS  PubMed  Google Scholar 

  • Mokdad AH, Marks JS, Stroup DF, Gerberding JL (2004) Actual causes of death in the United States, 2000. JAMA 291(10):1238–1245

    Article  PubMed  Google Scholar 

  • National Conference of State Legislatures (2021) State Partisan composition. Retrieved April 20, 2021, from https://www.ncsl.org/research/about-state-legislatures/partisan-composition.aspx

  • Nesson E (2017) Heterogeneity in smokers’ responses to tobacco control policies. Health Econ 26(2):206–225

    Article  PubMed  Google Scholar 

  • Orzechowski and Walker (2015) The tax burden on tobacco, volume 49, 1970–2014, Centers for Disease Control and Prevention (CDC)

  • Pacheco J (2012) The social contagion model: exploring the role of public opinion on the diffusion of antismoking legislation across the American States. J Polit 74(1):187–202

    Article  Google Scholar 

  • Parente PMDC, Santos Silva JMC (2012) A cautionary note on tests of overidentifying restrictions. Econ Lett 115(2):314–317

    Article  Google Scholar 

  • Peterson DE, Zeger SL, Remington PL, Anderson HA (1992) The effect of state cigarette tax increases on cigarette sales, 1955 to 1988. Am J Public Health 82(1):94–96

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Pogun S, Rodopman A (2021) Understanding nicotine addiction and the health effects of nicotine use. European Respiratory Society Monographs Supporting Tobacco Cessation, 18–32

  • Poole S (2019) From tobacco to milkshakes: where did 'sin taxes' come from? The Guardian. New York, NY, St Martin's Press

  • Ronning G, Schulz N (2004) A Microeconometric characterization of household consumption using quantile regression. Appl Econ Q 50(2):183–208

    Google Scholar 

  • Sanders A, Slade G (2013) State cigarette excise tax, secondhand smoke exposure, and periodontitis in US nonsmokers. Am J Public Health 103(4):740–746

    Article  PubMed  PubMed Central  Google Scholar 

  • Sandford A (2003) Government action to reduce smoking. Respirology 8(1):7–16

    Article  PubMed  Google Scholar 

  • Semadeni M, Withers MC, Trevis Certo S (2014) The perils of endogeneity and instrumental variables in strategy research: Understanding through simulations. Strateg Manag J 35(7):1070–1079

    Article  Google Scholar 

  • Shrestha V (2015) Estimating the price elasticity of demand for different levels of alcohol consumption among young adults. Am J Health Econ 1(2):224–254

    Article  Google Scholar 

  • Smith KE, Savell E, Gilmore AB (2013) What is known about tobacco industry efforts to influence tobacco tax? A systematic review of empirical studies. Tob Control 22(2):144–153

    Article  PubMed  Google Scholar 

  • Song AV, Dutra LM, Neilands TB, Glantz SA (2015) Association of smoke-free laws with lower percentages of new and current smokers among adolescents and young adults: an 11-year longitudinal study. JAMA Pediatr 169(9):e152285

    Article  PubMed  PubMed Central  Google Scholar 

  • Sorensen G, Barbeau E, Hunt MK, Emmons K (2004) Reducing social disparities in tobacco use: a social-contextual model for reducing tobacco use among blue-collar workers. Am J Public Health 94(2):230–239

    Article  PubMed  PubMed Central  Google Scholar 

  • Sylvestre MP, Hanusaik N, Berger D, Dugas E, Pbert L, Winickoff J, O'Loughlin JL (2018) A tool to identify adolescents at risk of cigarette smoking initiation. Pediatrics 142(5)

  • U.S. Department of Health and Human Services (2014) The Health consequences of smoking-50 years of progress. a report of the surgeon general. Atlanta, GA, U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health

  • Wamamili BM, Garrow AP (2017) Have higher cigarette taxes in the United States discouraged smoking? A review of data from 1999–2013. Tob Prev Cessat 3:15

    Article  PubMed  PubMed Central  Google Scholar 

  • Wilkins N, Yurekli A, Hu T-W (2013) Economics of tobacco toolkit, tool 3: economic analysis of tobacco demand. World Bank: Washington, DC

  • Xu X, Bishop EE, Kennedy SM, Simpson SA, Pechacek TF (2015) Annual healthcare spending attributable to cigarette smoking: an update. Am J Prev Med 48(3):326–333

    Article  PubMed  Google Scholar 

  • Yu L, Cohen JE, Hoe C, Yang T, Wu D (2020) Male smoking reduction behaviour in response to China’s 2015 cigarette tax increase. Tob Control 29(4):405–411

    PubMed  Google Scholar 

  • Zhang X, Cowling DW, Tang H (2010) The impact of social norm change strategies on smokers’ quitting behaviours. Tob Control 19(Suppl 1):i51-55

    Article  PubMed  Google Scholar 

  • Zheng Y, Zhen C, Nonnemaker J, Dench D (2016) Advertising, habit formation, and U.S. tobacco product demand. Am J Agr Econ 98(4):1038–1054

    Article  Google Scholar 

Download references

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author information

Authors and Affiliations

  1. Agricultural and Applied Economics Department, University of Wyoming, 1000 E. University Ave., AG-203, Laramie, WY, 82071, USA

    Vardges Hovhannisyan

  2. Director of the Health, and Behavioral Economics Research Lab, Health Management, Economics, and Policy Department, Augusta University, 1120 15th Street, AE 1016, Augusta, GA, 30912, USA

    Vahé Heboyan

  3. School of Economic Sciences, Washington State University, Pullman, WA, 99164-6210, USA

    Magdana Kondaridze

Authors
  1. Vardges Hovhannisyan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vahé Heboyan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Magdana Kondaridze
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Vardges Hovhannisyan.

Ethics declarations

Conflict of interest

None of the coauthors have any potential conflicts of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hovhannisyan, V., Heboyan, V. & Kondaridze, M. An empirical assessment of effectiveness of the US tobacco control policies: a smoothed instrumental variables quantile regression approach. Empir Econ (2024). https://doi.org/10.1007/s00181-024-02562-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00181-024-02562-7

Keywords

JEL Classification

Search

Navigation