i high lighted the chosen project that i am working on gg2. .there's two links, the first one is the paper that i attached the pdf in here and second link is data.
Screen Shot 2020-11-18 at 9.05.16 AM Replication and Extension Project: Paper List Note: You are welcome to choose a paper not on this list. However, it is your responsibility to (1) verify that the data in the paper are available, (2) check with me that the paper is acceptable. I know not everyone is interested in drug policy! If you have a specific area of interest, let me know and I can try to help you find something in that area. 1. Supply-Side Drug Policy in the Presence of Substitutes: Evidence from the Introduction of Abuse-Deterrent Opioids: Abby Alpert, David Powell, and Rosalie Pacula a. Paper: https://www.aeaweb.org/articles?id=10.1257/pol.20170082 b. Overdose deaths: https://wonder.cdc.gov/mcd.html c. OxyContin misuse data: https://rdas.samhsa.gov/#/ 2. Origins of the Opioid Crisis and Its Enduring Impacts: Abby Alpert, William Evans, Ethan Lieber, and David Powell a. Paper: https://www.nber.org/papers/w26500 b. Overdose deaths: https://wonder.cdc.gov/mcd.html c. OxyContin misuse data: https://rdas.samhsa.gov/#/ d. State-law data: see paper 3. Macroeconomic Conditions and Opioid Abuse: Alex Hollingsworth, Christopher Ruhm, and Kosali Simon a. Paper: https://www.sciencedirect.com/science/article/pii/S0167629617303387 b. Emergency department data are not publicly available, but overdose data are available at the links above. c. Unemployment data available here: https://www.bls.gov/lau/lauov.htm 4. Is the Rise in Illicit Opioids Affecting Labor Supply and Disability Claiming Rates? Sujeong Park, David Powell a. Paper: https://www.nber.org/papers/w27804?utm_campaign=ntwh&utm_medium=email&utm_source=ntwg6 b. OxyContin misuse: see above c. ACS State Employment: https://data.census.gov/cedsci/table?q=United%20States&tid=ACSDP1Y2018.DP05&hidePreview=false d. SSA Claims Data: https://www.ssa.gov/disability/data/ssa-sa-fywl.htm 5. The Cross-Border Spillover Effects of Recreational Marijuana Legalization: Zhuang Hao and Benjamin Cowan a. Paper: https://www.nber.org/papers/w23426 b. Arrest data: https://www.ucrdatatool.gov/ A couple of non-drug papers: 6. Decriminalizing Indoor Prostitution: Implications for Sexual Violence and Public Health: Scott Cunningham and Manisha Shah a. Paper: https://academic.oup.com/restud/article-abstract/85/3/1683/4756165?redirectedFrom=fulltext b. STI Data: https://wonder.cdc.gov/std-race-age.html c. Arrest data: https://www.ucrdatatool.gov/ 7. Intergenerational Effects of Women’s Status: Evidence from Joint Indian Households a. Paper: https://riceinstitute.org/research/womens-status-and-childrens-height-in-india-evidence-from-joint-rural-households/ b. Data: https://www.dhsprogram.com/data/ i. Note: I do not know much about these data, so I will be of somewhat limited help if you choose this paper. Macroeconomic conditions and opioid abuse M A a b c a A R A A K M U O 1 n p d a 2 e h 2 2 g h d t ( s U p f e T h 0 Journal of Health Economics 56 (2017) 222–233 Contents lists available at ScienceDirect Journal of Health Economics jo u r n al homep age: www.elsev ier .com/ locate /econbase acroeconomic conditions and opioid abuse lex Hollingswortha, Christopher J. Ruhmb,c, Kosali Simona,c,∗ School of Public and Environmental Affairs, Indiana University, United States Public Policy and Economics, Frank Batten School of Leadership and Public Policy, University of Virginia, United States NBER, United States r t i c l e i n f o rticle history: eceived 10 April 2017 ccepted 31 July 2017 a b s t r a c t We examine how deaths and emergency department (ED) visits related to use of opioid analgesics (opi- oids) and other drugs vary with macroeconomic conditions. As the county unemployment rate increases vailable online 23 August 2017 eywords: acroeconomic conditions nemployment pioids by one percentage point, the opioid death rate per 100,000 rises by 0.19 (3.6%) and the opioid overdose ED visit rate per 100,000 increases by 0.95 (7.0%). Macroeconomic shocks also increase the overall drug death rate, but this increase is driven by rising opioid deaths. Our findings hold when performing a state- level analysis, rather than county-level; are primarily driven by adverse events among whites; and are stable across time periods. © 2017 Elsevier B.V. All rights reserved. . Introduction Covering a variety of countries and time periods, volumi- ous research conducted over the last two decades indicates that hysical health improves when economic conditions temporarily eteriorate.1 In the case of mental health, however, research shows pparent declines during periods of economic weakness (Ruhm, 000, 2003; Charles and DeCicca, 2008; Modrek et al., 2015). Some vidence suggests, moreover, that the procyclicality of physical ealth has declined considerably in recent years (Stevens et al., 015; McInerney and Mellor, 2012; Lam and Piérard, 2015; Ruhm, 015) just as drug poisoning deaths, often involving opioid anal- esics (henceforth opioids) such as hydrocodone and oxycodone, ave trended sharply upwards (Rudd et al., 2016).2 Understanding the relationship between local economic con- itions and drug-related adverse outcomes is important because he United States is “experiencing an epidemic of drug overdose poisoning) deaths” (Rudd et al., 2016, p. 1378), with fatal drug poi- onings increasing by 146% from 1999 to 2014 (Fig. 1). Poisoning ∗ Corresponding author at: School of Public and Environmental Affairs, Indiana niversity, United States. E-mail address:
[email protected] (K. Simon). 1 This literature often dates from Ruhm (2000)’s study of the US for the 1972–1991 eriod. However, there are indications that mortality was procyclical in research rom as early as the 1920s (Ogburn and Thomas, 1922). 2 Heroin is classified as a separate category of narcotics. Heroin deaths have risen xtremely rapidly since 2010 but were relatively stable before that (Ruhm, 2017). his increase is too recent to be adequately captured in our study’s timeframe. ttp://dx.doi.org/10.1016/j.jhealeco.2017.07.009 167-6296/© 2017 Elsevier B.V. All rights reserved. deaths, around 90% of which are now caused by drugs (Warner et al., 2011), were the most important source of growth in the all-cause mortality rates of 45–54 year old non-Hispanic whites between 1999 and 2013 (Case and Deaton, 2015). The involvement of opioids and, more recently, heroin in these deaths has received particular attention (Volkow et al., 2014; Jones et al., 2015; Rudd et al., 2016), including a White House Summit in August 2014 (Hardesty, 2014). Drug poisoning deaths are higher for males than females, but have been rising rapidly over time for both sexes, as well as for almost all age groups, but particularly rapidly for 25–64 year olds (Ruhm, 2017). One notable feature is that non-Hispanic white (hereafter simply “white”) and non-Hispanic black (hereafter “black”) drug fatality rates closely tracked each other during the 1980s and 1990s, but since 1999 (the period examined here), white mortality rates have grown much faster. Fig. 2 illustrates this divergence. From 1999 to 2014 the U.S. white drug death rate per 100,000 grew by 203%, while the black and Hispanic drug death rates increased by 49% and 31%, respectively. Rising deaths are not the only indica- tion of serious health consequences related to the growing use of opioids. Emergency department (ED) visits involving narcotic pain relievers increased 117% between 2005 and 2011 (Crane, 2015) and opioid-related ED visits grew by 39.5% from 2006 to 2014 (see Fig. 3). While this rise has mostly occurred among prime-aged adults, all age groups have seen an increase in the risk of opioid poisoning ED visits (Tadros et al., 2015). This analysis examines how serious adverse health outcomes related to opioid and other drugs vary with short-term fluctuations in macroeconomic conditions. Specifically, we study how deaths and ED visits due to opioids and other drugs are related to local dx.doi.org/10.1016/j.jhealeco.2017.07.009 http://www.sciencedirect.com/science/journal/01676296 http://www.elsevier.com/locate/econbase http://crossmark.crossref.org/dialog/?doi=10.1016/j.jhealeco.2017.07.009&domain=pdf mailto:
[email protected] dx.doi.org/10.1016/j.jhealeco.2017.07.009 A. Hollingsworth et al. / Journal of Health Economics 56 (2017) 222–233 223 d dru S r Dise t u E t i t f r o i i n a r t 2 fl m Particularly relevant to the current analysis is suggestive evi- dence, provided by Ruhm (2015), that one of the main reasons deaths shifted from being sharply procyclical to acyclical or coun- S Fig. 1. U.S. unemployment rate an ource: Author calculations using National Vital Statistics System of the Centers fo ogether with unemployment rates from the Bureau of Labor Statistics. nemployment rates. Our main findings are that opioid deaths and D visits are predicted to rise when county unemployment rates emporarily increase. The same is true for all sources of drug poison- ng mortality, and consistent results are obtained when performing he analysis at the state-level rather than the county-level, proxying or macroeconomic conditions with employment-to-population atios rather than unemployment rates, and conducting a variety f other robustness and sensitivity checks. Importantly, our find- ngs are relatively stable regardless of the time period considered, ndicating that they represent a general connection between eco- omic conditions and severe adverse consequences of substance buse that is not restricted to periods of recession. Moreover, our esults are predominantly driven by changes among whites (rather han blacks or Hispanics) in most specifications. . Prior research and contribution of this investigation The vast literature examining the connection between economic uctuations and health has considered effects on mortality and orbidity, health-related behaviors, health insurance and health Fig. 2. Total opioid death rat ource: Author calculations using National Vital Statistics System of the Centers for Disea g death rates by type, 1999–2014. ase Control and Prevention Multiple Cause of Death (MCOD) files for 1999–2014, care use.3 Mortality has been found to be procyclical in investiga- tions covering a wide variety of countries and time periods (e.g. Ruhm, 2000; Neumayer, 2004; Tapia Granados, 2005; Gerdtham & Ruhm, 2006; Buchmueller et al., 2007; Lin, 2009; Gonzalez & Quast, 2011; Ariizumi & Schirle, 2012). Similarly, many (though not all) studies suggest that lifestyle factors such as exercise, obe- sity, smoking and heavy drinking improve in bad economic times (e.g. see Freeman, 1999; Ruhm & Black, 2002; Ruhm, 2005; Gruber & Frakes, 2006; Xu, 2013).4 However, some current research sug- gests that these patterns have weakened or reversed in recent years for both mortality (McInerney & Mellor, 2012; Stevens et al., 2015; Lam & Piérard, 2015; Ruhm, 2015) and health behaviors (Dávalos et al.,