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The Role of Local Economic Conditions in the Opioid Crisis
- 1. The Role of Local Economic Conditions in the Opioid Crisis Michael Betz Assistant Professor, Dept. of Human Sciences
- 2. 2 Costs • Opioid abuse cost Ohioan’s $6.6-8.8 billion in 2015 • Roughly what Ohio spends on K-12 education • White House CEA (2017) • ~$500 billion in 2015 • $10.32 trillion in costs between 1999-2016 for entire US • ~50% of US GDP in 2017
- 3. 3 Demand versus Supply Drivers Supply-side drivers • Increasing availability of powerful drugs Demand-side drivers • Increasing demand for deadly substances
- 4. 4 10 30 50 70 90 110 0 5 10 15 20 1999 2001 2003 2005 2007 2009 2011 2013 2015 PrescriptionRate OverdoseDeathRate US Overdose Death and Prescription Rates 1999-2016 All Drugs Prescription opioids Prescription rates OxyContin Reformulation 2010 KY, OH, WV PDMPs
- 5. 5 Overview 1. Supply-side drivers 2. Demand-side drivers
- 6. 6 Leading Causes of Death Under 55 in 2016 Cause KY, OH, PA, WV US Drug overdoses 10,415 56,679 Cancer 6,422 58,740 Heart disease 5,694 49,498 Suicide 3,048 28,999 Homicide 1,638 16,970 Chronic liver disease 998 12,190
- 7. 7 Leading Causes of Death Under 55 in 2016 Cause KY, OH, PA, WV US Drug overdoses 10,415 56,679 Cancer 6,422 58,740 Heart disease 5,694 49,498 Suicide 3,048 28,999 Homicide 1,638 16,970 Chronic liver disease 998 12,190
- 8. 8 Leading Causes of Death Under 55 in 2016 Cause KY, OH, PA, WV US Drug overdoses 10,415 56,679 Cancer 6,422 58,740 Heart disease 5,694 49,498 Suicide 3,048 28,999 Homicide 1,638 16,970 Chronic liver disease 998 12,190
- 9. 9 Demand-side Factors - Community economic disadvantage - Mental health problems - Relational problems - Health conditions (chronic pain, sedentary life styles, etc.)
- 10. 10 Demand-side Factors - Community economic disadvantage - Mental health problems - Relational problems - Health conditions (chronic pain, sedentary life styles, etc.)
- 11. 11 Rateper100,000 Ohio Overdose Rates by Education Level HS Grad Some college Associates Bachelors
- 12. 12 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 US and Ohio Unemployment Rates 2000-16 US Ohio
- 13. 13
- 14. 14
- 15. 15 Unemployment rates 1. Mask type of job
- 16. 16Source: Autor and Dorn (2013)
- 17. 17 Twin Forces Driving Trend 1. Outsourcing 2. Technological Change/Automation
- 18. 18 Twin Forces Driving Trend 1. Outsourcing 2. Technological Change/Automation
- 19. 19 11,000 13,000 15,000 17,000 19,000 1967 1975 1983 1991 1999 2007 2015 US Manufacturing Jobs 1967-2016
- 20. 20
- 21. 21 Pierce and Schott (2017) • Counties more exposed to trade liberalization had larger manufacturing declines • More exposed counties had higher rates of suicide and related causes of death
- 22. 22 Koffi, Hurst, and Schwartz (2018) • Manufacturing decline lowered incomes for prime aged workers • State manufacturing decline increased OD rates (causal)
- 23. 23 Twin Forces Driving Trend 1. Outsourcing 2. Technological Change/Automation
- 24. 24 Workmen take out their anger on the machines by C L Doughty
- 25. 25 Median Family Real Income Productivity: Output per Hour
- 26. 26 0 200 400 600 800 1000 1200 1400 0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 800,000 900,000 1,000,000 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 MillionsofShortTons CoalMiningWorkers Coal Mining Employment and Production 1920- 2016 Coal employment Production
- 27. 27
- 28. 28 11,000 13,000 15,000 17,000 19,000 1967 1975 1983 1991 1999 2007 2015 US Manufacturing Jobs 1967-2016
- 29. 29 8090100110 2000 2005 2010 2015 ManufacturingOutputIndex Source: Kofi, Hurst, Schwartz 2018
- 30. 30 One more robot per thousand workers reduces the Employment/Pop Ratio by about 0.18-0.24 percentage points Source: Acemoglu and Restrepo 2017
- 31. 31 Ohio’s Industries 2000 2015 Manufacturing 15.4 10.4 Government and government enterprises 12.1 11.5 Retail trade 11.7 10.1 Health care and social assistance 9.9 12.8 Accommodation and food services 6.4 7.2 1992 < HS HS 2-YEAR BACHELORS 2016 < HS HS 2-YEAR BACHELORS
- 32. 32
- 33. 33 Involuntarily job displacement approximately doubled the short-term mortality rates of those displaced and reduced their life expectancy on average by 1.5 years -Sullivan and von Wachter (2009)
- 34. 34 Carnegie Mellon Reels After Uber Lures Away Researchers Uber staffs new tech center with researchers poached from its collaborator on self-driving technology Amazon opens grocery store with no checkouts January 22, 2018 Robot spending will hit $188 billion by 2020, report predicts Robotics and related services are expected to reach new heights, driven by an expanding market. First Fully Automated Indoor Farm Being Built In Ohio September 25, 2018
- 35. 35 Currently 47 million workers with HS degree or less Driving: 3.4 million Grocery store attendants: 2.4 million Fast food counter workers: 3.7 million
- 36. 36 What’s the net result?
- 37. 37 Median Family Real Income Productivity: Output per Hour
- 38. 38 Productivity: Output per Hour Median Family Real Income
- 39. 39Source: Chetty et al. 2014
- 40. 40 Unemployment rates 1. Mask type of job 2. Mask LF participation
- 41. 41 58 59 60 61 62 63 64 65 66 67 68 1940 1950 1960 1970 1980 1990 2000 2010 2020 Labor Force Participation 1948-2016 Source: BLS
- 42. 42Source: Kofi, Hurst, Schwartz 2018 FractionWorkingZeroWeeksDuringYear High school or less Some College Bachelors or more Fraction Working Zero Weeks During the Year Males 21-55 by Education
- 43. 43 In 2017, ~2.1 million people with opioid use disorder Could account for 78% of non-boomer LFP drop Could be 100% in KY, OH, PA, WV
- 44. 44 Men NLF express much lower levels of meaning to their daily lives than LF men • Not so for women Half of prime age men NLF use daily pain medication (Krueger 2017)
- 46. 46 Aliprantis, Fee, and Schweitzer 10% increase in local prescription rate • 0.17 pp decline for women • 0.50 pp decline in LFP for men • 0.70 pp decline low educated white men • 1.01 pp decline for minority men
- 47. 47 When you have people who are not taking part of the economic life of the country in a meaningful way, who don’t have the skills and aptitudes to play a role or who are not doing so because they’re addicted to drugs or in jail, then in a sense, they are being left behind. -Federal Reserve Chairman Jerome Powell
- 48. 48 But are these things new?
- 49. 49 Trends in substance use disorder in the past year age 18+ 2002-2014 -2.6m SUD -2.6m AUD
- 50. 50 Trends in substance use disorder in the past year age 18+ by drug +230k HUD
- 51. 51 Past month Marijuana use age 12+ +10m Using Marijuana
- 52. 52 Policy recommendations Help existing users 1. Increase availability/access of MAT 2. Development of long term care 3. Public health, not criminal justice approach
- 53. 53 Policy recommendations Prevent new users 1. More thoughtful (slower) approach to economic policy 2. Proactive approach to automation 3. Reduce prescription rates back to 1995 levels 4. Interrupt intergenerational transmission
- 56. 56 Single, Never married Widowed Married Men HS/GED BA or more OpioidOverdosesper100,000,Age25+ Divorced Widowed Married
- 57. 57
- 58. 58
- 59. 59
- 60. 60 Social isolation, loneliness, and living alone correspond increase likelihood of mortality by 29%, 26%, and 32%, respectively
- 61. 61 Uhis et al. (2014) • Preteens who spent 5 days away from screens had significantly better recognition of facial emotion expression
Hinweis der Redaktion
- The opioid crisis is no longer an epidemic it is endemic Because the crisis is so wide-spread, a lot of academics across a wide range of disciplines from public health, to medicine, to sociology, to economics, and many others have tried to figure what are the main drivers of the crisis in the hope that we can reverse trend and save lives Economists in particular have framed the question by dividing causal factors into supply-side factors versus demand-side factors
- This was prior to much federal funding to address the drug crisis. Wanted to give some sense of the economic costs of the crisis in order to show what magnitude of resources is justified to address the crisis.
- Supply side—What role does having 69 doses of prescription opioids per year for every man woman child in Ohio have on overdose rates? Demand side—Why are people demanding these incredibly dangerous substances at a higher rate than in previous generations
- 400% increase in opioid prescriptions between 1999-2010…but only a 30% decrease from 2010-2016. Still have 3x as many prescriptions as in 1999.
- Drug overdoses are now the leading cause of death for Ohioans under 55 Deaths went up to about 4,100 in 2016
- Drug overdoses are now the leading cause of death for Ohioans under 55 Deaths went up to about 4,100 in 2016
- US Suicide rate increased 25% 1999-2016
- Economic disadvantage: where you lives affects your economic prospects Mental health: Increase in the diagnosis of anxiety and depression Relational problems: Americans have always placed a high value on personal autonomy and self-reliance, but one of the consequences of that we’re one of the most social isolated and relationally lonely cultures that has ever existed Health conditions: Hard to know how this compares to past generations, but could be a plausible factor driving people to turn toward drugs
- This a an epidemic that is highly concentrated among those with a low education HS grads have OD rates 4.5 times higher than those with some college, 14 times higher than those with bachelors Even though we have anecdotes of the suburban high school football player who got hooked after an injury
- Things this hides Geographic differences Types of jobs Labor force participation
- We’re all aware of the magnitude of this crisis. In 2016, over 64k Americans died of drug overdose and it became the leading cause of death of Americans under the age of 50. But as we know with a lot of other economic and social trends, there are a wide range of regional outcomes within the US and often between rural and urban areas. This session in particular is good example of that since we have representatives from Ohio, PA, and WV, three of the four states with the highest OD rates in the country, but at the opposite end of the spectrum there are states like Nebraska and South Dakota whose rates aren’t much higher than the national average in 2000. Just looking at this map and seeing not only the variation, but the pockets of both high and low overdose rates it just makes you ask man what is going on in those four states that I mentioned that have such high rates.
- any period since 1990, roughly 52 percent of men with a high school degree or less have been engaged in one of three activities at any point in time: working in manufacturing; working in construction; or not working at all. During the period depicted in the Figure, the share of men working in construction was quite similar in 1990, 2000 and 2017. It therefore follows that, over approximately 30 years, there has been a one-to-one mapping between declining manufacturing shares and rising non-employment rates for prime age men with a high school degree or less.
- any period since 1990, roughly 52 percent of men with a high school degree or less have been engaged in one of three activities at any point in time: working in manufacturing; working in construction; or not working at all. During the period depicted in the Figure, the share of men working in construction was quite similar in 1990, 2000 and 2017. It therefore follows that, over approximately 30 years, there has been a one-to-one mapping between declining manufacturing shares and rising non-employment rates for prime age men with a high school degree or less.
- There was legitimate concern that machines would destroy most peoples jobs The power loom and the cotton gin increased worker productivity by a factor of 40-50 This movement didn’t gain traction because people found alternative work quickly. Some people were still needed to run the machines and others were needed to produce parts What was largely true through most of the 20th and 21st centuries is that machines did relatively simple jobs, they couldn’t make decisions, These jobs though were beginning to become a little more complex, so you would need more education and training.
- The process of machines replacing human workers has continued throughout the 20th and 21st centuries Coal mining is a very poignant example. In 1920 almost 900k coal miners worked in the mines. December’s estimate from the BLS is 53k coal miners But at the same time production continued to steadily increase. These jobs didn’t go to China. The US is producing twice as much coal as it did 60 years ago. I’m sure these sentiments to bring back coal jobs are well meaning to those in coal country, in order to get coal jobs back they would have to stop using this…
- any period since 1990, roughly 52 percent of men with a high school degree or less have been engaged in one of three activities at any point in time: working in manufacturing; working in construction; or not working at all. During the period depicted in the Figure, the share of men working in construction was quite similar in 1990, 2000 and 2017. It therefore follows that, over approximately 30 years, there has been a one-to-one mapping between declining manufacturing shares and rising non-employment rates for prime age men with a high school degree or less.
- The study period was 1990-2007. Since 2007 the capabilities of robots and automation has risen substantially. In 2007, the first iPhone had just been released This is only industrial robots, like in mfg. Does not capture the effects of AI or nonindustrial robots
- In 1980 the HS/College wage gap was about 20%. Now its about 75% The people losing mfg jobs are not the same people getting heath and social assistance jobs
- The pace of automation is quickening faster than anyone expected. Quote about self-driving cars in 2005 (it would never happen)
- High skill workers are more valuable because they can work as complements with complex machines Mid-skill workers have largely moved to low skill jobs if they transitioned at all
- Rate of nonworking men has tripled in the last 50 years ~5.2 million workers from 2009-2014 Half from boomers retiring Some from great recession Almost half from prime aged men and women not entering labor force Abraham and Kearney (2017) suggests that the secular decline in real wages of less skilled workers is a major contributor to the secular decline in their participation rate
- By 2016, fully one-fith of all men who had only a high school education or less worked ZERO weeks during the year In 2016, only 82.2 percent of prime age men were working, compared to 86.8 percent of men aged 21-55 worked in 2000. About half of this decline occurred prior to the Great Recession. Figure 2 shows the annual decline in hours worked for men aged 21 to 55
- 4 Estimates for the population 12 years old and older is not readily available from the American Community Survey, thus we use the more commonly used 16 years and older. In 2015, there were no opioid overdose deaths among the population under 15 years old, so we assume the number of opioid abusers 12 to 14 is small. In 2016, the active Ohio labor force was 5.7 million people, down from a peak of 6 million in 2007 (BLS). If we consider the change over time, there were 300,000 fewer active workers in the labor force in 2016 than 2007. Given that opioid dependency and abuse can limit a person’s ability to participate in the labor force, one way at looking at the estimates for opioid abuse and dependency is that it could account for a third to more than a half of the decline in workforce participation since 2007. Drugs are so addictive that those who leave the labor force are more likely to leave it permanently
- This is a cyclical problem
- For many people, substances just aren’t their thing