2021
DOI: 10.1257/jep.35.4.171
|View full text |Cite
|
Sign up to set email alerts
|

When Innovation Goes Wrong: Technological Regress and the Opioid Epidemic

Abstract: The fourfold increase in opioid deaths between 2000 and 2017 rivals even the COVID-19 pandemic as a health crisis for America. Why did it happen? Measures of demand for pain relief – physical pain and despair – are high and in many cases rising, but their increase was nowhere near as large as the increase in deaths. The primary shift is in supply, primarily of new forms of allegedly safer narcotics. These new pain relievers flowed in greater volume to areas with more physical pain and mental health impairment,… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

3
24
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
4
2

Relationship

0
6

Authors

Journals

citations
Cited by 28 publications
(27 citation statements)
references
References 33 publications
3
24
0
Order By: Relevance
“…If changes in the quantity of opioids dispensed in the USA are determined by economic incentives to suppliers based on the price of the raw material, this mechanism can be expected to be stronger in areas with higher ex‐ante exposure to opioids, as proxied by (the log of) the per capita number of mining sites in 1983. These counties would represent the most fertile local markets for analgesics, where PO promotion campaigns presumably have the greatest chance of success (Cutler and Glaeser, 2021; Alpert et al ., 2022). Accordingly, we estimate the following model: normalΔlnMGEpcct=α+βfalse(lnMines1983pccnormalΔlnOpiumPtfalse)+δt+γc+tθc+ϵct,$$ \Delta \mathrm{ln} MGEp{c}_{ct}=\alpha +\beta \left(\ln Mines1983p{c}_c\ast \Delta \mathrm{ln} Opium{P}_t\right)+{\delta}_t+{\gamma}_c+t{\theta}_c+{\epsilon}_{ct}, $$ where normalΔlnMGEpcct$$ \Delta \mathrm{ln} MGEp{c}_{ct} $$ is the log change in the per capita amount of morphine gram equivalent (MGE) dispensed in county c$$ c $$ between quarter tprefix−1$$ t-1 $$ and quarter t$$ t $$, normalΔlnOpiumPt$$ \Delta \mathrm{ln} Opium{P}_t $$ is the log change in the average price of dry opium in Afghanistan between quarters tprefix−1$$ t-1 $$ and t$$ t $$, and lnMines...…”
Section: Empirical Strategymentioning
confidence: 99%
See 3 more Smart Citations
“…If changes in the quantity of opioids dispensed in the USA are determined by economic incentives to suppliers based on the price of the raw material, this mechanism can be expected to be stronger in areas with higher ex‐ante exposure to opioids, as proxied by (the log of) the per capita number of mining sites in 1983. These counties would represent the most fertile local markets for analgesics, where PO promotion campaigns presumably have the greatest chance of success (Cutler and Glaeser, 2021; Alpert et al ., 2022). Accordingly, we estimate the following model: normalΔlnMGEpcct=α+βfalse(lnMines1983pccnormalΔlnOpiumPtfalse)+δt+γc+tθc+ϵct,$$ \Delta \mathrm{ln} MGEp{c}_{ct}=\alpha +\beta \left(\ln Mines1983p{c}_c\ast \Delta \mathrm{ln} Opium{P}_t\right)+{\delta}_t+{\gamma}_c+t{\theta}_c+{\epsilon}_{ct}, $$ where normalΔlnMGEpcct$$ \Delta \mathrm{ln} MGEp{c}_{ct} $$ is the log change in the per capita amount of morphine gram equivalent (MGE) dispensed in county c$$ c $$ between quarter tprefix−1$$ t-1 $$ and quarter t$$ t $$, normalΔlnOpiumPt$$ \Delta \mathrm{ln} Opium{P}_t $$ is the log change in the average price of dry opium in Afghanistan between quarters tprefix−1$$ t-1 $$ and t$$ t $$, and lnMines...…”
Section: Empirical Strategymentioning
confidence: 99%
“…This evidence is consistent with recent contributions by Cutler et al . (2019) and Cutler and Glaeser (2021), who show that patient demand is relatively less important than supply‐side factors in explaining the US opioid crisis. Furthermore, this result is in line with the literature that investigates the initial causes of the opioid crisis, showing the crucial importance of supply‐side factors (Van Zee, 2009; Alpert et al ., 2022; Arteaga and Barone, 2022).…”
Section: The Role Of Demand‐ and Supply‐side Factorsmentioning
confidence: 99%
See 2 more Smart Citations
“…17 Individuals using powdered heroin are often unaware of whether fentanyl is mixed in it(Ciccarone, 2019; Drug Enforcement Administration, 2018;Gladden et al, 2017). As opioid prescriptions fell by one third from 2011(Cutler & Glaeser, 2021) and OxyContin was reformulated in 2010, heroin and fentanyl use became more prominent that may have increased the unintentional intake of fentanyl. Because the individual does not realize the amount of fentanyl he/she has taken, the unexpected impairment while driving could increase which may have translated into higher traffic fatalities.18 There is not a single factor contributing to the decreasing trends in overall traffic fatalities (shown in Supporting Information S1: FigureA1), and researchers have identified many different potential factors, including public health policies and state regulations(Bandi et al, 2015).…”
mentioning
confidence: 99%