The first paper is this one in the Journal of Health Economics by Emily Conover of Hamilton College and Dean Scrimgeour of Colgate University (earlier ungated version here). The second paper is this IZA Discussion Paper by Stefan Boes of the University of Lucerne and Steve Stillman of the University of Otago (hereafter B&S).
Remarkably, both papers use almost the same dataset and almost the same methods. While it's not unusual for several research teams to be working on the same research question at the same time, it's surprising to see too such similar papers appear in quick succession. And with similar results, though interpreted in meaningfully different ways.
Conover and Scrimgeour (hereafter C&S) look specifically at the health impacts of the law change. They used NZ Health Information Service (NZHIS) data covering all hospitalisations in New Zealand over the period 1993 to 2006. They use both a difference-in-difference approach (DiD), and a regression discontinuity design approach (RDD), to evaluate the difference in alcohol-related hospitalisations for those aged 18-19 years before/after 1 December 1999 (they also look at impacts on those aged 15-17 years). They estimate their models separately for each sex, and in both cases their control group is those aged 20-23 years (though they also present results that use a control group of those aged 20-21 years).
Boes and Stillman (hereafter B&S) look at a broader set of impacts than simply hospitalisations, including self-reported alcohol consumption, and alcohol-related motor vehicle accidents. They also use NZHIS data, over the period 1996 to 2007, and use similar DiD and RDD approaches to C&S. The key age group is again those aged 18-19 years (and they also look at those aged 15-17 years), but they don't present separate results by sex, and their control group is those aged 20-21 years.
The results are interesting. Using their preferred DiD approach, C&S find:
...a significant increase in hospitalizations as a consequence of passage of the Sale of Liquor Amendment Act (1999). Among eighteen and nineteen year old males difference-in-difference estimates indicate a 24.6% (s.e. = 5.5%) increase in alcohol-related hospitalizations. For females in the same age group, the estimated effect is 22% (s.e. = 8.1%).They find qualitatively similar results using RDD, and conclude (in the abstract) that this shows "a substantial increase in alcohol-related hospitalisations among those newly eligible to purchase liquor". And you'd have to agree, the relative effects seem quite large - more than a 20% increase in hospitalisations for both young men and young women is pretty substantial.
B&S find even larger relative effects:
Overall, our results imply that the reduction of the [drinking age] from 20 to 18 led to a 75-91% increase in alcohol related hospital admission rates for 18-19 year olds.These are BIG effects, right? In relative terms, yes. But in absolute terms, B&S point out just how many additional hospitalisations their effects translate into:
Translating the relative impacts using population figures from 1999 implies that the reduction in the [drinking age] from 20 to 18 led to approximately an additional... 2.1-2.6 [admissions] per month for 18-19 year olds... in the immediate aftermath of the law change.So, across the country as a whole that would be an additional 25-31 alcohol-related hospitalisations per year. And remember, C&S found smaller effects than B&S. So, the effect is only very SMALL in absolute terms.
But that's not the end of this story. Aside from the period of the data and the control group, part of the difference in the two papers lies in their choice of what constitutes an 'alcohol-related hospitalisation'. C&S use all ICD-9 or ICD-10 codes that mention alcohol. B&S use a smaller subset of the ICD-9 codes, limited to alcohol use disorder (code 3050). In comparing their results with C&S, B&S argue that "...we use a much narrower definition of alcohol-related admissions that intentionally excludes more chronic conditions, which we show below are unresponsive to the reduction in the [drinking age]."
But there is a problem with both studies. In both cases, the hospitalisation data used was based on a limited set of ICD-9 or ICD-10 codes that are directly related to alcohol. However, there are a large number of ICD codes that could be related to alcohol, but are not alcohol use disorder and don't explicitly mention alcohol. For instance, the most obvious example are injuries or assaults that would be coded to S or T or X codes, none of which mention alcohol. Having spoken to a couple of clinicians, they pointed out that the ICD codes are very specific - unless they are sure the symptoms arise directly from alcohol, then the alcohol codes are not used.
Given that, it is likely that the small effects (in absolute terms) described by B&S may in fact be big effects if all of the hospitalisations that result from alcohol (including injuries, assaults, etc.) were included. Some estimates suggest that an average of 18 percent of emergency room admissions at peak party time are alcohol related. So, the jury has to remain out on the question of whether the decrease in the drinking age had a big effect or small effect on hospitalisations. More research required. [**]
[*] Technically, there is no legal drinking age in New Zealand. Instead there is a minimum age for purchasing alcohol. I'm using the term 'drinking age' in this post purely for simplicity.
[**] Wellington Hospital has been collecting data on alcohol-related emergency room admissions for a number of years, even when the primary diagnosis is not alcohol-related (see here for example). As I understand it, most hospitals do this now, although completeness might be an issue. These data could be leveraged (along with associated time/day of admission data) to get an estimate of the proportion of ICD codes that are not included in the C&S study that might be alcohol-related. Imperfect of course, but possible.