Hey John, just to throw in a couple of subjective narratives here. Basically I’m very skeptical that there would be any net happiness benefit to alcohol.
The negative effects of drinking are immense here in LMICs like Uganda—acknowleged almost everyone in society, even sadly by most drinkers. Ask Ugandans “Do you think alcohol makes people more happy or more sad?” and I can guess the answer. Alcohol is a multifaceted life sucker, it eats too many people’s (especially men’s) productive hours, reduces household income, fuels gender based violence and precipitates and potentiates depression.
Just drive through any village center here at 3:00pm at the afternoon—the side of the road ain’t a pretty site. Not only the plastic alcohol bottles littering the street, but also the hundreds drunk men in bar shacks who could have “counterfactually” been digging in the garden, or mentoring their sons, or doing basically anything else mildly productive. The negative happiness “spillovers” to their families might beat even Strongmind’s positive ones....
And even leaving that serious stuff aside and looking at “happiness” isolated (if that’s possible). If there was no alcohol available in the whole world tomorrow, if we just looked at point-in-time-whole-world happiness, say the day before and the day after alcohol was vanished away, I would bet (with low certainty of course) that happiness might even go up. For every 5 people that might get a slight happiness benefit from drinking, I reckon there’s one person ii whom alcohol illicits at least moderate depression and negativity that wipes out the benefit of those 5 people who drink casually and (perhaps) healthily and it makes their life perhaps a tiny fraction better.
I read the little alcohol enjoyment paper James and co wrote, which seem to have one study showing no change in happiness, three longitudinal (better) studies showing negative changes for heavy drinkers and no changes for moderate drinkers (expected), one large cross-sectional survey showing an incredible third of drinkers want to drink less next year which is telling/
And just one “I phone based” cross-sectional subjective study showing a increase in moment-to-moment happiness while drinking alcohol (I mean of course), while not looking at future negative effects. Above anecdotes like mine, basically the lowest level of evidence. Typed in by an unrepresentative sample on Iphones.… I mean...
If it was me I would possibly be discounting for happiness by −10% :D, or at least by 0%.
Hi Nick, yeah I get that there are costs to alcohol, I just think it is important to consider the benefits when deciding what to do. A lot of public health policies are defended by only focusing on the costs of doing something, not the benefits. So, I think it is important to consider the benefits.
My own intuition is that if there were no alcohol, happiness would go down for the vast majority of people and would go up for a small minority. From my own experience, people often seem close to their happiest when drinking, and it is a very important social lubricant.
I think the best study in James’ review was the subjective wellbeing one because it measures what, in my view, actually matters, which is people’s moment to moment wellbeing. It’s also a very large sample. I wouldn’t class the benefits found in the study as ‘tiny’. The increase in wellbeing while drinking is nearly as large as that produced during spending time with friends. And this is a benefit which would be spread across billions of people.
Thanks John those are reasonable points. Completely agree we should consider the benefits, just disagree that alcohol is probably net positive for happiness in LMICs, no comment really on Staten countries.
You are right the difference isn’t “tiny” in the study have deleted.
From a study design standpoint, a cross sectional phone study where people opt in, would fall close to the bottom of the heirachy of evidence, traditionally at least. Personally I think it’s not useless, but at best very weak. I can see your argument that what they measure is what “actually matters”, but the bias and confounding of this kind of the study makes it so so hard to put much weight on. Given that, a huge sample size doesnt really help at all.
If your rate moment by moment wellbeing as the most important thing to measure, there would have to be some kind of random sampling and ways to avoid the kind of “I’m drinking and happy now” bias, while not attributing the hangover or bad mood the next day to alcohol.
I’m not sure the phone study has the traditional weaknesses as cross-sectional studies. It’s a bit more like a panel study where you can track in very fine-grained detail what events are happening and what happens to subjective wellbeing at the time. Because the event data is so fine-grained and there are so many contiguous datapoints, it provides very good evidence of causation. These sorts of studies also give intuitively plausible results for all other events. People don’t like work, getting divorced, being unemployed, being widowed; people like sex, seeing their friends etc.
It’s true that people opt in, but I don’t see any particular reasons to think that this would have a bias towards ‘happy drinkers’. The same is true for other life events. Like maybe there is some bias such that people who enjoy sex are more likely to opt in to phone-based subjective wellbeing studies, but I don’t think that is what is driving the results.
I’m surprised you think it provides “good evidence of causation”. Having fine grained data and many datapoints doesn’t as far as I can tell do anything to counter selection bias and confounding. Usually these kind of studies would not even claim that themselves. I’m going to have to read the study properly now rather than just skimming lol.
How do you get away from the confounding? People drink at social events with friends, people drink in the evening when they are relaxing anyway. Are people drinking because they are happy it happy because they are drinking?
And self selection seems like a pretty massive deal why do you think it isn’t? Seems likely to heavily select for “happy” drinkers f again I could be missing something.
Re confounding, the headline estimate that James uses is adjusted for various potential confounders.
“Aside from controlling for all time-invariant factors using FE models, we control for a variety of moment-specific factors, including: what people were doing (40 activities), who they were doing it with (7 types), time of day (three-hour blocks split by weekday vs. weekend/bank holiday), location Page 16 (inside/outside/in vehicle and home/work/other), and how many responses the participant has previously given. OLS estimates also include time-invariant controls for gender, employment status, marital and relationship status, household income, general health, children, single parent status, region, age and age squared at baseline. Derivations/descriptive statistics are given in Web Appendix S5.
I don’t have a strong view on what effect the potential selection effect would point.
Thanks John. It’s great that hey adjusted for confounders (and any similar study would). That such a lot of controlling for confounders needed to be done at all shows the major weakness in this kind of study design.
I’m not saying it’s a bad study, just that it’s not fit for analysis of causation.
I think you would struggle to find many (if any) researchers who would say this study provided any more than a decent correlation between drinking and increased happiness, rather than evidence of causation. Happy to be proved wrong here and others can feel free to weigh in!
Along those lines it was mainly this comment I disagreed with.
“Because the event data is so fine-grained and there are so many contiguous datapoints, it provides very good evidence of causation.”
Another thought—I think there is a risk of overcontrolling with some of the controls used in that paper. The controls in effect assume that if people were not drinking, they would do the same thing they were in fact doing while drinking, except without drinking. But drinking might lead people to be more likely to spend time with friends, go dancing etc. If you control for what people were doing and who they were doing it with, you assume that if they weren’t drinking, people would see their friends and go dancing sober. I think this is unlikely. I don’t like dancing, no matter what I have imbibed, but I think most people would basically never go dancing with friends if they didn’t drink. The uncontrolled effect on SWB is 10 points, though some of the controls seems sensible, so that probably overstates it.
Yeah that’s fair enough re that part of the comment.
Yeah I suppose I would disagree with how a lot of researchers view the strength of evidence provided by cross-sectional studies. I think a lot of researchers seem to endorse the proposition ‘if this could be confounded, it provides no evidence of causation’, which I don’t think is right. It depends on one’s prior on how plausible the confounder is. I think this is why a lot of economics has stopped trying to focus on some of the more important macro questions, and I think this is a mistake.
eg consider the potential effects of climate change on economic performance. I do think cross-sectional evidence is highly relevant and should update one’s view. If economic performance were very strongly climatically determined, I would expect this to show up strongly in the cross-section. I wouldn’t expect to see California being way richer than Baja California. I wouldn’t expect gross state product for US states to look like this as a function of state average temperature:
I would expect growth rates to be uniformly low in climatically exposed places like Vietnam, Bangladesh, Indonesia, India etc, which is not what we see. So, I do think this sort of evidence should update one’s view, even though there are obviously loads of potential confounders.
In climate economics, people don’t like this, so they have started using panel data approaches which aim to test the exogenous effects of weather changes on economic performance in particular periods of time. This supposedly provides better evidence of causation, but I think should be completely ignored because of huge researcher degrees of freedom, reporting bias and political bias. I think they leave the door open for econometric skullduggery to provide inflated estimates. In part because the cross-sectional evidence is more transparent, I think it is more reliable.
I assume many potential alcohol-reduction efforts would reduce an individual’s alcohol consumption at the margin, not lead to a world with no alcohol. I don’t drink myself, but it would seem challenging to measure the lost happiness from—e.g., going down from four beers at a social occasion to three due to higher taxation. I don’t think extrapolating from the status quo to an alcohol-free world would work here.
Hey John, just to throw in a couple of subjective narratives here. Basically I’m very skeptical that there would be any net happiness benefit to alcohol.
The negative effects of drinking are immense here in LMICs like Uganda—acknowleged almost everyone in society, even sadly by most drinkers. Ask Ugandans “Do you think alcohol makes people more happy or more sad?” and I can guess the answer. Alcohol is a multifaceted life sucker, it eats too many people’s (especially men’s) productive hours, reduces household income, fuels gender based violence and precipitates and potentiates depression.
Just drive through any village center here at 3:00pm at the afternoon—the side of the road ain’t a pretty site. Not only the plastic alcohol bottles littering the street, but also the hundreds drunk men in bar shacks who could have “counterfactually” been digging in the garden, or mentoring their sons, or doing basically anything else mildly productive. The negative happiness “spillovers” to their families might beat even Strongmind’s positive ones....
And even leaving that serious stuff aside and looking at “happiness” isolated (if that’s possible). If there was no alcohol available in the whole world tomorrow, if we just looked at point-in-time-whole-world happiness, say the day before and the day after alcohol was vanished away, I would bet (with low certainty of course) that happiness might even go up. For every 5 people that might get a slight happiness benefit from drinking, I reckon there’s one person ii whom alcohol illicits at least moderate depression and negativity that wipes out the benefit of those 5 people who drink casually and (perhaps) healthily and it makes their life perhaps a tiny fraction better.
I read the little alcohol enjoyment paper James and co wrote, which seem to have one study showing no change in happiness, three longitudinal (better) studies showing negative changes for heavy drinkers and no changes for moderate drinkers (expected), one large cross-sectional survey showing an incredible third of drinkers want to drink less next year which is telling/
And just one “I phone based” cross-sectional subjective study showing a increase in moment-to-moment happiness while drinking alcohol (I mean of course), while not looking at future negative effects. Above anecdotes like mine, basically the lowest level of evidence. Typed in by an unrepresentative sample on Iphones.… I mean...
If it was me I would possibly be discounting for happiness by −10% :D, or at least by 0%.
Hi Nick, yeah I get that there are costs to alcohol, I just think it is important to consider the benefits when deciding what to do. A lot of public health policies are defended by only focusing on the costs of doing something, not the benefits. So, I think it is important to consider the benefits.
My own intuition is that if there were no alcohol, happiness would go down for the vast majority of people and would go up for a small minority. From my own experience, people often seem close to their happiest when drinking, and it is a very important social lubricant.
I think the best study in James’ review was the subjective wellbeing one because it measures what, in my view, actually matters, which is people’s moment to moment wellbeing. It’s also a very large sample. I wouldn’t class the benefits found in the study as ‘tiny’. The increase in wellbeing while drinking is nearly as large as that produced during spending time with friends. And this is a benefit which would be spread across billions of people.
Thanks John those are reasonable points. Completely agree we should consider the benefits, just disagree that alcohol is probably net positive for happiness in LMICs, no comment really on Staten countries.
You are right the difference isn’t “tiny” in the study have deleted.
From a study design standpoint, a cross sectional phone study where people opt in, would fall close to the bottom of the heirachy of evidence, traditionally at least. Personally I think it’s not useless, but at best very weak. I can see your argument that what they measure is what “actually matters”, but the bias and confounding of this kind of the study makes it so so hard to put much weight on. Given that, a huge sample size doesnt really help at all.
If your rate moment by moment wellbeing as the most important thing to measure, there would have to be some kind of random sampling and ways to avoid the kind of “I’m drinking and happy now” bias, while not attributing the hangover or bad mood the next day to alcohol.
I’m not sure the phone study has the traditional weaknesses as cross-sectional studies. It’s a bit more like a panel study where you can track in very fine-grained detail what events are happening and what happens to subjective wellbeing at the time. Because the event data is so fine-grained and there are so many contiguous datapoints, it provides very good evidence of causation. These sorts of studies also give intuitively plausible results for all other events. People don’t like work, getting divorced, being unemployed, being widowed; people like sex, seeing their friends etc.
It’s true that people opt in, but I don’t see any particular reasons to think that this would have a bias towards ‘happy drinkers’. The same is true for other life events. Like maybe there is some bias such that people who enjoy sex are more likely to opt in to phone-based subjective wellbeing studies, but I don’t think that is what is driving the results.
I’m surprised you think it provides “good evidence of causation”. Having fine grained data and many datapoints doesn’t as far as I can tell do anything to counter selection bias and confounding. Usually these kind of studies would not even claim that themselves. I’m going to have to read the study properly now rather than just skimming lol.
How do you get away from the confounding? People drink at social events with friends, people drink in the evening when they are relaxing anyway. Are people drinking because they are happy it happy because they are drinking?
And self selection seems like a pretty massive deal why do you think it isn’t? Seems likely to heavily select for “happy” drinkers f again I could be missing something.
Re confounding, the headline estimate that James uses is adjusted for various potential confounders.
I don’t have a strong view on what effect the potential selection effect would point.
Thanks John. It’s great that hey adjusted for confounders (and any similar study would). That such a lot of controlling for confounders needed to be done at all shows the major weakness in this kind of study design.
I’m not saying it’s a bad study, just that it’s not fit for analysis of causation.
I think you would struggle to find many (if any) researchers who would say this study provided any more than a decent correlation between drinking and increased happiness, rather than evidence of causation. Happy to be proved wrong here and others can feel free to weigh in!
Along those lines it was mainly this comment I disagreed with.
“Because the event data is so fine-grained and there are so many contiguous datapoints, it provides very good evidence of causation.”
Another thought—I think there is a risk of overcontrolling with some of the controls used in that paper. The controls in effect assume that if people were not drinking, they would do the same thing they were in fact doing while drinking, except without drinking. But drinking might lead people to be more likely to spend time with friends, go dancing etc. If you control for what people were doing and who they were doing it with, you assume that if they weren’t drinking, people would see their friends and go dancing sober. I think this is unlikely. I don’t like dancing, no matter what I have imbibed, but I think most people would basically never go dancing with friends if they didn’t drink. The uncontrolled effect on SWB is 10 points, though some of the controls seems sensible, so that probably overstates it.
Yeah that’s fair enough re that part of the comment.
Yeah I suppose I would disagree with how a lot of researchers view the strength of evidence provided by cross-sectional studies. I think a lot of researchers seem to endorse the proposition ‘if this could be confounded, it provides no evidence of causation’, which I don’t think is right. It depends on one’s prior on how plausible the confounder is. I think this is why a lot of economics has stopped trying to focus on some of the more important macro questions, and I think this is a mistake.
eg consider the potential effects of climate change on economic performance. I do think cross-sectional evidence is highly relevant and should update one’s view. If economic performance were very strongly climatically determined, I would expect this to show up strongly in the cross-section. I wouldn’t expect to see California being way richer than Baja California. I wouldn’t expect gross state product for US states to look like this as a function of state average temperature:
I would expect growth rates to be uniformly low in climatically exposed places like Vietnam, Bangladesh, Indonesia, India etc, which is not what we see. So, I do think this sort of evidence should update one’s view, even though there are obviously loads of potential confounders.
In climate economics, people don’t like this, so they have started using panel data approaches which aim to test the exogenous effects of weather changes on economic performance in particular periods of time. This supposedly provides better evidence of causation, but I think should be completely ignored because of huge researcher degrees of freedom, reporting bias and political bias. I think they leave the door open for econometric skullduggery to provide inflated estimates. In part because the cross-sectional evidence is more transparent, I think it is more reliable.
I assume many potential alcohol-reduction efforts would reduce an individual’s alcohol consumption at the margin, not lead to a world with no alcohol. I don’t drink myself, but it would seem challenging to measure the lost happiness from—e.g., going down from four beers at a social occasion to three due to higher taxation. I don’t think extrapolating from the status quo to an alcohol-free world would work here.