No, California's $20 Minimum Wage for Fast-Food Workers Did Not Create Jobs
A University of California, Berkeley, study trumpeted in the media doesn't say what the press release claims.
HD DownloadAfter California's $20 minimum wage for fast-food workers went into effect in April, some economists expected affected restaurants to cut jobs. So what actually happened? They not only added workers but did so at a faster pace than fast-food restaurants in the nation as a whole—or at least that was the claim of a research paper by two labor economists at the University of California, Berkeley, and the University of California, Davis.
If you actually read it, you'll find that the results celebrated in the press release and echoed by the media aren't in the paper. In fact, it barely addresses the effect of the minimum wage increase on fast-food employment in California. It offers no numbers and no models. There's no evidence that fast-food jobs increased after the law was implemented.
The paper's findings were trumpeted as evidence that government-mandated wage increases have no adverse effect and that we should be raising the minimum wage higher and in more places.
Only toward the end of the 25-page study is employment shown. There you'll find a graph that represents the closest thing to an argument in the paper. It shows full-service and fast-food restaurant employment in California, represented by the red line, and in the U.S., represented by the blue line, from 2023 to 2024.

The authors state that the data are prone to sampling errors, and make an inconclusive finding that "we do not detect evidence of an adverse employment effect." But the paper's abstract neglected the fine print caution, boldly asserting, "We find that the policy…did not reduce employment." The accompanying press release, which is likely all that journalists bothered to read, states that "contrary to fears expressed by restaurant groups, the wage increase did not lead to job cuts."
But the solid red line on the chart clearly shows California fast-food employment increasing more slowly than the solid blue line showing national fast-food employment, which is the opposite of the authors' claim. If they suggest anything, these data show that the minimum wage increase reduced California fast-food jobs.

But it's still hard to make a precise estimate from the way the chart is presented. So I looked up the numbers, which tell a different story than the authors claim. Even though the paper was published in September, the chart ends in July 2024, when California fast-food employment was up 1.85 percent since March 2024 while national fast food was up 3.22 percent.

This is a sign that the minimum wage is having a negative impact. In 2021 and 2022, national and California fast-food employment grew at nearly identical rates: 7.7 percent over the two years nationally, and 7.8 percent in California. But in 2024, growth slowed dramatically in California, and after July, employment began to decline.

The slowdown started a couple of months before the law took effect, but that's exactly what you'd expect because it was signed by the governor in September 2023 and management's decisions to close, open, or rebrand their restaurants would have been made in anticipation of the law being implemented.

But there's a big problem even with my version of the chart. The data used to draw the red solid line don't only represent fast-food restaurants impacted by the law; they also include casual dining restaurants exempted from the law, such as buffets, Panera Breads, smaller fast-food chains, donut and snack shops, grocery store concessions, and most delis. If fast-food restaurants were negatively impacted by the law, we would expect some of the exempted establishments to expand to take their market share, thus adding jobs. By combining data from exempted establishments that were likely growing with data from restaurants impacted by the minimum wage increase, the negative effect of the law may be hidden in the data.
Looking at crude aggregates tells us little. But California possesses the information from employer job reports that would settle the issue. Every quarter, California employers submit a series of reports to the state giving details of each employee's hours and pay by Social Security number. The state knows everyone who worked for a fast-food operation covered by the law, and what their wages and hours were before and after the law took effect.
Another study on the same subject, "Early Effects of California's $20 Fast Food Minimum Wage" by Daniel Schneider, Kristen Harknett, and Kevin Bruey, sponsored by Harvard's Malcolm Wiener Center for Social Policy, used data from semi-annual surveys of retail workers in Western states. In this case, the researchers focused only on fast-food workers covered by the law, excluding exempt restaurants.
Immediately after the new fast-food law became effective, California fast-food workers lost an average of two work hours per week due to the law, according to the paper. But the authors used misleading language to report this result because their margin of error for the estimate meant that the actual change could be anything from an average loss of five hours to an average gain of one hour. "We can reject large reductions in work hours," the study reports. "We find no significant effects of the minimum wage increase on usual hours."
Both statements are misleading. The authors can reject that the average loss in hours was greater than five per week, but five hours–or even two–is a large loss. The estimated two hours per week loss is economically significant to the low-wage workers, just not statistically significant by conventional criteria (which means it might be the result of random noise). The correct phrasing is "we failed to find statistically significant proof" of wage losses, not "we find no significant effects." Absence of evidence is not evidence of absence.
Another deficiency is that the study only covered fast-food workers who kept their jobs after the law went into effect, excluding missing workers who were laid off and the employees of restaurants that closed. And the respondents were self-selected—people who respond to Facebook and Instagram ads to take a survey for a chance to win a $500 gift card. This is not a random selection of people, and they do not always answer the questions seriously or honestly. This is not a sample from which anyone would expect to get solid proof of anything, so failure to find it doesn't mean much one way or the other.
Finally, the study only deals with the first few months after the law took effect. Some changes can take months or years to emerge.
The main objection to high minimum wages is not their effect on overall employment, prices, or profits—it's the fear that they cut off the bottom rungs of the economic ladder for low-skill workers. Instead of being able to work at low wages while improving job skills and making contacts for advancement, they are forced into the underground cash economy or public assistance. Therefore studies of these laws should focus on the effect on these low-skill workers, not on economic aggregates.
The correct way to study the impact of the $20 minimum wage is to see what happened to fast-food workers who were earning less than that amount before April 1, 2024. How many had their pay raised and hours maintained? How many lost their jobs or lost hours, and what did they do afterward? Were low-skill workers able to compete for the new job openings after the law's implementation?
If minimum wage increases were a drug, governments would have to conduct trials and monitor adverse effects afterward. That's what happened in Seattle when it raised the minimum wage in 2014. The city called for proposals to study the impact on actual workers earning below the minimum before the law. The Evans School of Public Policy and Governance at the University of Washington was the only volunteer. Its researchers found that the law didn't cause an increase in layoffs among workers who had previously earned below minimum wage, but it did reduce their hours by an average of 7 percent. That was partly offset by a 3 percent increase in hourly pay for the hours they did work. On net, the law cost these workers an average of $888 per year.
That amount is significant in itself, but it's important to consider that it accounts for only the short-term effects. As mentioned above, some layoffs and hour reductions will happen immediately, but others—such as more businesses closing and fewer opening, or automation and other changes reducing employment—can take years. Another point is that the workers who benefited from higher pay were the ones most likely to have risen out of the minimum wage ranks to the middle class even without a mandated increase, while the workers who lost much more than $888 per year are more likely to be the ones blocked forever from economic advancement. In fact, the paper found that the workers who benefitted net were the most experienced and highest paid among the group–earning more than the old minimum but less than the new–while the less-experienced workers earning the old minimum or close to it, lost considerably more than the average.
Seattle legislators must have been unhappy with those findings because they cut funding for the Evans School and reached out to the same group at U.C. Berkeley that did the California minimum wage study to do its own distorted analysis, which was rushed out a week before the Evans study was made public. Eventually, Seattle raised the minimum wage again.
These studies aren't about the search for truth with statistics; their purpose is to score political points, with little regard for the low-skill workers whose lives are directly impacted.
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"No, California's $20 Minimum Wage for Fast-Food Workers Did Not Create Jobs."
1. Well, duh.
2. This outrageous raise in the minimum wage created more unemployment in the Peoples' Republic of California, a fact the notorious MSM fails to report.
3. It never ceases to amaze me how ignorant the do-gooders are when it comes to rudimentary economics.
It's not even Econ 101, just plain common sense. People buy less of things which cost more.
This has nothing to do with economics, and everything to do with power.
Liberals ignore reality. Film at 11. But not shown on the propaganda outlets.
"We reject reality and substitute our own." - Seattle legislators
It worked so well, we should make it $50 /hour!
$500!
We’ll all be rich!
$500?
Piker. How about $50,000/hr. Work one day and go to Hawaii all year.
I am amazed that Reason actually published such a well-researched and clear article.
What is not amazing is that any such article would even be necessary. Raise the price, demand dwindles. How anyone could think otherwise is the question.
I see you have never studied Marxist "economics".
Well, you can't study what doesn't exist. There's more value in zero than any Marxist anything.
My econ professor was one of these Marxists. He said very straightforward that raising the minimum wage would eliminate jobs, but that it was good because it eliminates bad jobs.
Sounds like a super smart guy. How are young people supposed to get their start in the work force and gain experience if there are no 'entry level' jobs?
It kind of reminds me of when I graduated from college, and every firm I sent a resume to was looking for someone with '3-5 years experience', and almost no-one was hiring fresh out of school. And complaining that they couldn't find anyone with that experience range. Well, if you had hired someone fresh out of school, 3-5 years ago, you'd have one?
A significant number of these firms called to see if I was still interested, 3-5 years later.
When I’ve made that argument the most common response was “Well you got a job, didn’t you? That means you’re wrong.” Talk about missing the point.
Poor sarc.
Pour Sarc.
I mean, I worked in a different design field outside of what I went to school to do, for a couple of years, until the market opened up a bit. Finally got my shot and have excelled since, but, it was rough starting out.
I try to advocate in my current company to recruit people straight out of school, or even while they are still in school, so that we can all avoid that. And it has the benefit of being able to find and train good talent before they get ruined by bad habits or corporate practices at other companies.
It's been a long time, but I still relate. The first few years on my own were very uncertain and stressful and as far as work went really sucked.
Absence of evidence is not evidence of absence.
But it's remarkably common to use p > 0.05 as an argument of "no difference." I see this in clinical trials all the time. It's wrong, but convenient.
Thay should be p<0.05. In science, unlike in life, the smaller the p the better.
Lies, damned lies and Statistics.
Minimum wage was created to keep undesirables unemployed. And it still does.
Who is undesirable?
"Minimum wage was created to keep undesirables unemployed."
Sarc says something true for a change.
Same with unions. Both were born of racism.
Minimum wage was originally set to prevailing union wages to appease white union workers who didn’t like competition from blacks who were moving north.
Sarc went to the Howard Cosell School of Economics. Even when he is right, it is for the wrong reason. But he states it confidently.
Sarc accidentally says something true, once every blue moon or two. Maybe some day he will reach broken clock level.
I like this guy, he's a good presenter on YouTube when he periodically pops up on a ReasonTV video.
That said, the argument comparing the slopes of the lines for the charts is not a good one. The scales and the zero points for both sets of data are different. You could scale either one side or the other up or down, or slide the zero points, and use the same data to make the opposite argument.
The following argument point using percentage-based changes in restaurant worker employment is much more sound. And it's also much easier to make apples-to-apples comparisons with, and take conclusions from.
The observation that they truncated their data collection period in such a way that it coincidentally coincided with a downturn in industry employment in the state is pretty devastating as well.
Hide the decline!
Hey, it worked before.
"trumpeted in the media doesn't say what the press release claims."
In other news: water is wet and the sky is blue.
Look, I'm sympathetic to the author's argument, but this is just ignorant:
""We can reject large reductions in work hours," the study reports. "We find no significant effects of the minimum wage increase on usual hours."
Both statements are misleading. The authors can reject that the average loss in hours was greater than five per week, but five hours–or even two–is a large loss. The estimated two hours per week loss is economically significant to the low-wage workers, just not statistically significant by conventional criteria (which means it might be the result of random noise). The correct phrasing is "we failed to find statistically significant proof" of wage losses, not "we find no significant effects." Absence of evidence is not evidence of absence."
I'm not even going to defend the first sentence from the study, but the second sentence is absolutely correct, and to say it is wrong is to demonstrate your own ignorance.
An effect is significant if and only if you can reject the null hypothesis (no hours were lost because of increased minimum wage laws). Since the confidence interval includes no change in hours, you can't reject that hypothesis. Therefore, the effect isn't significant.
"Significant" is a technical word in statistics. It's not talking about the *size* of the effect, it's talking about whether the effect was different from the null hypothesis. They don't need to use the author's preferred word salad - that's the only thing "significant" means in a statistical context.
(In fact, with enough data, significant results can have "insignificant" effect sizes, in the sense the author wants to use the word - ie, the null hypothesis has been rejected, but the measured effect size is tiny. This is why the word 'significant' is a technical word used with a specific meaning in statistical contexts, so you don't have the confusion the author is imputing.)
Mr. Brown, you've convinced me you aren't qualified to read or comment on statistical analysis. For someone trying to position themself as the adult in the room (relative to the media and even the authors) on talking about an academic analysis, something which should have been an easy task in this situation, shame on you.
(And the reason the author's wording is absolutely correct is because statistical analysis, correctly understood, is about the *limits* of our knowledge. From the study's data, we don't *know* that there was any effect on hours worked. The sample average could not represent the true population average very well - the true population average probably falls somewhere within the confidence interval. So it could really be no hours lost. Mr. Brown errs, in part, because he assumes the sample average of 2 hours is *real*. It's not. It's an estimate. We can't *know* there was a real decrease in hours worked unless and until we can reject the null hypothesis).
It should also be pointed out that it's silly to fault a paper published in September for only using data up through July. It takes time for an article to be peer reviewed and published - and it looks like it was peer reviewed and accepted pretty rapidly. Having data up through two months ago is actually pretty good. Mr. Brown has apparently never published a peer-reviewed paper before.
(It's absolutely right to call out how short-term the paper is compared to the expected timeframe over which the effect might operate over, and note how things have changes since the paper was written. But not to criticize them for not using data from after the paper was written and working its way through the publisher.)
Assuming that everything you say is true, then it's the responsibility of the pollsters to convey their findings in a way that the press or the casual reader (who has no training in statistics) can understand.
A loss of two to five hours of work represents a considerable loss for the working class. If that's the direct result of min wage increase, then its effect should be rightfully characterized as significant. You're saying that the authors were correct to consider that as "insignificant" in the context of null hypothesis, which is that min wage hike resulted in zero loss of job hours. That seems like silly sophistry. The authors almost certainly used the term "significant" in a way that term is widely understood.
The authors, in their academically published work, have a duty to clearly convey their results to an academic audience. (Seriously, the quote is from an academic paper, not a communication to the public). 'Significant' has one meaning in the context of statistical analysis.
And it's not a loss of 2-5 hours. The actual range was a gain of 1 hour to a loss of 5 hours. That's the confidence interval, and it includes 0 hour loss (ie, no change). They can't say where in that range the true average is, only that it is probably somewhere in that range.
Since they can't reject a 0-hour loss, the result is not significant. (ie, their sample average could have reasonably been randomly sampled from a true population with a 0-hour loss).
You're making the same epistemic error Mr. Brown is. You're assuming the '2-5 hour' *possibility* is real. It's not. 2 hours was the *measured* average of the sample, but it's not the true average of the population (which we don't know). The statistical test said that a measured two-hour-average loss was indistinguishable from no hours lost.
"significant" and "insignificant" refer only to the result of the statistical test. If you can reject the null hypothesis, the result is significant. If you can't reject the null hypothesis, the result is not significant. They couldn't reject the null hypothesis (their data did not allow them to rule out the possibility that the true average of the population was zero hours of work).
It doesn't matter if a loss of 2 hours of work is 'significant to the worker', because *that is not what is being expressed at all*, and *the reality is probably not 2 hours, but instead something in the range of +1 to -5 hours*. Statistics uses the words 'effect size' to talk about the *magnitude* of measured effects (how different is it from the null hypothesis?), but we only bother to talk about that for significant effects (because if you can't reject the null hypothesis, you can't talk about how different the result is from the null hypothesis, since it's *not different*).
It should also probably be said that we should teach people how to understand statistical analyses, and how to talk about them. But again, this particular sentence is from an academic paper written for other experts in the field, not the general public.
---------------------------
Even their press release, which has the much more public friendly language "contrary to fears expressed by restaurant groups, the wage increase did not lead to job cuts." is just slightly overclaimed, mostly because they're expressing it as a finding rather than the failure to make a finding. They could not reject the null hypothesis, so they did not find a reduction in jobs attributable to the change in policy. (ie, the sample could have been drawn from a population that lost no hours of work). I would personally support the more cautious: "our study does not find any effect on hours worked from the increase in wages." But the increased cautiousness of that phrasing would be entirely lost on the naive public reader, who would read it the same as what they actually wrote.
Now, Mr. Brown does point out some flaws with the data used, and the short timeframe. But their language about their results is accurate for academics, and their version for the public is not unreasonable.
But then Mr. Brown goes on to further demonstrate his ignorance when he looks at the more recent data - he just gives us a plot with *no confidence intervals*, and no statistical test, and just claims that one is bigger than the other. As much as I'm inclined to believe the law should decrease hours worked, Mr. Brown's visual case is unconvincing. We don't know reality that precisely. Mr. Brown is ignorant of his own ignorance here.
(Here's a quick example of why we do statistics: Let's say there's a random collection of billiard balls in a large bin. Each billiard ball has a number from 1 to 15 on it. You want to know what the average of the numbers in the bin is. Now, you could go through and record the whole bin, but in real world problems, the whole bin is unmeasurable, and we'd have to take a sample. So we sample some number of balls from the bin, say 5, and record their numbers. That sample has an average, which is our estimate for the bin's average. But our sample could be off, potentially by a lot. If we just happened to draw 2 elevens, a thirteen, a fifteen, and a five, we'd estimate an eleven average. If the bin is actually an equal distribution of numbers 1 through 15, the real average is 8. Or other distributions of billiard balls could have even lower or higher averages. A confidence interval gives us a range across which we'd expect the real average of the whole bin to fall, based on our sample. And with that confidence interval, we can ask questions, such as, could the balls have been drawn from a collection of evenly distributed billiard balls? If the answer is yes, then there's no significant result. If the answer is no, we'd say that the average is significantly different from 8 (that is, to some degree of certainty, we can reject the hypothesis that 8 is the true average). (The degree of certainty is set by the p-value, which is the probability that your significant result is wrong, generally never allowed to be any higher than 5%).)
You're saying that the authors were correct to consider that as "insignificant" in the context of null hypothesis, which is that min wage hike resulted in zero loss of job hours. That seems like silly sophistry. The authors almost certainly used the term "significant" in a way that term is widely understood.
Squirrelloid is correct, but may be engaging in a bit of sperg dunking.
The short version is that in the context of statistical significance, not significant is not related to insignificance. Insignificance is a qualitative observation. If the authors of the study are confounding the two, then they are being disingenuous. If the author quoting the study is doing so, he is being fallacious.
The quote is right there in my first comment, and 'no significant effects' is perfectly good language for what they're expressing. (Could not reject the null hypothesis).
The real problem is Mr. Brown's misinterpretation of their language, combined with his facile analysis of the trend lines (with no use of confidence intervals or statistical analysis), makes it impossible to trust him to do any data analysis, much less *this* data analysis.
Was it ever promised to create job? I think the point is if you pay someone more, they won't have to use welfare or other government assistance.
You have fewer jobs, but better paying ones.
Obviously its a tradeoff. But why should taxes go to support workers when companies don't want to pay enough for someone to live on? Yeah, you could argue that no jobs means the government will have to pay unemployment, but that at least is not subsidizing a business
Sure, except that the people who can’t get a job because they lack the skills and experience to be worth $20/hr to an employer end up on welfare.
Keeping people of low intelligence from gainful employment was a stated goal of the Progressive party when they first promoted minimum wages 100 years ago. You tried to make it a racist thing up above, but it was really about keeping idiots from breeding. It has always been part of their platform, they just rebranded it as "looking out for the little guy".
The main objection to high minimum wages is not their effect on overall employment, prices, or profits
My main objection is the government has neither the moral not the constitutional authority to set a floor on the price I can sell my labor for. Plus the hypocritical nitwits who argue for a higher minimum wage spend their every other walking minute bitching about how the government should keep its laws off their bodies. There is a reason you never see the words "intelligent" and "progressive" next to each other.
They don’t read the constitution. Just the cliff notes: “Congress shall do everything necessary and proper to promote the general welfare and regulate commerce.”
That’s unlimited power.
Unlimited? No.
Do they include a chart of the cost of fast food in CA v the rest of the US?
This is more evidence academia is thoroughly corrupt and in bed with the left.
What makes this hook juicy is that academics often refer to Economics departments as "right-wing". In fact studies show about 1/3 of Economics professors identify as not left-wing, mostly libertarian. The core nugget is that even the existence of a small minority of dissenting views is enough to distinguish this department from other departments. Leftists wrongly identify this as "right-wing" but they correctly recognize the existence of any non-leftist thought makes this department different than others.
Until we push left wing activists out of academia and return it to a balanced institution focused on knowledge rather than activism it will remain corrupt and do more damage than good for the majority of its customers.
Economics of Fascism (https://en.wikipedia.org/wiki/Economics_of_fascism)
Mussolini's Fascist Italy
A number of mixed entities were formed, called instituti or enti nazionali, whose purpose it was to bring together representatives of the government and of the major businesses. These representatives discussed economic policy and manipulated prices and wages so as to satisfy both the wishes of the government and the wishes of business.
California:
AB 1228 – Fast Food Council
On September 28, 2023, Governor Newsom signed into law AB 1228, the Fast Food Restaurant Industry legislation that raises the hourly minimum wage rate for certain fast food workers to $20 effective April 1, 2024. In addition, the legislation establishes a Fast Food Council within DIR to establish an hourly minimum wage for fast food restaurant employees and develop standards, rules, and regulations for the fast food industry.
The author commits the unforgivable sin of citing the pre-Covid Seattle study as evidence to support his premise. Any labor statisticians worth their pay know that Covid changed the US labor market in virtually every aspect his article attempts to cover. I don't dispute his description of the Berkeley study or its use, but he fails to make any kind of case to support his own opinion if you can figure out what it is. The fact is we don't know if the California minimum wage increase helped, hurt, or had no effect on fast food employment. In my own non-California college town community,where $16-17 per hour with no experience and automatic raises still have every fast food restaurant desperate to hire, workers who do sign up work as many hours as they want. My guess is this is now the case nationally and in California, although we need a good CURRENT study to show it.
"...In my own non-California college town community, where $16-17 per hour with no experience and automatic raises still have every fast food restaurant desperate to hire, workers who do sign up work as many hours as they want. My guess is this is now the case nationally and in California, although we need a good CURRENT study to show it..."
Yes, if the new M/W is nearly market rate it (A) has little effect and (B) really isn't needed.
Otherwise, it is a job-killer. If you claim otherwise, you are an econ-ignoramus.
"Multiple Pizza Hut franchises in California, collectively operating hundreds of stores, are laying off 1,200 in-house delivery drivers ahead of a new law taking effect in April that raises wages to $20 per hour"
"Excalibur Pizza, a franchisee of Round Table Pizza, has plans to cut 73 driver jobs in April, which amounts to 21% of its workforce, the company confirmed with USA TODAY Wednesday.
"The coffee chain [Starbucks] recently closed seven of its stores in the state of California, USA TODAY previously reported.
NY Post (Jun 6 2024) "California fast food restaurants have cut 10,000 jobs thanks to state’s $20 minimum wage: trade group The California Business and Industrial Alliance (CABIA) slammed Democratic Gov. Gavin Newsom for pushing through the law, which went into effect April 1 – and was blamed for forcing one beloved taco chain to shutter 48 locations in the state last week. Rubio’s California Grill, known for its fish tacos, closed 48 of its nearly 134 locations at the end of May – the first major chain to fall victim to the new law. The San Diego-based company cited the “rising cost of doing business” in the state for the closures. The chain filed for bankruptcy on Wednesday. Another fast food restaurant, Fosters Freeze, recently closed a location near Fresno, saying the franchise owner could no longer afford to pay workers the upgraded salaries.
Since they were fired before the law took effect, their unemployment is *clearly* not a result of the law, n'est-ce pas??
High min wage tends to increase efficiency, but importantly for employers to use more automation which the leads to new businesses to make the new machinery so that there are more advanced jobs in other industries while making fast food and other min wage businesses more productive.
Government setting wages is fascist. What more needs to be said?
that was the claim of a research paper by two labor economists at the University of California, Berkeley, and the University of California, Davis. If you actually read it...
Nope. Don't need to. UC Berkeley and UC Davis. Tells you everything you need to know right there.
Conservatives/ Republicans proven correct YET AGAIN BATMAN!
We tell the Truth, the Left lies.
About time the Left got their asses kicked, for abusing and beating on us Truth Tellers!
Holy Crap! A good Reason article like the old days. No TDS. No illegals can't do anything wrong. No other talking points.
Just looking at data.
Nothing better than having Gov-Gods packing 'Guns' stamping price-tags on your forehead. /s
That sure was a whole lot of words. It seems you can take the person out of the university but not the university out of the person.
"...The slowdown started a couple of months before the law took effect, but that's exactly what you'd expect because it was signed by the governor in September 2023 and management's decisions to close, open, or rebrand their restaurants would have been made in anticipation of the law being implemented..."
The market discounting the future effect is nearly always ignored in lefty claims that '...6 months after the law took effect, there was not loss of jobs...'
Yes, it happened in advance.