The South Korean kimchi crisis

The Washington Post reported this week (possibly paywalled for you):

In the foothills of the rugged Taebaek range, Roh Sung-sang surveys the damage to his crop. More than half the cabbages in his 50-acre patch sit wilted and deformed, having succumbed to extreme heat and rainfall over the summer.

“This crop loss we see is not a one-year blip,” said Roh, 67, who has been growing cabbages in the highlands of Gangwon province for two decades. “I thought the cabbages would be somehow protected by high elevations and the surrounding mountains.”

With its typically cool climate, this alpine region of South Korea is the summertime production hub for Napa, or Chinese cabbage, a key ingredient in kimchi, the piquant Korean staple. But this year, nearly half a million cabbages that otherwise would have been spiced and fermented to make kimchi lie abandoned in Roh’s fields. Overall, Taebaek’s harvest is two-thirds of what it would be in a typical year, according to local authorities’ estimates.

The result is a kimchi crisis felt by connoisseurs across South Korea, whose appetite for the dish is legendary. The consumer price of Napa cabbage soared this month to $7.81 apiece, compared with an annual average of about $4.17, according to the state-run Korea Agro-Fisheries Trade Corp.

The effects of poor weather on the markets for cabbage and kimchi can be easily analysed using the supply and demand model that my ECONS101 class covered the week before last. This is shown in the diagram below. Think about the market for cabbage first. The market was initially in equilibrium, where demand D0 meets supply S0, with a price of P0 and a quantity of cabbage traded of Q0. Bad weather reduces the cabbage harvest, decreasing supply to S1. This increases the equilibrium price of cabbage to P1, and reduces the quantity of cabbage traded to Q1.

Now consider the market for kimchi. The costs of producing kimchi have increased. That leads to a decrease in the supply of kimchi. The diagram for the market for kimchi is the same as that for cabbage, with the equilibrium price increasing, and the quantity of kimchi traded decreasing. At least, that is the case for kimchi made from cabbage. Kimchi can also be made from other vegetables. The Washington Post article notes that:

The fermented pickle dish can also be made from radish, cucumber, green onion and other vegetables.

What happens in the markets for kimchi made from radishes? That is shown in the diagram below. Radish kimchi is a substitute for cabbage kimchi. Since radish kimchi is now relatively cheaper than cabbage kimchi, some consumers will switch to using radish kimchi. The effect is shown in the diagram below, where the radish kimchi market is initially in equilibrium with a price of PA, and a quantity of radish kimchi traded of QA. This increases the demand for radish kimchi from DA to DB, increasing the equilibrium price of radish kimchi from PA to PB, and increasing the quantity of radish kimchi traded from QA to QB.

The South Korean kimchi crisis is echoing through all types of kimchi, even if it is just the cabbages that are affected.

[HT: Marginal Revolution]

Is the Australian egg market demonstrating a cobweb pattern?

Last month in The Conversation, Flavio Macau (Edith Cowan University) wrote an interesting article about the egg market in Australia:

Australia is experiencing a national egg shortage. Prices are rising and supermarket stocks are patchy. Some cafes are reportedly serving breakfast with one egg instead of two. Supermarket giant Coles has reverted to COVID-19 conditions with a two-carton limit.

It's worth thinking about what has gotten Australia into this situation. Macau notes that:

Between 2012 and 2017, free-range eggs’ share of the market grew about 10 percentage points, to about 48%. Growth in the past five years has been half that.

But with more rapid growth predicted, and the promise of higher profits, many egg farmers invested heavily in increasing free-range production. In New South Wales, for example, total flock size peaked in 2017-18.

Like many agricultural industries where farmers respond to price signals and predictions, this led to overproduction, leading to lower prices and profits. This in turn led to a 10% drop in egg production the next year.

Now, consider the market for free range eggs, as shown in the diagram below. Demand increased substantially from 2012 to 2018, which is shown by the increase in demand from D0 to D1 (from Time 0 to Time 1). That pushed the price of eggs up from P0 to P1, and the quantity of eggs produced increased from Q0 to Q1 in response (the farmers increased production). Now, with the high price P1, farmers want to continue producing more eggs (Q2 for Time 2), but the demand has decreased back to where it was before (D2). [*] The quantity Q1 is now too many eggs, and to sell that many eggs, the farmers have to accept a lower price (P2). So, now they respond to the low price by cutting production to Q3 (for Time 3). But that level of egg production is too low, and the farmers are able to sell those eggs for the high price P3. Then, with the price high at P3, the farmers decide to increase production to Q4. And so on. Notice that this market is forming a cobweb pattern (following the red lines).

Now, is what we just described happening in the Australian egg market? Is there a cobweb model here? The cobweb model, as I have described before, relies on a key assumption: that the market has a significant production lag. Producers make their decisions about how much to produce today, but don't receive that production until some time in the future. This is a common feature of agricultural markets, but is it a feature of egg production? Chickens lay eggs every day (approximately), so when you consider it at that level, there is no production lag. Certainly, farmers don't have to wait long for eggs. However, the relevant production lag here isn't the production of eggs by chickens, it is how long it takes the farmers to respond to a change in price. If price falls, farmers may want to reduce the number of chickens they have, but that takes time (albeit, not a lot of time, since they can round up chickens and send them to a meat processor). If price rises though, farmers may want to increase the number of chickens they have, and that takes time, since they have to raise those chickens until they are ready to lay eggs. So, maybe there is half a production lag here - a lag in increasing production, but little lag when it comes to reducing production. So, this is not quite the cobweb model that I describe in my ECONS101 class (and as described for the diagram above). It does share some of the features of the cobweb, but only when prices are too low - it takes farmers more time to adjust to low prices than to adjust to high prices.

Australia finds itself in the uncomfortable position of having to wait for farmers to raise enough chickens so that egg production can increase. Once that happens, the market will adjust back to equilibrium (with a higher egg price).

*****

[*] Astute readers will note that the article only says that demand growth has fallen, rather than demand per se. However, if farmers are expecting high demand growth, and demand is less than farmers expected, that is similar to a decrease in demand. Not exactly, but close enough for our purposes.

We should be careful not to conflate the effect of online revision with the effect of online teaching

The pandemic forced education online, and should afford a lot of opportunity for us to understand the impact of online teaching on student engagement, student achievement, and student learning (and yes, those are all different things). Most of the literature on online learning relates to the university context, but students at university tend to be a little more self-directed than students at high school or below. What works in the university context doesn't necessarily translate to those other contexts, so we need more research on how online teaching affects high school and primary school students. I discussed one such paper back in May, which looked at students in Grades 3 through 8 in the US.

In a new article published in the journal China Economic Review (sorry I don't see an ungated version online), Andrew Clark (Paris School of Economics), Huifu Nong (Guangdong University of Finance), Hongjia Zhu (Jinan University), and Rong Zhu (Flinders University) look at the effects for three urban middle schools in Guangxi Province in China. These three schools (A, B, and C) each took a different approach to the government-enforced lockdown from February to April 2020:

School A did not provide any online educational support to its students. School B used an online learning platform provided by the local government, which offered a centralized portal for video content, communication between students and teachers, and systems for setting, receiving, and marking student assignments. The students’ online lessons were provided by School B’s own teachers. School C used the same online platform as School B over the same period, and distance learning was managed by the school in the same fashion as in School B. The only difference between Schools B and C is that, instead of using recorded online lessons from the school’s own teachers, School C obtained recorded lessons from the highest-quality teachers in Baise City (these lessons were organized by the Education Board of Baise City).

Clark et al. argue that comparing the final exam performance of students in Schools B and C with students in School A, controlling for their earlier exam performances, provides a test of the effect of online teaching and learning for these students. Then, comparing the difference in effects between School B and School C provides a test for whether the quality of online resources matters. There is a problem with this comparison, which I'll come back to later.

Clark et al. have data from:

...20,185 observations on exam results for the 1835 students who took all of the first 11 exams in the five compulsory subjects.

The five compulsory subjects are Chinese, Maths, English, Politics, and History. Clark et al. combine the results of all the exams together, and using a difference-in-differences approach (comparing the 'treatment group' of students from Schools B and C with the 'control group' of students from School A), they find that:

...online learning during the pandemic led to 0.22 of a standard deviation higher exam grades in the treatment group than in the control group...

And there were statistically significant differences between Schools B and C:

The online learning in School B during lockdown improved student performance by 0.20 of a standard deviation... as compared to students who did not receive any learning support in School A. But the quality of the lessons also made a difference: students in School C, who had access to online lessons from external best-quality teachers, recorded an additional 0.06 standard-deviation rise in exam results... over those whose lessons were recorded by their own teachers in School B.

Clark et al. then go on to show that the effects were similar for rural and urban students, that they were better for girls (but only for School C, and not for School B), and that they were better for students with computers (rather than smartphones) in both treatment schools. But most importantly, when looking across the performance distribution, they find that:

The estimated coefficients... at the lower end of distribution are much larger than those at the top. For example, the positive academic impact of School B’s online education at the 20th percentile is over three times as large as that at the 80th percentile. Low performers thus benefited the most from online learning programs. We also find that the top academic performers at the 90th percentile were not affected by online education: these students did well independently of the educational practices their schools employed during lockdown. Outside of these top academic performers, the online learning programs in Schools B and C improved student exam performance.

Clark et al. go to great lengths to demonstrate that their results are likely causal (rather than correlations), and that there aren't unobservable differences between the schools (or students) that might muddy their results. However, I think there is a more fundamental problem with this research. I don't believe that it shows the effect of online teaching at all, despite what the authors are arguing. That's because:

For students in the Ninth Grade, all Middle Schools in the county had finished teaching them all of the material for all subjects during the first five semesters of Middle School (from September 2017 to January 2020). Schools B and C then used online education during the COVID-19 lockdown (from mid-February to early April 2020 in the final (sixth) semester) for the revision of the material that had already been taught, to help Ninth Graders prepare for the city-level High- School entrance exam at the end of the last semester in Middle School.

The students had all finished the in-person instruction part of ninth grade by the time the lockdown started, and the remaining semester would have only been devoted to revision for the final exams. What Clark et al. are actually investigating is the effect of online revision resources, not the effect of online teaching. They are comparing students in Schools B and C, who had already had in-person lessons but were also given online revision resources, with students in School A, who had already had in-person lessons but were not given online revision resources. That is quite a different research question from the one they are proposing to address.

So, I'm not even sure that we can take anything at all away from this study about the effect of online teaching and learning. It's not clear what revision resources (if any) students in School A were provided. If those students received no further support from their school at all, then the results of Clark et al. might represent a difference between students who have revision resources and those who don't, or it might represent a difference between those who have online revision resources and those who have other revision resources (but not online resources). We simply don't know. All we do know is that this is not the effect of online teaching, because it is online revision, not online teaching.

That makes the results of the heterogeneity analysis, which showed that the effects are largest for students at the bottom of the performance distribution, and zero for students at the top of the performance distribution, perfectly sensible. Any time spent on revision (online or otherwise) is likely to have a bigger effect on students at the bottom of the distribution, because they have the greatest potential to improve in performance, and because there are likely to be some 'easy wins' for performance for those who didn't understand at the time of the original in-person lesson. Students at the top of the distribution might gain from revision, but the scope to do so is much less. [*]

We do need more research on the impacts of online teaching and learning. However, this research needs to actually be studies of online teaching and learning, not studies of online revision. This study has a contribution to make. I just don't think it is the contribution that the authors think it is.

Read more:

• Online vs. blended vs. traditional classes
• Flipped classrooms work well for top students in economics
• Flipped classrooms are still best only for the top students
• Online classes lower student grades and completion
• Online classes may also make better students worse off
• Meta-analytic results support some positive effects of using videos on student learning
• New review evidence on recorded lectures in mathematics and student achievement
• Meta-analytic results may provide some support for flipping the classroom
• The value of an in-person university education
• The pandemic may have revealed all we need to know about online learning
• Live streamed video lectures and student achievement
• Low-performing students, online teaching, and self-selection
• A slightly more optimistic take on online learning during the pandemic
• Research-based instructional strategies and flipped classrooms in economics
• Using microcommitments and social accountability to improve online and hybrid learning
• What pandemic schooling tells us about online learning

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[*] This is the irony of providing revision sessions for students - it is the top students, who have the least to gain, who show up to those sessions.

What caused the French mustard shortage?

France24 reported earlier this month:

Pierre Grandgirard, the owner and head chef of La Régate restaurant in Brittany, headed out on his regular morning supply run in late May when he ran into an unusual problem: he couldn’t get his hands on mustard.

“I went everywhere, but they were all out,” he explained. To make matters worse, some shopkeepers told him astonishing tales of hoarding. “That a papy (French slang for grandfather) had come in and filled his shopping carrier with 10 or more pots in one go.”...

What caused this shortage? The article goes on to explain:

The French mustard crisis can largely be explained by a combination of three factors: climate change, the war in Ukraine and the extreme love the French have for the tangy condiment. 

Although France used to be a major producer of the brown-grain mustard seed known as Brassica Juncea that is the base for Dijon mustard, that cultivation has since moved to Canada, which now accounts for as much as 80 percent of the French supply. Last year’s heat wave over Alberta and Saskatchewan, which was blamed on climate change, slashed that production almost in half, leaving France’s top mustard brands – Unilever-owned Amora and Maille – scrambling for the precious seeds.

On top of that, a milder than usual winter resulted in many French mustard fields falling victim to insects, and thus producing much smaller harvests. 

The war in Ukraine has also affected the global mustard market. But the way it has affected the French is rather surprising, and is chiefly due to the mustard consumption habits of other European countries.

Although both Russia and Ukraine are big mustard-seed producers, they mainly cultivate the much milder, yellow mustard seed – a variety that is typically shunned by the French, but hugely popular in eastern and central European countries.

Since the war has halted much of the Ukrainian and Russian exports, yellow mustard-seed fans have had to turn to other types of mustards, including the much-loved French Dijon mustard, thereby upping demand.

But the main reason why France has become such a victim of the mustard shortage, according to Luc Vandermaesen, the president of the Mustard of Burgundy industry group, is because the French are simply enormous mustard consumers.

“Every French person consumes an average of 1 kilogram of mustard per year,” he told French daily Le Figaro in an interview earlier this summer. “Sales are much weaker in our neighbouring countries, and so their stocks last longer. That’s why you can find products abroad that were produced in France a long time ago.”

Ok, let's go through those explanations one-by-one, using the diagram below. The market started in equilibrium, where the supply curve S0 meets the demand curve D0. The equilibrium price of mustard was P0, and the equilibrium quantity of mustard was Q0. There is no shortage of mustard at this equilibrium, because the quantity of mustard demanded is exactly equal to the quantity of mustard supplied (both are equal to Q0). The first explanation for the shortage is climate change, which will have reduced the supply of mustard to S1. The market would move up to a new equilibrium, where the supply curve S1 meets the demand curve D0. The price will increase to P1, and the quantity will decrease to Q1. Does that cause a shortage? No, because the quantity of mustard demanded is still exactly equal to the quantity of mustard supplied (both are now equal to Q1). The second explanation is an increase in demand for French Dijon mustard. This arises because the price of a substitute (yellow mustard) increased, and Dijon mustard was now relatively cheaper. That will have increased to demand curve to D2. The market would move to a new equilibrium, where the supply curve S1 (because of the first explanation) meets the demand curve D2. The price will increase even more, to P2, and the quantity will increase to Q2. Does that cause a shortage? Again, no, because the quantity of mustard demanded is still exactly equal to the quantity of mustard supplied (both are now equal to Q2). What about the third argument? That isn't going to cause any change in the market, unless the French suddenly became even greater mustard consumers than before. The article doesn't say that, so the French people's love for mustard is already captured in the original demand curve.

The France24 article is missing a key point here. You get a shortage when the price is below the equilibrium price. If the market adjusts, there will be no shortage (because quantity demanded will be equal to quantity supplied). The shortage arises because the market price doesn't adjust (or doesn't adjust enough). This is illustrated in the diagram below. Say that we still have the decrease in supply (from S0 to S1) and the increase in demand (from D0 to D2), but that the market price stays at the original equilibrium price P0. Now, with the lower supply, sellers will only supply QS mustard at the price of P0. And, with the greater demand, consumers will demand QD mustard at the price of P0. The difference between QS and QD is the shortage (more mustard is demanded than there is mustard available).

So, while the changes in supply and demand created the conditions for the shortage of French mustard to form, it is actually the failure of the price to adjust that is the real cause of the shortage. If the price had adjusted (and increased), there would be no shortage at all. What stopped the price from adjusting? The article doesn't give any indication (because presumably, they never thought that price was the problem). However, it is likely that the sellers were simply reluctant to increase prices due to not wanting to make their customers angry. However, it's not clear that was really much of a solution. If that was the sellers' reasoning, then they simply chose to have customers who got angry about missing out on mustard (due to the shortage), rather than customers who got angry about higher prices.

[HT: Marginal Revolution]