The pandemic 'baby bust' in other countries

Last November, I wrote a post about the supposed lockdown 'baby boom' in New Zealand, noting that:

...while there has certainly been an increase in births, it is hardly a 'baby boom' (unless you have an extraordinarily liberal interpretation of what constitutes a boom). And, it is hard to make a case that it was caused by lockdown...

The fertility experience of other countries through the pandemic has been quite different from New Zealand's as outlined in this paper by Tomas Sobotka (Vienna Institute of Demography) and co-authors. They use Short-Term Fertility Fluctuations data from the Human Fertility Database, which includes monthly data on the number of births by country. Their paper was written in March last year, so it only includes data up to January 2021, and they exclude countries that had not yet reported December 2020 data, leaving them with 22 countries, mostly in Europe (plus the US, South Korea, and Taiwan). To overcome seasonality in the data, they compare the number of births in each month with the same month one year earlier (this short-term approach also mostly overcomes structural changes in the size of the female population of reproductive age, which won't change drastically from one year to the next). What they find is a substantial decline in the number of births across these countries as a whole, neatly summarised in Figure 14 from the paper:

A value of zero in the figure would mean no change in births from one year earlier. Clearly, there is a bigger decrease in births on average, particularly from October 2020 onwards (which would be the number of babies conceived from January 2020 onwards, when the pandemic was getting underway). However, not all countries had decreases in births (notice that Finland actually had more births over this period than twelve months earlier). And, there isn't a sudden drop-off in births on average either, so rather than the pandemic creating a sudden and large fertility shock across these countries, it appears to have mostly accelerated existing downward trends in fertility.

It would be really interesting to follow up on this work with more recent data, and data across more countries (which will have now reported births through this period and beyond). As far as I can see, Sobotka et al. have not yet done so.

Is side-loading a bigger issue than we realise?

Back in January 2020, I posted about some of my research (with Matt Roskruge of Massey University and Peter Miller of Deakin University) on pre-drinking and the night-time economy. The main aspects of that research are now forthcoming in the journal Drug and Alcohol Review (but you can read an ungated report on the research here). As a supplementary research question, we looked at the prevalence of side-loading (which we defined as the consumption of alcohol during a night out or event, occurring at a location other than a licensed venue or a private home). Side-loading has received much less research attention than pre-drinking, and that may be because most entertainment precincts in western developed countries have liquor bans or public drunkenness laws in place that should limit the extent of that behaviour.

Now, our research on side-loading has just been published in the journal Addictive Behaviors Reports (for ungated results, see the earlier HPA report on our research here). Based on our sample of 469 pedestrians randomly sampled from people out in Hamilton's night-time economy, we found that:

A large majority (84.4%) of the research participants had engaged in pre-drinking, meaning that 93.8 percent of those who had consumed any alcohol that day had been pre-drinking.

Compared with pre-drinking, a substantially smaller proportion of research participants had engaged in side-loading (82/469 = 17.8% of research participants, and 82/413 = 19.9% of drinkers). Of those engaging in side-loading, the majority did so in a car (61.0%), with smaller proportions engaging in side-loading in the street (17.1%), a carpark (12.2%), or somewhere else (13.4%).

So, while side-loading is nowhere near as prevalent as pre-drinking, it was still engaged in by over one in six people, and often in cars or in carparks. We also found that men were significantly more likely to engage in side-loading than women, and pre-drinkers were more likely to side-load than non-pre-drinkers. The second surprising thing we found was a lack of an association between side-loading and intoxication (as measured by breath alcohol content, measured using a breathalyser):

...engaging in side-loading behaviour is not statistically significantly associated with breath alcohol content in any of the models. The coefficient is small, and the sign is inconsistent across models. In contrast, pre-drinking is statistically significantly associated with higher breath alcohol content... pre-drinking is associated with 258 mcg/L higher breath alcohol content when considering the full sample, and 167 mcg/L higher breath alcohol content in the sample of drinkers.

How is it that pre-drinkers are more intoxicated than non-pre-drinkers, whereas side-loaders are not more intoxicated than non-side-loaders? We hypothesise that:

...as the overall effect on intoxication was not significant, it is possible that side-loading is not used as a method for drinkers to enhance intoxication, but may merely be a means of sustaining a target level of intoxication... As drinkers may use side-loading as a substitute for purchasing drinks at a bar or night club, the number of drinks consumed in total (and hence intoxication) may not change, only the location of the drinking. This potential role of side-loading as a substitute may arise through the same price-disparity mechanism that contributes to pre-drinking behaviour, i.e. the large disparity in the price of alcohol between on-licence outlets (night clubs, bars, or restaurants) and off-licence outlets (bottle stores, or supermarkets)... 

Unfortunately, as I mentioned above, side-loading wasn't the main focus of our research, and so we couldn't really answer questions of why side-loading was so prevalent in our sample. Our next forays into the night-time economy are going to have to look at side-loading behaviour in greater detail.

Read more:

• The temporal gradient of intoxication in the night-time economy
• Pre-drinking and the night-time economy

Just bought the farm (or rather not, if you understand dynamic supply and demand)

In my ECONS101 class, we teach a model of dynamic supply and demand that explains fluctuations in market prices, and has an exploitable business implication where, if a businessperson can recognise the cycle, they can profit significantly from capital gains. The model is best explained (as many models are) using a story. In this case the story goes like this:

Consider a perfectly competitive market, as shown in the diagram on the left below. The diagram on the right will track changes in firms' profits over time. Initially (at Time 0) the market is at equilibrium (where demand D0 meets supply S0) with price P0, and firms are making profits π0. Now say there is a permanent increase in demand at Time 1, to D1 (this is just one way to kick off the cycle, but not the only way). Prices increase to P1, and firm profits also increase (to π1). There are no barriers to entry (this is a perfectly competitive market), so the higher profits encourage new firms to enter this market. Supply increases to S2 (more producers) at Time 2. Price falls to P2, and firm profits also fall (to π2). Now, at Time 2 profits are low and some firms will exit the market (no barriers to exit because this is a perfectly competitive market). Supply decreases to S3 (fewer producers) at Time 3. Price increases to P3, and firm profits increase to π3. As you can see from the profits over time (in the right-hand diagram), a cycle of high profits-low profits-high profits- etc. is created.

Now, as I said, the implication of this model is that you can exploit it for capital gains. If prices (and profits) are high, that is a good time to get out of the market (and sell your firm for a high price). But if prices (and profits) are low, that is a good time to get into the market (since you could buy a firm for a low price). This is what we refer to as a 'hit-and-run' business strategy. Hit the market when prices and profits are low, and run when prices and profits are high.

Now, as I discuss in my ECONS101 class, there are some important things that must be true of a market for this strategy to work. First, it needs to be a perfectly competitive market (which few markets are). Second, the long-term the prospects for demand in this market must be good (or at least, stable), because you want to be sure that you don't buy into a failing market. And third, other business buyers and sellers must not have already realised the profit opportunities in this market. It is this third condition that should be the most problematic, because surely businesspeople can't be exploited in this way?

That brings me to this New Zealand Herald article from last week:

Data just released from the Real Estate Institute of New Zealand shows there were 256 fewer farm sales for the three months to December last year than for the three months ended December 2020 - a 46.6 per cent drop.

Comparing the same three month period the median price per hectare for all farms has risen by 39 per cent to $37,980.

Institute rural spokesman Brian Peacock said sales figures reflected an easing in volumes compared to similar periods over the last three years, with all categories being impacted.

"Logic would suggest that due to the very strong forecast for the dairy payout for the 2021-2022 season and particularly strong prices for beef, lamb and horticultural products, fewer rural properties have been available for sale as landowners - as would be expected - have retained properties in order to capitalise on the current high product returns.

Ok, so farmers are holding onto their farms now, because prices are high. On the surface, that seems sensible. However, based on our model of dynamic supply and demand outlined above, this is the time to be getting out of the market, selling farms for a high price. In terms of the three conditions for taking advantage of this, the market for agricultural products is about as close to a perfectly competitive market as you can get. The long-term demand outlook for agricultural products is good, or at least not falling. What about the third condition? Well, farmers are selling farms when prices and profits are high. And if they are doing that, then it is likely that they will be trying to sell their farms when prices (and profits) are lower.

All of this suggests that there is an exploitable business opportunity here, for anyone who can raise finance (which might be a key constraint, since banks will be less willing to lend when prices are low) to buy farms when dairy (and other commodity) prices are low (disclaimer: this is not investment advice - you should consult a professional advisor before you buy a farm!). Of course, that means waiting until we are out of the current expansionary part of the cycle, and farmers return to selling up.

Read more:

• The rise and fall of craft beer?

The haggling coordination game

The TVHE blog had an interesting post about haggling earlier this week:

[Gulnara]

On a recent trip to my beautician – link to her website below – I started negotiating the price of my visit. However, I quickly caught myself doing so and stopped. She understood where I was coming from, as she is also from the former Soviet Union, where such haggling is a normal part of daily life. But that isn’t the case in a country like New Zealand – which is why we both put a stop to it.

So why is haggling culture so different in different countries, and what are the economic consequences of this?

[Matt]

That is really interesting Gulnara. Such bargaining does depend on the expectations of consumers and producers – so bargaining cultures will tend to support individuals bargaining while societies that do not do that will make it costly.

This strategic complementarity implies that both societies with bargaining and those without are “equilibrium” outcomes – where people’s incentive is to do what everyone else is doing. We call these bargaining and non-bargaining equilibrium “states of the world”...

Strategic complementarity implies that there is a coordination game here. We can show how it works, and how there are two equilibrium outcomes, using some simple game theory. Consider two players, the buyer and seller, decided whether to haggle over prices. The game is outlined in the payoff table below. If the seller expects to haggle, they set a relatively high price, which might put off buyers who do not haggle. Hence, the seller gets a lower profit and the buyer is worse off as well. If the seller expects to haggle and the buyer haggles, then both benefit from the sale. On the other hand, if the seller doesn't expect to haggle, they set a lower price. If the buyer haggles, the sale may go through, or the seller may get pissed off and choose not to proceed. Hence, the seller gets a lower average profit and the buyer is worse off as well (not just by the chance that the sale doesn't go through, but because of the possibility of social sanctions on them). As Matt notes in the TVHE post linked above:

The willingness to haggle on both the customer’s and the firm’s behalf depends on whether it is something they expect other people to do – it feels pretty stink to go and haggle just for the other person, and other customers, to look down their nose at you. However, this is more than just some concern about underlying social judgment – the act of haggling is something the firm would like to be prepared for, and the act of undertaking haggling puts pressure on these other customers to take on the cost of haggling themselves.

Finally, if the seller expects not to haggle, and the player doesn't haggle, then both benefit from the sale.

We can establish the locations of Nash equilibriums using the 'best response method'. To do this, we track: for each player, for each strategy, what is the best response of the other player. Where both players are selecting a best response, they are doing the best they can, given the choice of the other player (this is the textbook definition of Nash equilibrium). In this game, the best responses are:

1. If the buyer chooses to haggle, the seller's best response is to expect to haggle (since 10 is a better payoff than 8) [we track the best responses with ticks, and not-best-responses with crosses; Note: I'm also tracking which payoffs I am comparing with numbers corresponding to the numbers in this list];
2. If the buyer chooses not to haggle, the seller's best response is not to expect to haggle (since 10 is a better payoff than 8);
3. If the seller chooses to expect to haggle, the buyer's best response is to haggle (since 10 is a better payoff than 5); and
4. If the seller chooses to not expect to haggle, the buyer's best response is not to haggle (since 10 is a better payoff than 4).

Notice that there are two Nash equilibriums in this game: (1) where the seller expects to haggle and the buyer haggles; and (2) where the seller expects not to haggle and the buyer doesn't haggle. The problem now, as with all of these sorts of coordination games, is: in which equilibrium will we end up? Sometimes this can be solved through government enacting laws. Think about which side of the road we drive on. It is a coordination game, where you want everyone to drive on the same side of the road, but it doesn't really matter too much which side that is.

In the case of haggling though, the TVHE blog provides some discussion about the consequences of being in one equilibrium or the other (and is worth reading for that reason). They conclude that:

...with price discrimination and tacit collusion, we’ve outlined two of the possible mechanisms that may differentiate market outcomes in countries with active market bargaining and those without.  Both of these arguments appeared to show bargaining in a favourable light – however, they also did point to trade-offs that may reverse this, namely the cost of bargaining, the proliferation of excess product variety, and broader related distributional consequences.

Unfortunately, that doesn't really answer the question of how we end up in one equilibrium or the other. So, let me venture a hypothesis: trust. In countries with relatively high levels of trust between buyers and sellers, the buyers can trust that sellers are not setting high prices that require haggling. The sellers realise this, and recognise that it is in their best interest not to set such high prices. On the other hand, in a lower trust society, a seller setting a lower price would make themselves worse off as they have set a lower starting point for the haggling process.

The problem with this hypothesis is that, if true, it simply shifts the question of 'why' on step further back. Instead of wondering why we are in a haggling or non-haggling equilibrium, we are left wondering why we are in a low-trust or high-trust environment. Unfortunately, that's about as far as the theory can get us. To understand more, we would need to look at some data.