The supply-side story behind falling meth prices in New Zealand

Chris Wilkins, Marta Rychert, and Robin van der Sanden (all Massey University) wrote an article in The Conversation last month about the price of methamphetamine:

Methamphetamine has become dramatically cheaper over the past seven years, even as authorities report record seizures, according to the latest New Zealand Drug Trends Survey.

The annual online survey of over 8,800 people who use drugs shows wholesale prices of the illegal and harmful substance (per gram sold to dealers) have fallen by 41%, while street-level “point” prices (0.1 gram retail deals) have dropped by 27%.

The decreasing price of meth is not a new phenomenon. In fact, I wrote about it last year. Wilkins et al. try to tease out the reason underlying the decreasing price. Based on a simple supply and demand model of the market for meth, there are two main possibilities: an increase in supply, or a decrease in demand. Wilkins et al. go through a number of plausible factors on both sides of the market, dismissing each in turn, including:

• sellers feeling that there is less risk of arrest (which would increase supply), but Police report record seizures, which Wilkins et al. argue seems to rule that out;
• less strict enforcement by Police against people found with small quantities of drugs (which would increase supply, but probably demand as well), but that wouldn't affect large sellers;
• decreasing production costs (which would increase supply), but production costs only make up a fraction of the street price; and
• a decrease in buyers (which would decrease demand), but wastewater data suggests that meth consumption has increased.

The last point, that meth consumption has increased alongside the decrease in price, points strongly to an increase in supply as the main change. That doesn't rule out a change in demand, but the increasing consumption tells us that the increase in supply must be greater than any possible decrease in demand. But if it isn't lower risks of arrest, weaker enforcement, or decreasing production costs, that is causing supply to increase in the New Zealand meth market, then what is? Wilkins et al. point to:

...new global sources of methamphetamine supply.

New Zealand and Australia have traditionally sourced methamphetamine from lawless regions of Asia known as the Golden Triangle. More recently, however, growing seizures have been linked to Mexican drug cartels, often transiting through Canada.

Australian authorities say these cartels can supply methamphetamine at less than one-third the price of Asian producers and that about 70% of seized meth now originates from North America.

It may also explain the rising supply of cocaine in New Zealand, with Mexican cartels deeply involved in global cocaine trafficking.

So, new sources of meth have increased the supply, decreasing the equilibrium price, and increasing the quantity of meth traded in the New Zealand market. Wilkins et al. also point to competition:

On top of this, digital drug markets – including darknets and social media sales – may be lowering the cost of finding alternative sellers and better deals, increasing competition and pushing prices down.

Economists often think of competition as a good thing. However, in the market for illegal drugs, that might not necessarily be the case. How can government best respond? Fighting the supply side of the market alone is unlikely to be successful, as I have noted before. The increased supply from new sources make this even more challenging. A renewed focus on reducing demand is necessary as well, and would likely be much more effective in the long run.

Read more:

• Police are not winning the P war - they need to focus on demand
• Evidence that the supply of methamphetamine is increasing
• The coronavirus lockdown and the New Zealand market for illegal drugs
• The increase in methamphetamine use in New Zealand has been driven more by supply than demand

The Strait of Hormuz blockade, trade passes in the Panama Canal, and the cost of imported goods

The New Zealand Herald reported last month:

The war in the Middle East has boosted demand to move vital cargo through the Panama Canal to such an extent that one vessel carrying liquefied natural gas (LNG) paid US$4 million ($6.7m) to skip the line and avoid a wait that can take up to five days, according to an official report.

A surge in such payments has been recorded since the US-Israeli attacks on Iran began February 28, which led to the blockade of the Strait of Hormuz, a critical waterway for one-fifth of the world’s oil and natural gas exports from Gulf countries.

The impact on the price of transits through the Panama Canal is shown in the diagram below. Before the Strait of Hormuz was blockaded, the market for Panama Canal transits was in equilibrium, where demand DA meets supply SA. The equilibrium price was PA, and the quantity of transits was QA. The blockade increased the demand for Panama Canal transits from DA to DB, increasing the equilibrium price of transits from PA to PB, and increasing the quantity of transits from QA to QB.

This increase in the price of Panama Canal transits doesn't just affect the cost of transporting oil or natural gas. Other ships must also pay the higher price. That increases the cost of shipping, which will flow through to the prices of imported goods, as shown in the diagram below. The market was initially in equilibrium, where demand D0 meets supply S0, with a price of P0 and a quantity of imported goods traded of Q0. The higher cost of Panama Canal transits increases the 'costs of production' of imported goods, which decreases supply to S1. This increases the equilibrium price of imported goods to P1, and reduces the quantity of imported goods traded to Q1.

So, it's not just oil and natural gas prices that will be pushed up by the blockade of the Strait of Hormuz. The resulting higher shipping costs will flow through to all sorts of other goods that are traded internationally and require shipping, including and especially those passing through the Panama Canal.

This week in research #124

Here's what caught my eye in research over the past week:

• Greenaway-McGrevy (open access) evaluates the impact of this widespread zoning reform in Auckland on housing starts, and finds that upzoning approximately doubled new dwelling permits per capita within five years

In an otherwise quiet week I have some exciting news. The latest issue of Australasian Journal of Regional Studies (AJRS) has just been published (backdated to December 2025). This issue has four papers (all open access), as well as the editorial:

• Duong et al. examine output divergence and club convergence across 63 provinces in Vietnam during the study period 2010–2023. The question of whether subnational regions move along a single common development path is important because it can help us to understand spatial inequality. In the case of Vietnam, this paper demonstrates that Vietnamese provinces are sorting into convergence clubs, suggesting that subnational growth in Vietnam is shaped by location, investment, and proximity to major economic centres rather than by uniform national catch-up (this paper won the John Dickinson Memorial Award for the best paper published in AJRS in 2025)
• Kanthilanka and Kingwell explore the export grain supply chain across Australian states. They find that grain producers in Australia benefitted from an increase in the velocity of Australia’s export grain supply chains. However, this presents a risk of higher food inflation if a prolonged drought were to strike eastern Australia, unless there is greater investment in grain storage and increased grain production
• Dutta explores the rural urbanisation process and the development of rural non-agricultural activities in West Bengal, India, an area of substantial urban growth. They find that districts with better infrastructure have higher percentages of non-agricultural enterprises employing hired workers, reinforcing the link between infrastructure and non-agricultural activity growth
• Leutwiler examines economic development planning for the Katherine region of the Northern Territory of Australia from 2014 to 2021 and contrasts this with a place-based development approach. This analysis highlights that formal economic strategies in the Katherin region are focused primarily on industries and projects that increase revenue for higher levels of government and large corporations, rather than creating local employment. This paper is important, as it provides justification for place-based development that prioritises local employment, diversification, and more sustainable regional outcomes

Dollar General opening may be a symptom, not a cause, of negative local market conditions

Dollar stores have a bad reputation for negatively impacting local communities (see here and here, for example). Some communities have pushed back, resisting the opening of new stores. One thing that dollar stores are accused of is hurting other local businesses, but is that the case?

That is the question addressed in this new article by Amelia Biehl, Amir Ferreira Neto (both Florida Gulf Coast University), and Juan Gomez (University of Iowa), published in the journal Economic Modelling (ungated earlier version here). They focus on the opening of new Dollar General stores in Florida, using data from Dun and Bradstreet's National Establishment Time Series dataset between 1990 and 2019. Over that period, there were a lot of store openings, with the state going from 202 stores to 1014 between 2000 and 2019. That's about one store per 23,000 people in Florida by the end of the period.

Biehl et al. look at the impact on revenue, employment, and probability of firm closure, by comparing firms operating within a half-mile of a new Dollar General store opening (the 'treated firms'), with firms operating between one and 1.5 miles away (the 'control firms'), in what is termed a difference-in-differences analysis. Biehl et al. limit their focus to firms with fewer than 50 employees, as they are more likely to be impacted by the opening of Dollar General. This still results in a sample of over 7.5 million observations of over 1.1 million firms. The hypothesis is that these small firms operating in close proximity to the new Dollar General store will be affected by its opening, whereas small firms located further away will not be.

Their results are summarised in Figure 4 from the paper, which shows an event study version of the analysis:

That figure shows the impact on each variable (revenue, employment, and probability of firm closure), year-by-year, from eight years before the store opening to eight years after. Focusing on the time after the store opening (from time zero onwards, because time -1 is the year of store opening), the positive and significant effects show that employment increases, revenue increases, and the probability of firm closure increases for treated firms compared with control firms after the store opening. These results are consistent with the overall difference-in-difference results.

However, there is a slight problem here. One of the assumptions of difference-in-differences is that there are parallel trends - that treated and control firms would have followed similar paths in terms of revenue, employment, and probability of closure, if no Dollar General store had opened. Obviously, this is impossible to establish for sure, because we don't know the counterfactual (we don't know what would have happened if Dollar General had not opened). But there is one indicator that is often used to argue in favour of parallel trends, which is to look at the estimated coefficients from the time period before the treatment started. If those coefficients are statistically insignificant, it establishes that there is little evidence that the treatment and control firms were diverging before the Dollar General even opened. But for this analysis, that isn't the case. Take a look back at Figure 4 shown above. There is a clear trend in the coefficients even before Dollar General opened, and that trend appears to continue through to the period after the Dollar General opens. If anything, the coefficients at time -1 (which is the year of opening) are unusually inconsistent with the coefficients on either side of them.

The failure of this analysis to consider a violation of the parallel trends assumption should make us very cautious about taking these results at face value. At least, I don't think they should be interpreted as showing that Dollar General leads to the closure of some local businesses, with the surviving firms having higher revenues and employment (which is how Biehl et al. interpret their results). Instead, I think it possibly shows that Dollar General stores locate in areas where stores are already closing (notice in Figure 4 that probability of closure is already positive and statistically significant for treated firms compared with control firms before the Dollar General opens).

Biehl et al. go on to look at the impacts on firms by industry and by retail category. However, given that their headline results don't really show what they are purported to show, I would place even less weight on the industry-specific results. Besides which, at that stage of the analysis they are doing multiple comparisons, meaning that some of their results might show up as statistically significant simply by chance, which they haven't adjusted for.

Overall, the results from the main analysis in this article are consistent with Dollar General finding new locations where there are open storefronts (because other firms have already closed), and setting up shop in those locations. So, it may be that it isn't the Dollar General that causes firm closures, and higher revenue and employment for surviving firms, but something else like local market conditions more generally. Considering that possibility, a Dollar General opening would be a symptom of those negative local market conditions, not a cause of them.