Door-to-door selective collection in Hungary: does convenience create more waste? An in-depth look at the Corvinus–ELTE study

Door-to-door selective collection has for years been one of the main tools of Hungarian waste management: a blue and a yellow bin at the gate should, in principle, make sorting easier and send more paper and plastic to recycling. A new study by Zalán Márk Maró (Corvinus University of Budapest) and József Ráti (ELTE, Ludovika University of Public Service) raises an uncomfortable question: what if convenience makes not only sorting easier, but consumption and disposal too?

The paper appeared in volume 24 of Environmental Challenges (online on 9 June 2026) and analyses official waste data for 93 Hungarian municipalities between 2012 and 2023. Below we walk through what exactly was measured, what the numbers mean, where caution is warranted, and what it all means for the Hungarian system.

In short: The bin-based form of door-to-door selective collection was associated with an average of 11.76 kg more selectively collected waste per resident per year during the COVID-19 period, while mixed waste did not fall in a statistically significant way. The authors read this as a “disposal ease” bias, but the data allow only an uncertain conclusion about total waste.

What did the study examine, and why is COVID the key?

The authors looked at bin-based door-to-door selective collection. The paper describes it as a “double-bin” system in which households receive two separate containers, one for paper and one for plastic – a description that only partly matches Hungarian practice, as we discuss in the critical section. Bag-based door-to-door collection was left out, because Ráti’s earlier research found no measurable effect from it. Glass is not part of the treatment either, as it is typically collected at drop-off “islands”.

The method is a two-way fixed effects (TWFE) regression within a difference-in-differences (DiD) framework. In plain terms, the model compares each municipality with its own past (municipality fixed effects) and strips out year-to-year swings that hit the whole country equally (year fixed effects). Per capita taxable income is included as a control.

The trick is the pandemic. The authors treat COVID-19 as an external shock: restrictions arrived everywhere at once and independently of local waste policy, while home consumption, online shopping and packaging-heavy home delivery surged. The question is therefore whether municipalities that already had bin-based selective collection before the pandemic reacted differently to the same shock than those that did not.

The sample structure matters for what follows:

• Treatment group: according to the text, 23 municipalities where bin-based selective collection was in place before the pandemic.
• Control group: 70 municipalities without such a system.
• By size: all 7 large towns (50,000–100,000 residents), all 8 county seats and major cities (over 100,000) and Budapest are in the treatment group; the control group consists only of small and medium-sized settlements.
• Sample averages: 206.40 kg of mixed and 30.69 kg of selectively collected waste per person per year.

The data come from the Hungarian Central Statistical Office (KSH), compiled from mandatory reports by municipalities and licensed operators, based on weighbridge-measured tonnages.

The main results in numbers

The study’s central finding comes down to two figures:

• Selective waste: +11.76 kg per person per year in municipalities with bin-based selective collection during the COVID period, relative to the control group. This is significant at the 5% level (standard error: 5.32).
• Mixed waste: −8.64 kg per person per year, but this cannot be statistically distinguished from zero (standard error: 7.15).

Income was not significantly associated with either waste stream, so the gap is not explained by higher consumption in wealthier municipalities.

It helps to put the 11.76 kg in proportion. The full-sample selective average is 30.69 kg, and the treatment-group average is 40.03 kg. The estimated surplus is therefore roughly 29% of the average selective volume in treated municipalities – a substantial shift, not a rounding error.

The authors’ conclusion: since the selective stream grew and mixed waste did not demonstrably shrink, the surplus is not simply a transfer from the mixed bin to the recycling bin, but at least partly new waste.

A misreading of the city figures: what does 11.71 kg in Miskolc mean?

Some of the first Hungarian media reports presented city-level “surpluses”: 12.13 kg in Budapest, 12.45 kg in Pécs, 12.22 kg in Debrecen, 11.71 kg in Miskolc, 11.81 kg in Szeged and 12.15 kg in Győr. That is a misreading.

These values come from Table 5, a leave-one-out sensitivity check. The authors removed each of the six largest cities from the sample one at a time and re-ran the model. So 11.71 kg does not mean Miskolc generated that surplus; it means that without Miskolc, the estimated effect for the whole sample is 11.71 kg. The study reports no city-level effects at all.

Read correctly, this is good news for the method: whichever large city is left out, the estimate stays between 11.71 and 12.45 kg, so the result is not driven by a single outlier.

How did the authors test the result?

The study runs three checks:

1. Parallel trends chart. Figure 1 shows selective waste in both groups from 2012. According to the authors, the trajectories rose similarly between 2013 and 2019, which is the core assumption of the DiD design.
2. Placebo test. The model was re-run with a fictitious “treatment period” (2016–2018). The placebo effect was small and not significant (selective: 1.18 kg; mixed: −0.71 kg), so no diverging pre-pandemic trend was detected.
3. Size-by-year effects. Because bin-based collection operates mainly in larger municipalities, the authors allowed each size category to follow its own time path. The selective effect remained positive and significant, rising to 21.54 kg; the mixed-waste effect (−15.54 kg) remained insignificant.

What it shows and what it does not: a critical reading

The study’s strengths are that it rests on official measured data, uses fixed effects and several robustness checks, and states its limitations openly. From a practitioner’s perspective, however, the interpretation deserves a few refinements.

What effect does the model actually measure?

The treatment variable (having a bin-based system) is constant over time for each municipality, and the “treatment” is the COVID period. The model therefore does not measure what happens to a municipality’s waste when it introduces bin-based selective collection, but whether municipalities that already had the system responded differently to the pandemic-driven consumption shock. That is a subtle but important distinction: the 11.76 kg is not the system’s general, “normal times” effect.

The exact years of the COVID period are not defined separately in the text; judging by the figure it starts in 2020, and 2023 is also in the sample.

How comparable are the two groups?

This is the most sensitive point. Every municipality above 50,000 residents is in the treatment group, and none is in the control group. Fixed effects remove differences in levels, but not necessarily differences in dynamics. The size-by-year robustness check tries to address this, but since the largest categories contain no control municipalities, that estimate effectively rests on the small group of treated small and medium-sized settlements (2 + 6). This explains why the effect nearly doubled (21.54 kg) while uncertainty rose sharply (standard error: 10.37).

Was it really a two-bin system?

This is one of the study’s most important inaccuracies, and one any Hungarian practitioner will notice at once. The authors describe treated municipalities as giving households separate containers for paper and for plastic. Such a two-bin (blue and yellow) system, however, typically operates in Hungary only in Budapest. Elsewhere – including most of the county seats and major cities in the sample – paper, plastic and metal go into a single shared selective bin; local ordinances set it up this way, and MOHU’s bin rollout programme also supplies one bin for paper, plastic and metal together.

Since every large town and county seat ended up in the treatment group, the “treatment” studied is almost certainly not separate paper and plastic bins, but whether door-to-door selective collection is bin-based or not (bags or drop-off islands). This is reinforced by the explicit exclusion of bag-based collection. It is also possible that “double-bin” means a selective bin alongside the mixed-waste bin, but the paper’s text contradicts this.

The inaccuracy does not invalidate the main result, but it changes how it should be read. The measured gap is the difference between bin-based and bag/island-based collection – which fits MOHU’s own experience that switching from bags to bins raised selectively collected volumes by 20–40% in the areas concerned. A single large shared bin also absorbs far more e-commerce cardboard than a bag, strengthening the capacity explanation discussed below.

Other methodological notes

A minor reporting discrepancy: the text mentions 23 treated and 70 control municipalities, while the rows of Table 2 add up to 24 treated and 69 control.

Were the trends really parallel?

In Figure 1 the treatment group is consistently higher, but the gap is not constant: the control group caught up considerably in 2017–2019. After 2020 the gap widens because the treatment group keeps rising (roughly from 50 to 55 kg, reading the chart) while the control group falls (roughly from 45 to 42 kg). Part of the estimated effect therefore comes from a decline in selectively collected volumes in municipalities without the bin system. The placebo test eases this concern but does not fully remove it.

Did total waste really increase?

The study’s conclusion states that the selective surplus exceeds the (insignificant) reduction in mixed waste, implying a net increase in total waste. On point estimates this holds: +11.76 − 8.64 = roughly +3.1 kg per person per year. Yet that is only about 1.3% of the combined mixed and selective volume (around 237 kg per person per year).

The uncertainty, however, is large. The 95% confidence interval for the mixed-waste effect runs roughly from −22.7 to +5.4 kg. The data are therefore consistent both with a meaningful reduction and with a slight increase in total waste. The fair wording is: the selective stream clearly grew, mixed waste did not demonstrably fall, and the change in total waste cannot be reliably determined.

Could there be other explanations for the “new” waste?

The authors see the perception bias as the main mechanism, but acknowledge that without composition data the mechanism cannot be proven. From an operator’s perspective, at least three complementary explanations deserve to be separated in future research:

• Capturing previously unmeasured flows. In small settlements, part of the paper and cardboard has traditionally disappeared into solid-fuel stoves or other unreported channels. If the bin pulls this volume into official statistics, it shows up as “new waste” in the data, when in reality it has merely become visible.
• Capacity. A 240-litre bin at the gate that takes paper, plastic and metal together absorbs a flood of e-commerce boxes more easily than an overflowing drop-off island. Where the island was full, cardboard may have ended up in mixed waste, in a stove or dumped illegally – partly outside the measured selective data as well.
• Mis-sorting. The KSH data measure collected tonnage, not the amount actually recycled. If more non-target material ends up in a convenient yellow bin, it increases selective tonnage but not sorting-plant output. The authors themselves note that contamination data were not available. As our piece on the European paper recycling rate also stressed, the quality of separate collection matters as much as the quantity.

None of these refutes the convenience bias – but each suggests that the “+11.76 kg” may reflect a mix of mechanisms.

Convenience, rebound and the disposal ease bias

The theoretical core of the study is the Perceived Disposal Ease Bias (PDEB): when disposal and sorting become effortless, consumers feel the environmental burden of consumption less, and more material passes through the household. It is a variant of the circular economy rebound effect – the same logic we discussed in the context of second-hand clothing at a festival vintage market: if the “green” choice adds to rather than replaces the old one, the net benefit melts away.

The international literature supports the direction in several ways:

• North Carolina: using a DiD design very similar to this study, Maier, Geyer and Steigerwald (2023) found that introducing curbside recycling increased household solid waste by 6–10% over 1999–2019, under flat-rate charging.
• Lab experiments: Catlin and Wang (2013) showed that the mere option to recycle leads to greater resource use; Sun and Trudel (2017) found that the good feeling of recycling can outweigh the bad feeling of wasting.
• Warm glow: van Doorn and Kurz (2021) showed that the positive feeling of recycling can paradoxically make people more wasteful.
• Packaging intensity: according to Kim et al. (2022), goods delivered by courier can require up to 4.8 times more packaging than those bought in a shop – which may have amplified the effect in the Hungarian COVID-period data.

An interesting comparison: the Hungarian net point estimate (about 1.3% of total volume) is much smaller than the US 6–10%. This suggests that if there is a Hungarian rebound effect, it is more modest, or that in the Hungarian data it is mixed with other mechanisms.

Why is the result different from the Italian PAYT experience?

The study’s most important policy message comes from this comparison. Italian studies – mainly from Emilia-Romagna – show that door-to-door collection combined with pay-as-you-throw (PAYT) pricing reduced residual and total waste, with the literature typically reporting reductions of 10–20%.

According to the authors, the two findings do not contradict each other, because they activate different mechanisms:

• Under PAYT, disposal becomes financially salient, so households have a reason to prevent waste.
• In a bin-based selective system with no price signal, only the effort is reduced; nothing encourages lower quantities.

The methods also differ: the Italian studies mostly compare the same municipality before and after a reform, which also bundles in tariff changes, communication campaigns and organic waste collection.

Lessons for door-to-door selective collection in Hungary

In Hungary, household waste fees have been administratively frozen for years, with the fee at most linked to container size – a very weak quantity signal. By the study’s logic, this is exactly the setting in which a convenience bias can operate. What follows from this?

1. As convenience grows, measurement must keep pace. From 2025, MOHU moved to emptying selective bins every two weeks instead of monthly in settlements with more than 5,000 residents. Professionally this is justified, but in light of the study the yardstick of success cannot simply be rising selective tonnage. Combined per capita mixed and selective volumes, and the share of sorting residues, should be tracked as well.

2. Collected does not mean recycled. The authors recommend regular waste composition audits, especially in newly served municipalities. Transparency is a recurring theme in the Hungarian debate, as our analysis of the government review of the waste management concession also showed.

3. Communication should be about prevention, not just sorting. The study explicitly recommends that infrastructure rollout be accompanied by campaigns that put waste prevention first, countering the idea that recycling alone equals responsible behaviour.

4. Packaging must be reduced at the source. Much of the COVID-period surplus was probably e-commerce paper and plastic packaging. A collection system cannot fix that on its own, but source-side regulation can: under the PPWR, which started to apply on 12 August 2026, empty-space limits will curb overpackaging from 2030, and reusable packaging systems are moving into e-commerce as well.

5. Post-2024 data must be read differently. The study period ends in 2023, the year the MOHU concession began on 1 July. From 1 January 2024, the mandatory deposit return system removed a large share of deposit-bearing PET bottles and metal cans from the yellow bin. A similar study for the post-2024 period would be measuring a selective stream with a different composition.

6. Budapest is a separate story. Budapest appears in the sample as a special case, and it is probably the only municipality in the sample with a genuine two-bin (separate paper and plastic) system. The capital’s system operates under its own logic (MOHU Budapest), so experience from Budapest and from the rest of the country should not be lumped together – a point that recurs in our coverage, for example of collection problems in Szentendre. The result remained stable when Budapest was excluded (12.13 kg).

7. Bag systems are not equivalent to bin systems. Many municipalities launched door-to-door collection with bags. The authors excluded bag systems because earlier research found no measurable effect; this also means the control group is not necessarily “without selective collection”, but partly made up of municipalities using bags or drop-off islands.

What can households do?

The study’s message to residents is simple: the recycling bin is not a free pass. The waste hierarchy still says the best waste is the waste never created.

• Where possible, choose consolidated, less frequent online orders and pick-up points.
• Prefer products with less or reusable packaging.
• Put only target materials in the selective bin – mis-sorted waste becomes residue at the sorting plant.
• Deposit-bearing bottles and cans belong at a REpont return point, not in the yellow bin.

Summary

Maró and Ráti’s study is important and fills a gap: it is the first Hungarian quasi-experimental study to measure the behavioural side effects of door-to-door selective collection. Its strongest finding is reliable: municipalities with bin-based selective collection collected substantially more selective waste during the COVID period, while mixed waste did not demonstrably decrease.

It should be clarified, though, that outside Budapest the system studied is not two-bin but single shared-bin selective collection. That total waste also grew, however, is only weakly supported by the data, and the “+11.76 kg” may reflect data-coverage, capacity and quality factors alongside the convenience bias. The practical lesson still stands: convenient collection is necessary but not sufficient. Without quantity-based incentives, source-side packaging regulation, prevention-focused communication and transparent measurement of total waste, even a well-functioning separate collection system can easily become a licence to consume.

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Door-to-door selective collection – frequently asked questions

How much more selective waste did bin-based door-to-door collection generate?

On average 11.76 kg more per resident per year during the COVID period, compared with municipalities without the system. Zalán Márk Maró and József Ráti analysed official data for 93 Hungarian municipalities from 2012 to 2023 using a two-way fixed effects difference-in-differences model. The result is significant at the 5% level and held when each of the six largest cities was excluded in turn.

Did mixed waste decrease in municipalities with recycling bins?

Not in a statistically detectable way. The model estimated a reduction of 8.64 kg per resident per year, but it cannot be distinguished from zero. On point estimates, total waste may have risen by about 3 kg, yet the uncertainty is so large that the data are consistent with both a meaningful decrease and a slight increase, so the overall change cannot be reliably determined.

What is the Perceived Disposal Ease Bias?

It is a behavioural bias in which easy disposal lowers the perceived environmental cost of consumption. When sorting becomes effortless, households feel less need to cut consumption or packaging, so more material passes through them. The phenomenon is a variant of the circular economy rebound effect, which US field studies and laboratory experiments have also reported.

Was the surplus in Miskolc really 11.71 kg?

No, that figure is a misreading. The values attached to city names come from a sensitivity check in which the researchers removed the large cities from the sample one at a time. The 11.71 kg means the estimated effect for the whole sample without Miskolc. The study reports no city-level surpluses, but the stable values show that no single city drives the result.

Why does the result differ from Italian pay-as-you-throw systems?

Because Italian schemes add a financial incentive, while here only convenience increases. In the Italian studies, door-to-door collection was combined with pay-as-you-throw (PAYT) pricing, which made disposal financially noticeable and typically cut waste by 10–20%. A two-bin system without a price signal reduces effort only and gives households no reason to reduce quantities.

What do the researchers recommend for waste policy?

They recommend complementing convenient collection with other instruments. According to the authors, infrastructure should come with prevention-focused communication, regular composition audits, quantity-based pricing and restrictions on single-use packaging. The aim is that better sorting does not become a licence to consume, but goes hand in hand with a reduction in total waste generation.

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🔗 Official sources and references: 👉

• Maró, Z. M., Ráti, J. (2026): Behavioral response to convenience: A natural experiment on door-to-door selective waste collection. Environmental Challenges, 24, 101546. https://doi.org/10.1016/j.envc.2026.101546 – available on ScienceDirect (open access, CC BY-NC-ND)
• Store Insider (6 November 2026): A kényelmesebb szelektív gyűjtés növelheti a hulladéktermelést (in Hungarian). https://storeinsider.hu/cikk/a-kenyelmesebb-szelektiv-gyujtes-novelheti-a-hulladektermelest
• Maier, J., Geyer, R., Steigerwald, D. G. (2023): Curbside recycling increases household consumption. Resources, Conservation and Recycling, 199, 107271.
• Zink, T., Geyer, R. (2017): Circular economy rebound. Journal of Industrial Ecology, 21, 593–602.
• Struk, M. (2017): Distance and incentives matter: the separation of recyclable municipal waste. Resources, Conservation and Recycling, 122, 155–162.

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