17.17% of Citizens Admit Paying “Extra Money” for Public Services: Reading the Anti-Corruption Behavior Index

We usually picture corruption as something huge: billions in value, senior officials, a courtroom full of cameras. But there is another side to corruption that is far more everyday, and precisely because it is everyday, it slips under the radar: extra money to speed up paperwork, a “thank you” that is practically demanded, or a little grease so things don’t get complicated.

The 2024/2025 Crime Statistics from BPS (Statistics Indonesia) include two measures that spotlight this side, drawn from the Anti-Corruption Behavior Survey (SPAK). Let’s look at what the data says, and what it doesn’t.

Two indicators from SPAK

1. The Anti-Corruption Behavior Index (IPAK). It runs from 0 to 5. The closer to 5, the stronger the anti-corruption behavior in society. The closer to 0, the more tolerant (permissive) people are toward corruption. The result: IPAK fell from 3.92 in 2023 to 3.85 in 2024, a drop of 0.07 points. IPAK is built from two dimensions: perception (how people judge habits in their family, community, and the public) and experience (direct experience of accessing public services).

2. The share of people who dealt with public services and handed over money, goods, or favors outside the rules. It rose from 16.33% in 2023 to 17.17% in 2024. BPS flags this as an important note because it points to growing permissiveness toward small-scale corruption, and to gaps in the public service system that can be exploited, whether on the citizen’s initiative or at an official’s request.

Put simply: roughly one in six people who deal with public services say they have given something outside the rules.

What is measured, and what is not

As always, let’s check how it was measured.

• What is measured is petty corruption: bribery, extortion, and nepotism in everyday public services. BPS states explicitly that the survey does not cover grand corruption. So IPAK says nothing about corruption at the policy level, in big procurement, or in abuse of power by senior officials.
• The sample is limited. In 2024, SPAK was carried out in 186 regencies/cities across 38 provinces with about 11,000 households as respondents. Results can only be presented at the national level, not broken down by province or region.
• It rests on admissions and perceptions. Admitting to paying outside the rules is a sensitive topic. Respondents may hold back out of shame or fear, so the figure may be lower than reality (social desirability bias). Or the reverse: some respondents may interpret “extra fees” differently.
• Giving is not the same as being asked. The indicator mixes two situations: citizens who offer on their own, and citizens who are asked or pressured. From a single 17.17% we cannot separate them. Yet for policy they differ: the first is about a permissive culture, the second about officials’ behavior and oversight systems.

Two datasets moving differently

It is interesting to compare SPAK with police incident data. In the Polri registration data, recorded corruption cases rose slightly from 483 to 512 in 2024. BPS says this increase deserves special attention because corruption, as white-collar crime, causes large-scale losses.

The two figures cannot be compared directly. 512 is the number of corruption cases handled and recorded by police (generally cases that have drawn attention and met the requirements for enforcement). 17.17% is the share of citizens who say they experienced petty bribery. The scale, definitions, and sources are very far apart. But that is exactly why the comparison teaches something: what citizens experience daily and what authorities handle are two entirely different layers of the same problem. Many small payments will never become criminal cases, which is why surveys like SPAK are needed to see the layer that goes unrecorded.

Why small-scale corruption still matters

It is tempting to wave off small payments as “not much”. From a criminology and public policy standpoint, petty corruption has several serious effects:

• Normalization. When “grease money” is seen as normal, the line between what is acceptable and what is a violation blurs. IPAK itself measures this permissiveness, and its decline is a signal that tolerance has crept up.
• Unfair burden. Small payments weigh more on low-income groups, who depend most on public services and have the fewest alternatives.
• Erosion of trust. Paying “extra” makes people trust institutions less, which in turn reduces willingness to report, as we see in the low reporting rate for crime.
• A doorway to bigger corruption. A culture that accepts small grease payments is fertile ground for larger practices.

What can be done?

The data itself offers no solution, but it points to several policy questions:

1. Which services are most vulnerable? A breakdown by service type (police, document processing, education, health, licensing) needs to be analyzed so interventions hit the right target.
2. Does digitizing services reduce face-to-face contact that opens room for payments? This is a hypothesis that can be tested with data.
3. How effective are complaint mechanisms? The low reporting of crime in general shows that complaint channels must be safe and trusted.
4. How does education affect permissiveness? IPAK can be tracked year to year to assess impact.

For researchers and students

SPAK and IPAK data are interesting research material, for example: what factors influence permissiveness toward petty corruption, how perception relates to actual experience, and how IPAK trends move from 2012 to 2024. Be careful with the limitations already discussed: national-level only, based on admissions, and covering only small-scale corruption.

How do you measure sensitive topics more honestly?

Surveys about bribery face a classic problem: respondents are reluctant to admit behavior seen as improper. Researchers have several techniques to reduce this bias. First, indirect questions, such as asking whether “people around you” have done it. Second, the randomized response technique, where respondents answer under a random rule that protects their privacy (for instance flipping a coin to decide whether to answer truthfully or give a set answer), so the researcher does not know any individual’s answer but can still estimate the overall proportion. Third, the list experiment, where one group sees a list of four statements and another sees five (the same four plus one sensitive item), and both only report how many statements apply to them. The difference in averages between the two groups estimates the share admitting the sensitive behavior, without any respondent having to state it directly. These techniques are more complex but worth considering for academic research on sensitive behavior.

Quick Q&A

Does 17.17% mean one in six public officials is corrupt? No. The figure shows the share of citizens who admit giving something outside the rules, and not all of them were necessarily asked by an official. It also says nothing about how many officials were involved.

Is the drop in IPAK from 3.92 to 3.85 big? A 0.07 gap on a 0 to 5 scale looks small, but the downward direction relates to rising permissiveness. To judge whether it is meaningful, we need to look at the IPAK series over several years and account for the survey’s sampling error.

Read also: [Market research and survey services](https://datalyticsindo.com/en/market-research-survey/)

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