Abstract
Expert elicitation is a research method designed to make estimations in areas where we have no certain knowledge. We tried to estimate the magnitude of white-collar crime in Norway. On our way to a final answer, we were faced with some obstacles in our research design. This chapter presents methodological challenges in estimating the magnitude of white-collar crime in a country in a year. The chapter makes a contribution to reflected learning from empirical research. The methodological issues are concerned with recruitment of experts, willingness and reactions from experts, and responses to different ways of representing the iceberg. A number of experts at first refused to participate. When they learned the identity of one of the researchers, this increased the response rate considerably.
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Keywords
- Dealing with outliers
- Distribution of experts
- Median answers
- Methodology
- Meyer and Booker
- Participation refusal
- Recruitment of experts
- Research design
- Response confusion
- Response rate
Expert elicitation is a research method designed to make estimations in areas where we have no knowledge, only indicators and experience. By systematically interviewing experts, we tried to estimate the magnitude of white -collar crime in Norway . On our way to a final answer, we were faced with obstacles in our research design. This chapter reports on our research journey by communicating our learning from methodological challenges when applying expert elicitation to estimate the size of an iceberg based on knowledge about the tip of the iceberg. In particular, participation refusals and response confusions are discussed.
This chapter presents methodological challenges when expert elicitation was applied to estimate the magnitude of white-collar crime in a country in a year. The chapter makes a contribution to reflected learning from empirical research. The methodological issues are concerned with the recruitment of experts, willingness and reactions from experts, and responses to different ways of representing the iceberg.
We were not completely successful in obtaining respondents as indicated in the previous chapter for several reasons. First, the category of victims was excluded, because victim experience is unfit for generalization. Next, some potential experts (e.g., executives at the stock exchange) refused to participate because of their role. Furthermore, several potential experts responded negatively to the email request. Our response rate was 33 percent. This is line with the literature, deeming a response rate of between one-third and three-querters as normal (Meyer and Booker 2001). A good distribution of experts rather than the participation rate among experts is regarded as more important in this kind of research.
Participation Refusal
A number of experts refused to participate in our interviews. It is interesting to study why they refused to contribute their expertise and what background they have.
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Journalist: “I have nothing against contributing knowledge and experience on economic crime. And I think including the term ‘white-collar crime’ is a little old-fashioned today when the greatest threat to the Norwegian welfare state might be in complex, organized labor market crime, in an unattractive alliance between white-collar offenders and others. The classic white-collar offender is only one among many players in economic crime. But I do not want to guess percentages. I think it is not serious.”
This refusal is interesting from two perspectives. First, the journalist considers white-collar crime to be an old-fashioned term. We disagree, because ever since Sutherland (1939) coined this term, the criminal justice system as well as society has found it problematic to prosecute offenders in this category. This indicates that white-collar offences are still an unresolved issue in most countries. Next, the journalist does not want to guess percentages and thinks this method is not serious. We disagree again, as expert elicitation is a systematic approach beyond pure guesswork.
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Victim: “My experience of such crime is more specific and related to one single case, and it gives me no foundation to consider the topic in general terms.” Second victim (public sector manager): “We do not see it as appropriate to attend, but wish you good luck with [the] work and dedication in this field.”
This seems indeed to be a relevant objection to expert classification, since a victim typically has only one experience of white-collar crime. We know that generalizing from only one observation is not justifiable in research.
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Bankruptcy auditor: “We have no case for refusal.”
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Internal auditor: “We have no case for refusal.”
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Tax administration employee: “We have no case for refusal.”
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Bank executive: “I do not have time, and I am generally unwilling to participate.” Second bank executive: “I work in practice not with white-collar crime and am not qualified to answer the questions.”
Some organizations are very hierarchical, where executives are afraid of participating in external surveys. This might be the case for bank executives who are not at the top level in the organization. However, when the bank executives some days later were contacted by someone on the project team they know, and the person they know referred to previous contacts, then both bank executives changed their minds and agreed to participate. The first bank executive responded: “My initial answer was honest. We only deal with irregularities and misconduct among bank employees, and there are hardly any financial crime cases. I have not been able to build competence in this area. But nevertheless, I shall involve more experienced colleagues and answer questions to the best of my abilities.” The second bank executive responded: “Since you are the one asking. OK.”
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External auditor: “I am on a mission abroad.” Second external auditor: “I am basically happy [to be involved], but am completely snowed under until Christmas.”
The first is an interesting excuse, since it is very often accepted that most busy people have more spare time while abroad than at home. Therefore, it is likely that the potential respondent found an excuse that he thought would be acceptable to the interviewer. The second external auditor is interesting as well, since it is workload that is communicated as the reason for not participating in the survey.
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Police officer: “I am in a hurry and do not want to prioritize this.”
Again, this is an interesting response, since police officers normally would like more attention directed at their work of combatting crime.
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Stock exchange executive: “I thank you for asking, but do not want to participate in the survey.”
We can only speculate on this refusal. One explanation might be that the stock exchange is sensitive to all kinds of issues and therefore members refrain from participation. Another reason might be that the Manifest Center for Social Analysis is considered a left-wing think tank so could be perceived negatively by a capitalist stock exchange.
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Other: We have no case for refusal.
Meyer and Booker (2001) argue that it is important to recruit a wide range of experts. Maybe our range of experts could have been expanded to politicians who work in the criminal justice area, and whistleblowers who have reported white-collar offences, although they may have the same problem as victims, only one observation. A third group of experts might be attorneys who practice white-collar crime defense. A fourth group might be convicts, but again, they only know their own story, just like victims and whistleblowers . A fifth and most relevant group of experts is private investigators who conduct fraud examinations. Often, these financial crime specialists are former police detectives who have considerable experience in law enforcement, financial crime cases, and white-collar criminal behavior.
Furthermore, Meyer and Booker (2001) argue that persuading potential experts is not easy and should be handled with care. Perhaps we should not have started with an email from the Manifest Center for Social Analysis. Emails do not easily create a commitment, and Manifest is considered a left-wing think tank.
Manifest is in fact a known player in the Norwegian public arena with a clear affiliation not only to the social democratic but also to the socialist side of the community. Grassroots trade unions around the country appreciate the think tank, and they provide it with a lot of financial support.
Meyer and Booker (2001: 90) stress the importance of “motivating the experts through communication of intrinsic aspects of the project”. In their experience, experts have responded well to these motivators: Recognition, experiencing something new and different, and need for meaning . Meyer and Booker (2001: 181) also stress common difficulties such as “experts resist the elicitation process or resist giving judgments under uncertainty ”.
Response Confusion
The first participant—an executive at the internal revenue service in Norway (Norwegian Tax Administration)—was faced with issues when she was asked to answer questions about both the total magnitude, as well as groups of the total, of white-collar crime occurrences. When she was asked about the total magnitude, she said that 5 percent of all white-collar crime is detected. However, when she was asked about groups, then most percentages were far above 5 percent, thus creating an average above 5 percent. For example, for groups of criminals , she estimated 15 percent, 30 percent and 4 percent. Similarly for categories of crime: Fraud 5 percent, theft 60 percent, manipulation 10 percent, and corruption 5 percent. The same occurred for groups of victims: Employers 20 percent, banks 10 percent, tax authority 10 percent, customers 5 percent, shareholders 40 percent, and others 5 percent. As a consequence, in subsequent interviews the interviewer needed to remind the respondent of the overall estimate when she was asked for subsequent estimates for groups of criminals, categories of crime, and groups of victims.
Maybe the interviewer’s mistake was not related to what we asked experts to assess, but how we asked it. Kynn (2008) suggests that this aspect appears to have gone largely unnoticed by the statistical literature. The psychological aspects that are involved in eliciting probabilities have been largely ignored.
An interesting issue is whether or not—or to what extent—responding experts were able to keep track of their estimates during the interview. This issue can be exemplified by one of the experts who seemed to be on track during the interview by ending up with 14, 16, 11, 15 and 9 billion NOK respectively. However, a surprise came at the end, when the expert was asked for the total magnitude of white-collar crime. The expert responded that to keep consistent with previous answers, the answer would be 3 billion NOK. From a methodological point of view this is fine, as there is no reason to argue that respondents should be able to keep track of previous estimates to keep consistency during the interview.
As illustrated by the two bank executives who first refused to participate, and then changed their minds as they were contacted by someone they knew on the project team, recruitment of experts can be influenced by previous relationships. The one researcher on the project team who they knew, is also quite well-known in Norway , because he frequently comments on white-collar crime cases in the media. This phenomenon caused even more experts to change their minds or to contribute the name of an alternative expert.
For example, one bankruptcy attorney responded:
Nice to hear from you, and I hope we can have a chat over a coffee or lunch about your stay in the United States. I currently receive inquiries from both home and abroad to participate in various surveys and the like, and I have therefore set a limit to what I can participate in. I was not aware that the inquiry received regarding white-collar crime is something you are involved in. Of course I want to prioritize this and will set aside time for the interview.
Dealing with Outliers
As is to be expected in surveys like this, there was some variation in our experts’ answers to the different questions. In line with the literature (Meyer and Booker 2001: 316), we were well aware of the danger of one single answer having a large influence on the average answer in small samples.
We considered using the median answer to all the questions as our estimate of the panel’s joint assessment. However, a majority of our expert panel thought the share of white-collar criminals being caught and sentenced was well below the average answer, and only a few gave answers above the average. This means that our median answers would imply considerably higher crime amounts (20–25 percent) than the ones we present in the tables earlier. In our calculations, we chose to exclude both the highest and the lowest estimate given for each question. In the end, this led only to small adjustments relative to using the pure averages to calculate our results. This means that we implicitly chose to give the experts who claimed that a relatively high share of white-collar criminals were indeed caught, a higher weight in our calculations, than if we had used median values.
This chapter has described some obstacles and challenges in crime science. Specifically, it has addressed methodological challenges when attempting to determine the magnitude of white-collar crime based on expert elicitation. Recruitment of experts was indeed a challenge, and it seems that the two-stage approach of first email and then a phone interview is not very well suited to this exercise. Only when the identity of one of the well-known researchers became apparent to potential respondents, did the response rate increase considera bly.
References
Kynn, M. (2008). The ‘Heuristics and Biases’ Bias in Expert Elicitation. Journal of the Royal Statistical Society, 171, 239–264.
Meyer, M. A., & Booker, J. M. (2001). Eliciting and Analyzing Expert Judgment: A Practical Guide, SIAM Books, ASA-SIAM Series on Statistics and Applied Probability. Philadelphia: Society for Industrial and Applied Mathematics (SIAM).
Sutherland, E. H. (1939). White-Collar Criminality. American Sociological Review, 5, 1–12.
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Gottschalk, P., Gunnesdal, L. (2018). Research Challenges. In: White-Collar Crime in the Shadow Economy. Palgrave Pivot, Cham. https://doi.org/10.1007/978-3-319-75292-1_5
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