Abstract
As governments with limited fiscal resources seek to invest in the “best” programs to prevent crime, they often first try to identify the true costs of crime to guide these decisions. Contingent valuation (CV) is a common survey method used to elicit how much the public is willing to pay (WTP) to reduce a particular crime. We utilize one of the first datasets in criminal justice that includes open-ended WTP data gathered from a survey using factorial design and random assignment. WTP figures are then input into a formula which also takes into account 1) the number of households and 2) the number of crimes “avoided,” which is calculated based upon the percentage crime reduction presented to survey respondents. Drawing upon data from a representative sample of the United States, we assess how sensitive respondents are to crime type, crime reduction percentages, program types, and framing. Results demonstrate that in general, open-ended WTP surveys elicit highly skewed responses and that respondents are more willing to pay for crime reduction programs with a higher number of individual components. However, respondents are not sensitive to crime reductions or several other survey framing techniques. Importantly, due to these highly skewed WTP values and lack of responsivity to crime control percentages, final cost of crime numbers vary widely – potentially altering policy decisions driven by these methods. We conclude with a discussion of the appropriateness of these methods for accurately estimating the costs of crime.
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Notes
Particularly as this number is one of two key numeric values in the denominator in Equation 1, even slight differences in this number can drive large differences in the final estimation.
GfK provided the authors with the following description of their sampling procedure: “Panel members are randomly recruited through probability-based sampling, and households are provided with access to the Internet and hardware if needed. GfK recruits panel members by using address-based sampling methods [previously GfK relied on random-digit dialing methods]. Once household members are recruited for the panel and assigned to a study sample, they are notified by email for survey taking, or panelists can visit their online member page for survey taking (instead of being contacted by telephone or postal mail).” Additional information is available at: http://www.knowledgenetworks.com/ganp/docs/KnowledgePanel(R)-Design-Summary.pdf
A pre-test was administered to a group of respondents (n = 26) on April 8–10, 2015 and several focus groups were conducted previously; input regarding WTP questions was taken into account during this process in order to produce the final survey.
Official response rates differ based upon calculation techniques. A total of 3675 surveys were sent out and by dividing the number of responses (2050) by this number, the response rate is 56%. More conservative estimation that takes into account respondents who completed only parts of the survey yields a response rate of 49.4% to 50.9%.
An ex-ante correction for hypothetical bias was also included for each crime type: “Remember that any money you agree to spend on crime prevention is your money that could otherwise be used for your own household’s food, clothing, or whatever you need. When estimating how much you’d pay, we want you to think about actually taking more money out of your pocket.”
This follows Cohen (2015), who also focused on NCVS and only household burglary. This excludes burglary of businesses.
The Winsorizing process and its purpose a discussed more fully below in the Data Analysis Methods section.
For an additional description of the Winsor command in Stata see http://fmwww.bc.edu/RePEc/bocode/w/winsor.html.
Each Winsorized dependent variable was treated as being a different independent variable by this study due to their importance to the aims of this study. In addition, as this method necessarily reduces variation and thus increases the likelihood of Type II errors, a Bonferroni Correction was not performed.
For simplicity’s sake, this paper will focus much of the remainder of analyses and hypothesis testing on WTP for Programs A and B.
Due to the high numbers of comparisons in these hypotheses, we present only significant results in Table 2. Full results are in Appendix 1.
Intra-individual changes have been assessed in a separate paper. See Galvin et al. (2018).
T-tests were also performed for the remainder of the program types, which included comparisons of 25% reduction vs. 10% crime reduction. Of the remaining 32 comparisons, only 5 were statistically significant. Interestingly, they were all for programs pertaining to either identity theft or burglary. These results support the conclusion that respondents are not overly affected by scope/crime reduction. Full results available upon request.
For purposes of simplicity, all analyses here were performed using WTP for Program A (Restitution, Deterrence, Education) only. As demonstrated in Hypothesis 4b, WTP was highest for Program A across all crime types and thus the estimates for costs of crime would be lower for all crime types using any of the other 5 programs presented in the survey.
Piquero et al. (2011) cost estimate for identity theft is not comparable to ours because they also included costs borne to businesses.
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Funding
This project was supported by Award 2013-IJ-CX-0058, granted by the National Institute of Justice, Office of Justice Programs, U.S. Department of Justice. Any opinions, viewpoints, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect those of the Department of Justice. All code for analyses are available upon request by contacting the first author. Data are available through the National Archive of Criminal Justice Data: https://www.icpsr.umich.edu/icpsrweb/NACJD/studies/36520/summary
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Appendix. Crime Type Comparisons (all)
Appendix. Crime Type Comparisons (all)
95% Winsorized | 99% Winsorized | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
Crime | n | Mean (SD) | t | sig | Crime | n | Mean (SD) | t | sig | ||
Program A (RDE) | Program A (RDE) | ||||||||||
Program A (RDE): FF vs. CF | FF | 1871 | 35.06 (57.12) | −1.08 | Program A (RDE): CF vs. FF | FF | 1871 | 56.24 (154.03) | −0.08 | ||
CF | 1875 | 37.18 (63.69) | CF | 1875 | 56.66 (154.91) | ||||||
Program A (RDE): ID vs. BURG | ID | 1873 | 43.74 (66.7) | 0.84 | Program A (RDE): ID vs. BURG | ID | 1873 | 62.16 (151.65) | 0.12 | ||
BURG | 1871 | 41.88 (67.59) | BURG | 1871 | 61.57 (154.76) | ||||||
Program A (RDE): CF vs. ID | CF | 1875 | 37.18 (63.69) | −3.08 | ** | Program A (RDE): CF vs. ID | CF | 1875 | 56.66 (154.91) | −1.10 | |
ID | 1873 | 43.74 (66.7) | ID | 1873 | 62.16 (151.65) | ||||||
Program A (RDE): CF vs. BURG | CF | 1875 | 37.18 (63.69) | −2.19 | * | Program A (RDE): CF vs. BURG | CF | 1875 | 56.66 (154.91) | −0.97 | |
BURG | 1871 | 41.88 (67.59) | BURG | 1871 | 61.57 (154.76) | ||||||
Program A (RDE): FF vs. ID | FF | 1871 | 35.06 (57.12) | −4.28 | *** | Program A (RDE): FF vs. ID | FF | 1871 | 56.24 (154.03) | −1.18 | |
ID | 1873 | 43.74 (66.7) | ID | 1873 | 62.16 (151.65) | ||||||
Program A (RDE): FF vs. BURG | FF | 1871 | 35.06 (57.12) | −3.34 | ** | Program A (RDE): FF vs. BURG | FF | 1871 | 56.24 (154.03) | −1.06 | |
BURG | 1871 | 41.88 (67.59) | BURG | 1871 | 61.57 (154.76) | ||||||
Program B (DE) | Program B (DE) | ||||||||||
Program B (DE): FF vs. CF | FF | 1819 | 18.03 (34.28) | −2.86 | ** | Program B (DE): FF vs. CF | FF | 1819 | 27.76 (77.46) | −1.40 | |
CF | 1819 | 21.61 (40.87) | CF | 1819 | 31.49 (83.54) | ||||||
Program B (DE): ID vs. BURG | ID | 1819 | 20.79 (36.64) | −1.33 | Program B (DE): ID vs. BURG | ID | 1819 | 31.07 (27.2) | −0.37 | ||
BURG | 1817 | 22.5 (40.72) | BURG | 1817 | 32.09 (28.27) | ||||||
Program B (DE): CF vs. ID | CF | 1819 | 21.61 (40.87) | 0.63 | Program B (DE): CF vs. ID | CF | 1819 | 31.49 (83.54) | 0.15 | ||
ID | 1819 | 20.79 (36.64) | ID | 1819 | 31.07 (27.2) | ||||||
Program B (DE): CF vs. BURG | CF | 1819 | 21.61 (40.87) | −0.66 | Program B (DE): CF vs. BURG | CF | 1819 | 31.49 (83.54) | −0.22 | ||
BURG | 1817 | 22.5 (40.72) | BURG | 1817 | 32.09 (28.27) | ||||||
Program B (DE): FF vs. ID | FF | 1819 | 18.03 (34.28) | −2.35 | Program B (DE): FF vs. ID | FF | 1819 | 27.76 (77.46) | −1.23 | ||
ID | 1819 | 20.79 (36.64) | ID | 1819 | 31.07 (84.07) | ||||||
Program B (DE): FF vs. BURG | FF | 1819 | 18.03 (34.28) | −3.58 | *** | Program B (DE): FF vs. BURG | FF | 1819 | 27.76 (77.46) | −1.62 | |
BURG | 1817 | 22.5 (40.72) | BURG | 1819 | 31.07 (27.2) | ||||||
Program C (RD) | Program C (RD) | ||||||||||
Program C (RD): FF vs. CF | FF | 903 | 13.3 (27.05) | −1.43 | Program C (RD): FF vs. FF | FF | 903 | 19.18 (58.41) | −1.64 | ||
CF | 903 | 15.2 (29.55) | CF | 903 | 24.19 (71.05) | ||||||
Program C (RD): ID vs. BURG | ID | 905 | 15.02 (29.31) | −2.04 | * | Program C (RD): ID vs. BURG | ID | 905 | 24.36 (76.81) | −0.58 | |
BURG | 959 | 18.01 (33.86) | BURG | 959 | 26.34 (71.26) | ||||||
Program C (RD): CF vs. ID | CF | 903 | 15.2 (29.55) | 0.13 | Program C (RD): CF vs. ID | CF | 903 | 24.19 (71.05) | −0.05 | ||
ID | 905 | 15.02 (29.31) | ID | 905 | 24.36 (76.81) | ||||||
Program C (RD): CF vs. BURG | CF | 903 | 15.2 (29.55) | −1.91 | Program C (RD): CF vs. BURG | CF | 903 | 24.19 (71.05) | −0.65 | ||
BURG | 959 | 18.01 (33.86) | BURG | 959 | 26.34 (71.26) | ||||||
Program C (RD): FF vs. ID | FF | 903 | 13.3 (27.05) | −1.3 | Program C (RD): FF vs. ID | FF | 903 | 19.18 (58.41) | −1.61 | ||
ID | 905 | 15.02 (29.31) | ID | 905 | 24.36 (76.81) | ||||||
Program C (RD): FF vs. BURG | FF | 903 | 13.3 (27.05) | −3.33 | *** | Program C (RD): FF vs. BURG | FF | 903 | 19.18 (58.41) | −2.38 | ** |
BURG | 959 | 18.01 (33.86) | BURG | 959 | 26.34 (71.26) | ||||||
Program D(RE) | Program D(RE) | ||||||||||
Program D (RE): FF vs. CF | FF | 921 | 13.32 (27.85) | −1.30 | Program D (RE): FF vs. CF | FF | 921 | 21.7 (17.22) | −1.33 | ||
CF | 861 | 15.14 (31.1) | CF | 861 | 26.47 (81.16) | ||||||
Program D (RE): ID vs. BURG | ID | 899 | 15.17 (29.18) | 0.69 | Program D (RE): ID vs. BURG | ID | 899 | 23.09 (67.16) | −1.29 | ||
BURG | 946 | 14.24 (28.84) | BURG | 946 | 28.01 (94.48) | ||||||
Program D (RE): CF vs. ID | CF | 861 | 15.14 (31.1) | −0.02 | Program D (RE): CF vs. ID | CF | 861 | 26.47 (81.16) | 0.95 | ||
ID | 899 | 15.17 (29.18) | ID | 899 | 23.09 (67.16) | ||||||
Program D (RE): CF vs. BURG | CF | 861 | 15.14 (31.1) | 0.64 | Program D (RE): CF vs. BURG | CF | 861 | 26.47 (81.16) | −0.37 | ||
BURG | 946 | 14.24 (28.84) | BURG | 946 | 28.01 (94.48) | ||||||
Program D (RE): FF vs. ID | FF | 921 | 13.32 (27.85) | −1.39 | Program D (RE): FF vs. ID | FF | 921 | 21.7 (17.22) | −0.44 | ||
ID | 899 | 15.17 (29.18) | ID | 899 | 23.09 (67.16) | ||||||
Program D (RE): FF vs. BURG | FF | 921 | 13.32 (27.85) | −0.7 | Program D (RE): FF vs. BURG | FF | 921 | 21.7 (17.22) | −1.65 | * | |
BURG | 946 | 14.24 (28.84) | BURG | 946 | 28.01 (94.48) | ||||||
Program E (D) | Program E (D) | ||||||||||
Program E (D): FF vs. CF | FF | 885 | 8.66 (0.67) | −2.54 | * | Program E (D): FF vs. CF | FF | 885 | 13.9 (46.98) | −1.79 | * |
CF | 946 | 11.38 (0.83) | CF | 946 | 18.65 (65.55) | ||||||
Program E (D): ID vs. BURG | ID | 908 | 11.36 (26.2) | −1.05 | Program E (D): ID vs. BURG | ID | 908 | 17.89 (61.23) | 0.76 | ||
BURG | 861 | 12.68 (26.61) | BURG | 861 | 15.98 (42.75) | ||||||
Program E (D): CF vs. ID | CF | 946 | 11.38 (25.6) | 0.02 | Program E (D): CF vs. ID | CF | 946 | 18.65 (65.55) | 0.26 | ||
ID | 908 | 11.36 (26.2) | ID | 908 | 17.89 (61.23) | ||||||
Program E (D): CF vs. BURG | CF | 946 | 11.38 (25.6) | −1.06 | Program E (D): CF vs. BURG | CF | 946 | 18.65 (65.55) | −1.03 | ||
BURG | 861 | 12.68 (26.61) | BURG | 861 | 15.98 (42.75) | ||||||
Program E (D): FF vs. ID | FF | 885 | 8.66 (0.67) | −2.46 | * | Program E (D): FF vs. ID | FF | 885 | 13.9 (46.98) | −1.55 | |
ID | 908 | 11.36 (26.2) | ID | 908 | 17.89 (61.23) | ||||||
Program E (D): FF vs. BURG | FF | 885 | 8.66 (0.67) | −3.56 | ** | Program E (D): FF vs. BURG | FF | 885 | 13.9 (46.98) | −0.97 | |
BURG | 861 | 12.68 (26.61) | BURG | 861 | 15.98 (42.75) | ||||||
Program F (E) | Program F (E) | ||||||||||
Program F (E): FF vs. CF | FF | 907 | 7.29 (16.74) | −3.03 | ** | Program F (E): FF vs. CF | FF | 907 | 11.45 (35.64) | −1.30 | |
CF | 904 | 10.31 (24.78) | CF | 904 | 13.85 (42.59) | ||||||
Program F (E): ID vs. BURG | ID | 901 | 10.98 (25.48) | 0.09 | Program F (E): ID vs. BURG | ID | 901 | 14.74 (43.81) | −1.48 | ||
BURG | 845 | 10.87 (26.04) | BURG | 845 | 18.81 (67.8) | ||||||
Program F(E): CF vs. ID | CF | 904 | 10.31 (24.78) | −0.57 | Program F(E): CF vs. ID | CF | 904 | 13.85 (42.59) | −0.44 | ||
ID | 901 | 10.98 (25.48) | ID | 901 | 14.74 (43.81) | ||||||
Program F(E): CF vs. BURG | CF | 904 | 10.31 (24.78) | −0.46 | Program F(E): CF vs. BURG | CF | 904 | 13.85 (42.59) | −1.82 | * | |
BURG | 845 | 10.87 (26.04) | BURG | 845 | 18.81 (67.8) | ||||||
Program F(E): FF vs. ID | FF | 907 | 7.29 (16.74) | −3.64 | ** | Program F(E): FF vs. ID | FF | 907 | 11.45 (35.64) | −1.75 | * |
ID | 901 | 10.98 (25.48) | ID | 901 | 14.74 (43.81) | ||||||
Program F(E): FF vs. BURG | FF | 907 | 7.29 (16.74) | −3.39 | ** | Program F(E): FF vs. BURG | FF | 907 | 11.45 (35.64) | −2.81 | * |
BURG | 845 | 10.87 (26.04) | BURG | 845 | 18.81 (67.8) | ||||||
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Lee, J.G., Fisher, D. The Influence of Scope, Frames, and Extreme Willingness to Pay Responses on Cost of Crime Estimates. Am J Crim Just 45, 236–272 (2020). https://doi.org/10.1007/s12103-019-09508-1
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DOI: https://doi.org/10.1007/s12103-019-09508-1