Peer Group Delinquency and Sexual Victimization: Does Popularity Matter?

Though a large body of research has found that peer social network characteristics influence both offending and victimization, relatively little is known about the influence of social network characteristics on adolescent sexual victimization. Attractiveness and sociability largely indicate popularity for teenage females, which in turn leads to earlier onset of dating, greater dating options, and potential risk of sexual victimization—an observation not tested in the criminological and criminal justice literature. We suggest and evaluate 2 competing hypotheses: that popularity within a network insulates females from sexual victimization and that popularity may increase exposure to delinquent others and facilitate sexual victimization. Results suggest that popularity does not have a consistent effect but instead that its role is conditioned by the deviance of the network. Popularity is associated with an increase in the likelihood of victimization when peer deviance is high but with a decrease when peer deviance is low. We further demonstrate that an interaction between a female's own drinking and the proportion of her friends that are male strongly affects her likelihood of sexual victimization. Implications for policy and future research are explored.     

Thermal Imaging as a Lie Detection Tool at Airports

We tested the accuracy of thermal imaging as a lie detection tool in airport screening. Fifty-one passengers in an international airport departure hall told the truth or lied about their forthcoming trip in an interview. Their skin temperature was recorded via a thermal imaging camera. Liars’ skin temperature rose significantly during the interview, whereas truth tellers’ skin temperature remained constant. On the basis of these different patterns, 64% of truth tellers and 69% of liars were classified correctly. The interviewers made veracity judgements independently from the thermal recordings. The interviewers outperformed the thermal recordings and classified 72% of truth tellers and 77% of liars correctly. Accuracy rates based on the combination of thermal imaging scores and interviewers’ judgements were the same as accuracy rates based on interviewers’ judgements alone. Implications of the findings for the suitability of thermal imaging as a lie detection tool in airports are discussed.     

Social Security cost-of-living adjustments and the Consumer Price Index

OASDI benefits are indexed for inflation to protect beneficiaries from the loss of purchasing power implied by inflation. In the absence of such indexing, the purchasing power of Social Security benefits would be eroded as rising prices raise the cost of living. By statute, cost-of-living adjustments (COLAs) for Social Security benefits are calculated using the Bureau of Labor Statistics (BLS) Consumer Price Index for Urban Wage Earners and Clerical Workers (CPI-W). Some argue that this index does not accurately reflect the inflation experienced by the elderly population and should be changed to an elderly-specific price index such as the Experimental Consumer Price Index for Americans 62 Years of Age and Older, often referred to as the Consumer Price Index for the Elderly (CPI-E). Others argue that the measure of inflation underlying the COLA is technically biased, causing it to overestimate changes in the cost of living. This argument implies that current COLAs tend to increase, rather than merely maintain, the purchasing power of benefits over time. Potential bias in the CPI as a cost-of-living index arises from a number of sources, including incomplete accounting for the ability of consumers to substitute goods or change purchasing outlets in response to relative price changes. The BLS has constructed a new index called the Chained Consumer Price Index for All Urban Consumers (C-CPI-U) that better accounts for those consumer adjustments. Price indexes are not true cost-of-living indexes, but approximations of cost-of-living indexes (COLI). The Bureau of Labor Statistics (2006a) explains the difference between the two: As it pertains to the CPI, the COLI for the current month is based on the answer to the following question: "What is the cost, at this month ' market prices, of achieving the standard of living actually attained in the base period?" This cost is a hypothetical expenditure-the lowest expenditure level necessary at this month's prices to achieve the base-period's living standard.... Unfortunately, because the cost of achieving a living standard cannot be observed directly, in operational terms, a COLI can only be approximated. Although the CPI cannot be said to equal a cost-of-living index, the concept of the COLI provides the CPI's measurement objective and the standard by which we define any bias in the CPI. While all versions of the CPI only approximate the actual changes in the cost of living, the CPI-E has several additional technical limitations. First, the CPI-E may better account for the goods and services typically purchased by the elderly, but the expenditure weights for the elderly are the only difference between the CPI-E and CPI-W. These weights are based on a much smaller sample than the other two indices, making it less precise. Second, the CPI-E does not account for differences in retail outlets frequented by the aged population or the prices they pay. Finally, the purchasing population measured in the CPI-E is not necessarily identical to the Social Security beneficiary population, where more than one-fifth of OASDI beneficiaries are under age 62. Likewise, over one-fifth of persons aged 62 or older are not beneficiaries, but they are included in the CPI-E population. Finally, changes in the index used to calculate COLAs directly affect the amount of benefits paid, and as a result, projected solvency of the Social Security program. A switch to the CPI-E for the December 2006 COLA (received in January 2007) would have resulted in an average monthly benefit OASDI benefits are indexed for inflation to protect beneficiaries from the loss of purchasing power implied by inflation. In the absence of such indexing, the purchasing power of Social Security benefits would be eroded as rising prices raise the cost of living. By statute, cost-of-living adjustments (COLAs) for Social Security benefits are calculated using the Bureau of Labor Statistics (BLS) Consumer Price Index for Urban Wage Earners and Clerical Workers (CPI-W). Some argue that this index does not accurately reflect the inflation experienced by the elderly population and should be changed to an elderly-specific price index such as the Experimental Consumer Price Index for Americans 62 Years of Age and Older, often referred to as the Consumer Price Index for the Elderly (CPI-E). Others argue that the measure of inflation underlying the COLA is technically biased, causing it to overestimate changes in the cost of living. This argument implies that current COLAs tend to increase, rather than merely maintain, the purchasing power of benefits over time. Potential bias in the CPI as a cost-of-living index arises from a number of sources, including incomplete accounting for the ability of consumers to substitute goods or change purchasing outlets in response to relative price changes. The BLS has constructed a new index called the Chained Consumer Price Index for All Urban Consumers (C-CPI-U) that better accounts for those consumer adjustments. Price indexes are not true cost-of-living indexes, but approximations of cost-of-living indexes (COLI). The Bureau of Labor Statistics (2006a) explains the difference between the two: As it pertains to the CPI, the COLI for the current month is based on the answer to the following question: "What is the cost, at this month ' market prices, of achieving the standard of living actually attained in the base period?" This cost is a hypothetical expenditure-the lowest expenditure level necessary at this month's prices to achieve the base-period's living standard.... Unfortunately, because the cost of achieving a living standard cannot be observed directly, in operational terms, a COLI can only be approximated. Although the CPI cannot be said to equal a cost-of-living index, the concept of the COLI provides the CPI's measurement objective and the standard by which we define any bias in the CPI. While all versions of the CPI only approximate the actual changes in the cost of living, the CPI-E has several additional technical limitations. First, the CPI-E may better account for the goods and services typically purchased by the elderly, but the expenditure weights for the elderly are the only difference between the CPI-E and CPI-W. These weights are based on a much smaller sample than the other two indices, making it less precise. Second, the CPI-E does not account for differences in retail outlets frequented by the aged population or the prices they pay. Finally, the purchasing population measured in the CPI-E is not necessarily identical to the Social Security beneficiary population, where more than one-fifth of OASDI beneficiaries are under age 62. Likewise, over one-fifth of persons aged 62 or older are not beneficiaries, but they are included in the CPI-E population. Finally, changes in the index used to calculate COLAs directly affect the amount of benefits paid, and as a result, projected solvency of the Social Security program. A switch to the CPI-E for the December 2006 COLA (received in January 2007) would have resulted in an average monthly benefit $0.90 higher than that received. If the December 2006 COLA had been adjusted by the Chained CPI-U instead, the average monthly benefit would have been $4.70 less than with current indexing. Any changes to the COLA that would cause faster growth in individual benefits would make the projected date of insolvency sooner, while slower growth would delay insolvency. Hobijn and Lagakos (2003) estimated that switching to the CPI-E for COLAs would move projected insolvency sooner by 3-5 years. A projection by SSA's Office of the Chief Actuary estimated that annual COLAs based on the Chained C-CPI-U beginning in 2006 would delay the date of OASDI insolvency by 4 years.     

Identifying the determinants of aggregate judicial performance: taxpayers’ money well spent?

There have been a sizeable number of studies trying to identify the determinants of judicial performance on the country level. Such a design is appropriate to identify underperforming individual judges or underperforming courts or court districts. However, it is not appropriate to identify institutions conducive to judicial performance. A dataset produced by the European Commission for the Efficiency of Justice contains very detailed information on the judicial systems of the 47 member countries of the Council of Europe. Drawing on robust regressions and using an objective variable, we find that (1) resolution rates are not a function of per capita income. In other words: poor countries can also afford them. (2) Countries belonging to the French legal tradition enjoy relatively lower resolution rates. (3) Resolution rates are negatively—and very robustly—correlated with court budget. As such, a higher budget will not “buy” more court decisions. (4) Resolution rates are never positively correlated with the presence of judicial councils. (5) Mandatory training for judges is correlated with higher resolution rates. Drawing on the subjectively perceived efficiency of the judiciary as the dependent variable we find that (6) countries belonging to both the French and the socialist legal tradition are less efficient and that (7) judicial councils are also negatively correlated with our measure of judicial efficiency, in other words: countries that do not have them should not introduce them.