The current study sought to determine whether traits typically associated with short-term mate attractiveness are related to the price female escorts charge for their services. Because female escorts are in the business of short-term mating for profit, it may be the case that those with more desirable traits can command higher prices for their services. Women who are physically attractive and younger are able to be more selective with prospective mates ( Campos, Otta, & Siqueira, 2002 ; Oda, 2001 ; Pawlowski & Dunbar, 1999 ; Waynforth & Dunbar, 1995 ). Attractive women realize that they are attractive to men, and they demand higher quality mates or they demand more investment from mates. We hypothesized that the amount charged by escorts would be correlated with several traits associated with female short-term mate attractiveness: WHR, BMI, weight, and age. We also predicted that escorts who provided recognizable facial shots and nude photographs in their advertisements would charge a higher rate because the photographs might represent an honest advertisement of their physical attractiveness, whereas those not displaying nudity might be concealing unappealing features. Lastly, a model will be developed based upon the significant bivariate relationships to examine which combination of variables best predict female escort fees.

Milrod and Monto (2012) examined a different perspective of the escort–client dyad by focusing on the motives and behaviors of male patrons that paid for online escorts. They reported that the most common behavior was penile–vaginal coitus with a condom. In addition, the top three reasons for seeking an escort were to be with a woman who really likes sex, to be with a woman who is very uninhibited, and to have a variety of sexual partners. Based on the findings, it was clear that men were interested in having sex with many uninhibited women who like to have sex. Additionally, a recent study by Saad (2008) investigated escorts’ advertisements in Europe, Asia, Oceania, Latin America, and North America, which showed that advertisements of WHR typically reported 0.7 across the different regions. Physical attractiveness may be one of the most important factors related to short-term mating ( Li & Kenrick, 2006 ). The importance of advertising one’s physical attributes is crucial in most short-term mating scenarios, and online escort services may also show similar patterns. Pruitt and Krull (2011) found that aspects of physical appearance were the most frequent theme in online escort advertisements, although their study was largely descriptive in nature.

Several studies have examined the content of escort advertisements. In a past content analysis of 76 escort websites, escorts appeared nude in 45% and semi-nude in 20% of the advertisements ( Castle & Lee, 2008 ). In this same study, ages of online escorts tended to be 18–29 years, and escorts often advertised their physical characteristics which included body measurements. Fifty-four percent of the advertisements included biographical sketches that focused on escorts’ physical attributes. In a smaller sample of escort advertisements, nearly 90% of escorts advertised their waist, hip, and chest measurements, and three of the five mentioned their beauty ( Pruitt & Krull, 2011 ).

Female escorts, by virtue of their work, provide sexual access to many partners. Clients expect sex from escorts and view them as promiscuous ( Milrod & Monto, 2012 ). Males prefer promiscuous females in short-term mating, as female promiscuity maximizes the male’s chances of procuring sexual access while limiting the amount of resources expended ( Buss & Schmitt, 1993 ). Escorts who advertise online offer brief sexual encounters for a posted fee. Clients know exactly how much of their resources they must invest in exchange for sex, with no further commitment expected from either side. Males possess evolved sexual selection mechanisms that may be evident in their preferences for online escorts.

In mating domains, men desire attractive women, and what is perceived to be attractive are a set of female traits and characteristics that indicate fertility and reproductive value ( Symons, 1979 ). Men seek women that have characteristics associated with fecundity and youth ( Buss, 1989 ). Preferences for youth and health solve the problem of identifying fertile females ( Buss & Schmitt, 1993 ). For short-term mating strategies, males need to also overcome the dilemma of identifying and attracting sexually accessible females, while simultaneously minimizing investment and commitment ( Buss & Schmitt, 1993 ). Escorts may provide a way for some men to access sexually available women with minimal investment and commitment.

The morphological appearance of female breasts may serve as a cue to age and fertility and is associated with perception of attractiveness ( Marlowe, 1997 ; Symons, 1979 ). Firm, high breasts are associated with nubility and youth, whereas drooping or sagging breasts are associated with increased age presumably declining residual reproductive value. Men consider women with large breasts size to be more attractive and healthy than those with smaller breasts, and they prefer symmetrical breasts ( Singh & Young, 1995 ); and larger breasts, especially symmetrical breasts, are associated with higher reproductive value ( Jasienska, Ziomkiewicz, Ellison, Lipson, & Thune, 2004 ). The preference for larger breasts is apparent in men with both restricted and unrestricted sociosexual orientation; however, unrestricted males have a significantly greater preference for large breasts ( Zelazniewicz & Pawlowski, 2011 ).

Age is another significant trait associated with female attractiveness. Female reproductive value declines with age and fertility peaks during early adulthood, so it is not surprising that males seem to possess an evolved preference for young, nubile females ( Buss, 1989 , Symons, 1979 ). Especially for short-term mating prospects, selection pressures seem to have left men with a strong attraction toward fertile women, and preferences for youth and health solve the fitness problem of identifying fertile females ( Buss & Schmitt, 1993 ). Men tend to be most attracted to women between the ages of 20 and 25 years presumably because that is when fertility peaks in female humans. This window of peak fertility is especially preferred by males for short-term mating, as it maximizes the probability of a brief sexual affair resulting in offspring. The importance of the subjective age of a female’s face on perceived attractiveness by males has also been investigated ( Furnham, Mistry, & McClelland, 2004 ). Females with younger looking faces were perceived by males to be more attractive, healthy, and fecund than females with older looking faces. The effect of age on male perception of these characteristics was even greater than WHR. The tendency for men to prefer younger women is consistent across cultures, both in the preferred age of mates and in the actual age of spouses ( Buss, 1989 ).

In both long-term and short-term mate selection, female WHR is a powerful cue in mate choice ( Furnham, Petrides, & Constantinides, 2005 ). Men consider females who display a 0.7 WHR to be more attractive, healthy, and reproductively valuable than those who deviate from that ratio in either direction ( Singh, 1993 ). Eye-tracking techniques have been used to identify the length of time that males fixate on various parts of the female body ( Dixson, Grimshaw, Linklater, & Dixson, 2010 ). When viewing back-posed women, men initially fixate on the waist and hips within 200 ms and then dwell there longer than any other region of the body. Furthermore, men rated images with a WHR of 0.7 to be most attractive. The desirability of a 0.7 WHR seems to be relatively independent of body weight ( Singh, 1994 ). Within Western cultures, the idealized body weight has declined over time, although the most favored WHR has remained stable ( Singh, 1993 ). There is some cultural variability in WHR preferences, but in the cultures that have been studied, men preferred female figures with WHRs lower than the local average of their cultural female conspecifics ( Sugiyama, 2005 ). Singh (1993 , 1994 ) argued that a WHR around 0.7 is most attractive because it is associated with fertility and fecundity, and considerable evidence seems to support this claim ( Sugiyama, 2005 ). The WHR may also be a predictor of women’s sexual strategies; women with relatively unrestricted sociosexuality and relatively high numbers of sexual partners had lower WHR than women with lower sociosexuality and low numbers of sexual partners ( Mikach & Bailey, 1999 ). Thus, WHR may be attractive to men because it signals both fertility and perhaps also because it serves as a cue to sexual accessibility.

Successful female sex workers may have some awareness of the traits and qualities that male patrons are seeking and they likely tailor their services and fees to the conditions of the market ( Edlund & Korn, 2002 ). Escort services and qualities highly sought after by male clientele should be more prevalent in online escort ads and should command higher prices. There is evidence that women possess an awareness of their mate value ( Buss & Shackelford, 2008 ; Perilloux, Cloud, & Buss, 2013 ) and that self-evaluation affects the standards that women set for prospective mates. Thus, the most desirable escorts should charge a higher fee than less desirable competitors ( Baumeister & Vohs, 2004 ).

Female prostitution can be viewed as a form of short-term sexual strategy ( Buss, 1994 ), where men gain immediate, opportunistic copulations without commitment in exchange for immediate allocation of financial resources to women. As prostitution is a sexual relationship, one would expect that any evolved mate preference variables seen in other short-term mate selection contexts would also be present in the context of prostitution. Prostitutes who have traits that are highly valued by most men should be able to command the highest prices in this sexual marketplace.

A female escort is a type of sex worker who provides sexual services and/or companionship in exchange for money. The solicitation of those escort services has shifted from street corners to easily-accessed online websites ( Castle & Lee, 2008 ). With the advent of the Internet, solicitation of sexual companionship via escort advertisements has allowed escorts to advertise physical attributes and descriptions and develop greater control of their occupation and clientele ( Koken, Bimbi, Parsons, & Halkitis, 2004 ). In these escort service websites, women often post pictures of themselves, describe the services they offer, describe their physical attributes, and indicate the amount they charge for services. An analysis of the information provided in escort advertisements may allow a unique means of exploring short-term mating preferences.

Photos featured within the escort advertisements ( N = 22,590) were initially coded for lineup identity, nude breast exposure, and nude buttocks exposure by two coders in the same manner as price, and a third coder was used to resolve discrepancies. A custom photo coding application allowed researchers to code each photo by checking Boolean (true/false) boxes, reducing chances of human error. Thus, each of the measures related to photos were dichotomous. Lineup identity was defined as being able to recognize and identify the escort (i.e., face) in a hypothetical police lineup. Because some advertisements did not show a facial picture or the face was sometimes blurred or censored in some manner (e.g., mask, hands covering the face, or photo-edited blur), it was evident that some escorts did not wish to be easily identified. This identity selection was based on being able to assign identity and feature recognition (e.g., if you saw the picture, then saw the escort in another situation, would you be able to recognize her). The breast exposure parameter was defined as an exposed nipple or areola, including instances when attributes were visible through semi-transparent clothing. The third parameter was buttocks exposure, defined as both buttocks exposed with no underwear being worn or underwear pulled down at least below the buttocks. Cohen’s κ for identity, breast, and buttocks were as follows: K = .87, p < .001; K = .93, p < .001; K = .81, p < .001, respectively. All disagreements were resolved by the third rater.

Escort fee data could not be automatically extracted from the website information using the customized software, so three researchers manually coded the hourly in-call and out-call rates. Two researchers independently coded the hourly fee for each advertisement and the third researcher was used as a tiebreaker when there were disagreements. The hourly rates were based on the fee of the first hour of escort services. Multiple researchers were needed to translate fees because some escort profiles listed fees without a unit (i.e., U.S. dollar) and to reduce errors while inputting the fees due to the large number of profiles. For escorts with a multihour minimum or different rates for varying locations, an average hourly fee was calculated. A custom price coding application was used that randomly presented the text of the advertisement and allowed the coders to enter the hourly rates for in-calls and out-calls, if a fee was found in the advertisement. Cohen’s κ for interrater agreement for in-call rate was K = .90, p < .001 and for out-call rate, K = .87, p < .001.

The website used a content management system (CMS) to display information on each escort, which allowed the use of automated data capture techniques. Because of the dynamic nature of the website, a snapshot was taken on June 4, 2013 which took 4 hr to download using a customized program developed specifically for this purpose. The dynamic nature of the website changes daily, thus manual coding of the advertisements would have to be done one at a time which would have taken a much longer time to collect. The captured data were then processed over the course of several weeks with no loss of coherency and no possibility of data entry errors. The CMS used by the website presented several attributes in a standard format for each escort. Most of the information was presented to users of the website in a table. The contact information was sorted and used to identify duplicates from the data set. When duplicates were found, one of the advertisements was randomly selected and the other ones deleted. This resulted in the deletion of 674 (18.7%) of the total sample of advertisements.

A custom data processing program was used to extract name, gender, age, hair color, eye color, height, bust, weight, waist, hip, and ethnicity, contact information, along with all textual information of the advertisement, which may or may not have included price. The WHR was computed by dividing each escort’s waist measurement by their corresponding hip measurement. Absolute differences from 0.7 WHR were then calculated. Weight was provided in pounds. BMI was computed by dividing weight in pounds by height in inches squared and multiplying by a conversion factor of 703, which is the standard conversion factor (i.e., metric into imperial) used by the Centers for Disease Control and Prevention (2011) . Age was given in years. Two different fees were extracted from the data corresponding to in-call and out-call prices. These fees were converted into a standard unit of U.S. dollars per hour. In-call and out-call services differ in price. In-call service refers to the client visiting the escort at her location, which may entail greater effort on the part of the client but increases the safety of the escort, whereas out-call service is when the escort travels to the client’s location, which is more dangerous and time consuming for the escort. All photos were also downloaded and coded as to whether or not we were able to view and identify the escort’s face, if there was nude breast exposure and if there was nude buttocks exposure. Additionally, contact information (i.e., phone, e-mail, and/or website) was extracted from the text of the advertisement and was subsequently used to identify duplicates across different geographical locations.

Escorts’ information was obtained from an online escort directory. This site was chosen because of the large number of advertisements and the consistent and well-formed structure of the data (i.e., each profile was designed to allow a women’s measurements, pictures, and biographical information to be presented in a standardized online template). A total of 3,599 female escort advertisements were collected for this study. After controlling for duplicates, the final sample of escort advertisements was 2,925. These duplicates were a result of the website allowing escorts to advertise in different states and cities which created multiple advertisements for those escorts. The escorts were all females offering services in the United States with ages ranging from 18 to 70, with a median age of 26. Participants were predominately in the age range of 18 to 29 (67.2%) with the remaining being 30–49 (31.2%) and 50–70 (1.6%). Participants were predominantly Caucasian (64.9%) followed by mixed (10.4%), Asian (8.1%), Hispanic (8.0%), Black (7.0%), and Other (1.5%).

Two step-wise regression models were built using the significant predictors for each type of service (i.e., in call and out call). For the in-call model, six variables were entered into the model. The results yielded a model with three significant predictors. The significant predictors were BMI, weight, and age, which accounted for 10.2% of the variance. The results of the final model can be seen in Table 3 . A similar analysis was used for out-call fees in which the six variables entered into the equation yielded a model with five significant predictors. The significant predictors were BMI, age, weight, WHR, and a photograph depicting breast nudity which accounted for 11.3% of the variance. The results of the final model can be seen in Table 4 . It should be noted that weight and BMI were highly correlated, thus it was of concern that multicollinearity may be an issue within the regression models because both used weight and BMI as predictors and both were found to be significant. The variance inflation factor (VIF) for each predictor was reported in Tables 3 and 4 . Interpreting VIF values vary to some degree, but several researchers have indicated that VIF values exceeding a value of 10 is cause for concern and values less than 10 tend to be interpreted as inconsequential collinearity (e.g., Hair, Anderson, Tatham, & Black, 1995 ; Kennedy, 1992 ; Mason, Gunst, & Hess, 1989 ; Neter, Wasserman, & Kutner, 1989 ). Based on those recommendations, multicollinearity was not considered to be of concern to merit alternative procedures.

Discussion

Although previous research has examined sex workers, that literature has predominantly focused on negative consequences such as violence (O’Doherty, 2011), coping difficulties (Sanders, 2005), and health risks such as contracting HIV and substance abuse (Vanwesenbeeck, 2001). The present study breaks new ground by examining factors related to the economics and marketing of sex workers. The present findings suggest that WHR, weight, BMI, age, and displays of nudity are related to the rates charged by escorts in online advertisements. Women marketing these characteristics in a desirable manner tend to charge higher rates for sexual services. Because physical appearance seems to be an important determinant for short-term mating (Li & Kenrick, 2006), these factors should play a role in determining the prices that escorts charge in online advertisements. Evolutionarily important variables were found to be related to fees charged by escorts for sexual services and predictor models showed that approximately 10% of the variance in the amounts they charge was accounted for when examining the factors in a combinatorial manner.

The advertised price in online escort advertisements increased as the escorts’ WHR approached 0.7. This is consistent with other studies that have shown that males are attracted to a WHR near 0.7 in females (e.g., Furnham et al., 2005; Saad, 2008; Singh & Young, 1995). Although the premise of a 0.7 WHR being universally preferred has been challenged in recent years (Yu & Shepard, 1998), the present findings support the position that in North America, males may place a premium on a WHR of 0.7 when they are paying for short-term sexual access. However, the homogeneity of the male clientele in terms of culture and geographic location (i.e., the United States) may limit the external validity of these findings. Weight plays an important role in the short-term mating preferences of males (Singh & Young, 1995), and it was found to be associated with escort fees. Similarly, BMI was also negatively correlated with prices charged by online escorts. This finding is consistent with previous findings on the female BMI preferences of men (e.g., Furnham et al., 2004). It should be noted that BMI was the strongest predictor of fees for both in-call and out-call services. This finding is also in alignment with prior research (Furnham et al., 2005) that identified BMI to be more strongly associated with higher mate value relative to WHR, although WHR and BMI are strongly related to each other. It may be the case that BMI serves as an important marker in identifying the value of available female escorts. Age was also negatively correlated with in-call and out-call rates. Because younger females are seen to be more desirable for short-term mating (Buss & Schmitt, 1993; Singh, 1993), it was expected that younger escorts would charge more than older escorts. Further support for this finding can be found in the example of age being negatively correlated with the cost of engagement ring that a bride-to-be is offered (Cronk & Dunham, 2007). As a woman’s age increases, the price of the good (i.e., engagement ring) offered for her companionship decreases.

Physical attractiveness and assessments of youth and health can be determined from various features of the nude body including skin qualities, fluctuating asymmetries, fat distribution, and musculature (Sugiyama, 2005). As sexual access is the ultimate reason for contacting escorts (Castle & Lee, 2008; Milrod & Monto, 2012; Pruitt & Krull, 2011), viewing the nude escort should provide clients with honest signals of youth, health, and attractiveness. Thus, clients might be willing to pay more for escorts who provide compelling evidence of possessing the traits desired by men. The results offered some support for this notion. Photographic displays of naked breasts and buttocks were related to higher prices charged by escorts when examining the bivariate correlations, although only the naked breasts factor was significant in the regression model that predicted out-call fees. Females often compete intrasexually by displaying their physical beauty (Buss, 1988; Buss & Schmitt, 1993; Fisher & Cox, 2010) in order to attract potential mates. Displaying nudity to potential mates allows what is normally obscured by clothing to be quickly viewed and as such may serve as an honest marker of reproductive fitness that may extend beyond well-established markers such as symmetry (Fink & Neave, 2005; Grammer & Thornhill, 1994; Penton-Voak & Perrett, 2000), complexion (Fink & Neave, 2005), and perhaps even WHR in some cases (Badaruddoza & Barna, 2010; Singh, 1993; Singh & Singh, 2011). The lack of consistent findings for nudity displays across the regression models does have a possible explanation. It may be the case that women with more attractive attributes (e.g., ideal WHR, lower BMI, younger age) do not need to display themselves nude and can be more selective in choosing clients (i.e., charge higher fees). And the more attractive women who do include nude photos may further “stack the odds” in their favor, although it may not be all that common. Less attractive women, on the other hand, may display nudity to compensate for less attractive attributes that they may possess.

The patterns for in-call and out-call prices were similar, although models were built for each type of service. Delineation of in-call and out-call service was justified in that each activity requires a different amount of effort for the escort and the customer. For example, escorts offering out-call services must travel to their customers and meet in areas that may vary in safety. On the other hand, patrons of the escort’s in-call services must travel to the escort and may have to use additional resources (e.g., transportation) to meet her. The WHR, BMI, and age were significant predictors in both models. Although 10% of the variance does not explain a relatively large amount of the variance in escort fees, this study does represent a first attempt to build a model that examined factors related to fees charged by escorts. Furthermore, the present study only examined evolutionary-relevant factors associated with the physical appearance of escorts’ bodies, so it certainly may be the case that there are other significant predictive factors in the advertisements that were not included in this analysis. A content analysis of the advertisements could be valuable in determining whether factors extracted from text (e.g., varying sexual experiences, interests, descriptions of companionship) might be important predictors of escort fees. Other studies have examined the content of online escort advertisements (Castle & Lee, 2008; Pruitt & Krull, 2011), although they have not examined how elements of the content might be related to fees.

Males want more sex and want more sexual partners than women. Buss and Schmitt (1993) asked individuals how many different sex partners they desired over the course of a lifetime; men indicated 18 partners, whereas women desired 5. Baumeister, Catanese, and Vohs (2001) reviewed sex differences on a variety of behavioral measures of sex drive. In terms of cognitive factors, men were more likely to think about sex, fantasize about sex, desire sex, have more permissive sexual attitudes, and rate their sex drive as higher than women. Sexual behaviors show a similar pattern as men were more likely to be sexually aroused, masturbate, enjoy more varied sexual practices, engage in goal-directed behavior to get sex, and have more partners. The data on sex differences of the sex drive is so compelling that there were no studies that reported women having a stronger sex drive than men. Byers and Lewis (1988) found that half of the couples in their study had arguments about sex at least once a month and in all of those cases, males wanted more sexual activity than women. It is also the case that women often determine when sex will occur. One study was conducted in which men and women in a given relationship were asked when they should have first had sex and when they actually had sex. The correlation for men was nonsignificant, whereas for women, the correlation was very high (i.e., r = .88; Cohen & Shotland, 1996). Other evidence can be found in disagreements about sexual access, commitment, and the exchange of resources. Buss (1989) asked men and women to state their primary complaint about their partners. As predicted, men were most upset about women who accepted resources and rejected their sexual advances. In contrast, women’s primary complaint involved men who offered a relationship but backed out after having sex. Based on these studies, there is a strong argument to consider sex as a female resource and within an economic context and to consider female sexuality as a resource that may have a monetary value in some contexts.

Limitations There are four limitations of this study that should be discussed. First, the study used data provided in advertisements, so it is not possible to confirm if the data provided were an actual representation of the escorts. This is related to the issue of photographs as well. There was no way to determine whether the photographs were of the escort claiming to be the individual in the advertisement and there was no way to confirm any of the indicators that were examined. However, it may not matter whether the advertised material is truthful. If the advertised material is related to male preference, and if the material is predictive of online escorts charging fees, then the validity of the advertised material may be irrelevant. Past justifications have been argued for escorts’ advertisement of their WHR metrics (Saad, 2008). It is not important whether the escorts lie about their characteristics, only that the metrics are related to male preference. Second, the present study only investigated the relationship between physical attributes and fees charged, but how does an escort’s skill set influence her career success? If an escort offers a particular sexual experience or level of companionship that is desirable, she may establish a customer relationship where she can profit from repeated visits. This limitation in the present study concerns escort behaviors that are assigned a particular value from male customers, and this could not be assessed with the present research design. However, future research should assess actual escort behaviors and customer’s ratings of such escorts in terms of their sexual skill to identify how specific behaviors influence fees charged by escorts. Third is the assumption that males procuring the services offered by the escorts are willing to pay the in-call and out-call rates. It is difficult to know if an escort’s rate for service will be accepted even if she possesses the attributes preferred by males. Just because an escort has a rate of US$500 per hour, does not necessarily mean that someone will actually pay that fee. A better measure would be to perhaps indicate how much an escort makes in a certain time period such as a week, month, or year. This would perhaps provide a better indicator of not only the fee but also how many individuals would be willing to pay that amount during a given time frame. Fourth, only one online escort website was used, so the generalizations to other escorts are limited. This particular website was used because it offered data fields with consistent information that could be extracted in an efficient manner. There are other websites that may or may not offer photographs, fees, measurements, and similar information that should be compared to the results found in the present study’s assessment of one particular escort website.