Standing and ‘survival’ in the adult film industry

ABSTRACT

It is conventional wisdom that knowing the right people is essential for one’s career. This claim is supported in the literature on social capital. However, the empirical evidence in this field remains ambiguous. While the literature recognizes that ‘connections’ help finding any job at all, it remains unclear if long-term benefits exist. In contrast to other industries, collaborations between performers in adult films are easily observed. Consequently, a collaborative network can be constructed which serves as an input in order to estimate the effect of a person’s centrality on individual success. Unfortunately, success is not easily observed either. Hence, in this manuscript, the survival in the industry is used as a proxy for professional success. This assumption is justified by the economic argument that, in the absence of lock-in effects, performers will remain in the industry as long as it remains profitable. The profitability does not only depend on monetary aspects but also includes costs from social stigma and adverse effects on health and mental well-being. Using a combination of network analysis and duration models, the results indicate that there is a strong correlation between network centrality and survival in the adult film industry.

KEYWORDS:

• duration analysis
• professional success
• network analysis
• centrality
• social capital

JEL CLASSIFICATION:

• C41
• D80
• C50

Acknowledgements

I am thankful to Pascal Hofmann and Julian Kessel for their assistance in obtaining and preprocessing the data. Further, I am thankful for the comments I received during the course on survival analysis (Guido Buinsdorf, Kassel University 2013), Statistische Woche 2016, the annual congress of the EEA 2016 and those I received from two anonymous referees and, in particular, Peter Winker. Last but not least, I want to thank IAFD.com and their contributors, whose data collection has enabled this work.

Technical Note

The computations in the document where conducted using R. The social network analysis was conducted using the package igraph (Csardi and Nepusz, 2015). The survival analysis relies on the packages survival (Terry, 2015) and eha (Broström, 2015). The tables were created using stargazer (Hlavac, 2014). The relative hazards were illustrated using simPH (Gandrud, 2015).

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

¹ https://en.wikipedia.org/wiki/Six_Degrees_of_Kevin_Bacon, accessed 8 March 2015.

² The People v. Harald Freeman: see https://en.wikipedia.org/wiki/People_v._Freeman, accessed 1 February 2016.

³ For the debate on the validity of this number, see Rich (2001), Ackman (2001) and Silverstein (2006).

⁴ “Appearing together” does not necessarily imply intercourse.