EconPapers    
Economics at your fingertips  
 

The Bigger Picture: Combining Econometrics with Analytics Improves Forecasts of Movie Success

Steven Lehrer () and Tian Xie

Management Science, 2022, vol. 68, issue 1, 189-210

Abstract: There exists significant hype regarding how much machine learning and incorporating social media data can improve forecast accuracy in commercial applications. To assess if the hype is warranted, we use data from the film industry in simulation experiments that contrast econometric approaches with tools from the predictive analytics literature. Further, we propose new strategies that combine elements from each literature in a bid to capture richer patterns of heterogeneity in the underlying relationship governing revenue. Our results demonstrate the importance of social media data and value from hybrid strategies that combine econometrics and machine learning when conducting forecasts with new big data sources. Specifically, although both least squares support vector regression and recursive partitioning strategies greatly outperform dimension reduction strategies and traditional econometrics approaches in forecast accuracy, there are further significant gains from using hybrid approaches. Further, Monte Carlo experiments demonstrate that these benefits arise from the significant heterogeneity in how social media measures and other film characteristics influence box office outcomes.

Keywords: machine learning; model specification; heteroskedasticity; movies; social media; big data (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.2020.3911 (application/pdf)

Related works:
Working Paper: The Bigger Picture: Combining Econometrics with Analytics Improve Forecasts of Movie Success (2020) Downloads
Working Paper: The Bigger Picture: Combining Econometrics with Analytics Improve Forecasts of Movie Success (2018) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:68:y:2022:i:1:p:189-210

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().

 
Page updated 2025-03-19
Handle: RePEc:inm:ormnsc:v:68:y:2022:i:1:p:189-210