Effects of accounting of characteristics heterogeneity in video game price indices
DOI:
https://doi.org/10.22394/1993-7601-2024-75-78-97Keywords:
гедонистические регрессии, видеоигры, ценовые индексы, модели с фиксированными эффектами, модели со случайными эффектами, многоуровневые моделиAbstract
This paper attempts to construct hedonistic price indices for the computer game market from 2007 to 2023. The peculiarity of the work is that we use hedonistic regressions that consider additional factors reflecting the consumer's reaction to the object of study. In the previous study, we considered only the parameters of the objects set by the manufacturer. Previously, we modelled prices assigned by the manufacturer at the time of game release, and the study period did not cover 2022 and 2023. This paper uses final product prices recorded at the data collection time, and the period captures 2023. Hedonistic regression cleared the time‐dependence of a price from the number of game characteristics and some game demand factors. However, there are unobservable hard‐to‐specify sets of characteristics, such as genre features or game mode. Calculating the outcomes of the described variables directly in the model equation is complex. At the same time, if we assume that they uncorrelation with the variables explicitly specified in the model equation, we can treat them as random effects of various kinds. It allows us to obtain efficient and perhaps even reasonable price index estimates. For building indexes, we use a standard hedonistic approach with temporary dummy variables, modified to allow for the random effects described above. We evaluate the constructed models using OLS and the simulation likelihood method. This approach identifies factors whose outcomes on prices differ significantly depending on which genres, modes and user audience scale groups the objects under consideration fall into. The final part of the study analyzes monthly data from 2020 to 2023 for a deeper examination of the effects following February 24, 2022. The indices based on annual data in the period 2007–2023 reflect key global economic events, which, at first glance, contradicts the opinion of gaming industry experts about the weak sensitivity of the gaming market to crises. However, the analysis conducted on monthly data makes it possible to verify that the gaming industry has a very high rate of adaptation to economic and political upheavals.Downloads
References
Арсланов М. В., Ратникова Т. А. (2024). Ценовой индекс на компьютерные игры: что скрыто от невооруженного глаза? Экономика и математические методы, 60 (3) (в печати).
Ильянов Д. С., Чернышева Т. К., Юревич М. А. (2020). Источники роста экономики в ХХI веке: индустрия видеоигр. Теоретическая и прикладная экономика, 3, 78–89. DOI: 10.25136/2409‑8647.2020.3.31693.
Турунцева М. Ю., Зямалов В. Е. (2022). Гедонистические ценовые индексы: опыт применения к российскому рынку. Экономический журнал Высшей школы экономики, 26 (3), 429–449. DOI: 10.17323/1813‑8691‑2022‑26‑3‑429‑449.
Berndt E. R., Griliches Z. (1990). Price indexes for microcomputers: An exploratory study. NBER Working Paper 3378. National Bureau of Economic Research. https://www.nber.org/system/files/working_papers/w3378/w3378.pdf
Brasington D. M., Hite D. (2008). A mixed index approach to identifying hedonic price models. Regional Science and Urban Economics, 38 (3), 271–284. DOI: 10.2139/ssrn.928252.
Choi K. J., Hwang J. H., Lee J. Y. (2021). Different effects of price discounts on game purchase: Comparison between single and multi-games. The Journal of the Korea Contents Association, 21 (6), 561–571. DOI: 10.5392/JKCA.2021.21.06.561.
Court A. T. (1939). Hedonic price indexes: with automotive examples. The Dynamics of Automobile Demand: Based Upon Papers Presented at a Joint Meeting of the American Statistical Association and the Econometric Society in Detroit, Michigan on December 27, 1938.
Cox J. (2014). What makes a blockbuster video game? An empirical analysis of US sales data. Managerial and Decision Economics, 35 (3), 189–198. DOI: 10.1002/mde.2608.
Cox J. (2017). Play it again, Sam? Versioning in the market for second-hand video game software. Managerial and Decision Economics, 38 (4), 526–533. DOI: 10.1002/mde.2800.
Gretz R. T. (2010). Console price and software availability in the home video game industry. Atlantic Economic Journal, 38 (1), 81–94. DOI: 10.1007/s11293‑009‑9209‑3.
Leavens D. H. (1938). Report of the Atlantic City and Indianapolis meetings, December 27–30, 1937. Econometrica, 6 (2), 180–192.
Triplett J. E. (1996). High-tech industry productivity and hedonic price indices. In: Industry Productivity: International Comparison and Measurement Issues, 119–142. Paris: OECD.
White A. G., Abel J. R., Berndt E. R., Monroe C. (2004). Hedonic price indexes for personal computer operating systems and productivity suites. NBER Working Paper 10427. National Bureau of Economic Research. https://www.nber.org/system/files/working_papers/w10427/w10427.pdf.
Arslanov M. V., Ratnikova T. A. (2024). Price index for computer games: What is hidden from the naked eye? Economics and Mathematical Methods, 60 (3) (in print) (in Russian).
Berndt E. R., Griliches Z. (1990). Price indexes for microcomputers: An exploratory study. NBER Working Paper 3378. National Bureau of Economic Research. https://www.nber.org/system/files/working_papers/w3378/w3378.pdf
Brasington D. M., Hite D. (2008). A mixed index approach to identifying hedonic price models. Regional Science and Urban Economics, 38 (3), 271–284. DOI: 10.2139/ssrn.928252.
Choi K. J., Hwang J. H., Lee J. Y. (2021). Different effects of price discounts on game purchase: Comparison between single and multi-games. The Journal of the Korea Contents Association, 21 (6), 561–571. DOI: 10.5392/JKCA.2021.21.06.561.
Court A. T. (1939). Hedonic price indexes: with automotive examples. The Dynamics of Automobile Demand: Based Upon Papers Presented at a Joint Meeting of the American Statistical Association and the Econometric Society in Detroit, Michigan on December 27, 1938.
Cox J. (2014). What makes a blockbuster video game? An empirical analysis of US sales data. Managerial and Decision Economics, 35 (3), 189–198. DOI: 10.1002/mde.2608.
Cox J. (2017). Play it again, Sam? Versioning in the market for second-hand video game software. Managerial and Decision Economics, 38 (4), 526–533. DOI: 10.1002/mde.2800.
Gretz R. T. (2010). Console price and software availability in the home video game industry. Atlantic Economic Journal, 38 (1), 81–94. DOI: 10.1007/s11293‑009‑9209‑3.
Ilyanov D. S., Chernysheva T. C., Yurevich M. A. (2020). Sources of economic growth in the XXI century: Video game industry. Theoretical and Applied Economics, 3, 78–89 (in Russian). DOI: 10.25136/2409‑8647.2020.3.31693.
Leavens D. H. (1938). Report of the Atlantic City and Indianapolis meetings, December 27–30, 1937. Econometrica, 6 (2), 180–192.
Triplett J. E. (1996). High-tech industry productivity and hedonic price indices. In: Industry Productivity: International Comparison and Measurement Issues, 119–142. Paris: OECD.
Turuntseva M. Yu., Zyamalov V. E. (2022). Hedonic price indices: Application to the Russian market. HSE Economic Journal, 26 (3), 429–449 (in Russian). DOI: 10.17323/1813‑8691‑2022‑26‑3‑429‑449.
White A. G., Abel J. R., Berndt E. R., Monroe C. (2004). Hedonic price indexes for personal computer operating systems and productivity suites. NBER Working Paper 10427. National Bureau of Economic Research. https://www.nber.org/system/files/working_papers/w10427/w10427.pdf.