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Measuring the Impact of Free Goods on Real Household Consumption

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  • Brynjolfsson, Erik
  • Collis, Avinash
  • Diewert, Erwin
  • Eggers, Felix
  • FOX, Kevin J.

Abstract

A puzzling development over the past 15 years is decline in Total Factor Productivity in many advanced economies. Part of this decline may be due to the rapid growth of free digital goods. Statistical agencies have no reliable way to measure the benefits of the introduction of free goods. This is true even when the provision of the goods is paid for via advertising. Yet these free goods are enormously popular and surely create substantial utility for households. In this paper, we suggest a methodology which will allow statistical agencies to form rough approximations to the benefits that flow to households from new free goods. The present paper draws heavily on the contributions of Brynjolfsson, Collis, Diewert, Eggers and Fox (2019) (subsequent references will be to BCDEF) and Diewert, Fox and Schreyer (2019). In section I, we outline how the reservation price methodology introduced by Hicks (1940; 114) can be used to measure the consumption benefits to households of new products that are provided at zero cost or costs that are close to zero. This Hicksian approach relies on normal index number theory but requires the estimation of reservation prices. In section II, we show how choice experiments about compensation for product withdrawals can be used to estimate these reservation prices. Section III concludes with a summary and implications.

Suggested Citation

  • Brynjolfsson, Erik & Collis, Avinash & Diewert, Erwin & Eggers, Felix & FOX, Kevin J., 2020. "Measuring the Impact of Free Goods on Real Household Consumption," Microeconomics.ca working papers erwin_diewert-2020-2, Vancouver School of Economics, revised 10 Jan 2020.
    • Handle: RePEc:ubc:pmicro:erwin_diewert-2020-2
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    References listed on IDEAS

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    1. Feenstra, Robert C, 1994. "New Product Varieties and the Measurement of International Prices," American Economic Review, American Economic Association, vol. 84(1), pages 157-177, March.
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    7. Erik Brynjolfsson & Avinash Collis & Felix Eggers, 2019. "Using massive online choice experiments to measure changes in well-being," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 116(15), pages 7250-7255, April.
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    10. W. Erwin Diewert & Kevin J. Fox & Paul Schreyer, 2022. "Experimental Economics and the New Commodities Problem," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 68(4), pages 895-905, December.
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    Cited by:

    1. Arvai Kai & Mann Katja, 2022. "Consumption Inequality in the Digital Age," Working papers 890, Banque de France.
    2. Diane Coyle & Leonard Nakamura, 2022. "Time Use, Productivity, and Household-centric Measurement of Welfare in the Digital Economy," International Productivity Monitor, Centre for the Study of Living Standards, vol. 42, pages 165-186, Spring.
    3. Leonard I. Nakamura, 2020. "Evidence of Accelerating Mismeasurement of Growth and Inflation in the U.S. in the 21st Century," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-15, Economic Statistics Centre of Excellence (ESCoE).
    4. Jaravel, Xavier, 2021. "Inflation inequality: measurement, causes, and policy implications," LSE Research Online Documents on Economics 123931, London School of Economics and Political Science, LSE Library.
    5. Diane Coyle & David Nguyen, 2020. "Free goods and economic welfare," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2020-18, Economic Statistics Centre of Excellence (ESCoE).
    6. Coyle, Diane & Hampton, Lucy, 2024. "21st century progress in computing," Telecommunications Policy, Elsevier, vol. 48(1).
    7. W. Erwin Diewert & Kevin J. Fox, 2020. "Measuring Real Consumption and CPI Bias under Lockdown Conditions," NBER Working Papers 27144, National Bureau of Economic Research, Inc.
    8. Mattsson, Pontus & Reshid, Abdulaziz, 2023. "Productivity divergence and the role of digitalisation," Economic Analysis and Policy, Elsevier, vol. 79(C), pages 942-966.
    9. Diane Coyle & Annabel Manley, 2021. "Potential social value from data: an application of discrete choice analysis," Economic Statistics Centre of Excellence (ESCoE) Discussion Papers ESCoE DP-2021-17, Economic Statistics Centre of Excellence (ESCoE).
    10. Cusolito,Ana Paula & Lederman,Daniel & Pena,Jorge O., 2020. "The Effects of Digital-Technology Adoption on Productivity and Factor Demand : Firm-level Evidence from Developing Countries," Policy Research Working Paper Series 9333, The World Bank.

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    More about this item

    Keywords

    Welfare measurement; GDP; Productivity; mismeasurement; productivity slowdown; new goods; free goods; online choice experiments; GDP-B.;
    All these keywords.

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • D60 - Microeconomics - - Welfare Economics - - - General
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights
    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity

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