IDEAS home Printed from https://ideas.repec.org/a/gam/jecomi/v10y2022i4p95-d794068.html
   My bibliography  Save this article

Computation of High-Frequency Sub-National Spatial Consumer Price Indexes Using Web Scraping Techniques

Author

Listed:
  • Ilaria Benedetti

    (Department of Economics, Engineering, Society and Business Organization, University of Tuscia, Via del Paradiso, 01100 Viterbo, Italy)

  • Tiziana Laureti

    (Department of Economics, Engineering, Society and Business Organization, University of Tuscia, Via del Paradiso, 01100 Viterbo, Italy)

  • Luigi Palumbo

    (Department of Economics, Engineering, Society and Business Organization, University of Tuscia, Via del Paradiso, 01100 Viterbo, Italy)

  • Brandon M. Rose

    (Jataware LLC, Washington, DC 20015, USA)

Abstract

The development of Information and Communications Technology and digital economies has contributed to changes in the consumption of goods and services in various areas of life, affecting the growing expectations of users in relation to price statistics. Therefore, it is important to provide information on differences in consumer prices across space and over time in a timely manner. Web-scraped data, which is the process of collecting large amounts of data from the web, offer the potential to improve greatly the quality and efficiency of consumer price indices. In this paper, we explore the use of web-scraped data for compiling high-frequency price indexes for groups of products by using the time-interaction-region product model. We computed monthly average prices for five entry-level items according to the Consumer Price Index for All Urban Consumers (CPI-U) classification and tracked their evolution over time in 11 USA cities reported in our dataset. Even if our dataset covers a small percentage of the CPI-U index, results show how web scraping data may provide timely estimates of sub-national SPI evolution and unveil seasonal trends for specific categories.

Suggested Citation

  • Ilaria Benedetti & Tiziana Laureti & Luigi Palumbo & Brandon M. Rose, 2022. "Computation of High-Frequency Sub-National Spatial Consumer Price Indexes Using Web Scraping Techniques," Economies, MDPI, vol. 10(4), pages 1-20, April.
    • Handle: RePEc:gam:jecomi:v:10:y:2022:i:4:p:95-:d:794068
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7099/10/4/95/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7099/10/4/95/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. José‐María Montero & Tiziana Laureti & Román Mínguez & Gema Fernández‐Avilés, 2020. "A Stochastic Model with Penalized Coefficients for Spatial Price Comparisons: An Application to Regional Price Indexes in Italy," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 66(3), pages 512-533, September.
    2. Selvanathan, E A, 1989. "A Note on the Stochastic Approach to Index Numbers," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(4), pages 471-474, October.
    3. Bricongne, Jean-Charles & Meunier, Baptiste & Pouget, Sylvain, 2023. "Web-scraping housing prices in real-time: The Covid-19 crisis in the UK," Journal of Housing Economics, Elsevier, vol. 59(PB).
    4. Robert J. Hill, 2004. "Constructing Price Indexes across Space and Time: The Case of the European Union," American Economic Review, American Economic Association, vol. 94(5), pages 1379-1410, December.
    5. Alberto Cavallo, 2017. "Are Online and Offline Prices Similar? Evidence from Large Multi-channel Retailers," American Economic Review, American Economic Association, vol. 107(1), pages 283-303, January.
    6. Bartlomiej Rokicki & Geoffrey J. D. Hewings, 2019. "Regional price deflators in Poland: evidence from NUTS-2 and NUTS-3 regions," Spatial Economic Analysis, Taylor & Francis Journals, vol. 14(1), pages 88-105, January.
    7. Chen, Yi Vivian & Heston, Alan & Lipsey, Robert, 2000. "International and interarea comparisons of income, output and prices," Journal of Asian Economics, Elsevier, vol. 11(3), pages 363-364, December.
    8. Jan de Haan & Frances Krsinich, 2014. "Scanner Data and the Treatment of Quality Change in Nonrevisable Price Indexes," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(3), pages 341-358, July.
    9. Rao, D.S. Prasada & Hajargasht, Gholamreza, 2016. "Stochastic approach to computation of purchasing power parities in the International Comparison Program (ICP)," Journal of Econometrics, Elsevier, vol. 191(2), pages 414-425.
    10. Mary F. Kokoski & Brent R. Moulton & Kimberly D. Zieschang, 1999. "Interarea Price Comparisons for Heterogeneous Goods and Several Levels of Commodity Aggregation," NBER Chapters, in: International and Interarea Comparisons of Income, Output, and Prices, pages 123-169, National Bureau of Economic Research, Inc.
    11. Amita Majumder & Ranjan Ray, 2020. "National and subnational purchasing power parity: a review," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 47(2), pages 103-124, June.
    12. Alberto Cavallo & W. Erwin Diewert & Robert C. Feenstra & Robert Inklaar & Marcel P. Timmer, 2018. "Using Online Prices for Measuring Real Consumption across Countries," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 483-487, May.
    13. E. A. Selvanathan & D. S. Prasada Rao, 1994. "Stochastic Approach to Index Numbers," Palgrave Macmillan Books, in: Index Numbers, chapter 0, pages 47-73, Palgrave Macmillan.
    14. Alex Costa & Jaume Garcia & Josep Lluís Raymond & Daniel Sanchez-Serra, 2019. "Subnational purchasing power of parity in OECD countries: Estimates based on the Balassa-Samuelson hypothesis," OECD Regional Development Working Papers 2019/12, OECD Publishing.
    15. Robert Summers, 1973. "International Price Comparisons Based Upon Incomplete Data," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 19(1), pages 1-16, March.
    16. Alberto Cavallo & Roberto Rigobon, 2016. "The Billion Prices Project: Using Online Prices for Measurement and Research," Journal of Economic Perspectives, American Economic Association, vol. 30(2), pages 151-178, Spring.
    17. Crystal G. Konny & Brendan K. Williams & David M. Friedman, 2019. "Big Data in the US Consumer Price Index: Experiences and Plans," NBER Chapters, in: Big Data for Twenty-First-Century Economic Statistics, pages 69-98, National Bureau of Economic Research, Inc.
    18. Harchaoui, Tarek M. & Janssen, Robert V., 2018. "How can big data enhance the timeliness of official statistics?," International Journal of Forecasting, Elsevier, vol. 34(2), pages 225-234.
    19. Paweł Macias & Damian Stelmasiak, 2019. "Food inflation nowcasting with web scraped data," NBP Working Papers 302, Narodowy Bank Polski.
    20. Robert J. Hill & Iqbal A. Syed, 2015. "Improving International Comparisons of Prices at Basic Heading Level: An Application to the Asia-Pacific Region," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 61(3), pages 515-539, September.
    21. Luigi Biggeri & Tiziana Laureti & Federico Polidoro, 2017. "Computing Sub-national PPPs with CPI Data: An Empirical Analysis on Italian Data Using Country Product Dummy Models," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 131(1), pages 93-121, March.
    22. Laureti Tiziana & Polidoro Federico, 2022. "Using Scanner Data for Computing Consumer Spatial Price Indexes at Regional Level: An Empirical Application for Grocery Products in Italy," Journal of Official Statistics, Sciendo, vol. 38(1), pages 23-56, March.
    23. World Bank, 2013. "Measuring the Real Size of the World Economy : The Framework, Methodology, and Results of the International Comparison Program—ICP," World Bank Publications - Books, The World Bank Group, number 13329, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Venera Timiryanova & Irina Lakman & Vadim Prudnikov & Dina Krasnoselskaya, 2022. "Spatial Dependence of Average Prices for Product Categories and Its Change over Time: Evidence from Daily Data," Forecasting, MDPI, vol. 5(1), pages 1-25, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. José‐María Montero & Tiziana Laureti & Román Mínguez & Gema Fernández‐Avilés, 2020. "A Stochastic Model with Penalized Coefficients for Spatial Price Comparisons: An Application to Regional Price Indexes in Italy," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 66(3), pages 512-533, September.
    2. Sebastian Weinand, 2022. "Measuring spatial price differentials at the basic heading level: a comparison of stochastic index number methods," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(1), pages 117-143, March.
    3. Alicia Gómez-Tello & Alfonso Díez-Minguela & Julio Martinez-Galarraga & Daniel A. Tirado, 2019. "Regional prices in early twentieth-century Spain: a country-product-dummy approach," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 13(2), pages 245-276, May.
    4. Laureti, Tiziana & Prasada Rao, D.S., 2018. "Measuring Spatial Price Level Differences within a Country: Current status and Future Developments /Medición de las diferencias de nivel de precios espaciales dentro de un país: Estado actual y evoluc," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 36, pages 119-148, Enero.
    5. Laureti Tiziana & Polidoro Federico, 2022. "Using Scanner Data for Computing Consumer Spatial Price Indexes at Regional Level: An Empirical Application for Grocery Products in Italy," Journal of Official Statistics, Sciendo, vol. 38(1), pages 23-56, March.
    6. Chunyun Wang & Xiaoxi Yu & Jiang Zhao, 2022. "Identifying the Real Income Disparity in Prefecture-Level Cities in China: Measurement of Subnational Purchasing Power Parity Based on the Stochastic Approach," Sustainability, MDPI, vol. 14(16), pages 1-24, August.
    7. Amita Majumder & Ranjan Ray, 2020. "National and subnational purchasing power parity: a review," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 47(2), pages 103-124, June.
    8. von Auer, Ludwig & Weinand, Sebastian, 2022. "A nonlinear generalization of the country-product-dummy method," Discussion Papers 45/2022, Deutsche Bundesbank.
    9. 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.
    10. Diewert W. Erwin & Fox Kevin J., 2022. "Measuring Inflation under Pandemic Conditions," Journal of Official Statistics, Sciendo, vol. 38(1), pages 255-285, March.
    11. Hai Long Vo & Duc Hong Vo, 2023. "The purchasing power parity and exchange‐rate economics half a century on," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 446-479, April.
    12. Menggen Chen, 2021. "Sub-National PPPs Based on House and Real Income Disparity across China: a Distinctive Spatial Deflator," The Journal of Real Estate Finance and Economics, Springer, vol. 62(2), pages 187-219, February.
    13. Weinand, Sebastian, 2020. "Measuring spatial price differentials: A comparison of stochastic index number methods," Discussion Papers 12/2020, Deutsche Bundesbank.
    14. Venera Timiryanova & Irina Lakman & Vadim Prudnikov & Dina Krasnoselskaya, 2022. "Spatial Dependence of Average Prices for Product Categories and Its Change over Time: Evidence from Daily Data," Forecasting, MDPI, vol. 5(1), pages 1-25, December.
    15. Menggen Chen & Yan Wang & D. S. Prasada Rao, 2020. "Measuring the spatial price differences in China with regional price parity methods," The World Economy, Wiley Blackwell, vol. 43(4), pages 1103-1146, April.
    16. Santiago E. Alvarez & Sarah M. Lein, 2020. "Tracking inflation on a daily basis," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 156(1), pages 1-13, December.
    17. Diewert, Erwin, 2019. "Quality Adjustment and Hedonics: A Unified Approach," Microeconomics.ca working papers erwin_diewert-2019-2, Vancouver School of Economics, revised 14 Mar 2019.
    18. Manisha Chakrabarty & Amita Majumder & Ranjan Ray, 2018. "A Framework for the Simultaneous Measurement of Spatial Variation and Temporal Movement in Prices in a Heterogeneous Country: The Dynamic Household Regional Product Dummy Model," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 64(3), pages 703-730, September.
    19. Majumder Amita & Ray Ranjan & Santra Sattwik, 2017. "Sensitivity of Purchasing Power Parity Estimates to Estimation Procedures and their Effect on Living Standards Comparisons," Journal of Globalization and Development, De Gruyter, vol. 8(1), pages 1-25, June.
    20. D. Coondoo & A. Majumder & R. Ray, 2001. "On a Method of Calculating Regional Price Differentials with Illustrative Evidence from India," ASARC Working Papers 2001-06, The Australian National University, Australia South Asia Research Centre.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jecomi:v:10:y:2022:i:4:p:95-:d:794068. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.