IDEAS home Printed from https://ideas.repec.org/f/ppo632.html
   My authors  Follow this author

Alexey Porshakov

Personal Details

First Name:Alexey
Middle Name:
Last Name:Porshakov
Suffix:
RePEc Short-ID:ppo632
[This author has chosen not to make the email address public]

Affiliation

Central Bank of the Russian Federation

Moscow, Russia
https://cbr.ru/
RePEc:edi:cbrgvru (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Alexey Porshakov & Elena Deryugina & Alexey Ponomarenko & Andrey Sinyakov, 2015. "Nowcasting and Short-Term Forecasting of Russian GDP with a Dynamic Factor Model," Bank of Russia Working Paper Series wps2, Bank of Russia.
  2. Porshakov, Alexey & Deryugina, Elena & Ponomarenko, Alexey & Sinyakov, Andrey, 2015. "Nowcasting and short-term forecasting of Russian GDP with a dynamic factor model," BOFIT Discussion Papers 19/2015, Bank of Finland Institute for Emerging Economies (BOFIT).

Articles

  1. Porshakov, A. & Ponomarenko, A. & Sinyakov, A., 2016. "Nowcasting and Short-Term Forecasting of Russian GDP with a Dynamic Factor Model," Journal of the New Economic Association, New Economic Association, vol. 30(2), pages 60-76.

    RePEc:nos:voprec:2008-07-5 is not listed on IDEAS
    RePEc:nos:voprec:2009-08-5 is not listed on IDEAS

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Alexey Porshakov & Elena Deryugina & Alexey Ponomarenko & Andrey Sinyakov, 2015. "Nowcasting and Short-Term Forecasting of Russian GDP with a Dynamic Factor Model," Bank of Russia Working Paper Series wps2, Bank of Russia.

    Cited by:

    1. Yury Achkasov, 2016. "Nowcasting of the Russian GDP Using the Current Statistics: Approach Modification," Bank of Russia Working Paper Series wps8, Bank of Russia.
    2. Konstantin S. Rybak, 2023. "Анализ Важности Глобальных Факторов Для Наукастинга Ввп," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 12, pages 18-23, December.
    3. Ming-Ming Zhao & Rongrong Li, 2018. "Decoupling and decomposition analysis of carbon emissions from economic output in Chinese Guangdong Province: A sector perspective," Energy & Environment, , vol. 29(4), pages 543-555, June.
    4. Anastasia Mogilat & Oleg Kryzhanovskiy & Zhanna Shuvalova & Yaroslav Murashov, 2024. "DYFARUS: Dynamic Factor Model to Forecast GDP by Output Using Input-Output Tables," Russian Journal of Money and Finance, Bank of Russia, vol. 83(2), pages 3-25, June.
    5. Mikosch, Heiner & Solanko, Laura, 2017. "Should one follow movements in the oil price or in money supply? Forecasting quarterly GDP growth in Russia with higher-frequency indicators," BOFIT Discussion Papers 19/2017, Bank of Finland Institute for Emerging Economies (BOFIT).
    6. Aizhan Bolatbayeva & Alisher Tolepbergen & Nurdaulet Abilov, 2020. "A macroeconometric model for Russia," Russian Journal of Economics, ARPHA Platform, vol. 6(2), pages 114-143, June.
    7. Fokin, Nikita & Polbin, Andrey, 2019. "A Bivariate Forecasting Model For Russian GDP Under Structural Changes In Monetary Policy and Long-Term Growth," MPRA Paper 95306, University Library of Munich, Germany, revised Apr 2019.
    8. Zhemkov, Michael, 2021. "Nowcasting Russian GDP using forecast combination approach," International Economics, Elsevier, vol. 168(C), pages 10-24.
    9. Stankevich, Ivan, 2023. "Application of Markov-Switching MIDAS models to nowcasting of GDP and its components," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 70, pages 122-143.
    10. Hopp Daniel, 2022. "Economic Nowcasting with Long Short-Term Memory Artificial Neural Networks (LSTM)," Journal of Official Statistics, Sciendo, vol. 38(3), pages 847-873, September.
    11. Stankevich, Ivan, 2020. "Comparison of macroeconomic indicators nowcasting methods: Russian GDP case," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 113-127.
    12. Makram El-Shagi & Kiril Tochkov, 2021. "Divisia Monetary Aggregates for Russia: Money Demand, GDP Nowcasting, and the Price Puzzle," CFDS Discussion Paper Series 2021/1, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China.
    13. Heiner Mikosch & Laura Solanko, 2019. "Forecasting Quarterly Russian GDP Growth with Mixed-Frequency Data," Russian Journal of Money and Finance, Bank of Russia, vol. 78(1), pages 19-35, March.
    14. Tóth, Peter, 2014. "Malý dynamický faktorový model na krátkodobé prognózovanie slovenského HDP [A Small Dynamic Factor Model for the Short-Term Forecasting of Slovak GDP]," MPRA Paper 63713, University Library of Munich, Germany.
    15. Dahlhaus, Tatjana & Guénette, Justin-Damien & Vasishtha, Garima, 2017. "Nowcasting BRIC+M in real time," International Journal of Forecasting, Elsevier, vol. 33(4), pages 915-935.
    16. Alexandra Bozhechkova & Urmat Dzhunkeev, 2024. "CLARA and CARLSON: Combination of Ensemble and Neural Network Machine Learning Methods for GDP Forecasting," Russian Journal of Money and Finance, Bank of Russia, vol. 83(3), pages 45-69, September.
    17. Aleksandra Riedl & Julia Wörz, 2018. "A simple approach to nowcasting GDP growth in CESEE economies," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q4/18, pages 56-74.
    18. Vladimir Boyko & Nadezhda Kislyak & Mikhail Nikitin & Oleg Oborin, 2020. "Methods for Estimating the Gross Regional Product Leading Indicator," Russian Journal of Money and Finance, Bank of Russia, vol. 79(3), pages 3-29, September.
    19. Zubarev Andrey & Rybak Konstantin, 2021. "GDP Nowcasting: Dynamic Factor Model vs. Official Forecasts [Наукастинг Ввп: Динамическая Факторная Модель И Официальные Прогнозы]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 12, pages 34-40, December.
    20. Anastasiia Pankratova, 2024. "Forecasting Key Macroeconomic Indicators Using DMA and DMS Methods," Russian Journal of Money and Finance, Bank of Russia, vol. 83(1), pages 32-52, March.
    21. Caruso, Alberto, 2018. "Nowcasting with the help of foreign indicators: The case of Mexico," Economic Modelling, Elsevier, vol. 69(C), pages 160-168.
    22. Daniel Armeanu & Jean Vasile Andrei & Leonard Lache & Mirela Panait, 2017. "A multifactor approach to forecasting Romanian gross domestic product (GDP) in the short run," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-23, July.
    23. Evžen Kočenda & Karen Poghosyan, 2020. "Nowcasting Real GDP Growth: Comparison between Old and New EU Countries," Eastern European Economics, Taylor & Francis Journals, vol. 58(3), pages 197-220, May.
    24. Мекенбаева Камила // Mekenbayeva Kamila & Karel Musil, 2017. "Система прогнозирования в Национальном Банке Казахстана: наукаст на основа опросов // Forecasting system at the National Bank of Kazakhstan: survey-based nowcasting," Working Papers #2017-1, National Bank of Kazakhstan.
    25. Danilo Leiva-Leon & Gabriel Pérez-Quirós & Eyno Rots, 2020. "Real-Time Weakness of the Global Economy: A First Assessment of the Coronavirus Crisis," MNB Working Papers 2020/4, Magyar Nemzeti Bank (Central Bank of Hungary).
    26. Anton Grui & Roman Lysenko, 2017. "Nowcasting Ukraine's GDP Using a Factor-Augmented VAR (FAVAR) Model," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 242, pages 5-13.
    27. Sergey V. Arzhenovskiy, 2024. "Forecasting GDP Dynamics Based on the Bank of Russia’s Enterprise Monitoring Data," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 1, pages 31-44, February.
    28. Andrey Zubarev & Daniil Lomonosov & Konstantin Rybak, 2022. "Estimation of the Impact of Global Shocks on the Russian Economy and GDP Nowcasting Using a Factor Model," Russian Journal of Money and Finance, Bank of Russia, vol. 81(2), pages 49-78, June.
    29. Zubarev Andrey & Rybak Konstantin, 2021. "Наукастинг Ввп: Динамическая Факторная Модель И Официальные Прогнозы," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 12, pages 34-40, December.
    30. Konstantin S. Rybak, 2023. "Evaluating the Role of Global Factors in GDP Nowcasting [Анализ Важности Глобальных Факторов Для Наукастинга Ввп]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 12, pages 18-23, December.

  2. Porshakov, Alexey & Deryugina, Elena & Ponomarenko, Alexey & Sinyakov, Andrey, 2015. "Nowcasting and short-term forecasting of Russian GDP with a dynamic factor model," BOFIT Discussion Papers 19/2015, Bank of Finland Institute for Emerging Economies (BOFIT).

    Cited by:

    1. Yury Achkasov, 2016. "Nowcasting of the Russian GDP Using the Current Statistics: Approach Modification," Bank of Russia Working Paper Series wps8, Bank of Russia.
    2. Konstantin S. Rybak, 2023. "Анализ Важности Глобальных Факторов Для Наукастинга Ввп," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 12, pages 18-23, December.
    3. Ming-Ming Zhao & Rongrong Li, 2018. "Decoupling and decomposition analysis of carbon emissions from economic output in Chinese Guangdong Province: A sector perspective," Energy & Environment, , vol. 29(4), pages 543-555, June.
    4. Anastasia Mogilat & Oleg Kryzhanovskiy & Zhanna Shuvalova & Yaroslav Murashov, 2024. "DYFARUS: Dynamic Factor Model to Forecast GDP by Output Using Input-Output Tables," Russian Journal of Money and Finance, Bank of Russia, vol. 83(2), pages 3-25, June.
    5. Mikosch, Heiner & Solanko, Laura, 2017. "Should one follow movements in the oil price or in money supply? Forecasting quarterly GDP growth in Russia with higher-frequency indicators," BOFIT Discussion Papers 19/2017, Bank of Finland Institute for Emerging Economies (BOFIT).
    6. Aizhan Bolatbayeva & Alisher Tolepbergen & Nurdaulet Abilov, 2020. "A macroeconometric model for Russia," Russian Journal of Economics, ARPHA Platform, vol. 6(2), pages 114-143, June.
    7. Fokin, Nikita & Polbin, Andrey, 2019. "A Bivariate Forecasting Model For Russian GDP Under Structural Changes In Monetary Policy and Long-Term Growth," MPRA Paper 95306, University Library of Munich, Germany, revised Apr 2019.
    8. Zhemkov, Michael, 2021. "Nowcasting Russian GDP using forecast combination approach," International Economics, Elsevier, vol. 168(C), pages 10-24.
    9. Stankevich, Ivan, 2023. "Application of Markov-Switching MIDAS models to nowcasting of GDP and its components," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 70, pages 122-143.
    10. Hopp Daniel, 2022. "Economic Nowcasting with Long Short-Term Memory Artificial Neural Networks (LSTM)," Journal of Official Statistics, Sciendo, vol. 38(3), pages 847-873, September.
    11. Stankevich, Ivan, 2020. "Comparison of macroeconomic indicators nowcasting methods: Russian GDP case," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 59, pages 113-127.
    12. Makram El-Shagi & Kiril Tochkov, 2021. "Divisia Monetary Aggregates for Russia: Money Demand, GDP Nowcasting, and the Price Puzzle," CFDS Discussion Paper Series 2021/1, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China.
    13. Heiner Mikosch & Laura Solanko, 2019. "Forecasting Quarterly Russian GDP Growth with Mixed-Frequency Data," Russian Journal of Money and Finance, Bank of Russia, vol. 78(1), pages 19-35, March.
    14. Tóth, Peter, 2014. "Malý dynamický faktorový model na krátkodobé prognózovanie slovenského HDP [A Small Dynamic Factor Model for the Short-Term Forecasting of Slovak GDP]," MPRA Paper 63713, University Library of Munich, Germany.
    15. Dahlhaus, Tatjana & Guénette, Justin-Damien & Vasishtha, Garima, 2017. "Nowcasting BRIC+M in real time," International Journal of Forecasting, Elsevier, vol. 33(4), pages 915-935.
    16. Alexandra Bozhechkova & Urmat Dzhunkeev, 2024. "CLARA and CARLSON: Combination of Ensemble and Neural Network Machine Learning Methods for GDP Forecasting," Russian Journal of Money and Finance, Bank of Russia, vol. 83(3), pages 45-69, September.
    17. Aleksandra Riedl & Julia Wörz, 2018. "A simple approach to nowcasting GDP growth in CESEE economies," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q4/18, pages 56-74.
    18. Vladimir Boyko & Nadezhda Kislyak & Mikhail Nikitin & Oleg Oborin, 2020. "Methods for Estimating the Gross Regional Product Leading Indicator," Russian Journal of Money and Finance, Bank of Russia, vol. 79(3), pages 3-29, September.
    19. Zubarev Andrey & Rybak Konstantin, 2021. "GDP Nowcasting: Dynamic Factor Model vs. Official Forecasts [Наукастинг Ввп: Динамическая Факторная Модель И Официальные Прогнозы]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 12, pages 34-40, December.
    20. Anastasiia Pankratova, 2024. "Forecasting Key Macroeconomic Indicators Using DMA and DMS Methods," Russian Journal of Money and Finance, Bank of Russia, vol. 83(1), pages 32-52, March.
    21. Caruso, Alberto, 2018. "Nowcasting with the help of foreign indicators: The case of Mexico," Economic Modelling, Elsevier, vol. 69(C), pages 160-168.
    22. Daniel Armeanu & Jean Vasile Andrei & Leonard Lache & Mirela Panait, 2017. "A multifactor approach to forecasting Romanian gross domestic product (GDP) in the short run," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-23, July.
    23. Evžen Kočenda & Karen Poghosyan, 2020. "Nowcasting Real GDP Growth: Comparison between Old and New EU Countries," Eastern European Economics, Taylor & Francis Journals, vol. 58(3), pages 197-220, May.
    24. Мекенбаева Камила // Mekenbayeva Kamila & Karel Musil, 2017. "Система прогнозирования в Национальном Банке Казахстана: наукаст на основа опросов // Forecasting system at the National Bank of Kazakhstan: survey-based nowcasting," Working Papers #2017-1, National Bank of Kazakhstan.
    25. Danilo Leiva-Leon & Gabriel Pérez-Quirós & Eyno Rots, 2020. "Real-Time Weakness of the Global Economy: A First Assessment of the Coronavirus Crisis," MNB Working Papers 2020/4, Magyar Nemzeti Bank (Central Bank of Hungary).
    26. Anton Grui & Roman Lysenko, 2017. "Nowcasting Ukraine's GDP Using a Factor-Augmented VAR (FAVAR) Model," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 242, pages 5-13.
    27. Sergey V. Arzhenovskiy, 2024. "Forecasting GDP Dynamics Based on the Bank of Russia’s Enterprise Monitoring Data," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 1, pages 31-44, February.
    28. Andrey Zubarev & Daniil Lomonosov & Konstantin Rybak, 2022. "Estimation of the Impact of Global Shocks on the Russian Economy and GDP Nowcasting Using a Factor Model," Russian Journal of Money and Finance, Bank of Russia, vol. 81(2), pages 49-78, June.
    29. Zubarev Andrey & Rybak Konstantin, 2021. "Наукастинг Ввп: Динамическая Факторная Модель И Официальные Прогнозы," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 12, pages 34-40, December.
    30. Konstantin S. Rybak, 2023. "Evaluating the Role of Global Factors in GDP Nowcasting [Анализ Важности Глобальных Факторов Для Наукастинга Ввп]," Russian Economic Development, Gaidar Institute for Economic Policy, issue 12, pages 18-23, December.

Articles

  1. Porshakov, A. & Ponomarenko, A. & Sinyakov, A., 2016. "Nowcasting and Short-Term Forecasting of Russian GDP with a Dynamic Factor Model," Journal of the New Economic Association, New Economic Association, vol. 30(2), pages 60-76.
    See citations under working paper version above.Sorry, no citations of articles recorded.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 2 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-CIS: Confederation of Independent States (2) 2016-06-09 2017-04-16. Author is listed
  2. NEP-FOR: Forecasting (2) 2016-06-09 2017-04-16. Author is listed
  3. NEP-MAC: Macroeconomics (2) 2016-06-09 2017-04-16. Author is listed

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Alexey Porshakov should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can 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.