IDEAS home Printed from https://ideas.repec.org/p/osf/osfxxx/j3dpm.html
   My bibliography  Save this paper

Strategi Ekonomi Bisnis dalam Upaya Menghadapi Ancaman Resesi 2023

Author

Listed:
  • Nugroho, Anggoro Dimas Pambudi

Abstract

Kasus resesi di tahun mendatang semakin nyata. Disini memaparkan beberapa upaya yang dapat dilakukan untuk menghadapi dan bertahan akan ancaman resesi di tahun mendatang.

Suggested Citation

  • Nugroho, Anggoro Dimas Pambudi, 2022. "Strategi Ekonomi Bisnis dalam Upaya Menghadapi Ancaman Resesi 2023," OSF Preprints j3dpm, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:j3dpm
    DOI: 10.31219/osf.io/j3dpm
    as

    Download full text from publisher

    File URL: https://osf.io/download/639f238050be9e0b25772124/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/j3dpm?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Foroni, Claudia & Marcellino, Massimiliano & Stevanovic, Dalibor, 2022. "Forecasting the Covid-19 recession and recovery: Lessons from the financial crisis," International Journal of Forecasting, Elsevier, vol. 38(2), pages 596-612.
    2. Heejeong Kim, 2022. "Inequality, Disaster risk, and the Great Recession," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 45, pages 187-216, July.
    Full references (including those not matched with items on IDEAS)

    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. Zhao, Xinyue & Chen, Heng & Zheng, Qiwei & Liu, Jun & Pan, Peiyuan & Xu, Gang & Zhao, Qinxin & Jiang, Xue, 2023. "Thermo-economic analysis of a novel hydrogen production system using medical waste and biogas with zero carbon emission," Energy, Elsevier, vol. 265(C).
    2. Baumeister, Christiane & Guérin, Pierre, 2021. "A comparison of monthly global indicators for forecasting growth," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1276-1295.
    3. Rybacki, Jakub & Gniazdowski, Michał, 2021. "Macroeconomic Forecasting in Poland: Lessons From the COVID-19 Outbreak," MPRA Paper 107682, University Library of Munich, Germany.
    4. Valentina Aprigliano & Alessandro Borin & Francesco Paolo Conteduca & Simone Emiliozzi & Marco Flaccadoro & Sabina Marchetti & Stefania Villa, 2021. "Forecasting Italian GDP growth with epidemiological data," Questioni di Economia e Finanza (Occasional Papers) 664, Bank of Italy, Economic Research and International Relations Area.
    5. Jakub Rybacki & Michał Gniazdowski, 2023. "Macroeconomic forecasting in Poland: lessons from the external shocks," Bank i Kredyt, Narodowy Bank Polski, vol. 54(1), pages 45-64.
    6. İsmail Cakmak & Selcen Öztürk, . "Analysing Impact of Economic Crises on Sector Profits with a New Approach," Prague Economic Papers, Prague University of Economics and Business, vol. 0.
    7. Cassetti, Gabriele & Boitier, Baptiste & Elia, Alessia & Le Mouël, Pierre & Gargiulo, Maurizio & Zagamé, Paul & Nikas, Alexandros & Koasidis, Konstantinos & Doukas, Haris & Chiodi, Alessandro, 2023. "The interplay among COVID-19 economic recovery, behavioural changes, and the European Green Deal: An energy-economic modelling perspective," Energy, Elsevier, vol. 263(PC).
    8. Paul Ho, 2021. "Forecasting in the Absence of Precedent," Working Paper 21-10, Federal Reserve Bank of Richmond.
    9. Yannis Psycharis & Anastasia Panori & Dimitrios Athanasopoulos, 2022. "Public Investment and Regional Resilience: Empirical Evidence from the Greek Regions," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 113(1), pages 57-79, February.
    10. Frank Schorfheide & Dongho Song, 2020. "Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic," PIER Working Paper Archive 20-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    11. Jang, Youngsoo, 2021. "Democracy or Optimal Policy: Income Tax Decisions without Commitment," MPRA Paper 110466, University Library of Munich, Germany.
    12. Shafiullah Qureshi & Ba Chu & Fanny S. Demers, 2021. "Forecasting Canadian GDP Growth with Machine Learning," Carleton Economic Papers 21-05, Carleton University, Department of Economics.
    13. Jang, Youngsoo, 2021. "Democracy or Optimal Policy: Income Tax Decisions without Commitment," MPRA Paper 110475, University Library of Munich, Germany.
    14. Sebastian Doerr & Leonardo Gambacorta & José María Serena Garralda, 2021. "Big data and machine learning in central banking," BIS Working Papers 930, Bank for International Settlements.
    15. Archanskaia, Elizaveta & Canton, Erik & Hobza, Alexandr & Nikolov, Plamen & Simons, Wouter, 2023. "The asymmetric impact of COVID-19: A novel approach to quantifying financial distress across industries," European Economic Review, Elsevier, vol. 158(C).
    16. Kevin Moran & Dalibor Stevanovic & Adam Kader Touré, 2022. "Macroeconomic uncertainty and the COVID‐19 pandemic: Measure and impacts on the Canadian economy," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(S1), pages 379-405, February.
    17. Teng, Bin & Wang, Sicong & Shi, Yufeng & Sun, Yunchuan & Wang, Wei & Hu, Wentao & Shi, Chaojun, 2022. "Economic recovery forecasts under impacts of COVID-19," Economic Modelling, Elsevier, vol. 110(C).
    18. Zhang, Qin & Ni, He & Xu, Hao, 2023. "Nowcasting Chinese GDP in a data-rich environment: Lessons from machine learning algorithms," Economic Modelling, Elsevier, vol. 122(C).
    19. Michael Zhemkov, 2021. "Nowcasting Russian GDP using forecast combination approach," International Economics, CEPII research center, issue 168, pages 10-24.
    20. De Backer, Bruno & Dewachter, Hans & Iania, Leonardo, 2021. "Macrofinancial information on the post-COVID-19 economic recovery: Will it be V, U or L-shaped?," Finance Research Letters, Elsevier, vol. 43(C).

    More about this item

    Statistics

    Access and download statistics

    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:osf:osfxxx:j3dpm. 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: OSF (email available below). General contact details of provider: https://osf.io/preprints/ .

    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.