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Petre Caraiani

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. Alvaro Silva & Petre Caraiani & Jorge Miranda-Pinto & Juan Olaya-Agudelo, 2023. "Commodity Price Shocks and Production Networks in Small Open Economies," Working Papers Central Bank of Chile 977, Central Bank of Chile.

    Cited by:

    1. Caraiani, Petre, 2023. "Oil news shocks, inflation expectations and social connectedness," Energy Economics, Elsevier, vol. 127(PB).

  2. Petre Caraiani & Rangan Gupta & Jacobus Nel & Joshua Nielsen, 2022. "Monetary Policy and Bubbles in G7 Economies: Evidence from a Panel VAR Approach," Working Papers 202230, University of Pretoria, Department of Economics.

    Cited by:

    1. Rangan Gupta & Jacobus Nel & Joshua Nielsen, 2022. "US Monetary Policy and BRICS Stock Market Bubbles," Working Papers 202243, University of Pretoria, Department of Economics.

  3. Petre Caraiani & Rangan Gupta & Chi Keung Marco Lau & Hardik A. Marfatia, 2019. "Effects of Conventional and Unconventional Monetary Policy Shocks on Housing Prices in the United States: The Role of Sentiment," Working Papers 201953, University of Pretoria, Department of Economics.

    Cited by:

    1. Gupta, Rangan & Ma, Jun & Theodoridis, Konstantinos & Wohar, Mark E., 2023. "Is there a national housing market bubble brewing in the United States?," Macroeconomic Dynamics, Cambridge University Press, vol. 27(8), pages 2191-2228, December.
    2. Marfatia, Hardik A. & Gupta, Rangan & Cakan, Esin, 2021. "Dynamic impact of the U.S. monetary policy on oil market returns and volatility," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 159-169.
    3. Rui Wang, 2021. "Evaluating the Unconventional Monetary Policy of the Bank of Japan: A DSGE Approach," JRFM, MDPI, vol. 14(6), pages 1-18, June.
    4. Hardik A. Marfatia & Rangan Gupta & Keagile Lesame, 2021. "Dynamic Impact of Unconventional Monetary Policy on International REITs," JRFM, MDPI, vol. 14(9), pages 1-19, September.
    5. Stephanos Papadamou & Νikolaos A. Kyriazis & Panayiotis G. Tzeremes, 2020. "US non-linear causal effects on global equity indices in Normal times versus unconventional eras," International Economics and Economic Policy, Springer, vol. 17(2), pages 381-407, May.

  4. Christophe André & Petre Caraiani & Adrian Cantemir Čalin & Rangan Gupta, 2018. "Can Monetary Policy Lean against Housing Bubbles?," Working Papers 201877, University of Pretoria, Department of Economics.

    Cited by:

    1. Petre Caraiani & Adrian Cantemir Călin, 2019. "Monetary Policy Effects on Energy Sector Bubbles," Energies, MDPI, vol. 12(3), pages 1-13, February.
    2. Petre Caraiani & Rangan Gupta & Jacobus Nel & Joshua Nielsen, 2022. "Monetary Policy and Bubbles in G7 Economies: Evidence from a Panel VAR Approach," Working Papers 202230, University of Pretoria, Department of Economics.
    3. Petre Caraiani & Rangan Gupta & Chi Keung Marco Lau & Hardik A. Marfatia, 2022. "Effects of Conventional and Unconventional Monetary Policy Shocks on Housing Prices in the United States: The Role of Sentiment," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 23(3), pages 241-261, July.
    4. Petre Caraiani & Adrian Cantemir Călin, 2020. "Housing markets, monetary policy, and the international co‐movement of housing bubbles," Review of International Economics, Wiley Blackwell, vol. 28(2), pages 365-375, May.
    5. Renzhi, Nuobu, 2022. "Do house prices play a role in unconventional monetary policy transmission in Japan?," Journal of Asian Economics, Elsevier, vol. 83(C).
    6. Goodness C. Aye & Christina Christou & Rangan Gupta & Christis Hassapis, 2024. "High-Frequency Contagion between Aggregate and Regional Housing Markets of the United States with Financial Assets: Evidence from Multichannel Tests," The Journal of Real Estate Finance and Economics, Springer, vol. 69(2), pages 253-276, August.
    7. Ben-Gad, M. & Pearlman, J. & Sabuga, I., 2021. "An Analysis of Monetary and Macroprudential Policies in a DSGE Model with Reserve Requirements and Mortgage Lending," Working Papers 21/04, Department of Economics, City University London.
    8. Chokri Zehri & Zagros Madjd‐Sadjadi, 2024. "Capital flow management and monetary policy to control credit growth," Economics and Politics, Wiley Blackwell, vol. 36(2), pages 637-676, July.
    9. Yildirim, Zekeriya, 2022. "Global financial risk, the risk-taking channel, and monetary policy in emerging markets," Economic Modelling, Elsevier, vol. 116(C).
    10. Caraiani, Petre & Gupta, Rangan & Nel, Jacobus & Nielsen, Joshua, 2023. "Monetary policy and bubbles in G7 economies using a panel VAR approach: Implications for sustainable development," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 133-155.

  5. Petre Caraiani & Adrian Cantemir Călin & Rangan Gupta, 2018. "Monetary Policy and Bubbles in US REITs," Working Papers 201845, University of Pretoria, Department of Economics.

    Cited by:

    1. Gupta, Rangan & Ma, Jun & Theodoridis, Konstantinos & Wohar, Mark E., 2023. "Is there a national housing market bubble brewing in the United States?," Macroeconomic Dynamics, Cambridge University Press, vol. 27(8), pages 2191-2228, December.
    2. Petre Caraiani & Rangan Gupta & Chi Keung Marco Lau & Hardik A. Marfatia, 2022. "Effects of Conventional and Unconventional Monetary Policy Shocks on Housing Prices in the United States: The Role of Sentiment," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 23(3), pages 241-261, July.
    3. Kola Ijasan & Peterson Owusu Junior & George Tweneboah & Tunbosun Oyedokun & Anokye M. Adam, 2021. "Analysing the relationship between global REITs and exchange rates: Fresh evidence from frequency-based quantile regressions," Advances in Decision Sciences, Asia University, Taiwan, vol. 25(3), pages 58-91, September.
    4. Cepni, Oguzhan & Dul, Wiehan & Gupta, Rangan & Wohar, Mark E., 2021. "The dynamics of U.S. REITs returns to uncertainty shocks: A proxy SVAR approach," Research in International Business and Finance, Elsevier, vol. 58(C).
    5. Yanlin Shi, 2023. "A new unique impulse response function in linear vector autoregressive models," International Review of Finance, International Review of Finance Ltd., vol. 23(2), pages 460-468, June.
    6. Shixuan Wang & Rangan Gupta & Matteo Bonato & Oguzhan Cepni, 2022. "The Effects of Conventional and Unconventional Monetary Policy Shocks on US REITs Moments: Evidence from VARs with Functional Shocks," Working Papers 202219, University of Pretoria, Department of Economics.
    7. Caraiani, Petre & Gupta, Rangan & Nel, Jacobus & Nielsen, Joshua, 2023. "Monetary policy and bubbles in G7 economies using a panel VAR approach: Implications for sustainable development," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 133-155.

  6. Petre Caraiani, 2016. "A quantitative explanation of the low productivity in South-Eastern European economies: the role of misallocations," wiiw Balkan Observatory Working Papers 119, The Vienna Institute for International Economic Studies, wiiw.

    Cited by:

    1. Busu, Mihail & Caraiani, Petre & Hadad, Shahrazad & Incze, Cynthia Bianka & Vargas, Madalina Vanesa, 2021. "The performance of publicly funded startups in Romania," Economic Systems, Elsevier, vol. 45(3).

Articles

  1. Caraiani, Petre & Gupta, Rangan & Nel, Jacobus & Nielsen, Joshua, 2023. "Monetary policy and bubbles in G7 economies using a panel VAR approach: Implications for sustainable development," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 133-155.

    Cited by:

    1. Gupta, Rangan & Nielsen, Joshua & Pierdzioch, Christian, 2024. "Stock market bubbles and the realized volatility of oil price returns," Energy Economics, Elsevier, vol. 132(C).
    2. Cao, Fangzhi & Su, Chi-Wei & Sun, Dian & Qin, Meng & Umar, Muhammad, 2024. "U.S. monetary policy: The pushing hands of crude oil price?," Energy Economics, Elsevier, vol. 134(C).
    3. Mohamed Sadok Gassouma & Adel Benhamed, 2023. "The Impact of the Islamic System on Economic and Social Factors: A Macroeconomic Uncertainty Context," Economies, MDPI, vol. 11(12), pages 1-17, December.
    4. Renee van Eyden & Rangan Gupta & Xin Sheng & Joshua Nielsen, 2023. "Predicting Multi-Scale Positive and Negative Stock Market Bubbles in a Panel of G7 Countries: The Role of Oil Price Uncertainty," Working Papers 202332, University of Pretoria, Department of Economics.
    5. Demirer, Riza & Gabauer, David & Gupta, Rangan & Nielsen, Joshua, 2024. "Gold, platinum and the predictability of bubbles in global stock markets," Resources Policy, Elsevier, vol. 90(C).
    6. Oguzhan Cepni & Rangan Gupta & Jacobus Nel & Joshua Nielsen, 2023. "Monetary Policy Shocks and Multi-Scale Positive and Negative Bubbles in an Emerging Country: The Case of India," Working Papers 202305, University of Pretoria, Department of Economics.
    7. Rangan Gupta & Jacobus Nel & Joshua Nielsen & Christian Pierdzioch, 2023. "Stock Market Volatility and Multi-Scale Positive and Negative Bubbles," Working Papers 202310, University of Pretoria, Department of Economics.
    8. Riza Demirer & David Gabauer & Rangan Gupta & Joshua Nielsen, 2023. "Gold-to-Platinum Price Ratio and the Predictability of Bubbles in Financial Markets," Working Papers 202317, University of Pretoria, Department of Economics.
    9. Karamti, Chiraz & Jeribi, Ahmed, 2023. "Stock markets from COVID-19 to the Russia–Ukraine crisis: Structural breaks in interactive effects panels," The Journal of Economic Asymmetries, Elsevier, vol. 28(C).

  2. Caraiani, Petre, 2022. "The impact of oil supply news shocks on corporate investments and the structure of production network," Energy Economics, Elsevier, vol. 110(C).

    Cited by:

    1. Sardar, Naafey & Qureshi, Irfan, 2024. "Revisiting the relationship between oil supply news shocks and U.S. economic activity: Role of the zero lower bound," Energy Economics, Elsevier, vol. 132(C).
    2. Chen, Lin & Wen, Fenghua & Zhang, Yun & Miao, Xiao, 2023. "Oil supply expectations and corporate social responsibility," International Review of Financial Analysis, Elsevier, vol. 87(C).
    3. Deng, Zhengxing & Hao, Yu, 2024. "Energy price uncertainty, environmental policy, and firm investment: A dynamic modeling approach," Energy Economics, Elsevier, vol. 130(C).
    4. Yin, Libo & Yang, Sen, 2023. "Oil price returns and firm's fixed investment: A production pattern," Energy Economics, Elsevier, vol. 125(C).
    5. Wei, Yanfeng & Qiu, Feng & An, Henry & Zhang, Xindon & Li, Changhong & Guo, Xiaoying, 2024. "Exogenous oil supply shocks and global agricultural commodity prices: The role of biofuels," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 394-414.

  3. Petre Caraiani & Rangan Gupta & Chi Keung Marco Lau & Hardik A. Marfatia, 2022. "Effects of Conventional and Unconventional Monetary Policy Shocks on Housing Prices in the United States: The Role of Sentiment," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 23(3), pages 241-261, July.
    See citations under working paper version above.
  4. André, Christophe & Caraiani, Petre & Călin, Adrian Cantemir & Gupta, Rangan, 2022. "Can monetary policy lean against housing bubbles?," Economic Modelling, Elsevier, vol. 110(C).
    See citations under working paper version above.
  5. Caraiani, Petre, 2022. "Using LASSO-family models to estimate the impact of monetary policy on corporate investments," Economics Letters, Elsevier, vol. 210(C).

    Cited by:

    1. Samer Adra & Elie Menassa, 2023. "Uncertainty and corporate investments in response to the Fed's dual shocks," The Financial Review, Eastern Finance Association, vol. 58(3), pages 463-484, August.

  6. Busu, Mihail & Caraiani, Petre & Hadad, Shahrazad & Incze, Cynthia Bianka & Vargas, Madalina Vanesa, 2021. "The performance of publicly funded startups in Romania," Economic Systems, Elsevier, vol. 45(3).

    Cited by:

    1. Anabela Marques Santos & Michele Cincera & Giovanni Cerulli, 2024. "Sources of financing: Which ones are more effective in innovation–growth linkage?," ULB Institutional Repository 2013/372408, ULB -- Universite Libre de Bruxelles.
    2. Călinescu Gabriela, 2023. "Clusters, Business Planning and Economic Growth: Stockholm’s Artificial Intelligence and Big Data Cluster," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 17(1), pages 1584-1594, July.
    3. Mueller, Christoph E., 2023. "Startup grants and the development of academic startup projects during funding: Quasi-experimental evidence from the German ‘EXIST – Business startup grant’," Journal of Business Venturing Insights, Elsevier, vol. 20(C).

  7. Petre Caraiani & Adrian C. Călin & Rangan Gupta, 2021. "Monetary policy and bubbles in US REITs," International Review of Finance, International Review of Finance Ltd., vol. 21(2), pages 675-687, June.
    See citations under working paper version above.
  8. Petre Caraiani & Adrian Cantemir Călin, 2020. "Housing markets, monetary policy, and the international co‐movement of housing bubbles," Review of International Economics, Wiley Blackwell, vol. 28(2), pages 365-375, May.

    Cited by:

    1. Shahriyar Aliev & Evžen Kočenda, 2022. "ECB monetary policy and commodity prices," FFA Working Papers 4.008, Prague University of Economics and Business, revised 21 Jun 2022.
    2. Caraiani, Petre & Gupta, Rangan & Nel, Jacobus & Nielsen, Joshua, 2023. "Monetary policy and bubbles in G7 economies using a panel VAR approach: Implications for sustainable development," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 133-155.

  9. Caraiani, Petre & Dutescu, Adriana & Hoinaru, Răzvan & Stănilă, Georgiana Oana, 2020. "Production network structure and the impact of the monetary policy shocks: Evidence from the OECD," Economics Letters, Elsevier, vol. 193(C).

    Cited by:

    1. Păcuraru-Ionescu Cătălin-Paul & Cîmpan Marius & Borlea Sorin Nicolae, 2023. "Determinants of Audit Quality and Connections with Economic Development and Education," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 17(1), pages 741-751, July.
    2. Petre Caraiani, 2023. "Monetary Policy Shocks and Input–Output Characteristics of Production Networks," JRFM, MDPI, vol. 16(3), pages 1-13, March.
    3. Caraiani, Petre, 2022. "The impact of oil supply news shocks on corporate investments and the structure of production network," Energy Economics, Elsevier, vol. 110(C).

  10. Caraiani, Petre & Cǎlin, Adrian Cantemir, 2020. "The impact of monetary policy shocks on stock market bubbles: International evidence," Finance Research Letters, Elsevier, vol. 34(C).

    Cited by:

    1. Christophe André & Petre Caraiani & Adrian Cantemir Čalin & Rangan Gupta, 2018. "Can Monetary Policy Lean against Housing Bubbles?," Working Papers 201877, University of Pretoria, Department of Economics.
    2. Vasilios Plakandaras & Rangan Gupta & Mehmet Balcilar & Qiang Ji, 2021. "Evolving United States Stock Market Volatility: The Role of Conventional and Unconventional Monetary Policies," Working Papers 202113, University of Pretoria, Department of Economics.
    3. Yang, Yang & Tang, Yanling & Cheng, Kai, 2023. "Spillback effects of US unconventional monetary policy," Finance Research Letters, Elsevier, vol. 53(C).
    4. Oguzhan Cepni & Rangan Gupta & Qiang Ji, 2021. "Sentiment Regimes and Reaction of Stock Markets to Conventional and Unconventional Monetary Policies: Evidence from OECD Countries," Working Papers 202126, University of Pretoria, Department of Economics.

  11. Petre Caraiani & Adrian Cantemir Călin, 2019. "Monetary Policy Effects on Energy Sector Bubbles," Energies, MDPI, vol. 12(3), pages 1-13, February.

    Cited by:

    1. Aslam, Faheem & Hunjra, Ahmed Imran & Memon, Bilal Ahmed & Zhang, Mingda, 2024. "Interplay of multifractal dynamics between shadow policy rates and energy markets," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    2. Radu Lupu & Adrian Cantemir Călin & Cristina Georgiana Zeldea & Iulia Lupu, 2021. "Systemic Risk Spillovers in the European Energy Sector," Energies, MDPI, vol. 14(19), pages 1-23, October.

  12. Caraiani, Petre, 2019. "Oil shocks and production network structure: Evidence from the OECD," Energy Economics, Elsevier, vol. 84(C).

    Cited by:

    1. Petre Caraiani, 2023. "Monetary Policy Shocks and Input–Output Characteristics of Production Networks," JRFM, MDPI, vol. 16(3), pages 1-13, March.
    2. Caraiani, Petre, 2023. "Oil news shocks, inflation expectations and social connectedness," Energy Economics, Elsevier, vol. 127(PB).
    3. Wei, Na & Xie, Wen-Jie & Zhou, Wei-Xing, 2022. "Robustness of the international oil trade network under targeted attacks to economies," Energy, Elsevier, vol. 251(C).
    4. Caraiani, Petre & Dutescu, Adriana & Hoinaru, Răzvan & Stănilă, Georgiana Oana, 2020. "Production network structure and the impact of the monetary policy shocks: Evidence from the OECD," Economics Letters, Elsevier, vol. 193(C).
    5. Na Wei & Wen-Jie Xie & Wei-Xing Zhou, 2024. "Resilience of international oil trade networks under extreme event shock-recovery simulations," Papers 2406.11467, arXiv.org.
    6. Caraiani, Petre, 2022. "The impact of oil supply news shocks on corporate investments and the structure of production network," Energy Economics, Elsevier, vol. 110(C).
    7. N. Wei & W. -J. Xie & W. -X. Zhou, 2021. "Robustness of the international oil trade network under targeted attacks to economies," Papers 2101.10679, arXiv.org, revised Jan 2021.
    8. Xie, Wen-Jie & Wei, Na & Zhou, Wei-Xing, 2023. "An interpretable machine-learned model for international oil trade network," Resources Policy, Elsevier, vol. 82(C).

  13. Petre Caraiani, 2018. "A quantitative explanation of the low productivity in South–Eastern European economies: the role of misallocations," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 45(4), pages 707-745, November.
    See citations under working paper version above.
  14. Caraiani, Petre & Călin, Adrian Cantemir, 2018. "The effects of monetary policy on stock market bubbles at zero lower bound: Revisiting the evidence," Economics Letters, Elsevier, vol. 169(C), pages 55-58.

    Cited by:

    1. Petre Caraiani & Adrian Cantemir Călin, 2019. "Monetary Policy Effects on Energy Sector Bubbles," Energies, MDPI, vol. 12(3), pages 1-13, February.
    2. Oguzhan Cepni & Rangan Gupta, 2020. "Time-Varying Impact of Monetary Policy Shocks on U.S. Stock Returns: The Role of Investor Sentiment," Working Papers 202039, University of Pretoria, Department of Economics.
    3. Petre Caraiani & Adrian C. Călin & Rangan Gupta, 2021. "Monetary policy and bubbles in US REITs," International Review of Finance, International Review of Finance Ltd., vol. 21(2), pages 675-687, June.
    4. Christophe André & Petre Caraiani & Adrian Cantemir Čalin & Rangan Gupta, 2018. "Can Monetary Policy Lean against Housing Bubbles?," Working Papers 201877, University of Pretoria, Department of Economics.
    5. Petre Caraiani & Adrian Cantemir Călin, 2020. "Housing markets, monetary policy, and the international co‐movement of housing bubbles," Review of International Economics, Wiley Blackwell, vol. 28(2), pages 365-375, May.
    6. Oguzhan Cepni & Rangan Gupta & Jacobus Nel & Joshua Nielsen, 2023. "Monetary Policy Shocks and Multi-Scale Positive and Negative Bubbles in an Emerging Country: The Case of India," Working Papers 202305, University of Pretoria, Department of Economics.
    7. Vasilios Plakandaras & Rangan Gupta & Mehmet Balcilar & Qiang Ji, 2021. "Evolving United States Stock Market Volatility: The Role of Conventional and Unconventional Monetary Policies," Working Papers 202113, University of Pretoria, Department of Economics.
    8. Oguzhan Cepni & Rangan Gupta & Qiang Ji, 2021. "Sentiment Regimes and Reaction of Stock Markets to Conventional and Unconventional Monetary Policies: Evidence from OECD Countries," Working Papers 202126, University of Pretoria, Department of Economics.
    9. Wang, Shengquan & Chen, Langnan, 2019. "Driving factors of equity bubbles," The North American Journal of Economics and Finance, Elsevier, vol. 49(C), pages 304-317.
    10. Caraiani, Petre & Luik, Marc-André & Wesselbaum, Dennis, 2020. "Credit policy and asset price bubbles," Journal of Macroeconomics, Elsevier, vol. 65(C).
    11. Aymeric Ortmans, 2020. "Evolving Monetary Policy in the Aftermath of the Great Recession," Documents de recherche 20-01, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
    12. Caraiani, Petre & Cǎlin, Adrian Cantemir, 2020. "The impact of monetary policy shocks on stock market bubbles: International evidence," Finance Research Letters, Elsevier, vol. 34(C).
    13. Caraiani, Petre & Gupta, Rangan & Nel, Jacobus & Nielsen, Joshua, 2023. "Monetary policy and bubbles in G7 economies using a panel VAR approach: Implications for sustainable development," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 133-155.
    14. Caraiani, Petre & Călin, Adrian Cantemir, 2024. "The comovement of bubbles’ responses to monetary policy shocks," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
    15. Yang, Jinyu & Dong, Dayong & Liang, Chao & Cao, Yang, 2024. "Monetary policy uncertainty and the price bubbles in energy markets," Energy Economics, Elsevier, vol. 133(C).
    16. Lee, Changju & Ku, Seungmo & Cho, Poongjin & Chang, Woojin, 2019. "Explaining future market return and evaluating market condition with common preferred spread index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 921-934.

  15. Caraiani, Petre, 2017. "Evaluating exchange rate forecasts along time and frequency," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 60-81.

    Cited by:

    1. Manuel M. F. Martins & Fabio Verona, 2020. "Forecasting Inflation with the New Keynesian Phillips Curve: Frequency Matters," CEF.UP Working Papers 2001, Universidade do Porto, Faculdade de Economia do Porto.
    2. Martins, Manuel Mota Freitas & Verona, Fabio, 2021. "Inflation dynamics and forecast: Frequency matters," Bank of Finland Research Discussion Papers 8/2021, Bank of Finland.
    3. Caraiani, Petre & Gupta, Rangan, 2020. "Is the response of the bank of England to exchange rate movements frequency-dependent?," Journal of Macroeconomics, Elsevier, vol. 63(C).
    4. He, Kaijian & Chen, Yanhui & Tso, Geoffrey K.F., 2018. "Forecasting exchange rate using Variational Mode Decomposition and entropy theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 15-25.
    5. Salisu, Afees A. & Gupta, Rangan & Kim, Won Joong, 2022. "Exchange rate predictability with nine alternative models for BRICS countries," Journal of Macroeconomics, Elsevier, vol. 71(C).
    6. Chang, Carolyn W. & Wang, Yu-Jen & Yu, Min-Teh, 2020. "Catastrophe bond spread and hurricane arrival frequency," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    7. Alexandros Pasiouras & Theodoros Daglis, 2020. "The Dollar Exchange Rates in the Covid-19 Era: Evidence from 5 Currencies," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 2), pages 352-361.
    8. Tasadduq Imam, 2021. "Model selection for one‐day‐ahead AUD/USD, AUD/EUR forecasts," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 1808-1824, April.
    9. Gonçalo Faria & Fabio Verona, 2021. "Time-frequency forecast of the equity premium," Quantitative Finance, Taylor & Francis Journals, vol. 21(12), pages 2119-2135, December.
    10. Konstantinos N. Konstantakis & Ioannis G. Melissaropoulos & Theodoros Daglis & Panayotis G. Michaelides, 2023. "The euro to dollar exchange rate in the Covid‐19 era: Evidence from spectral causality and Markov‐switching estimation," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 2037-2055, April.

  16. Caraiani, Petre, 2016. "The role of money in DSGE models: a forecasting perspective," Journal of Macroeconomics, Elsevier, vol. 47(PB), pages 315-330.

    Cited by:

    1. Jonathan Benchimol, 2016. "Money and monetary policy in Israel during the last decade," Post-Print hal-01272174, HAL.
    2. Kőrösi, Gábor, 2016. "A lány továbbra is szolgál.. [Modelling and econometrics]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(6), pages 647-667.
    3. Jonathan Benchimol & Makram El-Shagi, 2017. "Forecast Performance in Times of Terrorism," CFDS Discussion Paper Series 2017/1, Center for Financial Development and Stability at Henan University, Kaifeng, Henan, China.
    4. Roberta Cardani & Alessia Paccagnini & Stefania Villa, 2019. "Forecasting with instabilities: an application to DSGE models with financial frictions," Temi di discussione (Economic working papers) 1234, Bank of Italy, Economic Research and International Relations Area.

  17. Caraiani, Petre, 2016. "Money and output causality: A structural approach," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 220-236.

    Cited by:

    1. Donato Masciandaro, 2023. "How Elastic and Predictable Money Should Be: Flexible Monetary Policy Rules from the Great Moderation to the New Normal Times (1993-2023)," BAFFI CAREFIN Working Papers 23196, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    2. D. Masciandaro, 2019. "What Bird Is That? Central Banking And Monetary Policy In The Last Forty Years," BAFFI CAREFIN Working Papers 19127, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    3. Donato Masciandaro & Romano Vincenzo Tarsia, 2021. "Society, Politicians, Climate Change and Central Banks: An Index of Green Activism," BAFFI CAREFIN Working Papers 21167, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    4. Keating, John W. & Smith, A. Lee, 2019. "The optimal monetary instrument and the (mis)use of causality tests," Journal of Financial Stability, Elsevier, vol. 42(C), pages 90-99.
    5. Tomáš Urbanovský, 2017. "Granger Causalities Between Interest Rate, Price Level, Money Supply and Real Gdp in the Czech Republic," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 65(2), pages 745-757.
    6. Caraiani, Petre, 2017. "Evaluating exchange rate forecasts along time and frequency," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 60-81.

  18. Caraiani, Petre, 2015. "Estimating DSGE models across time and frequency," Journal of Macroeconomics, Elsevier, vol. 44(C), pages 33-49.

    Cited by:

    1. Fratianni, Michele & Gallegati, Marco & Giri, Federico, 2022. "The medium-run Phillips curve: A time–frequency investigation for the UK," Journal of Macroeconomics, Elsevier, vol. 73(C).
    2. Faria, Gonçalo & Verona, Fabio, 2020. "The yield curve and the stock market: Mind the long run," Journal of Financial Markets, Elsevier, vol. 50(C).
    3. Caraiani, Petre & Gupta, Rangan, 2020. "Is the response of the bank of England to exchange rate movements frequency-dependent?," Journal of Macroeconomics, Elsevier, vol. 63(C).
    4. Gallegati, Marco & Giri, Federico & Palestrini, Antonio, 2019. "DSGE model with financial frictions over subsets of business cycle frequencies," Journal of Economic Dynamics and Control, Elsevier, vol. 100(C), pages 152-163.
    5. Fan, Ying, 2022. "Demand shocks and price stickiness in housing market dynamics," Economic Modelling, Elsevier, vol. 110(C).
    6. Sui, Jianli & Liu, Biying & Li, Zhigang & Zhang, Chengping, 2022. "Monetary and macroprudential policies, output, prices, and financial stability," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 212-233.
    7. Gonçalo Faria & Fabio Verona, 2016. "Forecasting the equity risk premium with frequency-decomposed predictors," Working Papers de Economia (Economics Working Papers) 06, Católica Porto Business School, Universidade Católica Portuguesa.
    8. Caraiani, Petre, 2017. "Evaluating exchange rate forecasts along time and frequency," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 60-81.

  19. Petre Caraiani, 2014. "Do money and financial variables help forecasting output in emerging European Economies?," Empirical Economics, Springer, vol. 46(2), pages 743-763, March.

    Cited by:

    1. Dimitris P. Louzis, 2014. "Macroeconomic and credit forecasts in a small economy during crisis: A large Bayesian VAR approach," Working Papers 184, Bank of Greece.
    2. Dimitrios P. Louzis, 2017. "Macroeconomic and credit forecasts during the Greek crisis using Bayesian VARs," Empirical Economics, Springer, vol. 53(2), pages 569-598, September.

  20. Caraiani, Petre, 2014. "The predictive power of singular value decomposition entropy for stock market dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 571-578.

    Cited by:

    1. Gu, Rongbao & Shao, Yanmin, 2016. "How long the singular value decomposed entropy predicts the stock market? — Evidence from the Dow Jones Industrial Average Index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 150-161.
    2. Daniel Chiew & Judy Qiu & Sirimon Treepongkaruna & Jiping Yang & Chenxiao Shi, 2019. "The predictive ability of the expected utility-entropy based fund rating approach: A comparison investigation with Morningstar ratings in US," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-22, April.
    3. Alvarez-Ramirez, Jose & Rodriguez, Eduardo, 2021. "A singular value decomposition entropy approach for testing stock market efficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    4. Jiang, Jiaqi & Gu, Rongbao, 2016. "Using Rényi parameter to improve the predictive power of singular value decomposition entropy on stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 254-264.
    5. Gu, Rongbao & Xiong, Wei & Li, Xinjie, 2015. "Does the singular value decomposition entropy have predictive power for stock market? — Evidence from the Shenzhen stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 439(C), pages 103-113.
    6. Heiberger, Raphael H., 2018. "Predicting economic growth with stock networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 489(C), pages 102-111.
    7. Deshen Wang, 2017. "Adjustable Robust Singular Value Decomposition: Design, Analysis and Application to Finance," Data, MDPI, vol. 2(3), pages 1-15, August.
    8. Caraiani, Petre, 2017. "The predictive power of local properties of financial networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 79-90.
    9. Civitarese, Jamil, 2016. "Volatility and correlation-based systemic risk measures in the US market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 459(C), pages 55-67.
    10. Espinosa-Paredes, G. & Rodriguez, E. & Alvarez-Ramirez, J., 2022. "A singular value decomposition entropy approach to assess the impact of Covid-19 on the informational efficiency of the WTI crude oil market," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    11. Gu, Rongbao, 2017. "Multiscale Shannon entropy and its application in the stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 215-224.
    12. Ku, Seungmo & Lee, Changju & Chang, Woojin & Wook Song, Jae, 2020. "Fractal structure in the S&P500: A correlation-based threshold network approach," Chaos, Solitons & Fractals, Elsevier, vol. 137(C).

  21. Caraiani, Petre, 2014. "What drives the nonlinearity of time series: A frequency perspective," Economics Letters, Elsevier, vol. 125(1), pages 40-42.

    Cited by:

    1. Benjamas Jirasakuldech & Riza Emekter & Thuy Bui, 2023. "Non-linear structures, chaos, and bubbles in U.S. regional housing markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(1), pages 63-93, March.
    2. Xu, Chao & Zhao, Xiaojun & Wang, Yanwen, 2022. "Causal decomposition on multiple time scales: Evidence from stock price-volume time series," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).

  22. Petre Caraiani, 2013. "The uncertain unit root in GDP and CPI: a wavelet-based perspective," Applied Economics Letters, Taylor & Francis Journals, vol. 20(3), pages 297-299, February.

    Cited by:

    1. Stelios Bekiros & Duc Khuong Nguyen & Gazi Salah Uddin & Bo Sjö, 2014. "Business Cycle (De)Synchronization in the Aftermath of the Global Financial Crisis: Implications for the Euro Area," Working Papers 2014-437, Department of Research, Ipag Business School.

  23. Petre Caraiani, 2013. "Using Complex Networks to Characterize International Business Cycles," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-13, March.

    Cited by:

    1. Jonathan E. Ogbuabor & God’stime O. Eigbiremolen & Gladys C. Aneke & Manasseh O. Charles, 2018. "Measuring the dynamics of APEC output connectedness," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 32(1), pages 29-44, May.
    2. Ekeocha, Patterson & Ogbuabor, Jonathan, 2020. "Measuring and Evaluating the Dynamics of Trade Shock Propagation in the Oceania," Conference papers 333234, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    3. Ekeocha, Patterson & Ogbuabor, Jonathan, 2019. "Trade Shock Transmission: A Study of Selected African Economies, the BRIC and the Rest of the Global Economy," Conference papers 333085, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    4. Jonathan E. Ogbuabor & Anthony Orji & Gladys C. Aneke & Oyun Erdene-Urnukh, 2016. "Measuring the Real and Financial Connectedness of Selected African Economies with the Global Economy," South African Journal of Economics, Economic Society of South Africa, vol. 84(3), pages 364-399, September.
    5. Yong Tang & Jason Jie Xiong & Zi-Yang Jia & Yi-Cheng Zhang, 2018. "Complexities in Financial Network Topological Dynamics: Modeling of Emerging and Developed Stock Markets," Complexity, Hindawi, vol. 2018, pages 1-31, November.
    6. Michail Tsagris, 2021. "A New Scalable Bayesian Network Learning Algorithm with Applications to Economics," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 341-367, January.
    7. Theophilos Papadimitriou & Periklis Gogas & Georgios Sarantitis, 2016. "Convergence of European Business Cycles: A Complex Networks Approach," Computational Economics, Springer;Society for Computational Economics, vol. 47(2), pages 97-119, February.
    8. Antonakakis, Nikolaos & Gogas, Periklis & Papadimitriou, Theophilos & Sarantitis, Georgios Antonios, 2016. "International business cycle synchronization since the 1870s: Evidence from a novel network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 286-296.
    9. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    10. Anna Maria D’Arcangelis & Giulia Rotundo, 2016. "Complex Networks in Finance," Lecture Notes in Economics and Mathematical Systems, in: Pasquale Commendatore & Mariano Matilla-García & Luis M. Varela & Jose S. Cánovas (ed.), Complex Networks and Dynamics, pages 209-235, Springer.
    11. Amalia Repele & Sébastien Waelti, 2021. "Mapping the Global Business Cycle Network," Open Economies Review, Springer, vol. 32(4), pages 739-760, September.
    12. Theophilos Papadimitriou & Periklis Gogas & Fotios Gkatzoglou, 2022. "The Convergence Evolution in Europe from a Complex Networks Perspective," JRFM, MDPI, vol. 15(10), pages 1-14, October.
    13. Ogbuabor, Jonathan E. & Anthony-Orji, Onyinye I. & Manasseh, Charles O. & Orji, Anthony, 2020. "Measuring the dynamics of COMESA output connectedness with the global economy," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
    14. Matesanz, David & Ortega, Guillermo J., 2016. "On business cycles synchronization in Europe: A note on network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 287-296.

  24. Caraiani, Petre, 2013. "Testing for nonlinearity and chaos in economic time series with noise titration," Economics Letters, Elsevier, vol. 120(2), pages 192-194.

    Cited by:

    1. Tianbao Zhou & Xinghao Li & Peng Wang, 2021. "Statistics and Practice on the Trend’s Reversal and Turning Points of Chinese Stock Indices Based on Gann’s Time Theory and Solar Terms Effect," Mathematics, MDPI, vol. 9(15), pages 1-24, July.
    2. Leutcho, Gervais Dolvis & Kengne, Jacques, 2018. "A unique chaotic snap system with a smoothly adjustable symmetry and nonlinearity: Chaos, offset-boosting, antimonotonicity, and coexisting multiple attractors," Chaos, Solitons & Fractals, Elsevier, vol. 113(C), pages 275-293.
    3. Lucía Inglada-Pérez & Pablo Coto-Millán, 2021. "A Chaos Analysis of the Dry Bulk Shipping Market," Mathematics, MDPI, vol. 9(17), pages 1-35, August.
    4. Claudiu Tiberiu Albulescu & Aviral Kumar Tiwari & Phouphet Kyophilavong, 2021. "Nonlinearities and Chaos: A New Analysis of CEE Stock Markets," Mathematics, MDPI, vol. 9(7), pages 1-13, March.

  25. Caraiani, Petre, 2013. "Comparing monetary policy rules in CEE economies: A Bayesian approach," Economic Modelling, Elsevier, vol. 32(C), pages 233-246.

    Cited by:

    1. Benchimol, Jonathan, 2024. "Central bank objectives, monetary policy rules, and limited information," Journal of Macroeconomics, Elsevier, vol. 80(C).
    2. Georgios Georgiadis & Martina Jancokova, 2017. "Financial Globalisation, Monetary Policy Spillovers and Macro-modelling: Tales from 1001 Shocks," Globalization Institute Working Papers 314, Federal Reserve Bank of Dallas.
    3. Caraiani, Petre & Gupta, Rangan, 2020. "Is the response of the bank of England to exchange rate movements frequency-dependent?," Journal of Macroeconomics, Elsevier, vol. 63(C).
    4. Paweł Baranowski & Paweł Gajewski, 2016. "Credible enough? Forward guidance and perceived National Bank of Poland's policy rule," Applied Economics Letters, Taylor & Francis Journals, vol. 23(2), pages 89-92, February.
    5. Valeriu Nalban, 2015. "A small New Keynesian model to analyze business cycle dynamics in Poland and Romania," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 9(3), September.
    6. Alina BOBAŞU & Bogdan MURARAȘU, 2021. "Fiscal and Monetary Policy Interactions in a DSGE Model for the Romanian Economy," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 5-21, June.
    7. Iulian Vasile Popescu, 2014. "The impact of the recent global crisis on the prioritization of central banks final objectives. A structural approach in the context of Central and Eastern European states," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, vol. 7(2), pages 51-76, September.
    8. Maciej Ryczkowski, 2016. "Poland as an inflation nutter:The story of successful output stabilization," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 34(2), pages 363-392.

  26. Caraiani, Petre, 2012. "Stylized facts of business cycles in a transition economy in time and frequency," Economic Modelling, Elsevier, vol. 29(6), pages 2163-2173.

    Cited by:

    1. Pontines, Victor, 2017. "The financial cycles in four East Asian economies," Economic Modelling, Elsevier, vol. 65(C), pages 51-66.
    2. Aviral Tiwari & Niyati Bhanja & Arif Dar & Faridul Islam, 2015. "Time–frequency relationship between share prices and exchange rates in India: Evidence from continuous wavelets," Empirical Economics, Springer, vol. 48(2), pages 699-714, March.
    3. Özmen, M. Utku & Yılmaz, Erdal, 2017. "Co-movement of exchange rates with interest rate differential, risk premium and FED policy in “fragile economies”," Emerging Markets Review, Elsevier, vol. 33(C), pages 173-188.
    4. Verona, Fabio, 2016. "Time-frequency characterization of the U.S. financial cycle," Bank of Finland Research Discussion Papers 14/2016, Bank of Finland.
    5. Rita Sousa & Luís Aguiar-Conraria & Maria Joana Soares, 2014. "Carbon Financial Markets: a time-frequency analysis of CO2 price drivers," NIPE Working Papers 03/2014, NIPE - Universidade do Minho.
    6. Funashima, Yoshito, 2017. "Time-varying leads and lags across frequencies using a continuous wavelet transform approach," Economic Modelling, Elsevier, vol. 60(C), pages 24-28.
    7. Andrieș, Alin Marius & Căpraru, Bogdan & Ihnatov, Iulian & Tiwari, Aviral Kumar, 2017. "The relationship between exchange rates and interest rates in a small open emerging economy: The case of Romania," Economic Modelling, Elsevier, vol. 67(C), pages 261-274.
    8. Bilgili, Faik, 2015. "Business cycle co-movements between renewables consumption and industrial production: A continuous wavelet coherence approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 325-332.
    9. Tiwari, Aviral Kumar & Albulescu, Claudiu Tiberiu, 2016. "Oil price and exchange rate in India: Fresh evidence from continuous wavelet approach and asymmetric, multi-horizon Granger-causality tests," Applied Energy, Elsevier, vol. 179(C), pages 272-283.
    10. Luís Aguiar-Conraria & Maria Joana Soares, 2014. "The Continuous Wavelet Transform: Moving Beyond Uni- And Bivariate Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 28(2), pages 344-375, April.
    11. M. Utku Ozmen & Erdal Yilmaz, 2016. "Co-movement of Exchange Rates with Interest Rate Differential, Risk Premium and FED Policy in �Fragile Economies�," Working Papers 1621, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    12. Chen, Mei-Ping & Chen, Wen-Yi & Tseng, Tseng-Chan, 2017. "Co-movements of returns in the health care sectors from the US, UK, and Germany stock markets: Evidence from the continuous wavelet analyses," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 484-498.
    13. Abid, Fathi & Kaffel, Bilel, 2018. "Time–frequency wavelet analysis of the interrelationship between the global macro assets and the fear indexes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1028-1045.
    14. Funashima, Yoshito, 2016. "Governmentally amplified output volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 469-478.
    15. Fousekis, Panos & Grigoriadis, Vasilis, 2016. "Spatial price dependence by time scale: Empirical evidence from the international butter markets," Economic Modelling, Elsevier, vol. 54(C), pages 195-204.
    16. Jena, Sangram Keshari & Tiwari, Aviral Kumar & Roubaud, David, 2018. "Comovements of gold futures markets and the spot market: A wavelet analysis," Finance Research Letters, Elsevier, vol. 24(C), pages 19-24.

  27. Caraiani, Petre, 2012. "Nonlinear dynamics in CEE stock markets indices," Economics Letters, Elsevier, vol. 114(3), pages 329-331.

    Cited by:

    1. Balcilar, Mehmet & Bathia, Deven & Demirer, Riza & Gupta, Rangan, 2021. "Credit ratings and predictability of stock return dynamics of the BRICS and the PIIGS: Evidence from a nonparametric causality-in-quantiles approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 290-302.
    2. Mirzaee Ghazani, Majid & Khalili Araghi, Mansour, 2014. "Evaluation of the adaptive market hypothesis as an evolutionary perspective on market efficiency: Evidence from the Tehran stock exchange," Research in International Business and Finance, Elsevier, vol. 32(C), pages 50-59.
    3. Juan Benjamín Duarte Duarte & Juan Manuel Mascare?nas Pérez-Iñigo, 2014. "Comprobación de la eficiencia débil en los principales mercados financieros latinoamericanos," Estudios Gerenciales, Universidad Icesi, November.
    4. Urquhart, Andrew & Hudson, Robert, 2013. "Efficient or adaptive markets? Evidence from major stock markets using very long run historic data," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 130-142.
    5. Babangida, Jamilu Said, 2023. "Nonlinearity in emerging market indices: A comprehensive study of stock exchange market dynamics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 72, pages 23-37.
    6. Juan Benjamín Duarte Duarte & Juan Manuel Mascareñas Pérez-Iñigo, 2014. "¿Han sido los mercados bursátiles eficientes informacionalmente?," Apuntes del Cenes, Universidad Pedagógica y Tecnológica de Colombia, June.
    7. Claudiu Tiberiu Albulescu & Aviral Kumar Tiwari & Phouphet Kyophilavong, 2021. "Nonlinearities and Chaos: A New Analysis of CEE Stock Markets," Mathematics, MDPI, vol. 9(7), pages 1-13, March.
    8. Mehmet Balcilar & Riza Demirer, 2022. "U.S. monetary policy and the predictability of global economic synchronization patterns," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(3), pages 473-492, July.

  28. Caraiani, Petre, 2012. "Money and output: New evidence based on wavelet coherence," Economics Letters, Elsevier, vol. 116(3), pages 547-550.

    Cited by:

    1. Jens J. Krüger, 2021. "A Wavelet Evaluation of Some Leading Business Cycle Indicators for the German Economy," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(3), pages 293-319, December.
    2. Tiwari, Aviral Kumar & Kumar, Satish & Pathak, Rajesh & Roubaud, David, 2019. "Testing the oil price efficiency using various measures of long-range dependence," Energy Economics, Elsevier, vol. 84(C).
    3. Taniya Ghosh & Abhishek Gorsi, 2023. "Money and output asymmetry: The Unintended consequences of central banks' obsession with inflation," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2023-07, Indira Gandhi Institute of Development Research, Mumbai, India.
    4. Chang, Chun-Ping & Lee, Chien-Chiang, 2015. "Do oil spot and futures prices move together?," Energy Economics, Elsevier, vol. 50(C), pages 379-390.
    5. Verona, Fabio, 2016. "Time-frequency characterization of the U.S. financial cycle," Bank of Finland Research Discussion Papers 14/2016, Bank of Finland.
    6. Yingying XU & Zhixin LIU & Jaime ORTIZ, 2018. "Actual and Expected Inflation in the U.S.: A Time-Frequency View," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 42-62, December.
    7. Gandjon Fankem, Gislain Stéphane & Fouda Mbesa, Lucien Cédric, 2023. "Business cycle synchronization and African monetary union: A wavelet analysis," Journal of Macroeconomics, Elsevier, vol. 77(C).
    8. Jiang, Chun & Chang, Tsangyao & Li, Xiao-Lin, 2015. "Money growth and inflation in China: New evidence from a wavelet analysis," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 249-261.
    9. Yoshito Funashima, 2018. "Macroeconomic policy coordination between Japanese central and local governments," Empirical Economics, Springer, vol. 54(4), pages 1631-1651, June.
    10. Mihai Mutascu & Alexandre Sokic, 2023. "An extended wavelet approach of the money–output link in the United States," Empirical Economics, Springer, vol. 64(4), pages 1647-1665, April.
    11. Funashima, Yoshito, 2014. "Macroeconomic policy coordination between Japanese central and local governments," MPRA Paper 59821, University Library of Munich, Germany.
    12. Musa, Mustafa & Masih, Mansur, 2016. "Are the ASEAN stock markets integrated with the US market ? new evidence from wavelet coherence," MPRA Paper 101256, University Library of Munich, Germany.
    13. Funashima, Yoshito, 2015. "Automatic stabilizers in the Japanese tax system," Journal of Asian Economics, Elsevier, vol. 39(C), pages 86-93.
    14. Su-Ling TSAI & Tsangyao CHANG, 2018. "The Comovment between Money and Economic Growth in 15 Asia-Pacific Countries: Wavelet Coherency Analysis in Time-Frequency Domain," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 63-79, December.
    15. Chun-Ping Chang & Chien-Chiang Lee & GenFu Feng & Shao-Lin Ning, 2016. "Does higher government debt link to higher social expenditure? New method, new evidence," Applied Economics, Taylor & Francis Journals, vol. 48(16), pages 1429-1451, April.
    16. Ndubuisi, Gideon & Urom, Christian, 2023. "Dependence and risk spillovers among clean cryptocurrencies prices and media environmental attention," Research in International Business and Finance, Elsevier, vol. 65(C).
    17. Aggarwal, Divya & Kalia, Deepali, 2022. "Examining comovement and causality between producer price index for P&C insurance premium and uncertainty indices: Wavelet and non-parametric quantile causality approach," Research in Economics, Elsevier, vol. 76(2), pages 141-148.
    18. Georgios Magkonis & Karen Jackson, 2019. "Identifying Networks in Social Media: The case of #Grexit," Networks and Spatial Economics, Springer, vol. 19(1), pages 319-330, March.
    19. Torben Klarl, 2016. "The nexus between housing and GDP re-visited: A wavelet coherence view on housing and GDP for the U.S," Economics Bulletin, AccessEcon, vol. 36(2), pages 704-720.
    20. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Mefteh-Wali, Salma & Owusu, Patrick, 2023. "Measuring price efficiency in petroleum markets: New insights using various long-range dependence techniques," Resources Policy, Elsevier, vol. 82(C).
    21. Krüger, Jens J., 2024. "A Wavelet Evaluation of Some Leading Business Cycle Indicators for the German Economy," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 149438, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    22. Cheng-Feng Wu & Fangjhy Li & Hsin-Pei Hsueh & Chien-Ming Wang & Meng-Chen Lin & Tsangyao Chang, 2020. "A Dynamic Relationship between Environmental Degradation, Healthcare Expenditure and Economic Growth in Wavelet Analysis: Empirical Evidence from Taiwan," IJERPH, MDPI, vol. 17(4), pages 1-17, February.

  29. Caraiani, Petre, 2012. "Characterizing emerging European stock markets through complex networks: From local properties to self-similar characteristics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(13), pages 3629-3637.

    Cited by:

    1. Zhang, Yongjie & Cao, Xing & He, Feng & Zhang, Wei, 2017. "Network topology analysis approach on China’s QFII stock investment behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 77-88.
    2. Li, Jianxuan & Shi, Yingying & Cao, Guangxi, 2018. "Topology structure based on detrended cross-correlation coefficient of exchange rate network of the belt and road countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 1140-1151.
    3. Tang, Jinjun & Wang, Yinhai & Wang, Hua & Zhang, Shen & Liu, Fang, 2014. "Dynamic analysis of traffic time series at different temporal scales: A complex networks approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 303-315.
    4. de Pontes, Lucca Siebra & Rêgo, Leandro Chaves, 2022. "Impact of macroeconomic variables on the topological structure of the Brazilian stock market: A complex network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    5. Yong Tang & Jason Jie Xiong & Zi-Yang Jia & Yi-Cheng Zhang, 2018. "Complexities in Financial Network Topological Dynamics: Modeling of Emerging and Developed Stock Markets," Complexity, Hindawi, vol. 2018, pages 1-31, November.
    6. Chen, Kun & Luo, Peng & Sun, Bianxia & Wang, Huaiqing, 2015. "Which stocks are profitable? A network method to investigate the effects of network structure on stock returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 224-235.
    7. Chuangxia Huang & Xian Zhao & Renli Su & Xiaoguang Yang & Xin Yang, 2022. "Dynamic network topology and market performance: A case of the Chinese stock market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1962-1978, April.
    8. Cao, Guangxi & Zhang, Qi & Li, Qingchen, 2017. "Causal relationship between the global foreign exchange market based on complex networks and entropy theory," Chaos, Solitons & Fractals, Elsevier, vol. 99(C), pages 36-44.
    9. Sehrish Kayani & Usman Ayub & Imran Abbas Jadoon, 2019. "Adaptive Market Hypothesis and Artificial Neural Networks: Evidence from Pakistan," Global Regional Review, Humanity Only, vol. 4(2), pages 190-203, June.
    10. Marcello Esposito, 2021. "Stock marketsas a network: from description to inference," LIUC Papers in Economics 2021-10, Cattaneo University (LIUC).

  30. Acatrinei, Marius Cristian & Caraiani, Petre, 2011. "Modeling and Forecasting the Dynamics in Romanian Stock Market Indices Using Threshold Models," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 42-54, June.

    Cited by:

    1. Andrei ANGHEL & Dalina DUMITRESCU & Cristiana TUDOR, 2015. "Modeling Portfolio Returns On Bucharest Stock Exchange Using The Fama-French Multifactor Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 22-46, March.

  31. Caraiani, Petre, 2011. "Comparing Monetary Policy Rules in the Romanian Economy: A New Keynesian Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 30-46, December.

    Cited by:

    1. Caraiani, Petre, 2013. "Comparing monetary policy rules in CEE economies: A Bayesian approach," Economic Modelling, Elsevier, vol. 32(C), pages 233-246.
    2. Bogdan BĂDESCU, 2015. "A study of the impossible trinity in Romania," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(2(603), S), pages 199-214, Summer.
    3. Iulian Vasile Popescu, 2014. "The impact of the recent global crisis on the prioritization of central banks final objectives. A structural approach in the context of Central and Eastern European states," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, vol. 7(2), pages 51-76, September.

  32. Caraiani, Petre, 2010. "Modeling Business Cycles In The Romanian Economy Using The Markov Switching Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 130-136, March.

    Cited by:

    1. Kamel Helali, 2022. "Markov Switching-Vector AutoRegression Model Analysis of the Economic and Growth Cycles in Tunisia and Its Main European Partners," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(1), pages 656-686, March.
    2. Shirly Siew-Ling WONG & Chin-Hong PUAH & Shazali ABU MANSOR & Venus Khim-Sen LIEW, 2016. "Measuring Business Cycle Fluctuations: An Alternative Precursor To Economic Crises," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(4), pages 235-248.
    3. Cristi SPULBAR & Mihai NITOI & Cristian STANCIU, 2012. "Identifying The Industry Business Cycle Using The Markov Switching Approach In Central And Eastern Europe," Management and Marketing Journal, University of Craiova, Faculty of Economics and Business Administration, vol. 0(2), pages 293-300, November.
    4. Grecu Robert-Adrian, 2022. "Synchronization of Business Cycles in European Union Countries," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 16(1), pages 217-228, August.
    5. Kutu Adebayo Augustine & Ngalawa Harold, 2017. "Monetary Policy and Industrial Output in the BRICS Countries: A Markov-Switching Model," Folia Oeconomica Stetinensia, Sciendo, vol. 17(2), pages 35-55, December.

  33. Petre Caraiani, 2010. "Bayesian Linear Estimation of Okun Coefficient for Romania: Sensitivity to Priors Distributions," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 13(38), pages 53-65, December.

    Cited by:

    1. KARGI, Bilal, 2013. "Okun’s Law and Long Term Co-Integration Analysis for OECD Countries (1987-2012)," MPRA Paper 55700, University Library of Munich, Germany.
    2. Andrew Phiri, 2014. "Nonlinear Co-Integration Between Unemployment and Economic Growth in South Africa," Managing Global Transitions, University of Primorska, Faculty of Management Koper, vol. 12(4 (Winter), pages 303-324.
    3. Phiri, Andrew, 2014. "Re-evaluating Okun's law in South Africa: A nonlinear co-integration approach," MPRA Paper 57398, University Library of Munich, Germany.

  34. Caraiani, Petre, 2010. "Forecasting Romanian GDP Using a BVAR Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 76-87, December.

    Cited by:

    1. Spulbăr Cristi & Niţoi Mihai, 2013. "Monetary Policy Transmission Mechanism in Romania Over the Period 2001 to 2012: A Bvar Analysis," Scientific Annals of Economics and Business, Sciendo, vol. 60(2), pages 1-12, December.
    2. Dedu, Vasile & Stoica, Tiberiu, 2014. "The Impact of Monetaru Policy on the Romanian Economy," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 71-86, June.
    3. Margarit Monica-Ionelia, 2022. "Using The Bayesian Var In Monetary Policy Analysis: A Literature Review," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 1, pages 212-216, February.
    4. Ngomba Bodi, Francis Ghislain & Bikai, Landry, 2017. "Prévisions de l’inflation et de la croissance en zone CEMAC [Inflation and real growth forecasts in CEMAC zone]," MPRA Paper 116433, University Library of Munich, Germany.
    5. Abuselidze, George & Mamaladze, Lela, 2019. "U.S-Turkey Crisis and Its Impact on the Economy of the Black Sea Region," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 135.
    6. Andrei, Dalina Maria, 2012. "Foreign Direct Investments in Romania. A Structural and Dynamic View," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 129-146, December.
    7. 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.
    8. Mihaela SIMIONESCU, 2015. "Is Africa’s current growth reducing inequality? Evidence from some selected african countries," Computational Methods in Social Sciences (CMSS), "Nicolae Titulescu" University of Bucharest, Faculty of Economic Sciences, vol. 3(1), pages 68-74, June.
    9. Usman Shakoor & Mudassar Rashid & Ashfaque Ali Baloch & Muhammad Iftikhar ul Husnain & Abdul Saboor, 2021. "How Aging Population Affects Health Care Expenditures in Pakistan? A Bayesian VAR Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 153(2), pages 585-607, January.

  35. Petre Caraiani, 2009. "An Estimation of Output Gap in Romanian Economy Using the DSGE Approach," Prague Economic Papers, Prague University of Economics and Business, vol. 2009(4), pages 366-379.

    Cited by:

    1. Spulbăr Cristi & Niţoi Mihai & STANCIU Cristian, 2012. "Inflation Inertia and Inflation Persistence in Romania Using a DSGE Approach," Scientific Annals of Economics and Business, Sciendo, vol. 59(1), pages 115-124, July.

  36. Purica, Ionut & Caraiani, Petre, 2009. "Second Order Dynamics Of Economic Cycles," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 6(1), pages 36-47, March.

    Cited by:

    1. Caraiani, Petre, 2012. "Is the Romanian Business Cycle Characterized by Chaos?," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 142-151, September.
    2. Purica, Ionut, 2010. "Nonlinear Considerations on Economic Systems’ Behaviour," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(5), pages 74-81.
    3. Iancu, Aurel, 2011. "Financial System Fragility Models," Working Papers of National Institute for Economic Research 110211, Institutul National de Cercetari Economice (INCE).
    4. Purica, Ionut, 2012. "Oscillatory Dynamics of Industrial Production," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 117-128, December.
    5. Cristi SPULBAR & Mihai NITOI & Cristian STANCIU, 2012. "Identifying The Industry Business Cycle Using The Markov Switching Approach In Central And Eastern Europe," Management and Marketing Journal, University of Craiova, Faculty of Economics and Business Administration, vol. 0(2), pages 293-300, November.
    6. Dinu. Marin & Marinas, Marius Corneliu & Socol Cristian & Socol, Aura Gabriela, 2012. "Clusterization, Persistence, Dependency and Volatility of Business Cycles in an Enlarged Euro Area," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 5-23, June.
    7. Caraiani, Petre, 2010. "Modeling Business Cycles In The Romanian Economy Using The Markov Switching Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 130-136, March.
    8. Andrei Silviu DOSPINESCU, 2012. "The Behavior Of Prices As A Response To Structural Changes - The Role Of The Economic Transmission Mechanisms In Explaining The Observed Behavior," Romanian Journal of Economics, Institute of National Economy, vol. 35(2(44)), pages 201-217, December.
    9. Iancu, Aurel, 2011. "Models of Financial System Fragility," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 230-256, March.

  37. Caraiani, Petre, 2008. "An Analysis Of Domestic And External Shocks On Romanian Economy Using A Dsge Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 5(3), pages 100-114, September.

    Cited by:

    1. Umut UNAL, 2015. "Rethinking The Effects Of Fiscal Policy On Macroeconomic Aggregates: A Disaggregated Svar Analysis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 120-135, September.
    2. Martin Feldkircher, 2013. "A Global Macro Model for Emerging Europe," Working Papers 185, Oesterreichische Nationalbank (Austrian Central Bank).
    3. Valeriu Nalban, 2015. "A small New Keynesian model to analyze business cycle dynamics in Poland and Romania," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 9(3), September.
    4. Petre Caraiani, 2009. "An Estimation of Output Gap in Romanian Economy Using the DSGE Approach," Prague Economic Papers, Prague University of Economics and Business, vol. 2009(4), pages 366-379.
    5. Alina BOBAŞU & Bogdan MURARAȘU, 2021. "Fiscal and Monetary Policy Interactions in a DSGE Model for the Romanian Economy," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 5-21, June.
    6. Iulian Vasile Popescu, 2014. "The impact of the recent global crisis on the prioritization of central banks final objectives. A structural approach in the context of Central and Eastern European states," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, vol. 7(2), pages 51-76, September.

  38. Caraiani, Petre, 2007. "An Estimated New Keynesian Model for Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 4(4), pages 114-123, December.

    Cited by:

    1. Purica, Ionut & Caraiani, Petre, 2009. "Second Order Dynamics Of Economic Cycles," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 6(1), pages 36-47, March.
    2. Valeriu Nalban, 2015. "A small New Keynesian model to analyze business cycle dynamics in Poland and Romania," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 9(3), September.
    3. Caraiani, Petre, 2008. "An Analysis Of Domestic And External Shocks On Romanian Economy Using A Dsge Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 5(3), pages 100-114, September.

  39. Caraiani, Petre, 2007. "An Analysis of the Fluctuations in the Romanian Economy using the Real Business Cycles Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 4(2), pages 76-86, June.

    Cited by:

    1. Purica, Ionut & Caraiani, Petre, 2009. "Second Order Dynamics Of Economic Cycles," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 6(1), pages 36-47, March.
    2. Jula, Dorin & Jula, Nicolae Marius, 2009. "Regional Economic Voting In Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 6(1), pages 5-15, March.
    3. Petre Caraiani, 2009. "An Estimation of Output Gap in Romanian Economy Using the DSGE Approach," Prague Economic Papers, Prague University of Economics and Business, vol. 2009(4), pages 366-379.

  40. Caraiani, Petre, 2006. "Alternative Methods of Estimating the Okun Coefficient. Applications for Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 3(4), pages 82-89, December.

    Cited by:

    1. KORI YAHIA, Abdellah, 2018. "Bayesian Linear Estimation of Okun Coefficient for Romania: Sensitivity to Priors," MPRA Paper 84140, University Library of Munich, Germany.
    2. Petre Caraiani, 2010. "Bayesian Linear Estimation of Okun Coefficient for Romania: Sensitivity to Priors Distributions," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 13(38), pages 53-65, December.
    3. Mustafa Şit, 2024. "The Relationship Between Unemployment and Economic Growth in Selected Large Emerging Countries: A Revisit Using Threshold Regression Analysis," Journal of Economic Policy Researches, Istanbul University, Faculty of Economics, vol. 11(1), pages 76-85, January.
    4. Maria – Monica Haralambie & Bogdan Stefan Ionescu, 2017. "The economic implications of international migration – an analysis of capital remittances applied to Romania," The Audit Financiar journal, Chamber of Financial Auditors of Romania, vol. 15(148), pages 667-667.

  41. Pelinescu, Elena & Caraiani, Petre, 2006. "Does the Inflation Targeting Have a Positive Role upon the Convergence of the Inflation Rate?," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 3(3), pages 39-50, September.

    Cited by:

    1. Nikolay Nenovsky, 2009. "Monetary Regimes in Post-Communist Countries. Some Long-Term Reflections," Working paper series 12009en, Agency for Economic Analysis and Forecasting.
    2. Dejan Zivkov & Slavica Manic & Jasmina Duraskovic & Jelena Kovacevic, 2019. "Bidirectional Nexus between Inflation and Inflation Uncertainty in the Asian Emerging Markets – The GARCH-in-Mean Approach," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 69(6), pages 580-599, December.
    3. Paun, Cristian & Topan, Vladimir, 2013. "The Monetary Causes of Inflation in Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 5-23, March.
    4. Monica DAMIAN, 2011. "Evaluation of optimal monetary policy strategy in Romania in the context of fulfilment of convergence criteria," Romanian Journal of Economics, Institute of National Economy, vol. 33(2(42)), pages 146-168, December.

  42. Pelinescu, Elena & Caraiani, Petre, 2006. "Estimating the Real Effective Exchange Rate (REER) by Using the Unit Labor Cost (ULC) in Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 3(4), pages 5-22, December.

    Cited by:

    1. Elena Pelinescu & Marioara Iordan & Mihaela-Nona Chilian, 2012. "Competitiveness Of The Romanian Economy From European Perspective," New Trends in Modelling and Economic Forecast (MEF 2011), ROMANIAN ACADEMY – INSTITUTE FOR ECONOMIC FORECASTING;"Nicolae Titulescu" University of Bucharest, Faculty of Economic Sciences, vol. 1(1), pages 86-104, January.

  43. Caraiani, Petre, 2004. "Nominal And Real Stylized Facts Of The Business Cycles In Romanian Economy," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 1(4), pages 121-132, December.

    Cited by:

    1. Purica, Ionut & Caraiani, Petre, 2009. "Second Order Dynamics Of Economic Cycles," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 6(1), pages 36-47, March.
    2. Caraiani, Petre, 2007. "An Analysis of the Fluctuations in the Romanian Economy using the Real Business Cycles Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 4(2), pages 76-86, June.
    3. Caraiani, Petre, 2010. "Modeling Business Cycles In The Romanian Economy Using The Markov Switching Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 130-136, March.

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