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How External Factors Affect Domestic Economy; Nowcasting an Emerging Market

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  • Serhat Solmaz
  • Marzie Taheri Sanjani

Abstract

External headwinds, together with domestic vulnerabilities, have loomed over the prospects of emerging markets in recent years. We propose an empirical toolbox to quantify the impact of external macro-financial shocks on domestic economies in parsimonious way. Our model is a Bayesian VAR consisting of two blocks representing home and foreign factors, which is particularly useful for small open economies. By exploiting the mixed-frequency nature of the model, we show how the toolbox can be used for “nowcasting” the output growth. The conditional forecast results illustrate that regular updates of external information, as well as domestic leading indicators, would significantly enhance the accuracy of forecasts. Moreover, the analysis of variance decompositions shows that external shocks are important drivers of the domestic business cycle.

Suggested Citation

  • Serhat Solmaz & Marzie Taheri Sanjani, 2015. "How External Factors Affect Domestic Economy; Nowcasting an Emerging Market," IMF Working Papers 15/269, International Monetary Fund.
  • Handle: RePEc:imf:imfwpa:15/269
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    References listed on IDEAS

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    1. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
    2. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2006. "A comparison of direct and iterated multistep AR methods for forecasting macroeconomic time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 499-526.
    3. Koop, Gary & Korobilis, Dimitris, 2010. "Bayesian Multivariate Time Series Methods for Empirical Macroeconomics," Foundations and Trends(R) in Econometrics, now publishers, vol. 3(4), pages 267-358, July.
    4. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2005. "Nowcasting GDP and Inflation: The Real Time Informational Content of Macroeconomic Data Releases," CEPR Discussion Papers 5178, C.E.P.R. Discussion Papers.
    5. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
    6. Huseyin Cagri Akkoyun & Mahmut Gunay, 2012. "Nowcasting Turkish GDP Growth," Working Papers 1233, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    7. Kadiyala, K Rao & Karlsson, Sune, 1997. "Numerical Methods for Estimation and Inference in Bayesian VAR-Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(2), pages 99-132, March-Apr.
    8. Lisandro Abrego & Pär Österholm, 2010. "External Linkages and Economic Growth in Colombia: Insights from a Bayesian VAR Model," The World Economy, Wiley Blackwell, vol. 33(12), pages 1788-1810, December.
    9. Michal Andrle & Roberto Garcia-Saltos & Giang Ho, 2013. "The Role of Domestic and External Shocks in Poland; Results from an Agnostic Estimation Procedure," IMF Working Papers 13/220, International Monetary Fund.
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    Cited by:

    1. Simone Auer & Emidio Cocozza & Andrea COlabella, 2016. "The financial systems in Russia and Turkey: recent developments and challenges," Questioni di Economia e Finanza (Occasional Papers) 358, Bank of Italy, Economic Research and International Relations Area.
    2. M. Tiunova G. & М. Тиунова Г., 2018. "Влияние Внешних Шоков На Российскую Экономику // The Impact Of External Shocks On The Russian Economy," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, vol. 22(4), pages 146-170.

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