Meltem Gulenay Chadwick

Personal Details

First Name:	Meltem
Middle Name:	Gulenay
Last Name:	Chadwick
Suffix:
RePEc Short-ID:	pch1174
	[This author has chosen not to make the email address public]
	https://sites.google.com/site/meltemgulenaychadwick/
Terminal Degree:	2010 Department of Economics, Mathematics and Statistics; Birkbeck College (from RePEc Genealogy)

Affiliation

South East Asian Central Banks (SEACEN) Research and Training Centre

Kuala Lumpur, Malaysia
http://www.seacen.org/
RePEc:edi:seacemy (more details at EDIRC)

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. Meltem Gulenay Chadwick & Huseyin Ozturk, 2018. "Measuring Financial Systemic Stress for Turkey: A Search for the Best Composite Indicator," Working Papers 1816, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
   • Chadwick, Meltem Gulenay & Ozturk, Huseyin, 2019. "Measuring financial systemic stress for Turkey: A search for the best composite indicator," Economic Systems, Elsevier, vol. 43(1), pages 151-172.

   Cited by:

   1. Segun Thompson Bolarinwa & Richard Olaolu Olayeni & Xuan Vinh Vo, 2021. "Is there a nonlinear relationship between nonperforming loans and bank profitability? Evidence from dynamic panel threshold," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(3), pages 649-661, April.
   2. Ozcelebi, Oguzhan, 2020. "Assessing the impacts of financial stress index of developed countries on the exchange market pressure index of emerging countries," International Review of Economics & Finance, Elsevier, vol. 70(C), pages 288-302.
   3. Xuan Lv & Menggang Li & Yingjie Zhang, 2022. "Financial Stability and Economic Activity in China: Based on Mixed-Frequency Spillover Method," Sustainability, MDPI, vol. 14(19), pages 1-22, October.
   4. Kaelo Ntwaepelo & Grivas Chiyaba, 2022. "Financial Stability Surveillance Tools: Evaluating the Performance of Stress Indices," Economics Discussion Papers em-dp2022-06, Department of Economics, University of Reading.

2. Meltem Gulenay Chadwick & Emine Meltem Bastan, 2017. "Beef Price Volatility in Turkey: Can Import Policy Affect the Price and Its Uncertainty?," Working Papers 1709, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.

   Cited by:

   1. Faruk Urak & Abdulbaki Bilgic & Gürkan Bozma & Wojciech J. Florkowski & Erkan Efekan, 2022. "Volatility in Live Calf, Live Sheep, and Feed Wheat Return Markets: A Threat to Food Price Stability in Turkey," Agriculture, MDPI, vol. 12(4), pages 1-24, April.

3. Meltem Gulenay Chadwick & Gonul Sengul, 2012. "Nowcasting Unemployment Rate in Turkey : Let's Ask Google," Working Papers 1218, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
   • Meltem Gulenay Chadwick & Gonul Sengul, 2015. "Nowcasting the Unemployment Rate in Turkey : Let's ask Google," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 15(3), pages 15-40.

   Cited by:

   1. Mihaela Simionescu & Javier Cifuentes-Faura, 2022. "Forecasting National and Regional Youth Unemployment in Spain Using Google Trends," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 164(3), pages 1187-1216, December.
   2. Moses Tule & Taiwo Ajilore & Godday Ebuh, 2016. "A composite index of leading indicators of unemployment in Nigeria," Journal of African Business, Taylor & Francis Journals, vol. 17(1), pages 87-105, January.
   3. Pavlicek, Jaroslav & Kristoufek, Ladislav, 2015. "Nowcasting unemployment rates with Google searches: Evidence from the Visegrad Group countries," FinMaP-Working Papers 34, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
      • Jaroslav Pavlicek & Ladislav Kristoufek, 2015. "Nowcasting Unemployment Rates with Google Searches: Evidence from the Visegrad Group Countries," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-11, May.
   4. Tuhkuri, Joonas, 2016. "Forecasting Unemployment with Google Searches," ETLA Working Papers 35, The Research Institute of the Finnish Economy.
   5. H. Burcu Gurcihan & Gonul Sengul & Arzu Yavuz, 2013. "A Quest for Leading Indicators of the Turkish Unemployment Rate," Working Papers 1341, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
      • Burcu Gurcihan Yunculer & Gonul Sengul & Arzu Yavuz, 2014. "A Quest for Leading Indicators of the Turkish Unemployment Rate," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 14(1), pages 23-45.
   6. Jacques Bughin, 2015. "Google searches and twitter mood: nowcasting telecom sales performance," Netnomics, Springer, vol. 16(1), pages 87-105, August.
   7. Soybilgen, Barış & Yazgan, Ege, 2018. "Evaluating nowcasts of bridge equations with advanced combination schemes for the Turkish unemployment rate," Economic Modelling, Elsevier, vol. 72(C), pages 99-108.
   8. Mihaela Simionescu & Dalia Streimikiene & Wadim Strielkowski, 2020. "What Does Google Trends Tell Us about the Impact of Brexit on the Unemployment Rate in the UK?," Sustainability, MDPI, vol. 12(3), pages 1-10, January.
   9. Bulut Levent & Dogan Can, 2018. "Google Trends and Structural Exchange Rate Models for Turkish Lira–US Dollar Exchange Rate," Review of Middle East Economics and Finance, De Gruyter, vol. 14(2), pages 1-12, August.
   10. Per Nymand-Andersen, 2016. "Big data: the hunt for timely insights and decision certainty," IFC Working Papers 14, Bank for International Settlements.
   11. Nakamura, Nobuyuki & Suzuki, Aya, 2021. "COVID-19 and the intentions to migrate from developing countries: Evidence from online search activities in Southeast Asia," Journal of Asian Economics, Elsevier, vol. 76(C).
   12. M. Elshendy & A. Fronzetti Colladon & E. Battistoni & P. A. Gloor, 2021. "Using four different online media sources to forecast the crude oil price," Papers 2105.09154, arXiv.org.
   13. Jaroslav Pavlicek & Ladislav Kristoufek, 2014. "Can Google searches help nowcast and forecast unemployment rates in the Visegrad Group countries?," Papers 1408.6639, arXiv.org.
   14. Franch, Fabio, 2021. "Political preferences nowcasting with factor analysis and internet data: The 2012 and 2016 US presidential elections," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
   15. Jianchun Fang & Wanshan Wu & Zhou Lu & Eunho Cho, 2019. "Using Baidu Index To Nowcast Mobile Phone Sales In China," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 64(01), pages 83-96, March.
   16. Alessia Naccarato & Andrea Pierini & Stefano Falorsi, 2015. "Using Google Trend Data To Predict The Italian Unemployment Rate," Departmental Working Papers of Economics - University 'Roma Tre' 0203, Department of Economics - University Roma Tre.
   17. Simionescu, Mihaela & Zimmermann, Klaus F., 2017. "Big Data and Unemployment Analysis," GLO Discussion Paper Series 81, Global Labor Organization (GLO).
   18. Tuhkuri, Joonas, 2016. "ETLAnow: A Model for Forecasting with Big Data – Forecasting Unemployment with Google Searches in Europe," ETLA Reports 54, The Research Institute of the Finnish Economy.
   19. Simionescu, Mihaela & Cifuentes-Faura, Javier, 2022. "Can unemployment forecasts based on Google Trends help government design better policies? An investigation based on Spain and Portugal," Journal of Policy Modeling, Elsevier, vol. 44(1), pages 1-21.
   20. Simionescu, Mihaela & Raišienė, Agota Giedrė, 2021. "A bridge between sentiment indicators: What does Google Trends tell us about COVID-19 pandemic and employment expectations in the EU new member states?," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
   21. Gulsah Senturk, 2022. "Can Google Search Data Improve the Unemployment Rate Forecasting Model? An Empirical Analysis for Turkey," Journal of Economic Policy Researches, Istanbul University, Faculty of Economics, vol. 9(2), pages 229-244, July.
   22. Mihaela, Simionescu, 2020. "Improving unemployment rate forecasts at regional level in Romania using Google Trends," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
   23. Voraprapa Nakavachara & Nuarpear Lekfuangfu, 2017. "Predicting the Present Revisited: The Case of Thailand," PIER Discussion Papers 70, Puey Ungphakorn Institute for Economic Research.
   24. Omer ZEYBEK & Erginbay UGURLU, 2014. "Nowcasting Credit Demand in Turkey with Google Trends Data," International Conference on Economic Sciences and Business Administration, Spiru Haret University, vol. 1(1), pages 333-340, December.

4. Kurmas Akdogan & Selen Baser & Meltem Gulenay Chadwick & Dilara Ertug & Timur Hulagu & Sevim Kosem & Fethi Ogunc & M. Utku Ozmen & Necati Tekatli, 2012. "Short-Term Inflation Forecasting Models For Turkey and a Forecast Combination Analysis," Working Papers 1209, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
   • Öğünç, Fethi & Akdoğan, Kurmaş & Başer, Selen & Chadwick, Meltem Gülenay & Ertuğ, Dilara & Hülagü, Timur & Kösem, Sevim & Özmen, Mustafa Utku & Tekatlı, Necati, 2013. "Short-term inflation forecasting models for Turkey and a forecast combination analysis," Economic Modelling, Elsevier, vol. 33(C), pages 312-325.

   Cited by:

   1. Duncan, Roberto & Martínez-García, Enrique, 2019. "New perspectives on forecasting inflation in emerging market economies: An empirical assessment," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1008-1031.
      • Roberto Duncan & Enrique Martínez García, 2018. "New Perspectives on Forecasting Inflation in Emerging Market Economies: An Empirical Assessment," Globalization Institute Working Papers 338, Federal Reserve Bank of Dallas.
   2. Shahzad Ahmad & Farooq Pasha, 2015. "A Pragmatic Model for Monetary Policy Analysis I: The Case of Pakistan," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 11, pages 1-42.
   3. Afees A. Salisu & Kazeem Isah, 2017. "Predicting US CPI-Inflation in the presence of asymmetries, persistence, endogeneity, and conditional heteroscedasticity," Working Papers 026, Centre for Econometric and Allied Research, University of Ibadan.
      • Salisu, Afees A. & Isah, Kazeem O., 2018. "Predicting US inflation: Evidence from a new approach," Economic Modelling, Elsevier, vol. 71(C), pages 134-158.
   4. Carrera, Cesar & Ledesma, Alan, 2015. "Proyección de la inflación agregada con modelos de vectores autorregresivos bayesianos," Working Papers 2015-003, Banco Central de Reserva del Perú.
   5. Nyoni, Thabani & Nathaniel, Solomon Prince, 2018. "Modeling rates of inflation in Nigeria: an application of ARMA, ARIMA and GARCH models," MPRA Paper 91351, University Library of Munich, Germany.
   6. Christian Glocker & Serguei Kaniovski, 2022. "Macroeconometric forecasting using a cluster of dynamic factor models," Empirical Economics, Springer, vol. 63(1), pages 43-91, July.
      • Christian Glocker & Serguei Kaniovski, 2020. "Macroeconometric Forecasting Using a Cluster of Dynamic Factor Models," WIFO Working Papers 614, WIFO.
   7. Zeyyad Mandalinci, 2015. "Forecasting Inflation in Emerging Markets: An Evaluation of Alternative Models," CReMFi Discussion Papers 3, CReMFi, School of Economics and Finance, QMUL.
      • Mandalinci, Zeyyad, 2017. "Forecasting inflation in emerging markets: An evaluation of alternative models," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1082-1104.
   8. Hanif, Muhammad Nadim & Malik, Muhammad Jahanzeb, 2015. "Evaluating Performance of Inflation Forecasting Models of Pakistan," MPRA Paper 66843, University Library of Munich, Germany.
      • Muhammad Nadim Hanif & Muhammad Jahanzeb Malik, 2015. "Evaluating the Performance of Inflation Forecasting Models of Pakistan," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 11, pages 43-78.
   9. Chronis, George A., 2016. "Modelling the extreme variability of the US Consumer Price Index inflation with a stable non-symmetric distribution," Economic Modelling, Elsevier, vol. 59(C), pages 271-277.
   10. Scarpel, Rodrigo Arnaldo, 2015. "An integrated mixture of local experts model for demand forecasting," International Journal of Production Economics, Elsevier, vol. 164(C), pages 35-42.
   11. Meri Papavangjeli, 2019. "Forecasting the Albanian short-term inflation through a Bayesian VAR model," IHEID Working Papers 16-2019, Economics Section, The Graduate Institute of International Studies, revised 09 Oct 2019.
   12. Cesar Carrera & Alan Ledesma, 2015. "Aggregate Inflation Forecast with Bayesian Vector Autoregressive Models," Working Papers 50, Peruvian Economic Association.
   13. Sergiy Nikolaychuk & Yurii Sholomytskyi, 2015. "Using Macroeconomic Models for Monetary Policy in Ukraine," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 233, pages 54-64, September.
   14. Fayyaz Hussain & Zafar Hayat, 2016. "Do Inflation Expectations Matter for Inflation Forecastability: Evidence from Pakistan," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 55(3), pages 211-225.
   15. Krzysztof DRACHAL, 2020. "Forecasting the Inflation Rate in Poland and U.S. Using Dynamic Model Averaging (DMA) and Google Queries," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 18-34, July.
   16. Magdalena Petrovska & Gani Ramadani & Nikola Naumovski & Biljana Jovanovic, 2017. "Forecasting Macedonian Inflation: Evaluation of different models for short-term forecasting," Working Papers 2017-06, National Bank of the Republic of North Macedonia.
   17. Barakchian , Seyed Mahdi & Bayat , Saeed & Karami , Hooman, 2013. "Common Factors of CPI Sub-aggregates and Forecast of Inflation," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 8(4), pages 1-17, October.
   18. Xiaojie Xu, 2020. "Corn Cash Price Forecasting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1297-1320, August.
   19. Kurmaş Akdoğan, 2015. "Asymmetric Behaviour of Inflation around the Target in Inflation-Targeting Countries," Scottish Journal of Political Economy, Scottish Economic Society, vol. 62(5), pages 486-504, November.
   20. Afees A. Salisu & Kazeem Isah, 2017. "Predicting US Inflation: Evidence from a New Approach," Working Papers 039, Centre for Econometric and Allied Research, University of Ibadan.
       • Salisu, Afees A. & Isah, Kazeem O., 2018. "Predicting US inflation: Evidence from a new approach," Economic Modelling, Elsevier, vol. 71(C), pages 134-158.

5. Kurmas Akdogan & Meltem Gulenay Chadwick, 2012. "CDS-Bono Farki ve Duzeltme Hareketi," CBT Research Notes in Economics 1201, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.

   Cited by:

   1. KARGI, Bilal, 2014. "Credit Default Swap (CDS) Spreads: The Analysis of Time Series for The Integration with The Interest Rates and The Growth in Turkish Economy," MPRA Paper 57380, University Library of Munich, Germany.
      • Kargi, Bilal, 2014. "Credit Default Swap (CDS) Spreads: The Analysis of Time Series for The Integration with The Interest Rates and The Growth in Turkish Economy," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 10(1), pages 59-66.
      • Bilal Kargi, 2014. "Credit Default Swap (Cds) Spreads: The Analysis Of Time Series For The Interaction With The Interest Rates And The Growth In Turkish Economy," Montenegrin Journal of Economics, Economic Laboratory for Transition Research (ELIT), vol. 10(1), pages 59-66.
   2. Nurbanu Bursa & Hüseyin Tatlýdil, 2015. "Investigation of Credit Default Swaps using Detrended Fluctuation Analysis which is an Econophysical Technique," Eurasian Eononometrics, Statistics and Emprical Economics Journal, Eurasian Academy Of Sciences, vol. 2(2), pages 25-33, October.
   3. Nilufer KAYA KANLI & Osman AYDOGUS, 2017. "Ulke Risk Faktorlerinin Dogrudan Yabanci Yatirimlar Uzerindeki Belirleyici Etkisi," Ege Academic Review, Ege University Faculty of Economics and Administrative Sciences, vol. 17(2), pages 179-190.

6. Meltem Gulenay Chadwick & Fatih Fazilet & Necati Tekatli, 2012. "Common Movement of the Emerging Market Currencies," Working Papers 1207, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.

   Cited by:

   1. Chen, Bin-xia & Sun, Yan-lin, 2022. "The impact of VIX on China’s financial market: A new perspective based on high-dimensional and time-varying methods," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
   2. Rubén Albeiro Loaiza Maya & José Eduardo Gómez-González & Luis Fernando Melo Velandia, 2014. "Exchange Rates Contagion in Latin America," Borradores de Economia 12105, Banco de la Republica.
      • Loaiza-Maya, Rubén Albeiro & Gómez-González, José Eduardo & Melo-Velandia, Luis Fernando, 2015. "Exchange rate contagion in Latin America," Research in International Business and Finance, Elsevier, vol. 34(C), pages 355-367.
      • Rubén Albeiro Loaiza Maya & José Eduardo Gómez-González & Luis Fernando Melo Velandia, 2014. "Exchange Rates Contagion in Latin America," Borradores de Economia 842, Banco de la Republica de Colombia.
   3. Rubén Albeiro Loaiza Maya & Jose Eduardo Gomez-Gonzalez & Luis Fernando Melo Velandia, 2015. "Latin American Exchange Rate Dependencies: A Regular Vine Copula Approach," Contemporary Economic Policy, Western Economic Association International, vol. 33(3), pages 535-549, July.
      • Rubén Albeiro Loaiza Maya & Luis Fernando Melo Velandia, 2012. "Latin American Exchange Rate Dependencies: A Regular Vine Copula Approach," Borradores de Economia 9902, Banco de la Republica.
      • Rubén Albeiro Loaiza Maya & José Eduardo Gómez-González & Luis Fernando Melo Velandia, 2012. "Latin American Exchange Rate Dependencies: A Regular Vine Copula Approach," Borradores de Economia 729, Banco de la Republica de Colombia.

7. Chadwick, Meltem, 2010. "Performance of Bayesian Latent Factor Models in Measuring Pricing Errors," MPRA Paper 79060, University Library of Munich, Germany.

   Cited by:

   1. Chadwick, Meltem Gülenay & Fazilet, Fatih & Tekatli, Necati, 2015. "Understanding the common dynamics of the emerging market currencies," Economic Modelling, Elsevier, vol. 49(C), pages 120-136.

Articles

1. Chadwick, Meltem Gulenay, 2019. "Dependence of the “Fragile Five” and “Troubled Ten” emerging market financial systems on US monetary policy and monetary policy uncertainty," Research in International Business and Finance, Elsevier, vol. 49(C), pages 251-268.

   Cited by:

   1. Mustafa Okur & Ali Köse & Özgür Akpinar, 2021. "The Soundness of Financial Institutions In The Fragile Five Countries," International Journal of Business Research and Management (IJBRM), Computer Science Journals (CSC Journals), vol. 12(3), pages 89-102, June.
   2. Kassouri, Yacouba & Altıntaş, Halil, 2020. "Threshold cointegration, nonlinearity, and frequency domain causality relationship between stock price and Turkish Lira," Research in International Business and Finance, Elsevier, vol. 52(C).
   3. Assoumou-Ella, Giscard & Bastidon, Cécile & Bonijoly, Bastien, 2022. "Fed tapering announcements: Impact on Middle Eastern and African financial markets," Research in International Business and Finance, Elsevier, vol. 59(C).
      • Giscard Assoumou-Ella & Cécile Bastidon & Bastien Bonijoly, 2022. "Fed tapering announcements: Impact on Middle Eastern and African financial markets," Post-Print hal-03570691, HAL.

2. Chadwick, Meltem Gulenay & Ozturk, Huseyin, 2019. "Measuring financial systemic stress for Turkey: A search for the best composite indicator," Economic Systems, Elsevier, vol. 43(1), pages 151-172.
   • Meltem Gulenay Chadwick & Huseyin Ozturk, 2018. "Measuring Financial Systemic Stress for Turkey: A Search for the Best Composite Indicator," Working Papers 1816, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
   See citations under working paper version above.
3. Meltem Gulenay Chadwick, 2018. "Effectiveness of monetary and macroprudential shocks on consumer credit growth and volatility in Turkey," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 18(2), pages 69-83.

   Cited by:

   1. Kaelo Mpho Ntwaepelo, 2021. "The Effects of Macroprudential and Monetary Policy Shocks in BRICS economies," Economics Discussion Papers em-dp2021-20, Department of Economics, University of Reading.
   2. Stewart, Robert & Chowdhury, Murshed & Arjoon, Vaalmikki, 2021. "Interdependencies between regulatory capital, credit extension and economic growth," Journal of Economics and Business, Elsevier, vol. 117(C).
   3. Farrukh Shahzad & Zeeshan Fareed & Bushra Zulfiqar & Umme Habiba & Muhammad Ikram, 2019. "Does abnormal lending behavior increase bank riskiness? Evidence from Turkey," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-15, December.
   4. Stewart, Robert & Chowdhury, Murshed, 2021. "Banking sector distress and economic growth resilience: Asymmetric effects," The Journal of Economic Asymmetries, Elsevier, vol. 24(C).

4. Meltem Chadwick & Meltem Bastan, 2017. "News impact for Turkish food prices," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 17(2), pages 1-55–76.

   Cited by:

   1. Meller, Leandro & Larrosa, Juan M.C. & Delbianco, Fernando & Ramírez Muñoz de Toro, Gonzalo & Uriarte, Juan Ignacio, 2021. "Inflación semanal en galletitas: un enfoque de datos de panel. || Weekly Cookie Inflation: A Panel Data Approach," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 31(1), pages 417-440, June.
   2. Kurmas Akdogan, 2018. "Mean-reversion and structural change in European food prices," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 18(4), pages 163-173.
   3. Meltem Chadwick, 2023. "The significance of terms of trade shocks for retail food prices in Turkey," Agribusiness, John Wiley & Sons, Ltd., vol. 39(4), pages 915-940, October.

5. Meltem Gulenay Chadwick & Gonul Sengul, 2015. "Nowcasting the Unemployment Rate in Turkey : Let's ask Google," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 15(3), pages 15-40.
   • Meltem Gulenay Chadwick & Gonul Sengul, 2012. "Nowcasting Unemployment Rate in Turkey : Let's Ask Google," Working Papers 1218, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
   See citations under working paper version above.
6. Chadwick, Meltem Gülenay & Fazilet, Fatih & Tekatli, Necati, 2015. "Understanding the common dynamics of the emerging market currencies," Economic Modelling, Elsevier, vol. 49(C), pages 120-136.

   Cited by:

   1. Gannon, Gerard L. & Thuraisamy, Kannan S., 2017. "Sovereign risk and the impact of crisis: Evidence from Latin AmericaAuthor-Name: Batten, Jonathan A," Journal of Banking & Finance, Elsevier, vol. 77(C), pages 328-350.
   2. Arango-Castillo, Lenin & Orraca, María José & Molina, G. Stefano, 2023. "The global component of headline and core inflation in emerging market economies and its ability to improve forecasting performance," Economic Modelling, Elsevier, vol. 120(C).
   3. Krystian Jaworski, 2021. "Forecasting exchange rates for Central and Eastern European currencies using country‐specific factors," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 977-999, September.

7. Öğünç, Fethi & Akdoğan, Kurmaş & Başer, Selen & Chadwick, Meltem Gülenay & Ertuğ, Dilara & Hülagü, Timur & Kösem, Sevim & Özmen, Mustafa Utku & Tekatlı, Necati, 2013. "Short-term inflation forecasting models for Turkey and a forecast combination analysis," Economic Modelling, Elsevier, vol. 33(C), pages 312-325.
   • Kurmas Akdogan & Selen Baser & Meltem Gulenay Chadwick & Dilara Ertug & Timur Hulagu & Sevim Kosem & Fethi Ogunc & M. Utku Ozmen & Necati Tekatli, 2012. "Short-Term Inflation Forecasting Models For Turkey and a Forecast Combination Analysis," Working Papers 1209, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
   See citations under working paper version above.
8. Kurmaş Akdoğan & Meltem Gülenay Chadwick, 2013. "Nonlinearities in CDS-Bond Basis," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 49(3), pages 6-19, May.

   Cited by:

   1. Zongxin Qian & Qian Luo, 2016. "Regime-Dependent Determinants of China’s Sovereign Credit Default Swap Spread," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 52(1), pages 10-21, January.
   2. Hassan, M. Kabir & Ngene, Geoffrey M. & Yu, Jung-Suk, 2015. "Credit default swaps and sovereign debt markets," Economic Systems, Elsevier, vol. 39(2), pages 240-252.
      • M. Kabir Hassan & Geoffrey M. Ngene & Jung Suk-Yu, 2011. "Credit Default Swaps and Sovereign Debt Markets," NFI Working Papers 2011-WP-03, Indiana State University, Scott College of Business, Networks Financial Institute.
   3. Atilgan, Yigit & Demirtas, K. Ozgur & Simsek, Koray D., 2016. "Derivative markets in emerging economies: A survey," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 88-102.
   4. Rahmi Erdem Aktug, 2015. "Empirical dynamics of emerging financial markets during the global mortgage crisis," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 15(1), pages 17-36, March.
   5. Grabowski, Wojciech & Welfe, Aleksander, 2020. "The Tobit cointegrated vector autoregressive model: An application to the currency market," Economic Modelling, Elsevier, vol. 89(C), pages 88-100.

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Statistics

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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 12 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-MON: Monetary Economics (6) 2012-03-28 2019-02-18 2023-07-17 2024-01-08 2024-01-08 2024-01-08. Author is listed
2. NEP-ARA: MENA - Middle East and North Africa (5) 2012-03-28 2012-09-03 2018-02-05 2019-02-18 2019-11-11. Author is listed
3. NEP-FOR: Forecasting (2) 2012-03-28 2012-09-03
4. NEP-MAC: Macroeconomics (2) 2018-02-05 2019-02-18
5. NEP-URE: Urban and Real Estate Economics (2) 2024-01-08 2024-01-08
6. NEP-FMK: Financial Markets (1) 2011-08-15
7. NEP-IFN: International Finance (1) 2012-02-01
8. NEP-LAB: Labour Economics (1) 2012-09-03

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