Arikan, Cengiz and Yalcin, Yeliz (2017): Do The Countries’ Monetary Policies Have Spatial Impact?
PDF
MPRA_paper_83380.pdf Download (412kB) |
Abstract
Nowadays, not land border but economic cooperation and borders determine the neighborhood and closeness by globalization. No doubt, any economic event happens in any country affects other partners more and less according to economic relationship in globalization process. The desire of measuring of this interaction make occur spatial econometrics. Initially, in spatial models take into account land borders. Subsequently, studies about spatial econometric models allow economic interactions and relationships. After the global economic crises in 2008 Central Banks have started to vary monetary policy tool to ensure economic and financial stability. It is estimated that which tool will be implemented by following the policies of the central banks in which they are closely related. The spatial effect of monetary policy can be not only geographical but also economic or social. Different spatial models have set up to examine whether any spatial effect on monetary policy. Unlike other studies in this study not only geographic weight matrix but also economic weight matrix have been used in the spatial models. Different weight matrix models results have been compared and construed. Our preliminary findings reveal that there is a spatial effect on monetary policy between OECD, EU and G-20 countries. And also, economic weight matrix effect is more than geographic weight matrix.
Item Type: | MPRA Paper |
---|---|
Original Title: | Do The Countries’ Monetary Policies Have Spatial Impact? |
English Title: | Do The Countries’ Monetary Policies Have Spatial Impact? |
Language: | English |
Keywords: | Monetary Policy, Spatial Model, Spatial Impact, Econometrics |
Subjects: | C - Mathematical and Quantitative Methods > C0 - General > C01 - Econometrics C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation E - Macroeconomics and Monetary Economics > E5 - Monetary Policy, Central Banking, and the Supply of Money and Credit > E52 - Monetary Policy |
Item ID: | 83407 |
Depositing User: | Mr. Cengiz ARIKAN |
Date Deposited: | 22 Dec 2017 05:07 |
Last Modified: | 29 Sep 2019 21:42 |
References: | Anselin, L. (1988), “Spatial Econometrics: Methods and Models” First Edit, Dordrecht: Kluwer Academic Publishers. Anselin, L. and Bera, A. K. (1998), “Handbook of Applied Economic Statistics”, Marcel Dekker AG, Chapter 7, pages: 237-290 Bilur, A., Cihak, M. and Jansen, D.J. (2013), “Measuring the clarity of central-bank communication”, VOX CEPR's Policy Portal, http://voxeu.org/article/measuring-clarity-central-bank-communication Date: 08.08.2017 Blinder A. S., Ehrmann, M., Fratzscher, M., Haan, J.D. and Jansen, D.J, (2008)"Central Bank Communication and Monetary Policy: A Survey of Theory And Evidence," Journal of Economic Literature, American Economic Association, Vol. 46(4), pages 910-45 Borys, M.M. and R. Horvath & M. Franta (2009), “The effects of monetary policy in the Czech Republic: an Empirical Study”, Empirica, 36, 419-443. Chakraborty, I., I. Goldstein, and A. MacKinlay (2016). Monetary stimulus and bank lending. Working paper. Chuku A.C. (2009), “Measuring the Effects of Monetary Policy Innovations in Nigeria: A Structural Vector Autoregressive (SVAR) Approach”, African Journal of Accounting, Economics,Finance and Banking Research, 5(5), 112-129. Chua, Y.S. (2012), “Assessing the Effects of Monetar Policy Shocks in Malaysia: A Factor Aughmented Vector Autoregressive Approach”, The IUP Journal of Applied Economics,11(3), 65-83. Corrado, L. and Bernard, F., (2012), “Where is the Economics in Spatial Econometrics?”, Journal of Regional Science, 52 (2): 210-239. Elhorst, J. Paul (2010), “Applied Spatial Econometrics: Raising the Bar”, Spatial Economic Analysis,5 (1): 9-28. Elhorst, J. Paul (2014), “Linear Spatial Dependence Models for Cross-Section Data”, Spatial Econometrics from Cross-Sectional Data to Spatial Panels (Berlin, Heidelberg: Springer):5-37. Gabriel, S. and Lutz, C. (2015), “The Impact of Unconventional Monetary Policy on Real Estate Markets”, SSRN Working Paper Galvao, B.A. and M. Marcellino (2014), “The Effects of Monetary Policy Stance on the Transmission Mechanism”, Stud. Nonlinear Dyn. E., 18(3), 217-236. Gambacorta, L. and Hofmann, B. (2012), “The Effectiveness of Unconventional Monetary Policy at the Zero Lower Band: A Cross Country Analysis”, Bank for International Settlements Working Papers, No: 384 Giacinti, D. V. (2003), “Differential Regional Effects of Monetary Policy: A Geographical SVAR Approach”, İnternational Regional Science Review,26, 3: 313-341 LeSage, J. P. (1997), “Regression Analysis of Spatial Data”, Journal of Regional Analysis and Policy, 27 (2): 83-94. Luck, S. and Zimmermann, T. (2017), “Employment Effects of Unconventional Monetary Policy: Evidence from QE”, Federal Reserve Board, Working Paper, Munir, K. and A. Qayyum (2014), “Measuring the effects of monetary policy in Pakistan: a Factor Aughmented Vector Autoregressive Approach”, Empirical Economics, 46, 843-864. Oktar, S. and Dalyancı, L. (2012), “The Effect of The Monetary Policy on Economic Growth in Turkish Economy”, Marmara Universitesi IIB Dergisi, Vol. XXXII, Number:I, pages: 1-18 Ozdaglı, A.K. and Weber, M. (2016), “Monetary Policy Through Production Networks: Evidence from the Stock Market”, Federal Reserve Board, Working Paper, Tuzcu, S.E. (2016), “Mekânsal Ekonometri ve Sosyal Bilimlerde Kullanım Alanları”, Ankara Universitesi SBF Dergisi, Vol. 71, No. 2, pages: 401-436 Ward, M. D. ve Gleditsch, K.S. (2008), Spatial Regression Models (Los Angeles: Sage Publications). Wu, P.C. and Liu, S.Y. (2017), “Monetary Policy and the Time-Varying Spatial Effects of Bilateral Trade: Evidence from China-ASEAN-5 Countries”, Applied Spatial Analysis and Policy, Vol. 10 Issue 1, pp: 103-120 |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/83407 |