ENFLASYONİST KOŞULLARDA TÜRKİYE EKONOMİSİNE İLİŞKİN PARA ARZI TAHMİNİ

Para arzı artışı, faiz oranları ve harcama/gelir büyüklükleri arasındaki ilişkiyi anlamak, merkez bankaları ve politika yapıcılar için önemli bir konudur. Para politikasının isabeti ve etkinliği parasal büyüklüklerdeki değişmeler ile mevcut ve gelecekteki harcama/gelir ve enflasyonun hareketlerinin doğru yorumlanmasına bağlıdır. Para politikalarının temel amacı enflasyonu kontrol etmek olan merkez bankası, para ve kredi arzının büyüme oranını etkileyerek, ekonomideki mal ve hizmetlere yapılan toplam harcamalara müdahale edebilmektedir. Bu çalışmada, Merkez Bankası açısından hem bir ara hedef hem de bir bilgi değişkeni olan para arzı toplamlarından reel M2 serisinin ex-post öngörüsü ve ayrıca Reel M2 ile Sanayi Üretimi arasındaki ilişki incelenmiştir. Bu çerçevede, zaman serisi analizi ile bazı öngörü modelleri oluşturularak söz konusu modellerden elde edilen sonuçlar tartışılmıştır. MA(1) ve ARMA(0,0) kullanarak RM2’nin öngörülmesi makul sonuçlar vermiştir. Ayrıca, çeşitli VAR modelleri kullanılarak sanayi üretimi (dlY) ve reel para arzı (dlrM2) birlikte belirlenmiştir. En iyi VAR modeli, içsel değişkenler olan dlY ve dlrM2’in gecikmeli değerlerini içermektedir. Granger Nedensellik Testi, RM2'nin Y'ye neden olmadığını ancak Y’nin RM2'ye neden olduğunu göstermektedir. Bu sonuç, Merkez Bankasının ekonomik aktivite seviyesine bakarak para arzının büyüklüğünü belirlediğini göstermektedir. Örneğin yaz aylarında ekonomi daha yoğun faaliyet içermektedir (turizm, ihracat, ithalat) ve Merkez Bankası ekonomik aktiviteye göre para arzını artırmaktadır.

Forecasting Money Supply Growth in Turkey under Inflationary Conditions

Understanding the relationship between money supply growth, interest rates and spending/income volumes is an important issue for central banks and policy makers. The accuracy and effectiveness of monetary policy depends on the correct interpretation of changes in monetary aggregates, current and future expenditure/income and inflation movements. The central bank, whose main objective of monetary policies is to control inflation, can intervene in the total expenditures on goods and services in the economy by affecting the growth rate of money and credit supply. In this study, the ex-post prediction of the real M2 series and also the relationship between Real M2 and Industrial Production are examined. In this framework, some forecast models were formed and and discussed. Estimating RM2 using MA(1) and ARMA(0,0) yield reasonable results. In addition, industrial production (dlY) and real money supply (dlrM2) were determined together using various VAR models. The best VAR model includes the lagged values ​​of the endogenous variables dlY and dlrM2. The Granger Causality Test shows that RM2 does not cause Y, but Y does cause RM2. This result shows that the Central Bank determines the size of the money supply by looking at the level of economic activity.

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  • Asako, K. ve Wagner, H. (1992). Nominal income targeting versus money supply targeting. Scottish Journal of Political Economy, 39(2), 167–187.
  • Atuk, O. ve Ural, B.P. (2002). Seasonal adjustment methods: An application to the Turkish monetary aggregates. Central Bank Review, 2(1), 21–37.
  • Bagshaw, M.L. ve Gavin, W.T. (1983). Forecasting the money supply in time series models. Working Papers (Old Series) 8304. Federal Reserve Bank of Cleveland.
  • Box, Jenkins ve Reinsel, Ljung (2015). Time series analysis: Forecasting and control. 5th Edition. John Wiley and Sons Inc., Hoboken, New Jersey.
  • Breusch, T.S. (1978). Testing for autocorrelation in dynamic linear models. Australian Economic Papers, 17, 334–355. 
  • Brooks, C. ve Tsolacos, S. (2010). Real estate modelling and forecasting. Cambridge: Cambridge University Press.
  • Çavuşoğlu, A.T. (2003). The endogenous money growth: An outcome of high budget deficits in Turkey. H.Ü. İktisadi ve İdari Bilimler Fakültesi Dergisi, 21(1), 111–127. 
  • Chappell, D. ve Peel, D.A. (1979). On the dynamic stability of monetary models when the money supply is endogenous. The Manchester School, 47(4), 349–358.
  • Chang, C.-H., Chan, K.C. ve Fung, H.G. (2009). Effect of money supply on real output and price in China. China & World Economy, 17(2), 35–44.
  • Chatfield, C. ve Xing, H. (2019). The analysis of time series: An introduction with R. 7th Edition. New York: Chapman and Hall/CRC Press.
  • Enders, W. (2015). Applied econometric time series. Hoboken, NJ: Wiley.
  • Engle, R.F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987–1007.
  • Engle, R.F. (1984). Wald, likelihood ratio, and lagrange multiplier tests in econometrics. Handbook of Econometrics, Vol. 2, Chapter 13, 775–826.
  • Evans, G.W. ve Honkapohja, S. (2003). Friedman's money supply rule vs. optimal interest rate policy. Scottish Journal of Political Economy, 50(5), 550–566.
  • Friedman, M. (1970). Counter-revolution in monetary theory, Occasional Paper 33, Wincott Memorial Lecture, Institute of Economic Affairs.
  • Gavin, W.T. ve Kydland, F.E. (1999). Endogenous money supply and the business cycle. Review of Economic Dynamics, 2(2), 347–369.
  • Godfrey, L.G. (1978). Testing against general autoregressive and moving average error models when the regressors include lagged dependent variables. Econometrica, 46, 1293–1301.
  • Koenig, E.F. (1996). Forecasting M2 growth: An exploration in real time. Economic and Financial Policy Review, Federal Reserve Bank of Dallas, Issue Q II, 16–26.
  • Kwiatkowski, D., Phillips, P.C.B, Schmidt, P. ve Shin, Y. (1992). Testing for the null hypothesis of stationarity against the alternative of unit root: How sure are we that economics time series have a unit root. Journal of Econometrics, 54, 159–178.
  • Lane, T.D. (1985). The rationale for money-supply targets: A survey. The Manchester School, 53(2), 179–207.
  • Miyao, Ryuzo (2004). Use of money supply in the conduct of Japan's monetary policy: Reexamining the time series evidence. Discussion Paper Series, Research Institute for Economics & Business Administration, Kobe University.
  • Nelson, C.R. ve Plosser, C.I. (1982). Trends and random walks in macroeconomic time series: Some evidence and implications. Journal of Monetary Economics, 10, 139–162.
  • Jarque, C.M. ve Bera, A.K. (1980). Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Economics Letters, 6(3), 255–259.
  • Jarque, Carlos M. ve Bera, Anil K. (1987). A test for normality of observations and regression residuals. International Statistical Review, 55(2), 163–172.
  • Lombra, R.E. ve Kaufman, H.M. (1984). The money supply process: Identification, stability, and estimation. Southern Economic Journal, 50(4), 1147–1159.
  • Martin, V., Hurn, S. ve Harris, D. (2013). Econometric modelling with time series: Specification, estimation and testing. Cambridge: Cambridge University Press. 
  • Mercenier, J.ve Sekkat, K. (1988). Money stock targeting and money supply: An intertemporal optimization approach (with an application to Canada). Journal of Applied Econometrics, 3(3), 215–228.
  • Perron, P. (1989). The great crash, the oil price shock, and the unit root hypothesis. Econometrica, 57(6), 1361–1401.
  • Pindyck, R.S. ve Daniel L. R. (1991). Econometric models and economic forecasts. 3rd Edition. New York: McGraw-Hill.
  • Prasad, K. (1968). The impact of money supply on the price level and the rate of interest in India, 1950-51 to 1961-62. Bulletin of Economic Research, 20(1), 14–27.
  • Singh, R.A. (1993). Response of stock prices to money supply announcements: Australian evidence. Accounting & Finance, 33(2), 43–59.
  • Stemp, P.J. (1993). Optimal money supply rules under asymmetric objective criteria. Journal of Economics, 57(3), 215–232.