Suleyman Ozmucur

Exchange rates, inflation and money supply in Turkey: Testing the vicious circle hypothesis☆

Abstract A radical reform package has been implemented in Turkey in the post-1980 era involving simultaneously short-run adjustment and transition to an outward oriented regime. A major area where the programme has failed to register a significant success has been in the sphere of inflation. High and volatile rates of inflation continue to be a characteristic feature of the Turkish economy. This paper seeks to explain the persistence of this phenomenon with reference to the interactions between exchange rate, price level and money supply. The study employs monthly data and the period under consideration is January 1981 to December 1987, distinguished by managed exchange rate flexibility. Results of a four variable Vector Autoregressive model are presented and analyzed. These in turn provide the basis for a small-scale model in which high-powered money, price level, exports and the exchange rate are simultaneously explained. Judged in terms of its overall fit the model appears to be quite successful in accounting for the persistence phenomenon in the post-1980 period.

Prediction of Currency Crises: Case of Turkey

This paper explores the issue of constructing an economic predictive model of financial vulnerability through an alternative econometric methodology that addresses drawbacks in existing approaches. The methodology entails estimating a Markov regime switching model of exchange rate movements, with time-varying transition probabilities. Experiments with monthly and weekly models indicate that real exchange rate, foreign exchange reserves and domestic credit/deposit ratio are the most important determinants of financial vulnerability. These variables should be observed very closely by researchers and policy makers in order to determine if the country is heading for financially difficult times.

High-mixed-frequency forecasting models for GDP and inflation

This paper analyzes the technical and practical issues involved in the use of data at mixed frequencies (quarterly and monthly and, possibly, weekly and daily) to forecast monthly and quarterly economic activity in a country. In particular, it considers alternative high-frequency forecasting models for GDP growth and inflation in the Philippines, utilizing indicators that are observable at different frequencies and with particular focus on dynamic time-series models that involve latent factors. The study compares the forecasting performance of this approach with more commonly used data-intensive methods that have been developed in applications in the U.S. and Europe. These alternative approaches include Mixed Data Sampling (MIDAS) Regression and Current Quarter Modeling (CQM) with Bridge Equations. While these alternatives are mostly data-intensive, the dynamic latent factor modeling with mixed frequencies presents a parsimonious approach which depends on a much smaller data set that needs to be updated regularly. But it also faces additional complications in methodology and calculations as mixed-frequency data are included in the analysis…