Makroekonomik temeller ve gelişmekte olan ülkelerde varlık fiyatları

This thesis consists of three chapters which make empirical contributions to the field of emerging markets xed income, real estate and nancial markets. First chapter entitled 'Macroeconomics Fundamentals and Emerging Market Local Currency Debt'focus on Emerging market (EM) local currency debt market which is largely absent from the academic literature, despite the increasingly important role of local currency debt for EM sovereign issuers and its increasing share in the portfolio of foreign investors. In this chapter, I investigate the effects of macroeconomic fundamentals on EM local currency bond markets using a dynamic factor approach based on a large panel of economic and financial time series. I find strong predictable variation in the EM local currency excess bond returns that is associated with macroeconomic activity. I provide evidence that the main predictor variables are the factors based on real economic activity that are highly correlated with measures of industrial and manufacturing production, but factors based on global financial factors also contain information about the future local currency bond returns. The predictive power of the extracted factors is not just statistically significant but also economically important. In the second chapter entitled 'Predictability of Emerging Market Real Estate Prices' I approximate large information set of EM real estate market by large panel of economic and financial time series used in the first chapter. One of the main contributions of this chapter to the empirical literature is to document the mutuality of top three factors predicting the real house price fluctuations in a sample of leading emerging economies including Brazil, Mexico, South Africa, and Turkey. As two-thirds of the almost 50 systemic banking crises in recent decades were preceded by boom-bust patterns in house prices, I believe that my findings have important implications for policymakers and pension fund managers. Finally, third chapter entitled 'Forecasting Turkish Real GDP Using Targeted Predictors' examines whether there is any merit of selecting a limited number of variables for superior forecasting performance. A number of recent studies in current literature discuss the usefulness of factor models in the context of GDP forecasting using large panels of macroeconomic variables. However, there is no consensus on how to identify informative variables from a large set of relevant indicators for the purpose of GDP prediction. Including too many variables in the analysis is likely to cause complications in extracting appropriate signal for the factor model framework. I empirically compare the forecasting performance of the dynamic factor model on various samples based on different selection criteria including my own. The forecasting exercise is performed for Turkish real GDP growth. My results show that the new sampling technique performs best as it attains first place in ranking for all backcast, nowcast and one-quarter ahead forecast periods.