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Öğe Big data financial transactions and GDP nowcasting: The case of Turkey(WILEY, 2023-09-29) Barlas, Ali; Mert, Seda Güler; İsa, Berk Orkun; Ortiz, Alvaro; Rodrigo, Tomasa; Soybilgen, Barış; Yazgan, EgeWe use aggregated information from individual-to-firm and firm-to-firm transactions from the Garanti BBVA Bank to simulate domestic private demand and estimate aggregate consumption and investment for Turkey's quarterly national accounts in real time. We show that these big data variables successfully nowcast official consumption and investment flows. To further validate the usefulness of these indicators, we include both indicators among others which are generally used in gross domestic product (GDP) nowcasting and evaluate their contribution to nowcasting power of Turkish GDP by combining both linear and nonlinear models. The results are successful and confirm the usefulness of consumption and investment banking transactions for nowcasting purposes. These big data are valuable, especially at the beginning of the nowcasting process, when the traditional hard data are scarce. Accordingly, this information is especially relevant for countries with longer statistical release lags, such as emerging markets.Öğe Evaluating nowcasts of bridge equations with advanced combination schemes for the Turkish unemployment rate(Elsevier Science Bv, 2018) Soybilgen, Baris; Yazgan, EgeThe paper analyzes the point and density predictive performance of alternative nowcast combination schemes in the context of bridge equations for the Turkish unemployment rate. Furthermore, we also nowcast the unemployment rate by using dynamic factor models (DFMs). Our results indicate that most of the sophisticated forecast combination methods have better predictive accuracy than the simple forecast combinations, especially in higher forecast horizons, which constitutes a case for the nowcast combination puzzle. Furthermore, most of bridge equations with the advanced forecast combination schemes usually outperform DFMs which are assumed to be superior to the bridge equations. This latter result indicates that bridge equations augmented by advanced forecast combination schemes may be a viable alternative to the DFM. Finally, we show that real and labor variables play the most important role for nowcasting the Turkish unemployment rate, whereas financial variables and surveys do not seem to be beneficial. Overall, our results indicate that advanced combination schemes can increase the performance of nowcasting models.Öğe An evaluation of inflation expectations in Turkey(ELSEVIER, 2017-03) Soybilgen, Barış; Yazgan, EgeExpectations of inflation play a critical role in the process of price setting in the market. Central banks closely follow developments in inflation expectations to implement a successful monetary policy. The Central Bank of the Republic of Turkey (CBRT) conducts a survey of experts and decision makers in the financial and real sectors to reveal market expectations and predictions of current and future inflation. The survey is conducted every month. This paper examines the accuracy of these survey predictions using forecast evaluation techniques. We focus on both point and sign accuracy of the predictions. Although point predictions from CBRT surveys are compared with those of autoregressive models, sign predictions are evaluated on their value to a user. We also test the predictions for bias. Unlike the empirical evidence from other economies, our results show that autoregressive models outperform most of inflation expectations in forecasting inflation. This indicates that inflation expectations have poor point forecast accuracies. However, we show that sign predictions for all inflation expectations have value to a user.Öğe High versus low inflation: implications for price-level convergence(2016-11) Yazgan, Ege; Yılmazkuday, HakanThis paper investigates the relationship between the level of inflation and regional price-level convergence utilizing micro-level price data from Turkey during two clearly distinguishable periods of high and low inflation. The results indicate that higher persistence and slower convergence of price levels are evident during the low-inflation period, which corresponds to the inflation targeting (IT) regime. During the low-inflation IT regime, inflation convergence across regions appears to occur more quickly and may be responsible for the slower pace of convergence in price levels. Overall, IT in Turkey, which was successful in lowering and maintaining inflation at acceptable levels, also appears to be associated with faster convergence in inflation rates at the expense of slower convergence in price levels.Öğe How Successful Are Wavelets in Detecting Jumps?(MDPI AG, 2017-12) Eroğlu, Burak Alparslan; Gencay, Ramazan; Yazgan, EgeWe evaluate the performances of wavelet jump detection tests by using simulated high-frequency data, in which jumps and some other non-standard features are present. Wavelet-based jump detection tests have a clear advantage over the alternatives, as they are capable of stating the exact timing and number of jumps. The results indicate that, in addition to those advantages, these detection tests also preserve desirable power and size properties even in non-standard data environments, whereas their alternatives fail to sustain their desirable properties beyond standard data features.Öğe Markov regime switching in mean and in fractional integration parameter(Taylor & Francis Inc, 2017) Ozkan, Harun; Stengos, Thanasis; Yazgan, EgeWe propose a specific general Markov-regime switching estimation both in the long memory parameter d and the mean of a time series. We employ Viterbi algorithm that combines the Viterbi procedures in two state Markov-switching parameter estimation. It is well-known that existence of mean break and long memory in time series can be easily confused with each other in most cases. Thus, we aim at observing the deviation and interaction of mean and d estimates for different cases. A Monte Carlo experiment reveals that the finite sample performance of the proposed algorithm for a simple mixture model of Markov-switching mean and d changes with respect to the fractional integrating parameters and the mean values for the two regimes.Öğe Nowcasting the New Turkish GDP(Economics Bulletin, 2018) Soybilgen, Baris; Yazgan, EgeIn this study, we predict year-on-year and quarter-on-quarter Turkish GDP growth rates between 2012:Q1 and 2016:Q4 with a medium-scale dataset. Our proposed model outperforms both the competing dynamic factor model (DFM) and univariate benchmark models. Our results suggest that in nowcasting current GDP, all relevant information is released within the contemporaneous quarter; hence, no predictive power is added afterwards. Moreover, we show that the inclusion of construction/ service sector variables and credit variables improves the prediction accuracy of the DFM.Öğe Nowcasting Turkish GDP and news decomposition(Elsevier, 2016-10-01) Modugno, Michele; Soybilgen, Barış; Yazgan, EgeReal gross domestic product (GDP) data in Turkey are released with a very long delay relative those of to other economies, between 10 and 13 weeks after the end of the reference quarter. This means that policy makers, the media, and market practitioners have to infer the current state of the economy by examining data that are more timely and are released at higher frequencies than the GDP. This paper proposes an econometric model that allows us to read through these more current and higher-frequency data automatically, and translate them into nowcasts for the Turkish real GDP. Our model outperforms the nowcasts produced by the Central Bank of Turkey, the International Monetary Fund, and the Organisation for Economic Co-operation and Development. Moreover, our model allows us to quantify the importance of each variable in our dataset for nowcasting Turkish real GDP. In line with the findings for other economies, we find that real variables play the most important role; however, contrary to the findings for other economies, we find that financial variables are as important as surveys. © 2016Öğe Nowcasting US GDP Using Tree-Based Ensemble Models and Dynamic Factors(Springer, 2021) Soybilgen, Baris; Yazgan, EgeIn this study, we nowcast quarter-over-quarter US GDP growth rates between 2000Q2 and 2018Q4 using tree-based ensemble machine learning models, namely, bagged decision trees, random forests, and stochastic gradient tree boosting. To solve the ragged edge problem and reduce the dimension of the data set, we adopt a dynamic factor model. Dynamic factors extracted from 10 groups of financial and macroeconomic variables are fed to machine learning models for nowcasting US GDP. Our results show that tree-based ensemble models usually outperform linear dynamic factor models. Factors obtained from real variables appear to be more influential in machine learning models. The impact of factors derived from financial and price variables can only become important in predicting GDP after the great financial crisis of 2008-9, reflecting the effect extra loose monetary policies implemented in the period following the crisis.Öğe Observations on Turkey's Recent Economic Performance(Springer, 2013) Akat, Asaf Savas; Yazgan, EgeWe establish that the Turkish economy underwent a remarkable transformation during the last decade. We identify the underpinnings of this successful transformation as well as the inadequate policies that enabled vulnerabilities to accumulate. Despite improvement in the economic fundamentals, volatility and dependence on external finance not only persisted, but actually increased during the last decade. We discuss the structural causes of the widening external deficit. Finally, we evaluate Turkey's outstanding economic performance in the aftermath of the global financial crisis and the recent soft landing and rebalancing episode.Öğe Price-level convergence: New evidence from U.S. cities(2011-02) Yazgan, EgeThis paper tests the bilateral price-level convergence among 52 U.S. cities at the good level by using a new econometric approach. The estimated median half lives are far below the half lives found in the corresponding studies for the U.S. © 2010 Elsevier B.V.Öğe Quantile forecast combination using stochastic dominance(PHYSICA-VERLAG GMBH & CO, 2018-12-01) Yazgan, EgeThis paper derives optimal forecast combinations based on stochastic dominance efficiency (SDE) analysis with differential forecast weights for different quantiles of forecast error distribution. For the optimal forecast combination, SDE will minimize the cumulative density functions of the levels of loss at different quantiles of the forecast error distribution by combining different time-series model-based forecasts. Using two exchange rate series on weekly data for the Japanese yen/US dollar and US dollar/Great Britain pound, we find that the optimal forecast combinations with SDE weights perform better than different forecast selection and combination methods for the majority of the cases at different quantiles of the error distribution. However, there are also some very few cases where some other forecast selection and combination model performs equally well at some quantiles of the forecast error distribution. Different forecasting period and quadratic loss function are used to obtain optimal forecast combinations, and results are robust to these choices. The out-of-sample performance of the SDE forecast combinations is also better than that of the other forecast selection and combination models we considered.Öğe Relative price variability and inflation: New evidence(Elsevier, 2016-06) Bağlan, Deniz; Yazgan, Ege; Yılmazkuday, HakanThis paper investigates the relationship between relative price variability (RPV) and inflation using monthly micro-price data for 128 goods in 13 Turkish regions/cities for the period 1994–2010. The unique feature of this data set is the inclusion of annual inflation rates ranging between 0% and 90%. Semi-parametric estimations show that there is a hump-shaped relationship between RPV and inflation, where the maximum RPV is achieved when annual inflation is approximately 20%. It is shown that this result is consistent with a region- or city-level homogenous menu cost model that features Calvo pricing with an endogenous contract structure and non-zero steady-state inflation.Öğe Threshold Regression Model for Taylor Rule: The Case of Turkey(Rimini Centre Economic Analysis, 2020) Yazgan, Ege; Deniz, Pınar; Thanasis, StengosThis paper employs the structural threshold approach of Kourtellos et al. (2016) to examine various specifications of the Taylor rule model. Contrary to the previous work on the Taylor rule, this methodology allows for endogeneity of the threshold variable in addition to the right-hand-side variables suggesting a fully comprehensive flexible framework that does not rely on restrictive linearity and /or exogeneity assumptions. In order to examine the model, Turkey is selected as an inflation targeting developing economy, since its central bank (the Central Bank of Turkey) as argued by Dincer and Eichengreen (2014) has been one of the fastest improving central banks in terms of its transparency score. We will use monthly data for the period of 2004-2018 that includes a number of historical episodes such as the global financial crisis as well as various internal political developments that may have had an impact on the fluctuations of the relevant macroeconomic variables as well as on the functional form of the inflation targeting Taylor rule specification. Empirical findings highlight the di fferent reactions of the central bank in determining policy rate under di fferent regimes.
