Introduction |
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1 | (8) |
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Part I Empirical Economic Research |
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Decomposition of Time Series Using the Generalised Berlin Method (VBV) |
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9 | (36) |
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Time Series Segmentation Procedures to Detect, Locate and Estimate Change-Points |
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45 | (16) |
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Regularization Methods in Economic Forecasting |
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61 | (20) |
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Investigating Bavarian Beer Consumption |
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81 | (8) |
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The Algebraic Structure of Transformed Time Series |
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89 | (16) |
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Reliability of the Automatic Identification of ARIMA Models in Program TRAMO |
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105 | (18) |
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Panel Model with Multiplicative Measurement Errors |
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123 | (22) |
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A Modified Gauss Test for Correlated Samples with Application to Combining Dependent Tests or P-Values |
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145 | (14) |
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Panel Research on the Demand of Organic Food in Germany: Challenges and Practical Solutions |
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159 | (14) |
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The Elasticity of Demand for Gasoline: A Semi-parametric Analysis |
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173 | (22) |
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The Pitfalls of Ignoring Outliers in Instrumental Variables Estimations: An Application to the Deep Determinants of Development |
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195 | (20) |
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Evaluation of Job Centre Schemes: Ideal Types Versus Statistical Twins |
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215 | (8) |
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The Precision of Binary Measurement Methods |
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223 | (16) |
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Part II Empirical Financial Research |
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On EFARIMA and ESEMIFAR Models |
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239 | (16) |
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Prediction Intervals in Linear and Nonlinear Time Series with Sieve Bootstrap Methodology |
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255 | (20) |
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Do Industrial Metals Prices Exhibit Bubble Behavior? |
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275 | (12) |
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Forecasting Unpredictable Variables |
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287 | (18) |
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Dynamic Modeling of the Correlation Smile |
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305 | (22) |
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Findings of the Signal Approach: A Case Study for Kazakhstan |
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327 | (14) |
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Double Conditional Smoothing of High-Frequency Volatility Surface Under a Spatial Model |
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341 | (16) |
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Zillmer's Population Model: Theory and Application |
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357 | (16) |
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Part III New Econometric Approaches |
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Adaptive Estimation of Regression Parameters for the Gaussian Scale Mixture Model |
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373 | (6) |
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The Structure of Generalized Linear Dynamic Factor Models |
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379 | (22) |
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Forecasting Under Structural Change |
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401 | (20) |
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Distribution of the Durbin--Watson Statistic in Near Integrated Processes |
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421 | (16) |
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Testing for Cointegration in a Double-LSTR Framework |
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437 | (14) |
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Fitting Constrained Vector Autoregression Models |
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451 | (20) |
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Minimax Versions of the Two-Step Two-Sample-Gaus- and t-Test |
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471 | (16) |
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Dimensionality Reduction Models in Density Estimation and Classification |
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487 | (10) |
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On a Craig--Sakamoto Theorem for Orthogonal Projectors |
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497 | (6) |
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A Note of Appreciation: High Standards with Heart |
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503 | |
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