Three Essays on Nonlinear Nonstationary Econometrics and Applied Macroeconomics PDF Download
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Author: Youngsoo Bae
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Author: Youngsoo Bae
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Category :
Languages : en
Pages : 0
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Author: Mark Joseph Dwyer
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 172
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Author: Niels Haldrup
Publisher: OUP Oxford
ISBN: 0191669547
Category : Business & Economics
Languages : en
Pages : 393
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Book Description
This edited collection concerns nonlinear economic relations that involve time. It is divided into four broad themes that all reflect the work and methodology of Professor Timo Teräsvirta, one of the leading scholars in the field of nonlinear time series econometrics. The themes are: Testing for linearity and functional form, specification testing and estimation of nonlinear time series models in the form of smooth transition models, model selection and econometric methodology, and finally applications within the area of financial econometrics. All these research fields include contributions that represent state of the art in econometrics such as testing for neglected nonlinearity in neural network models, time-varying GARCH and smooth transition models, STAR models and common factors in volatility modeling, semi-automatic general to specific model selection for nonlinear dynamic models, high-dimensional data analysis for parametric and semi-parametric regression models with dependent data, commodity price modeling, financial analysts earnings forecasts based on asymmetric loss function, local Gaussian correlation and dependence for asymmetric return dependence, and the use of bootstrap aggregation to improve forecast accuracy. Each chapter represents original scholarly work, and reflects the intellectual impact that Timo Teräsvirta has had and will continue to have, on the profession.
Author: Lei Zhang
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 320
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Author: Zhengfeng Guo
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 86
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Author: Máximo Cosme Camacho Alonso
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Category :
Languages : en
Pages : 0
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Author: Charles Shaw
Publisher:
ISBN:
Category :
Languages : en
Pages : 101
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This thesis is submitted ...
Author: Novella Maugeri
Publisher:
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Category :
Languages : en
Pages :
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Author: Fei Han
Publisher:
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Category :
Languages : en
Pages : 296
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This dissertation consists of three chapters dealing with different topics in time series econometrics including generalized method of moments (GMM) estimation and vector autoregressions (VAR). These econometric models have revolutionized empirical research in macroeconomics. Previous work by Hansen and Singleton (1982) showed that the GMM method can be applied to estimate nonlinear rational expectations models in a simple way that the models need not even be solved. The seminal work of Sims (1980) has demonstrated how VAR models can be used for macroeconomic forecasting and policy analysis. The objective of this dissertation is to provide some new econometric tools for applied research in macroeconomics using time series data. The first chapter develops an asymptotic theory for the GMM estimator in nonlinear econometric models with integrated regressors and instruments. We establish consistency and derive the limiting distribution of the GMM estimator for asymptotically homogeneous regression functions. The estimator is consistent under fairly general conditions, and the convergence rates are determined by the degree of the asymptotic homogeneity of regression functions. Similar to linear regressions, we find that the limiting distribution is generally biased and non-Gaussian, and that instruments themselves cannot eliminate the bias even when they are strictly exogenous. Therefore, GMM yields inefficient estimates and invalid $t$- and chi-square test statistics in general. By implementing the fully modified method developed by Phillips and Hansen (1990), we obtain an efficient GMM estimator which has an unbiased and mixed normal limiting distribution. In the second chapter, we develop a novel shock identification strategy in the context of two-country/block structural vector autoregressive (SVAR) models to identify the transmission of credit shocks. Specifically, we investigate how credit shocks originating in the U.S. or euro area affect domestic economic activity in emerging Asia. Shocks within each block are identified using sign restrictions, whereas shocks across the two blocks are identified using a recursive structure (block Cholesky decomposition). This strategy not only enables us to distinguish the external credit shock from the other structural shocks, but also captures the responses of the domestic country. The main findings include that the transmission of credit shocks across countries through the channel of credit contagion is fast and protracted. The adverse effects of external credit tightening are mitigated by domestic credit policy easing in China, but lead to significant decreases in credit and GDP growth in the other emerging Asian countries. We also find that the external credit shocks play a non-negligible role in driving economic fluctuations in emerging Asia, although the role is smaller in China. In the last chapter, we use a global vector autoregressive (GVAR) model to forecast the principal macroeconomic indicators of the original five ASEAN member countries (i.e. Indonesia, Malaysia, Philippines, Singapore, and Thailand). The GVAR model is a compact model of the world economy designed to explicitly model the economic and financial interdependencies at national and international levels. Our GVAR model covers twenty countries which are grouped into nine countries/regions. After applying vector error correction model (VECM) to estimate parameters in the GVAR, we generate twelve one-quarter-ahead forecasts of real GDP growth, inflation, short-term interest rates, real exchange rates, real equity prices, and world commodity prices over the period 2009Q1-2011Q4, with four out-of-sample forecasts during 2009Q1-2009Q4. Forecast evaluation based on the panel Diebold-Mariano (DM) tests shows that the forecasts of our GVAR model tend to outperform those of country-specific VAR models, especially for short-term interest rates and real equity prices. These results suggest that the interdependencies among countries in the global financial market play an important role in macroeconomic forecasting.
Author:
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ISBN: 9789056297534
Category :
Languages : en
Pages : 160
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"This thesis explores the highly nonlinear profile of the modern financial world and assesses its relevance in monetary policy conduct and macroprudential supervision. It focuses on three possible different origins of nonlinear structures. Firstly, we study the role of the heterogeneous and boundedly rational expectations in driving the aggregate economic dynamics. Secondly, we investigate the irregularities of probability distributions and their consequences for quantitative inference. Thirdly, we assess the behavior of the global asset network through a prism of complex systems. Because of its extraordina1y relevance in the real world, a lot of attention is being paid to the banking side of the economy. The practical goal of this thesis is to provide the tools and general directions on how to incorporate possible nonlinear dependencies into existing economic modeling techniques. In times of very non-standard policy actions, these tools might prove to be of great importance as they offer more robust and flexible approaches to financial modeling and forecasting."--Samenvatting auteur.
