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Author: 郭穎文
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 172
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Book Description
Author: 郭穎文
Publisher:
ISBN:
Category : Econometric models
Languages : en
Pages : 172
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Book Description
Author: Zvi Griliches
Publisher: Edward Elgar Pub
ISBN: 9781852786595
Category : Business & Economics
Languages : en
Pages : 664
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Book Description
'Reading a paper by Griliches, one sees how empirical economic research should be done. As the twentieth century ends, researchers are specializing more and more. Sometimes the link between economics and econometrics is often weak, if not severed. Graduate students in economics programs should be required to read at least one classic paper by Griliches to see that economic theory, data and econometrics belong together.' - Journal of the American Statistical Association 'An excellent reference source of this eminent economist's foremost work on method, applied econometrics and specification problems over the last forty years.' - Aslib Book Guide Zvi Griliches has made many seminal contributions to econometrics during the course of a long and distinguished career. His work has focused primarily on the economics of technological change and the econometric problems that arise in trying to study it.
Author: Xinghua Yu
Publisher:
ISBN:
Category :
Languages : en
Pages : 228
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Book Description
Author: Tae Suk Lee
Publisher:
ISBN:
Category : Analysis of variance
Languages : en
Pages : 228
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Book Description
"This dissertation consists of two essays dealing respectively with estimation of volatility and test for a jump using high frequency data. Chapter 1 investigates the properties of pre-averaging estimators of integrated volatility, first considered by Podolskij and Vetter (2009). We relax their assumptions on the properties of market microstructure noise in order to include realistic and empirically relevant features of noise such as missing data and flat price trading. We develop an asymptotic theory of our estimator using martingale convergence theorems. Especially we deal with the boundary problem of pre-averaging and we provide a solution to the parameters-on-the-boundary problem posed by pre-averaging estimators. Building on that theory, we show that a general linear combination of estimators can be made unbiased, and we devise a rate-optimal estimator of the integrated volatility. In addition, we derive a bootstrap statistic to assess the variance of our estimator. This allows us to optimally select the estimator's smoothing parameter from the data, providing an additional improvement over previously-considered pre-averaging estimators. Because our methodology and assumptions on the market microstructure noise component are general, our estimator can also be applied to multivariate time series without any need to correct for asynchronicity in the observations. Monte Carlo experiments show that our theoretical results are valid in realistic cases. Chapter 2 shows that the power of any test of this hypothesis depends on the frequency of observation. In particular, we show that if the process is observed at intervals of length 1/n and the instantaneous volatility of the process is given by [sigma]t, at best one can detect jumps of height no smaller than [sigma]t[...characters removed]. We construct a test which achieves this rate in the case for diffusion-type processes. With simulation experiments, we show that our tests have good size and power properties in many cases with realistic sample sizes and that they outperform other tests that have been proposed in the recent literature. Applying our tests to high-frequency financial data, we detect more jumps in the data than are found by other tests."--Leaves v-vi.
Author: David F. Hendry
Publisher: OUP Oxford
ISBN: 0191522112
Category : Business & Economics
Languages : en
Pages : 560
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Book Description
"Econometrics: Alchemy or Science?" analyses the effectiveness and validity of applying econometric methods to economic time series. The methodological dispute is long-standing, and no claim can be made for a single valid method, but recent results on the theory and practice of model selection bid fair to resolve many of the contentious issues. The book presents criticisms and evaluations of competing approaches, based on theoretical economic and econometric analyses, empirical applications, and Monte Carlo simulations, which interact to determine best practice. It explains the evolution of an approach to econometric modelling founded in careful statistical analyses of the available data, using economic theory to guide the general model specification. From a strong foundation in the theory of reduction, via a range of applied and simulation studies, it demonstrates that general-to-specific procedures have excellent properties. The book is divided into four Parts: Routes and Route Maps; Empirical Modelling Strategies; Formalization; and Retrospect and Prospect. A short preamble to each chapter sketches the salient themes, links to earlier and later developments, and the lessons learnt or missed at the time. A sequence of detailed empirical studies of consumers' expenditure and money demand illustrate most facets of the approach. Material new to this revised edition describes recent major advances in computer-automated model selection, embodied in the powerful new software program PcGets, which establish the operational success of the modelling strategy.
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: Clive W. J. Granger
Publisher: Cambridge University Press
ISBN: 9780521796491
Category : Business & Economics
Languages : en
Pages : 400
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Book Description
These are econometrician Clive W. J. Granger's major essays in causality, integration, cointegration, and long memory.
Author: David Conway
Publisher:
ISBN: 9781321846010
Category :
Languages : en
Pages : 72
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Book Description
My dissertation is composed of three chapters that contribute to the fields of Applied Econometrics and Macroeconomics. The first chapter, 'A Copula Model for Discrete Duration Data with Sample Selection', presents a copula model to account for sample selection in a model of unemployment duration data. I apply two Markov Chain Monte Carlo (MCMC) methods to determine posterior distributions for the model parameters. In particular, a version of the Gibbs sampler is applied to evaluate the integrals that result from the copula representation of the likelihood, and the Random Walk Metropolis Hasting (RW-MH) algorithm for sampling from the posterior distribution. The model is applied to discrete data on unemployment duration from the 2011 Current Population Survey. Joint estimation of the selection and duration equations indicates that selection bias is present, and the data are informative about the model parameters. The second chapter, 'Monetary Policy and Equity Prices in a Multivariate GARCH Model', develops a model for the high-frequency analysis of a fundamental relationship in macroeconomics, between monetary policy and equity prices. A market-based approach to estimating daily changes in unexpected monetary policy is incorporated into a multivariate copula GARCH model. This allows for efficient estimation of parameters in the mean equations for each of the variables, as well as the conditional heteroskedasticity and spillovers in volatility. I found little evidence for a relationship between monetary surprises and equity prices on this scale, with a mean correlation of -0.0503 between the two time series, which does not vary systematically over time. The third chapter, 'Federal Reserve Communication and its Time-Varying Impact on the Yield Curve: A Dynamic Nelson-Siegel Model for Daily Data', implements the first Dynamic Nelson-Siegel (DNS) model for daily data. This allows for estimation of the effect of daily shocks to monetary policy and macroeconomic factors. Time-varying coefficients account for the changing degree to which the zero lower bound (ZLB) constrains medium-term yields. My results indicate that yields were most sensitive to shocks to the future path of monetary policy in 2006-2007 with a rapid decline in sensitivity from 2008 to 2013. By the second quarter of 2013 the effect of a one standard deviation path shock on maturities under two years had fallen by more than 50% from the fourth quarter of 2007. As of July 2014 the sensitivity of 1-year yields began to show a modest increase, suggesting the market expects lift-off from the ZLB by mid-2015.
Author: Yoosoon Chang
Publisher: Emerald Group Publishing
ISBN: 1837532141
Category : Business & Economics
Languages : en
Pages : 382
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Book Description
Volumes 45a and 45b of Advances in Econometrics honor Professor Joon Y. Park, who has made numerous and substantive contributions to the field of econometrics over a career spanning four decades since the 1980s and counting.
Author: Pierre Guérin
Publisher:
ISBN:
Category : Econometrics
Languages : en
Pages : 151
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Book Description
In the first chapter of this thesis, I estimate Markov-switching models with time-varying transition probabilities to predict the US business cycle regimes. In particular, I evaluate the predictive power of real and financial indicators and find that the slope of the yield curve turns out to be the most reliable indicator for regime predictions. This first chapter paves the way for the next two chapters of this thesis that also use models with Markov-switching for analysing the business cycle. The second chapter (a joint work with Massimiliano Marcellino) combines the Markovswitching model with the MIxed DAta Sampling (MIDAS) model. This new model uses information from variables sampled at different frequencies. We first show in a Monte-Carlo experiment that our estimation method yields accurate estimates. We then apply this new model to the prediction of both the business cycle regimes and GDP growth for the US and the UK. We find that the use of high frequency information and parameter switching performs better than using each of these two features separately. In the third chapter (a joint work with Laurent Maurin and Matthias Mohr), we estimate nine different models of the output gap (univariate, multivariate, linear and non-linear) and compute model-averaged estimates of the output gap. We find some evidence for changes in the slope of the trend of the Euro area output for few periods in 1974 and 2009. Moreover, our model-averages measures of the output gap reduce the uncertainty associated with the output gap estimates and soften the impact of data revisions. We then evaluate the forecasting performance of our output gap estimates for inflation and find that the output gap estimates improve on the forecasting performance of standard AR benchmarks for inflation although the inflation forecasts based on the output gap estimates exhibit a poor forecasting performance since 2008. The last chapter of this thesis (a joint work with Eric Ghysels and Massimiliano Marcellino) is an empirical evaluation of the risk-return relation. We use a MIDAS estimator of the conditional variance and model regime changes in the parameter entering before the conditional variance. We find evidence for a reversed risk-return relation in periods of high volatility, while we uncover the traditional positive risk-return relation in periods of low volatility. In particular, the high volatility regime is interpreted as a flight-to-quality regime. This finding is robust to a large range of specifications.
