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Structural-break Models Under Mis-specification

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Release : 2013
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Book Synopsis Structural-break Models Under Mis-specification by : Bonsoo Koo

Download or read book Structural-break Models Under Mis-specification written by Bonsoo Koo. This book was released on 2013. Available in PDF, EPUB and Kindle. Book excerpt:

Forecasting in the Presence of Structural Breaks and Model Uncertainty

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Release : 2008-02-29
Genre : Business & Economics
Kind : eBook
Book Rating : 42X/5 ( reviews)

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Book Synopsis Forecasting in the Presence of Structural Breaks and Model Uncertainty by : David E. Rapach

Download or read book Forecasting in the Presence of Structural Breaks and Model Uncertainty written by David E. Rapach. This book was released on 2008-02-29. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting in the presence of structural breaks and model uncertainty are active areas of research with implications for practical problems in forecasting. This book addresses forecasting variables from both Macroeconomics and Finance, and considers various methods of dealing with model instability and model uncertainty when forming forecasts.

Structural Break Tests Robust to Regression Misspecification

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Release : 2016
Genre :
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Book Synopsis Structural Break Tests Robust to Regression Misspecification by : Alaa Abi Morshed

Download or read book Structural Break Tests Robust to Regression Misspecification written by Alaa Abi Morshed. This book was released on 2016. Available in PDF, EPUB and Kindle. Book excerpt:

Essays on Structural Breaks and Forecasting in Econometric Models

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Release : 2019
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Book Synopsis Essays on Structural Breaks and Forecasting in Econometric Models by : Yaein Baek

Download or read book Essays on Structural Breaks and Forecasting in Econometric Models written by Yaein Baek. This book was released on 2019. Available in PDF, EPUB and Kindle. Book excerpt: Instability of parametric models is a common problem in many fields of economics. In econometrics, these changes in the underlying data generating process are referred to as structural breaks. Although there is an extensive literature on estimation and statistical tests of structural breaks, existing methods fail to adequately capture a break. This dissertation consists of three papers on developing econometric methods for structural breaks and forecasting. The first chapter develops a new method in estimating the location of a structural break in a linear model and provide theoretical results and empirical applications of the estimator. In finite sample the conventional least-squares estimates a break occurred at either ends of the sample with high probability, regardless of the true break point. I suggest an estimator of the break point that resolves this pile up issue and thus, provide a more accurate estimate of the break. The second chapter constructs a statistical test to test existence of a structural break when the direction of the parameter shift is known. In practice it is likely that a researcher is interested in testing for a structural break in a particular direction because the direction is known, such as policy change or historical data. We incorporate this information in constructing three tests that have higher power when direction is correctly specified. The last chapter proposes a multi-period forecasting method that is robust to model misspecification. When we are interested in obtaining long horizon ahead forecasts, the direct forecast method is more favorable than the iterated forecast because it is more robust to misspecification. However, direct forecast estimates tend to have jagged shapes across horizons. I use a mechanism analogous to ridge regression on the direct forecast model to maintain robustness while smoothing out erratic estimates.

Testing for Structural Breaks in Small Samples

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Release : 2008-03
Genre : Computers
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Book Synopsis Testing for Structural Breaks in Small Samples by : Sergei Antoshin

Download or read book Testing for Structural Breaks in Small Samples written by Sergei Antoshin. This book was released on 2008-03. Available in PDF, EPUB and Kindle. Book excerpt: In a recent paper, Bai and Perron (2006) demonstrate that their approach for testing for multiple structural breaks in time series works well in large samples, but they found substantial deviations in both the size and power of their tests in smaller samples. We propose modifying their methodology to deal with small samples by using Monte Carlo simulations to determine sample-specific critical values under the each time the test is run. We draw on the results of our simulations to offer practical suggestions on handling serial correlation, model misspecification, and the use of alternative test statistics for sequential testing. We show that, for most types of data generating processes in samples with as low as 50 observations, our proposed modifications perform substantially better.

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