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Testing
Bergbauer, Annika - 2018
School systems regularly use student assessments for accountability purposes. But, as highlighted by our conceptual model, different configurations of assessment usage generate performance-conducive incentives of different strengths for different stakeholders in different school environments. We...
Persistent link: https://www.econbiz.de/10012910939
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The Economic Roots of the Rise of Trumpism
Komlos, John - 2018
Donald Trump won the election in 2016 largely because enough voters in three states, all in the Rustbelt, who had voted for Barack Obama in both 2008 and 2012, switched their vote from Democratic to Republican. Economic dislocations played a crucial role in these swing states or democratic...
Persistent link: https://www.econbiz.de/10012924354
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Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle
Carstensen, Kai - 2017
We estimate a Markow-switching dynamic factor model with three states based on six leading business cycle indicators for Germany preselected from a broader set using the Elastic Net soft-thresholding rule. The three states represent expansions, normal recessions and severe recessions. We show...
Persistent link: https://www.econbiz.de/10012955198
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Structural Vector Autoregressions with Heteroskedasticity - A Comparison of Different Volatility Models
Luetkepohl, Helmut - 2015
A growing literature uses changes in residual volatility for identifying structural shocks in vector autoregressive (VAR) analysis. A number of different models for heteroskedasticity or conditional heteroskedasticity are proposed and used in applications in this context. This study reviews the...
Persistent link: https://www.econbiz.de/10013023197
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Identification and Estimation of the Environmental Kuznets Curve : Pairwise Differencing to Deal with Nonlinearity and Nonstationarity
Sen, Suphi - 2016
We propose an estimation strategy that accounts for two major problems raised in the empirical literature testing for … problems. Second, we apply nonlinear-nonstationary parametric and non-parametric estimation techniques to estimate the pairwise …
Persistent link: https://www.econbiz.de/10012993697
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Forecasting Random Walks Under Drift Instability
Pesaran, M. Hashem - 2011
This paper considers forecast averaging when the same model is used but estimation is carried out over different … estimation windows. It develops theoretical results for random walks when their drift and/or volatility are subject to one or … more structural breaks. It is shown that compared to using forecasts based on a single estimation window, averaging over …
Persistent link: https://www.econbiz.de/10012756639
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Deterministic versus Stochastic Seasonal Fractional Integration and Structural Breaks
Caporale, Guglielmo Maria; Cunado, Juncal; Gil-Alana, … - 2021
This paper considers a general model which allows for both deterministic and stochastic forms of seasonality, including fractional (stationary and nonstationary) orders of integration, and also incorporating endogenously determined structural breaks. Monte Carlo analysis shows that the suggested...
Persistent link: https://www.econbiz.de/10013317060
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A Multivariate Long-Memory Model with Structural Breaks
Caporale, Guglielmo Maria; Gil-Alana, Luis A. - 2021
This paper introduces a multivariate long-memory model with structural breaks. In the proposed framework, time series exhibit possibly fractional orders of integration which are allowed to be different in each subsample. The break date is endogenously determined using a procedure which minimises...
Persistent link: https://www.econbiz.de/10013317169
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Cointegration Analysis with Mixed-Frequency Data
Seong, Byeongchan; Ahn, Sung K.; Zadrozny, Peter A. - 2021
maximum likelihood estimation of the parameters in the model, we use an expectation maximization algorithm based on the state …
Persistent link: https://www.econbiz.de/10013317180
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Modelling Volatility of Cryptocurrencies Using Markov-Switching GARCH Models
Caporale, Guglielmo Maria - 2018
cryptocurrencies, i.e. Bitcoin, Ethereum, Ripple and Litecoin. More than 1,000 GARCH models are fitted to the log returns of the … well as using a Model Confidence Set (MCS) procedure for their loss functions. The results imply that using standard GARCH …
Persistent link: https://www.econbiz.de/10012910938