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1 – 10 of 15Claudia Foroni, Eric Ghysels and Massimiliano Marcellino
The development of models for variables sampled at different frequencies has attracted substantial interest in the recent literature. In this article, we discuss classical and…
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The development of models for variables sampled at different frequencies has attracted substantial interest in the recent literature. In this article, we discuss classical and Bayesian methods of estimating mixed-frequency VARs, and use them for forecasting and structural analysis. We also compare mixed-frequency VARs with other approaches to handling mixed-frequency data.
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Kirstin Hubrich and Timo Teräsvirta
This survey focuses on two families of nonlinear vector time series models, the family of vector threshold regression (VTR) models and that of vector smooth transition regression…
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This survey focuses on two families of nonlinear vector time series models, the family of vector threshold regression (VTR) models and that of vector smooth transition regression (VSTR) models. These two model classes contain incomplete models in the sense that strongly exogeneous variables are allowed in the equations. The emphasis is on stationary models, but the considerations also include nonstationary VTR and VSTR models with cointegrated variables. Model specification, estimation and evaluation is considered, and the use of the models illustrated by macroeconomic examples from the literature.
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Thomas B. Götz, Alain Hecq and Jean-Pierre Urbain
This article proposes a new approach to detecting the presence of common cyclical features when several time series are sampled at different frequencies. We generalize the…
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This article proposes a new approach to detecting the presence of common cyclical features when several time series are sampled at different frequencies. We generalize the common-frequency approach introduced by Engle and Kozicki (1993) and Vahid and Engle (1993). We start with the mixed-frequency VAR representation investigated in Ghysels (2012) for stationary time series. For non-stationary time series in levels, we show that one has to account for the presence of two sets of long-run relationships. The first set is implied by identities stemming from the fact that the differences of the high-frequency
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Thomas Garavan, Fergal O'Brien, Clare (Ruth) Power, Gerri Matthews-Smith and Joan Buckley
Rafael Galvão de Almeida and Harley Silva
This article delves into the contributions of Milton Santos (1926–2001) to the economic study of entrepreneurship. Santos made contributions to spatial economics, urbanization…
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This article delves into the contributions of Milton Santos (1926–2001) to the economic study of entrepreneurship. Santos made contributions to spatial economics, urbanization, and planning theories, being an important author to the field of regional and urban economics. His most famous idea is the “two circuits” of the urban economy. According to this approach, the urban economies in peripheral countries create two economic-urban circuits that are both distinct and connected. The superior circuit comes from the technological modernization and cultivates international relationships. High-value goods and networks and new technologies circulate through it. The inferior circuit works outside these networks. It consists of low-dimension activities from local populations. Santos elaborated this theory to understand urbanization in peripheral countries and to give voice to the ones left behind by the development process. He did not write directly on entrepreneurship. We argue, however, that his thoughts can be important to entrepreneurship studies. The entrepreneurship discourse, that had in Schumpeter one of its main sources, assumes that the entrepreneur has traits related to the superior circuit, such as access to resources and networks, which would not be available to entrepreneurs in the inferior circuit. We argue that Santos’ contributions can inform economic thought in entrepreneurship by calling attention to how literature can approach structural problems and contribute to making economics a more diverse discipline.
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This chapter analyzes the properties of an alternative least-squares based estimator for linear panel data models with general predetermined regressors. This approach uses…
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This chapter analyzes the properties of an alternative least-squares based estimator for linear panel data models with general predetermined regressors. This approach uses backward means of regressors to approximate individual specific fixed effects (FE). The author analyzes sufficient conditions for this estimator to be asymptotically efficient, and argue that, in comparison with the FE estimator, the use of backward means leads to a non-trivial bias-variance tradeoff. The author complements theoretical analysis with an extensive Monte Carlo study, where the author finds that some of the currently available results for restricted AR(1) model cannot be easily generalized, and should be extrapolated with caution.
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