نتایج جستجو برای: time series data jel classification c22

تعداد نتایج: 4292913  

1998
Simon M. Potter

The standard linear technique of impulse response function analysis is extended to the nonlinear case by de"ning a generalized impulse response function. Measures of persistence and asymmetry in response are constructed for a wide class of time series. ( 2000 Elsevier Science B.V. All rights reserved. JEL classixcation: C22; C51; C52; E32

2015
Ulrich K. Müller Mark W. Watson

Many questions in economics involve long-run or “trend” variation and covariation in time series. Yet, time series of typical lengths contain only limited information about this long-run variation. This paper suggests that long-run sample information can be isolated using a small number of low-frequency trigonometric weighted averages, which in turn can be used to conduct inference about long-r...

2011
Beth Andrews Richard A. Davis

We consider model identification for infinite variance autoregressive time series processes. It is shown that a consistent estimate of autoregressive model order can be obtained by minimizing Akaike’s information criterion, and we use all-pass models to identify noncausal autoregressive processes and estimate the order of noncausality (the number of roots of the autoregressive polynomial inside...

2010
Nikolaus Hautsch Peter Malec Melanie Schienle Uwe Walz

We propose a novel approach to model serially dependent positive-valued variables which realize a non-trivial proportion of zero outcomes. This is a typical phenomenon in financial time series observed at high frequencies, such as cumulated trading volumes. We introduce a flexible point-mass mixture distribution and develop a semiparametric specification test explicitly tailored for such distri...

2000
Luis E. Arango Andrés Gonzalez Timo Teräsvirta Marco Rodríguez

Evidence of smooth transition autoregressive (STAR) representations is found in two, out of three, time series of different measures of annual inflation in Colombia during this decade for monthly data. The STAR-type nonlinearities are asymmetric for inflation computed as the variation of CPI while for (a measure of ) core inflation are symmetric. Thus, LSTAR and ESTAR models were, respectively,...

Journal: :تحقیقات اقتصادی 0
سید محمدعلی کفایی استادیار دانشکده ی علوم اقتصادی و سیاسی دانشگاه شهید بهشتی جواد عرب یارمحمدی دانشجوی دکتری اقتصاد

in this paper, the effect of financial liberalization on household’s budget liquidity constraint is analyzed with the use of an error correction model. financial liberalization will decline liquidity constraint, with expanding means of making future incomes available for present consumption. here a financial liberalization index for iran is defined using principal component analysis technique, ...

Esmaiel Abounoori, Mohsen Ali Heydari

In this paper we intend to examine the application of Kullback-Leibler, Hellinger and LINEX loss function in Dynamic Linear Model using the real price of oil for 106 years of data from 1913 to 2018 concerning the asymmetric problem in filtering and forecasting. We use DLM form of the basic Hoteling Model under Quadratic loss function, Kullback-Leibler, Hellinger and LINEX trying to address the ...

2007
Dennis Gärtner

By means of a very simple example, this note illustrates the appeal of using Bayesian rather than classical methods to produce inference on hidden states in models of Markovian regime switching. JEL Classification: C11, C22.

2000
Luis A. Gil-Alana

We propose in this article a two-step testing procedure of fractional cointegration in macroeconomic time series. It is based on Robinson’s (1994) univariate tests and is similar in spirit to the one proposed by Engle and Granger (1987), testing initially the order of integration of the individual series and then, testing the degree of integration of the residuals from the cointegrating relatio...

2001
John C. Chao Valentina Corradi Norman R. Swanson

We perform a series of Monte Carlo experiments in order to evaluate the impact of data transformation on forecasting models, and ̄nd that vector error-corrections dominate di®erenced data vector autoregressions when the correct data transformation is used, but not when data are incorrectly tansformed, even if the true model contains cointegrating restrictions. We argue that one reason for this ...

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