Relevant bibliographies by topics / Vector autoregressivo

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Vector autoregressivo'

Author: Grafiati
Published: 10 September 2021
Last updated: 18 February 2022

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Journal articles on the topic "Vector autoregressivo"

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Shapor, Maria Alexandrovna, and Rafael Rubenovich Gevogyan. "Features of the vector autoregression models application in macroeconomic research." Mezhdunarodnaja jekonomika (The World Economics), no. 8 (August 10, 2021): 634–49. http://dx.doi.org/10.33920/vne-04-2108-05.

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In this paper, we analyzed articles by foreign authors that use various vector autoregression models to calculate the impact of qualitative indicators on the economic processes of countries or a group of countries. In particular, the article analyzed the classical model of vector autoregression (VAR), panel model of autoregressive (PVAR), Bayesian model of autoregressive (BVAR), structural model of autoregressive (SVAR), and the global model of autoregressive (GVAR). Among the works using vector autoregressive models, the main emphasis is on financial indicators. Moreover, articles with non-trivial variables are rare. This is because financial macroeconomic variables in most cases have a direct impact on economic processes in the country. The analysis of financial indicators and the results obtained can play a significant role in the development of economic strategies in different states, since the results obtained with the help of vector autoregression models are usually quite accurate. The studied articles analyze the data of both developed and developing states or groups of states in different periods. The studied articles were classified according to several criteria, which were selected by the author to structure the work. Note that among the works using vector autoregressive models, the main emphasis is on financial indicators. Moreover, articles with non-trivial variables are rare. This is since financial macroeconomic variables in most cases have a direct impact on economic processes in the country. The analysis of financial indicators and the results obtained can play a significant role in the development of economic strategies in different states, since the results obtained with the help of vector autoregression models are usually quite accurate. In the conclusion of this study, the author presented conclusions based on the analysis of autoregressive models.
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Gurrib, Muhammad I., and Syed Z. Ahmad. "Saudi Arabia’s Inflation Agenda: A Vector Autoregressive Framework." International Journal of Trade, Economics and Finance 1, no. 1 (2010): 63–67. http://dx.doi.org/10.7763/ijtef.2010.v1.12.

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Lee, Youngsoo. "Interest rate and housing market: MS-VAR approach." Journal of Housing and Urban Finance 6, no. 1 (June 2021): 5–22. http://dx.doi.org/10.38100/jhuf.2021.6.1.5.

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Dufour, Jean-Marie. "Unbiasedness of Predictions from Etimated Vector Autoregressions." Econometric Theory 1, no. 3 (December 1985): 387–402. http://dx.doi.org/10.1017/s0266466600011270.

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Forecasts from a univariate autoregressive model estimated by OLS are unbiased, irrespective of whether the model fitted has the correct order; this property only requires symmetry of the distribution of the innovations. In this paper, this result is generalized to vector autoregressions and a wide class of multivariate stochastic processes (which include Gaussian stationary multivariate stochastic processes) is described for which unbiasedness of predictions holds: specifically, if a vector autoregression of arbitrary finite order is fitted to a sample from any process in this class, the fitted model will produce unbiased forecasts, in the sense that the prediction errors have distributions symmetric about zero. Different numbers of lags may be used for each variable in each autoregression and variables may even be missing, without unbiasedness being affected. This property is exact in finite samples. Similarly, the residuals from the same autoregressions have distributions symmetric about zero.
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Wujung, Vukenkeng Andrew, and Mukete Emmanuel Mbella. "Entrepreneurship and poverty reduction in Cameroon: A Vector Autoregressive approach." Archives of Business Research 2, no. 5 (September 30, 2014): 1–11. http://dx.doi.org/10.14738/abr.25.345.

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Liao, Zhipeng, and Peter C. B. Phillips. "AUTOMATED ESTIMATION OF VECTOR ERROR CORRECTION MODELS." Econometric Theory 31, no. 3 (March 13, 2015): 581–646. http://dx.doi.org/10.1017/s026646661500002x.

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Model selection and associated issues of post-model selection inference present well known challenges in empirical econometric research. These modeling issues are manifest in all applied work but they are particularly acute in multivariate time series settings such as cointegrated systems where multiple interconnected decisions can materially affect the form of the model and its interpretation. In cointegrated system modeling, empirical estimation typically proceeds in a stepwise manner that involves the determination of cointegrating rank and autoregressive lag order in a reduced rank vector autoregression followed by estimation and inference. This paper proposes an automated approach to cointegrated system modeling that uses adaptive shrinkage techniques to estimate vector error correction models with unknown cointegrating rank structure and unknown transient lag dynamic order. These methods enable simultaneous order estimation of the cointegrating rank and autoregressive order in conjunction with oracle-like efficient estimation of the cointegrating matrix and transient dynamics. As such they offer considerable advantages to the practitioner as an automated approach to the estimation of cointegrated systems. The paper develops the new methods, derives their limit theory, discusses implementation, reports simulations, and presents an empirical illustration with macroeconomic aggregates.
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Saikkonen, Pentti. "Testing normalization and overidentification of cointegrating vectors in vector autoregressive processes." Econometric Reviews 18, no. 3 (January 1999): 235–57. http://dx.doi.org/10.1080/07474939908800444.

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Härdle, W., A. Tsybakov, and L. Yang. "Nonparametric vector autoregression." Journal of Statistical Planning and Inference 68, no. 2 (May 1998): 221–45. http://dx.doi.org/10.1016/s0378-3758(97)00143-2.

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Lanne, Markku, and Pentti Saikkonen. "NONCAUSAL VECTOR AUTOREGRESSION." Econometric Theory 29, no. 3 (November 12, 2012): 447–81. http://dx.doi.org/10.1017/s0266466612000448.

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In this paper, we propose a new noncausal vector autoregressive (VAR) model for non-Gaussian time series. The assumption of non-Gaussianity is needed for reasons of identifiability. Assuming that the error distribution belongs to a fairly general class of elliptical distributions, we develop an asymptotic theory of maximum likelihood estimation and statistical inference. We argue that allowing for noncausality is of particular importance in economic applications that currently use only conventional causal VAR models. Indeed, if noncausality is incorrectly ignored, the use of a causal VAR model may yield suboptimal forecasts and misleading economic interpretations. Therefore, we propose a procedure for discriminating between causality and noncausality. The methods are illustrated with an application to interest rate data.
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Zhu, Xuening, Rui Pan, Guodong Li, Yuewen Liu, and Hansheng Wang. "Network vector autoregression." Annals of Statistics 45, no. 3 (June 2017): 1096–123. http://dx.doi.org/10.1214/16-aos1476.

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Dissertations / Theses on the topic "Vector autoregressivo"

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Sato, João Ricardo. "Modelo autoregressivo vetorial com coeficientes variantes no tempo e aplicações em RMf." Universidade de São Paulo, 2007. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-22042013-151911/.

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Os avanços nas técnicas de neuroimagem, principalmente com o de- senvolvimento da ressonância magnética funcional (RMf), vem possibilitando um melhor compreendimento dos processos e mecanismos cerebrais. Este trabalho tem como objetivo o desenvolvimento de um modelo de conectividade dinâmico entre diversas áreas cerebrais útilzando dados de RMf. A modelagem dinâmica do fluxo de informação é realizada com a estimação dos parâmetros de um modelo autoregressivo multivariado com coeficientes variandos no tempo, baseado na projeçã o de funções em bases de ondaletas. Dessa forma, um método para estimação e a derivação de suas propriedades assintóticas são apresentados. Diversos conjuntos de simulações computacionais são realizados visando a avaliação do desempenho do método proposto. Por fim, são apresentadas aplicações do modelo de conectividade variante no tempo em dados de ressonância magnética funcional.
Advances in neuroimage technologies, mainly with the development of functional magnetic resonance imaging (fMRI), improve the comprehension of brain processes and mechanisms. The main goal of this work is the development of a time-varying connectivity model between many brain areas using fMRI datasets. The dynamic modelling of the information flow is related to the parameters estimation of a time-varying multivariate autoregressive process, based on functions projection in wavelet basis. We propose an estimation procedure and present its asymptotic properties. Computational simulations were performed focusing the evaluation of the proposed approach. Further, applications of these methodologies to real functional magnetic resonance datasets are presented.
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Fernandes, Pedro Manuel Ribeiro. "The role of banks in economic growth : an empirical application to Portugal." Master's thesis, Instituto Superior de Economia e Gestão, 2019. http://hdl.handle.net/10400.5/19408.

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Mestrado em Economia Monetária e Financeira
Esta dissertação avalia o contributo dos bancos para o crescimento económico em Portugal desde a adopção do Euro, usando testes de cointegração e causalidade, bem como funções de resposta a impulsos. Usando rácios de passivos líquidos (depósitos) dos bancos e empréstimos em percentagem do PIB nominal como medidas do desenvolvimento financeiro, encontramos forte evidência de que o crescimento económico exerce um impacto positivo no desenvolvimento financeiro, de acordo com Demetriades e Hussein (1996). Concluiu-se também que os empréstimos bancários não aumentam o produto real no longo e no curto prazo, também de acordo com Demetriades e Hussein (1996). Ao invés disso, estes têm um efeito negativo no PIB real per capita. Esses resultados corroboram a visão defendida por Robinson (1952), como citado em King e Levine (1993a) e Lucas (1988), de que o financiamento apenas evolui em resposta aos desenvolvimentos da economia.
This dissertation evaluates the role of banks in economic growth in Portugal since the adoption of the Euro, using cointegration and causality tests, as well as impulse response functions. Using ratios of banks? liquid liabilities (deposits) and loans to nominal GDP as a measure of financial development, we find strong evidence of economic growth exerting a positive impact on financial development, in line with Demetriades and Hussein (1996). It was also concluded that bank lending does not boost real output both in the long-run and in the short-run, also in line with Demetriades and Hussein (1996). Instead, it has a negative effect on real per capita GDP. These results support the view championed by Robinson (1952), as cited in King and Levine (1993a), and Lucas (1988), that finance only evolves in response to developments in the economy.
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Gudmundsson, Gudmundur Stefan. "Essays in network modelling." Doctoral thesis, Universitat Pompeu Fabra, 2018. http://hdl.handle.net/10803/663096.

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This thesis consists of two chapters on time series modelling. The first chapter introduces a class of vector autoregressive (VAR) models with a community structure for large panels of time series. In the model, the series are parti-tioned into latent groups such that spillovers are stronger within groups than between them. We then propose an algorithm that uses the eigenvectors of a function of the estimated autoregressive matrices to recover the communities. We study the properties of the procedure and establish its consistency. The algorithm motivates us to suggest a regularised VAR estimator, which per-forms favourably relative to a number of alternatives in a forecasting exercise. The methodology is applied to study clustering in industrial production for a set of major economies. The second chapter introduces a class of partial correlation network models with a community structure. The series form unknown groups, where correlation is higher within groups than otherwise. We propose an algorithm that consistently detects the communities using the eigenvectors of the sample covariance matrix. The procedure is used to analyse real activity clustering in the U.S. and Europe.
Aquesta tesi consisteix en dos capítols sobre models de dades de sèries temporals. El primer capítol introdueix una classe de models de vector autoregressius (VAR) amb una estructura de comunitat per panels de dades de sèries temporals. En el model, les sèries es parteixen en grups latents de tal manera que els spillover són ées forts dins de grups que entre ells. Llavors proposem un algoritme que utilitza el vector d’eigen d’una funció de les matrius autoregressives estimades per recuperar les comunitats. Estudiem les propietats del procediment i establim la seva consistència. L’algoritme ens motiva a suggerir un estimador regulat del VAR, el qual actua favorablement en relació a un nombre d’alternatives en una exercici d’ estimació. La metodologia s’aplica per estudiar el clustering en la producció industrial per un conjunt d’economies importants. El segon capítol introdueix una classe de models de xarxa de correlació parcials amb una estructura de comunitat. La èerie forma grups desconeguts, on la correlació és més alta dins de grups que altrament. Proposem un algoritme que detecta consistentment les comunitats que utilitzen els vectors d’eigen de la matriu de mostra de covariáncia. El procediment s’utilitza per analitzar el clustering en l’activitat real en els EUA i Europa.
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Oliveira, Jorge Manuel Caetano de. "Significado do 1º pilar da política monetária do Eurosistema." Master's thesis, Instituto Superior de Economia e Gestão, 2002. http://hdl.handle.net/10400.5/3582.

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Mestrado em Economia Monetária e Financeira
O presente estudo tem como objectivo fundamental investigar qual o significado do papel atribuído pelo Banco Central Europeu (BCE) ao agregado monetário largo M3 na condução da política monetária na zona euro. Partindo de um breve enquadramento teórico quanto ao papel atribuído pelo BCE à moeda, procede-se a uma análise empírica, baseada em vectores autoregressivos (usando essencialmente as variáveis macroeconómicas: taxa de crescimento do M3, hiato do M3 em termos reais, taxa de inflação e hiato do produto), no sentido de detectar evidência empírica de suporte ao papel proeminente que foi atribuído à moeda pelo BCE. As principais conclusões deste estudo apontam para a existência de uma enorme sensibilidade em torno da definição da taxa de inflação. No entanto, partindo-se da taxa de inflação medida pelo deflator do Produto Interno Bruto (PIB), a evidência empírica parece sugerir uma certa primazia como indicador de evolução futura dos preços o hiato do M3 em termos reais quando comparado quer com a taxa de crescimento do agregado monetário largo M3 quer com o hiato do produto.
The main target of this study is to investigate the meaning of the role assigned by the European Central Bank (ECB) to the broad monetary aggregate M3 in its conduction of the monetary policy for the euro area. The work begins with a brief theoretic framing of the role assigned to the money by ECB, which is followed by an empirical analysis, based on autoregressive vectors (employing essentially the following macroeconomic variables: growth rate of M3, real gap of M3, inflation rate and output gap), with the objective of detecting empirical evidence that support the prominent role of money assigned by the ECB. The main conclusions of this study support the existence of a high sensibility to the definition of the inflation rate. However, starting with the best measure of inflation rate based on Gross Domestic Product (GDP) deflator, the empirical evidence supports a certain primacy, as future inflation indicator, to the real gap of M3 rather than to the growth rate of M3 or output gap.
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Barão, Ricardo. "The relationships of alternative energies with the technology sector and non-renewable energies." reponame:Repositório Institucional do FGV, 2015. http://hdl.handle.net/10438/14152.

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Este trabalho tem como objectivo compreender de que forma os investidores veem as energias renováveis: se as veem como parte do sector tecnológico, à espera de novos desenvolvimentos, ou como uma alternativa aos métodos existentes de produção de energia. Para responder a esta questão, foi desenvolvido um modelo de vectores autoregressivos com quatro variáveis de forma a se poder aplicar um Granger causality test e Impulse Response function. Os resultados sugerem que para o período de 2002-2007 à escala global ambas as hipóteses se confirmam, porém de 2009-2014 os resultados sugerem que os investidores não reconhecem as energias renováveis como um ramo do sector tecnológico, neste período. Para além disso, durante o período de 2009-2014, e quando comparados investidores Americanos com Europeus, os resultados sugerem que apenas o último identifica as energias renováveis como uma fonte viável para a produção energética.
This work aimed to understand the investor perception on clean energy: if it is seen as part of the technology sector, awaiting new developments, or as an alternative to the existing energy production methods. To answer this question, a four variable vector autoregression model was developed so that a Granger causality test and Impulse response function could be applied. The results suggest that while both hypotheses were confirmed worldwide for the period 2002-2007, from 2009 to 2014 results suggest that investors do not recognize the field of clean energy as part of the technology sector. Moreover, during the period that ranges from 2009 to 2014, and when comparing the American investor with the European investor, only the latter identifies renewable energy as a viable source of energy production.
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Mendes, Giovanna Miranda. "Efeitos dos ganhos de produtividade total dos fatores da agropecuária sobre os preços agrícolas no Brasil: 1970-2006." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/11/11132/tde-17112015-084759/.

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A agropecuária brasileira tem crescido nas últimas décadas e os ganhos de produtividade tem sido importante neste bom desempenho do setor. O presente trabalho tem dois objetivos principais. O primeiro deles foi mensurar o crescimento desta produtividade total dos fatores na agropecuária brasileira estadual, decompondo o crescimento da PTF em progresso tecnológico e eficiência técnica. O segundo objetivo foi analisar o efeito do crescimento da PTF da agropecuária brasileira sobre os preços agrícolas, no Brasil, de 1970 a 2006. O crescimento desta produtividade foi mensurado a partir dos insumos terra, trabalho e capital na função de produção translog sob orientação do produto, a partir do método de Fronteira Estocástica de Produção e do índice de produtividade de Malmquist. Para avaliar o efeito do crescimento da PTF sobre os preços agrícolas foi construído o índice de preços agrícolas utilizando-se o Índice de preços de Laspeyres para estimar o vetor autoregressivo em painel (panel- VAR), acrescentando as variáveis produtividade total dos fatores (PTF), salário rural, financiamento agrícola e renda per capita domiciliar. Além disso, foi aplicado o teste de causalidade, no sentido de Granger, e estimada a função impulso resposta. A base de dados utilizada foi, obtida do Censo Agropecuário, a nível estadual, para os anos de 1970, 1975, 1980, 1985, 1995 e 2006. Os resultados indicaram que a taxa de crescimento da PTF foi crescente no Brasil e nos estados, sendo que, na maior parte das vezes, é explicada pelo progresso tecnológico, positivo e crescente para todos os estados. A eficiência técnica variou ao longo dos anos, apresentado taxas de crescimento médias positivas para a maioria dos estados. Em média, os estados estiveram situados abaixo da fronteira de produção da agropecuária brasileira. São Paulo foi o estado com maior nível de eficiência técnica. Embora a taxa de crescimento médio anual tenha sido positiva ao longo do período analisado, a eficiência reduziu para todos os estados analisados em 2006. Da análise dos efeitos do crescimento da PTF sobre os preços agrícolas, a PTF tem causalidade, no sentido de Granger, sobre os preços agrícolas. Na função impulso resposta, o choque inicial na variável PTF reduziu os preços nos primeiros anos. Assim, o crescimento da PTF do setor agropecuário contribuiu para o aumento da oferta de produtos, reduzindo os preços agrícolas. A maior disponibilidade de alimentos e, com a redução dos preços dos alimentos, os consumidores, principalmente os de renda mais baixa puderam ter maior acesso aos alimentos.
The Brazilian agriculture has grown in recent decades and productivity gains have been important in this good performance of the sector. This work had two main objectives. The first one was measure the growth of this total factor productivity in agriculture by the Brazilian\'s states, decomposing TFP growth by technological progress, technical efficiency and economies of scale. The second objective was to analyze the effect of TFP growth of Brazilian agriculture on agricultural prices. The growth in productivity was measured from the inputs like labor, gross and capital in the translog production function, from the Stochastic Frontier Analysis and of the outputoriented Malmquist productivity index. To analyze the effect of TFP growth on agricultural prices was constructed an index of agricultural prices through the Laspeyres price index to estimate the vector autoregressive panel (panel-VAR) and establish the relationships between TFP, rural wages, agricultural finance and income per capita household. The Granger causality test and the impulse response function were used to the data panel. The database used obtained from the Agricultural Census, at the state level for the years 1970, 1975, 1980, 1985, 1995 and 2006. The results showed that the growth rate of TFP has been growing in Brazil and in the states, and technological progress explained most of the growth being positive and growing for all states. Technical efficiency varied over the years, presented positive average growth rates for most states. The states were located below the production frontier of Brazilian agriculture and São Paulo was the state with the highest level of technical efficiency. Although the average annual growth rate has been increasing over the period analyzed, the efficiency decreased to all state analyzed in 2006. The results also showed that TFP growth has causality in the sense of Granger, on agricultural prices. In the impulse response function, the initial shock in TFP decreased prices in the early years. Thus, TFP growth of the agricultural sector contributed to the increased supply of agricultural products, reducing agricultural prices. The greater availability of food and with reducing food prices, consumers, especially those from lower income might had greater access to food.
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Ooms, M. "Empirical vector autoregressive modeling." [S.l. : Rotterdam : s.n.] ; Erasmus University [Host], 1993. http://hdl.handle.net/1765/14163.

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Fidalgo, Cristina Patrícia Gouveia Dias. "Teoria generalizada da paridade do poder de compra : uma aplicação às economias da Europa Central." Master's thesis, Instituto Superior de Economia e Gestão, 2020. http://hdl.handle.net/10400.5/21111.

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Mestrado em Econometria Aplicada e Previsão
No presente estudo pretende-se analisar se os três países da Europa Central em vias de aderir à União Económica Monetária - Hungria, Polónia e República Checa - constituem, de facto, uma Zona Monetária Ótima no espírito de Mundell (1961) com os países da Zona Euro vis-à-vis a economia da Alemanha, colocando, assim, um fim à fase de transição dos últimos 16 anos. Para tal, recorre-se à teoria Generalizada da Paridade do Poder de Compra, inicialmente proposta por Enders e Hurn (1994), empiricamente testável com recurso ao modelo vetorial de correção de erros. Os resultados empíricos indicam que, para o período entre 1993 e 2019, apesar da não estacionaridade das séries (do logaritmo) da taxa de câmbio real bilateral de cada economia, existe, efetivamente, um co-movimento entre as diferentes taxas em trajetória de equilíbrio, refletindo o processo de convergência real consistente com o critério de Zona Monetária Ótima.
The present study aims to analyze whether the three Central European countries that are about to join the Economic Monetary Union - Hungary, Poland and the Czech Republic - constitute, indeed, an Optimum Currency Area in the spirit of Mundell (1961) with the countries of the Eurozone vis-à-vis the German economy, thus putting an end to the transition phase of the past 16 years. The theoretical framework is based on Generalized Theory of Purchasing Power Parity, an hypothesis initially proposed by Enders and Hurn (1994), empirically testable using the vector error correction model. The empirical results indicate that, for the period between 1993 and 2019, despite the non-stationarity of the series (of the logarithm) of the bilateral real exchange rate of each economy, there is, effectively, a co-movement between the different rates on an equilibrium path, reflecting the process of real convergence consistent with the Optimum Currency Area criterion.
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Polito, Vito. "Vector autoregressive analysis of macroeconomic policy." Thesis, University of York, 2007. http://etheses.whiterose.ac.uk/11068/.

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Brüggemann, Ralf. "Model reduction methods for vector autoregressive processes /." Berlin [u.a.] : Springer, 2004. http://www.loc.gov/catdir/enhancements/fy0818/2003067373-d.html.

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Books on the topic "Vector autoregressivo"

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Empirical vector autoregressive modeling. Berlin: Springer-Verlag, 1994.

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Ooms, Marius. Empirical Vector Autoregressive Modeling. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-48792-7.

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Holden, K. Vector autoregression modelling and forecasting. [Liverpool]: Liverpool Business School, 1994.

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Brüggemann, Ralf. Model Reduction Methods for Vector Autoregressive Processes. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-17029-4.

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Ramaswamy, Ramana. Japan's stagnant nineties: A vector autoregression retrospective. [Washington, D.C.]: International Monetary Fund, Asia and Pacific Department, 1999.

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Likelihood-based inference in cointegrated vector autoregressive models. Oxford: Oxford University Press, 1995.

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Johansen, Søren. Likelihood-based inference in cointegrated vector autoregressive models. Oxford: Oxford University Press, 1995.

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Brännström, Tomas. Bias approximation and reduction in vector autoregressive models. [s.l.]: typescript, 1995.

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Kadiyala, K. R. Forecasting with Bayesian vector autoregressions. West Lafayette, Ind: Institute for Research in the Behavioral, Economic, and Management Sciences, Krannert Graduate School of Management, Purdue University, 1989.

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Ghatak, Anita. Vector autoregression modelling and forecasting growth of South Korea. Milton Keynes: De Montfort University, School of Social Sciences, 1997.

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Book chapters on the topic "Vector autoregressivo"

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Lütkepohl, Helmut. "Vector Autoregressive Models." In International Encyclopedia of Statistical Science, 1645–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-04898-2_609.

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Kirchgässner, Gebhard, Jürgen Wolters, and Uwe Hassler. "Vector Autoregressive Processes." In Introduction to Modern Time Series Analysis, 127–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33436-8_4.

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Kirchgässner, Gebhard, and Jürgen Wolters. "Vector Autoregressive Processes." In Introduction to Modern Time Series Analysis, 125–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73291-4_4.

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Lütkepohl, Helmut. "Stable Vector Autoregressive Processes." In Introduction to Multiple Time Series Analysis, 9–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-61695-2_2.

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Lütkepohl, Helmut. "Stable Vector Autoregressive Processes." In New Introduction to Multiple Time Series Analysis, 13–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-27752-1_2.

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Min, Chung-ki. "Vector autoregressive (VAR) models." In Applied Econometrics, 173–202. Abingdon, Oxon ; New York, NY : Routledge, 2019. | Series: Routledge advanced texts in economics and finance ; 31: Routledge, 2019. http://dx.doi.org/10.4324/9780429024429-9.

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Lütkepohl, Helmut. "Stable Vector Autoregressive Processes." In Introduction to Multiple Time Series Analysis, 9–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-662-02691-5_2.

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Aljandali, Abdulkader, and Motasam Tatahi. "Vector Autoregression (VAR) Model." In Economic and Financial Modelling with EViews, 211–35. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92985-9_10.

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Lütkepohl, Helmut. "Estimation of Vector Autoregressive Processes." In Introduction to Multiple Time Series Analysis, 62–117. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-61695-2_3.

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Lütkepohl, Helmut. "Vector Autoregressive Moving Average Processes." In Introduction to Multiple Time Series Analysis, 217–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-61695-2_6.

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Conference papers on the topic "Vector autoregressivo"

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Iseki, Toshio. "Instantaneous Spectral Analysis of Non-Stationary Ship Motion Data." In 25th International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2006. http://dx.doi.org/10.1115/omae2006-92197.

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The time varying coefficient vector autoregressive (TVVAR) modeling is applied to the cross-spectral analysis of non-stationary ship motion data. Introducing the instantaneous response, a vector autoregressive model can be reduced to simple time varying coefficient autoregressive (TVAR) models for each ship motion and the required CPU time is effectively reduced. The TVVAR model and stochastic perturbed difference equations are transformed into a state space model. The vector-valued unknown coefficients can be evaluated and the instantaneous cross spectra of ship motions can be calculated at every moment. The results showed good agreements with one of the TVAR modeling and also with the stationary autoregressive (SAR) modeling analysis under stationary conditions. Furthermore, the instantaneous relative noise contribution was also estimated using the TVVAR coefficients and illustrated how the structure of a spectrum changed according to the ship manoeuvres for the first time. Optimum order of the model and Akaike’s information criterion were also examined for several changes of parameters. Moreover, it is confirmed that the TVVAR modeling can estimate the instantaneous cross spectra and relative noise contribution of ship motions even under non-stationary conditions.
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Tören, Evrim. "The Impact of Stock Prices on Consumption and Interest Rate in Turkey: Evidence from a Time Varying Vector Autoregressive Model." In International Conference on Eurasian Economies. Eurasian Economists Association, 2014. http://dx.doi.org/10.36880/c05.01142.

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This paper aims to examine the spillovers from stock prices onto consumption and interest rate for Turkey by using a time-varying vector autoregressive model with stochastic volatility. A three-variable time-varying vector autoregressive model is estimated to capture the time-varying nature of the macroeconomic dynamics in the Turkish economy between real consumption, nominal interest rate and real stock prices. In order to obtain the macroeconomic dynamics in a small open economy, the data covers the period 1987:Q1 until 2013:Q3 in Turkey. The sample data is gathered from the official website of Central Bank of the Republic of Turkey. Overall, this study provides the evidence of significant time-varying spillovers on consumption and interest rate coming from the stock market during financial crises and implications of monetary policy in Turkey. In addition, a time-varying vector autoregressive model with stochastic volatility offers remarkable results about the impact of price shock on consumption levels in Turkey.
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Chung, Yu-An, Hao Tang, and James Glass. "Vector-Quantized Autoregressive Predictive Coding." In Interspeech 2020. ISCA: ISCA, 2020. http://dx.doi.org/10.21437/interspeech.2020-1228.

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Fujiki, Jun, and Masaru Tanaka. "Three-dimensional vector autoregressive coefficients." In International Symposium on Optical Science and Technology, edited by Longin J. Latecki, David M. Mount, and Angela Y. Wu. SPIE, 2000. http://dx.doi.org/10.1117/12.404817.

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Goyal, Vipul, Mengyu Xu, and Jayanta Kapat. "Use of Vector Autoregressive Model for Anomaly Detection in Utility Gas Turbines." In ASME Turbo Expo 2019: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/gt2019-90995.

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Abstract This study is based on time-series data from the combined cycle utility gas turbines consisting of three-gas turbine units and one steam turbine unit. We construct a multi-stage vector autoregressive model for the nominal operation of powerplant assuming sparsity in the association among variables and use this as a basis for anomaly detection and prediction. This prediction is compared with the time-series data of the plant-operation containing anomalies. Granger causality networks, which are based on the associations between the time series streams, are learned as an important implication from the vector autoregressive modelling. Anomaly is detected by comparing the observed measurements against their predicted value.
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Li, Tao, Xueyu Li, and Xu Zhang. "The Design and Implementation of Vector Autoregressive Model and Structural Vector Autoregressive Model Based on Spark." In 2017 3rd International Conference on Big Data Computing and Communications (BIGCOM). IEEE, 2017. http://dx.doi.org/10.1109/bigcom.2017.46.

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Cai, Xia. "Vector Autoregressive Weighting Reversion Strategy for Online Portfolio Selection." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/616.

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Aiming to improve the performance of existing reversion based online portfolio selection strategies, we propose a novel multi-period strategy named “Vector Autoregressive Weighting Reversion” (VAWR). Firstly, vector autoregressive moving-average algorithm used in time series prediction is transformed into exploring the dynamic relationships between different assets for more accurate price prediction. Secondly, we design the modified online passive aggressive technique and advance a scheme to weigh investment risk and cumulative experience to update the closed-form of portfolio. Theoretical analysis and experimental results confirm the effectiveness and robustness of our strategy. Compared with the state-of-the-art strategies, VAWR greatly increases cumulative wealth, and it obtains the highest annualized percentage yield and sharp ratio on various public datasets. These improvements and easy implementation support the practical applications of VAWR.
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"Constrained Estimation of Mixture Vector Autoregressive Model." In 19th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2011. http://dx.doi.org/10.36334/modsim.2011.d2.wong.

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Coluccia, Angelo, Fabrizio Dabbene, and Chiara Ravazzi. "Bayesian Identification of Distributed Vector AutoRegressive Processes." In 2019 18th European Control Conference (ECC). IEEE, 2019. http://dx.doi.org/10.23919/ecc.2019.8796302.

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Andriamanalimanana, Bruno R., and Saumen S. Sengupta. "Problem signatures from enhanced vector autoregressive modeling." In Aerospace/Defense Sensing, Simulation, and Controls, edited by Alex F. Sisti and Dawn A. Trevisani. SPIE, 2001. http://dx.doi.org/10.1117/12.440026.

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Reports on the topic "Vector autoregressivo"

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Rosser, J. Barkley, and Richard G. Sheehan. A Vector Autoregressive Model of Saudi Arabian Inflation. Federal Reserve Bank of St. Louis, 1985. http://dx.doi.org/10.20955/wp.1985.011.

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Ahmed, Ehsan, J. Barkley Rosser, and Richard G. Sheehan. A Model of Global Aggregate Supply and Demand Using Vector Autoregressive Techniques. Federal Reserve Bank of St. Louis, 1986. http://dx.doi.org/10.20955/wp.1986.004.

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Mocan, Naci. Business Cycles and Fertility Dynamics in the U.S.: A Vector-Autoregressive Model. Cambridge, MA: National Bureau of Economic Research, November 1989. http://dx.doi.org/10.3386/w3177.

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Xu, J., S. Yoo, J. Heiser, and P. Kalb. Sensor network based solar forecasting using a local vector autoregressive ridge framework. Office of Scientific and Technical Information (OSTI), April 2016. http://dx.doi.org/10.2172/1336118.

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Bernanke, Ben, Jean Boivin, and Piotr Eliasz. Measuring the Effects of Monetary Policy: A Factor-Augmented Vector Autoregressive (FAVAR) Approach. Cambridge, MA: National Bureau of Economic Research, January 2004. http://dx.doi.org/10.3386/w10220.

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Yamada, Tadashi. The Crime Rate and the Condition of the Labor Market: A Vector Autoregressive Model. Cambridge, MA: National Bureau of Economic Research, December 1985. http://dx.doi.org/10.3386/w1782.

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Baluga, Anthony, and Masato Nakane. Maldives Macroeconomic Forecasting:. Asian Development Bank, December 2020. http://dx.doi.org/10.22617/wps200431-2.

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This study aims to build an efficient small-scale macroeconomic forecasting tool for Maldives. Due to significant limitations in data availability, empirical economic modeling for the country can be problematic. To address data constraints and circumvent the “curse of dimensionality,” Bayesian vector autoregression estimations are utilized comprising of component-disaggregated domestic sectoral production, price, and tourism variables. Results demonstrate how this methodology is appropriate for economic modeling in Maldives. With the appropriate level of shrinkage, Bayesian vector autoregressions can exploit the information content of the macroeconomic and tourism variables. Augmenting for qualitative assessments, the directional inclination of the forecasts is improved.
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Ang, Andrew, and Monika Piazzesi. A No-Arbitrage Vector Autoregression of Term Structure Dynamics with Macroeconomic and Latent Variables. Cambridge, MA: National Bureau of Economic Research, July 2001. http://dx.doi.org/10.3386/w8363.

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Dime, Roselle, Juzhong Zhuang, and Edimon Ginting. Estimating Fiscal Multipliers in Selected Asian Economies. Asian Development Bank, August 2021. http://dx.doi.org/10.22617/wps210309-2.

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The surge of the coronavirus disease (COVID-19) pandemic has driven countries worldwide to launch substantial stimulus packages to support economic recovery. This paper estimates effects of fiscal measures on output using data from 2000 to 2019 for a panel of nine developing Asian economies and a vector autoregression model. Results show that (i) the 4-quarter and 8-quarter cumulative fiscal multipliers for general government spending range between 0.73 and 0.88 in baselines, in line with recent estimates for developed countries but larger than those for developing countries; (ii) government spending is more effective than tax cuts in boosting the economy; and (iii) an accommodative monetary policy regime can make fiscal measures more effective.
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Ahumada, Hildegart, Eduardo A. Cavallo, Santos Espina-Mairal, and Fernando Navajas. Sectoral Productivity Growth, COVID-19 Shocks, and Infrastructure. Inter-American Development Bank, July 2021. http://dx.doi.org/10.18235/0003411.

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This paper examines sectoral productivity shocks of the COVID-19 pandemic, their aggregate impact, and the possible compensatory effects of improving productivity in infrastructure-related sectors. We employ the KLEMS annual dataset for a group of OECD and Latin America and the Caribbean countries, complemented with high-frequency data for 2020. First, we estimate a panel vector autoregression of growth rates in sector level labor productivity to specify the nature and size of sectoral shocks using the historical data. We then run impulse-response simulations of one standard deviation shocks in the sectors that were most affected by COVID 19. We estimate that the pandemic cut economy-wide labor productivity by 4.9 percent in Latin America, and by 3.5 percent for the entire sample. Finally, by modeling the long-run relationship between productivity shocks in the sectors most affected by COVID 19, we find that large productivity improvements in infrastructure--equivalent to at least three times the historical rates of productivity gains--may be needed to fully compensate for the negative productivity losses traceable to COVID 19.
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