Search results for "Vector autoregression"

showing 10 items of 15 documents

Real wages-employment relationship in Finnish manufacturing: a VAR approach

1991

Granger's concept of causality and the vector autoregressive(VAR) technique is used to investigate the real wages-employment relationship in Finnish manufacturing. The stationarity of the time series is examined and a number of co-integration tests for the adequacy of a pure VAR specification performed. The results using a bivariate VAR model based on a lag structure determined by Akaike's information criterion suggests that real wages Granger-cause employment. The slight non-constancy of the model suggests, however, that the conclusion concerning the nature of the real wages-emploment relationship should be treated with causion.

Economics and EconometricsSeries (mathematics)Autoregressive modelLagEconometricsEconomicsBivariate analysisAkaike information criterionReal wagesCausalityVector autoregressionApplied Economics
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Estimation of Granger causality through Artificial Neural Networks: applications to physiological systems and chaotic electronic oscillators

2021

One of the most challenging problems in the study of complex dynamical systems is to find the statistical interdependencies among the system components. Granger causality (GC) represents one of the most employed approaches, based on modeling the system dynamics with a linear vector autoregressive (VAR) model and on evaluating the information flow between two processes in terms of prediction error variances. In its most advanced setting, GC analysis is performed through a state-space (SS) representation of the VAR model that allows to compute both conditional and unconditional forms of GC by solving only one regression problem. While this problem is typically solved through Ordinary Least Sq…

Artificial neural networks; Chaotic oscillators; Granger causality; Multivariate time series analysis; Network physiology; Penalized regression techniques; Remote synchronization; State-space models; Stochastic gradient descent L1; Vector autoregressive modelGeneral Computer ScienceDynamical systems theoryComputer science02 engineering and technologyChaotic oscillatorsPenalized regression techniquesNetwork topologySettore ING-INF/01 - ElettronicaMultivariate time series analysisVector autoregression03 medical and health sciences0302 clinical medicineScientific Computing and Simulation0202 electrical engineering electronic engineering information engineeringRepresentation (mathematics)Optimization Theory and ComputationNetwork physiologyState-space modelsArtificial neural networkArtificial neural networksData ScienceTheory and Formal MethodsQA75.5-76.95Stochastic gradient descent L1Granger causality State-space models Vector autoregressive model Artificial neural networks Stochastic gradient descent L1 Multivariate time series analysis Network physiology Remote synchronization Chaotic oscillators Penalized regression techniquesRemote synchronizationStochastic gradient descentAutoregressive modelAlgorithms and Analysis of AlgorithmsVector autoregressive modelElectronic computers. Computer scienceSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaGranger causality020201 artificial intelligence & image processingGradient descentAlgorithm030217 neurology & neurosurgeryPeerJ Computer Science
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Local Granger causality

2021

Granger causality is a statistical notion of causal influence based on prediction via vector autoregression. For Gaussian variables it is equivalent to transfer entropy, an information-theoretic measure of time-directed information transfer between jointly dependent processes. We exploit such equivalence and calculate exactly the 'local Granger causality', i.e. the profile of the information transfer at each discrete time point in Gaussian processes; in this frame Granger causality is the average of its local version. Our approach offers a robust and computationally fast method to follow the information transfer along the time history of linear stochastic processes, as well as of nonlinear …

FOS: Computer and information sciencesInformation transferGaussianFOS: Physical sciencestechniques; information theory; granger causalityMachine Learning (stat.ML)Quantitative Biology - Quantitative Methods01 natural sciences010305 fluids & plasmasVector autoregressionsymbols.namesakegranger causalityGranger causalityStatistics - Machine Learning0103 physical sciencesApplied mathematicstime serie010306 general physicsQuantitative Methods (q-bio.QM)Mathematicsinformation theoryStochastic processDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksComputational Physics (physics.comp-ph)Discrete time and continuous timeAutoregressive modelFOS: Biological sciencesSettore ING-INF/06 - Bioingegneria Elettronica E InformaticasymbolsTransfer entropytechniquesPhysics - Computational Physics
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The impact of economic and policy uncertainty shocks in Spain

2020

The purpose of this research is to quantify the impact of economic uncertainty shocks in Spain by using a structural vector autoregression (SVAR) approach with data from the first quarter of 2001 u...

Structural vector autoregressionEconomic uncertainty0502 economics and business05 social sciences050602 political science & public administrationEconometricsEconomics050207 economicsBusiness and International ManagementQuarter (United States coin)General Economics Econometrics and Finance0506 political scienceJournal of Economic Policy Reform
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The beer market and advertising expenditure

2009

PurposeThe purpose of this paper is to examine the impacts of advertising expenditure on brands' market shares, utilizing a novel four‐week advertising‐sales data from the highly competitive oligopolistic Finnish beer market in which price competition among the homogeneous larger‐type beer brands is not allowed during the period of the study.Design/methodology/approachCompetition is modelled using the Lanchester model. The impacts of advertising on market shares are estimated using the impulse‐response functions from vector autoregression, and the full information maximum likelihood and advertising elasticities.FindingsSome new insights into beer market dynamics are obtained. First, the imp…

MarketingCompetition (economics)OligopolyHomogeneousValue (economics)EconomicsAdvertisingCompetitor analysisMarket dynamicsMarket shareVector autoregressionMarketing Intelligence & Planning
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Assessing the Commodity Market Price and Terms of Trade Exposures of Macroeconomy in Emerging and Developing Countries

2021

This paper provides novel evidence on commodity market exposure, i.e., the impacts of commodity price and terms of trade fluctuations on macro performance amongst 46 emerging and developing countries (EMDCs) in Africa, Asia and the Latin American and Caribbean (LAC) region. We estimate the exposure of six macroeconomic variables to the commodity prices and terms of trade. Our results indicate that in overall terms, there is a strong and statistically significant long-run relationship between the vector of analyzed world trade prices and macro variables in all EMDCs. However, based on the short-term reactions, only about 10% of the macroeconomic variation amongst the EMDCs is due to commodit…

makrotalousterms of tradeemerging and developing countrieskansainväliset markkinatDeveloping countrystructural vector autoregressionhyödykkeetMonetary economicsTerms of tradeCommodity marketCommodity priceshintakehitysComputingMilieux_GENERALtaloudelliset vaikutuksetStructural vector autoregressionkehittyvät markkinatEconomicsMacroGeneral Economics Econometrics and FinanceCommodity (Marxism)kansainvälinen kauppaFinance
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Impact of COVID-19 on the travel and tourism industry.

2021

Abstract Our paper is among the first to measure the potential effects of the COVID-19 pandemic on the tourism industry. Using panel structural vector auto-regression (PSVAR) (Pedroni, 2013) on data from 1995 to 2019 in 185 countries and system dynamic modeling (real-time data parameters connected to COVID-19), we estimate the impact of the pandemic crisis on the tourism industry worldwide. Past pandemic crises operated mostly through idiosyncratic shocks' channels, exposing domestic tourism sectors to large adverse shocks. Once domestic shocks perished (zero infection cases), inbound arrivals revived immediately. The COVID-19 pandemic, however, is different; and recovery of the tourism ind…

Economic policybusiness.industry020209 energy05 social sciencesCapacity buildingPublic policyDomestic tourism02 engineering and technologyCOVID-19 ; pandemic crises ; panel structural vector autoregression (PSVAR) ; system dynamics ; tourism industry ; financial cyclesManagement of Technology and Innovation0502 economics and businessSustainabilityPandemic0202 electrical engineering electronic engineering information engineeringBusinessEconomic impact analysisBusiness and International Management050203 business & managementApplied PsychologyTourismRisk managementTechnological forecasting and social change
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Assessing commodity price risks and terms of trade exposures in emerging and developing countries

2020

This paper provides novel evidence on commodity exposure (impacts of commodity price and terms of trade fluctuations) amongst 46 emerging and developing countries (EMDCs) in Africa, Asia and the Latin American and Caribbean (LAC) region. We focus on the exposures of six macroeconomic variables to the commodity prices and terms of trade, based on the real business cycle (RBC) theory. Our empirical results indicate that, overall, about 10% of the macroeconomic variation amongst the EMDCs is due to commodity market-related exposures. The Asian and LAC economies are especially sensitive to changes in commodity prices. The changes in the prices of world trade have an imminent impact on non-commo…

HistoryLatin AmericansPolymers and PlasticsDeveloping countryWorld tradeMonetary economicsTerms of tradeCommodity marketIndustrial and Manufacturing EngineeringStructural vector autoregressionEconomicsBusiness cycleBusiness and International ManagementCommodity (Marxism)SSRN Electronic Journal
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How do normalization schemes affect net spillovers? A replication of the Diebold and Yilmaz (2012) study

2019

Abstract This paper replicates the Diebold and Yilmaz (2012) study on the connectedness of the commodity market and three other financial markets: the stock market, the bond market, and the FX market, based on the Generalized Forecast Error Variance Decomposition, GEFVD. We show that the net spillover indices (of directional connectedness), used to assess the net contribution of one market to overall risk in the system, are sensitive to the normalization scheme applied to the GEFVD. We show that, considering data generating processes characterized by different degrees of persistence and covariance, a scalar-based normalization of the Generalized Forecast Error Variance Decomposition is pref…

Normalization (statistics)Economics and EconometricsSocial connectedness020209 energySettore SECS-P/05 - Econometria02 engineering and technologyNormalization schemeconnectednessSpillover effect0502 economics and business0202 electrical engineering electronic engineering information engineeringEconometrics050207 economicsMathematicsspillover normalization connectednessVector autoregression models05 social sciencesFinancial marketCovarianceCausalitySpilloverGeneral EnergynormalizationGeneralized forecast error variance decompositionCommodity price fluctuations Driving forces Nonparametric additive regression modelsVariance decomposition of forecast errorsBond marketStock marketSimulationNormalization schemes
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Has 1997 Asian crisis increased information flows between international markets

2003

Abstract The Asian crisis started on July 2, 1997 and caused turmoil in developed as well as emerging international stock markets. The objective of this paper is to analyse the effects of the crisis on the relationships of the Southeast Asian stock markets with the stock markets of three geographical areas (Europe, North America, and Latin America). We use the Morgan Stanley national and international indexes (MSCI) for two homogeneous and nonoverlapping time intervals. The econometric techniques used in this paper include the cointegration test, vector autoregression analysis, forecast error variance decomposition (FEVD), and impulse–response relationships. Our results show that: (i) there…

MacroeconomicsInternational marketEconomics and EconometricsLatin AmericansCointegrationFinancial economicsVariance decomposition of forecast errorsEconomicsStock marketSoutheast asianFinanceStock (geology)Vector autoregressionInternational Review of Economics & Finance
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