Journal articles: 'Structural VAR model'

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MORITA, Yoji, and Shigeyoshi MIYAGAWA. "Structural VAR Model and Economic Fluctuations." Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications 1995 (May 5, 1995): 113–18. http://dx.doi.org/10.5687/sss.1995.113.

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Goodwin, Barry K. "Forecasting Cattle Prices in the Presence of Structural Change." Journal of Agricultural and Applied Economics 24, no. 2 (December 1992): 11–22. http://dx.doi.org/10.1017/s0081305200018331.

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AbstractRecent empirical research and developments in the cattle industry suggest several reasons to suspect structural change in economic relationships determining cattle prices. Standard forecasting models may ignore structural change and may produce biased and misleading forecasts. Vector autoregressive (VAR) models that allow parameters to vary with time are used to forecast quarterly cattle prices. The VAR procedures are flexible in that they allow the identification of structural change that begins at an a priori unknown point and occurs gradually. The results indicate that the lowest RMSE for out-of-sample forecasts of cattle prices is obtained using a gradually switching VAR model. However, differences between the gradually switching VAR model and a univariate ARIMA model are not strongly significant. Impulse response functions indicate that adjustments of cattle prices to new information have become faster in recent years.

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DUNGEY, MARDI, and ADRIAN PAGAN. "A Structural VAR Model of the Australian Economy." Economic Record 76, no. 235 (December 2000): 321–42. http://dx.doi.org/10.1111/j.1475-4932.2000.tb00030.x.

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Narayan, Seema. "A structural VAR model of the Fiji Islands." Economic Modelling 31 (March 2013): 238–44. http://dx.doi.org/10.1016/j.econmod.2012.11.014.

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Crowder, William J., and Mark E. Wohar. "A cointegrated structural VAR model of the Canadian economy." Applied Economics 36, no. 3 (February 20, 2004): 195–213. http://dx.doi.org/10.1080/0003684042000175325.

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Österholm, Pär. "A structural Bayesian VAR for model-based fan charts." Applied Economics 40, no. 12 (June 2008): 1557–69. http://dx.doi.org/10.1080/00036840600843947.

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Ben Arfa, Nabil. "Sources of economic fuctuations in France: A structural VAR model." European Journal of Government and Economics 1, no. 1 (June 30, 2012): 66. http://dx.doi.org/10.17979/ejge.2012.1.1.4277.

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This paper studies the economic fluctuations of an open economy such as the French economy. A system of variables containing output, price level, trade balance, real exchange rate and oil prices is analyzed by applying the structural vector autoregressive (SVAR) methodology initiated by Sims (1980). This set of variables allows to evaluate the main sources of impulses of the French economy fluctuations. The results show that five structural shocks are identified using the long-run constraints implemented by Blanchard and Quah (1989). From the SVAR dynamic properties, impulse response functions and variance decomposition, the French economy is shown to be particularly vulnerable to supply and oil price shocks, where these two shocks respectively contribute to 40% and 35% of the economic disturbance. France is also hit by important external shocks which damage its trade balance position. Finally, it is found that shocks related to economic policy (demand shocks) have a quite limited impact on the economic activity.

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Cho, Dongchul. "Aggregate demand gap based on a simple structural VAR model." Economics Letters 114, no. 2 (February 2012): 228–34. http://dx.doi.org/10.1016/j.econlet.2011.09.038.

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Kliem, Martin, and Alexander Kriwoluzky. "Reconciling narrative monetary policy disturbances with structural VAR model shocks?" Economics Letters 121, no. 2 (November 2013): 247–51. http://dx.doi.org/10.1016/j.econlet.2013.08.006.

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Assenmacher-Wesche, Katrin. "Modeling Monetary Transmission in Switzerland with a Structural Cointegrated VAR Model." Swiss Journal of Economics and Statistics 144, no. 2 (January 2, 2008): 197–246. http://dx.doi.org/10.1007/bf03399253.

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Pacifico, Antonio. "Structural Panel Bayesian VAR Model to Deal with Model Misspecification and Unobserved Heterogeneity Problems." Econometrics 7, no. 1 (March 11, 2019): 8. http://dx.doi.org/10.3390/econometrics7010008.

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This paper provides an overview of a time-varying Structural Panel Bayesian Vector Autoregression model that deals with model misspecification and unobserved heterogeneity problems in applied macroeconomic analyses when studying time-varying relationships and dynamic interdependencies among countries and variables. I discuss what its distinctive features are, what it is used for, and how it can be analytically derived. I also describe how it is estimated and how structural spillovers and shock identification are performed. The model is empirically applied to a set of developed European economies to illustrate the functioning and the ability of the model. The paper also discusses more recent studies that have used multivariate dynamic macro-panels to evaluate idiosyncratic business cycles, policy-making, and spillover effects among different sectors and countries.

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Alsudani, Rana Sabeeh Abood, Jicheng Liu, and Zahrah Ismael Salman. "Forecasting mortality patterns of thalassaemia major patients in Iraq by using VAR model and reasons for this mortality." JOURNAL OF ADVANCES IN MATHEMATICS 12, no. 11 (December 30, 2016): 6785–98. http://dx.doi.org/10.24297/jam.v12i11.18.

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The vector autoregression model (VAR) is a natural extension of the univariate autoregressive model dynamic multivariable time series. It is one of the most successful, flexible, and easy to use models for the analysis of multivariable time series. The VAR model has proved to be particularly useful describing the dynamic behaviour of economic and financial time series and forecasting. Often it provides superior forecasts to those of time-series models and univariate and detailed forecasts, based on the theory of simultaneous equation models. Expectations of VAR models are very flexible because they can be conditioned on possible paths for the future in the form of specific variables. In addition to describing the data and forecasting, the VAR model is used to deduce structural and policy analysis. This study used the VAR model for forecasting the number of deaths in patients with thalassemia in Maysan province in southern Iraq, and also addressed the causes of these deaths. There was a strong relationship between mortality in thalassemia patients and an increase in the proportion of iron and the highest number of deaths was recorded for patients who had a very high proportion of iron. It was â€žthe most important cause of mortality (Cardiac disease, infections, the liver, the spleen).

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Hossain, Md Jamal, and Mohd Tahir Ismail. "Performance of a Novel Hybrid Model Through Simulation and Historical Financial Data." Sains Malaysiana 51, no. 7 (July 31, 2022): 2249–64. http://dx.doi.org/10.17576/jsm-2022-5107-25.

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It is thoroughly acknowledged that the historical financial time series is not linear, exhibits structural changes, and is volatile. It has been noticed in the current literature that because of the existence of structural breaks in the historical time series, the GARCH family models provide misleading results and poor forecasts. Thus, it is unavoidable to incorporate models with nonlinearity in the conditional mean and conditional variance to capture volatility dynamics more precisely than the existing models. Therefore, inspiring in this matter, this study proposes a novel hybrid model of exponential autoregressive (ExpAR) with a Markov-switching GARCH (MSGARCH) model. This study also examines volatility dynamics and performances through simulation and real-world financial data. Moreover, this study investigates downside risk management performances using 5% VaR (Value-at-Risk) back-testing. The empirical findings showed that the proposed model outperforms the benchmark model for both simulation and real-world time series data. The VaR results also showed that the proposed model captures downside risk more meticulously than the benchmark model.

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Lhuissier, Stéphane, and Fabien Tripier. "Regime‐dependent effects of uncertainty shocks: A structural interpretation." Quantitative Economics 12, no. 4 (2021): 1139–70. http://dx.doi.org/10.3982/qe1298.

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Using a Markov‐switching VAR, we show that the effects of uncertainty shocks on output are four times higher in a regime of economic distress than in a tranquil regime. We then provide a structural interpretation of these facts. To do so, we develop a business cycle model in which agents are aware of the possibility of regime changes when forming expectations. The model is estimated using a Bayesian minimum distance estimator that minimizes, over the set of structural parameters, the distance between the regime‐switching VAR‐based impulse response functions and those implied by the model. Our results point to worsening credit‐market conditions that amplify shocks during distress periods. Finally, we show that the expectation effect of regime switching in financial conditions is an important component of the financial accelerator mechanism. If agents are more pessimistic about future financial conditions, then the output effects of shocks are amplified.

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Kano, Takashi. "A structural VAR approach to the intertemporal model of the current account." Journal of International Money and Finance 27, no. 5 (September 2008): 757–79. http://dx.doi.org/10.1016/j.jimonfin.2008.04.003.

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Buckle, Robert A., Kunhong Kim, Heather Kirkham, Nathan McLellan, and Jarad Sharma. "A structural VAR business cycle model for a volatile small open economy." Economic Modelling 24, no. 6 (November 2007): 990–1017. http://dx.doi.org/10.1016/j.econmod.2007.04.003.

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Pacifico, Antonio. "Structural Compressed Panel VAR with Stochastic Volatility: A Robust Bayesian Model Averaging Procedure." Econometrics 10, no. 3 (July 12, 2022): 28. http://dx.doi.org/10.3390/econometrics10030028.

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This paper improves the existing literature on the shrinkage of high dimensional model and parameter spaces through Bayesian priors and Markov Chains algorithms. A hierarchical semiparametric Bayes approach is developed to overtake limits and misspecificity involved in compressed regression models. Methodologically, a multicountry large structural Panel Vector Autoregression is compressed through a robust model averaging to select the best subset across all possible combinations of predictors, where robust stands for the use of mixtures of proper conjugate priors. Concerning dynamic analysis, volatility changes and conditional density forecasts are addressed ensuring accurate predictive performance and capability. An empirical and simulated experiment are developed to highlight and discuss the functioning of the estimating procedure and forecasting accuracy.

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Bolatbayeva, Aizhan, Alisher Tolepbergen, and Nurdaulet Abilov. "A macroeconometric model for Russia." Russian Journal of Economics 6, no. 2 (June 30, 2020): 114–43. http://dx.doi.org/10.32609/j.ruje.6.47009.

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The paper outlines a structural macroeconometric model for the economy of Russia. The aim of the research is to analyze how the domestic economy functions, generate forecasts for important macroeconomic indicators and evaluate the responses of main endogenous variables to various shocks. The model is estimated based on quarterly data starting from 2001 to 2019. The majority of the equations are specified in error correction form due to the non-stationarity of variables. Stochastic simulation is used to solve the model for expost and ex-ante analysis. We compare forecasts of the model with forecasts generated by the VAR model. The results indicate that the present model outperforms the VAR model in terms of forecasting GDP growth, inflation rate and unemployment rate. We also evaluate the responses of main macroeconomic variables to VAT rate and world trade shocks via stochastic simulation. Finally, we generate ex-ante forecasts for the Russian economy under the baseline assumptions.

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Bação, Pedro, Inês Gaspar, and Marta Simões. "Corruption and Economic Growth: The Case of Portugal." Notas Económicas, no. 49 (December 6, 2019): 11–33. http://dx.doi.org/10.14195/2183-203x_49_2.

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In this paper we investigate the impact of corruption on economic growth in Portugal over the period 1980-2018. The empirical approach makes use of a VAR model inspired by the standard Cobb-Douglas aggregate production function. The VAR model includes the capital stock, hours worked, total factor productivity and the corruption perceptions index (CPI) of Transparency International. The CPI combines several sources of information on the level of corruption in each country. The scale of this index goes from 0, the highest level of corruption, to 10, the lowest level. The magnitude of the estimated effect of corruption on economic growth in the unrestricted VAR model is large (and positive), but statistically not significantly different from zero. However, the results from the estimation of a structural VAR model with economically plausible long-run restrictions indicate modest gains from reducing corruption.

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Hu, Weigang, Yan Zhou, and Jun Liu. "Evaluation of Hot Money Drivers in China: A Structural VAR Approach." Complexity 2022 (July 4, 2022): 1–12. http://dx.doi.org/10.1155/2022/1066096.

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This paper investigates the drivers of hot money in China. It develops a model based on expectation-variance utility theory in the theoretical analysis section. The model considers a foreign investor who faces the question of how to distribute his wealth between foreign and domestic assets. The model’s analysis suggests that economic variations, such as expected domestic currency appreciation, rise in domestic asset return, drop in foreign asset return, domestic economic growth, decrease in domestic inflation, and rise in foreign asset risk will cause foreign investors to distribute more wealth in domestic assets. Therefore, hot money flows in, and vice versa. In the empirical analysis section, the paper estimates structural VAR models using data from 2000 to 2019 in China. The impulse response functions are consistent with the theoretical predictions: when there is a positive domestic inflation shock, hot money outflows increase (inflows decline) in the current period, but the response is not significant. When there is a positive domestic growth rate shock or positive domestic asset return rate shock, hot money inflows increase (outflows decline) in the current period, and the response reaches its peak in the next period. Furthermore, when there is a positive expected exchange rate shock, hot money outflows increase (inflows decline) in the current period. Of these drivers, the expected exchange rate has the largest impact on hot money, and the domestic growth rate has the most enduring effect.

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Monfort, A., and R. Rabemananjara. "From a var model to a structural model, with an application to the wage–price spiral." Journal of Applied Econometrics 5, no. 3 (July 1990): 203–27. http://dx.doi.org/10.1002/jae.3950050302.

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Lee, Chun-Chang. "Interactions between Asset Prices and Monetary Policy in Taiwan: A Structural VAR Model." British Journal of Economics, Management & Trade 3, no. 4 (January 10, 2013): 479–97. http://dx.doi.org/10.9734/bjemt/2013/4835.

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MORITA, Yoji, and Shigeyoshi MIYAGAWA. "On the Behavior of Call Rate and Money Supply in Structural VAR Model." Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications 1997 (May 5, 1997): 65–70. http://dx.doi.org/10.5687/sss.1997.65.

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Farka, Mira, and Amadeu DaSilva. "The fed and the term structure: Addressing simultaneity within a structural VAR model." Journal of Empirical Finance 18, no. 5 (December 2011): 935–52. http://dx.doi.org/10.1016/j.jempfin.2011.08.004.

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Stockhammer, Engelbert, and Özlem Onaran. "Accumulation, distribution and employment: a structural VAR approach to a Kaleckian macro model." Structural Change and Economic Dynamics 15, no. 4 (December 2004): 421–47. http://dx.doi.org/10.1016/j.strueco.2003.07.002.

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Shen, Shichang, and Xiaoyi Dong. "The Structural Relationship between Chinese Money Supply and Inflation Based on VAR Model." Applied Mathematics 10, no. 07 (2019): 578–87. http://dx.doi.org/10.4236/am.2019.107041.

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Marica, Vasile George, and Alexandra Horobet. "Conditional Granger Causality and Genetic Algorithms in VAR Model Selection." Symmetry 11, no. 8 (August 3, 2019): 1004. http://dx.doi.org/10.3390/sym11081004.

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Overcoming symmetry in combinatorial evolutionary algorithms is a challenge for existing niching methods. This research presents a genetic algorithm designed for the shrinkage of the coefficient matrix in vector autoregression (VAR) models, constructed on two pillars: conditional Granger causality and Lasso regression. Departing from a recent information theory proof that Granger causality and transfer entropy are equivalent, we propose a heuristic method for the identification of true structural dependencies in multivariate economic time series. Through rigorous testing, both empirically and through simulations, the present paper proves that genetic algorithms initialized with classical solutions are able to easily break the symmetry of random search and progress towards specific modeling.

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Branch, William A., Troy Davig, and Bruce McGough. "ADAPTIVE LEARNING IN REGIME-SWITCHING MODELS." Macroeconomic Dynamics 17, no. 5 (March 6, 2012): 998–1022. http://dx.doi.org/10.1017/s1365100511000800.

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We study adaptive learning in economic environments subject to recurring structural change. Stochastically evolving institutional and policymaking features can be described by regime-switching models with parameters that evolve according to finite state Markov processes. We demonstrate that in nonlinear models of this form, the presence of sunspot equilibria implies two natural schemes for learning the conditional means of endogenous variables: under mean value learning, agents condition on a sunspot variable that captures the self-fulfilling serial correlation in the equilibrium, whereas under vector autoregression learning (VAR learning), the self-fulfilling serial correlation must be learned. We show that an intuitive condition ensures convergence to a regime-switching rational expectations equilibrium. However, the stability of sunspot equilibria, when they exist, depends on whether agents adopt mean value or VAR learning: coordinating on sunspot equilibria via a VAR learning rule is not possible. To illustrate these phenomena, we develop results for an overlapping-generations model and a New Keynesian model.

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Götz, Thomas B., and Klemens Hauzenberger. "Large mixed-frequency VARs with a parsimonious time-varying parameter structure." Econometrics Journal 24, no. 3 (January 16, 2021): 442–61. http://dx.doi.org/10.1093/ectj/utab001.

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Summary In order to simultaneously consider mixed-frequency time series, their joint dynamics, and possible structural change, we introduce a time-varying parameter mixed-frequency vector autoregression (VAR). Time variation enters in a parsimonious way: only the intercepts and a common factor in the error variances can vary. Computational complexity therefore remains in a range that still allows us to estimate moderately large VARs in a reasonable amount of time. This makes our model an appealing addition to any suite of forecasting models. For eleven U.S. variables, we show the competitiveness compared to a commonly used constant-coefficient mixed-frequency VAR and other related model classes. Our model also accurately captures the drop in the gross domestic product during the COVID-19 pandemic.

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Sbrogiò, Luca. "Parametric approach to the reconstruction of timber structures in Campanian Roman houses." Virtual Archaeology Review 13, no. 26 (January 21, 2022): 45–61. http://dx.doi.org/10.4995/var.2022.15319.

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The virtual reconstruction of ancient architecture aims at describing the ‘original’ elevation and volume of a disappeared building. The feeble archaeological traces, often limited to their foundations, left by houses impair the reinstating of their image, in contrast to that which is made possible by the massive structures of public buildings. A twofold problem arises when dealing with timber structures during a reconstruction procedure: at the local scale of the individual beam (e.g. joists or rafters), one must define a beam’s cross-section given its span; at the overall scale, the shape of a building results from that which its structures allowed it to have been. Therefore, this work proposes a procedure to deal with the ‘local’ problem, i.e. the definition of a beam’s cross-section from its span. To that end, a simplified, parametric structural model is required. The available bits of information are organized into inputs, parameters and outputs of the analytical problem by matching each information with a structural quantity (load, cross-section, spacing, etc.). Two mathematical relationships among them are proposed, which express two equally possible dimensioning criteria, based either on joists’ strength or deformability. It seems that the joist’s strength was the option for lightly loaded joists, as in roofs or tightly spaced floor frames; conversely, heavily loaded joists conformed to the deformability criterion. Both dimensioning procedures are translated into a visual algorithm in Grasshopper, a plugin for Rhinoceros modelling software, which enables the parametric definition of objects. Finally, the proposed procedure is tentatively applied to automatically reconstruct the floor and roof frames that belonged to the domus on top of the Sarno Baths in Pompeii. The algorithm automatically picked the dimensioning criterion in relation to each frame’s span and hypothesized loads and determined joists’ orientation and minimum cross-sections. The obtained floor frames, whose structural conditions are considered as sensible, will be adopted in the overall virtual reconstruction proposal of the ruins, also based on the analytical evaluation of masonry structures.Highlights:- Proposal of a structural model for the dimensioning of timber floor beams in domestic spaces based on archaeological and literature information.- Parametrical interpretation of the model in Grasshopper for Rhinoceros software and optimization analysis of the structural parameters involved.- Application of the model to the reconstruction of floor frames in a house in the Sarno Baths complex, Pompeii.

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Benati, Luca, and Paolo Surico. "VAR Analysis and the Great Moderation." American Economic Review 99, no. 4 (August 1, 2009): 1636–52. http://dx.doi.org/10.1257/aer.99.4.1636.

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Most analyses of the US Great Moderation are based on structural VARs, and point toward good luck as the main explanation for the recent macroeconomic stability. Based on an estimated New-Keynesian model where the only source of change is the move from passive to active monetary policy, we show that (i) the theoretical VAR innovation variances for all series decrease across regimes; (ii) VAR-based counterfactuals assign a minor role to improved policy; and (iii) VAR impulse-response functions to a monetary shock exhibit little variation across regimes. Our analysis suggests that existing VAR evidence is also compatible with the “good policy” hypothesis. (JEL C32, C52, E13, E52, N12)

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Slimani, Slah. "Fiscal Policy Effectiveness in the Tunisian Economy." International Journal of Sustainable Economies Management 10, no. 4 (October 2021): 21–38. http://dx.doi.org/10.4018/ijsem.2021100102.

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Based on Blanchard and Perotti, Perotti, and Biau and Girard approaches, this paper evaluates the fiscal policy's effectiveness in Tunisia using Structural VAR model. The results show the short-run macroeconomic efficiency of a structural increase in public spending in Tunisia with a fiscal multiplier close to 1,806, in line with Keynesian's models. However, the estimated effect of a structural increase in tax revenues on activity is non-Keynesian. This is explained by the presence of a voracity effect in the case of the Tunisian economy.

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H. Ibrahim, Mansor, and Fadzlan Sufian. "A structural VAR analysis of Islamic financing in Malaysia." Studies in Economics and Finance 31, no. 4 (September 30, 2014): 371–86. http://dx.doi.org/10.1108/sef-05-2012-0060.

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Purpose – The purpose of this paper is evaluate the interrelations between Islamic financing and key economic and financial variables including real output, price level, interest rate and stock prices for the case of Malaysia. Design/methodology/approach – The paper makes use of a structural vector autoregressive (SVAR) model to discern the influences of key economic and financial variables on the behavior of Islamic financing. Findings – The basic results indicate that Islamic financing responds positively to innovations in real output. In addition, the price level shocks also tend to have significant but lagged effects on the financing provision of Islamic banks. Most interestingly, Islamic financing is impacted negatively and immediately by positive interest rate shocks, contradicting the argument that Islamic bank operations are shielded from interest rate fluctuations. Indeed, the excess sensitivity of Islamic banks to interest rate fluctuations and their lagged responses to price level shocks are found to be robust across alternative SVAR specifications. Practical implications – Operating under a dual banking system, Islamic banks are not immune from monetary conditions of the country. Indeed, it seems to be exposed to the interest rate risk, an aspect that needs to be accounted for by Islamic banks in their risk management. Originality/value – With the emergence of Islamic finance industry, understanding the implications of various macroeconomic factors on Islamic financing is essential. This study adds to this understanding, which has received limited attention.

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Suhendra, Indra, and Cep Jandi Anwar. "The response of asset prices to monetary policy shock in Indonesia: A structural VAR approach." Banks and Bank Systems 17, no. 1 (March 25, 2022): 104–14. http://dx.doi.org/10.21511/bbs.17(1).2022.09.

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This paper aims to determine the effect of central bank monetary policy on financial asset prices in Indonesia from 1990 Q1 to 2020 Q4. Furthermore, this study measures the responses of three different asset prices: bond yield, stock price and exchange rate to central bank rate shocks using the structural vector autoregression model. The impulse response functions showed that tightening monetary policy in Indonesia appreciated the exchange rate in four periods, lowered stock prices in five periods, and increased bond yield in all periods. These results imply that an increase in monetary policy interest rate appreciates exchange rate, lowers the stock price, and reduces bond yield. The result of variance decomposition showed that the most dominant central bank rate prediction was in predicting forecast error variance of bond yield but the smallest in predicting forecast error variance of the exchange rate. These results corroborated the hypothesis that tightening monetary policy in Indonesia increases financial asset prices. It also highlighted the informational role of monetary policy interest rate in stabilizing financial asset prices.

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Zhou, Donghai, Binxia Chen, Jiahui Li, and Yuanying Jiang. "Chinaʼs Economic Growth, Energy Efficiency, and Industrial Development: Nonlinear Effects on Carbon Dioxide Emissions." Discrete Dynamics in Nature and Society 2021 (May 31, 2021): 1–17. http://dx.doi.org/10.1155/2021/5547092.

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This paper analyzes the time-varying impacts of Chinaʼs economic growth, energy efficiency, and industrial development on carbon dioxide (CO2) emissions from 1970 to 2019. First, we examined and found that there are two significant structural changes in the CO2 sequence over the years, and there was a significant nonlinear relationship among the four. The first nonlinear structural model constructed is the TVP regression model. According to the Bayesian model comparison criterion, TVP-SV-VAR was selected as the second constructed model from four types of VAR models containing nonlinear structures. The results show that the conduction intensity value of energy use efficiency to CO2 emissions has increased year by year, from 0.45 in 1971 to 0.97 in 2019. The short-term transmission mechanism of energy use efficiency to carbon emissions is the most significant. The conduction intensity of Chinaʼs economic growth on CO2 emissions increases year by year. Chinaʼs economic growth plays a major role in long-term CO2 emission reduction. The impact of industrial development on CO2 emissions reached a peak of 0.34 in 1977, and the intensity of the impact has basically stabilized at 0.26.

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Li, Yan. "Nonlinear relationship between carbon market and energy market." E3S Web of Conferences 275 (2021): 02046. http://dx.doi.org/10.1051/e3sconf/202127502046.

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This paper divides the energy market into energy futures market and new energy stock market. At the same time, the closing price of Shenzhen carbon emission rights is used to represent the carbon market price, the energy futures composite index of China Securities Exchange is used to represent the energy futures market price, and the stock price of new energy listed companies is used to represent the new energy stock market price. VAR model and MSVAR model are used to empirically study the relationship between the three variables and the nonlinear relationship between them. VAR model results show that there will be more complex relationship among carbon market price, energy company stock price and energy futures price. MSVAR model shows that the energy futures market, new energy stock market and carbon market present nonlinear and structural changes, and MSVAR model can better explain the nonlinear relationship among the three markets than traditional VAR model.

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Zou, Yajie, Xuedong Hua, Yanru Zhang, and Yinhai Wang. "Hybrid short-term freeway speed prediction methods based on periodic analysis." Canadian Journal of Civil Engineering 42, no. 8 (August 2015): 570–82. http://dx.doi.org/10.1139/cjce-2014-0447.

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Short-term traffic speed forecasting is an important issue for developing Intelligent Transportation Systems applications. So far, a number of short-term speed prediction approaches have been developed. Recently, some multivariate approaches have been proposed to consider the spatial and temporal correlation of traffic data. However, as traffic data often demonstrates periodic patterns, the existing methodologies often fail to take into account spatial and temporal information as well as the periodic features of traffic data simultaneously in the multi-step prediction. This paper comprehensively evaluated the multi-step prediction performance of space time (ST) model, vector autoregression (VAR), and autoregressive integrated moving average (ARIMA) models using the 5 minute freeway speed data collected from five loop detectors located on an eastbound segment of Interstate 394 freeway, in Minnesota. To further consider the cyclical characteristics of freeway speed data, hybrid prediction approaches were proposed to decompose speed into two different components: a periodic trend and a residual part. A trigonometric regression function is introduced to capture the periodic component and the residual part is modeled by the ST, VAR, and ARIMA models. The prediction results suggest that for multi-step freeway speed prediction, as the time step increases, the ST model demonstrates advantages over the VAR and ARIMA models. Comparisons among the ST, VAR, ARIMA, and hybrid models demonstrated that modeling the periodicity and the residual part separately can better interpret the underlining structure of the speed data. The proposed hybrid prediction approach can accommodate the periodic trends and provide more accurate prediction results when the forecasting horizon is greater than 30 min.

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Malakhovskaya, O. "DSGE-based forecasting: What should our perspective be?" Voprosy Ekonomiki, no. 12 (December 20, 2016): 129–46. http://dx.doi.org/10.32609/0042-8736-2016-12-129-146.

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The article compares the accuracy of point forecasts made with a structural dynamic stochastic general equilibrium model (DSGE) to those made with vector autoregressions estimated by OLS (VAR) and by Bayesian methods (BVAR). The main question addressed in the article is whether DSGE-based forecasts are as accurate as non-structural model ones. The comparison is made on the ground of mean squared forecast errors. The results show that the forecasting ability of the DSGE model is in general inferior to that of the BVAR. However, the difference is not critical. Moreover, for some variables and forecasting horizons, the DSGE model produces the forecast with the lowest error among all three models in question.

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Cuestas, Juan C. "The EU real exchange rates: A structural Bayesian VAR. A note." Revista de Economía y Estadística 56, no. 1 (December 1, 2018): 43–57. http://dx.doi.org/10.55444/2451.7321.2018.v56.n1.29387.

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In this paper we contribute to the long literature on the real exchange determination by estimating a Bayesian structural vector autoregressive model. We aim at identifying the effect on the EU-28 RER of shock originating in its main fundamental variables, namely, current account, government consumptions, investment and real income. We find in most of the shocks that the RER moves away for long periods, proving yet again, that the purchasing power parity condition is rarely fulfilled empirically.

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Eberle, Jonathan, Thomas Brenner, and Timo Mitze. "Public Research, Local Knowledge Transfer, and Regional Development: Insights from a Structural VAR Model." International Regional Science Review 43, no. 6 (August 12, 2019): 555–86. http://dx.doi.org/10.1177/0160017619863466.

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This article estimates the regional economic effects of public research activities. In order to identify the underlying transmission channels from knowledge creation to the regional environment, the empirical identification strategy goes beyond traditional partial effects analyses and studies the complex linkages between public research, innovativeness, and regional development on the basis of a structural vector autoregressive model. A particular focus is thereby set on assessing whether the effects of local public research activity differ by the type of research actors (universities, technical colleges, and public research institutes). The empirical results indicate that an increase in the volume of (public) third-party funding to technical colleges is associated with a rise in the regional investment and employment rate as well as the human capital stock. Increasing public third-party funding to both universities and technical colleges positively affects the regional patent activity, the employment rate, and per workforce output. In comparison, the empirical results provide limited evidence for regional economic effects stemming from an increase in local knowledge creation measured in terms of scientific publications. Here, only variations in the publication rate of public research institutes can be linked to positive private sector investment and employment effects.

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Schreiber, Sven. "Did work-sharing work in France? Evidence from a structural co-integrated VAR model." European Journal of Political Economy 24, no. 2 (June 2008): 478–90. http://dx.doi.org/10.1016/j.ejpoleco.2007.11.004.

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Wang, Yu, and Lei Liu. "Spillover effect in Asian financial markets: A VAR-structural GARCH analysis." China Finance Review International 6, no. 2 (May 16, 2016): 150–76. http://dx.doi.org/10.1108/cfri-11-2014-0095.

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Purpose – The purpose of this paper is to provide a method for computing the spillover index first proposed by Diebold and Yilmaz (2009), with empirical application on Asian stock markets. Design/methodology/approach – It is based on a VAR-structural-GARCH model. Findings – The results clearly show that the main driver of fluctuations in Asian financial markets is the USA, with China having little connection with other markets. Further, evidence of financial contagion is found during both the 1997 Asian financial crisis and the 2008 global financial crisis. Originality/value – The method has two advantages: it is both uniquely determined and dynamic.

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IWATA, SHIGERU, and SHU WU. "MACROECONOMIC SHOCKS AND THE FOREIGN EXCHANGE RISK PREMIA." Macroeconomic Dynamics 10, no. 4 (August 23, 2006): 439–66. http://dx.doi.org/10.1017/s136510050606007x.

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In this paper we empirically examine the sources of the volatility of the foreign exchange risk premia. Using a nonlinear structural Vector Autoregression (VAR) model based on no-arbitrage condition to identify various macroeconomic shocks and the foreign exchange risk premia, we find that more than 80% of the volatilities of the currency risk premia can be accounted for by the standard macroeconomic shocks that drive output and inflation. By explicitly modelling the currency risk premia in the VAR system, we also offer a potential reconciliation for the seemingly contradicting observations from the previous VAR analysis of the exchange rate “overshooting” behavior under exogenous monetary innovations.

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Bahaddi, Tlaytmaste, and Mohamed Karim. "Macroeconomic Effects of Fiscal Policy in Morocco: An Approach to Structural VAR." Applied Economics and Finance 5, no. 1 (December 19, 2017): 75. http://dx.doi.org/10.11114/aef.v5i1.2874.

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This article evaluates the short-term macroeconomic effectiveness of a structural rise in public spending in Morocco through a Structural Vector Autoregressive Model (SVAR) inspired by the approach of Blanchard and Perotti (2002).The response of the real economic activity following a structural rise of the public spending is small and significant only in the very short term. The evaluation of transmission channels reveals, moreover, a deterioration of the trade balance and a depreciation of the real effective exchange rate. Finally, the results of the estimation concluded that discretionary fiscal shocks have a Keynesian effect on the level of activity.

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Teapon, Rizal Rahman H., and Rachman Dano Mustafa. "Shock of Monetary Policy Transmission and Macroeconomic Variable in Indonesia: A Structural VAR Approach." Jurnal Economia 14, no. 2 (October 1, 2018): 177–96. http://dx.doi.org/10.21831/economia.v14i2.21480.

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Abstract: Shock of Monetary Policy Transmission and Macroeconomic Variable in Indonesia: A Structural VAR Approach. The purpose of this paper is to find out how much the shock of monetary policy transmission affects macroeconomic variables in Indonesia and vice versa by using Structural Vector Autoregression (SVAR) model. The results showed that the transmission of monetary policy in Indonesia only gives a weak influence toward inflation, but it greatly stimulates economic growth. However, the shock of macroeconomic variables influences the transmission of monetary policy in Indonesia significantly. Keywords: Structural Vector Autoregression (SVAR), monetary policy, macroeconomic policy.Abstrak: Kejutan Transmisi Kebijakan Moneter dan Variabel Makro Ekonomi di Indonesia: Suatu Pendekatan Structural Vector Autoregression. Tujuan dari tulisan ini adalah untuk mengetahui berapa besar guncangan transmisi kebijakan moneter mempengaruhi variabel makro ekonomi di Indonesia dan sebaliknya, dengan menggunakan model Structural Vector Autoregression (SVAR). Hasil penelitian menunjukan bahwa transmisi kebijakan moneter di Indonesia masih lemah dalam mempengaruhi inflasi tetapi sangat kuat dalam merangsang pertumbuhan ekonomi. Sebaliknya, guncangan variabel makro ekonomi sangat signifikan dalam mempengaruhi transmisi kebijakan moneter di Indonesia. Kata kunci: Structural Vector Autoregression (SVAR), kebijakan moneter, kebijakan makro ekonomi

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Syapriatama, Imronjana, and Intan Kusuma Pratiwi. "MENGUJI KEBERADAAN STRUCTURAL BREAKS PADA TRANSMISI KEBIJAKAN MONETER DI INDONESIA." Journal of Enterprise and Development 1, no. 02 (December 2, 2019): 1–6. http://dx.doi.org/10.20414/jed.v1i02.969.

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This paper investigates the present of structural breaks in order to determine the regime shift in case of Indonesia economy. We use the Bai-Perron (2003) to test the breaks within period of Januari 2014 – Desember 2018. We also use Structural Vector Autoregression (VAR) to generate the model which constructed to analyze monetary transmission mechanism. The result shows that there are 4 significant structural breaks while SVAR shows the negative relationship between SBIS and the Output and negative relationship between PUAS and Inflation.

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Amokrane, Lamia, Tsouria Kassab, and Juan Monjo-Carrio. "Ancient restorations: computer-based structural approach for the identification and reinterpretation of the Medracen’s constructive sequence." Virtual Archaeology Review 13, no. 27 (June 10, 2022): 33–48. http://dx.doi.org/10.4995/var.2022.17394.

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This paper addresses the importance of a structural approach for identifying and interpreting building chronology, as well as for the establishment of historical stratigraphy. Through structural analyses, carried out on the oldest extant royal mausoleum in North Africa, the Medracen (4th-3rd century BC), located in eastern Algeria, it has been possible to identify building sequences and structural characteristics; a reinterpretation of its constructive sequence within a specific historical context was also suggested. A static linear Finite Element Method (FEM) analysis was performed on a simplified 3D model conceived with solid elements to assess the structural behaviour of the structure under the effect of its self-weight and to identify, consequently, its construction sequence. The equilibrium approach was effective in identifying the structure’s geometry. Results show that Medracen’s ancient restoration was a strengthening intervention strategy and had a symbolic aim related to the function of the funerary building. Restoration works, consisting of repairing specific parts of the building and adding an external cladding, as a whole architectural entity, contributed to reducing the effect of tensile stress, therefore, stabilizing the inner core. Besides, this same action was a means for the Numidian elite to transform an ancient monumental burial (sepulchrum) into a monument (monumentum) with cultural significance likely to convey socio-political messages relating to power and sovereignty. Therefore, we can speak of an “evolutionary restoration” that reflects the ambitions of the Numidian elite to become part of the Mediterranean orbit.

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Drautzburg, Thorsten. "A narrative approach to a fiscal DSGE model." Quantitative Economics 11, no. 2 (2020): 801–37. http://dx.doi.org/10.3982/qe1083.

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Structural DSGE models are used for analyzing both policy and the sources of business cycles. Conclusions based on full structural models are, however, potentially affected by misspecification. A competing method is to use partially identified SVARs based on narrative shocks. This paper asks whether both approaches agree. Specifically, I use narrative data in a DSGE‐SVAR that partially identify policy shocks in the VAR and assess the fit of the DSGE model relative to this narrative benchmark. In developing this narrative DSGE‐SVAR, I develop a tractable Bayesian approach to proxy VARs and show that such an approach is valid for models with a certain class of Taylor rules. Estimating a DSGE‐SVAR based on a standard DSGE model with fiscal rules and narrative data, I find that the DSGE model identification is at odds with the narrative information as measured by the marginal likelihood. I trace this discrepancy to differences in impulse responses, identified historical shocks and policy rules. The results indicate monetary accommodation of fiscal shocks.

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Pöchtrager, Markus, Gudrun Styhler-Aydın, Marina Döring-Williams, and Norbert Pfeifer. "Digital reconstruction of historic roof structures: developing a workflow for a highly automated analysis." Virtual Archaeology Review 9, no. 19 (July 20, 2018): 21. http://dx.doi.org/10.4995/var.2018.8855.

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<p>Planning on adaptive reuse, maintenance and restoration of historic timber structuresrequiresextensive architectural and structural analysis of the actual condition. Current methods for a modellingof roof constructions consist of several manual steps including the time-consuming dimensional modelling. The continuous development of terrestrial laser scanners increases the accuracy, comfort and speed of the surveying work inroof constructions. Resultingpoint clouds enabledetailed visualisation of theconstructionsrepresented by single points or polygonal meshes, but in fact donot containinformation about the structural system and the beam elements. The developed workflow containsseveral processing steps on the point cloud dataset. The most important among them arethenormal vector computation, the segmentation of points to extract planarfaces, a classification of planarsegmentsto detect the beam side facesand finally theparametric modelling of the beams on the basis of classified segments. Thisenablesa highly automated transitionfrom raw point cloud data to a geometric model containing beams of the structural system. The geometric model,as well as additional information about the structural properties of involved wooden beams and their joints,is necessaryinput for a furtherstructural modellingof timber constructions. The results of the workflow confirm that the proposed methods work well for beams with a rectangularcross-section and minor deformations. Scan shadows and occlusionof beamsby additional installationsor interlockingbeamsdecreases the modelling performance, but in generala high level ofaccuracy and completeness isachieved ata high degree of automation</p><div data-canvas-width="62.83200000000001"><strong>Highlights:</strong></div><div data-canvas-width="62.83200000000001"> </div><div><ul><li><p>This article presents a novel approach to automated reconstruction of beam structures by modelling geometry from segmented point clouds.</p></li><li><p>Wooden beams are modelled as cuboids, thus a rectangular cross-section with minor deformation is required.</p></li><li><p>An accuracy of less than 1 cm can be reached for modelled beams, compared to the reference LiDAR point cloud.</p></li></ul></div>

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Gerdesmeier, Dieter, Barbara Roffia, and Hans-Eggert Reimers. "Forecasting Euro Area Inflation Using Single-Equation and Multivariate VAR–Models." Folia Oeconomica Stetinensia 17, no. 2 (December 1, 2017): 19–34. http://dx.doi.org/10.1515/foli-2017-0016.

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AbstractForecasting inflation is of key relevance for central banks, not least because the objective of low and stable inflation is embodied in most central banks’ mandates and the monetary policy transmission mechanism is well known to be subject to long and variable lags. To our best knowledge, central banks around the world use conditional as well as unconditional forecasts for such purposes. Turning to unconditional forecasts, these can be derived on the basis of structural and non-structural models. Among the latter, vector autoregressive (VAR)-models are among the most popular tools.This study aims at assessing and deriving a set of unconditional forecasts for euro area inflation based on several specifications which take into account the information content of, inter alia, monetary and credit variables. The models are ordered and based on their in-sample performance and the “best” model is selected accordingly. The results indicate that the inclusion of money and credit variables in the information set improves the quality of the forecasts over a horizon of one to eight quarters. This supports the view that central banks should regularly monitor developments in money and credit.

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Journal articles on the topic 'Structural VAR model'

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