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Добірка наукової літератури з теми "Nonlinear Structural Vector AutoRegressions"

Автор: Grafiati
Опубліковано: 11 березня 2023

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Статті в журналах з теми "Nonlinear Structural Vector AutoRegressions"

1

Harris, Glen R. "Markov Chain Monte Carlo Estimation of Regime Switching Vector Autoregressions." ASTIN Bulletin 29, no. 1 (May 1999): 47–79. http://dx.doi.org/10.2143/ast.29.1.504606.

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AbstractFinancial time series data are typically found to possess leptokurtic frequency distributions, time varying volatilities, outliers and correlation structures inconsistent with linear generating processes, nonlinear dependence, and dependencies between series that are not stable over time. Regime Switching Vector Autoregressions are of interest because they are capable of explaining the observed features of the data, can capture a variety of interactions between series, appear intuitively reasonable, are vector processes, and are now tractable.This paper considers a vector autoregression subject to periodic structural changes. The parameters of a vector autoregression are modelled as the outcome of an unobserved discrete Markov process with unknown transition probabilities. The unobserved regimes, one for each time point, together with the regime transition probabilities, are determined in addition to the vector autoregression parameters within each regime.A Bayesian Markov Chain Monte Carlo estimation procedure is developed which efficiently generates the posterior joint density of the parameters and the regimes. The complete likelihood surface is generated at the same time, enabling estimation of posterior model probabilities for use in non-nested model selection. The procedure can readily be extended to produce joint prediction densities for the variables, incorporating both parameter and model uncertainty.Results using simulated and real data are provided. A clear separation of the variance between a stable and an unstable regime was observed. Ignoring regime shifts is very likely to produce misleading volatility estimates and is unlikely to be robust to outliers. A comparison with commonly used models suggests that Regime Switching Vector Autoregressions provide a particularly good description of the observed data.
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2

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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3

Kumar, Nikeel, Ronald Ravinesh Kumar, Radika Kumar, and Peter Josef Stauvermann. "Is the tourism–growth relationship asymmetric in the Cook Islands? Evidence from NARDL cointegration and causality tests." Tourism Economics 26, no. 4 (July 2, 2019): 658–81. http://dx.doi.org/10.1177/1354816619859712.

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We examine whether tourism sector development measured by visitor arrivals per capita has asymmetric growth effects in the Cook Islands using quarterly data from 2010Q1 to 2016Q3. Asymmetric cointegration, long-run elasticities, and dynamic multipliers are estimated using the nonlinear autoregressive distributed lag model developed by Shin et al. Asymmetric causality testing is done using the asymmetric vector autoregression approach with insights from Hatemi-J. We identify structural breaks using the Lee and Strazicich multiple endogenous structural break unit root test. The results indicate that a 1% increase in visitor arrivals would increase gross domestic product (GDP) per capita by 0.92%, whereas a 1% decrease in visitor arrivals would decrease GDP per capita by 0.34%. The identified breaks, 2013Q2 and 2015Q3, are positive and significant in the short run only. The causality result confirms a bidirectional association, thus mutually reinforcing the asymmetric relationship between visitor arrivals and economic growth.
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4

Stock, James H., and Mark W. Watson. "Vector Autoregressions." Journal of Economic Perspectives 15, no. 4 (November 1, 2001): 101–15. http://dx.doi.org/10.1257/jep.15.4.101.

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Анотація:
This paper critically reviews the use of vector autoregressions (VARs) for four tasks: data description, forecasting, structural inference, and policy analysis. The paper begins with a review of VAR analysis, highlighting the differences between reduced-form VARs, recursive VARs and structural VARs. A three variable VAR that includes the unemployment rate, price inflation and the short term interest rate is used to show how VAR methods are used for the four tasks. The paper concludes that VARs have proven to be powerful and reliable tools for data description and forecasting, but have been less useful for structural inference and policy analysis.
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5

Iwata, Shigeru, and Shu Wu. "A NOTE ON FOREIGN EXCHANGE INTERVENTIONS AT ZERO INTEREST RATES." Macroeconomic Dynamics 16, no. 5 (September 7, 2012): 802–17. http://dx.doi.org/10.1017/s1365100512000120.

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This note uses a nonlinear structural vector autoregression model to empirically investigate the effectiveness of official foreign exchange (FX) interventions in an economy when interest rates are constrained to the zero level, based on Japanese data in the 1990s. The model allows us to estimate the effects of FX interventions operating through different channels. We find that FX interventions are still capable of influencing the foreign exchange rate in a zero-interest-rate environment, even though their effects are greatly reduced by the zero lower bound on interest rates. Our results suggest that although it might be feasible to use the exchange rate as an alternative monetary policy instrument at zero interest rates as proposed by McCallum (Inflation Targeting and the Liquidity Trap, NBER working paper 8225, 2000), the exchange rate–based Taylor rule may not be very effective in achieving the ultimate policy goals.
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6

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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7

Lanne, Markku, and Helmut Lütkepohl. "Structural Vector Autoregressions With Nonnormal Residuals." Journal of Business & Economic Statistics 28, no. 1 (January 2010): 159–68. http://dx.doi.org/10.1198/jbes.2009.06003.

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8

Zha, Tao. "Block recursion and structural vector autoregressions." Journal of Econometrics 90, no. 2 (June 1999): 291–316. http://dx.doi.org/10.1016/s0304-4076(98)00045-1.

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9

Lanne, Markku, Helmut Lütkepohl, and Katarzyna Maciejowska. "Structural vector autoregressions with Markov switching." Journal of Economic Dynamics and Control 34, no. 2 (February 2010): 121–31. http://dx.doi.org/10.1016/j.jedc.2009.08.002.

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10

Baumeister, Christiane, and James D. Hamilton. "Structural Vector Autoregressions with Imperfect Identifying Information." AEA Papers and Proceedings 112 (May 1, 2022): 466–70. http://dx.doi.org/10.1257/pandp.20221044.

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The problem of identification is often the core challenge of empirical economic research. The traditional approach to identification is to bring in additional information in the form of identifying assumptions, such as restrictions that certain magnitudes have to be zero. In this paper, we suggest that what are usually thought of as identifying assumptions should more generally be described as information that the analyst had about the economic structure before seeing the data. Such information is most naturally represented as a Bayesian prior distribution over certain features of the economic structure.
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Більше джерел

Дисертації з теми "Nonlinear Structural Vector AutoRegressions"

1

Schlaak, Thore [Verfasser]. "Essays on Structural Vector Autoregressions Identified Through Time-Varying Volatility / Thore Schlaak." Berlin : Freie Universität Berlin, 2019. http://d-nb.info/1202996515/34.

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2

Pereira, Manuel Bernardo Videira Coutinho Rodrigues. "Effects of fiscal policy: measurement issues and structural change." Doctoral thesis, Instituto Superior de Economia e Gestão, 2011. http://hdl.handle.net/10400.5/3431.

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Doutoramento em Economia
Considerable uncertainty surrounds the macroeconomic effects of fiscal policy. The re-search presented in this dissertation firstly aims at improving on the methods used to measure such effects - which feature vector autoregressions (VARs) as the basic tool. The investigation is partly carried out using structural VARs. The methodological innova¬tions in that part concern the joint identification of fiscal shocks vis-a-vis monetary policy shocks and the estimation of a model with time-varying parameters using a non-recursive identification scheme. I also use reduced-form VARs to assess the effects of a novel shock measure, derived from budget forecasts, that is arguably free of anticipatory movements. The second aim of the dissertation is to present empirical results for the US, focusing on the way the impacts of the government budget on the economy have changed over time. The thesis is divided into three essays. In the first one, I present evidence that taxes and transfers were the most important force attenuating the severity of recessions up to the eighties, surpassing the role of monetary policy. Fiscal policy has, however, become less effective in stimulating output in the course of the last decades. The findings in the second and the third essays corroborate this conclusion. Such a change in effectiveness is particularly marked for the shock measure that is relatively unaffected by anticipation, which features multipliers with non-conventional signs in the recent period. In general, these findings call for more research on the factors that intervene in the transmission mechanism of fiscal policy and can bring about important variation in its impacts.
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3

Azarskov, V. N., O. U. Kurganskyi, O. V. Ermolaeva, and G. I. Rudyuk. "Structural Identification Algorithm Based on Results of Multidimensional Nonlinear Stabilization Plant Test." Thesis, Kyiv, "Osvita Ukrainy", 2015. http://er.nau.edu.ua/handle/NAU/28365.

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4

Figueres, Juan Manuel. "Nonlinear Effects of Macroeconomic Shocks." Doctoral thesis, Università degli studi di Padova, 2016. http://hdl.handle.net/11577/3421777.

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Анотація:
This thesis investigates the nonlinear macroeconomic effects of fiscal and uncertainty shocks. It comprises three contained chapters, each one of them being self-contained. In each chapter, theoretical predictions coming from theoretical models are presented and discussed. Such predictions are then tested using state-of-the-art econometric techniques. The first chapter is titled “News in State-Dependent Fiscal Multipliers: The Role of Confidence”. This study scrutinizes the role of consumer confidence in determining the real effects that unanticipated (news) government spending shocks have on output in recessions and expansions by estimating a Smooth-Transition VAR model. To account for fiscal foresight, I employ a measure of anticipated fiscal shocks defined as the sums of expectations’ revisions over future fiscal spending. This variable is shown to carry relevant information about movements on government spending. My results indicate that fiscal multipliers during recession is both statistically larger than in expansions and greater than one. Importantly, consumer confidence is shown to play a decisive role on determining the effects of an anticipated spending shock within nonlinear framework. In particular, the response of confidence is key in explaining the statically larger fiscal multiplier during recessions. Moreover, the role of confidence is found to be relevant for the transmission of anticipated shocks only. These results qualify confidence as a key ingredient for understanding the transmission of fiscal news shocks (as opposed to unanticipated fiscal shocks). The second chapter is titled “Fiscal-Monetary Policy Mix in Recessions and Expansions”. This study investigates the role of monetary policy in determining the size of the fiscal spending multiplier in recessions and expansions as for the U.S. economy. To this end, I quantify the size of state-dependent fiscal multipliers by using a nonlinear VAR model endowed with fiscal and monetary variables. I carefully separate anticipated and unexpected fiscal spending shocks by jointly modeling fiscal spending and the measure of spending news proposed by Ramey (2011 QJE). My results indicate that the fiscal multiplier in recessions is larger than one and statistically different from that corresponding to expansions. Importantly, the role of monetary policy during recessions triggers a crowding out effect. In particular, a counterfactual exercise clearly have the role played for the systematic policy to emerge. These findings highlight the importance of jointly consider monetary and fiscal indicators when studying the effects of a fiscal stimulus. The third chapter titled “Economic Policy Uncertainty Spillovers in Booms and Busts” is joint paper with Giovanni Caggiano and Efrem Castelnuovo. This study aims at quantifying the impact of economic policy uncertainty shocks originating in the U.S. on the Canadian business cycle in booms and busts. It does so by employing a nonlinear Smooth-Transition VAR model to identify and simulate an increase in the U.S. economic policy uncertainty on a number of Canadian macroeconomics variables, including real activity indicators (industrial production and unemployment), inflation, a short-term interest rate, and the bilateral exchange rate. Our results point to statistically and economically relevant nonlinear spillover effects. Uncertainty shocks originated in the U.S. explain about the 27% of the variance of the 2-years ahead forecast error of the Canadian unemployment rate in periods of slack vs. 8% during economic booms. Counterfactual simulations lead to the identification of a novel “economic policy uncertainty spillovers channel”. According to this channel, spikes in the U.S. economic policy uncertainty foster economic policy uncertainty in Canada in first place and, because of the latter, an increase in the Canadian rate of unemployment occurs.
La tesi analizza gli effetti macroeconomici nonlineari di shock fiscali e di incertezza. Essa comprende tre capitoli, ciascuno dei quali è independente dagli altri. In ciascun capitolo, le predizioni teoriche derivanti da modelli macroeconomici vengono presentate e discusse. Tali predizioni sono poi testate empiricamente utilizzando tecniche econometriche all'avanguardia. Il primo capitolo si intitola “News in State-Dependent Fiscal Multipliers: The Role of Confidence”. Questo studio analizza il ruolo giocato dalla fiducia dei consumatori nella determinazione degli effetti reali che shock di spesa pubblica non previsti hanno sul livello della produzione in recessione e in espansione utilizzando un modello vettoriale autoregressivo “Smooth-Transition”. Per tenere conto degli effetti di anticipazione sulla politica fiscale, utilizzo una misura di shock fiscali previsti, definita come la somma delle revisioni delle aspettative circa il livello futuro della spesa pubblica. Questa variabile risulta possedere rilevanti informazioni circa variazioni future effettive della spesa pubblica. I miei risultati indicano che il moltiplicatore fiscale durante le fasi recessive è statisticamente più elevato rispetto alle fasi espansive, oltre a essere maggiore di uno. In maniera importante, i risultati mostrano come il livello della fiducia dei consumatori giochi un ruolo decisivo nel determinare gli effetti di uno shock fiscale non previsto all’interno di un contesto non-lineare. In particolare, la risposta del livello di fiducia è cruciale nello spiegare la differenza statistica trovata in recessione. Inoltre, il ruolo del livello della fiducia è rilevante per la trasmissione soltanto degli shock previsti di politica fiscale. Questi risultati qualificano il livello di fiducia come un fattore determinante nel comprendere la trasmissione di shock fiscali previsti (a differenza degli shock fiscali non previsti). Il secondo capitolo si intitola “Fiscal-Monetary Policy Mix in Recessions and Expansions”. Questo lavoro analizza il ruolo della politica monetaria nella determinazione della grandezza dei moltiplicatori fiscali in recessione e in espansione per l’economia degli Stati Uniti. A questo scopo, quantifico i moltiplicatori fiscali utilizzando un modello VAR non lineare che include variabili sia fiscali che monetarie. Per separare gli shock fiscali anticipati da quelli non anticipati, utilizzo sia variabili di spesa pubblica che la misura di “news” fiscale proposta da Ramey (2011 QJE). I miei risultati indicano che il moltiplicatore fiscale in recessione è maggiore di uno e statisticamente differente da quello che si ottiene in espansione. In maniera importante, il ruolo della politica monetaria in recessione comporta un effetto spiazzamento. In particolare, un esercizio controfattuale mostra in maniera chiara come emerga il ruolo giocato dalla politica monetaria. Questi risultati sottolineano l’importanza di considerare in maniera congiunta indicatori fiscali e monetari per analizzare gli effetti di politiche fiscali espansive. Il terzo capitolo intitolato “Economic Policy Uncertainty Spillovers in Booms and Busts” è un lavoro congiunto con Giovanni Caggiano e Efrem Castelnuovo. Questo lavoro ha come obiettivo la quantificazione dell’impatto di shock di incertezza politico-economica che hanno origine negli USA sull’andamento del ciclo economico canadese in recessione e in espansione. A tal fine, utilizziamo un modello vettoriale autoregressivo “Smooth-Transition” per identificare e analizzare gli effetti di un aumento del livello di incertezza economico-politica negli USA su una serie di variabili macroeconomiche canadesi, inclusi indicatori del livello dell’attività economica (produzione industriale e tasso di disoccupazione), tasso di inflazione, tasso di interesse a breve termine, e tasso di cambio bilaterale. I nostri risultati mostrano che ci sono effetti contagio non lineari rilevanti sia da un punto di vista statistico che economico. Gli shock di incertezza che hanno origine negli USA spiegano in recessione circa il 27% della varianza dell’errore di previsione a due anni del tasso di disoccupazione canadese, contro un valore pari a 8% in fasi di boom economico. Simulazioni controfattuali identificano un nuovo canale di contagio dell’incertezza economico-politica. In base a esso, aumenti del livello di incertezza economico-politica negli USA provocano in primo luogo un aumento del livello di incertezza in Canada e, per questo tramite, un aumento del tasso di disoccupazione canadese.
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5

Pellegrino, Giovanni. "Uncertainty and Monetary Policy: Assessing their Nonlinear Interactions." Doctoral thesis, 2016. http://hdl.handle.net/11562/936395.

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Questa tesi esamina le interazioni tra l'incertezza e la politica monetaria mediante l'utilizzo di metodi econometrici non lineari. Si compone di tre capitoli distinti. Il primo capitolo si occupa degli effetti degli stimoli inattesi (shock da ora in avanti) di politica monetaria condizionali a diversi livelli di incertezza. Sulla base della letteratura teorica, diverse spiegazioni si pensa siano in grado di ridurre l'efficacia della politica monetaria in tempi incerti (ad esempio, l'esistenza di opzioni reali, un differente comportamento price-maker delle imprese e un maggiore risparmio precauzionale). Al fine di valutare empiricamente le supposizioni teoriche si stima un modello Interacted-VAR non lineare dove, in maniera innovativa rispetto alla letteratura, si modella la variabile condizionante - un indicatore di incertezza nel mio caso - endogenamente nel VAR. Questo implica la necessità di adottare le funzioni di risposta generalizzate (GIRFs, dall'inglese Generalized Impulse Response Functions) à la Koop et al. (1996). I risultati suggeriscono che gli shock di politica monetaria sono significativamente meno efficaci in tempi incerti, con le reazioni di picco di diverse variabili reali circa due terzi più lievi di quelle durante i periodi tranquilli. Trovo anche che l'incertezza diminuisce dopo uno shock di politica monetaria espansiva. Inoltre, mostro che, coerentemente con i risultati teorici di Vavra (2014), la reazione dei prezzi risulta più grande durante i periodi di maggiore incertezza a livello di impresa. Il secondo capitolo (lavoro congiunto con G. Caggiano e E. Castelnuovo) si interessa dell'impatto di aumenti inattesi (shock) di incertezza in presenza di un tasso di interesse a breve periodo pari a zero (in breve ZLB, dall'inglese zero lower bound), una situazione in essere negli Stati Uniti a partire dal dicembre 2008. Diversi recenti studi teorici suggeriscono che, in questa evenienza, gli shock di incertezza dovrebbero generare un calo molto più grande e persistente dell'attività reale (si veda Fernandez-Villaverde et al. (2015), Johannsen (2013), Nakata (2013), and Basu and Bundick (2014, 2015)). Tuttavia, sul lato empirico, non è stata ancora proposta alcuna analisi che modelli esplicitamente la non linearità degli effetti reali degli shock di incertezza dovuta allo ZLB. A questo scopo, ci si avvale di un parsimonioso modello Interacted-VAR non lineare allo scopo di valutare empiricamente le predizioni teoriche. I risultati mostrano che gli effetti recessivi degli shock di incertezza sono statisticamente maggiori in presenza dello ZLB, con differenze che sono economicamente importanti. Si mostra che tali differenze non sono dovute al verificarsi contemporaneo della Great Recession. Il terzo capitolo ritorna sull'argomento del capitolo 1, con l'obiettivo di indagare sulle ragioni strutturali alla base della minore efficacia degli shock di politica monetaria durante i tempi incerti. A questo scopo si adotta un affermato modello DSGE (dall'inglese Dynamic Stochastic General Equilibrium) Neo-Keynesiano. In particolare, si propone una semplice strategia econometrica per stimare con metodo Minimum Distance il modello DSGE condizionalmente a due regimi identificati sulla base dei dati per mezzo di modello Threshold VAR. Questa strategia poi si applica al modello di Altig, Christiano, Eichenbaum e Lindé (ACEL, 2011). Si trova che il modello di ACEL risulta essere notevolmente in grado di eguagliare le risposte del VAR, soprattutto in tempi tranquilli. Questa performance è guidata da dei valori stimati per alcuni parametri strutturali del tutto differenti tra i due regimi. In particolare, una maggiore pendenza della curva di Phillips Neo-Keynesiana, un maggior costo per variare il tasso di utilizzo del capitale, e un minore grado di abitudini nel consumo sono i principali driver della capacità del modello di predire inferiori effetti reali degli shock di politica monetaria in periodi di elevata incertezza.
This thesis assesses the interactions between uncertainty and monetary policy by means of nonlinear econometric methods. It consists of three separate chapters. The first chapter is concerned with the effects of monetary policy shocks conditional on different levels of uncertainty. On the basis of the theoretical literature, several explanations are thought to be able to reduce the effectiveness of monetary policy during uncertain times (e.g., real option effects, …firm-price setting behavior and precautionary savings). In order to empirically assess theoretical predictions I estimate a nonlinear Interacted VAR model, where, in a novel way with respect to the literature, I model the conditioning indicator - uncertainty, in my case, which discriminate "high" from "low" uncertainty states - endogenously in the VAR. This implies the necessity to adopt the Generalized Impulse Response Functions à la Koop, Pesaran and Potter (1996). This strategy enables me to consider both the possible endogenous reaction of uncertainty to the policy shock and its feedbacks on the dynamics of the system. My findings suggest that monetary policy shocks are significantly less effective during uncertain times, with the peak reactions of a battery of real variables being about two-thirds milder than those during tranquil times. I also find that uncertainty decreases after an expansionary monetary policy shock. Further, I show that, consistently with Vavra's (2014) predictions, the reaction of prices appears greater during firm-level uncertain times. The second chapter (coauthored with G. Caggiano and E. Castelnuovo) is concerned with the impact of uncertainty shocks at the zero lower bound (ZLB), which has been hit since December 2008 in the U.S. On the theoretical side, several recent studies suggest that when monetary policy is constrained by the ZLB, uncertainty shocks should generate a much larger and persistent drop in real activity (see Fernandez-Villaverde, Guerron-Quintana, Kuester, and Rubio-Ramirez (2015), Johannsen (2013), Nakata (2013), and Basu and Bundick (2014, 2015)). However, on the empirical side, no analysis explicitly modeling the nonlinearity of the real effects of uncertainty shocks due to the ZLB has been proposed so far. To this aim we employ a parsimonious nonlinear Interacted-VAR model to examine whether the real effects of uncertainty shocks are greater when the economy is at the ZLB. Our results show that the contractionary effects of uncertainty shocks are statistically larger when the ZLB is binding, with differences that are economically important. Such differences are shown not to be driven by the contemporaneous occurrence of the Great Recession. The third chapter returns on the argument of Chapter 1 with the aim of enquiring on the structural reasons behind the lower effectiveness of monetary policy shocks during uncertain times. To do so I adopt the lens of the workhorse New Keynesian model. In particular, I propose a simple state-conditional Minimum Distance estimation strategy of a DSGE model, which I apply to the Altig, Christiano, Eichenbaum and Lindè's (ACEL, 2011) model. The estimator matches as closely as possible the regime-dependent responses coming from an unrestricted Threshold VAR model with the corresponding model-based responses. This approach may capture possibly unmodelled mechanisms through regime-specific estimates of structural parameters. I find the ACEL model to be remarkably able to match the VAR impulse responses, particularly in tranquil times. This performance is driven by very different estimated values for some key-structural parameters in the two states. A higher slope of the new-Keynesian Phillips curve, a higher cost of the variation in capital utilization, and a lower degree of habit formation in consumption are shown to be behind the model ability to predict the lower real effects of monetary policy shocks in periods of high uncertainty.
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6

NETŠUNAJEV, Aleksei. "Structural vector autoregressions with Markov switching : identification via heteroskedasticity." Doctoral thesis, 2013. http://hdl.handle.net/1814/26775.

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Анотація:
Defence date: 27 March 2013
Examining Board: Professor Helmut Lütkepohl, DIW Berlin and Freie Universität (External Supervisor); Professor Fabio Canova, European University Institute; Professor Helmut Herwartz, Georg-August-Universität Göttingen; Professor Markku Lanne, University of Helsinki
Structural vector autoregressions are of great importance in applied macroeconometric work. The main di culty associated with structural analysis is to identify unique shocks of interest. In a conventional approach this is done via zero or sign restrictions. Heteroskedasticity is proposed for use in identi cation. Under certain assumptions when volatility of shocks changes over time, unique shocks can be obtained. Then formal testing of the restrictions and impulse response analysis can be performed. In this thesis I show how identi cation via heteroskedasticity can be used in di erent contexts. In the rst chapter I analyze the dynamics of trade balances in response to macroeconomic shocks. I show that identifying restrictions, which are known in the literature, are rejected for two out of seven countries. Partially identi ed models fail to provide enough information to fully identify shocks. The second chapter, coauthored with my supervisor, demonstrates how one can bene t from identi cation via heteroskedasticity when sign restrictions are used. The approach is illustrated with a model of the crude oil market. It is shown that shocks identi ed via previously known sign restrictions are in line with the properties of the data. Use of tighter restrictions uncovers that the approach can be discriminative. The third chapter reconsiders the con icting results in the debate on the e ects of technology shocks on hours worked. Using six ways of identifying technology shocks, I nd that not all of them are supported by the data. There is no clear-cut evidence in favor of positive reaction of hours to technology shocks. However, it is plausible for real wage and disentangled investment-speci c and neutral technology shocks, even though conventional identi cation of the latter shocks is rejected.
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7

Seymen, Atılım [Verfasser]. "Business cycle analysis with structural vector autoregressions : four applications / by Atılım Seymen." 2009. http://d-nb.info/1000197395/34.

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8

Tai, Ru Yuh, and 戴如育. "NONLINEAR STRUCTURAL OPTIMIZATION ON THE VECTOR AND PARALLEL SUPERCOMPUTER." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/21297933897859596164.

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碩士
國立中山大學
機械工程研究所
82
The purpose of this study is to investigate the optimum design of geometrically nonlinear structure by means of multilevel optimization method with sensitivity analysis. In this study the tangent stiffness method is used to solve the nonlinear problem. The Jacobian conjugate gradient, an iterative solution algorithm, is employed to promote the performance of finite element analysis for structure. The proposed solution procedures are programmed in FORTRAN for implementation on vector-parallel supercomputer CONVEX C3840. The difference of weight optimum design between linear elasticity and considering the geometrical nonlinearity behavior from large displacements are discussed. The suitable tolerances for tangent stiffness method and Jacobian conjugate method are proposed. And the results of examples are presented. Further discussion and suggestions for the results are also stated.
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9

Nodari, Gabriela Thais. "Uncertainty, Fiscal, and Financial Shocks in a Nonlinear World: Empirical Investigations." Doctoral thesis, 2015. http://hdl.handle.net/11562/909410.

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Questa tesi studia gli effetti macroeconomici degli shock di incertezza, shock fiscali e shock finanziari sul ciclo economico USA. La tesi si divide in quattro capitoli indipendenti, ognuno dei quali utilizza sistemi vettoriali autoregressivi, lineari e non-lineari, e local projections, al fine di estendere la ricerca empirica e valutare l’importanza dei diversi canali di trasmissione degli shock, così come proposti da modelli teorici. I risultati ottenuti dimostrano come tali shock hanno effetti non-lineari lungo il ciclo economico, e cioè la reazione delle variabili macroeconomiche è statisticamente differente se lo shock avviene durante una recessione piuttosto che durante un’espansione. Dalla prospettiva teorica, questi risultati sottolineano l’importanza di sviluppare modelli teorici non-lineari. Dalla prospettiva di politica economica, i risultati favoriscono l’implementazione di politiche asimmetriche come risposta a instabilità a livello macroeconomico.
This thesis investigates the macroeconomic effects of uncertainty, fiscal and financial shocks on the US economy. It is set out in four self-contained chapters, which use linear and nonlinear (Smooth Transition) Vector Autoregressive models, and Local Projections techniques, to extend the literature, and evaluate the importance of different transmission channels of macroeconomic shocks suggested by theoretical models. The main results show that these shocks have nonlinear effects over the business cycle, i.e., the response of macro aggregates following the shocks are statistically different depending on whether the economy is in a recession or expansion. From a theoretical perspective, this finding highlights the importance of accounting for nonlinearities when developing macroeconomic models. From a policy perspective, the results suggest the implementation of nonlinear policy rules to properly deal with macroeconomic instability.
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10

Σαλαμαλίκη, Παρασκευή. "Μελέτες στην εφαρμοσμένη μακροοικονομετρία : Αιτιότητα κατά Granger σε πολλαπλούς ορίζοντες και μη-γραμμικές τάσεις σε μακροοικονομικές χρονολογικές σειρές". Thesis, 2013. http://hdl.handle.net/10889/6542.

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Η παρούσα διατριβή ασχολείται με δύο ιδιαιτέρως σημαντικά και διαχρονικά επίκαιρα ζητήματα στην ανάλυση χρονολογικών σειρών, τα οποία εντάσσονται, υπό ευρεία έννοια, στο πεδίο της Μακροοικονομετρίας. Ειδικότερα, μελετώνται θέματα και μεθοδολογίες ή τεχνικές ιδιαίτερα χρήσιμες για εκείνους τους ερευνητές, οι οποίοι επικεντρώνονται στην ανάλυση της συμπεριφοράς των συναθροιστικών (aggregate) μεγεθών της οικονομίας, βασιζόμενοι στη χρήση δεδομένων χρονοσειρών ή πιο απλά χρονοσειρές (time series). Το πρώτο ζήτημα αφορά στη μελέτη της δυναμικής αλληλεξάρτησης ανάμεσα σε μακροοικονομικές μεταβλητές κάτω από την υιοθέτηση ενός πολλαπλού πλαισίου ανάλυσης χρονοσειρών. Το ενδιαφέρον εστιάζεται κυρίως στην γενικευμένη ή εκτεταμένη έννοια της αιτιότητας κατά Granger, δηλαδή στην επέκταση της τυπικής έννοιας της αιτιότητας κατά Granger σε μεγαλύτερους του ενός ή σε πολλαπλούς ορίζοντες πρόβλεψης. Το δεύτερο ζήτημα αφορά στην παρουσία μη-γραμμικών χαρακτηριστικών σε μακροοικονομικές χρονοσειρές, καθώς και την υποδειγματοποίηση της μη-γραμμικότητας με τη χρήση μη-γραμμικών οικονομετρικών μοντέλων. Επικεντρώνεται δε ιδιαίτερα στον έλεγχο μοναδιαίας ρίζας κάτω από την εναλλακτική υπόθεση της στασιμότητας γύρω από μη-γραμμικές τάσεις της μορφής τάσεων ομαλής μετάβασης (smooth transition trends) στις μακροοικονομικές χρονοσειρές. Ουσιαστικά, η διατριβή διακρίνεται σε δύο κεφάλαια. Στο Κεφάλαιο 1 παρουσιάζεται η τυπική έννοια της αιτιότητας κατά Granger, καθώς και η γενικευμένη ή εκτεταμένη έννοια της αιτιότητας ή η αιτιότητα σε πολλαπλούς ορίζοντες (multi-horizon causality), στο πλαίσιο των διανυσματικών αυτοπαλίνδρομων υποδειγμάτων (VAR). Η τυπική έννοια της αιτιότητας κατά Granger περιορίζεται στη βελτίωση της προβλεψιμότητας σε ορίζοντα πρόβλεψης μίας περιόδου (one-step ahead), ενώ λαμβάνει υπ'όψιν μόνο τις άμεσες ροές πληροφόρησης μεταξύ των μεταβλητών ενδιαφέροντος (direct causality). Ωστόσο, σε υποδείγματα VAR με περισσότερες από δύο μεταβλητές η τυπική έννοια της αιτιότητας μπορεί να επεκταθεί με την μελέτη της βελτίωσης της προβλεψιμότητας σε μεγαλύτερους του ενός ορίζοντες πρόβλεψης. Σε μία περίπτωση όπως η τελευταία, πλην της άμεσης αιτιότητας, δύνανται να μελετηθούν και οι έμμεσες σχέσεις αιτιότητας (indirect causality) που ενδέχεται να προκύψουν μέσω των πρόσθετων μεταβλητών του συστήματος. Το θεωρητικό πλαίσιο της γενικευμένης έννοιας της αιτιότητας που παρουσιάζει η παρούσα διατριβή έχει αναπτυχθεί από τους Dufour and Renault (1998). Παράλληλα, δίνεται ιδιαίτερη βαρύτητα σε δύο πρόσφατες μεθόδους στατιστικής επαγωγής αιτιωδών σχέσεων κατά Granger σε πολλαπλούς ορίζοντες, οι οποίες παρέχουν πρόσθετη πληροφόρηση σχετικά με τη δυναμική αλληλεξάρτηση οικονομικών χρονοσειρών, και πιο συγκεκριμένα σχετικά με τον άμεσο ή έμμεσο χαρακτήρα των αιτιωδών σχέσεων, το διαχωρισμό μεταξύ βραχυχρόνιας και μακροχρόνιας (μη)-αιτιότητας, καθώς και τις πιθανές χρονικές υστερήσεις της αιτιότητας. Τέλος, στα πλαίσια του Κεφαλαίου 1, ερευνάται η δυνατότητα εφαρμογής των μεθόδων αυτών μέσω εμπειρικών εφαρμογών πάνω σε δύο διαχρονικά ζητήματα αιτιωδών σχέσεων ανάμεσα σε οικονομικές μεταβλητές. Στο Κεφάλαιο 2 παρουσιάζονται υποδείγματα ομαλής μετάβασης, καθώς και έλεγχοι μοναδιαίας ρίζας οι οποίοι επιτρέπουν την στασιμότητα γύρω από ομαλές ή βαθμιαίες μεταβάσεις κάτω από την εναλλακτική υπόθεση. Κύριο χαρακτηριστικό των υποδειγμάτων ομαλής μετάβασης είναι η παρουσία μη-γραμμικών τάσεων στη διαχρονική εξέλιξη των χρονοσειρών. Κεντρικό ρόλο στα υποδείγματα αυτά κατέχουν οι διαρθρωτικές μεταβολές (structural changes) στην προσδιοριστική τάση, οι οποίες, δεδομένου ότι αντιπροσωπεύουν μεταβολές της συναθροιστικής συμπεριφοράς, υποδειγματοποιούνται με τη χρήση ενός προσδιοριστικού στοιχείου το οποίο επιτρέπει την βαθμιαία αντί της στιγμιαίας προσαρμογής. Οι έλεγχοι μοναδιαίας ρίζας, οι οποίοι επιτρέπουν περισσότερη ευελιξία στην συνάρτηση της τάσης σε σχέση με την γραμμική εξειδίκευση της προσδιοριστικής τάσης που χρησιμοποιούν οι τυπικοί έλεγχοι μοναδιαίας ρίζας, αποτελούν το επίκεντρο μελέτης του Κεφαλαίου 2 της διατριβής. Η αναγκαιότητα υιοθέτησης πρόσθετων ελέγχων μοναδιαίας ρίζας, όπως οι έλεγχοι μοναδιαίας ρίζας οι οποίοι επιτρέπουν στασιμότητα γύρω από ομαλές μεταβάσεις κάτω από την εναλλακτική υπόθεση, ισχυροποιείται από τα αποτελέσματα της εφαρμογής των ελέγχων αυτών σε ένα σύνολο οικονομικών χρονοσειρών.
This thesis discusses two central research topics in applied time series econometrics that generally belong in the field of Macroeconometrics. In particular, we investigate issues and methods which are of interest to those researchers who want to analyze economic problems or economic aggregates by means of time series data. The first topic deals with the dynamic interrelationships between sets of theory related variables in a multiple time series context. Research interest is primarily focused on the generalized or extended notion of Granger causality, that is the extension of the standard Granger causality concept to higher forecast horizons. The second topic deals with nonlinear behavior of macroeconomic time series, as well as the modelling of nonlinearities in economic time series using nonlinear econometric models. Specific attention is paid to unit root tests that allow stationarity around nonlinear trends in the form of smooth transitions under the alternative. The dissertation consists of two chapters. The first chapter presents the standard concept of Granger causality, along with the generalized or extended notion of causality, also known as multiple-horizon causality, in the vector autoregressive (VAR) framework. The standard notion of Granger causality restricts prediction improvement to a forecast horizon of one period, while it considers only direct flows of information between the variables of interest. However, in VAR models with more than two variables, the concept of standard Granger causality can be extended by studying prediction improvement at forecast horizons greater than one. If this is the case, then, except for direct causality, indirect flows of information might be revealed through the additional variables of the system. The theoretical framework of the extended concept of causality which is presented in the present dissertation has been developed by Dufour and Renault (1998). In addition, special attention is paid to two recent methods for testing hypothesis of non-causality at various horizons which can provide further information on the dynamic interaction of time series, and more specifically on the direct or indirect nature of causal effects, the distinction between short-run and long-run (non)-causality, as wells as the possibility of causal delays. Finally, the potential implementation of these methods is examined through empirical applications on causality relations among different sets of economic variables. Chapter 2 presents smooth transition (STR) trend models, as well as unit root tests that allow stationarity around smooth transitions under the alternative. Smooth transition regression models presume the presence of nonlinear trends in the long-run evolution of time series. A key feature of these models is the presence of structural changes in the deterministic trend which, given that they represent changes in aggregate behavior (economic aggregates), are modelled through a deterministic component that permits gradual rather than instantaneous adjustment between regimes. Unit root tests that permit a more versatile trend function in the unit root procedure, rather than the standard linear trends, are the main concern of Chapter 2. The necessity of employing additional unit root tests, such as unit root tests that allow stationarity around smooth transitions under the alternative, becomes evident through the unit root test results that are observed in an application in a set of economic time series.
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Книги з теми "Nonlinear Structural Vector AutoRegressions"

1

Rubio-Ramírez, Juan Francisco. Markov-Switching structural vector autoregressions: Theory and application. [Atlanta, Ga.]: Federal Reserve Bank of Atlanta, 2005.

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2

Healy, Brian E. Applications of parallel and vector algorithms in nonlinear structural dynamics using the finite element method. Urbana, Ill: Dept. of Civil Engineering, University of Illinois at Urbana-Champaign, 1992.

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3

F, Knight Norman, and United States. National Aeronautics and Space Administration., eds. Nonlinear structural response using adaptive dynamic relaxation on a massively-parallel-processing system. [Washington, DC: National Aeronautics and Space Administration, 1994.

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4

United States. National Aeronautics and Space Administration., ed. Parallel-vector computation for structural analysis and nonlinear unconstrained optimization problems: Final report for the period ended June 15, 1990. Norfolk, Va: Old Dominion University Research Foundation, Dept. of Civil Engineering, College of Engineering & Technology, Old Dominion University, 1990.

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5

United States. National Aeronautics and Space Administration., ed. Parallel-vector computation for structural analysis and nonlinear unconstrained optimization problems: Final report for the period ended June 15, 1990. Norfolk, Va: Old Dominion University Research Foundation, Dept. of Civil Engineering, College of Engineering & Technology, Old Dominion University, 1990.

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6

Parallel-vector computation for structural analysis and nonlinear unconstrained optimization problems: Final report for the period ended June 15, 1990. Norfolk, Va: Old Dominion University Research Foundation, Dept. of Civil Engineering, College of Engineering & Technology, Old Dominion University, 1990.

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Частини книг з теми "Nonlinear Structural Vector AutoRegressions"

1

Fernández-Villaverde, Jesús, and Juan F. Rubio-Ramírez. "Structural Vector Autoregressions." In The New Palgrave Dictionary of Economics, 13228–31. London: Palgrave Macmillan UK, 2018. http://dx.doi.org/10.1057/978-1-349-95189-5_2633.

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2

Fernández-Villaverde, Jesús, and Juan F. Rubio-Ramírez. "Structural Vector Autoregressions." In The New Palgrave Dictionary of Economics, 1–5. London: Palgrave Macmillan UK, 2008. http://dx.doi.org/10.1057/978-1-349-95121-5_2633-1.

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3

Fernández-Villaverde, Jesús, and Juan F. Rubio-Ramírez. "Structural vector autoregressions." In Macroeconometrics and Time Series Analysis, 303–7. London: Palgrave Macmillan UK, 2010. http://dx.doi.org/10.1057/9780230280830_33.

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4

Brosowski, Bruno. "A Recursive Procedure for the Solution of Linear and Nonlinear Vector Optimization Problems." In Discretization Methods and Structural Optimization — Procedures and Applications, 95–101. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-83707-4_13.

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5

Stock, J. H., and M. W. Watson. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics." In Handbook of Macroeconomics, 415–525. Elsevier, 2016. http://dx.doi.org/10.1016/bs.hesmac.2016.04.002.

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6

"11.6. Vector Autoregressions and Structural Econometric Models." In Time Series Analysis, 324–36. Princeton University Press, 1994. http://dx.doi.org/10.1515/9780691218632-097.

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7

Lütkepohl, Helmut. "Identifying Structural Vector Autoregressions Via Changes in Volatility." In VAR Models in Macroeconomics – New Developments and Applications: Essays in Honor of Christopher A. Sims, 169–203. Emerald Group Publishing Limited, 2013. http://dx.doi.org/10.1108/s0731-9053(2013)0000031005.

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8

Lütkepohl, Helmut. "Identifying Structural Vector Autoregressions Via Changes in Volatility." In Var Models in Macroeconomics - New Developments and Applications: Essays in Honor of Christopher A. Sims, 169–203. Emerald Group Publishing Limited, 2014. http://dx.doi.org/10.1108/s0731-905320130000031005.

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9

Callot, Laurent A. F., and Anders Bredahl Kock. "Oracle Efficient Estimation and Forecasting With the Adaptive Lasso and the Adaptive Group Lasso in Vector Autoregressions." In Essays in Nonlinear Time Series Econometrics, 238–66. Oxford University Press, 2014. http://dx.doi.org/10.1093/acprof:oso/9780199679959.003.0010.

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10

Harding, Don, and Adrian Pagan. "Accounting for Observed Cycle Features with a Range of Statistical Models." In The Econometric Analysis of Recurrent Events in Macroeconomics and Finance. Princeton University Press, 2016. http://dx.doi.org/10.23943/princeton/9780691167084.003.0007.

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This chapter looks at observed features of the cycle in a variety of time series. It sets out these features for the United States and a number of other countries, and then asks whether these features can be replicated by the use of a particular statistical model—a linear autoregression. For such linear models it is possible to broadly account for the observed features using moments of the series for growth rates, and this strategy is employed in the chapter. It then uses a particular nonlinear statistical model to see if it can match all the features, and further looks at two other nonlinear models first dealt with in Chapter 4. The chapter concludes with an examination of whether the binary indicators summarizing the recurrent states can be used in the context of standard multivariate methods such as vector autoregressions. This turns out not to be straightforward owing to the nature of the binary variables.
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Тези доповідей конференцій з теми "Nonlinear Structural Vector AutoRegressions"

1

Xiao, Li, and Wenzhong Qu. "Nonlinear structural damage detection using support vector machines." In SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, edited by Tribikram Kundu. SPIE, 2012. http://dx.doi.org/10.1117/12.914688.

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2

Zhang, Jian, and Tadanobu Sato. "Linear and nonlinear structural identifications using the support vector regression." In Smart Structures and Materials, edited by Masayoshi Tomizuka, Chung-Bang Yun, and Victor Giurgiutiu. SPIE, 2006. http://dx.doi.org/10.1117/12.658419.

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3

BADDOURAH, MAJDI, and DUC NGUYEN. "GEOMETRIC ALLY NONLINEAR DESIGN SENSITIVlTY ANALYSIS ON PARALLEL-VECTOR HIGH-PERFORMANCE COMPUTERS." In 34th Structures, Structural Dynamics and Materials Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1993. http://dx.doi.org/10.2514/6.1993-1528.

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4

QIN, JIANGNING, CHUH MEI, and CARL GRAY, JR. "A vector unsymmetric eigenequation solver for nonlinear flutter analysis on high-performance computers." In 32nd Structures, Structural Dynamics, and Materials Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1991. http://dx.doi.org/10.2514/6.1991-1169.

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5

Shen, Yanning, Brian Baingana, and Georgios B. Giannakis. "Topology inference of directed graphs using nonlinear structural vector autoregressive models." In 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2017. http://dx.doi.org/10.1109/icassp.2017.7953411.

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6

Kumar, Nishant, and Thomas D. Burton. "On Combined Use of POD Modes and Ritz Vectors for Model Reduction in Nonlinear Structural Dynamics." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-87416.

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An approach to develop Proper Orthogonal Decomposition (POD) based reduced order models for systems with local nonlinearities is presented in this paper. This technique is applied to multi-degree of freedom systems of coupled oscillators with isolated nonlinear elements. Typically, reduced order models are obtained using POD modes exclusively. In this work, we explore the suitability of using a combination of POD modes and other physically based “Ritz vectors” to produce the reduced model. The objectives are 1). to improve the accuracy of the reduced order differential equation model and 2). to expand the range of system parameters for which the reduced basis provides reasonably accurate approximations. The “Ritz vectors” used in this work are static displacement vectors that are calculated in one of the following three ways: 1). “Load – based Ritz vectors” [1, 2, 7, 8, 12, 16–18] – This is the static displacement vector due to a static loading that is proportional to the static version of the actual (assumed dynamic) loading to which the structure is subjected. 2). “Milman – Chu vectors” [3] – This is the static Ritz vector due to the imposition of equal and opposite static loads on the two masses to which the non-linear element is connected. The loading used to generate the first M – C vector is dictated by the location of the non-linearity. 3). “K – B (Kumar – Burton) vector” – This is a new Ritz vector defined in the spirit of the Milman – Chu vector. The K – B vector is the static displacement vector due to the imposition of a). equal and opposite static loads on the two masses to which the nonlinear element is connected (i.e. same as M – C loading) and b). equal and opposite static loads on the nearest neighbors. Thus, four masses are statically loaded. As for the M – C vector, the K – B loading is dictated by the location of the nonlinear element. The nonlinear model is numerically integrated to generate a full ODE model solution, which we call the “baseline solution”. We select a set of POD modes of the baseline nonlinear system response as basis functions. The POD modes are then augmented by various combinations of the three aforementioned Ritz vectors to generate reduced order models for system having parameters in vicinity of baseline system parameters. Our results indicate that the K – B augmentation vector combined with the Milman – Chu vector is an effective way to account for nonlinear effects for the system considered. The use of combined M – C/K – B augmentation also expands the range of system parameters for which the baseline POD modes provide accurate reduction. This is considered to be a significant result.
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7

Li, Yilun, Shuangxi Guo, Yue Kong, Min Li, and Weimin Chen. "Non-Linearly Restoring Performance and its Hysteresis Behavior of Dynamic Catenary." In ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/omae2019-95651.

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Abstract Catenary is increasingly used as mooring-line and riser system as the water depth gets larger due to its lower cost and easier installment. Its dynamic response and restoring performance become more complicated, as the length of the mooring-line become larger, and the structural and fluid dynamics the mooring-line become consequently more obvious. Compared to the quasi-static method where the static restoring force is mainly involved, the dynamic behaviors and its hysteresis of the catenary mooring-line are considered here so as to comprehensively examine the non-linearly restoring performance of mooring-lines. Based on the 3d dynamic vector equations along with the modified FEM simulations, the hysteresis character of the restoring stiffness and the influences of the catenary dynamics on its restoring performance are presented and discussed. It is found that, principally owing to the damping and inertial effect coming from the fluid and structural dynamics, the restoring force of the mooring-line depends on both the structural displacement and velocity. Moreover, the dynamic stiffness behaves as a hysteresis loop, instead of a curve. Our numerical results show that the energy consumption during one period rises nonlinearly with the increase of the body frequency ωd and amplitude A0. And, the influence of nonlinear restoring stiffness on the structural response along with the slack-taut phenomenon caused by structural /hydrodynamic inertia and damping is discussed.
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8

Guo, Shuangxi, Yilun Li, Min Li, Weimin Chen, and Yue Kong. "Dynamic Response Analysis on Flexible Riser With Different Configurations in Deep-Water Based on FEM Simulation." In ASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/omae2018-77838.

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For case of oil/gas exploitation and mining in deep water, the length of riser is pretty large and, consequently, it brings huge challenges in both offshore installation and production operations and results in significant cost elevation due to the factors such as extreme tension loads induced from riser suspended self-weight and large structural flexibility. Therefore, there are several alternative riser configurations, e.g. lazy wave, hybrid tower and lazy-wave riser beside free hanging catenary, which have been proposed. In this paper, the dynamic characteristics and responses of several risers with typical configurations are considered and compared with each other based on our numerical simulations. Firstly, the nonlinear dynamic model of the riser systems are developed based on our 3d dynamic riser equations along with the modified FEM simulations. Then the dynamic response is analyzed based on our 3d curved flexible beam approach where the structural curvature changes with its spatial position and time in terms of vector equations. Compared with the linear approach, the nonlinear FEM method is used so as to consider large displacement/deformation, configuration geometry and structural stiffness changing with body motion. Moreover, the hydrodynamic force is considered as being related to body motion too. Based on the FEM numerical simulations, the influences of the amplitude/frequency of the top vessel motion along with the buoyancy modules/tower distribution along structural length on riser’s dynamic responses, in terms of the temporal-spatial evolution of displacement, curvature/bending stress and dynamic tension, are studied for different riser’s configurations. Our results show that the dynamic responses, particularly the maximum top tension, of different riser systems significantly change. Among the examined riser configurations, the response of the riser with more buoyancy modules may have lower value, and buoyancy distribution along structural length can influence the top tension and curvature.
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9

Luo, Weilin, Bin Fu, Carlos Guedes Soares, and Zaojian Zou. "Robust Control for Ship Course-Keeping Based on Support Vector Machines: Particle Swarm Optimization and L2-Gain." In ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/omae2013-11076.

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To achieve a robust autopilot for ship course-keeping, a controller based on support vector machines (SVM) and L2-gain is proposed. A cascaded plant consists of a nonlinear ship response model and the rudder actuator dynamics. Uncertainties including modeling errors and external disturbances are taken into account in the response model. SVM is applied to identify the complicated nonlinear dynamics including the modeling errors, while L2-gain design is used to suppress the uncertain disturbances. To obtain the optimized structural parameters in SVM, particle swarm optimization (PSO) method is incorporated. Stability analysis and simulation results demonstrate the validity of the proposed control scheme.
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10

Nguyen, Son Hai, and David Chelidze. "Characteristic Lengths and Distances: Fast and Robust Features for Nonlinear Time Series." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-71281.

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Estimation of most of the metrics used to characterize dynamical systems’ output require fairly long time series (e.g., Lyapunov Exponents, Fractal Dimensions), or substantial computational resources (e.g., phase space warping metrics, sensitivity vector fields). In many practical applications, when there is abundance of data (e.g., in Atomic Force Microscopy) fast and simple features are needed, and when there is sparsity of data (e.g., in many Structural Health Monitoring situations) robust features are needed. Here, we propose a new class of features based on Birkhoff Ergodic Theorem, which are fast to calculate and do not require large data or computational resources. Applications of these metrics, in conjunction with the smooth orthogonal decomposition, to identifying underlying processes causing nonstationarity both in simulations and actual experiments are demonstrated.
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Звіти організацій з теми "Nonlinear Structural Vector AutoRegressions"

1

Ludvigson, Sydney, Sai Ma, and Serena Ng. Shock Restricted Structural Vector-Autoregressions. Cambridge, MA: National Bureau of Economic Research, March 2017. http://dx.doi.org/10.3386/w23225.

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2

Baumeister, Christiane, and James Hamilton. Advances in Structural Vector Autoregressions with Imperfect Identifying Information. Cambridge, MA: National Bureau of Economic Research, April 2020. http://dx.doi.org/10.3386/w27014.

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3

Baumeister, Christiane, and James Hamilton. Sign Restrictions, Structural Vector Autoregressions, and Useful Prior Information. Cambridge, MA: National Bureau of Economic Research, December 2014. http://dx.doi.org/10.3386/w20741.

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4

Baumeister, Christiane, and James Hamilton. Drawing Conclusions from Structural Vector Autoregressions Identified on the Basis of Sign Restrictions. Cambridge, MA: National Bureau of Economic Research, January 2020. http://dx.doi.org/10.3386/w26606.

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5

Read, Matthew. Estimating the Effects of Monetary Policy in Australia Using Sign-restricted Structural Vector Autoregressions. Reserve Bank of Australia, January 2023. http://dx.doi.org/10.47688/rdp2022-09.

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Existing estimates of the macroeconomic effects of Australian monetary policy tend to be based on strong, potentially contentious, assumptions. I estimate these effects under weaker assumptions. Specifically, I estimate a structural vector autoregression identified using a variety of sign restrictions, including restrictions on impulse responses to a monetary policy shock, the monetary policy reaction function, and the relationship between the monetary policy shock and a proxy for this shock. I use an approach to Bayesian inference that accounts for the problem of posterior sensitivity to the choice of prior that arises in this setting, which turns out to be important. Some sets of identifying restrictions are not particularly informative about the effects of monetary policy. However, combining the restrictions allows us to draw some useful inferences. There is robust evidence that an increase in the cash rate lowers output and consumer prices at horizons beyond a year or so. The results are consistent with the macroeconomic effects of a 100 basis point increase in the cash rate lying towards the upper end of the range of existing estimates.
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6

Baumeister, Christiane J. S., and James Hamilton. Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Demand Shocks. Cambridge, MA: National Bureau of Economic Research, December 2017. http://dx.doi.org/10.3386/w24167.

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7

Baumeister, Christiane, and James Hamilton. Inference in Structural Vector Autoregressions When the Identifying Assumptions are Not Fully Believed: Re-evaluating the Role of Monetary Policy in Economic Fluctuations. Cambridge, MA: National Bureau of Economic Research, May 2018. http://dx.doi.org/10.3386/w24597.

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8

A note on global identification in structural vector autoregressions. Cemmap, лютий 2021. http://dx.doi.org/10.47004/wp.cem.2021.0321.

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