Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 106 for “"autoregression"”.
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Nonlinear network vector autoregression
As we all know, the time series model is one of the most important aspects of modern econometric analysis. The autoregressive model is the theoretical basis of time series. The classic autoregressive model has two features that can be improved, linear, and one-dimensional. Economic theory shows …
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Quantile autoregression with censored data
Quantile autoregression (QAR) provides an alternative way to study asymmetric dynamics and local persistence in time series. It is particularly attractive for censored data, where the classical autoregressive models are unidentifiable without further parametric assumptions on the distributions. …
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Modified Burg algorithms for multivariate subset autoregression
… method for recursive modeling of univariate autoregressions on a full set of lags, to multivariate modeling on a subset of lags. The key step in the algorithm involves minimizing the sum of the norm of the forward and backward prediction error residual vectors, as a function of the reflection …
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An improved method for estimating the moderator temperature coefficient of pressurized water reactors using multivariate autoregression
An improved method for evaluating the moderator temperature coefficient (MTC) of reactivity in pressurized water reactors based on a newly established technique is described. Previous work has correlated stochastic fluctuations in the reactor core-exit temperature with similar fluctuations in the …
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Three essays on long memory tests for persistence in volatility and structural vector autoregression modeling of real exchange rates
… three extends the structural vector autoregression model by incorporating cointegration effects. Using the method of Warne (1993), in a simple four-variable vector autoregression (VAR) characterized by cointegration, the response of real exchange rates to various economic shocks are …
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A New State Transition Model for Forecasting-Aided State Estimation for the Grid of the Future
… angles and magnitudes) is modeled by using autoregression, while the spatial correlation among the system states (i.e. voltage angles) is modeled using vector autoregression. Simulation results show significant improvement in power system state forecasting accuracy especially in presence of …
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Time series analysis of macroeconometric constructs
… representation is found for a bivariate vector autoregression for log U.S. GNP and unemployment rates. It is found that there is considerable uncertainty about both the persistence of the permanent component and the implied univariate persistence for even lightly parameterized vector …
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Estimating elasticities of demand and supply for South African manufactured exports using a vector error correction model
… are estimated using the co-integrating vector autoregression / vector error correction model approach in order toaddress simultaneity and non-stationarity issues. Demand is highly price-elastic, ranging from-3 to -6. The price elasticity of supply is 1. Competitors' prices and world income are …
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The role of financial sector development in economic growth : case study of Botswana
… techniques such as the cointegration vector autoregression approach.
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On Explosive Time Series
… framework using a bivariate coexplosive vector autoregression as in Nielsen (2010). Firstly, we apply a co-explosive vector autoregression to model whether the WTI crude oil price run-up of 2007-2008 can be attributed to the existence of a bubble as well as whether the WTI crude oil collapse of …
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Examining The Sustainability Of The Current Account Balance Using A Probability Approach
… models, including autoregressive model, vector autoregression, vector error correction model, bayesian vector autoregression and bayesian time-varying coefficient, applied to a diverse set of countries and data from 1980 to 2023. It examines the macroeconomic and global determinants of current …
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Essays in Applied Monetary and Financial Economics
… in particular, the factor-augmented vector autoregression, is very flexible. It can be used to analyze dynamic systems, allowing researchers to analyze micro-markets and extract conclusions about their agents. This thesis presents (i) a quantitative assessment of the heterogeneous effects of …
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Robust Inference in Multiple Nonstationary Time Series
… no breaks in the constant term of the vector autoregression. Under the alternative, there are additional cointegrating vectors that are potentially obscured by multiple breaks in the deterministic terms. The test is based on the likelihood ratio test of Johansen (1988, 1991) and involves …
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Machine learning for time series anomaly detection
… models such as Long Short-Term Memory (LSTM), autoregression, Multi-Layer Perceptron, and Encoder-Decoder LSTM. I used the "Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding" paper as a basis for my analysis, and was able to beat their performance on anomaly …
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Essays on Bayesian Macroeconometrics
… from ICS innovations in a structural vector autoregression. The second chapter, co-authored with Minchul Shin, proposes the multivariate stochastic volatility in vector autoregression model as a framework for studying the real effects of uncertainty shocks. We advance a new approach to …
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Three Essays on Leverage and the Macroeconomy
… leverage in the context of a structural vector autoregression model. I apply short-run and long-run restrictions based on economic theory to identify monetary policy and leverage shocks. I also use the sign restrictions approach to the identification of a leverage demand shock and examine its …
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The Importance Of Housing Variables In Predicting Economic Fluctuations
… By using Granger-Causality test and vector autoregression (VAR) model, combination of factor analysis and VAR model, and hard thresholding method to identify the importance of each housing variable, the results show that housing price indexes are not important in forecasting the economy, but …
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US Financial Expansions and Exchange Rate Determination
… driving force of financial cycles. Using vector autoregression (VAR) analysis I test the relationships between the ratio of US shadow banking assets relative to commercial banking assets, portfolio investment liabilities, and the exchange rates for South Korea, Mexico, India and Brazil. I find …
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Fiscal and Monetary Policies and Stock Market
… at the sectoral level in a structural vector autoregression (SVAR) framework. I adopt alternative variables as a policy instrument. When the spread is used as a policy instrument, I find that contractionary monetary policy has a significant negative effect on both output and the price level …
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