[PDF] Top 20 Forecasting macroeconomic variables using a structural state space model
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Forecasting macroeconomic variables using a structural state space model
... small macroeconomic model in state space form, the second is to demonstrate that it produces accurate ...a structural state space macroeconomic model to ... See full document
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Nonlinear Differential Equation of Macroeconomic Dynamics for Long Term Forecasting of Economic Development
... the model of non-linear accelerator of induced ...trend using Krylov-Bogoliubov-Mitropolsky aver- ...to structural change and accepting ...nonequilibrium state has a dy- namics with ... See full document
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Bayesian and Frequentist Approach to Time Series Forecasting with Application to Kenya’s GDP per Capita
... [8] state space model (also known as dynamic linear model) provides a methodology for treating a wide range of problems in time series ...this model, the development of the system over ... See full document
15
Macroeconomic Variables and Stock Market Performance: Testing for Dynamic Linkages with a Known Structural Break
... four macroeconomic variables and stock prices in Pakistan, using cointegration and Granger causality tests that are robust to structural ...and macroeconomic variables ...said ... See full document
30
A Comparison of Forecasting Procedures for Macroeconomic Series : The Contribution of Structural Break Models
... when forecasting subject to structural breaks. Such forecasting models can differ in three important ...the state space literature where the conditional mean coefficients in the most ... See full document
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Sprincenatu, Maria (2019): Modeling and forecasting the co-movement of international yield curve drivers. Dissertation, LMU München: Fakultät für Mathematik, Informatik und Statistik
... detecting structural breaks, past literature contains very few empirical studies of structural breaks in yield curves and yield curve ...multiple structural breaks in the mean real interest rate and ... See full document
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Comparison of Neural Network Models, Vector Auto Regression (VAR), Bayesian Vector-Autoregressive (BVAR), Generalized Auto Regressive Conditional Heteroskedasticity (GARCH) Process and Time Series in Forecasting Inflation in Iran
... econometric structural models which widely do economic forecasts, the problem of too much fit- ting is solved by entering the variables into the equation that suggests economic theory and have the greatest ... See full document
10
Using VARs and TVP-VARs with Many Macroeconomic Variables
... dependent variables in each equation, also require the use of MCMC ...are state space models and one of their advantages is that well-known statis- tical methods for state space models ... See full document
35
A macroeconomic structural model for the Portuguese economy
... as structural models) seem more appealing for policy simulation purposes than traditional macroeconometric mod- ...a structural model, economic agents’ decision rules corresponding to reduced-form ... See full document
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RESULTS OF INTERBANK EXCHANGE RATES FORECASTING USING STATE SPACE MODEL
... linear state space model has become a standard modeling framework for the statistical analysis of time ...extraction, forecasting, and seasonal adjustment of time series in economics, ... See full document
9
The state of macroeconomic forecasting
... of macroeconomic forecasts arises from (i) the quality of the model including its structure and its robustness to mis- specification, (ii) the judgement of the modeler or (iii) the forecasts of the ... See full document
59
Forecasting pelagic fish in Malaysia using ETS State Space Approach
... environmental variables to determine habitat suitability indices for Chub mackerel during July to September in the East China ...Mean Model (AMM) was found to be most suitable according to Akaike ... See full document
47
The Sydney Olympics, seven years on: an ex-post dynamic CGE assessment
... determine macroeconomic variables for each state at their observed values, allowing the model to endogenously determine values for relevant structural ...the state level is ... See full document
27
Forecasting Australian Macroeconomic variables, evaluating innovations state space approaches
... 4.2 Innovations vs Naı̈ve Four alternatives to the Naı̈ve approach are considered in this section, they are the univariate innovation state space alternative option 2 denoted as ETS2 , t[r] ... See full document
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Using VARs and TVP-VARs with many macroeconomic variables
... dependent variables in each equation, also require the use of MCMC ...are state space models and one of their advantages is that well-known statis- tical methods for state space models ... See full document
34
Incorporating an economic model in the health impact assessment approach
... The model framework presented above starts with a damage function approach using dose-response relationships to estimate the health impacts (health cases – mortality and morbidity figures) of a policy ... See full document
12
Forecasting the Saudi Arabia Stock Prices Based on Artificial Neural Networks Model
... (2) using back propagation network (BPN) to predict the buy/sell points (wave peak and wave trough) of stock price and (3) adopting case based dynamic window (CBDW) to further improve the forecasting ... See full document
10
Modelling and Forecasting Unbiased Extreme Value Volatility Estimator: A Study Based on EUR/USD Exchange Rate
... risk managers having off-shore exposure. Volatility plays an important role in portfolio theory and helps in optimal allocation of investors’ money in different asset classes or securities. The choice of the optimal ... See full document
15
Discrete-Space Analysis of Partial Differential Equations
... efficiently using support function-based method implemented in SpaceEx [1] or zonotope-based method utilized in CORA ...Hylaa using simulation-based method [3, 4] can analyze linear systems with up to 10000 ... See full document
11
Forecasting VARMA processes using VAR models and subspace based state space models
... series, state-space-based system-identification methods present some additional advantages over VARMA modelling, especially for the specification step: there is only one hyperparameter to estimate, namely ... See full document
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