U Midas
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U Midas
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Author : Claudia Foroni
language : en
Publisher:
Release Date : 2011
U Midas written by Claudia Foroni and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.
U Midas
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Author : Claudia Foroni
language : en
Publisher:
Release Date : 2016
U Midas written by Claudia Foroni and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
Mixed-data sampling (MIDAS) regressions allow to estimate dynamic equations that explain a low-frequency variable by high-frequency variables and their lags. When the difference in sampling frequencies between the regressand and the regressors is large, distributed lag functions are typically employed to model dynamics avoiding parameter proliferation. In macroeconomic applications, however, differences in sampling frequencies are often small. In such a case, it might not be necessary to employ distributed lag functions. In this paper, we discuss the pros and cons of unrestricted lag polynomials in MIDAS regressions. We derive unrestricted MIDAS regressions (U-MIDAS) from linear high-frequency models, discuss identification issues, and show that their parameters can be estimated by OLS. In Monte Carlo experiments, we compare U-MIDAS to MIDAS with functional distributed lags estimated by NLS. We show that U-MIDAS generally performs better than MIDAS when mixing quarterly and monthly data. On the other hand, with larger differences in sampling frequencies, distributed lag-functions outperform unrestricted polynomials. In an empirical application on out-of-sample nowcasting GDP in the US and the Euro area using monthly predictors, we find a good performance of U-MIDAS for a number of indicators, albeit the results depend on the evaluation sample. We suggest to consider U-MIDAS as a potential alternative to the existing MIDAS approach in particular for mixing monthly and quarterly variables. In practice, the choice between the two approaches should be made on a case-by-case basis, depending on their relative performance.
Nowcasting By The Bsts U Midas Model
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Author : Jun Duan
language : en
Publisher:
Release Date : 2015
Nowcasting By The Bsts U Midas Model written by Jun Duan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
Using high frequency data for forecasting or nowcasting, we have to deal with three major problems: the mixed frequency problem, the high dimensionality (fat regression, parameter proliferation) problem, and the unbalanced data problem (miss-ing observations, ragged edge data). We propose a BSTS-U-MIDAS model (Bayesian Structural Time Series-Unlimited-Mixed-Data Sampling model) to handle these problem. This model consists of four parts. First of all, a structural time series with regressors model (STM) is used to capture the dynamics of target variable, and the regressors are chosen to boost the forecast accuracy. Second, a MIDAS model is adopted to handle the mixed frequency of the regressors in the STM. Third, spike-and-slab regression is used to implement variable selection. Fourth, Bayesian model averaging (BMA) is used for nowcasting. We use this model to nowcast quarterly GDP for Canada, and find that this model outperform benchmark models: ARIMA model and Boosting model, in terms of MAE (mean absolute error) and MAPE (mean absolute percentage error).
Estimating Midas Regressions Via Ols With Polynomial Parameter Profiling
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Author : Eric Ghysels
language : en
Publisher:
Release Date : 2016
Estimating Midas Regressions Via Ols With Polynomial Parameter Profiling written by Eric Ghysels and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
A typical MIDAS regression involves estimating parameters via nonlinear least squares, unless U-MIDAS is applied - which involves OLS - the latter being appealing when the sampling frequency differences are small. In this paper we propose to use OLS estimation of the MIDAS regression slope and intercept parameters combined with profiling the polynomial weighting scheme parameter(s). The use of Beta polynomials is particularly attractive for such an approach. The new procedure shares many of the desirable features of U-MIDAS, while it is not restricted to small sampling frequency differences.
Nowcasting And Near Term Forecasting Cambodia S Economy
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Author : Dyna Heng
language : en
Publisher: International Monetary Fund
Release Date : 2024-07-12
Nowcasting And Near Term Forecasting Cambodia S Economy written by Dyna Heng and has been published by International Monetary Fund this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-12 with categories.
Assessing the current state of the economy and forecast the economic outlook in the next few quarters are important inputs for policymakers. This paper presents a suite of models with an integrated approach to forecast Cambodia’s economy in the current and next few quarters. First, we estimate historical quarterly GDP using information extracted from high-frequency indicators to construct quarterly nowcasting model. Second, we forecast current economic activities using a high-frequency data such as credit, export, tourist arrival, foreign reserves, and trading partner’s GDP. Third, we present inflation forecasting models for Cambodia. Fourth, the paper present a vector autoregression model to forecast Cambodia’s GDP in the next few quarters using global forecasts of China’s and US’s economy as well as oil and rice price. This paper showcase how high-frequency data set can be utilized in assessing current economic activities in countries with limited and lagged data.
Project Midas
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Author : P. Alotto
language : en
Publisher:
Release Date : 1996
Project Midas written by P. Alotto and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Computer software categories.
Financial Macro And Micro Econometrics Using R
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Author :
language : en
Publisher: Elsevier
Release Date : 2020-01-25
Financial Macro And Micro Econometrics Using R written by and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-25 with Mathematics categories.
Financial, Macro and Micro Econometrics Using R, Volume 42, provides state-of-the-art information on important topics in econometrics, including multivariate GARCH, stochastic frontiers, fractional responses, specification testing and model selection, exogeneity testing, causal analysis and forecasting, GMM models, asset bubbles and crises, corporate investments, classification, forecasting, nonstandard problems, cointegration, financial market jumps and co-jumps, among other topics. Presents chapters authored by distinguished, honored researchers who have received awards from the Journal of Econometrics or the Econometric Society Includes descriptions and links to resources and free open source R Gives readers what they need to jumpstart their understanding on the state-of-the-art
Theory And Applications Of Time Series Analysis
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Author : Olga Valenzuela
language : en
Publisher: Springer Nature
Release Date : 2023-12-11
Theory And Applications Of Time Series Analysis written by Olga Valenzuela and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-11 with Mathematics categories.
This book presents the latest developments in the theory and applications of time series analysis and forecasting. Comprising a selection of refereed papers, it is divided into several parts that address modern theoretical aspects of time series analysis, forecasting and prediction, with applications to various disciplines, including econometrics and energy research. The broad range of topics discussed, including matters of particular relevance for sustainable development, will give readers a modern perspective on the subject. The included contributions were originally presented at the 8th International Conference on Time Series and Forecasting, ITISE 2022, held in Gran Canaria, Spain, June 27-30, 2022. The ITISE conference series provides a forum for scientists, engineers, educators and students to discuss the latest advances and implementations in the foundations, theory, models and applications of time series analysis and forecasting. It focuses on interdisciplinary research encompassing computer science, mathematics, statistics and econometrics.
Identifying Optimal Indicators And Lag Terms For Nowcasting Models
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Author : Jing Xie
language : en
Publisher: International Monetary Fund
Release Date : 2023-03-03
Identifying Optimal Indicators And Lag Terms For Nowcasting Models written by Jing Xie and has been published by International Monetary Fund this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-03 with Business & Economics categories.
Many central banks and government agencies use nowcasting techniques to obtain policy relevant information about the business cycle. Existing nowcasting methods, however, have two critical shortcomings for this purpose. First, in contrast to machine-learning models, they do not provide much if any guidance on selecting the best explantory variables (both high- and low-frequency indicators) from the (typically) larger set of variables available to the nowcaster. Second, in addition to the selection of explanatory variables, the order of the autoregression and moving average terms to use in the baseline nowcasting regression is often set arbitrarily. This paper proposes a simple procedure that simultaneously selects the optimal indicators and ARIMA(p,q) terms for the baseline nowcasting regression. The proposed AS-ARIMAX (Adjusted Stepwise Autoregressive Moving Average methods with exogenous variables) approach significantly reduces out-of-sample root mean square error for nowcasts of real GDP of six countries, including India, Argentina, Australia, South Africa, the United Kingdom, and the United States.
Credible Asset Allocation Optimal Transport Methods And Related Topics
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Author : Songsak Sriboonchitta
language : en
Publisher: Springer Nature
Release Date : 2022-07-29
Credible Asset Allocation Optimal Transport Methods And Related Topics written by Songsak Sriboonchitta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-29 with Technology & Engineering categories.
This book describes state-of-the-art economic ideas and how these ideas can be (and are) used to make economic decision (in particular, to optimally allocate assets) and to gauge the results of different economic decisions (in particular, by using optimal transport methods). Special emphasis is paid to machine learning techniques (including deep learning) and to different aspects of quantum econometrics—when quantum physics and quantum computing models are techniques are applied to study economic phenomena. Applications range from more traditional economic areas to more non-traditional topics such as economic aspects of tourism, cryptocurrencies, telecommunication infrastructure, and pandemic. This book helps student to learn new techniques, practitioners to become better knowledgeable of the state-of-the-art econometric techniques, and researchers to further develop these important research directions