Essays On Forecasting Macroeconomic Variables Using Mixed Frequency Data
DOWNLOAD
Download Essays On Forecasting Macroeconomic Variables Using Mixed Frequency Data PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Essays On Forecasting Macroeconomic Variables Using Mixed Frequency Data book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Essays On Forecasting Macroeconomic Variables Using Mixed Frequency Data
DOWNLOAD
Author : Kihwan Kim
language : en
Publisher:
Release Date : 2016
Essays On Forecasting Macroeconomic Variables Using Mixed Frequency Data written by Kihwan Kim and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Economic forecasting categories.
This dissertation investigate the forecasting performance of mixed frequency factor models with mixed frequency dataset. In the first chapter, I consider the mixed fre- quency factor approach used in ADS (2009) to construct their co-incident activity index, and ask the question of whether a class of mixed frequency indexes is useful for predicting the future values of quarterly U.S. real GDP growth and monthly industrial production, unemployment and inflation. My forecasting assessment of the mixed frequency factor model is performed in conjunction with standard prediction models such as autoregression, multivariate distributed lag models, and diffu- sion index models of the variety examined by Stock and Watson (2002a). The main findings of the study are as follows. First, prediction models using only mixed frequency indexes show their best performance at short-term GDP forecasting horizons, and are particularly good during recessions. Second, prediction models using both mixed frequency indexes and diffusion indexes forecast monthly variables more accurately than models using single frequency type indexes. Third, model combi- nations perform relatively poorly in real GDP forecasting contexts, although they perform better when applied to the prediction of monthly variables. Fourth, survey information can be conveniently exploited with higher frequency variables such as daily and weekly variables, and mixed frequency indexes using such survey information are sometimes useful in forecasting lower frequency variables. In the second chapter, I evaluate the predictive performance of hybrid models for forecasting four economic variables. The hybrid approach takes into account the notion that simple autoregression and sophisticated factor models' predictive abilities may change according to the state of the econ- omy. I find that hybrid prediction models produce better forecasts than standard models and than combination models, in most cases, using the same menu of models discussed above. For example, in one-quarter ahead GDP forecasts, the best hybrid model reduces the mean squared forecast error of the best model combinations and the linear models by 14 and 11 percent, on average, respectively. More specifically, the mean squared forecast error of autoregression is reduced by approximately 35 percent. In 12-month ahead predictions of inflation, the best hybrid model improves the best model combinations and the linear models by 11 percent and 16 percent, on average, respectively. This number again increases, in this case to 36 percent, when comparing only with autoregression. One reason for these findings is that hybrid prediction models more effectively utilize survey information.
Macroeconomic Forecasting In The Era Of Big Data
DOWNLOAD
Author : Peter Fuleky
language : en
Publisher: Springer Nature
Release Date : 2019-11-28
Macroeconomic Forecasting In The Era Of Big Data written by Peter Fuleky and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-28 with Business & Economics categories.
This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency data; and how to evaluate forecasts, among others. Each chapter is self-contained with references, and provides solid background information, while also reviewing the latest advances in the field. Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.
Macroeconomic Forecasting With Mixed Frequency Data
DOWNLOAD
Author :
language : en
Publisher:
Release Date : 2007
Macroeconomic Forecasting With Mixed Frequency Data written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.
Essays On Financial Economics And Macroeconomics
DOWNLOAD
Author : Haibin Zhang
language : en
Publisher:
Release Date : 2019
Essays On Financial Economics And Macroeconomics written by Haibin Zhang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
This thesis, entitled Essays on Financial Economics and Macroeconomics, studies the interactions between real macroeconomics and financial variables. There is an emerging literature aims to investigate how can we reduce the impacts from the financial crisis by considering both macroeconomics and finance conditions together. For example, decision-makers should consider the financial market conditions first before policies are made. Meanwhile, the forecasting of short term financial variables' returns should take long term macroeconomic conditions into consideration. This has motivated us to explore further in the relationship between the macroeconomic factors and financial market conditions. In the first chapter, we examine the short-run and long-run dynamics of the correlation between exchange rate and commodity returns, and assess the extent to which the long-run correlation is determined by economic fundamentals. Our empirical analysis is based on the dynamic conditional correlation model with mixed data sampling (DCC-MIDAS) of Colacito, Engle and Ghysels (2011). This model provides a framework that captures the high-frequency relation between exchange rate and commodity returns as well as the low-frequency relation of volatility and correlation to economic fundamentals. Using both economic and statistical criteria, we find that the DCC-MIDAS\ model augmented with economic fundamentals performs better than competing models in sample and out of sample. In the second chapter, we investigate the direction of Granger causality between business and financial cycles. Our analysis is based on a vector autoregression model applied on mixed frequency data. This allows us to condition on data from higher frequency variables (such as monthly industrial production) and lower frequency variables (such as quarterly aggregate credit) in a way that avoids the effects on data aggregation. Our empirical investigation focuses on five industrialized countries: USA, Canada, UK, Germany and Japan. Firstly, we examine whether the monthly industrial production index causes quarterly aggregate credit or vice versa. Then, we determine the timing of when causality is statistically significant. We find that there is strong bidirectional causality between business and financial cycles. The timing of causality varies across countries, but for all countries, bidirectional causality is significant during the financial crisis. The third and final chapter, which is an extension of the second chapter, investigates the role of the US as a global leader. Specifically, by paring US with other country (i.e, Canada, UK, Germany and Japan), we examine whether the US industrial production or credit causes the industrial production or credit of the other countries. In addition, we investigate whether causality is affected by the nominal interest rate. Our main finding is that the US business cycle strongly causes the business cycles of Canada, the UK and Germany. Finally, there is strong evidence that causality tends to be significant when the US interest rate is higher.
Macroeconomic Forecasting With Mixed Frequency Data
DOWNLOAD
Author : Michael P. Clements
language : en
Publisher:
Release Date : 2006
Macroeconomic Forecasting With Mixed Frequency Data written by Michael P. Clements and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.
Essays In Forecasting
DOWNLOAD
Author : Nii Ayi Christian Armah
language : en
Publisher:
Release Date : 2009
Essays In Forecasting written by Nii Ayi Christian Armah and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Economic forecasting categories.
This dissertation comprises three essays in macroeconomic forecasting. The first essay discusses model selection and predictive accuracy tests in the context of parameter and model uncertainty under recursive and rolling estimation schemes. Particular emphasis is placed on the construction of valid bootstrap procedures for calculating the impact of parameter estimation error on the class of test statistics with limiting distributions that are functionals of Gaussian processes. Results of an empirical investigation of the marginal predictive content of money for income are also presented. The second essay outlines a number of approaches to the selection of factor proxies (observed variables that proxy unobserved estimated factors) using statistics based on large sample datasets. This approach to factor proxy selection is examined via a small Monte Carlo experiment and a set of prediction experiments, where evidence supporting our proposed methodology is presented. The third essay compares the predictive content of a set of macroeconomic indicators with that of various other observable variables that act as proxies to factors constructed using diffusion index methodology. The analysis suggests that certain spreads constructed as the difference between short or long term debt instruments and the federal funds rate are found to be useful indicators. Surprisingly, traditional spreads, such as the yield curve slope and the reverse yield gap are not found to provide additional predictive power.
Estimation And Forecasting Using Mixed Frequency Dsge Models
DOWNLOAD
Author : Alexander Meyer-Gohde
language : de
Publisher:
Release Date : 2022
Estimation And Forecasting Using Mixed Frequency Dsge Models written by Alexander Meyer-Gohde and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
In this paper, we propose a new method to forecast macroeconomic variables that combines two existing approaches to mixed-frequency data in DSGE models. The first existing approach estimates the DSGE model in a quarterly frequency and uses higher frequency auxiliary data only for forecasting (see Giannone, Monti and Reichlin (2016)). The second method transforms a quarterly state space into a monthly frequency and applies, e.g., the Kalman filter when faced missing observations (see Foroni and Marcellino (2014)). Our algorithm combines the advantages of these two existing approaches, using the information from monthly auxiliary variables to inform in-between quarter DSGE estimates and forecasts. We compare our new method with the existing methods using simulated data from the textbook 3-equation New Keynesian model (see, e.g., Galí (2008)) and real-world data with the Smets and Wouters (2007) model. With the simulated data, our new method outperforms all other methods, including forecasts from the standard quarterly model. With real world data, incorporating auxiliary variables as in our method substantially decreases forecasting errors for recessions, but casting the model in a monthly frequency delivers better forecasts in normal times.
Predictive Performance Of Mixed Frequency Nowcasting And Forecasting Models
DOWNLOAD
Author : Roberto S. Mariano
language : en
Publisher:
Release Date : 2020
Predictive Performance Of Mixed Frequency Nowcasting And Forecasting Models written by Roberto S. Mariano and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
Using Mixed Frequency Data To Forecast Recessions And Gdp
DOWNLOAD
Author : Ryan Mitchell
language : en
Publisher:
Release Date : 2021
Using Mixed Frequency Data To Forecast Recessions And Gdp written by Ryan Mitchell and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
This dissertation studies how and if mixed frequency time series data should be used to forecast recessions in the US and Canada, as well as GDP in a selection of OECD countries. The first chapter combines daily and weekly financial data with monthly macroeconomic indicators in a mixed frequency probit (MFP) regression to forecast and nowcast US and Canadian recessions. This chapter adds to the existing literature in multiple ways, including; developing a mixed frequency binary model that could be helpful for topics outside of recession forecasting, examining how higher frequency data should be weighted in the context of recession prediction, as well as a methodology that can nowcast current economic conditions. Overall I find significant improvements in the forecasting and nowcasting accuracy of recessions when using mixed frequency data, compared to a benchmark model that aggregates data into the same frequency. The second chapter extends from the first to apply machine learning techniques to the same problem. I add to the existing literature by incorporating mixed frequency data directly into a classification artificial neural network (MF-ANN) as well as using novel cross validation methods to tune hyperparameters and carry out feature selection with time series data. Overall when comparing US recession forecasting results to the reduced form methodology of Chapter 1, I find mixed results. While some metrics indicate similar performance between the two methods, the ANN makes less extreme forecasting errors on average. The third chapter uses a seemingly unrelated regressions (SUR) approach with a mixed frequency framework to forecast GDP of 10 OECD countries. This chapter adds to the literature as a way to efficiently include cross country information in GDP forecasting equations, as well as being an effective methodology when the researcher is constrained by small sample sizes. Overall we find that SUR outperforms OLS for the majority of countries and forecasting horizons, however as sample sizes are extended this benefit is reduced.
Var Models In Macroeconomics New Developments And Applications
DOWNLOAD
Author : Thomas B. Fomby
language : en
Publisher: Emerald Group Publishing Limited
Release Date : 2013-12-18
Var Models In Macroeconomics New Developments And Applications written by Thomas B. Fomby and has been published by Emerald Group Publishing Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-18 with Business & Economics categories.
Advances in Econometrics publishes original scholarly econometric papers with the intention of expanding the use of developed and emerging econometric techniques by disseminating ideas on the theory and practice of econometrics, throughout the empirical economic, business and social science literature.