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Guzman, Giselle C. - Volkswirtschaftliche Fakultät, … - 2010

For decades, the academic literature has focused on three survey measures of expected inflation: the Livingston Survey, the Survey of Professional Forecasters, and the Michigan Survey. While these measures have been useful in developing models of forecasting inflation, the data are low frequency...

Persistent link: https://www.econbiz.de/10009647457

Forecasting inflation in Vietnam with univariate and vector autoregressive models

2017

In this paper, I apply univariate and vector autoregressive (VAR) models to forecast inflation in Vietnam. To investigate the forecasting performance of the models, two naive benchmark models (one is a variant of a random walk and the other is an autoregressive model) are first built based on...

Persistent link: https://www.econbiz.de/10011663290

Forecasting inflation in Vietnam with univariate and vector autoregressive models

Tran Thanh Hoa - 2017

Persistent link: https://www.econbiz.de/10011606109

Short-term inflation projections model and its assessment in Latvia

Bessonovs, Andrejs; Krasnopjorovs, Olegs - In: Baltic journal of economics 21 (2021) 2, pp. 184-204

This paper builds a short-term inflation projections (STIP) model for Latvia. The model is designed to forecast highly disaggregated consumer prices using cointegrated ARDL approach of [Pesaran, M., & Shin, Y. (1998). An Autoregressive Distributed Lag Modelling Approach to Cointegration...

Persistent link: https://www.econbiz.de/10012805901

Predictive Performance of Mixed-Frequency Nowcasting and Forecasting Models (with Application to Philippine Inflation and GDP Growth)

Mariano, Roberto S.; Ozmucur, Suleyman - 2020

This paper studies the comparative predictive accuracy of forecasting methods using mixed-frequency data, as applied to nowcasting Philippine inflation, real GDP growth, and other related macroeconomic variables. It focuses on variations of mixed-frequency dynamic latent factor models (DFM for...

Persistent link: https://www.econbiz.de/10014094788

Assessing the uncertainty in central banks' inflation outlooks

Knüppel, Malte; Schultefrankenfeld, Guido - 2019

Recent research has found that macroeconomic survey forecasts of uncertainty exhibit several deficiencies, such as horizon-dependent biases and lower accuracy than simple unconditional uncertainty forecasts. We examine the inflation uncertainty forecasts from the Bank of England, the Banco...

Persistent link: https://www.econbiz.de/10011962843

Long memory modelling of inflation with stochastic variance and structural breaks

Bos, Charles S.; Koopman, Siem Jan; Ooms, Marius - 2007

We investigate changes in the time series characteristics of postwar U.S. inflation. In a model-based analysis the conditional mean of inflation is specified by a long memory autoregressive fractionally integrated moving average process and the conditional variance is modelled by a stochastic...

Persistent link: https://www.econbiz.de/10011373822

Time series models with a common stochastic variance for analysing economic time series

Koopman, Siem Jan; Bos, Charles S. - 2002

The linear Gaussian state space model for which the common variance istreated as a stochastic time-varying variable is considered for themodelling of economic time series. The focus of this paper is on thesimultaneous estimation of parameters related to the stochasticprocesses of the mean part...

Persistent link: https://www.econbiz.de/10011327834

Forecasting with a Noncausal VAR Model

Nyberg, Henri - 2012

We propose simulation-based forecasting methods for the noncausal vector autoregressive model proposed by Lanne and … Saikkonen (2012). Simulation or numerical methods are required because the prediction problem is generally nonlinear and … simulation procedures. Simulation experiments demonstrate that gains in forecasting accuracy are achieved by using the correct …

Persistent link: https://www.econbiz.de/10013098167

Unobserved components with stochastic volatility in U.S. inflation : estimation and signal extraction

Li, Mengheng; Koopman, Siem Jan - 2018

We consider unobserved components time series models where the components are stochastically evolving over time and are subject to stochastic volatility. It enables the disentanglement of dynamic structures in both the mean and the variance of the observed time series. We develop a simulated...

Persistent link: https://www.econbiz.de/10011809984

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