We introduce a novel quantitative methodology to detect real estate bubbles and forecast their critical end time, which we apply to the housing markets of China's major cities. Building on the Log-Periodic Power Law Singular (LPPLS) model of self-reinforcing feedback loops, we use the quantile...

This paper proposes a measure of real-time inflation expectations based on metadata, i.e., data about data, constructed from internet search queries performed on the search engine Google. The forecasting performance of the Google Inflation Search Index (GISI) is assessed relative to 37 other...

We investigate and construct forecasting models for the exchange rate of the Indonesian rupiah against the US dollar. Monthly data for three variables; exchange rate, interest rate and foreign reserves were employed in the Economic Forecasting Program (EFP) to obtain the forecasting results. The...

In this chapter, we analysing and forecasting the New Taiwanese Dollar against the US dollar. Forecasting models were tested using the three variables; exchange rate, money supply and Balance Remittance. Both VAR and VARMA models accurately predicted turning points and no false fluctuations were...

In this chapter, economic forecasting techniques were used to forecast the exchange rate of the New Taiwan (N.T.) dollar, given that there is a tolerable amount of favourable trade balance between Taiwan and the US. To test this monthly data for the economic variables; Taiwanese exchange rate...

In this chapter, a vector subset autoregressive process is fitted using a block modified Choleski decomposition method and a leaps-and-bounds algorithm to attain the best subset autoregression for each size (number of non-zero coefficient matrices). Model selection criteria are then employed to...

The paper presents an incomplete competition model (ICM), where inflation is determined jointly with unit labour cost growth. The ICM is estimated on data for the Euro area and evaluated against existing models, i.e. the implicit inflation equation of the Area Wide model (AWM) - cf. Fagan, Henry...

This study presents extensive results on the benefits of rolling window and model averaging. Building on the recent work on rolling window averaging by Pesaran et al (2010, 2009) and on exchange rate forecasting by Molodtsova and Papell (2009), we explore whether rolling window averaging can be...

This paper proposes a novel and flexible framework to estimate autoregressive models with time-varying parameters. Our setup nests various adaptive algorithms that are commonly used in the macroeconometric literature, such as learning-expectations and forgetting-factor algorithms. These are...

US inflation appears to undergo shifts in its mean level and variability. We evaluate the performance of three useful models for capturing such shifts. The models studied are the Markov switching models, state space models with heavy-tailed errors, and state space models with compound error...