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...

Although many studies on the directional accuracy of forecasts by international organizations and professional forecasters have been scrutinized, little attention has been paid to forecasts by business leaders. In order to address this gap, we use directional tests to investigate whether...

A maximal overlap discrete wavelet transform is used to obtain time scale decompositions of economic forecasts and their errors. The generated time scale components can be used in loss measures and tests for comparing forecast accuracy to evaluate whether the forecasts accurately capture the...

Accurate and timely information on GDP is important to gauge the overall state of the economy and is thus essential for economic policymaking. A single-index dynamic factor model is estimated using mixed-frequency data on GDP, industrial production, employment, private consumption and exports to...

In periods of unusual weather, forecasters face a problem of interpreting economic data: Which part goes back to the underlying economic trend and which part arises from a special weather effect? In this paper, we discuss ways to disentangle weather-related from business cycle-related influences...

Output gap is generally used in assessing both the inflationary pressures and the cyclical position of a nation’s economy. However, this variable is not observable and must be estimated. In this paper, we accomplish two tasks. First, we estimate the output gap for the United Arab Emirates...

This paper develops an estimable hybrid model that combines the micro-founded DSGE model with the flexibility of the theoretical VAR model. The model is estimated via the maximum likelihood technique based on quarterly data on real Gross National Product (GNP), consumption, investment and hours...

The paper develops a Bayesian vector autoregressive (BVAR) model of the South African economy for the period of 1970:1-2000:4 and forecasts GDP, consumption, investment, short-term and long term interest rates, and the CPI. We find that a tight prior produces relatively more accurate forecasts...

This paper develops an estimable hybrid model that combines the theoretical rigor of a micro-founded DSGE model with the flexibility of an atheoretical VAR model. The model is estimated via maximum likelihood technique based on quarterly data on real Gross National Product (GNP), consumption,...

This paper estimates Bayesian Vector Autoregressive (BVAR) models, both spatial and non-spatial (univariate and multivariate), for the twenty largest states of the US economy, using quarterly data over the period 1976:Q1 to 1994:Q4; and then forecasts one-to-four quarters ahead real house price...