In this research note we report on our current efforts on developing a leading indicator of housing prices that could be used to forecast housing prices. Specifically we use Google search index at city level to predict Case-Shiller index. The methodology is based on Granger causality where we...

It is a common understanding that bankruptcy is not a sudden occurrence for any organizations. Macro and micro economic studies have suggested numerous influential factors, which have substantial evidence toward firm's performance (Bekeris, 2012) and survivability (Nehrebecka & Dzik, 2013). With...

Campbell and Shiller average 10 years of real S&P 500 earnings to construct its Cyclically Adjusted P/E ratio, or CAPE, which they then use to forecast its future 10-year returns. In essence, Campbell and Shiller kill two birds with one large stone - they use the 10-year average to reduce noise...

This paper presents a stochastic integrated model to forecast the German population and labour supply until 2060. Within a cohort-component approach, the population forecast applies principal components to birth, mortality, emigration and immigration rates. The labour force participation rates...

The paper derives analytical transitions probabilities following an exogenous shock to the deterministic component in the conditional logit model. The solution draws on the postestimation distribution of the model's stochastic component, identified on the basis of a direct utility maximization...

This paper examines point and density forecasts from the European Central Bank’s Survey of Professional Forecasters. We derive individual uncertainty measures along with individual point- and density-based measures of disagreement. We also explore the relationship between uncertainty and...

In this paper, we provide a novel way to estimate the out-of-sample predictive ability of a trading rule. Usually, this ability is estimated using a sample-splitting scheme, true out-of-sample data being rarely available. We argue that this method makes poor use of the available data and creates...

We review key aspects of forecasting using nonlinear models. Because economic models are typically misspecified, the resulting forecasts provide only an approximation to the best possible forecast. Although it is in principle possible to obtain superior approximations to the optimal forecast...