This paper analyses the long-memory properties of a high-frequency financial time series dataset. It focuses on temporal aggregation and other features of the data, and how they might affect the degree of dependence of the series. Fractional integration or I(d) models are estimated with a...

This paper analyses the long-memory properties of high frequency financial time series. It focuses on temporal aggregation and the influence that this might have on the degree of dependence of the series. Fractional integration or I(d) models are estimated with a variety of specifications for...

This paper suggests a novel approach to pre-selection of the component series of the diffusion index based on their individual forecasting performance. It is shown that this targeted selection allows substantially improving the forecasting ability compared to the diffusion index models that are...

Antibiotic resistance constitutes a major health threat. Predicting bacterial causes of infections is key to reducing antibiotic misuse, a leading driver of antibiotic resistance. We train a machine learning algorithm on administrative and microbiological laboratory data from Denmark to predict...

An emerging question in demographic economics is whether there is a link between family size and the geographic distance between adult children and elderly parents. Given current population trends, understanding how different configurations of fam- ily size and sibship influence patterns of...

In this paper a dynamic bi-factor model with Markov switching is proposed to measure and predict turning points of the German business cycle. It estimates simultaneously the composite leading indicator (CLI) and composite coincident indicator (CCI) together with corresponding probabilities of...

The appropriately selected leading indicators can substantially improve the forecasting of the peaks and troughs of the business cycle. Using the novel methodology of the dynamic bi-factor model with Markov switching and the data for three largest European economies (France, Germany, and UK) we...

Human decision-making differs due to variation in both incentives and available information. This generates substantial challenges for the evaluation of whether and how machine learning predictions can improve decision outcomes. We propose a framework that incorporates machine learning on...

Expectations form the basis of economic decisions of market participants in an uncertain world. Sentiment indicators reflect those expectations and thus have a proven track record for predicting economic variables. However, respondents of surveys perceive the world to a large extent with the...

Before the World War I, the urban rental housing market in Germany could be described as a free and competitive market. The government hardly interfered in the relationships between the landlords and ten- ants. The rents were set freely. During the World War I, the market was hit by several...