Respondent driven sampling (RDS) is a network sampling technique typically employed for hard-to-reach populations (e.g. drug users, men who have sex with men, people with HIV). Similar to snowball sampling, initial seed respondents recruit additional respondents from their network of friends....

This paper assesses the validity of the perception-based governance indicators used by the US Millennium Challenge Account (MCA) for aid allocation decisions. By conducting Explanatory and Confirmatory Factor Analysis of data from 1996 to 2009, we find that although the MCA purports to measure...

In this paper a mixed-frequency VAR à la Mariano & Murasawa (2004) with Markov regime switching in the parameters is estimated by Bayesian inference. Unlike earlier studies, that used the pseuo-EM algorithm of Dempster, Laird & Rubin (1977) to estimate the model, this paper describes how to...

Who makes it to the top? We use the leading, socio-economic survey in Germany supplemented by extensive data on the rich to answer this question. We identify the key predictors for belonging to the top 1 percent of income, wealth, and both distributions jointly. Although we consider many, only a...

Structural VAR models require two ingredients: (i) Informational sufficiency, and (ii) a valid identification strategy. These conditions are unlikely to be met by small-scale recursively identified VAR models. I propose a Bayesian Proxy Factor-Augmented VAR (BP-FAVAR) to combine a large...

The standardisation of the European systems of national accounts has progressed significantly in recent years. Some room for interpretation remains in regard to some accounting standards, the periodicity of the data, and the quality of the forecasts of budget deficits. Yet national accounts data...

A new method for constructing R&D capital stocks is proposed. Following Schumpeter, the development of R&D capital stocks is modelled as a process of creative destruction. Newly generated knowledge is assumed not only to add to the existing R&D capital stocks but also, by displacing old...

The current economic crisis requires fast information to predict economic behavior early, which is difficult at times of structural changes. This paper suggests an innovative new method of using data on internet activity for that purpose. It demonstrates strong correlations between keyword...

The Google Insights data are a collection of recorded Internet searches for a huge number of the keywords, which are available since January 2004. These searches represent a kind of revealed perceptions of Internet users, which are a (possibly not entirely representative) sample of the general...

In this paper, we investigate whether the Google search activity can help in nowcasting the year-on-year growth rates of monthly US private consumption using a real-time data set. The Google-based forecasts are compared to those based on a benchmark AR(1) model and the models including the...