In Germany, package holidays are an important driver of consumer prices. Several challenges arise when measuring the price development of these bundled travel and accommodation services, such as the quality of accommodation and the timing of booking. Statistical practices are currently based on...

In Germany, package holidays, which consist of a bundle of flight and accommodation services, are an important driver of consumer prices. Several challenges arise when measuring the price development of package holidays, for example the quality of accommodation, the timing of the booking, the...

This paper proposes a generalized repeat sales regression (GRSR) that uses repeat sales from the entire market, in which properties may have heterogeneous value appreciation processes, to estimate price indices for not only the entire market, but also submarkets or customized portfolios of...

The increasing availability of geospatial data (i.e., exact longitudes and latitudes for each house) has the potential to improve the quality of house price indexes. It is not clear though how best to use this information. We show how geospatial data can be included as a nonparametric spline...

Hedonic house price indices adjust the average sales prices for the change in the quality of the property sold over time. This paper proposes a framework to disentangle the contribution of each individual dwelling characteristic to this quality change. We apply our framework to a unique dataset...

This study presents the detailed method of the MNB's house price index and the results of the new price indices. The index family is considered to be a novelty among Hungarian housing market statistics in several regards. Firstly, the national index was derived from a database starting in 1990,...

Hedonic regressions are used for residential property price index (RPPI) measurement to control for changes in the quality-mix of properties transacted. This paper consolidates the confusing array of existing approaches and methods of implementation. It further develops an innovative form of...

We consider time series models in which the conditional mean of the response variable given thepast depends on latent covariates. We assume that the covariates can be estimated consistentlyand use an iterative nonparametric kernel smoothing procedure for estimating the conditional meanfunction....

The term structure of American interest rates is filtered to reduce the influence of cross correlations and auto correlations on its factors. A three-factor model is fitted to the filtered data. Contrary to most studies of the term structure on monthly data, performing statistical tests we...

Quantile regression (QR) is a principal regression method for analyzing the impact of covariates on outcomes. The impact is described by the conditional quantile function and its functionals. In this paper we develop the nonparametric QR series framework, covering many regressors as a special...