Narrow search
Showing 1 - 10 of 251
Cover Image
A unit-level quantile nested error regression model for domain prediction with continuous and discrete outcomes
Weidenhammer, Beate; Schmid, Timo; Salvati, Nicola; … - 2016
In this paper we will present recent work on a new unit-level small area methodology that can be used with continuous and discrete outcomes. The proposed method is based on constructing a model-based estimator of the distribution function by using a nested-error regression model for the...
Persistent link: https://www.econbiz.de/10011496844
Cover Image
A joint top income and wealth distribution
Steiner, Viktor; Zhu, Junyi - 2021
estimation of these two top distributions by using the best data available for Germany. We leverage the bivariate copula to … model. The copula modelling grants the separability in choosing the estimation domain as well as the parametric … model fit with external validation. The copula estimate can help us to perform out-of-sample prediction on the very top of …
Persistent link: https://www.econbiz.de/10012424292
Cover Image
Testing missing at random using instrumental variables
Breunig, Christoph - 2017
This paper proposes a test for missing at random (MAR). The MAR assumption is shown to be testable given instrumental variables which are independent of response given potential outcomes. A nonparametric testing procedure based on integrated squared distance is proposed. The statistic's...
Persistent link: https://www.econbiz.de/10011894725
Cover Image
The determinants of CDS spreads : evidence from the model space
Pelster, Matthias; Vilsmeier, Johannes - 2016
specifications used elsewhere in the literature, including different copula models. The approach followed supports ultimate … results suggest that dynamic copula based measures of tail dependence incorporate almost all essential pricing information …
Persistent link: https://www.econbiz.de/10011561899
Cover Image
Analysis of nonlinear comovement of benchmark Thai government bond yields
Rewat Khanthaporn - 2022
Persistent link: https://www.econbiz.de/10013429426
Cover Image
A severity function approach to scenario selection
Mokinski, Frieder - 2017
The severity function approach (abbreviated SFA) is a method of selecting adverse scenarios from a multivariate density. It requires the scenario user (e.g. an agency that runs banking sector stress tests) to specify a "severity function", which maps candidate scenarios into a scalar severity...
Persistent link: https://www.econbiz.de/10011755965
Cover Image
Kernel density estimation for heaped data
Groß, Marcus; Rendtel, Ulrich - 2015
In self-reported data usually a phenomenon called 'heaping' occurs, i.e. survey participants round the values of their income, weight or height to some degree. Additionally, respondents may be more prone to round off or up due to social desirability. By ignoring the heaping process a severe bias...
Persistent link: https://www.econbiz.de/10011325727
Cover Image
Estimation of heterogeneous agent models : a likelihood approach
Parra-Alvarez, Juan Carlos; Posch, Olaf; Wang, Mu-Chun - 2020
We study the statistical properties of heterogeneous agent models. Using aBewley-Hugget-Aiyagari model we compute the density function of wealth and in-come and use it for likelihood inference. We study the finite sample properties of themaximum likelihood estimator (MLE) using Monte Carlo...
Persistent link: https://www.econbiz.de/10012256501
Cover Image
Confidence bands for regression surfaces
Richmond, J. - 1981
Persistent link: https://www.econbiz.de/10003527879
Cover Image
Estimating the density of ethnic minorities and aged people in Berlin : multivariate kernel density estimation applied to sensitive geo-referenced administrative data protected via...
Groß, Marcus; Rendtel, Ulrich; Schmid, Timo; Schmon, … - 2015
Modern systems of official statistics require the timely estimation of area-specific densities of sub-populations. Ideally estimates should be based on precise geo-coded information, which is not available due to confidentiality constraints. One approach for ensuring confidentiality is by...
Persistent link: https://www.econbiz.de/10010486952