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Measurement errors arising when using distances in microeconometric modelling and the individuals' position is geo-masked for confidentiality
Arbia, Giuseppa; Espa, Giuseppe; Giuliani, Diego - In: Econometrics : open access journal 3 (2015) 4, pp. 709-718
In many microeconometric models we use distances. For instance, in modelling the individual behavior in labor economics or in health studies, the distance from a relevant point of interest (such as a hospital or a workplace) is often used as a predictor in a regression framework. However, in...
Persistent link: https://www.econbiz.de/10011411576
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Estimating economic impact using ex post econometric analysis : cautionary tales
Baumann, Robert; Matheson, Victor A. - 2011
Persistent link: https://www.econbiz.de/10010436918
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Uniform confidence bands for pricing kernels
Härdle, Wolfgang; Okhrin, Yarema; Wang, Weining - 2010
-neutral density estimator and the subjective density estimator. The former density can be represented as the second derivative w …
Persistent link: https://www.econbiz.de/10003952791
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Pricing kernel modeling
Belomestny, Denis; Ma, Shujie; Härdle, Wolfgang - 2015
nonparametrically by using the ratio of the risk-neutral density estimator and the subjective density estimator. The risk …-neutral density is approximated by a weighted kernel density estimator with varying unknown weights for different observations, and … the subjective density is approximated by a kernel density estimator with equal weights. We represent the European call …
Persistent link: https://www.econbiz.de/10010462645
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Estimation and Calibration of a Dynamic Variance Gamma Model Using Vix Data
Mercuri, Lorenzo - 2015
The aim of this paper is to investigate the ability of the Dynamic Variance Gamma model, recently proposed by Bellini and Mercuri (2010), to evaluate option prices on the S&P500 index. We also provide a simple relation between the Dynamic Variance Gamma model and the Vix index. We use this...
Persistent link: https://www.econbiz.de/10013038504
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Estimation of Variance of Gini Coefficient for Income Distribution
Frangos, Christos C. - 2014
Gini coefficient is a Statistical measure for Income Distribution. This paper is an exposition of data concerning the Gini Coefficients for the Greek Income Tax Service for the years 1960 to 2000. Using von Mises Expansions we find second-order properties of Gini Coefficient. We estimate its...
Persistent link: https://www.econbiz.de/10012750888
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Testing Categorized Bivariate Normality with Two-Stage Polychoric Correlation Estimates
Maydeu Olivares, Alberto - 2007
equals X^2 with an adjustment to take into account that the estimator is not asymptotically efficient. Also, Mn < or = X^2 … where Mn = X^2 in the case of the one-stage maximum likelihood estimator …
Persistent link: https://www.econbiz.de/10014049104
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A Cautionary Note on the Use of Matching to Estimate Causal Effects : An Empirical Example Comparing Matching Estimates to an Experimental Benchmark
Arceneaux, Kevin; Gerber, Alan; Green, Donald P. - 2011
In recent years, social scientists have increasingly turned to matching as a method for drawing causal inferences from observational data. Matching compares those who receive a treatment to those with similar background attributes who do not receive a treatment. Researchers who use matching...
Persistent link: https://www.econbiz.de/10014187492
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Voluntary turnover : what we measure and what it (really) means
Will, Matthias Georg - 2017
In this paper, we run regression analyses to explain voluntary turnover intentions with data from more than 5,000 employees and with about 250 explanatory variables. The findings of our multi-factor approach highlight the fact that previous empirical research might have over-estimated the impact...
Persistent link: https://www.econbiz.de/10011751677
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Voluntary turnover : what we measure and what it (really) means
Will, Matthias Georg - 2017
In this paper, we run regression analyses to explain voluntary turnover intentions with data from more than 5,000 employees and with about 250 explanatory variables. The findings of our multi-factor approach highlight the fact that previous empirical research might have over-estimated the impact...
Persistent link: https://www.econbiz.de/10011622208