scholarly journals The finite sample performance of semi- and non-parametric estimators for treatment effects and policy evaluation

2017 ◽  
Vol 115 ◽  
pp. 91-102 ◽  
Author(s):  
Markus Frölich ◽  
Martin Huber ◽  
Manuel Wiesenfarth
Keyword(s):  
Policy Evaluation ◽  
Treatment Effects ◽  
Finite Sample ◽  
Non Parametric

scholarly journals Manifolds of differentiable densities

2018 ◽  
Vol 22 ◽  
pp. 19-34 ◽  
Author(s):  
Nigel J. Newton
Keyword(s):  
Continuous Function ◽  
Likelihood Function ◽  
Probability Measures ◽  
Fréchet Spaces ◽  
Finite Sample ◽  
Infinite Dimensional ◽  
Statistical Manifolds ◽  
Covariant Derivatives ◽  
Finite Measures ◽  
Non Parametric

We develop a family of infinite-dimensional (non-parametric) manifolds of probability measures. The latter are defined on underlying Banach spaces, and have densities of class Cbk with respect to appropriate reference measures. The case k = ∞, in which the manifolds are modelled on Fréchet spaces, is included. The manifolds admit the Fisher-Rao metric and, unusually for the non-parametric setting, Amari’s α-covariant derivatives for all α ∈ ℝ. By construction, they are C∞-embedded submanifolds of particular manifolds of finite measures. The statistical manifolds are dually (α = ±1) flat, and admit mixture and exponential representations as charts. Their curvatures with respect to the α-covariant derivatives are derived. The likelihood function associated with a finite sample is a continuous function on each of the manifolds, and the α-divergences are of class C∞.

scholarly journals Policy evaluation via a statistical control: A non-parametric evaluation of the ‘Want2Work’ active labour market policy

2015 ◽  
Vol 51 ◽  
pp. 635-645 ◽  
Author(s):  
Joanne Lindley ◽  
Steven Mcintosh ◽  
Jennifer Roberts ◽  
Carolyn Czoski Murray ◽  
Richard Edlin
Keyword(s):  
Labour Market ◽  
Policy Evaluation ◽  
Labour Market Policy ◽  
Statistical Control ◽  
Active Labour Market Policy ◽  
Market Policy ◽  
Active Labour ◽  
Non Parametric

scholarly journals Estimation of Treatment Effects in Repeated Public Goods Experiments

Econometrics ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 43
Author(s):  
Jianning Kong ◽  
Donggyu Sul
Keyword(s):  
Public Goods ◽  
Treatment Effects ◽  
Time Varying ◽  
Initial Condition ◽  
Finite Sample ◽  
Cross Sectional ◽  
Public Goods Experiments ◽  
Voluntary Contribution Mechanism ◽  
Average Contribution ◽  
Cross Sectional Average

This paper provides a new statistical model for repeated voluntary contribution mechanism games. In a repeated public goods experiment, contributions in the first round are cross-sectionally independent simply because subjects are randomly selected. Meanwhile, contributions to a public account over rounds are serially and cross-sectionally correlated. Furthermore, the cross-sectional average of the contributions across subjects usually decreases over rounds. By considering this non-stationary initial condition—the initial contribution has a different distribution from the rest of the contributions—we model statistically the time varying patterns of the average contribution in repeated public goods experiments and then propose a simple but efficient method to test for treatment effects. The suggested method has good finite sample performance and works well in practice.

scholarly journals Monte Carlo Comparison for Nonparametric Threshold Estimators

2018 ◽  
Author(s):  
Chaoyi Chen ◽  
Yiguo Sun
Keyword(s):  
Monte Carlo ◽  
Structural Change ◽  
Monte Carlo Method ◽  
Relative Position ◽  
Threshold Level ◽  
Finite Sample ◽  
Tail Part ◽  
Threshold Estimators ◽  
Non Parametric

This paper compares the finite sample performance of three non-parametric threshold estimators via Monte Carlo method. Our results show that the finite sample performance of the three estimators is not robust to the relative position of the threshold level along the distribution of threshold variable, especially when a structural change occurs at the tail part of the distribution.

scholarly journals Rank-based procedures in factorial designs: hypotheses about non-parametric treatment effects

2016 ◽  
Vol 79 (5) ◽  
pp. 1463-1485 ◽  
Author(s):  
Edgar Brunner ◽  
Frank Konietschke ◽  
Markus Pauly ◽  
Madan L. Puri
Keyword(s):  
Treatment Effects ◽  
Factorial Designs ◽  
Non Parametric
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