Different bootstrap methods and estimation techniques for inference for structural vector autoregressive (SVAR) models identified by generalized autoregressive conditional heteroskedasticity (GARCH) are reviewed and compared in a Monte Carlo study. .
In this comment on Callen et al. (2014), I revisit recent evidence uncovering a "preference for certainty" in violation of dominant normative and descriptive theories of decision-making under risk. I show that the empirical findings are potentially .
The performance of information criteria and tests for residual heteroscedasticity for choosing between different models for time‐varying volatility in the context of structural vector autoregressive analysis is investigated. Although it can be ...
The central limit theorem says that, provided an estimator fulfills certain weak conditions, then, for reasonable sample sizes, the sampling distribution of the estimator converges to normality. We propose a procedure to find out what a “reasonably .
We compare three recently developed frontier estimators, namely the conditional DEA (Daraio and Simar, 2005; 2007b), the latent class SFA (Greene, 2005; Orea and Kumbhakar, 2004), and the StoNEZD approach (Johnson and Kuosmanen, 2011) by means of ...
EDDI18 is organized jointly by SOEP - The German Socio-Economic Panel, GESIS - Leibniz Institute for the Social Sciences and IDSC of IZA - International Data Service Center of the Institute for the Study of Labor. The conference will bring together ...
When designing stated-choice experiments modellers may consider offering respondents an “indifference” alternative to avoid stochastic choices when utility differences between alternatives are perceived as too small. By doing this, the modeller ...
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