Double-Robust Identification for Causal Panel Data Models

a new approach to credibility premium for zero-inflated poisson models for panel data

هدف اصلی از این تحقیق به دست آوردن و مقایسه حق بیمه باورمندی در مدل های شمارشی گزارش نشده برای داده های طولی می باشد. در این تحقیق حق بیمه های پبش گویی بر اساس توابع ضرر مربع خطا و نمایی محاسبه شده و با هم مقایسه می شود. تمایل به گرفتن پاداش و جایزه یکی از دلایل مهم برای گزارش ندادن تصادفات می باشد و افراد برای استفاده از تخفیف اغلب از گزارش تصادفات با هزینه پائین خودداری می کنند، در این تحقیق ...

Robust Priors in Nonlinear Panel Data Models Robust Priors in Nonlinear Panel Data Models

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Improved double-robust estimation in missing data and causal inference models.

Recently proposed double-robust estimators for a population mean from incomplete data and for a finite number of counterfactual means can have much higher efficiency than the usual double-robust estimators under misspecification of the outcome model. In this paper, we derive a new class of double-robust estimators for the parameters of regression models with incomplete cross-sectional or longit...

Causal Inference with Panel Data

For nearly half a century, the fundamental problem for statistical analysis in the social sciences has been how to make causal inferences from nonexperimental data (Blalock 1961). For nearly as long, there has been a widespread consensus that the best kind of nonexperimental data for making causal inferences is longitudinal data. Unfortunately, there has not been nearly as much consensus on the...

Binary Response Models for Panel Data: Identification and Information