Document Type : Research Paper
Authors
1 Department of Economics, University of Isfahan, Isfahan, Iran
2 Department of Economics, University of Isfahan, Isfahan,Iran
Abstract
Propensity score matching is extensively utilized in estimating the effects of policy interventions and programs for data observations. This method compares two treatment and control groups to make statistical inferences about the significance of the effects of these policies on target variables. Therefore, when using propensity score matching, it is significant to obtain the standard error to estimate the treatment effect. The precise estimations of variance and standard deviation facilitate more efficient statistical testing and more accurate confidence intervals. However, there is no agreement in the literature on the estimation method of standard error; some methods rely on resampling, while others do not. This study compares these methods using Monte Carlo simulation and calculating the Mean Squared Errors (MSE) of these estimators. Our results indicate that Jackknife and standard methods are superior to Abadie and Imbens (2006) bootstrap, and subsampling ones in terms of accuracy. Finally, reviewing Tayyebi et al. (2019) indicated that different methods of estimating variance in the matching estimator led to different statistical inferences in terms of statistical significance.
Keywords
Main Subjects
Article Title [Persian]
مقایسه‌ی روشهای متفاوت برآورد واریانس در برآوردگر مچینگ ضریب تمایل
Authors [Persian]
- علیرضا کمالیان 1
- سید کمیل طیبی 1
- علیمراد شریفی 1
- هادی امیری 2
1 دانشکده اقتصاد، دانشگاه اصفهان، اصفهان، ایران
2 دانشکده اقتصاد، دانشگاه اصفهان، اصفهان، ایران
Abstract [Persian]
مچینگ ضریب تمایل به وفور برای تخمین اثر برنامه و مداخلات سیاستی برای داده های مشاهده‌ای استفاده شده است. این روش با مقایسه ی میان دوگروه درمان و کنترل به استنتاج آماری درباره معنی داری تاثیر این سیاستها بر متغیرهای هدف می پردازد و به همین دلیل یکی از موضوعات مهم در هنگام استفاده از مچینگ ضریب تمایل، برآورد انحراف معیار برای تخمین اثر درمان است. برآورد دقیق واریانس و انحراف معیار،آزمون آماری کاراتر و فاصله اطمینان دقیق تر را ممکن می سازد. با این حال اختلافات بسیاری در ادبیات چگونگی تخمین انحراف معیار وجود دارد. برخی از این روش‌ها مبتنی بر بازنمونه‌گیری و برخی مستقل از آن است. در این پژوهش با به‌کارگیری شبیه‌سازی مونت کارلو و محاسبه‌ی میانگین حداقل مربعات خطای این برآوردگرها( MSE) به مقایسه این روش‌ها پرداخته شده‌است. نتایج شبیه‌سازی در این مطالعه دلالت بر مزیت روشهای جکنایف و استاندارد نسبت به روش های آبادی-ایمبنز ، بوت استرپ و زیرنمونه داشته‌است. در پایان نیز با بررسی مقاله طیبی و همکاران نشان داده شد که روش های مختلف برآورد واریانس در برآوردگر مچینگ منجر به استنتاج آماری متفاوت از لحاظ معنی داری آماره ها می شد.
Keywords [Persian]
- مچینگ
- ضریب تمایل
- مونت‌کارلو
- بازنمونه‌گیری
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