کاربرد تحلیل خوشه‌ای و تحلیل عاملی در مطالعات اقتصادی و محیط‌زیستی چندمقطعی با استفاده از مؤلفه‌های مؤثر

نویسندگان
1 دانشگاه تهران
2 پژوهشکده امور اقتصادی وزارت امور اقتصادی و دارایی
چکیده
همگنی گروه‌ها در مطالعاتی که از روش‌های چند مقطعی استفاده می‌نمایند از اهمیت ویژه‌ای برخوردار است. این امر در مطالعات اقتصادی بویژه مطالعات متکی بر روش داده‌های تابلویی برای اعتبار نتایج و برآوردها اهمیت زیادی دارد. در تحلیل‌های چند مقطعی با مقاطع زیاد، بویژه تحلیل‌های مبتنی بر داده‌های تابلویی، خوشه‌بندی ضمن افزایش اطمینان از همگنی موردنظر و استحکام و اعتبار نتایج بدست‌آمده، امکان مقایسه گروه‌های مختلف با ویژگی‌های متفاوت را نیز فراهم می‌آورد. در این مقاله به ارائه روش‌های مرسوم در خوشه‌بندی و همگن‌سازی گروه‌ها در مطالعات چند مقطعی اقتصادی و محیط‌زیستی بر مبنای مؤلفه‌های مؤثر پرداخته شده است. بدین منظور نمونه‌ای متشکل از 92 کشور با بیشترین میزان انتشار CO2 در دوره زمانی 1990 تا 2012 که داده‌های مربوط به آنها در این دوره در دسترس بوده است، براساس 18 معیار مؤثر خوشه‌بندی شده‌اند. معیارهای مذکور با استفاده از تحلیل عاملی به پنج مؤلفه اصلی تقلیل پیدا کرده و خوشه‌بندی کشورها به روش سلسله مراتبی بر مبنای مؤلفه‌های اصلی (HCPC) انجام شده است. انجام خوشه‌بندی به تفکیک 92 کشور به هفت خوشه متفاوت هرکدام با ویژگی‌های خاص منجر شده است. بررسی مشخصات غالب کشورها، نشان از همگنی در هر یک از خوشه‌های مشخص‌شده دارد.
کلیدواژه‌ها

عنوان مقاله English

Using Clustering and Factor Analysis in Cross Section Analysis Based on Economic-Environment Factors

نویسندگان English

Vahid Majed 1
Hossein Mirshojaeian Hosseini 2
Samira Riazi ِdoust 1
1 University of Tehran
2 Economic Affairs Research Institute
چکیده English

Homogeneity of groups in studies those use cross section and multi-level data is important. Most studies in economics especially panel data analysis need some kinds of homogeneity to ensure validity of results. This paper represents the methods known as clustering and homogenization of groups in cross section studies based on enviro-economics components. For this, a sample of 92 countries which produce the most greenhouse gases including CO2, clustered based on 18 criteria. Those criteria reduced to five primary components using factor analysis. Clustering of countries done by HCPC (Hierarchical Clustering on Principal Component) method. All 92 countries were clustered in 7 different groups. For each group properties of countries indicates the homogeneity of each cluster. In cross section analysis with many sections, especially analysis based on panel data, clustering, increases assurance of expected homogeneity and validity of result.

کلیدواژه‌ها English

Dentist Cluster Analysis
Factor analysis
Cross Section Studies
Enviro-Economic Components
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