Khan, Asad ul Islam

Profil fotoğrafı
 E-posta Adresi
asad.khan@ihu.edu.tr
ORCID Profili
0000-0002-5131-577X
WoS Profili
AAJ-6453-2021
Scopus Profili
57204558870
YÖK Araştırmacı Profili
D34BC22808527E8F
Google Akademik Profili
IISCIjsAAAAJ&hl=tr&oi=ao
TR-Dizin Profili
0000-0002-5131-577X
SOBİAD Profili
311599
Web Sitesi
akademik.ihu.edu.tr/tr/asad-khan

Araştırma projeleri

Organizasyon Birimleri

Organizasyon Birimi Logosu
Organizasyon Birimi
Yönetim Bilimleri Fakültesi, İktisat Bölümü
İktisat Bölümü, başta Türkiye ve çevre ülkeler olmak üzere küresel ekonomileri anlayan, var olan sorunları analiz ederken, iktisadi kuramları ve kavramları yetkin ve özgün bir şekilde kullanma becerisine sahip bireyler yetiştirmeyi amaçlamaktadır.

Adı Soyadı

Khan

İlgi Alanları

Solunum Sistemi, Genel ve Dahili Tıp, Çevre Bilimleri ve Ekoloji, İş Ekonomisi, Bilim ve Teknoloji

Kurumdaki Durumu

Aktif Personel

Filtreler

2020 - 20222
Filtreleri Sıfırla

Ayarlar

Konu: Comparison ×

Arama Sonuçları

Listeleniyor 1 - 2 / 2
  • Küçük Resim
    Yayın
    On the ranks of tests having null of cointegration: A Monte Carlo comparison
    (Research Center Public ADM & Public Service, 2020) Khan, Asad ul Islam; Khan, Asad ul Islam; Isac, Nicoleta; Dobrin, Cosmin; Hussan, Mehmood; Khan, Asad ul Islam; Marin, Alina-Andreea; Yönetim Bilimleri Fakültesi, İktisat Bölümü; Yönetim Bilimleri Fakültesi, İktisat Bölümü
    The null of cointegration tests for testing the existence of cointegration are available in literature in great diversity. The selection of a particular test from all these available tests is the crucial problem and often researchers face this. This study is carried out to solve this problem by comparing eight tests on basis two properties of size and power using a new proposed methodology of rank scores. Three different specifications of deterministic component and four sample sizes are considered. It is concluded that if asymptotic critical values are used then it results into an uncontrolled empirical size. While, if the simulated critical values are used, then the empirical size is controlled around nominal size. Moreover, on basis of power, a simple test, which is based on KPSS statistic, is the sole better performer for all of the different 132 different cases of data generations considered in the study.
  • Küçük Resim
    Yayın
    Most stringent test of null of cointegration: A Monte Carlo comparison
    (Taylor & Francis, 2022) Khan, Asad ul Islam; Khan, Asad ul Islam; Khan, Asad ul Islam; Khan, Waqar Muhammad; Hussan, Mehmood; Yönetim Bilimleri Fakültesi, İktisat Bölümü; Yönetim Bilimleri Fakültesi, İktisat Bölümü
    To test for the existence of long run relationship, a variety of null of cointegration tests have been developed in literature. This study is aimed at comparing these tests on basis of size and power using stringency criterion: a robust technique for comparison of tests as it provides with a single number representing the maximum difference between a test’s power and maximum possible power in the entire parameter space. It is found that in general, asymptotic critical values tends to produce size distortion and size of test is controlled when simulated critical values are used. The simple LM test based on KPSS statistic is the most stringent test at all sample sizes for all three specifications of deterministic component, as it has the maximum difference approaching to zero and lesser than 20% for the entire parameter space.