Publication: Gelişmiş ve gelişmekte olan ülkelerdeki suç oranlarının iktisadi büyüme üzerindeki etkisinin panel veri modelleri ile analizi
Abstract
Ülkeden ülkeye, bölgeden bölgeye, toplumdan topluma ve insandan insana değişen yasalara aykırı davranış biçimi olarak tanımlanan olgunun adı suçtur. Dünyada var olan bu suç olgusu ülkelerin iktisadi büyümesi üzerinde oldukça etkilidir. Bu etkide bu olgunun nedenleri, nasıl engellenebileceği ve sonuçları hakkında bilgi sahibi olunması gereklidir.Çalışmada gelişmiş ve gelişmekte olan 47 ülke için 2000-2018 dönemi verilerinden yararlanılarak suç oranının iktisadi büyüme üzerindeki etkisin panel veriyle saptanmıştır. Bu noktada yol gösterici olarak panel verinin zaman serisi ve yatay kesit boyutunu birlikte ele alması araştırmacılar için incelemiş olduğu konularda farklı bakış açıları kazanmasını sağlamaktadır.İlk olarak panel veri modelin sabit ya da rassal etkili olduğunu belirlemek amacıyla Hausman testi yapılmıştır. Söz konusu test sonucunda modelin sabit etkiler modeline uygun olduğuna karar verilmiştir. Bu aşamadan sonra, modelin ekonometrik varsayımlara uygunluğuna dair testler yapılmış, ortaya çıkan varsayımlardan sapmaları kaldırmak için gerekli düzeltmeler yapıldıktan sonra panel birim kök testleri kullanılarak serilerde birim kökün varlığı incelenmiştir. Durağanlık mertebeleri belirlenen değişkenlerle yeni bir model kurularak bu model için de varsayımlardan sapmalar incelenip gerekli düzeltmeler yapıldıktan sonra meydana gelen değişimler açıklanmıştır.
The name of the phenomenon is defined as a crime which is defined as a violation of laws that vary from country to country, from region to region, from society to society and from people to people. This crime phenomenon that exists in the world is very effective on the economic growth of countries. In this effect, it is necessary to be informed about the causes of this phenomenon, how it can be prevented and its consequences.In the study, the impact of the crime rate on economic growth was determined with panel data by using the data of 2000-2018 period for 47 developed and developing countries. At this point, the fact that the panel data handles the time series and the horizontal cross-section dimension together provides a different perspective for the researchers.Firstly, Hausman test was performed to determine whether the panel data model is fixed or random. As a result of the test in question, it was decided that the model was suitable for the fixed effects model. After this stage, tests were made on the compatibility of the model with the econometric assumptions, and after the necessary corrections were made to remove the deviations from the emerging assumptions, the existence of the unit root in the series was examined by using panel unit root tests. By establishing a new model with the variables whose stationarity levels are determined, the changes that occur after the deviations from the assumptions are examined and necessary corrections are made for this model.
The name of the phenomenon is defined as a crime which is defined as a violation of laws that vary from country to country, from region to region, from society to society and from people to people. This crime phenomenon that exists in the world is very effective on the economic growth of countries. In this effect, it is necessary to be informed about the causes of this phenomenon, how it can be prevented and its consequences.In the study, the impact of the crime rate on economic growth was determined with panel data by using the data of 2000-2018 period for 47 developed and developing countries. At this point, the fact that the panel data handles the time series and the horizontal cross-section dimension together provides a different perspective for the researchers.Firstly, Hausman test was performed to determine whether the panel data model is fixed or random. As a result of the test in question, it was decided that the model was suitable for the fixed effects model. After this stage, tests were made on the compatibility of the model with the econometric assumptions, and after the necessary corrections were made to remove the deviations from the emerging assumptions, the existence of the unit root in the series was examined by using panel unit root tests. By establishing a new model with the variables whose stationarity levels are determined, the changes that occur after the deviations from the assumptions are examined and necessary corrections are made for this model.