Investigation of the Factors Affecting the Homicide Counts in the USA by Quantile Regression

Year 2020, Volume: 11 Issue: Ek (Suppl.) 1, 346 - 363, 29.12.2020

Oğuzhan Demirel

https://doi.org/10.29048/makufebed.744870

Abstract

This study has conducted in the United States of America (USA) in the 1960s, 1970s, 1980s, and 1990s to determine whether divorce rates, unemployment rates, and the population had an impact on homicide numbers. Initially, all variables were examined and interpreted geographically on the map by districts. Subsequently, the stationary circumstance of variables has been tested with the Augmented Dickey-Fuller (ADF) Test, which is one of the unit root tests. After it has found that the variables did not need to stabilize, regression analysis has performed by the Least Squares (LS) method. Quantile regression, which is an alternative method to the LS method, has been used since all the resulting models do not have a normal distribution. These models have been created with 3 diverse quantile values for each period. Among these models, the ones with the highest correlation coefficient are the models having the 0.75 quantile value. Therefore, the results have been obtained from models with the 0.75 quantile value. Hence, for the homicide counts in the USA, those have found that the country population had a positive effect in the 1960s, the country population and the divorce rates had positive effects in the 1970s, the country population had a positive effect in the 1980s, and the country population and the unemployment rates had positive effects in the 1990s. Furthermore, the unemployment rates in the 1970s and 1980s had a negative effect on the homicide counts in the USA.

Keywords

Homicide counts, GeoDa, Least squares method, Quantile regression, the USA homicide

ABD'de Cinayet Sayısını Etkileyen Faktörlerin Kantil Regresyon ile İncelenmesi

Abstract

Bu çalışma, 1960, 1970, 1980 ve 1990'larda ABD'deki boşanma oranlarının, işsizlik oranlarının ve ülke nüfusunun cinayet sayılarını etkileyip etkilemediğini belirlemek amacıyla yapılmıştır. İlk olarak, tüm değişkenler harita üzerinde bölgeler tarafından coğrafi olarak incelenmiş ve yorumlanmıştır. Ardından değişkenlerin durağanlık durumu, birim kök testlerinden biri olan ADF testi ile test edilmiştir. Değişkenlerin durağanlaştırılmasına gerek olmadığı tespit edildikten sonra, en küçük kareler (EKK) yöntemi ile regresyon analizi yapılmıştır. Elde edilen tüm modellerin normal dağılım göstermemesi nedeniyle, EKK yöntemine alternatif bir yöntem olan kantil regresyon kullanılmıştır. Oluşturulan bu modellerde, her bir dönem için 3 farklı kantil değeri kullanılmıştır. Bu modeller arasında 0,75 kantil değerine sahip modeller, en yüksek korelasyon katsayına sahiptir. Bu nedenle 0,75 kantil değerine sahip modeller kullanılarak sonuçlar elde edilmiştir. Elde edilen bu sonuçlara göre, ABD’deki cinayet sayıları için; 1960'larda yalnızca ülke nüfusunun olumlu bir etkisi olduğu, 1970'lerde ülke nüfusunun ve boşanma oranlarının olumlu etkileri olduğu, 1980'lerde ülke nüfusunun olumlu bir etkisi olduğu ve son olarak ülke nüfusunun ve işsizlik oranlarının 1990'larda olumlu etkilerinin olduğu bulunmuştur. Ayrıca, işsizlik oranlarının 1970 ve 1980'lerde cinayet sayıları üzerinde olumsuz bir etkisinin olduğu sonucu da elde edilmiştir.

Keywords

Cinayet sayıları, GeoDa, En küçük kareler yöntemi, Kantil regresyon, ABD cinayet

References

• Abadie, A., Angrist, J., Imbens, G. (2002). Instrumental vari-ables estimates of the effect of subsidized training on the quantiles of trainee earnings. Econometrica 70(1): 91-117.
• Baller, R., Anselin, L., Messner, S., Deane, G., Hawkins, D. (2001). Structural covariates of us county homicide rates, incorporating spatial effects. Criminology 39: 561-590.
• Davino, C., Furno, M., Vistocco, D. (2013). Quantile Regression, Theory and Applications. John Wiley and Sons.
• Dickey, D.A., Fuller, W.A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association 74(366): 427-431.
• Dickey, D.A., Fuller, W.A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, Journal of the Econometric Society 49(4): 1057-1072.
• Djuraidah, A., Wigena, A.H. (2011). Regression quantile for exploration rainfall patterns in indramayu. A Basic Sciences 12(1): 50-56.
• Foussier, P. (2010). Improving CER building, basing a cer on the median. Journal of Cost Analysis and Parametrics 3(2): 1-12.
• GeoDa Data and Lab (2003). Homicides + socio-economics (1960-90). https://geodacenter.github.io/data-and-lab/ncovr/. (Access Date: 12.19.2019).
• Hosseini, S.M., Ahmad, Z., Lai, Y.W. (2011). The role of macroeconomic variables on stock market index in China and India. International Journal of Economics and Finance 3(6): 233-143.
• Humphreys, D., Gasparrini, A., Wiebe, D. (2017). Evaluating the impact of Florida's "stand your ground" self-defense lawon homicide and suicide by firearm, an interrupted time series study. JAMA Internal Medicine 177(1): 44-50.
• Darity, W.A. (2008). Ordinary least squares regression. International Encyclopedia of the Social Sciences 2(6): 57-61.
• Koenker, R., Hallock, K.F. (2001). Quantile regression. Journal of Economic Perspectives 15: 143-56.
• Koenker, R. (2005). Quantile Regression. London, Cambridge University Press, 1-30.
• Kposowa, A., Breault, K., Harrison, B. (1995). Reassessing the structural covariates of violent and property crimes in the USA, a county level analysis. The British Journal of Sociology 46(1): 79.
• Messner, S.F., Anselin, L., Hawkins, D., Deane G., Tolnay S., Baller, R. (2000). An atlas of the spatial patterning of county level homicide, 1960-1990. Pittsburgh, National Consortium on Violence Resarch, Carnegie-Mellon University.
• Mushtaq, R. (2012). Augmented Dickey Fuller Test. SSRN Electronic Journal, 1-19.
• Ousey, G.C., Kubrin, C.E. (2014). Immigration and the changing nature of homicide in us cities, 1980-2010. Journal of Quantitative Criminology 30: 453-483.
• Sen, B., Wingate, M., Kirby, R. (2012). The relationship between state abortion-restrictions and homicide deaths among children under 5 years of age, a longitudinal study. Social Science and Medicine 75(1): 156-164.
• Sipsma, H., Canavan, M., Rogan, E., Taylor, L.A., Talbert-Slagle, K.M., Bradley, E.H. (2017). Spending on social and public health services and its association with homicide in the USA, an ecological study. BMJ Open 7(10): 1-7.
• Time (1979). Business: Oil Squeeze. http://content.time.com/time/magazine/article/0,9171,946222,00.html (Access Date: 29.12.2019).
• What-when-how (2019). Ordinary least squares regression (social science). http://what-when-how.com/social-sciences/ordinary-least-squares-regression-social-science/ (Access Date: 12.22.2019).
• Yavuz, A.A., Aşik, E.G. (2017). Quantile regression. Internati-onal Journal of Engineering Research and Development 9(2): 137-146.