KaydedilenlerDerginizi ekleyin

Dergiler / Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi / 2022 / Cilt: 24 - Sayı: 1

Transportation Services, Financial Market, and Industrial Production in the US: Evidence from the Recursive Evolving Causality Test

ABD’de Ulaşım Hizmetleri, Finansal Piyasa ve Endüstriyel Üretim: Özyinelemeli Nedensellik Testinden Elde Edilen Bulgular

Mehmet Aldonat BEYZATLAR
Efe Çağlar ÇAĞLI
Sayfa
183–200
Yayın Tarihi
2022-03-27
DOI
—
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Then we come up with some suggestions that the transportation institutions should modulate the transportation sector's financial structure and intensify to adjust industry structures within transportation mobility before, during, and after recessionary periods.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:This paper examines the relationship between Transportation Services Index (TSI), Dow Jones Transportation Average Index (DJT), and Industrial Production Index (IND) for the United States of America by using monthly data in the period from January 2000 to March 2019.
📊
Temel Bulgular & Veri:The long-run nexus is demonstrated through the cointegration test and dynamic cointegrating regression (Dynamic OLS), both with structural breaks.
💡
Sonuç & Katkı:Then we come up with some suggestions that the transportation institutions should modulate the transportation sector's financial structure and intensify to adjust industry structures within transportation mobility before, during, and after recessionary periods.
🔬Tür:Araştırma Makalesi
📍Kapsam:2000 Verileri
⚙️Değişkenler:Transportation services index · Dow Jones transportation index · industrial production index

Özet

This paper examines the relationship between Transportation Services Index (TSI), Dow Jones Transportation Average Index (DJT), and Industrial Production Index (IND) for the United States of America by using monthly data in the period from January 2000 to March 2019. The long-run nexus is demonstrated through the cointegration test and dynamic cointegrating regression (Dynamic OLS), both with structural breaks. The results show that the long-run relations proved by both tests from IND to TSI, IND to DJT, and two-sided between DJT and TSI. More importantly, the Granger-causality relationship is revealed with the forward, rolling, and recursive evolving window algorithms. This is the first study in the literature investigating the causality ties in transportation measures using the novel econometric methodology, following the algorithms. The rolling and recursive causality results detect bi-directional causality between IND and TSI, IND and DJT, and TSI and DJT. Then we come up with some suggestions that the transportation institutions should modulate the transportation sector's financial structure and intensify to adjust industry structures within transportation mobility before, during, and after recessionary periods.

Abstract

Bu makale, Amerika Birleşik Devletleri için Ulaşım Hizmetleri Endeksi (TSI), Dow Jones Ulaşım Ortalama Endeksi (DJT) ve Endüstriyel Üretim Endeksi (IND) arasındaki ilişkiyi Ocak 2000'den Mart 2019'a kadar olan dönemdeki aylık verileri kullanarak incelemektedir. Uzun dönemli bağ, her ikisi de yapısal kırılmaları dikkate alan eşbütünleşme testi ve dinamik eşbütünleşme regresyonu (Dinamik OLS) ile gösterilmektedir. Sonuçlar, uzun dönemli ilişkilerin IND'den TSI'ye, IND'den DJT'ye ve DJT ile TSI arasında iki yönlü testlerle kanıtlandığını göstermektedir. Daha da önemlisi, Granger-nedensellik ilişkisi ileri, yuvarlanan ve özyinelemeli pencere algoritmalarıyla ortaya çıkar. Bu, algoritmaları takip ederek yeni ekonometrik metodolojiyi kullanarak ulaşım ölçülerindeki nedensellik bağlarını araştıran literatürdeki ilk çalışmadır. Yuvarlanan ve özyinelemeli nedensellik sonuçları, IND ile TSI, IND ve DJT ve TSI ve DJT arasındaki iki yönlü nedenselliği tespit eder. Ardından ulaşım kuruluşlarının, ulaşım sektörünün finansal yapısını modifiye etmesi ve durgunluk dönemlerinden önce, sırasında ve sonrasında ulaşım hareketliliği içinde endüstri yapılarını yeniden düzenlemeye yoğunlaşması gerektiği yönünde bazı öneriler getirmekteyiz.

🔖

Bu Makaleye Atıf Yap

BEYZATLAR, M. A., ÇAĞLI, E. Ç. (2022). Transportation Services, Financial Market, and Industrial Production in the US: Evidence from the Recursive Evolving Causality Test. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, Cilt: 24 - Sayı: 1, 183–200. https://ajindex.com/articles/389916

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (14)

  1. Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 47-78.
  2. Bai, J., & Perron, P. (2003). Computation and analysis of multiple structural change models. Journal of Applied Econometrics, 18(1), 1-22.
  3. Baker, D., Merkert, R., & Kamruzzaman, M. (2015). Regional aviation and economic growth: Cointegration and causality analysis in Australia. Journal of Transport Geography, 43, 140–150. https://doi.org/10.1016/j.jtrangeo.2015.02.001
  4. Banister, D., & Berechman, Y. (2001). Transport investment and the promotion of economic growth. Journal of Transport Geography, 9(3), 209–218. https://doi.org/10.1016/S0966-6923(01)00013-8
  5. Barro, R. J. (1990). The Stock Market and Investment. The Review of Financial Studies, 3(1), 115–131.
  6. Bencivenga, V. R., Smith, B. D., & Starr, R. M. (1996). Equity markets, transactions costs, and capital accumulation: An illustration. World Bank Economic Review, 10(2), 241–265. https://doi.org/10.1093/wber/10.2.241
  7. Beyzatlar, M. A., & Yetkiner, H. (2017). Convergence in transportation measures across the EU-15. Transportation, 44(5), 927–940. https://doi.org/10.1007/s11116-016-9686-6
  8. Beyzatlar, M. A., Karacal, M., & Yetkiner, H. (2014). Granger-causality between transportation and GDP: A panel data approach. Transportation Research Part A: Policy and Practice, 63, 43–55. https://doi.org/10.1016/j.tra.2014.03.001
  9. Boarnet, M. G. (1996). The Direct and Indirect Economic Effects of Transportation Infrastructure. UCTC Working Paper, 340(340), 1–29.
  10. Bose, N., & Haque, M. E. (2005). Causality Between Public Investment in Transport and Communication and Economic Growth. Journal of Economic Development, 30(1), 95–106. https://doi.org/10.2139/ssrn.764465
  11. Brueckner, J. K. (2003). Airline Traffic and Urban Economic Development. Urban Studies, 40(8), 1455–1469. https://doi.org/10.1080/0042098032000094388
  12. Brugnoli, A., Dal Bianco, A., Martini, G., & Scotti, D. (2018). The impact of air transportation on trade flows: A natural experiment on causality applied to Italy. Transportation Research Part A: Policy and Practice, 112, 95–107. https://doi.org/10.1016/j.tra.2018.01.010
  13. Button, K., & Taylor, S. (2000). International air transportation and economic development. Journal of Air Transport Management, 6(4), 209–222. https://doi.org/10.1016/S0969-6997(00)00015-6
  14. Button, K., & Yuan, J. (2013). Airfreight Transport and Economic Development: An Examination of Causality. Urban Studies, 50(2), 329–340. htt