Impact of the COVID-19 pandemic on return and risk transmission between oil and precious metals: Evidence from DCC-GARCH model

It is frequently discussed in the literature that the correlation between low-correlation assets under ordinary market conditions may increase during crisis periods. To contribute to the ongoing debates, this paper empirically examines risk transmission between oil and precious metal markets induced by the COVID-19 pandemic using the DCC-GARCH model. The findings reveal evidence of a significant risk transmission between oil prices and precious metal prices, particularly during the onset of the COVID-19 pandemic. The findings point out that the negative relationship between oil and all precious metals returns in the pre-COVID-19 period has changed with the effect of the pandemic. In this process, it is revealed that the negative relationship between oil and gold has strengthened, but the negative relationship between oil and silver has weakened. In addition, the correlations between oil and platinum and palladium turn positive. The empirical findings imply that investors and portfolio managers seeking portfolio diversification and hedging opportunities in a high-risk environment such as the COVID-19 pandemic should consider gold and silver assets for investment

The relationship between economic growth and employment: A dynamic empirical analysis for TurkeyEkonomik büyüme istihdam ilişkisi: Türkiye için dinamik bir uygulama

The effect of economic growth on employment has become an important topic in the literature with the effect of jobless growth debate in recent years. When we investigate the studies in the literature, we could find a few empirical studies which employ dynamic analysis in order to investigate effects of economic growth on employment for the Turkish economy. In order to fill this gap, we investigate the effect of economic growth on employment dynamically for the Turkish economy covering the period of 2000-2012 employing Kalman filter model. Our results indicate that, we found increasing effect of economic growth on employment at high growth term after the global financial crisis which different from high growth term between 2004-2005. We think that these results depend on the realization of demand postponed in the crisis period. Shortly, the usage of unemployed capacities showed positive effect on growth and employment in the economy after the global crisis.Ekonomik büyümenin istihdam üzerindeki etkisi son yıllarda istihdamsız büyüme tartışmalarının da etkisiyle gittikçe önemi artan konulardan biri haline gelmektedir. Geçmişteki çalışmalar dikkate alındığında Türkiye için büyüme ve istihdam ilişkisini dinamik olarak inceleyen çalışma eksikliği dikkati çekmektedir. Bu boşluğu biraz olsun doldurabilmek amacıyla, bu çalışmada 2000-2012 döneminde Türkiye ekonomisi için ekonomik büyümenin istihdam üzerindeki etkisi dinamik olarak Kalman Filtresi yöntemiyle incelenmiştir. Çalışma sonucunda, 2004-2005 dönemindeki yüksek büyüme dönemlerinden farklı olarak, küresel finansal kriz sonrası yaşanan        yüksek büyüme dönemlerinde büyümenin istihdam üzerindeki etkisinin artığı görülmektedir. Bu sonucun, kriz süresince ertelenen talebin realize edilmesine bağlı olduğunu düşünmekteyiz. Kısacası, kriz sonrası artan büyüme-istihdam ilişkisi atıl kapasitelerin kriz sonrasında kullanılması ile ilişkilendirilmektedir

TÜRKİYE’DE ENERJİ TÜKETİMİ GSYH İLİŞKİSİ: DİNAMİK BİR ANALİZ

Enerji tüketiminin GSYH üzerindeki etkileri Türkiye gibi enerji tüketiminde dışa bağımlılığı yüksek olan ülkelerde özellikle politika yapıcıları için önem arz eden bir konudur. Çalışmada enerji tüketimi GSYH ilişkisi 1970-2011 dönemleri arasında Türkiye ekonomisi için literatürden farklı olarak dinamik olarak incelenmiştir. Çalışmada önce, GSYH ve enerji tüketimi serileri arasındaki eş bütünleşme ilişkisi incelenmiş ve seriler arasında eş bütünleşme ilişkisi bulunmuş, daha sonra seriler arasındaki dinamik ilişki zamana göre değişen parametre yaklaşımı olan Kalman Filtresi modeliyle analiz edilmiştir. Çalışma bulgularına göre, enerji tüketimindeki %1’lik bir artışın GSYH üzerinde yol açacağı yüzdelik artışı ifade eden GSYH’nin enerji tüketimi esnekliğinin 1980-2003 döneminde genel olarak bir azalma eğiliminde olduğu, 2003 yılından itibaren ise söz konusu esneklik değerinin artmaya başladığı görülmektedir. Bu bulgular, Türkiye ekonomisinde özellikle 2003 yılından itibaren sanayide gözlenen, yüksek katma değerli ve enerji tüketiminin yoğun olduğu sektörlere doğru gerçekleşen dönüşümle uyumludur. Söz konusu esneklik değerinin önümüzdeki dönemde artış eğilimini devam ettirmesi halinde, GSYH artışı için enerji tüketiminin öneminin artacağı görülmektedir. Bu durumda Türkiye’nin enerjide yüksek dışa bağımlılığı da düşünüldüğünde enerji arz güvenliği sorunu politika yapıcılar için önemli bir husus olarak ön plana çıkmaktadır. Bu sebeple enerji dengesi içerisinde yerli kaynakların payının mümkün olduğunca arttırılması ve ithal kaynaklarda ise mümkün olduğu kadar ithalatçı ülke çeşitliliğine gidilmesi enerji arz güvenliği için son derece önemlidir

Does credit composition matter for current account dynamics? Evidence from Turkey

Based on a dynamic approach using the Kalman filter we depict effects of time-varying interactions between different components of credit stock on the current account in the Turkish Economy for the period 2002Q3–2014Q3. We decompose the credit stock into consumer and non-financial corporate sector credit and show empirically that both types of credit stock have negative effects on the current account dynamicsWOS:000381516800003Scopus - Affiliation ID: 60105072Social Sciences Citation IndexQ3ArticleUluslararası işbirliği ile yapılmayan - HAYIRKasım2016YÖK - 2016-1

The impact of foreign direct investment on environmental quality: A bounds testing and causality analysis for Turkey

This study aims to investigate the impact of foreign direct investment (FDI), together with gross domestic product (GDP), the square of GDP, and energy consumption, on carbon dioxide (CO2) emissions in Turkey over the period 1974-2010. We employ both the bounds test approach which has superior properties especially in small samples and the Hatemi-J test which takes structural breaks into consideration in the co-integration analysis. Due to the co-integration relationship between CO2 emissions and other variables, the autoregressive distributed lag (ARDL) model is used in order to investigate short and long run elasticity between the variables. The long-run coefficients of the ARDL model indicate that the effect of FDI on CO2 emissions is positive but relatively small, while the effects of the GDP and energy consumption on CO2 emissions are quite considerable. Moreover, the short-run coefficients obtained by the error correction model (ECM) are found to be similar to those of the long-run model. The findings support the validity of the environmental Kuznets curve (EKC) hypothesis in both time-horizons. The vector ECM based Granger causality test is also applied to investigate the causal link. The causality test results indicate the existence of a causality running from all explanatory variables to CO2 emissions in the long run. Overall, the findings suggest that Turkey should promote energy efficiency with sustainable growth, and encourage more FDI inflows particularly in technology-intensive and environment-friendly industries to improve environmental quality. (C) 2015 Elsevier Ltd. All rights reserved

Effect of Inflation Targeting on Inflation Uncertainty: A SWARCH Analysis

We analyse the success of inflation targeting (IT) in decreasing inflation volatility by investigating inflation variance before and after IT. We contribute to the literature by implementing Markov?Switching AutoRegressive Conditional Heteroscedastic methodology to model inflation volatility. After determining the unbiased conditional variances of inflation in each inflation?targeting country, we investigate structural breaks in inflation variability by both analysing individual countries and conducting a panel data analysis. All of these methods conclude that IT helps most of the countries to achieve lower inflation uncertainty (volatility). We also examine the country?specific factors that determine the effectiveness of inflation?targeting adoption

Stationarity Properties of Monthly Employment in Turkey: Conventional, Structural Break and Seasonal Unit Root Tests

İstihdam gerek politika yapıcıları gerekse akademisyenler tarafından çok önemli ve yakından takip edilen bir göstergedir. İstihdam değişkeninin zaman serisi özellikleri kullanılan tahmin yöntemleri ve ekonometrik modellerin geçerliliği açısından önemli yer tutmaktadır. Bu makalede mevsimsellik gösteren bir değişken olan aylık istihdam serisinin durağanlığı, geleneksel, yapısal kırılmalı ve mevsimsel birim kök testleriyle analiz edilmiştir. Literatürde sıklıkla yapıldığı gibi serinin mevsimsellikten arındırılarak devam edildiği ya da mevsimsel birim kök testleri dışındaki birim kök testleriyle durağanlığının incelendiği durumda yanlış sonuçlara gidilebilmektedir. Çalışma sonucunda geleneksel ve yapısal kırılmalı testlerin sonuçlarının mevsimsel birim kök testleri sonuçlarıyla çeliştiği bulunmuştur. Geleneksel ve yapısal kırılmalı testlerin karışık sonuçlar verirken mevsimsel birim kök testlerine göre istihdam serisinin durağan olma eğiliminde olduğu görülmektedir. Bu sonuç Türkiye’de istihdam serisini kullanan çalışmalara, serinin durağanlık özelliklerini değerlendirme aşamasında yön gösterici rol oynayacaktır. Bu çalışma ayrıca mevsimsellik içeren serilerin durağanlık özelliklerini incelerken mevsimsel birim kök sınamalarının daha uygun olabileceğini göstermektedir</p

Mind the gap: Turkish case study of policy change in private pension schemes

Inadequacy of domestic savings in Turkey limits the potential for sustainable growth in the long-term and exacerbates the vulnerabilities associated with dependency on volatile foreign capital flows. The private pension system that was designed to complement public pension system demonstrated limited impact on savings rates. Thus, former tax incentives are replaced by matching contributions as of 2013. Our paper aims to assess the effectiveness of the recent incentives introduced to the private pension system in Turkey. We find that the state contribution has positive significant effect on the number of participants by using alternative asset returns and a dummy variable for state contribution in two samples covering different time periods. We analyze the dynamic time varying interaction between the state contribution and the number of participants in our second sample that focus on post reform period. The model estimated with the dynamic Kalman filter indicates that the positive effect of the state contribution on the number of participants tends to decline slightly in time. We conclude that the fund management in the private pension system should be improved in order to make use of the state incentive efficiently

Determinants of Electricity Prices in Turkey:An Application of Machine Learning and Time Series Models

The study compares the prediction performance of alternative machine learning algorithms and time series econometric models for daily Turkish electricity prices and defines the determinants of electricity prices by considering seven global, national, and electricity-related variables as well as the COVID-19 pandemic. Daily data that consist of the pre-pandemic (15 February 2019–10 March 2020) and the pandemic (11 March 2020–31 March 2021) periods are included. Moreover, various time series econometric models and machine learning algorithms are applied. The findings reveal that (i) machine learning algorithms present higher prediction performance than time series models for both periods, (ii) renewable sources are the most influential factor for the electricity prices, and (iii) the COVID-19 pandemic caused a change in the importance order of influential factors on the electricity prices. Thus, the empirical results highlight the consideration of machine learning algorithms in electricity price prediction. Based on the empirical results obtained, potential policy implications are also discussed

Determinants of Electricity Prices in Turkey: An Application of Machine Learning and Time Series Models

The study compares the prediction performance of alternative machine learning algorithms and time series econometric models for daily Turkish electricity prices and defines the determinants of electricity prices by considering seven global, national, and electricity-related variables as well as the COVID-19 pandemic. Daily data that consist of the pre-pandemic (15 February 2019&ndash;10 March 2020) and the pandemic (11 March 2020&ndash;31 March 2021) periods are included. Moreover, various time series econometric models and machine learning algorithms are applied. The findings reveal that (i) machine learning algorithms present higher prediction performance than time series models for both periods, (ii) renewable sources are the most influential factor for the electricity prices, and (iii) the COVID-19 pandemic caused a change in the importance order of influential factors on the electricity prices. Thus, the empirical results highlight the consideration of machine learning algorithms in electricity price prediction. Based on the empirical results obtained, potential policy implications are also discussed