erhan mugaloglu | Abdullah Gül University (original) (raw)

Papers by erhan mugaloglu

MPRA Paper, 2018

This paper observes the possible co-movements of oil price and CO2 emissions in China by followin... more This paper observes the possible co-movements of oil price and CO2 emissions in China by following wavelet coherence and wavelet partial coherence analyses to be able to depict short-run and long-run co-movements at both low and high frequencies. To this end, this research might provide the current literature with the output of potential short run and long run, structural, changes in CO2 emissions upon a shock (a change) in oil prices in China together with the control variables of World oil prices, fossil energy consumption, and renewables consumption, and, urban population in China. Therefore, this research aims at determining wavelet coherencies between the variables and phase differences to exhibit the leading variable in potential co-movements. By following the time domain and frequency domain analyses of this research, one may claim that the oil prices in China has considerable negative impact on CO2 emissions at high frequencies for the periods 1960-2014 and 1971-2014 in China. Besides, one may underline as well other important output of the research exploring that the urban population and CO2 emissions have positive associations, move together for the period 1960-2014 in China. Eventually, this paper might suggest that authorities follow demand side management policies considering energy demand behavior at both shorter cycles and longer cycles to diminish the CO2 emissions in China.

Springer eBooks, 2020

Renewable Energy

The most important challenge for both developed and developing countries is to ensure sustainabil... more The most important challenge for both developed and developing countries is to ensure sustainability while struggling with environmental degradation. CO 2 emissions as a proxy for environmental degradation can be considered an obstacle to sustainability. There exist several significant works in the literature on the effects of solar energy use on environmental degradation/sustainability. In this study, the effects of the use of solar energy within different time and frequency dimensions on CO 2 emissions were examined with the methodology of the continuous wavelet transform. The paper investigated the association between solar energy consumption and total energy-related CO 2 emissions in the USA through Morlet wavelet analysis, which is one of the most advanced time-frequency analysis methods for the period 1990:1-2022:6. In the wavelet coherency computations, geothermal energy consumption, hydroelectric energy consumption, industrial production, and manufacturing industry production variables were also included as control variables. Empirical findings demonstrate that solar energy consumption can have reducing effects on CO 2 emissions at lower frequencies (longer-term cycles) and sub-time periods (2014:1-2022:1) in the USA. The findings can guide the energy and environmental policies of developed and developing countries that aim to struggle with global warming and/or climate change through the increase in solar energy usage.

Elsevier Science, Oxford/Amsterdam, 2019

Frontiers in Psychology, 2021

This article aims at answering the following questions: (1) What is the influence of age structur... more This article aims at answering the following questions: (1) What is the influence of age structure on the spread of coronavirus disease 2019 (COVID-19)? (2) What can be the impact of stringency policy (policy responses to the coronavirus pandemic) on the spread of COVID-19? (3) What might be the quantitative effect of development levelincome and number of hospital beds on the number of deaths due to the COVID-19 epidemic? By employing the methodologies of generalized linear model, generalized moments method, and quantile regression models, this article reveals that the shares of median age, age 65, and age 70 and older population have significant positive impacts on the spread of COVID-19 and that the share of age 70 and older people in the population has a relatively greater influence on the spread of the pandemic. The second output of this research is the significant impact of stringency policy on diminishing COVID-19 total cases. The third finding of this paper reveals that the n...

Environmental Kuznets Curve (EKC), 2019

Abstract Environmental Kuznets curve (EKC) hypothesis claims that there exists an inverted U-shap... more Abstract Environmental Kuznets curve (EKC) hypothesis claims that there exists an inverted U-shaped relationship between environmental degradation and income. Recent prominent works have been testing EKC by monitoring the influence of economic development on environmental indicators, such as climate change, ozone layer, air quality, water quality, waste generation, etc., as listed by OECD (2008). These papers/projects follow field studies, survey analyses, time series applications, or panel data analyses. However, mathematical calibrations, or time series and/or panel data estimations for EKC, in general, obtain the parameter estimations that do not change within whole sample period. Although some seminal works consider the structural breaks in cross-sectional dependence tests of panel data, they reveal eventually constant estimates in observing the effect of gross domestic income (GDI) on environmental degradation for the observed time period. Few articles aim at detecting the relevant estimates of coefficients with one or two structural breaks in a dynamic structure. The aim of this work is to analyze the EKC by considering all possible shifts (structural breaks) in estimated parameters. To this end, this chapter follows wavelet model estimations at different time periods corresponding to different time frequencies in the United States for the quarterly period 1980:1–2018:2. This chapter eventually explores that, as GDI of the United States increases, carbon dioxide (CO2) emissions tend to increase in the beginning of sample period, whereas it tends to decline during the last years of the observed period. Hence, for the United States, EKC hypothesis is verified by wavelet coherence estimations considering possible strong and weak associations between GDI and CO2.

Renewable and Sustainable Energy Reviews, 2019

In this research, we aim at exploring the influence of renewables on industrial production (Ip) i... more In this research, we aim at exploring the influence of renewables on industrial production (Ip) in the US by following continuous wavelet coherence and partial continuous wavelet coherence analyses. To this end, we observed the co-movements between, biofuels and Ip, solar and Ip, wind and Ip, geothermal and Ip, wood and Ip, and, waste and Ip in the US for the monthly period from January 1989 to November 2016. The primary motivations behind this research are twofold. Firstly, it attempts to reach the co-movements, if exists, between renewables' consumption and industrial production by following time domain and frequency domain analyses. Secondly, it aims at observing the potential co-movements between renewable energy sources (geothermal, solar, wind, biofuels, wood, and, waste) and Ip by adding some control variables (fossil fuels, total biomass etc.) into the wavelet models to understand clearly the responses of the industrial production to the impulses in renewables in both short term and long term periods. The paper hence eventually reveals significant effects of geothermal, wind, solar, biofuels, wood, and, waste on US industrial production in short term cycles and long term cycles. Thereby, following this paper's results of continuous wavelet analyses which depict the impact of renewables on US economy at 1-3-year frequency and 3-8-year frequency for the time period from January 1989 to November 2016, one might provide policy makers with relevant current and future efficient renewables' energy policy for the US and other countries which have similar structures with the US.

Journal of Yaşar University

Despite the unemployment data have been recently released as seasonally adjusted, seasonality may... more Despite the unemployment data have been recently released as seasonally adjusted, seasonality may still exist in moving average (MA) or auto-regressive (AR) terms. This can be detected by searching for a regular pattern in auto-correlation function (ACF) and partial ACF (PACF) diagrams. Therefore, models that aim to forecast unemployment rates should consider their seasonal properties so as to obtain better mean equation estimations. Univariate models mostly employ integrated ARMA (ARIMA) or generalized auto regressive conditional heteroscedastic (GARCH) models or any combination of them. Once the mean equations are structured better, GARCH estimations of variance equation is expected to perform better accuracy in forecasts. This study first examines the ACF's and PACF's of seasonally adjusted unemployment rate data in G-7 countries for 1995-2019 period. Then it compares the 4-quarter and 8-quarter ahead forecast performance of the seasonal ARIMA (SARIMA) coupled volatility models of GARCH in mean, absolute value GARCH, GJR-GARCH, exponential GARCH and asymmetric GARCH models. The performance of these models are also compared to SARIMA and MA filtered volatility models. The results show that seasonality should be reexamined even in seasonally adjusted unemployment data, since SARIMA models outperform ARIMA models in terms of out of sample forecast errors. Besides SARIMA-GARCH models provide better out of sample prediction accuracy.

Econometrics of Green Energy Handbook

We investigate the dynamic relationship between global oil prices, the stock market, and oil and ... more We investigate the dynamic relationship between global oil prices, the stock market, and oil and gas stock (FTSE-OG) returns in the UK through a structural vector autoregressive (VAR) framework during the COVID-19 pandemic. The structural VAR results suggest that the impact of structural shocks related to the global oil price on FTSE-OG index returns becomes less important and loses its explanatory power during the pandemic. However, stock market shocks increase their explanatory power in the variations of FTSE-OG index returns.

Journal of Economic Studies

PurposeThis study aims to measure economic uncertainty in Turkey by a novel economic uncertainty ... more PurposeThis study aims to measure economic uncertainty in Turkey by a novel economic uncertainty index (EUI) employing principal component analysis (PCA). We assess the impact of Covid-19 pandemic in Turkey with our constructed uncertainty index.Design/methodology/approachIn order to obtain the EUI, this study employs a dimension reduction method of PCA using 14 macroeconomic indicators that spans from January 2011 to July 2020. The first principal component is picked as a proxy for the economic uncertainty in Turkey which explains 52% of total variation in entire sample. In the second part of our analysis, with our constructed EUI we conduct a structural vector autoregressions (SVAR) analysis simulating the Covid-19-induced uncertainty shock to the real economy.FindingsOur EUI sensitively detects important economic/political events in Turkey as well as Covid-19-induced uncertainty rising to extremely high levels during the outbreak. Our SVAR results imply a significant decline in e...

Environmental Science and Pollution Research, 2016

In terms of today, one may argue, throughout observations from energy literature papers, that (i)... more In terms of today, one may argue, throughout observations from energy literature papers, that (i) one of the main contributors of the global warming is carbon dioxide emissions, (ii) the fossil fuel energy usage greatly contributes to the carbon dioxide emissions, and (iii) the simulations from energy models attract the attention of policy makers to renewable energy as alternative energy source to mitigate the carbon dioxide emissions. Although there appears to be intensive renewable energy works in the related literature regarding renewables&amp;#39; efficiency/impact on environmental quality, a researcher might still need to follow further studies to review the significance of renewables in the environment since (i) the existing seminal papers employ time series models and/or panel data models or some other statistical observation to detect the role of renewables in the environment and (ii) existing papers consider mostly aggregated renewable energy source rather than examining the major component(s) of aggregated renewables. This paper attempted to examine clearly the impact of biomass on carbon dioxide emissions in detail through time series and frequency analyses. Hence, the paper follows wavelet coherence analyses. The data covers the US monthly observations ranging from 1984:1 to 2015 for the variables of total energy carbon dioxide emissions, biomass energy consumption, coal consumption, petroleum consumption, and natural gas consumption. The paper thus, throughout wavelet coherence and wavelet partial coherence analyses, observes frequency properties as well as time series properties of relevant variables to reveal the possible significant influence of biomass usage on the emissions in the USA in both the short-term and the long-term cycles. The paper also reveals, finally, that the biomass consumption mitigates CO2 emissions in the long run cycles after the year 2005 in the USA.

Crude Oil is one of the most important worldwide traded commodities. Since its derivatives are ma... more Crude Oil is one of the most important worldwide traded commodities. Since its derivatives are main source of energy, it is widely demanding in different industries. World suffers from oil-sourced financial crises, such as 1973 and 1979 oil shocks and in Russia recently. This work aims to examine whether WTI (West Texas Intermediate) and Brent crude oil spot prices have been mean-reverting during the period between 1995 and 2015, or not. To realize this, first crude oil spot prices are assumed to follow a mean-reverting stochastic Ornstein-Uhlenbeck process (Schwartz 1997) and then MLE (Maximum Likelihood Estimation) is employed so as to estimate speed of convergence and long-run mean. Besides, Lee and Strazicich (2003) Lagrange multiplier unit root test with two structural breaks is used in order to validate structural changes in crude oil prices determined endogenously. The stochastic differential equations behind Ornstein-Uhlenbeck process with ITO’s Lemma yields a mean reverting...