Frequency Domain Causality Analysis Research Articles

Do clean energy and dependence on natural resources stimulate environmental sustainability? A new approach with load capacity factor and temperature

AbstractIndia, not being an exception from the rest of the globe, has also been suffering from the unprecedented challenges of survival of the ecosphere, which is highly threatened by a continuous weakening of the environmental quality as a result of accelerated accumulation of anthropogenic emissions in the biosphere. As an immediate aftermath of the famous Glasgow Conference of Parties (COP26), while the Government of India is aiming to find realistic solutions to achieve net zero emissions goals by 2070 without much confrontion with its ambitious economic progression goals, accordingly proposes the alternative pathway to achieve environmental sustainability goals, this study has considered one of the three pivotal drivers of economic sustainability in the modern era of digitization, that is, natural resources rent, renewable energy consumption, and economic growth and examined their role on rendering environmental sustainability. Instead of CO2 emissions, load capacity factor and temperature have been considered proxies of environmental quality. This study has employed a novel dynamic autoregressive distributed lag (ARDL) estimation technique to portray the short‐ and long‐run elasticity of environmental quality indicators by considering 48 years of annual time series data from 1970 to 2017. The findings of this study have documented that while natural resources rent and economic growth stimulate environmental squalor, renewable energy consumption promotes environmental sustainability. This study also unveiled different causal relationships using the frequency domain causality analysis. Subsequently, this study designs some vital policy measures and integration of which in the existing energy‐climate framework may assist Indian policymakers in achieving the net zero climate goal.

Outperforming the market: a comparison of Star and NonStar analysts’ investment strategies and recommendations

AbstractWe employ StarMine to investigate the impact of analyst recommendations on stock performance. We test whether star-ranked analysts generate abnormal returns and outperform non-stars in short and long portfolios. Utilizing buy-and-hold calendar-time portfolio methodology, we calculate portfolio alphas using various asset pricing models, including CPM, the Fama and French 3-factor model, and the Carhart 4-factor model. Results indicate that all analyst groups can generate abnormal returns exceeding the market average. Star-ranked analysts outperform non-stars in short portfolios by 0.5523% in monthly alpha, though no significant difference exists in long portfolio alphas. We also conduct regressor endogeneity tests and explore investor sentiment mechanisms by utilizing the GARCH model and frequency-domain causality analysis, with NASDAQ as a proxy for investor sentiment. These tests reveal that the momentum factor is exogenous, and investor sentiments have a statistically significant positive effect on stock return volatility, with changes occurring between 5 and 10 days. This research underscores the value of analyst insights for investors, validates StarMine’s ranking effectiveness, and suggests market participants can benefit from incorporating analyst recommendations into their investment decisions. Our study makes a significant contribution to the existing literature by introducing a novel approach to understanding investor sentiment mechanisms through a causality model.

Can Energy Efficiency Promote Human Development in a Developing Economy?

It has recently been underscored that access to energy has adverse impacts upon human development in South Asia. In this paper, we apply different variants of the autoregressive distributed lag (ARDL) model to explain how improved access to energy might adversely impact human development in India over 1980–2018. From the basic ARDL model, a 1% increase (decrease) in energy efficiency will increase (lower) human development by 6.1% in the long run. We note that the causality runs from energy efficiency to human development. The application of the novel dynamic ARDL simulations offers two insights; first, it confirms the importance of energy efficiency for driving human development. Secondly, it shows asymmetric effects: we find that a 10% increase in energy efficiency boosts human development from 7% to 12% in the long run, while a 10% decrease in energy efficiency lowers human development from 7% to 3%. Using the frequency domain causality analysis, we establish that energy efficiency drives human development in India. We also explore the symmetric and asymmetric impacts of several control variables on human development in India. Our findings establish that energy efficiency will not only help India reduce its environmental footprint but also propel human development.

The nexus of disaggregated energy sources and cement production carbon emission in China

Cement production reportedly accounts for the largest global materials flow, thus achieving global environmental sustainability through responsible consumption and production is central to the sustainable development scenario. But even that China, the world's largest carbon emitter and largest cement producer, is under-studied. Thus, the current study employed the nonlinear ARDL and frequency domain causality methods to unearth the contributory or mitigating role of energy sources and economic progress in China's cement carbon emission (CCE) over the period 1971-2020. Overall, the study establishes long-run equilibrium relationship between the study variables of interest Subsequently, the baseline regression suggests that a positive shift in economic growth, energy from fossil fuel and primary energy consumption all increase emissions while a negative shift does not have a significant effect on emissions. Moreover, a positive (negative) shift in renewable energy decreases (increases) emissions in both the short and long-run. The result of the Frequency Domain causality analysis resonates with the results of NARDL regression. As a policy, this study infers energy development and economic-related measures are strategically important in achieving sustainable cement production and consumption.

The Relationship Between the Health Services Price Index and The Real Effective Exchange Rate Index in Turkey: A Frequency Domain Causality Analysis

This paper examines whether the causal relationship between the health care price index and the real exchange rate index is temporary or permanent. To do this, we first apply the Toda- Yamamoto causality test with a structural break and then continue with frequency domain causality tests based on the Toda-Yamamoto causality test with a structural break. The results of the Toda- Yamamoto causality test with a structural break indicates that there is causality running from the real exchange rate index to the health care price index. Moreover, the frequency domain causality test results based on the Toda-Yamamoto causality test with a structural break provide evidence that the real effective exchange rate causes temporarily (in the short-and medium term) to the health care price index. The effect of the real exchange rate index on the health care price index lasts between 2 months and 8.37 months. These findings imply that there is a significant exchange rate pass-through in health care inflation in the short-and medium term. Thus, the health authorities should take into account these findings when planning health care policies in Turkey, especially health care services heavily dependent on imported materials.

The Nexus Between Fiscal Decentralization and Environmental Sustainability in Japan

This paper adds to the existing body of knowledge by incorporating the role of fiscal decentralization (FD) in influencing CO2 emissions. Therefore, this study looked at the effect of FD on CO2 emissions in the presence of nonrenewable energy consumption (NRE), renewable energy consumption (REN), gross domestic product (GDP), and trade openness (TOP) for the period 1994–2018 in Japan. Thus, the current work intends to fill this knowledge gap by employing econometric techniques such as Bayer and Hanck cointegration, dynamic ordinary least squares (DOLS), fully modified ordinary least squares (FMOLS), and canonical cointegration regression (CCR). Additionally, the frequency domain causality analysis is used in the investigation to determine the causal impact of FD, NRE, REN, GDP, and TOP on CO2 emissions. The novelty of the frequency-domain approach is that it can differentiate between nonlinearity and causality levels and show causality among parameters with different frequencies. The DOLS, FMOLS, and CCR results reveal that NRE, GDP, and TOP augment CO2 emissions in Japan, whereas FD and REN increase the quality of the atmosphere. Furthermore, the frequency causality test results show that FD, REN, GDP, and TOP have implications for CO2 emissions in the long run, while NRE raises CO2 emissions in the medium run. As a policy direction, the current study suggests expanding renewable energy consumption in Japan by emphasizing more on Sustainable Development Goals (7, 8, and 13).

Mexico at the crossroads of natural resource dependence and COP26 pledge: Does technological innovation help?

The nexus between natural resource depletion and environmental quality has been a heated topic of debate among policy experts in recent years. This nexus is crucial to achieve Sustainable Development Goal (SDG) 13 which deals with climate change mitigation. However, the extant literature has not paid due attention to this nexus, particularly in the case of Mexico. Against this backdrop, the present study examines the relationship between ecological footprint and natural resource depletion, economic growth, energy consumption, technological innovation, and foreign direct investment in the Mexican economy. The present research leverages the novel dynamic autoregressive distributed lag (ARDL) simulations approach and uses annual frequency data from 1980 to 2018. Empirical findings from the ARDL bounds test substantiate the presence of long-run association among studied variables. Furthermore, the result of the novel dynamic ARDL simulation does not validate the Environmental Kuznets curve (EKC) hypothesis. Thus, implying that Mexico's economy remains at the scale stage, with a scope of economic expansion relative to environmental quality. However, the Pollution Haven Hypothesis (PHH) is validated. Interestingly, natural resource rent accompanied with energy use and foreign direct investment deteriorate the environmental quality in the short-and long-run. However, technological innovation seems to emanate as a panacea for environmental degradation in the long-run. Result analysis also demonstrates that 10% positive and negative simulation graphs for the studied variables. The Frequency Domain Causality analysis also corroborates the above findings. These findings have far-reaching policy implications for Mexico's sustainable environment amid prudent use of natural resources, which are prescribed in the final section.

The Relationship between Globalization and Energy Consumption in Turkey: Frequency Domain Causality Analysis

Küreselleşme süreci olumlu ve olumsuz yönleriyle geçmişten bugüne tartışılan konuların başında gelmektedir. Özellikle teknolojik gelişmeler ve dünya ticaretindeki gelişmeler ile birlikte ülkeler arasındaki sınırlar ortadan kalkmıştır. Ülkelerin en temel hedefi toplumsal refahı artırmaktır. Ekonomik büyüme hedefini gerçekleştirebilmek için enerji girdisinin temini çok önemlidir. Enerji kaynaklarının fosil enerjiden yenilenebilir enerjiye dönüşümü, sürdürülebilir enerji arzı açısından önemli bir gerekliliktir. Ülkeler arasındaki ekonomik, sosyal ve politik ilişkilerin gelişmiş olması, enerji tüketiminin fosil enerjiden yenilenebilir kaynaklara dönüşümü ve seyri açısından kritik bir öneme sahiptir. Bu çalışmanın amacı, Türkiye’de ekonomik, sosyal ve politik küreselleşme ile enerji tüketimi ilişkisini ampirik olarak araştırmaktır. Söz konusu araştırma için 1970-2017 arası döneme ait yıllık verilerle zaman serisi yöntemi kullanılmıştır. Elde edilen ampirik bulgular, değişkenler arasında uzun dönemli ilişkinin olduğunu göstermektedir. Değişkenlere ait uzun dönem katsayıları ise istatistiki olarak anlamsızdır. Yapılan nedensellik testlerinde ise Hacker ve Hatemi-J testinde herhangi bir nedensellik yokken, Breitung ve Candelon (2006) frekans dağılımı testinde uzun, orta ve kısa vadede nedensellik ilişkileri tespit edilmiştir. Sosyal ve politik küreselleşme ve ekonomik büyüme ile enerji tüketimi arasında ilişki olduğu sonucuna ulaşılmıştır.

Industrial production index - crude oil price nexus: Russia, Kazakhstan and Azerbaijan

The study aims to examine the causality between industrial production index and crude oil price for Russia, Kazakhstan and Azerbaijan by using Frequency Domain Causality Analysis. For this purpose, the monthly data of the industrial production index and Brent oil price data over the period 1993-2019 are used. The Frequency Domain Causality Analysis suggests that the uni-directional causality relationship runs from oil prices to industrial production index is valid in the medium run for Russia and Azerbaijan and in the short run for Kazakhstan. However, there is no uni-directional causality linkage between oil prices and industrial production index in the long run for any of the countries. We hope to contribute to the literature by using frequency-domain causality test which examines the interrelation of crude oil prices on industrial production with the periodicity in these countries. The finding of this study is expected to serve as a tool for industrial production policy.

Frequency domain causality analysis of intra- and inter-regional return and volatility spillovers of South-East European (SEE) stock markets

In this study the return spillovers and volatility spillovers between South-East European (SEE) stock markets are investigated as well as vis-à-vis regional and global stock markets (e.g. Europe, Japan, China and the US). By using Frequency Domain Causality approach, the evidence is found of significant spillover effects between markets. The results of study indicate both short-and long-run intra- and inter-regional return and volatility spillovers detected between South-East European (SEE) stock markets and the emerging and the mature markets around the globe, implying limited diversification benefits for international investor portfolios allocated to these markets. Thus, these results should be taken into account by portfolio managers, investors and policy makers before making any investment decision into region’s stock markets. The policy makers and regulators of these markets should consider the nature and frequency of regional and global integration of their stock markets.

Cross-border workers and financial instability: a frequency domain causality analysis applied to the Luxembourg financial centre

ABSTRACTThis paper aims to examine the causal relationship between workers (cross-border and resident workers) and financial instability in the Luxembourg financial centre, using a Granger causality test in the frequency domain. The evidence shows that cross-border workers are more sensitive to financial shocks than resident workers. In addition to the causal relationship there is a ‘nonlinear’ reaction: one smooth in the short term and a second more structural one in the long term.

Frequency domain causality analysis of tourism and economic activity in Turkey

This paper studies the dynamic relationships between real Gross Domestic Product (GDP), real exchange rate (RER) and real tourism income (TOTREC) in Turkey over the period from 2003: Q1 to 2014: Q4 by using frequency domain causality approach developed by Breitung and Candelon (2006). Our findings reveal that real GDP Granger causes real tourism income both in the short-and long-run, while real tourism income only Granger causes real GDP in the short run. Moreover, there is no Granger causality neither between real tourism income and real exchange rate nor between real GDP and real exchange rate. These findings support Tourism-led Growth Hypothesis (TLGH) only in the short-run. Therefore, there is an urgent need to develop and implement appropriate tourism policies so that the sector’s contribution to economic growth can be extended to long-run.

Frequency Domain Causality Analysis of Interactions between Financial Markets of Turkey

<p class="Abstracttext"><span lang="EN-US">In this paper, we examined the dynamic linkages between financial markets of Turkey by using frequency domain causality analysis, proposed by Breitung and Candelon (2006), for the weekly Turkish data from 2003 to 2015. The results show that there are volatility spillovers from stock market returns to interest rate and EURO both in the mid and long terms, and short and medium-terms to U.S. Dollar; but, from U.S. Dollar to stock market returns in the short-term. In the long-run, EURO exchange rate Granger cause to interest rate; but, interest rate Granger cause to EURO exchange rate in the short-run. On the other hand, there is no evidence of volatility spillovers from EURO and interest rate to stock market returns. Based on these results, we can conclude that there are certain degree of interdependence and volatility spillovers among the financial markets of Turkey, which have serious policy implications.</span></p>

Frequency domain causality analysis of stock market and economic activity in India

In this study, we analyze the Granger-causality in frequency domain between stock prices and economic growth in India, in order to identify the direction of the causality at different frequencies. For this purpose we use in the first step different seasonal and structural breaks unit root tests. In the second step we use a conditional VAR model as benchmark, and we focus on the conditional and non-conditional frequency domain causality tests. We find evidence of unidirectional causal relationship between stock prices and industrial production in the long-run, running from stock prices to industrial production. When using the non-conditional model, we find evidence of insignificant business cycle causality from both directions. Our study shows that stock prices are a leading indicator for growth in the industrial production in India. In this case, in order to adjust the industrial production in the long-term, the Indian economic policies should be focused with predilection on the stock market environment.

The frequency domain causality analysis between energy consumption and income in the United States

We investigated Granger-causality in the frequency domain between primary energy consumption/electricity consumption and GDP for the US by employing approach of Lemmens et al. (2008) and covering the period of January, 1973 to December, 2008. We found that causal and reverse causal relations between primary energy consumption and GDP and electricity consumption and GDP vary across frequencies. Our unique contribution in the existing literature lies in decomposing the causality on the basis of time horizons and demonstrating bidirectional the short-run, the medium-run and the long-run causality between GDP and primary energy consumption/electricity consumption and thus providing evidence for the feedback hypothesis. These results have important implications for the US for planning of the short, the medium and the long run energy and economic growth related policies.

Frequency Domain Causality Analysis Method for Multivariate Systems in Hypothesis Testing Framework

A variety of causality analysis methods have been proposed and used for complex large multivariate systems. In the frequency domain, partial directed coherence (PDC) is an important method. We expect that the frequency domain methods can provide a more detailed explanation of causal influence over different frequencies, but PDC provides no quantitative information to quantify the causal strength and the interpretation of causality over a specific frequency is still unexplained. Based on the statistical property of the renormalized PDC, a frequency domain causality analysis method in the hypothesis testing framework is employed in this paper to resolve these issues. In order to achieve a lower computational load, another method with a simpler definition is proposed. The interpretations of causal strength given by these two methods are shown to be consistent with that given by Granger causality, and the frequency distribution is reasonable and informative. Several simulation examples are demonstrated to illustrate the performance of these two methods.

Government expenditures and trade deficits in Turkey: Time domain and frequency domain analyses

The purpose of this study is to determine the causality between trade deficit and government expenditures in the Turkish economy. We employ bootstrap process-based Toda-Yamamoto causality and frequency domain analysis methods. Results obtained from both methods imply that there is a bi-directional causality between trade deficits and government expenditures. Different from Toda-Yamamoto causality analysis, frequency domain causality analysis indicates that the causality running from government expenditures to trade deficits exists in the short and medium terms while causality runs from trade deficits to government expenditures in the short and long runs.