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Using the Environmental Kuznets Curve (EKC) hypothesis as a theoretical framework and applying Estimated Generalised Least Square (EGLS) approach, this chapter examines the impact of energy consumption, economic growth, industrialisation and corruption on carbon dioxide emissions as well as finds out the causal relationship among them using panel data of 10 Asian economies over the period 1980–2019. Our empirical findings from EGLS model suggest that there exists an ongoing rising relationship between CO₂ emissions and economic growth both in the short-run and long-run which is opposing to what is claimed by the EKC hypothesis. Moreover, per capita CO₂ emissions rise positively with respect to increase in energy consumption, urbanisation, gradual industrialisation and growth in urban population in the long-run. Moreover, countries with adoption of more corruptive practices are found to have causing more environmental degradation through excessive emission of carbon dioxide in the long-run. The study also indicates the existence of unidirectional causalities running from carbon dioxide emission to energy consumption, from industrialisation and urban population growth to per capita CO₂ emissions, from industrialisation to GDP growth per capita and bidirectional causality between financial development and economic growth via GDP growth per capita. Therefore, these unidirectional causalities entail that CO₂ emission reduction or abatement measures can be applied without having any unpleasant effect on the real industrialisation, energy consumption and urbanisation in selected Asian countries.

Conventional methods to test for long-term PPP based on the theory of cointegration are typically undertaken in the framework of vector error correction models (VECM). The standard approach in the use of VECMs is to employ a model of full-order, which assumes nonzero entries in all the coefficient matrices. But, the use of full-order VECM models may lead to incorrect inferences if zero entries are required in the coefficient matrices. Specifically, if we wish to test for indirect causality, instantaneous causality, or Granger non-causality, and employ “overparameterised” full-order VECM models that ignore entries assigned a priori to be zero, then the power of statistical inference is weakened and the resultant specifications can produce different conclusions concerning the cointegrating relationships among the variables. In this paper, an approach is presented that incorporates zero entries in the VECM analysis. This approach is a more straightforward and effective means of testing for causality and cointegrating relations. The paper extends prior work on PPP through an investigation of causality between the U.S. Dollar and the Japanese Yen. The results demonstrate the inconsistencies that can arise in the area and show that bi-directional feedback exists between prices, interest rates and the exchange rate such that adjustment mechanisms are complete within the context of PPP.

The study investigates the interdependence of the stock markets between the following countries Hong Kong, Japan, Korea, Taiwan, Indonesia, Malaysia, Philippines, Singapore, Thailand and the advanced stock markets of Australia, Germany, United Kingdom and the United States. Using data from 1994 to 2003 the paper employs both correlation, causality and cointegration analysis to describe the behaviour of the above stock market indices over the period pre and post the 1997 Asian Financial Crises. The paper investigates both the short- and long-run relationships between the Asian markets and the markets of selected advanced industrial countries.

Introduction: The credit default swap (CDS) represents a country’s credit risk premium. CDS premium changes by being affected by several factors. These changes are followed by international investor for their investment decisions. CDS premium is important for country to determine the country default risk correctly. Purpose: In this study, the authors seek to examine the effects of macroeconomic indicators on the CDS premium, which is used as a measure of sovereign credit risk. Accordingly, in addition to the CDS premium, economic growth, the inflation rate, the interest rate, the real exchange rate, the net foreign debt rate, and the foreign trade deficit rate were employed to represent macroeconomic indicators. Methodology: The relationship between the given variables during the period spanning from 2009:I–2019:II in Turkey was analyzed with the help of the Dolado–Lütkepohl causality test and the autoregressive distributed lag method. Findings: The inflation rate, the real exchange rate, the interest rate, the net foreign debt rate, and the foreign trade deficit rate, which are among the macroeconomic variables (excluding economic growth), have a positive effect on the CDS premium in the short term as well as the long term. The effect of economic growth is negative. Additionally, from an economic standpoint, the coefficients of macroeconomic variables are in the expected direction. These findings verify the effects of macroeconomic indicators on the CDS premium.

It is important for stakeholders to understand the driving forces of the aviation industry and economic wellbeing and how these sectors are interconnected. This chapter studies the relationships between the African aviation industry and the economy. It is framed as a causal linkage considering the priority investment sector that enhances the sustainable wellbeing of the society. Analyses were conducted for 38 African countries using time series data from 1981 to 2019. The results show that causal relationships are heterogeneous and context-specific. Four patterns of causal relationships between air travel demand and the economy are identified: unidirectional causality in either directions; bidirectional causality; and indeterminate causal direction. However, the causal direction in any economic or policy-related matter may change with political reforms and changes to economic policy.

The present study deals with the growth performance of export (X), ­import (M), and economic growth (Y) in India over the period 1970–1971 to 2016–2017 as well as tariff (TR) for the period 1990–2017 by employing the methodology of one-time endogenous structural break suggested by Zivot and Andrews (1992). Also, an attempt has been taken to examine the direction of causality between the above-mentioned trade-related variables and economic growth using Granger Causality Test. Results of estimation reveal that all the variables converge toward a stationarity process having constant variability overtime. There exists structural break in the year 1996, 2006, 2008, and 2010, respectively, for economic growth, tariff, imports, and exports. Bidirectional causality is found running from economic growth to tariff and from tariff to economic growth. But there is unidirectional causality from imports to tariff, imports to exports and from exports to tariff.

Purpose: Through globalization, financial markets have become more integrated and their tendency to act together has increased. The majority of the literature states that there is a cointegration between developed and emerging markets. How do positive or negative shocks in developed markets affect emerging markets? And how do positive or negative shocks in emerging markets affect developed markets? For this reason, the aim of the study is to investigate the asymmetric causality relationship between developed and emerging markets with Hatemi-J asymmetric causality test.

Design/methodology/approach: In this study, the Dow Jones Industrial Average (DJIA) index was used to represent developed markets and the Morgan Stanley Capital International (MSCI) Emerging Market Index was used to represent emerging markets. The asymmetric causality relationship between the DJIA Index and the MSCI Emerging Market Index was investigated using monthly data between January 2009 and April 2019. In the first step of the study, the Johansen Cointegration Test was used to determine whether there is a cointegration between the markets. In the next step, the Hatemi-J asymmetric causality test was applied to see the asymmetric causality relationship between the markets.

Findings: There is a weak correlation between developed and emerging markets. This result is important for international investors who want to diversify their portfolios. As a result of the Johansen Cointegration Test, it was found that there is a long-term relationship between the MSCI Emerging Market Index and the DJIA Index. Therefore, investors who make long-term investment plans should not forget that these markets act together and take into account the causal relationship between them. According to the asymmetric causality test results, a unidirectional causality relationship from the MSCI Emerging Market Index to the DJIA Index was determined. This causality shows that negative shocks in the MSCI Emerging Market Index have positive effects on the DJIA Index.

Originality/value: This study contributes to the literature as it is one of the first studies to examine the asymmetrical relationship between developed and emerging markets. This study is also useful in predicting the short- and long-term relationship between markets. In addition, this study helps investors, portfolio managers, company managers, policymakers, etc., to understand the integration of financial markets.

This chapter investigates the impact change of the composition of market agents on the timing of the arrival of information in Bursa Malaysia. The price discovery role of futures trading on the spot market is examined through three distinct sub-periods: pre-crisis, crisis and after capital controls. For this purpose, the Johansen Cointegration (1988, 1991) and VECM and Granger causality are used. The analysis shows that there is no significant long-run relationship. As for short-run, the results show futures lead spot. However, futures’ lead is shorter in pre-crisis and crisis periods where foreign institutional investors dominate. This study deduces that the significant change in the composition of market agents could contribute to the variation of lead–lag relationship.