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Article
Publication date: 29 January 2024

Clement Olalekan Olaniyi and Nicholas M. Odhiambo

This study examines the roles of cross-sectional dependence, asymmetric structure and country-to-country policy variations in the inflation-poverty reduction causal nexus in…

Abstract

Purpose

This study examines the roles of cross-sectional dependence, asymmetric structure and country-to-country policy variations in the inflation-poverty reduction causal nexus in selected sub-Saharan African (SSA) countries from 1981 to 2019.

Design/methodology/approach

To account for cross-sectional dependence, heterogeneity and policy variations across countries in the inflation-poverty reduction causal nexus, this study uses robust Hatemi-J data decomposition procedures and a battery of second-generation techniques. These techniques include cross-sectional dependency tests, panel unit root tests, slope homogeneity tests and the Dumitrescu-Hurlin panel Granger non-causality approach.

Findings

Unlike existing studies, the panel and country-specific findings exhibit several dimensions of asymmetric causality in the inflation-poverty nexus. Positive inflationary shocks Granger-causes poverty reduction through investment and employment opportunities that benefit the impoverished in SSA. These findings align with country-specific analyses of Botswana, Cameroon, Gabon, Mauritania, South Africa and Togo. Also, a decline in poverty causes inflation to increase in the Congo Republic, Madagascar, Nigeria, Senegal and Togo. All panel and country-specific analyses reveal at least one dimension of asymmetric causality or another.

Practical implications

All stakeholders and policymakers must pay adequate attention to issues of asymmetric structures, nonlinearities and country-to-country policy variations to address country-specific issues and the socioeconomic problems in the probable causal nexus between the high incidence of extreme poverty and double-digit inflation rates in most SSA countries.

Originality/value

Studies on the inflation-poverty nexus are not uncommon in economic literature. Most existing studies focus on inflation’s effect on poverty. Existing studies that examine the inflation-poverty causal relationship covertly assume no asymmetric structure and nonlinearity. Also, the issues of cross-sectional dependence and heterogeneity are unexplored in the causal link in existing studies. All panel studies covertly impose homogeneous policies on countries in the causality. This study relaxes this supposition by allowing policies to vary across countries in the panel framework. Thus, this study makes three-dimensional contributions to increasing understanding of the inflation-poverty nexus.

Details

International Trade, Politics and Development, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2586-3932

Keywords

Book part
Publication date: 25 September 2020

Letife Özdemir

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…

Abstract

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.

Details

Uncertainty and Challenges in Contemporary Economic Behaviour
Type: Book
ISBN: 978-1-80043-095-2

Keywords

Book part
Publication date: 23 June 2016

Eric Renault and Daniela Scidá

Many Information Theoretic Measures have been proposed for a quantitative assessment of causality relationships. While Gouriéroux, Monfort, and Renault (1987) had introduced the…

Abstract

Many Information Theoretic Measures have been proposed for a quantitative assessment of causality relationships. While Gouriéroux, Monfort, and Renault (1987) had introduced the so-called “Kullback Causality Measures,” extending Geweke’s (1982) work in the context of Gaussian VAR processes, Schreiber (2000) has set a special focus on Granger causality and dubbed the same measure “transfer entropy.” Both papers measure causality in the context of Markov processes. One contribution of this paper is to set the focus on the interplay between measurement of (non)-markovianity and measurement of Granger causality. Both of them can be framed in terms of prediction: how much is the forecast accuracy deteriorated when forgetting some relevant conditioning information? In this paper we argue that this common feature between (non)-markovianity and Granger causality has led people to overestimate the amount of causality because what they consider as a causality measure may also convey a measure of the amount of (non)-markovianity. We set a special focus on the design of measures that properly disentangle these two components. Furthermore, this disentangling leads us to revisit the equivalence between the Sims and Granger concepts of noncausality and the log-likelihood ratio tests for each of them. We argue that Granger causality implies testing for non-nested hypotheses.

Abstract

Details

New Directions in Macromodelling
Type: Book
ISBN: 978-1-84950-830-8

Article
Publication date: 22 August 2023

Xunfa Lu, Jingjing Sun, Guo Wei and Ching-Ter Chang

The purpose of this paper is to investigate dynamics of causal interactions and financial risk contagion among BRICS stock markets under rare events.

Abstract

Purpose

The purpose of this paper is to investigate dynamics of causal interactions and financial risk contagion among BRICS stock markets under rare events.

Design/methodology/approach

Two methods are adopted: The new causal inference technique, namely, the Liang causality analysis based on information flow theory and the dynamic causal index (DCI) are used to measure the financial risk contagion.

Findings

The causal relationships among the BRICS stock markets estimated by the Liang causality analysis are significantly stronger in the mid-periods of rare events than in the pre- and post-periods. Moreover, different rare events have heterogeneous effects on the causal relationships. Notably, under rare events, there is almost no significant Liang's causality between the Chinese and other four stock markets, except for a few moments, indicating that the former can provide a relatively safe haven within the BRICS. According to the DCIs, the causal linkages have significantly increased during rare events, implying that their connectivity becomes stronger under extreme conditions.

Practical implications

The obtained results not only provide important implications for investors to reasonably allocate regional financial assets, but also yield some suggestions for policymakers and financial regulators in effective supervision, especially in extreme environments.

Originality/value

This paper uses the Liang causality analysis to construct the causal networks among BRICS stock indices and characterize their causal linkages. Furthermore, the DCI derived from the causal networks is applied to measure the financial risk contagion of the BRICS countries under three rare events.

Details

International Journal of Emerging Markets, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-8809

Keywords

Article
Publication date: 29 March 2023

Şerif Canbay, İnci Oya Coşkun and Mustafa Kırca

This study investigates if the causal relationships between the exchange rates and selected inbound markets’ tourism demand are temporary or permanent, and compares market…

Abstract

Purpose

This study investigates if the causal relationships between the exchange rates and selected inbound markets’ tourism demand are temporary or permanent, and compares market reactions in Türkiye.

Design/methodology/approach

Tourism demand is examined with a regional approach, focusing on the geographical markets, namely Europe, Commonwealth of Independent States (CIS) members and Asian countries, as the top inbound tourism markets, in addition to the total number of inbound tourists to Türkiye. Granger, frequency-domain causality, asymmetric Toda–Yamamoto, and asymmetric frequency-domain causality tests were employed to investigate and compare markets on exchange rate–tourism demand relationship for 2008M01-2020M02.

Findings

The results indicate that exchange rates affect European tourism demand both in the short and long run. The meaning of this Frequency Domain Causality (FDC) analysis finding shows that the exchange rate has both permanent and temporary effects on European tourists. The relationships are statistically insignificant for CIS members and Asian countries. The exchange rates also permanently affect total inbound tourism demand, but the independent variable has no short-run (temporary) effects on total demand. Asymmetric causality tests confirmed a permanent causality relationship from the positive and negative components of exchange rates to the positive and negative components of European and total tourism demand.

Originality/value

The Granger causality test provides information on the presence of a causal relation, while the FDC test, an extended version of Granger causality, enlightens the short- (temporary) and long-run (permanent) relationships and allows for analyzing the duration of the impact. In addition, asymmetric causality relationships are also investigated in the study. Besides, this study is the first in the literature to examine the relationship between tourism demand and the exchange rate regionally (continentally) for Türkiye.

Details

International Journal of Emerging Markets, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-8809

Keywords

Article
Publication date: 9 September 2022

Xiaojie Xu and Yun Zhang

With the rapid-growing house market in the past decade, the purpose of this paper is to study the important issue of house price information flows among 12 major cities in China…

Abstract

Purpose

With the rapid-growing house market in the past decade, the purpose of this paper is to study the important issue of house price information flows among 12 major cities in China, including Shanghai, Beijing, Xiamen, Shenzhen, Guangzhou, Hangzhou, Ningbo, Nanjing, Zhuhai, Fuzhou, Suzhou and Dongguan, during the period of June 2010 to May 2019.

Design/methodology/approach

The authors approach this issue in both time and frequency domains, latter of which is facilitated through wavelet analysis and by exploring both linear and nonlinear causality under the vector autoregressive framework.

Findings

The main findings are threefold. First, in the long run of the time domain and for timescales beyond 16 months of the frequency domain, house prices of all cities significantly affect each other. For timescales up to 16 months, linear causality is weaker and is most often identified for the scale of four to eight months. Second, while nonlinear causality is seldom determined in the time domain and is never found for timescales up to four months, it is identified for scales beyond four months and particularly for those beyond 32 months. Third, nonlinear causality found in the frequency domain is partly explained by the volatility spillover effect.

Originality/value

Results here should be of use to policymakers in certain policy analysis.

Details

International Journal of Housing Markets and Analysis, vol. 16 no. 6
Type: Research Article
ISSN: 1753-8270

Keywords

Article
Publication date: 11 November 2022

Özcan Karahan and Olcay Çolak

The direction of the causality relationship between Foreign Direct Investment (FDI) and economic growth is a highly controversial issue in the literature. There are two basic…

Abstract

Purpose

The direction of the causality relationship between Foreign Direct Investment (FDI) and economic growth is a highly controversial issue in the literature. There are two basic approaches advocating different causal directions between FDI and growth, which are called hypotheses of FDI-led Growth and Growth-led FDI. The aim of this study is to analyze the causality relationship between FDI and economic growth in RCEP countries and thus make a new contribution to the discussions in the relevant literature. In addition, the results of the study are expected to provide important implications for the policies to be designed for economic growth based on FDI flows to RCEP countries. Thus, by examining the direction of causality between FDI and economic growth in RCEP countries, we aim to provide a new contribution to related literature and make some implications for the policy design process of economic growth in the RCEP area.

Design/methodology/approach

We empirically examined the direction of a causal link between FDI and economic growth in the context of Regional Comprehensive Economic Partnership (RPEC) countries in order to test the hypothesis of FDI-led growth and Growth-led FDI. Accordingly, as our main variables of interest, we incorporated the inward foreign direct investment stock to gross domestic product ratio (FDI) and gross domestic product per capita (GDP). Hatemi-J (2012) asymmetric causality test has been employed in the investigation of the direction of causality between FDI and GDP over the period of 1980–2020. Thus, unlike most of the studies investigating the direction of causality between FDI and growth using the linear causality analysis method, our study performed a nonlinear causality analysis.

Findings

Empirical results reveal that the causal relationship between FDI and national income in RPEC countries is non-linear or asymmetric . The results of the symmetric causality test for both from FDI to national income and from national income to FDI are statistically insignificant for all countries. Therefore, this finding obtained from the study provided an important guide to the econometric methods to be used in other studies to be conducted in the same region in the future. Concerning the asymmetric causality relationship from FDI to growth, positive FDI shocks are an important cause of national income in most RCEP countries. However, the effect of negative FDI shocks on national income is quite weak compared to positive shocks. Regarding the asymmetric causality relationship from growth to FDI, positive national income shocks do not create a significant causal relationship with FDI. Similarly, the effects of negative national income shocks on FDI are statistically insignificant. Overall, asymmetric causality test results reveal that positive FDI shocks have an important causal impact on economic growth in most RCEP countries. Thus, the results of econometric analysis mostly support the argument that the FDI-led growth hypothesis rather than the Growth-led FDI hypothesis in RCEP countries. Accordingly, policy-makers in most of the RCEP countries should continue to provide more incentives and facilities to multinational companies in order to ensure constant economic growth.

Originality/value

Our study brings a significant difference in the econometric method used compared to most of the other studies in the literature. Existing empirical studies on the direction of causality between FDI and growth mostly use standard Granger-linear causality-type tests to detect the direction of causality among FDI and growth. Unlike most of the studies in the literature, our study adopted a different methodological approach, namely the Hatemi J test to detect the non-linear causality between FDI and economic growth in RCEP countries. Therefore, this paper made a new methodological contribution significantly to the literature focusing on the causal relationship between FDI and economic growth by using a non-linear causality method rather than a linear causality one.

Details

Journal of Economic and Administrative Sciences, vol. 40 no. 1
Type: Research Article
ISSN: 1026-4116

Keywords

Article
Publication date: 28 February 2023

Amal Ghedira and Mohamed Sahbi Nakhli

This study aims to examine the dynamic bidirectional causality between oil price (OIL) and stock market indexes in net oil-exporting (Russia) and net oil-importing (China…

Abstract

Purpose

This study aims to examine the dynamic bidirectional causality between oil price (OIL) and stock market indexes in net oil-exporting (Russia) and net oil-importing (China) countries.

Design/methodology/approach

The authors use monthly data for the period starting from October 1995 to October 2021. In this study, the bootstrap rolling-window Granger causality approach introduced by Balcilar et al. (2010) and the probit regression model are performed in order to identify the bidirectional causality.

Findings

The results show that the causal periods mainly occur during economic, financial and health crises. For oil-exporting country, the results suggest that any increase (decrease) in the OIL leads to an appreciation (depreciation) in the stock market index. The effect of the stock market on OIL is more relevant for the oil-importing country than that for the oil-exporting one. The COVID-19 consequences are demonstrated in the impact of oil on the Russian stock market. The probit regression shows that the US financial instabilities increase the probability of causality between OIL and stock market indexes in Russia and China.

Practical implications

The dynamic relationship between the variables must be taken into account in investment decisions. As financial instabilities in the USA drive the relationship between oil and stocks, investors should consider geopolitical, economic and financial elements when constructing their portfolios. Shareholders are required to include other assets in their portfolios since oil–stock relationship is highly risky.

Originality/value

This study provides further evidence of the bidirectional oil–stock causal link. Additionally, it examines the impact of financial instabilities on the probability that the OIL and the stock market index cause each other through the Granger effect.

Details

International Journal of Emerging Markets, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-8809

Keywords

Article
Publication date: 5 May 2015

Wasim Ahmad and Sanjay Sehgal

– This paper aims to examine the destabilization effect in the case of India’s agricultural commodity market for the sample period of 01 January 2009 to 31 May 2013.

Abstract

Purpose

This paper aims to examine the destabilization effect in the case of India’s agricultural commodity market for the sample period of 01 January 2009 to 31 May 2013.

Design/methodology/approach

The daily data of eight agricultural commodities traded on the National Commodity & Derivatives Exchange, viz., barley, castor seed, chana (chickpea), chilli, potato, pepper, refined soya and soybean, have been used in this study. At the first stage of the empirical analysis, the study estimates the time-varying spot market volatility by using the exponential generalized autoregressive conditional heteroscedasticity model and applies three different high and band-pass filters, viz., the two-sided linear band-pass filter by Hodrick and Prescott (1997), the fixed-length symmetric band-pass filter by Baxter and King (1999) and the asymmetric band-pass filter by Christiano and Fitzgerald (2003), to calculate the unexpected liquidity of sample commodities. At the second stage of the empirical analysis, the study applies linear Granger causality and recently developed non-linear causality given by Diks and Panchenko (2006) to examine the cause and effect between time-varying volatility of spot market and futures market liquidity of sample commodities.

Findings

The linear and non-linear causality results suggest the destabilizing effect of commodity futures on the underlying spot market for chana, chilli and pepper. The empirical findings are in contrast with the recommendations of Abhijit Sen’s committee and provide important direction for further policy research.

Research limitations/implications

The study has a limitation in that it is based on the daily data. The use of intra-day data would have been more suitable for such type of analysis.

Practical implications

The study has strong policy implications from a financial policy perspective, as there is already disagreement among researchers and policy makers with regard to the functioning of commodity derivatives markets in India. There have been many occasions when commodity market regulators have to undertake decisions of suspension of trading of many commodities. The study also provides new directions of policy research with regards to the restructuring of the commodity derivatives market in India.

Social implications

The findings of this study may further help the regulators and policy makers to undertake decisions about how to provide an alternative platform for farmers to sell their agricultural produce more efficiently. This will certainly have some impact on the socioeconomic set-up of the country, as India is primarily an agriculture-dominated country.

Originality/value

So far not many studies have investigated the destabilization hypothesis in the case of emerging markets. This study is a novel attempt to fill the gap. In the case of emerging markets and especially in the case of India’s commodity derivatives market, this is the first study that examines the destabilization hypothesis in the case of India by applying new methods of high and band-pass filters and non-linear causality.

Details

Journal of Financial Economic Policy, vol. 7 no. 2
Type: Research Article
ISSN: 1757-6385

Keywords

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