Analysis of Wavelet Coherence: Service Sector Index and Economic Growth in an Emerging Market

Orhan, Ayhan; Kırıkkaleli, Derviş; Ayhan, Fatih

doi:10.3390/su11236684

Cited by 26 publications

(18 citation statements)

References 35 publications

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“…This supports both the supply-side perspective engineered by Schumpeter [ 9 ], which posits causality from finance to economic growth and the demand-side approach led by Robinson [ 17 ] which proposes that economic growth causes financial development. The outcome of the study also supports prior empirical studies within the field of financial development and economic growth [ 97 , 98 ], while other studies also indicate a unidirectional relationship [ 87 , 99 ]. We, therefore, advocate that finance-growth nexus as well as causality dynamics are time-varying, and are likely to be influenced by external policy uncertainty shocks.…”

Section: Empirical Analysissupporting

confidence: 86%

“…As a result, the aforementioned countries’ economic development hinges on the effective development of their financial sector. Accordingly, the development of the financial system contributes to economic growth via fund inflow by offering capital accumulation and technological development infrastructure to economies [ 87 ]. The few right-pointing arrows downwards for Russia from 2007–2010 at scales 8–16 months demonstrates that economic growth significantly drives the financial sector.…”

Section: Empirical Analysismentioning

confidence: 99%

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Financial sector and economic growth amid external uncertainty shocks: Insights into emerging economies

et al. 2021

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The study aims to shed new lights on the lead-lag relationships between the financial sector (RFSI) and economic growth (GDP) in the midst of global economic policy uncertainty (GEPU) shocks for BRICS economies. Hence, the bivariate, partial, and wavelet multiple correlations techniques are employed. From the bivariate analysis, we document positive bi-directional causality between the RFSI and economic growth over the sample period. The partial wavelet reveals that GEPU shocks distort the significance and directional comovements between the RFSI and GDP. Moreover, the outcome from the wavelet multiple cross correlations (WMCC) indicates that the RFSI is a first mover at most time scales for the BRICS economies. This is followed by GEPU which either leads or lags for most scales, especially for South Africa. The impact of GEPU on RFSI and GDP is worst for South Africa in about four cases in the medium-, and long-terms. This signifies that South Africa’s financial markets and economic growth are vulnerable to GEPU. However, the impetus for GEPU to drive the comovements between the financial sector and economic activity was less pronounced in the pre-COVID analysis conducted with the WMCC. The study supports both the supply-leading and demand-following hypotheses. Our findings also underscore the need for policymakers, investors and academics alike to incessantly observe the dynamics between finance and growth across time and periodicity while considering adverse shocks from global economic policy uncertainty in tandem.

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Section: Empirical Analysissupporting

confidence: 86%

Section: Empirical Analysismentioning

confidence: 99%

Financial sector and economic growth amid external uncertainty shocks: Insights into emerging economies

et al. 2021

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“…As discussed by Kirikkaleli (2019) and Adebayo (2020), time (represented by k) and frequency (represented by f ) are the main two elements of the wavelet approach. "The k parameter has an important role in detecting the exact location of a wavelet by relocating the wavelet over time, while f monitors the distended wavelet for localizing different frequencies" (Orhan et al 2019). The transformation of the wavelet ψ equation with k and f elements is shown as…”

Section: Methodsmentioning

confidence: 99%

Co-movement of commodity price indexes and energy price index: a wavelet coherence approach

Kırıkkaleli

Güngör

2021

Financ Innov

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This research sheds light on the causal link between commodity price indexes, i.e., the Agricultural Raw Materials Price Index, Industry Input Price Index, Metal Price Index, and Energy Price Index, in the global market, using wavelet coherence, Toda–Yamamoto causality, and gradual shift causality tests over the period 1992M1 to 2019M12. Findings from the wavelet power spectrum and partial wavelet coherence reveal that: (1) there was significant volatility in the Agricultural Raw Materials Price Index, Industry Input Price Index, Metal Price Index, and Energy Price Index between 2004 and 2014 at different frequencies; and (2) commodity price indexes significantly caused the energy price index at different time periods and frequencies. It is noteworthy that the outcomes of the Toda–Yamamoto causality and gradual-shift causality tests are in line with the results of wavelet coherence.

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“…On the other vein, if R 2 (u,s) approaches 0, it indicates that there is no correlation between tested variables as shown in blue area on the next section. Overall, wavelet coherence is a suitable instrument to evaluate the stock market co-movement throughout time (Aloui & Hkiri, 2014: Orhan et al, 2019.…”

Section: Wavelet Coherencementioning

confidence: 99%

Co-movement between GCC stock markets and the US stock markets: A wavelet coherence analysis

Matar

Al-Rdaydeh

Ghazalat

et al. 2021

Cogent Business & Management

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In this article, the co-movement between GCC and US stock market returns was investigated using the wavelet coherence method. The Dynamic Conditional Correlation GARCH (DCC-GARCH) modelling is then applied on timevarying components in order to provide a point of comparison with the results extracted from wavelet analysis. The investigation was conducted on the weekly stock index prices of two USA stock markets, namely Dow Jones and S&P 500 and six GCC stock markets, namely the United Arab Emirates, Saudi Arabia, Qatar, Oman, Kuwait, and Bahrain. The data were retrieved from Thomson Reuters's data stream and the sample duration was from 7 January 2007 to 24 June 2018. As a result, a definite co-movement between several GCC stock markets and those of the US stock markets for a long term was found. Moreover, the results also displayed signs of the significant disparity between the co-movements of the stock markets throughout the scales of time during economic decline. This phenomenon was possibly expected during the economic decline, where a significant divergence occurred as opposed to co-movement. The implications of the findings for global investors were considerable due to the indication from long-term co-movement that these investors would not be capable of gaining simultaneous profit from time and portfolio being diversified. In fact, the results showed the major difference in the opportunities for international portfolio diversification throughout these markets in terms of scale and time.

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Analysis of Wavelet Coherence: Service Sector Index and Economic Growth in an Emerging Market

Cited by 26 publications

References 35 publications

Financial sector and economic growth amid external uncertainty shocks: Insights into emerging economies

Financial sector and economic growth amid external uncertainty shocks: Insights into emerging economies

Co-movement of commodity price indexes and energy price index: a wavelet coherence approach

Co-movement between GCC stock markets and the US stock markets: A wavelet coherence analysis

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