scholarly journals Causality Analysis of Google Trends and Dengue Incidence in Bandung, Indonesia With Linkage of Digital Data Modeling: Longitudinal Observational Study

10.2196/17633 ◽  
2020 ◽  
Vol 22 (7) ◽  
pp. e17633 ◽  
Author(s):  
Muhammad Syamsuddin ◽  
Muhammad Fakhruddin ◽  
Jane Theresa Marlen Sahetapy-Engel ◽  
Edy Soewono
Keyword(s):  
Linear Combination ◽  
Stationary Process ◽  
Impulse Response Function ◽  
Google Trends ◽  
Digital Data ◽  
Causality Analysis ◽  
Long Term Effects ◽  
Long Run ◽  
Dengue Outbreaks ◽  
Long Run Equilibrium

Background The popularity of dengue can be inferred from Google Trends that summarizes Google searches of related topics. Both the disease and its Google Trends have a similar source of causation in the dengue virus, leading us to hypothesize that dengue incidence and Google Trends results have a long-run equilibrium. Objective This research aimed to investigate the properties of this long-run equilibrium in the hope of using the information derived from Google Trends for the early detection of upcoming dengue outbreaks. Methods This research used the cointegration method to assess a long-run equilibrium between dengue incidence and Google Trends results. The long-run equilibrium was characterized by their linear combination that generated a stationary process. The Dickey-Fuller test was adopted to check the stationarity of the processes. An error correction model (ECM) was then adopted to measure deviations from the long-run equilibrium to examine the short-term and long-term effects. The resulting models were used to determine the Granger causality between the two processes. Additional information about the two processes was obtained by examining the impulse response function and variance decomposition. Results The Dickey-Fuller test supported an implicit null hypothesis that the dengue incidence and Google Trends results are nonstationary processes (P=.01). A further test showed that the processes were cointegrated (P=.01), indicating that their particular linear combination is a stationary process. These results permitted us to construct ECMs. The model showed the direction of causality of the two processes, indicating that Google Trends results will Granger-cause dengue incidence (not in the reverse order). Conclusions Various hypothesis testing results in this research concluded that Google Trends results can be used as an initial indicator of upcoming dengue outbreaks.

scholarly journals Causality Analysis of Google Trends and Dengue Incidence in Bandung, Indonesia With Linkage of Digital Data Modeling: Longitudinal Observational Study (Preprint)

2019 ◽  
Author(s):  
Muhammad Syamsuddin ◽  
Muhammad Fakhruddin ◽  
Jane Theresa Marlen Sahetapy-Engel ◽  
Edy Soewono
Keyword(s):  
Linear Combination ◽  
Stationary Process ◽  
Impulse Response Function ◽  
Google Trends ◽  
Digital Data ◽  
Causality Analysis ◽  
Long Term Effects ◽  
Long Run ◽  
Dengue Outbreaks ◽  
Long Run Equilibrium

BACKGROUND The popularity of dengue can be inferred from Google Trends that summarizes Google searches of related topics. Both the disease and its Google Trends have a similar source of causation in the dengue virus, leading us to hypothesize that dengue incidence and Google Trends results have a long-run equilibrium. OBJECTIVE This research aimed to investigate the properties of this long-run equilibrium in the hope of using the information derived from Google Trends for the early detection of upcoming dengue outbreaks. METHODS This research used the cointegration method to assess a long-run equilibrium between dengue incidence and Google Trends results. The long-run equilibrium was characterized by their linear combination that generated a stationary process. The Dickey-Fuller test was adopted to check the stationarity of the processes. An error correction model (ECM) was then adopted to measure deviations from the long-run equilibrium to examine the short-term and long-term effects. The resulting models were used to determine the Granger causality between the two processes. Additional information about the two processes was obtained by examining the impulse response function and variance decomposition. RESULTS The Dickey-Fuller test supported an implicit null hypothesis that the dengue incidence and Google Trends results are nonstationary processes (<i>P</i>=.01). A further test showed that the processes were cointegrated (<i>P</i>=.01), indicating that their particular linear combination is a stationary process. These results permitted us to construct ECMs. The model showed the direction of causality of the two processes, indicating that Google Trends results will Granger-cause dengue incidence (not in the reverse order). CONCLUSIONS Various hypothesis testing results in this research concluded that Google Trends results can be used as an initial indicator of upcoming dengue outbreaks.

scholarly journals Intermediary performance of Islamic banks in the disruption era: Does it contribute to economic growth?

2021 ◽  
Vol 16 (1) ◽  
pp. 103-115
Author(s):  
Umrotul Khasanah ◽  
Ahmad Tibrizi Soni Wicaksono
Keyword(s):  
Economic Growth ◽  
Impulse Response Function ◽  
Third Party ◽  
Islamic Banks ◽  
Long Term Effects ◽  
Vector Error Correction ◽  
Long Run ◽  
Short And Long Term ◽  
Vector Error Correction Models

The study aims to measure the intermediary performance of Islamic banks in relation to economic growth in Indonesia in the short and long term. There are four main variables used, namely financing, fund placement in BI (Central Bank of Indonesia), investment in securities, and third-party funds in all Islamic banks from 2007 to 2019. The data were tested using vector error correction models (VECM), Granger Causality, Impulse Response Function (IRF), and Variant Decomposition (VDC) to examine causality relationships, the short- and long-term effects, shocks, and variances in Islamic bank intermediary performance to economic growth. The results show that there is a two-way causality relationship between financing and third-party funds to economic growth. While in the short term, fund placement in BI, investment in securities, and financing have a significant influence on economic growth, but in the long run, only the placement of funds in BI will affect economic growth. Also, only fund placement in BI can shock and significantly contribute to economic growth in the long term. The overall intermediary performance of Islamic banks has not contributed to Indonesia’s economic growth in the long term.

Foreign Direct Investment and Current Account Deficit - A Causality Analysis in Context of India

2012 ◽  
Vol 13 (2) ◽  
pp. 85-106
Author(s):  
Manpreet Kaur ◽  
Surendra Yadav ◽  
Vinayshil Gautam
Keyword(s):  
Foreign Direct Investment ◽  
Granger Causality ◽  
Current Account ◽  
Direct Investment ◽  
Current Account Deficit ◽  
Impulse Response Function ◽  
Causality Analysis ◽  
Long Run ◽  
The Impact ◽  
The Relationship

Current Account Deficit is one of the major macroeconomic problems facing India. In this paper, we have tried to investigate the relationship between Foreign Direct Investment (FDI) and current account in the context of India. Using the Toda-Yamamoto (T-Y) granger causality technique for the period 1975-2009, our results indicate that FDI and current account are co-integrated in the long run. There is evidence of unidirectional causality from FDI to current account. Furthermore, the analysis of FDI and international trade components (Exports and Imports), which are the major constituents of current account, supports our results of granger causality. Also, an attempt has been made to provide for the impact of FDI on current account through impulse response function.

Fraud and Bank Performance in Nigeria – Var Granger Causality Analysis

e-Finanse ◽  
2020 ◽  
Vol 16 (1) ◽  
pp. 20-26
Author(s):  
Taiwo A. Muritala ◽  
Muftau A. Ijaiya ◽  
Olatanwa H. Afolabi ◽  
Abdulrasheed B. Yinus
Keyword(s):  
Control Systems ◽  
Granger Causality ◽  
Internal Control ◽  
Banking Sector ◽  
Bank Performance ◽  
Causality Analysis ◽  
Vector Autoregressive ◽  
Granger Causality Analysis ◽  
Long Run ◽  
Multivariate Cointegration

AbstractThis paper examines the causality between fraud and bank performance in Nigeria over the period 2000-2016 for quarterly financial data using Johansen’s Multivariate Cointegration Model and Vector Autoregressive (VAR) Granger Causality analysis. The results show a long-run relationship between the variables. Bank performance was found to be linked to Granger fraud variables and vice versa at 10% significant level. This study reveals that there was a direct causal relationship between bank performance and fraud because increase in fraudulent activities in the banking sector leads to reduction in bank performance. Hence, this study recommends that internal control systems of banks should be strengthened so as to detect and prevent fraud. In this way, bank assets would be protected.

Non-Performing Loans, Banking System and Macroeconomy

2018 ◽  
Vol 63 (2) ◽  
pp. 67-86
Author(s):  
Akinola Morakinyo ◽  
Colette Muller ◽  
Mabutho Sibanda
Keyword(s):  
Exchange Rate ◽  
Serial Correlation ◽  
Banking System ◽  
Impulse Response Function ◽  
Credit Market ◽  
Variance Decomposition ◽  
Structural Var ◽  
Long Run ◽  
Correlation Tests ◽  
The Exchange Rate

Abstract The study builds on previous studies of the consequences of non-performing loans on an economy. Using a seven-by-seven matrix in the impulse response function (IRF) of the structural autoregressive model, we find a long-run impact of an impulse to non-performing loans on the banking system and the macroeconomy in Nigeria. Conversely, non-performing loans also respond to the innovation of all macro-banking variables aside from the exchange rate and the growth rate to GDP. Also, the level of non-performing loans grows in influence in relation to the changes to the exchange rate using the variance decomposition tool of Structural VAR. Hence, a prominent role is assigned to the level of NPLs in linking the friction in the credit market to the susceptibility of both the banking system and the macroeconomy. This study passes the serial correlation tests and the three tests of normality.

An Econometric Analysis on the Relationship between Globalisation and Inequality in South Africa

2020 ◽  
Vol 11 (1) ◽  
pp. 89-89
Author(s):  
Jacques de Jongh
Keyword(s):  
South Africa ◽  
Well Being ◽  
Causality Analysis ◽  
Global Integration ◽  
Development Indicators ◽  
Long Run ◽  
The World ◽  
Distribution Of Resources ◽  
Short Run ◽  
The Impact

Globalisation has had an unprecedented impact on the development and well-being of societies across the globe. Whilst the process has been lauded for bringing about greater trade specialisation and factor mobility many have also come to raise concerns on its impact in the distribution of resources. For South Africa in particular this has been somewhat of a contentious issue given the country's controversial past and idiosyncratic socio-economic structure. Since 1994 though, considerable progress towards its global integration has been made, however this has largely coincided with the establishment of, arguably, the highest levels of income inequality the world has ever seen. This all has raised several questions as to whether a more financially open and technologically integrated economy has induced greater within-country inequality (WCI). This study therefore has the objective to analyse the impact of the various dimensions of globalisation (economic, social and political) on inequality in South Africa. Secondary annual time series from 1990 to 2018 were used sourced from the World Bank Development indicators database, KOF Swiss Economic Institute and the World Inequality database. By using different measures of inequality (Palma ratios and distribution figures), the study employed two ARDL models to test the long-run relationships with the purpose to ensure the robustness of the results. Likewise, two error correction models (ECM) were used to analyse the short-run dynamics between the variables. As a means of identifying the casual effects between the variables, a Toda-Yamamoto granger causality analysis was utilised. Keywords: ARDL, Inequality, Economic Globalisation; Social Globalisation; South Africa

scholarly journals The Integration of Conventional Equity Indices with Environmental, Social, and Governance Indices: Evidence from Emerging Economies

2021 ◽  
Vol 13 (2) ◽  
pp. 676
Author(s):  
Ramiz ur Rehman ◽  
Muhammad Zain ul Abidin ◽  
Rizwan Ali ◽  
Safwan Mohd Nor ◽  
Muhammad Akram Naseem ◽  
...  
Keyword(s):  
South Africa ◽  
Function Analysis ◽  
Impulse Response Function ◽  
Decomposition Analysis ◽  
Individual Country ◽  
Brics Countries ◽  
Long Run ◽  
Integration Test ◽  
Short Run ◽  
Equity Indices

This study investigates the integration of environmental, social, and governance (ESG) equity indices with conventional indices in Brazil, Russia, India, China, and South Africa (BRICS) individually and across all BRICS countries to better understand regional economic cooperation. Accordingly, we look at daily returns from 13 July 2013 to 28 February 2018 for the Morgan Stanley Capital International (MSCI) ESG indices and MSCI composite indices of the respective countries. To analyze the integration between the ESG equity indices of the sampled countries with their regional and across regional conventional counterparts, the Johansen Co-integration test is employed in this study. Further, the vector error correction model (VECM) is applied to test the causality between the sampled time-series. The impulse response function analysis further explains the impulse responses of each country’s MSCI ESG returns to one standard deviation of innovations to MSCI composite returns of the same country and across countries. Finally, the extent of the MSCI composite returns’ impact on the MSCI ESG returns in the same country indices, and cross-regional indices is examined with variance decomposition analysis. The results suggest that all ESG equity indices are integrated with conventional indices in all BRICS countries. Furthermore, there is a short-or long-run causality between MSCI ESG and MSCI composite equity indices of China and South Africa. Moreover, the study finds only short-run causality between conventional and non-conventional equity indices of Brazil and Russia, whereas we find only long-run causality between India’s non-conventional and conventional equity indices. Finally, the study finds that the all-individual country MSCI ESG equity indices shows a long-run causality with MSCI composite equity indices of all other BRICS countries. The findings also confirm the economic and financial cooperation between the BRICS countries.

Exchange rates in India: current account monetarism in a nonlinear context

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Aditi Chaubal
Keyword(s):  
Exchange Rate ◽  
Current Account ◽  
Polynomial Function ◽  
Mean Reversion ◽  
Smooth Transition ◽  
Monetary Model ◽  
Forecast Performance ◽  
Long Run ◽  
Nonlinear Mean Reversion ◽  
Long Run Equilibrium

AbstractThe Indian exchange rate system has evolved from a pegged system to the current managed float. The study examines the presence of a long-run equilibrium in the monthly Indian exchange rate (Rs/USD) using a current account monetary model (or flexible price monetary model) while accounting for different nonlinearities over the period January 1993 to January 2014 (pre-inflation targeting period). The nonlinear adjustment to disequilibria is modelled using a nonlinear error correction model (NLECM). The nonlinear current account monetarism (CAM) model includes nonlinear transformations of long-run dynamics in the ECM to account for different nonlinearities: multiple equilibria (cubic polynomial function), nonlinear mean reversion (rational polynomial function), and smooth and gradual regime switches (exponential smooth transition autoregressive (ESTAR) function). The NLECM-ESTAR model outperforms other alternatives based on model and forecast performance measures, implying the existence of nonlinear mean reversion and smooth transition across different periods of overvaluation and undervaluation of the exchange rate. This implies the presence of asymmetric adjustment to the movements from the long-run equilibrium, but the nature of such transitions is smooth and not abrupt. The paper also establishes the uniqueness of the long-run equilibrium. A comparison to the sticky price monetary model could not be made due to stationary exchange rate disequilibrium.

Fish Exports and Economic Growth: The Pakistan’s Experience

2019 ◽  
Vol 20 (2) ◽  
pp. 279-296 ◽  
Author(s):  
Syed Tehseen Jawaid ◽  
Mohammad Haris Siddiqui ◽  
Zeeshan Atiq ◽  
Usman Azhar
Keyword(s):  
Economic Growth ◽  
Time Series Data ◽  
Positive Impact ◽  
Impulse Response Function ◽  
Policy Implications ◽  
Sensitivity Analyses ◽  
Series Data ◽  
Distributed Lag ◽  
Long Run ◽  
Short Run

This study attempts to explore first time ever the relationship between fish exports and economic growth of Pakistan by employing annual time series data for the period 1974–2013. Autoregressive distributed lag and Johansen and Juselius cointegration results confirm the existence of a positive long-run relationship among the variables. Further, the error correction model reveals that no immediate or short-run relationship exists between fish exports and economic growth. Different sensitivity analyses indicate that initial results are robust. Rolling window analysis has been applied to identify the yearly behaviour of fish exports, and it remains negative from 1979 to 1982, 1984 to 1988, 1993 to 1999, 2004 and from 2010 to 2013, and it shows positive impact from 1989 to 1992, 2000 to 2003 and from 2005 to 2009. Furthermore, the variance decomposition method and impulse response function suggest the bidirectional causal relationship between fish exports and economic growth. The findings are beneficial for policymakers in the area of export planning. This study also provides some policy implications in the final section.

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