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This study aims to investigate the interactions among macroeconomic variable shocks, banking fragility and home financing provided by conventional and Islamic banks in Malaysia. Identifying the causes of financial instability and the effects of macroeconomic shocks can help to foil the onset of future financial turbulence.

The autoregressive distributed lag bound-testing cointegration approach, impulse response functions (IRFs) and forecast error variance decomposition are used in this study to unravel the long-run and short-run dynamics among the selected macroeconomic variables and amount of home financing offered by both conventional and Islamic banks. In addition, the study uses Granger causality tests to investigate the short-run causalities among the selected variables to further understand the impact of one macroeconomic shock to Islamic and conventional home financing.

This study provides evidence that macroeconomic shocks have different long-run and short-run effects on amount of home financing offered by conventional and Islamic banks. Both in the long run and short run, home financing provided by Islamic banks is more linked to real sector economy and thus is more stable as compared to home financing provided by conventional banks. The Granger causality test reveals that only gross domestic product (GDP), Kuala Lumpur Syariah Index (KLSI)/Kuala Lumpur Composite Index (KLCI) and house price index (HPI) are found to have a statistically significant causal relationship with home financing offered by both conventional and Islamic banks. Unlike the case of Islamic banks, conventional home financing is found to have a unidirectional causality with interest rates.

This study has focused on analyzing the macroeconomic shocks on home financing. However, this study does not assess the impact of financial deregulation and enhanced information technology on amount of financing offered by both conventional and Islamic banks. In addition, it is not within the ambit of this present study to examine the effects of agency costs and information asymmetry.

The analysis of cointegration and IRFs exhibits that in the long run and short run, home financing provided by Islamic banks are more linked to real sector economy like GDP and House Prices (HPI) and therefore more resilient to economic vulnerabilities as compared to home financing provided by conventional banks. However, in the long run, both conventional and Islamic banks are more susceptible to fluctuations in interest rates. The results of the study suggest that monetary policy ramifications to improve banking fragility should focus on stabilizing interest rates or finding an alternative that is free from interest.

Because interest plays a significant role in pricing of home loans, the potential of an alternative such as rental rate is therefore timely and worth the effort to investigate further. Therefore, Islamic banks can explore the possibility of pricing home financing based on rental rate as proposed in this study.

This paper examines the unresolved issues in Islamic home financing where Islamic banks still benchmark their products especially home financing, to interest rates in dual banking system such as in the case of Malaysia. To the best of the authors’ knowledge, studies conducted in this area are meager and therefore is imperative to be examined.

The objective of this study is to examine the long-run relationship between workers' remittances and economic growth in Sri Lanka using time series data spanning 1975–2021.

This study employed both exploratory data analysis (EDA) and inferential data analysis (IDA) tools. EDA includes the scatter plots, confidence ellipse with Kernel fit, whereas IDA covers unit root test, the autoregressive distributed lag (ARDL) bounds technique, the Granger's causality test, and impulse response function (IRF) analysis.

EDA confirms that workers' remittances have a positive relationship with per-capita gross domestic product (GDP). All variables used in this study are I(1). This study is exhibited that workers' remittances have a positive long-run relationship with per-capita GDP. The estimated coefficient of the error correction term shows that the dependent variable moves towards the long-run equilibrium path. Workers' remittances have a short-run and long-run causal relationship with per-capita GDP. The IRF analysis indicates that a one standard deviation shock to workers' remittances has initially an immediate significant positive impact on economic growth.

This study provides insights into workers' remittances in economic growth in Sri Lanka. Further, the findings of this study also provide evidence that workers' remittances increase economic growth.

Using ARDL bounds test, Granger's Causality test and IRF analysis for examining the relationship between workers' remittances and economic growth are the originality of this study.

This paper investigates the structural model of vector autoregression (SVAR) of the interdependent relationship of inflation, monetary policy and Islamic banking variables (RDEP, RFIN, DEP, FIN) in Indonesia. By using monthly data for the period 2001M01-2019M12, the impulse response function (IRF), forecasting error decomposition variation (FEDV) is used to track the impact of Sharīʿah variables on inflation (prices).

This research uses quantitative approach with SVAR model to reveal the problem.

The empirical results of SVAR, the IRF show that policy shocks have a negative impact on all variables in Islamic banking except the equivalent deposit interest rate (RDEP). The impact of both conventional (7DRR) and Sharīʿah (SBIS) policies has a similar pattern. While the transmission of Sharīʿah monetary variables as a policy operational target in influencing inflation is positive. In addition, the FEDV clearly revealed that the variation in the Sharīʿah financial sector was relatively large in monetary policy shocks and their role in influencing prices.

The empirical results of SVAR, the IRF show that policy shocks have a negative impact on all variables in Islamic banking except the equivalent deposit interest rate ‘RDEP’. The impact of both conventional “7DRR” and Sharīʿah “SBIS” policies has a similar pattern. While the transmission of Sharīʿah monetary variables as a policy operational target in influencing inflation is positive. In addition, the FEDV clearly revealed that the variation in the Sharīʿah financial sector was relatively large in monetary policy shocks and their role in influencing prices.

The purpose of this paper is to explore empirically the effects of the current financial crisis on the integration and co‐movements of selected stock markets of the emerging economies, namely Indonesia and Malaysia.

The paper employs the standard time series technique and vector autoregressive framework.

The results of this paper support the general view that stock markets tend to show greater degree of integration or increased co‐movements during the crisis period, resulting in lesser benefit of diversification that can be gained by investors participating in these markets.

This paper only focuses on emerging equity markets of Malaysia and Indonesia.

This paper reveals that unlike during the pre‐crisis period, the long‐run diversification benefits that can be earned by investors across the emerging equity markets of Indonesia and Malaysia during the crisis period tend to diminish.

By dividing the study periods into the pre‐crisis period and during the crisis period, it enables us to explore whether the cross‐market linkages between these markets change due to the crisis.

This study aims to investigate the dynamic relationships between oil price shocks and Indian stock market.

The study used daily data for the period starting from January 2001 to March 2013. In this study, Johansen's cointegration test, vector error correction model (VECM), Granger causality test, impulse response functions (IRFs) and variance decompositions (VDCs) test have been applied to exhibit the long-run and short-run relationship between them.

The cointegration result indicates the existence of long-term relationship. Further, the error correction term of VECM shows a long-run causality moves from Indian stock market to oil price but not the vice versa. The results of the Granger causality test under the VECM framework confirm that no short-run causality between the variables exists. The VDCs analysis revealed that the Indian stock markets and crude oil prices are strongly exogenous. Finally, from the IRFs, analysis revealed that a positive shock in oil price has a small but persistence and growing positive impact on Indian stock markets in short run.

The study would enhance the understandings of the interaction between oil price volatilities and emerging stock market performances. Further, the study would enable foreign investors who are interested in Indian stock market helps in understanding the conditional relationship between the variables.

In this paper, the authors investigate whether coronavirus disease 2019 (COVID-19) impacts household finances, like household debt repayments in the UK.

This paper employs a vector autoregressive (VAR) model that nests neural networks and uses Mixed Data Sampling (MIDAS) techniques. The authors use data information related to COVID-19, financial markets and household finances.

The authors' results show that household debt repayments' response to the first principal component of COVID-19 shocks is negative, albeit of low magnitude. However, when the authors employ specific COVID-19-related data like vaccines and tests the responses are positive, insinuating the underlying dynamic complexities. Overall, confirmed deaths and hospitalisations negatively affect household debt repayments. The authors also report low persistence in household debt repayments. Generalised impulse response functions (IRFs) confirm the main results. As draconian measures, the lockdowns are eased and the COVID-19 shocks are diminishing, and household financial data converge to the levels prior to the pandemic albeit with some lags.

To the best of the authors' knowledge, this is the first study that examines the impact of the pandemic on household debt repayments. The authors' findings show that policy response in the future should prioritise innovation of new vaccines and testing.

This paper aims to empirically examine the impact of economic development and energy consumption in Saudi Arabia (the leading OPEC giant and the Arab energy icon country) between 1971 and 2015, whilst incorporating globalization, financial development and capital accumulation.

This study uses econometric tools and the analytical framework based on the autoregressive distributed lag (ARDL) model.

The study found that, unlike economic development, globalization and financial development increased energy consumption. Also, capital accumulation created a boost in the country’s energy consumption. Results of variance decomposition indicate that the innovative shocks in globalization and financial development affected energy consumption at the rates of 15.28% and 28.98%, respectively, over 15 years’ period, while shocks in capital accumulation affected energy consumption at a rate of only about 1.24%. In addition, the results of impulse response function show that globalization and economic development were highly responsive to shocks in financial development, and capital accumulation greatly spurred financial development.

The findings of this study have implication for promoting an efficient and sustainable energy systems that enhance sustainable development based on the accrued benefits of globalization, financial development and capital accumulation.

Given the increasing level of globalization, financial development and energy consumption, our study uses econometric tools and the analytical framework based on the ARDL model to revisit how energy consumption is influenced by economic development in Saudi Arabia by incorporating other determinants of energy consumption such as globalization, financial development and capital accumulation. The results were validated based on the innovative accounting.

There are many studies related to finance-growth nexus, but existing empirical evidences still have not provided conclusive result of the nature and direction of this relationship. Moreover, there are only few studies about finance-growth nexus seen from Islamic finance perspective, especially in Indonesia. Therefore, this study aims to examine the nature of causal relationship between Islamic finance development and economic growth in Indonesia seen from the development of Islamic banking, sukuk market and Islamic stock market.

By using quarterly data from 2002Q3 to 2017Q4, this study uses vector autoregressive (VAR) model, then uses granger causality and impulse response function to analyze the causal relationship between Islamic finance development and economic growth and also among three main sub-sectors of Islamic finance.

This study found that Islamic banking development and Islamic stock market development support neutrality hypotheses view, while sukuk market development supports supply-leading hypotheses view. Moreover, this study also found that there are unidirectional causalities from sukuk market development to Islamic banking development and from sukuk market development to Islamic stock market development.

This study focuses only on the development of Islamic finance viewed from a macro perspective and only looks at how the three main sub-sectors in Islamic finance develop. In addition, the results of research related to finance-growth nexus are also sensitive to the object of research, the method and the proxies of variables used.

To the best of the authors’ knowledge, there is no study that examines the causal relationship between Islamic finance development and economic growth in Indonesia based on its three main sub-sectors simultaneously. So, this study gives empirical evidence to contribute on finance-growth nexus discussion based on three main sub-sectors of Islamic finance development in Indonesia.

The purpose of this study is to conduct a comparative analysis of the Medicare patients discharged to a long-term (acute) care hospitals (LTCH), skilled nursing facility (SNF) or inpatient rehabilitation facility (IRF) following an acute inpatient hospitalization under Medicare-severity diagnosis-related group (MS-DRG) 207. The likelihood of discharge by provider type was also examined to determine criteria informing patient discharge to a LTCH, SNF or IRF for treatment.

Retrospective cohort study, based on secondary data analysis, utilizing Medicare Provider Analysis and Review (MedPAR) File data collected by Centers for Medicare & Medicaid Services for fiscal year 2011, October 1, 2010, through September 30, 2011.

Numerous analyses were conducted upon those patients discharged to a LTCH, SNF or IRF following an acute inpatient hospitalization under MS-DRG 207. Concerning those patients discharged to LTCHs, patients were not significantly older, did not have the highest length of stay and had comparable diagnoses and diagnosis counts to those discharged to SNFs or IRFs. However, costs were significantly higher among discharges to LTCHs. Multinomial logistic regression analyses also indicated numerous associations between certain variables and discharge location.

With the aging of the US population and increasing costs of rendering services, both the Medicare population and Medicare expenditures, already at their highest levels in the history of the program, are projected to rise going forward (The Boards of Trustees, 2012). As such, recent research has focused on Part A hospitals/facilities and the variations in costs submitted and payments received for treatment/services provided. This study aims to address whether patients discharged to LTCHs, which receive higher payment(s) as a result of serving a higher proportion of medically complex beneficiaries, are more medically complex than those discharged to SNFs/IRFs.

This chapter studies the dynamic responses of the conditional quantiles and their applications in macroeconomics and finance. The authors build a multi-equation autoregressive conditional quantile model and propose a new construction of quantile impulse response functions (QIRFs). The tool set of QIRFs provides detailed distributional evolution of an outcome variable to economic shocks. The authors show the left tail of economic activity is the most responsive to monetary policy and financial shocks. The impacts of the shocks on Growth-at-Risk (the 5% quantile of economic activity) during the Global Financial Crisis are assessed. The authors also examine how the economy responds to a hypothetical financial distress scenario.