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The purpose of this paper is to conduct a systematic literature review of research conducted in the economic Islamicity (EI) index field, in terms of non-Islamic countries.

This study thoroughly assessed the literature on the EI index by conducting extensive systematic literature reviews.

The critical analysis of these indices shows the need for amendments, which can be achieved by improving the Islamicity index seen in non-Islamic countries. This step will help validate the Islamicity index assessment and help Islamic countries develop and strengthen Islamic economic values.

As the first comprehensive literature review in the Islamicity indices domain to the best of the authors’ knowledge, this research may contribute for Islamic country to increase the Islamicity index in terms of economic issue for future research themes.

This chapter examines the impact of macroeconomic factors on the financial performance of Chinese companies. Using multiple regression analysis, the study finds that gross domestic product (GDP) growth rate, inflation rate, interest rate, exchange rate, and government expenditure are significant predictors of the financial performance of Chinese companies. The results show that GDP growth rate, leverage, size, liquidity, profitability, and growth in sales all have significant positive impacts on financial performance, while growth in assets has a negative impact. The study provides insights into the impact of macroeconomic factors on the financial performance of Chinese companies. Policymakers and investors should take these findings into account when making decisions about economic policies and investments, and companies operating in China should be aware of the potential impact of these factors on their financial performance and look for ways to manage them effectively. The chapter also includes a model specification test and a robustness test to validate the accuracy of the results. The findings have important guiding significance for policy makers and investors in making economic policies and investment decisions. However, the study has limitations such as the use of horizontal panel data and the limited data sources used.

This paper studies the dynamic effects of selected macroeconomic factors on the performance of the housing market in Kenya using Autoregressive Distributed Lag (ARDL) Models. This study aims to explain the dynamic effects of the macroeconomic factors on the three indicators of the housing market performance: housing prices growth, sales index and rent index.

This study used ARDL Models on time series data from 1975 to 2020 of the selected macroeconomic factors sourced from Kenya National Bureau of Statistics, Central Bank of Kenya and Hass Consult Limited.

The results indicate that household income, gross domestic product (GDP), inflation rates and exchange rates have both short-run and long-run effects on housing prices while interest rates, diaspora remittance, construction output and urban population have no significant effects on housing prices both in the short and long run. However, only household income, interest rates, private capital inflows and exchange rates have a significant effect on housing sales both in the short and long run. Furthermore, household income, GDP, interest rates and exchange rates significantly affect housing rental growth in the short and long run. The findings are key for policymaking, especially at the appraisal stages of real estate investments by the developers.

The authors recommend the use of both the traditional hedonic models in conjunction with the dynamic models during real estate project appraisals as this would ensure that developers only invest in the right projects in the right economic situations.

The imbalance between housing demand and supply has prompted an investigation into the role of macroeconomic variables on the housing market in Kenya. Although the effects of the variables have been documented, there is a need to document the short-run and long-term effects of the factors to precisely understand the behavior of the housing market as a way of shielding developers from economic losses.

This research investigates the impact of strategic research and development (R&D) (one led by a firm’s innovation orientation) on stock market performance during the economic disruption caused by the 2016 demonetization of high-value currency notes in India. It shows how firms’ strategic focus on innovation and integrated R&D initiatives can help mitigate shareholders’ losses and protect market value during negative macroeconomic shocks.

We analyzed financial and administrative data from firms listed in the Bombay Stock Exchange (BSE) 500 index and used the Fama French market model with appropriate instruments accounting for possible endogeneity to identify the impact. To ensure the reliability of our findings, we conducted robustness checks with alternate event windows, estimation methods, and variable measurements.

Strategic R&D plays a crucial role in building resilience against macroeconomic shocks. It effectively mitigated shareholders’ losses in the immediate aftermath of the shock, with an elasticity of abnormal returns of 7.65% on day zero, 13.1% during the first five days and 10.5% after the first fortnight. We also find that firms that are business-to-business (B2B), as well as those that are older and less leveraged, are better able to combat such a shock.

The study looked at one shock, namely demonetization. Future research is needed to demonstrate the generalizability of results during other macroeconomic shocks, like the COVID-19 pandemic. The study focuses on relatively near-term impacts, leaving the long-term value-creation effects of strategic R&D unexplored.

Innovation orientation acts as a structural enabler, allowing firms to make strategic R&D investments that mitigate losses during macroeconomic shocks. It explains that managers should avoid myopically managing R&D investments and align them with the firm’s innovation focus to enhance value creation.

While the currency demonetization was widely considered to be detrimental for firms as an unannounced negative monetary shock, our research shows that firms with high levels of strategic R&D were successfully able to counteract such a shock.

This is the first study to examine the short-term loss mitigation impact of firms’ focus on innovation and strategic R&D. It emphasizes the role of innovation-focused strategies during economic crises.

Czechia is a small open economy and a member state of the European Union. Several important trends and episodes that have determined economic growth can be identified over the last two decades. This chapter deals with some macroeconomic features like macroeconomic and labour market performance within the business cycle, the Czech National Bank (CNB) exchange rate commitment and interest rate policy, increasing indebtedness and budget deficits, foreign trade and the international investment position. We applied publicly available data from Eurostat, the Organisation for Economic Co-operation and Development and CNB databases. The data show that the Czech economy was significantly converging to the average economic level of the European Union. We also identified key turning points in business cycles. Macroeconomic data on economic development of the economy indicate an atypical course of the business cycle between 2020 and 2022, which can be evaluated as different from the one that followed the global financial crisis.

This current study draws a comparison between the performance indicators of public sector banks (PSBs) and private sector banks (or non-PSBs) in India. The study controls for the impact of COVID-19.

The study uses strongly balanced panel data for seven years of 12 PSBs and 10 non-PSBs from the Nifty PSU Bank Index and Nifty Private Bank Index. The study applies panel data methodology to arrive at the results.

The study demonstrates that the behavior of indicators of performance and returns volatility for PSBs and non-PSBs differs substantially. While factors like capital adequacy ratio (CAR), cost management (COST), liquidity (LIQ), inflation and economic growth exhibit a similar impact on both categories of Indian banks, the effect of credit risk (RISK), market power (POWER) and COVID-19 on performance and returns stability is different for PSBs and non-PSBs.

There is a limited sample size of banks in India.

PSBs and non-PSBs need distinct treatments when calibrating performance indicators.

The performance and stability of banks are essential for society at large, the depositors and the investors.

The study provides vibrant implications for insight for banks to calibrate the variables that determine performance and stability, regulators and policymakers for effective governance of the banking ecosystem and effective utilization of public funds and capital. The findings are relevant for policymaking today, when the government is considering the privatization of a few PSBs.

The study investigates the effectiveness of government policies to mitigate the impact of a pandemic. The study adopts the small open economy of Nigeria for the following reasons. First, Nigeria is the largest economy in SSA. Second, Nigeria was also significantly impacted by the COVID-19 pandemic.

The study employed the time-varying structural autoregressive (TVSVAR) model to control for the potential asymmetry in fiscal variables and to control for the shift in the structural shift, following a macroeconomic shock. As a form of robustness, the study also implements the time-varying Granger causality to formally assess the temporal instability of the variable of interest.

The results show that an oil price shock is an important source of macroeconomic instability in Nigeria. Importantly, the results indicate that the effects of fiscal policy are strongly time varying. Specifically, the results show that fiscal policy helps to stabilize the economy, (i.e. they help to reduce inflation and spur output growth) following macroeconomic shock. Further, the Granger test shows that fiscal policy helped to spur growth in Nigeria. The research and policy implications are discussed.

The study accounts for the time-varying effects of fiscal policy.

The purpose of this study is to construct a new index to assess the impact of an energy price shock on macroeconomic indicators of India. This paper also shows a comparative analysis of the constructed index along with pre-existing World Bank and International Monetary Fund indices on energy.

This paper uses three vector autoregressions and compute the long-term impact of the indices on the considered macroeconomic variables through impulse response functions.

This paper finds that an energy price shock has a detrimental impact on the macroeconomic indicators of India in the long run. This study also finds that the constructed index acts as a relatively more sensitive index in comparison to the International Monetary Fund and World Bank indices, which is bespoke to a developing economy case. This sensitivity is ascribed to dynamic weighting for a different basket of energy components, which are more pertinent to an Indian context.

The novelty of this research lies in the construction of a new index and its comparison to the existing ones. This study justifies why a developing economy would require a different measure of energy as opposed to the existing indices.

The novel coronavirus (COVID-19) has caused financial stress and limited their lending agility, resulting in more non-performing loans (NPLs) and lower performance during the II wave of the coronavirus crisis. Therefore, it is essential to identify the risky factors influencing the financial performance of Indian banks spanning 2018–2022.

Our sample consists of a balanced panel dataset of 75 scheduled commercial banks from three different ownership groups, including public, private and foreign banks, that were actively engaged in their operations during 2018–2022. Factor identification is performed via a fixed-effects model (FEM) that solves the issue of heterogeneity across different with banks over time. Additionally, to ensure the robustness of our findings, we also identify the risky drivers of the financial performance of Indian banks using an alternative measure, the pooled ordinary least squares (OLS) model.

Empirical evidence indicates that default risk, solvency risk and COVAR reduce financial performance in India. However, high liquidity, Z-score and the COVID-19 crisis enhance the financial performance of Indian banks. Unsystematic risk and systemic risk factors play an important role in determining the prognosis of COVID-19. The study supports the “bad-management,” “moral hazard” and “tail risk spillover of a single bank to the system” hypotheses. Public sector banks (PSBs) have considerable potential to achieve financial performance while controlling unsystematic risk and exogenous shocks relative to their peer group. Finally, robustness check estimates confirm the coefficients of the main model.

This study contributes to the knowledge in the banking literature by identifying risk factors that may affect financial performance during a crisis nexus and providing information about preventive measures. These insights are valuable to bankers, academics, managers and regulators for policy formulation. The findings of this paper provide important insights by considering all the risk factors that may be responsible for reducing the probability of financial performance in the banking system of an emerging market economy.

The empirical analysis has been done with a fresh perspective to consider unsystematic risk, systemic risk and exogenous risk (COVID-19) with the financial performance of Indian banks. Furthermore, none of the existing banking literature explicitly explores the drivers of the I and II waves of COVID-19 while considering COVID-19 as a dependent variable. Therefore, the aim of the present study is to make efforts in this direction.