Global uncertainty and climate-aligned ETFs: Evidence from wavelet-quantile-based analysis

Purpose- In this study, it is aimed to investigate the effects of global uncertainty shocks on the macroeconomic variables of the Turkish economy. Methodology- In the study, the global world uncertainty index (WUI) constructed by Ahir et al. (2022) is used as an indicator of global uncertainty. A structural auto regressive (SVAR) model is established, which includes five variables (global uncertainty indicator, economic growth rate, inflation rate, unemployment rate, and interest rate). In addition, three real variables representing economic activity (real consumption, real investment and real bank loans) are substituted for unemployment rate in the model, respectively. The data set covers the period 2003Q1-2020Q1. Findings- According to the findings of impulse response and variance decomposition analyses, real GDP growth, real consumption growth, real investment growth and real credit growth react negatively and significantly to an increase in global uncertainty. On the other hand, inflation rate, unemployment rate and interest rate respond positively and significantly to an increase in global uncertainty. These results prove that a global uncertainty shock creates the similar effects of a negative supply shock on the Turkish economy. In addition, the robustness of the findings is checked using the global economic policy uncertainty (GEPU) index developed by Baker et al. (2016). Conclusion- In the light of these findings, it can be suggested that the negative effects of global uncertainty shocks on domestic macroeconomic indicators should be mitigated through monetary and fiscal policies. Keywords: Global uncertainty, structural VAR, economic growth, inflation, unemployment JEL Codes: C32, E30, F40

The Impact of Global Uncertainty on the Global Economy, and Large Developed and Developing Economies

Global uncertainty shocks are associated with a sharp decline in global inflation, global growth and in the global interest rate. Over 1981 to 2014 global financial uncertainty forecasts 18.26% and 14.95% of the variation in global growth and global inflation respectively. Global uncertainty shocks have more protracted, statistically significant and substantial effects on global growth, inflation and interest rate than U.S. uncertainty shocks. U.S. uncertainty lags global uncertainty by one month. When controlling for domestic uncertainty, the decline in output following a rise in global uncertainty is statistically significant in each country, with the exception of the decline for China. The effects for the U.S. and for China are also relatively small. For most economies, a positive shock to global uncertainty has a depressing effect on prices and official interest rates. Exceptions are Brazil, Mexico and Russia, economies with large capital outflows during financial crises. Decomposition of global uncertainty shocks shows that global financial uncertainty shocks are more important than non-financial shocks.

The world is currently facing unprecedented uncertainty in social, political, and economic aspects, which continuously evolve every year owing to extraordinary events that impact countries worldwide. In contrast, The growth strategy of a country organizes must include Foreign Direct Investment (FDI), especially in Indonesia. The fluctuation in foreign investment in Indonesia indicates that foreign investors also consider growing global uncertainty alongside the development of Indonesia’s financial sector. This study examines the relationship between global uncertainty and financial development on FDI in Indonesia from 1997 to 2020 using the Autoregressive Distributed Lag (ARDL) method. The results indicate that global uncertainty significantly negatively impacts Indonesia’s FDI in the short and long terms. However, global economic policy uncertainty positively influences Indonesia’s FDI in the long term. This indicates that Indonesia has become an attractive alternative for foreign investors during global economic policy uncertainty. Regarding financial development, the amount of credit provided by the domestic banking sector to the private sector in Indonesia positively influences Indonesia’s FDI in both the short and long terms. This demonstrates that Indonesia’s financial condition and infrastructure can determine foreign investors’ decisions to invest in Indonesia.

Purpose ― This paper examines the impact of major uncertainty indices and global uncertainty on the volume of Sukuk issuance in Türkiye. Method — The NARDL method is applied to determine the short- and long-term relationships between Türkiye's sukuk issuance and global uncertainty and financial stress indices, capturing both symmetric and asymmetric dimensions.Findings — Although a symmetric relationship exists between Global Economic Policy Uncertainty (GEPU) and Sukuk issuance, the Financial Stress Index (FSI) has no long-term impact on Sukuk issuance. During periods of global uncertainty, sukuk issuances increase, whereas in conditions of less uncertainty, they fall. There is an inverse relationship between Geopolitical Risk (GPR) and Sukuk issuance. Since all factors affect sukuk issuance in the short run, GEPU has the highest impact. Decreases in the GEPU index positively affect sukuk securities and increase their issuance volumes. Therefore, GPR and GEPU indices have asymmetric effects on sukuk issuances in the short and long term.Implication — Evidence suggests that sukuk is more resilient to crises than its conventional equivalents. Sukuks are strategically crucial for portfolios and provide sufficient assurance to reduce risk.Originality — No study has assessed how global financial distress and uncertainty influence Türkiye's sukuk issuance. This study differs from previous studies by focusing on sukuk issuance volumes rather than sukuk yields.

As economies become increasingly interconnected, individual economies are at risk of shocks from external uncertainties ranging from fluctuations in climate regulations to geopolitical conflicts and international economic policies.The purpose of the study is to investigate the time-varying correlation between global uncertainties (e. g., global economic policy uncertainty, climate policy uncertainty and geopolitical risk) and economic activity in a developing economy using a dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) model.The relevance of the research lies in the increasing interconnectedness of global economies and the subsequent exposure of individual economies to external shocks.The scientific novelty is hinged on the study being among the first to study the relationship in Ghana. Using monthly data for the 2002–2022 period for Ghana, we estimate a multivariate GARCH model.The results of the study indicate that climate policy uncertainty and global economic policy uncertainty are mean reverting, implying that the volatility of the variables decay slowly and persists for a longer time such that the conditional variance will eventually return to its long-term average level after being disturbed by shocks. Global uncertainties over time are strongly negatively correlated with economic activity and produce significant spikes, especially during periods of major world events.The study recommends that policymakers need to consider the prolonged impact of global uncertainties on economic performance when designing economic policies and interventions. The significant spikes during major global events highlight the importance of crisis management and preparedness in maintaining economic stability during periods of heightened uncertainty.

Quantifying uncertainty in petroleum resources is important for development planning and decision making. Increasingly, geostatistical techniques are used to integrate diverse data sources and provide a defensible model of uncertainty. Petroleum resources are calculated from a combination of variables including thickness, porosity and saturation. Uncertainty in global petroleum resources are calculated stepwise:establish the local uncertainty in each variable using a conventional Gaussian geostatistical model;sample the local distributions with spatial correlation using a p-field based technique;modify the p-field samples to have the correct multivariate variability using the LU technique; and,assemble the distribution of uncertainty over any volume using the joint spatial/multivariate realizations. The alternatives to this technique are a simplistic Monte Carlo simulation without spatial correlation or a more complex high resolution geostatistical model. Speed and mathematical consistency are the main advantages of the proposed technique. The theoretical basis of the spatial/multivariate decomposition approach is developed with the assumptions and implementation details. A synthetic example from a realistic case study is presented showing the global uncertainty in oil-in-place over arbitrarily large areas. Introduction Geostatistical techniques have been increasingly used for reservoir characterization for two main reasons:different data sources can be integrated to predict a reservoir property between wells; and,an assessment of uncertainty in the estimation can be obtained(1). Quantifying global uncertainty in petroleum resources is important for reservoir development planning and decision making. There are two challenges that must be addressed:the scale of uncertainty ---local uncertainty must be scaled to global uncertainty; and,the multivariate relationship between the variables that go into resource calculations ---predictions of uncertainty must account for the correlation between variables. Conventional geostatistical techniques predict local uncertainty at the scale of the data. Global uncertainty refers to the petroleum resource, or the oil-in-place (OIP), for an arbitrarily large area. The global uncertainty in OIP cannot be calculated by simply summing the local uncertainties. The spatial continuity of the variables must be considered in scaling local uncertainty to global uncertainty. If the variable is very discontinuous, then the uncertainty decreases quickly with scale. If the variable is continuous, then the uncertainty decreases slowly, but fewer data are needed to constrain the uncertainty. Simulation must be used to combine uncertainty reconciling these two notions. OIP is calculated from several reservoir properties, such as net pay thickness, porosity and oil saturation. Treating the variables independently has a risk of underestimating the global resource uncertainty. High values average out with low values. The correlation between the multiple constituent variables of OIP must be calculated. A spatial/multivariate decomposition approach is proposed for assessing the global uncertainty in OIP from local uncertainties. The joint spatial and multivariate correlations are taken into account. The key idea is to simulate a set of spatially correlated probability values (a ‘p-field’) and then simultaneously draw the variable of interest at multiple locations. The LU decomposition is used to account for the multivariate correlations at each location.

Global Uncertainty and the Global Economy: Decomposing the Impact of Uncertainty Shocks

Global Bad and Good Uncertainties and Their Impact on Macro Aggregates and Stock Returns

The objective of this study is to examine the influences of institutions, globalization, and world uncertainty on bank profitability in small developing economies. Consequently, we emphasize the significance of both bank-specific and other external factors influencing bank profitability. The empirical estimation is based on seven banks in Fiji—a small island economy—over the period 2000–2021. Together with bank-specific and macro factors, we account for institutions, globalization, and world uncertainty in analyzing the determinants of bank profitability. The study uses the fixed-effect estimation method. From the results, we observe that bank-specific variables, like the net interest margin, non-interest income, bank size, and capital adequacy ratio, are positively associated with bank profitability. Non-performing loans and credit risk are negatively associated with bank profitability. Macro variables, such as real GDP growth and remittances, have positive effects on bank profitability. Institutional factors, such as government effectiveness and voice and accountability, are positively associated with bank profitability. Regarding globalization, we find that it supports bank profitability. Global uncertainty and the Global Financial Crisis (2007–2008) are positively associated with profitability, whereas the global pandemic (COVID-19) is negatively associated. This study underscores the need to analyze the bank performance with factors beyond those reported in financial statements to derive a comprehensive understanding and appreciation of the complex nature of banking operations.

Global Uncertainty, Shocks, and Macroeconomic Performance: The Cases of Indonesia, Malaysia, the Philippines, and Thailand

Overall and time-varying effects of global and domestic uncertainty on the Korean economy

This study examines how monetary and fiscal policies affect economic growth in China under global economic uncertainty. We estimate a Markov Switching Regression (MSR) model using quarterly data from 1996: Q1 to 2024: Q4. We also apply Bayesian Model Averaging (BMA) to choose the relevant control variables. During expansions, higher policy rates, government revenue, moderate inflation, FDI inflows, and export growth support growth. Government expenditure can crowd out private investment. During recessions, higher policy rates reduce growth. Government expenditure has limited impact, but revenue collection remains growth-supportive. Global uncertainty steadily reduces growth. Government expenditure shows negative effects, which indicates possible crowding out. The findings support that monetary and fiscal policies coordination may sustain long-term growth in China and strengthen the resilience amid global uncertainty. The Impulse response functions (IRFs) from Bayesian Vector Autoregression (BVAR) confirm the persistence and dynamics of policy shocks under global uncertainty. This study adds to the empirical literature on the role of macroeconomic policies in shaping economic growth in the case of China.

This study aims to examine the relationship between CUM, CPU, CU, and UCT with the FTSE China Technology Index (FTXIN410) and SZSE Environmental Protection Index (SZEPI) using ARDL and NARDL methods. To test the robustness of the model, three additional parametric methods are employed: FMOLS, DOLS, and CCR. The technology and environmental protection sectors in China are crucial for the country's sustainable economic future. Understanding the impact of global and local uncertainties on these sectors is critical for predicting sectoral trends and future market dynamics. Climate uncertainties and global uncertainties can impact investors' returns and market behaviors. In critical sectors such as technology and environmental protection, uncertainties need to be closely monitored for their implications on investment decisions and market stability. The results of the study indicate a long-term relationship between China’s climate uncertainties and global uncertainties with technology and environmental protection indices.

This inquiry extended uncertainty reduction theory to include actors’ uncertainty about acquaintanceship in general (global uncertainty). Study 1 involved examination of the self-reports of 139 female and 85 male participants. Results of the analysis showed that participants high in global uncertainty define initial interaction in comparatively negative ways, more frequently attempt to avoid conversations with unfamiliar targets, perform less effectively when meeting others for the first time, and develop less satisfactory long-term relationships than persons low in global uncertainty. Global uncertainty also combined with participants’ sense of the self-assuredness-awkwardness of first encounters to predict initial interaction performance. Study 2 examined the conversational performance of 48 females and 28 males who had participated in the first investigation. This analysis revealed that, during the first minute of interaction, persons high in global uncertainty engaged in comparatively low levels of question asking but relatively high levels of disclosure. High globally uncertain participants were also rated less competent by their partners than were persons low in global uncertainty. Study 3 explored the relationship between global uncertainty, communication competence, and communication apprehension. Examination of the self-reports of 63 females and 49 males showed that persons high in global uncertainty are apprehensive when meeting strangers and enact acquaintanceship episodes relatively inexpertly, although the magnitude of correlations between the constructs provide strong evidence that global uncertainty is distinguishable from both competence and apprehension. The implications of these findings are discussed.