Determinants of the Elderly Share of Population: A Cross-Country Empirical Analysis.

COVID-19 has had a disproportionate impact on the elderly, who are over-represented among those who suffered severe illness or death. The obvious implication is that the share of the elderly in the population significantly affects the impact of COVID-19 on the overall health of a country. More generally, the elderly share has far-reaching economic and social ramifications. In this paper, we perform empirical analysis of cross-country data from 1970 to 2018 to identify the determinants of the share of the elderly-i.e., those aged 65 and over-in a country's population. We find that the quality of health care, life expectancy, and female labor participation increases the elderly share while higher fertility and female education attainment lower the elderly share. In addition, we find that the share is higher for high income countries and countries in Europe and Central Asia.

Corrigendum: Elevated IFNA1 and suppressed IL12p40 associated with persistent hyperinflammation in COVID-19 pneumonia.

[This corrects the article DOI: 10.3389/fimmu.2023.1101808.].

The impact of COVID-19 on the economic performance of Wuhan, China (2019-2021).

This paper attempts to evaluate the impact of massive infectious and contagious diseases and its final impact on the economic performance anywhere and anytime. We are considering to evaluate the case of Wuhan, China. We are taking in consideration the case of COVID-19 to be evaluated under a domestic, national, and international level impact. In this paper, we also propose a new simulator to evaluate the impact of massive infections and contagious diseases on the economic performance subsequently. This simulator is entitled "The Impact of Pandemics on the Economic Performance Simulator (IPEP-Simulator)" Hence, this simulator tries to show a macro and micro analysis with different possible scenarios simultaneously. Finally, the IPEP-Simulator was applied to the case of Wuhan-China respectively.

Elevated IFNA1 and suppressed IL12p40 associated with persistent hyperinflammation in COVID-19 pneumonia.

Introduction: Despite of massive endeavors to characterize inflammation in COVID-19 patients, the core network of inflammatory mediators responsible for severe pneumonia stillremain remains elusive. Methods: Here, we performed quantitative and kinetic analysis of 191 inflammatory factors in 955 plasma samples from 80 normal controls (sample n = 80) and 347 confirmed COVID-19 pneumonia patients (sample n = 875), including 8 deceased patients. Results: Differential expression analysis showed that 76% of plasmaproteins (145 factors) were upregulated in severe COVID-19 patients comparedwith moderate patients, confirming overt inflammatory responses in severe COVID-19 pneumonia patients. Global correlation analysis of the plasma factorsrevealed two core inflammatory modules, core I and II, comprising mainly myeloid cell and lymphoid cell compartments, respectively, with enhanced impact in a severity-dependent manner. We observed elevated IFNA1 and suppressed IL12p40, presenting a robust inverse correlation in severe patients, which was strongly associated with persistent hyperinflammation in 8.3% of moderate pneumonia patients and 59.4% of severe patients. Discussion: Aberrant persistence of pulmonary and systemic inflammation might be associated with long COVID-19 sequelae. Our comprehensive analysis of inflammatory mediators in plasmarevealed the complexity of pneumonic inflammation in COVID-19 patients anddefined critical modules responsible for severe pneumonic progression.

On the volatility of WTI crude oil prices: A time-varying approach with stochastic volatility

This study investigates the impacts of crude oil-market-specific fundamental factors and financial indicators on the realized volatility of West Texas Intermediate (WTI) crude oil price. A time-varying parameter vector autoregression model with stochastic volatility (TVP-VAR-SV) is applied to weekly data series spanning January 2008 to October 2021. It is found that the WTI oil price volatility responds positively to a shock in oil production, oil inventories, the US dollar index, and VIX but negatively to a shock in the US economic activity. The response to the EPU index was initially positive and then turned slightly negative before fading away. The VIX index has the most significant effect. Furthermore, the time-varying nature of the response of the WTI realized oil price volatility is evident. Extreme effects materialize during economic recessions and crises, especially during the COVID-19 pandemic. The findings can improve our understanding of the time-varying nature and determinants of WTI oil price volatility.

ICT and Economic Resilience during COVID-19: Cross-Country Analysis

The central objective of this paper is to empirically assess whether countries with better information and communication technology (ICT) infrastructure suffered less GDP growth deceleration during COVID-19. The scope of this paper is to apply linear estimation to a sample of 117 economies, including 86 emerging market and developing economies and 31 advanced economies, to analyze the relationship between ICT and GDP growth deceleration during the pandemic period. Controlling for other variables that can also influence economic performance, we find empirical support for a positive impact of ICT. For a given COVID-19 infection rate, we find that economies with better internet access showed greater resilience, defined as less in terms of economic growth. The obvious policy implication is that governments should invest more in ICT infrastructure to strengthen the resilience of their economies in the face of major shocks.

Establishment of the large-scale longitudinal multi-omics dataset in COVID-19 patients: data profile and biospecimen.

Understanding and monitoring virus-mediated infections has gained importance since the global outbreak of the coronavirus disease 2019 (COVID-19) pandemic. Studies of high-throughput omics-based immune profiling of COVID-19 patients can help manage the current pandemic and future virus-mediated pandemics. Although COVID-19 is being studied since past 2 years, detailed mechanisms of the initial induction of dynamic immune responses or the molecular mechanisms that characterize disease progression remains unclear. This study involved comprehensively collected biospecimens and longitudinal multi-omics data of 300 COVID-19 patients and 120 healthy controls, including whole genome sequencing (WGS), single-cell RNA sequencing combined with T cell receptor (TCR) and B cell receptor (BCR) sequencing (scRNA(+scTCR/BCR)-seq), bulk BCR and TCR sequencing (bulk TCR/BCR-seq), and cytokine profiling. Clinical data were also collected from hospitalized COVID-19 patients, and HLA typing, laboratory characteristics, and COVID-19 viral genome sequencing were performed during the initial diagnosis. The entire set of biospecimens and multi-omics data generated in this project can be accessed by researchers from the National Biobank of Korea with prior approval. This distribution of largescale multi-omics data of COVID-19 patients can facilitate the understanding of biological crosstalk involved in COVID-19 infection and contribute to the development of potential methodologies for its diagnosis and treatment. [BMB Reports 2022; 55(9): 465-471].

On Hedging Properties of Infrastructure Assets during the Pandemic: What We Learn from Global and Emerging Markets?

Infrastructure investment is essential for economic development for both developed and developing economies. We analyze the short-term return behavior and portfolio characteristics of the global, regional, and selected Asian countries’ infrastructure indexes during the pandemic over the sample period 3 July 2018 to 1 July 2021. According to the multivariate Glosten, Jagannathan, and Runkle (GJR) Generalized Autoregressive Conditional Heteroscedasticity (GARCH) with dynamic conditional correlation (DCC) model, infrastructure assets are very heterogeneous depending on the corresponding asset classes. Empirical evidence suggests that infrastructure can be treated as a separate asset sub-class within conventional financial assets. Moreover, we quantify the co-movements between returns on various listed infrastructure indexes and major asset classes, including equity, commodity, currency, and bond index returns. We find that infrastructure assets offer hedging potential against the USD index and USD denominated assets.

Go green or stay black: Bond market dynamics in Asia

This paper presents a picture of the risk spillover relationship of green & black bonds in Asia. In normal situations and the long-term horizon, green bonds and black bonds have similar impacts with each other, with a slight predominance of black bonds. From the dynamic connectedness results, the sample period is classified into three stages. The first stage is a period with equal role of green and black bonds from Jan 2018 to Feb 2020, which is regarded as a normal situation of the bond market. The second stage is the unbalanced period with a turning point of the Covid-19, with the increased gap of the connectedness exported by green and black bonds. The third stage is the recovery period after Oct 2020, with the role of green and black bonds recovered slowly to the equal status. In addition, the green-to-black connectedness in longer term witnesses faster and stronger recovery, which suggests that the long-term influences of green bonds are relatively stable than the short-term influences. Moreover, the paper tests the effects of the same issuer. Our analysis shows that there are strong connections among bonds in the Philippines that are issued by the same institution. However, the same issuer is not a sufficient condition for a strong connectedness. Furthermore, our analysis in China Mainland, reveals that the green policy will firstly cause the change of green bonds price and then spillover the impact to conventional markets. Through the study of the drivers of connectedness dynamics in four directions (green-to-green, black-to-black, green-to-black, black-to-green), we present empirical findings that are crucial for investors and policymakers in risk management, hedging strategy, and green investment acceleration.

Dynamic Interactions between Trade Globalization and Financial Globalization: A Heterogeneous Panel VAR Approach

The postwar period has seen a rapid growth in trade and financial globalization. However, trade globalization has decelerated since the global financial crisis (GFC) and may decelerate even further after COVID-19. An interesting and significant issue is whether trade deglobalization may lead to financial deglobalization. This paper analyzes the dynamic interactions between trade integration and financial integration by employing the panel VAR models that allow full heterogeneity among individual countries. We find that trade integration positively affects financial integration. This result is robust to various specifications of the model. We also find that financial integration tends to positively affect trade integration. However, such a tendency disappeared after the GFC. Our results suggest that the ongoing trade deglobalization may adversely affect financial globalization in the future.

Good-Bye Original Sin, Hello Risk On-Off, Financial Fragility, and Crises?

We analyze the sovereign bond issuance data of eight major emerging markets (EMs) - Brazil, China, India, Indonesia, Mexico, Russia, South Africa and Turkey from 1970 to 2018. Our analysis suggests that (i) EM local currency bonds tend to be smaller in size, shorter in maturity, or lower in coupon rate than foreign currency bonds;(ii) EMs are more likely to issue local-currency sovereign bonds if their currencies appreciated before the global financial crisis of 2008 (GFC);(iii) inflation-targeting monetary policy increases the likelihood of issuing local-currency debt before GFC but not after;and (iv) EMs that offer higher sovereign yields are more likely to issue local-currency bonds after GFC. Future data will allow us to test and identify structural changes associated with the COVID-19 pandemic and its aftermath.

Financial uncertainty and interest rate movements: is Asian bond market volatility different?

The COVID-19 pandemic has given rise to a spike in financial market volatility. In this paper, we attempt to assess the effects of financial & news-driven uncertainty shocks in growing Asian economies, using country-specific bond volatility shocks as a measure of local interest rate uncertainty. Also, we contrast the effects of local uncertainty with global stock market uncertainty. Using bond market data from nine Asian markets, we uncover a transmission mechanism of uncertainty shocks via the bond market. The mechanism works as a crowding-out effect due to government-led excessive market borrowing with supply-side consequences for the private sector, as opposed to economic policy or global stock market uncertainty which works more like a demand shock as in the literature. We conclude that countries with growing fiscal deficits that entail a larger government bond market or higher current account deficits, tend to experience an increase in the cost of borrowing due to this bond market volatility or interest rate uncertainty shocks.

The shape of recovery: Implications of past experience for the duration of the COVID-19 recession.

In this paper we seek to make headway on the question of what recovery from Covid-19 recession may look like, focusing on the duration of the recovery - that is, how long it will take to re-attain the levels of output and employment reached at the prior business cycle peak. We start by categorizing all post-1960 recessions in advanced countries and emerging markets into supply-shock, demand-shock and both-shock induced recessions. We measure recovery duration as the number of years required to re-attain pre-recession levels of output or employment. We then rely on the earlier literature on business cycle dynamics to identify candidate variables that can help to account for variations in recovery duration following different kinds of shocks. By asking which of these variables are operative in the Covid-19 recession, we can then draw inferences about the duration of the recovery under different scenarios. A number of our statistical results point in the direction of lengthy recoveries.

Measuring the Economic Risk of COVID-19

Abstract We measure the economic risk of COVID-19 at a geo-spatially detailed resolution. In addition to data about the current prevalence of confirmed cases, we use data from 2014?2018 and a conceptual disaster risk model to compute measures for exposure, vulnerability, and resilience of the local economy to the shock of the epidemic. Using a battery of proxies for these four concepts, we calculate the hazard, the principal components of exposure and vulnerability to it, and of the economy?s resilience (i.e. its ability of the recover rapidly from the shock). We find that the economic risk of this pandemic is particularly high in most of Sub-Saharan Africa, South Asia, and Southeast Asia. These results are consistent when comparing an ad hoc equal weighting algorithm for the four components of the index, an algorithm that assumes equal hazard for all countries, and one based on estimated weights using previous aggregated disability-adjusted life years losses associated with communicable diseases.