A study on the changes in the ICT industry after the COVID-19 pandemic

Purpose: The aim of this paper is to explore the changes in the ICT and global value chains (GVCs) after the COVID-19 pandemic. Design/methodology/approach: This study compared the difference between Korea' domestic ICT industries, ICT imports and ICT exports before and after the COVID-19 outbreak by using trade data of ICT products and national economic indicators, and presents growth strategy for the ICT industry in the post-COVID 19 era. For this purpose, this study determined the causalities between Korea's imports/exports of ICT products and composite Indexes before and after COVID-19, and derived implications in the ICT industry environment after the COVID-19 pandemic. Findings: Analysis results showed the following changes in Korea's ICT industry in the post-COVID-19 world. (1) Non-face-to-face and contact-free technologies related sectors in the ICT industry, such as the semiconductor sector, have grown exponentially;(2) as the USA has grown as the new key player, the causal relationship with China, a key player of the GVC in the pre-COVID-19 era, disappeared;and (3) the GVC of the ICT industry is not a rigid one-way vertical structure, but is changing to a flexible structure influenced by cooperation and competition between countries. Originality/value: The results indicate that it is essential to constantly develop new ICT sectors that make use of non-face-to-face and contact-free technologies in the post-COVID-19 era, and the main strategies in response to the changed GVC would be taking the initiative by securing source technologies and expanding through cooperation with other GVCs and resource sharing. © 2022, Emerald Publishing Limited.

Forecasting Spanish economic activity in times of COVID-19 by means of the RT-LEI and machine learning techniques

The main aim of this paper is to analyse and estimate the behaviour of the Spanish economic activity in the next 12 months, by means of a Real-Time Leading Economic Indicator (RT-LEI), based on Google Trends, and the real GDP. We apply methodologies based on fractional integration and cointegration to measure the degree of persistence and to examine the long-term relationship. Finally, we carry out a forecast using a Machine Learning model based on an Artificial Neural Network. Our results indicate that the Spanish economy will experience a contraction in 1Q-21 and will require strong measures to reverse the situation and recover the original trend.

Nowcasting of Lumber Futures Price with Google Trends Index Using Machine Learning and Deep Learning Models

L/umber futures have been traded at Chicago Mercantile Exchange since 1969 (Mehrotra and Carter 2017). Since the COVID-19 pandemic, the lumber futures price has experienced huge volatility. The unusual fluctuations exposed lumber futures products that were originally designed to hedge uncertainties to huge risks. [...]there is an urgent need to find a reliable method to predict the lumber futures price, which would help enterprises and investors hedge risks and make correct decisions in the market. [...]Google Trends index is widely used to predict economic indicators and socioeconomic indicators, such as sales, unemployment, travel, consumer confidence (Choi and Varian 2012), consumer behavior (Carriere-Swallow and Labbe 2013), housing market (Dietzel 2016), the stock price (Hu et al. 2018), and so on. [...]the components of variables will change to capture dynamic trends of the real world.

THE ASYMMETRICAL IMPACT OF POLICY RESPONSES ON VOLATILITY OF SOVEREIGN DEFAULT SWAPS

The COVID-19 pandemic has adversely influenced economies around the world through supply and demand channels. The increasing uncertainty and the decreasing demand due to the strict social measures of the government to cushion the spread of the pandemic have transformed COVID-19 from a health crisis into an economic crisis. To moderate the negative economic atmosphere during this period, the governments have implemented expansionary fiscal policy. The purpose of this paper is to investigate the impacts of the social and economic measures taken during COVID-19 on the volatility of sovereign credit default swaps for Turkey, Italy, Spain, the United Kingdom, and the United States. The empirical findings indicate that social distancing measures increase uncertainty, but health and economic policies moderate the negative impacts on the economy of Turkey, Spain, and the United Kingdom. The impact of the policies in question is greater in the high number of case regimes.

Interconnections between Social and Economic Indicators in the Context of EU Resilience

The COVID 19 pandemic has once again exposed a number of important risks and problems for the world's economies. Although the present analyzes in the literature are more and more often aggregated between fields, emphasizing the capacity of digitalization and international relations to improve the transition to the circular economy, resilience speaks not only of positive aspects but also of vulnerabilities. Thus, the article deals with the link between vulnerabilities and capacities of the socio-economic domain at EU27 level. The study uses Eurostat data for the period 2011-2020, systematized in the panel form. The results once again demonstrate the need to strengthen public support for health and education, for research and development, in order to reduce socio-economic vulnerabilities at EU27 level, demonstrating the need to correlate policy efforts with results.

Is this full employment? assessing global labor force dynamics

How do we define full employment? It depends on things such as demographics and the particulars of why or why not people are looking for work. Also, have we achieved full employment when some groups are clearly not fully employed? The behavior of earnings and hours also need to be considered. In the US, some groups are not fully employed. Europe appears to be fully employed, but that in part reflects reductions in hours. China shows a substantial mismatch where skilled youth have problems in finding appropriate jobs. Finally, in Saudi Arabia and other Gulf states, there is sharp difference between the labor markets for nationals and non-nationals.

Small scale handline tuna fishery in Buru Island, Maluku Province, Indonesia, during the Covid-19 pandemic

. Small scale handline tuna fishery is an important livelihood for the coastal communities in Buru Island which includes Buru and South Buru Regency. Information regarding the livelihood condition of the tuna handline fishery in Buru Island is still limited. This situation is increasingly complex, due to the COVID-19 pandemic which impacted the communities livelihood, due a significant decrease of the prices and demand. Understanding of socioeconomic conditions is important for planning and developing policies and programs for sustainable fisheries. The study aimed to assess the socioeconomic conditions of tuna handline fisheries in Buru Island, including the costs-revenues balance and the fishers' income. Data collection was carried out in March-August 2020 in Buru and South Buru Regency. This study showed that the average revenue, gross profit and income of fishers during the pandemic period decreased by 39.05, 66.26 and 63.22%, respectively, compared to the situation in 2019.

PANDEMIA Y DESIGUALDAD: UN ANÁLISIS EN TIEMPO REAL (*)

Diversos estudios bioarqueológicos han mostrado que las pandemias tienen un impacto muy relevante en el incremento de las desigualdades preexistentes. Una preocupación importante durante el periodo de propagación del COVID-19 fue que su impacto económico pudiera afectar de manera desproporcionada a los segmentos más vulnerables de la población. Un problema habitual con las medidas de desigualdad es que su cálculo se produce con bastante retraso y de forma muy infrecuente. En este artículo presentamos una metodología pionera para analizar la evolución de la desigualdad en tiempo real que permite reajustar las acciones de política económica para mitigar el impacto de un shock de desarrollo rápido, como la pandemia, sobre la desigualdad. Este trabajo es fruto de un proyecto pionero de colaboración público-privada entre la Universitat Pompeu Fabra-IPEG y el Departamento de Investigación de CaixaBank. Los resultados muestran el enorme aumento de la desigualdad que se produjo durante los primeros meses de la pandemia y el efecto que tuvieron los ERTE en la mitigación de dicho aumento. A principios de 2022 la desigualdad había vuelto al nivel prepandémico tanto en términos agregados como por subgrupos de la población.Alternate :Several bio-archaeological studies have shown that pandemics have a very significant impact on the increase in pre-existing inequalities. A major concern during the period of spread of COVID-19 was that its economic impact could disproportionately affect the most vulnerable segments of the population A common problem with inequality measures is that their calculation is produced with considerable delay and very low frequency. In this article, we present a pioneering methodology to analyze the evolution of inequality in real time that allows economic policy actions to be readjusted to mitigate the impact of a rapidly developing shock, such as the pandemic, on inequality. This work is the result of an innovative public-private collaboration project between the Universitat Pompeu Fabra-IPEG and the CaixaBank research department. The results show the enormous increase in inequality that occurred during the first months of the pandemic, and the effect that ERTE had in mitigating this increase. By early 2022, inequality had returned to the pre-pandemic level both at the aggregate level and by population subgroups.

Privacy and Integrity Threats in Contact Tracing Systems and Their Mitigations

Several countries adopted the Google & Apple exposure notification system (GAEN) to slow the spread of the SARS-CoV-2 virus down. GAEN promised to guarantee security and privacy through a decentralized approach. In this paper, we report several relevant privacy and integrity threats in GAEN, including new attacks. GAEN's security issues are not inherent risks of contact tracing systems. Indeed, we also propose a system named Pronto-B2 which enjoys a much better resilience with respect to mass surveillance and replay attacks. IEEE

Bank-specific performance indicators, macroeconomic variables and capital adequacy of Nigerian banking industry

[...]we canvass those Nigerian banks should reduce dividend payouts and increase retained profits as a buffer against exposed risks. To ensure the healthiness of banks in the banking industry as well as facilitate international transaction, the central bank of ten countries (Belgium, Canada, France, Germany, Italy, Japan, the Netherlands, Sweden, the UK and the US) formed the committee of banking supervision in 1988 (the Basel Committee on Banking Supervision). Since the formation of this committee, it has undergone at least three stages called the Basel I, Basel II and Basel III. Premised on shock to the economy brought on by the coronavirus pandemic, with economic growth in 2020 expected to contract by as much as 4.4 percent to 8.94 percent, a drop in oil receipt and a devalued Naira in the range of 380-450 to US dollar, the capital adequacy of banks could be severely threatened, (Egba, 2020). [...]scholars have extensively shown that bank specific performance indicators and macroeconomic factors affected capital adequacy ratio. [...]this paper examined the effect of banks specific-performance indicators and macroeconomic factors on bank financing which is the minimum funds required for their short-term obligation or capital adequacy ratio.

Editorial: Logistics connectivity in East Asia: practices and challenges

In Tomoya Kawasaki, Takuma Matsuda, Yui-yip Lau and Xiaowen Fu (The durability of economic indicators in container shipping demand: a case study of East Asia–US container transport), the durability of economic indicators on container movements from East Asia to the USA are identified by a vector autoregression model using monthly-based time-series data. Takuma Matsuda, Enna Hirata and Tomoya Kawasaki aim to contribute to the empirical literature on the container shipping industry market structure (Monopoly in the container shipping market: an econometric approach). Phong Nha Nguyen and Hwayoung Kim aim to identify the characteristics of the maritime shipping network in Northeast Asia as well as compare the level of port connectivity among these container ports in the region (Analyzing the international connectivity of the major container ports in Northeast Asia).

Partisanship and Fear are Associated with Resistance to COVID-19 Directives

Ideological differences have had a large impact on individual and community response to the COVID-19 pandemic in the United States. Early behavioral research during the pandemic showed that conservatives were less likely to adhere to health directives, which contradicts a body of work suggesting that conservative ideology emphasizes a rule abiding, loss aversion, and prevention focus. We reconcile this contradiction by analyzing semantic content of local press releases, federal press releases, and localized tweets during the first month of the government response to COVID-19 in the United States. Controlling for factors such as COVID-19 confirmed cases and deaths, local economic indicators, and more, we find that online expressions of fear in conservative areas lead to an increase in adherence to public health recommendations concerning COVID-19, and that expressions of fear in government press releases are a significant predictor of expressed fear on Twitter. © 2021 Association for Computational Linguistics.

Strategic sectors to the post COVID-19 economic recovery of Parana. (Estrutura e dinamica da economia paranaense.) [Portuguese]

Sectors strategic to the post Covid-19 economic recovery Parana are identified here by using an input-output matrix and economic indicators calculated from 2018 Parana-Rest of Brazil interregional system data. Intersectoral linkages indices portray food industry, civil construction, commerce and land transport as driving sectors of the state economy. Results concerning production, employment and income are higher for the textile and clothing, commerce, accommodation and food, education, health, and software development sectors, the latter being an important sector for the emergence of micro and small business. Incentive actions directed to strategic sectors in the economic recovery involve professional qualification, microcredit, business incubators, and extension activities focusing the dissemination of new communication and sales technologies.

Impact of Mass Tourism on the Quality of Life in Split, Croatia : Residents’ Opinions in the Light of the COVID-19 Pandemic

This study addresses the everyday life in the city of Split during the tourist season from the perspective of the quality of life (QOL) concept. The research was conducted in June 2020, through an online survey distributed among a sample of 328 residents of Split aged 18 and above. A high percentage of respondents earn income from tourism (41.5%). Opinions are divided concerning its overall impact on the quality of life. While economic indicators are seen as positive, the rest are mostly rated negatively. The majority of respondents do not find the existing model of tourism to be sustainable, with their responses independent of earning income within the sector. The locals’ attitudes toward tourists are mostly assessed as friendly (45.1%). However, a significant percentage of respondents also point to indifference (24.7%) or hostility (10%), which can be associated with the work in the tourism industry and the assessment of its negative impacts on the quality of life. The general divisions among respondents within the study, as well as numerous negatively rated QOL elements, indicate the need for planning a more sustainable model of tourism. This includes achieving a greater representation of selective forms of tourism, reducing the dominance of the sector compared to other branches of the economy and increasing the quality of life in Split.

With the Continuing Increase in Sub-Saharan African Countries, Will Sustainable Development of Goal 1 Ever Be Achieved by 2030?

The poor in Sub-Saharan Africa (SSA) are in a worse predicament than their counterparts in other regions. The goal of this study was to establish the key drivers of poverty in SSA by looking at how economic variables affect growth and poverty. Data from ten SSA nations—upper-middle-income countries (UMIC), lower-middle-income countries (LMIC), and low-income countries (LIC)—were analyzed based on historical values from 2015 to 2019. From the six economic variables studied, the best model reveals that 78% of the differences in poverty can be accounted for using a methodical, statistical approach. Poverty and unemployment rates have a substantial positive relationship (p = 0.001662). The gross domestic product (GDP) growth rate and poverty have a slight link, which is significant at the 10% level (p = 0.067) but is not a significant contributor to poverty alleviation. The secondary school enrolment rate has no bearing on poverty variation (p = 0.33). Increased GDP does not necessarily correspond to poverty reduction. Unemployment, on the other hand, is a major contributor to poverty in the region. Moreover, education (secondary school ennoblement) plays a less important role in reducing poverty, whereas per capita personal consumer spending and GDP growth rate have a bigger impact on poverty reduction. The proposed theoretical and numerical model works on general indicators and trends;it does not guarantee that people in the UMIC, LMIC, and LIC countries may not fall below the international poverty line ($1.90 per day). The poverty rates are predicted to climb by more than 2% by 2030, postponing poverty elimination in the SSA region by almost five years. This signifies that more than half of the SSA population will remain poor.

Pandemic-Era Uncertainty

We examine several measures of uncertainty to make five points. First, equity market traders and executives at nonfinancial firms have shared similar assessments about one-year-ahead uncertainty since the pandemic struck. Both the one-year VIX and our survey-based measure of firm-level uncertainty at a one-year forecast horizon doubled at the onset of the pandemic and then fell about half-way back to pre-pandemic levels by mid-2021. Second, and in contrast, the 1-month VIX, a Twitter-based Economic Uncertainty Index, and macro forecaster disagreement all rose sharply in reaction to the pandemic but retrenched almost completely by mid-2021. Third, Categorical Policy Uncertainty Indexes highlight the changing sources of uncertainty—from healthcare and fiscal policy uncertainty in spring 2020 to elevated uncertainty around monetary policy and national security as of May 2022. Fourth, firm-level risk perceptions skewed heavily to the downside in spring 2020 but shifted rapidly to the upside from fall 2020 onwards. Perceived upside uncertainty remains highly elevated as of early 2022. Fifth, our survey evidence suggests that elevated uncertainty is exerting only mild restraint on capital investment plans for 2022 and 2023, perhaps because perceived risks are so skewed to the upside.

A Generalized Entropy Approach to Portfolio Selection under a Hidden Markov Model

This paper develops a dynamic portfolio selection model incorporating economic uncertainty for business cycles. It is assumed that the financial market at each point in time is defined by a hidden Markov model, which is characterized by the overall equity market returns and volatility. The risk associated with investment decisions is measured by the exponential Rényi entropy criterion, which summarizes the uncertainty in portfolio returns. Assuming asset returns are projected by a regime-switching regression model on the two market risk factors, we develop an entropy-based dynamic portfolio selection model constrained with the wealth surplus being greater than or equal to the shortfall over a target and the probability of shortfall being less than or equal to a specified level. In the empirical analysis, we use the select sector ETFs to test the asset pricing model and examine the portfolio performance. Weekly financial data from 31 December 1998 to 30 December 2018 is employed for the estimation of the hidden Markov model including the asset return parameters, while the out-of-sample period from 3 January 2019 to 30 April 2022 is used for portfolio performance testing. It is found that, under both the empirical Sharpe and return to entropy ratios, the dynamic portfolio under the proposed strategy is much improved in contrast with mean variance models.

Can older workers be retrained? Canadian evidence from worker-firm linked data

Our empirical analysis is based on Statistics Canada’s worker-firm matched data set, the 2003 Workplace and Employee Survey (WES). The sample size is substantial: about 4,000 workers over the age of 50 and 12,000 between the ages of 25 and 49. Training was a focus of the survey, which offers a wealth of worker-related and firm-related training variables. We found that the mean probability of receiving training was 9.3 percentage points higher for younger workers than for older ones. Almost half of the gap is explained by older workers having fewer training-associated characteristics (personal, employment, workplace, human resource practices and occupation/industry/region), and slightly more than half by them having a lower propensity to receive training, this being the gap that remained after we controlled for differences in training-associated characteristics. Their lower propensity to receive training likely reflects the higher opportunity cost of lost wages during the time spent in training, possible higher psychological costs and lower expected benefits due to their shorter remaining work-life and lower productivity gains from training, as discussed in the literature. The lower propensity of older workers to receive training tended to prevail across 54 different training measures, with notable exceptions discussed in detail. We found that older workers can be trained, but their training should be redesigned in several ways: by making instruction slower and self-paced;by assigning hands-on practical exercises;by providing modular training components to be taken in stages;by familiarizing the trainees with new equipment;and by minimizing required reading and amount of material covered. The concept of “one-size-fits- all” does not apply to the design and implementation of training programs for older workers.Alternate :Notre analyse empirique est fondée sur l’ensemble des données appariées entre les travailleurs et les entreprises de Statistique Canada, le Workplace and Employee Survey (WES) de 2003. La taille de l’échantillon est importante, environ 4 000 travailleurs de plus de 50 ans et 12 000 qui ont entre 25 et 49 ans. Cette enquête est centrée sur la formation, de sorte qu’elle comporte une multitude de variables sur ce sujet tant pour les travailleurs que pour les entreprises. Notre analyse économétrique a révélé que la probabilité moyenne de recevoir une formation était de 9,3 points de pourcentage plus élevée chez les jeunes que chez les travailleurs plus âgés. Près de la moitié de cet écart peut être attribué au fait que les travailleurs âgés ont moins de caractéristiques associées à la réception de la formation (c’est-à-dire caractéristiques personnelles, d’emploi, du milieu de travail, des pratiques en matière de ressources humaines et de la profession/industrie/région). D’autre part, un peu plus de la moitié de l’écart est attribué au fait qu’ils ont moins tendance à recevoir des formations après avoir pris en compte leurs caractéristiques. Cela reflète probablement un coût d’opportunité plus élevé des salaires perdus pendant la formation et des coûts psychiques possiblement plus élevés pour les travailleurs plus âgés. Comme le révèle la littérature, cela reflète aussi le fait qu’il y a moins d’avantages à former les personnes plus âgées en raison de leur horizon de vie professionnelle plus court et des gains de productivité plus faibles associés à la formation. La faible tendance des travailleurs âgés à recevoir une formation s’exprime dans 54 mesures de la formation, avec quelques exceptions notables. Nous constatons que les travailleurs âgés peuvent être formés, mais cela nécessite une formation conçue pour répondre aux besoins des travailleurs âgés. Ces caractéristiques comprennent une instruction plus lente et auto-rythmée, des exercices pratiques, des composants de formation modulaires qui se construisent par étapes, les familiariser avec de nouveaux équipements et minimiser la lecture requise et la quantité de matériel couvert. Le concept d’uniformité ne s’applique pas à la conception et à la mise en oeuvre de formations pour les travailleurs âgés.

GDP Forecasting Model for China’s Provinces Using Nighttime Light Remote Sensing Data

In order to promote the economic development of China’s provinces and provide references for the provinces to make effective economic decisions, it is urgent to investigate the trend of province-level economic development. In this study, DMSP/OLS data and NPP/VIIRS data were used to predict economic development. Based on the GDP data of China’s provinces from 1992 to 2016 and the nighttime light remote sensing (NTL) data of corresponding years, we forecast GDP via the linear model (LR model), ARIMA model, ARIMAX model, and SARIMA model. Models were verified against the GDP records from 2017 to 2019. The experimental results showed that the involvement of NTL as exogenous variables led to improved GDP prediction.

Spherical Fuzzy Present Worth Analysis Method for Emergency Hospital Investment Analysis

As a subject of engineering economics, investment analysis plays an important role and use analysis techniques in the solution process. Present worth analysis, return of investment, and cost/benefit analysis are the most popular investment analysis techniques in engineering economics. However, since some investment values are determined by humans/experts and these values are based on human thoughts, it is very difficult to specify exact values. In this way, fuzzy logic can be a better alternative for calculating vagueness in engineering economics' applications. Thus, uncertain cash flows, indefinite life, and indefinite time value of money require to use fuzzy present worth analysis. As a new extension of fuzzy sets, spherical fuzzy sets have stronger capabilities to model uncertain information in investment analysis problems. In this article, spherical fuzzy present worth analysis method is presented for the first time to address the fuzzy parameters of public emergency hospital investment, which is currently a major subject in Turkey. The public emergency hospital for three locations on the European side of Istanbul is evaluated using spherical fuzzy present worth analysis method. While the best location for the emergency hospital is determined as Kemerburgaz, we also conduct a sensitivity and comparison analysis in order to show the robustness and applicability of the proposed method.