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A number of reports have shown that workers with certain characteristics are disproportionately affected by the COVID-19 pandemic. Since these characteristics are associated with vulnerable workers, we hypothesise that the income distribution in the pandemic era will be polarised compared to the pre-pandemic period. This article compares the pre-COVID income distribution (February 2020) with the one that prevailed just after the hard lockdown (April 2020). Consistent with the hypothesis, the result shows evidence of polarisation. Disaggregating the analysis by worker characteristics, we find that the polarisation was stronger in vulnerable groups. Our decomposition result suggests that, apart from job losses, returns to gender and job characteristics explain the location and shape differences in the COVID-19 era income distribution. Although this analysis only looks at the short-term effect of the pandemic on income distribution, the result suggests that the structure of labour markets in developing countries is not conducive to a future of work where disruptions (or pandemics) may become more frequent. © The Author(s), 2023. Published by Cambridge University Press on behalf of UNSW Canberra.
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Reducing carbon emissions from municipal solid waste (MSW) treatment is non-negligible for China to meet its "carbon peaking and carbon neutrality" targets. It is critical to objectively evaluate the spatiotemporal patterns and drivers of carbon emissions from MSW treatment. This study estimates the carbon emissions from MSW treatment across 30 Chinese provinces from 2011 to 2020. The joint approach LMDI-PDA model is further used to refine the impact of policy on carbon emission changes from technical and efficiency perspectives, while considering the socio-economic factors. The results showed that carbon emissions from MSW treatment grew significantly until peaking at 202.05Mt CO2e in 2017 and then stabilized, finally dropping to 165.10 Mt CO2e in 2020 due to the impact of COVID-19. Compared with the "12th Five-Year Plan" period, the MSW emissions intensity declined significantly during the "13th Five-Year Plan" period, indicating the effective implementation of waste emission control measures. Furthermore, the slowdown in the growth of national emissions was primarily driven by technological advances in waste treatment. Technical efficiency change effect, MSW generation intensity effect, economic scale effect, and population scale effect impeded national emissions decline. Since the performance of various drivers varied greatly in different provinces, a cluster analysis was conducted to provide policy recommendations in provinces with similar characteristics. Both the methods and results of this study can provide better decision-making support for national and provincial carbon emissions control policies targeting MSW treatment.
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PurposeTourism is a labor-intensive sector with extensive links to other industries and plays a vital role in creating employment. This study aims to propose a new framework to analyze the intrinsic structure of the employment effects of tourism-related sectors and their drivers.Design/methodology/approachThis study uses input–output and structural decomposition analysis (IO-SDA) to quantify the employment effects of tourism-related sectors and their driving mechanisms based on China's I-O tables of 2002, 2007, 2012 and 2017.FindingsThe results show a declining trend in the intensity of direct or indirect employment effects in tourism-related sectors, indicating a decreasing number of jobs directly or indirectly required to create a unit of tourism output. Among tourism-related sectors, catering has the highest intensity of indirect employment effects over the study period. Catering stimulates the indirect employment of agriculture, forestry, animal husbandry, fishery and food and tobacco manufacturing. The decomposition analysis reveals that final demand is the largest contributor to the increase in tourism employment, while technological progress shifts from an employment-creation effect in 2002–2012 to an employment-destruction effect in 2012–2017.Originality/valueThis study proposes a new analytical framework to investigate the structural proportional relationship between the direct and indirect employment effects of various tourism-related sectors and their dynamic changes. Doing so, it provides valuable references for policymakers to promote tourism employment.
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Since the outbreak of the COVID-19 pandemic, power generation and the associated CO2 emissions in major countries have experienced a decline and rebound. Knowledge on how an economic crisis affects the emission dynamics of the power sector would help alleviate the emission rebound in the post-COVID-19 era. In this study, we investigate the mechanism by which the 2008 global financial crisis sways the dynamics of power decarbonization. The method couples the logarithmic mean Divisia index (LMDI) and environmentally extended input-output analysis. Results show that, from 2009 to 2011, global power generation increased rapidly at a rate higher than that of GDP, and the related CO2 emissions and the emission intensity of global electricity supply also rebounded;the rapid economic growth in fossil power-dominated countries (e.g., China, the United States, and India) was the main reason for the growth of electricity related CO2 emissions;and the fixed capital formation was identified as the major driver of the rebound in global electricity consumption. Lessons from the 2008 financial crisis can provide insights for achieving a low-carbon recovery after the COVID-19 crisis, and specific measures have been proposed, for example, setting electricity consumption standards for infrastructure construction projects to reduce electricity consumption induced by the fixed capital formation, and attaching energy efficiency labels and carbon footprint labels to metal products (e.g., iron and steel, aluminum, and fabricated metal products), large quantities of which are used for fixed capital formation. © 2023 The Authors
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BACKGROUND: In Chicago in 2018, the average life expectancy (ALE) for NH Blacks was 71.5 years, 9.1 fewer years than for NH Whites (80.6 years). Inasmuch as some causes of death are increasingly recognized products of structural racism, in urban areas, such causes may have potential for reducing racial inequities through public health intervention. Our purpose is to allocate racial inequities in ALE in Chicago to differentials in cause-specific mortality. METHODS: Using multiple decrement processes and decomposition analysis, we examine cause-specific mortality in Chicago to determine the causes of death that contribute to the gap in life expectancy between NH Blacks and NH Whites. RESULTS: Among females, the racial difference in ALE was 8.21 years; for males, it was 10.53 years. We find that cancer and heart disease mortality account for 3.03 years or 36% of the racial gap in average life expectancy among females. Differences in homicide and heart disease mortality rates comprised over 45% of the disparity among males. CONCLUSIONS: Strategies for improving inequities in life expectancy should account for differences between males and females in cause-specific mortality rates. In urban areas with high levels of segregation, reducing inequities in ALE may be possible by dramatically reducing mortality rates from some causes. CONTRIBUTION: This paper illustrates the state of inequities in ALE between NH Blacks and NH Whites in Chicago for the period just prior to the onset of the COVID-19 pandemic, using a well-established method of decomposing mortality differentials for sub-populations.
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In the context of the outbreak of the COVID-19 pandemic and China's "digital power” strategy, the realization of a green shift of manufacturing has become a necessary condition to promote the economy, and the digital factor has increasingly become a new driving force. The DEA-Malmquist index and entropy method were used to measure the manufacturing green total factor productivity (GTFP) and the level of digital economy level from 2011 to 2018, respectively. This study then explored the impact of digital economy on manufacturing GTFP based on the system generalized method of moments (GMM) model, as well as the adjustment effects of talent aggregation and financial scale according to the moderating model. This research came to four conclusions. (1) The digital economy can significantly improve the manufacturing GTFP of China, and the influence shows the characteristic of a "marginal increase”;(2) notably, the perspective of manufacturing GTFP decomposition indicates that the digital economy exerts a significant positive effect on manufacturing technical efficiency during the current period but obviously hinders technical progress;(3) interestingly, a mechanistic test showed that the two dimensions of innovation environment—talent aggregation (0.385) and financial scale (0.359)—play critical moderating roles in the influencing process;and (4) the influence has evident regional heterogeneity—it is significantly positive in the east and negative in the central region and west. Finally, corresponding policy suggestions are suggested. © 2022 ERP Environment and John Wiley & Sons Ltd.
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Purpose: The purpose of this study is to investigate connectedness between the four main GCC stock markets (Saudi Arabia, United Arab Emirates, and Oman) and two major cryptocurrencies i.e. Bitcoin and Ethereum. The outcome of the research will help in identifying the diversification in these markets during crises like Covid-19. Design/methodology/approach: The study has used Augmented Dickey-Fuller Test (ADF) and Phillips-Perron test (PP) to test stationary of data, pairwise Granger causality test, followed by variance decomposition test of vector auto-regression (VAR) model to investigate the linkages between the stock markets and cryptocurrencies under study. Descriptive statistics and graphs were used to study the volatility behavior of markets before, during, and after Covid-19. Finding(s): Results showed that volatility was highest for Bitcoin and Ethereum throughout the study period as compared to stock indices. Oman stock indices were found to be a source of diversified investment. During covid Bitcoin and Ethereum were highly endogenous. Dubai Financial Market (DFM) was found highly connected to all indices during covid. Hence, Bitcoin, Ethereum, and DFM do not provide a diversification choice to investors. High linkages were found in all other markets under this study. Connectedness between the stock indices increased during covid. Lastly, series in the study moved to their normal pattern after the covid. Research limitations/implications: The study has the scope to be extended to capture the effects of regulations on cryptocurrencies' performance. The results of the study may well help firms and investors to understand the GCC stock market behavior during pandemics and find out diversification choices in these markets. Originality/value: Investigating the pattern and connectedness of GCC stock markets and cryptocurrencies with reference to the Covid-19 Pandemic is the originality of this study. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.
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People with long-term mental health problems that affect their daily activities are a growing proportion of the UK working population and they have a particularly low employment rate. We analyse gaps in labour market outcomes between mental health disabled and non-disabled people during the COVID-19 pandemic in the UK. We also decompose the outcome gaps in order to explore the relative importance of different factors in explaining these gaps. Our results suggest that the employment effects of the pandemic for mental health disabled people may have been temporary. However, they were more likely to be away from work and/or working reduced hours than people without a disability. Workers with mental health disability were over-represented in part-time work and in caring, leisure and other service occupations, which were disproportionately affected by COVID-19 and the economic response. This is important new evidence on the contribution of segmentation and segregation in explaining the labour market position of people with mental health disability. The longer term effects of the pandemic were still not apparent at the end of our analysis period (2021:Q3), but the concentration of disabled workers in cyclically sensitive sectors and part-time work means that they will always be particularly vulnerable to economic downturns.
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Thailand is a net energy importer that has steadily increased the demand for energy over the past several decades. But there has not been a systematic analysis of the energy demand change factors. Therefore, in this study, a decomposition analysis was applied to determine the major driving forces of the changes in energy use from the years 1990-2020. The analysis period covered a regional financial crisis known in Thailand as the “Tom Yum Kung” crisis in 1997-1998 and a global pandemic COVID-19 in 2020. The analysis results showed that the value-added of economic sectors is the most important factor in requiring more energy, while energy intensity is the most important factor in reducing energy consumption. Therefore, increasing the value-added of productions and enhancing the energy efficiency more stringent will lead to a decoupling of energy consumption against GDP and sooner peak demand of energy in Thailand. © 2022, Econjournals. All rights reserved.
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Energy efficiency shows tremendous potential for enhancing economic growth while also conquering the emissions of greenhouse gases. It is generally acknowledged that Pakistan's decarbonization has to be escorted by energy efficiency developments. This study analyzes key factors behind the energy consumption variations at the sectorial level, such as agriculture, industrial and services that consume almost 70% of Pakistan's final energy. The logarithmic mean Divisia index method is applied to detect the impacting variables (i.e., energy intensity, economic activity, labor productivity, and employed labor), which oversee energy consumption for 2000–2020. Results show (1) the observed sectors provide a positive energy intensity at the maximum period, which is the main reason for negative economic activity. (2) Significant and optimistic labor productivity appeared during 2000–2020, which could be discussed due to an upsurge in capital investment and economic activity liable for increasing productivity. (3) Each factor's ratio increases in which labor productivity and economic activity present maximum input, excluding the epidemic period. (4) The sectorial energy efficiency accounting system under current energy consumption declined by 40.7 Mtoe because of COVID-19. Finally, the study provides policies linked to energy efficiency, pollution reduction, and economic sustainability based on empirical results.
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Renewable energy is significant for addressing climate change and energy security. This study focused on the drivers of China's renewable energy consumption (REC) by an extended production-theoretical decomposition analysis and emphasized REC technical efficiency and technological change in 28 provinces during 1997-2017. We then projected China's REC to 2030 based on nine scenarios using a Monte Carlo simulation approach and specifically considering the impacts of the COVID-19 pandemic on the national economy. The decomposition results showed that economic growth and population scale generally contributed to an increase in REC at national and provincial levels over the period while the overall technical efficiency and technological change in REC played limited roles in prompting REC nationally. The projection results indicated that the target that generates 50% of its electricity from renewable energy sources for China, could be achieved by 2030 if enough actions are taken to accelerate renewable energy development. Finally, we provided policy proposals that support our findings.
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As one of the most vulnerable sectors exposed to the COVID-19 pandemic, transport sectors have been severely affected. However, the shocks and impact mechanisms of infectious diseases on transport sectors are not fully understood. This paper employs a multi-sectoral computable general equilibrium model of China, CHINAGEM, with highly disaggregated transport sectors to examine the impacts of the COVID-19 pandemic on China's transport sectors and reveal the impact mechanisms of the pandemic shocks with the decomposition analysis approach. This study suggests that, first, multiple shocks of the COVID-19 pandemic to transport sectors are specified, including the supply-side shocks that raised the protective cost and reduced the production efficiency of transport sectors, and the demand-side shocks that reduced the demand of households and production sectors for transportation. Second, the outputs of all transport sectors in China have been severely affected by the COVID-19 pandemic, and passenger transport sectors have larger output decreases than freight transport sectors. While the outputs of freight transport sectors are expected to decline by 1.03-2.85%, the outputs of passenger transport sectors would decline by 3.08-11.44%. Third, with the decomposition analysis, the impacts of various exogenous shocks are quite different, while the changes in the output of different transport sectors are dominated by different exogenous shocks. Lastly, while the supply-side shocks of the pandemic would drive output decline in railway, waterway, and aviation transport sectors, the demand-side shocks would drive so in the road, pipeline, and other transport sectors. Moreover, the COVID-19 pandemic has negative impacts on the output of most non-transport sectors and the macro-economy in China. Three policy implications are recommended to mitigate the damages caused by the COVID-19 pandemic to the transport sectors.
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Social security is an important social and public policy measure to help address poverty in any contemporary society. The Comprehensive Social Security Assistance (CSSA) system in Hong Kong provides a safety net for those aged children and adults below 65 years old who cannot support themselves financially. It is designed to bring their income up to a prescribed level to meet their basic needs. The rapid increase in social welfare expenditure in the last decade has become a concern to the Hong Kong SAR Government. The overall social welfare expenditure has accounted for nearly 15.6% of government expenditure in 2018, with the total amount increasing from $58 billion to $90 billion (an increase of 72.4%) for the period 2014-2018. However, the amount spent on CSSA only increased from $20.7 billion to $22.3 billion with an increase of 7.7% only for the same period. The much slower magnitude of increase is related to the reduction in the number of CSSA recipients, which decreased from 237,501 to 185,528 over the period. A decomposition method was used to assess the changes in the number of people in the CSSA system. It showed that the rate of arriving into the system has been decreasing due to a robust economy with a very low unemployment rate; whereas moving out of the system has also been decreasing in the past 5 years. This phenomenon can be partly attributed to the widening of the income gap in the community in the period. Despite the increase in population size, as long as employment conditions remain strong and the momentum of leaving the system can be maintained, the number of CSSA recipients will continue to decrease. However, the results also suggested that a certain proportion of CSSA recipients will not be able to move out of the system and have been trapped. Some innovative methods to help them out of CSSA are discussed. In view of the poor economic outlook arising from the COVID-19 pandemic, it is important for the Government to have effective measures to keep people in their jobs. If the unemployment rate will does not substantially increase and then increase of in CSSA recipients can be contained.