PurposeThis study explores the effects of the COVID-19 outbreak and its following lockdown on daily stock returns in Vietnam, a fast-growing emerging market that successfully revived after the pandemic lockdown.Design/methodology/approachThis study uses panel-data regression models to evaluate the influence of the daily increase in the number of COVID-19 confirmed cases during pre-lockdown and lockdown on daily stock returns of 723 listed firms in Vietnam from 30 January to 30 May 2020.FindingsThe study confirms the adverse impact of the daily increasing number of COVID-19 cases on stock returns in Vietnam. The study also discloses that the Vietnam stock market before and during the nationwide lockdown performed in opposing ways. Though COVID-19 pre-lockdown had a significant, negative impact on Vietnam's stock returns, the lockdown period had a significant, positive influence on stock performance of the entire market and the different business sectors in Vietnam. The financial sector was hardest hit on the Vietnam stock market during the COVID-19 outbreak.Research limitations/implicationsThe study indicates investors' confidence and trust in the Vietnam government's decisions to combat COVID-19 and favorable stocks prices were the main reasons that the Vietnam stock market rebounded during and after lockdown.Originality/valueThis is the first study to examine the impact of COVID-19 during the pre-lockdown and lockdown periods on stock performance in Vietnam, a rapidly developing economy that was successful in controlling the pandemic with a rejuvenated stock market after lockdown.
PurposeThis study investigates the short-run and long-run impacts of agricultural credit on Vietnam's agricultural GDP over the period 2004:Q4–2016:Q4, with the incorporation of agricultural labor, public investment and rainfall as important determinants of agricultural GDP.Design/methodology/approachThis study applies the indicator saturation (IS) break tests and the autoregressive distributed lag (ARDL) bounds test with structural breaks to examine the credit–agricultural performance nexus. The causal relationships among variables are explored through the Toda–Yamamoto Granger causality test.FindingsThe results indicate that agricultural credit positively influences agricultural GDP in both the short-run and long-run. A unidirectional causal relationship running from credit to agricultural GDP is confirmed. The results also discover the positive and significant effects of labor and rainfall on agricultural GDP in the long-run.Practical implicationsThe results imply that the government should focus on expanding agricultural credit as well as enhancing the efficiency of agricultural credit. Furthermore, formal credit institutions should be encouraged to work closely with farmers and agricultural enterprises to offer flexible lending periods and amounts to meet the real situation of agricultural production.Originality/valueThis study is the first to examine the credit–agricultural performance relationship at the macro-level in Vietnam. Based on the empirical results, the study provides crucial implications for policymakers to optimize the effectiveness of agricultural credit and enhance nationwide agricultural performance.
Agriculture is an integral sector in China mandated to feed over 1.3 billion of its people and provide essential inputs for many industries. Sichuan, a central grain-producing province in Southwest China, is a significant supplier of cereals in the country. Yet, it is likely to be threatened by yield damages induced by climate change. Therefore, this study examines the effects of technological progress (via fertilizers usage and mechanization) and climatic changes (via temperature and precipitation) on the productivity of main food crops, such as rice (Oryza sativa), wheat (Triticum aestivum), and maize (Zea mays) in Sichuan province. We employ the generalized method of moments (GMM) model to analyze Sichuan provincial data from 1980 to 2018. Our findings show a positive nexus between fertilizers use and yields of main food crops. Only rice and maize yields are significantly improved by mechanization. Increased average temperature reduces rice and wheat yields significantly. Rainfall is unlikely to have a significant impact on agricultural production. The study suggests that the Chinese government should consider revising its strategies and policies to reduce the impact of climate change on food crop production and increase farmers’ adaptive ability.
PurposeThis study investigates the Chinese stocks' returns during different epidemic periods to assess their effects on firms' market performance.Design/methodology/approachThe study employs an event study method on more than 3,000 firms listed on Shanghai and Shenzhen stock exchanges during periods of SARS, H5N1, H7N9 and COVID-19FindingsEpidemics' effect on firms' stock returns is persistent up to 10 days after the event dates. Although the impact varies with types and development of the disease, most firms experience a negative impact of the epidemics. Among the epidemics, COVID-19 has the greatest impact, especially when it grows into a pandemic. The epidemics' impact is uneven across industries. In addition, B-shares and stocks listed on Shanghai Stock Exchange are more negatively influenced by the epidemic than A-shares and those listed on Shenzhen Stock Exchange.Research limitations/implicationsThe results of the study contribute to the limited literature on the effects of disease outbreaks as an economic shock on firm market performance. Given the possibility of other epidemics in the future, the study provides guidance for investors in designing an appropriate investing strategy to cope with the epidemic shocks to the market.Originality/valueThe research is novel in the way it compares and assesses the economic impact of different epidemics on firms and considers their impact at different development stages.
PurposeThis study investigates the psychological impact of the COVID-19 lockdown on Vietnamese people and examines the factors affecting their psychological well-being during and after the lockdown period.Design/methodology/approachBased on the survey answers of 701 Vietnamese respondents, this study explores the psychological impact associated with COVID-19 lockdown in Vietnam. Using a newly developed “mvord” package in R that controls the heterogeneity in error structure of the sample units (Hirk et al., 2020), the study runs multivariate ordinal logistic regression models to examine the determinants of the emotional outcomes.FindingsThe study discloses negative psychological states among the Vietnamese community during and after the lockdown, including boredom, anxiety, sadness, stress, anger, precautionary measures and post-traumatic stress symptoms. Demographic characteristics (male gender, young age, poor-health condition, high educational level, small family size, officers or professionals, using public transport, quarantine experience before the lockdown, non-extended lockdown period and living in rural areas) and various difficulties during lockdown (insufficient information about COVID-19, income loss, having daily-life difficulties and unhappy experiences during lockdown) are related to higher degrees of different psychological symptoms during and after lockdown in Vietnam.Originality/valueThis study identifies the importance of mitigating the detrimental effects of the COVID-19 lockdown on Vietnamese well-being and prepares the Vietnamese government better to handle the public mental issues during future lockdowns.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.