Purpose: This 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/approach: This 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.Findings: The 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/implications: The 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/value: This 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.

Purpose: This 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/approach: This 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.Findings: The 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 implications: The 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/value: This 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.

Purpose: This study investigates the Chinese stocks' returns during different epidemic periods to assess their effects on firms' market performance.Design/methodology/approach: The 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-19Findings: Epidemics' 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/implications: The 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/value: The 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.

Purpose: The purpose of this paper is to measure profitability and marketability efficiencies as well as examine the efficiencies’ determinants of listed manufacturing firms in Vietnam.Design/methodology/approach: This study employs a bootstrap two-stage data envelopment analysis (DEA) approach to investigate the profitability and marketability efficiencies of 102 listed manufacturing firms on Vietnam stock market from 2007 to 2018. The study also applies fractional regression models (FRM) to identify the determinants of Vietnam manufacturing firms’ efficiencies.Findings: The results reveal that Vietnam manufacturing firms obtain higher average profitability efficiency scores (0.888) than marketability efficiency scores (0.527) from 2007 to 2018. The high-tech firms achieve better profitability and marketability efficiencies than the traditional (resource-intensive and labour-intensive) Vietnam manufacturing firms in recent years (2016–2018). Further, the financial and non-financial factors have heterogeneous impacts on Vietnam manufacturing enterprises’ profit and market valuation efficiencies.Research limitations/implications: Due to the nature of DEA technique that requires every decision-making unit to have available data of all inputs and outputs, the listed Vietnam manufacturing firms that have incomplete data or go public after 2007 are not included in the data set.Practical implications: This study provides a reference for Vietnam manufacturing managers to position their firms competitively in the market as well as make wise operating, financing and management decisions.Originality/value: This is the first study that attempts to combine bootstrap two-stage DEA and FRM, which are considered advantageous methods for DEA scores’ measurements and determinant evaluations in the current literature.