Factors Influencing the Adoption of Agricultural Machinery by Chinese Maize Farmers

As the major labor force has shifted from rural areas to cities, labor shortages in agricultural production have resulted. In the context of technical progress impact, and depending on farm resource endowments, farmers will choose effective labor saving technology such as machinery to substitute for the missing manual labor. The reasons behind farmers’ adoption of machinery technology are worth exploring. Therefore, this study uses 4165 Chinese maize farmers as the target group. Multivariate probit models were performed to identify the factors that affect maize farmers’ adoption of four machinery technologies as well as the interrelation between these adoption decisions. The empirical results indicate that maize sowing area, arable land area, crop diversity, family labor, subsidy, technical assistance, and economies of scale have positive effects on machinery adoption, while the number of discrete fields in the farm has a negative impact. Maize farmers in the Northeast and North have higher machinery adoption odds than other regions. The adoption of these four machinery technologies are interrelated and complementary. Finally, moderate scale production, crop diversification, subsidizing agricultural machinery and its extension education, and land consolidation, are given as recommendations for promoting the adoption of agricultural machinery by Chinese maize farmers.

Climate Change Adaptation Strategies Vary With Climatic Stress: Evidence From Three Regions of Vietnam

Vietnam faces several adverse climatic stresses such as increases in temperature, drought, flooding, saltwater intrusion, and sea-level rise. Past research on climate change adaptation in Vietnam has highlighted that climatic stresses and challenges faced by populations vary across the country. In this study, we are interested to know if autonomous responses also vary, depending on which stress individuals are responding to. To answer this question, we use primary-collected data of 1,306 individuals from the Mekong River Delta, Central Vietnam, and the Red River Delta. Adaptation choices of these individuals are analyzed at two levels: the household-level and the agricultural-level. We estimate multivariate probit models by Geweke-Hajivassilou-Keane (GHK) simulated maximum likelihood methods. Our results show that climate change adaptations vary depending on which stresses individuals are responding to. At the household level, droughts and floods have the strongest effect on climate change adaptation. However, adaptations at the agricultural level depend more on the impacts of the stress and less so on the climatic strss itself. Understanding what climatic stresses are already eliciting a response, and what adaptations are being used by individuals, is invaluable for designing successful climate change policies. This understanding can also help policymakers identify where gaps exist in individual climate change adaptations and fill these gaps with a public response.

Economic Sustainability and Multiple Risk Management Strategies: Examining Interlinked Decisions of Small American Farms

Economic viability of small farms and farming businesses depends on multiple factors. These farms have limited production and financial resources to maintain their operation. Therefore, to sustain farming, adopting appropriate risk management strategies is a pivotal decision for small farmers. We surveyed Tennessee’s small farms and utilized multivariate probit models to study factors influencing the adoption of various risk management strategies. Our findings suggest that the decisions related to the adoption of risk management strategies are significantly interlinked. Along with factors representing the operator’s age, education, and farm operator’s income and land holdings, we also found that the government incentives (payments), smartphones, and farmers’ continuation plan significantly influence the strategic decisions of adopting risk management strategies.

THE IMPACTS OF INFORMALITY ON ENTERPRISE INNOVATION, SURVIVAL AND PERFORMANCE: SOME EVIDENCE FROM PAKISTAN

The aim of this paper is to evaluate the relationship between informality, innovation and firm survival. To do so, a study of a cluster of electrical fittings firms in Pakistan is reported. Reporting bivariate and multivariate probit models to analyze two surveys conducted between 2008 and 2017, the finding is that there is a significant relationship between informality and the extent of innovation, firm survival and firm performance. Informality has an adverse negative effect on firm-level innovation, firm survival and firm performance. Given that formal enterprises in this cluster are better performing in terms of innovation, survival and employment growth than informal businesses, the paper concludes by discussing the theoretical, policy and research implications.

Cross-sectoral differences in the drivers of innovation

Purpose The purpose of this paper is to analyse differences in the drivers of firm innovation performance across sectors. The literature often makes the assumption that firms in different sectors differ in their propensity to innovate but not in the drivers of innovation. The authors empirically assess whether this assumption is accurate through a series of econometric estimations and tests. Design/methodology/approach The data used are derived from the Irish Community Innovation Survey 2004-2006. A series of multivariate probit models are estimated and the resulting coefficients are tested for parameter stability across sectors using likelihood ratio tests. Findings The results indicate that there is a strong degree of heterogeneity in the drivers of innovation across sectors. The determinants of process, organisational, new to firm and new to market innovation varies across sectors suggesting that the pooling of sectors in an innovation production function may lead to biased inferences. Research limitations/implications The implications of the results are that innovation policies targeted at stimulating innovation need to be tailored to particular industries. One size fits all policies would seem inappropriate given the large degree of heterogeneity observed across the drivers of innovation in different sectors. Originality/value The value of this paper is that it provides an empirical test as to whether it is suitable to group sectoral data when estimating innovation production functions. Most papers simply include sectoral dummies, implying that only the propensity to innovate differs across sectors and that the slope of the coefficient estimates are in fact consistent across sectors.