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This paper aims to assesses impacts of perceived weather changes (i.e. temperature, wind and rainfall) at the farm household level on income, poverty, wheat yield and use of timber and non-timber forest products in Pakistan’s Himalayan region. Mountains are fragile ecosystems – particularly for farming and in the context of climate change. Yet for many such geographies, there is limited empirical understanding of the potential impacts of climate change.

It uses a comprehensive field survey of 500 farmers from the Gilgit-Baltistan territory (comprising seven districts Ghizer, Gilgit, Diamer, Astore, Skardu, Ghance and Hunza-Nagar). A multivariate probit model first assesses the factors associated with perceived weather changes by farm households and a propensity score matching (PSM) approach then estimates the impacts of the perceived changes in temperature, wind and rainfall.

The empirical results show that an overwhelming majority of the farmers experience climate change, which primarily has adverse impacts on household income, poverty levels and wheat yields and increases dependence on both timber and non-timber forest products.

This paper contributes to the scanty literature on the climate change in the Himalayan region of Pakistan.

Constraints associated with public agricultural extension services imply that farmers increasingly rely on input providers for agricultural innovations and knowledge. Yet such providers are typically commercial profit-making agents and may have an incentive to suggest relatively costly inputs and/or high rates. The purpose of this paper is to look into the case of Bangladesh and the role of fertilizer traders in terms of farmers’ decisions on which fertilizer to apply and at what rate. Using primary data, the authors examine farmers’ chemical fertilizer use and the associated rice production efficiency, based on different information sources (fertilizer traders, government extension agents or own/peer experience).

Using primary data, the present study estimates an ordered probit model and production functions separately based on whether or not a farmer relied on information from fertilizer traders or own experience and government extension agents, and examines the efficiency score of each type of farmer.

The findings demonstrate that the resource-poor farmers rely more on traders’ suggestions for fertilizer application than public extension – but the actual fertilizer information source has no significant effect on the production efficiency of the rice farmers. This study, therefore, does not find exploitative behavior of fertilizer traders. Thus, this study concludes that small rural traders in Bangladesh are working as agricultural extension agents and provide necessary fertilizer application information to resource-poor farmers.

This is a case study based on Bangladesh – an emerging economy in South Asia. The findings of the study may not be generalized for other countries.

To the authors’ knowledge, this is the first study that confirms the role of agricultural input sellers as the extension agent in developing countries.

The adoption of climate-smart agricultural practices (CSAPs) is important for sustaining Indian agriculture in the face of climate change. Despite considerable effort by both national and international agricultural organizations to promote CSAPs in India, adoption of these practices is low. This study aims to examine the elements that affect the likelihood and intensity of adoption of multiple CSAPs in Bihar, India.

The probability and intensity of adoption of CSAPs are analyzed using multivariate and ordered probit models, respectively.

The results show significant correlations between multiple CSAPs, indicating that their adoptions are interrelated, providing opportunities to exploit the complementarities. The results confirm that both the probability and intensity of adoption of CSAPs are affected by numerous factors, such as demographic characteristics, farm plot features, access to market, socio-economics, climate risks, access to extension services and training. Farmers who perceive high temperature as the major climate risk factor are more likely to adopt crop diversification and minimum tillage. Farmers are less likely to adopt site-specific nutrient management if faced with short winters; however, they are more likely to adopt minimum tillage in this case. Training on agricultural issues is found to have a positive impact on the likelihood and the intensity of CSAPs adoption.

The major policy recommendations coming from of our results are to strengthen local institutions (public extension services, etc.) and to provide more training on CSAPs.

By applying multivariate and ordered probit models, this paper provides some insights on the long-standing discussions on whether farmers adopt CSAPs in a piecemeal or in a composite way.

Increasing trends of climatic risk pose challenges to the food security and livelihoods of smallholders in vulnerable regions, where farmers often face loss of the entire crop, pushing farmers (mostly men) out of agriculture in destitution, creating a situation of agricultural making agriculture highly feminization and compelling male farmers to out-migrate. Climate-smart agricultural practices (CSAPs) are promoted to cope with climatic risks. This study aims to assess how knowledge related to CSAPs, male out-migration, education and income contribute to the determinants of male out-migration and CSAPs adoption and how they respond to household food security.

Sex-disaggregated primary data were collected from adopter and non-adopter farm families. STATA 13.1 was used to perform principle component analysis to construct knowledge, yield and income indices.

Yield and income index of adopters was higher for men than women. The probability of out-migration reduced by 21% with adoption of CSAPs. An increase in female literacy by 1 unit reduces log of odds to migrate by 0.37. With every unit increase in knowledge index, increase in log-odds of CSAPs adoption was 1.57. Male:female knowledge gap was less among adopters. Non-adopters tended to reduce food consumption when faced with climatic risks significantly, and the probability of migration increased by 50% with a one-unit fall in the nutrition level, thus compelling women to work more in agriculture. Gender-equitable enhancement of CSAP knowledge is, therefore, key to safeguarding sustainable farming systems and improving livelihoods.

The enhancement of gender equitable knowledge on CSAPs is key to safeguard sustainable farming systems and improved livelihoods.

This study is based on the robust data sets of 100 each of male and female from 100 households (n = 200) using well-designed and validated survey instrument. From 10 randomly selected climate-smart villages in Samastipur and Vaishali districts of Bihar, India, together with focus group discussions, the primary data were collected by interviewing both men and women from the same household.

Population and income are growing rapidly in South Asia, spurring the demand for food in general, and the demand for higher-valued food items in particular. This poses particular food security challenges for densely populated and emerging countries, such as Bangladesh. The purpose of this paper is to analyze the increasing and changing cereal consumption pattern in developing countries using Bangladesh as a case.

Using Bangladesh’s Household Income and Expenditure Survey 2000, 2005a, b data, and applying a two-stage quadratic almost ideal system estimation procedure, the present study separately estimates the expenditure elasticities for rural and urban households for five food items: rice, wheat and rice and wheat products, pulses, fish and vegetables. Second, using the estimated elasticities, projected population and the per capita GDP growth rates, this study projects the consumption of the sampled food items by 2030.

This study demonstrates that in 2030 both rural and urban households in Bangladesh will consume more wheat, pulses and fish, but the urban households will consume less rice compared to the current levels of consumption in 2015.

To the authors’ knowledge, this is the first study on developing countries that examines the evolving food items consumption separately by rural and urban households. Using Bangladesh as a case, this study warns that with rapid urbanization and income growth, developing countries need to supply more wheat, fish and pulses. The provision of the maximum usage of scarce resources, such as arable land, the development and dissemination of improved varieties and the best management practices must be ensured to boost domestic food production in developing countries to cater to the future evolving food consumption.

The purpose of this paper is to examine the rice consumption by rice grain types under the rising income scenario in Bangladesh. Generally, with an increase in income, households tend to consume more food items that are high-value, enriched foods and protein, such as meat and fish, by substituting for cereals. However, consumers also substitute when it comes to grain quality. For example, cereals, such as rice, are available in a range of qualities from the ordinary type (coarse-grain) to the premium type (fine grain). The authors postulate that as household incomes increase, households may consume more premium-type rice (or fine-grain rice), while overall consuming less rice or fewer carbohydrates.

Using the Bangladesh Household Income and Expenditure Survey 2000, 2005, and 2010, and applying multivariate probit and seemingly unrelated regression estimation procedures, this study quantifies the impact of income, household demographics, and urbanization on rice consumption by rice grain types (coarse-grain, medium-grain, and fine-grain types).

The results show that urban, wealthy households and, households headed by educated heads and spouses, are more likely to consume fine-grain rice than their counterparts.

After yield, grain type is the second most important factor for farmers when considering the adoption of a new variety. The price of rice and other cereals is highly associated with the grain type. This study concludes that plant breeding programs of major cereals, such as rice and wheat, should take into account the consumer grain-type preferences when developing new varieties.

International commodity prices have escalated to an unprecedented level since 2008. Although commodity prices have declined recently, prices are still high compared to the pre-2008 levels. Combining this market phenomenon with Bangladesh Government’s Household Income and Expenditure Survey (HIES) data sets HIES 2005 and HIES 2010, and applying the seemingly unrelated regression (SUR) estimation process, the purpose of this paper is to examine paddy rice marketing, and the cereal and non-cereal food expenditure behavior of rural smallholders in Bangladesh under rising commodity prices.

This study uses information collected by the Government of Bangladesh and applies two-step Heckman-type selection model estimation procedure, first to estimate total rice production by the rice production self-sufficiency status of the household. Second, the study estimates the paddy marketing behavior by the households by their rice self-sufficiency status under rising commodity price regime applying SUR estimation process combing with Heckman’s selection model estimation procedure.

Empirical findings demonstrate that there was no positive assertion between higher paddy rice prices and paddy rice marketing by the rural smallholders. Rather, under the rising commodity price regime, smallholders significantly reduced consumption expenditure on high food value-enriched non-cereal food items to adjust to the market shocks.

This is a Bangladesh-based case study. Individual country-level case studies should be conducted in order to generalize the findings of the present study.

The present study warns that the market volatility may discourage farm households to market their cereals more due to uncertain future. To the authors’ knowledge, this is the first attempt to explore the cereal marketing behavior of the farm households in Bangladesh under commodity price hikes by the rice production self-sufficiency status of the farm households.

The purpose of this paper is to examine the impact of urbanicity on rural–urban migrants' dietary diversity and nutrition intake and whether its effect differs across various urban environments of migrants.

Using the individual- and time-invariant fixed effects (two-way FE) model and five-year panel data from the China Health and Nutrition Survey (CHNS), this paper estimates a linear and nonlinear relationship between urbanicity and nutrition. The paper also explores the spatial heterogeneity between rural–urban migrants and rural–suburban migrants. Dietary diversity, total energy intake and the shares of energy obtained from protein and fat, respectively, are used to measure rural–urban migrants' nutrition on both quality and quantity aspects.

The study shows that rural–urban migrants have experienced access to more diverse, convenient and prepared foods, and the food variety consumed is positively associated with community urbanicity. Energy intake is positively and significantly affected by community urbanicity, and it also varies with per capita household income. The obvious inverse U-shaped relationship reveals that improving community urbanicity promotes an increase in the shares of energy obtained from protein and fat at a decreasing rate, until reaching the urbanicity index threshold of 66.69 and 54.26, respectively.

This paper focuses on the nutritional status of rural–urban migrants, an important pillar for China's development, which is often neglected in the research. It examines the urbanicity and the nutrition of migrants in China, which provides a new perspective to understand the dietary and nutritional intake among migrants in the economic and social development. Moreover, the urbanicity index performs better at measuring urban feathers rather than the traditional rural/urban dichotomous classification.

Conservation agriculture-based wheat production system (CAW) can serve as an ex ante measure to minimize loss due to climate risks, especially the extreme rainfall during the wheat production season in India. This study aims to examine whether farmers learn from their past experiences of exposure to climate extremes and use the knowledge to better adapt to future climate extremes.

The authors used data collected from 184 farmers from Haryana over three consecutive wheat seasons from 2013-2014 to 2015-2016 and multivariate logit model to analyse the driver of the adoption of CAW as an ex ante climate risk mitigating strategies based on their learning and censored Tobit model to analyse the intensity of adoption of CAW as an ex ante climate risk mitigation strategy. Farmer’s knowledge and key barriers to the adoption of CAW were determined through focus group discussions.

The analysis shows that the majority of farmers who had applied CAW in the year 2014-2015 (a year with untimely excess rainfall during the wheat season) have continued to practice CAW and have increased the proportion of land area allocated to it. Many farmers shifted from CTW to CAW in 2015-2016.

While farmers now consider CAW as an ex ante measure to climate risks, a technology knowledge gap exists, which limits its adoption. Therefore, designing appropriate methods to communicate scientific evidence is crucial.

This paper uses three years panel data from 184 farm households in Haryana, India, together with focus groups discussions with farmers and interviews with key informants to assess if farmers learn adaptation to climate change from past climate extremes.

Productivity and production risks affect the use of agricultural production practices and inputs, particularly in developing countries. This paper aims to investigate the effects of adopting drought-tolerant maize varieties (DTMVs) on farm productivity, yield variance and downside risk exposure of maize growing households of Zambia.

The study uses household survey data collected from 11 maize producing districts of Eastern, Southern and Copperbelt provinces of Zambia using a structured questionnaire. The Antle’s flexible moment-based approach was used in specifying, estimating and testing a stochastic production function. The study further applied an endogenous switching regression model to control for both observable and unobservable sources of bias.

The study revealed that DTMV adoption increases maize yield by 15 per cent and reduces the risk of crop failure: reducing yield variance by 38 per cent and exposure to downside risk by 36 per cent.

This study establishes the benefits of DTMV adoption in Zambia with regards to productivity, yield stability and downside risk in the face of climate change. Results from this study underscore the need for more concerted efforts to scale-out DTMVs for both maize productivity enhancement and for risk mitigation against weather shocks.