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The purpose of this paper is to explore the impacts of climate change on crop net revenue by region. Particularly, the authors focus on the impact differences between north and south regions.

The authors applied the Ricardian approach which assumes that each farmer wishes to maximize revenue subject to the exogenous conditions of their farm. The climate data are based on actual measurements in 753 national meteorological stations and the socio-economic data covers 8,405 farms across 28 provinces in China.

On average, the rise of annual temperature will hurt farms both in the north or south. The impacts of climate change on both precipitation and temperatures have different seasonal impacts on producers in the north and the south of China. As a consequence, the impact on net farm revenues varies with farms in the north and the south being adversely affected (to different degrees) by a rise in the temperature, but both benefiting from an anticipated increase in rainfall. The results also reveal that irrigation is one key adaption measure to dealing with climate change. Whether in the north or south of China, increasing temperature is beneficial to irrigated farms, while for rainfed farms, higher temperature will result in a reduction in net revenues. The results also reveal that farms in the north are more vulnerable to temperature and precipitation variation than that in the south. Irrigated farms in the south are more vulnerable to precipitation variation than that in the north; but rainfed farms in the north are more vulnerable to precipitation variation than that in the south.

Applying empirical analysis to identify the differences of climate change impacts between north and south regions will help policy makers to design reasonable adaptation policies for various regions.

Climate change is the most concerned issue in the global economy; increase in climate variability and uncertain climate events have caused distress in agriculture sector. The study estimates economic effect of climate change on agriculture income for the Indian state of Karnataka. The study reports the difference of result from past studies, where estimates from present study indicate higher negative impact of rise in temperature.

Fixed effect panel regression method was used to examine change in agriculture revenue to climate response. Climate variables were classified based on the crop calendar to capture the damage caused by climate change. The authors use fine scale climate data set constructed at regional context for 20 districts and time period of 21 years (1992–2012).

The result showed that with 1-degree rise in average maximum temperature, the revenue declined by 17–21%. The prediction behavior of the different models was evaluated using out-of-sample forecast approach by training and testing historical data set.

The study adopts recent data sets on agriculture and the updated climate variables to estimate the climate change impact on agriculture. The study yields the better results when compared to previous traditional models applied in literature in Indian context. The study further evaluates the prediction behavior and robustness of the estimated models using out-of-sample forecast method.

Since the 1980s agricultural biotech investments by the public sector have increased substantially in both China and India. In the last two decades there has also been a dramatic increase in private section investment in agricultural biotechnology particularly in India. The promise of major benefits of Bt cotton identified in early socioeconomic studies of Bt cotton has proven to be true. Bt cotton has spread to at least 66% and 85% of total cotton areas of China and India, respectively – wherever bollworm is a major problem. Bt cotton continues to control bollworm in both countries, and farmers continue as major beneficiaries rather than biotech or seed companies. The major impacts have been yield increases in India and reduced pesticides consumption in China. In China, evidence also suggests that Bt cotton has suppressed the bollworm population so that non-Bt cotton growers and producers of other crops that are susceptible to bollworm are also benefitting.

The chapter also provides evidence that in the near future Bt rice and Bt eggplant could have major positive impacts by reducing pesticide use and farmers’ exposure to chemical pesticides and increasing yields. Both crops were approved for commercial production by government biosafety regulators, but are not yet available for commercial cultivation.

This paper aims to investigate the impacts of climate change on the People's Republic of China's (PRC) grain output using rural household survey data. The paper highlights the regional differences of impacts by estimating output elasticities (with respect to climate change) for different grain crops and different regions.

The paper uses production function to investigate the responses of grain output to climate variables as well as other traditional input variables. The use of production function approach allows us to do away with the competitive land market assumption as required in the Ricardian approach. The paper will use interaction terms of climate variables and regional dummies to capture the regional differences of climate change impact on grain crops.

The results indicate that the overall negative climate impacts on the PRC's grain output range from −0.31 to −2.69 percent in 2030 and from −1.93 to −3.07 percent in 2050, under different emission scenarios. The impacts, however, differ substantially for different grain crops and different regions.

This paper addresses the limitations of existing literature by highlighting regional differences and crop varieties using the most recent nationwide rural household survey data. The results indicate pronounced regional differences and crop differences in the impacts of climate changes on PRC's grain output.

The empirical literature on climate change and agriculture does not adequately address the issue of potential endogeneity between climatic variables and agriculture, which makes their estimates unreliable. This paper aims to investigate the relationships between climate change and agriculture and test the potential reverse causality and endogeneity of climatic variables to agriculture.

This study introduces a geographical instrument, longitude and latitude, for temperature to assess the impact of climate change on agriculture by estimating regression using IV-two-stage least squares method over annual panel data for 60 countries for the period of 1999-2011. The identification and F-statistic tests are used to choose and exclude the instrument. The inclusion of some control variables is supposed to reduce the omitted variable bias.

The study finds a negative relationship between temperature and agriculture. Surprisingly, the magnitude of the coefficient on temperature is mild, at least 20 per cent, as compared to previous studies, which may be because of the use of the instrumental variable (IV), which is also supported by an alternative robust measure when estimated across different regions.

The study provides strong implications for policymakers to confront climate change, which is an impending danger to agriculture. In designing effective policies and strategies, policymakers should focus not only on crop production but also on other agricultural activities such as livestock production and fisheries, in addition to national and international socio-economic and geopolitical dynamics.

This paper contributes to the growing literature in at least four aspects. First, empirical settings introduce an innovative geographical instrument, Second, it includes a wider set of control variables in the analysis. Third, it extends previous studies by involving agriculture value addition. Finally, the effects of temperature and precipitation on a single aggregate measure, agriculture value addition, are separately investigated.

Following the trend in the world over and on the African continent, the Parliament of Ghana passed a new law in 2020, the Narcotics Control Commission Act (Act 1019) that eased the legal restrictions on cannabis cultivation and use, subject to obtaining license from the relevant authority/authorities. This paper aims to examine the implications of Ghana’s decision to legalise the cultivation of cannabis for industrial purposes for the production of fibre and for medicinal purposes.

The author adopted the qualitative analysis critical review methodology in sourcing information from peer-reviewed articles, coupled with the author’s own professional knowledge, background and training, to critically analyse and review the reasons behind Ghana’s decision to legalise cannabis cultivation and the implications such a major policy change/shift.

It was found that, while the law mentions industrial and medicinal purposes for the legalisation of cannabis, the real reason, at least in the immediate term, is mainly economic. This agrees with those of other African countries that have legalised cannabis cultivation but appears to contrast with those of Europe and America.

This research is limited to Ghana and the few African countries that have legalised cannabis cultivation so far. The main reason for the legalisation (economic benefits) may also change in the future when the economics of scale turn in the favour of the country. Therefore, Ghana’s case may not represent the case of all countries legalising cannabis cultivation.

The research implication of this paper is that it brings to the world the law on cannabis cultivation in Ghana. It provides a professional and scientific position paper on Ghana’s drug law regime regarding cannabis, thus, serving as a useful reference literature to the academic and research community on the topic. More importantly, it discusses the implications of such major policy change from an objective perspective, unravelling the real reason behind the State’s decision to legalise the cultivation of cannabis in Ghana.

This paper will bring to the fore the other consequences of Ghana’s cannabis cultivation legalisation policy change, which little attention has been devoted to so far.

This paper, apart from reference to other published texts on the topic, which have been duly acknowledged, represents the sole work of the author. It has not been produced anywhere or by anyone else either in Ghana or elsewhere.

This paper aims to investigate how climatic, market and policy factors interact to determine food production in Togo. Specifically, we estimate acreage and yield response to market prices, weather and policy changes for maize and rice.

We use panel data estimators in a Seemingly Unrelated Regressions Equation (SURE) model with region-level data from the Food and Agriculture Organization statistics department and the National Oceanic and Atmospheric Administration (NOAA) of the US Department of commerce.

We found lower fertilizer price and higher grain price effects on maize acreage and yield. In addition, we found a positive effect of expected rice price on both its acreage and yield. As expected, rainfall during planting months has a significant impact on both maize (April) and paddy (May) acreage allocations. Similarly, total rainfall during the growing season has a positive impact on both maize and paddy yields. Moreover, recent agricultural policy initiative designed to boost domestic food production has significantly increased acreage and yield for maize, and yield for paddy, especially the strategy for agricultural growth.

The dataset includes region-level observations from 1991 to 2012 which limits the observation span. However, we had enough variability in key variables to determine the estimated coefficients.

Although the dataset is limited in time (1991–2012) and uses national-level output prices, this investigation reveals that cropland allocation to maize and rice is sensitive to fertilizer and grain prices, weather expectations and policy interventions. These findings provide evidence for sustainable food production and productivity enhancement in Togo.

Understanding drivers of cropland allocation and cereal yield contribute to better food security and poverty reduction in developing countries, especially Togo.

Prior to this study, little was known on the effect of price, climate and policy on cropland allocation in Togo. This investigation contributes significantly to filling this knowledge gap and provides insights for effective interventions.

This study aims to examine the impact of renewable energy consumption on agricultural productivity while accounting for the effect of financial inclusion and foreign direct investment in Brazil, Russia, India, China and South Africa (BRICS) countries during 2000–2020.

The study has used the latest data from World Bank and International Monetary Fund databases. The dependent variable in the study is agricultural productivity. Renewable energy consumption, carbon emissions, financial inclusion and foreign direct investment are independent variables. Autoregressive distributed lag (ARDL) approach was used to examine the short-run and long-run impact of renewable energy consumption, carbon emissions, foreign direct investment and financial inclusion on agricultural productivity.

The findings imply that consumption of renewable energy, carbon emissions and foreign direct investment have a positive impact on agricultural productivity while financial inclusion in terms of access does not seem to have any significant impact on agricultural productivity. Providing farmers, access to financial services can be beneficial, but its usage holds more importance in impacting rural outcomes. The problem lies in the fact that there is still a gap between access and usage of financial services.

Policymakers should encourage the increase in the usage of renewable energy and become less reliant on non-renewable energy sources which will eventually help in tackling the problems associated with climate change as well as enhance agricultural productivity.

Most of the earlier studies were based on tabular analysis without any empirical base to establish the causal relationship between determinants of agricultural productivity and renewable energy consumption. These studies were also limited to a few regions. The study is one of its kind in exploring the severity of various factors that determine agricultural productivity in the context of emerging economies like BRICS while accounting for the effect of financial inclusion and foreign direct investment.

Global climate change characterized by an increase in temperature has become the focus of attention all over the world. China is a sensitive and significant area of global climate change. This paper specifically aims to examine the association between agricultural productivity and the climate change by using China’s provincial agricultural input–output data from 2000 to 2019 and the climatic data of the ground meteorological stations.

The authors used the three-stage spatial Durbin model (SDM) model and entropy method for analysis of collected data; further, the authors also empirically tested the climate change marginal effect on agricultural productivity by using ordinary least square and SDM approaches.

The results revealed that climate change has a significant negative effect on agricultural productivity, which showed significance in robustness tests, including index replacement, quantile regression and tail reduction. The results of this study also indicated that by subdividing the climatic factors, annual precipitation had no significant impact on the growth of agricultural productivity; further, other climatic variables, including wind speed and temperature, had a substantial adverse effect on agricultural productivity. The heterogeneity test showed that climatic changes ominously hinder agricultural productivity growth only in the western region of China, and in the eastern and central regions, climate change had no effect.

The findings of this study highlight the importance of various social connections of farm households in designing policies to improve their responses to climate change and expand land productivity in different regions. The study also provides a hypothetical approach to prioritize developing regions that need proper attention to improve crop productivity.

The paper explores the impact of climate change on agricultural productivity by using the climatic data of China. Empirical evidence previously missing in the body of knowledge will support governments and researchers to establish a mechanism to improve climate change mitigation tools in China.

This study evaluates the impacts on gross revenue distributions of the use of alternative crop insurance products across different coverage levels and across locations with differing yield risks. Results are presented in terms of net costs, values‐at‐risk, and certainty equivalent returns associated with five types of multi‐peril crop insurance across different coverage levels. Findings show that the group policies often result in average payments exceeding their premium costs. Individual revenue products reduce risk in the tails more than group policies, but result in greater reductions in mean revenues. Rankings based on certainty equivalent returns and low frequency VaRs generally favor revenue products. As expected, crop insurance is associated with greater relative risk reduction in locations with greater underlying yield variability.