Tag: climate change

Climate Factors and Maize Price Volatility in Developing Countries: Evidence from Benin

Changes in climate conditions are expected to significantly alter food production patterns and increase food price volatility, leading to challenges for food and nutrition security. Thus, this paper aims to investigate the extent to which climate factors contribute to the volatility of maize price in Benin, using monthly data from 7 markets. To this end, an autoregressive conditional heteroskedasticity in mean (ARCH-M) model is estimated. Mean and variance equations of monthly maize price are specified as functions of temperature, rainfall of the growing season and a set of control variables including a policy variable and the international price of maize with an ARCH(1) term in the variance equation. The findings from the mean equation suggest that rainfall has a negative effect on maize prices. Moreover, the estimation results from the variance equation indicate that rainfall and temperature are negatively associated with price volatility. Therefore, the findings indicate that climate change will affect maize price volatility.

Multidimensional assessment of European agricultural sector adaptation to climate change

The agricultural sector and how it relates to climate change is today emerging as a central subject of debate and critique, because it is heavily impacted by, and at the same time, a primary contributor to, climate change. The intertwined, complex relationship between the sector and climate change is among the unprecedented challenges now facing the European Union (EU). The complexity of the relationship calls for the establishment of a sustainable, future climate-proof, adapted and resilient sector with strong adaptive capacity. This paper argues that over the past decades, strong emphasis has been placed on how to mitigate the negative effects of climate change across the sector, causing it to fall behind in terms of adaptation. Although adaptation is now part of the sector’s development agenda, sectoral adaptation performance across member states remains low. In order to justify an accelerated adaptation process across the sector, the paper develops a Relative Climate Change Adaption Index (RCCAI) for the sector based on Eurostat data. The analysis shows that there is no single member state across the EU whose agricultural sector can be considered as fully climate-adapted (resilient), and thus validates the hypothesis that adaption efforts must be stepped up across the sector. ...

Impacts of climate on technical efficiency in the Hungarian arable sector

The aim of this study is to estimate the influence of climate factors on the technical efficiency of Hungarian arable farms. The technical efficiency of farms is affected by several factors such as the technology used, the relative factor abundance, the institutional reforms with the input and output market environment, the farm size and scale economies, the organisation and management, and the farm’s specialisation. We employed a two-step approach to identify the impact of climate change on the efficiency of these farms. In the first step, using the Data Envelopment Analysis model, we calculated the efficiency (dependent variable in the second stage of analysis) of these processes. In the second step, we investigated the effect of climate and soil factors (independent variables) on efficiency by applying the Simar and Wilson (2007) approach. In this way we can assess the impacts of matched environmental variables through a robust, representative dataset for Hungary. Our results show that temperature and precipitation increases had statistically significant, positive effects on the technical efficiency of farms in the seeding and vegetative periods in both the constant and variable returns to scale models, and temperature increase during the generative phase of crop production had a negative effect ...

Modelling climate effects on Hungarian winter wheat and maize yields

Hungarian cereal production is situated in the zone of Europe which is most vulnerable to the effects of changes in climatic conditions. The objectives of this paper are to present the calibration and validation of the 4M crop simulation model using farm-level observed representative values, and to estimate the potential yields of winter wheat and maize production for the next three decades. Analysing the differences between the estimated and observed yields, we identified as key influencing factors the heterogeneity of technologies and of land quality. A trend of slightly decreasing yields is projected for the next three decades for both cereals. The precise impact of environmental change on crop yields will depend on which climate scenario occurs.

How can weather affect crop area diversity? Panel data evidence from Andhra Pradesh, a rice growing state of India

This study analyses the temporal as well as the spatial shift in cropping pattern in Andhra Pradesh during the period from 1971 to 2009. The temporal associations between crop diversity, weather and economic variables have been examined to understand adaptation dynamics by means of cropping pattern shift. We find a significant impact of rabi (winter) season temperature and kharif (summer) season rainfall on cropping diversity. Along with mean weather, annual rainfall distribution has a significant, positive influence on crop diversity. The intra-seasonal distribution of dry days during rabi and kharif has a heterogeneous impact on crop diversity in districts of Andhra Pradesh. Within the state, geographical redistribution of rice area over the years can be considered as adaptation to climatic risk; however, sustainability of the emerging cropping pattern is under question due to a declining share of dry land crops during the study period. Drawing from the results, improving cropping intensity, increasing use of technology inputs and employing a season-wise incentive policy can be useful measures for sustainable diversification of the crop sector in the state.

Journal Metrics

Scimago Journal & Country Rank





  • Scopus SJR (2022): 0.27
  • Scopus CiteScore (2022): 2.0
  • WoS Journal Impact Factor (2022): 1.2
  • WoS Journal Citation Indicator (2022): 0.45
  • ISSN (electronic): 2063-0476
  • ISSN-L 1418-2106



Publisher Name: Institute of Agricultural Economics Nonprofit Kft. (AKI)

Publisher Headquarters: Zsil utca 3-5, 1093-Budapest, Hungary

Name of Responsible Person for Publishing:        Dr. Pal Goda

Name of Responsible Person for Editing:             Dr. Attila Jambor

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

The publication cost of the journal is supported by the Hungarian Academy of Sciences.

Most viewed