Relevant bibliographies by topics / Developing Economies Forecasting

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Developing Economies Forecasting'

Author: Grafiati
Published: 4 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Developing Economies Forecasting"

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González-Rivera, Gloria, Prakash Loungani, and Xuguang (Simon) Sheng. "Forecasting issues in developing economies." International Journal of Forecasting 35, no. 3 (2019): 927–28. http://dx.doi.org/10.1016/j.ijforecast.2019.04.005.

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Bhawnani, Vijay, and K. Rao Kadiyala. "Forecasting foreign exchange rates in developing economies." Applied Economics 29, no. 1 (1997): 51–62. http://dx.doi.org/10.1080/000368497327399.

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Chuku, Chuku, Anthony Simpasa, and Jacob Oduor. "Intelligent forecasting of economic growth for developing economies." International Economics 159 (October 2019): 74–93. http://dx.doi.org/10.1016/j.inteco.2019.06.001.

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Iskandar, Iskandar, Roger Willett, and Shuxiang Xu. "The development of a government cash forecasting model." Journal of Public Budgeting, Accounting & Financial Management 30, no. 4 (2018): 368–83. http://dx.doi.org/10.1108/jpbafm-04-2018-0036.

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Purpose Government cash forecasting is central to achieving effective government cash management but research in this area is scarce. The purpose of this paper is to address this shortcoming by developing a government cash forecasting model with an accuracy acceptable to the cash manager in emerging economies. Design/methodology/approach The paper follows “top-down” approach to develop a government cash forecasting model. It uses the Indonesian Government expenditure data from 2008 to 2015 as an illustration. The study utilises ARIMA, neural network and hybrid models to investigate the best pr
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Kaboudan, Mahmoud A. "Oil Revenue and Kuwait's Economy: An Econometric Approach." International Journal of Middle East Studies 20, no. 1 (1988): 45–66. http://dx.doi.org/10.1017/s0020743800057500.

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This paper presents a macroeconomic model for a small developing oil-exporting economy: Kuwait. The model is a simultaneous system of difference equations. Historic effects of changes in revenues from oil exports on the country's economic conditions are simulated. The model is then used to forecast these conditions through 1990, and to test two fiscal policy alternatives under the assumption that revenues from Kuwait's oil exports will remain constant from 1986 to 1990. The following are key words: developing economies; oil-exporting economies; Middle East economies; Kuwait; Kuwait's economy;
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Umoru, David, Solomon Edem Effiong, Salisu Shehu Umar, et al. "Forecasting exchange rate dynamics in developing countries." Corporate and Business Strategy Review 4, no. 2, special issue (2023): 238–50. http://dx.doi.org/10.22495/cbsrv4i2siart3.

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Given that volatility influences decisions about currency rates, monetary policy, and macroeconomic policy, it is crucial to predict and anticipate volatility in emerging economies. The study employed generalized autoregressive conditional heteroskedasticity (GARCH) asymmetric models to estimate and forecast exchange rate dynamics in developing countries. We found that South Africa model had similar variance and covariance proportion of 0.99356 percent and 0.995901 percent respectively and the exchange rate could rise or fall by 2 to 6 units of rand, in exchange for USD. In Kenya, exchange rat
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PANKRATOV, E. L. "MODEL FOR PROGNOSIS OF ECONOMIC GROWTH: ACCOUNTING OF INFLUENCE OF THE ENVIRONMENT." Global Economy Journal 19, no. 01 (2019): 1950007. http://dx.doi.org/10.1142/s2194565919500076.

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In this paper, we introduce a model for forecasting economic growth. The introduced model describes the dynamics of developing economies that are under conditions of a strong impact of effects related to the state of the environment.
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Dong Thi Ngoc, Lan, Nguyen Dinh Hoan, and Ha-Nam Nguyen. "Gross Domestic Product Forecasting Using Deep Learning Models with a Phase-Adaptive Attention Mechanism." Electronics 14, no. 11 (2025): 2132. https://doi.org/10.3390/electronics14112132.

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Forecasting GDP is a highly practical task in macroeconomics, especially in the context of rapidly changing economic environments caused by both economic and non-economic factors. This study proposes a deep learning model that integrates Long Short-Term Memory (LSTM) networks with a phase-adaptive attention mechanism (PAA-LSTM model) to improve forecasting accuracy. The attention mechanism is flexibly adjusted according to different phases of the economic cycle—recession, recovery, expansion, and stagnation—allowing the model to better capture temporal dynamics compared to traditional static a
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Ibrahim, Barrie, Paul Agupugo Chijioke, Omoze Iguare Happy, and Folarin Abisade. "Leveraging machine learning to optimize renewable energy integration in developing economies." Global Journal of Engineering and Technology Advances 20, no. 3 (2024): 080–93. https://doi.org/10.5281/zenodo.14921953.

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The integration of renewable energy sources into power grids is a critical challenge for developing economies, where infrastructure limitations, unpredictable energy demand, and policy gaps hinder effective energy transitions. Machine learning (ML) offers transformative potential in addressing these challenges, enabling more efficient and reliable energy systems through advanced data analytics, predictive modeling, and real-time decision-making. This review explores how ML can optimize renewable energy integration by improving forecasting accuracy, enhancing grid stability, and optimizing reso
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Henry, James, and Amade Peter. "Application of Autoregressive Integrated Moving Average (ARIMA) Model to Forecast Electricity Consumption for Nigeria." Journal of Environmental and Energy Economics 2, no. 1 (2024): 13–21. https://doi.org/10.56946/jeee.v2i1.311.

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The electricity demand relative to supply has increased in the developed and developing economies. Hence, forecasting adequate electricity supply plays a crucial role in driving economic production activities and growth. This is so because electricity supply in relation to demand is vital for future energy planning and policy formulation. Thus, this study employed the Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) model and data on electricity consumption from 1971 to 2014. The result indicates that the ARIMA (1, 1, 2) model is adequate for forecasting and modelling electricity c
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Dissertations / Theses on the topic "Developing Economies Forecasting"

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Savy, Neil Edward. "Impact of the global financial crisis on economic growth: implications for South Africa and other developing economies." Thesis, Rhodes University, 2015. http://hdl.handle.net/10962/d1017542.

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This paper examines the impact of the recent global financial crisis on economic growth in developing economies and South Africa in particular. It explores whether the events experienced by developing countries conform to what would be anticipated from economic theory. This is done by firstly comparing country growth forecasts for 2012 captured in 2008 at the beginning of the crisis to actual 2012 GDP growth data. Secondly, panel data analysis is used to investigate three important transmission channels, namely those of Trade, Capital Flows and Exchange Rates for 25 developing economies. The r
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López, Buenache Germán. "Essays on Forecasting Methods and Monetary Policy Evaluation." Doctoral thesis, Universidad de Alicante, 2015. http://hdl.handle.net/10045/50225.

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Choi, Jeong-Gil. "The hotel industry cycle: developing an economic indicator system for the hotel industry." Thesis, Virginia Polytechnic Institute and State University, 1996. http://hdl.handle.net/10919/77739.

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The principal objective of this study was to develop an economic indicator system for the hotel industry in order to project the industry's growth and turning points. This study developed for the U.S. hotel industry a business cycle that would cover hotel activity as broadly as possible and one that would represent the magnitude of growth of the industry. This study also identified and selected seventy economic indicators for the hotel industry by reviewing literature and testing the characteristics of each time series which are available in public. By classifying the indicators into leading,
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Handura, Vetjevera Mercy. "Modelling and forecasting metal prices: evidence from developing African economies." Thesis, 2017. https://hdl.handle.net/10539/26261.

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Research thesis submitted in partial fulfilment of the requirements for the degree Master of Management in Finance and Investment Faculty of Commerce Law and Management University of the Witwatersrand Wits Business School<br>Developing Africa has been heavily dependent on primary commodities for decades as these countries are rich in mineral resources and often tend to export that and little else. However, commodities are highly susceptible to volatility and their effects on these economies are enormous. This paper investigates the extent to which the GARCH and EGARCH models can accu
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Costa, Diogo Carvalho. "Forecasting banking crises in developing countries: a dynamic probit approach." Master's thesis, 2020. http://hdl.handle.net/10362/105989.

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Banking crises have afflicted economies in developing countries at least as much as they have in developed ones. In this paper, we discuss possible indicators that allow an effective forecast of banking crises based on an historical analysis of past crises, and develop several probit models, using yearly data from 1960 to 2014 for 33 developing countries across Latin America, Africa and Asia-Pacific. We find that a dynamic probit model which incorporates exuberance dummy variables gives the best forecasting results. Data on exports, inflation, broad money an
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Books on the topic "Developing Economies Forecasting"

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(Japan), Ajia Keizai Kenkyūjo. Catalog of English publications published by the Institute of Developing Economies 1960-1994. Institute of Developing Economies, 1995.

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Akiko, Akemine, Ajia Keizai Kenkyūjo (Japan), and Nihon Bōeki Shinkōkai, eds. Catalog of English publications published by the Institute of Developing Economies, 1995-1999. Institute of Developing Economies, Japan External Trade Organization, 2000.

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Global Prospects Conference (2nd 1990 World Bank). Problems of developing countries in the 1990s. Edited by McCarthy F. Desmond. World Bank, 1990.

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Global Prospects Conference (2nd 1990 World Bank). Problems of developing countries in the 1990s. Edited by McCarthy F. Desmond. World Bank, 1990.

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Global Prospects Conference (2nd 1990 World Bank). Problems of developing countries in the 1990s. Edited by McCarthy F. Desmond 1936-. World Bank, 1990.

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Bank, World. Global economic prospects and the developing countries. The World Bank, 1996.

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Development, International Bank for Reconstruction and. Problems of developing countries in the 1990s: V. 2, country studies. World Bank, 1990.

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International Bank for Reconstruction and Development. Problems of developing countries in the 1990s: V. 1, general topics. Edited by McCarthy F. Desmond 1936- and Global Prospects Conference. (2nd : 1990 : World Bank). World Bank, 1990.

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(IBRD), World Bank. Global economic prospects and the developing countries. Library of Congress, 2000.

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Bank, World, ed. Global economic prospects and the developing countries. World Bank, 1997.

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Book chapters on the topic "Developing Economies Forecasting"

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Tharinda, Nipun, Dilina Kosgoda, Amila Tibbotuwawa, and Izabela Nielsen. "Spare Parts Categorization and Machine Learning Approaches for Demand Forecasting in Automotive Spare Parts Sector of Developing Economies." In Lecture Notes in Mechanical Engineering. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-99159-2_19.

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Ntalaperas, Dimitris, Iosif Angelidis, Giorgos Vafeiadis, and Danai Vergeti. "A Decision-Support System for the Digitization of Circular Supply Chains." In New Business Models for the Reuse of Secondary Resources from WEEEs. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-74886-9_8.

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AbstractAs it has been already explained, it is very important for circular economies to minimize the wasted resources, as well as maximize the utilization value of the existing ones. To that end, experts can evaluate the materials and give an accurate estimation for both aspects. In that case, one might wonder, why is a decision support system employing machine learning necessary? While a fully automated machine learning model rarely surpasses a human’s ability in such tasks, there are several advantages in employing one. For starters, human experts will be more expensive to employ, rather th
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Antolini, Fabrizio, Antonio Giusti, and Francesca Petrei. "Tourism and territorial economy: beyond satellite accounting." In Proceedings e report. Firenze University Press and Genova University Press, 2023. http://dx.doi.org/10.36253/979-12-215-0106-3.13.

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The tourism sector can be an important factor for the economic development. The increase in the present population, due to tourist flows, also activates a series of other sectors, generating significant economic benefits. At international level, the main tool for this type of evaluation has been identified in satellite accounting, which estimates the value added of the tourism sector, possibly increased by that coming from other similar sectors, obtaining the tourism value added. At European level, satellite accounting is a voluntary exercise for countries, which almost never finds a dimension
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"Spatial Load Forecasting in Developing Economies." In Power Engineering (Willis). CRC Press, 2002. http://dx.doi.org/10.1201/9780203910764.ch20.

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Anand, Atul, and L. Suganthi. "Forecasting of Electricity Demand by Hybrid ANN-PSO Models." In Deep Learning and Neural Networks. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-0414-7.ch048.

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Developing economies need to invest in energy projects. Because the gestation period of the electric projects is high, it is of paramount importance to accurately forecast the energy requirements. In the present paper, the future energy demand of the state of Tamil Nadu in India, is forecasted using an artificial neural network (ANN) optimized by particle swarm optimization (PSO) and by Genetic Algorithm (GA). Hybrid ANN Models have the potential to provide forecasts that perform well compared to the more traditional modelling approaches. The forecasted results obtained using the hybrid ANN-PS
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Thakur, Anusha. "Market for Plant-Based Meat Alternatives." In Environmental, Health, and Business Opportunities in the New Meat Alternatives Market. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7350-0.ch012.

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Shifting consumer preferences towards meat alternatives can be attributed to the factors such as health and ecological benefits, as well as meat adulteration. Increasing consumer demand for better grade of meat alternatives is also expected to boost the market growth in the near future. Protein sources from maize, peas, rice, and chickpeas are anticipated to witness significant growth and new developments. Alternatives such as bean curd or wheat gluten are expected to be the beneficial source of protein and phosphorous. This can be attributed to the fact that 50 g of vital wheat gluten in comb
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Yevmieshkina, Olena. "DEVELOPMENT OF CONCEPTUAL PRINCIPLES OF SOCIO-ECONOMIC FORECASTING." In Development of scientific, technological and innovation space in Ukraine and EU countries. Publishing House “Baltija Publishing”, 2021. http://dx.doi.org/10.30525/978-9934-26-151-0-24.

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The purpose of the paper examines the development of conceptual foundations of socio-economic forecasting. The subject of the study is socio-economic forecasting. The aim of the study is to carry out the conceptual analysis of social and economic forecasting. The theoretical and methodological basis of the study are the fundamental provisions of the theory of public administration, strategic planning, the work of domestic and foreign scientists in public administration, public administration, methodology of public administration science, forecasting, strategic planning. The choice of the subje
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Aleskerova, Yuliia, and Volodimir Todosiichuk. "PLANNING AND FORECASTING OF FINANCIAL ACTIVITIES IN OSCHADBANK." In Theoretical and practical aspects of the development of modern scientific research. Publishing House “Baltija Publishing”, 2022. http://dx.doi.org/10.30525/978-9934-26-195-4-1.

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The purpose is to scientifically substantiate theoretical and methodological provisions on planning and forecasting the financial results of the bank, objectifying the practical application of the concept of strategic plan development, justification of the effectiveness of the implemented method of machine learning in planning and forecasting. The financial and economic crises of recent years have been the result of serious shortcomings in the system, structure and functioning of most credit institutions. In the process of creating and operating a new credit system and intensifying interbank c
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Kaur, Babalpreet, and Manjit Kour. "Impact of Artificial Intelligence on Investment Decision-Making." In Advances in Finance, Accounting, and Economics. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-7357-6.ch001.

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Due to the increasing digitization of several sectors, businesses are utilizing robotic process automation (RPA) to digitize different aspects of their operations. RPA uses computer codes and rules-based software robots to automate repetitive tasks. It has completely changed the manner in which we approach work. Financial forecasting is not exempt from this evolution, since digital technology present enormous opportunities. By digitally managing and tracking financial transactions, robotic financial forecasting technologies are essential to preserving the financial stability of organizations.
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Pochukaevа, Olga, Evgenia Balagurova, Tatyana Orlova, and Kirill Pochukaev. "Active and Developing Import Substitution in the Investment Equipment Market." In Scientific Articles – Institute of Economic Forecasting Russian Academy of Sciences. LLC MAKS Press, 2019. http://dx.doi.org/10.29003/m818.sp_ief_ras2019/210-227.

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Conference papers on the topic "Developing Economies Forecasting"

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Dardor, Dareen, Daniel Fl�rez-Orrego, Reginald Germanier, Manuele Margni, and Fran�ois Mar�chal. "On the Economic Uncertainty and Crisis Resiliency of Decarbonization Solutions for the Aluminium Industry." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.116664.

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The aluminium industry emits approximately 1.1 billion tonnes of CO2-eq annually, contributing about 2% of global industrial emissions. Decarbonization pathways aim to achieve net-zero emissions by 2050, but this requires making decisions today for technologies having lifetimes of 20 � 25 years, based on uncertain economic assumptions, particularly given the volatility of energy prices. Traditional price forecasting models often fail to anticipate major disruptions, such as the 2022 energy crisis. This work applies Monte-Carlo Analysis (MCA) to evaluate the financial stability of decarbonizati
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Desraches, Florian, Oihane Kamara-Esteban, Diego Casado-Mansilla, and Cruz E. Borges. "Forecasting the usage of appliances of shared use: an analysis of simplicity over complexity." In 2018 Energy and Sustainability for Small Developing Economies (ES2DE). IEEE, 2018. http://dx.doi.org/10.1109/es2de.2018.8494230.

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Baptista, Dario, and Fernando Morgado-Dias. "Energy production forecasting for a wind farm composed of turbines with different features." In 2017 International Conference in Energy and Sustainability in Small Developing Economies (ES2DE). IEEE, 2017. http://dx.doi.org/10.1109/es2de.2017.8015339.

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Bohdanov, Oleksandr, Serhii Piechka, and Dmitrii Litvinov. "Mechanism of organizational and economic ensuring the implementation of the diversification strategy of agricultural enterprises." In Economic growth in the face of global challenges. Consolidation of national economies and reduction of social inequalities: International Scientific-Practical Conference, XVIIIth edition. National Institute for Economic Research, 2024. https://doi.org/10.36004/nier.cecg.ii.2024.18.17.

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The sphere of agricultural production does not belong to the stable spheres of business. Along with this situation, the pressure on agribusiness is increasing when it comes to finding new, more stable sources of income. One of the possible solutions is the use of a diversification strategy for the development of agrarian enterprises, or rather, the use of diversification opportunities.To ensure an effective diversification strategy, an important role is assigned to marketing activity and its tools, covering all stages of the campaign: studying demand in new markets, forecasting demand, develop
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Gonçalves, Victor H., and João L. G. Rosa. "Forecasting economic time series using chaotic neural networks." In XV Encontro Nacional de Inteligência Artificial e Computacional. Sociedade Brasileira de Computação - SBC, 2018. http://dx.doi.org/10.5753/eniac.2018.4470.

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This paper describes the application of KIII, a biologically more plausible neural network model, for forecasting economic time series. K-sets are connectionist models based on neural populations and have been used in many machine learning applications. In this paper, this method was applied to IPCA, a Brazilian consumer price index surveyed by IBGE. The values ranged from August 1994 to June 2017. Experiments were performed using four non-parametric models and seven parametric methods. The statistical metric RMSE was used to compare methods performance. Freeman KIII sets worked well as a filt
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Tarko, Alexander Mikhailovich. "World development and global warming." In 4th International Conference “Futurity designing. Digital reality problems”. Keldysh Institute of Applied Mathematics, 2021. http://dx.doi.org/10.20948/future-2021-5.

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The article considers the processes of world development - the systemic economic crisis and the factors that strengthen or hinder it. The analysis shows that the vectors of development have shifted significantly over the past 20 years. Conventional mathematical forecasting methods are becoming ineffective. In developed countries, measures to slow global warming contribute to positive development and recovery from the crisis, in developing countries, the reduction in the use of fossil organic fuels will lead to a slowdown in the pace of development.
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Eker, Bulent, and Mustafa Cem Aldag. "HOW TO INCREASE THE FUNCTIONS OF ARTIFICIAL INTELLIGENCE IN BUSINESSES." In INTERNATIONAL Conference on Business, Management, and Economics Engineering Future-BME. Faculty of Technical Sciences, Novi Sad, 2025. https://doi.org/10.24867/future-bme-2024-088.

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Artificial intelligence (AI) is a revolutionary technology with far-reaching implications for humanity across all disciplines. Businesses must enhance their AI capabilities to ensure customer satisfaction and gain a competitive advantage. Key measures to improve AI utilization include: AI Integration and Application Areas; Automation is increasingly used in customer service and production processes, with AI also enhancing prediction and data analytics for forecasting and strategic planning. Additionally, AI helps personalize customer experiences and supports quality assurance systems. AI Inves
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Ozdoeva, Alina, and Denis Seleznev. "Tools for innovation strategies." In International Conference "Computing for Physics and Technology - CPT2020". Bryansk State Technical University, 2020. http://dx.doi.org/10.30987/conferencearticle_5fce2771a37ca5.74416745.

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The current article is devoted to search tools for determining the optimal solution and forming the optimal company strategy for small innovative companies in the business innovation environment of the oil and gas complex. The main area of research in the article is the reasons for the difficulties of innovative Russian entrepreneurship and its entry into the domestic market and work in this market. We also consider tools such as SWIFT-analysis of assessment and forecasting of the company's performance, the portfolio model of BCG (Boston consulting group), a multi-factor matrix for selecting s
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Levitskaia, Alla. "Роль гибридных форм обучения в образовании в сфере предпринимательства". У Economic growth in the conditions of globalization. International Scientific-Practical Conference, XVIth edition. National Institute for Economic Research, 2022. https://doi.org/10.36004/nier.cecg.i.2022.16.11.

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Modern trends in technological development, demographic and migration processes affect the emergence of new professions and atypical forms of employment, methods of education and types of vocational education and training. This fact requires the intensification of the actions of state structures and organizations intermediaries responsible for the formation of career guidance policies based on: a study of the evolution of needs for professional skills in the labor market; forecasting demand for professions that are relevant in the future; developing strategies for the development of educationa
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Panteleeva, A., T. Bezrukova, Evgeniy Kovalev, and K. Manmareva. "THE MAIN ASPECTS OF THE ECONOMIC JUSTIFICATION FOR THE INTRODUCTION OF INNOVATIVE TYPES OF FURNITURE PRODUCTS INTO EXISTING PRODUCTION." In MANAGER OF THE YEAR – 2024. FSBE Institution of Higher Education Voronezh State University of Forestry and Technologies named after G.F. Morozov, 2024. https://doi.org/10.58168/moty_177-184.

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The development and implementation of innovative types of furniture products is one of the most important components of the strategic development of an existing enterprise. This process allows you to create unique competitive advantages in the industry. This is facilitated by the latest trends in the market, namely the record commissioning of new buildings, which creates an incredible demand for furnishing new apartments. Restrictions on the import of furniture from unfriendly countries and the emergence of new markets, for example, the ability to supply domestic furniture to Chinese consumers
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Reports on the topic "Developing Economies Forecasting"

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Iyer, Ananth V., Thomas Brady, Steven R. Dunlop, et al. Forecasting Freight Logistic Needs and INDOT Plans. Purdue University, 2022. http://dx.doi.org/10.5703/1288284317372.

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This project focused on forecasting freight logistics needs and developing and analyzing capacity plans for INDOT to consider. The forecast timeframe ranges from the 2020 to 2045; the commodities considered are those used in the FHWA framework. We considered five SSP (Shared Socio-Economic Pathways) scenarios that are in sync with those used by the IPCC (International Protocol for Climate Change). We also use the IPCC forecasts of world GDP and FHWA forecasts to develop county-level freight forecasts by commodity. A survey of industry participants, primarily in manufacturing, suggests that Ind
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Perera, Duminda, Ousmane Seidou, Jetal Agnihotri, et al. Flood Early Warning Systems: A Review Of Benefits, Challenges And Prospects. United Nations University Institute for Water, Environment and Health, 2019. http://dx.doi.org/10.53328/mjfq3791.

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Floods are major water-related disasters that affect millions of people resulting in thousands of mortalities and billiondollar losses globally every year. Flood Early Warning Systems (FEWS) - one of the floods risk management measures - are currently operational in many countries. The UN Office for Disaster Risk Reduction recognises their importance and strongly advocates for an increase in their availability under the targets of the Sendai Framework for Disaster Risk Reduction, and Sustainable Development Goals (SDGs). However, despite widespread recognition of the importance of FEWS for dis
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Thomas, Samuel, Elaine Baker, Kamal Aryal, et al. Towards Climate Resilient Agriculture in Nepal: Solutions for smallholder farmers. International Centre for Integrated Mountain Development (ICIMOD), 2024. https://doi.org/10.53055/icimod.1077.

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Nepal, one of the world’s most climate-vulnerable countries, is facing severe impacts from climate change, particularly in its agricultural sector, which employs two-thirds of the population and contributes more than a quarter of the nation’s GDP. Smallholder farmers, the backbone of this sector, are grappling with rising temperatures, erratic monsoon patterns, droughts, and increasingly frequent extreme weather events. Adapting to these challenges through Climate-Resilient Agriculture (CRA) is essential to ensuring food security and safeguarding the livelihoods of millions. CRA incorporates n
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