What determines crop diversification in
            <scp>North‐East</scp>
            zone of India?

Kumar, Chinmaya Ranjan; Nayak, Chittaranjan; Pradhan, Ashis Kumar

doi:10.1002/pa.2450

Cited by 6 publications

(4 citation statements)

References 48 publications

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“…We also reported the results of the normality test to ascertain whether the variables follow the properties of normal distribution or not by employing Royston's (1991) normality test. This normality test holds merit over the conventional approaches as it provides asymptotic standard errors thereby correcting sample size (Kumar et al., 2020). We find statistically significant p ‐values of the variables, namely AGCA, LNPDTY, LNRAIN, CDI and HDI, confirming that these variables follow the non‐normal distribution, and that these variables are found to be skewed or vary depending on the factors of production.…”

Section: Resultsmentioning

confidence: 99%

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Untangling the factors influencing finger millet production: Evidence from the Indian states

2023

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Our study focuses on the effect of agro‐based factors and human development indicators on the production of finger millet in eight states of India. Departing from the past studies, we employed the common and dynamic common correlated effects model, and our findings showed that the past year's finger millet production, productivity, area under finger millet production, rainfall and human development indicators positively influenced the finger millet production among the eight Indian states. The variable crop diversification has no impact on the production of finger millet. Overall result indicates the prominent role of human development assisting in the promotion of finger millet production. The empirical findings suggest corrective government policies in order to boost the overall production and consumption of finger millet at the macro level.

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Section: Resultsmentioning

confidence: 99%

“…The CDI is a technique that depicts the shifting in diversified crops (high‐value crops) from the conventional crops such as finger millet (Kar et al., 2004; Kumar et al., 2020). The impact of this method is expected to decline the production of conventional crops because of the perception that these crops are treated as inferior food items.…”

Section: Resultsmentioning

confidence: 99%

Untangling the factors influencing finger millet production: Evidence from the Indian states

2023

Self Cite

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“…Given that there could be a co-integration among the variables in equation 1, this study uses a dynamic ordinary least square (DOLS) estimation technique to achieve its goals. This method is, thus, preferred to the other estimation techniques in that it includes the contemporaneous values, leads, and lag values of the independent variables in its first difference form to solve the issues of endogeneity and serial correlation (Kumar, Nayak, & Pradhan, 2020;Pradhan et al, 2022). Endogeneity may occur due to a reversed causality between FDI and economic complexity (Khan et al, 2020;Sadeghi, Shahrestani, Kiani, & Torabi, 2020).…”

Section: Model Specification and Methods Of Analysismentioning

confidence: 99%

Foreign direct investment and economic complexity in emerging economies

Osinubi

Ajide

2022

Econ. J. Emerg. Mark.

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Purpose ― In this study, we investigate the impact of foreign direct investment (FDI) on economic complexity in MINT and BRICS countries. Methodology ― Data on economic complexity from MIT’s Observatory of Economic Complexity and data on FDI and other determinants of economic complexity are sourced from World Development indicators which spanned between 1991 and 2020. The countries are divided into three categories: All countries pooled together, MINT and BRICS countries. We employ panel co-integrating regression. Findings ― Findings based on panel co-integration regression show that foreign direct investment positively impacts economic complexity in all the countries and MINT countries, while its impact is negative in BRICS countries. Originality ― This study adds value to the literature by scrutinizing the nexus between FDI and economic complexity in the context of emerging economies and employs the panel co-integration technique for robust analysis. The study's findings shed light on the need for governments in developing countries to implement appropriate policies encouraging FDI inflows into their respective countries. Contributing to the host country's economic complexity, FDI inflows should be focused on highly technical investment and, most importantly, should be selective to enhance the development of priority sectors. An investment promotion policy may be required to encourage foreign investment in the host country.

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“…Various studies have been conducted to examine the determinants of crop diversification (Chen, 2007;Kasem & Thapa, 2011;Kumar, Nayak, & Pradhan, 2020;Lin, 2011). Previous studies have examined the determinants of crop diversification such as socioeconomic characteristics of farmers and farms (Burchfield & Poterie, 2018).…”

Section: Introductionmentioning

confidence: 99%

Resilience Through Crop Diversification in Pakistan

Nazir

Lohano

2021

Climate Change and Community Resilience

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Climate change-induced variability in rainfall patterns and temperature has caused significant losses to the agriculture sector in Pakistan. Crop diversification is recognized as an effective risk management strategy for farmers to cope with climate-related risks and is therefore a potentially sustainable community-based solution for enhancing community resilience to climate change. This chapter examines how past exposure to extreme weather events, risk attitude, and other communityand farm characteristics affect the farmer’s decision of crop diversification. Using farm-level data from 480 farmers in Sindh province of Pakistan, the study examines the determinants of crop diversification decisions. The results show that previous exposure to flood or excessive rainfall in the community, farm size, and farmer’s risk attitude significantly affect crop diversification. Furthermore, location-specific factors account for differences in local climatic and agro-ecological conditions and significantly determine the extent of crop diversification.

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What determines crop diversification in North‐East zone of India?

Cited by 6 publications

References 48 publications

Untangling the factors influencing finger millet production: Evidence from the Indian states

Untangling the factors influencing finger millet production: Evidence from the Indian states

Foreign direct investment and economic complexity in emerging economies

Resilience Through Crop Diversification in Pakistan

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