Quantifying heterogeneity, heteroscedasticity and publication bias effects on technical efficiency estimates of rice farming: A meta‐regression analysis.
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| Title: | Quantifying heterogeneity, heteroscedasticity and publication bias effects on technical efficiency estimates of rice farming: A meta‐regression analysis. |
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| Authors: | Trong Ho, Phuc1,2 (AUTHOR) htphuc@hueuni.edu.v, Burton, Michael2 (AUTHOR), Ma, Chunbo2 (AUTHOR), Hailu, Atakelty2 (AUTHOR) |
| Source: | Journal of Agricultural Economics. Jun2022, Vol. 73 Issue 2, p580-597. 18p. |
| Subjects: | Publication bias, Rice farming, Heteroscedasticity, Heterogeneity, Returns to scale, Executive ability (Management) |
| Geographic Terms: | South Asia, Southeast Asia |
| Abstract: | In recent decades, numerous studies have focused on technical efficiency in rice farming, finding considerable variation in mean technical efficiency (MTE) estimates. We conducted a meta‐regression analysis (MRA), using a random‐effects meta‐regression model, to understand the variation in MTE estimates due to study heterogeneity, heteroscedasticity and publication bias. We used 443 observations extracted from 175 primary studies published in English in the last three decades. The results show that MTE estimates are affected by study heterogeneity. Variable returns to scale specification yielded higher MTE scores than constant returns to scale ones. Panel data, secondary data and value data had lower MTE estimates than cross‐sectional data, primary data and physical (quantity) data, respectively. Compared to Southeast Asia, countries in East and South Asia had higher MTE estimates, whereas African countries had lower MTE estimates. We suggest that practitioners and policy‐makers should consider carefully estimation specifications, data types and geographical regions of empirical studies when comparing and interpreting empirical results. The average genuine (predicted) MTE score was 0.76 (range 0.54–0.89), indicating the potential to improve technical efficiency in global rice farming and the need for further research to bridge managerial ability gaps among farmers. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Agricultural Economics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 157358551 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Quantifying heterogeneity, heteroscedasticity and publication bias effects on technical efficiency estimates of rice farming: A meta‐regression analysis. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Trong+Ho%2C+Phuc%22">Trong Ho, Phuc</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> htphuc@hueuni.edu.v</i><br /><searchLink fieldCode="AR" term="%22Burton%2C+Michael%22">Burton, Michael</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ma%2C+Chunbo%22">Ma, Chunbo</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hailu%2C+Atakelty%22">Hailu, Atakelty</searchLink><relatesTo>2</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Agricultural+Economics%22">Journal of Agricultural Economics</searchLink>. Jun2022, Vol. 73 Issue 2, p580-597. 18p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Publication+bias%22">Publication bias</searchLink><br /><searchLink fieldCode="DE" term="%22Rice+farming%22">Rice farming</searchLink><br /><searchLink fieldCode="DE" term="%22Heteroscedasticity%22">Heteroscedasticity</searchLink><br /><searchLink fieldCode="DE" term="%22Heterogeneity%22">Heterogeneity</searchLink><br /><searchLink fieldCode="DE" term="%22Returns+to+scale%22">Returns to scale</searchLink><br /><searchLink fieldCode="DE" term="%22Executive+ability+%28Management%29%22">Executive ability (Management)</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22South+Asia%22">South Asia</searchLink><br /><searchLink fieldCode="DE" term="%22Southeast+Asia%22">Southeast Asia</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: In recent decades, numerous studies have focused on technical efficiency in rice farming, finding considerable variation in mean technical efficiency (MTE) estimates. We conducted a meta‐regression analysis (MRA), using a random‐effects meta‐regression model, to understand the variation in MTE estimates due to study heterogeneity, heteroscedasticity and publication bias. We used 443 observations extracted from 175 primary studies published in English in the last three decades. The results show that MTE estimates are affected by study heterogeneity. Variable returns to scale specification yielded higher MTE scores than constant returns to scale ones. Panel data, secondary data and value data had lower MTE estimates than cross‐sectional data, primary data and physical (quantity) data, respectively. Compared to Southeast Asia, countries in East and South Asia had higher MTE estimates, whereas African countries had lower MTE estimates. We suggest that practitioners and policy‐makers should consider carefully estimation specifications, data types and geographical regions of empirical studies when comparing and interpreting empirical results. The average genuine (predicted) MTE score was 0.76 (range 0.54–0.89), indicating the potential to improve technical efficiency in global rice farming and the need for further research to bridge managerial ability gaps among farmers. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Agricultural Economics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1111/1477-9552.12468 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 18 StartPage: 580 Subjects: – SubjectFull: Publication bias Type: general – SubjectFull: Rice farming Type: general – SubjectFull: Heteroscedasticity Type: general – SubjectFull: Heterogeneity Type: general – SubjectFull: Returns to scale Type: general – SubjectFull: Executive ability (Management) Type: general – SubjectFull: South Asia Type: general – SubjectFull: Southeast Asia Type: general Titles: – TitleFull: Quantifying heterogeneity, heteroscedasticity and publication bias effects on technical efficiency estimates of rice farming: A meta‐regression analysis. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Trong Ho, Phuc – PersonEntity: Name: NameFull: Burton, Michael – PersonEntity: Name: NameFull: Ma, Chunbo – PersonEntity: Name: NameFull: Hailu, Atakelty IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 0021857X Numbering: – Type: volume Value: 73 – Type: issue Value: 2 Titles: – TitleFull: Journal of Agricultural Economics Type: main |
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