A Meta-Analysis of Water Institutions and Their Performance: Implications for Water Resource Management

Abstract This paper uses meta-regression analysis to investigate the empirical literature on the performance of water institutions. This pioneering study synthesizes and quantifies the overall water institution-performance effect using data extracted from 23 original studies. A bivariate meta-regression and funnel asymmetric test are estimated and conducted, respectively, and for our multivariate meta-regressions (MMRs), four different fixed and random effects weighted least square models are estimated. Both bivariate and MMRs confirm the presence of a publication selection bias that favors the positive impact of water institutions on performance. Once this bias is corrected, evidence of a genuine empirical effect of water institutions on the performance is evident. Also, the variations in this literature are attributable to differences in the way these studies capture water institutions, the variables used to capture performance, and the estimation strategies, among others. Primary studies that use the water law, water policy, and/or some aspects of these to capture performance tend to report a greater impact of water institutions on performance. This paper contributes not only to improving the quality of research, reporting, review, and publication in the water space but also provides further insights for additional development, facilitation, and strengthening of water laws, policies, and administration to lower transaction costs in the water space.

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Publication Details

Journal
Water Resources Management
Published
2024-10-18
DOI
https://doi.org/10.1007/s11269-024-04000-w
Citations
1
Primary Topic
Water resources management and optimization
Type
article
Field-Weighted Citation Impact
0.34

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article

A Meta-Analysis of Water Institutions and Their Performance: Implications for Water Resource Management

Ariel Dinar, Alfred Tunyire Apio, Djiby Thiam
1 citations
Water Resources Management
Water resources management and optimization
0.34
article

A Meta-Analysis of Water Institutions and Their Performance: Implications for Water Resource Management

Ariel Dinar, Alfred Tunyire Apio, Djiby Thiam
article en
1 citations

Abstract

Abstract This paper uses meta-regression analysis to investigate the empirical literature on the performance of water institutions. This pioneering study synthesizes and quantifies the overall water institution-performance effect using data extracted from 23 original studies. A bivariate meta-regression and funnel asymmetric test are estimated and conducted, respectively, and for our multivariate meta-regressions (MMRs), four different fixed and random effects weighted least square models are estimated. Both bivariate and MMRs confirm the presence of a publication selection bias that favors the positive impact of water institutions on performance. Once this bias is corrected, evidence of a genuine empirical effect of water institutions on the performance is evident. Also, the variations in this literature are attributable to differences in the way these studies capture water institutions, the variables used to capture performance, and the estimation strategies, among others. Primary studies that use the water law, water policy, and/or some aspects of these to capture performance tend to report a greater impact of water institutions on performance. This paper contributes not only to improving the quality of research, reporting, review, and publication in the water space but also provides further insights for additional development, facilitation, and strengthening of water laws, policies, and administration to lower transaction costs in the water space.

Water Resources ManagementVol. 39(2)
University of California, Riverside (US), University of Cape Town (ZA)
University of Cape Town
Clean water and sanitation
Openalex Percentile: Top 40%
Water resources management and optimization
0.34
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A Meta-Analysis of Water Institutions and Their Performance: Implications for Water Resource Management — Ariel Dinar, Alfred Tunyire Apio, et al. · Water Resources Management (2024) | TGRS Research Map | TGRS