TY - JOUR

T1 - Pond aquaculture performance over time

T2 - A perspective of small-scale extensive pond farming in Bangladesh

AU - Rahman, Md Takibur

AU - Nielsen, Rasmus

AU - Khan, Md Akhtaruzzaman

N1 - Publisher Copyright: © 2021 Taylor & Francis Group, LLC.

PY - 2022

Y1 - 2022

N2 - The continuous growth of the aquaculture sector has motivated numerous empirical studies investigating farm productivity and technical performance over time. However, empirical works focusing on low-value species in developing countries are scarcer due to the lack of data. This paper investigates the sources of productivity changes over time using a meta-frontier Malmquist productivity index. The dataset contains 2,100 observations in an unbalanced panel data set for pangas and tilapia in Bangladesh. The results indicate that the overall productivity index and its components increase over time but at a decreasing rate. The technology change effect has the largest impact, followed by technical efficiency change. The scale effects are less than one, indicating that farms are scale inefficient. Nevertheless, the convergence toward the technology frontier seems to level off due to a declining ability to minimize the efficiency change and technological change gaps over time. The results also show a larger disparity among the farms in recent years, lowering the mean technical efficiency, with a few farms driving the frontier outward and the average farms lagging.

AB - The continuous growth of the aquaculture sector has motivated numerous empirical studies investigating farm productivity and technical performance over time. However, empirical works focusing on low-value species in developing countries are scarcer due to the lack of data. This paper investigates the sources of productivity changes over time using a meta-frontier Malmquist productivity index. The dataset contains 2,100 observations in an unbalanced panel data set for pangas and tilapia in Bangladesh. The results indicate that the overall productivity index and its components increase over time but at a decreasing rate. The technology change effect has the largest impact, followed by technical efficiency change. The scale effects are less than one, indicating that farms are scale inefficient. Nevertheless, the convergence toward the technology frontier seems to level off due to a declining ability to minimize the efficiency change and technological change gaps over time. The results also show a larger disparity among the farms in recent years, lowering the mean technical efficiency, with a few farms driving the frontier outward and the average farms lagging.

KW - C43

KW - D24

KW - Data Envelopment Analysis (DEA)

KW - efficiency change

KW - Malmquist index

KW - meta-frontier

KW - O33

KW - O47

KW - Q10

KW - Q22

KW - unbalanced panel data

U2 - 10.1080/13657305.2021.1979122

DO - 10.1080/13657305.2021.1979122

M3 - Journal article

AN - SCOPUS:85115127339

VL - 26

SP - 192

EP - 214

JO - Aquaculture, Economics and Management

JF - Aquaculture, Economics and Management

SN - 1365-7305

IS - 2

ER -