Agricultural Research Management Information System

Home
Research Summary
Search
About Us
- ARMIS
- Brochure
Contact Us
Report
User Request
Data Input
Help
- Operation Manual
  - PDF
  - Video
- Program Area & Commodity
We have reached 37600 number of research entries at this moment.

- Logout

Research Detail

Home
Research
Detail

Influence of Environmental Constraints on Rice Productive Technical Efficiency in Bangladesh

Md. Kamrul Hossain
School of Distance Education, Universiti Sains Malaysia, 11800 Pulau Pinang, Malaysia

Tajul Ariffin Masron
School of Management, Universiti Sains Malaysia, 11800 Pulau Pinang, Malaysia

Anton Abdulbasah Kamil
School of Distance Education, Universiti Sains Malaysia, 11800 Pulau Pinang, Malaysia

Adli Mustafa
School of Mathematical Sciences, Universiti Sains Malaysia, 11800 Pulau Pinang, Malaysia

Md. Azizul Baten
Department of Decision Science, Universiti Utara Malaysia, 01610 UUM Sintok, Kedah, Malaysia

Abstract/ Executive Summary:

This paper investigates the impact of environmental constraints on efficiency of Bangladeshi rice (AUS, AMAN and BORO) using data from year 1989 to year 2008. Constant Returns to Scale (CRS) and Variable Returns to Scale (VRS) Data Envelopment Analysis (DEA) efficiency scores indicate technical efficiencies. The results show that technical efficiency (TE) of AUS in both CRS and VRS DEA is lowest in 2004. But for AMAN and BORO in case of CRS DEA, TE is lowest in 1998 and 1992. We applied a Tobit model to evaluate the effects of environmental constraints on technical efficiencies. We regressed TE of AUS, AMAN and BORO with environmental constraints Rainfall, humidity and temperature to weigh up the impact on TE. For AUS and AMAN, humidity is found positive and significant whereas rainfall and temperature are observed negative but not significant. For BORO, humidity and rainfall are recorded positive effect but temperature is found to be negative.

Keywords: DEA, Tobit model, Environmental-constraints, Technical Efficiency, Bangladesh.

Location:

Start Date:

End Date:

Program Area: Socio-economic and Policy

Commodity: Rice

Objectives:

In this paper, we measure technical efficiency of different types of rice as well as we try to assess the impact of environmental factors on technical efficiency. We use Tobit regression model to measure influence of environmental factors on efficiency.

Methodology:

Data: The Agriculture branch of Bangladesh Bureau of Statistics (BBS) is responsible for collecting, compiling, and disseminating crop statistics and other agriculture-related data. Additionally, secondary data from other organizations are also included in the year book. Information about the three types of rice are generally available, such AUS, AMAN and BORO in “The Yearbook of Agriculture Statistics, Bangladesh”. The dependent variable is production of rice, and independent variables are the area, amount of seed, and amount of fertilizer for each type of rice collected from Yearbook 2009. For this study, we consider 20-year period from 1989 to 2008. To the best of our knowledge, it is the only existing comprehensive farm level data set available for the three types of Bangladeshi rice.

Source of Information: INTERNATIONAL CONFERENCE ON MANAGEMENT, ECONOMICS AND FINANCE (ICMEF 2012) PROCEEDING 15th - 16th OCTOBER 2012. HILTON HOTEL, KUCHING, SARAWAK, MALAYSIA ISBN: 978-967-5705-09-0. WEBSITE:www.g l o b a l r e s e a r c h.com.my

Article Link (Online Journal):

Funding Source:

Budget:

Total Budget (Tk.) :

Achievement/Findings:

BORO is more efficient than AUS and AMAN. Temperature is a cause for less efficiency of all kinds of rice. Rainfall has negative impact on AUS and AMAN but it is influence to increase efficiency of BORO. Humidity has a positive influence on efficiency of all rice. To increase rice production, need to improve the efficiency of AUS more. This study has so many limitations such as for rice production we only consider area, seed and fertilizer. There is many others input do not consider. For environmental variables, we take average of all the production period. In future research we can split the variables in three as sewing time, growing time and harvest time.

Knowledge Management: Report/Proceedings