The Bhutan Statistical System is a decentralized system with NSB as the central agency. However, RNR Statistics Division (RSD) at MOAF coordinates, generates and disseminates the RNR statistics which includes surveys/censuses and administrative data. In the earlier RNR Statistical setup, the mandate for generation of the RNR Statistics was decentralized to various departments and agencies within MOAF with the institution of an Information Management Sections (IMS) and appointment of respective focal persons in the departments and agencies. However, due to different survey methods and definitions adopted, resulting data was found to be inconsistent between the agencies, limiting its reliability. The In-depth Country Assessment Report (IdCA 2014) published by the MOAF with support of FAO, provided an insight into the problems in the domain of RNR statistics in the country. The findings of the IdCA report specified the reforms needed to strengthen the statistical system with emphasis on efficient collection of data on RNR sector.
Recognizing the importance of RNR statistics, the MOAF created an independent division in 2017 as the Renewable Natural Resources Statistical Division (RSD) to coordinate and streamline the RNR data collection, validation, harmonization and dissemination processes. Therefore, RSD is mandated to generate and disseminate quality RNR data with high competence through better coordination of surveys, enhancement of statistical capacity, timely dissemination of RNR data and introduction of efficient and effective statistical methodologies.
- Strengthen administrative data collection and flow on quarterly basis using CAPI method;
- Standard manual developed for the conduct of annual livestock and agricultural surveys;
- Data gaps on cross-cutting issues in RNR sector such as gender, climate change and environmental indicators identified and strategy developed to generate cross cutting statistics;
- Development and maintenance of survey data archival and retrieval system;
- Capacity of the RNR statistical officials enhanced in agricultural and livestock surveys, survey data analysis and report writing
Qualifications and skills:
- At least a Master’s degree in statistics with specialization in agriculture and livestock surveys/censuses;
- Profound knowledge of agriculture and livestock survey methodologies and data collection methods such as computer assisted personal interviewing (CAPI), including survey data analysis;
- Knowledge of collecting statistics for on-farm social forestry and agroforestry land use systems
- Well versed with statistical packages such as STATA, SPSS, etc. for survey data analysis;
- Working knowledge of database applications and management;
- Excellent interpersonal and time management skills
General professional experience:
- Preferably 15 years’ experience in collecting, managing and processing of agricultural, livestock, forestry, and other rural statistics;
Specific professional experience:
- At least five years of professional experience in the design of survey, survey questionnaire and implementation of agriculture (includes social forestry) and livestock surveys;
- At least five years of professional experience in analysis of survey data including report writing and publication;
- Knowledge of how to integrate cross-cutting issues such as gender, environment/waste management, climate change, and social inclusion statistics relevant to farmers and farming systems into integrated RNR data reporting systems;
- At least five years working experience in SAARC countries;
- Good written and oral English.
Start/end date: November (10 working days), December (10 working days) 2019 and February/March 2020 (20 working days). Two (2) desk days for final editing are added.
Inputs: Two split inputs in Bhutan (after Inception Plan, there may be a need for three split inputs if agreed by RSD)
Travel: Mostly based in Thimphu, with limited travel for validation
Supervision: Reporting to the EU-TACS Project’s SKE1-RNR at PPD Offices, MOAF for on-site technical matters and deliverables (through e-mail when not in country)
Application Deadline: 03/11/2019
Only shortlisted candidates will be contacted.