The meso-level dataset contains data pertaining to the performance, structure and behavior of a national or regional economy at a disaggregated district, state, or province level in India and Bangladesh. Maintained by ICRISAT since 1966, it provides a comprehensive one-stop shop for data that identifies relevant regions/counties for targeted poverty alleviation development initiatives. It acts as a link between country-level macro data and household-level micro data. Its consistent collection and level of detail serve as a powerful research response tool for priority setting and in tracking inter-district and intra-district economic changes. The dataset is invaluable in catalyzing policy advocacy and providing feedback to researchers by analyzing the meso-level data corroborated with micro-level evidence, thus ensuring that vulnerable sections of society have a significant involvement in the policy dialogue process.
India
The district dataset is divided into two parts -- apportioned and unapportioned.
Apportioned: Data for all the variables for the districts formed after 1966 have been returned to their parent district and removed from the database. For example, data for all the variables for Rangareddy district that was formed in 1978-79 from Hyderabad, was returned to Hyderabad district (100%) and Rangareddy district removed from the database. The criterion used to determine the apportioning percentage was based on the geographical area of the parent district transferred to the new district. The data for all the variables in the database [except for rainfall, farm harvest prices (FHP) and wages] are apportioned using this proportion. Thus the continuity of data over time is ensured for ease of comparison of key trends over time, enabling time series analysis. This database contains data for 311 districts spread across 19 states of India from 1966-67 to 2011-12.
Unapportioned: This dataset covers variables for all the existing districts from 1990-91 to 2007-08 (to be available shortly).
Andhra Pradesh |
Bihar |
Gujarat |
Haryana |
Karnataka |
Madya Pradesh |
Maharashtra |
Orissa |
Punjab |
Rajasthan |
Tamil Nadu |
Uttar Pradesh |
West Bengal |
Assam |
Himachal Pradesh |
Kerala |
Chhattisgarh |
Jharkhand |
Uttarakhand |
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Bangladesh
Bandarban |
Bandarban |
Dinajpur |
Dinajpur |
Kishoregonj |
Kishoregonj |
Rangpur |
Gaibandha |
Barisal |
Barisal |
Panchagarh |
Netrokona |
Kurigram |
Bhola |
Thakurgaon |
Kushtia |
Chuadanga |
Lalmonirhat |
Jalakati |
Faridpur |
Faridpur |
Kushtia |
Nilphamari |
Pirojpur |
Gopalganj |
Meherpur |
Rangpur |
Bogra |
Bogra |
Madaripur |
Mymensingh |
Mymensingh |
Sylhet |
Habiganj |
Joypurhat |
Rajbari |
Noakhali |
Feni |
Moulivibazar |
Chittagong |
Chittagong |
Shariatpur |
Lakshmipur |
Sunamganj |
Cox's Bazar |
Jamalpur |
Jamalpur |
Noakhali |
Sylhet |
Comilla |
Brahmanbaria |
Sherpur |
Pabna |
Pabna |
Tangail |
Tangail |
Chandpur |
Jessore |
Jessore |
Sirajganj |
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Comilla |
Jhenaidah |
Patuakhali |
Barguna |
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Dhaka |
Dhaka |
Magura |
Patuakhali |
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Gazipur |
Narail |
Rajshahi |
Naogaon |
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Manikganj |
Khagrachari |
Khagrachhari |
Natore |
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Munshiganj |
Khulna |
Bagerhat |
Chapai Nawabgonj |
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Narayanganj |
Khulna |
Rajshahi |
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Narshingdi |
Satkhira |
Rangamati |
Rangamati |
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