Bangladesh BD: Rural Population: % of Total Population data was reported at 59.527 % in 2023. This records a decrease from the previous number of 60.289 % for 2022. Bangladesh BD: Rural Population: % of Total Population data is updated yearly, averaging 79.566 % from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 94.865 % in 1960 and a record low of 59.527 % in 2023. Bangladesh BD: Rural Population: % of Total Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bangladesh – Table BD.World Bank.WDI: Population and Urbanization Statistics. Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population.;World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.;Weighted average;

Bangladesh BD: Rural Land Area data was reported at 79,328.863 sq km in 2015. This records a decrease from the previous number of 85,189.642 sq km for 2000. Bangladesh BD: Rural Land Area data is updated yearly, averaging 85,189.642 sq km from Dec 1990 (Median) to 2015, with 3 observations. The data reached an all-time high of 90,000.474 sq km in 1990 and a record low of 79,328.863 sq km in 2015. Bangladesh BD: Rural Land Area data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bangladesh – Table BD.World Bank.WDI: Environmental: Land Use, Protected Areas and National Wealth. Rural land area in square kilometers, derived from urban extent grids which distinguish urban and rural areas based on a combination of population counts (persons), settlement points, and the presence of Nighttime Lights. Areas are defined as urban where contiguous lighted cells from the Nighttime Lights or approximated urban extents based on buffered settlement points for which the total population is greater than 5,000 persons.;Center for International Earth Science Information Network (CIESIN)/Columbia University. 2013. Urban-Rural Population and Land Area Estimates Version 2. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/lecz-urban-rural-population-land-area-estimates-v2.;Sum;

The Long-Term Impact of Microcredit Impacts 1998 is a follow up survey conducted by Bangladesh Institute of Development Studies (BIDS) and the World Bank. The survey was first carried out in 1991-1992 and the survey's main focus was to provide data for an analysis of three major credit programs (Grameen Bank, Bangladesh Rural Advancement Committee, and the Rural Development-12 program of the Bangladesh Rural Development Board). The survey covered both villages from each of the programs under study as well as villages where no lending took place. The 1991-1992 survey included 1,798 households randomly drawn from 87 villages of 29 thanas in rural Bangladesh. These households from 87 villages of 29 thanas were surveyed first in 1991/92, and then revisited in 1998/99. In 1998-1999, altogether 2,599 households were surveyed, out of which 2,226 were from old villages and 373 were from new villages.

This dataset is about countries per year in Bangladesh. It has 64 rows. It features 4 columns: country, rural land area, and birth rate.

This is the dataset file (.dta) containing all the variables used for the paper “Does rural transformation affect rural income inequality? Insights from cross-district panel data analysis in Bangladesh.” The data are secondary and panel in nature. The original source of this dataset is Household Income and Expenditure Survey (HIES) data collected by Bangladesh Bureau of Statistics.

Bangladesh BD: Rural Population Growth data was reported at -0.245 % in 2023. This records a decrease from the previous number of -0.186 % for 2022. Bangladesh BD: Rural Population Growth data is updated yearly, averaging 1.307 % from Dec 1961 (Median) to 2023, with 63 observations. The data reached an all-time high of 2.765 % in 1962 and a record low of -0.245 % in 2023. Bangladesh BD: Rural Population Growth data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bangladesh – Table BD.World Bank.WDI: Population and Urbanization Statistics. Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population.;World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.;Weighted average;

Dataset

This dataset was created by Sabbir Hasan

Released under Data files © Original Authors

Contents

Bangladesh Strategic Plan on Agricultural and Rural Statistics (2016-2030).

The dataset described here originates from a detailed household survey conducted in the Lower Gangetic Basin, Bangladesh. This survey was designed to investigate the multifaceted aspects of agrarian transformation and its implications on rural community food security. The dataset comprises responses from 250 households within a defined mouza, offering extensive data on several pivotal areas: Land Ownership and Use, Agricultural Practices and Transformation, Socio-cultural and Environmental Factors, Role of Power Dynamics, Food Security Status and Food Security Strategies and Practices.

The Long-Term Impact of Microcredit Impacts was conducted in 1991-1992 by Bangladesh Institute of Development Studies (BIDS) and the World Bank. The survey's main focus was to provide data for an analysis of three major credit programs (Grameen Bank, Bangladesh Rural Advancement Committee, and the Rural Development-12 program of the Bangladesh Rural Development Board). The survey covered both villages from each of the programs under study as well as villages where no lending took place. The survey included 1,798 households randomly drawn from 87 villages of 29 thanas in rural Bangladesh. These households from 87 villages of 29 thanas were surveyed first in 1991-1992, and then revisited in 1998-1999.

Bangladesh LFS: Unemployment Rate: Rural data was reported at 4.000 % in 2017. This records a decrease from the previous number of 4.100 % for 2016. Bangladesh LFS: Unemployment Rate: Rural data is updated yearly, averaging 4.000 % from Jun 2000 (Median) to 2017, with 7 observations. The data reached an all-time high of 4.200 % in 2006 and a record low of 3.700 % in 2013. Bangladesh LFS: Unemployment Rate: Rural data remains active status in CEIC and is reported by Bangladesh Bureau of Statistics . The data is categorized under Global Database’s Bangladesh – Table BD.G011: Labour Force Survey: Unemployment and Unemployment Rate.

This is the second round of Bangladesh Integrated Household Survey (BIHS). BIHS is the only nationally representative survey in Bangladesh that collects detailed data on (1) plot-level agricultural production and practices, (2) dietary intake of individual household members, (3) anthropometric measurements (height and weight) of all household members, and (4) data to measure women’s empowerment in agriculture index (WEAI). A community survey supplements the BIHS data to provide information on area-specific contextual factors. The BIHS covers 6500 households in 325 primary sampling units. The sample is statistically representative at following levels: (a) nationally representative of rural Bangladesh; (b) representative of rural areas of each of the seven administrative divisions of the country: Barisal, Chittagong, Dhaka, Khulna, Rajshahi, Rangpur, and Sylhet; and (c) representative of the Feed the Future (FTF) zone of influence. To retrieve the data, navigate to the landing page.

Bangladesh BD: Urban Land Area data was reported at 56,970.021 sq km in 2015. This records an increase from the previous number of 51,109.241 sq km for 2000. Bangladesh BD: Urban Land Area data is updated yearly, averaging 51,109.241 sq km from Dec 1990 (Median) to 2015, with 3 observations. The data reached an all-time high of 56,970.021 sq km in 2015 and a record low of 46,298.409 sq km in 1990. Bangladesh BD: Urban Land Area data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bangladesh – Table BD.World Bank.WDI: Environmental: Land Use, Protected Areas and National Wealth. Urban land area in square kilometers, based on a combination of population counts (persons), settlement points, and the presence of Nighttime Lights. Areas are defined as urban where contiguous lighted cells from the Nighttime Lights or approximated urban extents based on buffered settlement points for which the total population is greater than 5,000 persons.;Center for International Earth Science Information Network (CIESIN)/Columbia University. 2013. Urban-Rural Population and Land Area Estimates Version 2. Palisades, NY: NASA Socioeconomic Data and Applications Center (SEDAC). http://sedac.ciesin.columbia.edu/data/set/lecz-urban-rural-population-land-area-estimates-v2.;Sum;

The Chronic Poverty and Long Term Impact Study in Bangladesh project, which focuses on 102 villages characteristic of rural Bangladesh, aims to further our understanding of the economic, social and political processes that shape chronic poverty in Bangladesh together with the impact of selected anti-poverty interventions on poverty dynamics. After initial community level fieldwork approximately 1,907 core households first surveyed in 1994, 1996, or 2000 were interviewed in late 2006 to ascertain how their living standards, endowment and other characteristics have changed over time and what role selected interventions have had on their welfare trajectories. 365 households who had split from their original households were also interviewed Detailed life-histories were then collected from a stratified sub-sample of approximately 293 adult men and women living in 161 households in order to better understand which events, institutions and processes have trapped certain households in chronic poverty while allowing others to escape from it. By analysing the results of the community level focus groups, panel survey and life-histories interviews together, a much fuller and more nuanced understanding of chronic poverty and the impact of the selected interventions is produced. The panel survey component of the study builds on evaluation studies on the provision of Food or Cash for Education (FFE/CFE) to poor families; production-related interventions, through the introduction of new agricultural technologies; and microfinance, through Non-Governmental organizations (NGOs). This webpage presents the combined dataset of all the three individual datasets for each study. The Food for Education (FFE) survey was conducted in Bangladesh in 2000 and 2003 to evaluate the effect of a conditional transfer of food or cash to poor families, which was designed to increase school attendance. In 2000, the survey covered 600 households in 60 villages in 30 unions in 10 thanas, and 110 schools in the same 30 unions from which the household sample was drawn. In 2003, two thanas were dropped from the sample, reducing the sample size to 480 households and the number of thanas to 8. In 2006/7, there were 511 households from 8 upazilas (the new name for thana). These datasets are available from IFPRI’s website at Impact Evaluation of Food for Education Program in Bangladesh, 2000 and Comparing Food versus Cash for Education Program in Bangladesh, 2003. The Micronutrients-Gender study, also known as the Agricultural Technology Study, was carried out in 1996-1997 to evaluate the micronutrient/gender impact of new agricultural technologies being disseminated by nongovernmental organizations (NGOs) through a variety of targeting mechanisms in three sites in rural Bangladesh: improved vegetables (Saturia); individual fishponds (Mymensingh); and group fishponds (Jessore). The survey covered 330 households in three categories in each site: NGO-member adopting households, NGO-member likely adopter households in villages where the technology was not yet introduced, and a sampling of all other households in both types of villages to represent the general population. This individual dataset is available from IFPRI’s website at Commercial vegetable and polyculture fish production -- their impacts on income, household resource allocation, and nutrition, 1996-1997. The Microfinance study was conducted in Bangladesh in 1994 to analyze the determinants of the formation of and participation in group-based rural financial institutions and the effects of participation on household resource allocation, income generation, and food and nonfood consumption. The study included a 120-village community level survey, 128 credit groups, and a household survey of 350 households in 7 villages. The study included credit groups formed by three Nongovernmental organizations (NGOs)- Association for Social Advancement (ASA), Bangladesh Rural Advancement Committee (BRAC), and Rangpur-Dinajpur Rural Services (RDRS). Household surveys were based on stratified random sampling, with household possession of land as the stratifier, irrespective of membership in NGO programs. This individual dataset is available from IFPRI’s website at Rural Finance and Food Security Study in Bangladesh, 1994.

The dataset includes information on antibiotic-resistance and resistance genes in bacteria (Escherichia coli) from humans, poultry and the environment in rural households, poultry farms and urban food markets. The rural households and poultry farms (broiler chickens) were located in Mirzapur, Tangail district; and urban food markets were located in Dhaka city, Bangladesh. Environmental samples were collected from surface water, water supply, wastewater, soil, animal faeces (poultry and cattle) and solid waste between February 2017 and October 2018 . DNA samples from antibiotic-resistant bacteria found in all samples were analysed for quantitative assessment of two resistance genes. Trained staff from the International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) undertook sample collection and laboratory analysis. The aim of the study was to assess the prevalence and abundance of antibiotic-resistant bacteria and associated genes among humans, poultry and environmental compartments in Bangladesh. The survey was part of a wider research project, Spatial and Temporal Dynamics of Antimicrobial Resistance Transmission from the Outdoor Environment to Humans in Urban and Rural Bangladesh. The research was funded by NERC/BBSRC/MRC on behalf of the Antimicrobial Resistance Cross-Council Initiative award NE/N019555/1.

This dataset presents an assortment of high-resolution images that exhibit six well-known banana varieties procured from two distinct regions in Bangladesh. These bananas were thoughtfully selected from rural orchards and local markets, providing a diverse and comprehensive representation. The dataset serves as a visual reference, offering a thorough portrayal of the distinct characteristics of these banana types, which aids in their precise classification. It encompasses six distinct categories, namely, Shagor, Shabri, Champa, Anaji, Deshi, and Bichi, with a total of 1166 original images and 6000 augmented JPG images. These images were diligently captured during the period from August 01 to August 15, 2023. The dataset includes two variations: one with raw images and the other with augmented images. Each variation is further categorized into six separate folders, each dedicated to a specific banana variety. The images are of non-uniform dimensions and have a resolution of 4608 × 3456 pixels. Due to the high resolution, the initial file size amounted to 4.08 GB. Subsequently, data augmentation techniques were applied, as machine vision deep learning models require a substantial number of images for effective training. Augmentation involves transformations like scaling, shifting, shearing, zooming, and random rotation. Specific augmentation parameters included rotations within a range of 1° to 40°, width and height shifts, zoom range, and shear ranges set at 0.2. As a result, an additional 1000 augmented images were generated from the original images in each category, resulting in a dataset comprising a total of 6000 augmented images (1000 per category) with a data size of 4.73 GB.

Review of Economics and Statistics: Forthcoming.. Visit https://dataone.org/datasets/sha256%3A85847fda83c737c4a7df54c0b22a06e6a3a843178fd17621d770c35b756c7472 for complete metadata about this dataset.

This point shapefile includes estimation on the economic value of the exposed assets in Bangladesh as well as their physical characteristics in urban and rural agglomerations including estimation of population too. This information is key to assess the potential damages from different hazards to each of the exposed elements. The global exposure database is developed at 1km spatial resolution at coastal areas and at 5km spatial resolution everywhere else on the globe. It includes economic value, number of residents, and construction type of residential, commercial and industrial buildings, as well as hospitals and schools. Accessing national census has proved to be quite challenging. For estimating the non- residential distributions, especially for the countries for which no relevant published census data were available, several other sources such as World Housing Encyclopedia as well as expert judgment are used to make assumptions necessary to estimate the properties of the building stock. Combining all the components mentioned above, the economic value of each building class in one cell is assessed based on the disaggregation of the (national) Produced Capital at grid level. This downscaling was done by using the sub-national values of economic activity as a proxy. The result is the global distribution of the economic value of the urban and rural produced capital by construction class. Further details on the GAR Global Exposure Dataset can be found in technical background papers (De Bono, et.al, 2015), (Tolis et al., 2013) and (Pesaresi, et.al, 2015)..

This is the third round of the Bangladesh Integrated Household Survey (BIHS). BIHS is the only nationally representative survey in Bangladesh that collects detailed data on (1) plot-level agricultural production and practices, (2) dietary intake of individual household members, (3) anthropometric measurements (height and weight) of all household members, and (4) data to measure women’s empowerment in agriculture index (WEAI). A community survey supplements the BIHS data to provide information on area-specific contextual factors. The BIHS covers 5604 households in 325 primary sampling units. The sample is statistically representative at the following levels: (a) nationally representative of rural Bangladesh; and (b) representative of rural areas of each of the seven administrative divisions of the country: Barisal, Chittagong, Dhaka, Khulna, Rajshahi, Rangpur, and Sylhet. The first round of BIHS was published in 2013 and thesecond round of BIHS was published in 2016. These surveys can be accessed from here.

The dataset provides observational information on events when humans are in contact with poultry in rural and urban Bangladesh. Data were collected during observation periods of three hours duration in three settings where humans and poultry have close interactions: rural households with domestic poultry and small-scale commercial farms in rural areas of Tangail district and market stalls that sell, slaughter and process live poultry in Dhaka city. Observations on hygiene or handwashing behaviours that take place before or after contact with poultry, poultry products (eggs, meat) or poultry waste (bedding, faeces or carcasses) were also recorded. A structured observation sheet was used to record the number of occurrences of pre-defined activities. The objective was to record the types of contact behaviours and proportion of human-poultry interactions that could result in human exposure to antibiotic-resistant bacteria carried by poultry. The research was part of a wider research project, Spatial and Temporal Dynamics of Antimicrobial Resistance (AMR) Transmission from the Outdoor Environment to Humans in Urban and Rural Bangladesh. The research was funded by NERC/BBSRC/MRC on behalf of the Antimicrobial Resistance Cross-Council Initiative, award NE/N019555/1.