The Seasonal Ground Cover Summary Statistics datasets provide long-term statistical summaries derived from the seasonal ground cover v3 data, calculated separately for each fraction. Two distinct product types are available, differentiated by their seasonal aggregation and statistical content.

Seasonal Statistics per Fraction (Product Code: dpi)For each season and ground cover fraction, a separate raster image is generated for the full time series of available imagery. Each image includes the following statistical layers: include:band 1 – 5th percentile minimum;band 2 – mean value for pixel over full time series;band 3 – median value for pixel over full time series;band 4 – 95th percentile maximum;band 5 – Standard deviation - the temporal standard deviation of the full time-series;band 6 – Count - the number of observations statistics for that pixel are based on.

All-Seasons Percentile Summary (Product Code: dph)This product summarises the 5th and 95th percentiles across all seasons for each ground cover fraction. It is delivered as a 2-band image, capturing the overall long-term minimum and maximum percentiles across the full time series (currently 1990-2020).

Version 4 update: Dataset filenames have been revised to now include fraction and season tags, replacing multiple stage codes. Related products are grouped under a single code for improved clarity and usability. Additionally, band values are now expressed as percentages (0–100) to match the parent seasonal ground cover dataset, rather than using the previous percent + 100 scaling.

Time series data for the statistic Regulatory Quality: Percentile Rank, Lower Bound of 90% Confidence Interval and country Bahamas, The. Indicator Definition:Regulatory Quality captures perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Lower refers to lower bound of 90 percent confidence interval for governance, expressed in percentile rank terms.The indicator "Regulatory Quality: Percentile Rank, Lower Bound of 90% Confidence Interval" stands at 36.32 as of 12/31/2023. Regarding the One-Year-Change of the series, the current value constitutes an increase of 22.22 percent compared to the value the year prior.The 1 year change in percent is 22.22.The 3 year change in percent is -2.21.The 5 year change in percent is -17.09.The 10 year change in percent is -18.47.The Serie's long term average value is 53.90. It's latest available value, on 12/31/2023, is 32.61 percent lower, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2022, to it's latest available value, on 12/31/2023, is +22.22%.The Serie's change in percent from it's maximum value, on 12/31/2002, to it's latest available value, on 12/31/2023, is -49.86%.

Survey years

The Poverty and Inequality Platform: Percentiles database reports 100 points ranked according to the consumption or income distributions for country-year survey data available in the World Bank’s Poverty and Inequality Platform (PIP). There are, as of September 19, 2024, a total of 2,456 country-survey-year data points, which include 2,274 distributions based on microdata, binned data, or imputed/synthetic data, and 182 based on grouped data. For the grouped data, the percentiles are derived by fitting a parametric Lorenz distribution following Datt (1998). For ease of communication, all distributions are referred to as survey data henceforth, and the welfare variable is referred to as income.

Details

Each distribution reports 100 points per country per survey year ranked from the smallest (percentile 1) to the largest (percentile 100) income or consumption. For each income percentile, the database reports the following variables: the average daily per person income or consumption (avg_welfare); the income or consumption value for the upper threshold of the percentile (quantile); the share of the population in the percentile (which might deviate slightly from 1% due to coarseness in the raw data) (pop_share); and the share of income or consumption held by each percentile (welfare_share). In addition, the database reports the welfare measure (welfare_type) used in the survey data—income or consumption—and the region covered (reporting_level)—urban, rural, or national. The distributions are available in 2011 or 2017 PPP$.

Stata code example

Below is an example of how to use the database to generate an anonymous growth incidence curve for Bangladesh between 2005 and 2010

keep if country_code"BGD" & reporting_level1 & ///

inlist(year,2005,2010)

bys country_code percentile (year): ///

gen growth05_10 = (avg_welfare/avg_welfare[_n-1] - 1) * 100

twoway connected growth05_10 percentile, ytitle("%") ///

title("Cumulative growth in Bangladesh, 2005-2010")

Metadata

Some metadata of the data set, such as the version of the data, can be found by typing char dir in the Stata console. Alternatively, please refer to this portal, which contains all the information available.

PIP version date: 20250401 (updated June 05, 2025)

Lineup years

Not currently available

Time series data for the statistic Regulatory Quality: Percentile Rank, Lower Bound of 90% Confidence Interval and country Thailand. Indicator Definition:Regulatory Quality captures perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Lower refers to lower bound of 90 percent confidence interval for governance, expressed in percentile rank terms.The indicator "Regulatory Quality: Percentile Rank, Lower Bound of 90% Confidence Interval" stands at 44.34 as of 12/31/2023. Regarding the One-Year-Change of the series, the current value is equal to the value the year prior.The 1 year change in percent is 0.0.The 3 year change in percent is 7.03.The 5 year change in percent is 16.39.The 10 year change in percent is -3.55.The Serie's long term average value is 46.12. It's latest available value, on 12/31/2023, is 3.86 percent lower, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/1998, to it's latest available value, on 12/31/2023, is +23.61%.The Serie's change in percent from it's maximum value, on 12/31/2005, to it's latest available value, on 12/31/2023, is -23.99%.

Abstract

This dataset was derived by the Bioregional Assessment Programme. The parent datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

This dataset contains raster data layers estimating the rate of groundwater recharge for each hydrogeological formation in the Galilee subregion, by a chloride mass balance method. This method compares groundwater chloride concentrations (GUID: 6b1a0358-40d6-4bcf-b864-28cb2c823fd1) with chloride deposition in rainfall (GUID: c1649bd7-227f-41ff-9964-b55479bef640) for each hydrogeological formation. Cell values for each raster represent a rate in mm/year.

Purpose

This dataset is created to provide groundwater recharge volume estimates as an input into the Galilee groundwater model. For the purposes of the model, boundary extents used in the calculations are simplified and estimates should be used with caution if using for another purpose.

Dataset History

To create the recharge extent grids, the input data went through the following processes:

1. Groundwater chloride concentration (Point data to raster)

Using the 'Topo to Raster' Tool in ArcCatalog, the input chloride data (GUID: 6b1a0358-40d6-4bcf-b864-28cb2c823fd1) for each hydrogeological formation's outcrop extent was converted into a raster dataset using the following parameters:

Feature layer - Input chemistry point data (GUID: 6b1a0358-40d6-4bcf-b864-28cb2c823fd1)

Field - Cl

Type - Point Elevation

Output cell size - 0.01

Output extent - Recharge outcrop (GUID: b0f0385e-c456-4fa4-9cdb-a5441cca407b)

Margin in cells - 20

Smallest z value to be used in interpolation - 10th percentile of Chloride Values

Largest z value to be used in interpolation - 90th percentile of Chloride Values

Drainage enforcement - NO_ENFORCE

Primary type of input data - SPOT

Maximum number of iterations - 40

1. Output Chloride grid clipped to recharge boundary

Using the 'Extract by Mask' tool in ArcCatalog, the newly created chloride raster was clipped to the boundary of the recharge extent for each formation from the Galilee Groundwater Model, Hydrogeological Formation Recharge (Outcrop) Extents v01 (GUID: b0f0385e-c456-4fa4-9cdb-a5441cca407b) dataset.

1. Chloride mass balance calculation between the groundwater chloride raster and the chloride deposition in rainfall raster (cl_deposition_final ascii file from the dataset - Australian 0.05º gridded chloride deposition v2 - GUID: c1649bd7-227f-41ff-9964-b55479bef640).

Using the 'Raster Calculator' Tool in Arc Catalogue the following statement was used to calculate the final recharge estimate for each formation: ([cl_deposition_final]" * 100) / [clipped groundwater chloride raster]

Dataset Citation

Bioregional Assessment Programme (2015) Galilee model recharge estimates: chloride mass balance v02. Bioregional Assessment Derived Dataset. Viewed 07 December 2018, http://data.bioregionalassessments.gov.au/dataset/d42a8497-9d67-42ad-9e7d-70a8d519875f.

Dataset Ancestors

• Derived From Galilee Hydrochemistry: Quality control for Chloride model recharge v02

• Derived From Queensland petroleum exploration data - QPED

• Derived From Three-dimensional visualisation of the Great Artesian Basin - GABWRA

• Derived From Phanerozoic OZ SEEBASE v2 GIS

• Derived From Galilee Groundwater Model, hydrogeological formation recharge (Outcrop) extents v01

• Derived From QLD Department of Natural Resources and Mines Groundwater Database Extract 20142808

• Derived From Galilee Groundwater Model, Hydrogeological Formation Extents v01

• Derived From GAL Aquifer Formation Extents v01

• Derived From Queensland Geological Digital Data - Detailed state extent, regional. November 2012

• Derived From QLD Geological Digital Data - QLD Geology, Structural Framework, November 2012

• Derived From Australian 0.05º gridded chloride deposition v2

• Derived From GAL Aquifer Formation Extents v02

The data set contains the daily statistics for the SOILM0-100cm variable (0-100 cm top 1 meter soil moisture content) of the North American Land Data Assimilation System Version 2 (NLDAS-2) model. The period of analysis is from 1979-01-02 to 2013-12-31. The statistics for each calendar month are the mean, standard deviation, minimum, maximum, and percentiles in 0.05 interval. The data set also includes a p-value per calendar day of the Kolmogorov-Smirnov (KS) test. The p-value of the KS test shows if the computed empirical cumulative distribution function (CDF) comes from a fitted normal distribution

Time series data for the statistic Government Effectiveness: Percentile Rank, Lower Bound of 90% Confidence Interval and country Bermuda. Indicator Definition:Government Effectiveness captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Lower refers to lower bound of 90 percent confidence interval for governance, expressed in percentile rank terms.The indicator "Government Effectiveness: Percentile Rank, Lower Bound of 90% Confidence Interval" stands at 62.26 as of 12/31/2023, the lowest value since 12/31/2015. Regarding the One-Year-Change of the series, the current value constitutes a decrease of -5.04 percent compared to the value the year prior.The 1 year change in percent is -5.04.The 3 year change in percent is -15.09.The 5 year change in percent is -13.41.The 10 year change in percent is -4.10.The Serie's long term average value is 67.51. It's latest available value, on 12/31/2023, is 7.78 percent lower, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2014, to it's latest available value, on 12/31/2023, is +4.44%.The Serie's change in percent from it's maximum value, on 12/31/1996, to it's latest available value, on 12/31/2023, is -20.32%.

The Seasonal ground cover statistics products are long-term temporal statistic products derived from the seasonal ground cover product for each fraction across Queensland for the 30 year timeseries. There is one raster image for each season and each bare and green fraction for the full time series of imagery available. Statistics include: band 1 – 5th percentile minimum; band 2 – mean value for pixel over full time series for that season only (percentage + 100); band 3 – median value for pixel over full time series for that season only (percentage + 100); band 4 – 95th percentile maximum; band 5 – Standard deviation - the temporal standard deviation of the full time-series for that season only; band 6 – Count - the number of observations statistics for that pixel are based on for that season only. Min/max (5th and 95th percentile) products are also made for each fraction using all seasonal ground cover images available during the long term data period (currently 1990-2020).

Time series data for the statistic Regulatory Quality: Percentile Rank, Lower Bound of 90% Confidence Interval and country Cayman Islands. Indicator Definition:Regulatory Quality captures perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Lower refers to lower bound of 90 percent confidence interval for governance, expressed in percentile rank terms.The indicator "Regulatory Quality: Percentile Rank, Lower Bound of 90% Confidence Interval" stands at 66.51 as of 12/31/2023. Regarding the One-Year-Change of the series, the current value constitutes a decrease of -2.08 percent compared to the value the year prior.The 1 year change in percent is -2.08.The 3 year change in percent is 3.46.The 5 year change in percent is 3.46.The 10 year change in percent is -1.86.The Serie's long term average value is 67.86. It's latest available value, on 12/31/2023, is 1.98 percent lower, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2016, to it's latest available value, on 12/31/2023, is +9.98%.The Serie's change in percent from it's maximum value, on 12/31/2004, to it's latest available value, on 12/31/2023, is -15.39%.

Time series data for the statistic Government Effectiveness: Percentile Rank, Upper Bound of 90% Confidence Interval and country Uzbekistan. Indicator Definition:Government Effectiveness captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Upper refers to upper bound of 90 percent confidence interval for governance, expressed in percentile rank terms.The indicator "Government Effectiveness: Percentile Rank, Upper Bound of 90% Confidence Interval" stands at 58.02 as of 12/31/2023, the highest value at least since 12/31/1998, the period currently displayed. Regarding the One-Year-Change of the series, the current value constitutes an increase of 1.65 percent compared to the value the year prior.The 1 year change in percent is 1.65.The 3 year change in percent is 23.07.The 5 year change in percent is 29.62.The 10 year change in percent is 70.03.The Serie's long term average value is 38.89. It's latest available value, on 12/31/2023, is 49.18 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2005, to it's latest available value, on 12/31/2023, is +181.81%.The Serie's change in percent from it's maximum value, on 12/31/2023, to it's latest available value, on 12/31/2023, is 0.0%.

Time series data for the statistic Regulatory Quality: Percentile Rank, Lower Bound of 90% Confidence Interval and country Cyprus. Indicator Definition:Regulatory Quality captures perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Lower refers to lower bound of 90 percent confidence interval for governance, expressed in percentile rank terms.The indicator "Regulatory Quality: Percentile Rank, Lower Bound of 90% Confidence Interval" stands at 64.15 as of 12/31/2023. Regarding the One-Year-Change of the series, the current value constitutes an increase of 0.7407 percent compared to the value the year prior.The 1 year change in percent is 0.7407.The 3 year change in percent is -10.78.The 5 year change in percent is -5.79.The 10 year change in percent is -4.68.The Serie's long term average value is 72.55. It's latest available value, on 12/31/2023, is 11.58 percent lower, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2022, to it's latest available value, on 12/31/2023, is +0.741%.The Serie's change in percent from it's maximum value, on 12/31/2010, to it's latest available value, on 12/31/2023, is -20.67%.

Spatial predictions of plant available water capacity (PAWC), drained upper limit (DUL) and crop lower limit (CLL) for grain-growing regions of NSW, Australia, from Padarian Campusano pedotransfer functions and NSW Office of Environment and Heritage (NSW OEH) datasets.

PAWC is the amount of water a soil can hold against gravity (i.e. water which does not freely drain) that is available to plants through their roots. This soil property is very important in dryland cropping areas which rely on rainfall. The maximum amount of water which can be held by a soil against gravity is called the DUL. The water that remains in a soil after plants have extracted all that is available to them is called the CLL. PAWC is calculated as DUL minus CLL.

Digital soil mapping (DSM) allows the spatial prediction of soil properties across large areas using modelling techniques which combine point data measured in the field and continuous datasets related to soil forming processes such as climate, topography, land cover, existing soil mapping and lithology. Pedotransfer functions (PTFs) are equations which use the easier to measure soil attributes, e.g. sand, clay, bulk density, to model the harder to measure attributes like DUL and CLL. DSM techniques such as Latin Hypercube (LHC) sampling can be used to incorporate the uncertainties associated with the input datasets in the modelling, and to produce estimates of model output precision and reliability.

This data collection consists of spatially predicted PAWC, DUL and CLL for the grain-growing regions of New South Wales, Australia, as defined by the boundary of the Grains Research and Development Corporation's Northern Region. PAWC was modelled using PTFs for DUL and CLL from Padarian Campusano, with LHC sampling to incorporate the uncertainties associated with the input datasets. The PAWC, DUL and CLL were modelled at the six Global Soil Map depths of 0-5 cm, 5-15 cm, 15-30 cm, 30-60 cm, 60-100 cm, and 100-200 cm. The top five depths have been aggregated to create a PAWC prediction for 0-100 cm.

Lineage: INPUT DATASETS 1. Soil attribute layers from the NSW OEH via the eSpade website: clay (%), sand (%), and effective cation exchange capacity (CEC; cmol/kg). The estimated value (mean) and the RMSE values were used for all six Global Soil Map depths (0-5 cm, 5-15 cm, 15-30 cm, 30-60 cm, 60-100 cm, and 100-200 cm). https://www.environment.nsw.gov.au/eSpade2Webapp 2. The Northern Region boundary from the Grains Research and Development Corporation (GRDC)

PEDOTRANSFER FUNCTIONS DUL and CLL equations from Padarian Campusano (2014), which used a subset of 806 soil profiles from the APSoil database that included field measurements of DUL and CLL: 1. DUL = 0.2358 + 0.002572*CEC + 0.001001*clay – 1.70 x 10^-7*sand^3 2. CLL = 0.6151*DUL – 0.02192 3. PAWC = DUL – CLL

METHODS These methods are available from Austin et al. (2019), see Related Links section.

The NSW OEH input datasets were clipped to the study area boundary and divided into tiles of 200 x 200 grid cells prior to parallel processing in a supercomputer environment. Except for the LHC sampling and correlation matrices, all code was written in Python. Layer thickness for each of the six soil depths was calculated in mm from the depth layer upper and lower bounds (e.g. 5 to 15 cm).

A correlation matrix was generated in the R package for the NSW OEH clay, sand, and CEC input datasets for each of the six depths, with correlation values derived using data for the whole study area for each of the inputs.

Each of the six soil depth layers was modelled separately. For every grid cell in each depth layer, the following steps were used to calculate DUL, CLL and PAWC: 1. The RMSE values for the clay, sand, and CEC input variables were used as approximations of standard deviation (SD) for input to the LHC sampling

1. LHC sampling with a correlation matrix (from the R pse library; Chalom and Prado, 2014), using means, SDs and a correlation matrix as inputs, produced fifty realisations of each input variable. Fifty realisations were chosen following the work of Malone et al. (2015) who found that there was little difference in outcome when using more than 50 samples

2. 50 DUL and CLL values were calculated from the 50 input variable realisations using the DUL and CLL equations from Padarian Campusano (2014)

3. 50 PAWC values were calculated from the DUL and CLL values, constrained by the depth layer thickness, with units of mm

4. From the 50 DUL, CLL and PAWC values for each grid cell, the mean, median, 5th and 95th percentiles, and SD were calculated and written to file as geotiffs

The tiled outputs were merged to form single rasters of the study area for DUL, CLL and PAWC at each of the six depths. Additionally, the 0-5, 5-15, 15-30, 30-60 and 60-100 cm soil depth layers were used to calculate 0-1 m versions of DUL, CLL and PAWC. The mean, median, 5th and 95th percentile values were summed to produce the 0-1 m DUL, CLL or PAWC prediction for each grid cell. This aggregation of depths assumes high correlation between layers – for example, the 95th percentile for the 0 – 1 m layer is the sum of the 95th percentiles for each contributing layer. If the layers were uncorrelated, the 95th percentile would end up closer to the mean. The SD for each of the 0-1 m DUL, CLL and PAWC layers was calculated from the summed 5th and 95th percentiles, as per the equation from Malone et al. (2011).

Time series data for the statistic Government Effectiveness: Percentile Rank, Upper Bound of 90% Confidence Interval and country Ghana. Indicator Definition:Government Effectiveness captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Upper refers to upper bound of 90 percent confidence interval for governance, expressed in percentile rank terms.The indicator "Government Effectiveness: Percentile Rank, Upper Bound of 90% Confidence Interval" stands at 58.96 as of 12/31/2023. Regarding the One-Year-Change of the series, the current value constitutes a decrease of -3.10 percent compared to the value the year prior.The 1 year change in percent is -3.10.The 3 year change in percent is 4.05.The 5 year change in percent is 15.72.The 10 year change in percent is -0.4717.The Serie's long term average value is 58.48. It's latest available value, on 12/31/2023, is 0.83 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2015, to it's latest available value, on 12/31/2023, is +15.72%.The Serie's change in percent from it's maximum value, on 12/31/2000, to it's latest available value, on 12/31/2023, is -12.28%.

Time series data for the statistic Government Effectiveness: Percentile Rank, Upper Bound of 90% Confidence Interval and country Nepal. Indicator Definition:Government Effectiveness captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Upper refers to upper bound of 90 percent confidence interval for governance, expressed in percentile rank terms.The indicator "Government Effectiveness: Percentile Rank, Upper Bound of 90% Confidence Interval" stands at 36.79 as of 12/31/2023, the highest value since 12/31/2009. Regarding the One-Year-Change of the series, the current value constitutes an increase of 11.43 percent compared to the value the year prior.The 1 year change in percent is 11.43.The 3 year change in percent is 13.62.The 5 year change in percent is 13.62.The 10 year change in percent is 10.90.The Serie's long term average value is 37.68. It's latest available value, on 12/31/2023, is 2.34 percent lower, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2015, to it's latest available value, on 12/31/2023, is +67.97%.The Serie's change in percent from it's maximum value, on 12/31/2000, to it's latest available value, on 12/31/2023, is -38.23%.

This table presents income shares, thresholds, tax shares, and total counts of individual Canadian tax filers, with a focus on high income individuals (95% income threshold, 99% threshold, etc.). Income thresholds are based on national threshold values, regardless of selected geography; for example, the number of Nova Scotians in the top 1% will be calculated as the number of taxfiling Nova Scotians whose total income exceeded the 99% national income threshold. Different definitions of income are available in the table namely market, total, and after-tax income, both with and without capital gains.

Time series data for the statistic Regulatory Quality: Percentile Rank, Lower Bound of 90% Confidence Interval and country Namibia. Indicator Definition:Regulatory Quality captures perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Lower refers to lower bound of 90 percent confidence interval for governance, expressed in percentile rank terms.The indicator "Regulatory Quality: Percentile Rank, Lower Bound of 90% Confidence Interval" stands at 35.38 as of 12/31/2023, the lowest value since 12/31/2018. Regarding the One-Year-Change of the series, the current value constitutes a decrease of -7.41 percent compared to the value the year prior.The 1 year change in percent is -7.41.The 3 year change in percent is -8.28.The 5 year change in percent is -8.28.The 10 year change in percent is -21.43.The Serie's long term average value is 45.25. It's latest available value, on 12/31/2023, is 21.82 percent lower, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2017, to it's latest available value, on 12/31/2023, is +6.13%.The Serie's change in percent from it's maximum value, on 12/31/2002, to it's latest available value, on 12/31/2023, is -41.56%.

Time series data for the statistic Government Effectiveness: Percentile Rank, Upper Bound of 90% Confidence Interval and country Seychelles. Indicator Definition:Government Effectiveness captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Upper refers to upper bound of 90 percent confidence interval for governance, expressed in percentile rank terms.The indicator "Government Effectiveness: Percentile Rank, Upper Bound of 90% Confidence Interval" stands at 82.08 as of 12/31/2023. Regarding the One-Year-Change of the series, the current value is equal to the value the year prior.The 1 year change in percent is 0.0.The 3 year change in percent is -3.17.The 5 year change in percent is 1.99.The 10 year change in percent is 8.24.The Serie's long term average value is 81.63. It's latest available value, on 12/31/2023, is 0.549 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2014, to it's latest available value, on 12/31/2023, is +8.74%.The Serie's change in percent from it's maximum value, on 12/31/2021, to it's latest available value, on 12/31/2023, is -8.81%.

Time series data for the statistic Government Effectiveness: Percentile Rank, Upper Bound of 90% Confidence Interval and country Zambia. Indicator Definition:Government Effectiveness captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Upper refers to upper bound of 90 percent confidence interval for governance, expressed in percentile rank terms.The indicator "Government Effectiveness: Percentile Rank, Upper Bound of 90% Confidence Interval" stands at 37.74 as of 12/31/2023. Regarding the One-Year-Change of the series, the current value constitutes a decrease of -8.05 percent compared to the value the year prior.The 1 year change in percent is -8.05.The 3 year change in percent is 11.61.The 5 year change in percent is -2.17.The 10 year change in percent is -16.19.The Serie's long term average value is 35.68. It's latest available value, on 12/31/2023, is 5.75 percent higher, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/1996, to it's latest available value, on 12/31/2023, is +77.07%.The Serie's change in percent from it's maximum value, on 12/31/2012, to it's latest available value, on 12/31/2023, is -17.06%.

Time series data for the statistic Government Effectiveness: Percentile Rank, Lower Bound of 90% Confidence Interval and country Nepal. Indicator Definition:Government Effectiveness captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Lower refers to lower bound of 90 percent confidence interval for governance, expressed in percentile rank terms.The indicator "Government Effectiveness: Percentile Rank, Lower Bound of 90% Confidence Interval" stands at 9.91 as of 12/31/2023, the highest value since 12/31/2015. Regarding the One-Year-Change of the series, the current value constitutes an increase of 10.53 percent compared to the value the year prior.The 1 year change in percent is 10.53.The 3 year change in percent is 30.01.The 5 year change in percent is 30.01.The 10 year change in percent is 10.00.The Serie's long term average value is 10.02. It's latest available value, on 12/31/2023, is 1.17 percent lower, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2004, to it's latest available value, on 12/31/2023, is +121.23%.The Serie's change in percent from it's maximum value, on 12/31/1996, to it's latest available value, on 12/31/2023, is -61.43%.

Time series data for the statistic Regulatory Quality: Percentile Rank, Lower Bound of 90% Confidence Interval and country Uganda. Indicator Definition:Regulatory Quality captures perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development. Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank. Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI. Percentile Rank Lower refers to lower bound of 90 percent confidence interval for governance, expressed in percentile rank terms.The indicator "Regulatory Quality: Percentile Rank, Lower Bound of 90% Confidence Interval" stands at 20.75 as of 12/31/2023, the lowest value at least since 12/31/1998, the period currently displayed. Regarding the One-Year-Change of the series, the current value constitutes a decrease of -2.22 percent compared to the value the year prior.The 1 year change in percent is -2.22.The 3 year change in percent is -16.18.The 5 year change in percent is -31.90.The 10 year change in percent is -33.65.The Serie's long term average value is 30.65. It's latest available value, on 12/31/2023, is 32.28 percent lower, compared to it's long term average value.The Serie's change in percent from it's minimum value, on 12/31/2023, to it's latest available value, on 12/31/2023, is +0.0%.The Serie's change in percent from it's maximum value, on 12/31/2004, to it's latest available value, on 12/31/2023, is -46.52%.