We use real-time data on vessel movements—Automatic Identification System (AIS) signals of vessels—as our primary data source. Source: Arslanalp, S., Koepke, R., & Verschuur, J. Tracking Trade from Space: An Application to Pacific Island Countries. IMF Working Paper No. 2021/225. https://www.imf.org/en/Publications/WP/Issues/2021/08/20/Tracking-Trade-from-Space-An-Application-to-Pacific-Island-Countries-464345 Concepts:Chokepoint: the full list of chokepoints we cover and associated additional information can be found here. Transit Calls: a transit call is defined when a ship transits through the chokepoint boundary. Transits that span across several days are counted only once and a threshold of 48 hours is applied before counting the same ship again.Trade Volume Estimates: as described in the paper, we use the vessel information (length, width, draft, capacity, block coefficient) to estimate the payload (or utilization rate) of the vessel when transiting through the chokepoint. The vessel payload (in percentage points) multiplied by the vessel’s deadweight tonnage (the maximum carrying capacity) in metric tons is the resulting trade volume estimate in metric tons carried by the ship. Ship Categories: all the indicators are available by 5 main ship categories: container, dry bulk, general cargo, ro-ro and tanker. Variables: date: all transit call dates are expressed in Coordinated Universal Time (UTC), a standard used to set all time zones around the world.year: as extracted from date.month: month 1-12 extracted from date. day: day 1-31 extracted from date. portid: chokepoint id. Full list of chokpoints and associated additional information can be found here. portname: chokepoint name. n_container: number of container ships transiting through the chokepoint at this date. n_dry_bulk: number of dry bulk carriers transiting through the chokepoint at this date. n_general_cargo: number of general cargo ships transiting through the chokepoint at this date. n_roro: number of ro-ro ships transiting through the chokepoint at this date. n_tanker: number of tankers transiting through the chokepoint at this date. n_cargo: total number of ships (excluding tankers) transiting through the chokepoint at this date. This is the sum of n_container, n_dry_bulk, n_general_cargo and n_roro.n_total: total number of ships transiting through the chokepoint at this date. This is the sum of n_container, n_dry_bulk, n_general_cargo, n_roro and n_tanker.capacity_container: total trade volume (in metric tons) of all container ships transiting through the chokepoint at this date.capacity_dry_bulk: total trade volume (in metric tons) of all dry bulk carriers transiting through the chokepoint at this date. capacity_general_cargo: total trade volume (in metric tons) of all general cargo ships transiting through the chokepoint at this date. capacity_roro: total trade volume (in metric tons) of all ro-ro ships transiting through the chokepoint at this date. capacity_tanker: total trade volume (in metric tons) of all tankers transiting through the chokepoint at this date. capacity_cargo: total trade volume (in metric tons) of all ships (excluding tankers) transiting through the chokepoint at this date. This is the sum of capacity_container, capacity_dry_bulk, capacity_general_cargo and capacity_roro.capacity: total trade volume (in metric tons) of all ships transiting through the chokepoint at this date. This is the sum of capacity_container, capacity_dry_bulk, capacity_general_cargo, capacity_roro and capacity_tanker. How to Cite?These datasets are based on raw AIS data from the United National Global Platform and estimates by the PortWatch team based on the methodology described in the paper. The recommended citation is: “Sources: UN Global Platform; IMF PortWatch (portwatch.imf.org).”About AIS DataThe UN has made available satellite-based AIS data through the UN Global Platform (UNGP) to national and international agencies that are members to the UN-CEBD (UN, 2021). The platform contains live data and global archive data from December 1, 2018. AIS data at the UNGP are provided by Spire, which collects AIS messages from two different satellite constellations, with more than 65 AIS equipped satellites. Spire complements this information with data collected by FleetMon through terrestrial receivers. There are several challenges with using AIS data. The AIS was originally developed by the International Maritime Organization (IMO) in 2004 as an outcome of amendments to the International Convention SOLAS (Safety of Life at Sea) in 2002. It is a self-reporting system, which allows vessels to periodically broadcast their identity, navigation, position data and other characteristics. The AIS has been made compulsory for all international commercial ships with gross tonnage of 300 or more tons (i.e., virtually all commercial ships) and all passenger ships regardless of size. There are three main types of information in AIS messages. AIS broadcasts voyage-related information (including ship location, speed, course, heading, rate of turn, destination, draft, and estimated arrival time), static information (including ship ID, ship type, ship size and dimensions), and dynamic information. Dynamic information such as the positional aspects (latitude and longitude) is automatically transmitted, depending on the vessels’ speed and course. The signals can be picked up by satellite or terrestrial receivers. For ships in open seas, however, the signals can only be picked up by satellite receivers as terrestrial receivers typically cover only about 15–20 nautical miles from the coast. For island states, satellite data tend to be much more reliable as the coverage of terrestrial receivers can be low (or nonexistent) for these smaller countries. Terrestrial receivers are useful for congested ports where congestion may make it difficult for satellites to capture all emitted messages. Additional information on AIS data can be found in Arslanalp et al. (2019), Verschuur et al. (2020), and the UN’s AIS Handbook.References: Arslanalp, S., Koepke, R., & Verschuur, J. Tracking Trade from Space: An Application to Pacific Island Countries. IMF Working Paper No. 2021/225. https://www.imf.org/en/Publications/WP/Issues/2021/08/20/Tracking-Trade-from-Space-An-Application-to-Pacific-Island-Countries-464345 AIS Handbook https://unstats.un.org/wiki/display/AIS/AIS+Handbook

Concepts:Chokepoint: the full list of chokepoints we cover and associated additional information. Vessel Count: we use real-time data on vessel movements—Automatic Identification System (AIS) signals of vessels— to calculate the yearly average number of ships passing through the chokepoint, over the timeframe 2019-2024. These yearly averages are available by 5 main ship categories (container, dry bulk, general cargo, ro-ro and tanker) plus the total. Top Industries: dominant traded industries based on the volume of goods estimated to flow through the chokepoint. Note that this is not based on official statistics.Variables: portid: chokepoint unique id. portname: chokepoint name. lat: latitude of the chokepoint location.lon: longitude of the chokepoint location.vessel_count_total: yearly average number of all ships transiting through the chokepoint. Estimated using AIS data between 2019-2024. The total is calculated over the sum of vessel_count_container, vessel_count_dry_bulk, vessel_count_general_cargo, vessel_count_roro and vessel_count_tanker.vessel_count_container: yearly average number of containers transiting through the chokepoint. Estimated using AIS data between 2019-2024. vessel_count_dry_bulk: yearly average number of dry bulk carriers transiting through the chokepoint. Estimated using AIS data between 2019-2024. vessel_count_general_cargo: yearly average number of general cargo ships transiting through the chokepoint. Estimated using AIS data between 2019-2024. vessel_count_roro: yearly average number of Ro-Ro ships transiting through the chokepoint. Estimated using AIS data between 2019-2024. vessel_count_tanker: yearly average number of tankers transiting through the chokepoint. Estimated using AIS data between 2019-2024. industry_top1: first dominant traded industries based on the volume of goods estimated to flow through the chokepoint.industry_top2: second dominant traded industries based on the volume of goods estimated to flow through the chokepoint.industry_top3: third dominant traded industries based on the volume of goods estimated to flow through the chokepoint.How to Cite?These datasets are based on raw AIS data from the United National Global Platform and estimates by the PortWatch team based on the methodology described in the paper. The recommended citation is: “Sources: UN Global Platform; IMF PortWatch (portwatch.imf.org).”

We use real-time data on vessel movements—Automatic Identification System (AIS) signals of vessels—as our primary data source.Source:Arslanalp, S., Koepke, R., & Verschuur, J. Tracking Trade from Space: An Application to Pacific Island Countries. IMF Working Paper No. 2021/225. https://www.imf.org/en/Publications/WP/Issues/2021/08/20/Tracking-Trade-from-Space-An-Application-to-Pacific-Island-Countries-464345Concepts:Ports: Full list of ports we cover and associated additional information can be found here. Port Calls: a port call is defined when a ship enters the port boundary. Port calls with a turnaround time of less than 5 hours and no draft change between the current and next port are excluded to filter out vessels in transit (i.e., vessels that visit a port for reasons other then loading and discharging cargo, such as anchoring, refueling or provisioning). Trade Estimates: as described in the paper, we use the vessel information (length, width, draft, capacity, block coefficient) to estimate the payload (or utilization rate) of the vessel when entering and leaving the port boundary. The change in the vessel payload (in percentage points) multiplied by the vessel’s deadweight tonnage (the maximum carrying capacity) in metric tons is the resulting trade flow (either import or export) in metric tons.Ship Categories: all the indicators are available by 5 main ship categories: container, dry bulk, general cargo, ro-ro and tanker.Variables: date: all port call dates are expressed in Coordinated Universal Time (UTC), a standard used to set all time zones around the world. year: as extracted from date. month: month 1-12 extracted from date. day: day 1-31 extracted from date. portid: port id. Full list of ports and associated additional information can be found here. portname: port name. country: country the port resides in. ISO3: ISO 3-letter country code of the port. portcalls_container: number of container ships entering the port at this date. portcalls_dry_bulk: number of dry bulk carriers entering the port at this date. portcalls_general_cargo: number of general cargo ships entering the port at this date. portcalls_roro: number of ro-ro ships entering the port at this date. portcalls_tanker: number of tankers entering the port at this date. portcalls_cargo: total number of ships (excluding tankers) entering the port at this date. This is the sum of portcalls_container, portcalls_dry_bulk, portcalls_general_cargo and portcalls_roro. portcalls: total number of ships entering the port at this date. This is the sum of portcalls_container, portcalls_dry_bulk, portcalls_general_cargo, portcalls_roro and portcalls_tanker. import_container: total import volume (in metric tons) of all container ships entering the port at this date. import_dry_bulk: total import volume (in metric tons) of all dry bulk carriers entering the port at this date. import_general_cargo: total import volume (in metric tons) of all general cargo ships entering the port at this date. import_roro: total import volume (in metric tons) of all ro-ro ships entering the port at this date. import_tanker: total import volume (in metric tons) of all tankers entering the port at this date. import_cargo: total import volume (in metric tons) of all ships (excluding tankers) entering the port at this date. This is the sum of import_container, import_dry_bulk, import_general_cargo and import_roro. import: total import volume (in metric tons) of all ships entering the port at this date. This is the sum of import_container, import_dry_bulk, import_general_cargo, import_roro and import_tanker. export_container: total export volume (in metric tons) of all container ships entering the port at this date. export_dry_bulk: total export volume (in metric tons) of all dry bulk carriers entering the port at this date. export_general_cargo: total export volume (in metric tons) of all general cargo ships entering the port at this date. export_roro: total export volume (in metric tons) of all ro-ro ships entering the port at this date. export_tanker: total export volume (in metric tons) of all tankers entering the port at this date. export_cargo: total export volume (in metric tons) of all ships (excluding tankers) entering the port at this date. This is the sum of export_container, export_dry_bulk, export_general_cargo and export_roro. export: total export volume (in metric tons) of all ships entering the port at this date. This is the sum of export_container, export_dry_bulk, export_general_cargo, export_roro and export_tanker.How to Cite? These datasets are based on raw AIS data from the United National Global Platform and estimates by the PortWatch team based on the methodology described in the paper. The recommended citation is: “Sources: UN Global Platform; IMF PortWatch (portwatch.imf.org).”About AIS Data The UN has made available satellite-based AIS data through the UN Global Platform (UNGP) to national and international agencies that are members to the UN-CEBD (UN, 2021). The platform contains live data and global archive data from December 1, 2018. AIS data at the UNGP are provided by Spire, which collects AIS messages from two different satellite constellations, with more than 65 AIS equipped satellites. Spire complements this information with data collected by FleetMon through terrestrial receivers. There are several challenges with using AIS data. First, ships can turn off their AIS transponder to avoid being detected. Strictly speaking, this is not legal and is mostly limited to fishing vessels conducting illegal fishing or oil tankers circumventing international sanctions, usually in international waters. It is not common for container and other cargo ships (which is the focus of our study) entering a country’s port. In fact, in most jurisdictions, port authorities make it mandatory for ships entering a port to keep their AIS transponders on at all times for the safety all vessels in the port. Second, the AIS data do not have information about the ship’s carrying capacity (i.e., deadweight tonnage) and maximum draft. To fill this gap, we use ship registry databases from FleetMon and IHS Markit (the latter is available from the UNGP), with information for around 120,000 vessels. Finally, a potentially more serious challenge with AIS data is that some information is entered manually and, hence, may have human errors. This is expected as AIS was intended originally for safety at sea, not for producing statistics. For our purposes, the key issue is that the crew may not always update the draft information after a ship leaves the port. The draft is the vertical distance between the waterline and the bottom of the ship’s hull and is a measure of the payload of the vessel. However, our algorithm uses techniques to address this issue. Particularly, the missing information can be backtracked or imputed in most cases, given the wealth of information in the AIS data (Arslanalp, Koepke, Verschuur, 2021). The AIS was originally developed by the International Maritime Organization (IMO) in 2004 as an outcome of amendments to the International Convention SOLAS (Safety of Life at Sea) in 2002. It is a self-reporting system, which allows vessels to periodically broadcast their identity, navigation, position data and other characteristics. The AIS has been made compulsory for all international commercial ships with gross tonnage of 300 or more tons (i.e., virtually all commercial ships) and all passenger ships regardless of size. There are three main types of information in AIS messages. AIS broadcasts voyage-related information (including ship location, speed, course, heading, rate of turn, destination, draft, and estimated arrival time), static information (including ship ID, ship type, ship size and dimensions), and dynamic information. Dynamic information such as the positional aspects (latitude and longitude) is automatically transmitted, depending on the vessels’ speed and course. The signals can be picked up by satellite or terrestrial receivers. For ships in open seas, however, the signals can only be picked up by satellite receivers as terrestrial receivers typically cover only about 15–20 nautical miles from the coast. For island states, satellite data tend to be much more reliable as the coverage of terrestrial receivers can be low (or nonexistent) for these smaller countries. Terrestrial receivers are useful for congested ports where congestion may make it difficult for satellites to capture all emitted messages. Additional information on AIS data can be found in Arslanalp et al. (2019), Verschuur et al. (2020), and the UN’s AIS Handbook. References: Arslanalp, S., Koepke, R., & Verschuur, J. Tracking Trade from Space: An Application to Pacific Island Countries. IMF Working Paper No. 2021/225. https://www.imf.org/en/Publications/WP/Issues/2021/08/20/Tracking-Trade-from-Space-An-Application-to-Pacific-Island-Countries-464345 AIS Handbook https://unstats.un.org/wiki/display/AIS/AIS+Handbook

Sources:GDACS platform: https://www.gdacs.org/ Concepts:GDACS was created in 2004 as a cooperation framework between the United Nations and the European Commission, to address significant gaps in information collection and analysis in the early phase of major sudden-onset disasters. GDACS provides real-time access to disaster information systems and currently reports are issued for earthquakes and possible subsequent tsunamis, tropical cyclones, floods and volcanic eruptions. The platform includes Disaster Alerts, a virtual On-Site Operations Coordination Centre (OSOCC) to cooperate and exchange disaster-related real time information, and maps and satellite imagery. GDACS information and data are used by many governments, disaster response organizations, and researchers and are publicly available through the GDACS platform.The data provided by GDACS is utilized in the following manner: Scan GDACS data. We scan the GDACS data on an automated and daily basis to retrieve information on active disruptions​. From each disaster report, we extract three types of information: basic information, the polygon of the impacted area, and the affected population, that is the population that is in a certain proximity of the disaster. The basic information includes information on name, location, type, event severity, countries that are impacted, etc. To determine the severity of each disaster, GDACS produces a score. The score varies between 0 to 3, for which disasters with a score between 0 to 1 are marked green, 1 to 2 orange, and 2 to 3 red. For calculation of the severity score of each disaster type (earthquakes, tsunamis, tropical cyclones, floods, volcano, or droughts) different criteria are taken into consideration. For example, for details on how alert scores are calculated for Tropical Cyclones, please visit: https://www.gdacs.org/Knowledge/models_tc.aspx. As of now, we only consider disasters with a severity score of 2 to 3 (red).Intersect disaster impact area with PortWatch ports boundaries and chokepoints boundaries. For each disaster with a severity score above 2 (a disaster in red category), we intersect the extracted impact area from GDACS with the PortWatch ports and chokepoints. The PortWatch ports and chokepoints with boundaries within the disaster impact area are marked as disrupted ports. PortWatch alerts. We send out an email alert combining the information about the disaster disrupted ports and the satellite based data​ which provides real-time information on port calls and import and export activity through the disrupted ports. Click here to subscribe to our email alerts and other updates about the PortWatch platform.PortWatch disruption pages. We include the disruption in our disruption monitor. Users can access details on each disruption with detailed analysis on spillovers at connected ports and countries, along with the unfolding of the impact on the real-time data.Variables:eventid= unique id of the event.eventtype = one of earthquakes (EQ), wild fires (WF), tropical cyclones (TC), floods (FL), volcano (VO), or droughts (DR) or other - e.g. geopolitical tensions - (OT).eventname= short name for event.htmlname = descriptive version of the eventname. htmldescription = description of event.alertlevel = refer to GDACS alert levels. They are based on a risk matrix that considers the likelihood of societies being unable to cope with a disaster at the national level. The final score also takes into account the affected country's coping capacity, which is based on the INFORM Index. This index measures a country's ability to deal with disasters through organized activities, government efforts, and infrastructure. See https://www.gdacs.org/Knowledge/models_eq.aspx for more information.country = affected country(ies). Derived based on the intersected ports.fromdate = start date of the event.todate = end date of the event.lat = latitude coordinate of the centroid of the event polygon.long = longitude coordinate of the centroid of the event polygon.affectedports = list of ports that intersect with the disruption polygon.n_affectedports = number of ports that intersect with the disruption polygon.affectedpopulation = exposed population based on GDACS assessment.How to cite? These dataset combine data from the journal article published by researchers affiliated with Oxford University and calculations by the PortWatch team. The recommended citation is: “Sources: University of Oxford; IMF PortWatch (portwatch.imf.org).”

Various indicators for MENA countries to get an overview of the countries energy and economic profiles. The indicators are organized in 6 categories: economic indicators, energy indicators, oil indicators, gas indicators, electricity indicators & energy efficiency indicators. Each indicator includes name, unit, yearand value for that year. Format included are Excel spreasheet, CSV & JSON. Sources vary for each indicators, please look at the Excel spreadsheet for details. Main sources are the World Bank Group, the IMF, KNOEMA aggregating platform and EIA.

Directorio de las Instituciones de Microfinanzas del Programa Nacional de Financiamiento al Microempresario (PRONAFIM)

Various indicators for MENA countries to get an overview of the countries energy and economic profiles. The indicators are organized in 6 categories: economic indicators, energy indicators, oil indicators, gas indicators, electricity indicators & energy efficiency indicators. Each indicator includes name, unit, yearand value for that year. Format included are Excel spreasheet, CSV & JSON. Sources vary for each indicators, please look at the Excel spreadsheet for details. Main sources are the World Bank Group, the IMF, KNOEMA aggregating platform and EIA.

The AfDB Statistics Department and the Fragile States Unit have compiled this data set from various sources (the World Bank, WHO, IMF, and many others)