variables

This table contains all the variables of all the datasets we have at Our World In Data. Note that this includes only the information about the variables like name and default display settings, not the data itself.

Data license: CC-BY

6 rows where datasetId = 3094 sorted by id descending

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id ▲ name unit description createdAt updatedAt code coverage timespan datasetId sourceId shortUnit display columnOrder originalMetadata grapherConfigAdmin shortName catalogPath dimensions schemaVersion processingLevel processingLog titlePublic titleVariant attributionShort attribution descriptionShort descriptionFromProducer descriptionKey descriptionProcessing licenses license grapherConfigETL type sort dataChecksum metadataChecksum
98777 Trust (Falk et al. (2018) GPS)   Trust is measured based on one item asking respondents whether they assume other people only have the best intentions. Responses range from 0 - 10 on the Likert scale. For more information, see Table I in Falk et al. (2018). Higher values indicate the country average for trust is above the world average. 2018-11-06 20:25:24 2023-06-15 05:05:42       Global Preferences Survey (GPS) - Falk, Becker, Dohmen, Enke, Huffman, and Sunde (2018) 3094 Falk, Becker, Dohmen, Enke, Huffman, and Sunde (2018) - Global Preferences Survey (GPS) 16229   
{}
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98776 Altruism (Falk et al. (2018) GPS)   Altruism was measured using one quantitative and one qualitative question both relating to donations. The quantitative scenario asked if the respondent unexpectedly received 1,000 euros how much of this amount they would donate. The qualitative items asked how willing respondents would be to give to good causes without expecting anything in return on an 11 point scale. Higher values indicate the country average for altruism is above the world average. The quantitative item is given a weight of roughly two-thirds, and the qualitative item a weight of about a third. For more information, see Table I in Falk et al. (2018). 2018-11-06 20:25:24 2023-06-15 05:05:42       Global Preferences Survey (GPS) - Falk, Becker, Dohmen, Enke, Huffman, and Sunde (2018) 3094 Falk, Becker, Dohmen, Enke, Huffman, and Sunde (2018) - Global Preferences Survey (GPS) 16229   
{}
 0           1                                  
98775 Negative reciprocity (Falk et al. (2018) GPS)   Negative reciprocity was measured using three self-assessments. First, respondents were asked if they would exact revenge if treated unjustly, even if doing so comes with a cost (0-10). The second and third questions asked about respondents' willingness to punish someone for unfair behavior, either towards themselves or a third person. The third question captures prosocial punishment comparable to norm enforcement. Higher values indicate the country average for negative reciprocity is above the world average. The three items receive roughly equal weights, a third each. For more information, see Table I in Falk et al. (2018). 2018-11-06 20:25:24 2023-06-15 05:05:42       Global Preferences Survey (GPS) - Falk, Becker, Dohmen, Enke, Huffman, and Sunde (2018) 3094 Falk, Becker, Dohmen, Enke, Huffman, and Sunde (2018) - Global Preferences Survey (GPS) 16229   
{}
 0           1                                  
98774 Positive reciprocity (Falk et al. (2018) GPS)   Positive reciprocity preferences were measured using one quantitative and one qualitative question. In the quantitative item respondents were presented with a scenario where they got lost in an unfamiliar area and a stranger - when asked directions - offered to take them to their destination. Respondents then asked which out of six presents (worth between 5 and 30 euros, or respective country equivalents) they would give to the stranger as a "thank you". Respondents were also asked to provide a self-assessment about how willing they are to return a favor on an 11 point Likert scale. Higher values indicate the country average for positive reciprocity is above the world average. The two items receive roughly equal weights. For more information, see Table I in Falk et al. (2018). 2018-11-06 20:25:24 2023-06-15 05:05:42       Global Preferences Survey (GPS) - Falk, Becker, Dohmen, Enke, Huffman, and Sunde (2018) 3094 Falk, Becker, Dohmen, Enke, Huffman, and Sunde (2018) - Global Preferences Survey (GPS) 16229   
{}
 0           1                                  
98773 Risk taking (Falk et al. (2018) GPS)   Participants' risk preference was measured using both quantitative questions and a qualitative question. The quantitative question posed a series of 5 binary choices where participants chose between a fixed lottery (individual could win x or zero) and varying payments y (paid with certainty). Choice of the lottery resulted in an increase of the sure amount being offered in the next question, and vice versa, to determine an individual's certainty equivalent. The qualitative question asks for the participant's self assessment of their willingness to take risks on an 11 point scale: "In general, how willing are you to take risks?" Higher values indicate the country average for risk taking is above the world average. The qualitative and quantitative responses were combined using roughly equal weights. For more information, see Table I in Falk et al. (2018). 2018-11-06 20:25:24 2023-06-15 05:05:42       Global Preferences Survey (GPS) - Falk, Becker, Dohmen, Enke, Huffman, and Sunde (2018) 3094 Falk, Becker, Dohmen, Enke, Huffman, and Sunde (2018) - Global Preferences Survey (GPS) 16229   
{}
 0           1                                  
98772 Patience (time preference) (Falk et al. (2018) GPS)   The measure of patience (time preference) is a combination of two survey measures, one quantitative item and one qualitative item. The quantitative survey poses 5 interdependent binary choices between immediate and delayed financial rewards - the "staircase" (or "unfolding brackets") procedure. In each of the 5 questions, participants had to decide whether to receive a payment today or a larger payment in 12 months. The immediate payment x remained the same in all four subsequent questions, but the delayed payment y was increased or decreasing depending on the participant's previous choices. In the international survey, monetary amounts x and y were expressed in the local currency, scaled relative to the median household income in the given country. The qualitative patience measure is collected using the individuals' self-assessment regarding their willingness to wait on an 11 point Likert scale, asking: "How willing are you to give up something that is beneficial for you today in order to benefit more from that in the future?" Higher values indicate the country average for patience is above the world average. The quantitative item has a weight of 71% in the patience (time preference) measure. For more information, see Table I in Falk et al. (2018). 2018-11-06 20:25:24 2023-06-15 05:05:42       Global Preferences Survey (GPS) - Falk, Becker, Dohmen, Enke, Huffman, and Sunde (2018) 3094 Falk, Becker, Dohmen, Enke, Huffman, and Sunde (2018) - Global Preferences Survey (GPS) 16229   
{}
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CREATE TABLE "variables" (
	"id" INTEGER PRIMARY KEY AUTOINCREMENT,
	"name" VARCHAR(750) NULL  ,
	"unit" VARCHAR(255) NOT NULL  ,
	"description" TEXT NULL  ,
	"createdAt" DATETIME NOT NULL DEFAULT CURRENT_TIMESTAMP ,
	"updatedAt" DATETIME NULL  ,
	"code" VARCHAR(255) NULL  ,
	"coverage" VARCHAR(255) NOT NULL  ,
	"timespan" VARCHAR(255) NOT NULL  ,
	"datasetId" INTEGER NOT NULL  ,
	"sourceId" INTEGER NULL  ,
	"shortUnit" VARCHAR(255) NULL  ,
	"display" TEXT NOT NULL  ,
	"columnOrder" INTEGER NOT NULL DEFAULT '0' ,
	"originalMetadata" TEXT NULL  ,
	"grapherConfigAdmin" TEXT NULL  ,
	"shortName" VARCHAR(255) NULL  ,
	"catalogPath" VARCHAR(767) NULL  ,
	"dimensions" TEXT NULL  ,
	"schemaVersion" INTEGER NOT NULL DEFAULT '1' ,
	"processingLevel" VARCHAR(30) NULL  ,
	"processingLog" TEXT NULL  ,
	"titlePublic" VARCHAR(512) NULL  ,
	"titleVariant" VARCHAR(255) NULL  ,
	"attributionShort" VARCHAR(512) NULL  ,
	"attribution" TEXT NULL  ,
	"descriptionShort" TEXT NULL  ,
	"descriptionFromProducer" TEXT NULL  ,
	"descriptionKey" TEXT NULL  ,
	"descriptionProcessing" TEXT NULL  ,
	"licenses" TEXT NULL  ,
	"license" TEXT NULL  ,
	"grapherConfigETL" TEXT NULL  ,
	"type" TEXT NULL  ,
	"sort" TEXT NULL  ,
	"dataChecksum" VARCHAR(64) NULL  ,
	"metadataChecksum" VARCHAR(64) NULL,
	FOREIGN KEY("datasetId") REFERENCES "datasets" ("id") ON UPDATE RESTRICT ON DELETE RESTRICT,
	FOREIGN KEY("sourceId") REFERENCES "sources" ("id") ON UPDATE RESTRICT ON DELETE RESTRICT
);
CREATE UNIQUE INDEX "idx_catalogPath" ON "variables" ("catalogPath");
CREATE UNIQUE INDEX "unique_short_name_per_dataset" ON "variables" ("shortName", "datasetId");
CREATE UNIQUE INDEX "variables_code_fk_dst_id_7bde8c2a_uniq" ON "variables" ("code", "datasetId");
CREATE INDEX "variables_datasetId_50a98bfd_fk_datasets_id" ON "variables" ("datasetId");
CREATE UNIQUE INDEX "variables_name_fk_dst_id_f7453c33_uniq" ON "variables" ("name", "datasetId");
CREATE INDEX "variables_sourceId_31fce80a_fk_sources_id" ON "variables" ("sourceId");