Moody's · Schema

Moody's Analytics Time Series

Schema for a Moody's Analytics Data Buffet time series response, representing economic, demographic, or financial observations and forecasts over a date range with associated metadata.

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Properties

Name Type Description
mnemonic string The unique series mnemonic identifier following the Data Buffet naming convention. Mnemonics encode the concept, geography, and source of the data.
description string Human-readable description of the time series including the indicator name, geographic scope, and data source.
frequency string The temporal frequency of the observations in the data array. Indicates how often data points are recorded or reported.
source string The original data source or statistical agency that produces the raw data.
geography string The geographic area the series covers. Can range from global aggregates to subnational regions.
geographyCode string Standardized geographic area code (ISO 3166 country code or FIPS state/county code).
units string The unit of measurement for the series values, describing what the numeric values represent.
transformation string The mathematical transformation applied to the original data, if any.
category string The broad economic or demographic category the series belongs to.
startDate string The earliest observation date in the returned data range.
endDate string The latest observation or forecast date in the returned data range.
vintage string The vintage date of the data, representing when this revision of the data was published. Enables tracking of historical data revisions.
lastUpdated string ISO 8601 timestamp indicating when the series was last updated in the Data Buffet repository.
isForecast boolean Whether the series includes forecast values generated by Moody's Analytics proprietary macroeconomic models.
forecastStartDate string The date at which forecast data begins within the series. All observations before this date are historical actuals.
seasonalAdjustment string Whether and how the data has been seasonally adjusted.
data array Array of chronologically ordered date-value pairs representing the time series observations and/or forecasts. Each element corresponds to one period at the series frequency.
View JSON Schema on GitHub

JSON Schema

moodys-time-series-schema.json Raw ↑
{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "https://economy.com/schemas/moodys/time-series.json",
  "title": "Moody's Analytics Time Series",
  "description": "Schema for a Moody's Analytics Data Buffet time series response, representing economic, demographic, or financial observations and forecasts over a date range with associated metadata.",
  "type": "object",
  "required": [
    "mnemonic",
    "description",
    "frequency",
    "data"
  ],
  "properties": {
    "mnemonic": {
      "type": "string",
      "description": "The unique series mnemonic identifier following the Data Buffet naming convention. Mnemonics encode the concept, geography, and source of the data.",
      "examples": [
        "FGDP_US",
        "EMPLPAY.IUSA",
        "UCUR.IUSA",
        "FHPI_US"
      ]
    },
    "description": {
      "type": "string",
      "description": "Human-readable description of the time series including the indicator name, geographic scope, and data source.",
      "examples": [
        "Gross Domestic Product, United States",
        "Total Nonfarm Payrolls, United States",
        "Consumer Price Index, All Urban Consumers, United States"
      ]
    },
    "frequency": {
      "type": "string",
      "description": "The temporal frequency of the observations in the data array. Indicates how often data points are recorded or reported.",
      "enum": [
        "Annual",
        "Quarterly",
        "Monthly",
        "Weekly",
        "Daily"
      ]
    },
    "source": {
      "type": "string",
      "description": "The original data source or statistical agency that produces the raw data.",
      "examples": [
        "Bureau of Labor Statistics",
        "Bureau of Economic Analysis",
        "Federal Reserve Board",
        "International Monetary Fund",
        "Eurostat",
        "Moody's Analytics"
      ]
    },
    "geography": {
      "type": "string",
      "description": "The geographic area the series covers. Can range from global aggregates to subnational regions.",
      "examples": [
        "United States",
        "United Kingdom",
        "European Union",
        "China",
        "California",
        "New York-Newark-Jersey City, NY-NJ-PA MSA"
      ]
    },
    "geographyCode": {
      "type": "string",
      "description": "Standardized geographic area code (ISO 3166 country code or FIPS state/county code).",
      "examples": [
        "US",
        "GB",
        "EU",
        "CN",
        "US-CA"
      ]
    },
    "units": {
      "type": "string",
      "description": "The unit of measurement for the series values, describing what the numeric values represent.",
      "examples": [
        "Billions of Chained 2017 Dollars",
        "Thousands of Persons",
        "Index 1982-84=100",
        "Percent",
        "Millions of Units"
      ]
    },
    "transformation": {
      "type": "string",
      "description": "The mathematical transformation applied to the original data, if any.",
      "enum": [
        "Level",
        "SimpleDifference",
        "PercentChange",
        "AnnualizedGrowth",
        "YearOverYearPercentChange",
        "CompoundAnnualGrowthRate"
      ]
    },
    "category": {
      "type": "string",
      "description": "The broad economic or demographic category the series belongs to.",
      "examples": [
        "National Accounts",
        "Labor Markets",
        "Prices and Inflation",
        "Housing",
        "Financial Markets",
        "Demographics",
        "Trade",
        "Government Finance"
      ]
    },
    "startDate": {
      "type": "string",
      "format": "date",
      "description": "The earliest observation date in the returned data range."
    },
    "endDate": {
      "type": "string",
      "format": "date",
      "description": "The latest observation or forecast date in the returned data range."
    },
    "vintage": {
      "type": "string",
      "format": "date",
      "description": "The vintage date of the data, representing when this revision of the data was published. Enables tracking of historical data revisions."
    },
    "lastUpdated": {
      "type": "string",
      "format": "date-time",
      "description": "ISO 8601 timestamp indicating when the series was last updated in the Data Buffet repository."
    },
    "isForecast": {
      "type": "boolean",
      "description": "Whether the series includes forecast values generated by Moody's Analytics proprietary macroeconomic models."
    },
    "forecastStartDate": {
      "type": "string",
      "format": "date",
      "description": "The date at which forecast data begins within the series. All observations before this date are historical actuals."
    },
    "seasonalAdjustment": {
      "type": "string",
      "description": "Whether and how the data has been seasonally adjusted.",
      "enum": [
        "Seasonally Adjusted",
        "Not Seasonally Adjusted",
        "Seasonally Adjusted Annual Rate"
      ]
    },
    "data": {
      "type": "array",
      "description": "Array of chronologically ordered date-value pairs representing the time series observations and/or forecasts. Each element corresponds to one period at the series frequency.",
      "items": {
        "$ref": "#/$defs/Observation"
      }
    }
  },
  "$defs": {
    "Observation": {
      "type": "object",
      "title": "Time Series Observation",
      "description": "A single data point in the time series representing an observed historical value, a preliminary estimate, or a forecast for a specific date period.",
      "required": [
        "date",
        "value"
      ],
      "properties": {
        "date": {
          "type": "string",
          "format": "date",
          "description": "The observation date in YYYY-MM-DD format. For frequencies coarser than daily, this represents the period start date (e.g., 2024-01-01 for Q1 2024 or January 2024).",
          "examples": [
            "2024-01-01",
            "2024-04-01",
            "2024-07-15"
          ]
        },
        "value": {
          "type": ["number", "null"],
          "description": "The observed, estimated, or forecast value for this period. Null indicates missing or unavailable data.",
          "examples": [
            22038.2,
            157.5,
            3.7,
            null
          ]
        },
        "status": {
          "type": "string",
          "description": "Indicates whether this data point is a confirmed historical observation, a preliminary estimate subject to revision, or a model-generated forecast.",
          "enum": [
            "History",
            "Forecast",
            "Preliminary"
          ]
        }
      }
    }
  }
}