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The AEC Transparency Register is a vital tool for understanding the financial landscape of Australian politics, offering detailed insights into the financial activities of political entities such as political parties, candidates, donors, and third parties. Governed by the Commonwealth Electoral Act 1918, the register aims to enhance transparency by making public the financial dealings that may influence the electoral process. This guide introduces the Transparency Register, explains the datasets available through the get_disclosure_data function from the scgElectionsAU package, and provides context on the legislative framework, including upcoming changes.

Understanding the Transparency Register

The Transparency Register, hosted by the Australian Electoral Commission (AEC), is a comprehensive database that compiles financial disclosure information submitted by various political entities. These entities include registered political parties, significant third parties, associated entities, members of parliament, senators, donors, and others involved in electoral processes. The register’s primary purpose is to inform the public and allow scrutiny of financial activities that could impact elections, as mandated by Part XX of the Commonwealth Electoral Act 1918 (AEC Financial Disclosure).

The register organises data into three main types of returns:

  • Annual Returns: These cover financial activities for a financial year (July 1 to June 30), including donations, expenditures, debts, and other financial details. They are published on the first business day of February each year (AEC Annual Returns).
  • Election Returns: These pertain to federal elections or by-elections, detailing donations and electoral expenditures specific to those events. They are published 24 weeks after polling day.
  • Referendum Returns: These relate to referendums, capturing financial information such as donations and expenditures, published 24 weeks after voting day (AEC Transparency Register).

The Transparency Register faced a temporary outage on 15 May 2024 due to a privacy issue involving the publication of candidates’ postal addresses. An external review led to eight recommendations, all accepted by the AEC, to improve data handling (AEC Transparency FAQs). The AEC made the necessary changes to the register, which is now back online without any sensitive information.

The get_disclosure_data Function

The get_disclosure_data function, simplifies access to the Transparency Register’s datasets. The function takes three parameters:

  • type: Specifies the return type (Annual, Election, Referendum), defaulting to Annual.
  • group: Indicates the entity category, such as Donor, Party, Candidate, or Third Party, defaulting to Donor if not provided.
  • file_name: Denotes the specific dataset, such as Donations Made or Returns, defaulting to Donations Made if not specified.

The function validates inputs against predefined options and retrieves data from zipped folders on the AEC’s Transparency Register download page (AEC Downloads). Not all combinations of type, group, and file_name are valid; the function checks for valid datasets using an internal index (aec_disclosure_index) within the scgElectionsAU package.

Dataset Descriptions

The Transparency Register offers various datasets, each corresponding to a specific aspect of financial disclosure. Below is a summary of the datasets accessible via the get_disclosure_data function, organized by their file_name:

Dataset Description
Capital Contributions Details contributions to the entity’s capital, often relevant for associated entities or parties.
Debts Lists outstanding debts as of the end of the financial year, including creditor details and amounts.
Discretionary Benefits Records benefits received from the Commonwealth, State, or Territory, such as grants or subsidies.
Donations Made Provides details of donations given by the entity to political parties, candidates, or others, including recipient, amount, and date.
Donations Received Lists donations received by the entity, often used for electoral expenditure or further donations, including donor, amount, and date.
Expenses Covers expenditures, typically electoral, incurred by entities like candidates or third parties, detailing purpose and amount.
Media Advertisement Details Contains information on media advertisements, such as those for election or referendum campaigns, including medium and cost.
Receipts Comprehensive list of all receipts, including donations and other income, with details like source and amount.
Return Summary Summarizes key financial figures from the return, such as total receipts and payments.
Returns The complete financial return, including total receipts, payments, debts, donations, and discretionary benefits, as required by the AEC.

These datasets are available for different groups and types, as outlined in the examples below. For instance, Donations Made by a Donor in an Annual return lists their contributions to political entities, while Returns for a Party includes all required financial disclosures.

Legislative Context

The datasets are governed by the Commonwealth Electoral Act 1918, which mandates financial disclosure to maintain electoral integrity. For the 2023–24 financial year, the disclosure threshold was $16,300, indexed annually on July 1 (AEC Media Release). Entities must lodge returns through the AEC’s eReturns portal, with annual returns due by October 20 (or November 17 for MPs and Senators) and election/referendum returns due 24 weeks after the event.

Significant reforms to the funding and disclosure scheme are scheduled for July 1, 2026, and will not affect the 2025 federal election returns. These changes include:

  • Reducing the disclosure threshold to $5,000, indexed post-election.
  • Introducing expedited disclosure for donations over $5,000 (e.g., within 7 days during election periods).
  • Implementing donation caps (e.g., $50,000 annually per recipient) and expenditure caps (e.g., $90 million for parties federally).
  • Requiring federal accounts for electoral expenditure and donations.
  • Shifting to a calendar-year reporting period and replacing election returns with expedited disclosures (AEC Legislative Changes).

Minor amendments, such as changes to registration processes, will take effect on February 21, 2025, but are unlikely to impact dataset structures significantly.

Available Datasets and Examples

The following sections detail the datasets available for each return type, including example usage of the get_disclosure_data function and sample data. These examples demonstrate how to retrieve and explore the data, helping users analyse political financial activities.

Annual

Donations

Example Usage (Made):

df <- get_disclosure_data(
  file_name = "Donations Made",
  group = "Donor",
  type = "Annual"
)

Sample Data (Made):

Financial Year Donor Name Donation Made To Date Value
2023-24 Australian Energy Producers Australian Labor Party (Western Australian Branch) 31/07/2023 5500

Example Usage (Received):

df <- get_disclosure_data(
  file_name = "Donations Received",
  group = "Donor", # OR "Third Party"
  type = "Annual"
)

Sample Data (Received - Donor):

Financial Year Name Donation Received From Date Value
2023-24 Climate 200 Pty Limited Stuart Argue 11/07/2023 200

Sample Data (Received - Third Party):

Financial Year Name Donation Received From Date Value
2021-22 SEARCH Foundation JJ Fiasson 19/04/2022 23100


Returns

Example Usage:

df <- get_disclosure_data(
  file_name = "Returns",
  group = "Associated Entity", # OR "Donor", "MPs", "Party", "Significant Third Party", "Third Party"
  type = "Annual"
)

Sample Data (Associated Entity):

Financial Year Name Lodged on behalf of AssociatedParties Total Receipts Total Payments Total Debts Discretionary Benefits Capital Contributions
2023-24 1973 Foundation Pty Ltd NA Australian Labor Party (ACT Branch); 8003471 3408057 4277719 0 0

Sample Data (Donor):

Financial Year Name Lodged on behalf of Total Donations Made Total Donations Received
2023-24 Australian Energy Producers NA 171888 0

Sample Data (MPs):

Financial Year Return Type Name Total Donations Received Number of Donors
2023-24 Member of House of Representatives Return Dr Helen Haines MP 58318 176

Sample Data (Party):

Financial Year Name Party Group Total Receipts Total Payments Total Debts Total Discretionary Benefits
2023-24 Animal Justice Party NA 1186307 741013 129470 0

Sample Data (Significant Third Party):

Financial Year Return Type ClientFileId Name ABN ACN Lodged on behalf of Total Receipts Total Payments Total Debts Total Discretionary Benefits Electoral Expenditure
2023-24 Significant Third Party Return 42742 1 in 50 Incorporated NA NA NA 0 0 0 0 0

Sample Data (Third Party):

Financial Year ClientFileId Name ABN ACN Total Expenditure Electoral Expenditure Cat. 1 Electoral Expenditure Cat. 2 Electoral Expenditure Cat. 3 Electoral Expenditure Cat. 4 Electoral Expenditure Cat. 5 Total Gifts Received ClientType
2023-24 18736 Australian Rail Tram & Bus Industry Union New South Wales Branch 55090785801 NA 0 NA NA NA NA NA 0 associatedentity


Other

Example Usage:

df <- get_disclosure_data(
  file_name = "Capital Contributions", # OR "Debts", "Discretionary Benefits", "Receipts"
  group = "Other",
  type = "Annual"
)

Sample Data (Capital Contributions):

Financial Year Return Type Name Contributor Value
2019-20 Associated Entity Return Independent Education Union of Australia WA Branch Australian Labor Party (Western Australian Branch) 52419

Sample Data (Debts):

Financial Year Return Type Name Creditor Name Amount owed Financial or Non-financial institution
2023-24 Associated Entity Return 1973 Foundation Pty Ltd Australian Labor Party ACT Branch 4267719 Non-financial

Sample Data (Discretionary Benefits):

Financial Year Return Type Name Received From Date Value
2023-24 Significant Third Party Return Australian Council of Trade Unions Department of Foreign Affairs & Trade NA 883

Sample Data (Receipts):

Financial Year Return Type Recipient Name Received From Receipt Type Value
2023-24 Significant Third Party Return Advance Australia Australian Taxation Office Other Receipt 189572


Election

Donations

Example Usage (Made):

df <- get_disclosure_data(
  file_name = "Donations Made",
  group = "Donor", # OR "Candidate", "Third Party"
  type = "Election"
)

Sample Data (Made - Donor):

Event Donor Code Donor Name Donated To Donated To Date Of Gift Donated To Gift Value
2022 Federal election 45165 ANDREADIS JIM PRIESTLY Robert Anthony 19/04/2022 20000

Sample Data (Made - Candidate):

Event Return Type (Candidate/Senate Group) Name Donor Name Date Of Gift Gift Value
Fadden by-election Candidate DAVIS Marnie Laree Jonathan Cookson 16/06/2023 2000

Sample Data (Made - Third Party):

Event Third Party Code Third Party Name Client ID Name Date Of Donation Donation Value
2004 Federal Election S1820 AAMI 14657 FERGUSON Martin John 01/05/2004 3000

Example Usage (Received):

df <- get_disclosure_data(
  file_name = "Donations Received",
  group = "Donor", # OR "Third Party"
  type = "Election"
)

Sample Data (Received - Donor):

Event Donor Code Donor Name Gift From Name Gift From Date Of Gift Gift From Gift Value
2022 Federal election 44986 Bayside Community Voices MINAX URIEL PL 01/09/2020 80000

Sample Data (Received - Third Party):

Event Third Party Code Third Party Name Donor Id Donor Name Date Of Gift Gift Value
2004 Federal Election T886 Australian Conservation Foundation Inc (incl. SA Office) 3750 Bill Peine 18/12/2003 610000


Expenses

Example Usage:

df <- get_disclosure_data(
  file_name = "Expenses",
  group = "Candidate", # OR "Third Party"
  type = "Election"
)

Sample Data (Candidate):

Event Return Type (Candidate/Senate Group) Name Total Electoral Expenditure Broadcasting Cost Publishing Cost Display Ad Cost Direct Mailing Campaign Material Costs Opinion Polls
Cook by-election Candidate BROWN Natasha Jade 0 0 0 0 0 0 0

Sample Data (Candidate):

Event Third Party Code Third Party Name Broadcasting Cost Publishing Cost Display Ad Cost Direct Mailing Campaign Material Costs Opinion Polls
2004 Federal Election T983 ABARE 0 0 0 0 0 0


Returns

Example Usage (Returns):

df <- get_disclosure_data(
  file_name = "Returns",
  group = "Donor", # OR "Media"
  type = "Election"
)

Sample Data (Returns):

Event Donor Code Donor Name Total Donations Made Total Donations Received
2022 Federal election 45111 Andrew Killion 25000 0

Sample Data (Returns):

Event Media ID Name Business Name Return Type Total Amount
2004 Federal Election 5097 1 ART Artsound FM Broadcaster 0

Example Usage (Return Summary):

df <- get_disclosure_data(
  file_name = "Return Summary",
  group = "Candidate",
  type = "Election"
)

Sample Data (Return Summary):

Event Return Type (Candidate/Senate Group) Name Party ID Party Name Electorate Name Electorate State Nil Return Amendment No Total Gift Value Number Of Donors Total Electoral Expenditure Discretionary Benefits Received
Cook by-election Candidate BROWN Natasha Jade 28769 Animal Justice Party Cook NSW Y 0 0 0 0 0


Other

Example Usage (Discretionary Benefits):

df <- get_disclosure_data(
  file_name = "Discretionary Benefits",
  group = "Candidate",
  type = "Election"
)

Sample Data (Discretionary Benefits):

Event Return Type (Candidate/Senate Group) Name Discretionary Benefits Received From Date Amount
Eden-Monaro by-election Candidate STADTMILLER Matthew Peter Department of Infrastructure and Regional Development 05/09/2019 12100

Example Usage (Media Advertisement Details):

df <- get_disclosure_data(
  file_name = "Media Advertisement Details",
  group = "Other",
  type = "Election"
)

Sample Data (Media Advertisement Details):

Event Media ID Name Business Name Return Type Advertiser Advertiser Type Date Run Amount
2004 Federal Election 4134 100.3FM (2NEB-FM) New England Broadcasters Pty Ltd Broadcaster National Party of Australia - N.S.W. Party 27/09/2004 1689


Referendum

Donations

Example Usage (Made):

df <- get_disclosure_data(
  file_name = "Donations Made",
  group = "Donor",
  type = "Referendum"
)

Sample Data (Made):

Event Donor Name Donated to name Date Value
2023 Referendum Aarnja Limited Kimberley Land Council 24/08/2023 12:00:00 AM 1e+05

Example Usage (Received):

df <- get_disclosure_data(
  file_name = "Donations Received",
  group = "Referendum Entity",
  type = "Referendum"
)

Sample Data (Received):

Event Name Donor name Date Value
2023 Referendum Jabree Ltd MaiTri Foundation 27/06/2023 12:00:00 AM 54000

Returns

Example Usage:

df <- get_disclosure_data(
  file_name = "Returns",
  group = "Donor", # OR "Referendum Entity"
  type = "Referendum"
)

Sample Data (Donor):

Event Event ID Name ClientFileID ABN ACN Total donations made
2023 Referendum 29581 Aarnja Limited 47503 74159924900 NA 1e+05

Sample Data (Referendum Entity):

Event Event ID Name ClientFileID ABN ACN Total donations received Total number of donors Total referendum expenditure
2023 Referendum 29581 Advance Aus Ltd 47334 55628503702 NA 1320089 9400 10439901