A Guide to the AEC's Disclosure Datasets

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