# Australia House Prices, Inflation and Wage Growth (`scrapemint/australia-economic-data`) Actor

Mean residential dwelling price by state, consumer price inflation and wage growth from the Australian Bureau of Statistics, quarterly with history. Keyless, no browser and no proxy.

- **URL**: https://apify.com/scrapemint/australia-economic-data.md
- **Developed by:** [Ken M](https://apify.com/scrapemint) (community)
- **Categories:** Business, Real estate
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$4.00 / 1,000 data rows

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Australia House Prices, Inflation and Wage Growth

Mean residential dwelling price for Australia and every state and territory, plus consumer price inflation and wage growth, straight from the Australian Bureau of Statistics.

Official government statistics, quarterly, with history.

No login, no API key, no proxy.

### What you get

One row per series per region per period:

```json
{
  "dataset": "dwellings",
  "measure": "Mean price of residential dwellings",
  "region": "New South Wales",
  "period": "2026-Q1",
  "value": 1324800,
  "rawValue": 1324.8,
  "unitMultiplier": "Thousands",
  "unit": "Australian Dollars",
  "frequency": "Quarterly",
  "isStale": false
}
```

`value` is the figure in real units. The ABS publishes magnitude separately, so a mean price arrives as `1324.8` with a multiplier of `Thousands`; both the scaled figure and the raw one are on the row so you can check the arithmetic.

### Datasets

| Key | Series | Source |
| --- | --- | --- |
| `dwellings` | Mean price of residential dwellings, and dwelling counts | RES\_DWELL\_ST |
| `inflation` | Consumer price index, all groups | CPI |
| `wages` | Wage price index, total hourly rates including bonuses | WPI |

### Input

| Field | Description |
| --- | --- |
| `datasets` | Which series to pull |
| `regions` | Names to match, e.g. `["Australia"]` or `["New South Wales","Victoria"]` |
| `periods` | How many recent quarters per series |
| `allMeasures` | Return every measure rather than the headline one |
| `maxRows` | Total rows returned (default 200) |

### Examples

Latest national figures:

```json
{ "datasets": ["dwellings","inflation","wages"], "regions": ["Australia"] }
```

Five years of dwelling prices by state:

```json
{ "datasets": ["dwellings"], "regions": ["New South Wales","Victoria","Queensland"], "periods": 20 }
```

### Things worth knowing

Each dataset returns its headline measure by default. Without that filter the dwellings series mixes mean price with total dwelling stock value, which runs into the trillions and is not a comparable number. Set `allMeasures` if you want everything.

Region matching prefers an exact name. This matters in Australia, where asking for `Australia` would otherwise also return South Australia and Western Australia.

Mean price is published at state and territory level only, not by city or postcode.

Every row carries `isStale`, which flags a series whose newest period has fallen well behind its publication schedule. The ABS leaves discontinued datasets online and they keep answering normally, so this is how a retired series announces itself rather than quietly looking current.

A suppressed or unavailable observation comes back as `null` and never as a zero.

### Who it's for

Property investors comparing Australian states, mortgage and proptech dashboards, economists and journalists tracking prices against wages, and anyone needing Australian figures without a subscription terminal. Pairs with **UK House Prices**, **Europe House Prices**, **Canada Economic Data** and **US Rent and Home Price Index**.

### Pricing

Pay per data row. The first 2 rows of every run are free so you can validate the output before you pay.

# Actor input Schema

## `datasets` (type: `array`):

Which series to pull. Choices: dwellings (mean residential dwelling price and dwelling counts), inflation (consumer price index), wages (wage price index).

## `regions` (type: `array`):

Names to match, e.g. \["Australia"], \["New South Wales","Victoria"]. Matching is partial. Leave empty for every region the dataset publishes.

## `periods` (type: `integer`):

How many recent periods per series. These datasets are quarterly.

## `allMeasures` (type: `boolean`):

By default each dataset returns its headline measure only, for example mean dwelling price rather than total dwelling stock value. Turn this on to return every measure, which mixes very different units on the same output.

## `maxRows` (type: `integer`):

Total rows to return.

## Actor input object example

```json
{
  "datasets": [
    "dwellings"
  ],
  "regions": [
    "New South Wales",
    "Queensland"
  ],
  "periods": 1,
  "allMeasures": false,
  "maxRows": 200
}
```

# Actor output Schema

## `rows` (type: `string`):

Mean residential dwelling price, consumer price inflation and wage growth by region and quarter, with the raw observation alongside the scaled value.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "datasets": [
        "dwellings",
        "inflation",
        "wages"
    ],
    "regions": [
        "Australia"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapemint/australia-economic-data").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "datasets": [
        "dwellings",
        "inflation",
        "wages",
    ],
    "regions": ["Australia"],
}

# Run the Actor and wait for it to finish
run = client.actor("scrapemint/australia-economic-data").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "datasets": [
    "dwellings",
    "inflation",
    "wages"
  ],
  "regions": [
    "Australia"
  ]
}' |
apify call scrapemint/australia-economic-data --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapemint/australia-economic-data"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/a1PnEIWYd8ibBWc8H/builds/WRdpN4GChWSf1xcNP/openapi.json