Annual Real GDP by Economic Sector

Data as of 2023

Annual gross domestic product (GDP) at constant 2015 prices for the 5 main economic sectors.

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Real GDP

How is this data produced?

Gross domestic product (GDP) is the total value of goods and services produced within that year, after deducting the cost of goods and services used in production, but before deducting the consumption of fixed capital. In Malaysia, GDP is estimated in compliance with the System of National Accounts (2008).

In general, GDP can be measured via 3 approaches, namely production, expenditure, and income. Because the measurement employs double entry accounting, the overall value must be the same across all 3 approaches. However, the different approaches allow GDP to be analysed in different ways. The GDP estimates in this dataset were produced using the production method (also known as the value added approach), which allows insight into the specific contribution of each economic sector. For that reason, the results of the production approach are often referenced in economic writing as supply-side GDP. The values were measured at constant 2015 prices, i.e. with price effects removed relative to a base year (2015 = 100). For a full description of the methodology, please refer to the Technical Notes.

What caveats I should bear in mind when using this data?

Values for 2022 and 2023 may be revised in future releases. Furthermore, the sum of GDP for all sectors may not always equal to the values for overall GDP because of independent rounding to one decimal place. However, the differences are not obvious.

Publication(s) using this data

Gross Domestic Product, 2023, the latest edition of the annual GDP statistics published by DOSM. OpenDOSM also features a dashboard on GDP which enables you to explore Malaysia's GDP data interactively.


Dataset description

Annual gross domestic product (GDP) at constant 2015 prices for the 5 main economic sectors.

Variable definitions
  • Series Type
  • Date
  • Economic Sector
  • Value
Last updated:

17 May 2024, 12:00

Next update:

16 May 2025, 12:00

Data source(s)
  • DOSM

This data is made open under the Creative Commons Attribution 4.0 International License (CC BY 4.0). A copy of the license is available Here.


Full Dataset (CSV)

Full Dataset (CSV)

Recommended for individuals seeking an Excel-friendly format.


Full Dataset (Parquet)

Full Dataset (Parquet)

Recommended for data scientists seeking to work with data via code.



Connect directly to the data with Python.

# If not already installed, do: pip install pandas fastparquet import pandas as pd URL_DATA = '' df = pd.read_parquet(URL_DATA) if 'date' in df.columns: df['date'] = pd.to_datetime(df['date']) print(df)

Sample OpenAPI query

The following code is an example of how to make an API query to retrieve the data catalogue mentioned above. You can use different programming languages by switching the code accordingly. For a complete guide on possible query parameters and syntax, please refer to the official Open API Documentation.

import requests import pprint url = "" response_json = requests.get(url=url).json() pprint.pprint(response_json)