GDP by Activity: Import Duties

Data as of 30 Sept 2022, 23:59

Amount in RM mil; real GDP is produced with reference to a base of 2015.

How is this data produced?

GDP is the total value of all goods and services produced in a certain period after deducting the cost of goods and services used up in the process of production. This value is before deducting the allowances for consumption of fixed capital i.e. the sum of value added of resident producer in producer's price plus import duties. GDP is equivalent to expenditure on the GDP (in purchaser's price) i.e. the sum of all components of final expenditure on goods and services less imports of goods and services.

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

Quarterly and annual estimates are reconciled where necessary. In situation, whereby the annual and quarterly accounts uses the same data sources, no reconciliation of the quarterly need to be made to fit the annual accounts.


Dataset description

Laporan ini merangkumi anggaran statistik akaun negara suku tahunan mengikut aktiviti ekonomi dan jenis perbelanjaan pada harga semasa dan harga malar tahun asas 2015.

Variable definitions
  • GDP by Activity: Import Duties
  • Series Type
  • Date
  • GDP (Gross Domestic Product)
  • GDP by Activity: Agriculture
  • GDP by Activity: Mining
  • GDP by Activity: Manufacturing
  • GDP by Activity: Construction
  • GDP by Activity: Services
  • GDP by Expenditure: Private Consumption
  • GDP by Expenditure: Government Spending
  • GDP by Expenditure: GFCF
  • GDP by Expenditure: Exports
  • GDP by Expenditure: Imports
  • GDP by Expenditure: Net Exports
  • GDP by Expenditure: Change in Inventories
Last updated

23 Dec 2022, 12:00

Next update

31 Jan 2023, 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 human-readable copy of the license is available Here.



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)

Department of Statistics Malaysia

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