Welcome to Kiel Institute Africa Monitor

The Africa Monitor is a joint effort of the research center for International Development and the Kiel Institute's Africa Initiative, to build an interactive platform that tracks leading economic indicators for 55 African economies, and provides economic analysis as well as analytical tools to monitor economic developments in Africa. The monitor consists of several building blocks accessible through this website:


Data Stories

A collection of short analytical pieces on selected topics concerning Africa's economic development and global linkages, combining data and visualizations in interactive notebook formats.

Dashboard

Web-Application to interactively visualize monitor data and build custom charts.

Data Portal

Portal to access monitor data interactively and download it in various standard formats.

Data Catalog

Provides an overview of the indicators and African countries available through the monitors database, and the sources from which data were collected. The database itself covers all 195 countries, but data for non-African countries is only accessible through the APIs.

APIs

High-speed access to the entire database through dedicated R and Python packages.




Copyright © 2022, Sebastian Krantz | Legal Notice (Kiel Institute)

Data Stories

Data stories are short analytical pieces combining data visualizations and analysis to expound a topic concerning economic development in Africa.


The New Urban Middle Class in Africa

By Sekou Metiki - December 14, 2022

This data story provides an overview of the African's middle class. It includes different measures of the middle class share and population for a set of 46 African countries from 2009 to 2020. Additionaly, it gives some projections of what will be the size of the middle class in Africa under different scenarios.


Africa's External Sector

By Alexander Ligai and Sebastian Krantz - December 13, 2022

This datastory provides an overview of Africa's external positions and flows with the rest of the world, as recorded in the current account and international investment position. It includes detailed analysis of trade flows, international reserves, and external debt.


Patterns of Innovation and Firm Growth in Nigeria

By Sophia Fehrenbacher - August 25, 2022

While the majority of Sub-Saharan African firms operate in resource constrained environments, analyzing innovation strategy among formally registered Nigerian firms shows that cooperation is a frequently used form of sourcing knowledge for innovative activities.


Africa's Integration into Global Value Chains

By Sebastian Krantz - June 28, 2022

This data story uses the EORA Global Supply Chain Database to map the structure of world production in value-added terms, with a specific emphasis on Africa's role as a provider and consumer of value-added, and as an emerging participant in Global Value Chains.


Logistics, Public Infrastructure and the Business Environment in Africa

By Sebastian Krantz - May 30, 2022

This data story provides a detailed analysis of logistic performance and the business environment across African economies. A particular focus is laid on the development of public infrastructure and its role in enhancing logistics and economic growth.

Copyright © 2022, Sebastian Krantz | Legal Notice (Kiel Institute)

Select Data to Visualize





Interactive Correlation Matrix

Correlation Matrix


Download Data





Download

Application Programming Interfaces (APIs)


The R package africamonitor provides high-speed access to the Africa Monitor Database, which provides >700 time series at different frequencies, with high coverage of African economies, for 195 countries.

The API allows bulk download of the entire database or query of individual series. The functions am_sources() and am_series(), as well as the am_countries table provide information about the available data, analogous to the 'Data Catalog' tab. Country and series codes from these tables are needed to query data using the am_data() function. An additional am_entities table records country membership in various regional entities. The API is fully documented on the R help pages, calling help(africamonitor) after installation. A small demonstration is provided below.

Installation

The package can be installed from the R console by executing the following line of R code:

install.packages('africamonitor')

Example Usage

The following code downloads real GDP growth and Inflation for Uganda, Tanzania, Rwanda, and Kenya from 2000 onwards.


                
The africamonitor package also provides functions am_pivot_longer() and am_pivot_wider() to reshape data from the API.


                
The format of the data can also be set directly in the API call, the default option in am_data() is wide = TRUE.

The database stores data at all frequencies in a 'Date' column. The function am_expand_date() can be used to generate additional identifiers from the date for series at higher frequency. This function can also be invoked directly in the API call with option expand.date = TRUE.


                
The data is returned as a 'data.table' in R, and thus allows for easy further manipulation, such as computing rolling averages.


              

The Python package africamonitor provides high-speed access to the Africa Monitor Database, which provides >700 time series at different frequencies, with high coverage of African economies, for 195 countries.

The API allows bulk download of the entire database or query of individual series. The functions am.sources() and am.series(), as well as the am.countries() table provide information about the available data, analogous to the 'Data Catalog' tab. Country and series codes from these tables are needed to query data using the am.data() function. An additional am.entities() table records country membership in various regional entities. The API is fully documented on the Python help pages, calling help(am) after installation. A small demonstration is provided below.

Installation

The package can be installed from the Terminal using:

pip install africamonitor

Example Usage

The following code downloads real GDP growth and Inflation for Uganda, Tanzania, Rwanda, and Kenya from 2000 onwards.


                
The africamonitor package also provides functions am.pivot_longer() and am.pivot_wider() to reshape data from the API.


                
The format of the data can also be set directly in the API call, the default option in am.data() is wide = True.

The database stores data at all frequencies in a 'Date' column. The function am.expand_date() can be used to generate additional identifiers from the date for series at higher frequency. This function can also be invoked directly in the API call with option expand_date = True.


                
The data is returned as a Polars DataFrame, and thus allows for easy further manipulation with Polars, such as computing rolling averages.


              
Copyright © 2022, Sebastian Krantz | Legal Notice (Kiel Institute)

About

The Africa Monitor provides research briefs (data stories), custom visualizations, and access to public macroeconomic data on Africa, allowing you to track macroeconomic developments across the continent. Data is collected from several public sources (mostly from the IMF and the World Bank) and updated once a month. The data is serviced to the monitor from a database hosted at the Kiel Institute for the World Economy. API packages for R and Python allow free high-speed access to the entire database.

Technical Details

This website was built using the shiny web-application framework in R, complemented with some custom HTML and CSS elements.
Author: Sebastian Krantz.

Bug Reports

Any issues with this website, the database, or the R and Python API packages, can be reported on GitHub (preferred), or by sending an e-mail to sebastian.krantz@ifw-kiel.de

Development Log

  • 13th January 2022
    Added an indicator of market size, calculated as value added + imports - exports, and data from the UN National Accounts Main Aggregates Database providing a breakdown of gross value added into 7 sectors in constant 2015 USD. Both additions resulted from conversations with Prof. Philipp von Carlowitz regarding indicators relevant for firms aspiring engagement in Africa.
  • 14th December 2022
    Added 2 new data stories: one on the African Middle Class - by Sekou Metiki, and one on Africa's External Sector - by Alexander Ligai and Sebastian Krantz.
  • 30th November 2022
    Added a Python API package, available through PyPi i.e. via pip install africamonitor. Furthermore, the database was expanded to include data for all countries in the world (193 UN Members, Western Sahara and Taiwan) where available. The API packages for R and Python by default only query data for Africa, but now include an additional countries_wld dataset with ISO3 codes and descriptions of all 195 countires. Users can use these codes to query data for other countries using the API packages.
  • 14th October 2022
    Added aggregate bilateral direct and portfolio investement data from IMF Coordindate Direct and Portfolio Investment Surveys (CDIS and CPIS), and increased the number of bilateral trading partners obtained from IMF Direction of Trade Statistics (DOT). The R package was also updated, with minor improvements to the functions am_pivot_wider() and am_pivot_longer(). See NEWS.
  • 25th August 2022
    Sophia Fehrenbacher contributed a data story on Patterns of Innovation and Firm Growth in Nigeria.