Home Economy How Realistic is the 2022 Population Census: A Critical Analysis

How Realistic is the 2022 Population Census: A Critical Analysis

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By: Teakon J. Williams, DBA, PMP

Liberia’s population has grown incrementally from year to year. Since 1962, Liberia’s population has increased from 1.2 million in 1962 to 5.2 million in 2022, a 333% growth. Population increase is driven by a series of factors that includes a reduction in the death rate, an increase in the birth rate, migration, lack of family planning, and pull factors (job opportunities, educational pursuit, etc.).

Mahtta et al. (2022) asserted that population growth in developing countries is mainly in urban areas that foster economic development.

However, the 2022 population census in Liberia showed high population growth for counties experiencing low economic activities, limited employment opportunities, little access to health, high prices due to limited road access, little access to markets, etc. This situation brings into question the credibility of the entire Census Process.

Fig. 1: Liberia’s Population Trend from 1962 to 2022

In light of the increased trend in the population of Libera over the years, the publication of the 2022 Population Census reflecting an increased population was never going to be a surprise.

However, the correlation of values with United Nations Population Fund – UNFPA (World Population Dashboard -Liberia | United Nations Population Fund (unfpa.org), Worldometer (Liberia Population (2023) – Worldometer (worldometers.info)), Population Pyramid (Population of Liberia 2022 – PopulationPyramid.net), and World Population Review (Liberia Population 2023 (Live) (worldpopulationreview.com)) all at 5.3 million (compared to 5.2 million from LISGIS), leaves one to wonder whether survey personnel did not simulate the new population data based on the population growth rate (as opposed to actual counting) by LISGIS.

Table 1 displayed a simple simulation of the population value from 2008 to 2022 at a 3% population growth rate.

Table 1: Population Growth Rate Simulation at 3%
Year Annual Growth Rate Total Population
At 3% you get
2008 3,489,072
2009 104,672.16 3,593,744.16
2010 107,812.32 3,701,556.48
2011 111,046.69 3,812,603.18
2012 114,378.10 3,926,981.27
2013 117,809.44 4,044,790.71
2014 121,343.72 4,166,134.43
2015 124,984.03 4,291,118.47
2016 128,733.55 4,419,852.02
2017 132,595.56 4,552,447.58
2018 136,573.43 4,689,021.01
2019 140,670.63 4,829,691.64
2020 144,890.75 4,974,582.39
2021 149,237.47 5,123,819.86
2022 153,714.60 5,277,534.46

The total population for 2022 as depicted in Table 1, is similar to those provided by LISGIS. A critical analysis of population variance of the 15 counties of three different censuses (1984, 2008, and 2022) shows some anomalies in value in some counties. Before delving into details, figure 2, displayed a graphical representation of population trends per county over the three censuses.

Fig. 2: Liberia’s Population Trend – 1984, 2008, and 2022

An analysis of variance showed a steady trend among Grand Bassa, Grand Cape Mount, Nimba, Rivercess, and Sinoe. However, the rapid increase in population for Bomi, Bong, Grand Gedeh, Grand Kru, Margibi, and River Gee is unprecedented and calls for serious concern. What are the pull factors that drove this rapid increase? A critical look at these counties showed that they experienced high absolute poverty, food poverty, and extreme poverty (MFDP, 2018). These indicators are all push factors adverse to high population growth. Moreover, most of these counties (Grand Gedeh, River Gee, and Grand Kru) as part of the southeastern region of Liberia, are the highest users of contraceptives at 22% (LDHS, 2013). The mere fact that the reported counties with the least opportunities for migration, with little attraction for domicile, and with the highest use of contraceptives, will attract high population growth creates room for more questioning of the process.

LISGIS needs to explain this variation in these numbers and the factors that inform the result. Data are not conflicted; they speak to each other. The report on contraceptive use, for example, is not speaking to the result provided by the LISGIS. Figure 3 further depicts a population change comparison from 1984 to 2008 (24 years) and 2008 to 2022 (14 years).

Fig. 3: Population Change (1984 to 2008) and (2008 – 2022)
Bomi County’s population increase was 15,616 between 1984 and 2008 and 51,632 between 2008 and 2022. Bomi’s multi-dimensional poverty index value of 79.1 is above the national average of 71.2% (MFDP, 2018). This figure connotes that almost 80% of the people of Bomi are multi-dimensionally poor and deprived of basic necessities. Similarly, Grand Kru, in which the population increased from -5,685 (indicating negative population growth) from 1984 to 2008 dramatically increased in population by 52,236 (91%) despite being the most deprived and poverty-ridden county in Liberia at 90.6% (incidence of multi-dimensional poverty) (MFDP, 2018). This analysis is the same with Grand Gedeh and River Gee with the incidence of multidimensional poverty of 74.9% and 81.4% respectively (MFDP, 2018).
Conversely, Montserrado, Nimba, and Lofa counties, with many pull factors (agriculture activities, mining activities, better road access, access to jobs, etc.) showed marginal increases between 1984 and 2008 and 2008 to 2022. For example, Montserrado had a population differential of 653,728 between 1984 and 2008 and 776,108 between 2008 and 2022. Moreover, the difference between the variances of the two periods (1984-2008 & 2008-2022) for Nimba is just 1,285. Similarly, the difference between the two periods for Lofa is 26,390. In a nutshell, there seems to be no correlation between counties with high pull factors and population increase. The reverse seems to be true.

Census information affects policies in a country-where do we build more schools, which county has more representatives, where do we build more roads, etc.? To make sound policy, decision-makers need information that is reliable and valid. Unfortunately, the preliminary census data reeks of inconsistencies. No wonder skeptics are wondering whether the data was manipulated to give certain regions competitive advantage for political reasons or data was just provided based on the UNFPA projection of the population. Even the UNFPA projection is based on the growth rate. Assuming we were just collating the data from the growth rate, the percentage distribution would not have been fluctuating and unparallel. There are queries that can be run to inform statistical data, these queries, when run, cannot validate the veracity or authenticity of the data provided by LISGIS. Statistics is not about politics. Liberia is a gullible society where academicians are seen as nothing but mediocrity is awarded. We need reliable information to make sound decisions. As it stands, there are valid reasons to question the preliminary findings.


Liberia Demographic Health Survey (LDHS) (2013). LDHS 2013 .pdf
Liberia Institute of Statistics and Geo-Information Services (LISGIS) (2022). 2022 national population and housing census. LISGIS OFFICIAL
Liberia Population 2023 (Live) (worldpopulationreview.com)
Liberia Population (2023) – Worldometer (worldometers.info)
Mahtta, R., Fragkias, M., Güneralp, B., Mahendra, A., Reba, M., Wentz, E. & Seto, K. (2022). Urban land expansion: The role of population and economic growth for 300+ cities. Nature Partner Journal (NPJ), 2(5). https://doi.org/10.1038/s42949-022-00048-y.
Ministry of Finance and Development Planning (MFDP) (2018). Pro-Poor Agenda for Prosperity and Development.
Pro-Poor Agenda for Prosperity and Development(PAPD) (mfdp.gov.lr)
PopulationPyramid.net (1950-2100). Liberia Population 1962.
Population of Liberia 1962 – PopulationPyramid.net
UNFPA (2022). World population dashboard: Liberia.
World Population Dashboard -Liberia | United Nations Population Fund (unfpa.org)
World Population Dashboard -Liberia | United Nations Population Fund (unfpa.org)

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