A Development Expert in Bolgatanga in the Upper East Region, Reuben Jagri Binpori, has firmly rubbished findings of a recent survey that declared Garu District as the poorest District in the Upper East Region.
The survey which was conducted by the Ghana National Household Registry (GNHR), a monitoring database in Ghana, revealed that its 2018 survey has identified Garu District as the poorest District in the Upper East Region.
Under the chart records, Garu District was declared extreme poorest District in the region with 42.02 percent.
According to the survey, 184,125 households in the region were registered out of which 28 percent households were categorized as the most extremely poor, 37 percent were poor whereas 35 percent were non-poor households.
The data also revealed that only 15 percent of households in the Upper East Region had benefited from at least one of the social protection programmes.
However, Mr. Binpori (MPhil, BSc) in a statement critiquing the survey, described the GNHR data as superfluous, misleading, and are at variance with Ghana Living Standards Survey (GLSS) 7 and other existing evidence.
He also questioned why the need for the GNHR to conduct another survey when the GSS conducted its latest survey (GLSS 7) which was published in June 2019.
Mr. Binpori, therefore, suspects that a number of things would have gone amiss in the GNHR survey resulting in what he describes as awful outcomes.
BELOW IS THE FULL STATEMENT
DEBRIEFING OF THE GHANA NATIONAL HOUSEHOLD REGISTRY DATA FOR UPPER EAST REGION: OUTLIER OR TRUISM?
On Monday, the 20th of January 2020, the Ministry of Gender and Social Protection launched the Upper East Regional report of the Ghana National Household Registry (GNHR) survey in a Data dissemination workshop at Bolgatanga. The report declared the “Garu District as the extremely poorest of 42.02% as compared to the Bolgatanga Municipality with the least of 14. 97%” (a1radioonline.com). This report has received mixed feelings and apprehension among stakeholders (Municipal and District Assemblies), Development Partners, Non-Government Organisations, Researchers and Development Practitioners. For instance, the Garu DCE, Mr. Emmanuel Avoka covered his mouth in dismay after the announcement that his district was the poorest in the Upper East Region (a1radioonline.com)
As a development practitioner, I seek to have a reflection, an impartial review of the report and proffer suggestions on the way forward. I choose to do my critique on two important indicators that came out strongly at the workshop: Unemployment rate and Poverty levels in the region.
THE UNEMPLOYMENT ASSESSMENT.
The GNHR data indicated that 386,596 households representing about 68.5% in Upper East region were unemployed whilst the employed were 156,284 representing 31.5% (GNA, Jan 2020). That is quite curious, isn’t it? These figures from GNHR appear superfluous, misleading, and are at variance with GLSS 7 and other existing evidence.
Let me proceed by stating the position of the Ghana Statistical Service’s Ghana Living Standards Survey (GLSS) which is the body responsible for providing information on living conditions and also monitoring the welfare system in Ghana. It is a customized version of the Living Standards Measurement Study (LSMS), initiated in 1980 by the Policy Research Division of the World Bank. Over the past 30 years (since 1987), Ghana has conducted seven of living standard surveys. The GLSS has, therefore, been established as a permanent welfare monitoring tool in Ghana. So I beg to ask why the need to conduct another survey when the GSS with all its skills, experience and expertise in data collection and analysis [has published its data]? In any case, GSS has just conducted its latest survey (GLSS 7) which was published in June 2019.
According to (GLSS 7) in the Upper East region, among the economically active (the population of 15 years and older), 55.8% were employed, and 4.7% were unemployed while 39.6% were not in labour force (economically inactive). These results kind of reflect the reality on the ground to me as a development practitioner working in the region for about ten years. Therefore I am very hesitant to accept the GNHR conclusions that 31.5% were employed while a whopping 68.5% were not employed.
POVERTY INDICATORS IN THE REGION.
The GNHR report suggests to me that instead of the districts graduating households out of poverty, they are busily enrolling more households into the poverty academy. Although poverty is often discussed in terms of dollar amounts, quality of life is also part of the conversation. But extreme poverty is not only about low income; it is also about what people can or cannot afford. Living in poverty means a life of struggle and deprivation.
Historically, poverty has been calculated based on a person’s income and how much he or she can buy with that income. Before I go further, let me explain some key terms that will be used frequently in my review: International poverty line, Prevalence and Depth of Poverty.
International poverty line is the standard poverty line for measuring poverty globally. This line helps measure number of people in extreme poverty and also helps compare poverty levels among districts, regions and countries. Since 2015, the World Bank has pegged poverty as people living on 1.90 USD or less a day.
Prevalence is the proportion of the population below the poverty line. It is also termed Poverty incidence or poverty headcount.
Depth of Poverty is the gap between the poor people’s income and the poverty line expressed as percentage. It is also called the Poverty gap.
In determining both the Prevalence and Depth of poverty at any location, two nutritionally-based national poverty lines are required: The national extreme poverty line, and The national absolute poverty line.
The national extreme poverty line: This is the lower poverty line which is about GHS 2.17 per day per adult equivalent expenditure.
The national absolute poverty line: This is the upper poverty line which is about GHS 3.60 per day per adult equivalent expenditure
Having laid the foundation to Poverty Assessment, I now proceed to look at the existing evidence and compare them to the GNHR poverty indicators in the region.
Firstly, The Ghana Poverty and Inequality Report: Using the 6th Ghana Living Standards Survey (GLSS 6) acknowledged “progress in reducing poverty in Upper East appears to have been dramatic since 2006, declining from 72.9% in 2006 to 44.4% in 2013” (Cooke et al, 2016).
Secondly, The Feed the Future indicators for Upper East Region, Ghana 2015 District baseline estimates USAID METSS (Guvele et al, 2016) had the following revelations;
That, using the international poverty line (1.90 USD). The prevalence of poverty per day in Upper East Region was 25.8%. It ranged from 10.9% in Bawku Municipal to 39.6% in Kassena Nankana West District, while average poverty depth in the region was also 9.1%. The Garu district recorded 23.1% prevalence and 9.0% depth of poverty.
Also, the average prevalence of poverty at the national extreme poverty line (GHS 2.17 per day) was 33.1% while the regional average depth of poverty is 12.3%. The Garu district recorded 37.1% and 12.8% of prevalence and Depth of poverty respectively.
Again, using the national absolute poverty line (GHS3.60 daily per), the average Prevalence was 57.6 percent whilst the depth of poverty averaged 26.8 percent. However, this time around Garu district scored 67.1% prevalence and 29.7% depth of poverty. Remember that this measure is the upper poverty line so therefore you don’t expect many people to be there. In fact, it is just the direct opposite of the lower poverty line.
My take is that, the Poverty and Inequality report had predicted a progressive and consistent decline in poverty in the Upper East Region. And since 2016, a number of development interventions had taken place in the region targeted at food security and poverty reduction by government and its development partners. Mention is made of the USAID/ADVANCE program, Northern Rural Growth Program, SADA/NDA initiatives, the Planting for Food and Jobs, and other social interventions. So I am struggling to understand why poverty which is on a steady decline in the region has increased to those levels with specific emphasis on Garu district (42%) according GNHR report.
In conclusion, I reckon that a number of things would have gone amiss in this particular GNHR survey resulting in these awful outcomes. My suspicion includes the following;
Pre-field. I think some important steps before the data collection have been skipped. For example piloting (letting experts in development issues assess the questionnaire to correct wording, ordering, simplifying, amending certain questions) before pre-testing.
On field activities. During data collection, the ability of the enumerator to effectively translate the questions into the respondent’s local language is key in collecting quality data. Also, some respondent interests would have aroused when they began to here certain words like poverty, jobs, among others during the interview. These frequently occurring words stimulate them to respond to the questions in a way that makes them eligible for any anticipated or future program arising from the survey.
Finally, Post data analysis, it is always advisable to get the report reviewed by external independent Development practitioners, same way when you send an article for publication in a reputable journal for publication. This would enable the independent reviewers to critique the report and offer useful suggestions before it became public.
I suggest the following ways to effectively measure employment and poverty going forward;
Firstly, that future surveys should adapt the Standard labour force framework which is very useful in monitoring employment and labour market developments. There are also new indicators such as forms of work, potential labour force and labour underutilization which need to be measured. These new indicators offer us the opportunity to have more comprehensive measures of labour underutilization for monitoring labour markets and thus help improve policy decision making.
Secondly, future surveys could employ the Multidimensional poverty approach. I think it is more integrated and sustainable as compared to the poverty line. This approach acknowledges that poverty isn’t always about income. It also goes beyond income to measure a person’s healthcare, education, and living standards to determine poverty levels. Within the categories of health, education, and living standards. There are ten key indicators of multidimensional poverty that include nutrition, child mortality, years of schooling, school attendance, cooking fuel, sanitation, drinking water, electricity, housing, and assets. If a person is experiencing deprivation in three or more of these standards, then he or she is compositely poor.
The author is a Development Practitioner with emphasis on Agriculture, Food Security, Sustainable Livelihoods and Rural Development.
Reuben Jagri Binpori (MPhil, BSc)