Adequate data had a need to capture true impact of Covid-19
The speed at which Covid-19 has spread around the world is unforeseen and its own impact regarding health problems, lack of enough health services and death was immediately evident.
Bangladesh, like a great many other countries, attempted to support the pandemic through shutdown of normal monetary activities and public life during April-May. Then your country experienced the gradual reopening of economical activities.
The economic crisis following a shutdown of activities included lack of income and employment.
The government taken care of immediately the issues with announcements of transfer programmes for low-income groups and incentive packages for financial activities. Implementation exercise of the policies revealed that there surely is inadequate data for identifying the mark groups.
The impact of the shutdown and related financial crisis has drawn attention of researchers and there have been many studies on the subject. These were predicated on secondary data and projections using past data.
These could be useful for short-term policy interventions when there is absolutely no scope of carrying out national sample surveys.
However, the limitations of these estimates are obvious. Many parameters have changed through the pandemic in fact it is difficult to take those into consideration.
Estimates of poverty incidence through the immediate aftermath of the pandemic have already been attempted and they are predicated on existing data and various assumptions. The study studies and media reports have highlighted severe undesireable effects of Covid-19 on employment and poverty.
Many organisations also have conducted "rapid surveys" for making estimates of poverty and income of poor households. Rapid surveys can yield quick results and so are useful for short-term policy adoption, but cannot go in-depth in to the details of source of income, kind of employment etc. The rapid surveys cannot reach a nationally representative random sample.
Therefore immediate steps must generate adequate data to capture the details of the downturn of the economy and the phases of its recovery and the processes by which these cycles took place in order that a national picture emerges. Otherwise valuable information will be lost forever. Such information may be relevant not only for current policy making but also as historical data, which may guide future generations within their fight against financial and social downturn, in particular when induced by pandemics like the present one.
The next discussion highlights the necessity for generation of data on employment and poverty for an effective assessment of short-and medium-term impact of Covid-19. Most of it is addressed to the national statistical organisation (BBS) but will also be relevant for other organisations who take up similar surveys.
The problems raised here can even be relevant for surveys covering effect on other socio-economic areas of households, activities of enterprises, etc. The next discussion targets data on a few monetary and social dimensions only and it does not form a thorough list.
The concerns raised here could be relevant for other developing countries, which don't have in place a normal quarterly/annual data generation system. High income countries accumulate monthly/quarterly and annual data on key financial indicators, including unemployment, and thus the impact of Covid-19 unfolds continuously.
Survey of labour force, employment and unemployment
The Labour Force Survey (LFS) of Bangladesh Bureau of Statistics (BBS) covers pretty much a comprehensive group of issues, which are believed essential to understand the functioning of the labour market. However the coverage is sufficient only in a normal situation and cannot capture the result of a pandemic like the present one.
Therefore you will find a dependence on reviewing the problems covered plus the methodology that is employed in the survey. Following are some areas of labour market, which needs attention.
Loss of employment connected with Covid-19 may take various forms like work sharing and low hours of work resulting in underemployment, low productivity per person, termination from jobs, momentary loss of job, lower wage, deferred wage, denial of other benefits as provided in the country's labour law.
Contracts regarding paid employment could be formal and written, informal and unwritten or might take in-between forms and after and during Covid-19, the form of contract may change to worse.
Lack of employment and rising unemployment will probably have a discouraging influence on labour force entrants, who may opt out of the labour force and join the category NEET (not in employment education and training).
The discouraged workforce can pose a challenge not merely as a lost prospect of economic activities but can also cause social problems.
LFS adheres to definitions supplied by ILO. That is useful for international comparison. But this may often lead to misleading interpretation in national contexts. To fully capture the impact of pandemic, data collection efforts could be meaningful if they are based on concepts which are suitable in the socio-cultural context of the country. Therefore, modification of a number of the definitions should be considered.
Timing of the surveys: The most recent round of LFS has been completed in June 2017. Another one, regardless if starts early next year means an interval of 3.5 years. Thus, an analysis of the impact of Covid-19 will miss out information on both ends.
There is no updated information on 2018, 2019, which could form the bottom year for comparison. You have to depend on the assumption of continuation of parameters of 2017 and make projection for 2019 as the bottom year.
The survey will commence twelve months after the beginning of the pandemic. This will be beneficial to capture the medium-term impact but cannot capture the impact and the processes connected with it in the original peak pandemic period (hopefully you will have no second wave) and the federal government responses during those months. To comprehend the procedure of change of the labour market in the short run and its own comparison with the medium term, the survey must rely upon memory recall.
Appropriate questions ought to be included in the survey to generate data through such recall. It'll be a complex matter and can require a relatively good details including recall of three points of time: immediately before Covid-19, during April-June 2020 and during the survey in 2021.
One must balance the usefulness of detailed data generation through recall with the likely decline in quality of such data.
Poverty and household income data
Over the last three decades, Bangladesh has been assessing poverty incidence based on data of Household Income and Expenditure Survey (HIES). This is normally conducted at 4/5 years of intervals.
The most recent round has been completed in 2016. The next round hasn't yet started and could be expected to commence in 2021. In the standard situation this serves the objective of poverty assessment and analysis of the causes of the changes.
However, with the spread of coronavirus, there's been evidence from rapid surveys that poverty has accentuated. But these surveys aren't predicated on nationally representative samples. Therefore, these can't be weighed against the national survey results. Then how would one reach national estimates of poverty through the various phases of the pandemic? HIES poverty estimates use detailed information of consumption of individual foods and other consumption items throughout a short reference period. It will not be possible to collect such details through recall method for periods three to six months earlier. The method of obtaining idea about consumption standard or poverty during the pandemic isn't thus, quite straightforward.
You can resort to qualitative indicators which might be easily recalled or self assessment of the extent of decline of consumption. Furthermore, there can be recall based data on consumption of major items/groups of items. Questions on the extent of decline/increase in consumption of the items might provide a basis of comparison regardless if it does not provide estimates of poverty predicated on standard methodology. Indicators found in the international multi-indicator poverty assessment method could be considered in this context.
Organisational issues
A comprehensive arrange for data generation on "Pandemic and its own effect on health, economy and society" should be adopted. The major tasks will of course be with the national statistical organisation, BBS. Nonetheless, large surveys might not have the ability to go sufficiently in-depth and for that reason cannot be an alternative for small and micro surveys.
The author is the executive chairperson of the Centre for Development and Employment Research and a former person in the board of directors of Bangladesh Bank.
