Question Why has not more work been completed on this issue given its current significance?
Answer: In the mid-1960s and late 1960s both FAO and the reports of the first United Nations Conference on Trade & Development (UNCTAD) covered a lot of these issues linked to producer cooperatives including the early proposals on fair trade linked to more processing being completed on the exporting country side. This was resisted by importing countries and we now see where this ended up.
Our own ventures into this area followed an asessment of the FAO and UNCTAD work (McNeill, H. W., "Defects of Commodity Control Schemes", School of Agriculture, University of Cambridge, 1967) and then later with the impact of slumpflation on developing countries, starting out in 1975. So the emphasis became a concentration on real incomes, once this work defined the production, accessibility and consumption model to replace the aggregate demand model which upholds the logic of monetary policy for the new fiat currency system.
Living income is simply the lowest real income that provides the ability of families to purchase their basic essential needs at prevailing prices. This is not a new concept. It has been applied using the FAO Food Balance Sheets which linked consumption profiles to the nutritive value and balance of different foods, household budget surveys that recorded prices paid and the disposable incomes of families from all sources. This has been applied for something like 50 years although today it is difficult to find the original FAO Food Balance Sheets.
Question Does big data have any contribution to make here? Maybe combined with dashboards?
The big data concept has been linked to data warehouses and the wider use of administrative data (data from regulatory and other government-related data gathering activities). We have never considered this to be a sound idea even although it is promoted by such agencies as EuroStat. Regulatotry data is collected for a different reason to say census data and census data is usually a decade interval process. Much regulatory data is unreliable as a result of intentional manipulation by providers or even governments themselves. There is no substitute, in terms of quality of data, for community-based stakeholder involvement in the collection process as long as adequate safeguards are taken with regard to protection of inividual family data sets. In terms of anonymity, the norm tends to be to combine at least 5 separate family data sets into a single representative set for a specific income category.
Dashboards are a convenient way of representing data sets in summary format and this has emerged from what is now referred to as analytics i.e. standard diagnostic report summaries. If dashboard indicators are based on big data their utility for real income estimates is probably doubtful but on detailed community-based annual data sets, they are likely to be of utility.
Question Although weather and market prices are significant sources of instability for small farmer incomes. Are you saying monetary policy is another source of instability?
For lower income segments the baseline stability of the purchasing power of the currency is important in maintaining real income levels. Depressed consumption resulting from depressed incomes is further exacerbated by a monetary policy that considers a 2% annual inflation to be a policy target. No matter what is happening to the weather and market prices, this is guaranteed to lower purchasing power by 18% each decade, on average. This is why increasing numbers of lower income segments are becoming destitute in high and low income economies.