Giuseppe Sandro Mela.
Dell’Onu e della Fao ci siamo già interessati.
World Humanitarian Summit. Disertato da tutti.
Torniamo sull’argomento per un aspetto che interessa tutti noi: l’ONU e la Fao infatti ce le stiamo mantenendo con le tasse. Un sintetico prologo è tuttavia necessario quanto istruttivo.
Ogni scienza definisce un certo numero di “grandezze fondamentali“. Per esempio, in fisica sono tali gli intervalli di tempo, la lunghezza e la massa: esse sono sette nel Sistema Internazionale.
Da queste grandezze fondamentali si ottengono le “grandezze derivate“. Per esempio, la velocità altro non è che la distanza percorsa diviso il tempo impiegato. La sua misura è espressa in metri / secondi, metri al secondo.
Tutte le misure godono la caratteristica di avere delle dimensioni.
Non così le costanti, quali per esempio pi greco (π), che è un numero puro, un irrazionale con infiniti decimali. Utilizzando infatti la definizione della geometria piana, π è il rapporto tra la misura della lunghezza della circonferenza di un cerchio e la misura del suo diametro. Le dimensioni “lunghezza” a numeratore ed a denominatore si elidono.
Sono i ricordi di terza elementare: avrebbero potuto essere espressi in termini ben più rigorosi, ma questo è ciò che basta.
Questi ricordi tornano utili per comprendere come ogni numero riportato sia espresso sia dal numero in senso stretto sia dalle sue dimensioni.
Come corollario ne deriva come siano trattabili, ovvero anche solo comparabili, numeri che abbia identiche dimensioni ovvero definizioni.
Un esempio? Non è lecito sommare sette pere con sette pesche. Al massimo, la “somma” potrebbe essere quattordici “frutti“.
Ma dimensioni e definizioni hanno importanza logica non solo per i dati esprimibili tramite dei numeri, bensì anche per ogni altra entità logica.
Non si inquieti il Lettore: nessuno intende sminuirne le sue capacità intellettive.
Lo si vorrebbe soltanto mettere in guardia: guardare sempre le dimensioni e le definizioni prima di eseguire alcuna operazione su numeri ed enunciati. A valutare sempre con attenzione le definizioni dei termini usati. Se non altro, per cercare di capirci qualcosa.
Facciamo un esempio, che piglieremo dall’Istat.
Tutti parlano a destra e manca di “occupati” e di disoccupati”, ma quasi nessuno sa in realtà a cosa esattamente si riferisca.
«Occupati: comprendono le persone di 15 anni e più che nella settimana di riferimento:
– hanno svolto almeno un’ora di lavoro in una qualsiasi attività che preveda un corrispettivo monetario o in natura;
– hanno svolto almeno un’ora di lavoro non retribuito nella ditta di un familiare nella quale collaborano abitualmente;
– sono assenti dal lavoro (ad esempio, per ferie o malattia). I dipendenti assenti dal lavoro sono considerati occupati se l’assenza non supera tre mesi, oppure se durante l’assenza continuano a percepire almeno il 50% della retribuzione. Gli indipendenti assenti dal lavoro, ad eccezione dei coadiuvanti familiari, sono considerati occupati se, durante il periodo di assenza, mantengono l’attività. I coadiuvanti familiari sono considerati occupati se l’assenza non supera tre mesi.»
« Disoccupati: comprendono le persone non occupate tra i 15 e i 74 anni che:
– hanno effettuato almeno un’azione attiva di ricerca di lavoro nelle quattro settimane che precedono la settimana di riferimento e sono disponibili a lavorare (o ad avviare un’attività autonoma) entro le due settimane successive;
– oppure, inizieranno un lavoro entro tre mesi dalla settimana di riferimento e sarebbero disponibili a lavorare (o ad avviare un’attività autonoma) entro le due settimane successive, qualora fosse possibile anticipare l’inizio del lavoro.»
Definire “occupata” una persona che abbia svolto almeno un’ora di lavoro lascia già perplessi: usualmente si devono sgobbare molte ore per mettere la galletta sul tavolo. Ma il bello è che questa definizione pudicamente omette il “quando” si sarebbe dovuto lavorare almeno un’ora per essere considerati occupati.
Nei tempi felici in cui si stava peggio, si definiva “occupato” chi otteneva un salario tale da mantenere una famiglia. Ma erano tempi bui ed oscuri.
Poi si introdusse il concetto di ha “svolto almeno un’ora di lavoro” nella settimana antecedente il rilevamento. Non semplice mantenersi e mantenere la famiglia.
Ma l’etica del momento ha meglio definito lo “occupato” come chi ha “svolto almeno un’ora di lavoro” nel mese antecedente il rilevamento. Ecco invero una definizione molto lassa, almeno a parere di molti, ma pur tuttavia politicamente corretta.
Manca a dirlo, l’Istat riporta ad ogni cambio di definizione significativi incrementi degli occupati.
Se l’Istat definisse come “occupata” quella persona in grado di respirare, l’occupazione sarebbe il 100% della popolazione, lattanti inclusi. Ed il Governo sarebbe incensato.
Discorso analogo potrebbe essere fatto per i disoccupati. È sufficiente cambiarne la definizione ed il gioco è fatto. Nessun disoccupato per merito del Governo che ha cambiato le definizioni.
Tanto per essere chiari, questa non è statistica. In termini politicamente corretti dovrebbe essere definita come “truffa aggravata”.
Veniamo adesso ai dati forniti dalla Nazioni Unite e dalla Fao.
«The estimation of the parameters was also reviewed.
Recent revisions of the methodology.»
Cambiate le definizioni, cambiato immediatamente il numero dei miseri e degli affamati.
«the changes are nothing but “cosmetic efforts”»
E siccome il risultato è davvero incoraggiante, si richiedano ulteriori fondi di finanziamento.
→ Spiegel. 2016-06-28. Fudging the Numbers: Is UN Hunger and Poverty Data Reliable?
The UN is celebrating: Hunger and poverty around the world are in decline according to data from the global body. But that success is not nearly as great if you scrutinize the numbers.
The stink is unbearable, garbage is strewn everywhere and clean water is at a premium. But the old movie theater in the Cambodian capital of Phnom Penh is nevertheless home to Ngong Theavy, a young mother of three. And it is one she shares. Hundreds of people live in the old cinema building, which has become a notorious slum, and most of them live on just a little more than $1.25 per day. It is a pittance, but according to the definition used by the United Nations, they are not considered to be suffering from extreme poverty. It is a definition that very clearly does not correspond to the lives they lead.
In 2015, the UN claimed that the number of people suffering from extreme poverty in the world had been cut by more than half since 1990. A significant contributor to this success story, the UN said, was the establishment at the beginning of the last decade of the Millennium Development Goals, which include, among other aims, the fight against poverty and hunger, the struggle for better education and greater equality, and improved healthcare and environmental protection. The goals have “galvanized unprecedented efforts to meet the needs of the world’s poorest,” the UN claims on its Millennium Goals website. In an editorial published in September, philanthropist Melinda Gates wrote: “Given what we have achieved so far, it would be difficult to overstate what’s possible.”
And there have indeed been positive developments in the battle against extreme poverty, illiteracy and child mortality in recent years.
But are the advances really a result of the UN campaign? And in light of the kind of poverty facing people like Theavy, how significant has this progress really been?
Researchers from a variety of fields have been extremely critical of the UN and have argued that the progress made toward achieving the Millennium Goals has been portrayed as more significant than it actually has been. The 2015 Millennium Development Goals Report claims, for example, that “in 1990, nearly half of the population in the developing world lived on less than $1.25 a day; that proportion dropped to 14 percent in 2015.”
That statement is not factually inaccurate, but the goals were only established in 2000. As such, they could not have had any effect on developments during the decade before the new millennium. But as can be seen in the graph below, in the decade from 1990 to 2000 the number of people suffering from extreme poverty was already declining steeply. By choosing 1990 as its year of comparison, it looks as though the UN is claiming this development as its own.
And that’s not only true of the battle against poverty. The American statistician and UN employee Howard Friedman concluded in a 2013 paper that the positive developments in most areas began accelerating prior to 2000. It is an observation that doesn’t per se negate the positive results that the Millennium Goals may have achieved, but it does cast those effects in a different light.
Damage Done by Misguided Incentives
Nicole Rippin, a researcher with the German Development Institute, goes even further, saying that the goals have actually been harmful in some cases. An example she mentions pertains to one of the sub-targets: that of improving the lives of slum dwellers. To establish a criterion for success in this area, the share of a country’s population living in slums was determined. According to Rippin, this led some countries to simply clear slums to meet the targets laid out by the Millennium Goals. The result was a statistical success but a disaster for those who lost their homes.
The measurement of global hunger provides a further indication that statistics do not always provide a reliable approximation of reality. In the 2015 Millennium Goals report, a diagram shows the number of people suffering from undernourishment over time. Since 1990, the trend has clearly been downward. Furthermore, the proportion of the global population suffering from hunger has plunged even more rapidly than the absolute number. The message is clear: We are on the path to eliminating hunger.
But in 2010, the Food and Agricultural Organization of the UN released a report that presented the global hunger situation in a starkly different light. Since 2006, the FAO has registered a steep rise in the number of undernourished people in the world and noted that in 2009, 1 billion people in the world were suffering from hunger.
How can these two accounts be reconciled? The reason for the discrepancy is that the FAO began measuring undernourishment differently in 2012. It isn’t possible, after all, to simply count the number of people in a population who are suffering from hunger. Rather, a variety of figures pertaining to a given country are analyzed by way of complex statistical formulas.
In 2012, the FAO adopted a new mathematical formula to describe the probability that a resident of a particular country consumes a certain amount of food and takes in a certain number of calories. If the nutritional situation of a country improves, the new statistical method is better able to account for that improvement, the FAO says in an explanation of the methodology it uses.
For Thomas Pogge, a professor of philosophy at Yale, the changes are nothing but “cosmetic efforts” aimed at making the trends look as positive as possible. He also believes that the definition of undernourishment used is of little value because it is based on the amount of calories necessary for a sedentary lifestyle — and not for the kind of hard work that many in the developing world must perform to get by.
When it comes to the monitoring of a different Millennium Goal — that of reducing extreme poverty — badly needed modifications to the way it is measured have been neglected for years. It is “a scandal to define a poverty level of $1.25, which is then left unmodified over the course of several years even though the global economy has grown massively during that time,” writes Franz Josef Radermacher, a professor of informatics in Ulm and a globalization scholar.
Better Luck with New Targets?
Last fall, the Millennium Goals were replaced by Agenda 2030, calling for 17 sustainable development goals and fully 169 sub-targets to be met within the next 15 years. They address almost all facets of our lives, including the pursuit of prosperity, species protection, the fight against climate change and the struggle against inequality.
A commission of experts proposed a total of 231 indicators to measure progress in each of the target areas. And these indicators too have been criticized. The group Open Knowledge Foundation Germany, for example, believes that the responsibility borne by rich countries isn’t adequately accounted for in some indicators nor are all aspects of the sub-targets sufficiently covered.
Sven Kaumanns doesn’t share the group’s concerns. Kaumann works for Germany’s Federal Statistical Office and is a member of the commission of experts assembled by the UN. The responsibilities borne by individual nations must be — should it be politically desired — codified in the goals, not in the indicators, he says. Furthermore, he adds, every sub-target is covered by at least one indicator and the indicators are also linked in myriad ways. He argues the monitoring regime must be viewed as a comprehensive system.
The expert commission didn’t take the easy road when it came to defining the indicators. There have been several conferences since last year, called for the purpose of talking with a variety of interest groups. The final list of indicators is to be approved this year by the UN General Assembly. The list will be reevaluated in 2020 and again in 2025.
Already, there is reason for hope: The controversial extreme-poverty definition of $1.25 per day could soon be revised to reflect reality. In the future, the share of country’s population below the international poverty line is to be measured, and that baseline can change over time. Last October, for example, the World Bank raised the international poverty line to $1.90 per day. That is still extremely low, but it could mean that the situation of people like Ngong Theavy of Cambodia will be assessed a bit more realistically in the future.
The discussion of the successes or failures of the Millennium Goals shows that it is certainly possible to be optimistic — as Melinda Gates is — about the positive developments that have been seen worldwide. But that optimism should not lead one to blindly trust the data and the way in which it is presented.
→ Fao. 2016-06-28. Food security methodology
The 1996 World Food Summit (WFS) called for a 50 percent reduction in the number of undernourished people by 2015. In 2000, the Millennium Declaration (MD) recognized the value of hunger and poverty reduction by setting the MDG target of “halving, between 1990 and 2015, the proportion of people who suffer from hunger” (target 1.C).
To monitor progress towards the WFS and the MDG1 targets, FAO provides regular updates to the number and proportion of persons below the minimum level of dietary energy requirement (MDG indicator 1.9). Such estimates, which are produced at global, regional and country levels where reliable data is available, are presented annually in the State of Food Insecurity in the World (SOFI) report.
According to the FAO, undernourishment is a condition of “continued inability to obtain enough food”, and the Prevalence of Undernourishment (PoU) measures the “probability that a randomly selected individual from a population is found to be consuming less than her/his requirement for an active and healthy life”. This probability is assessed against a normative minimum threshold established by nutritionists for reference age and sex groups. While it is not possible to assess precisely the individual dietary energy requirement, the PoU is based on an inference at the population level in probabilistic terms. Indeed, the FAO methodology for estimating the prevalence of undernourishment refers to:
- a probability distribution of habitual Dietary Energy Consumption (DEC) of a representative individual in a population; and
- a cut-off point for intake adequacy – Minimum Dietary Energy Requirement (MDER) – specific for the same population.
In 2011-12 the FAO methodology for estimating the prevalence of undernourishment was deeply reviewed. The revised methodology was first introduced in the 2012 SOFI. Models adopted to describe the habitual dietary energy consumption in the population were reviewed and changed where national level survey data were available. The estimation of the parameters was also reviewed.
Recent revisions of the methodology.
Parameters to characterize the distribution of food consumption employed to estimate the PoU are derived from different sources. To compute per mean or per capita DEC at a national level, FAO relies on Food Balance Sheets. The latest data from this source refer to 2011; therefore, additional sources were needed to estimate the DEC for the last 3 years, from 2012-14. The main source for 2012 and 2013 estimates were projections prepared by the Trade and Market Division of FAO. The Holt-Winters distributed lag model was instead used to project the DEC for 2014. In some cases, the same model was applied to compute projections also for 2012 and 2013, when data from the Trade and Market Division were not available. The Holt-Winters model uses a process known as exponential smoothing, which attributes higher weights to the more recent data and progressively less weight to the older observations. Weights decrease in each period by a constant amount, which lies on an exponential curve. For countries showing peculiar patterns, other simpler forecasting models were used, such as linear or exponential trends.
Two more parameters are required to characterize the distribution of food consumption: the Coefficient of Variation (CV) and the Skewness (SK). These are computed from national household surveys where they are available, which is the case for a wide sub-sample of the monitored countries. In recent years, thanks to the collaboration between FAO and National Statistical Offices, the Statistics Division has processed more than 100 surveys to obtain new parameters for about 50 countries that, together, cover more than 60 percent of the number of undernourished in developing regions.
When FAO started the regular monitoring of undernourishment, after the 1996 World Food Summit, the distribution of dietary energy consumption in the population was assumed to be log-normal. One of the main changes that FAO introduced in 2012 was the adoption, for the countries where adequate survey data were available, of a skew-normal distribution. This is fully characterized by the three parameters: the mean, the CV and the SK. The skew-normal distribution is more flexible than the log-normal and therefore better accounts for changes in the asymmetry that take place when food consumption changes, that is, when countries make progress toward greater food security.
In the SOFI 2014 edition, an even further refinement was introduced. The data are used to determine the appropriate distributional form for food consumption. In this way, the empirical SK from the distribution of per capita calorie consumption is derived from available national household surveys. The resulting model makes it possible to account for reductions in inequality of food consumption, such as those made by targeted food intervention programmes, thus ensuring a smooth transition towards a distribution in which food consumption is symmetric.
The 2014 edition of SOFI also introduced a new outlier detection method for consumption data derived from national household surveys. This is known as “leave-out-one cross-validation”, and allows for a robust calculation of the parameters in case of noisy data. Excess variability was also controlled for by using a linear regression, linking the log of per capita income to per capita calorie consumption, along with indicator variables for the month the survey was conducted to control for seasonality.
The MDER is estimated according to the normative standards set forth in the 2001 FAO/WHO/UNU Expert Consultation. To minimize the probability of overestimating undernourishment, the FAO method uses the minimum of the range of values consistent with adequate nourishment , therefore the lowest acceptable body weight for a given height and light activity. The cut-off point for a population is derived by aggregating sex and age-specific MDERs using the proportion of the population in the different sex and age groups as weights. Since the sex-age distribution of the population changes over time, the cut-off point is updated every year to reflect changes in the demographic structure of the population. This edition of SOFI uses updated population estimates from the latest revision published by the UN Population Division in June 2013. When data on population heights are not available, reference is either made to data on heights from countries where similar ethnicities prevail, or to models that use partial information to estimate heights for various sex and age classes.
Food losses occurring at the retail level were also introduced for the first time in 2012. Country-specific values regarding the average per capita loss of calories have been estimated taking into account data provided by a recent FAO study on food losses at various stages of the commodity chain.
SOFI 2014 also includes a new estimation of CVs for countries where reliable consumption data from surveys are not available. The method is based on a relationship between the CV due to income and macroeconomic variables – GDP per capita, and the Gini – and food prices. Finally, SOFI 2014 introduces a time-varying computation of variability in food consumption due to requirements in order to account for the world’s rapidly changing population structure.