Data and evidence-based policy making

“Data for development can be likened to money in an economy or blood in the system of a human being.”
…

Demographic data provide an essential evidence base for the development and evaluation of policies. The bottom line is that “a country cannot develop without data.” Although the term “data” has technical overtones and there are important technical issues that need to be considered, the more fundamental connection is between good data and good governance. It is in part through the collection and inspection of data that nations and communities have defined themselves, identified inequities, challenged misconceptions, and justified their claims upon resources.
…

An overriding issue-indeed, one that is seen in rich and poor countries alike – is that policies are often driven by political views rather than by empirical analysis. In rich countries, however, quantitative data provide a means by which such ill-founded policies can be challenged.
…

In an ideal world, policy development would always take into account the evidence base. In reality, policymakers need to balance a wide range of factors and pressures. Data may be ignored if they challenge policymakers’ personal views or political needs. In the cases where policymakers do seek out data, it may occur after the fact to support policies already enacted. In one country, a research organization reported seeing the greatest demand for data during election season; another respondent seconded this notion by saying “it appears that data are quoted for the sake of elections rather than for planning.” The consequences of not considering the evidence can be detrimental: “it is like crisis management. The policies are not well thought out and that is why sometimes we get policies that do not stand the test of time.” Until a culture develops whereby data are used to inform policy, the demand for data collection and use will remain low among policymakers themselves.

Even when national policies become evidence-based (because at that stage many interested parties and key stakeholders are involved and the available data is reviewed), problems can arise during the process of policy implementation, when data are often completely ignored. As noted in one country: “Policies are made for the shelves. We hardly implement…You find that the two are not related at all…When it comes to the actual implementation of programs, there is very little or weak linkage with available data to inform those programs.”

from this report.

International demand for monitoring and evaluation of the development goals has some influences:

The international approach of linking investments with measurable outcomes often places great pressure on developing countries. These countries may be ill-equipped to produce the requisite data, and the consequences can be severe. Interviewees reported that their country recently lost 30 million Euros in funding due to an inability to produce data showing that the relevant targets had been met.

and potentially, media:

“quality information used by the media is the most effective advocacy tool.”

Once-in-100 years

The terms like “once-in-100 years drought”, “a 50-year flood” and “once-in-30 years wildfire” to describe how likely an event occurs are based on statistics, on the premise that the world works as if it is static (note the similarity of the words “static” and “statistics”).

But the world is not like that. It is changing (dynamic). So the yesterday “once-in-100 years storm” may become more frequent to “once-in-30 years storm” today due to climate change.

For example, given a distribution of river discharges for the years 1950 to 2000, can this distribution be used to predict how often a certain river discharge will be exceeded in the years 2000 to 2050? The answer is yes, provided that the environmental conditions do not change. If the environmental conditions do change, such as alterations in the infrastructure of the river’s watershed or in the rainfall pattern due to climatic changes, the prediction on the basis of the historical record is subject to a systematic error.

from Wikipedia.

Other good explanations are Teaching recurrence intervals and Two streams, two stories… How Humans Alter Floods and Streams.

This post is my comment to this news (in Chinese).