Statistical methods in public policy research


Chapter by Andrew Heiss: “This essay provides an overview of statistical methods in public policy, focused primarily on the United States. I trace the historical development of quantitative approaches in policy research, from early ad hoc applications through the 19th and early 20th centuries, to the full institutionalization of statistical analysis in federal, state, local, and nonprofit agencies by the late 20th century.

I then outline three core methodological approaches to policy-centered statistical research across social science disciplines: description, explanation, and prediction, framing each in terms of the focus of the analysis. In descriptive work, researchers explore what exists and examine any variable of interest to understand their different distributions and relationships. In explanatory work, researchers ask why does it exist and how can it be influenced. The focus of the analysis is on explanatory variables (X) to either (1) accurately estimate their relationship with an outcome variable (Y), or (2) causally attribute the effect of specific explanatory variables on outcomes. In predictive work, researchers as what will happen next and focus on the outcome variable (Y) and on generating accurate forecasts, classifications, and predictions from new data. For each approach, I examine key techniques, their applications in policy contexts, and important methodological considerations.

I then consider critical perspectives on quantitative policy analysis framed around issues related to a three-part “data imperative” where governments are driven to count, gather, and learn from data. Each of these imperatives entail substantial issues related to privacy, accountability, democratic participation, and epistemic inequalities—issues at odds with public sector values of transparency and openness. I conclude by identifying some emerging trends in public sector-focused data science, inclusive ethical guidelines, open research practices, and future directions for the field…(More)”.

So You Want to Be a Dissident?


Essay by Julia Angwin and Ami Fields-Meyer: “…Heimans points to an increasingly hostile digital landscape as one barrier to effective grassroots campaigns. At the dawn of the digital era, in the two-thousands, e-mail transformed the field of political organizing, enabling groups like MoveOn.org to mobilize huge campaigns against the Iraq War, and allowing upstart candidates like Howard Dean and Barack Obama to raise money directly from people instead of relying on Party infrastructure. But now everyone’s e-mail inboxes are overflowing. The tech oligarchs who control the social-media platforms are less willing to support progressive activism. Globally, autocrats have more tools to surveil and disrupt digital campaigns. And regular people are burned out on actions that have failed to remedy fundamental problems in society.

It’s not clear what comes next. Heimans hopes that new tactics will be developed, such as, perhaps, a new online platform that would help organizing, or the strengthening of a progressive-media ecosystem that will engage new participants. “Something will emerge that kind of revitalizes the space.”

There’s an oft-told story about Andrei Sakharov, the celebrated twentieth-century Soviet activist. Sakharov made his name working as a physicist on the development of the U.S.S.R.’s hydrogen bomb, at the height of the Cold War, but shot to global prominence after Leonid Brezhnev’s regime punished him for speaking publicly about the dangers of those weapons, and also about Soviet repression.

When an American friend was visiting Sakharov and his wife, the activist Yelena Bonner, in Moscow, the friend referred to Sakharov as a dissident. Bonner corrected him: “My husband is a physicist, not a dissident.”

This is a fundamental tension of building a principled dissident culture—it risks wrapping people up in a kind of negative identity, a cloak of what they are not. The Soviet dissidents understood their work as a struggle to uphold the laws and rights that were enshrined in the Soviet constitution, not as a fight against a regime.

“They were fastidious about everything they did being consistent with Soviet law,” Benjamin Nathans, a history professor at the University of Pennsylvania and the author of a book on Soviet dissidents, said. “I call it radical civil obedience.”

An affirmative vision of what the world should be is the inspiration for many of those who, in these tempestuous early months of Trump 2.0, have taken meaningful risks—acts of American dissent.

Consider Mariann Budde, the Episcopal bishop who used her pulpit before Trump on Inauguration Day to ask the President’s “mercy” for two vulnerable groups for whom he has reserved his most visceral disdain. For her sins, a congressional ally of the President called for the pastor to be “added to the deportation list.”..(More)”.

Trump Wants to Merge Government Data. Here Are 314 Things It Might Know About You.


Article by Emily Badger and Sheera Frenkel: “The federal government knows your mother’s maiden name and your bank account number. The student debt you hold. Your disability status. The company that employs you and the wages you earn there. And that’s just a start. It may also know your …and at least 263 more categories of data.These intimate details about the personal lives of people who live in the United States are held in disconnected data systems across the federal government — some at the Treasury, some at the Social Security Administration and some at the Department of Education, among other agencies.

The Trump administration is now trying to connect the dots of that disparate information. Last month, President Trump signed an executive order calling for the “consolidation” of these segregated records, raising the prospect of creating a kind of data trove about Americans that the government has never had before, and that members of the president’s own party have historically opposed.

The effort is being driven by Elon Musk, the world’s richest man, and his lieutenants with the Department of Government Efficiency, who have sought access to dozens of databases as they have swept through agencies across the federal government. Along the way, they have elbowed past the objections of career staff, data security protocols, national security experts and legal privacy protections…(More)”.

The Social Biome: How Everyday Communication Connects and Shapes Us


Book by Andy J. Merolla and Jeffrey A. Hall: “We spend much of our waking lives communicating with others. How does each moment of interaction shape not only our relationships but also our worldviews? And how can we create moments of connection that improve our health and well-being, particularly in a world in which people are feeling increasingly isolated?
 
Drawing from their extensive research, Andy J. Merolla and Jeffrey A. Hall establish a new way to think about our relational life: as existing within “social biomes”—complex ecosystems of moments of interaction with others. Each interaction we have, no matter how unimportant or mundane it might seem, is a building block of our identities and beliefs. Consequently, the choices we make about how we interact and who we interact with—and whether we interact at all—matter more than we might know. Merolla and Hall offer a sympathetic, practical guide to our vital yet complicated social lives and propose realistic ways to embrace and enhance connection and hope…(More)”.

LLM Social Simulations Are a Promising Research Method


Paper by Jacy Reese Anthis et al: “Accurate and verifiable large language model (LLM) simulations of human research subjects promise an accessible data source for understanding human behavior and training new AI systems. However, results to date have been limited, and few social scientists have adopted these methods. In this position paper, we argue that the promise of LLM social simulations can be achieved by addressing five tractable challenges. We ground our argument in a literature survey of empirical comparisons between LLMs and human research subjects, commentaries on the topic, and related work. We identify promising directions with prompting, fine-tuning, and complementary methods. We believe that LLM social simulations can already be used for exploratory research, such as pilot experiments for psychology, economics, sociology, and marketing. More widespread use may soon be possible with rapidly advancing LLM capabilities, and researchers should prioritize developing conceptual models and evaluations that can be iteratively deployed and refined at pace with ongoing AI advances…(More)”.

Need a Side Gig? In China, Just Shake Your Phone


Article by Chen Yiru: “From a restaurant shift to a quick plumbing job, gig work in China is now just a phone shake away.

That’s the idea behind Tencent’s new “Nearby Jobs” feature, which was quietly rolled out nationwide on its messaging super app WeChat last week. Aimed at flexible job seekers, the tool connects users to verified listings in fields like driving, design, tech support, and catering — all within the country’s most-used app.

First piloted in Jiangmen, a city in the southern Guangdong province, the mini-program has expanded to more than 200 cities including Beijing, Shanghai, and Shenzhen. Tencent says it has already helped over 24,000 people secure short-term work, with filters that let users sort listings by pay, distance, payment schedule, and even gender preferences.The “Nearby Jobs” tool borrows from WeChat’s classic “Shake” feature, first introduced in 2012 to connect nearby users by physically shaking their phones. While the original version was discontinued for mainland users in early 2024 due to privacy concerns, traces of the function have recently resurfaced in limited testing — hinting at a possible revival.

The launch comes amid rising demand for platforms that can bridge the gap between gig employers and job seekers. China is home to an estimated 200 million flexible workers, and market demand for blue-collar labor has surged 380% over the past five years, according to a 2024 industry report. Younger workers are driving much of this growth, with job applicants under 25 rising by 165% during the same period…(More)”.

Massive, Unarchivable Datasets of Cancer, Covid, and Alzheimer’s Research Could Be Lost Forever


Article by Sam Cole: “Almost two dozen repositories of research and public health data supported by the National Institutes of Health are marked for “review” under the Trump administration’s direction, and researchers and archivists say the data is at risk of being lost forever if the repositories go down. 

“The problem with archiving this data is that we can’t,” Lisa Chinn, Head of Research Data Services at the University of Chicago, told 404 Media. Unlike other government datasets or web pages, downloading or otherwise archiving NIH data often requires a Data Use Agreement between a researcher institution and the agency, and those agreements are carefully administered through a disclosure risk review process. 

A message appeared at the top of multiple NIH websites last week that says: “This repository is under review for potential modification in compliance with Administration directives.”

Repositories with the message include archives of cancer imagery, Alzheimer’s disease research, sleep studies, HIV databases, and COVID-19 vaccination and mortality data…

“So far, it seems like what is happening is less that these data sets are actively being deleted or clawed back and more that they are laying off the workers whose job is to maintain them, update them and maintain the infrastructure that supports them,” a librarian affiliated with the Data Rescue Project told 404 Media. “In time, this will have the same effect, but it’s really hard to predict. People don’t usually appreciate, much less our current administration, how much labor goes into maintaining a large research dataset.”…(More)”.

Beyond data egoism: let’s embrace data altruism


Blog by Frank Hamerlinck: “When it comes to data sharing, there’s often a gap between ambition and reality. Many organizations recognize the potential of data collaboration, yet when it comes down to sharing their own data, hesitation kicks in. The concern? Costs, risks, and unclear returns. At the same time, there’s strong enthusiasm for accessing data.

This is the paradox we need to break. Because if data egoism rules, real innovation is out of reach, making the need for data altruism more urgent than ever.

…More and more leaders recognize that unlocking data is essential to staying competitive on a global scale, and they understand that we must do so while upholding our European values. However, the real challenge lies in translating this growing willingness into concrete action. Many acknowledge its importance in principle, but few are ready to take the first step. And that’s a challenge we need to address – not just as organizations but as a society…

To break down barriers and accelerate data-driven innovation, we’re launching the FTI Data Catalog – a step toward making data sharing easier, more transparent, and more impactful.

The catalog provides a structured, accessible overview of available datasets, from location data and financial data to well-being data. It allows organizations to discover, understand, and responsibly leverage data with ease. Whether you’re looking for insights to fuel innovation, enhance decision-making, drive new partnerships or unlock new value from your own data, the catalog is built to support open and secure data exchange.

Feeling curious? Explore the catalog

By making data more accessible, we’re laying the foundation for a culture of collaboration. The road to data altruism is long, but it’s one worth walking. The future belongs to those who dare to share!..(More)”

The Measure of Progress: Counting What Really Matters


Book by Diane Coyle: “The ways that statisticians and governments measure the economy were developed in the 1940s, when the urgent economic problems were entirely different from those of today. In The Measure of Progress, Diane Coyle argues that the framework underpinning today’s economic statistics is so outdated that it functions as a distorting lens, or even a set of blinkers. When policymakers rely on such an antiquated conceptual tool, how can they measure, understand, and respond with any precision to what is happening in today’s digital economy? Coyle makes the case for a new framework, one that takes into consideration current economic realities.

Coyle explains why economic statistics matter. They are essential for guiding better economic policies; they involve questions of freedom, justice, life, and death. Governments use statistics that affect people’s lives in ways large and small. The metrics for economic growth were developed when a lack of physical rather than natural capital was the binding constraint on growth, intangible value was less important, and the pressing economic policy challenge was managing demand rather than supply. Today’s challenges are different. Growth in living standards in rich economies has slowed, despite remarkable innovation, particularly in digital technologies. As a result, politics is contentious and democracy strained.

Coyle argues that to understand the current economy, we need different data collected in a different framework of categories and definitions, and she offers some suggestions about what this would entail. Only with a new approach to measurement will we be able to achieve the right kind of growth for the benefit of all…(More)”.

DOGE comes for the data wonks


The Economist: “For nearly three decades the federal government has painstakingly surveyed tens of thousands of Americans each year about their health. Door-knockers collect data on the financial toll of chronic conditions like obesity and asthma, and probe the exact doses of medications sufferers take. The result, known as the Medical Expenditure Panel Survey (MEPS), is the single most comprehensive, nationally representative portrait of American health care, a balkanised and unwieldy $5trn industry that accounts for some 17% of GDP.

MEPS is part of a largely hidden infrastructure of government statistics collection now in the crosshairs of the Department of Government Efficiency (DOGE). In mid-March officials at a unit of the Department of Health and Human Services (HHS) that runs the survey told employees that DOGE had slated them for an 80-90% reduction in staff and that this would “not be a negotiation”. Since then scores of researchers have taken voluntary buyouts. Those left behind worry about the integrity of MEPS. “Very unclear whether or how we can put on MEPS” with roughly half of the staff leaving, one said. On March 27th, the health secretary, Robert F. Kennedy junior, announced an overall reduction of 10,000 personnel at the department, in addition to those who took buyouts.

There are scores of underpublicised government surveys like MEPS that document trends in everything from house prices to the amount of lead in people’s blood. Many provide standard-setting datasets and insights into the world’s largest economy that the private sector has no incentive to replicate.

Even so, America’s system of statistics research is overly analogue and needs modernising. “Using surveys as the main source of information is just not working” because it is too slow and suffers from declining rates of participation, says Julia Lane, an economist at New York University. In a world where the economy shifts by the day, the lags in traditional surveys—whose results can take weeks or even years to refine and publish—are unsatisfactory. One practical reform DOGE might encourage is better integration of administrative data such as tax records and social-security filings which often capture the entire population and are collected as a matter of course.

As in so many other areas, however, DOGE’s sledgehammer is more likely to cause harm than to achieve improvements. And for all its clunkiness, America’s current system manages a spectacular feat. From Inuits in remote corners of Alaska to Spanish-speakers in the Bronx, it measures the country and its inhabitants remarkably well, given that the population is highly diverse and spread out over 4m square miles. Each month surveys from the federal government reach about 1.5m people, a number roughly equivalent to the population of Hawaii or West Virginia…(More)”.