Accessing economic data these days can be almost deceptively easy. A few clicks on the U.S. Bureau of Labor Statistics’ website or a simple search on the St. Louis Federal Reserve’s FRED site reveals thousands of datasets that anyone interested in economics can grab. Such quick-and-easy access to data has helped drive the “credibility revolution” in empirical economics research. Yet this multitude of data sets does not burst forth into the world fully formed. Rather, the creation of data can be a messy process, especially when considering the version that the U.S. public and researchers may eventually see.

Here’s one such mess—a new paper presented at last week’s Brooking Panel on Economic Activity warns that procedures used to protect privacy might be distorting many of the data sets that researchers use. Large data sets can be incredibly powerful in the amount of information they capture about individuals, but they also present a risk to those individuals’ privacy. Take the Current Population Survey, which is maintained by the U.S. Bureau of Labor Statistics and the U.S. Census Bureau. The survey contains information about a person’s family status, their income, their location, and quite a few more variables. If these data were made available to the public unaltered, then someone could look into the data and conceivably identify a respondent.

To avoid identification through these means, both private and public sector data providers mask the identity through a number of statistical processes. In the new Brookings paper, John M. Abowd of Cornell University and Ian M. Schmutte of the University of Georgia detail the ways that statistical disclosure limitations, or SDL—the catch-all name for these processes—can affect economic analyses. The authors single out one form of SDL that is particularly nefarious: swapping. In this process, the statistical agency or company will swap certain attributes of respondents. The location of individuals, for example, might be switched in order to protect their identities, but that could corrupt the economic analysis a researcher is running.

What the authors call for is a certain amount of disclosure from the organization creating these limited datasets. Abowd and Schmutte don’t want the raw, unaltered data, but rather better disclosure of how exactly the organization changed the data. If the agencies or companies let researchers know about certain aspects of the process that anonymized the data, then the researchers could account for these distortions in their analysis.

Of course, the agencies could just make more of the raw data available. But as participants at the Brookings panel noted, there are severe consequences for the employees of these agencies if someone is identified in the data. The punishment could include a fine of several thousand dollars or jail time. That potential punishment makes agency staff quite averse to disclosing data.

These statistical disclosure limitation processes right now are almost exclusively used on survey data, which makes some economists sanguine about the future of data. Microeconomists have increasingly turned to administrative data, which is taken directly from government sources and includes things like tax receipts, and away from survey data. But one participant warned that these SDL processes will almost certainly make their way to administrative data.

Abowd and Schmutte’s paper is an important reminder that we all need to pay attention to the sources and presentation of economic data. The old joke about economic analysis is that it’s like looking for a set of lost keys only where the streetlight illuminates the pavement. The least we can do is to make sure the light shines as bright and as wide as possible.

According to long-trusted economic models, when economic inequality increases so too does government redistribution of income. As the average income in an economy pulls away from the median income, more voters will want to redistribute the uneven gains from economic growth accruing to the wealthy. Yet in the United States, redistribution towards the bottom and middle hasn’t increased even though inequality has increased quite a bit. Why have these long-trusted models failed to accurately predict reality?

There is some evidence that U.S. elected officials’ responsiveness to preferences for redistribution has declined over time. But voters’ demand for redistribution also appears not to have increased over time. A new paper presented last week as part of a recent Brookings Papers on Economic Activity event tries to understand why preferences for redistribution have changed among voters over time.

Political scientist Vivekinan Ashok of Yale University and economists Ebonya Washington of Yale and Ilyana Kuziemko of Princeton University try to understand the demand for redistribution by looking at responses to questions from the General Social Survey and American National Election Studies survey— which include questions that are related to redistribution. What they find is that while the overall trend in support of redistribution stood still, two groups that were once traditionally in favor of redistribution shifted away from it over time.

Those two groups: seniors and black Americans.

The three authors also point to some of the reasons why this may be the case with these two important voting blocs. For seniors, it all comes down to one particular form of redistribution: health care. The authors argue that calls for higher redistribution make seniors, who receive health insurance via Medicare, believe this particular form of redistribution will be curtailed. Ashok, Washington, and Kuziemko point out that support for redistribution among seniors in other advanced economies that provide universal health insurance has not declined more compared to their general population, which makes sense as they wouldn’t have to fear about cuts to healthcare in order to expand it to others. And the survey data show that attitudes among U.S. seniors toward redistribution via health insurance are strongly predictive of overall attitudes toward redistribution.

The authors are less sure of an explanation for African Americans’ declining preference for redistribution. The authors’ research shows that most of the decline among blacks is because of declining demand for race-based redistributive programs. But why that has happened even as the relative economic progress of blacks compared to whites has stalled isn’t clear.

At the Brookings event, one of the constant comments about the paper was that their findings could also be explained by the shifting generational arc. The decline in demand for redistribution among seniors could be about the passing of the Greatest Generation, who were generally in favor of redistribution, alongside the aging of the Baby Boomers, who appear to not prefer redistribution as they near or enter retirement. One participant added that some preliminary research finds that Americans believe inequality is a problem but that they think it’s the responsibility of business to reduce the gap between the rich and the poor.

Ashok, Kuziemko, and Washington are clear that their paper doesn’t provide all the answers. But in pointing out some key facts and offering some possible explanations, they provide an important jumping-off point for understanding how public opinion about redistribution have changed in an era of rising inequality.