Lars Peter Hansen Quotes

There are many types of economic data, but the type considered by Rob Engle and myself is know as time series.

Econometrics may be defined as the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of inference.

I think the rise of quantitative econometrics and a highly mathematical approach to risk management was the obverse of a decline in interest in financial history.

Data scientist is just a sexed up word for statistician.

You don't want to influence the same system you are trying to forecast.

During the early 1960s, I decided to supplement research support for quantitative economic studies at Pennsylvania by selling econometric forecasts to private and public sector buyers.

The Cowles Commission was the optimal environment for the type of research that I wanted to do.

We have professional economists who can defend any viewpoint with statistics and they do that everywhere in the world.

The data are what matter in economics, and the more ruthlessness that an economist can summon to make sense of the data, the more useful his findings will be.

The big mystery of Big Data is causation versus correlation.

I bathe in statistics.

Some people hate the very name of statistics, but I find them full of beauty and interest. Whenever they are not brutalized, but delicately handled by the higher methods, and are warily interpreted, their power of dealing with complicated phenomena is extraordinary. They are the only tools by which an opening can be cut through the formidable thicket of difficulties that bars the path of those who pursue the Science of Man.

I don’t believe in statistics. I believe in calculus.

One more fagot of these adamantine bandages is the new science of Statistics.

Evolving technologies that allow economists to gather new types of data and to manipulate millions of data points are just one factor among several that are likely to transform the field in coming years.

There is no such thing as quantitative economics.

I was in charge of the Bureau of Labor Statistics. So I had some of the most brilliant mathematical statistical minds in the country, who would put together the modern technology, if you like, of understanding the economy and tracking it and trying to influence it.

In a sense, there are as many forecasting methods as there are forecasters. But I would argue that most projections are derived from two major methods: macro-econometric models and eclectic judgment.

The numbers are hard to control.

I'm not too worried about stats and stuff like that.

I've got a lot of stats. I did a lot of stuff.

The bigger a data set that you have, the more polls, the more surveys that you have that people undertake, the more accurate your models are going to be. That's just a fact of data science.

In economics, it is easier to agree on the data than to agree on causality.

A lot of people seem to think that data science is just a process of adding up a bunch of data and looking at the results, but that's actually not at all what the process is.

Data drives success. That is how we began our success with eSpeed. It was always based on the data.