It strikes me as rather odd that a discipline in which a person purports to be on solid analytical ground would eschew learning how to write their research and modeling code in Fortran, C, C++, Scala, Python, etc. I can't think of a single colleague of mine, when I was in academia, who did not know how to write code in at least one of the languages you mentioned. That's because such knowledge is necessary to do rigorous, proper numerical computation in an analytical discipline like math, a variety of sciences and, yes, economics.

The "GIGO" issue you note is irrelevant, but even if it weren't GIGO is compounded and amplified by the copy-and-paste paradigm of spreadsheet "programming", so if anything bringing up GIGO is even more damning of the use of spreadsheets for analytical work.

There are plenty of much better tools that many economists use. For example, Stata. Stata allows you to view your data at any point in time in a nice table, but also to manipulate it using a very easy to learn (and yet very expressive) language that you can write interactively as well as in .do files. The economist I worked for wanted the whole process, from cleaning the data, running the regressions, outputting the tables, etc., to be in a set of .do files so we could hand over the original data files and all the code for review and replication. While building the final analysis, though, you could also work interactively to figure out what you wanted the final product to be, though of course you could log everything you did interactively so there would always be a record.

Economists are expected to know how to program, and they do. They just have a tendency to reserve writing programs for complex models and prefer spreadsheets for what they consider "simple" data analysis.

On the point about transcription errors: Using python could have avoided some transcription errors. If the error was in copying a single constant from a source into the program, then in python it might be buried as an unlabeled magic number deep in the source tree, but it also might be labeled as a top level constant identifier. In the former case it would have the same problem as in a spreadsheet, but in the latter, a typo would likely be caught by someone reading over the code at some point. Or if some of the data came in a file format that excel couldn't automatically import, maybe he could have used a python library instead of manually transcribing 50 data points. It's hard to think of a situation where using python would have lead to more transcription errors.

I don't know where this sentiment that economists (who are not trained as programmers) are expected to know computer programming languages comes from.

Both Harvard and Stanford economics degrees do not list Computer Science 101 as a core requirement to graduate.

Compare Stanford's requirements for Economics[1] with Electrical Engineering[2]. The engineering major has core classes including computing and programming. The economics major does not. (Whether or not economics studies should include it (and therefore Stanford is "wrong" in leaving it out) is a separate conversation.)

Since Thomas Piketty is from France, is there a tradition of European schools requiring computer programming language courses in their training?

As for the Python vs Excel comparisons, I say people are overestimating Python's syntax to avoid errors and underestimating Excel's visual spatial grid of cells & near-universal collaboration to also avoid certain classes of errors. For non-programmers, the rows-columns grid displayed visually at all times is almost a perfect 1-to-1 correspondence to their mental model. For Python loops, it takes programmer training to mentally "unroll" loops and see how data is munged. This visual "blindness" in programming languages ends up creating its own class of errors.

I've done programming in MS Excel + Excel macros/VBA, MS Access, Oracle PL/SQL, MS Transact-SQL, C++ Qt, C# ADO.NET/LINQ, Python,etc and I'm not convinced the syntax of programming languages leads to reduced errors. It's just a different class of errors.

[1]http://economics.stanford.edu/undergraduate/economics-major-...

[2]http://exploredegrees.stanford.edu/schoolofengineering/elect...

"It's not realistic to expect Mr. Piketty to set aside months (years) of his time to master C++/Python/Scala/Fortran/etc to avoid using Excel."

I tend to disagree. Mr Piketty graduated in Mathematics (from a highly selective institution). It is realistic to expect him to be able to use those tools if needed.

Until you realize that there is more to mathematics than discrete mathematics. For someone doing, let's say, Topology computers are so useless you could well spend your entire postgraduate life without using anything more complicated than Word.