We often speak of economic development as a phenomenon of sovereign national countries, but the process by which that happens is through what happens at individual firms in the economy. The decisions by firms to upgrade their products (services), export, and adopt new technology are the most important determinants of economic development. The incentives and conditions that shape these decisions are the subjects of my conversation with my guest on this episode. Eric Verhoogen is a professor of economics at Columbia University school of international and public affairs. He is one of the leading thinkers and researchers on industrial development. TRANSCRIPT (edited slightly for context and clarity) Tobi; Usually, in the development literature, I know things have changed quite a bit in the last few years. But there is a lot of emphasis on cross-country comparisons and looking at aggregate data, and a lot less focus, at least as represented in the popular media on firms. And we know that, really, the drivers of growth and employment and the source of prosperity usually are the firms. The firms in an economy, firms are the ones creating jobs, they are the ones investing in technology, and doing innovation. So firms are really important. One of the things you often hear a lot is that one of the reasons poor countries are poor is that the firms are not productive enough. So that's sort of my first question to you, how exactly do we define and also measure productivity, you know, for us to be able to distinguish why firms in the developed countries are more productive than the lower income countries? Eric; Yeah, this is a big important question. So I agree, in principle, that firm productivity is very key. So countries that are going to be doing well are countries that are populated by firms that are being very innovative, and their productivity is rising, they're learning how to do new stuff, they're producing new products, etc. And so there's a reason why people are very focused on this conversation about firm productivity. The sort of, I would say, dirty secret of economics is that it's very hard to measure productivity well, right? And so the productivity measures we have, I think, are very noisy, and most likely fairly biased. But basically, the way you estimate productivity is you run a regression of like sales on inputs, okay, so on how much you're spending on labour and how much you're spending on materials, and then the part that's left over, we call that productivity. So it's like unexplained sales, you know, sales that can't be explained by the fact that you're just purchasing inputs and purchasing workers. But that is actually a very noisy measure of productivity. And so I've been working on a review paper, and a separate research paper kind of pointing out some of the issues with productivity estimation. So in principle, it's exactly what we want to know; in practice, it's very hard to measure. So one argument I was making in that paper is we should go to things that we can actually directly observe. Okay, so sometimes like technology adoption, we can often directly observe whether the firm has adopted this particular new technology, or if they're producing new products, we can directly observe that. Sometimes we can observe the quality of products that can be measured. Now, the standard datasets that we have typically don't have those things. It is possible now, in many countries, to follow manufacturing firms or even other sorts of firms, [to] follow them over time, which is great, at a micro level. But those that have the technology, they don't have quality, they do it now increasingly have like what products they're producing, often they don't have the product people are producing and so it's harder, you have to go out and you have to talk to people, you have to access new sorts of data, there's a lot more work, a lot more shoe leather - we'd say you wear out your shoe is going to talk to people trying to get