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Welcome everybody to another edition of Data Talks.
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This is a very special occasion for me.
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I'm speaking to my previous boss, Philip Loharou.
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He has a very distinguished career with the World Bank, also with the European Bank, previous managing director and CEO of the IFC.
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Welcome to the show, Philip.
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Thank you, Wolfgang.
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Glad to be here with you.
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So good to have you, Philip.
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Obviously, you were uh a legendary person at the World Bank.
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I think everybody would say that who worked with you or interacted with you.
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Um and uh and a very long career, but uh we always start with a person and how it all started.
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And in your case, and I know this uh through our own interactions in Africa, it started in Ethiopia.
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So tell us about your time in Ethiopia at school and how that shaped you.
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Well, I arrived uh in in Addis because I was following my father who uh who had the job uh there for research.
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He was a scientist and working on uh climate change, although at the time it was not called like this.
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And that was in 73, 74, 75, that's what we're talking about.
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And that was also when the um the Derg uh got rid of the emperor, Alice Alassier, and started the revolution.
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So, and here I was at the last year of the French uh school, you know, it's called Terminal, literally the last year of the high school, and then you go to university.
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So I was in Terminal, I was 17, and uh in Addis Abeba just during this the beginning of this revolution.
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And so my focus at school was really math and science.
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Why?
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Because it was easy, uh, not that it was easy for me, but it was good input-output ratio.
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It was so important as a coefficient for the general average that a little effort in math was better, went much further than a lot of efforts in French or English or geography or history.
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So it was for me a way, and then my father was a scientist, so uh was being pushed in this direction.
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But then in Ethiopia I started to see after this revolution, or during the revolution, a lot of uh young uh Ethiopians, including in school, in the French school in uh in Gebremariam in Addis Abeba, being killed and tortured, and that's in the name of three white men from a century ago, like Marx Engels and Lenin.
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So three white men in the middle of Africa in a country that was uh an imperial country with um uh a very traditional structure.
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Uh and and for these three guys, people were killing themselves.
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So I it was very hard for me.
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And again, that's why he said I was in mathematics, I was not into politics, literature, maybe it will have helped me to understand, but I couldn't understand.
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It was just that simple.
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I just couldn't understand.
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And to be honest, sorry I take a little bit of time on this one, but I can say that since then, since 17, that traumatic experiment for me.
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It was really traumatic, but it was also foundational in the sense that I spent really the rest of my life trying to understand this basic question.
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Why do you kill young kids?
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I mean, 17, 18, 19 students, uh in the name of principles and ideology that is important.
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It's not even yours.
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I mean, it's just and not necessarily adapted to the to your condition.
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I didn't know all this, so I read everything Marxist, I read all Marx, including Das Capital, that many have not read, and it's very difficult to digest.
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I read all Lenin, I read Engels, I read everything, because it was the distributed for free, by the way, by the revolution.
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That was the only perk of this thing.
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But it was a very tough thing, it was very violent.
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Uh, there is a museum now in Addis on this period.
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It's what's called the Red Terror.
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And you have, if you go to this museum, it's a very small one, but it's mostly photograph and uh artifacts, it's horrible.
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It's really uh I'm sure that plenty of those in during the history, um, many, many of those, but that's the one I witnessed when I was uh in uh at 17 year old, very impressionable.
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And uh at the point where I had to decide my life.
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In fact, I thought it was all directed.
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I would have ended up as a scientist or um medical doctor or something.
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That was uh there was no question.
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I mean, it was really on a one-track mind.
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Um but I Ethiopia kind of hijacked completely and shaped my whole uh career and my whole life, to be honest, and many things that I thought and triggered uh the questions.
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And you know, as you know, one question triggers another question, and you start digging and digging and digging and digging.
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So I'll stop here.
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But it was really traumatic and foundational for me.
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And and Philippe, you I think previously even called it like that ideology kills.
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Um, and and how is this in contrast to then later the life when we met right at the World Bank?
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Why was that you know work in development such a contrast in for you to the experience you just shared with us?
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Well, I mean, again, fundamentally, little by little, you and the fact that again science was important in my life, uh, evidence-based uh analysis and then conclusion and their action for me became very, very important.
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I realized that was that if you don't do that, you substitute that by a whole ready-made ideology that may fit or not fit reality.
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And when reality doesn't fit an ideology, then this is where the violence starts because you try to push it by force.
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So that's kind of uh I'm I'm taking a lot of shortcuts here, but that's what I found.
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So I felt good at the World Bank, and that's why I stayed much longer than I expected to, um, because it was fundamentally evidence-based.
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The premium of data was very important.
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I think we should done we should have done even more to develop the data systems in countries, but the bank has done some, could have done more.
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But uh for me it uh it was the only way because when you're faced to a problem, um you have two ways you you need to when you're a decision maker, okay?
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You have to make a decision.
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Now, how do you make a decision based on what?
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Some kind of analysis, okay.
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But what is the input to the analysis?
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If you can, you have the data.
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If you can't, you substitute by the ready-made set of uh preconceived ideas that come from wherever in history, and that is when it becomes dangerous for me.
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And that's the bank by being evidence-based and based on data, was important.
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By the way, uh, one thing you can quote, it's a quote from Wolfenson.
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I know I told you that uh the data I sent you on mission and asking you to bring data no matter what.
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Micro, macro, wrong, not wrong, because then you can always try to check, double check, uh, cross-check.
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But um it's better than nothing.
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But I had uh the same uh uh uh problem once with um Wolfenson, who was the president of the World Bank at one point, and I was doing the AIDA replenishment.
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And he was always asking me, what is the present value of this?
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What is the present value of that?
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And I was really furious because I didn't know.
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And he could do the present value mentally.
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I couldn't.
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And I was pissed because I wanted to go for strategic direction, not for a freaking present value of that string of data or whatever with that.
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My staff could do it.
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So I complained and I told him, I mean, stop asking me, you know, the present value.
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I mean, I can do it like you on mentally, and my staff can do it on their computer, no problem.
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But what I want you is some strategic guidance.
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And he was shocked.
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But he looked at me and I think he had a fantastic comeback.
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He said, Listen, numbers are the x-ray to many problems or many issues.
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I think that could be a title for your our uh little discussion.
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It's not mine, it's uh it's a better way to say what I told you when uh you were a young economist.
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Uh, but that's what Wolfenson told me when I was a director for IDA.
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Super.
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Thanks so much, Shachamin.
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I think um I'll ask the team to put it together now.
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I think that that the voice is good now and even better than last time.
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Super.
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Thanks so much for we can do some of the other thing now, so you can have something to play with.
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I don't know what is the quality of the rest.
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Um the rest was uh sure.
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Um yeah, the wait a quick second, because we went then right into the I think the World Bank part.
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Uh let me just do this one kind thing.
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Um one second.
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Okay, this was okay.
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Um good, okay.
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Then let's um um good, then we'll it's funny because you already anticipated it, but I'll I'll keep going.
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Um so Philip, we first met in the um uh in the early 2000s.
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You were uh the manager at that time what was called sector manager still of Southern Africa that included Madagascar and Comor Islands, which is also a region that you previously uh were responsible for as what you could be called the World Bank Ambassador out of Madagascar.
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And I remember still, I went on on this mission to Comoro Islands, and then uh you said, Wolfgang, bring me back data, as you just said, whatever it is, because you you call it that time, and I think you stand by that.
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It cuts through a lot of crap.
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Um tell us a bit about that that mindset, that quantitative mindset that you had and that you wanted to instill into your teams.
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Again, it comes from some of what we discussed earlier.
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I mean, um that is the link to the Ethiopia and everything, kind of uh uh permanent um search for evidence.
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Uh and the problem with evidence is when you come with a very small detail, I mean the problem is it is is it material?
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So you met someone very rich in that country.
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It means that everybody is rich in this country?
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No, obviously.
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And whatever, I take this example, it just comes through my mind.
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So the problem is materiality.
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So you really need to find some data.
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And if you don't have structured, well-structured data with a good GDP, with uh everything behind the GDP, very well documented, etc., then you have to try to do your best to come close to it through proxies.
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And I think even if it's far from perfect, proxies that try to do that, to say what is the situation to grasp a situation and the materiality of this situation is better than nothing, or just what you heard at the hotel during the mission.
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Or, you know, a couple of traders that you talk to.
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It's important, but it's you see what I'm saying?
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So that for me was always kind of this drive to try to go beyond the simplification of and the expediency of just picking a few things and uh either a full concept, ideologic, but also just something.
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You know, people are rich or they're or they're poor or whatever.
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Uh a statement that try to capture reality, but behind it, you need to document it.
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So this obsession to document, I think, came from that experiment in Ethiopia.
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You need to have the best possible diagnosis with whatever you have.
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If you have in a very data-intensive uh country, great.
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So then you have a lot of other theories and uh and how to use the data that you have at your disposals, and that's probabilities, statistics, no matter what.
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But if you are in a country with very little statistics, try to build them.
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Go interviews.
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That's why the bank used a lot of surveys.
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And uh the the thing started in the 90s when we got into poverty under Wolf and Son, by the way.
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Uh, but that's they are very useful.
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And I'm sure that where you stand now, you can witness to that.
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But what is a survey?
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It's to try again to have representative data so that you can make something out of it that is not wrong by from from inception, because the data behind is wrong.
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It's like I for me, I always like comparison with medical comparisons.
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If your diagnostic is wrong, because you got the wrong temperature, you got the wrong x-ray, you got everything that as an input, everything is wrong, then you'll have the wrong diagnostic that will lead to the wrong treatment that may lead to uh very serious conditions down the line.
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I think economics it's a little bit the same and social.
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So you need the data.
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For me, the x-ray, it's not a bad way to think about it.
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And when you again in a country with scant data, go after it.
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It's not easy, you don't go behind, you can stay in some country, everything is available, so it's great, but in some countries not.
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So go for it because there's always data.
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And you can find proxy, you have to have to be imaginative, you can find a lot of uh proxies, and then use judgment.
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Again, data doesn't uh exclude judgment, you have to apply still the judgment on the data.
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One thing I like very much at the World Bank is the exercise in prem in for the macro to go through modeling.
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You know, we had the RIMSIN X model, which was maybe very simplistic, but it forced you to ask some basic question.
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How can I grow if imports go down?
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Where will the equipment for investment come from?
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And if I cannot invest, how can I grow?
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I mean, you know, basic stuff because otherwise the system doesn't work.
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So I think that this is the strength and the power of data, but at the end, you you need your judgment.
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So it's the combination that is powerful.
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Thank you, Philip.
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Things have to add up, um, as you implicitly um highlight here.
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And Philip, you obviously have been around for a long time in that field, and not just with the World Bank and its sister organization IFC, but also uh with the European Bank in London, and now as the chairman of the French Development Corporation.
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Um how what's your assessment of how far the development sector has come in providing good data?
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How much do you think uh the the industry is at the frontier and how much more could it do?
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I think we've done we've we went a long, long way on the positive side.
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Um in improving data in all the sectors in many countries, including some very poor.
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Now, to go to countries where you have very little data, you really have to go to countries that are post-conflict or in conflict.
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Where, but I I I saw during my career of what 40 years, a huge improvement.
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Is it perfect?
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No, can we improve?
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Yes, but we can say we can improve also uh in the most advanced countries.
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Um, but I think we went a long, long way.
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I think that the quality of management in emerging markets has been improving, or public uh policy has been improving, and every minister of finance, prime minister, or president uh wants to make sure that, like a pilot in a plane, there have tools to navigate, or in a boat.
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You need tools and numbers to navigate.
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Uh so I think that, and then there have been a lot of efforts from the World Bank, from the AMF, from the UN, from bilaterals to help countries develop their statistical capacity.
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Are we there?
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Not, but we have made a huge, huge, huge improvement in my it's very hard to put the number, but I think that when I look at the countries in uh especially in the emerging markets, it has been really, really impressive.
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Thank you, Philip.
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Philip, just wait a second because I need to put actually the charger back here.
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Um, but then we have the IFC question and the favorite number.
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Um okay, we're perfect.
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Good.
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Um good.
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Um Philip, you spoke a lot about the um the improvements, and uh obviously you inspired the young group of economists that I was part of.
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Um and then fast forward, um, you took over as the CEO of the International Financial Corporation, which is the largest, you know, basically we call it equity institution in the development field.
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Um, but equity, I think, in a in the non-World Bank way, maybe you can comment to this in a minute.
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Um, but tell us what your priorities were and also how that empiric economic mindset was important to help you know put IFC on the new track.
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Well, I took the IFC because it was um proposed to me by um um Jim Kim, the president.
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I left the World Bank because of him, because of his reforms, but he called me back when I was in London.
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Uh but I couldn't refuse because I saw from the World Bank side, uh I was frustrated by the fact that IFC, in my view, was not taking enough risk, was not going very much into Africa, or were very timid in Africa, but which is linked to a bit timid in terms of risk taking.
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Uh, I saw when I was VP for um for uh the East uh Europe that uh, for example, I mean AFC was uh investing in private quasi-monopolies or oligarchs.
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I didn't like that because that is good for the bottom line, but not very good for the welfare of the people of these countries.
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I mean, we all know that monopolies, private or public, are not usually very good and destroy welfare rather than increase it.
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So um so I had this chance, so I took it, and then very quickly I uh when I came to from London to DC, I met uh the US uh executive director who told me how welcome and um you're now at the head of a second rate commercial bank.
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That shocked me a lot because I knew there was improvement to be made in IFC, but that your number one shareholders tell you that.
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I mean, you're the head of a company now.
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Imagine your number one shareholder tells you that you're a second rate commercial bank.
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I mean, it's not very good.
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And the worst is that they were right.
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The board was not happy.
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Uh he was the most kind of direct, but uh the rest of the board was not very happy.
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And when I look at the numbers, here are the numbers again, uh they were right.
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Because, as you know, in the World Bank we have this independent evaluation that report to the board and they go for every project.
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And then evaluate exposed what have been the impact of the project, and then they rate it from unsatisfactory all the way to uh best practice and everything.
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But the average is kind of satisfactory.
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So if you take satisfactory and above, only 48% of uh IFC input uh projects were satisfactory and above.
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48%, less than half.
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So it's like flipping a coin, whether you have impact or no impact, which is uh horrible.
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So that was a huge so I push very hard two things.
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One is more on the AIDA countries, especially Africa, where we are doing much less than we should.
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Uh, and two, quantifying the development impact.
00:22:52.960 --> 00:22:58.480
After all, you quantify the the projected internal rate of return of your uh investment.
00:22:58.799 --> 00:23:03.839
Why can't we do it for the economic side on development impact?
00:23:04.480 --> 00:23:14.559
So we did that, it was a lot of work, and uh uh we had a whole new vice presidency headed by Hans-Peter Lankes to do that.
00:23:15.039 --> 00:23:36.079
So, and it was very successful and and it worked because at one point the director started to go to the board with two numbers: internal rate of return, which is how much profitable is your project, but as I said, you can invest in an oligarch, it's very profitable, but it's not very good for the economy or the social or the whatever.
00:23:36.480 --> 00:23:50.480
But then they have you had another number, which was the development impact from zero to 100, and done with uh a methodology that was quite rigorous that generated a lot of data, by the way, and numbers.
00:23:50.640 --> 00:23:58.559
We had to go and uh and dig very deep in many sectors in many countries, but we had a number, one synthetic number.
00:23:58.720 --> 00:24:07.519
So you go to the board, you say, well, we have an internal rate of return of 12, but uh uh development impact of 60 out of 100.
00:24:07.680 --> 00:24:11.119
Then the board grills you mostly on the 60.
00:24:11.359 --> 00:24:13.519
Why, how, what are your assumptions?
00:24:13.680 --> 00:24:20.400
And the and the team has all of a sudden to defend that, and not only that it is good for the bottom line.
00:24:20.640 --> 00:24:40.799
So that changed completely the dynamics inside the institution, and directors started to pay attention and their staff to not only the the finance but also the economics uh and the impact of uh of the of the projects, which was what I wanted.
00:24:41.039 --> 00:24:49.599
And also I developed uh the talking about data, a dashboard, very rich dashboard, because what is not measured doesn't get done.
00:24:50.640 --> 00:24:52.640
Um I believe in that.
00:24:52.720 --> 00:24:59.279
It's not uh it's someone much more famous than me that said it, um, but I think it's true.
00:24:59.599 --> 00:25:05.039
So I started every month to have a very thick package, and I had everything.
00:25:05.519 --> 00:25:08.480
And again, that's the X-ray of Wolfenson.
00:25:09.039 --> 00:25:20.960
Really, with a few tenths of numbers, you you could capture everything that was going on in the enterprise, in dynamics, and uh in stock, in flow, everything.
00:25:21.279 --> 00:25:37.839
So that was a very uh very uh very useful, and then I called the the whole reform drive that was very hard, ISC 3.0, because it was not only an evolution that we had evolutions before.
00:25:38.000 --> 00:25:48.559
IFC was first financing semen's and multilateral multinationals going to serve the world country at the time that in the 50s and 60s, in the 60s.
00:25:48.640 --> 00:25:49.200
Sorry.
00:25:50.079 --> 00:26:00.640
Then they moved in the 90s to uh uh local corporates, but always with the same thing, the same offer.
00:26:00.799 --> 00:26:05.519
What I proposed was very different, which was to change the operating system.
00:26:05.759 --> 00:26:09.599
In other words, to become proactive, not reactive.
00:26:09.839 --> 00:26:21.440
The model of the IFC was we finance the private sector, but the private sector has to come, propose the project, and then we decide whether we finance it or not based on risk and price.
00:26:21.599 --> 00:26:24.079
But like any commercial bank.
00:26:24.480 --> 00:26:25.920
So that was a model.
00:26:26.640 --> 00:26:43.039
What I said is if we want to go to Africa and the poorest country on earth, we need to be proactive because there is no there is no um not enough projects coming our ways in these uh regions.
00:26:43.839 --> 00:26:56.079
So becoming proactive entailed a lot of things, including becoming having strategies, including pushing the World Bank to push some reforms to help the private sector to prosper.
00:26:56.319 --> 00:27:20.880
Uh that meant imagining projects and then trying to find investors that would be interested and preparing and doing the work and the uh the preparatory work for investors to come at the project level, at the sector level, at the economic level, directly and indirectly through the World Bank.
00:27:21.119 --> 00:27:31.599
So that was a completely shift, but for that you needed a strategy, and for a strategy, you needed to have a very clear understanding of what was the situation for the private sector in that country.
00:27:31.759 --> 00:27:46.000
So I launched what came to be known as the private sector diagnostics, and you worked on the one in Kazakhstan thing, and I was adamant that it has to be done with the bank and the IFC.
00:27:46.160 --> 00:27:48.400
One way to force better collaboration.
00:27:48.559 --> 00:27:57.680
I knew the bank had better economists, but I knew that they didn't understand a lot of private finance and uh vice versa.
00:27:57.759 --> 00:28:02.079
In IFC, typically they understand private finance, but not necessarily uh economics.
00:28:02.480 --> 00:28:16.319
So that was a way to have the diagnostic as an input to the strategy of IFC in that country, proactive, and then pushing that into the global uh World Bank Group strategy.
00:28:16.480 --> 00:28:17.920
That was the idea.
00:28:18.160 --> 00:28:29.039
To be able to generate new projects that would not have come if we had just done nothing and waited for the system to come and bring us the project.
00:28:29.200 --> 00:28:39.599
So that's why IFC 3.0 is a shift in the operating system, as opposed to adding a geography or adding uh a new product.
00:28:39.759 --> 00:28:44.400
It was a way of thinking and of approaching uh the issue.
00:28:44.480 --> 00:29:03.599
And it worked because I checked the numbers recently because I had to make a presentation to the Asian Development Bank that was interested by AFC 3.0, and I checked that in fact we went from 19, 20 billion a year to 56 billion a year last year.
00:29:03.839 --> 00:29:09.279
So huge increase thanks to the capital increase that we got, thanks to the AFC 3.0.
00:29:10.000 --> 00:29:19.440
So that strategy worked, but it was a huge amount of efforts and reforms, and not necessarily very popular, as you know.
00:29:19.680 --> 00:29:24.640
Uh staff don't like changes typically, despite whatever they said.
00:29:24.880 --> 00:29:37.279
And that was a big shift in staff because when you wait for a project to come and then decide whether you will finance it or not, it's very different from you going out to find a project.
00:29:37.519 --> 00:29:38.880
Very different.
00:29:39.279 --> 00:29:44.799
And then we had to replace, in fact, 40% of the staff over three years or four years.
00:29:45.039 --> 00:29:53.920
So that was a big, big shift, but that was the cost of getting the capital increase, and in my view, survival of the AFC.
00:29:54.799 --> 00:30:04.160
Because, as I started to say, the board was, and for good reason, it was quantified, uh, becoming a second-rate commercial bank.
00:30:04.240 --> 00:30:05.440
Who needs that?
00:30:06.559 --> 00:30:07.440
We have plenty.
00:30:07.519 --> 00:30:13.599
I mean, the free, you know, you go to uh BNP Paribas, you can go to Mitsubishi Bank, you can go to JP Morgan.
00:30:13.680 --> 00:30:15.200
I mean, they are very good.
00:30:15.599 --> 00:30:23.279
If you try to do the same thing, you better privatize yourself and give uh the the money to AIDA then.
00:30:24.160 --> 00:30:27.119
And I guess these guys are not uh have a second rate, right?
00:30:27.200 --> 00:30:29.359
These are first-rate commercial banks.
00:30:29.440 --> 00:30:34.799
Um and uh just on this one, Philip, maybe as we close that for the substantive block.
00:30:34.960 --> 00:30:42.720
Um the um it's again, congratulations to what IFC is now achieving, and you laid the foundation there now.
00:30:42.960 --> 00:30:52.640
Um but the IFC story, and I guess the World Bank Group story is not um not this, not the regular, the not the norm now in this current day and age.
00:30:52.799 --> 00:31:04.880
Obviously, the development sector is undergoing severe cuts, severe challenges, obviously fragmentation of the world, new players, um, and obviously maybe the victim of its own success because governments themselves have the most resources.
00:31:05.119 --> 00:31:16.400
Where do you where do you put now IFC, the World Bank Group, in the broad architecture of development, and where you just see the development sector advancing the next decade or so?
00:31:17.440 --> 00:31:34.079
Well, there's been a huge shift in the last few years in the sense that the success in some sense of the emerging markets, especially uh in Asia, but not only, but especially in Asia and Eastern Europe, I mean, these guys are catching up very quickly.
00:31:34.240 --> 00:31:37.839
You go to Poland now, I mean, it's European countries.
00:31:38.079 --> 00:31:43.920
I I went to Poland uh 30 years ago, it was another it was another world.
00:31:44.160 --> 00:31:47.680
Uh, you go to China now, it was it's it's unbelievable.
00:31:48.000 --> 00:31:55.039
When I went to China in 87 for AFC, by the way, as a young professional, it was feudalism.
00:31:55.200 --> 00:31:59.440
I mean, the the technology was not there, uh very basic.
00:31:59.920 --> 00:32:02.799
So the progress has been unbelievable.
00:32:03.119 --> 00:32:03.920
Unbelievable.
00:32:04.079 --> 00:32:07.039
Poverty alleviation has been it's a miracle.
00:32:07.119 --> 00:32:16.880
I don't think that any other period in history we have seen such success in eliminating poverty, despite a huge increase in population.
00:32:17.759 --> 00:32:27.599
So, I mean, we can take some credit for you know the post-World War II uh system uh of trade.
00:32:27.759 --> 00:32:39.359
I believe trade was very powerful, uh and uh development finance and stability through the AMF on the macro side worked extremely well.
00:32:39.839 --> 00:32:43.279
I think that we need to repeat that again and again.
00:32:43.440 --> 00:32:48.559
Now things change in some sense because you are a victim of your own uh success.
00:32:49.279 --> 00:32:54.960
When I see that in Europe, some of the country or many of the countries are more indebted than emerging markets.
00:32:55.119 --> 00:33:00.559
So they say, well, if we are why should we borrow to land to China?
00:33:00.799 --> 00:33:08.000
So there's a questioning in Europe at least, and I think in the US also, to be honest, on aid.
00:33:08.960 --> 00:33:12.559
That we knew for the last what 50 years, half a century.
00:33:12.720 --> 00:33:17.519
So there's a questioning in uh and questioning is not a bad thing in itself.
00:33:18.799 --> 00:33:28.960
But I still believe that the we are much better in a world that is prosperous than in a world where poverty increases fundamentally.
00:33:29.279 --> 00:33:31.599
So, how do you morph this?
00:33:31.920 --> 00:33:40.720
So, in my view, it's a transition because traditional donors are cutting aid for many reasons.
00:33:40.880 --> 00:33:51.200
They want to increase their defense spending, they don't have enough fiscal rule, uh, their population, the appetite to uh the for international aid is coming down.
00:33:51.440 --> 00:33:53.039
A mixture of all this.
00:33:53.359 --> 00:33:54.480
So it's going down.
00:33:54.799 --> 00:34:05.680
Emerging markets are not ready yet to put uh aid kind of in a non-mercantilist way and multilateral.
00:34:06.559 --> 00:34:14.400
Part of it is because of the of the governance of many of the MDBs is against them.
00:34:14.480 --> 00:34:23.280
So if you put uh more money in uh some of the regional development bank, you may not get the shares that goes with it.
00:34:23.920 --> 00:34:26.079
So that's it has to be reopened.
00:34:26.159 --> 00:34:32.719
But that's hard because those that are uh having the control don't want to lose it.
00:34:32.960 --> 00:34:35.599
So there's a governance uh issue.
00:34:35.760 --> 00:34:48.320
So the transition between uh Europe and traditional donors and potential new donors, we are a bit caught and we are not yet uh this transition is not happening and has not happened.
00:34:48.639 --> 00:34:53.519
Also, China is increasing, but we are still a long way.
00:34:54.079 --> 00:34:55.360
Uh so that's one.
00:34:55.519 --> 00:35:09.519
And second, the the type, because we have been successful, I think more and more will be on the donors on the on the private sector side, which was a little bit what I tried to do with IFC.
00:35:09.599 --> 00:35:13.440
So in my view, IFC should be as big as the World Bank.
00:35:14.079 --> 00:35:17.679
An economy should work on two legs, public and private.
00:35:17.920 --> 00:35:21.280
And the private was tiny compared to the public in the World Bank.
00:35:21.440 --> 00:35:24.880
This is changing, and I think this is the direction of travel.
00:35:24.960 --> 00:35:33.199
I I don't anticipate massive increase to IDA, on the contrary, it will be harder and harder as time goes by.
00:35:33.360 --> 00:35:57.599
Uh IDA is for uh government loans subsidized or on concessional terms, which means donors have to contribute every three years, but IFC can come can continue to grow if they're ready to take more risk, to be creative, and to work upstream and work public-private.
00:35:57.760 --> 00:36:00.400
I don't know an economy that is completely private.
00:36:00.559 --> 00:36:05.920
I don't know even the pure communist country are not completely public.
00:36:06.559 --> 00:36:08.880
The reality is a mix of the two.
00:36:08.960 --> 00:36:14.159
The problem is where you put the cursor, but that's another story.
00:36:14.400 --> 00:36:21.440
Um, so that's what I think that it's gonna be a difficult moment of evolution and change.
00:36:22.079 --> 00:36:30.559
And uh I see from uh on the bilateral, regional, and international, at all level, it's gonna be harder.
00:36:31.119 --> 00:36:45.199
And uh but the private sector will have its um, but everybody will have an incentive to to improve private sector flows uh to uh emerging countries, but it has to be on a win-win.
00:36:45.280 --> 00:36:49.519
A win for the investor and win for the recipient countries.
00:36:49.760 --> 00:36:53.280
So that's in fact, that's where I believe we're going.
00:36:54.880 --> 00:37:01.280
Philip, thank you for for your perspective and all your wisdom over decades of experience.
00:37:01.440 --> 00:37:06.880
And and Philip, the this podcast always ends with the question of your favorite number.
00:37:07.039 --> 00:37:11.840
So tell us your favorite number and the story behind that number.
00:37:12.239 --> 00:37:17.280
A lot of people will give you their mother's birthday or their own birthday or something, I assume.
00:37:17.440 --> 00:37:22.559
But for me, and I thought about because you you you warned me about the question.
00:37:22.719 --> 00:37:25.840
I have to be honest with everybody and transparent.
00:37:26.239 --> 00:37:36.000
Uh, I thought about it, and uh I think that really what I don't know if it's my favorite, but the one that puzzles me and fascinates me the most is zero.
00:37:37.440 --> 00:37:42.880
I always thought put yourself in the shoes of a you know a caveman.
00:37:44.079 --> 00:37:51.840
You can count one, two, three, you have one, you know, one pig, two pigs, three pigs, or sheep or whatever, or grains.
00:37:52.639 --> 00:37:53.760
But zero.
00:37:54.400 --> 00:37:58.639
The concept of zero and was not obvious.
00:37:58.880 --> 00:38:00.800
In fact, it was a huge breakthrough.
00:38:00.880 --> 00:38:12.159
I don't know who is a genius, or maybe a string of genius, to come, and apparently it came from uh philosophy um from uh India, the concept of nothingness.
00:38:12.400 --> 00:38:17.519
But then how do you take this philosophical concept into a numerals?
00:38:18.159 --> 00:38:21.760
And that enabled you to do decimals to do the 19.
00:38:21.920 --> 00:38:31.519
What is 19 in in Greek or in Roman or 1957, my birthday?
00:38:31.760 --> 00:38:38.480
I mean, you know, it's a lot of X and Y's and V's and stuff, it makes no sense.
00:38:38.800 --> 00:38:44.639
So zero for me was uh is the most fascinating uh number for me.
00:38:44.800 --> 00:38:55.280
The guy or the that came up with it is one of the huge geniuses of uh the human history, in my view.
00:38:56.719 --> 00:38:59.920
Well, zero, where math and philosophy meet.
00:39:00.079 --> 00:39:03.840
I didn't expect to end us on that note, but it's even more fascinating.
00:39:03.920 --> 00:39:06.159
Thank you so much, Philip, for being on the show.
00:39:06.639 --> 00:39:08.000
Thank you, Wolfgang.
00:39:08.079 --> 00:39:08.559
Take care.
00:00:00.400 --> 00:00:03.919
Welcome everybody to another edition of Data Talks.
00:00:04.320 --> 00:00:06.959
This is a very special occasion for me.
00:00:07.040 --> 00:00:10.560
I'm speaking to my previous boss, Philip Loharou.
00:00:10.880 --> 00:00:19.359
He has a very distinguished career with the World Bank, also with the European Bank, previous managing director and CEO of the IFC.
00:00:19.519 --> 00:00:21.199
Welcome to the show, Philip.
00:00:21.519 --> 00:00:22.879
Thank you, Wolfgang.
00:00:23.519 --> 00:00:25.199
Glad to be here with you.
00:00:25.679 --> 00:00:27.280
So good to have you, Philip.
00:00:27.440 --> 00:00:31.839
Obviously, you were uh a legendary person at the World Bank.
00:00:31.920 --> 00:00:35.840
I think everybody would say that who worked with you or interacted with you.
00:00:36.000 --> 00:00:42.079
Um and uh and a very long career, but uh we always start with a person and how it all started.
00:00:42.240 --> 00:00:48.000
And in your case, and I know this uh through our own interactions in Africa, it started in Ethiopia.
00:00:48.159 --> 00:00:53.200
So tell us about your time in Ethiopia at school and how that shaped you.
00:00:53.920 --> 00:01:01.439
Well, I arrived uh in in Addis because I was following my father who uh who had the job uh there for research.
00:01:01.600 --> 00:01:07.840
He was a scientist and working on uh climate change, although at the time it was not called like this.
00:01:08.480 --> 00:01:14.079
And that was in 73, 74, 75, that's what we're talking about.
00:01:14.480 --> 00:01:26.159
And that was also when the um the Derg uh got rid of the emperor, Alice Alassier, and started the revolution.
00:01:26.959 --> 00:01:38.560
So, and here I was at the last year of the French uh school, you know, it's called Terminal, literally the last year of the high school, and then you go to university.
00:01:38.719 --> 00:01:48.480
So I was in Terminal, I was 17, and uh in Addis Abeba just during this the beginning of this revolution.
00:01:49.680 --> 00:01:54.400
And so my focus at school was really math and science.
00:01:54.719 --> 00:01:55.040
Why?
00:01:55.200 --> 00:02:01.840
Because it was easy, uh, not that it was easy for me, but it was good input-output ratio.
00:02:02.159 --> 00:02:16.560
It was so important as a coefficient for the general average that a little effort in math was better, went much further than a lot of efforts in French or English or geography or history.
00:02:17.039 --> 00:02:24.240
So it was for me a way, and then my father was a scientist, so uh was being pushed in this direction.
00:02:24.800 --> 00:02:52.639
But then in Ethiopia I started to see after this revolution, or during the revolution, a lot of uh young uh Ethiopians, including in school, in the French school in uh in Gebremariam in Addis Abeba, being killed and tortured, and that's in the name of three white men from a century ago, like Marx Engels and Lenin.
00:02:52.719 --> 00:03:04.719
So three white men in the middle of Africa in a country that was uh an imperial country with um uh a very traditional structure.
00:03:04.879 --> 00:03:08.400
Uh and and for these three guys, people were killing themselves.
00:03:08.479 --> 00:03:10.479
So I it was very hard for me.
00:03:10.879 --> 00:03:19.280
And again, that's why he said I was in mathematics, I was not into politics, literature, maybe it will have helped me to understand, but I couldn't understand.
00:03:19.439 --> 00:03:20.719
It was just that simple.
00:03:20.879 --> 00:03:22.719
I just couldn't understand.
00:03:23.039 --> 00:03:33.360
And to be honest, sorry I take a little bit of time on this one, but I can say that since then, since 17, that traumatic experiment for me.
00:03:33.520 --> 00:03:43.759
It was really traumatic, but it was also foundational in the sense that I spent really the rest of my life trying to understand this basic question.
00:03:44.240 --> 00:03:47.439
Why do you kill young kids?
00:03:47.599 --> 00:03:58.000
I mean, 17, 18, 19 students, uh in the name of principles and ideology that is important.
00:03:58.240 --> 00:03:59.199
It's not even yours.
00:03:59.280 --> 00:04:04.240
I mean, it's just and not necessarily adapted to the to your condition.
00:04:04.719 --> 00:04:14.800
I didn't know all this, so I read everything Marxist, I read all Marx, including Das Capital, that many have not read, and it's very difficult to digest.
00:04:15.039 --> 00:04:24.000
I read all Lenin, I read Engels, I read everything, because it was the distributed for free, by the way, by the revolution.
00:04:24.079 --> 00:04:26.560
That was the only perk of this thing.
00:04:26.720 --> 00:04:29.519
But it was a very tough thing, it was very violent.
00:04:29.680 --> 00:04:33.920
Uh, there is a museum now in Addis on this period.
00:04:34.079 --> 00:04:36.160
It's what's called the Red Terror.
00:04:36.720 --> 00:04:44.639
And you have, if you go to this museum, it's a very small one, but it's mostly photograph and uh artifacts, it's horrible.
00:04:44.959 --> 00:05:01.279
It's really uh I'm sure that plenty of those in during the history, um, many, many of those, but that's the one I witnessed when I was uh in uh at 17 year old, very impressionable.
00:05:01.920 --> 00:05:05.600
And uh at the point where I had to decide my life.
00:05:05.839 --> 00:05:08.800
In fact, I thought it was all directed.
00:05:08.879 --> 00:05:13.120
I would have ended up as a scientist or um medical doctor or something.
00:05:13.839 --> 00:05:15.519
That was uh there was no question.
00:05:15.600 --> 00:05:19.279
I mean, it was really on a one-track mind.
00:05:19.839 --> 00:05:32.560
Um but I Ethiopia kind of hijacked completely and shaped my whole uh career and my whole life, to be honest, and many things that I thought and triggered uh the questions.
00:05:32.720 --> 00:05:38.720
And you know, as you know, one question triggers another question, and you start digging and digging and digging and digging.
00:05:38.800 --> 00:05:39.920
So I'll stop here.
00:05:40.079 --> 00:05:45.519
But it was really traumatic and foundational for me.
00:05:46.399 --> 00:05:52.639
And and Philippe, you I think previously even called it like that ideology kills.
00:05:52.800 --> 00:05:59.199
Um, and and how is this in contrast to then later the life when we met right at the World Bank?
00:05:59.439 --> 00:06:07.519
Why was that you know work in development such a contrast in for you to the experience you just shared with us?
00:06:09.040 --> 00:06:29.839
Well, I mean, again, fundamentally, little by little, you and the fact that again science was important in my life, uh, evidence-based uh analysis and then conclusion and their action for me became very, very important.
00:06:30.240 --> 00:06:41.600
I realized that was that if you don't do that, you substitute that by a whole ready-made ideology that may fit or not fit reality.
00:06:41.759 --> 00:06:49.439
And when reality doesn't fit an ideology, then this is where the violence starts because you try to push it by force.
00:06:49.920 --> 00:06:56.079
So that's kind of uh I'm I'm taking a lot of shortcuts here, but that's what I found.
00:06:56.240 --> 00:07:06.639
So I felt good at the World Bank, and that's why I stayed much longer than I expected to, um, because it was fundamentally evidence-based.
00:07:06.879 --> 00:07:10.399
The premium of data was very important.
00:07:10.639 --> 00:07:21.199
I think we should done we should have done even more to develop the data systems in countries, but the bank has done some, could have done more.
00:07:21.680 --> 00:07:35.759
But uh for me it uh it was the only way because when you're faced to a problem, um you have two ways you you need to when you're a decision maker, okay?
00:07:36.319 --> 00:07:38.240
You have to make a decision.
00:07:39.199 --> 00:07:42.160
Now, how do you make a decision based on what?
00:07:43.600 --> 00:07:45.680
Some kind of analysis, okay.
00:07:45.839 --> 00:07:48.079
But what is the input to the analysis?
00:07:48.560 --> 00:07:50.560
If you can, you have the data.
00:07:51.360 --> 00:08:03.360
If you can't, you substitute by the ready-made set of uh preconceived ideas that come from wherever in history, and that is when it becomes dangerous for me.
00:08:04.319 --> 00:08:10.160
And that's the bank by being evidence-based and based on data, was important.
00:08:10.319 --> 00:08:16.319
By the way, uh, one thing you can quote, it's a quote from Wolfenson.
00:08:16.720 --> 00:08:23.040
I know I told you that uh the data I sent you on mission and asking you to bring data no matter what.
00:08:23.519 --> 00:08:32.240
Micro, macro, wrong, not wrong, because then you can always try to check, double check, uh, cross-check.
00:08:33.120 --> 00:08:36.000
But um it's better than nothing.
00:08:36.639 --> 00:08:48.080
But I had uh the same uh uh uh problem once with um Wolfenson, who was the president of the World Bank at one point, and I was doing the AIDA replenishment.
00:08:49.600 --> 00:08:53.279
And he was always asking me, what is the present value of this?
00:08:53.440 --> 00:08:54.639
What is the present value of that?
00:08:54.799 --> 00:08:57.279
And I was really furious because I didn't know.
00:08:58.320 --> 00:09:00.559
And he could do the present value mentally.
00:09:00.720 --> 00:09:01.840
I couldn't.
00:09:02.240 --> 00:09:11.679
And I was pissed because I wanted to go for strategic direction, not for a freaking present value of that string of data or whatever with that.
00:09:11.840 --> 00:09:13.279
My staff could do it.
00:09:13.519 --> 00:09:17.759
So I complained and I told him, I mean, stop asking me, you know, the present value.
00:09:17.840 --> 00:09:23.759
I mean, I can do it like you on mentally, and my staff can do it on their computer, no problem.
00:09:23.919 --> 00:09:26.000
But what I want you is some strategic guidance.
00:09:26.080 --> 00:09:27.039
And he was shocked.
00:09:27.200 --> 00:09:30.320
But he looked at me and I think he had a fantastic comeback.
00:09:30.399 --> 00:09:37.679
He said, Listen, numbers are the x-ray to many problems or many issues.
00:09:37.919 --> 00:09:42.000
I think that could be a title for your our uh little discussion.
00:09:42.159 --> 00:09:48.879
It's not mine, it's uh it's a better way to say what I told you when uh you were a young economist.
00:09:49.279 --> 00:09:53.440
Uh, but that's what Wolfenson told me when I was a director for IDA.
00:09:55.279 --> 00:09:55.919
Super.
00:09:56.480 --> 00:09:58.320
Thanks so much, Shachamin.
00:09:58.480 --> 00:10:01.200
I think um I'll ask the team to put it together now.
00:10:01.279 --> 00:10:05.120
I think that that the voice is good now and even better than last time.
00:10:05.279 --> 00:10:05.840
Super.
00:10:06.000 --> 00:10:11.919
Thanks so much for we can do some of the other thing now, so you can have something to play with.
00:10:12.080 --> 00:10:14.159
I don't know what is the quality of the rest.
00:10:14.799 --> 00:10:17.120
Um the rest was uh sure.
00:10:17.360 --> 00:10:24.960
Um yeah, the wait a quick second, because we went then right into the I think the World Bank part.
00:10:25.440 --> 00:10:28.159
Uh let me just do this one kind thing.
00:10:29.120 --> 00:10:33.519
Um one second.
00:10:35.440 --> 00:10:40.000
Okay, this was okay.
00:10:40.720 --> 00:10:44.960
Um good, okay.
00:10:45.039 --> 00:10:52.720
Then let's um um good, then we'll it's funny because you already anticipated it, but I'll I'll keep going.
00:10:53.039 --> 00:10:58.000
Um so Philip, we first met in the um uh in the early 2000s.
00:10:58.159 --> 00:11:13.360
You were uh the manager at that time what was called sector manager still of Southern Africa that included Madagascar and Comor Islands, which is also a region that you previously uh were responsible for as what you could be called the World Bank Ambassador out of Madagascar.
00:11:13.519 --> 00:11:24.720
And I remember still, I went on on this mission to Comoro Islands, and then uh you said, Wolfgang, bring me back data, as you just said, whatever it is, because you you call it that time, and I think you stand by that.
00:11:24.799 --> 00:11:26.639
It cuts through a lot of crap.
00:11:26.799 --> 00:11:34.639
Um tell us a bit about that that mindset, that quantitative mindset that you had and that you wanted to instill into your teams.
00:11:35.679 --> 00:11:39.919
Again, it comes from some of what we discussed earlier.
00:11:40.240 --> 00:11:54.720
I mean, um that is the link to the Ethiopia and everything, kind of uh uh permanent um search for evidence.
00:11:56.000 --> 00:12:03.600
Uh and the problem with evidence is when you come with a very small detail, I mean the problem is it is is it material?
00:12:03.840 --> 00:12:07.120
So you met someone very rich in that country.
00:12:07.279 --> 00:12:09.440
It means that everybody is rich in this country?
00:12:09.600 --> 00:12:10.639
No, obviously.
00:12:10.879 --> 00:12:14.799
And whatever, I take this example, it just comes through my mind.
00:12:15.039 --> 00:12:17.200
So the problem is materiality.
00:12:18.320 --> 00:12:21.200
So you really need to find some data.
00:12:21.360 --> 00:12:36.879
And if you don't have structured, well-structured data with a good GDP, with uh everything behind the GDP, very well documented, etc., then you have to try to do your best to come close to it through proxies.
00:12:37.600 --> 00:12:56.480
And I think even if it's far from perfect, proxies that try to do that, to say what is the situation to grasp a situation and the materiality of this situation is better than nothing, or just what you heard at the hotel during the mission.
00:12:57.120 --> 00:13:00.000
Or, you know, a couple of traders that you talk to.
00:13:00.240 --> 00:13:03.120
It's important, but it's you see what I'm saying?
00:13:03.200 --> 00:13:23.679
So that for me was always kind of this drive to try to go beyond the simplification of and the expediency of just picking a few things and uh either a full concept, ideologic, but also just something.
00:13:23.759 --> 00:13:27.120
You know, people are rich or they're or they're poor or whatever.
00:13:27.279 --> 00:13:33.919
Uh a statement that try to capture reality, but behind it, you need to document it.
00:13:34.080 --> 00:13:39.759
So this obsession to document, I think, came from that experiment in Ethiopia.
00:13:40.000 --> 00:13:46.159
You need to have the best possible diagnosis with whatever you have.
00:13:46.720 --> 00:13:50.399
If you have in a very data-intensive uh country, great.
00:13:50.639 --> 00:14:02.559
So then you have a lot of other theories and uh and how to use the data that you have at your disposals, and that's probabilities, statistics, no matter what.
00:14:02.639 --> 00:14:07.200
But if you are in a country with very little statistics, try to build them.
00:14:07.519 --> 00:14:08.559
Go interviews.
00:14:08.639 --> 00:14:11.200
That's why the bank used a lot of surveys.
00:14:11.519 --> 00:14:18.240
And uh the the thing started in the 90s when we got into poverty under Wolf and Son, by the way.
00:14:18.399 --> 00:14:20.320
Uh, but that's they are very useful.
00:14:20.399 --> 00:14:25.519
And I'm sure that where you stand now, you can witness to that.
00:14:25.759 --> 00:14:26.799
But what is a survey?
00:14:26.960 --> 00:14:43.440
It's to try again to have representative data so that you can make something out of it that is not wrong by from from inception, because the data behind is wrong.
00:14:43.519 --> 00:14:48.960
It's like I for me, I always like comparison with medical comparisons.
00:14:49.200 --> 00:15:08.639
If your diagnostic is wrong, because you got the wrong temperature, you got the wrong x-ray, you got everything that as an input, everything is wrong, then you'll have the wrong diagnostic that will lead to the wrong treatment that may lead to uh very serious conditions down the line.
00:15:08.799 --> 00:15:11.919
I think economics it's a little bit the same and social.
00:15:12.320 --> 00:15:13.759
So you need the data.
00:15:13.919 --> 00:15:18.720
For me, the x-ray, it's not a bad way to think about it.
00:15:18.879 --> 00:15:25.200
And when you again in a country with scant data, go after it.
00:15:25.919 --> 00:15:33.440
It's not easy, you don't go behind, you can stay in some country, everything is available, so it's great, but in some countries not.
00:15:33.519 --> 00:15:35.919
So go for it because there's always data.
00:15:36.159 --> 00:15:45.120
And you can find proxy, you have to have to be imaginative, you can find a lot of uh proxies, and then use judgment.
00:15:45.360 --> 00:15:55.360
Again, data doesn't uh exclude judgment, you have to apply still the judgment on the data.
00:15:55.840 --> 00:16:02.159
One thing I like very much at the World Bank is the exercise in prem in for the macro to go through modeling.
00:16:02.399 --> 00:16:11.120
You know, we had the RIMSIN X model, which was maybe very simplistic, but it forced you to ask some basic question.
00:16:11.840 --> 00:16:14.559
How can I grow if imports go down?
00:16:15.279 --> 00:16:18.240
Where will the equipment for investment come from?
00:16:18.720 --> 00:16:21.759
And if I cannot invest, how can I grow?
00:16:22.000 --> 00:16:26.240
I mean, you know, basic stuff because otherwise the system doesn't work.
00:16:27.360 --> 00:16:35.440
So I think that this is the strength and the power of data, but at the end, you you need your judgment.
00:16:35.519 --> 00:16:38.240
So it's the combination that is powerful.
00:16:39.519 --> 00:16:40.480
Thank you, Philip.
00:16:40.559 --> 00:16:44.960
Things have to add up, um, as you implicitly um highlight here.
00:16:45.120 --> 00:16:59.440
And Philip, you obviously have been around for a long time in that field, and not just with the World Bank and its sister organization IFC, but also uh with the European Bank in London, and now as the chairman of the French Development Corporation.
00:16:59.679 --> 00:17:07.519
Um how what's your assessment of how far the development sector has come in providing good data?
00:17:07.680 --> 00:17:13.440
How much do you think uh the the industry is at the frontier and how much more could it do?
00:17:15.359 --> 00:17:20.480
I think we've done we've we went a long, long way on the positive side.
00:17:21.039 --> 00:17:29.440
Um in improving data in all the sectors in many countries, including some very poor.
00:17:29.680 --> 00:17:37.839
Now, to go to countries where you have very little data, you really have to go to countries that are post-conflict or in conflict.
00:17:38.319 --> 00:17:46.000
Where, but I I I saw during my career of what 40 years, a huge improvement.
00:17:46.240 --> 00:17:46.960
Is it perfect?
00:17:47.039 --> 00:17:48.000
No, can we improve?
00:17:48.079 --> 00:17:52.799
Yes, but we can say we can improve also uh in the most advanced countries.
00:17:52.960 --> 00:17:56.079
Um, but I think we went a long, long way.
00:17:56.480 --> 00:18:18.160
I think that the quality of management in emerging markets has been improving, or public uh policy has been improving, and every minister of finance, prime minister, or president uh wants to make sure that, like a pilot in a plane, there have tools to navigate, or in a boat.
00:18:18.319 --> 00:18:21.440
You need tools and numbers to navigate.
00:18:22.160 --> 00:18:34.240
Uh so I think that, and then there have been a lot of efforts from the World Bank, from the AMF, from the UN, from bilaterals to help countries develop their statistical capacity.
00:18:34.799 --> 00:18:35.599
Are we there?
00:18:35.759 --> 00:18:52.559
Not, but we have made a huge, huge, huge improvement in my it's very hard to put the number, but I think that when I look at the countries in uh especially in the emerging markets, it has been really, really impressive.
00:18:53.759 --> 00:18:54.559
Thank you, Philip.
00:18:54.720 --> 00:18:59.279
Philip, just wait a second because I need to put actually the charger back here.
00:18:59.359 --> 00:19:03.119
Um, but then we have the IFC question and the favorite number.
00:19:03.279 --> 00:19:05.119
Um okay, we're perfect.
00:19:05.279 --> 00:19:05.680
Good.
00:19:05.839 --> 00:19:07.119
Um good.
00:19:07.599 --> 00:19:16.720
Um Philip, you spoke a lot about the um the improvements, and uh obviously you inspired the young group of economists that I was part of.
00:19:16.799 --> 00:19:31.440
Um and then fast forward, um, you took over as the CEO of the International Financial Corporation, which is the largest, you know, basically we call it equity institution in the development field.
00:19:31.519 --> 00:19:36.559
Um, but equity, I think, in a in the non-World Bank way, maybe you can comment to this in a minute.
00:19:36.720 --> 00:19:47.839
Um, but tell us what your priorities were and also how that empiric economic mindset was important to help you know put IFC on the new track.
00:19:48.720 --> 00:19:57.119
Well, I took the IFC because it was um proposed to me by um um Jim Kim, the president.
00:19:57.279 --> 00:20:03.039
I left the World Bank because of him, because of his reforms, but he called me back when I was in London.
00:20:03.440 --> 00:20:24.799
Uh but I couldn't refuse because I saw from the World Bank side, uh I was frustrated by the fact that IFC, in my view, was not taking enough risk, was not going very much into Africa, or were very timid in Africa, but which is linked to a bit timid in terms of risk taking.
00:20:25.599 --> 00:20:41.759
Uh, I saw when I was VP for um for uh the East uh Europe that uh, for example, I mean AFC was uh investing in private quasi-monopolies or oligarchs.
00:20:42.000 --> 00:20:49.200
I didn't like that because that is good for the bottom line, but not very good for the welfare of the people of these countries.
00:20:49.359 --> 00:20:56.559
I mean, we all know that monopolies, private or public, are not usually very good and destroy welfare rather than increase it.
00:20:57.039 --> 00:21:16.960
So um so I had this chance, so I took it, and then very quickly I uh when I came to from London to DC, I met uh the US uh executive director who told me how welcome and um you're now at the head of a second rate commercial bank.
00:21:17.279 --> 00:21:26.720
That shocked me a lot because I knew there was improvement to be made in IFC, but that your number one shareholders tell you that.
00:21:26.880 --> 00:21:28.559
I mean, you're the head of a company now.
00:21:28.720 --> 00:21:34.960
Imagine your number one shareholder tells you that you're a second rate commercial bank.
00:21:35.119 --> 00:21:36.640
I mean, it's not very good.
00:21:37.279 --> 00:21:39.920
And the worst is that they were right.
00:21:40.079 --> 00:21:42.160
The board was not happy.
00:21:42.559 --> 00:21:48.000
Uh he was the most kind of direct, but uh the rest of the board was not very happy.
00:21:48.240 --> 00:21:53.039
And when I look at the numbers, here are the numbers again, uh they were right.
00:21:53.279 --> 00:21:59.599
Because, as you know, in the World Bank we have this independent evaluation that report to the board and they go for every project.
00:22:00.079 --> 00:22:10.880
And then evaluate exposed what have been the impact of the project, and then they rate it from unsatisfactory all the way to uh best practice and everything.
00:22:11.039 --> 00:22:13.440
But the average is kind of satisfactory.
00:22:13.680 --> 00:22:23.759
So if you take satisfactory and above, only 48% of uh IFC input uh projects were satisfactory and above.
00:22:24.079 --> 00:22:26.480
48%, less than half.
00:22:26.720 --> 00:22:34.000
So it's like flipping a coin, whether you have impact or no impact, which is uh horrible.
00:22:35.039 --> 00:22:39.119
So that was a huge so I push very hard two things.
00:22:39.359 --> 00:22:49.119
One is more on the AIDA countries, especially Africa, where we are doing much less than we should.
00:22:49.359 --> 00:22:52.799
Uh, and two, quantifying the development impact.
00:22:52.960 --> 00:22:58.480
After all, you quantify the the projected internal rate of return of your uh investment.
00:22:58.799 --> 00:23:03.839
Why can't we do it for the economic side on development impact?
00:23:04.480 --> 00:23:14.559
So we did that, it was a lot of work, and uh uh we had a whole new vice presidency headed by Hans-Peter Lankes to do that.
00:23:15.039 --> 00:23:36.079
So, and it was very successful and and it worked because at one point the director started to go to the board with two numbers: internal rate of return, which is how much profitable is your project, but as I said, you can invest in an oligarch, it's very profitable, but it's not very good for the economy or the social or the whatever.
00:23:36.480 --> 00:23:50.480
But then they have you had another number, which was the development impact from zero to 100, and done with uh a methodology that was quite rigorous that generated a lot of data, by the way, and numbers.
00:23:50.640 --> 00:23:58.559
We had to go and uh and dig very deep in many sectors in many countries, but we had a number, one synthetic number.
00:23:58.720 --> 00:24:07.519
So you go to the board, you say, well, we have an internal rate of return of 12, but uh uh development impact of 60 out of 100.
00:24:07.680 --> 00:24:11.119
Then the board grills you mostly on the 60.
00:24:11.359 --> 00:24:13.519
Why, how, what are your assumptions?
00:24:13.680 --> 00:24:20.400
And the and the team has all of a sudden to defend that, and not only that it is good for the bottom line.
00:24:20.640 --> 00:24:40.799
So that changed completely the dynamics inside the institution, and directors started to pay attention and their staff to not only the the finance but also the economics uh and the impact of uh of the of the projects, which was what I wanted.
00:24:41.039 --> 00:24:49.599
And also I developed uh the talking about data, a dashboard, very rich dashboard, because what is not measured doesn't get done.
00:24:50.640 --> 00:24:52.640
Um I believe in that.
00:24:52.720 --> 00:24:59.279
It's not uh it's someone much more famous than me that said it, um, but I think it's true.
00:24:59.599 --> 00:25:05.039
So I started every month to have a very thick package, and I had everything.
00:25:05.519 --> 00:25:08.480
And again, that's the X-ray of Wolfenson.
00:25:09.039 --> 00:25:20.960
Really, with a few tenths of numbers, you you could capture everything that was going on in the enterprise, in dynamics, and uh in stock, in flow, everything.
00:25:21.279 --> 00:25:37.839
So that was a very uh very uh very useful, and then I called the the whole reform drive that was very hard, ISC 3.0, because it was not only an evolution that we had evolutions before.
00:25:38.000 --> 00:25:48.559
IFC was first financing semen's and multilateral multinationals going to serve the world country at the time that in the 50s and 60s, in the 60s.
00:25:48.640 --> 00:25:49.200
Sorry.
00:25:50.079 --> 00:26:00.640
Then they moved in the 90s to uh uh local corporates, but always with the same thing, the same offer.
00:26:00.799 --> 00:26:05.519
What I proposed was very different, which was to change the operating system.
00:26:05.759 --> 00:26:09.599
In other words, to become proactive, not reactive.
00:26:09.839 --> 00:26:21.440
The model of the IFC was we finance the private sector, but the private sector has to come, propose the project, and then we decide whether we finance it or not based on risk and price.
00:26:21.599 --> 00:26:24.079
But like any commercial bank.
00:26:24.480 --> 00:26:25.920
So that was a model.
00:26:26.640 --> 00:26:43.039
What I said is if we want to go to Africa and the poorest country on earth, we need to be proactive because there is no there is no um not enough projects coming our ways in these uh regions.
00:26:43.839 --> 00:26:56.079
So becoming proactive entailed a lot of things, including becoming having strategies, including pushing the World Bank to push some reforms to help the private sector to prosper.
00:26:56.319 --> 00:27:20.880
Uh that meant imagining projects and then trying to find investors that would be interested and preparing and doing the work and the uh the preparatory work for investors to come at the project level, at the sector level, at the economic level, directly and indirectly through the World Bank.
00:27:21.119 --> 00:27:31.599
So that was a completely shift, but for that you needed a strategy, and for a strategy, you needed to have a very clear understanding of what was the situation for the private sector in that country.
00:27:31.759 --> 00:27:46.000
So I launched what came to be known as the private sector diagnostics, and you worked on the one in Kazakhstan thing, and I was adamant that it has to be done with the bank and the IFC.
00:27:46.160 --> 00:27:48.400
One way to force better collaboration.
00:27:48.559 --> 00:27:57.680
I knew the bank had better economists, but I knew that they didn't understand a lot of private finance and uh vice versa.
00:27:57.759 --> 00:28:02.079
In IFC, typically they understand private finance, but not necessarily uh economics.
00:28:02.480 --> 00:28:16.319
So that was a way to have the diagnostic as an input to the strategy of IFC in that country, proactive, and then pushing that into the global uh World Bank Group strategy.
00:28:16.480 --> 00:28:17.920
That was the idea.
00:28:18.160 --> 00:28:29.039
To be able to generate new projects that would not have come if we had just done nothing and waited for the system to come and bring us the project.
00:28:29.200 --> 00:28:39.599
So that's why IFC 3.0 is a shift in the operating system, as opposed to adding a geography or adding uh a new product.
00:28:39.759 --> 00:28:44.400
It was a way of thinking and of approaching uh the issue.
00:28:44.480 --> 00:29:03.599
And it worked because I checked the numbers recently because I had to make a presentation to the Asian Development Bank that was interested by AFC 3.0, and I checked that in fact we went from 19, 20 billion a year to 56 billion a year last year.
00:29:03.839 --> 00:29:09.279
So huge increase thanks to the capital increase that we got, thanks to the AFC 3.0.
00:29:10.000 --> 00:29:19.440
So that strategy worked, but it was a huge amount of efforts and reforms, and not necessarily very popular, as you know.
00:29:19.680 --> 00:29:24.640
Uh staff don't like changes typically, despite whatever they said.
00:29:24.880 --> 00:29:37.279
And that was a big shift in staff because when you wait for a project to come and then decide whether you will finance it or not, it's very different from you going out to find a project.
00:29:37.519 --> 00:29:38.880
Very different.
00:29:39.279 --> 00:29:44.799
And then we had to replace, in fact, 40% of the staff over three years or four years.
00:29:45.039 --> 00:29:53.920
So that was a big, big shift, but that was the cost of getting the capital increase, and in my view, survival of the AFC.
00:29:54.799 --> 00:30:04.160
Because, as I started to say, the board was, and for good reason, it was quantified, uh, becoming a second-rate commercial bank.
00:30:04.240 --> 00:30:05.440
Who needs that?
00:30:06.559 --> 00:30:07.440
We have plenty.
00:30:07.519 --> 00:30:13.599
I mean, the free, you know, you go to uh BNP Paribas, you can go to Mitsubishi Bank, you can go to JP Morgan.
00:30:13.680 --> 00:30:15.200
I mean, they are very good.
00:30:15.599 --> 00:30:23.279
If you try to do the same thing, you better privatize yourself and give uh the the money to AIDA then.
00:30:24.160 --> 00:30:27.119
And I guess these guys are not uh have a second rate, right?
00:30:27.200 --> 00:30:29.359
These are first-rate commercial banks.
00:30:29.440 --> 00:30:34.799
Um and uh just on this one, Philip, maybe as we close that for the substantive block.
00:30:34.960 --> 00:30:42.720
Um the um it's again, congratulations to what IFC is now achieving, and you laid the foundation there now.
00:30:42.960 --> 00:30:52.640
Um but the IFC story, and I guess the World Bank Group story is not um not this, not the regular, the not the norm now in this current day and age.
00:30:52.799 --> 00:31:04.880
Obviously, the development sector is undergoing severe cuts, severe challenges, obviously fragmentation of the world, new players, um, and obviously maybe the victim of its own success because governments themselves have the most resources.
00:31:05.119 --> 00:31:16.400
Where do you where do you put now IFC, the World Bank Group, in the broad architecture of development, and where you just see the development sector advancing the next decade or so?
00:31:17.440 --> 00:31:34.079
Well, there's been a huge shift in the last few years in the sense that the success in some sense of the emerging markets, especially uh in Asia, but not only, but especially in Asia and Eastern Europe, I mean, these guys are catching up very quickly.
00:31:34.240 --> 00:31:37.839
You go to Poland now, I mean, it's European countries.
00:31:38.079 --> 00:31:43.920
I I went to Poland uh 30 years ago, it was another it was another world.
00:31:44.160 --> 00:31:47.680
Uh, you go to China now, it was it's it's unbelievable.
00:31:48.000 --> 00:31:55.039
When I went to China in 87 for AFC, by the way, as a young professional, it was feudalism.
00:31:55.200 --> 00:31:59.440
I mean, the the technology was not there, uh very basic.
00:31:59.920 --> 00:32:02.799
So the progress has been unbelievable.
00:32:03.119 --> 00:32:03.920
Unbelievable.
00:32:04.079 --> 00:32:07.039
Poverty alleviation has been it's a miracle.
00:32:07.119 --> 00:32:16.880
I don't think that any other period in history we have seen such success in eliminating poverty, despite a huge increase in population.
00:32:17.759 --> 00:32:27.599
So, I mean, we can take some credit for you know the post-World War II uh system uh of trade.
00:32:27.759 --> 00:32:39.359
I believe trade was very powerful, uh and uh development finance and stability through the AMF on the macro side worked extremely well.
00:32:39.839 --> 00:32:43.279
I think that we need to repeat that again and again.
00:32:43.440 --> 00:32:48.559
Now things change in some sense because you are a victim of your own uh success.
00:32:49.279 --> 00:32:54.960
When I see that in Europe, some of the country or many of the countries are more indebted than emerging markets.
00:32:55.119 --> 00:33:00.559
So they say, well, if we are why should we borrow to land to China?
00:33:00.799 --> 00:33:08.000
So there's a questioning in Europe at least, and I think in the US also, to be honest, on aid.
00:33:08.960 --> 00:33:12.559
That we knew for the last what 50 years, half a century.
00:33:12.720 --> 00:33:17.519
So there's a questioning in uh and questioning is not a bad thing in itself.
00:33:18.799 --> 00:33:28.960
But I still believe that the we are much better in a world that is prosperous than in a world where poverty increases fundamentally.
00:33:29.279 --> 00:33:31.599
So, how do you morph this?
00:33:31.920 --> 00:33:40.720
So, in my view, it's a transition because traditional donors are cutting aid for many reasons.
00:33:40.880 --> 00:33:51.200
They want to increase their defense spending, they don't have enough fiscal rule, uh, their population, the appetite to uh the for international aid is coming down.
00:33:51.440 --> 00:33:53.039
A mixture of all this.
00:33:53.359 --> 00:33:54.480
So it's going down.
00:33:54.799 --> 00:34:05.680
Emerging markets are not ready yet to put uh aid kind of in a non-mercantilist way and multilateral.
00:34:06.559 --> 00:34:14.400
Part of it is because of the of the governance of many of the MDBs is against them.
00:34:14.480 --> 00:34:23.280
So if you put uh more money in uh some of the regional development bank, you may not get the shares that goes with it.
00:34:23.920 --> 00:34:26.079
So that's it has to be reopened.
00:34:26.159 --> 00:34:32.719
But that's hard because those that are uh having the control don't want to lose it.
00:34:32.960 --> 00:34:35.599
So there's a governance uh issue.
00:34:35.760 --> 00:34:48.320
So the transition between uh Europe and traditional donors and potential new donors, we are a bit caught and we are not yet uh this transition is not happening and has not happened.
00:34:48.639 --> 00:34:53.519
Also, China is increasing, but we are still a long way.
00:34:54.079 --> 00:34:55.360
Uh so that's one.
00:34:55.519 --> 00:35:09.519
And second, the the type, because we have been successful, I think more and more will be on the donors on the on the private sector side, which was a little bit what I tried to do with IFC.
00:35:09.599 --> 00:35:13.440
So in my view, IFC should be as big as the World Bank.
00:35:14.079 --> 00:35:17.679
An economy should work on two legs, public and private.
00:35:17.920 --> 00:35:21.280
And the private was tiny compared to the public in the World Bank.
00:35:21.440 --> 00:35:24.880
This is changing, and I think this is the direction of travel.
00:35:24.960 --> 00:35:33.199
I I don't anticipate massive increase to IDA, on the contrary, it will be harder and harder as time goes by.
00:35:33.360 --> 00:35:57.599
Uh IDA is for uh government loans subsidized or on concessional terms, which means donors have to contribute every three years, but IFC can come can continue to grow if they're ready to take more risk, to be creative, and to work upstream and work public-private.
00:35:57.760 --> 00:36:00.400
I don't know an economy that is completely private.
00:36:00.559 --> 00:36:05.920
I don't know even the pure communist country are not completely public.
00:36:06.559 --> 00:36:08.880
The reality is a mix of the two.
00:36:08.960 --> 00:36:14.159
The problem is where you put the cursor, but that's another story.
00:36:14.400 --> 00:36:21.440
Um, so that's what I think that it's gonna be a difficult moment of evolution and change.
00:36:22.079 --> 00:36:30.559
And uh I see from uh on the bilateral, regional, and international, at all level, it's gonna be harder.
00:36:31.119 --> 00:36:45.199
And uh but the private sector will have its um, but everybody will have an incentive to to improve private sector flows uh to uh emerging countries, but it has to be on a win-win.
00:36:45.280 --> 00:36:49.519
A win for the investor and win for the recipient countries.
00:36:49.760 --> 00:36:53.280
So that's in fact, that's where I believe we're going.
00:36:54.880 --> 00:37:01.280
Philip, thank you for for your perspective and all your wisdom over decades of experience.
00:37:01.440 --> 00:37:06.880
And and Philip, the this podcast always ends with the question of your favorite number.
00:37:07.039 --> 00:37:11.840
So tell us your favorite number and the story behind that number.
00:37:12.239 --> 00:37:17.280
A lot of people will give you their mother's birthday or their own birthday or something, I assume.
00:37:17.440 --> 00:37:22.559
But for me, and I thought about because you you you warned me about the question.
00:37:22.719 --> 00:37:25.840
I have to be honest with everybody and transparent.
00:37:26.239 --> 00:37:36.000
Uh, I thought about it, and uh I think that really what I don't know if it's my favorite, but the one that puzzles me and fascinates me the most is zero.
00:37:37.440 --> 00:37:42.880
I always thought put yourself in the shoes of a you know a caveman.
00:37:44.079 --> 00:37:51.840
You can count one, two, three, you have one, you know, one pig, two pigs, three pigs, or sheep or whatever, or grains.
00:37:52.639 --> 00:37:53.760
But zero.
00:37:54.400 --> 00:37:58.639
The concept of zero and was not obvious.
00:37:58.880 --> 00:38:00.800
In fact, it was a huge breakthrough.
00:38:00.880 --> 00:38:12.159
I don't know who is a genius, or maybe a string of genius, to come, and apparently it came from uh philosophy um from uh India, the concept of nothingness.
00:38:12.400 --> 00:38:17.519
But then how do you take this philosophical concept into a numerals?
00:38:18.159 --> 00:38:21.760
And that enabled you to do decimals to do the 19.
00:38:21.920 --> 00:38:31.519
What is 19 in in Greek or in Roman or 1957, my birthday?
00:38:31.760 --> 00:38:38.480
I mean, you know, it's a lot of X and Y's and V's and stuff, it makes no sense.
00:38:38.800 --> 00:38:44.639
So zero for me was uh is the most fascinating uh number for me.
00:38:44.800 --> 00:38:55.280
The guy or the that came up with it is one of the huge geniuses of uh the human history, in my view.
00:38:56.719 --> 00:38:59.920
Well, zero, where math and philosophy meet.
00:39:00.079 --> 00:39:03.840
I didn't expect to end us on that note, but it's even more fascinating.
00:39:03.920 --> 00:39:06.159
Thank you so much, Philip, for being on the show.
00:39:06.639 --> 00:39:08.000
Thank you, Wolfgang.
00:39:08.079 --> 00:39:08.559
Take care.
