WEBVTT

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okay so um today we're want to start

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talking about the long run I've been

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talking about the business cycles and

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today we're going to start talking about

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things that happen over decades H but

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before I do that before we finish with

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the the short run medium run I just

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don't want you to I want I don't want to

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give you the impression that that you

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know once you understand the ISL MPC

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sort of you you can start managing

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monetary

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policy immediately I

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I there's a lot of noise of all sort of

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kind of complexity in the real world of

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course that can make um policies

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uh uh very hard to manage in practice

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macroeconomic policies and one

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fundamental principle I would say is

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that policy makers understand that speed

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can kill okay and uh that's very obvious

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during financial crisis there we all

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understand that ER the response needs to

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be large it has to be a response with

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overwhelming Force essentially because

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things are happening so fast that very

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few corporations even healthy

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corporations that that can adjust

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quickly enough uh to the PACE at which

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things are changing prices become

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noninformative uh fire cells take place

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and and and obviously it's very

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difficult to make economic decisions in

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that context and so that's the reason

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they are the speed in the on the on the

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policy Direction goes very clearly in

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One Direction do it quickly and very

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large

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now on the other hand ER when you're

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going through a period in which you're

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are hiking interest rates for example

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ER like we're going through now um the

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the Tendencies towards gradualism to do

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it very slowly because something can

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break along the path and it's often the

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case that with for sufficiently large

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adjustments something breaks okay and so

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here you have an example of sort of

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major episodes of hiking in the US and

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things that have happened about those

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those H major episodes

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this one actually I I have a personal

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attachment to that one because you know

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I was studying in Chile around then

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everything was going wonderfully massive

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Capital flows to Chile emerging markets

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were very popular we all felt very

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wealthy rich and so on and right after I

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finished College ER I was not planning

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to come to the usy things were going

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very well in Chile H but the US decided

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to hike interest rate very aggressively

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all of the sudden Capital flows to

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emergy markets disappear we went into an

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enormous financial crisis I lost I had

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no opportunity cost and I had to come to

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study to the US that that's my so I know

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that hikes aggressive hikes can matter

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can make differences to people but and

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that

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was there's a decade that followed that

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episode that is called the L decade of

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Latin America essentially so things did

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break and and one of the main reasons

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they did break is because at the time

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most of the capital close that's not

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what happens today we really being

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managed by global Banks and the banks

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can get very distressed when interest

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rate rise H very very quickly and so

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that that was essentially a problem with

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us the US Banks major Global Banks but

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the US Banks in particular that trigger

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an Emerging Market

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crisis this one also had huge

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consequences actually and it's

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interesting because this episode is is

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similar to to to to what we're going on

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what is going on right now or what may

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happen in soon so this is episode of

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hikes that ended what is called The

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Savings and Loan crisis and those so the

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best parallel to today are the small

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Regional Banks if you will and they they

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weren't able to withstand this sort of

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sharp rise in interest rate which is

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very much what is going on right now in

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the US this one actually end up with

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also another problem which is the the

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the bubble burst in Japan episode of

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hiking in the US and there we had a

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major crisis in in Japan the price of

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real estate

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collapsed ER and and essentially they

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since then they have never been able to

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grow as they used to before that that

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episode that's called sometimes the

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tequila crisis it's a Mexican

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Bond crisis and it was again the result

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of a hiking episode in the US conditions

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tighten to Emerging Market ER their bone

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Market essentially

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exploded um well this is the global

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financial crisis the Great Recession it

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was again preceded by episode of sort of

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aggressive hikes which eventually er um

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led to a turn around as house prices

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were Rising steadily throughout the

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episode and a lot of financial assets

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were created around that housing wealth

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that was been created that hike and

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interest rate eventually put a stop an

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end to that that appreciation of house

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prices in fact they turn around and it

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led to a very significant financial

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crisis and this is where we're at right

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now okay and so we already seen sort of

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some Tremors and so on so the point is

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when when sometimes you say well why is

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isn't the FED more aggressive if we have

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high inflation and go very quickly at it

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well it's because things can go wrong

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okay and it it typically happens that

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things do go wrong you don't know

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exactly what will blow up but something

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may blow up and typically is associated

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to some Financial Market that is very

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hot and the market and the banks are

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always involved in that because the

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banks are very

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lever you know they have little Capital

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relative to the assets they have and

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that means small variation in the price

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of assets can lead to very large H

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changes in the value of their

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capital anyway so just a warning so if

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you get a job at the FED please be

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careful okay now let me switch gears and

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and we're going to talk about um um

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something a little different from what

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we have been discussing up to now so

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this is some this is growth projections

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for different regions in the world ER

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this is something that is in publishing

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by the IMF it's called the world

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economic Outlook I think I mentioned it

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before and here you have some forecast

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you know well this is actually what

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happened so growth in the global economy

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was about 3.4% 2022 advanced economies

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grew at 2.7% emerging markets and

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developing economies at

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3.9% and then you see forast and the

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further out you go er um the okay the

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further out you go sort of it's less

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related to the current cycle is more

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related to what is structural the

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structural

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growth of the different parts of the

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world and you see that for

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2024 the global economy is projected

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expected to grow at around 3.1% this

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forecast were made before the mess

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Financial mess that we're going on right

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now so probably the next World economic

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Outlook will have at least for 2023 will

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will downgrade the growth probably not

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for 2024 but yes for 2023 anyways

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advanced economies expected to grow

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1.4% emerging markets at

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4.2% so

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these forecasts are based on on a

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combination of cyclical factors

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fluctuations of the short run medium run

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the kind of things we have been

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discussing up to now some economies will

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have to go through recession some

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economies are going through Booms that

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probably dominates 20 the forus on 2023

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but as I said before the further out you

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go the more the less relevant is the

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current business cycle and the more

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relevant is the structural trend of the

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different regions of the world okay so I

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would that in this when they formulated

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this forecast this is very much based on

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more longer run growth model the kind of

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models we're going to discuss now okay

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while this is probably totally dominated

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by the kind of things we discuss up to

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now okay

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um there are several things that that

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that are interesting here aside from

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sort of the the the

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fluctuations year to year one thing you

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can see for example is that regardless

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of year

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on average Emerging Markets tend to grow

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faster than develop economies advanced

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economies okay so one of the things we

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want to understand is why is that the

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case okay but that's is very clear here

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that's the first model we're going to

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look at which probably will happen on

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Wednesday we'll try to explain

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essentially that why is it that these

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guys tend to grow faster than the

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advanced economies

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okay so growth is important I mean the

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standing economic growth is hugely

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important for the weal for understanding

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sort of the health of an economy here

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you see this comes from the textbook er

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er the the US GDP in 20 20

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uh2 from

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1890 to to 2017 I think is this one the

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the end year the important thing to

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notice here is how large is the change

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in GDP in during the period I mean GDP

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here measuring the same prices so 20

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2012 prices is 50 times that in 1890

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that's a big thing I mean when we talk

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about business cycle fluctuations we're

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talking about in an economy like the US

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two two and a half% up 3% up and down

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this is 50 times so over longer period

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of time you can almost ignore the

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business cycle and it's all about that

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long run H trend

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here what is this episode so so you here

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if you if you look at this picture know

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especially the F out you are on the on

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the on the room what dominates here is

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clearly the

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trend the only action you see really

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significant action different from the

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trend is around here what happened

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there it's the Great Depression so even

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the Great Depression you know doesn't

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look that big relative to what the trend

00:10:57.919 --> 00:11:01.278
can do so

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of course it's very difficult to affect

00:11:01.278 --> 00:11:05.600
the trend of a country but the trend

00:11:03.278 --> 00:11:07.000
makes a huge difference for the welfare

00:11:05.600 --> 00:11:11.000
for

00:11:07.000 --> 00:11:12.600
the economic well-being of a

00:11:11.000 --> 00:11:17.078
country

00:11:12.600 --> 00:11:20.120
good now a lot of that is because also

00:11:17.078 --> 00:11:23.439
the US population grew up grew up grew

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up and grew a lot during this episode

00:11:23.440 --> 00:11:27.880
so often when you look at sort of long

00:11:26.120 --> 00:11:30.120
run Trends rather than looking at the

00:11:27.879 --> 00:11:33.679
level of GDP you tend to look at the

00:11:30.120 --> 00:11:35.480
level of GDP per person per capita or

00:11:33.679 --> 00:11:37.679
something like that and that picture is

00:11:35.480 --> 00:11:40.039
exactly the same pictures as the

00:11:37.679 --> 00:11:43.799
previous one but divided by population

00:11:40.039 --> 00:11:45.319
at each point in time okay and and and

00:11:43.799 --> 00:11:46.919
and that's an important over long

00:11:45.320 --> 00:11:49.278
periods of you at the business cycle

00:11:46.919 --> 00:11:51.639
frequency you can almost ignore changes

00:11:49.278 --> 00:11:53.679
in popul no Chang ination you can ignore

00:11:51.639 --> 00:11:55.278
completely unless you are in a war you

00:11:53.679 --> 00:11:57.799
can you worry about other things labor

00:11:55.278 --> 00:11:59.480
force participation and stuff like that

00:11:57.799 --> 00:12:01.559
but population is irrelevant that the

00:11:59.480 --> 00:12:03.680
business cycle growth is irrelevant at

00:12:01.559 --> 00:12:06.479
the business cycle frequency but not

00:12:03.679 --> 00:12:08.719
over long periods of time in this period

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here population in the US increased from

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63 million to 320 million so that's a

00:12:11.759 --> 00:12:17.360
lot more workers in principle that you

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have you know for that economy so a lot

00:12:17.360 --> 00:12:23.519
of that trend is explained by population

00:12:20.159 --> 00:12:26.399
growth and that's one of the reason

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sorry a lot of the trend in this picture

00:12:26.399 --> 00:12:30.679
here is explained by population growth

00:12:29.399 --> 00:12:32.879
that's one of the reasons we're in a

00:12:30.679 --> 00:12:34.359
tricky time in the global economy

00:12:32.879 --> 00:12:35.838
because there are many important regions

00:12:34.360 --> 00:12:38.039
of the world where population is no

00:12:35.839 --> 00:12:40.399
longer growing so we got used to a

00:12:38.039 --> 00:12:43.639
period in which population growth was

00:12:40.399 --> 00:12:45.720
very steady and high and now you know

00:12:43.639 --> 00:12:48.399
many parts of the world important parts

00:12:45.720 --> 00:12:53.160
of of the world have negative population

00:12:48.399 --> 00:12:56.159
growth Japan Korea China most of

00:12:53.159 --> 00:12:58.198
Continental Europe H even places in

00:12:56.159 --> 00:13:01.039
Latin America and so on so so this is a

00:12:58.198 --> 00:13:03.319
big change for the world

00:13:01.039 --> 00:13:05.480
but anyways during that period there was

00:13:03.320 --> 00:13:07.199
a lot of population growth and in the US

00:13:05.480 --> 00:13:09.720
in particular when again as I said

00:13:07.198 --> 00:13:12.319
before from 63 to 320 million so if you

00:13:09.720 --> 00:13:15.240
really want to measure sort of welfare

00:13:12.320 --> 00:13:16.519
of the economy how well how the

00:13:15.240 --> 00:13:19.360
well-being of

00:13:16.519 --> 00:13:21.078
individuals in in in in the US the

00:13:19.360 --> 00:13:24.240
previous picture is misleading because

00:13:21.078 --> 00:13:26.759
you have to yeah it's the final Pi is 50

00:13:24.240 --> 00:13:29.159
times larger than the first one than the

00:13:26.759 --> 00:13:31.759
beginning Pi but you have 320 million

00:13:29.159 --> 00:13:35.278
people to split it among as opposed to

00:13:31.759 --> 00:13:36.919
63 million so this picture captures that

00:13:35.278 --> 00:13:39.198
statistic that is often described when

00:13:36.919 --> 00:13:43.039
you talk about long run

00:13:39.198 --> 00:13:45.319
growth ER is GDP per person and you

00:13:43.039 --> 00:13:48.919
still see that what dominates this

00:13:45.320 --> 00:13:51.800
picture is a trend ER but the difference

00:13:48.919 --> 00:13:53.759
between this out out GDP per person in

00:13:51.799 --> 00:13:55.838
the US at the end of the sample versus

00:13:53.759 --> 00:13:58.639
the beginning of the sample is 10 to1

00:13:55.839 --> 00:14:00.560
not 50 to1 so it makes a difference

00:13:58.639 --> 00:14:02.799
population it's still big it's still

00:14:00.559 --> 00:14:05.000
what dominates this picture is that of

00:14:02.799 --> 00:14:07.559
course the Great Recession looks bigger

00:14:05.000 --> 00:14:09.278
now because you know you comparing it

00:14:07.559 --> 00:14:11.679
with with a number that grows by a

00:14:09.278 --> 00:14:14.198
factor of 10 not by a factor of 50

00:14:11.679 --> 00:14:16.239
that's so it looks bigger naturally know

00:14:14.198 --> 00:14:18.958
the same 30% decline output is a lot

00:14:16.240 --> 00:14:21.120
bigger when you're comparing it with

00:14:18.958 --> 00:14:23.879
the a factor of 10 than when you're

00:14:21.120 --> 00:14:27.679
comparing it with a factor of 50 but

00:14:23.879 --> 00:14:30.240
still it looks bigger but the picture is

00:14:27.679 --> 00:14:33.159
dominated by the

00:14:30.240 --> 00:14:35.159
so all this to say that we're going to

00:14:33.159 --> 00:14:36.879
study now is very important it's not

00:14:35.159 --> 00:14:39.159
what dominates the day-to-day news

00:14:36.879 --> 00:14:41.879
because it happens slowly and over time

00:14:39.159 --> 00:14:41.879
but it is very

00:14:43.399 --> 00:14:48.320
important so how do we measure these

00:14:45.839 --> 00:14:51.199
things well when you're looking within a

00:14:48.320 --> 00:14:54.278
country you do reasonably well not

00:14:51.198 --> 00:14:56.078
perfect but reasonably well and perhaps

00:14:54.278 --> 00:14:58.720
not over periods as long as I want I

00:14:56.078 --> 00:15:01.879
show you by looking at GDP per capita

00:14:58.720 --> 00:15:04.879
that's that's fine is you measure it

00:15:01.879 --> 00:15:06.480
real GDP per capita that's about fine

00:15:04.879 --> 00:15:09.198
but when you compare across different

00:15:06.480 --> 00:15:12.440
regions of the world and so on those

00:15:09.198 --> 00:15:17.838
comparisons is very misleading so to say

00:15:12.440 --> 00:15:21.440
that the US has um I don't know

00:15:17.839 --> 00:15:23.959
ER what is the US GDP per capita today

00:15:21.440 --> 00:15:28.040
in the US somebody should check it but

00:15:23.958 --> 00:15:31.039
but about maybe $70,000 something like

00:15:28.039 --> 00:15:34.838
that I don't know ER and then then then

00:15:31.039 --> 00:15:37.399
you see a another country that has say

00:15:34.839 --> 00:15:40.959
Italy $50,000 per

00:15:37.399 --> 00:15:43.440
capita that comparison is not that

00:15:40.958 --> 00:15:45.000
meaningful it's indicative of something

00:15:43.440 --> 00:15:46.160
but it's not completely meaningful and

00:15:45.000 --> 00:15:48.600
I'm going to show you an example which

00:15:46.159 --> 00:15:51.360
is much more extreme than that but the

00:15:48.600 --> 00:15:53.120
reason is not very meaningful is

00:15:51.360 --> 00:15:55.879
essentially because the prices are not

00:15:53.120 --> 00:15:59.560
the same across different parts of the

00:15:55.879 --> 00:16:01.360
world so we have a method to to to to do

00:15:59.559 --> 00:16:03.359
that to to be able to compare across

00:16:01.360 --> 00:16:05.480
countries and again even for a one a

00:16:03.360 --> 00:16:09.159
given country over long long period of

00:16:05.480 --> 00:16:12.120
time we make a correction to the GDP

00:16:09.159 --> 00:16:13.600
numbers we have and we make we call them

00:16:12.120 --> 00:16:16.799
we correct them by what is called the

00:16:13.600 --> 00:16:19.120
PPP purchasing power parity and I'll

00:16:16.799 --> 00:16:23.318
explain what that is okay so whenever

00:16:19.120 --> 00:16:25.120
almost whenever you see comparisons of a

00:16:23.318 --> 00:16:27.399
GDP per capita across countries when

00:16:25.120 --> 00:16:31.278
somebody's doing a growth analysis is

00:16:27.399 --> 00:16:34.519
going to be PPP adjusted okay now let me

00:16:31.278 --> 00:16:36.159
explain the logic of

00:16:34.519 --> 00:16:39.000
PB

00:16:36.159 --> 00:16:41.679
um and and and again I said within the

00:16:39.000 --> 00:16:44.318
same country over periods perhaps not

00:16:41.679 --> 00:16:48.359
300 years but over periods of 40 years

00:16:44.318 --> 00:16:50.399
it's reasonable H to use just real GDP

00:16:48.360 --> 00:16:53.560
but when you start comparing sort of you

00:16:50.399 --> 00:16:56.278
know bana versus the US it gets a lot

00:16:53.559 --> 00:16:58.439
tricky trickier because there's a lot of

00:16:56.278 --> 00:17:01.958
goods that are a lot cheaper in poorer

00:16:58.440 --> 00:17:03.920
countries in particular food okay and

00:17:01.958 --> 00:17:05.159
and so so you have to be careful with

00:17:03.919 --> 00:17:07.678
those comparisons so I'm going to give

00:17:05.160 --> 00:17:09.759
you this example which is somewhat

00:17:07.679 --> 00:17:12.759
hypothetical but the numbers are not

00:17:09.759 --> 00:17:15.879
crazy so suppose you have a a two

00:17:12.759 --> 00:17:18.879
economies the US and Russia

00:17:15.880 --> 00:17:18.880
and

00:17:20.199 --> 00:17:25.640
um anyways

00:17:22.720 --> 00:17:29.200
ER and suppose that that in both

00:17:25.640 --> 00:17:32.520
economies ER households consume houses

00:17:29.200 --> 00:17:35.400
and firms consume cars and

00:17:32.519 --> 00:17:37.319
food okay and suppose that the average

00:17:35.400 --> 00:17:41.120
consumer in the US buys one car a year

00:17:37.319 --> 00:17:44.639
for $10,000 and a bundle of food for

00:17:41.119 --> 00:17:46.839
$10,000 as well okay so the total

00:17:44.640 --> 00:17:49.720
expenditure in consumption for this

00:17:46.839 --> 00:17:53.000
household on average is about $20,000 a

00:17:49.720 --> 00:17:55.519
year that's what a US household consumes

00:17:53.000 --> 00:17:59.119
these numbers are fantasy numbers but

00:17:55.519 --> 00:18:00.158
the big picture is not that fantasy

00:17:59.119 --> 00:18:03.279
ER

00:18:00.159 --> 00:18:07.600
Russia the average consumer buys

00:18:03.279 --> 00:18:10.079
0.07 cars a year for 40,000 rubles and

00:18:07.599 --> 00:18:12.480
the same bundle of food that in the US

00:18:10.079 --> 00:18:14.639
okay same assume that same bundle of

00:18:12.480 --> 00:18:17.960
food goes for 880,000

00:18:14.640 --> 00:18:21.600
rubles so the total expenditure of this

00:18:17.960 --> 00:18:24.880
H average household in Russia is

00:18:21.599 --> 00:18:27.558
120,000 rubles suppose that exchange is

00:18:24.880 --> 00:18:31.480
60 rubles per dollar this thing has

00:18:27.558 --> 00:18:33.798
moved a lot recent times but suppose

00:18:31.480 --> 00:18:36.919
that's the the number of rubles per

00:18:33.798 --> 00:18:38.918
dollar so you divide $120,000 and you

00:18:36.919 --> 00:18:41.919
want to convert them into Dollars you

00:18:38.919 --> 00:18:43.799
divide the 120,000 rubles by 60,000

00:18:41.919 --> 00:18:45.440
rubles per dollar and then you get how

00:18:43.798 --> 00:18:48.798
much the Russians spend a Russian

00:18:45.440 --> 00:18:51.320
household on average spends on on on

00:18:48.798 --> 00:18:54.839
consumption in a year and and it's

00:18:51.319 --> 00:18:58.038
$2,000 a year okay so here you have

00:18:54.839 --> 00:18:59.240
120,000 divided by 60 is 2,000 that's

00:18:58.038 --> 00:19:01.798
the number of dollar

00:18:59.240 --> 00:19:04.200
that an average household in Russia

00:19:01.798 --> 00:19:06.759
consumes so the question

00:19:04.200 --> 00:19:10.000
is you have a US household spends

00:19:06.759 --> 00:19:13.599
$20,000 a year a Russian household

00:19:10.000 --> 00:19:16.400
spends $22,000 a year and the question

00:19:13.599 --> 00:19:18.399
is then is Russia 10 times poorer than

00:19:16.400 --> 00:19:20.360
the

00:19:18.400 --> 00:19:22.919
US

00:19:20.359 --> 00:19:26.798
okay that if you were to compare real

00:19:22.919 --> 00:19:29.240
GDP that would be answer so yeah they

00:19:26.798 --> 00:19:30.918
and it's true if you look at a again in

00:19:29.240 --> 00:19:33.679
this

00:19:30.919 --> 00:19:36.159
example if you look at the at the real

00:19:33.679 --> 00:19:38.640
GDP numbers of on the same year

00:19:36.159 --> 00:19:40.159
converted all into dollars that answer

00:19:38.640 --> 00:19:42.400
is

00:19:40.159 --> 00:19:44.000
correct but it doesn't represent the

00:19:42.400 --> 00:19:45.679
point is that it doesn't represent

00:19:44.000 --> 00:19:48.400
really The Well beinging of the average

00:19:45.679 --> 00:19:52.400
household in Russia for this reason at

00:19:48.400 --> 00:19:56.320
least why not well

00:19:52.400 --> 00:19:59.919
let's what you ultimately matter is how

00:19:56.319 --> 00:20:02.359
much real Goods the house

00:19:59.919 --> 00:20:03.840
consumes that's what really matters I

00:20:02.359 --> 00:20:06.158
mean if you live in a country where the

00:20:03.839 --> 00:20:08.079
price of everything is zero your

00:20:06.159 --> 00:20:09.200
consumption expenditure consumption will

00:20:08.079 --> 00:20:12.319
be

00:20:09.200 --> 00:20:14.080
zero but that doesn't mean that you are

00:20:12.319 --> 00:20:16.000
as unhappy as somebody that consumes

00:20:14.079 --> 00:20:18.639
zero you're consuming whatever it is it

00:20:16.000 --> 00:20:20.519
happens the prices tend to be very low

00:20:18.640 --> 00:20:22.520
and that's essentially the story here as

00:20:20.519 --> 00:20:24.918
I said before it tends to be the case

00:20:22.519 --> 00:20:28.240
that in poorer countries a lot of things

00:20:24.919 --> 00:20:30.480
are cheaper there is certain very high

00:20:28.240 --> 00:20:32.599
tech things that that are not even

00:20:30.480 --> 00:20:34.798
consumed in poorer countries so you have

00:20:32.599 --> 00:20:36.519
to adjust for that as well but a lot of

00:20:34.798 --> 00:20:39.480
the regular things the bulk of the

00:20:36.519 --> 00:20:41.918
purchases tend to be a lot cheaper in

00:20:39.480 --> 00:20:44.720
poorer countries and that's exactly what

00:20:41.919 --> 00:20:45.840
is behind the reason why in this example

00:20:44.720 --> 00:20:48.159
the answer is

00:20:45.839 --> 00:20:50.199
no it's not true that the Russians are

00:20:48.159 --> 00:20:52.840
10 time that Russian household in this

00:20:50.200 --> 00:20:55.600
example is 10 times poorer than the US

00:20:52.839 --> 00:20:59.199
let's check it so that's our

00:20:55.599 --> 00:21:01.439
example and I said no so fast

00:20:59.200 --> 00:21:03.440
let's use so assume that the goods are

00:21:01.440 --> 00:21:06.480
the same so the cars that the Russians

00:21:03.440 --> 00:21:09.759
buy is the same as the as the cars that

00:21:06.480 --> 00:21:13.880
the US households buy that was

00:21:09.759 --> 00:21:15.679
truer a few months ago than now but but

00:21:13.880 --> 00:21:18.840
assume that's the case it's just that

00:21:15.679 --> 00:21:21.480
the Russians by you know change their

00:21:18.839 --> 00:21:23.359
cars less frequently in this example the

00:21:21.480 --> 00:21:26.120
US household is changing the car once a

00:21:23.359 --> 00:21:28.959
year while while while the Russians are

00:21:26.119 --> 00:21:31.918
changing the car you know less than once

00:21:28.960 --> 00:21:34.880
every 10 year one every 15 years or

00:21:31.919 --> 00:21:37.440
so let's assume also that the the bundle

00:21:34.880 --> 00:21:40.600
of the of food is exactly the same in

00:21:37.440 --> 00:21:44.600
both Place places so since the car is

00:21:40.599 --> 00:21:47.839
the same and the and the and the and the

00:21:44.599 --> 00:21:49.879
bundle of food is the same I can use us

00:21:47.839 --> 00:21:53.119
prices to

00:21:49.880 --> 00:21:56.559
measure Uh Russian consumption and

00:21:53.119 --> 00:21:59.439
that's is comparable to what us

00:21:56.558 --> 00:22:00.879
consumption is because I'm taking I'm

00:21:59.440 --> 00:22:02.960
trying to convert the goods they're

00:22:00.880 --> 00:22:05.799
consuming into something is comparable

00:22:02.960 --> 00:22:08.440
to what the US consumes since the goods

00:22:05.798 --> 00:22:10.038
themselves are the same if I value them

00:22:08.440 --> 00:22:12.640
at the same price either of the two

00:22:10.038 --> 00:22:14.038
prices but at the same prices then I'm

00:22:12.640 --> 00:22:17.360
going to be able to make the comparison

00:22:14.038 --> 00:22:20.839
I really want that's what purchase power

00:22:17.359 --> 00:22:22.639
PVP adjustment means okay so look at our

00:22:20.839 --> 00:22:26.199
particular example here the Russian

00:22:22.640 --> 00:22:29.240
would household would be consuming 0.07

00:22:26.200 --> 00:22:32.120
cars times 10,000 dollar which is the

00:22:29.240 --> 00:22:36.880
price of a car plus one unit of of the

00:22:32.119 --> 00:22:39.959
bundle of of of of food and the price us

00:22:36.880 --> 00:22:41.799
price is 10,000 for that so the total

00:22:39.960 --> 00:22:44.960
consumption of the household PPP

00:22:41.798 --> 00:22:49.480
adjusted the Russian household is

00:22:44.960 --> 00:22:53.880
10,700 okay that's not one10 it's

00:22:49.480 --> 00:22:55.960
53% of us consumption so true Russian

00:22:53.880 --> 00:22:58.960
household is poorer than than than than

00:22:55.960 --> 00:23:02.640
an average US household but it's not 10

00:22:58.960 --> 00:23:05.200
poor no it has it's

00:23:02.640 --> 00:23:10.880
a is

00:23:05.200 --> 00:23:13.080
53% uh as rich as the US household okay

00:23:10.880 --> 00:23:15.400
and so this is big and all the numbers

00:23:13.079 --> 00:23:16.918
I'm going to show you next especially

00:23:15.400 --> 00:23:18.720
when we compare across sort of countries

00:23:16.919 --> 00:23:20.919
that are very different in terms of

00:23:18.720 --> 00:23:23.919
level of development and so on have

00:23:20.919 --> 00:23:25.400
these kind of Corrections built in okay

00:23:23.919 --> 00:23:27.278
if you need the data for these kind of

00:23:25.400 --> 00:23:29.200
things for whatever reason you find them

00:23:27.278 --> 00:23:30.960
in what is called the pen tables the pen

00:23:29.200 --> 00:23:33.240
tables essentially collects all the

00:23:30.960 --> 00:23:34.480
national accounts of all places and

00:23:33.240 --> 00:23:36.240
makes these

00:23:34.480 --> 00:23:39.000
Corrections the problem is they don't

00:23:36.240 --> 00:23:40.640
have update them very frequently but but

00:23:39.000 --> 00:23:42.839
if you look in Fred for example which

00:23:40.640 --> 00:23:45.919
you use in one of the p sets there will

00:23:42.839 --> 00:23:49.759
be numbers for a few countries that have

00:23:45.919 --> 00:23:49.759
this um PPP

00:23:49.798 --> 00:23:54.599
adjustment okay so that that's that's

00:23:53.119 --> 00:23:56.038
going to remain in the background now

00:23:54.599 --> 00:23:57.839
but I just wanted to tell you how how

00:23:56.038 --> 00:23:59.679
you construct numbers when you want to

00:23:57.839 --> 00:24:00.918
talk about long run and comparison

00:23:59.679 --> 00:24:04.880
across

00:24:00.919 --> 00:24:08.400
countries first set of numbers here look

00:24:04.880 --> 00:24:10.760
at these are obviously all today at

00:24:08.400 --> 00:24:13.519
least develop economies look at the

00:24:10.759 --> 00:24:16.000
growth between 1950 2017 obviously the

00:24:13.519 --> 00:24:17.679
war created a big mess there but before

00:24:16.000 --> 00:24:20.159
that so let's start from

00:24:17.679 --> 00:24:22.798
1950 and what you see here is you know

00:24:20.159 --> 00:24:25.919
France on average during this period

00:24:22.798 --> 00:24:27.038
France grew 2017 I think is the last yes

00:24:25.919 --> 00:24:29.440
it's the last

00:24:27.038 --> 00:24:31.679
year I think they were recently updated

00:24:29.440 --> 00:24:33.480
but at least when the book was published

00:24:31.679 --> 00:24:36.278
that was the last year they had pen

00:24:33.480 --> 00:24:40.278
tables for but

00:24:36.278 --> 00:24:42.159
um er France grew on average 2.6% per

00:24:40.278 --> 00:24:44.679
year on average they also had a business

00:24:42.159 --> 00:24:47.520
cycle and so on but on average 2.6% per

00:24:44.679 --> 00:24:49.320
year Japan during this period grew by

00:24:47.519 --> 00:24:53.798
four four

00:24:49.319 --> 00:24:56.599
4.1% the UK 2.1% the US 2% so the

00:24:53.798 --> 00:25:00.798
developed World essentially grew around

00:24:56.599 --> 00:25:03.639
2.7% on average during this

00:25:00.798 --> 00:25:07.440
period look at the effect that that this

00:25:03.640 --> 00:25:10.360
has on on the level of GDP per per per

00:25:07.440 --> 00:25:13.000
per person and all this PPP

00:25:10.359 --> 00:25:17.079
adjusted ER for the case of

00:25:13.000 --> 00:25:20.798
France 5.6 times so they started with

00:25:17.079 --> 00:25:24.918
$7,000 and they were close to $40,000 in

00:25:20.798 --> 00:25:28.599
2017 so the r is RA

00:25:24.919 --> 00:25:31.360
5.6 look at the US the US is 2% and that

00:25:28.599 --> 00:25:33.240
ratio is is still richer than France per

00:25:31.359 --> 00:25:36.959
per person in

00:25:33.240 --> 00:25:39.240
2017 but but the ratio of that to that

00:25:36.960 --> 00:25:40.759
is smaller than that so over a long

00:25:39.240 --> 00:25:42.960
period of time that's what a trend in

00:25:40.759 --> 00:25:44.679
the picture capture a small difference

00:25:42.960 --> 00:25:46.679
in the rate of growth if they are

00:25:44.679 --> 00:25:49.000
sustained for a long period of time can

00:25:46.679 --> 00:25:54.600
make quite a bit of difference for the

00:25:49.000 --> 00:25:56.919
change in in GDP okay and so what do you

00:25:54.599 --> 00:25:59.480
what is the first what is the p is I

00:25:56.919 --> 00:26:01.038
mean let's find the pattern here here

00:25:59.480 --> 00:26:04.720
there's a very clear pattern in that

00:26:01.038 --> 00:26:07.278
picture in that table what is it do you

00:26:04.720 --> 00:26:07.278
can you spot

00:26:15.919 --> 00:26:20.679
it I hadn't

00:26:18.200 --> 00:26:22.720
actually realized it when I was looking

00:26:20.679 --> 00:26:24.360
at my notes and then I realized is very

00:26:22.720 --> 00:26:26.558
clear in this table that's the reason I

00:26:24.359 --> 00:26:30.240
added this line I updated the slide this

00:26:26.558 --> 00:26:30.240
morning do you see a pattern

00:26:34.240 --> 00:26:40.038
yes the higher growth rate have a higher

00:26:37.640 --> 00:26:41.240
multiple yeah well that's yes that but

00:26:40.038 --> 00:26:43.640
that's

00:26:41.240 --> 00:26:45.558
math okay which is so it's a true

00:26:43.640 --> 00:26:48.640
statement but that's just

00:26:45.558 --> 00:26:49.639
math there's an economic thing that that

00:26:48.640 --> 00:26:53.038
that I want

00:26:49.640 --> 00:26:54.480
to so so you're right but but I want

00:26:53.038 --> 00:26:58.480
they should have clarified there's an

00:26:54.480 --> 00:26:58.480
economic pattern there

00:27:03.880 --> 00:27:10.760
let let me simplify just look at these

00:27:05.839 --> 00:27:13.439
two columns because a higher number here

00:27:10.759 --> 00:27:15.640
simply sorry a higher number here simply

00:27:13.440 --> 00:27:18.038
means that you had a higher rate of

00:27:15.640 --> 00:27:20.360
growth that's your math fact so ignore

00:27:18.038 --> 00:27:23.158
this column what I suggest is that you

00:27:20.359 --> 00:27:23.158
just look at these two

00:27:24.278 --> 00:27:29.599
columns do you see a

00:27:27.159 --> 00:27:31.520
pattern just look at these two columns

00:27:29.599 --> 00:27:33.119
this one in a sense just repeats

00:27:31.519 --> 00:27:35.440
information that is here for the reason

00:27:33.119 --> 00:27:38.678
you describe but just look at these two

00:27:35.440 --> 00:27:38.679
columns is there a pattern

00:27:40.398 --> 00:27:45.918
there exactly very important Richard

00:27:44.240 --> 00:27:49.000
countri sent to grow slower the richest

00:27:45.919 --> 00:27:50.720
country here is the US had the lowest

00:27:49.000 --> 00:27:54.720
rate of growth on

00:27:50.720 --> 00:27:58.200
average the poorest was Japan there and

00:27:54.720 --> 00:27:59.640
they had the highest rate of growth okay

00:27:58.200 --> 00:28:00.960
so that's a very important correlation

00:27:59.640 --> 00:28:02.480
and again the first model we're going to

00:28:00.960 --> 00:28:05.159
see of economic growth is going to

00:28:02.480 --> 00:28:07.360
explain that correlation why is that we

00:28:05.159 --> 00:28:09.799
see

00:28:07.359 --> 00:28:11.079
that those were for five economy you

00:28:09.798 --> 00:28:13.480
could say it's an accident but look at

00:28:11.079 --> 00:28:16.158
this this this is just a this is rich

00:28:13.480 --> 00:28:18.278
countries in general since 1950s and you

00:28:16.159 --> 00:28:19.880
look at here in this axis you have the

00:28:18.278 --> 00:28:23.640
annual rate of growth the average rate

00:28:19.880 --> 00:28:26.519
of growth and here the GDP per person in

00:28:23.640 --> 00:28:29.399
1950 so at the beginning of the sample

00:28:26.519 --> 00:28:32.159
1950 these countries had have this level

00:28:29.398 --> 00:28:36.038
of GDP per capita and then here is the

00:28:32.159 --> 00:28:39.000
rate of growth on average from 1950 to

00:28:36.038 --> 00:28:42.599
1987 and it's very clear there that

00:28:39.000 --> 00:28:44.558
there's a downward sloping pattern no so

00:28:42.599 --> 00:28:46.879
that's the same fact now for many more

00:28:44.558 --> 00:28:48.759
countries there's a downward sloping

00:28:46.880 --> 00:28:51.039
relationship really the richest

00:28:48.759 --> 00:28:52.679
countries tend to grow much slower than

00:28:51.038 --> 00:28:54.319
the countries were poorer at the

00:28:52.679 --> 00:28:56.000
beginning of the

00:28:54.319 --> 00:28:59.278
sample

00:28:56.000 --> 00:29:02.798
okay there are some interesting

00:28:59.278 --> 00:29:05.119
liers like Mexico and and is an

00:29:02.798 --> 00:29:08.918
interesting in itself I'm not going to

00:29:05.119 --> 00:29:12.398
say a lot about why that's the case

00:29:08.919 --> 00:29:14.840
but but but let me for now stick to the

00:29:12.398 --> 00:29:17.798
to the pattern the dominant pattern

00:29:14.839 --> 00:29:19.480
which is is a downward sloping

00:29:17.798 --> 00:29:22.519
relationship that's another way of

00:29:19.480 --> 00:29:25.399
seeing it and this is for just a bigger

00:29:22.519 --> 00:29:29.038
variety of countries I have Botana China

00:29:25.398 --> 00:29:32.278
Thailand and so on and and you see here

00:29:29.038 --> 00:29:33.278
GDP at the beginning of the 1950 and GDP

00:29:32.278 --> 00:29:35.640
rate

00:29:33.278 --> 00:29:37.079
2018 and the pattern here which is

00:29:35.640 --> 00:29:38.960
essentially a repetition of the pattern

00:29:37.079 --> 00:29:44.918
that I showed you before is that there

00:29:38.960 --> 00:29:47.240
is much more compression here than

00:29:44.919 --> 00:29:50.559
here how can you have more compression

00:29:47.240 --> 00:29:52.839
here than here well because there is

00:29:50.558 --> 00:29:55.240
some sort of convergence no there's a

00:29:52.839 --> 00:29:58.079
sense of convergence is that those that

00:29:55.240 --> 00:30:00.359
were poorer tend to grow a little faster

00:29:58.079 --> 00:30:02.158
than those that were richer and

00:30:00.359 --> 00:30:04.240
therefore they tend to converge to each

00:30:02.159 --> 00:30:06.399
other so that's the the point I'm

00:30:04.240 --> 00:30:10.558
highlighting here a lot of this persion

00:30:06.398 --> 00:30:13.278
1950 much less isers in 2018 that means

00:30:10.558 --> 00:30:17.119
that on average the poorer countries are

00:30:13.278 --> 00:30:17.119
growing faster than the Richer

00:30:19.200 --> 00:30:26.679
countries and again all this is per

00:30:21.398 --> 00:30:26.678
capita PPP adjust and all that okay

00:30:30.319 --> 00:30:34.519
this

00:30:31.839 --> 00:30:37.918
picture again sort of makes the the

00:30:34.519 --> 00:30:40.519
point but now it takes a much many more

00:30:37.919 --> 00:30:43.960
countries and you can what the point of

00:30:40.519 --> 00:30:46.200
this picture is in the book is is is to

00:30:43.960 --> 00:30:49.000
highlight that it's a little messy the

00:30:46.200 --> 00:30:52.519
picture but to highlight that if you

00:30:49.000 --> 00:30:55.398
look in different regions oecd a major

00:30:52.519 --> 00:30:57.638
the major economies H tend to the

00:30:55.398 --> 00:31:00.518
pattern I show you holds if you look at

00:30:57.638 --> 00:31:03.038
only isolate only the blue the blue

00:31:00.519 --> 00:31:06.919
squares you tend to see that negative

00:31:03.038 --> 00:31:11.000
relationship if you look at within

00:31:06.919 --> 00:31:13.639
Asia it's also it's a little bit noisier

00:31:11.000 --> 00:31:15.440
but you also tend to see a negative

00:31:13.638 --> 00:31:17.918
relationship

00:31:15.440 --> 00:31:21.960
okay if you look at

00:31:17.919 --> 00:31:23.679
Africa that relationship is lost

00:31:21.960 --> 00:31:27.519
completely

00:31:23.679 --> 00:31:28.798
okay so so when you look at the world as

00:31:27.519 --> 00:31:30.519
a whole

00:31:28.798 --> 00:31:32.558
the picture is not as neat as the one I

00:31:30.519 --> 00:31:33.960
show you because there are certain

00:31:32.558 --> 00:31:35.720
pockets of the world that are not

00:31:33.960 --> 00:31:38.360
behaving according to the kind of mods I

00:31:35.720 --> 00:31:39.839
want I discuss in the next few lectures

00:31:38.359 --> 00:31:42.000
and the reason they're not behaving is

00:31:39.839 --> 00:31:45.359
entirely it's almost outside economics

00:31:42.000 --> 00:31:47.599
it has it's political conflicts Wars and

00:31:45.359 --> 00:31:49.359
things of that nature which continuously

00:31:47.599 --> 00:31:50.719
disrupt sort of the economic forces that

00:31:49.359 --> 00:31:53.398
I'm going to highlight in the next few

00:31:50.720 --> 00:31:56.720
lectures

00:31:53.398 --> 00:31:58.599
okay so that's a different different

00:31:56.720 --> 00:32:01.278
different issue where going to be about

00:31:58.599 --> 00:32:06.959
the all the moles I'll show you next are

00:32:01.278 --> 00:32:06.960
about the blue and the and the

00:32:07.319 --> 00:32:13.918
green squares and and and triangles

00:32:10.599 --> 00:32:13.918
there not about the red

00:32:14.798 --> 00:32:20.599
ones what about so I look I show you

00:32:17.759 --> 00:32:23.200
what happens across countries over over

00:32:20.599 --> 00:32:26.678
certain period of time which is long but

00:32:23.200 --> 00:32:29.798
not that long here you see what happens

00:32:26.679 --> 00:32:31.720
in longer here history there are two

00:32:29.798 --> 00:32:35.558
patterns that I like to highlight here

00:32:31.720 --> 00:32:37.839
is that H first for a while sort of you

00:32:35.558 --> 00:32:40.480
you didn't see much but but you tend to

00:32:37.839 --> 00:32:45.038
see a sort of a big acceleration in the

00:32:40.480 --> 00:32:48.599
Western World especially around the the

00:32:45.038 --> 00:32:50.158
1950s or so okay so so clearly the

00:32:48.599 --> 00:32:52.519
Western world was growing faster than

00:32:50.159 --> 00:32:56.360
the rest of the world H the Western

00:32:52.519 --> 00:32:59.839
Hemisphere this is a um um world Bank

00:32:56.359 --> 00:32:59.839
IFI type type

00:33:01.200 --> 00:33:05.798
um

00:33:03.159 --> 00:33:07.919
grouping and and you see that there's a

00:33:05.798 --> 00:33:12.119
very fast acceleration in growth in this

00:33:07.919 --> 00:33:14.240
episode here Western Europe H was also

00:33:12.119 --> 00:33:16.079
flattish and then picked up very

00:33:14.240 --> 00:33:18.558
strongly there and you see the different

00:33:16.079 --> 00:33:21.480
regions of the world and again you see

00:33:18.558 --> 00:33:26.879
the sub Sahara Africa region that sort

00:33:21.480 --> 00:33:26.880
of has hasn't really picked up okay

00:33:28.599 --> 00:33:34.079
much longer history well that's the way

00:33:31.440 --> 00:33:36.639
it looks for the world as a whole

00:33:34.079 --> 00:33:38.798
okay you know exponential pictures tend

00:33:36.638 --> 00:33:41.959
to look like that but but this is more

00:33:38.798 --> 00:33:44.240
dramatic than exponential and again what

00:33:41.960 --> 00:33:46.840
happens is

00:33:44.240 --> 00:33:49.679
that what happen here is is going to be

00:33:46.839 --> 00:33:51.480
very different from from the kind of

00:33:49.679 --> 00:33:53.759
mods I'll describe

00:33:51.480 --> 00:33:55.480
next this period here is mostly

00:33:53.759 --> 00:33:58.558
dominated by what's called sort of the

00:33:55.480 --> 00:34:01.440
malthusian era which is essentially

00:33:58.558 --> 00:34:03.759
people live population grew and so on

00:34:01.440 --> 00:34:06.679
depending on how good was the the

00:34:03.759 --> 00:34:07.960
harvest that year and so on no so so you

00:34:06.679 --> 00:34:10.200
had this mod in which you know his

00:34:07.960 --> 00:34:13.079
population grew faster that was a main

00:34:10.199 --> 00:34:15.000
driver of of of growth well but you know

00:34:13.079 --> 00:34:17.280
there wasn't enough food to sustain a a

00:34:15.000 --> 00:34:18.878
higher population and then you stay

00:34:17.280 --> 00:34:21.760
soort of there was a fight between food

00:34:18.878 --> 00:34:23.559
and and and people and and and no much

00:34:21.760 --> 00:34:26.960
space for most people were in

00:34:23.559 --> 00:34:28.679
agriculture and and the and and and

00:34:26.960 --> 00:34:31.320
there wasn't sort of

00:34:28.679 --> 00:34:33.159
much to build on nowadays there are

00:34:31.320 --> 00:34:36.119
pocket in the world and we had the

00:34:33.159 --> 00:34:38.358
severe situations during covid but food

00:34:36.119 --> 00:34:41.838
is not really a constraint for growth

00:34:38.358 --> 00:34:44.679
for the world as a whole

00:34:41.838 --> 00:34:47.358
okay and but you see

00:34:44.679 --> 00:34:49.878
so in other words had you taken this

00:34:47.358 --> 00:34:51.878
course in 20 in year 1000 or in the

00:34:49.878 --> 00:34:54.000
Renaissance nobody would have talked

00:34:51.878 --> 00:34:56.960
about growth it's not something that

00:34:54.000 --> 00:34:59.159
happened really it's it's a very modern

00:34:56.960 --> 00:35:02.679
thing to think about these pictures with

00:34:59.159 --> 00:35:05.118
these long Trends and so on

00:35:02.679 --> 00:35:06.598
okay I mean there you would have talked

00:35:05.119 --> 00:35:09.079
about a lot more interesting things than

00:35:06.599 --> 00:35:12.280
this but but not not about growth that's

00:35:09.079 --> 00:35:13.839
for sure and growth the last point I I

00:35:12.280 --> 00:35:15.359
think I want to make about this is it

00:35:13.838 --> 00:35:17.320
makes a big

00:35:15.358 --> 00:35:21.199
difference I don't know if you can read

00:35:17.320 --> 00:35:23.680
that I I can't but er um what I have

00:35:21.199 --> 00:35:28.159
here is GDP per capita in

00:35:23.679 --> 00:35:30.358
1950 versus GDP per capita in 2016

00:35:28.159 --> 00:35:33.239
and you have this isoquants here you

00:35:30.358 --> 00:35:35.559
move you as you move up so this line

00:35:33.239 --> 00:35:38.959
here is what happens to countries that

00:35:35.559 --> 00:35:40.920
is a 45 degree line so if you are on the

00:35:38.960 --> 00:35:43.199
45 degree line means that you haven't

00:35:40.920 --> 00:35:45.920
grown at all during this period no

00:35:43.199 --> 00:35:48.838
because that means that your GDP per

00:35:45.920 --> 00:35:52.079
capita 1950 is the same as you g GDP per

00:35:48.838 --> 00:35:54.960
capita in 2016 that means on average you

00:35:52.079 --> 00:35:57.680
grow okay but as I keep moving these

00:35:54.960 --> 00:35:58.960
lines up means you grew faster and fter

00:35:57.679 --> 00:36:03.078
faster and

00:35:58.960 --> 00:36:05.280
faster okay so and if you if you move

00:36:03.079 --> 00:36:07.318
along this line here that means you have

00:36:05.280 --> 00:36:10.280
negative growth on average during that

00:36:07.318 --> 00:36:13.719
period okay so each of these lines

00:36:10.280 --> 00:36:17.280
represents multiples so I think this is

00:36:13.719 --> 00:36:19.318
for example this top line here is 30

00:36:17.280 --> 00:36:21.760
times richer these are guys that grew

00:36:19.318 --> 00:36:23.838
very very fast yeah you I cannot read

00:36:21.760 --> 00:36:24.960
either but I I sort of know who is in

00:36:23.838 --> 00:36:26.559
each

00:36:24.960 --> 00:36:30.358
Place

00:36:26.559 --> 00:36:36.279
h this is an example here this is

00:36:30.358 --> 00:36:38.880
Taiwan okay this is Taiwan and H this is

00:36:36.280 --> 00:36:41.319
Singapore they have a name how do we

00:36:38.880 --> 00:36:41.318
call those

00:36:41.400 --> 00:36:44.680
countries no

00:36:44.960 --> 00:36:51.800
well the Asian tigers they grew very

00:36:48.318 --> 00:36:55.440
very strong for for a long time since

00:36:51.800 --> 00:36:57.760
the 60s or so but there you see you can

00:36:55.440 --> 00:37:01.679
compare if you could see you would see

00:36:57.760 --> 00:37:03.480
that you know that that Taiwan and the

00:37:01.679 --> 00:37:05.759
Democratic Republic of Congo had the

00:37:03.480 --> 00:37:10.079
same GDP in

00:37:05.760 --> 00:37:14.119
1950 okay now the Republic Democratic

00:37:10.079 --> 00:37:19.760
Republic of of of of Congo has less GDP

00:37:14.119 --> 00:37:23.880
than it had ER in 1950 it had 1700 here

00:37:19.760 --> 00:37:25.720
and 800 today while Taiwan Taiwan has 30

00:37:23.880 --> 00:37:28.480
times what it used to

00:37:25.719 --> 00:37:31.799
have and so today is one of the richest

00:37:28.480 --> 00:37:35.960
economies in the world close to 7

00:37:31.800 --> 00:37:40.079
$50,000 per capita while the Republic of

00:37:35.960 --> 00:37:44.639
Congo ER has

00:37:40.079 --> 00:37:47.119
700 $800 per capita so growth makes a

00:37:44.639 --> 00:37:49.078
big big difference okay and these are

00:37:47.119 --> 00:37:54.079
not that many years I mean you know this

00:37:49.079 --> 00:37:56.318
is just 70 years H and I can assure you

00:37:54.079 --> 00:37:58.079
that these people they have other

00:37:56.318 --> 00:38:00.159
concerns but

00:37:58.079 --> 00:38:01.640
their standard of living is a lot higher

00:38:00.159 --> 00:38:04.639
than these people and at some point they

00:38:01.639 --> 00:38:06.358
were the same the big difference is some

00:38:04.639 --> 00:38:09.639
countries that grew and some

00:38:06.358 --> 00:38:12.279
countries got a stuck um where is

00:38:09.639 --> 00:38:13.400
Argentina here I don't know somewhere

00:38:12.280 --> 00:38:16.599
here

00:38:13.400 --> 00:38:16.599
probably it's

00:38:18.760 --> 00:38:26.359
Argentina I don't know I cannot

00:38:21.880 --> 00:38:28.318
see have the chance here I can say okay

00:38:26.358 --> 00:38:30.159
good so growth that's make a difference

00:38:28.318 --> 00:38:33.119
and he has made a huge the world we see

00:38:30.159 --> 00:38:36.199
today and the countries we think as rich

00:38:33.119 --> 00:38:38.760
or poor were not the same countries that

00:38:36.199 --> 00:38:41.919
you thought in in those terms in

00:38:38.760 --> 00:38:44.160
1950 Asia is one of the most prominent

00:38:41.920 --> 00:38:46.440
differences they have massive growth

00:38:44.159 --> 00:38:48.039
through the

00:38:46.440 --> 00:38:51.079
60s

00:38:48.039 --> 00:38:53.039
um starting with Japan but then the rest

00:38:51.079 --> 00:38:56.280
and again were the famous the Tigers

00:38:53.039 --> 00:38:58.800
Hong Kong Taiwan

00:38:56.280 --> 00:39:02.640
Singapore uh

00:38:58.800 --> 00:39:08.560
and Korea South

00:39:02.639 --> 00:39:11.159
Korea good so let's start building some

00:39:08.559 --> 00:39:13.599
moles of what we have just

00:39:11.159 --> 00:39:16.039
seen remember when we look at the short

00:39:13.599 --> 00:39:18.039
run we really didn't care about the

00:39:16.039 --> 00:39:19.800
supply side of the economy remember it

00:39:18.039 --> 00:39:22.679
was all about demand they said well you

00:39:19.800 --> 00:39:25.560
know demand look what consumers invest

00:39:22.679 --> 00:39:28.000
firms and governments do with demand

00:39:25.559 --> 00:39:30.559
that determines output and output

00:39:28.000 --> 00:39:32.880
happens well it happens we didn't really

00:39:30.559 --> 00:39:35.078
care too much about it then when we talk

00:39:32.880 --> 00:39:36.920
about the medium term we say okay we're

00:39:35.079 --> 00:39:40.880
going to no no we have to care because

00:39:36.920 --> 00:39:42.440
you know to produce you need workers and

00:39:40.880 --> 00:39:44.640
and you know workers are not going to

00:39:42.440 --> 00:39:47.920
work for any wage and so we had to begin

00:39:44.639 --> 00:39:50.519
to talk about ER the the supply side of

00:39:47.920 --> 00:39:52.119
the economy but we made it very simple

00:39:50.519 --> 00:39:54.400
we just look at the problem of wage

00:39:52.119 --> 00:39:56.160
bargaining and price setting but the

00:39:54.400 --> 00:39:57.760
production function itself wasn't that

00:39:56.159 --> 00:39:59.318
interesting it was outputting equal to

00:39:57.760 --> 00:40:01.920
labor and I told you it's very

00:39:59.318 --> 00:40:04.239
unrealistic but it was convenient for

00:40:01.920 --> 00:40:06.440
that part of the course because Capital

00:40:04.239 --> 00:40:08.199
doesn't grow that fast so typical

00:40:06.440 --> 00:40:10.599
production function we have both capital

00:40:08.199 --> 00:40:12.799
and labor but at the business cycle

00:40:10.599 --> 00:40:14.480
frequency investment the change in

00:40:12.800 --> 00:40:16.039
capital can be large but the stock of

00:40:14.480 --> 00:40:18.039
capital doesn't move that much and so

00:40:16.039 --> 00:40:20.000
you can ignore it for business cycle

00:40:18.039 --> 00:40:22.239
type fluctuations but if we want to look

00:40:20.000 --> 00:40:24.400
at the long run Capital plays a huge

00:40:22.239 --> 00:40:27.000
role capital accumulation and so we have

00:40:24.400 --> 00:40:28.559
to be explicit about the role of capital

00:40:27.000 --> 00:40:31.239
in the the production

00:40:28.559 --> 00:40:32.400
function so this is going to be our now

00:40:31.239 --> 00:40:34.239
and now we're going to forget about

00:40:32.400 --> 00:40:35.800
aggregate demand we're going to say look

00:40:34.239 --> 00:40:37.358
we're going to focus about AGG supply

00:40:35.800 --> 00:40:41.640
and demand will do whatever it needs to

00:40:37.358 --> 00:40:46.960
do so so so we get what what the supply

00:40:41.639 --> 00:40:49.480
site says so output now will be will be

00:40:46.960 --> 00:40:51.599
a an increasing function of both capital

00:40:49.480 --> 00:40:54.000
and

00:40:51.599 --> 00:40:57.640
labor now this function will have a

00:40:54.000 --> 00:40:58.440
bunch of er properties which are many of

00:40:57.639 --> 00:41:00.879
which

00:40:58.440 --> 00:41:03.039
are no at a broad level they are

00:41:00.880 --> 00:41:04.559
empirically validated but they're also

00:41:03.039 --> 00:41:07.239
very convenient from the modeling point

00:41:04.559 --> 00:41:08.799
of view the first and most

00:41:07.239 --> 00:41:12.639
important

00:41:08.800 --> 00:41:15.280
property um is constant returns to

00:41:12.639 --> 00:41:19.039
scale okay we're going to use a lot of

00:41:15.280 --> 00:41:22.400
property so so please get that concept

00:41:19.039 --> 00:41:25.119
constant return to scale means simply

00:41:22.400 --> 00:41:28.480
that if you scale the factors of

00:41:25.119 --> 00:41:33.519
production you also scale the output

00:41:28.480 --> 00:41:36.838
okay so say if x is 1.1 that means if

00:41:33.519 --> 00:41:40.519
you increase capital and labor by 10%

00:41:36.838 --> 00:41:42.559
you get 10% more output okay so that's

00:41:40.519 --> 00:41:44.079
Conant return to scale if I scale all

00:41:42.559 --> 00:41:46.880
the factors of production by the same

00:41:44.079 --> 00:41:49.839
amount the same proportion then output

00:41:46.880 --> 00:41:51.880
Grows by the same proportion it's

00:41:49.838 --> 00:41:54.279
scalable that's what it mean constant

00:41:51.880 --> 00:41:54.280
return to

00:41:54.838 --> 00:42:02.599
scale very important property what comes

00:41:58.280 --> 00:42:02.599
next decreasing returns to

00:42:03.000 --> 00:42:08.519
Capital that

00:42:05.440 --> 00:42:11.039
is H as you increase capital for a fixed

00:42:08.519 --> 00:42:13.239
amount of Labor so conent scale is a

00:42:11.039 --> 00:42:15.679
property of scaling everything

00:42:13.239 --> 00:42:17.639
up the property I'm describing here is

00:42:15.679 --> 00:42:20.598
what happens if we increase only K what

00:42:17.639 --> 00:42:23.118
happens to Output if we increase only K

00:42:20.599 --> 00:42:27.480
but fixing

00:42:23.119 --> 00:42:29.039
n in other words set this to one and

00:42:27.480 --> 00:42:31.318
start moving this

00:42:29.039 --> 00:42:33.519
up you're not going to get X here you're

00:42:31.318 --> 00:42:36.838
going to get something different from

00:42:33.519 --> 00:42:39.159
X and but this tells you is that yes

00:42:36.838 --> 00:42:42.078
you're going to get more output but less

00:42:39.159 --> 00:42:45.440
and less the more Capital you

00:42:42.079 --> 00:42:48.079
have Okay so this says for example

00:42:45.440 --> 00:42:50.440
suppose you start with 100 workers and

00:42:48.079 --> 00:42:53.079
100 units of capital and it happens that

00:42:50.440 --> 00:42:57.920
this produces 100 units of

00:42:53.079 --> 00:42:59.640
goods if you add now 10 units of capital

00:42:57.920 --> 00:43:04.639
say you're going to

00:42:59.639 --> 00:43:06.199
get seven units of output not 10 seven

00:43:04.639 --> 00:43:07.920
because you didn't increase labor had I

00:43:06.199 --> 00:43:09.879
increased labor also by by 10 I would

00:43:07.920 --> 00:43:13.800
have gotten 10 of output but I

00:43:09.880 --> 00:43:16.519
increasing only h capital by 10 then and

00:43:13.800 --> 00:43:18.640
keeping output fixed then labor fixed

00:43:16.519 --> 00:43:21.000
then output will increase by less than

00:43:18.639 --> 00:43:23.199
10 but what this decrease in returns to

00:43:21.000 --> 00:43:26.639
Capital says is that now if you increase

00:43:23.199 --> 00:43:27.960
again from 110 to 120 units of capital

00:43:26.639 --> 00:43:30.279
you're going to get get less than seven

00:43:27.960 --> 00:43:32.480
units of output more you're going to get

00:43:30.280 --> 00:43:34.720
five and if you increase a again from

00:43:32.480 --> 00:43:37.199
120 to 130 you're going to get less than

00:43:34.719 --> 00:43:39.199
five you're going to get three and so on

00:43:37.199 --> 00:43:41.960
so forth that's decreasing returns to

00:43:39.199 --> 00:43:45.598
scale and and decreasing returns to

00:43:41.960 --> 00:43:47.838
Capital and the reason for that is is

00:43:45.599 --> 00:43:49.280
economically is that more and more

00:43:47.838 --> 00:43:51.440
capital is working with a fixed number

00:43:49.280 --> 00:43:52.400
of workers so labor becomes very scarce

00:43:51.440 --> 00:43:55.440
for

00:43:52.400 --> 00:43:57.720
capital okay and that's the reason so so

00:43:55.440 --> 00:43:58.838
you have very little

00:43:57.719 --> 00:44:00.439
the other these are factors of

00:43:58.838 --> 00:44:02.799
production which are complementary they

00:44:00.440 --> 00:44:05.760
need each other labor and capital if you

00:44:02.800 --> 00:44:07.760
fix one and it start increasing only one

00:44:05.760 --> 00:44:09.720
then it's harder and harder for each

00:44:07.760 --> 00:44:11.839
extra new unit of this one to work with

00:44:09.719 --> 00:44:13.480
sort of fewer and fewer of the other

00:44:11.838 --> 00:44:16.000
factor of production so the same

00:44:13.480 --> 00:44:18.639
principle applies to labor if you fix

00:44:16.000 --> 00:44:21.480
capital and you only increase labor then

00:44:18.639 --> 00:44:22.920
initially you get a big jumping output

00:44:21.480 --> 00:44:26.318
but it's going to be smaller and smaller

00:44:22.920 --> 00:44:29.039
and smaller the more you keep adding a

00:44:26.318 --> 00:44:29.039
um

00:44:29.119 --> 00:44:36.960
labor okay so in pi so let me One X that

00:44:34.079 --> 00:44:40.880
we're going to use

00:44:36.960 --> 00:44:46.318
throughout is we want to make x one of

00:44:40.880 --> 00:44:46.318
our favorite X will be 1 /

00:44:46.400 --> 00:44:52.760
n you see what I'm trying to do when we

00:44:49.039 --> 00:44:56.239
set x equal to 1 / n so that x equal to

00:44:52.760 --> 00:44:58.440
1 / n what I get here is output per

00:44:56.239 --> 00:45:00.239
person

00:44:58.440 --> 00:45:02.519
no that's what I

00:45:00.239 --> 00:45:08.039
get y Over

00:45:02.519 --> 00:45:09.920
N so if I set xal to 1/ n i can using

00:45:08.039 --> 00:45:11.079
con to scale I know that this is equal

00:45:09.920 --> 00:45:16.159
to

00:45:11.079 --> 00:45:18.839
y/n k/ n n/ n so that is one so this guy

00:45:16.159 --> 00:45:22.239
doesn't move and I have now

00:45:18.838 --> 00:45:24.679
that a output per person is increasing

00:45:22.239 --> 00:45:26.039
in capital per worker worker and

00:45:24.679 --> 00:45:28.719
population this part of the course are

00:45:26.039 --> 00:45:31.639
the same for get an EMP employment and

00:45:28.719 --> 00:45:34.358
is population is employment if labor

00:45:31.639 --> 00:45:38.440
force is everything I'm not this is not

00:45:34.358 --> 00:45:38.440
a place to worry about unemployment

00:45:41.800 --> 00:45:47.640
okay okay so remember that all the plots

00:45:45.079 --> 00:45:50.039
I show you the different Figures were

00:45:47.639 --> 00:45:52.078
about this variable how it changed over

00:45:50.039 --> 00:45:54.679
time how was different across different

00:45:52.079 --> 00:45:57.800
countries how grew at a different rate

00:45:54.679 --> 00:46:00.879
in in different countries but from this

00:45:57.800 --> 00:46:01.839
very simple model you see that in order

00:46:00.880 --> 00:46:05.039
to

00:46:01.838 --> 00:46:07.119
explain the change in this or growth in

00:46:05.039 --> 00:46:09.719
why over and why one country grows more

00:46:07.119 --> 00:46:12.960
than the other you have with the simple

00:46:09.719 --> 00:46:12.959
model only two

00:46:13.280 --> 00:46:20.720
options so if I tell you country a grew

00:46:17.559 --> 00:46:23.280
more over this period than grew more per

00:46:20.719 --> 00:46:28.358
per person than this other

00:46:23.280 --> 00:46:29.920
country er um over this period of time

00:46:28.358 --> 00:46:32.239
there are only two options here the

00:46:29.920 --> 00:46:34.400
first one is that in that country there

00:46:32.239 --> 00:46:37.879
was more capital accumulation per worker

00:46:34.400 --> 00:46:39.838
so K Over N went up no if K Over N goes

00:46:37.880 --> 00:46:42.960
up more in one country than the other

00:46:39.838 --> 00:46:45.679
one y Over N will go up more in that

00:46:42.960 --> 00:46:49.559
country than the other one and the other

00:46:45.679 --> 00:46:51.358
option is that the this H function

00:46:49.559 --> 00:46:56.280
itself shifted

00:46:51.358 --> 00:46:58.719
up so for any given amount of K Over N

00:46:56.280 --> 00:47:00.359
now you could produ more y over n and

00:46:58.719 --> 00:47:04.078
that's what we call technological

00:47:00.358 --> 00:47:07.239
progress that's a second thing so so if

00:47:04.079 --> 00:47:09.760
if if the difference in in in in growth

00:47:07.239 --> 00:47:12.358
of output per

00:47:09.760 --> 00:47:13.880
person is due to an increasing K Over

00:47:12.358 --> 00:47:16.358
end well we call that a capill

00:47:13.880 --> 00:47:18.880
accumulation mechanism if it is because

00:47:16.358 --> 00:47:20.759
the function f shifts up that's

00:47:18.880 --> 00:47:22.680
technological progress and what we're

00:47:20.760 --> 00:47:24.359
going to do is in the next lecture we're

00:47:22.679 --> 00:47:28.440
going to talk about this channel the

00:47:24.358 --> 00:47:30.880
capital accumulation Channel and in the

00:47:28.440 --> 00:47:32.960
lecture after the spring break we're

00:47:30.880 --> 00:47:36.400
going to talk about shift in the

00:47:32.960 --> 00:47:38.318
function f so in in in in

00:47:36.400 --> 00:47:40.760
figures

00:47:38.318 --> 00:47:43.199
so fixing the technology that this is

00:47:40.760 --> 00:47:45.480
the function f is fixed and you just

00:47:43.199 --> 00:47:48.279
move K Over N this is the picture you

00:47:45.480 --> 00:47:51.000
have now that's a produ this I'm

00:47:48.280 --> 00:47:55.079
plotting this function here as a

00:47:51.000 --> 00:47:57.559
function of k/ n for a fixed function f

00:47:55.079 --> 00:48:00.318
and that's what you get so output per I

00:47:57.559 --> 00:48:02.160
have here Capital per worker and output

00:48:00.318 --> 00:48:05.400
per per

00:48:02.159 --> 00:48:06.838
worker and you see that obviously it's

00:48:05.400 --> 00:48:08.240
in an increasing function the more

00:48:06.838 --> 00:48:10.199
Capital per worker you have the more

00:48:08.239 --> 00:48:13.799
output per worker you'll

00:48:10.199 --> 00:48:13.799
produce but it's also

00:48:13.920 --> 00:48:17.318
concave why is it

00:48:19.559 --> 00:48:25.559
concave that's decrease in returns to

00:48:21.760 --> 00:48:28.000
Capital is look for any when you have

00:48:25.559 --> 00:48:30.040
very little Capital per work

00:48:28.000 --> 00:48:31.519
a change in capital per worker gives

00:48:30.039 --> 00:48:33.800
gives you a big jumping output per

00:48:31.519 --> 00:48:35.239
worker because you know there was sort

00:48:33.800 --> 00:48:36.760
of very little Capital that was the

00:48:35.239 --> 00:48:39.318
problem of that

00:48:36.760 --> 00:48:42.800
economy when the economy has more and

00:48:39.318 --> 00:48:44.880
more Capital the same change in capital

00:48:42.800 --> 00:48:47.519
leads to a much smaller change in output

00:48:44.880 --> 00:48:49.599
here at this level when when Capital per

00:48:47.519 --> 00:48:53.798
worker was very low the economy was very

00:48:49.599 --> 00:48:56.798
poor then this change LED to this change

00:48:53.798 --> 00:48:59.480
in output per capita at this level of

00:48:56.798 --> 00:49:01.358
wealth if you get as capital economies

00:48:59.480 --> 00:49:04.400
with higher Capital are richer Capital

00:49:01.358 --> 00:49:06.199
per worker the same change this change

00:49:04.400 --> 00:49:08.079
is of the same size as that leads to a

00:49:06.199 --> 00:49:10.558
much smaller change in

00:49:08.079 --> 00:49:13.559
output okay and that's a result of

00:49:10.559 --> 00:49:15.640
decreasing returns to

00:49:13.559 --> 00:49:16.720
Capital and that's the other option

00:49:15.639 --> 00:49:20.078
again that's what we're going to talk

00:49:16.719 --> 00:49:21.519
about in the next lecture this this one

00:49:20.079 --> 00:49:24.000
and two lectures from now we're going to

00:49:21.519 --> 00:49:25.519
talk about growth that comes from shift

00:49:24.000 --> 00:49:27.440
in the production function this

00:49:25.519 --> 00:49:32.679
technological progress

00:49:27.440 --> 00:49:32.679
okay very good see you on Wednesday