[00:16] okay so um today we're want to start
[00:19] talking about the long run I've been
[00:20] talking about the business cycles and
[00:23] today we're going to start talking about
[00:24] things that happen over decades H but
[00:27] before I do that before we finish with
[00:30] the the short run medium run I just
[00:34] don't want you to I want I don't want to
[00:36] give you the impression that that you
[00:38] know once you understand the ISL MPC
[00:41] sort of you you can start managing
[00:43] monetary
[00:44] policy immediately I
[00:47] I there's a lot of noise of all sort of
[00:50] kind of complexity in the real world of
[00:52] course that can make um policies
[00:57] uh uh very hard to manage in practice
[01:01] macroeconomic policies and one
[01:03] fundamental principle I would say is
[01:06] that policy makers understand that speed
[01:09] can kill okay and uh that's very obvious
[01:14] during financial crisis there we all
[01:16] understand that ER the response needs to
[01:19] be large it has to be a response with
[01:22] overwhelming Force essentially because
[01:25] things are happening so fast that very
[01:27] few corporations even healthy
[01:28] corporations that that can adjust
[01:31] quickly enough uh to the PACE at which
[01:33] things are changing prices become
[01:35] noninformative uh fire cells take place
[01:39] and and and obviously it's very
[01:40] difficult to make economic decisions in
[01:42] that context and so that's the reason
[01:45] they are the speed in the on the on the
[01:47] policy Direction goes very clearly in
[01:48] One Direction do it quickly and very
[01:51] large
[01:52] now on the other hand ER when you're
[01:56] going through a period in which you're
[01:57] are hiking interest rates for example
[02:00] ER like we're going through now um the
[02:05] the Tendencies towards gradualism to do
[02:07] it very slowly because something can
[02:10] break along the path and it's often the
[02:13] case that with for sufficiently large
[02:16] adjustments something breaks okay and so
[02:19] here you have an example of sort of
[02:21] major episodes of hiking in the US and
[02:24] things that have happened about those
[02:27] those H major episodes
[02:30] this one actually I I have a personal
[02:32] attachment to that one because you know
[02:35] I was studying in Chile around then
[02:38] everything was going wonderfully massive
[02:40] Capital flows to Chile emerging markets
[02:42] were very popular we all felt very
[02:44] wealthy rich and so on and right after I
[02:48] finished College ER I was not planning
[02:51] to come to the usy things were going
[02:53] very well in Chile H but the US decided
[02:56] to hike interest rate very aggressively
[02:58] all of the sudden Capital flows to
[02:59] emergy markets disappear we went into an
[03:01] enormous financial crisis I lost I had
[03:05] no opportunity cost and I had to come to
[03:06] study to the US that that's my so I know
[03:09] that hikes aggressive hikes can matter
[03:12] can make differences to people but and
[03:15] that
[03:15] was there's a decade that followed that
[03:18] episode that is called the L decade of
[03:21] Latin America essentially so things did
[03:23] break and and one of the main reasons
[03:26] they did break is because at the time
[03:28] most of the capital close that's not
[03:30] what happens today we really being
[03:32] managed by global Banks and the banks
[03:36] can get very distressed when interest
[03:38] rate rise H very very quickly and so
[03:41] that that was essentially a problem with
[03:43] us the US Banks major Global Banks but
[03:46] the US Banks in particular that trigger
[03:49] an Emerging Market
[03:51] crisis this one also had huge
[03:54] consequences actually and it's
[03:56] interesting because this episode is is
[03:58] similar to to to to what we're going on
[04:02] what is going on right now or what may
[04:05] happen in soon so this is episode of
[04:08] hikes that ended what is called The
[04:11] Savings and Loan crisis and those so the
[04:15] best parallel to today are the small
[04:17] Regional Banks if you will and they they
[04:20] weren't able to withstand this sort of
[04:21] sharp rise in interest rate which is
[04:23] very much what is going on right now in
[04:26] the US this one actually end up with
[04:29] also another problem which is the the
[04:32] the bubble burst in Japan episode of
[04:35] hiking in the US and there we had a
[04:37] major crisis in in Japan the price of
[04:41] real estate
[04:42] collapsed ER and and essentially they
[04:46] since then they have never been able to
[04:47] grow as they used to before that that
[04:51] episode that's called sometimes the
[04:54] tequila crisis it's a Mexican
[04:57] Bond crisis and it was again the result
[04:59] of a hiking episode in the US conditions
[05:02] tighten to Emerging Market ER their bone
[05:06] Market essentially
[05:08] exploded um well this is the global
[05:10] financial crisis the Great Recession it
[05:13] was again preceded by episode of sort of
[05:16] aggressive hikes which eventually er um
[05:22] led to a turn around as house prices
[05:24] were Rising steadily throughout the
[05:26] episode and a lot of financial assets
[05:28] were created around that housing wealth
[05:31] that was been created that hike and
[05:33] interest rate eventually put a stop an
[05:35] end to that that appreciation of house
[05:37] prices in fact they turn around and it
[05:39] led to a very significant financial
[05:42] crisis and this is where we're at right
[05:45] now okay and so we already seen sort of
[05:48] some Tremors and so on so the point is
[05:52] when when sometimes you say well why is
[05:54] isn't the FED more aggressive if we have
[05:56] high inflation and go very quickly at it
[05:58] well it's because things can go wrong
[06:01] okay and it it typically happens that
[06:04] things do go wrong you don't know
[06:05] exactly what will blow up but something
[06:08] may blow up and typically is associated
[06:11] to some Financial Market that is very
[06:13] hot and the market and the banks are
[06:15] always involved in that because the
[06:16] banks are very
[06:17] lever you know they have little Capital
[06:20] relative to the assets they have and
[06:22] that means small variation in the price
[06:24] of assets can lead to very large H
[06:26] changes in the value of their
[06:28] capital anyway so just a warning so if
[06:32] you get a job at the FED please be
[06:35] careful okay now let me switch gears and
[06:38] and we're going to talk about um um
[06:42] something a little different from what
[06:43] we have been discussing up to now so
[06:45] this is some this is growth projections
[06:48] for different regions in the world ER
[06:51] this is something that is in publishing
[06:53] by the IMF it's called the world
[06:55] economic Outlook I think I mentioned it
[06:57] before and here you have some forecast
[06:59] you know well this is actually what
[07:01] happened so growth in the global economy
[07:04] was about 3.4% 2022 advanced economies
[07:08] grew at 2.7% emerging markets and
[07:11] developing economies at
[07:13] 3.9% and then you see forast and the
[07:16] further out you go er um the okay the
[07:20] further out you go sort of it's less
[07:22] related to the current cycle is more
[07:25] related to what is structural the
[07:26] structural
[07:27] growth of the different parts of the
[07:30] world and you see that for
[07:32] 2024 the global economy is projected
[07:35] expected to grow at around 3.1% this
[07:37] forecast were made before the mess
[07:38] Financial mess that we're going on right
[07:40] now so probably the next World economic
[07:42] Outlook will have at least for 2023 will
[07:46] will downgrade the growth probably not
[07:48] for 2024 but yes for 2023 anyways
[07:51] advanced economies expected to grow
[07:54] 1.4% emerging markets at
[07:57] 4.2% so
[08:00] these forecasts are based on on a
[08:03] combination of cyclical factors
[08:05] fluctuations of the short run medium run
[08:07] the kind of things we have been
[08:08] discussing up to now some economies will
[08:10] have to go through recession some
[08:12] economies are going through Booms that
[08:14] probably dominates 20 the forus on 2023
[08:17] but as I said before the further out you
[08:19] go the more the less relevant is the
[08:21] current business cycle and the more
[08:23] relevant is the structural trend of the
[08:26] different regions of the world okay so I
[08:28] would that in this when they formulated
[08:31] this forecast this is very much based on
[08:33] more longer run growth model the kind of
[08:35] models we're going to discuss now okay
[08:38] while this is probably totally dominated
[08:41] by the kind of things we discuss up to
[08:42] now okay
[08:46] um there are several things that that
[08:48] that are interesting here aside from
[08:51] sort of the the the
[08:54] fluctuations year to year one thing you
[08:56] can see for example is that regardless
[08:59] of year
[09:00] on average Emerging Markets tend to grow
[09:02] faster than develop economies advanced
[09:04] economies okay so one of the things we
[09:06] want to understand is why is that the
[09:08] case okay but that's is very clear here
[09:12] that's the first model we're going to
[09:13] look at which probably will happen on
[09:15] Wednesday we'll try to explain
[09:17] essentially that why is it that these
[09:19] guys tend to grow faster than the
[09:21] advanced economies
[09:25] okay so growth is important I mean the
[09:28] standing economic growth is hugely
[09:30] important for the weal for understanding
[09:32] sort of the health of an economy here
[09:35] you see this comes from the textbook er
[09:39] er the the US GDP in 20 20
[09:44] uh2 from
[09:46] 1890 to to 2017 I think is this one the
[09:50] the end year the important thing to
[09:53] notice here is how large is the change
[09:57] in GDP in during the period I mean GDP
[10:01] here measuring the same prices so 20
[10:04] 2012 prices is 50 times that in 1890
[10:09] that's a big thing I mean when we talk
[10:10] about business cycle fluctuations we're
[10:12] talking about in an economy like the US
[10:15] two two and a half% up 3% up and down
[10:19] this is 50 times so over longer period
[10:22] of time you can almost ignore the
[10:25] business cycle and it's all about that
[10:27] long run H trend
[10:30] here what is this episode so so you here
[10:33] if you if you look at this picture know
[10:36] especially the F out you are on the on
[10:37] the on the room what dominates here is
[10:40] clearly the
[10:41] trend the only action you see really
[10:43] significant action different from the
[10:45] trend is around here what happened
[10:50] there it's the Great Depression so even
[10:53] the Great Depression you know doesn't
[10:54] look that big relative to what the trend
[10:57] can do so
[10:59] of course it's very difficult to affect
[11:01] the trend of a country but the trend
[11:03] makes a huge difference for the welfare
[11:05] for
[11:07] the economic well-being of a
[11:11] country
[11:12] good now a lot of that is because also
[11:17] the US population grew up grew up grew
[11:20] up and grew a lot during this episode
[11:23] so often when you look at sort of long
[11:26] run Trends rather than looking at the
[11:27] level of GDP you tend to look at the
[11:30] level of GDP per person per capita or
[11:33] something like that and that picture is
[11:35] exactly the same pictures as the
[11:37] previous one but divided by population
[11:40] at each point in time okay and and and
[11:43] and that's an important over long
[11:45] periods of you at the business cycle
[11:46] frequency you can almost ignore changes
[11:49] in popul no Chang ination you can ignore
[11:51] completely unless you are in a war you
[11:53] can you worry about other things labor
[11:55] force participation and stuff like that
[11:57] but population is irrelevant that the
[11:59] business cycle growth is irrelevant at
[12:01] the business cycle frequency but not
[12:03] over long periods of time in this period
[12:06] here population in the US increased from
[12:08] 63 million to 320 million so that's a
[12:11] lot more workers in principle that you
[12:13] have you know for that economy so a lot
[12:17] of that trend is explained by population
[12:20] growth and that's one of the reason
[12:23] sorry a lot of the trend in this picture
[12:26] here is explained by population growth
[12:29] that's one of the reasons we're in a
[12:30] tricky time in the global economy
[12:32] because there are many important regions
[12:34] of the world where population is no
[12:35] longer growing so we got used to a
[12:38] period in which population growth was
[12:40] very steady and high and now you know
[12:43] many parts of the world important parts
[12:45] of of the world have negative population
[12:48] growth Japan Korea China most of
[12:53] Continental Europe H even places in
[12:56] Latin America and so on so so this is a
[12:58] big change for the world
[13:01] but anyways during that period there was
[13:03] a lot of population growth and in the US
[13:05] in particular when again as I said
[13:07] before from 63 to 320 million so if you
[13:09] really want to measure sort of welfare
[13:12] of the economy how well how the
[13:15] well-being of
[13:16] individuals in in in in the US the
[13:19] previous picture is misleading because
[13:21] you have to yeah it's the final Pi is 50
[13:24] times larger than the first one than the
[13:26] beginning Pi but you have 320 million
[13:29] people to split it among as opposed to
[13:31] 63 million so this picture captures that
[13:35] statistic that is often described when
[13:36] you talk about long run
[13:39] growth ER is GDP per person and you
[13:43] still see that what dominates this
[13:45] picture is a trend ER but the difference
[13:48] between this out out GDP per person in
[13:51] the US at the end of the sample versus
[13:53] the beginning of the sample is 10 to1
[13:55] not 50 to1 so it makes a difference
[13:58] population it's still big it's still
[14:00] what dominates this picture is that of
[14:02] course the Great Recession looks bigger
[14:05] now because you know you comparing it
[14:07] with with a number that grows by a
[14:09] factor of 10 not by a factor of 50
[14:11] that's so it looks bigger naturally know
[14:14] the same 30% decline output is a lot
[14:16] bigger when you're comparing it with
[14:18] the a factor of 10 than when you're
[14:21] comparing it with a factor of 50 but
[14:23] still it looks bigger but the picture is
[14:27] dominated by the
[14:30] so all this to say that we're going to
[14:33] study now is very important it's not
[14:35] what dominates the day-to-day news
[14:36] because it happens slowly and over time
[14:39] but it is very
[14:43] important so how do we measure these
[14:45] things well when you're looking within a
[14:48] country you do reasonably well not
[14:51] perfect but reasonably well and perhaps
[14:54] not over periods as long as I want I
[14:56] show you by looking at GDP per capita
[14:58] that's that's fine is you measure it
[15:01] real GDP per capita that's about fine
[15:04] but when you compare across different
[15:06] regions of the world and so on those
[15:09] comparisons is very misleading so to say
[15:12] that the US has um I don't know
[15:17] ER what is the US GDP per capita today
[15:21] in the US somebody should check it but
[15:23] but about maybe $70,000 something like
[15:28] that I don't know ER and then then then
[15:31] you see a another country that has say
[15:34] Italy $50,000 per
[15:37] capita that comparison is not that
[15:40] meaningful it's indicative of something
[15:43] but it's not completely meaningful and
[15:45] I'm going to show you an example which
[15:46] is much more extreme than that but the
[15:48] reason is not very meaningful is
[15:51] essentially because the prices are not
[15:53] the same across different parts of the
[15:55] world so we have a method to to to to do
[15:59] that to to be able to compare across
[16:01] countries and again even for a one a
[16:03] given country over long long period of
[16:05] time we make a correction to the GDP
[16:09] numbers we have and we make we call them
[16:12] we correct them by what is called the
[16:13] PPP purchasing power parity and I'll
[16:16] explain what that is okay so whenever
[16:19] almost whenever you see comparisons of a
[16:23] GDP per capita across countries when
[16:25] somebody's doing a growth analysis is
[16:27] going to be PPP adjusted okay now let me
[16:31] explain the logic of
[16:34] PB
[16:36] um and and and again I said within the
[16:39] same country over periods perhaps not
[16:41] 300 years but over periods of 40 years
[16:44] it's reasonable H to use just real GDP
[16:48] but when you start comparing sort of you
[16:50] know bana versus the US it gets a lot
[16:53] tricky trickier because there's a lot of
[16:56] goods that are a lot cheaper in poorer
[16:58] countries in particular food okay and
[17:01] and so so you have to be careful with
[17:03] those comparisons so I'm going to give
[17:05] you this example which is somewhat
[17:07] hypothetical but the numbers are not
[17:09] crazy so suppose you have a a two
[17:12] economies the US and Russia
[17:15] and
[17:20] um anyways
[17:22] ER and suppose that that in both
[17:25] economies ER households consume houses
[17:29] and firms consume cars and
[17:32] food okay and suppose that the average
[17:35] consumer in the US buys one car a year
[17:37] for $10,000 and a bundle of food for
[17:41] $10,000 as well okay so the total
[17:44] expenditure in consumption for this
[17:46] household on average is about $20,000 a
[17:49] year that's what a US household consumes
[17:53] these numbers are fantasy numbers but
[17:55] the big picture is not that fantasy
[17:59] ER
[18:00] Russia the average consumer buys
[18:03] 0.07 cars a year for 40,000 rubles and
[18:07] the same bundle of food that in the US
[18:10] okay same assume that same bundle of
[18:12] food goes for 880,000
[18:14] rubles so the total expenditure of this
[18:17] H average household in Russia is
[18:21] 120,000 rubles suppose that exchange is
[18:24] 60 rubles per dollar this thing has
[18:27] moved a lot recent times but suppose
[18:31] that's the the number of rubles per
[18:33] dollar so you divide $120,000 and you
[18:36] want to convert them into Dollars you
[18:38] divide the 120,000 rubles by 60,000
[18:41] rubles per dollar and then you get how
[18:43] much the Russians spend a Russian
[18:45] household on average spends on on on
[18:48] consumption in a year and and it's
[18:51] $2,000 a year okay so here you have
[18:54] 120,000 divided by 60 is 2,000 that's
[18:58] the number of dollar
[18:59] that an average household in Russia
[19:01] consumes so the question
[19:04] is you have a US household spends
[19:06] $20,000 a year a Russian household
[19:10] spends $22,000 a year and the question
[19:13] is then is Russia 10 times poorer than
[19:16] the
[19:18] US
[19:20] okay that if you were to compare real
[19:22] GDP that would be answer so yeah they
[19:26] and it's true if you look at a again in
[19:29] this
[19:30] example if you look at the at the real
[19:33] GDP numbers of on the same year
[19:36] converted all into dollars that answer
[19:38] is
[19:40] correct but it doesn't represent the
[19:42] point is that it doesn't represent
[19:44] really The Well beinging of the average
[19:45] household in Russia for this reason at
[19:48] least why not well
[19:52] let's what you ultimately matter is how
[19:56] much real Goods the house
[19:59] consumes that's what really matters I
[20:02] mean if you live in a country where the
[20:03] price of everything is zero your
[20:06] consumption expenditure consumption will
[20:08] be
[20:09] zero but that doesn't mean that you are
[20:12] as unhappy as somebody that consumes
[20:14] zero you're consuming whatever it is it
[20:16] happens the prices tend to be very low
[20:18] and that's essentially the story here as
[20:20] I said before it tends to be the case
[20:22] that in poorer countries a lot of things
[20:24] are cheaper there is certain very high
[20:28] tech things that that are not even
[20:30] consumed in poorer countries so you have
[20:32] to adjust for that as well but a lot of
[20:34] the regular things the bulk of the
[20:36] purchases tend to be a lot cheaper in
[20:39] poorer countries and that's exactly what
[20:41] is behind the reason why in this example
[20:44] the answer is
[20:45] no it's not true that the Russians are
[20:48] 10 time that Russian household in this
[20:50] example is 10 times poorer than the US
[20:52] let's check it so that's our
[20:55] example and I said no so fast
[20:59] let's use so assume that the goods are
[21:01] the same so the cars that the Russians
[21:03] buy is the same as the as the cars that
[21:06] the US households buy that was
[21:09] truer a few months ago than now but but
[21:13] assume that's the case it's just that
[21:15] the Russians by you know change their
[21:18] cars less frequently in this example the
[21:21] US household is changing the car once a
[21:23] year while while while the Russians are
[21:26] changing the car you know less than once
[21:28] every 10 year one every 15 years or
[21:31] so let's assume also that the the bundle
[21:34] of the of food is exactly the same in
[21:37] both Place places so since the car is
[21:40] the same and the and the and the and the
[21:44] bundle of food is the same I can use us
[21:47] prices to
[21:49] measure Uh Russian consumption and
[21:53] that's is comparable to what us
[21:56] consumption is because I'm taking I'm
[21:59] trying to convert the goods they're
[22:00] consuming into something is comparable
[22:02] to what the US consumes since the goods
[22:05] themselves are the same if I value them
[22:08] at the same price either of the two
[22:10] prices but at the same prices then I'm
[22:12] going to be able to make the comparison
[22:14] I really want that's what purchase power
[22:17] PVP adjustment means okay so look at our
[22:20] particular example here the Russian
[22:22] would household would be consuming 0.07
[22:26] cars times 10,000 dollar which is the
[22:29] price of a car plus one unit of of the
[22:32] bundle of of of of food and the price us
[22:36] price is 10,000 for that so the total
[22:39] consumption of the household PPP
[22:41] adjusted the Russian household is
[22:44] 10,700 okay that's not one10 it's
[22:49] 53% of us consumption so true Russian
[22:53] household is poorer than than than than
[22:55] an average US household but it's not 10
[22:58] poor no it has it's
[23:02] a is
[23:05] 53% uh as rich as the US household okay
[23:10] and so this is big and all the numbers
[23:13] I'm going to show you next especially
[23:15] when we compare across sort of countries
[23:16] that are very different in terms of
[23:18] level of development and so on have
[23:20] these kind of Corrections built in okay
[23:23] if you need the data for these kind of
[23:25] things for whatever reason you find them
[23:27] in what is called the pen tables the pen
[23:29] tables essentially collects all the
[23:30] national accounts of all places and
[23:33] makes these
[23:34] Corrections the problem is they don't
[23:36] have update them very frequently but but
[23:39] if you look in Fred for example which
[23:40] you use in one of the p sets there will
[23:42] be numbers for a few countries that have
[23:45] this um PPP
[23:49] adjustment okay so that that's that's
[23:53] going to remain in the background now
[23:54] but I just wanted to tell you how how
[23:56] you construct numbers when you want to
[23:57] talk about long run and comparison
[23:59] across
[24:00] countries first set of numbers here look
[24:04] at these are obviously all today at
[24:08] least develop economies look at the
[24:10] growth between 1950 2017 obviously the
[24:13] war created a big mess there but before
[24:16] that so let's start from
[24:17] 1950 and what you see here is you know
[24:20] France on average during this period
[24:22] France grew 2017 I think is the last yes
[24:25] it's the last
[24:27] year I think they were recently updated
[24:29] but at least when the book was published
[24:31] that was the last year they had pen
[24:33] tables for but
[24:36] um er France grew on average 2.6% per
[24:40] year on average they also had a business
[24:42] cycle and so on but on average 2.6% per
[24:44] year Japan during this period grew by
[24:47] four four
[24:49] 4.1% the UK 2.1% the US 2% so the
[24:53] developed World essentially grew around
[24:56] 2.7% on average during this
[25:00] period look at the effect that that this
[25:03] has on on the level of GDP per per per
[25:07] per person and all this PPP
[25:10] adjusted ER for the case of
[25:13] France 5.6 times so they started with
[25:17] $7,000 and they were close to $40,000 in
[25:20] 2017 so the r is RA
[25:24] 5.6 look at the US the US is 2% and that
[25:28] ratio is is still richer than France per
[25:31] per person in
[25:33] 2017 but but the ratio of that to that
[25:36] is smaller than that so over a long
[25:39] period of time that's what a trend in
[25:40] the picture capture a small difference
[25:42] in the rate of growth if they are
[25:44] sustained for a long period of time can
[25:46] make quite a bit of difference for the
[25:49] change in in GDP okay and so what do you
[25:54] what is the first what is the p is I
[25:56] mean let's find the pattern here here
[25:59] there's a very clear pattern in that
[26:01] picture in that table what is it do you
[26:04] can you spot
[26:15] it I hadn't
[26:18] actually realized it when I was looking
[26:20] at my notes and then I realized is very
[26:22] clear in this table that's the reason I
[26:24] added this line I updated the slide this
[26:26] morning do you see a pattern
[26:34] yes the higher growth rate have a higher
[26:37] multiple yeah well that's yes that but
[26:40] that's
[26:41] math okay which is so it's a true
[26:43] statement but that's just
[26:45] math there's an economic thing that that
[26:48] that I want
[26:49] to so so you're right but but I want
[26:53] they should have clarified there's an
[26:54] economic pattern there
[27:03] let let me simplify just look at these
[27:05] two columns because a higher number here
[27:10] simply sorry a higher number here simply
[27:13] means that you had a higher rate of
[27:15] growth that's your math fact so ignore
[27:18] this column what I suggest is that you
[27:20] just look at these two
[27:24] columns do you see a
[27:27] pattern just look at these two columns
[27:29] this one in a sense just repeats
[27:31] information that is here for the reason
[27:33] you describe but just look at these two
[27:35] columns is there a pattern
[27:40] there exactly very important Richard
[27:44] countri sent to grow slower the richest
[27:45] country here is the US had the lowest
[27:49] rate of growth on
[27:50] average the poorest was Japan there and
[27:54] they had the highest rate of growth okay
[27:58] so that's a very important correlation
[27:59] and again the first model we're going to
[28:00] see of economic growth is going to
[28:02] explain that correlation why is that we
[28:05] see
[28:07] that those were for five economy you
[28:09] could say it's an accident but look at
[28:11] this this this is just a this is rich
[28:13] countries in general since 1950s and you
[28:16] look at here in this axis you have the
[28:18] annual rate of growth the average rate
[28:19] of growth and here the GDP per person in
[28:23] 1950 so at the beginning of the sample
[28:26] 1950 these countries had have this level
[28:29] of GDP per capita and then here is the
[28:32] rate of growth on average from 1950 to
[28:36] 1987 and it's very clear there that
[28:39] there's a downward sloping pattern no so
[28:42] that's the same fact now for many more
[28:44] countries there's a downward sloping
[28:46] relationship really the richest
[28:48] countries tend to grow much slower than
[28:51] the countries were poorer at the
[28:52] beginning of the
[28:54] sample
[28:56] okay there are some interesting
[28:59] liers like Mexico and and is an
[29:02] interesting in itself I'm not going to
[29:05] say a lot about why that's the case
[29:08] but but but let me for now stick to the
[29:12] to the pattern the dominant pattern
[29:14] which is is a downward sloping
[29:17] relationship that's another way of
[29:19] seeing it and this is for just a bigger
[29:22] variety of countries I have Botana China
[29:25] Thailand and so on and and you see here
[29:29] GDP at the beginning of the 1950 and GDP
[29:32] rate
[29:33] 2018 and the pattern here which is
[29:35] essentially a repetition of the pattern
[29:37] that I showed you before is that there
[29:38] is much more compression here than
[29:44] here how can you have more compression
[29:47] here than here well because there is
[29:50] some sort of convergence no there's a
[29:52] sense of convergence is that those that
[29:55] were poorer tend to grow a little faster
[29:58] than those that were richer and
[30:00] therefore they tend to converge to each
[30:02] other so that's the the point I'm
[30:04] highlighting here a lot of this persion
[30:06] 1950 much less isers in 2018 that means
[30:10] that on average the poorer countries are
[30:13] growing faster than the Richer
[30:19] countries and again all this is per
[30:21] capita PPP adjust and all that okay
[30:30] this
[30:31] picture again sort of makes the the
[30:34] point but now it takes a much many more
[30:37] countries and you can what the point of
[30:40] this picture is in the book is is is to
[30:43] highlight that it's a little messy the
[30:46] picture but to highlight that if you
[30:49] look in different regions oecd a major
[30:52] the major economies H tend to the
[30:55] pattern I show you holds if you look at
[30:57] only isolate only the blue the blue
[31:00] squares you tend to see that negative
[31:03] relationship if you look at within
[31:06] Asia it's also it's a little bit noisier
[31:11] but you also tend to see a negative
[31:13] relationship
[31:15] okay if you look at
[31:17] Africa that relationship is lost
[31:21] completely
[31:23] okay so so when you look at the world as
[31:27] a whole
[31:28] the picture is not as neat as the one I
[31:30] show you because there are certain
[31:32] pockets of the world that are not
[31:33] behaving according to the kind of mods I
[31:35] want I discuss in the next few lectures
[31:38] and the reason they're not behaving is
[31:39] entirely it's almost outside economics
[31:42] it has it's political conflicts Wars and
[31:45] things of that nature which continuously
[31:47] disrupt sort of the economic forces that
[31:49] I'm going to highlight in the next few
[31:50] lectures
[31:53] okay so that's a different different
[31:56] different issue where going to be about
[31:58] the all the moles I'll show you next are
[32:01] about the blue and the and the
[32:07] green squares and and and triangles
[32:10] there not about the red
[32:14] ones what about so I look I show you
[32:17] what happens across countries over over
[32:20] certain period of time which is long but
[32:23] not that long here you see what happens
[32:26] in longer here history there are two
[32:29] patterns that I like to highlight here
[32:31] is that H first for a while sort of you
[32:35] you didn't see much but but you tend to
[32:37] see a sort of a big acceleration in the
[32:40] Western World especially around the the
[32:45] 1950s or so okay so so clearly the
[32:48] Western world was growing faster than
[32:50] the rest of the world H the Western
[32:52] Hemisphere this is a um um world Bank
[32:56] IFI type type
[33:01] um
[33:03] grouping and and you see that there's a
[33:05] very fast acceleration in growth in this
[33:07] episode here Western Europe H was also
[33:12] flattish and then picked up very
[33:14] strongly there and you see the different
[33:16] regions of the world and again you see
[33:18] the sub Sahara Africa region that sort
[33:21] of has hasn't really picked up okay
[33:28] much longer history well that's the way
[33:31] it looks for the world as a whole
[33:34] okay you know exponential pictures tend
[33:36] to look like that but but this is more
[33:38] dramatic than exponential and again what
[33:41] happens is
[33:44] that what happen here is is going to be
[33:46] very different from from the kind of
[33:49] mods I'll describe
[33:51] next this period here is mostly
[33:53] dominated by what's called sort of the
[33:55] malthusian era which is essentially
[33:58] people live population grew and so on
[34:01] depending on how good was the the
[34:03] harvest that year and so on no so so you
[34:06] had this mod in which you know his
[34:07] population grew faster that was a main
[34:10] driver of of of growth well but you know
[34:13] there wasn't enough food to sustain a a
[34:15] higher population and then you stay
[34:17] soort of there was a fight between food
[34:18] and and and people and and and no much
[34:21] space for most people were in
[34:23] agriculture and and the and and and
[34:26] there wasn't sort of
[34:28] much to build on nowadays there are
[34:31] pocket in the world and we had the
[34:33] severe situations during covid but food
[34:36] is not really a constraint for growth
[34:38] for the world as a whole
[34:41] okay and but you see
[34:44] so in other words had you taken this
[34:47] course in 20 in year 1000 or in the
[34:49] Renaissance nobody would have talked
[34:51] about growth it's not something that
[34:54] happened really it's it's a very modern
[34:56] thing to think about these pictures with
[34:59] these long Trends and so on
[35:02] okay I mean there you would have talked
[35:05] about a lot more interesting things than
[35:06] this but but not not about growth that's
[35:09] for sure and growth the last point I I
[35:12] think I want to make about this is it
[35:13] makes a big
[35:15] difference I don't know if you can read
[35:17] that I I can't but er um what I have
[35:21] here is GDP per capita in
[35:23] 1950 versus GDP per capita in 2016
[35:28] and you have this isoquants here you
[35:30] move you as you move up so this line
[35:33] here is what happens to countries that
[35:35] is a 45 degree line so if you are on the
[35:38] 45 degree line means that you haven't
[35:40] grown at all during this period no
[35:43] because that means that your GDP per
[35:45] capita 1950 is the same as you g GDP per
[35:48] capita in 2016 that means on average you
[35:52] grow okay but as I keep moving these
[35:54] lines up means you grew faster and fter
[35:57] faster and
[35:58] faster okay so and if you if you move
[36:03] along this line here that means you have
[36:05] negative growth on average during that
[36:07] period okay so each of these lines
[36:10] represents multiples so I think this is
[36:13] for example this top line here is 30
[36:17] times richer these are guys that grew
[36:19] very very fast yeah you I cannot read
[36:21] either but I I sort of know who is in
[36:23] each
[36:24] Place
[36:26] h this is an example here this is
[36:30] Taiwan okay this is Taiwan and H this is
[36:36] Singapore they have a name how do we
[36:38] call those
[36:41] countries no
[36:44] well the Asian tigers they grew very
[36:48] very strong for for a long time since
[36:51] the 60s or so but there you see you can
[36:55] compare if you could see you would see
[36:57] that you know that that Taiwan and the
[37:01] Democratic Republic of Congo had the
[37:03] same GDP in
[37:05] 1950 okay now the Republic Democratic
[37:10] Republic of of of of Congo has less GDP
[37:14] than it had ER in 1950 it had 1700 here
[37:19] and 800 today while Taiwan Taiwan has 30
[37:23] times what it used to
[37:25] have and so today is one of the richest
[37:28] economies in the world close to 7
[37:31] $50,000 per capita while the Republic of
[37:35] Congo ER has
[37:40] 700 $800 per capita so growth makes a
[37:44] big big difference okay and these are
[37:47] not that many years I mean you know this
[37:49] is just 70 years H and I can assure you
[37:54] that these people they have other
[37:56] concerns but
[37:58] their standard of living is a lot higher
[38:00] than these people and at some point they
[38:01] were the same the big difference is some
[38:04] countries that grew and some
[38:06] countries got a stuck um where is
[38:09] Argentina here I don't know somewhere
[38:12] here
[38:13] probably it's
[38:18] Argentina I don't know I cannot
[38:21] see have the chance here I can say okay
[38:26] good so growth that's make a difference
[38:28] and he has made a huge the world we see
[38:30] today and the countries we think as rich
[38:33] or poor were not the same countries that
[38:36] you thought in in those terms in
[38:38] 1950 Asia is one of the most prominent
[38:41] differences they have massive growth
[38:44] through the
[38:46] 60s
[38:48] um starting with Japan but then the rest
[38:51] and again were the famous the Tigers
[38:53] Hong Kong Taiwan
[38:56] Singapore uh
[38:58] and Korea South
[39:02] Korea good so let's start building some
[39:08] moles of what we have just
[39:11] seen remember when we look at the short
[39:13] run we really didn't care about the
[39:16] supply side of the economy remember it
[39:18] was all about demand they said well you
[39:19] know demand look what consumers invest
[39:22] firms and governments do with demand
[39:25] that determines output and output
[39:28] happens well it happens we didn't really
[39:30] care too much about it then when we talk
[39:32] about the medium term we say okay we're
[39:35] going to no no we have to care because
[39:36] you know to produce you need workers and
[39:40] and you know workers are not going to
[39:42] work for any wage and so we had to begin
[39:44] to talk about ER the the supply side of
[39:47] the economy but we made it very simple
[39:50] we just look at the problem of wage
[39:52] bargaining and price setting but the
[39:54] production function itself wasn't that
[39:56] interesting it was outputting equal to
[39:57] labor and I told you it's very
[39:59] unrealistic but it was convenient for
[40:01] that part of the course because Capital
[40:04] doesn't grow that fast so typical
[40:06] production function we have both capital
[40:08] and labor but at the business cycle
[40:10] frequency investment the change in
[40:12] capital can be large but the stock of
[40:14] capital doesn't move that much and so
[40:16] you can ignore it for business cycle
[40:18] type fluctuations but if we want to look
[40:20] at the long run Capital plays a huge
[40:22] role capital accumulation and so we have
[40:24] to be explicit about the role of capital
[40:27] in the the production
[40:28] function so this is going to be our now
[40:31] and now we're going to forget about
[40:32] aggregate demand we're going to say look
[40:34] we're going to focus about AGG supply
[40:35] and demand will do whatever it needs to
[40:37] do so so so we get what what the supply
[40:41] site says so output now will be will be
[40:46] a an increasing function of both capital
[40:49] and
[40:51] labor now this function will have a
[40:54] bunch of er properties which are many of
[40:57] which
[40:58] are no at a broad level they are
[41:00] empirically validated but they're also
[41:03] very convenient from the modeling point
[41:04] of view the first and most
[41:07] important
[41:08] property um is constant returns to
[41:12] scale okay we're going to use a lot of
[41:15] property so so please get that concept
[41:19] constant return to scale means simply
[41:22] that if you scale the factors of
[41:25] production you also scale the output
[41:28] okay so say if x is 1.1 that means if
[41:33] you increase capital and labor by 10%
[41:36] you get 10% more output okay so that's
[41:40] Conant return to scale if I scale all
[41:42] the factors of production by the same
[41:44] amount the same proportion then output
[41:46] Grows by the same proportion it's
[41:49] scalable that's what it mean constant
[41:51] return to
[41:54] scale very important property what comes
[41:58] next decreasing returns to
[42:03] Capital that
[42:05] is H as you increase capital for a fixed
[42:08] amount of Labor so conent scale is a
[42:11] property of scaling everything
[42:13] up the property I'm describing here is
[42:15] what happens if we increase only K what
[42:17] happens to Output if we increase only K
[42:20] but fixing
[42:23] n in other words set this to one and
[42:27] start moving this
[42:29] up you're not going to get X here you're
[42:31] going to get something different from
[42:33] X and but this tells you is that yes
[42:36] you're going to get more output but less
[42:39] and less the more Capital you
[42:42] have Okay so this says for example
[42:45] suppose you start with 100 workers and
[42:48] 100 units of capital and it happens that
[42:50] this produces 100 units of
[42:53] goods if you add now 10 units of capital
[42:57] say you're going to
[42:59] get seven units of output not 10 seven
[43:04] because you didn't increase labor had I
[43:06] increased labor also by by 10 I would
[43:07] have gotten 10 of output but I
[43:09] increasing only h capital by 10 then and
[43:13] keeping output fixed then labor fixed
[43:16] then output will increase by less than
[43:18] 10 but what this decrease in returns to
[43:21] Capital says is that now if you increase
[43:23] again from 110 to 120 units of capital
[43:26] you're going to get get less than seven
[43:27] units of output more you're going to get
[43:30] five and if you increase a again from
[43:32] 120 to 130 you're going to get less than
[43:34] five you're going to get three and so on
[43:37] so forth that's decreasing returns to
[43:39] scale and and decreasing returns to
[43:41] Capital and the reason for that is is
[43:45] economically is that more and more
[43:47] capital is working with a fixed number
[43:49] of workers so labor becomes very scarce
[43:51] for
[43:52] capital okay and that's the reason so so
[43:55] you have very little
[43:57] the other these are factors of
[43:58] production which are complementary they
[44:00] need each other labor and capital if you
[44:02] fix one and it start increasing only one
[44:05] then it's harder and harder for each
[44:07] extra new unit of this one to work with
[44:09] sort of fewer and fewer of the other
[44:11] factor of production so the same
[44:13] principle applies to labor if you fix
[44:16] capital and you only increase labor then
[44:18] initially you get a big jumping output
[44:21] but it's going to be smaller and smaller
[44:22] and smaller the more you keep adding a
[44:26] um
[44:29] labor okay so in pi so let me One X that
[44:34] we're going to use
[44:36] throughout is we want to make x one of
[44:40] our favorite X will be 1 /
[44:46] n you see what I'm trying to do when we
[44:49] set x equal to 1 / n so that x equal to
[44:52] 1 / n what I get here is output per
[44:56] person
[44:58] no that's what I
[45:00] get y Over
[45:02] N so if I set xal to 1/ n i can using
[45:08] con to scale I know that this is equal
[45:09] to
[45:11] y/n k/ n n/ n so that is one so this guy
[45:16] doesn't move and I have now
[45:18] that a output per person is increasing
[45:22] in capital per worker worker and
[45:24] population this part of the course are
[45:26] the same for get an EMP employment and
[45:28] is population is employment if labor
[45:31] force is everything I'm not this is not
[45:34] a place to worry about unemployment
[45:41] okay okay so remember that all the plots
[45:45] I show you the different Figures were
[45:47] about this variable how it changed over
[45:50] time how was different across different
[45:52] countries how grew at a different rate
[45:54] in in different countries but from this
[45:57] very simple model you see that in order
[46:00] to
[46:01] explain the change in this or growth in
[46:05] why over and why one country grows more
[46:07] than the other you have with the simple
[46:09] model only two
[46:13] options so if I tell you country a grew
[46:17] more over this period than grew more per
[46:20] per person than this other
[46:23] country er um over this period of time
[46:28] there are only two options here the
[46:29] first one is that in that country there
[46:32] was more capital accumulation per worker
[46:34] so K Over N went up no if K Over N goes
[46:37] up more in one country than the other
[46:39] one y Over N will go up more in that
[46:42] country than the other one and the other
[46:45] option is that the this H function
[46:49] itself shifted
[46:51] up so for any given amount of K Over N
[46:56] now you could produ more y over n and
[46:58] that's what we call technological
[47:00] progress that's a second thing so so if
[47:04] if if the difference in in in in growth
[47:07] of output per
[47:09] person is due to an increasing K Over
[47:12] end well we call that a capill
[47:13] accumulation mechanism if it is because
[47:16] the function f shifts up that's
[47:18] technological progress and what we're
[47:20] going to do is in the next lecture we're
[47:22] going to talk about this channel the
[47:24] capital accumulation Channel and in the
[47:28] lecture after the spring break we're
[47:30] going to talk about shift in the
[47:32] function f so in in in in
[47:36] figures
[47:38] so fixing the technology that this is
[47:40] the function f is fixed and you just
[47:43] move K Over N this is the picture you
[47:45] have now that's a produ this I'm
[47:48] plotting this function here as a
[47:51] function of k/ n for a fixed function f
[47:55] and that's what you get so output per I
[47:57] have here Capital per worker and output
[48:00] per per
[48:02] worker and you see that obviously it's
[48:05] in an increasing function the more
[48:06] Capital per worker you have the more
[48:08] output per worker you'll
[48:10] produce but it's also
[48:13] concave why is it
[48:19] concave that's decrease in returns to
[48:21] Capital is look for any when you have
[48:25] very little Capital per work
[48:28] a change in capital per worker gives
[48:30] gives you a big jumping output per
[48:31] worker because you know there was sort
[48:33] of very little Capital that was the
[48:35] problem of that
[48:36] economy when the economy has more and
[48:39] more Capital the same change in capital
[48:42] leads to a much smaller change in output
[48:44] here at this level when when Capital per
[48:47] worker was very low the economy was very
[48:49] poor then this change LED to this change
[48:53] in output per capita at this level of
[48:56] wealth if you get as capital economies
[48:59] with higher Capital are richer Capital
[49:01] per worker the same change this change
[49:04] is of the same size as that leads to a
[49:06] much smaller change in
[49:08] output okay and that's a result of
[49:10] decreasing returns to
[49:13] Capital and that's the other option
[49:15] again that's what we're going to talk
[49:16] about in the next lecture this this one
[49:20] and two lectures from now we're going to
[49:21] talk about growth that comes from shift
[49:24] in the production function this
[49:25] technological progress
[49:27] okay very good see you on Wednesday