1
00:00:16,480 --> 00:00:20,920
okay so um today we're want to start

2
00:00:19,199 --> 00:00:23,080
talking about the long run I've been

3
00:00:20,920 --> 00:00:24,400
talking about the business cycles and

4
00:00:23,079 --> 00:00:27,919
today we're going to start talking about

5
00:00:24,399 --> 00:00:30,559
things that happen over decades H but

6
00:00:27,920 --> 00:00:34,280
before I do that before we finish with

7
00:00:30,559 --> 00:00:36,238
the the short run medium run I just

8
00:00:34,280 --> 00:00:38,480
don't want you to I want I don't want to

9
00:00:36,238 --> 00:00:41,280
give you the impression that that you

10
00:00:38,479 --> 00:00:43,359
know once you understand the ISL MPC

11
00:00:41,280 --> 00:00:44,679
sort of you you can start managing

12
00:00:43,359 --> 00:00:47,399
monetary

13
00:00:44,679 --> 00:00:50,399
policy immediately I

14
00:00:47,399 --> 00:00:52,280
I there's a lot of noise of all sort of

15
00:00:50,399 --> 00:00:57,439
kind of complexity in the real world of

16
00:00:52,280 --> 00:01:01,439
course that can make um policies

17
00:00:57,439 --> 00:01:03,718
uh uh very hard to manage in practice

18
00:01:01,439 --> 00:01:06,319
macroeconomic policies and one

19
00:01:03,719 --> 00:01:09,599
fundamental principle I would say is

20
00:01:06,319 --> 00:01:14,079
that policy makers understand that speed

21
00:01:09,599 --> 00:01:16,839
can kill okay and uh that's very obvious

22
00:01:14,079 --> 00:01:19,959
during financial crisis there we all

23
00:01:16,840 --> 00:01:22,680
understand that ER the response needs to

24
00:01:19,959 --> 00:01:25,438
be large it has to be a response with

25
00:01:22,680 --> 00:01:27,240
overwhelming Force essentially because

26
00:01:25,438 --> 00:01:28,798
things are happening so fast that very

27
00:01:27,239 --> 00:01:31,118
few corporations even healthy

28
00:01:28,799 --> 00:01:33,600
corporations that that can adjust

29
00:01:31,118 --> 00:01:35,200
quickly enough uh to the PACE at which

30
00:01:33,599 --> 00:01:39,158
things are changing prices become

31
00:01:35,200 --> 00:01:40,680
noninformative uh fire cells take place

32
00:01:39,159 --> 00:01:42,560
and and and obviously it's very

33
00:01:40,680 --> 00:01:45,118
difficult to make economic decisions in

34
00:01:42,560 --> 00:01:47,040
that context and so that's the reason

35
00:01:45,118 --> 00:01:48,478
they are the speed in the on the on the

36
00:01:47,040 --> 00:01:51,040
policy Direction goes very clearly in

37
00:01:48,478 --> 00:01:52,879
One Direction do it quickly and very

38
00:01:51,040 --> 00:01:56,399
large

39
00:01:52,879 --> 00:01:57,879
now on the other hand ER when you're

40
00:01:56,399 --> 00:02:00,718
going through a period in which you're

41
00:01:57,879 --> 00:02:05,438
are hiking interest rates for example

42
00:02:00,718 --> 00:02:07,640
ER like we're going through now um the

43
00:02:05,438 --> 00:02:10,038
the Tendencies towards gradualism to do

44
00:02:07,640 --> 00:02:13,719
it very slowly because something can

45
00:02:10,038 --> 00:02:16,279
break along the path and it's often the

46
00:02:13,719 --> 00:02:19,479
case that with for sufficiently large

47
00:02:16,280 --> 00:02:21,759
adjustments something breaks okay and so

48
00:02:19,479 --> 00:02:24,719
here you have an example of sort of

49
00:02:21,759 --> 00:02:27,399
major episodes of hiking in the US and

50
00:02:24,719 --> 00:02:30,598
things that have happened about those

51
00:02:27,400 --> 00:02:32,959
those H major episodes

52
00:02:30,598 --> 00:02:35,719
this one actually I I have a personal

53
00:02:32,959 --> 00:02:38,039
attachment to that one because you know

54
00:02:35,719 --> 00:02:40,239
I was studying in Chile around then

55
00:02:38,039 --> 00:02:42,158
everything was going wonderfully massive

56
00:02:40,239 --> 00:02:44,599
Capital flows to Chile emerging markets

57
00:02:42,158 --> 00:02:48,359
were very popular we all felt very

58
00:02:44,598 --> 00:02:51,238
wealthy rich and so on and right after I

59
00:02:48,360 --> 00:02:53,120
finished College ER I was not planning

60
00:02:51,239 --> 00:02:56,080
to come to the usy things were going

61
00:02:53,120 --> 00:02:58,239
very well in Chile H but the US decided

62
00:02:56,080 --> 00:02:59,840
to hike interest rate very aggressively

63
00:02:58,239 --> 00:03:01,800
all of the sudden Capital flows to

64
00:02:59,840 --> 00:03:05,120
emergy markets disappear we went into an

65
00:03:01,800 --> 00:03:06,840
enormous financial crisis I lost I had

66
00:03:05,120 --> 00:03:09,439
no opportunity cost and I had to come to

67
00:03:06,840 --> 00:03:12,840
study to the US that that's my so I know

68
00:03:09,439 --> 00:03:15,120
that hikes aggressive hikes can matter

69
00:03:12,840 --> 00:03:15,840
can make differences to people but and

70
00:03:15,120 --> 00:03:18,759
that

71
00:03:15,840 --> 00:03:21,080
was there's a decade that followed that

72
00:03:18,759 --> 00:03:23,919
episode that is called the L decade of

73
00:03:21,080 --> 00:03:26,440
Latin America essentially so things did

74
00:03:23,919 --> 00:03:28,719
break and and one of the main reasons

75
00:03:26,439 --> 00:03:30,400
they did break is because at the time

76
00:03:28,719 --> 00:03:32,479
most of the capital close that's not

77
00:03:30,400 --> 00:03:36,319
what happens today we really being

78
00:03:32,479 --> 00:03:38,079
managed by global Banks and the banks

79
00:03:36,318 --> 00:03:41,560
can get very distressed when interest

80
00:03:38,080 --> 00:03:43,760
rate rise H very very quickly and so

81
00:03:41,560 --> 00:03:46,640
that that was essentially a problem with

82
00:03:43,759 --> 00:03:49,919
us the US Banks major Global Banks but

83
00:03:46,639 --> 00:03:51,759
the US Banks in particular that trigger

84
00:03:49,919 --> 00:03:54,518
an Emerging Market

85
00:03:51,759 --> 00:03:56,318
crisis this one also had huge

86
00:03:54,519 --> 00:03:58,680
consequences actually and it's

87
00:03:56,318 --> 00:04:02,759
interesting because this episode is is

88
00:03:58,680 --> 00:04:05,239
similar to to to to what we're going on

89
00:04:02,759 --> 00:04:08,840
what is going on right now or what may

90
00:04:05,239 --> 00:04:11,920
happen in soon so this is episode of

91
00:04:08,840 --> 00:04:15,319
hikes that ended what is called The

92
00:04:11,919 --> 00:04:17,319
Savings and Loan crisis and those so the

93
00:04:15,318 --> 00:04:20,079
best parallel to today are the small

94
00:04:17,319 --> 00:04:21,680
Regional Banks if you will and they they

95
00:04:20,079 --> 00:04:23,560
weren't able to withstand this sort of

96
00:04:21,680 --> 00:04:26,000
sharp rise in interest rate which is

97
00:04:23,560 --> 00:04:29,240
very much what is going on right now in

98
00:04:26,000 --> 00:04:32,439
the US this one actually end up with

99
00:04:29,240 --> 00:04:35,160
also another problem which is the the

100
00:04:32,439 --> 00:04:37,879
the bubble burst in Japan episode of

101
00:04:35,160 --> 00:04:41,280
hiking in the US and there we had a

102
00:04:37,879 --> 00:04:42,399
major crisis in in Japan the price of

103
00:04:41,279 --> 00:04:46,198
real estate

104
00:04:42,399 --> 00:04:47,758
collapsed ER and and essentially they

105
00:04:46,199 --> 00:04:51,639
since then they have never been able to

106
00:04:47,759 --> 00:04:54,080
grow as they used to before that that

107
00:04:51,639 --> 00:04:57,199
episode that's called sometimes the

108
00:04:54,079 --> 00:04:59,959
tequila crisis it's a Mexican

109
00:04:57,199 --> 00:05:02,560
Bond crisis and it was again the result

110
00:04:59,959 --> 00:05:06,000
of a hiking episode in the US conditions

111
00:05:02,560 --> 00:05:08,000
tighten to Emerging Market ER their bone

112
00:05:06,000 --> 00:05:10,759
Market essentially

113
00:05:08,000 --> 00:05:13,399
exploded um well this is the global

114
00:05:10,759 --> 00:05:16,280
financial crisis the Great Recession it

115
00:05:13,399 --> 00:05:22,318
was again preceded by episode of sort of

116
00:05:16,279 --> 00:05:24,879
aggressive hikes which eventually er um

117
00:05:22,319 --> 00:05:26,560
led to a turn around as house prices

118
00:05:24,879 --> 00:05:28,560
were Rising steadily throughout the

119
00:05:26,560 --> 00:05:31,120
episode and a lot of financial assets

120
00:05:28,560 --> 00:05:33,360
were created around that housing wealth

121
00:05:31,120 --> 00:05:35,038
that was been created that hike and

122
00:05:33,360 --> 00:05:37,080
interest rate eventually put a stop an

123
00:05:35,038 --> 00:05:39,519
end to that that appreciation of house

124
00:05:37,079 --> 00:05:42,918
prices in fact they turn around and it

125
00:05:39,519 --> 00:05:45,198
led to a very significant financial

126
00:05:42,918 --> 00:05:48,240
crisis and this is where we're at right

127
00:05:45,199 --> 00:05:52,680
now okay and so we already seen sort of

128
00:05:48,240 --> 00:05:54,800
some Tremors and so on so the point is

129
00:05:52,680 --> 00:05:56,600
when when sometimes you say well why is

130
00:05:54,800 --> 00:05:58,600
isn't the FED more aggressive if we have

131
00:05:56,600 --> 00:06:01,199
high inflation and go very quickly at it

132
00:05:58,600 --> 00:06:04,240
well it's because things can go wrong

133
00:06:01,199 --> 00:06:05,840
okay and it it typically happens that

134
00:06:04,240 --> 00:06:08,918
things do go wrong you don't know

135
00:06:05,839 --> 00:06:11,399
exactly what will blow up but something

136
00:06:08,918 --> 00:06:13,279
may blow up and typically is associated

137
00:06:11,399 --> 00:06:15,198
to some Financial Market that is very

138
00:06:13,279 --> 00:06:16,638
hot and the market and the banks are

139
00:06:15,199 --> 00:06:17,879
always involved in that because the

140
00:06:16,639 --> 00:06:20,280
banks are very

141
00:06:17,879 --> 00:06:22,360
lever you know they have little Capital

142
00:06:20,279 --> 00:06:24,239
relative to the assets they have and

143
00:06:22,360 --> 00:06:26,840
that means small variation in the price

144
00:06:24,240 --> 00:06:28,560
of assets can lead to very large H

145
00:06:26,839 --> 00:06:32,239
changes in the value of their

146
00:06:28,560 --> 00:06:35,720
capital anyway so just a warning so if

147
00:06:32,240 --> 00:06:38,759
you get a job at the FED please be

148
00:06:35,720 --> 00:06:42,000
careful okay now let me switch gears and

149
00:06:38,759 --> 00:06:43,319
and we're going to talk about um um

150
00:06:42,000 --> 00:06:45,720
something a little different from what

151
00:06:43,319 --> 00:06:48,560
we have been discussing up to now so

152
00:06:45,720 --> 00:06:51,840
this is some this is growth projections

153
00:06:48,560 --> 00:06:53,959
for different regions in the world ER

154
00:06:51,839 --> 00:06:55,519
this is something that is in publishing

155
00:06:53,959 --> 00:06:57,239
by the IMF it's called the world

156
00:06:55,519 --> 00:06:59,598
economic Outlook I think I mentioned it

157
00:06:57,240 --> 00:07:01,199
before and here you have some forecast

158
00:06:59,598 --> 00:07:04,560
you know well this is actually what

159
00:07:01,199 --> 00:07:08,759
happened so growth in the global economy

160
00:07:04,560 --> 00:07:11,439
was about 3.4% 2022 advanced economies

161
00:07:08,759 --> 00:07:13,720
grew at 2.7% emerging markets and

162
00:07:11,439 --> 00:07:16,000
developing economies at

163
00:07:13,720 --> 00:07:20,879
3.9% and then you see forast and the

164
00:07:16,000 --> 00:07:22,759
further out you go er um the okay the

165
00:07:20,879 --> 00:07:25,000
further out you go sort of it's less

166
00:07:22,759 --> 00:07:26,800
related to the current cycle is more

167
00:07:25,000 --> 00:07:27,959
related to what is structural the

168
00:07:26,800 --> 00:07:30,038
structural

169
00:07:27,959 --> 00:07:32,038
growth of the different parts of the

170
00:07:30,038 --> 00:07:35,120
world and you see that for

171
00:07:32,038 --> 00:07:37,478
2024 the global economy is projected

172
00:07:35,120 --> 00:07:38,918
expected to grow at around 3.1% this

173
00:07:37,478 --> 00:07:40,639
forecast were made before the mess

174
00:07:38,918 --> 00:07:42,598
Financial mess that we're going on right

175
00:07:40,639 --> 00:07:46,240
now so probably the next World economic

176
00:07:42,598 --> 00:07:48,199
Outlook will have at least for 2023 will

177
00:07:46,240 --> 00:07:51,519
will downgrade the growth probably not

178
00:07:48,199 --> 00:07:54,520
for 2024 but yes for 2023 anyways

179
00:07:51,519 --> 00:07:57,758
advanced economies expected to grow

180
00:07:54,519 --> 00:08:00,918
1.4% emerging markets at

181
00:07:57,759 --> 00:08:03,000
4.2% so

182
00:08:00,918 --> 00:08:05,079
these forecasts are based on on a

183
00:08:03,000 --> 00:08:07,399
combination of cyclical factors

184
00:08:05,079 --> 00:08:08,399
fluctuations of the short run medium run

185
00:08:07,399 --> 00:08:10,679
the kind of things we have been

186
00:08:08,399 --> 00:08:12,079
discussing up to now some economies will

187
00:08:10,680 --> 00:08:14,560
have to go through recession some

188
00:08:12,079 --> 00:08:17,598
economies are going through Booms that

189
00:08:14,560 --> 00:08:19,199
probably dominates 20 the forus on 2023

190
00:08:17,598 --> 00:08:21,560
but as I said before the further out you

191
00:08:19,199 --> 00:08:23,478
go the more the less relevant is the

192
00:08:21,560 --> 00:08:26,079
current business cycle and the more

193
00:08:23,478 --> 00:08:28,959
relevant is the structural trend of the

194
00:08:26,079 --> 00:08:31,158
different regions of the world okay so I

195
00:08:28,959 --> 00:08:33,559
would that in this when they formulated

196
00:08:31,158 --> 00:08:35,918
this forecast this is very much based on

197
00:08:33,559 --> 00:08:38,359
more longer run growth model the kind of

198
00:08:35,918 --> 00:08:41,038
models we're going to discuss now okay

199
00:08:38,360 --> 00:08:42,839
while this is probably totally dominated

200
00:08:41,038 --> 00:08:46,159
by the kind of things we discuss up to

201
00:08:42,839 --> 00:08:48,800
now okay

202
00:08:46,159 --> 00:08:51,719
um there are several things that that

203
00:08:48,799 --> 00:08:54,000
that are interesting here aside from

204
00:08:51,720 --> 00:08:56,440
sort of the the the

205
00:08:54,000 --> 00:08:59,000
fluctuations year to year one thing you

206
00:08:56,440 --> 00:09:00,079
can see for example is that regardless

207
00:08:59,000 --> 00:09:02,759
of year

208
00:09:00,078 --> 00:09:04,799
on average Emerging Markets tend to grow

209
00:09:02,759 --> 00:09:06,600
faster than develop economies advanced

210
00:09:04,799 --> 00:09:08,319
economies okay so one of the things we

211
00:09:06,600 --> 00:09:12,079
want to understand is why is that the

212
00:09:08,320 --> 00:09:13,680
case okay but that's is very clear here

213
00:09:12,078 --> 00:09:15,559
that's the first model we're going to

214
00:09:13,679 --> 00:09:17,319
look at which probably will happen on

215
00:09:15,559 --> 00:09:19,039
Wednesday we'll try to explain

216
00:09:17,320 --> 00:09:21,800
essentially that why is it that these

217
00:09:19,039 --> 00:09:25,240
guys tend to grow faster than the

218
00:09:21,799 --> 00:09:25,240
advanced economies

219
00:09:25,559 --> 00:09:30,359
okay so growth is important I mean the

220
00:09:28,720 --> 00:09:32,560
standing economic growth is hugely

221
00:09:30,360 --> 00:09:35,759
important for the weal for understanding

222
00:09:32,559 --> 00:09:39,399
sort of the health of an economy here

223
00:09:35,759 --> 00:09:44,720
you see this comes from the textbook er

224
00:09:39,399 --> 00:09:46,639
er the the US GDP in 20 20

225
00:09:44,720 --> 00:09:50,959
uh2 from

226
00:09:46,639 --> 00:09:53,519
1890 to to 2017 I think is this one the

227
00:09:50,958 --> 00:09:57,479
the end year the important thing to

228
00:09:53,519 --> 00:10:01,480
notice here is how large is the change

229
00:09:57,480 --> 00:10:04,480
in GDP in during the period I mean GDP

230
00:10:01,480 --> 00:10:09,440
here measuring the same prices so 20

231
00:10:04,480 --> 00:10:10,920
2012 prices is 50 times that in 1890

232
00:10:09,440 --> 00:10:12,720
that's a big thing I mean when we talk

233
00:10:10,919 --> 00:10:15,679
about business cycle fluctuations we're

234
00:10:12,720 --> 00:10:19,519
talking about in an economy like the US

235
00:10:15,679 --> 00:10:22,919
two two and a half% up 3% up and down

236
00:10:19,519 --> 00:10:25,519
this is 50 times so over longer period

237
00:10:22,919 --> 00:10:27,439
of time you can almost ignore the

238
00:10:25,519 --> 00:10:30,759
business cycle and it's all about that

239
00:10:27,440 --> 00:10:33,440
long run H trend

240
00:10:30,759 --> 00:10:36,200
here what is this episode so so you here

241
00:10:33,440 --> 00:10:37,959
if you if you look at this picture know

242
00:10:36,200 --> 00:10:40,278
especially the F out you are on the on

243
00:10:37,958 --> 00:10:41,319
the on the room what dominates here is

244
00:10:40,278 --> 00:10:43,879
clearly the

245
00:10:41,320 --> 00:10:45,440
trend the only action you see really

246
00:10:43,879 --> 00:10:50,039
significant action different from the

247
00:10:45,440 --> 00:10:50,040
trend is around here what happened

248
00:10:50,240 --> 00:10:54,919
there it's the Great Depression so even

249
00:10:53,200 --> 00:10:57,920
the Great Depression you know doesn't

250
00:10:54,919 --> 00:10:59,838
look that big relative to what the trend

251
00:10:57,919 --> 00:11:01,278
can do so

252
00:10:59,839 --> 00:11:03,279
of course it's very difficult to affect

253
00:11:01,278 --> 00:11:05,600
the trend of a country but the trend

254
00:11:03,278 --> 00:11:07,000
makes a huge difference for the welfare

255
00:11:05,600 --> 00:11:11,000
for

256
00:11:07,000 --> 00:11:12,600
the economic well-being of a

257
00:11:11,000 --> 00:11:17,078
country

258
00:11:12,600 --> 00:11:20,120
good now a lot of that is because also

259
00:11:17,078 --> 00:11:23,439
the US population grew up grew up grew

260
00:11:20,120 --> 00:11:26,120
up and grew a lot during this episode

261
00:11:23,440 --> 00:11:27,880
so often when you look at sort of long

262
00:11:26,120 --> 00:11:30,120
run Trends rather than looking at the

263
00:11:27,879 --> 00:11:33,679
level of GDP you tend to look at the

264
00:11:30,120 --> 00:11:35,480
level of GDP per person per capita or

265
00:11:33,679 --> 00:11:37,679
something like that and that picture is

266
00:11:35,480 --> 00:11:40,039
exactly the same pictures as the

267
00:11:37,679 --> 00:11:43,799
previous one but divided by population

268
00:11:40,039 --> 00:11:45,319
at each point in time okay and and and

269
00:11:43,799 --> 00:11:46,919
and that's an important over long

270
00:11:45,320 --> 00:11:49,278
periods of you at the business cycle

271
00:11:46,919 --> 00:11:51,639
frequency you can almost ignore changes

272
00:11:49,278 --> 00:11:53,679
in popul no Chang ination you can ignore

273
00:11:51,639 --> 00:11:55,278
completely unless you are in a war you

274
00:11:53,679 --> 00:11:57,799
can you worry about other things labor

275
00:11:55,278 --> 00:11:59,480
force participation and stuff like that

276
00:11:57,799 --> 00:12:01,559
but population is irrelevant that the

277
00:11:59,480 --> 00:12:03,680
business cycle growth is irrelevant at

278
00:12:01,559 --> 00:12:06,479
the business cycle frequency but not

279
00:12:03,679 --> 00:12:08,719
over long periods of time in this period

280
00:12:06,480 --> 00:12:11,759
here population in the US increased from

281
00:12:08,720 --> 00:12:13,720
63 million to 320 million so that's a

282
00:12:11,759 --> 00:12:17,360
lot more workers in principle that you

283
00:12:13,720 --> 00:12:20,160
have you know for that economy so a lot

284
00:12:17,360 --> 00:12:23,519
of that trend is explained by population

285
00:12:20,159 --> 00:12:26,399
growth and that's one of the reason

286
00:12:23,519 --> 00:12:29,399
sorry a lot of the trend in this picture

287
00:12:26,399 --> 00:12:30,679
here is explained by population growth

288
00:12:29,399 --> 00:12:32,879
that's one of the reasons we're in a

289
00:12:30,679 --> 00:12:34,359
tricky time in the global economy

290
00:12:32,879 --> 00:12:35,838
because there are many important regions

291
00:12:34,360 --> 00:12:38,039
of the world where population is no

292
00:12:35,839 --> 00:12:40,399
longer growing so we got used to a

293
00:12:38,039 --> 00:12:43,639
period in which population growth was

294
00:12:40,399 --> 00:12:45,720
very steady and high and now you know

295
00:12:43,639 --> 00:12:48,399
many parts of the world important parts

296
00:12:45,720 --> 00:12:53,160
of of the world have negative population

297
00:12:48,399 --> 00:12:56,159
growth Japan Korea China most of

298
00:12:53,159 --> 00:12:58,198
Continental Europe H even places in

299
00:12:56,159 --> 00:13:01,039
Latin America and so on so so this is a

300
00:12:58,198 --> 00:13:03,319
big change for the world

301
00:13:01,039 --> 00:13:05,480
but anyways during that period there was

302
00:13:03,320 --> 00:13:07,199
a lot of population growth and in the US

303
00:13:05,480 --> 00:13:09,720
in particular when again as I said

304
00:13:07,198 --> 00:13:12,319
before from 63 to 320 million so if you

305
00:13:09,720 --> 00:13:15,240
really want to measure sort of welfare

306
00:13:12,320 --> 00:13:16,519
of the economy how well how the

307
00:13:15,240 --> 00:13:19,360
well-being of

308
00:13:16,519 --> 00:13:21,078
individuals in in in in the US the

309
00:13:19,360 --> 00:13:24,240
previous picture is misleading because

310
00:13:21,078 --> 00:13:26,759
you have to yeah it's the final Pi is 50

311
00:13:24,240 --> 00:13:29,159
times larger than the first one than the

312
00:13:26,759 --> 00:13:31,759
beginning Pi but you have 320 million

313
00:13:29,159 --> 00:13:35,278
people to split it among as opposed to

314
00:13:31,759 --> 00:13:36,919
63 million so this picture captures that

315
00:13:35,278 --> 00:13:39,198
statistic that is often described when

316
00:13:36,919 --> 00:13:43,039
you talk about long run

317
00:13:39,198 --> 00:13:45,319
growth ER is GDP per person and you

318
00:13:43,039 --> 00:13:48,919
still see that what dominates this

319
00:13:45,320 --> 00:13:51,800
picture is a trend ER but the difference

320
00:13:48,919 --> 00:13:53,759
between this out out GDP per person in

321
00:13:51,799 --> 00:13:55,838
the US at the end of the sample versus

322
00:13:53,759 --> 00:13:58,639
the beginning of the sample is 10 to1

323
00:13:55,839 --> 00:14:00,560
not 50 to1 so it makes a difference

324
00:13:58,639 --> 00:14:02,799
population it's still big it's still

325
00:14:00,559 --> 00:14:05,000
what dominates this picture is that of

326
00:14:02,799 --> 00:14:07,559
course the Great Recession looks bigger

327
00:14:05,000 --> 00:14:09,278
now because you know you comparing it

328
00:14:07,559 --> 00:14:11,679
with with a number that grows by a

329
00:14:09,278 --> 00:14:14,198
factor of 10 not by a factor of 50

330
00:14:11,679 --> 00:14:16,239
that's so it looks bigger naturally know

331
00:14:14,198 --> 00:14:18,958
the same 30% decline output is a lot

332
00:14:16,240 --> 00:14:21,120
bigger when you're comparing it with

333
00:14:18,958 --> 00:14:23,879
the a factor of 10 than when you're

334
00:14:21,120 --> 00:14:27,679
comparing it with a factor of 50 but

335
00:14:23,879 --> 00:14:30,240
still it looks bigger but the picture is

336
00:14:27,679 --> 00:14:33,159
dominated by the

337
00:14:30,240 --> 00:14:35,159
so all this to say that we're going to

338
00:14:33,159 --> 00:14:36,879
study now is very important it's not

339
00:14:35,159 --> 00:14:39,159
what dominates the day-to-day news

340
00:14:36,879 --> 00:14:41,879
because it happens slowly and over time

341
00:14:39,159 --> 00:14:41,879
but it is very

342
00:14:43,399 --> 00:14:48,320
important so how do we measure these

343
00:14:45,839 --> 00:14:51,199
things well when you're looking within a

344
00:14:48,320 --> 00:14:54,278
country you do reasonably well not

345
00:14:51,198 --> 00:14:56,078
perfect but reasonably well and perhaps

346
00:14:54,278 --> 00:14:58,720
not over periods as long as I want I

347
00:14:56,078 --> 00:15:01,879
show you by looking at GDP per capita

348
00:14:58,720 --> 00:15:04,879
that's that's fine is you measure it

349
00:15:01,879 --> 00:15:06,480
real GDP per capita that's about fine

350
00:15:04,879 --> 00:15:09,198
but when you compare across different

351
00:15:06,480 --> 00:15:12,440
regions of the world and so on those

352
00:15:09,198 --> 00:15:17,838
comparisons is very misleading so to say

353
00:15:12,440 --> 00:15:21,440
that the US has um I don't know

354
00:15:17,839 --> 00:15:23,959
ER what is the US GDP per capita today

355
00:15:21,440 --> 00:15:28,040
in the US somebody should check it but

356
00:15:23,958 --> 00:15:31,039
but about maybe $70,000 something like

357
00:15:28,039 --> 00:15:34,838
that I don't know ER and then then then

358
00:15:31,039 --> 00:15:37,399
you see a another country that has say

359
00:15:34,839 --> 00:15:40,959
Italy $50,000 per

360
00:15:37,399 --> 00:15:43,440
capita that comparison is not that

361
00:15:40,958 --> 00:15:45,000
meaningful it's indicative of something

362
00:15:43,440 --> 00:15:46,160
but it's not completely meaningful and

363
00:15:45,000 --> 00:15:48,600
I'm going to show you an example which

364
00:15:46,159 --> 00:15:51,360
is much more extreme than that but the

365
00:15:48,600 --> 00:15:53,120
reason is not very meaningful is

366
00:15:51,360 --> 00:15:55,879
essentially because the prices are not

367
00:15:53,120 --> 00:15:59,560
the same across different parts of the

368
00:15:55,879 --> 00:16:01,360
world so we have a method to to to to do

369
00:15:59,559 --> 00:16:03,359
that to to be able to compare across

370
00:16:01,360 --> 00:16:05,480
countries and again even for a one a

371
00:16:03,360 --> 00:16:09,159
given country over long long period of

372
00:16:05,480 --> 00:16:12,120
time we make a correction to the GDP

373
00:16:09,159 --> 00:16:13,600
numbers we have and we make we call them

374
00:16:12,120 --> 00:16:16,799
we correct them by what is called the

375
00:16:13,600 --> 00:16:19,120
PPP purchasing power parity and I'll

376
00:16:16,799 --> 00:16:23,318
explain what that is okay so whenever

377
00:16:19,120 --> 00:16:25,120
almost whenever you see comparisons of a

378
00:16:23,318 --> 00:16:27,399
GDP per capita across countries when

379
00:16:25,120 --> 00:16:31,278
somebody's doing a growth analysis is

380
00:16:27,399 --> 00:16:34,519
going to be PPP adjusted okay now let me

381
00:16:31,278 --> 00:16:36,159
explain the logic of

382
00:16:34,519 --> 00:16:39,000
PB

383
00:16:36,159 --> 00:16:41,679
um and and and again I said within the

384
00:16:39,000 --> 00:16:44,318
same country over periods perhaps not

385
00:16:41,679 --> 00:16:48,359
300 years but over periods of 40 years

386
00:16:44,318 --> 00:16:50,399
it's reasonable H to use just real GDP

387
00:16:48,360 --> 00:16:53,560
but when you start comparing sort of you

388
00:16:50,399 --> 00:16:56,278
know bana versus the US it gets a lot

389
00:16:53,559 --> 00:16:58,439
tricky trickier because there's a lot of

390
00:16:56,278 --> 00:17:01,958
goods that are a lot cheaper in poorer

391
00:16:58,440 --> 00:17:03,920
countries in particular food okay and

392
00:17:01,958 --> 00:17:05,159
and so so you have to be careful with

393
00:17:03,919 --> 00:17:07,678
those comparisons so I'm going to give

394
00:17:05,160 --> 00:17:09,759
you this example which is somewhat

395
00:17:07,679 --> 00:17:12,759
hypothetical but the numbers are not

396
00:17:09,759 --> 00:17:15,879
crazy so suppose you have a a two

397
00:17:12,759 --> 00:17:18,879
economies the US and Russia

398
00:17:15,880 --> 00:17:18,880
and

399
00:17:20,199 --> 00:17:25,640
um anyways

400
00:17:22,720 --> 00:17:29,200
ER and suppose that that in both

401
00:17:25,640 --> 00:17:32,520
economies ER households consume houses

402
00:17:29,200 --> 00:17:35,400
and firms consume cars and

403
00:17:32,519 --> 00:17:37,319
food okay and suppose that the average

404
00:17:35,400 --> 00:17:41,120
consumer in the US buys one car a year

405
00:17:37,319 --> 00:17:44,639
for $10,000 and a bundle of food for

406
00:17:41,119 --> 00:17:46,839
$10,000 as well okay so the total

407
00:17:44,640 --> 00:17:49,720
expenditure in consumption for this

408
00:17:46,839 --> 00:17:53,000
household on average is about $20,000 a

409
00:17:49,720 --> 00:17:55,519
year that's what a US household consumes

410
00:17:53,000 --> 00:17:59,119
these numbers are fantasy numbers but

411
00:17:55,519 --> 00:18:00,158
the big picture is not that fantasy

412
00:17:59,119 --> 00:18:03,279
ER

413
00:18:00,159 --> 00:18:07,600
Russia the average consumer buys

414
00:18:03,279 --> 00:18:10,079
0.07 cars a year for 40,000 rubles and

415
00:18:07,599 --> 00:18:12,480
the same bundle of food that in the US

416
00:18:10,079 --> 00:18:14,639
okay same assume that same bundle of

417
00:18:12,480 --> 00:18:17,960
food goes for 880,000

418
00:18:14,640 --> 00:18:21,600
rubles so the total expenditure of this

419
00:18:17,960 --> 00:18:24,880
H average household in Russia is

420
00:18:21,599 --> 00:18:27,558
120,000 rubles suppose that exchange is

421
00:18:24,880 --> 00:18:31,480
60 rubles per dollar this thing has

422
00:18:27,558 --> 00:18:33,798
moved a lot recent times but suppose

423
00:18:31,480 --> 00:18:36,919
that's the the number of rubles per

424
00:18:33,798 --> 00:18:38,918
dollar so you divide $120,000 and you

425
00:18:36,919 --> 00:18:41,919
want to convert them into Dollars you

426
00:18:38,919 --> 00:18:43,799
divide the 120,000 rubles by 60,000

427
00:18:41,919 --> 00:18:45,440
rubles per dollar and then you get how

428
00:18:43,798 --> 00:18:48,798
much the Russians spend a Russian

429
00:18:45,440 --> 00:18:51,320
household on average spends on on on

430
00:18:48,798 --> 00:18:54,839
consumption in a year and and it's

431
00:18:51,319 --> 00:18:58,038
$2,000 a year okay so here you have

432
00:18:54,839 --> 00:18:59,240
120,000 divided by 60 is 2,000 that's

433
00:18:58,038 --> 00:19:01,798
the number of dollar

434
00:18:59,240 --> 00:19:04,200
that an average household in Russia

435
00:19:01,798 --> 00:19:06,759
consumes so the question

436
00:19:04,200 --> 00:19:10,000
is you have a US household spends

437
00:19:06,759 --> 00:19:13,599
$20,000 a year a Russian household

438
00:19:10,000 --> 00:19:16,400
spends $22,000 a year and the question

439
00:19:13,599 --> 00:19:18,399
is then is Russia 10 times poorer than

440
00:19:16,400 --> 00:19:20,360
the

441
00:19:18,400 --> 00:19:22,919
US

442
00:19:20,359 --> 00:19:26,798
okay that if you were to compare real

443
00:19:22,919 --> 00:19:29,240
GDP that would be answer so yeah they

444
00:19:26,798 --> 00:19:30,918
and it's true if you look at a again in

445
00:19:29,240 --> 00:19:33,679
this

446
00:19:30,919 --> 00:19:36,159
example if you look at the at the real

447
00:19:33,679 --> 00:19:38,640
GDP numbers of on the same year

448
00:19:36,159 --> 00:19:40,159
converted all into dollars that answer

449
00:19:38,640 --> 00:19:42,400
is

450
00:19:40,159 --> 00:19:44,000
correct but it doesn't represent the

451
00:19:42,400 --> 00:19:45,679
point is that it doesn't represent

452
00:19:44,000 --> 00:19:48,400
really The Well beinging of the average

453
00:19:45,679 --> 00:19:52,400
household in Russia for this reason at

454
00:19:48,400 --> 00:19:56,320
least why not well

455
00:19:52,400 --> 00:19:59,919
let's what you ultimately matter is how

456
00:19:56,319 --> 00:20:02,359
much real Goods the house

457
00:19:59,919 --> 00:20:03,840
consumes that's what really matters I

458
00:20:02,359 --> 00:20:06,158
mean if you live in a country where the

459
00:20:03,839 --> 00:20:08,079
price of everything is zero your

460
00:20:06,159 --> 00:20:09,200
consumption expenditure consumption will

461
00:20:08,079 --> 00:20:12,319
be

462
00:20:09,200 --> 00:20:14,080
zero but that doesn't mean that you are

463
00:20:12,319 --> 00:20:16,000
as unhappy as somebody that consumes

464
00:20:14,079 --> 00:20:18,639
zero you're consuming whatever it is it

465
00:20:16,000 --> 00:20:20,519
happens the prices tend to be very low

466
00:20:18,640 --> 00:20:22,520
and that's essentially the story here as

467
00:20:20,519 --> 00:20:24,918
I said before it tends to be the case

468
00:20:22,519 --> 00:20:28,240
that in poorer countries a lot of things

469
00:20:24,919 --> 00:20:30,480
are cheaper there is certain very high

470
00:20:28,240 --> 00:20:32,599
tech things that that are not even

471
00:20:30,480 --> 00:20:34,798
consumed in poorer countries so you have

472
00:20:32,599 --> 00:20:36,519
to adjust for that as well but a lot of

473
00:20:34,798 --> 00:20:39,480
the regular things the bulk of the

474
00:20:36,519 --> 00:20:41,918
purchases tend to be a lot cheaper in

475
00:20:39,480 --> 00:20:44,720
poorer countries and that's exactly what

476
00:20:41,919 --> 00:20:45,840
is behind the reason why in this example

477
00:20:44,720 --> 00:20:48,159
the answer is

478
00:20:45,839 --> 00:20:50,199
no it's not true that the Russians are

479
00:20:48,159 --> 00:20:52,840
10 time that Russian household in this

480
00:20:50,200 --> 00:20:55,600
example is 10 times poorer than the US

481
00:20:52,839 --> 00:20:59,199
let's check it so that's our

482
00:20:55,599 --> 00:21:01,439
example and I said no so fast

483
00:20:59,200 --> 00:21:03,440
let's use so assume that the goods are

484
00:21:01,440 --> 00:21:06,480
the same so the cars that the Russians

485
00:21:03,440 --> 00:21:09,759
buy is the same as the as the cars that

486
00:21:06,480 --> 00:21:13,880
the US households buy that was

487
00:21:09,759 --> 00:21:15,679
truer a few months ago than now but but

488
00:21:13,880 --> 00:21:18,840
assume that's the case it's just that

489
00:21:15,679 --> 00:21:21,480
the Russians by you know change their

490
00:21:18,839 --> 00:21:23,359
cars less frequently in this example the

491
00:21:21,480 --> 00:21:26,120
US household is changing the car once a

492
00:21:23,359 --> 00:21:28,959
year while while while the Russians are

493
00:21:26,119 --> 00:21:31,918
changing the car you know less than once

494
00:21:28,960 --> 00:21:34,880
every 10 year one every 15 years or

495
00:21:31,919 --> 00:21:37,440
so let's assume also that the the bundle

496
00:21:34,880 --> 00:21:40,600
of the of food is exactly the same in

497
00:21:37,440 --> 00:21:44,600
both Place places so since the car is

498
00:21:40,599 --> 00:21:47,839
the same and the and the and the and the

499
00:21:44,599 --> 00:21:49,879
bundle of food is the same I can use us

500
00:21:47,839 --> 00:21:53,119
prices to

501
00:21:49,880 --> 00:21:56,559
measure Uh Russian consumption and

502
00:21:53,119 --> 00:21:59,439
that's is comparable to what us

503
00:21:56,558 --> 00:22:00,879
consumption is because I'm taking I'm

504
00:21:59,440 --> 00:22:02,960
trying to convert the goods they're

505
00:22:00,880 --> 00:22:05,799
consuming into something is comparable

506
00:22:02,960 --> 00:22:08,440
to what the US consumes since the goods

507
00:22:05,798 --> 00:22:10,038
themselves are the same if I value them

508
00:22:08,440 --> 00:22:12,640
at the same price either of the two

509
00:22:10,038 --> 00:22:14,038
prices but at the same prices then I'm

510
00:22:12,640 --> 00:22:17,360
going to be able to make the comparison

511
00:22:14,038 --> 00:22:20,839
I really want that's what purchase power

512
00:22:17,359 --> 00:22:22,639
PVP adjustment means okay so look at our

513
00:22:20,839 --> 00:22:26,199
particular example here the Russian

514
00:22:22,640 --> 00:22:29,240
would household would be consuming 0.07

515
00:22:26,200 --> 00:22:32,120
cars times 10,000 dollar which is the

516
00:22:29,240 --> 00:22:36,880
price of a car plus one unit of of the

517
00:22:32,119 --> 00:22:39,959
bundle of of of of food and the price us

518
00:22:36,880 --> 00:22:41,799
price is 10,000 for that so the total

519
00:22:39,960 --> 00:22:44,960
consumption of the household PPP

520
00:22:41,798 --> 00:22:49,480
adjusted the Russian household is

521
00:22:44,960 --> 00:22:53,880
10,700 okay that's not one10 it's

522
00:22:49,480 --> 00:22:55,960
53% of us consumption so true Russian

523
00:22:53,880 --> 00:22:58,960
household is poorer than than than than

524
00:22:55,960 --> 00:23:02,640
an average US household but it's not 10

525
00:22:58,960 --> 00:23:05,200
poor no it has it's

526
00:23:02,640 --> 00:23:10,880
a is

527
00:23:05,200 --> 00:23:13,080
53% uh as rich as the US household okay

528
00:23:10,880 --> 00:23:15,400
and so this is big and all the numbers

529
00:23:13,079 --> 00:23:16,918
I'm going to show you next especially

530
00:23:15,400 --> 00:23:18,720
when we compare across sort of countries

531
00:23:16,919 --> 00:23:20,919
that are very different in terms of

532
00:23:18,720 --> 00:23:23,919
level of development and so on have

533
00:23:20,919 --> 00:23:25,400
these kind of Corrections built in okay

534
00:23:23,919 --> 00:23:27,278
if you need the data for these kind of

535
00:23:25,400 --> 00:23:29,200
things for whatever reason you find them

536
00:23:27,278 --> 00:23:30,960
in what is called the pen tables the pen

537
00:23:29,200 --> 00:23:33,240
tables essentially collects all the

538
00:23:30,960 --> 00:23:34,480
national accounts of all places and

539
00:23:33,240 --> 00:23:36,240
makes these

540
00:23:34,480 --> 00:23:39,000
Corrections the problem is they don't

541
00:23:36,240 --> 00:23:40,640
have update them very frequently but but

542
00:23:39,000 --> 00:23:42,839
if you look in Fred for example which

543
00:23:40,640 --> 00:23:45,919
you use in one of the p sets there will

544
00:23:42,839 --> 00:23:49,759
be numbers for a few countries that have

545
00:23:45,919 --> 00:23:49,759
this um PPP

546
00:23:49,798 --> 00:23:54,599
adjustment okay so that that's that's

547
00:23:53,119 --> 00:23:56,038
going to remain in the background now

548
00:23:54,599 --> 00:23:57,839
but I just wanted to tell you how how

549
00:23:56,038 --> 00:23:59,679
you construct numbers when you want to

550
00:23:57,839 --> 00:24:00,918
talk about long run and comparison

551
00:23:59,679 --> 00:24:04,880
across

552
00:24:00,919 --> 00:24:08,400
countries first set of numbers here look

553
00:24:04,880 --> 00:24:10,760
at these are obviously all today at

554
00:24:08,400 --> 00:24:13,519
least develop economies look at the

555
00:24:10,759 --> 00:24:16,000
growth between 1950 2017 obviously the

556
00:24:13,519 --> 00:24:17,679
war created a big mess there but before

557
00:24:16,000 --> 00:24:20,159
that so let's start from

558
00:24:17,679 --> 00:24:22,798
1950 and what you see here is you know

559
00:24:20,159 --> 00:24:25,919
France on average during this period

560
00:24:22,798 --> 00:24:27,038
France grew 2017 I think is the last yes

561
00:24:25,919 --> 00:24:29,440
it's the last

562
00:24:27,038 --> 00:24:31,679
year I think they were recently updated

563
00:24:29,440 --> 00:24:33,480
but at least when the book was published

564
00:24:31,679 --> 00:24:36,278
that was the last year they had pen

565
00:24:33,480 --> 00:24:40,278
tables for but

566
00:24:36,278 --> 00:24:42,159
um er France grew on average 2.6% per

567
00:24:40,278 --> 00:24:44,679
year on average they also had a business

568
00:24:42,159 --> 00:24:47,520
cycle and so on but on average 2.6% per

569
00:24:44,679 --> 00:24:49,320
year Japan during this period grew by

570
00:24:47,519 --> 00:24:53,798
four four

571
00:24:49,319 --> 00:24:56,599
4.1% the UK 2.1% the US 2% so the

572
00:24:53,798 --> 00:25:00,798
developed World essentially grew around

573
00:24:56,599 --> 00:25:03,639
2.7% on average during this

574
00:25:00,798 --> 00:25:07,440
period look at the effect that that this

575
00:25:03,640 --> 00:25:10,360
has on on the level of GDP per per per

576
00:25:07,440 --> 00:25:13,000
per person and all this PPP

577
00:25:10,359 --> 00:25:17,079
adjusted ER for the case of

578
00:25:13,000 --> 00:25:20,798
France 5.6 times so they started with

579
00:25:17,079 --> 00:25:24,918
$7,000 and they were close to $40,000 in

580
00:25:20,798 --> 00:25:28,599
2017 so the r is RA

581
00:25:24,919 --> 00:25:31,360
5.6 look at the US the US is 2% and that

582
00:25:28,599 --> 00:25:33,240
ratio is is still richer than France per

583
00:25:31,359 --> 00:25:36,959
per person in

584
00:25:33,240 --> 00:25:39,240
2017 but but the ratio of that to that

585
00:25:36,960 --> 00:25:40,759
is smaller than that so over a long

586
00:25:39,240 --> 00:25:42,960
period of time that's what a trend in

587
00:25:40,759 --> 00:25:44,679
the picture capture a small difference

588
00:25:42,960 --> 00:25:46,679
in the rate of growth if they are

589
00:25:44,679 --> 00:25:49,000
sustained for a long period of time can

590
00:25:46,679 --> 00:25:54,600
make quite a bit of difference for the

591
00:25:49,000 --> 00:25:56,919
change in in GDP okay and so what do you

592
00:25:54,599 --> 00:25:59,480
what is the first what is the p is I

593
00:25:56,919 --> 00:26:01,038
mean let's find the pattern here here

594
00:25:59,480 --> 00:26:04,720
there's a very clear pattern in that

595
00:26:01,038 --> 00:26:07,278
picture in that table what is it do you

596
00:26:04,720 --> 00:26:07,278
can you spot

597
00:26:15,919 --> 00:26:20,679
it I hadn't

598
00:26:18,200 --> 00:26:22,720
actually realized it when I was looking

599
00:26:20,679 --> 00:26:24,360
at my notes and then I realized is very

600
00:26:22,720 --> 00:26:26,558
clear in this table that's the reason I

601
00:26:24,359 --> 00:26:30,240
added this line I updated the slide this

602
00:26:26,558 --> 00:26:30,240
morning do you see a pattern

603
00:26:34,240 --> 00:26:40,038
yes the higher growth rate have a higher

604
00:26:37,640 --> 00:26:41,240
multiple yeah well that's yes that but

605
00:26:40,038 --> 00:26:43,640
that's

606
00:26:41,240 --> 00:26:45,558
math okay which is so it's a true

607
00:26:43,640 --> 00:26:48,640
statement but that's just

608
00:26:45,558 --> 00:26:49,639
math there's an economic thing that that

609
00:26:48,640 --> 00:26:53,038
that I want

610
00:26:49,640 --> 00:26:54,480
to so so you're right but but I want

611
00:26:53,038 --> 00:26:58,480
they should have clarified there's an

612
00:26:54,480 --> 00:26:58,480
economic pattern there

613
00:27:03,880 --> 00:27:10,760
let let me simplify just look at these

614
00:27:05,839 --> 00:27:13,439
two columns because a higher number here

615
00:27:10,759 --> 00:27:15,640
simply sorry a higher number here simply

616
00:27:13,440 --> 00:27:18,038
means that you had a higher rate of

617
00:27:15,640 --> 00:27:20,360
growth that's your math fact so ignore

618
00:27:18,038 --> 00:27:23,158
this column what I suggest is that you

619
00:27:20,359 --> 00:27:23,158
just look at these two

620
00:27:24,278 --> 00:27:29,599
columns do you see a

621
00:27:27,159 --> 00:27:31,520
pattern just look at these two columns

622
00:27:29,599 --> 00:27:33,119
this one in a sense just repeats

623
00:27:31,519 --> 00:27:35,440
information that is here for the reason

624
00:27:33,119 --> 00:27:38,678
you describe but just look at these two

625
00:27:35,440 --> 00:27:38,679
columns is there a pattern

626
00:27:40,398 --> 00:27:45,918
there exactly very important Richard

627
00:27:44,240 --> 00:27:49,000
countri sent to grow slower the richest

628
00:27:45,919 --> 00:27:50,720
country here is the US had the lowest

629
00:27:49,000 --> 00:27:54,720
rate of growth on

630
00:27:50,720 --> 00:27:58,200
average the poorest was Japan there and

631
00:27:54,720 --> 00:27:59,640
they had the highest rate of growth okay

632
00:27:58,200 --> 00:28:00,960
so that's a very important correlation

633
00:27:59,640 --> 00:28:02,480
and again the first model we're going to

634
00:28:00,960 --> 00:28:05,159
see of economic growth is going to

635
00:28:02,480 --> 00:28:07,360
explain that correlation why is that we

636
00:28:05,159 --> 00:28:09,799
see

637
00:28:07,359 --> 00:28:11,079
that those were for five economy you

638
00:28:09,798 --> 00:28:13,480
could say it's an accident but look at

639
00:28:11,079 --> 00:28:16,158
this this this is just a this is rich

640
00:28:13,480 --> 00:28:18,278
countries in general since 1950s and you

641
00:28:16,159 --> 00:28:19,880
look at here in this axis you have the

642
00:28:18,278 --> 00:28:23,640
annual rate of growth the average rate

643
00:28:19,880 --> 00:28:26,519
of growth and here the GDP per person in

644
00:28:23,640 --> 00:28:29,399
1950 so at the beginning of the sample

645
00:28:26,519 --> 00:28:32,159
1950 these countries had have this level

646
00:28:29,398 --> 00:28:36,038
of GDP per capita and then here is the

647
00:28:32,159 --> 00:28:39,000
rate of growth on average from 1950 to

648
00:28:36,038 --> 00:28:42,599
1987 and it's very clear there that

649
00:28:39,000 --> 00:28:44,558
there's a downward sloping pattern no so

650
00:28:42,599 --> 00:28:46,879
that's the same fact now for many more

651
00:28:44,558 --> 00:28:48,759
countries there's a downward sloping

652
00:28:46,880 --> 00:28:51,039
relationship really the richest

653
00:28:48,759 --> 00:28:52,679
countries tend to grow much slower than

654
00:28:51,038 --> 00:28:54,319
the countries were poorer at the

655
00:28:52,679 --> 00:28:56,000
beginning of the

656
00:28:54,319 --> 00:28:59,278
sample

657
00:28:56,000 --> 00:29:02,798
okay there are some interesting

658
00:28:59,278 --> 00:29:05,119
liers like Mexico and and is an

659
00:29:02,798 --> 00:29:08,918
interesting in itself I'm not going to

660
00:29:05,119 --> 00:29:12,398
say a lot about why that's the case

661
00:29:08,919 --> 00:29:14,840
but but but let me for now stick to the

662
00:29:12,398 --> 00:29:17,798
to the pattern the dominant pattern

663
00:29:14,839 --> 00:29:19,480
which is is a downward sloping

664
00:29:17,798 --> 00:29:22,519
relationship that's another way of

665
00:29:19,480 --> 00:29:25,399
seeing it and this is for just a bigger

666
00:29:22,519 --> 00:29:29,038
variety of countries I have Botana China

667
00:29:25,398 --> 00:29:32,278
Thailand and so on and and you see here

668
00:29:29,038 --> 00:29:33,278
GDP at the beginning of the 1950 and GDP

669
00:29:32,278 --> 00:29:35,640
rate

670
00:29:33,278 --> 00:29:37,079
2018 and the pattern here which is

671
00:29:35,640 --> 00:29:38,960
essentially a repetition of the pattern

672
00:29:37,079 --> 00:29:44,918
that I showed you before is that there

673
00:29:38,960 --> 00:29:47,240
is much more compression here than

674
00:29:44,919 --> 00:29:50,559
here how can you have more compression

675
00:29:47,240 --> 00:29:52,839
here than here well because there is

676
00:29:50,558 --> 00:29:55,240
some sort of convergence no there's a

677
00:29:52,839 --> 00:29:58,079
sense of convergence is that those that

678
00:29:55,240 --> 00:30:00,359
were poorer tend to grow a little faster

679
00:29:58,079 --> 00:30:02,158
than those that were richer and

680
00:30:00,359 --> 00:30:04,240
therefore they tend to converge to each

681
00:30:02,159 --> 00:30:06,399
other so that's the the point I'm

682
00:30:04,240 --> 00:30:10,558
highlighting here a lot of this persion

683
00:30:06,398 --> 00:30:13,278
1950 much less isers in 2018 that means

684
00:30:10,558 --> 00:30:17,119
that on average the poorer countries are

685
00:30:13,278 --> 00:30:17,119
growing faster than the Richer

686
00:30:19,200 --> 00:30:26,679
countries and again all this is per

687
00:30:21,398 --> 00:30:26,678
capita PPP adjust and all that okay

688
00:30:30,319 --> 00:30:34,519
this

689
00:30:31,839 --> 00:30:37,918
picture again sort of makes the the

690
00:30:34,519 --> 00:30:40,519
point but now it takes a much many more

691
00:30:37,919 --> 00:30:43,960
countries and you can what the point of

692
00:30:40,519 --> 00:30:46,200
this picture is in the book is is is to

693
00:30:43,960 --> 00:30:49,000
highlight that it's a little messy the

694
00:30:46,200 --> 00:30:52,519
picture but to highlight that if you

695
00:30:49,000 --> 00:30:55,398
look in different regions oecd a major

696
00:30:52,519 --> 00:30:57,638
the major economies H tend to the

697
00:30:55,398 --> 00:31:00,518
pattern I show you holds if you look at

698
00:30:57,638 --> 00:31:03,038
only isolate only the blue the blue

699
00:31:00,519 --> 00:31:06,919
squares you tend to see that negative

700
00:31:03,038 --> 00:31:11,000
relationship if you look at within

701
00:31:06,919 --> 00:31:13,639
Asia it's also it's a little bit noisier

702
00:31:11,000 --> 00:31:15,440
but you also tend to see a negative

703
00:31:13,638 --> 00:31:17,918
relationship

704
00:31:15,440 --> 00:31:21,960
okay if you look at

705
00:31:17,919 --> 00:31:23,679
Africa that relationship is lost

706
00:31:21,960 --> 00:31:27,519
completely

707
00:31:23,679 --> 00:31:28,798
okay so so when you look at the world as

708
00:31:27,519 --> 00:31:30,519
a whole

709
00:31:28,798 --> 00:31:32,558
the picture is not as neat as the one I

710
00:31:30,519 --> 00:31:33,960
show you because there are certain

711
00:31:32,558 --> 00:31:35,720
pockets of the world that are not

712
00:31:33,960 --> 00:31:38,360
behaving according to the kind of mods I

713
00:31:35,720 --> 00:31:39,839
want I discuss in the next few lectures

714
00:31:38,359 --> 00:31:42,000
and the reason they're not behaving is

715
00:31:39,839 --> 00:31:45,359
entirely it's almost outside economics

716
00:31:42,000 --> 00:31:47,599
it has it's political conflicts Wars and

717
00:31:45,359 --> 00:31:49,359
things of that nature which continuously

718
00:31:47,599 --> 00:31:50,719
disrupt sort of the economic forces that

719
00:31:49,359 --> 00:31:53,398
I'm going to highlight in the next few

720
00:31:50,720 --> 00:31:56,720
lectures

721
00:31:53,398 --> 00:31:58,599
okay so that's a different different

722
00:31:56,720 --> 00:32:01,278
different issue where going to be about

723
00:31:58,599 --> 00:32:06,959
the all the moles I'll show you next are

724
00:32:01,278 --> 00:32:06,960
about the blue and the and the

725
00:32:07,319 --> 00:32:13,918
green squares and and and triangles

726
00:32:10,599 --> 00:32:13,918
there not about the red

727
00:32:14,798 --> 00:32:20,599
ones what about so I look I show you

728
00:32:17,759 --> 00:32:23,200
what happens across countries over over

729
00:32:20,599 --> 00:32:26,678
certain period of time which is long but

730
00:32:23,200 --> 00:32:29,798
not that long here you see what happens

731
00:32:26,679 --> 00:32:31,720
in longer here history there are two

732
00:32:29,798 --> 00:32:35,558
patterns that I like to highlight here

733
00:32:31,720 --> 00:32:37,839
is that H first for a while sort of you

734
00:32:35,558 --> 00:32:40,480
you didn't see much but but you tend to

735
00:32:37,839 --> 00:32:45,038
see a sort of a big acceleration in the

736
00:32:40,480 --> 00:32:48,599
Western World especially around the the

737
00:32:45,038 --> 00:32:50,158
1950s or so okay so so clearly the

738
00:32:48,599 --> 00:32:52,519
Western world was growing faster than

739
00:32:50,159 --> 00:32:56,360
the rest of the world H the Western

740
00:32:52,519 --> 00:32:59,839
Hemisphere this is a um um world Bank

741
00:32:56,359 --> 00:32:59,839
IFI type type

742
00:33:01,200 --> 00:33:05,798
um

743
00:33:03,159 --> 00:33:07,919
grouping and and you see that there's a

744
00:33:05,798 --> 00:33:12,119
very fast acceleration in growth in this

745
00:33:07,919 --> 00:33:14,240
episode here Western Europe H was also

746
00:33:12,119 --> 00:33:16,079
flattish and then picked up very

747
00:33:14,240 --> 00:33:18,558
strongly there and you see the different

748
00:33:16,079 --> 00:33:21,480
regions of the world and again you see

749
00:33:18,558 --> 00:33:26,879
the sub Sahara Africa region that sort

750
00:33:21,480 --> 00:33:26,880
of has hasn't really picked up okay

751
00:33:28,599 --> 00:33:34,079
much longer history well that's the way

752
00:33:31,440 --> 00:33:36,639
it looks for the world as a whole

753
00:33:34,079 --> 00:33:38,798
okay you know exponential pictures tend

754
00:33:36,638 --> 00:33:41,959
to look like that but but this is more

755
00:33:38,798 --> 00:33:44,240
dramatic than exponential and again what

756
00:33:41,960 --> 00:33:46,840
happens is

757
00:33:44,240 --> 00:33:49,679
that what happen here is is going to be

758
00:33:46,839 --> 00:33:51,480
very different from from the kind of

759
00:33:49,679 --> 00:33:53,759
mods I'll describe

760
00:33:51,480 --> 00:33:55,480
next this period here is mostly

761
00:33:53,759 --> 00:33:58,558
dominated by what's called sort of the

762
00:33:55,480 --> 00:34:01,440
malthusian era which is essentially

763
00:33:58,558 --> 00:34:03,759
people live population grew and so on

764
00:34:01,440 --> 00:34:06,679
depending on how good was the the

765
00:34:03,759 --> 00:34:07,960
harvest that year and so on no so so you

766
00:34:06,679 --> 00:34:10,200
had this mod in which you know his

767
00:34:07,960 --> 00:34:13,079
population grew faster that was a main

768
00:34:10,199 --> 00:34:15,000
driver of of of growth well but you know

769
00:34:13,079 --> 00:34:17,280
there wasn't enough food to sustain a a

770
00:34:15,000 --> 00:34:18,878
higher population and then you stay

771
00:34:17,280 --> 00:34:21,760
soort of there was a fight between food

772
00:34:18,878 --> 00:34:23,559
and and and people and and and no much

773
00:34:21,760 --> 00:34:26,960
space for most people were in

774
00:34:23,559 --> 00:34:28,679
agriculture and and the and and and

775
00:34:26,960 --> 00:34:31,320
there wasn't sort of

776
00:34:28,679 --> 00:34:33,159
much to build on nowadays there are

777
00:34:31,320 --> 00:34:36,119
pocket in the world and we had the

778
00:34:33,159 --> 00:34:38,358
severe situations during covid but food

779
00:34:36,119 --> 00:34:41,838
is not really a constraint for growth

780
00:34:38,358 --> 00:34:44,679
for the world as a whole

781
00:34:41,838 --> 00:34:47,358
okay and but you see

782
00:34:44,679 --> 00:34:49,878
so in other words had you taken this

783
00:34:47,358 --> 00:34:51,878
course in 20 in year 1000 or in the

784
00:34:49,878 --> 00:34:54,000
Renaissance nobody would have talked

785
00:34:51,878 --> 00:34:56,960
about growth it's not something that

786
00:34:54,000 --> 00:34:59,159
happened really it's it's a very modern

787
00:34:56,960 --> 00:35:02,679
thing to think about these pictures with

788
00:34:59,159 --> 00:35:05,118
these long Trends and so on

789
00:35:02,679 --> 00:35:06,598
okay I mean there you would have talked

790
00:35:05,119 --> 00:35:09,079
about a lot more interesting things than

791
00:35:06,599 --> 00:35:12,280
this but but not not about growth that's

792
00:35:09,079 --> 00:35:13,839
for sure and growth the last point I I

793
00:35:12,280 --> 00:35:15,359
think I want to make about this is it

794
00:35:13,838 --> 00:35:17,320
makes a big

795
00:35:15,358 --> 00:35:21,199
difference I don't know if you can read

796
00:35:17,320 --> 00:35:23,680
that I I can't but er um what I have

797
00:35:21,199 --> 00:35:28,159
here is GDP per capita in

798
00:35:23,679 --> 00:35:30,358
1950 versus GDP per capita in 2016

799
00:35:28,159 --> 00:35:33,239
and you have this isoquants here you

800
00:35:30,358 --> 00:35:35,559
move you as you move up so this line

801
00:35:33,239 --> 00:35:38,959
here is what happens to countries that

802
00:35:35,559 --> 00:35:40,920
is a 45 degree line so if you are on the

803
00:35:38,960 --> 00:35:43,199
45 degree line means that you haven't

804
00:35:40,920 --> 00:35:45,920
grown at all during this period no

805
00:35:43,199 --> 00:35:48,838
because that means that your GDP per

806
00:35:45,920 --> 00:35:52,079
capita 1950 is the same as you g GDP per

807
00:35:48,838 --> 00:35:54,960
capita in 2016 that means on average you

808
00:35:52,079 --> 00:35:57,680
grow okay but as I keep moving these

809
00:35:54,960 --> 00:35:58,960
lines up means you grew faster and fter

810
00:35:57,679 --> 00:36:03,078
faster and

811
00:35:58,960 --> 00:36:05,280
faster okay so and if you if you move

812
00:36:03,079 --> 00:36:07,318
along this line here that means you have

813
00:36:05,280 --> 00:36:10,280
negative growth on average during that

814
00:36:07,318 --> 00:36:13,719
period okay so each of these lines

815
00:36:10,280 --> 00:36:17,280
represents multiples so I think this is

816
00:36:13,719 --> 00:36:19,318
for example this top line here is 30

817
00:36:17,280 --> 00:36:21,760
times richer these are guys that grew

818
00:36:19,318 --> 00:36:23,838
very very fast yeah you I cannot read

819
00:36:21,760 --> 00:36:24,960
either but I I sort of know who is in

820
00:36:23,838 --> 00:36:26,559
each

821
00:36:24,960 --> 00:36:30,358
Place

822
00:36:26,559 --> 00:36:36,279
h this is an example here this is

823
00:36:30,358 --> 00:36:38,880
Taiwan okay this is Taiwan and H this is

824
00:36:36,280 --> 00:36:41,319
Singapore they have a name how do we

825
00:36:38,880 --> 00:36:41,318
call those

826
00:36:41,400 --> 00:36:44,680
countries no

827
00:36:44,960 --> 00:36:51,800
well the Asian tigers they grew very

828
00:36:48,318 --> 00:36:55,440
very strong for for a long time since

829
00:36:51,800 --> 00:36:57,760
the 60s or so but there you see you can

830
00:36:55,440 --> 00:37:01,679
compare if you could see you would see

831
00:36:57,760 --> 00:37:03,480
that you know that that Taiwan and the

832
00:37:01,679 --> 00:37:05,759
Democratic Republic of Congo had the

833
00:37:03,480 --> 00:37:10,079
same GDP in

834
00:37:05,760 --> 00:37:14,119
1950 okay now the Republic Democratic

835
00:37:10,079 --> 00:37:19,760
Republic of of of of Congo has less GDP

836
00:37:14,119 --> 00:37:23,880
than it had ER in 1950 it had 1700 here

837
00:37:19,760 --> 00:37:25,720
and 800 today while Taiwan Taiwan has 30

838
00:37:23,880 --> 00:37:28,480
times what it used to

839
00:37:25,719 --> 00:37:31,799
have and so today is one of the richest

840
00:37:28,480 --> 00:37:35,960
economies in the world close to 7

841
00:37:31,800 --> 00:37:40,079
$50,000 per capita while the Republic of

842
00:37:35,960 --> 00:37:44,639
Congo ER has

843
00:37:40,079 --> 00:37:47,119
700 $800 per capita so growth makes a

844
00:37:44,639 --> 00:37:49,078
big big difference okay and these are

845
00:37:47,119 --> 00:37:54,079
not that many years I mean you know this

846
00:37:49,079 --> 00:37:56,318
is just 70 years H and I can assure you

847
00:37:54,079 --> 00:37:58,079
that these people they have other

848
00:37:56,318 --> 00:38:00,159
concerns but

849
00:37:58,079 --> 00:38:01,640
their standard of living is a lot higher

850
00:38:00,159 --> 00:38:04,639
than these people and at some point they

851
00:38:01,639 --> 00:38:06,358
were the same the big difference is some

852
00:38:04,639 --> 00:38:09,639
countries that grew and some

853
00:38:06,358 --> 00:38:12,279
countries got a stuck um where is

854
00:38:09,639 --> 00:38:13,400
Argentina here I don't know somewhere

855
00:38:12,280 --> 00:38:16,599
here

856
00:38:13,400 --> 00:38:16,599
probably it's

857
00:38:18,760 --> 00:38:26,359
Argentina I don't know I cannot

858
00:38:21,880 --> 00:38:28,318
see have the chance here I can say okay

859
00:38:26,358 --> 00:38:30,159
good so growth that's make a difference

860
00:38:28,318 --> 00:38:33,119
and he has made a huge the world we see

861
00:38:30,159 --> 00:38:36,199
today and the countries we think as rich

862
00:38:33,119 --> 00:38:38,760
or poor were not the same countries that

863
00:38:36,199 --> 00:38:41,919
you thought in in those terms in

864
00:38:38,760 --> 00:38:44,160
1950 Asia is one of the most prominent

865
00:38:41,920 --> 00:38:46,440
differences they have massive growth

866
00:38:44,159 --> 00:38:48,039
through the

867
00:38:46,440 --> 00:38:51,079
60s

868
00:38:48,039 --> 00:38:53,039
um starting with Japan but then the rest

869
00:38:51,079 --> 00:38:56,280
and again were the famous the Tigers

870
00:38:53,039 --> 00:38:58,800
Hong Kong Taiwan

871
00:38:56,280 --> 00:39:02,640
Singapore uh

872
00:38:58,800 --> 00:39:08,560
and Korea South

873
00:39:02,639 --> 00:39:11,159
Korea good so let's start building some

874
00:39:08,559 --> 00:39:13,599
moles of what we have just

875
00:39:11,159 --> 00:39:16,039
seen remember when we look at the short

876
00:39:13,599 --> 00:39:18,039
run we really didn't care about the

877
00:39:16,039 --> 00:39:19,800
supply side of the economy remember it

878
00:39:18,039 --> 00:39:22,679
was all about demand they said well you

879
00:39:19,800 --> 00:39:25,560
know demand look what consumers invest

880
00:39:22,679 --> 00:39:28,000
firms and governments do with demand

881
00:39:25,559 --> 00:39:30,559
that determines output and output

882
00:39:28,000 --> 00:39:32,880
happens well it happens we didn't really

883
00:39:30,559 --> 00:39:35,078
care too much about it then when we talk

884
00:39:32,880 --> 00:39:36,920
about the medium term we say okay we're

885
00:39:35,079 --> 00:39:40,880
going to no no we have to care because

886
00:39:36,920 --> 00:39:42,440
you know to produce you need workers and

887
00:39:40,880 --> 00:39:44,640
and you know workers are not going to

888
00:39:42,440 --> 00:39:47,920
work for any wage and so we had to begin

889
00:39:44,639 --> 00:39:50,519
to talk about ER the the supply side of

890
00:39:47,920 --> 00:39:52,119
the economy but we made it very simple

891
00:39:50,519 --> 00:39:54,400
we just look at the problem of wage

892
00:39:52,119 --> 00:39:56,160
bargaining and price setting but the

893
00:39:54,400 --> 00:39:57,760
production function itself wasn't that

894
00:39:56,159 --> 00:39:59,318
interesting it was outputting equal to

895
00:39:57,760 --> 00:40:01,920
labor and I told you it's very

896
00:39:59,318 --> 00:40:04,239
unrealistic but it was convenient for

897
00:40:01,920 --> 00:40:06,440
that part of the course because Capital

898
00:40:04,239 --> 00:40:08,199
doesn't grow that fast so typical

899
00:40:06,440 --> 00:40:10,599
production function we have both capital

900
00:40:08,199 --> 00:40:12,799
and labor but at the business cycle

901
00:40:10,599 --> 00:40:14,480
frequency investment the change in

902
00:40:12,800 --> 00:40:16,039
capital can be large but the stock of

903
00:40:14,480 --> 00:40:18,039
capital doesn't move that much and so

904
00:40:16,039 --> 00:40:20,000
you can ignore it for business cycle

905
00:40:18,039 --> 00:40:22,239
type fluctuations but if we want to look

906
00:40:20,000 --> 00:40:24,400
at the long run Capital plays a huge

907
00:40:22,239 --> 00:40:27,000
role capital accumulation and so we have

908
00:40:24,400 --> 00:40:28,559
to be explicit about the role of capital

909
00:40:27,000 --> 00:40:31,239
in the the production

910
00:40:28,559 --> 00:40:32,400
function so this is going to be our now

911
00:40:31,239 --> 00:40:34,239
and now we're going to forget about

912
00:40:32,400 --> 00:40:35,800
aggregate demand we're going to say look

913
00:40:34,239 --> 00:40:37,358
we're going to focus about AGG supply

914
00:40:35,800 --> 00:40:41,640
and demand will do whatever it needs to

915
00:40:37,358 --> 00:40:46,960
do so so so we get what what the supply

916
00:40:41,639 --> 00:40:49,480
site says so output now will be will be

917
00:40:46,960 --> 00:40:51,599
a an increasing function of both capital

918
00:40:49,480 --> 00:40:54,000
and

919
00:40:51,599 --> 00:40:57,640
labor now this function will have a

920
00:40:54,000 --> 00:40:58,440
bunch of er properties which are many of

921
00:40:57,639 --> 00:41:00,879
which

922
00:40:58,440 --> 00:41:03,039
are no at a broad level they are

923
00:41:00,880 --> 00:41:04,559
empirically validated but they're also

924
00:41:03,039 --> 00:41:07,239
very convenient from the modeling point

925
00:41:04,559 --> 00:41:08,799
of view the first and most

926
00:41:07,239 --> 00:41:12,639
important

927
00:41:08,800 --> 00:41:15,280
property um is constant returns to

928
00:41:12,639 --> 00:41:19,039
scale okay we're going to use a lot of

929
00:41:15,280 --> 00:41:22,400
property so so please get that concept

930
00:41:19,039 --> 00:41:25,119
constant return to scale means simply

931
00:41:22,400 --> 00:41:28,480
that if you scale the factors of

932
00:41:25,119 --> 00:41:33,519
production you also scale the output

933
00:41:28,480 --> 00:41:36,838
okay so say if x is 1.1 that means if

934
00:41:33,519 --> 00:41:40,519
you increase capital and labor by 10%

935
00:41:36,838 --> 00:41:42,559
you get 10% more output okay so that's

936
00:41:40,519 --> 00:41:44,079
Conant return to scale if I scale all

937
00:41:42,559 --> 00:41:46,880
the factors of production by the same

938
00:41:44,079 --> 00:41:49,839
amount the same proportion then output

939
00:41:46,880 --> 00:41:51,880
Grows by the same proportion it's

940
00:41:49,838 --> 00:41:54,279
scalable that's what it mean constant

941
00:41:51,880 --> 00:41:54,280
return to

942
00:41:54,838 --> 00:42:02,599
scale very important property what comes

943
00:41:58,280 --> 00:42:02,599
next decreasing returns to

944
00:42:03,000 --> 00:42:08,519
Capital that

945
00:42:05,440 --> 00:42:11,039
is H as you increase capital for a fixed

946
00:42:08,519 --> 00:42:13,239
amount of Labor so conent scale is a

947
00:42:11,039 --> 00:42:15,679
property of scaling everything

948
00:42:13,239 --> 00:42:17,639
up the property I'm describing here is

949
00:42:15,679 --> 00:42:20,598
what happens if we increase only K what

950
00:42:17,639 --> 00:42:23,118
happens to Output if we increase only K

951
00:42:20,599 --> 00:42:27,480
but fixing

952
00:42:23,119 --> 00:42:29,039
n in other words set this to one and

953
00:42:27,480 --> 00:42:31,318
start moving this

954
00:42:29,039 --> 00:42:33,519
up you're not going to get X here you're

955
00:42:31,318 --> 00:42:36,838
going to get something different from

956
00:42:33,519 --> 00:42:39,159
X and but this tells you is that yes

957
00:42:36,838 --> 00:42:42,078
you're going to get more output but less

958
00:42:39,159 --> 00:42:45,440
and less the more Capital you

959
00:42:42,079 --> 00:42:48,079
have Okay so this says for example

960
00:42:45,440 --> 00:42:50,440
suppose you start with 100 workers and

961
00:42:48,079 --> 00:42:53,079
100 units of capital and it happens that

962
00:42:50,440 --> 00:42:57,920
this produces 100 units of

963
00:42:53,079 --> 00:42:59,640
goods if you add now 10 units of capital

964
00:42:57,920 --> 00:43:04,639
say you're going to

965
00:42:59,639 --> 00:43:06,199
get seven units of output not 10 seven

966
00:43:04,639 --> 00:43:07,920
because you didn't increase labor had I

967
00:43:06,199 --> 00:43:09,879
increased labor also by by 10 I would

968
00:43:07,920 --> 00:43:13,800
have gotten 10 of output but I

969
00:43:09,880 --> 00:43:16,519
increasing only h capital by 10 then and

970
00:43:13,800 --> 00:43:18,640
keeping output fixed then labor fixed

971
00:43:16,519 --> 00:43:21,000
then output will increase by less than

972
00:43:18,639 --> 00:43:23,199
10 but what this decrease in returns to

973
00:43:21,000 --> 00:43:26,639
Capital says is that now if you increase

974
00:43:23,199 --> 00:43:27,960
again from 110 to 120 units of capital

975
00:43:26,639 --> 00:43:30,279
you're going to get get less than seven

976
00:43:27,960 --> 00:43:32,480
units of output more you're going to get

977
00:43:30,280 --> 00:43:34,720
five and if you increase a again from

978
00:43:32,480 --> 00:43:37,199
120 to 130 you're going to get less than

979
00:43:34,719 --> 00:43:39,199
five you're going to get three and so on

980
00:43:37,199 --> 00:43:41,960
so forth that's decreasing returns to

981
00:43:39,199 --> 00:43:45,598
scale and and decreasing returns to

982
00:43:41,960 --> 00:43:47,838
Capital and the reason for that is is

983
00:43:45,599 --> 00:43:49,280
economically is that more and more

984
00:43:47,838 --> 00:43:51,440
capital is working with a fixed number

985
00:43:49,280 --> 00:43:52,400
of workers so labor becomes very scarce

986
00:43:51,440 --> 00:43:55,440
for

987
00:43:52,400 --> 00:43:57,720
capital okay and that's the reason so so

988
00:43:55,440 --> 00:43:58,838
you have very little

989
00:43:57,719 --> 00:44:00,439
the other these are factors of

990
00:43:58,838 --> 00:44:02,799
production which are complementary they

991
00:44:00,440 --> 00:44:05,760
need each other labor and capital if you

992
00:44:02,800 --> 00:44:07,760
fix one and it start increasing only one

993
00:44:05,760 --> 00:44:09,720
then it's harder and harder for each

994
00:44:07,760 --> 00:44:11,839
extra new unit of this one to work with

995
00:44:09,719 --> 00:44:13,480
sort of fewer and fewer of the other

996
00:44:11,838 --> 00:44:16,000
factor of production so the same

997
00:44:13,480 --> 00:44:18,639
principle applies to labor if you fix

998
00:44:16,000 --> 00:44:21,480
capital and you only increase labor then

999
00:44:18,639 --> 00:44:22,920
initially you get a big jumping output

1000
00:44:21,480 --> 00:44:26,318
but it's going to be smaller and smaller

1001
00:44:22,920 --> 00:44:29,039
and smaller the more you keep adding a

1002
00:44:26,318 --> 00:44:29,039
um

1003
00:44:29,119 --> 00:44:36,960
labor okay so in pi so let me One X that

1004
00:44:34,079 --> 00:44:40,880
we're going to use

1005
00:44:36,960 --> 00:44:46,318
throughout is we want to make x one of

1006
00:44:40,880 --> 00:44:46,318
our favorite X will be 1 /

1007
00:44:46,400 --> 00:44:52,760
n you see what I'm trying to do when we

1008
00:44:49,039 --> 00:44:56,239
set x equal to 1 / n so that x equal to

1009
00:44:52,760 --> 00:44:58,440
1 / n what I get here is output per

1010
00:44:56,239 --> 00:45:00,239
person

1011
00:44:58,440 --> 00:45:02,519
no that's what I

1012
00:45:00,239 --> 00:45:08,039
get y Over

1013
00:45:02,519 --> 00:45:09,920
N so if I set xal to 1/ n i can using

1014
00:45:08,039 --> 00:45:11,079
con to scale I know that this is equal

1015
00:45:09,920 --> 00:45:16,159
to

1016
00:45:11,079 --> 00:45:18,839
y/n k/ n n/ n so that is one so this guy

1017
00:45:16,159 --> 00:45:22,239
doesn't move and I have now

1018
00:45:18,838 --> 00:45:24,679
that a output per person is increasing

1019
00:45:22,239 --> 00:45:26,039
in capital per worker worker and

1020
00:45:24,679 --> 00:45:28,719
population this part of the course are

1021
00:45:26,039 --> 00:45:31,639
the same for get an EMP employment and

1022
00:45:28,719 --> 00:45:34,358
is population is employment if labor

1023
00:45:31,639 --> 00:45:38,440
force is everything I'm not this is not

1024
00:45:34,358 --> 00:45:38,440
a place to worry about unemployment

1025
00:45:41,800 --> 00:45:47,640
okay okay so remember that all the plots

1026
00:45:45,079 --> 00:45:50,039
I show you the different Figures were

1027
00:45:47,639 --> 00:45:52,078
about this variable how it changed over

1028
00:45:50,039 --> 00:45:54,679
time how was different across different

1029
00:45:52,079 --> 00:45:57,800
countries how grew at a different rate

1030
00:45:54,679 --> 00:46:00,879
in in different countries but from this

1031
00:45:57,800 --> 00:46:01,839
very simple model you see that in order

1032
00:46:00,880 --> 00:46:05,039
to

1033
00:46:01,838 --> 00:46:07,119
explain the change in this or growth in

1034
00:46:05,039 --> 00:46:09,719
why over and why one country grows more

1035
00:46:07,119 --> 00:46:12,960
than the other you have with the simple

1036
00:46:09,719 --> 00:46:12,959
model only two

1037
00:46:13,280 --> 00:46:20,720
options so if I tell you country a grew

1038
00:46:17,559 --> 00:46:23,280
more over this period than grew more per

1039
00:46:20,719 --> 00:46:28,358
per person than this other

1040
00:46:23,280 --> 00:46:29,920
country er um over this period of time

1041
00:46:28,358 --> 00:46:32,239
there are only two options here the

1042
00:46:29,920 --> 00:46:34,400
first one is that in that country there

1043
00:46:32,239 --> 00:46:37,879
was more capital accumulation per worker

1044
00:46:34,400 --> 00:46:39,838
so K Over N went up no if K Over N goes

1045
00:46:37,880 --> 00:46:42,960
up more in one country than the other

1046
00:46:39,838 --> 00:46:45,679
one y Over N will go up more in that

1047
00:46:42,960 --> 00:46:49,559
country than the other one and the other

1048
00:46:45,679 --> 00:46:51,358
option is that the this H function

1049
00:46:49,559 --> 00:46:56,280
itself shifted

1050
00:46:51,358 --> 00:46:58,719
up so for any given amount of K Over N

1051
00:46:56,280 --> 00:47:00,359
now you could produ more y over n and

1052
00:46:58,719 --> 00:47:04,078
that's what we call technological

1053
00:47:00,358 --> 00:47:07,239
progress that's a second thing so so if

1054
00:47:04,079 --> 00:47:09,760
if if the difference in in in in growth

1055
00:47:07,239 --> 00:47:12,358
of output per

1056
00:47:09,760 --> 00:47:13,880
person is due to an increasing K Over

1057
00:47:12,358 --> 00:47:16,358
end well we call that a capill

1058
00:47:13,880 --> 00:47:18,880
accumulation mechanism if it is because

1059
00:47:16,358 --> 00:47:20,759
the function f shifts up that's

1060
00:47:18,880 --> 00:47:22,680
technological progress and what we're

1061
00:47:20,760 --> 00:47:24,359
going to do is in the next lecture we're

1062
00:47:22,679 --> 00:47:28,440
going to talk about this channel the

1063
00:47:24,358 --> 00:47:30,880
capital accumulation Channel and in the

1064
00:47:28,440 --> 00:47:32,960
lecture after the spring break we're

1065
00:47:30,880 --> 00:47:36,400
going to talk about shift in the

1066
00:47:32,960 --> 00:47:38,318
function f so in in in in

1067
00:47:36,400 --> 00:47:40,760
figures

1068
00:47:38,318 --> 00:47:43,199
so fixing the technology that this is

1069
00:47:40,760 --> 00:47:45,480
the function f is fixed and you just

1070
00:47:43,199 --> 00:47:48,279
move K Over N this is the picture you

1071
00:47:45,480 --> 00:47:51,000
have now that's a produ this I'm

1072
00:47:48,280 --> 00:47:55,079
plotting this function here as a

1073
00:47:51,000 --> 00:47:57,559
function of k/ n for a fixed function f

1074
00:47:55,079 --> 00:48:00,318
and that's what you get so output per I

1075
00:47:57,559 --> 00:48:02,160
have here Capital per worker and output

1076
00:48:00,318 --> 00:48:05,400
per per

1077
00:48:02,159 --> 00:48:06,838
worker and you see that obviously it's

1078
00:48:05,400 --> 00:48:08,240
in an increasing function the more

1079
00:48:06,838 --> 00:48:10,199
Capital per worker you have the more

1080
00:48:08,239 --> 00:48:13,799
output per worker you'll

1081
00:48:10,199 --> 00:48:13,799
produce but it's also

1082
00:48:13,920 --> 00:48:17,318
concave why is it

1083
00:48:19,559 --> 00:48:25,559
concave that's decrease in returns to

1084
00:48:21,760 --> 00:48:28,000
Capital is look for any when you have

1085
00:48:25,559 --> 00:48:30,040
very little Capital per work

1086
00:48:28,000 --> 00:48:31,519
a change in capital per worker gives

1087
00:48:30,039 --> 00:48:33,800
gives you a big jumping output per

1088
00:48:31,519 --> 00:48:35,239
worker because you know there was sort

1089
00:48:33,800 --> 00:48:36,760
of very little Capital that was the

1090
00:48:35,239 --> 00:48:39,318
problem of that

1091
00:48:36,760 --> 00:48:42,800
economy when the economy has more and

1092
00:48:39,318 --> 00:48:44,880
more Capital the same change in capital

1093
00:48:42,800 --> 00:48:47,519
leads to a much smaller change in output

1094
00:48:44,880 --> 00:48:49,599
here at this level when when Capital per

1095
00:48:47,519 --> 00:48:53,798
worker was very low the economy was very

1096
00:48:49,599 --> 00:48:56,798
poor then this change LED to this change

1097
00:48:53,798 --> 00:48:59,480
in output per capita at this level of

1098
00:48:56,798 --> 00:49:01,358
wealth if you get as capital economies

1099
00:48:59,480 --> 00:49:04,400
with higher Capital are richer Capital

1100
00:49:01,358 --> 00:49:06,199
per worker the same change this change

1101
00:49:04,400 --> 00:49:08,079
is of the same size as that leads to a

1102
00:49:06,199 --> 00:49:10,558
much smaller change in

1103
00:49:08,079 --> 00:49:13,559
output okay and that's a result of

1104
00:49:10,559 --> 00:49:15,640
decreasing returns to

1105
00:49:13,559 --> 00:49:16,720
Capital and that's the other option

1106
00:49:15,639 --> 00:49:20,078
again that's what we're going to talk

1107
00:49:16,719 --> 00:49:21,519
about in the next lecture this this one

1108
00:49:20,079 --> 00:49:24,000
and two lectures from now we're going to

1109
00:49:21,519 --> 00:49:25,519
talk about growth that comes from shift

1110
00:49:24,000 --> 00:49:27,440
in the production function this

1111
00:49:25,519 --> 00:49:32,679
technological progress

1112
00:49:27,440 --> 00:49:32,679
okay very good see you on Wednesday