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Macroeconomics: Unit 3, Productivity 0 Views
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Transcript
- 00:01
no macro economics Allah shmoop productivity All right people you
- 00:08
sit down to write your final paper You've got one
- 00:11
hand on your keyboard and the other on your well
- 00:13
extra large coffee mug there But you can't bring yourself
- 00:17
to start writing You spend hours just staring at the
Full Transcript
- 00:20
screen with your fingers doing you know that awkward dance
- 00:24
Then there's a ding like that Yu check yur Facebook
- 00:28
notifications and you're sucked into the vortex of finding out
- 00:32
which friends character you are Well there's no escape Your
- 00:35
productivity just tanked And you khun say goodbye to finishing
- 00:39
your paper You can always retake the course next year
- 00:42
which is such a phoebe thing to dio All right
- 00:44
you measure your own writing productivity in words Words per
- 00:47
minute words per hour Words per day Well guess what
- 00:51
Economist meter and or measure the productivity of an economy
- 00:55
more or less the same way by looking at the
- 00:57
volume usually in dollars of output each unit of an
- 01:01
input produces All right How do we say that in
- 01:04
English Well how many cars can given person working one
- 01:08
day at an auto manufacturing company produced how many coffees
- 01:11
work of beans Can the new grindr churn out per
- 01:14
day How many balloons gloves and condoms on a gallon
- 01:19
of latex make productivity of latex Yeah well the big
- 01:22
driver in most economies is the deployment of capital Resource
- 01:26
is I mean machines that cost a lot and then
- 01:29
you know produce a lot And generally speaking the more
- 01:32
tech savvy the machine on the more productivity it produces
- 01:36
Well economists breakdown productivity into a couple of different structured
- 01:40
metrics The Bureau of Labor Statistics reports all kinds of
- 01:43
data relative the labors productivity in the previous period usually
- 01:47
1/4 like 13 ish weeks This measurement quantifies the productivity
- 01:52
of all workers across all industries in an economy I'II
- 01:55
super general and broad Well that stat is found by
- 01:59
measuring the ratio between the value of all the goods
- 02:02
and services produced a VP and the total hours humans
- 02:07
worked to produce those goods and services Why the little
- 02:12
snarky humans thing in there Well because yeah like we've
- 02:15
noted a revolution in labor is taking place today that
- 02:19
will rival that of the Industrial Revolution of the 19th
- 02:22
century Because Computer Power's gotten Sochi and standardized well robots
- 02:28
have gotten sheep as well and smart And very soon
- 02:31
the skill set of a basic burger flipping worker will
- 02:34
become economically replaced by robots and a mass dislocation of
- 02:39
the usefulness of the lower end of the labor force
- 02:43
Will for society to do some heavy thinking about what
- 02:46
it does for the unskilled want to work but aren't
- 02:49
talented enough Workers Yeah well the data here for labor
- 02:54
productivity presented is for non farm business Why Why nonfarm
- 03:00
What do they have against Farm's Well many farms employ
- 03:03
migratory laborers and undocumented immigrants Records may be absent because
- 03:10
workers were paid in cash to keep things you know
- 03:12
off the books And the industry in general operates with
- 03:15
different structures and pricing pressures than most urban businesses Labor
- 03:20
productivity therefore is often reported for farm and then for
- 03:24
non farm business payrolls Separately we'll labor productivity doesn't just
- 03:30
vary by industry Certain groups and types of people are
- 03:33
more productive than others After an earthquake in the late
- 03:36
19 nineties much of the U S Highway 10 that
- 03:39
thing in L A There it is was destroyed well
- 03:43
To rebuild the roads union workers would have required 144
- 03:47
people per freeway mile while nonunion workers found a way
- 03:52
to do it with just 89 people Will the labor
- 03:55
per dollar of the average nonunion worker was higher than
- 03:59
a union workers because they don't need the layers of
- 04:02
support bureaucrats Which is to say that they can pour
- 04:05
their own coffee They can fill out their own time
- 04:08
sheets They can click on their own for a one
- 04:10
K investment choices and so on Productivity can change over
- 04:15
time as well and not just because everyone decides that
- 04:18
now they have to hunker down and really start churning
- 04:20
products out Advancements in technology investments in better and more
- 04:25
efficient plants and equipment and better management and organization all
- 04:30
improve productivity Well one thing Cos Evaluate is marginal productivity
- 04:35
Like for each incremental unit of labor What do I
- 04:38
get for each incremental unit of capital What do I
- 04:42
get Okay so all this brings us to total factor
- 04:46
productivity or T f p or All right So what
- 04:50
is this factor thing And that we're now adding like
- 04:52
Max factor the makeup No more like the X factor
- 04:58
Total factor productivity also called the solo residual spell it
- 05:03
no relation Hans represents changes in productivity caused by better
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tech and different organizational strategies So basically it has to
- 05:11
do with the process of production rather than the inputs
- 05:14
Create a more efficient process and you'll be able to
- 05:18
use your resource is better I e make more with
- 05:21
less And yes Henry Ford's assembly line People were looking
- 05:25
at you Yeah it was a big innovation back then
- 05:27
Well you can picture how all this works with technology
- 05:30
like Well say your boss wants you to write a
- 05:33
report about a location where the company might open a
- 05:35
new store Well the 1958 you'd have to go to
- 05:38
the library Look up Demographic stats In a book you
- 05:41
might have to call around various agencies to get data
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Wait for everyone to call you back Once you have
- 05:45
your research you type it up on a manual typewriter
- 05:48
You know one of these old fangled contraptions If you
- 05:51
wanted to edit something or add something well you'd have
- 05:53
to re type the whole thing That's going to create
- 05:55
enough documents to give everyone for the next meeting Well
- 05:58
you have to go to a printer and get copies
- 06:00
made by an expert Well nowadays you can do all
- 06:03
your research online Type it up on a word processor
- 06:06
is Aaron while just email copies to everyone like right
- 06:09
there much more efficient And you Khun get several reports
- 06:12
done today in the time it took you to generate
- 06:15
on Lee maybe one in 1958 Well there are other
- 06:19
ways to squeeze out additional productivity other than via technology
- 06:23
or at least this kind biz School grads loved to
- 06:26
come up with a handy dandy How to guides to
- 06:28
streamline business Here's a particularly famous example of one of
- 06:32
these processes meant to boost productivity Thie agile development cycle
- 06:38
Yeah we use it here tomorrow It's a six step
- 06:40
framework for teams working on projects together to streamline their
- 06:43
processes And there are not surprisingly six steps Yes denial
- 06:48
anger bargaining different first plan then you designed Then you
- 06:53
develop Then you test then you evaluate Then you meet
- 06:57
all that simple right well But every Silicon Valley startup
- 07:00
manager and their mother uses this workflow process to increase
- 07:04
productivity and efficiency The idea is to lay out the
- 07:06
process in discreet steps so that everything is as clear
- 07:10
as possible Otherwise it becomes and disorganized Hot project Yeah
- 07:14
it's kind of like when you do laundry like the
- 07:17
people in Silicon Valley don't want to end up you 00:07:20.311 --> [endTime] know losing socks that's what we do
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