Explain five ways that the world is globalising, plus “first” and “second” waves.

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How do researchers attempt to untangle the factors that contribute to economic growth and development?

May 5, 2018

What should the government do if the price as determined by the free market for essentials like housing and food, if the free market price is too high for many people to afford?

May 5, 2018

Week 2: The process of development, why simplifying a complex process of development is useful, and how is evidence used to support/contradict theories of growth?

Course objective

Provide you with a set of historical facts to provide context to debates about growth and globalisation.

Learn some of the core and contemporary theories and learn the “language of economics”. This will help you when conducting your own research.

Foster a critical mindset about how to interrogate theories and evidence for/against them, and an appreciation of details!

Simulate an interest in economics.

Recap

Malthusian trap

GDP invented – correlates with many “well-being” measures

Use of Log transformation for charts – what does it do?

Five ways that the world is globalising, plus “first” and “second” waves.

Convergence not the norm, hence the interest in Asian tigers

Global inequality pattern – elephant chart

What now?

Why is it useful to simplify a complex process of development with simple theories?

How is evidence gathered to support/contradict theories of growth?

Ultimately seek to be able to create informed policy to get what we want in terms of growth, well-being and international trade outcomes.

No shortage of candidate explanations. Are there other ‘factors’ or ‘causes’ of growth and development people have heard?

Proximate cause: Because the ship failed to change course to avoid it.

Ultimate cause: Because the ship was under autopilot and the autopilot’s data was inaccurate.

(even stronger): Because the shipwrights made mistakes in the ship’s construction.

(stronger yet): Because the scheduling of labor at the shipyard allows for very little rest.

(in absurdum): Because the shipyard’s owners have very small profit margins in an ever-shrinking market.

Why did the ship hit the rock?

Ultimate causality

Some ultimate reason for biological existence

Geography lent itself to domestication of plants/animals by humans leading to larger tribes (Jared Diamond)

War selected better organised tribes and those with better war technology (Peter Turchin + Jared Diamond)

Winner are those with better “institutions” and “technology”

Repeat.

Society is complex

Societies are the emergent outcomes many individual interactions and feedback loops arising from them.

They are not linear.

We have to accept that many factors could lead to growth, and that each will apply in particular circumstances.

Some factors can independently help (substitutes), others work in conjunction (complements – one only works with the other).

Examples of substitute and complementary policies –

Complementarities

For example, if there is no road access to a village, then people can’t travel to access healthcare, teachers can’t get to schools in order to teach and farmers can’t get their goods to market.

Improving the clinic in the nearby town, or paying teachers extra to show up on time, or creating a mobile phone price information system, has little impact, because of the constraints of the existing infrastructure.

On the other hand, building the road doesn’t, in itself, improve the clinic, change incentives for teachers, or resolve agricultural market failures.

http://www.fight-entropy.com/2011/07/complementarity-in-economic-development.html

Example

We think that education independently causes growth. In other words, in the absence of any other change made, a region that increases education inputs has higher overall growth.

It’s a plausible story. Smarter people are better able to invent new and more productive ways of doing things and are able to make better use of capital (like computers, vehicles, machines, etc). Focussed input has broad output.

How do you know if simply adding more ‘education’ into a country/region works?

Untrained workforce

Lack of education

Economic decline

Low investment and productivity

More skilled workforce

More education

Economic improvement

Higher investment and productivity

From this

To this

But still not really clear?

A thought experiment

The highly educated German people (83mill) move to West Bengal, while the West Bengalese (92mill) move to Germany.

Will this radically increase GDP in West Bengal and lower it in Germany because of the transfer of “human capital”?

Germany GDP per capita is 30x that of West Bengal.

Alternatively, add even more doctors and engineers to Cuba.

Causality

Actually a really tricky concept.

Proximate causes seem easy to identify. For example, more teachers and schools, plus compulsory schooling, lead to more education.

But what causes more teachers and a public policy decision to make schooling compulsory?

And so on…

Untrained workforce

Lack of education

No funds for school

Economic decline

Low household incomes

Low investment and productivity

Skilled workforce

Increased education

Pressure to fund public schools

Economic growth

Payoff to schooling

High investment

and productivity

High returns

to investment

More capital

investment

Economies of

scale

Competitive

exports

Skilled workforce

Increased education

Economic growth

High payoff

to schooling

High investment

and productivity

High returns

to investment

More capital

investment

Economies of

scale

Competitive

exports

Depress

exchange rate

Subsidise desirable

investments

Use public agency

to make desirable

investments

Create public

school system

How to untangle

Seems like at first glance that doing what rich countries do in any loop will work. But the question is what constraint is binding?

Your car engine is not starting. It needs fuel, air, and heat for combustions. If you have fuel and air, but no heat, the heat is the binding constraint – adding more of the other “ingredients” won’t help!

Finding the binding constraint for different regions and addressing that first is the basis of Hausman, Rodrik, Velasco’s “Growth Diagnostics” approach. No “one size fits all”

http://siteresources.worldbank.org/INTDEBTDEPT/Resources/468980-1218567884549/mindbook.pdf

Traditional Methods

Cross-country panels Take longitudinal data from a number of countries/regions, and look to find the common patterns that correlate with high growth, controlling for as many other factors as possible.

Growth accounting Decomposes growth in terms of the amounts contributed by the accumulation of physical capital of various sorts, human capital of different kinds and labor (talk more in Wk 4). More limited for practical use.

Example

Barro, R. (2003). Determinants of Economic Growth in a Panel of Countries. Annals of Economics and Finance. 4, 231–274

What about number of years as open economy? Could that be spurious and simply catch the already rich countries which growth faster except in rare cases of convergence?

Likelihood of GDP in mining being above 95% depends on weighting the summation of likelihood distributions.

http://www.ecostat.unical.it/aiello/didattica/economia_Crescita/CRESCITA/CRESCITA_Sala-i-Martin-AER-1997.pdf

Magic happens

More Confucians, Buddhists,

Catholics, or Protestants?

Economic growth

Social stability

High returns

to investment

More capital

investment

Don’t export

primary products

Something?

No financial

sophistication measure

No education measure

No scale effects

(population growth weak

-ve correlation)

Growth accounting

The contribution of a factor to total growth is its rate of growth weighted by the share of national income accruing to that factor.

Has a history in traditional economic theories of “land, labour, capital”, and a data gathering method developed in National Accounting systems.

Y = A f(K, L, Z)

%∆A = %∆Y — (capital share x %∆K) — (labour share x %∆L) —

(other factor share x %∆Z)

A is the residual (often called technology, but is everything non-labour, capital, or land)

Example

Growth Factor Share
Land 1% 10%
Labour 2% 60%
Capital 2% 20%
Output (GDP) 3%

How much of total growth is caused by

Increase in labour

Increase in capital

Multifactor productivity?

Better methods

Natural experiments Use naturally occurring randomisation to test for the marginal impact of certain policies.

Randomised controlled trials (RCTs) Implement a policy with a random component to create an identifiable and traceable treatment and control group.

Case studies In depth analysis of finer details of policy implementation in certain regions to help tease apart mechanisms of effect.

Natural experiments

“Since many vouchers were awarded by lottery, we use a quasi-experimental research design comparing educational and other outcomes of lottery winners and losers.”

“Lottery winners scored just over 0.2 standard deviations more than lottery losers, though this difference is (not surprisingly, given the small test sample) only marginally significant.”

Follow up test was 3yrs after the program.

How would you critically analyse this in terms of development? Sure, you can improve relative test scores, but not everyone can be high paid.

RCTs

Help decipher effects in small parts of the big causal picture.

Also called “field experiment”. Usually done in poorer countries.

“The reform changed the traditional fund ow practice by instead conditioning fund disbursement for wage payments on incurred expenditure as re ected in worker detail entry on a new electronic platform. This reform reduced the number of administrative tiers associated with wage disbursement and changed the informational requirements for requesting and disbursing program funds. We nd that program expenditure and reported employment declined by 25%, but with no discernible impact on actual employment as measured by independent surveys.”

https://economics.mit.edu/files/10565

Case studies

Japanese institutional reforms after WWII that led to one of the largest reductions in inequality in human history.

In week 8 we will read this case.

Case studies help to unpick some of the proximate causes, then compare them between cases to look for commonalities.

https://press.princeton.edu/titles/10921.html

Limits of evidence

RCTs can’t really help understand the effect of public goods, since they are non-excludable.

Failure of RCT does not help to understand why it failed, nor does the success help understand why it worked (and how translatable it is to other circumstances)

Mix of evidence of different types provides more confidence about the reality of a relationship, particularly a causal one.

How to approach evidence critically

What evidence do they have?

Are they making claims of causality?

Is there a plausible alternative explanation? (Does it pass the “sniff test”?)

How complete is the mechanism it describes?

Example

Export promotion programs — do they help a country to increase economic growth through “export discipline”?

“we partnered with a US-based non-governmental organization (NGO) and an Egyptian intermediary to secure export orders from foreign buyers through trade fairs and direct marketing channels.”

http://cdep.sipa.columbia.edu/sites/default/files/cdep/WP%2023%20-%20Atkin.pdf

Evidence

RCT with rug manufacturers in Egypt. Treatment encouraged take up of export orders.

“we asked all firms in our sample to manufacture an identical domestic rug using identical inputs and a common loom in a workshop that we leased (a “quality lab”). The rugs that treatment firms produce received higher scores along every qual- ity metric and were more accurate in terms of the desired size and weight; moreover, treatment firms do not take longer to produce these rugs despite their higher levels of quality.”

Causality

Claim causal chain is: Exposure to export markets -> Discipline in quality and price -> Learning -> More profits

Research also finds that there is no “spillover” of skills from exporters to other rug makers, as their quality does not improve.

Sniff test

Did the exporters just get more orders then hire the best staff from other firms?

Were they always able to make better rugs but didn’t because they did not have high-price buyers?

Mechanism

Claim concerns “learning by doing” with the mechanisms identified involving feedback from more discerning international buyers.

Increasing output might involve some scale effects.

 

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