Lant Pritchett's presentation - OECD - PGD Expert Meeting

1. The feasibility and potential
impacts of free human mobility
Lant Pritchett
Harvard Kennedy School and Center for Global Development
Feb. 24, 2015
At
OECD first expert group meeting:
Perspectives on Global Development
International Migration and Development

2. Outline
• What would we expect the impact to be? A
dizzying and dazzling tour of caricatures of
different theories of cross-national income
• What do we find the marginal impact to be:
– Micro-economic estimates
– Macro-economic estimates
• How does labor mobility affect the “A” of
growth theories?

3. Massive cross national inequality: incomes from
all of modern history exists in countries today

4. More inequality, and more of it dues
to location

5. The (statistically) rich of poor countries
are poorer than the poor of rich
countries

6. Branko Milanovic’s 21st century
trilemma
We are connected instantaneously by internet and cell phone with, and are
only a 6 ½ hour flight from Paris to, countries with levels of per capita
income last experienced in the West in the Middle Ages—even a country like
Morocco has a level of income lower than prior to the Franco-Prussian war.

7. What we expect the impact of human mobility to be?
Depends on our explanation of why incomes are
different
Manna from Heaven (Modern) economic production
Endowed with natural
resources that yield
income—either
concentrated (oil,
diamonds, gold, copper) or
diffuse (wheat, rubber)—
with just sector specific
institutions (e.g. enclave)
and effort (fixed assets—
e.g. holes in the ground)
Example: Kuwait is rich
because it has low marginal
cost oil
Stuff (K, HK) plus A as
“technical knowledge
“A” as “institutions” or
“capabilities”—tacit, non-
transferrable, augmenters
of productivity
(Augmented) Solow model
with “capital” and “human
capital” and an “A” term
interpreted as “technology”
or “blueprints” or “codified
knowledge”
“Institutions” (of the right,
creative destruction
inclusive market
supporting) type are the
causal key to prosperity
(e.g. AJR, NWW, RS)
A large number of
“Capabilities” as non-
tradable collective inputs
that require tacit
knowledge is key to
prosperity (Hausmann)

8. In rich “manna” countries migration welcome—
as long as no manna for (most) migrants
On mover On host country On sending country
Mover gets access
to manna
Moves to more
manna—better off
Less manna per
person—worse off
More manna per
person—better off
Mover has access
to manna in home
country does not
get access to
manna in host
country
Mover only moves
if wages/incomes
are higher in
modern sector are
higher
Doesn’t have to
share manna—
depends on impact
on modern sector, if
manna is abundant
(manna/person>
reservation wage)
then host better off,
indeed rely on
migrant labor (e.g.
Gulf States) for
both unskilled and
skilled labor
More manna per
person—better off
(or with only
consequences on
modern sector)

9. General approach of augmented Solow-Swan or
“neo-classical” growth model
• A is T—the “A” of the production function was “knowledge” that was
common to all countries (e.g. laws of physics) and/or would diffuse rapidly
across borders so technical progress was a global externality
• K and HK as stocks had to be accumulated by savings/investment today for
higher stocks tomorrow and hence growth dynamics were driven by
capital(s) accumulation dynamics
• Wage differences across countries driven by HK differences did not lead to
migration motivation (“skill price” equalized across countries with same A
and K/L
• If K/L drove higher wages then migration had “dilution” effects as workers
arriving with no capital drove down average K/L.
• If A(T) converged and capital markets worked then incomes and wages
should converge (with dynamics driven by investment) and no need for
labor mobility to equalized incomes.
• (Plus models with trade and “factor price equalization” by exchanging
goods which embody different K/L ratios equalize w and r via trade)

10. Nearly everything about neoclassical model as
model of “development” is wrong
• There hasn’t been (much) convergence across countries and over the long-
horizon massive divergence (Pritchett 1997, Milanovic 2012, Bourginon
and Morrison 2002)
• This is in spite of massive convergence in K and HK (Grier and Grier
2007)—so rather than A(T) rapidly converging and convergence dynamics
limited by K and HK dynamics A (measured as residual) has been (until
perhaps recently) diverging (e.g. Bosworth and Collins ).
• Empirical growth decompositions find that K and HK account for a quarter
to at best a third of cross-national differences even as proximate
determinants (Casselli 2005, Inklaar and Timmer 2013) (and if K and HK
are endogenous to A(I) or A(C) then causally even less)
• The price dynamics of interest rates are wildly inconsistent with equalized
A and K dynamics (King and Rebelo 1989) and MPK appears to be already
equalized (Casselli and Feyrer 2007)
• Factors flow to rich areas (Easterly and Levine 2001)

11. Two new models of what the “A” is that makes
equivalent L, K and HK more productive
“Institutions” (A is I)
• “Institutions” (Acemoglu,
Johnson, Robinson (2000), North,
Wallis, Weingast (2012) or “social
infrastructure” (Hall and Jones
1999) account for the bulk of the
differences in cross-national
income
• “Institutions” are “norms” or
“patterns of behavior” that
structure relationships among
actors and “market supporting”
institutions that are restraining
on the “grabbing hand” and
“inclusive enough” for creative
destruction are needed
“Capabilities” (A is C)
• “Capabilities” (Hausmann and
Hidalgo 2009, Hausmann et al
2011) are the key to prosperity
• “Capabilities” can be generated
from a product specific Leontief
production function with many
inputs and “simple” products
require few inputs and “complex”
products many inputs so
countries with many available
inputs—including collectively
produced inputs (like public
goods, infrastructure, rule of law,
specific policies)—are able to
produce complex products

12. Levels of GDP per capita and
“institutions”

13. Higher “economic complexity” as a measure of the
countries sophistication of exports in the product
space is highly correlated with level of GDP
Source: Hausmann et al 2011
“Manna” countries
(nat’l resource exports>
10% of GDP)
Non-resource
exporters
GDP per capita
Economic Complexity of Exports

14. What would we expect to see at the margin if A
as I or A as C explained most cross-national
income/labor productivity/wage dispersion?
Growth model of
A as I or A as C
drives levels
For movers For host countries For sending
countries
A (I or C driven) is
place/country
Specific,
determines the
productivity of all
factors, and is fixed
at the margin
Massive wage gains
for movers as their
labor productivity
(for given HK) is
place dependent
and the additional
productivity is “in
the air” (of I and C)
and hence rapid
and near complete
wage convergence
for given skills
(including
language)
Almost no impact at
all as at the margin
“A” as I or C is fixed
and public good
(non-rival and non-
excludable)
Some relative price
impacts on types of
L and HK and K
depending on
whether migrants
are substitutes or
complements
Almost no impact at
all, for the same
reason.

15. What properties the new A as “institutions” or
“capabilities” has to have (versus the old A as T)
Properties of the new A
• “A” does not diffuse rapidly
across national borders
(perhaps not even regionally if
“capabilities” are place specific
due to IRS)
• “A” has a dynamics in which
“poverty traps” are possible
(lower A leads to less growth of
A)—versus “advantages of
backwardness” dynamics
• “A” capable of reversals within
countries in which “A”
deteriorates
Facts to accomodate
• Long-run historical and post
war divergence across
countries not due to factors
• Countries in long-run
poverty/slow growth traps
• Massive and sustained
reversals in output per worker
at same (or rising) K and HK
inputs (Liberia, Venezuela,
Cote d’Ivoire, Zambia (‘67-’94))

16. We see in the data exactly what we expect to
see based on A as I or A as C macroeconomic
theories of income (or manna)
• Microeconomic estimates of wage gains
– Data on observational equivalent workers
– Data on differences across occupations
– Experiments (and quasi-experiments)
• Macroeconomic
– Modeling
– Experiences

17. Wages of observationally equivalent
workers between USA and 41 other
countries
Wages
Worker characteristics
(e.g. schooling, residence, age)
USA born, educated
Workers in USA
Foreign born, foreign educated
workers in USA (wage profile
estimated with US Census)
Foreign born, foreign educated
workers in foreign country
(estimated with country data)
Place premium:
Same worker
characteristics
(for all available
observables)
just different
places
X

18. Estimated average wage differences of observationally
equivalent low skill (9 years schooling), urban, male, formal
sector, young (35 year old) workers between USA and source
country is (PPP adjusted) $15,000 a year
Simple arithmetic for 35
year old, male, urban,
formal sector, 9 years
of schooling:
Wage in Haiti: 80 cents/hr
Wage in USA: $8.25 /hr
Annual hours 8hrs/day,
22/days month, 12
months year:
(8.25-.80)*
(8*22*12)=$15,738
Average (of 41 countries):
Wage in foreign: $2.53
Wage in USA: $9.83
Annual wage gap:
$15,411
0
5000
10000
15000
20000
25000
Haiti
Ghana
IndonesiaBangladesh
Guatemala
Annualeanrings(inPPP)
In home
In USA

19. Wage gap is absolutely higher the more
education (if the proportionate return to
schooling is the same in both markets)
Table 1: Estimates of the annual gain in earnings from moving to the USA for a typical
male wage earner from a sample of 41 developing countries
Estimates 9 years 12 years (assuming 10
percent Mincer return)
Observationally equivalent, 100 percent of
spending in USA (PPP adjusted)
$15,298 $20,361
Observationally equivalent, adjust “real”
consumption wage upward for 40 percent of
spending in home (remittances or savings) at lower
prices $23,130 $30,785
Adjust downward by 1.25 (maximum empirically
demonstrated positive selection of low skill
migrants on unobserved characteristics) with 40
percent spent at home
$18,504 $24,628
Source: Based on Clemens, Montenegro and Pritchett 2008

20. The observed wage gap across countries for
workers in the same occupation is higher for
medium skill (construction workers) than low
skill (waiters)
$13,111
$34,824
$0
$5,000
$10,000
$15,000
$20,000
$25,000
$30,000
$35,000
$40,000
$45,000
Waiters Construction workers
Annualizedearnings,inPPP
Wage in bottom 30 reporting countries in
OWW (in PPP)
USA reported wages
Gap between bottom 30 and USA
Source: Pritchett and Smith, forthcoming, based on OWW data (Oostendorp, 2013)

21. Gains from temporary Tonga-New Zealand
migration for agriculture—using lottery to
control of selection
$7,509
$26,381
$18,872
$0
$5,000
$10,000
$15,000
$20,000
$25,000
$30,000
Applicants earnings in Tonga Estimated earnings (using lottery
outcome for identification)
Migrant gain (corrected for selection)
Annualized(52week)earningsinUS$
McKenzie, Gibson and Stillman, 2010

22. Temporary workers on H-1B visas. Exchange-rate dollar annual wage differences for observably and unobservably identical workers producing seamlessly tradable good (software)
interpreted as productivity differences. Source: Michael A. Clemens, 2013, “Why Do Programmers Earn More in Houston than Hyderabad? Evidence from Randomized Processing of
U.S. Visas”, American Economic Review Papers & Proceedings, 103 (3): 198–202.
Computer programmers (India to US)—
identified from random access to US visas
0
20000
40000
60000
India US
Annualwage(employed),XRUS$

23. Temporary workers on 3-year labor card. Exchange-rate dollar annual wage differences for observably and unobservably identical workers, who remit about 85% of these earnings to
India, spent at Indian prices. Source: Michael A. Clemens (2015), “Household effects of temporary low-skill work visas: Evidence from the India-Gulf corridor”, Working Paper,
Washington, DC: Center for Global Development.
Construction workers (India to Gulf)
0
1000
2000
3000
4000
5000
India UAE
Annualwage(employed),XRUS$

24. Experiment: Tonga-New Zealand seasonal
mobility for agricultural work with applicants
chosen by lottery
$7,509
$26,381
$18,872
$0
$5,000
$10,000
$15,000
$20,000
$25,000
$30,000
Applicants earnings in Tonga Estimated earnings (using lottery
outcome for identification)
Migrant gain (corrected for selection)
Annualized(52week)earningsinUS$

25. What should be completely uncontested at this
point based on our “best available” theories and
evidence
• Macro/growth: Most of (upwards of 2/3) of differences in
productivity per worker across countries in the world are driven by
“in the air” elements at the national level which diffuse only slowly
and can be stuck or reverse
• Micro/wages: The annual wage/labor productivity gain to a low
skill (<=12 years schooling) worker from moving from a poor
country to rich country of unskilled laborers is P$10,000-P$30,000
per worker—factor multiples (4 to 5) of earnings in their home
country—and higher for richer workers
• Legal barriers to mobility imposed by rich countries prevent people
from moving in response to these potential gains.
• At the margin (e.g. “A” unchanged) labor mobility has small net
positive impacts on the recipient countries with also small
distributional impacts on citizens—and possibly, depending on
structure, eligibility, etc. some fiscal issues.

26. Open Borders and the Pushback to
Open Borders
• One can do calculations
of the total gains from
free labor mobility
• If one assumes that
country “A” is
unaffected by
population mobility the
gains are in the tens of
trillions—a rough
doubling of global GDP
109.25
1.2
0
20
40
60
80
100
120
Median of 4 estimates
of complete labor
mobility
Median of 7 estimates
of policy barriers to
merchandise trade
GainaspercentofworldGDP

27. The key question about the gains from open
borders is the responsiveness of the new “A” to
flows of migrants
Change in country specific A
(as T? as I? as C?)
Some measure of the stock
of migrants (weighted by
characteristics)
One (default) theory:
Invariant
Collier/Borjas
conjecture:
Threshold effect after
which host country A
starts to converge to
sending country A
?
Immigrants good
(up to a point)

28. What is a red herring and what is a red
flag?
• For marginal increases in the rate of labor mobility this is a
complete red herring—unless and until one is at the threshold—
and there is no evidence there is a threshold, much less than any
OECD country is near it
• For “temporary” schemes this is a red herring—the Gulf states and
Singapore have migrant/citizen ratios over 1 (>50 percent migrants)
and have not detectable impact on A
• The argument: “a stock of politically and institutionally relevant
migrants that passes a threshold may deteriorate the market
supporting institutions that create high productivity hence
estimates of ‘open borders’ are exaggerated” has ceded the day to
all policy relevant arguments as no one is talking about “open
borders” as a near term policy or political agenda—just “relaxation”
of existing controls.

29. High immigration OECD countries are
at levels of 20 percent or more
0
5
10
15
20
25
30
Foreignbornaspercentofpopulation

30. Order of magnitude variation across
US states—is Montana doing better on
“institutions” than California or Texas?

31. Lets distinguish sophisticated economic
arguments from garden variety xenophobia
(which may be politically powerful)
Cultural norms
• How people dress , worship,
celebrate New Years, marry,
socialize
• What actions are
“honorable” or
“dishonorable”
• How “inside” and “outside”
the relevant social unit are
treated
Market supporting norms
• Restraints on arbitrary
action of governments—
including ‘rule of law”
• Legal arrangements that
allow making and enforcing
private contracts and
“thick” financial sectors
• “Markets” that allow liberty
people and firms to engage
in arms-length transactions

32. “Culture” as determinant of incomes:
Largely Claptrap
North and South Korea at night:
culture?
Why “culture” doesn’t work well to
explain per capita income differences
• Argued as barrier against many
countries—just before they have
dramatic acceleration: Japan (Meiji),
Russia (pre-revolution), China (pre-
Deng)
• Measures like “trust” are endogenous
and culture adapts (e.g. Fiji)
• Migrant communities succeed even
while host country is poor: Indians,
Chinese
• Clear examples of common culture,
different outcomes
• Singapore higher GDP per capita than
any (non-manna) Western country

33. Elements of a model of “threshold”
impact of stock of migrants on “A”
• Norms are properties of places, not
individuals, and individuals understand that.
• Not “cultural” norms by “market supporting
norms”—the entire point of market
supporting norms, especially norms
formalized into organizations and laws, is to
allow people to transact who don’t share
cultural norms.

34. Elements of the “immigrants erode
institutions” argument
• People who choose to move may seek out places
with the desire to adopt the new norms
• People who move may choose to adopt
compliance with the “market supporting”
norms—even perhaps internalized them—if not
immediately then over time—the speed of
“assimilation” (not “cultural” but “market
supporting”)
• If people move from lots of different norms this
may not create any impetus to switch to a new
norm

35. A theory about “A as I” needs to reflect the
“pressure on I” from migrants, not “migrants”
Threshold of “pressure”
Stock of migrants,
Pressure on A from stock
Rapid expansion, little assimilation/internalization,
concentrated migrants
Pressure on market support
institutions that sustain high
productivity
Time

36. A theory about “A as I” needs to reflect the
“pressure on I” from migrants, not “migrants”
Threshold of “pressure”
Stock of migrants,
Pressure on A from stock Slower increase in stock
Depending on pace of immigration versus
assimilation/internalization, initial gap,
concentration, etc. even huge stocks of “foreign
born” are compatible with never reaching
threshold pressure on institutions
Time

37. It’s the stupid politics stupid
• The economics of the benefits of greater labor mobility are,
at this stage, largely uncontested: at the margin gaps in “A”
that are “in the air” produce massive (PPP$10,000 to
30,000 per mover) gains in labor productivity with little
impact on citizens (on aggregate, positive)
• The push back on “general equilibrium” effects on A: (1)
cedes the field on the policy relevant issues, (2) is, at this
stage, a completely empirically unsupported conjecture
• The politics of migration hinge almost entirely on cultural
arguments, which have enormous political traction but
which are enormously intellectually problematic as “just”
or “legitimate” grounds for discrimination