FACULTE DES HAUTES ETUDES COMMERCIALES DE L'UNIVERSITE DE LAUSANNE
Mid-term exam
with suggested answers
Professeur :
Olivier Cadot
Matière :
Session :
Globalization and
development
Fall 2015
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Duration : 3 hours
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No documentation

No calculator
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Exam is 9 pages long

Please return the exam questions with your answers

Multiple-choice questions have only one correct answer, and there is
no penalty for wrong answers.

If you are stuck on one question, do not panick ; just move on to the next.
Make sure you keep some time to re-read your answers at the end of the
exam.
Name, first name
Matricule #
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Seat #
Grade
Question 1
Consider the following tables of regression results for Tunisia’s export-promotion program,
FAMEX. The effects were estimated at the firm level using data from 2000 to 2009.
Table 1: FAMEX treatment effects estimated by DID without matching
Forwarding degree
Estimator
Outcome
Total exports
R-squared
Nb. destinations
R-squared
Nb. products
R-squared
TY (k = 0)
OLS
(1)
TY+1 (k = 1)
OLS
(2)
TY+2 (k = 2)
OLS
(3)
TY+3 (k = 3)
OLS
(4)
TY+4 (k = 4)
OLS
(5)
TY+5 (k = 5)
OLS
(6)
0.774***
[0.187]
0.550
0.890***
[0.204]
0.552
0.445**
[0.220]
0.551
0.600***
[0.227]
0.551
0.519*
[0.282]
0.544
0.852***
[0.290]
0.551
0.338***
[0.033]
0.413
0.355***
[0.033]
0.417
0.323***
[0.037]
0.416
0.288***
[0.036]
0.417
0.305***
[0.043]
0.412
0.353***
[0.045]
0.418
0.290***
[0.039]
0.414
0.285***
[0.041]
0.415
0.240***
[0.042]
0.415
0.230***
[0.044]
0.414
0.265***
[0.054]
0.411
0.337***
[0.053]
0.416
21,077
18,638
13,802
9,197
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Observations
18,805
21,089
Fixed effects included in 3 regressions above
Firm
Yes
Yes
Sector-year
Yes
Yes
Note: Standard effors in brackets. *** means significant at 1%, ** at 5%, and * at 1%.
1. (10 points) FAMEX is Tunisia’s export-promotion program, which reimburses half the
expenses that firms incur in going to foreign fairs either as attendant or with a company stand,
and also provides some (not terribly useful) assistance in packaging and product design. Table 1
gives estimates of the effect of FAMEX on three dimensions of firm performance: total exports,
number of products exported, and number of destinations served. In the estimation equation, the
dependent variable is in log, so the estimates are roughly proportional to the percent increase in
the outcome for treated firms compared to control ones (0.774  77%). The equation includes a
bunch of control variables at the firm level (employment etc.) all evaluated at the sample’s
initial year. Each column estimates them at a different point in time: The year in which the firm
was in the program for column (1), one year after in column (2), two years after in column (3),
and so on. Please discuss the plausibility of the treatment effect’s magnitude. Discuss any
endogeneity/unobserved heterogeneity issue that you may think relevant and how the
specification shown seems to deal with it.
The coefficients imply that the total export value of firms that participated in the program
-1-
increased by 77% the year they took the program and by 89% one year after compared to a
control group. That’s really big for a program that reimburses half the airplane ticket and hotel
expenses to go to fairs in Frankfurt. Similarly the number of products exported rises by about
30% and the number of destinations by 25%. That looks like a complete transformation of the
firm. Moreover, the effect is intact 5 years after the treatment. Wow. That sounds to good to be
true.
Could it be some massive endogeneity bias or unobserved heterogeneity? The equation
apparently controls for some firm characteristics. Those could be a factor of endogeneity (take
employment: FAMEX could induce the firms to hire more) but they are evaluated at the start of
the sample period, so reverse causation is unlikely. Could it be unobserved heterogeneity, like
smart managers perform better and are more likely to take FAMEX? Maybe, but firm fixed
effects control for this if the management performance differential is permanent.
The results could also pick up innovation or stuff like that, but it would likely to affect the
whole sector and that’s controlled for by sector-year fixed effects.
So if the effect is overblown, which is what common sense suggests, the reason must be
somewhere else.
2. (15 points) Compare now the estimates in Table 1 and Table 2, focusing on the first line which
gives treatment-effect estimates using the firm’s total exports as the outcome variable. Discuss
the difference between the estimates in Table 1 and Table 2, both in terms of econometrics
(explain what propensity-score matching does, possibly using the information in Table 1 if it is
relevant) and in terms of “substance” (how effective is export promotion). Do the results show
that FAMEX induced firms to expand abroad? Why or why not? What feature of FAMEX could
have mitigated a windfall effect?
Table 2: FAMEX treatment effects estimated by DID with propensity-score matching
Forwarding degree
Estimator
Outcome
Total exports
R-squared
Nb. destinations
R-squared
Nb. products
R-squared
TY (k = 0)
PS weighted
(1)
TY+1 (k = 1)
PS weighted
(2)
TY+2 (k = 2)
PS weighted
(3)
TY+3 (k = 3)
PS weighted
(4)
TY+4 (k = 4)
PS weighted
(5)
TY+5 (k = 5)
PS weighted
(6)
0.411**
[0.171]
0.793
0.486**
[0.200]
0.770
0.208
[0.216]
0.765
0.080
[0.280]
0.762
0.009
[0.349]
0.746
0.144
[0.327]
0.740
0.104***
[0.022]
0.840
0.111***
[0.027]
0.825
0.076**
[0.032]
0.813
0.022
[0.033]
0.807
-0.014
[0.046]
0.787
0.039
[0.045]
0.783
0.086***
[0.031]
0.799
0.081**
[0.037]
0.783
0.062
[0.042]
0.773
-0.025
[0.047]
0.761
-0.009
[0.053]
0.755
0.072
[0.055]
0.755
21,077
18,638
13,802
9,197
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Observations
18,805
21,089
Fixed effects included in 3 regressions above
Firm
Yes
Yes
Sector-year
Yes
Yes
-2-
Table 3: Effect of matching on average firm characteristics
Table 2 combines DID estimation with propensity-score matching. All of a sudden the estimated
effects are much smaller and most importantly they become transient (non-persistent). Why?
The answer is in Table 3. Treated firms were fast-growing “gazelles” even before treatment, with
growth rates around 65% (against 8% for control firms). Thus the treatment-effect estimates
likely pick up that specific growth. Note that this growth differential has to be a temporary
phenomenon, since otherwise it would have been picked up by the fixed effects. Matching using
propensity scores based on (inter alia) lagged growth eliminates a lot of that bias since it selects
control firms with 59% growth in the last 2-3 years, quite close to the treated ones (67%). So in
this case PSM seems to work to reduce bias.
What this all suggests is that firms that went to FAMEX were already in a fast-growth period.
So perhaps they already intended to expand into new products and markets and FAMEX was
just a “windfall” to them. That’s often the case with subsidies: The government thinks of them
as inducing firms to do something, but what firms do is pocket the money and keep on with
business as usual.
What mitigates the windfall in the case of FAMEX is that it is a matching grant rather than a
full subsidy, so companies have to put their own money into what they do. So they won’t go to
the fair in Frankfurt just to do tourism and bring sausages back home.
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3. (15 points) Putting aside the issues relating to matching that you just discussed, please discuss
one important factor that could explain the absence of significant effect in columns (3)-(6) of
Table 2. How would you go about testing for the presence of that factor? If it were there, what
would be the policy implication?
Conceptually, there are two possible reasons for why FAMEX has no effect left after 2-3 years.
Either (i) the program’s effect is not persistent (a form of program failure), or (ii) control firms
caught up with treated ones through indirect exposure to treatment effects (“contagion”). In that
case, the program succeeded even more than if the estimated treatment effect were significant,
since it “leaked” to the non-treated population as well. In fact, only in that case is the program a
true public good, which is the condition for a subsidy to be optimal.
In other words, a program with significant treatment effects is a private good that benefits only
its direct beneficiaries. In that case it should be put on a full-cost recovery basis (sold to
beneficiaries). By contrast, a program with non-significant treatment effects can be either a
failure, in which case it should be discontinued, or a success leaking to non-treated populations,
in which case it should be delivered as a public good.
One way of testing for such spillovers is through an extenality regression where the performance
of control firms (only them) is regressed on their exposure to treated ones. The class notes show
that in the case of FAMEX, externalities did not come out significant, suggesting that the
reasons behind the results in Table 2 is a lack of persistence in the effects.
4. (15 points) Consider the following two quotes from Tunisian business people, taken from a
recent World Bank report:
The owner of a small firm employing nine female workers in Sousse, Tunisia, used to make lingerie
for a Belgian client who provided the inputs and paid the owner a fee. When asked, as part of a
survey, why she did not prospect other clients abroad to produce independently, she responded, “I
am afraid to do it, because my sole client may learn about it, and I may lose him. You understand, I
would need to invest a lot upfront in market research, travel abroad, and so on. Also, there is no one
with expertise in Tunisia who could help me overcome these knowledge gaps. The upfront
investment is just too high for me when I am very uncertain about the outcome. I just cannot afford
it.” […] Another Tunisian garment producer had a French designer come to his premises for two
months to design his Ladies Spring collection for export to Italy and France. The designer’s trip
expenses and fees, about $60,000, were covered by a government program. The firm’s owner had an
unsurprisingly positive view of government intervention: “Overall, the business environment is good
in Tunisia. The government supports the industry, as it did for the design of my Spring collection.
My problem is that we can only benefit from that program once. What am I going to do for the
coming Fall collection? This is a problem. The government should change its program and allow us
to benefit from it more often.” (Caroline Freund and Mélise Jaud, Champions Wanted; Washington,
DC: The World Bank, 2013, p. 50)
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If you were to decide whether to continue to finance the program using public funds (say, a World
Bank loan to be repaid out of the Government budget), what would those two quotes suggest to
you?
The first quote suggests that FAMEX addresses a real need for diversification for small firms.
The owners seems not to have the resources necessary to do the prospection of new clients that
would allow her to diversify her client base. This could be seen as a market failure that can be
usefully addressed by a government program, especially given that small firms lack access to
bank credit.
By contrast, the second quote suggests that government support is addictive. The respondent is
basically asking the taxpayer to pay for his designer’s work. This is absurd. Moreover he is
complaining that the government is not doing it every year. What else?
Again, the underlying issue is the “windfall effect”. Do subsidy programs fill a need that
genuinely cannot be filled by markets, or are they just handouts to private operators? In the case
of a small-money program like FAMEX, the issue is not too crucial, but when one thinks of
industrial policy on a large scale (e.g. garments in Bangladesh, automobile in Indonesia, steel
in South Korea in the 1980s) this is a real question.
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Question 2 (multiple choice)
Each multiple-choice question is worth 5 points. Please respond on the grid on page 7.
1. The ratio of international trade to GDP has been
a. Increasing until the last decade and then stabilizing under the effect of the “global trade
slowdown”
b. Increasing faster for industrial countries than for developing countries because of structural
adjustment programs
c. Decreasing, although at a decreasing rate, leading to a recent stabilization
d. Increasing during the first wave of globalization between 1848 and 1913 and then
decreasing
e. None of the above.
2. Purchasing-power parity (PPP) adjustment means
a. Manufactured products are evaluated at their international cost of production, based on
input-output data;
b. Prices are inferred from Living Standards Measurement Surveys (LSMS) which are carried
out by the World Bank in all developing countries every 5 years;
c. GDP is adjusted in nominal terms to satisfy trade-balance equilibrium;
d. Prices are adjusted, in particular those of services, to be roughly comparable across
countries for the same type of service ;
e. None of the above.
3. Consider the following equation estimated by Mankiw, Romer and Weill (1992):
ln yi  1 ln si  2 ln   ni   i   ui
(1)
where i is a country, yi is GDP per capita at PPP, si is the savings rate approximated by the
investment rate,  is the rate of capital depreciation, ni is the rate of population growth, and  i is a
proxy for technology/productivity. Under the Solow growth model,
a. 1    2  1 / 2 ; the estimates were qualitatively consistent with that hypothesis, but the
magnitudes were wrong
b. 1   2  1 / 3 ; the estimates rejected that hypothesis, implying no convergence
c. 1    2  2 / 3 ; the estimates had the right sign but were not significant because of the
small sample size
d. 1    2  1 / 2 ; the estimates flatly rejected absolute and conditional convergence.
e. None of the above.
4. As GDP per capita increases, for all countries for which there is data, the share of manufacturing
value added in GDP
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a. Rises at an increasing rate (the Kuznets curve)
b. Rises only for the sub-sample with high initial levels of human capital (“conditional
convergence”)
c. Rises with income levels, except when estimated for the period after the Global Financial
Crisis where it has been decreasing (the “great growth slowdown”)
d. Rises, reaches a maximum, and then decreases for rich countries, but for Africa it is already
decreasing at very low levels of income
e. None of the above.
5. Consider a trade model with two countries, monopolistic competition, and heterogeneous firms
characterized by different levels of their marginal cost. Trade liberalization will
a. Increase the number of varieties available but compress profit margins (the “competitive
effect”), with margins shrinking more for large firms
b. Keep product variety constant (by construction of the model) but increase the demand faced
by all firms in a symmetric way
c. Increase varieties available to consumers, increase the demand faced by large firms, but
decrease the demand faced by small firms, some of which will exit
d. Can induce the exit of the largest firms through general-equilibrium effects
e. none of the above
6. When total factor productivity growth (TFPG) measured through econometric estimation is
higher when time increases, it must be that
a. Production is characterized by economies of scale (since under constant returns to scale it
would be on average zero)
b. Factors of production are used more efficiently (since accumulation does not account for
observed growth)
c. The estimation suffers from unobserved heterogeneity (since the residual is increasing)
d. There is capital-deepening (since labor productivity depends on the capital/labor ratio)
e. None of the above.
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7. Under the WTO’s SPS agreement,
a. Free-trade agreements are allowed only under an exception clause, because they are
discriminatory;
b. Tariffs must be “bound” at levels under their level agreed at the previous Round of
negotiations;
c. Sanitary regulations must be science-based;
d. Non-tariff measures are prohibited except in order to protect consumer health
e. The SPS agreement has nothing to do with the WTO (it was signed at the OECD).
8. International evidence on Export Processing Zones (EPZs) in developing countries suggests that
a. They have strong backward linkages, especially in countries with high values of the World
Bank’s Logistics Performance Index (LPI)
b. They create jobs with remuneration on average about three times the average level of
remuneration in the rest of the economy
c. They are strong growth engines in most countries, but the effect is stronger in countries with
favorable business environments (as measured by the Doing Business index)
d. They are essentially fiscal handouts to multinationals with few benefits in terms of “quality
jobs” or spillovers
e. none of the above
9. In a gravity equation, the “multilateral resistance term” measures
a. The level of a uniform tariff that would generate the same deadweight loss as the current
array of tariffs at differentiated rates, which enters the equation as a country-level timevariant control
b. How difficult it is for a country to trade with all of its trade partners, which usually relates to
its remoteness, and is time-dependent, implying the gravity equation should be estimated
with country-time fixed effects
c. The level of a uniform tariff that would generate the same aggregate level of imports as the
current array of tariffs at differentiated rates, which enters the equation as a country-level
time-variant control
d. A set of dyadic variables including distance, whether the country pair shares a common
language, a common land border etc.
e. The term “multilateral resistance” has nothing to do with the gravity equation and refers to
blocking coalitions of countries in multilateral rounds of trade liberalization such as the
Doha Round.
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ANSWER GRID
(PLEASE CIRCLE THE CORRECT ANSWER) :
Example of correct formatting (b being the right answer):
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Example of wrong formatting (b being the right answer):
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Answers:
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