Presentation by Rana Hendy (ERF) at the ERF 20th Annual Conference - Cairo, 21 March 2014

1. TRADE FACILITATIONAND FIRMS EXPORTS:
THE CASE OFEGYPT
Rana Hendy and Chahir Zaki
ERF Policy Seminar
March 21, 2014
Cairo- Egypt

2. Motivation
• Numerous studies have highlighted MENA’s weak performance
in aggregate trade and diversification (Dogruel and Tekce,
2011).
• Yet, little is known about the impact of administrative barriers
on firm-level exporter behavior largely because of a lack of
data.
• This paper tackles the impact of red tape barriers on firms’
exports.

3. Motivation
The topic of this paper is crucial in international trade for three
main reasons:
1. First, trade barriers- as argued by the WTO- are highly
correlated to lengthy, bureaucratic and time consuming
trade procedures that do negatively affect firms’ exports.
2. Second, these barriers are significantly highly persistent
and costly in developing countries such as Egypt.
3. Third, they represent a deadweight loss as they do not
generate any rent or revenue.

4. MENAversus the Rest of the World
Red Tape Barriers vs. Tariffs
Source: Zaki (2013)

5. Egypt versus MENAand OECD
TradingAcross Borders

6. Literature
• Dennis and Ben Shepherd (2011) showed that a 10%
improvement in trade facilitation is associated with product
diversity gains of the order of 3%- 4%.
• In Asia, Li and Wilson (2009) found that improvement in trade
facilitation indicators tend to increase the probability that Small
and Medium Enterprises (SMEs) will become exporter as well
as their export propensity.

7. Literature
• In Africa, Yoshino (2008) found that public infrastructure
constraints, such as customs delays, seem to have immediate
impacts on regional exports in general, implying the relevance
of addressing behind-the-border constraints in fostering regional
integration.
• In the same line, Hoekstra (2013) found that trade facilitation
can increase African firms’ probability to participate in
international trade.
• Shepherd (2012) proved that licensing times do matter for the
ability of firms to access imported intermediates.

8. What we do
• We estimate a gravity model using Egyptian firm-level
customs data, for the first time, to examine the impact of these
barriers on firms’ exports.
• These data are merged with administrative barriers that come
from the Doing Business dataset developed by the World Bank.
• We examine this effect for both the intensive margin (the value
of exports) and the extensive one (the probability of exporting a
product to a new destination).

9. Outline
 Stylized Facts
 Methodology
 Data
 Empirical Results
 Policy Implications

10. Outline
 Stylized Facts
 Methodology
 Data
 Empirical Results
 Policy Implications

11. Proceeds of Merchandise Exports by
Degree of Processing
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
FY06 FY07 FY08 FY09 FY10
Others
Finished goods
Semi-finished goods
Raw Materials
Fuel, Mineral Oils & Products

12. Geographical Distribution of Exports
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
FY02 FY03 FY04 FY05 FY06 FY07 FY08 FY09 FY10
Others
Australia
Africa
Asia
Arab
USA
Russian Federation
Other European
EU

13. Exports and Number of Firms
Source: Constructed by the authors using the customs dataset.
17,000
18,000
19,000
20,000
21,000
22,000
23,000
24,000
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
18.0
20.0
2006 2007 2008 2009 2010
Sum of Export (in billion - LHS) Number of Firms (RHS)

14. Firms Entry and Exit
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
2007 2008 2009 2010
New Entrants Continuing Firms Exiting Firms

15. Number and mean size of importers
02468
15 20 25 30
Ln(GDP of Importer)
lnumfirm Fitted values

16. Egypt’s top importers (2006-2010)
-10.0%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
2006 2007 2008 2009 2010
CHN
JOR
CHE
NLD
LBN
TUR
FRA
SDN
ESP
ARE
LBY
IRL
SYR
SAU
ITA
USA

17. Firms per destination
0
500
1000
1500
2000
2500
2006 2007 2008 2009 2010
USA
ITA
SAU
SYR
IRL

18. New Exporters (by year)

19. Average Time to Import of Top Destinations
0 10 20 30 40 50 60 70
USA (2)
NLD (11)
CHE (15)
ARE (7)
ESP (10)
IRL (4)
FRA (8)
SAU (1)
ITA (3)
Egypt
TUR (6)
JOR (14)
CHN (13)
SYR (5)
LBN (12)
SDN (9)

20. Exports and Time to Import of Top Destinations
y = -17.225x + 1558.5
0
500
1000
1500
2000
2500
3000
3500
0 10 20 30 40 50 60 70
Exports(thousands)
Time to Import of Destination

21. Outline
 Stylized Facts
 Methodology
 Data
 Empirical Results
 Policy Implications

22. Methodology
• We estimate a gravity model to determine the effect of red tap
barriers on Egyptian exports.
• We control for the following variables:
• GDP (for Egypt and the destination)
• Gravitational Variables: common language, contiguity,
distance, common colonizer.
• Trade Facilitation Variables: time to import, time to export.
• Policy Variables: tariffs.

23. Different Definitions

24. Outline
 Stylized Facts
 Methodology
 Data
 Empirical Results
 Policy Implications

25. Data Sources
• Firm level customs data come from the General Organization
for Export and Import Control (GOEIC), the Ministry of
Industry and Foreign Trade in Egypt from 2006 to 2010 (at the
HS4 level).
• Red tape variable (the logarithm of the time to export multiplied
by the log of time to import) are taken from the Doing Business
database constructed by the World Bank → To have a bilateral
variable.

26. Data Sources
• The Gross Domestic Product (GDP) for each country comes
from the World Development Indicators database.
• Other classic gravitational variables, for instance contiguity,
common language, distance, common colonizer, etc. come from
the Centre des Etudes Prospectives et d’Information
Internationales (CEPII) Distance database.

27. Outline
 Stylized Facts
 Methodology
 Data
 Empirical Results
 Policy Implications

28. Major Findings (1/2)
• Time to export and time to import have a statistically significant
impact on the probability of exporting across different
destinations.

29. Major Findings (2/2)
• We disentangle the incidence of administrative barriers on
exporter by their size:
Small exporters (<10% or <25%) are more negatively
affected by these barriers than larger firms (>90%).
Small and medium enterprises (SMEs) gain much
more from trade facilitation than large
multinational ones. These gains are amplified while
taking into account the fact that the vast majority of
firms in developing countries are small and
medium ones and that these companies create more
jobs (National Board of Trade, 2003)

30. To sum up
• Red tape barriers negatively affect Egyptian firms.
• This effect seems to be robust for both the intensive margin (the
value of exports) and the extensive one (the probability of
exporting across different destinations).

31. Outline
• Stylized Facts
• Methodology
• Data
• Empirical Results
• Policy Implications

32. Policy Implications of this study
• The majority of gains are reaped by Sub-Saharan Africa and
Middle East and North Africa as the exports of electronics, in
machinery, metallic products, and textiles and garments are
highly boosted (finding in line with Zaki, 2013).
• Policies that lower trade costs and favor access to export
markets are likely to increase the number of destinations served
by new exporters.
In a general equilibrium framework, more destinations mean
more exports, more production and consequently a higher labor
demand. This would in turn be beneficial for productivity and
job creation, since exporters perform better.

33. Policy Implications of this study
• Red tape barriers may explain why the MENA region is
underperforming in terms of exports performance.
Improving customs authorities by reducing redundant trade
procedures:
 Single window policies
 Provide support for SMEs through exports clusters.
 Computerization of Egyptian customs to speed up clearance
time and reduce corruption (already implemented in some
Egyptian ports but still needs to be generalized).

34. Thanks for your attention!