An Economic Inquiry into Ethiopian Exports: Pattern, characteristics, Dynamics and Survival

An Economic Inquiry into Ethiopian

Exports: Pattern, Characteristics,

Dynamics and Survival

Presented by

Berihu Assefa Gebrehiwot (EDRI)

EDRI Conference Room, Addis Ababa

18 December 2015

ETHIOPIAN DEVELOPMENT RESEARCH INSTITUTE (EDRI)

1 Introduction

2 Objectives and Questions

3 Data

4 Results and Discussions

Structure

5 Conclusions

Introduction

International trade is a key driver of economic growth and poverty reduction [Reis & Farole, 2012; Frankel &

Romer, 1999; Samuelson, 1939; Dollar & Kraay, 2003; Irwin & Terviö, 2002; Krueger, 1998; Balassa, 1982]

Some of the mechanisms through which trade contributes to economic growth include (Samen, 2010;

Brenton & Newfarmer, 2009; Reis & Farole, 2012):

Trade increases potential market size (via exports) - increasing market size means more profits and scale effects leading to growth

Trade increases domestic competition (via imports) – efficiency gain

Trade increases specialization and expands efficiency-raising benefits of comparative advantage (via factor price equalization)

Trade affords greater capacity utilization

Trade induces rapid technological change, and productivity gains leading to wage premiums and job creation (via DCA)

Introduction

Empirical literature also shows a wide consensus on the positive association between trade and economic growth (Edwards, 1992; Krueger, 1997; Wacziarg & Welch,

2003)

Special emphasis on the role of exports • Rapid and sustained economic growth through productivity

gains and technological upgrading (Spence, 2007; Brenton & Newfarmer, 2009)

» Export sectors have higher productivity and

» And within sectors, exporting firms tend to be more productive than non-exporters

Introduction

Following these spectrum of theoretical and empirical grounds and the drive for industrialization, many developing countries have started promoting exports through direct policy incentives and export institutions Particularly, since the 1980s, most developing countries abandoned import

substitution strategies in favor of export-led growth and start to undertake trade reform measures as part of the Structural Adjustment Program (SAP)

Since then designing policies that promote trade and trade competitiveness have been at the heart of growth strategies for developing countries

Likewise, since the early 1990s Ethiopia has been striving to set the right conditions for increasing exports Overall economic liberalization and macroeconomic stability reforms Introduction of several export incentive schemes Set up a number of export support institutions (ESI) aimed at boosting

exports in general and manufactured exports in particular

1 Introduction


3 Data


Structure

5 Conclusions

Research Objectives and Questions

So our goal in this paper is to analyze Ethiopia’s export performance and dynamics over the period 1995 to 2014 Ethiopia’s trade/export patterns Export growth characteristics

What characterizes and drives export growth? How concentrated/diversified are Ethiopia’s exports in

terms of exporters, products, and markets?

Export Dynamics and Survival Over the past decade or so, has Ethiopia added

economically significant numbers of new products and markets to its export portfolio?

And to what extend do Ethiopian exporters survive beyond their first year of entry to the export market?

1 Introduction


3 Data


Structure

5 Conclusions

Our dataset come mostly from ERCA administrative data

We use both Aggregate data – provide a good picture of the trade flows

Firm-level data - has the merit of giving a richer and more accurate picture of export dynamics

We used complementary data from international data sources – Uncomtrade, WB, IMF, UNCTAD, etc When Customs data is not available

When comparison is necessary and

Dataset

Two Main Sections

Section 1: Aggregate Data – Trends, Patterns and Key Performance Indices

• Overall Openness

• Trade Composition (sectoral, geographical, etc)

Section 2: Firm-Level Data – Export Diversification

– Export Dynamics

– Export Survival

Section 1: Aggregate Data

Trends in Ethiopia’s Exports, Imports and GDP

Figure 1: Trends in Exports, Imports and GDP of Ethiopia (1995- 2013)

• High import growth following the rapid increase in GDP after 2003

• Increase in exports not equally remarkable

• As a result, trade deficit widened

Ethiopia: Trends in Trade Growth

Figure 6: Annual Growth Rates of Exports of Goods and Services in Ethiopia (1995-2013)

• The growth rates in exports over the reviewed period have been positive except for the negative growth rates observed in 1999 and 2012 and the close to zero rates in 2008 and 2009.


Figure 7: Export Value and Annual Growth Rate of Merchandize Exports (2005/2006 - 2014/2015).

Source: ERCA


We observe large annual fluctuations in the level and growth of exports (see Figures 6 and 7) – This is driven largely by changes in international commodity

prices of major exports such as Coffee • For example, the country's strong export performance recorded in

2010 and 2011 can largely be attributed to the rise in international commodity price in general and that of coffee in particular

• Similarly, the negative export growth rates observed in 2012 appears to coincide with the fall in international commodity price particularly that of coffee

– This co-movement of international commodity price and Ethiopia's export performance clearly shows how the country is heavily reliant on commodity exports and signals the need for further diversification of the country’s exports base

Figure 10: Coffee Commodity prices, annual, 1960 - 2014. Source: UNCTAD



Figure 9: Indices of Non-Fuel Primary Commodity Prices (2005 = 100). Source: IMF Commodity Prices

Notes: (1) Indices comprise 60 price series for 44 non-fuel primary commodities; (2) Weights are based on the

2002-2004 average of world export earnings; and (3) Real means that it is deflated by U.S. CPI

Key Trade Performance Indices

Discussion on trade performance commonly revolves around 3 questions – how much, what and with whom a country trades

We focus on two key performance measures

1) Trade Openness (at the aggregate level)

Measures a country’s ability to integrate in global trade

2) Trade Composition

Sectoral and geographic compositions

(1) Overall Openness Measures

Raw Trade Openness – measured as the sum of imports and exports over GDP Common measure but has defects (e.g., cross country

comparison is difficult because openness is correlated with country characteristics such as income, location, size, etc)

For example, while smaller countries (such as Singapore, Belgium, etc) appear to have higher levels of trade share in GDP, large countries such as the U.S. and Japan appear to have the lowest level of trade share in GDP. (This is so because larger countries trade more with themselves)

Relative Trade Openness – measures a country’s trade share in world trade Corrects for some of the weaknesses of the raw measure but

cross-country comparisons still remain difficult

Adjusted Trade Openness – controls for the influence of country characteristics through regression analysis Generates meaningful comparisons

Raw Measure: Ethiopia’s Trade Openness

Figure 2: Trends in Shares of Trade, Exports and Imports of Goods and Services in GDP Ethiopia

(1995-2013)

26%

51% 40% Mainly attributed to the rapid increase of imports

During the 2006-2009, rapid growth rate of GDP was largely driven by growth in the non - tradable (service sector)

Improvements in international commodity prices.

Raw Measure: Ethiopia’s Trade Openness

Figure 3: Trends in Shares of Merchandise Trade, Exports and Imports in GDP Ethiopia (1995-2013)

• Trend is similar but the share of merchandise exports in GDP remains flat and its contribution to the overall merchandise trade openness is meagre

• In the case of merchandise, it is clear that the overall trade openness is to a greater extent dictated by trends in share of merchandise imports in GDP.

Raw Measure: Ethiopia’s Trade Openness Relative to Other Countries

Trade openness: Merchandise Trade Share in GDP (%GDP)

Period Ethiopia Kenya Zambia Tanzania Mozambique Uganda Zimbabwe Madagascar

1994-1998 21.67 44.9 47.98 34.44 34.42 29.38 65.83 32.98

1999-2003 27.61 39.02 51.31 24.32 45.1 30.41 55.32 39.03

2004-2008 37.74 44.36 56.81 41.45 63.93 36.07 86.52 53.88

2009-2013 33.5 43.29 66.67 54.51 72.28 41.78 66.78 46.49

Export Share in GDP (%GDP)


1994-1998 5.95 18 26.39 10.53 6.52 8.88 29.6 14.57

1999-2003 5.87 14.89 24.59 8.1 14.63 7.76 27 16.83

2004-2008 6.64 15.04 27.58 12.84 27.47 9.98 39.31 17.66

2009-2013 6.83 12.29 35.73 17.26 26.33 11.51 30.17 14.95

Import Share in GDP (%GDP)


1994-1998 15.72 26.9 21.59 23.91 27.91 20.49 36.23 18.41

1999-2003 21.74 24.13 26.72 16.22 30.47 22.64 28.32 22.2

2004-2008 31.1 29.32 29.23 28.61 36.45 26.09 47.21 36.22

2009-2013 26.68 31 30.94 37.25 45.95 30.26 36.61 31.54

Table 1: Ethiopia's Trade Openness Relative to Selected Sub-Saharan African Countries (1994 - 2013). Source:

World Bank

Relative Measure: Comparing Ethiopia's Share in World Trade with Selected Sub-Saharan African

Countries Taking all countries in the world, 𝑗 = {1, 2, … , 𝑁}, country 𝑖’𝑠, world

trade share is given by:

𝐖𝐨𝐫𝐥𝐝 𝐓𝐫𝐚𝐝𝐞 𝑺𝒉𝒂𝒓𝒆𝒊 = (𝐗 +𝐌)𝒊

𝐗 +𝑴 𝒋𝑵𝐣=𝟏

, where i ∈ j

This measure corrects for some of the weaknesses of trade share in GDP as a measure of openness

Trade Openness: share in world trade (%)


1994-1998 0.016 0.046 0.017 0.02 0.01 0.016 0.047 0.011

1999-2003 0.017 0.039 0.016 0.019 0.015 0.014 0.027 0.013

2004-2008 0.025 0.044 0.026 0.026 0.02 0.015 0.018 0.013

2009-2013 0.037 0.058 0.044 0.042 0.028 0.022 0.021 0.013

Table 2: Ethiopia's Trade Share in World Trade Relative to Selected Sub-Saharan African Countries (1994 -

2013). Source: World Bank

Adjusted Trade to GDP Ratio: Regression Analysis to Control for Country

Characteristics Having a lower trade share in GDP doesn't necessarily mean that

the country in question is less open to international trade In fact, these countries might be trading as much as they would be expected to trade

given their size, level of development and geographical location etc

In order to measure correctly how much a country trades relative to how much it can be expected to, given its fundamentals, one can run a trade-openness regression of the type

𝑂𝑖 = 𝛼0 + 𝛼1𝑌𝑖 + 𝛼2𝐴𝑖 + 𝛼3𝑅𝑖 + 𝛼4𝐿𝐿𝑖 + 𝛼5𝐼𝐿𝑖 + 𝑈𝑖

Where Yi is GDP per capita (2005 USD); Ai is area in sq. kms; Ri is remoteness index; LLi and ILi are dummies for landlocked and island; and Ui is an error term.

Remoteness index measures a country’s average weighted distance from its trading partners (Head, 2003), where weights are the partner countries’ shares of world GDP

Since the distance variable used in calculating the remoteness index is measured between capitals of trading partners, it is can also capture internal cost of transportation

Country size measured by total population and land size

Adjusted Trade to GDP Ratio: Regression Analysis to Control Country

Characteristics

The difference between 𝑂𝑖 and its predicted value,

𝑂𝑖 , can be taken as an adjusted indicator of openness, i.e., adjusted for the structural factors included in the model

Positive – trades more than it can be expected to

Negative – trades less

Zero – trading as expected

Log Openness: Log Trade (% of GDP) (1) (2) (3) (4) (5)

Log GDP per capita (2005$) 0.053 0.027 0.046 0.033 0.012

(0.010)∗∗∗ (0.013)∗∗ (0.013)∗∗∗ (0.020)∗ -0.027

Log Population -0.07 -0.089 -0.086 -0.077 -0.079

(0.016)∗∗∗ (0.019)∗∗∗ (0.018)∗∗∗ (0.025)∗∗∗ (0.033)∗∗

Log Area in sq. kms -0.045 -0.04 -0.056 -0.047 -0.1

(0.013)∗∗∗ (0.014)∗∗∗ (0.014)∗∗∗ (0.023)∗∗ (0.029)∗∗∗

Remoteness Index -0.179 -0.09 -0.108 -0.092

(0.044)∗∗∗ (0.050)∗ -0.071 -0.08

Dummy for Landlocked 0.064 0.179 0.1 -0.04 (0.059)∗∗∗ -0.066

Dummy for Islands -0.218 -0.224 -0.235

(0.057)∗∗∗ (0.078)∗∗∗ (0.092)∗∗

Log Cost to Exp. & Imp. -0.197

(0.059)∗∗∗

Log Time to Exp. & Imp. -0.089

(0.045)∗∗ Number of Obs. 715 715 715 346 222 Adj. R2 0.31 0.33 0.35 0.35 0.44

• Robust standard errors in parentheses. Note that clustering at Country level doesn’t change the result in any meaningful way. The numbers of observations in

these two last columns are greatly reduced as data on these two variables is available only for the last two five year periods. All regressions include Period

Fixed Effects. ∗ p < 0.1, ∗∗ p < 0.05, ∗∗∗ p < 0.01

• Based on data for all countries (where data is available) over the four five-year periods

Table 3: Trade Openness and its Major Determinants

Adjusted Measure: Controlling for Country Characteristics

Adjusted Openness Based on Model 3: Trade share in GDP (% GDP)

Period Ethiopia SSA S. Asia N. America LAC MENA ECA EAP

1994-1998 -20.84 8.64 -6.34 -8.53 3.66 4.92 5.59 24.61

1999-2003 -12.92 4.83 2.47 -8.36 -4.60 -0.06 9.87 34.07

2004-2008 -8.90 0.96 1.59 -16.37 -6.57 5.28 6.78 34.43

2009-2013 -10.12 2.71 -0.57 -16.65 -11.51 5.07 10.68 33.43

Adjusted Openness Based on Model 4: Trade share in GDP (% GDP)

Period Ethiopia SSA S. Asia N. America LAC MENA ECA EAP

1994-1998

1999-2003

2004-2008 -10.84 3.27 -1.43 -16.81 -0.59 0.79 4.67 33.34

2009-2013 -13.18 5.20 -1.93 -17.06 -6.64 2.73 8.53 29.91 NOTE: We don’t have data on Cost of Importing and exporting for the first two periods

Data Source: WB and Ethiopian Revenues and Customs Authority (ERCA)

Table 4: Comparing Adjusted Openness across Regions

Adjusted Measure: Ethiopia’s Trade Openness


2009-2013 period Ethiopia traded 10 percentage points less than what

would be expected once the influence of the factors is accounted for

Using this adjusted measure, Sub Saharan African countries (including Ethiopia), on average, appear to be relatively more open compared to North America and Latin America and Caribbean regions once the influence of these factors is taken into account (contrary to what the "raw" measure of openness reported earlier)

When we further control for inland costs of trading (local costs associated with exporting and importing), Ethiopia becomes relatively less open - trades 13 percentage points less than would be expected.

Figure 5: Adjusted Openness to Trade for Sub-Saharan African Countries (Average of

2009 - 2013)


Ethiopia - 14th least open based on models 3 & 4

Ethiopia - 6th open when comparison is made based on the "raw" measure of openness.

(2) Trade Composition: Sectoral Composition of Exports

• Agriculture still largest contributor to Ethiopia’s merchandise exports - accounting for close to 87 percent, on average, during the past decade (2005/06 – 2014/15)

• While the manufacturing sector contributed about 7 percent for total merchandise exports, all the other sectors (minerals, base metals, etc) account for about 7 percent during the same period

• The other interesting observation is that although still dominant the export value share of Agriculture fell from 88 percent in 2005/2006 to 85 percent in 2014/2015

• On the other hand, the export value share of Manufacturing rose from 6.6 percent in 2005/2006 to 10 percent in 2014/2015. – Although these are small changes, this would

suggest that Ethiopian exporters are slightly diversifying into higher value sectors and sectors that are not heavily affected by external price and demand shocks.

– Likewise, in terms of the number of exporters, agriculture has the largest number of exporters followed by the manufacturing sector.

– On the contrary, the number of exporters is smallest in Mineral and Base Metals sectors.

(2) Trade Composition: Geographical Composition of Exports

In terms of geographic composition, modest diversification away from traditional partners such as Europe

Figure 14: Regional Share of Ethiopia's Merchandise Export over Periods

(2) Trade Composition: Geographical Composition of Exports

.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

40.0%

45.0%

50.0%

2005/2

006

2006/2

007

2007/2

008

2008/2

009

2009/2

010

2010/2

011

2011/2

012

2012/2

013

2013/2

014

2014/2

015

Year

Overall Export Value Share BY Region (%)

South & Central Asia

Europe

East Asia & Pacific

Latin America & Caribbean

Middle East & North Africa

Sub-Saharan Africa

North America

COMESA

Section 2: Firm-Level Data

1 Overall Trade Pattern

2 Export Base and Diversification

3 Export Dynamics

4 Export Survival

Results & Analysis

5 Conclusions

Export Base – measured in terms of number of exporters, products and markets

Export diversification – a measure of risk and vulnerability arising from relying on a narrow range of exporters, products and markets – It makes countries less vulnerable to demand shocks and price swings in

overseas markets by stabilizing export revenues (Ghosh & Ostry, 1994) – Creates greater opportunities through knowledge spillovers and increasing

returns to scale, which are critical to long-run growth (Amin Gutiérrez de Piñeres & Michael, 2000; Hausmann & Klinger, 2006)

As argued by (Samen, 2010), export diversification takes the following forms: – Horizontal diversification - within the same sector (primary, secondary or

tertiary) – Vertical diversification entails a shift from the primary to the secondary or

tertiary sector (e.g., moving from basic commodity extraction to commodity processing)

– Diagonal diversification entails a shift from imported inputs into the secondary and tertiary sector (e.g., using imported goods to produce manufactured products for exports)

Export Base and Diversification

Export Base and Diversification

Diversification is critical in any trade strategy (Reis & Farole, 2012) Justified to avoid the so-called “natural resource curse”

(a negative correlation between growth and dependence on primary commodity exports) (Sachs and Warner, 1999)

In addition, diversification at the extensive margin reflects “export entrepreneurship” (Hausman & Rodrik, 2003)

History: few countries have developed quickly on the basis of exports of primary products alone

Ethiopia’s Export Base and Diversification

In order to investigate export diversification performance in Ethiopia more robustly, we consider the following diversification measures: 1) Number of exporters, export products and destination

markets a simple count

2) Share of top exporters, products and markets Top 1, 5 and 25 percent

3) Theil Diversification Index Within and between-group diversification

4) Extensive and Intensive Margins: Export Growth Decomposition What is the contribution of the extensive margin?

1. Ethiopia’s Export Base - A Simple Count

Figure 15: Export Base of Ethiopia (2005/06 - 2014/2015). Source: ERCA

2. Ethiopia’s Export Base and Diversification: Export Value Share of Top 1, 5 and 25 percent Exporters, Products and Markets

Export Years Based on Ethiopian Fiscal Year Calendar 2005/2006 2006/2007 2007/2008 2008/2009 2009/2010 2010/2011 2011/2012 2012/2013 2013/2014 2014/2015

Firm

Top 1%

Exporters

Number 13 15 16 17 21 22 20 19 18 18 Export

Value Share

(%) 31 35 34 32 38 35 32 31 28 28

Top 5%

Exporters

Number 62 75 80 85 101 106 96 94 90 89 Export

Value Share

(%) 68 69 67 65 69 68 65 65 61 60

Top 25%

Exporters

Number 306 375 396 423 504 528 479 468 448 443 Export

Value Share

(%) 96.0 95.4 95.0 94.3 94.7 93.7 92.7 93.3 92.9 92.5

Product

Top 1%

Exporters

Number 8 7 7 7 7 8 8 7 7 8 Export

Value Share

(%) 77.7 72.3 68.3 76.9 77.1 76.8 75.9 73.2 67.3 76.8

Top 5%

Exporters

Number 36 35 35 33 34 38 36 35 35 37 Export

Value Share

(%) 95.0 93.7 92.4 95.1 95.2 94.1 94.5 93.7 91.7 92.3

Top 25%

Exporters

Number 179 174 174 163 169 187 177 172 175 181 Export

Value Share

(%) 99.5 99.5 99.5 99.5 99.6 99.5 99.7 99.6 99.4 99.4

Market

Top 1%

Exporters

Number 2 2 2 2 2 2 2 2 2 2 Export

Value Share

(%) 21.6 19.4 17.5 22.4 22.5 23.8 22.9 21.1 27.8 24.1

Top 5%

Exporters

Number 6 7 6 6 7 7 7 7 7 7 Export

Value Share

(%) 50.0 49.1 44.1 53.0 58.5 56.5 60.1 53.2 57.1 56.3

Top 25%

Exporters

Number 29 31 28 30 31 32 33 34 31 34 Export

Value Share

(%) 95.7 96.4 94.5 96.3 96.9 96.6 96.7 96.5 95.5 96.5

3. Ethiopia’s Export Base and Diversification – Theil Index

The Theil Export Diversification Index Theil’s index is another widely used diversification measure – upper

limit is ln(n) and lower limit is zero

The higher the Theil index, the higher the concentration (or the lower the diversification)

Theil’s index is decomposable - additively to measure diversification within (intensive) and among groups (extensive) of exports

Changes in the within-group Theil index measure changes at the intensive margin (i.e., changes in concentration among active lines only)

Changes in the between-groups component of Theil’s index measure changes at the extensive margin (i.e., proportional changes in the number of active lines)

Our results for the intensive (within) and extensive (between) Theil indices are based on the definitions and methods used in (Cadot, Carrère, & Strauss-Kahn, 2011)


Following (Cadot et al., 2011), Theil’s entropy index (Theil, 1972) is given by:

Let 𝑛 denote the number of export products (products are defined at the 4-digit SITC (Rev. 1) level), 𝑛

𝑗 the number of export lines in group 𝑗, µ the average dollar export value, µ

𝑗

group 𝑗’𝑠 average dollar export value, and 𝑋𝑘 the dollar value of export line 𝑘. Then the

between-groups component is:

And the within-group (intensive margin) component is

Where


Overall Theil index and its components are calculated for Ethiopia for the period 1993 – 2010 (where data is available) – Results based on an updated version of the UN–NBER dataset as compiled

by the IMF, which harmonizes COMTRADE bilateral trade flow data at the 4-digit SITC (Rev. 1) level

– Results are consistent with earlier measures - Ethiopia’s export diversification has generally remained low through out the period Compared to the Sub-Saharan average, Ethiopia performed lower than

the average until the year 2001, beyond which Ethiopia’s diversification appears to be better than the Sub-Saharan average

Compared to many Sub-Saharan African Countries including Kenya, Tanzania, Uganda, Mauritius, Zimbabwe and Madagascar

However, Ethiopia does better than some Sub-Saharan countries such as Mozambique, Ghana, Rwanda, Malawi and Sudan in terms of export diversification

Since 2001 Ethiopia has shown some improvements in terms of diversifying its exports compared to the period 1994 – 2000


Figure 16: Theil Diversification Indices: Overall, Intensive and Extensive (1993 - 2010). Source: IMF Diversification

Database


Figure 19: diversification index: Ethiopia against the Sub-Saharan average (1962 - 2010). Source: IMF Diversification Database


Figure 17: Diversification Index for Selected Sub-Saharan (COMESA) Countries (1962 - 2010). Source: IMF Diversification Database

Figure 18: Diversification Index for Selected Sub-Saharan (COMESA) Countries (1962 - 2010). Source: IMF Diversification Database


4. So, What Drives Export Growth? Roles of IM and EM

To understand what drives short run export growth (or contraction), we consider a simple decomposition of the change in exports between consecutive years

Following (Cebeci, Fernandes, Freund, & Pierola, 2012), if 𝑡 designates a year, 𝑋 designates total exports and 𝑛 is the number of exporters, then total exports in a given year (𝑋𝑡) is simply the product of the number of exporters in a given year (𝑛𝑡) and the average exporter size in a given year (𝑆𝑡):

𝑋𝑡 = 𝑛𝑡 ∗ 𝑆𝑡

Thus, the change in exports between years 𝑡 − 1 and 𝑡 can be written as:

𝑑𝑋𝑡 = 𝑛𝑡 ∗ 𝑑𝑆𝑡 + 𝑆𝑡 ∗ 𝑑𝑛𝑡 – where 𝑑𝑆𝑡 is the change in the average exporter size between years 𝑡 − 1 and 𝑡, 𝑑𝑛𝑡 is the change in the number of

exporters between years 𝑡 − 1 and 𝑡, 𝑛𝑡 is the average number of exporters across years 𝑡 − 1 and 𝑡, and 𝑆𝑡 is the average exporter size across years 𝑡 − 1 and 𝑡.

The contribution of the intensive margin (IM) to a change in exports is given by:

𝐼𝑀 = 𝑛𝑡 ∗𝑑𝑆𝑡𝑑𝑋𝑡

And the contribution of the extensive margin (EM) to a change in exports is given by:

𝐸𝑀 = 𝑆𝑡 ∗𝑑𝑛𝑡𝑑𝑋𝑡

4. So, What Drives Export Growth? Roles of IM and EM

Figure 11: Decomposition of Export Growth into Intensive and Extensive Margins (2006/07 - 2014/15). Source: ERCA

o While expansions in existing trade flows (the intensive margin) explained more than 92 percent of the overall changes in merchandize exports, the extensive margin explained, on average, only about 8 percent o Indicates the existence of weak diversification in terms of new products and markets

Average Exporter Size – How Large is the Average Ethiopian Exporter?

Exporter size (measured by mean exports per exporter) is about 1.15 million USD (WB: average for developing countries is about 2.21 million USD)

Difference in Average Exporter Size: The Top vs the Bottom

– In terms of contribution to the national export value, the top 10 percent of exporters (an average of 175 firms over the period 2005/2006 – 2014/2015) contributed a very high share of exports – close to or more than 80 percent over the past decade (2005/2006 – 2014/2015)

– The difference in the average exporter size (measured by mean exports per exporter) in the top 10 percent and bottom 90 percent of exporters is simply tremendous In 2014/2015, while the average export value among firms in the top 10

percent of exporters is 13.7 million USD, the corresponding value for firms in the bottom 90 percent is only 0.5 million USD

Considering a longer period (2005/2006 – 2014/2015), the mean export per exporter (or average firm size) has been 9 million USD for the top 10 percent and 0.26 million USD for the bottom 90 percent

This means that over the entire period, an exporter in the top 10 percent of exporters is, on average, about 35 times larger in size than an exporter in the bottom 90 percent of exporters (see Table 7)

Average Exporter Size – How Large is the Average Ethiopian Exporter?

Ethiopian Fiscal Years Ten Year

Average 2005/2006 2006/2007 2007/2008 2008/2009 2009/2010 2010/2011 2011/2012 2012/2013 2013/2014 2014/2015

Top 10%

Total Number of

Firms 123 150 159 170 202 211 192 188 179 178 175

Total Export Value

(USD Millions) 792 918 1,206 1,147 1,526 1,928 2,121 2,072 2,227 2,430 1,637

Average Value

(USD Million) 6.44 6.12 7.58 6.75 7.56 9.14 11.05 11.02 12.44 13.65 9.17

Export Value

Share (%) 84.6 83.5 82.2 80.0 81.4 80.7 78.7 79.3 76.8 75.5 80.3

Bottom

90%

Total Number of

Firms 1100 1348 1423 1521 1811 1898 1720 1683 1609 1593 1571

Total Export Value

(USD Millions) 145 181 260 287 349 460 574 542 674 788 426

Average Value

(USD Million) 0.13 0.13 0.18 0.19 0.19 0.24 0.33 0.32 0.42 0.49 0.26

Export Value

Share 15.4 16.5 17.8 20.0 18.6 19.3 21.3 20.7 23.2 24.5 19.7

Table 7: Export Performance of the Top 10 and Bottom 90 percent Exporters (2005/2006 - 2014/2015). Source: ERCA



3 Export Dynamics

4 Export Survival

Results & Analysis

5 Conclusions

Export Dynamics: Entry and Exit

Explores to what extent Ethiopia has been able to add economically significant new exporters, new products and new markets to its export portfolios

Firm entry and exit

– Entrants as exporting firms that exported in the current period but did not export in previous periods

– Exiters are firms that exported in the previous period but did not export in the current period,

– Firm Entry Ratet = Number of Entrantst / Number of Exporterst

– Firm Exit Ratet = Number of Exiterst / Number of Exporterst-1

Export Dynamics - Firm Entry and Exit Rates

Years

Average 2006/2007 2007/2008 2008/2009 2009/2010 2010/2011 2011/2012 2012/2013 2013/2014 2014/2015

Total Number

of Exporters 1498 1582 1691 2013 2109 1912 1871 1788 1771 1804

Total Number

of Entrants 690 511 684 844 762 604 524 430 494 616

Total Number

of Exiters 415 427 575 522 666 801 565 513 511 555

Net Exporter

Entry 275 84 109 322 96 -197 -41 -83 -17 61

Exporter Entry

Rate (%) 46.1 32.3 40.5 41.9 36.1 31.6 28.0 24.1 27.9 34.3

Exporter Exit

Rate (%)* 33.9 28.5 36.4 30.9 33.1 38.0 29.6 27.4 28.6 31.8

Net Exporter

Entry Rate (%) 12.1 3.8 4.1 11.1 3.1 -6.4 -1.5 -3.4 -0.7 2.5

Table 8: Entry and Exit of Ethiopian Exporters (2006/2007 - 2014/2015). Source: ERCA

Export Dynamics - Firm Entry and Exit Rates Ethiopian exporters exhibited high degree of exporter churning over

the past nine years (2006/2006 - 2014/2015) – Export firm entry rate averaged 34.3 percent – Firm Exit Rate averaged 31.8 percent – Consistent with a number of studies who find rates of entry into

exporting of 30-60 percent a year (e.g., see Alvarez and Lopez, 2008 for Chile; Eaton, Eslava, Kugler and Tybout, 2008 for Colombia; Volpe-Martincus and Carballo, 2008 for Peru; and Albornoz et. Al., 2010 for Argentina)

Both entry and exit rates initially increased and peaked in 2010/2011 and slowed down since then until the current period 2014/2015. – But, the number of entrants is consistently higher than the number of

exiters between 2006/2007 and 2010/2011. – The opposite is true for the period between 2011/2012 and 2014/2015 – However, the gap between the two rates shrinks towards the end of the

analysis period.

Overall, net firm entry has been 2.5 percent on average over the past nine years

Export Dynamics - Product and Market Entry and Exit Rates

Years Average

2006/2007 2007/2008 2008/2009 2009/2010 2010/2011 2011/2012 2012/2013 2013/2014 2014/2015

Product

Dynamics

Product

Entry Rate 59.52 58.50 65.04 59.46 60.21 55.18 54.21 55.17 55.51 57.92

Product

Exit Rate 58.78 59.20 59.90 59.55 60.17 56.79 54.80 55.30 55.10 57.63

Net

Product

Entry Rate

0.74 -0.7 5.14 -0.9 0.05 -1.61 -0.59 -0.14 0.41 0.28

Market

Dynamics

Market

Entry Rate

(%)

57.8 56.5 57.4 57.7 58.1 54.6 54.8 54.9 54.2 56.2

Market

Exit Rate

(%)

54.3 56.3 57.2 56.9 57.5 54.1 54.0 54.3 53.7 55.4

Net Market

Entry/Exit

Rate (%)

3.5 0.2 0.2 0.8 0.6 0.5 0.8 0.5 0.5 0.9

Table 9: Product and Market Entry and Exit Rates (2006/2007 - 2014/2015). Source: ERCA

Export Dynamics - Product and Market Entry and Exit Rates

Similar to the exporter churning, product and market churning is also relatively high in the Ethiopian export market – Product entry rate averaged at 57.9 percent over the past nine

years (2006/2007 – 2014/2015) – While product exit rate has been 57.6 percent – Relatively high product entry, however, most of these new products

die out as can be seen from the high product exit rates, which suggests accidental deaths beyond experimentation

Likewise, market entry and exit rates have been high, 56.2 and 55.4 percent respectively

Overall – Net Product entry rate averaged at 0.28 percent – Net market entry rate has been positive in all the years over the

past 9 years (2006/2007 – 2014/2015) averaging at about 1 percent



3 Export Dynamics

4 Export Survival

Results & Analysis

5 Conclusions

Ethiopia: Exporter Firm Survival

• For any developing country, survival (the ability of those new export portfolios to survive and thrive in export markets) is as important as entry (Reis J. G., 2011; Cebeci, Fernandes, Freund, & Pierola, 2012)

• Firm Survival Ratet = Number of Survivorst / Number of Entrantst 1-year Survival Ratet = Number of Survivorst / Number of

Entrantst

2-year Survival Ratet = Number of 2-year Survivorst / Number of Entrantst

3-year Survival Ratet = N. 3-year Survivorst / N. Entrantst


Table 10: Exporter Survival (2007/2008 - 2014/2015). Source: ERCA

Firm Type 2007/2008 2008/2009 2009/2010 2010/2011 2011/2012 2012/2013 2013/2014 2014/2015 Average

1-Year

Survival

Rate (%)

85.5 37.9 47.2 61.8 64.2 62.0 70.7 50.2 59.9

2-Year

Survival

Rate (%)

34.4 18.8 31.1 41.6 46.0 51.4 39.1 37.5

3-Year

Survival

Rate (%)

21.7 15.0 23.3 37.8 43.3 26.7 28.0

Definition


1-Year Survival Rate On average, about 60 percent of the new entrants survive for just

one year High variability in firm survival rate (ranging from 37.9% to 85.5%) In the current year 2014/2015, firm survival rate is 50 percent,

which is lower than the eight-year average, suggesting that entrant firms have recently been experiencing trouble remaining in the export market

2-year and 3-year Survival Rates Again, high variability in firm survival (ranging from 18.8 to 51.4

percent) and the 3-year firm survival rate (ranging from 14.9 to 43.3 percent)

Survival beyond the first year becomes more and more difficult And the survival rate for 1-year, 2-year and 3-year survivors in the

current year 2014/2015 is much lower than the previous three years; indicating that firms recently have had trouble remaining in the export market relative to the last 3 years



3 Export Dynamics

4 Export Survival

Results & Analysis

5 Conclusions

Conclusions

Several key patterns emerge from our analysis

– Falling Agriculture and rising Manufacturing Although these are small changes, this would suggest

that Ethiopian exporters are slightly diversifying into higher value sectors and sectors that are not heavily affected by external price and demand shocks

– Increasing roles of more dynamic and emerging markets in Asia, Latin America, Sub-Saharan, etc EAP, Sub-Saharan Africa, LAC

Conclusions

Several key patterns emerge from our analysis – In any one year, almost all export expansion or

contraction comes from changes in exports by existing firms (the intensive margin)

– This dominance of existing firms is despite the fact that one-third to one-half of all exporters are new entrants in a typical year

– These new firms by and large do not add much to export growth simply because (i) the majority do not last more than a year and (ii) their export sales are very small

– Each year, large numbers of new exporters enter the export market, but most drop out after 2 years of export. And even much smaller after 3 years Death beyond experimentation

Conclusions

• But Still Sources of Vulnerability Remain – Ethiopia’s export sector remains heavily dependent on

primary commodity exports and a few large exporting firms • The top 10 percent exporters (only 175 firms on average

between 2005/06 – 2014/15) contributed close to or more than 80 percent of the country’s exports

• So, while export value has shown a modest increase, it is dominated and driven by the top tier of larger exporters and few export products

– Similarly, in terms of destination markets, Ethiopia’s exports are focused on a small number of countries (135 markets out of a total of 247 potential markets)

– Limited diversification – the extensive margin’s contribution to overall export growth is weak, unable to expand the country’s export base

Policy Issues?

• If most of your export values are coming from a few top (superstar) exporters, should export promotion target SMEs?

• Should policy target more entry or longer survival?

– Virtuous export growth theory – survival as important as entry?

• Is knowing what to export is as important as knowing where to export?

Government & Nonprofit

An Economic Inquiry into Ethiopian Exports: Pattern, characteristics, Dynamics and Survival