Employment effects of DEG’s
investment - the Löwenstein theory
Washington, January 29th
Christiane Rudolph
Director Corporate Strategy and Development Policy
Results chain for employment effects
Effects beyond what we can directly count
Direct employment effects
Construction / Implementation
Operations
Construction firm/service provider carries out project
Operations / Maintenance
Construction firm/service provider employs staff
Operating company employs staff
Indirect effects
Value Chain
upstream
downstream
Construction
firm/ operator
requires input
Beneficiaries
increase local
output
Supplying and buying firms employ
staff / Increased opportunities for
self-employed people (e.g. farmers)
Induced employment effects
Business Climate and Productivity
New business
opportunities
Production
costs
New firms emerge
Labor
productivity
Existing firms increase
productivity
Local demand
Laborers earn
income
Increased local
demand
New and existing companies employ staff
Graph based on
Estimating induced employment effects using Cobb-Douglas function / Washington / January 29th
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Selecting a method to estimate induced employment effects
Neoclassical growth theory: Cobb-Douglas production function
We are searching for the change in employment brought about by a typical DEG financed investment
project in the formal sector of an economy. There are several options to approximate a project’s
contribution to employment at the national level, e.g.
-  rely on input-output tables
-  use computable general equilibrium models
-  base calculations on models of economic growth
Study by DEG aimed to derive a project’s contribution to employment at the national level from neoclassical growth theory. The aggregate production function that underlies formal sector production is of
Cobb-Douglas type:
Y = GDP
A = Technology level
K = Capital Stock
L = Employment
Assumptions:
-  technology level (A) remains constant
-  absence of full employment (challenging neo-classical assumptions)
-  constant economies of scale and constant partial production elasticities of capital and labour
Estimating induced employment effects using Cobb-Douglas function / Washington / January 29th
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Calculating the induced employment effect
The employment effect is measured by comparing employment in reality (index r) (with the DEG investment) with the counterfactual employment (index c) (without the DEG investment).
In order to calculate ΔLf we need to know about the effect of the DEG investment on formal sector
capital stock growth. The model assumes that ΔgLf = ΔgKf.
For the calculation of the capital coefficient kf we make use of the properties of the underlying aggregate
production function (for the steps to get to this point, see report)
Data on I, Y, gY and gL is provided by the World Bank (WDI). Research on partial production elasticity
shows that most estimated labor shares lie between 0.6 and 0.8 (avg. 0.65). The presented model took
a conservative approach and assumed that a = 1/3. With that information, we can calculate ΔLf .
Estimating induced employment effects using Cobb-Douglas function / Washington / January 29th
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Applying the model to DEG’s projects
Issues to keep in mind when applying the model:
-  Ideally the model is used after total reimbursement of the project (ex-post). In that case, actual data
on Y, K and L development during the project’s lifetime is available.
-  The model should only be used for greenfield and expansion projects. Unfortunately model is not
sector-specific as this data is not readily available.
-  Calculations are based on the total investment costs of a project, not the contribution of DEG (only
the project as a whole contributes to employment).
Within DEG, due to some data issues, we are not yet able to calculate ex-post. Instead, we used data
from 2000-2010 to make estimations for the commitments in 2012.
-  A spreadsheet was built to calculate the change in employment (ΔLf) brought about by a USD 10.000
investment for approximately 100 countries (depending on data availability).
-  For each country, DEG aggregated the total investment volumes of the projects DEG participated in.
-  Multiply both indicators
Estimating induced employment effects using Cobb-Douglas function / Washington / January 29th
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Employment effects for infrastructure commitments 2012
DEG highly underestimates employment effects
Aggregated total
investment volume
in USD
Total dL per
USD 10.000
Induced employment
from model
Total employment
in the GPR
COTE D'IVOIRE
398.520.000
0,25
10.051
57
GHANA
394.800.000
6,75
266.562
10
1.134.755.963
1,73
195.752
6.920
INDONESIA
174.318.206
0,74
12.962
180
MEXICO
47.400.000
0,03
158
428
NAMIBIA
15.360.000
0,19
296
124
NICARAGUA
103.320.000
n/a
PERU
747.480.000
0,50
37.133
25
SRI LANKA
25.320.000
1,27
3.212
50
SOUTH AFRICA
853.560.000
0,13
11.390
119
URUGUAY
306.000.000
0,16
4.806
25
4.200.834.169
-
542.322
7.938
Country
INDIA
SUM
Estimating induced employment effects using Cobb-Douglas function / Washington / January 29th
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Thank you for your attention!
Department for Corporate Strategy
and Development Policy
Chrsitiane Rudolph
DIrector
DEG – Deutsche Investitions- und
Entwicklungsgesellschaft mbH
Kämmergasse 22
50676 Cologne
Phone
Fax
+49 221 4986 – 1530
+49 221 4986 - 1292
christiane.rudolph@deginvest.de
Estimating induced employment effects using Cobb-Douglas function / Washington / January 29th
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Country ranking for “total dL per USD 10.000”
Based on data from 2000-2010
Country
Malawi
Congo
Uganda
Cambodia
Tanzania
Tajikistan
Nepal
Lao PDR
Ghana
Chad
Afghanistan
Gambia, The
Niger
Eritrea
Bangladesh
Moldova
CAR
Georgia
Benin
Vietnam
Madagascar
Total dL per Country
USD 10.000
21,37
14,64
12,78
11,54
10,18
9,64
8,03
7,43
6,75
6,53
5,61
5,34
5,06
4,97
4,65
4,23
3,79
3,69
3,49
3,27
2,87
Kenya
Zambia
Guyana
Mali
Senegal
Togo
India
Guinea
Uzbekistan
Honduras
Sri Lanka
Sudan
Lesotho
China
El Salvador
Philippines
Liberia
Mauritania
Djibouti
Mongolia
Pakistan
Total dL per Country
USD 10.000
2,70
2,63
2,51
2,23
2,21
1,92
1,73
1,72
1,66
1,37
1,27
1,23
1,18
1,13
1,10
1,05
1,05
1,05
1,04
1,01
1,00
Bhutan
Azerbaijan
Jordan
Macedonia
Turkmenistan
Ukraine
Angola
Bolivia
Indonesia
Dom. Rep.
Cuba
Vanuatu
Belarus
Cameroon
Guatemala
Bulgaria
Peru
Timor-Leste
Paraguay
Egypt,
Romania
Total dL per Country
USD 10.000
0,98
0,97
0,93
0,91
0,89
0,86
0,78
0,77
0,74
0,73
0,71
0,70
0,67
0,65
0,57
0,50
0,50
0,49
0,49
0,49
0,47
Papua New Guinea
West Bank and Gaza
Kazakhstan
St. Vincent
Thailand
Morocco
Ecuador
Yemen, Rep.
Lithuania
Bosnia and Herz.
Syria
Colombia
Maldives
Cote d'Ivoire
Congo, Rep.
Belize
Mauritius
Latvia
Russia
Panama
Jamaica
Estimating induced employment effects using Cobb-Douglas function / Washington / January 29th
Total dL per Country
USD 10.000
0,44
0,44
0,43
0,43
0,41
0,39
0,39
0,37
0,31
0,30
0,30
0,28
0,27
0,25
0,25
0,24
0,23
0,23
0,22
0,22
0,22
Brazil
Swaziland
Tunisia
Namibia
Costa Rica
Uruguay
Botswana
Argentina
South Africa
Turkey
Malaysia
Iran
Tonga
St. Lucia
Venezuela
Chile
Algeria
Mexico
Libya
Total dL per
USD 10.000
0,21
0,20
0,20
0,19
0,16
0,16
0,14
0,14
0,13
0,13
0,10
0,10
0,09
0,08
0,06
0,06
0,04
0,03
0,03
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