Working Paper No. 4
Enterprise Agglomeration, Output Prices, and Physical
Productivity: Firm-Level Evidence from Ethiopia
1
1
2
Eyerusalem Siba Måns Söderbom Arne Bigsten and Mulu Gebreeyesus
Abstract
We use census panel data on Ethiopian manufacturing firms to analyze the connections between
enterprise agglomeration, firm-level output prices and physical productivity. We find a negative
and statistically significant relationship between the agglomeration of firms that produce a given
product in a given location and the price of that product in the location. We further find a positive
and statistically significant relationship between the agglomeration of firms that produce a given
product in a location and the physical productivity of firms in the same location producing that
product. These results are consistent with the notion that agglomeration generates higher
competitive pressure and positive externalities. The net effect of agglomeration of own-product
firms on firmlevel revenues is close to zero, suggesting that firms do not have strong incentives
to agglomerate endogenously. Across firms that produce different products, we find no
statistically significant relationship between agglomeration and firm-level output prices and
productivity.
Keywords: agglomeration, productivity, output prices, firm-level data, Ethiopia, Africa, manufacturing
JEL classification: D2, D4, L6, O1, O3, O4
1University of Gothenburg, Sweden 2UNU-MERIIT; corresponding author email:
[email protected]
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Learning to Compete (L2C) is a collaborative research program of the Africa Growth Initiative at Brookings
(AGI), the African Development Bank, (AfDB), and the United Nations University World Institute for
Development Economics Research (UNU-WIDER) on industrial development in Africa. Outputs in this Working
Paper Series have been supported by all three institutions.
AGI-Brookings is grateful for the contribution of an anonymous donor for funding its work under the
collaborative research program.
The views expressed in this publication are those of the author(s), and do not reflect the views of the Institution,
its management, or its other scholars. Publication does not imply endorsement by any of the collaborating
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%"&
45 8@:G7:G< &6C>:G :C@6G9 - :GGN 6C9 *6@:H T8DCDB:IG>8 .DDAH ;DG C6ANO>C< '6G@:I
)JI8DB:HU &''# ' '&'%+)"* V
45 <=>DC * , AJC9:AA , !G>WI= * "DL>II 6C9 - *G6CIA T.=: X:8IH D; CIGN DC #C8JB7:CI
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'&'%"* ' )&*"+"'& V
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45 ><HI:C 6C9 ' !:7G::N:HJH T.=: -B6AA I=: 2DJC< 6C9 I=: *GD9J8I>K: :I:GB>C6CIH D;
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DJ<A6H *GD9J8I>DC *6G6B:I:GH
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45 : &J8>D $ $ $ ":G8: 6C9 !D>8DA:6 T.=: X:8IH D; MI:GC6A>I>:H DC *GD9J8I>K>IN !GDLI=
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45
6;8=6BEH ' T'6CJ;68IJG>C< !GDLI= 6C9 <<ADB:G6I>DC X:8IHU 1DG@>C< *6E:G )M;DG9
/C>K:GH>IN D; )M;DG9 - 45
6;8=6BEH ' 6C9 - A "6B>C: T >GB *GD9J8I>K>IN 16<:H 6C9 <<ADB:G6I>DC MI:GC6A>I>:HU
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6;8=6BEH ' 6C9 ' -Z9:G7DB T(:ILDG@ *GDM>B>IN 6C9 JH>C:HH *G68I>8:H >C ;G>86C '6CJ;68
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DHI:G & $ "6AI>L6C<:G 6C9 -NK:GHDC T,:6AAD86I>DC >GB .JGCDK:G 6C9 W8>:C8N -:A:8
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DHI:G & $ "6AI>L6C<:G 6C9 -NK:GHDC T.=: -ADL !GDLI= D; (:L *A6CIH &:6GC>C< 7DJI
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%&+ & ,$+,)$ !& V
45 !A6:H:G & " %6AA6A $ -8=:>C@B6C 6C9 -=A:>;:G T!GDLI= >C >I>:HU ',)&$ '
'$"+"$ '&'%/ V
45 !DA97:G< * % %=6C9:AL6A ( *6K8C>@ 6C9 * .DE6ADK6 T#BEDGI:9 #CI:GB:9>6I: #CEJIH 6C9
DB:HI>8 *GD9J8I !GDLI= K>9:C8: ;GDB #C9>6U 1DG@>C< *6E:G 6B7G>9<: ' (,
45 !DA97:G< * % % %=6C9:AL6A ( *6K8C>@ 6C9 * .DE6ADK6 T'JAI>EGD9J8I >GBH 6C9 *GD9J8I
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45 "6G9>C< ' -Z9:G7DB 6C9
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45 ":C9:GHDC $ 0 T'6GH=6AASH -86A: 8DCDB>:HU ',)&$ ' )& '&'%"* V
45 ":C9:GHDC $ 0 %JC8DGD 6C9 ' .JGC:G T#C9JHIG>6A :K:ADEB:CI >C >I>:HU ',)&$ ' '
$"+"$ '&'%/ V
45 $68D7H $ ! '&'%/ ' "+"* (:L 2DG@ ,6C9DB "DJH: 45 %6I6N6B6 " - &J 6C9 $ , .N7DJI T >GB
A:K:A *GD9J8I>K>IN -IJ9>:H #AAJH>DCH 6C9 6 -DAJI>DCU
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45 %:AA:G 1 T!:D<G6E=>8 &D86A>O6I>DC D; #CI:GC6I>DC6A .:8=CDAD<N >XJH>DCU %)"& '&'%"
-". 45 %=6C9:AL6A T.=: &DC< 6C9 -=DGI D; +J6A>IN &699:GHU -". ' '&'%" +,"* V
45 '6GH=6AA )"&"($* ' '&'%"* !J>AA:76J9 9>I>DC &DC9DC '68B>AA6C 45 ':A>IO ' $ THI>B6I>C<
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45 *6<: $ T6C ;G>86 #C9JHIG>6A>H:U ',)&$ ' )"& '&'%"* HJEEA >>V>>
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V
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++"*+"* 6 V
45 -NK:GHDC T'6G@:I -IGJ8IJG: 6C9 *GD9J8I>K>IN DC8G:I: M6BEA:U ',)&$ ' '$"+"$ '&
'%/ 7 V
45 -NK:GHDC T*G>8:H -E6I>6A DBE:I>I>DC 6C9 ":I:GD<:CDJH *GD9J8:GH C BE>G>86A .:HIU ',)&$
' &,*+)"$ '&'%"* V
45 06C >:H:7GD:8@ $ TMEDGI>C< ,6>H:H *GD9J8I>K>IN >C HJ7
-6=6G6C ;G>86C '6CJ;68IJG>C< >GBHU
',)&$ ' &+)&+"'&$ '&'%"* 6 V
45 06C >:H:7GD:8@ $ T >GB ->O: '6II:GH !GDLI= 6C9 *GD9J8I>K>IN !GDLI= >C ;G>86C '6CJ;68IJG
>C<U '&'%" -$'(%&+ & ,$+,)$ !& 7 V
45 06C >:H:7GD:8@ $ T.=: -:CH>I>K>IN D; *GD9J8I>K>IN HI>B6I:HU ',)&$ ' ,*"&** & '&'%"
++"*+"* V
Figure 1: The Geographical Distribution of Firms 2005/6
Note: The green filled circles indicate locations in which at least one firm was located in 2005/6.
The size of the circles indicates the number of firms located in that town (see graph legend).
Source: Number of firms in each town is calculated based on CSA plant level data (1996-2006)
26
Figure 2: Firm and Employment Trends, 1996-2006
1200
160
140
1000
120
800
100
600
80
60
400
40
200
0
1995
20
1997
1999
2001
Number of firms (left axis)
2003
2005
0
2007
Average firm employment (right axis)
Source: Own calculation based on CSA plant level data (1996-2006)
27
Table 1: Summary Statistics
Mean
Std. Dev.
log Value-added per employee
9.35
1.34
log Employment
3.77
1.39
log Capital stock per employee
9.65
1.94
log Energy expenditures per employee
6.61
1.55
log Raw material expenditures per employee
9.61
1.47
Number of firms in the same town and sector producing the same product as
firm i, at time (NSAMEPROD)
Number of firms in the same town and sector as firm i not producing the same
product as firm i, at time t (NDIFPRODSAMESEC)
Number of firms in the same town as firm i that belong to a different sector than
i, at time t (NDIFSEC)
Share of new entrants in own town and sector, at time t
9.41
12.57
25.24
35.64
216.46
201.16
0.17
0.21
Share of exporters in own town and sector, at time t
0.06
0.20
log Total employment in own town and same sector, at time t
8.49
2.80
log Total employment in own town and different sector, at time t
8.20
3.06
4858
Observations
1341
Firms
Note: Financial variables are expressed in constant 1994/95 Ethiopian Birr. The exchange rate to the USD in
January 1995 was 5.53.
Source: Own calculation based on CSA plant level data (1996-2006)
28
-0.754***
(0.236)
-0.0431
(0.131)
0.0149
(0.0353)
-0.220***
(0.0203)
0.144***
(0.0177)
-0.277***
(0.0197)
0.334***
(0.0275)
-0.648***
(0.220)
0.00996
(0.130)
0.00489
(0.0335)
(2)
0.152***
(0.0180)
0.00506
(0.0126)
0.0543**
(0.0249)
0.0115
(0.00939)
0.221***
(0.0176)
-0.285***
(0.0200)
-0.685***
(0.219)
-0.0483
(0.130)
0.0171
(0.0324)
(3)
-0.0302
(0.0422)
0.0777
(0.0520)
0.187
(0.126)
-0.756***
(0.236)
-0.0524
(0.133)
0.00924
(0.0353)
-0.220***
(0.0203)
(4)
-0.0177
(0.0418)
0.0828
(0.0516)
0.162
(0.114)
0.144***
(0.0177)
-0.277***
(0.0197)
0.334***
(0.0275)
-0.649***
(0.220)
0.00313
(0.132)
-0.00100
(0.0334)
(5)
0.00392
(0.0125)
0.0566**
(0.0245)
0.0113
(0.00938)
0.221***
(0.0175)
-0.0276
(0.0417)
0.0934*
(0.0512)
0.168
(0.119)
0.152***
(0.0180)
-0.285***
(0.0200)
-0.688***
(0.219)
-0.0574
(0.132)
0.0108
(0.0323)
(6)
29
Observations
14161
14161
14161
14161
14161
14161
Firms
1176
1176
1176
1176
1176
1176
Note: The dependent variable is log price. All regressions include year dummies, town dummies, product dummies and controls for firm fixed effects. Standard errors are
clustered at the level of the firm. Significance at the 10, 5 and 1 percent level is indicated by *, ** and ***, respectively.
Revenue share
Only firm in town
Only firm in this sector in town
Only firm with this product in town
log Raw materials
log Energy
log Employment
log Capital stock
All inputs
Quantity of output
TFP
NDIFSEC / 100
NDIFPRODSAMESEC / 100
NSAMEPROD / 100
(1)
Table 2: Agglomeration and Output Prices
0.911**
(0.394)
0.0346
(0.222)
-0.0383
(0.0535)
0.965***
(0.00841)
0.922**
(0.394)
0.0968
(0.224)
-0.0472
(0.0532)
1.084***
(0.0389)
(2)
log Output
0.966***
(0.00841)
0.0170
(0.0224)
0.151***
(0.0477)
0.0819***
(0.0172)
0.676***
(0.0275)
0.837**
(0.388)
-0.0548
(0.222)
-0.0124
(0.0515)
(3)
log Output
0.0451
(0.0538)
-0.188**
(0.0874)
-0.0666
(0.156)
0.915**
(0.394)
0.0455
(0.225)
-0.0274
(0.0538)
(4)
TFP
0.0433
(0.0533)
-0.173*
(0.0890)
-0.0819
(0.157)
0.965***
(0.00841)
0.926**
(0.395)
0.107
(0.227)
-0.0369
(0.0536)
1.082***
(0.0388)
(5)
log Output
0.0177
(0.0224)
0.149***
(0.0474)
0.0822***
(0.0172)
0.675***
(0.0274)
0.0113
(0.0525)
-0.140*
(0.0824)
-0.0707
(0.145)
0.966***
(0.00841)
0.839**
(0.388)
-0.0498
(0.223)
-0.00382
(0.0518)
(6)
log Output
30
Observations
14161
14161
14161
14161
14161
14161
Firms
1176
1176
1176
1176
1176
1176
Note: All regressions include year dummies, town dummies, product dummies and controls for firm fixed effects. Standard errors are clustered at the level of the firm.
Significance at the 10, 5 and 1 percent level is indicated by *, ** and ***, respectively.
Revenue share
Only firm in town
Only firm in this sector in town
Only firm with this product in town
log Raw materials
log Energy
log Employment
log Capital stock
All inputs
NDIFSEC / 100
NDIFPRODSAMESEC / 100
NSAMEPROD / 100
(1)
TFP
Table 3: Agglomeration and Productivity
-0.653*
(0.368)
-0.0331
(0.263)
-0.0546
(0.0567)
-0.181***
(0.0259)
0.930**
(0.425)
0.0696
(0.297)
0.0103
(0.0633)
(2)
TFP
-0.826***
(0.279)
-0.0901
(0.153)
0.0292
(0.0395)
-0.221***
(0.0203)
0.283
(0.328)
0.111
(0.135)
-0.0241
(0.0270)
0.272
(0.481)
-0.205
(0.168)
0.00780
(0.0317)
0.838*
(0.461)
0.138
(0.248)
-0.0416
(0.0569)
Interaction terms: Product type
x agglomeration variables
(3)
(4)
log price
TFP
-0.0485
(0.0313)
0.00905
(0.0223)
-0.748***
(0.236)
-0.0414
(0.131)
0.0141
(0.0356)
-0.220***
(0.0204)
(5)
log price
0.0605
(0.0391)
0.00998
(0.0222)
0.909**
(0.394)
0.0434
(0.222)
-0.0395
(0.0538)
(6)
TFP
Cluster employment
31
Observations
8245
8245
14161
14161
14161
14161
Firms
699
699
1177
1177
1176
1176
Note: All regressions include year dummies, town dummies, product dummies and controls for firm fixed effects. Standard errors are
clustered at the level of the firm. Significance at the 10, 5 and 1 percent level is indicated by *, ** and ***, respectively. The variables
NSAMEPRD, NDIFPRODSAMESEC and NDIFSEC are lagged in columns (1)-(2).
Homogeneous product x
NSAMEPROD / 100
Homogeneous product x
NDIFPRODSAMESEC / 100
Homogeneous product x
NDIFSEC / 100
Number of employees in own
town & own sector
Number of employees in own
town & different sector
TFP
NDIFSEC / 100
NDIFPRODSAMESEC / 100
NSAMEPROD / 100
(1)
log price
Lagged agglomeration variables
Table 4: Robustness to Lag Effects, Product Type Interaction Effects, and Employment Based Measures of Agglomeration
Table 5: Tests for Agglomeration Effects across Towns
Dependent variable: log price
(1)
(2)
NSAMEPROD / 100
NDIFPRODSAMESEC / 100
NDIFSEC / 100
TFP
Number of firms in nearest neighboring
town /100
Number of firms in nearest neighboring
town producing the same product /100
Number of firms in nearest neighboring
town producing different product /100
-0.768***
(0.236)
-0.0466
(0.132)
0.0111
(0.0363)
-0.220***
(0.0204)
-0.0991*
(0.0513)
-0.761***
(0.236)
-0.0496
(0.132)
0.0126
(0.0363)
-0.221***
(0.0204)
Dependent variable: TFP
(3)
(4)
0.935**
(0.394)
0.0464
(0.223)
-0.0241
(0.0542)
0.946**
(0.395)
0.0420
(0.222)
-0.0219
(0.0544)
0.186*
(0.100)
1.239
(1.811)
-0.113**
(0.0539)
2.158
(2.027)
0.166*
(0.100)
Observations
14161
14161
14161
14161
Firms
1176
1176
1176
1176
Note: All regressions include year dummies, town dummies, product dummies and controls for firm fixed
effects. Standard errors are clustered at the level of the firm. Significance at the 10, 5 and 1 percent level is
indicated by *, ** and ***, respectively.
32
Table 6: Tests for Heterogeneous Agglomeration Effects Depending on the Share of New
Entrants and Exporters in Own Town and Sector
NSAMEPROD / 100
NDIFPRODSAMESEC / 100
NDIFSEC / 100
TFP
Share of new entrants in own sector
and town
Share of new entrants in own sector
and town x NSAMEPROD / 100
Share of new entrants in own sector
and town x NDIFPRODSAMESEC /
100
Share of new entrants in own sector
and town x NDIFSEC / 100
Share of exporters in own sector
and town
Share of exporters in own sector
and town x NSAMEPROD / 100
Share of exporters in own sector
and town x NDIFPRODSAMESEC /
100
Share of exporters in own sector
and town x NDIFSEC / 100
Observations
Firms
(1)
log price
(2)
TFP
(3)
log price
(4)
TFP
-0.386
(0.309)
0.0821
(0.152)
-0.0383
(0.0357)
-0.220***
(0.0202)
-0.00283
(0.0454)
-2.094*
(1.084)
-0.891**
(0.371)
0.327
(0.547)
0.0234
(0.224)
0.000831
(0.0555)
-0.810***
(0.253)
0.0894
(0.161)
0.0145
(0.0366)
-0.221***
(0.0205)
1.066***
(0.391)
0.109
(0.236)
-0.0141
(0.0555)
0.253***
(0.0543)
-0.113
(0.0863)
-0.0467
(0.110)
3.384
(4.705)
-4.162
(2.773)
0.254**
(0.122)
-7.256
(6.189)
-2.396
(2.849)
0.0327
(0.0878)
-0.0977
(0.0913)
14161
1176
14161
1176
14161
1176
-0.142
(0.0885)
2.968**
(1.485)
0.313
(0.505)
14161
1176
33
Gunny bags
Hosieries
Injection of 100A
Iron bars
Iron sheets
Jano thread
Leather garment*
Leather shoes and boots*
Leather sole
Leather upper and lining
Lemonade (soft drinks)*
Canvas and rubber shoes
Capsules
Carbon dioxide
Carpets
Cement*
Cement blocks*
Cement floor tiles*
Cement tubes
Cheese
Cigarettes
Coffe (Milled)*
Plastic sole
Plastic footwear*
Particle board
Paraffine*
Paper
Palstic crate
Paints
Oxygen
Orange juce
Ointment
Oil cakes*
Nylon fabrics*
Nails*
Motor vehicles spring
Molasses
Mineral water
Milk pasterurized
Metalic window
Metalic door
Meat
Marmalade
Marble
Malt
Macaroni and pasta
Liquor*
34
Cotton fabrics*
Lime
Polyethylene products
Note:* indicates products used to check robustness of the main results to product homogeneity
Glasses
Bricks of clay*
Gravel*
Glass bottles
Bread*
Candles
Galleta
Boxing paper
Butter and ghee
Flour (wheat)*
Foam
Blankets
Fafa, dube, edget,metin
Flour (other)
Biscuts and cakes (excl. galleta)
Bed sheet
Beer*
Electric wires
Embroidery thread
Ballpen
Crust hides and wetblue hides*
Edible oil*
Antibiotics
Crown cork
Alchohol (non-drink)
Animal feed
Cotton yarn*
Acrylic (yarn)
Appendix Table 1: Products in the dataset
APPENDIX
Zign and shiro wet (minchet abish)
Wires*
Wine
Wearing apparel (leather)
Wearing apparel (excl. leather)
Vegetable soup
Vasilin*
Varnishes and lacquers
Tyres
Tubes
Tomato paste
Timber*
Tea*
Tablets
Syrup
Sweets (candy)
Sweater
Sugar*
Soap
Shirts
Sewing thread
Semiprocessed skins
Raw cotton
185
186
189
194
239
245
265
299
1998
1999
2000
2001
2002
2003
2004
2006
41
38
39
36
41
45
45
52
1998
1999
2000
2001
2002
2003
2004
2006
49%
41
1997
Growth 96-06
35
Chemicals
1996
Year
115%
154
Growth 96-06
139
1997
Food
1996
Year
67%
35
29
28
28
26
25
23
21
22
21
Textiles
320%
63
42
39
37
27
27
30
26
23
15
Rubber&plastics Non-metal
Beverage
67%
137
117
111
96
81
76
78
80
89
82
31%
42
38
36
34
31
33
33
32
33
32
Metal
Apparel
112
85
83
72
60
57
45
45
47
42
30%
30
35
32
29
24
25
27
26
26
23
8
17
17
15
14
15
15
14
11
11
-36%
9
9
9
7
7
13
17
17
13
14
113%
Machinery
Leather
35
167%
Appendix Table 2 Growth in the Number of Establishments by Sector
Furniture
Footwear
55
144%
183
161
157
146
112
113
115
114
108
75
-22%
43
45
41
38
37
37
35
46
49
Others
Wood
26
0%
12
8
8
7
7
10
10
12
11
12
-19%
21
20
17
21
14
16
16
16
23
98%
85
72
73
73
51
63
55
53
45
43
Paper&printing