52nd Philippine Economic Society Annual Meeting
Science, Technology, Research & Innovation for
Development (STRIDE) Panel
Trade Reforms, Competition,
and Innovation in the
Philippines
Rafaelita M. Aldaba
Intercontinental Hotel, Makati City
November 14, 2014 3:30-5:00 PM
Main Objective
• What is the impact of trade liberalization on
the manufacturing firms’ innovative
activities?
• With competition as the main channel linking
trade reforms with innovation, did the
increase in competition arising from trade
reforms lead to increases in innovation?
Outline
I. Industry indicators: trade, growth,
performance & structure, innovation/R&D
II. Theoretical Literature: Trade, competition
and innovation
III. Empirical model
IV. Data & analysis of regression results
V. Broad conclusions & policy suggestions
Part I. Industry Background
Average Manufacturing Tariff Rates
25
Manufacturing
Food manufacturing
20
Beverages
Tobacco
Textile & garments
15
Leather & leather prods
Wood & wood products
10
Furniture & fixtures
Paper & paper products
Chemicals & chemical
5
Rubber & plastic prods
Non-metallic mineral
0
Basic metals
1998
1999
2000
2001
2002
2003
2004
• increases from 2002-2004, widening of tariff
dispersion between 1998 and 2004
Effective Protection Rates: 1985-2004
80
70
60
50
40
30
All Sectors
20
Agriculture
10
Manufacturing
Food Processing
0
1985 1986 1988 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
• Tariff reforms substantially reduced protection
Performance by sector
Growth Rate
1950s
1960s
1970s
GDP
6.2
4.8
5.7
1.7
3.0
4.7
Agri,Fishery,Forestry
4.8
4.2
3.9
1.1
1.8
3.0
Industry Sector
7.1
5.5
7.6
0.3
3.0
4.2
Manufacturing
9.4
5.7
5.9
0.9
2.5
4.1
Service Sector
6.7
4.7
5.2
3.3
3.6
5.8
Value Added
1950s
1960s
1970s
1980s
1990s
2000s
Agri,Fishery,Forestry
32.5
29.7
25.6
23.9
20.8
18.9
Industry Sector
30.6
32.6
38.3
38.0
34.1
33.1
Manufacturing
22.3
25.6
28.2
26.3
24.3
23.7
38.3
38.4
36.6
40.4
42.4
48.0
Service Sector
1980s
1990s
2000s
• Mfg growth sluggish from 1980s-1990s, modest
gains 2000s
Employment structure
1975-78
1980-89
1990-99
Agri,Fishery,Forestry
52.83
49.60
43.16
36.1
Industry Sector
15.23
14.49
15.98
15.1
Manufacturing
11.29
9.93
10.01
9.1
31.87
35.90
40.94
48.8
Service Sector
2000-09
• Mfg failed to create enough employment to
absorb new entrants to labor force





800K new entrants/year
3M unemployed ; 7.3M underemployed
Services cannot provide all the needed jobs
Manufacturing can employ skilled, semi-skilled, unskilled
Need for structural transformation
Manufacturing value added structure
1981-89
Consumer Goods
1990-99
2000-10
57
50
51
Food manufactures
44
36
40
Beverage industries
4
4
4
Footwear & wearing apparel
5
6
4
31
35
27
Chemical & chemical products
7
6
6
Products of petroleum & coal
12
17
14
10
13
19
Basic metal industries
3
2
3
Electrical machinery
3
6
12
Intermediate Goods
Capital Goods
• Consumer products dominated, intermediate
products declining
Total factor productivity growth, 2006
Industry
TFP
Industry
TFP
All manufacturing
-3.37
coke, petroleum,
chemicals & rubber
-4.76
food, beverages, &
tobacco
-1.44
non-metallic products
-0.65
textile
2.35
basic metal & fabricated metal
1.32
garments
0.99
machinery & equipment, motor
vehicles & other transport
-0.86
leather
9.54
furniture
1.86
wood, paper, &
publishing
-3.85
Other manufacturing
0.63
• Mfg TFP growth declined due to failure to invest in state of
the art technology, lack of investment in human capital,
lack of movement of resources towards manufacturing
Market concentration
Industry
Coke, Refined Petroleum and other Fuel Products
Tobacco Products
Beverages
Other non-metallic: flat glass
Motor Vehicles, Trailers, and Semi-trailers
Food
Other Non-Metallic Mineral products
CR4
79.8
72.0
62.4
82.4
57.2
55.7
54.3
• Manufacturing industry already contestable, CR4 in
most sectors below 35%, except for certain sectors
with CR4 ranging from 62 to 82%
Price Cost Margins
Roeger
Method
***
0.62
Beverages
***
0.59
Tobacco
***
0.60
Pottery, cement & other nonmetallic
***
0.50
Glass and Glass Products
***
0.45
Other chemicals
***
0.38
Paper and Paper Products
***
0.38
Industrial chemicals
***
0.34
Rubber products
Sector
Simple
Method
0.53
0.47
0.57
0.52
0.37
0.36
0.35
0.28
• Industry average is 29%, low from 8 to 19%, moderate
from 22 to 38%, but for certain sectors high PCM from
45% to 62%
R&D as % of GDP & R&D per capita
YEAR
PHIL
SING
THAI
MAL
INDO
2002
0.14
2.10
0.24
0.65
...
2003
0.13
2.05
0.26
...
...
YEAR
PHIL
SING
THAI
MAL
INDO
2002 2003
3.8
3.7
800.9 795.1
14.3 16.3
70.4
...
...
...
2004 2005
... 0.11
2.13 2.19
0.26 0.23
0.60
...
...
…
2004
...
878.6
16.7
70.4
...
2006 2007 2009
... 0.11
…
2.16 2.36 2.2
0.25 0.21 0.25
0.61
… 1.01
...
… 0.08
2005 2006
2007
3.4
...
3.6
945 986.4
1145.5
16
17.7
15.9
...
76.8 106.5 (‘08)
...
3.1 (‘09)
• In PPP$, constant 2005 prices
No. of researchers: total & per million
inhabitants
YEAR
PHIL
SING
THAI
MAL
YEAR
PHIL
SING
THAI
MAL
2002
2003
2004
2005
2007
... 9390
... 9407 9357
21871 23514 21359 28586 32198
... 42379
... 36967 42624
10731
... 17887
... 13416
2002
...
5288
...
440
2003
114
5527
657
...
2004
...
5826
...
705
2005
2007
110
779
6359
6840
564
645
... 816(‘08)
• Philippines has been underinvesting in R&D
Part II. Literature Review
(1).Competition & Innovation
•
•
•
•
•
•
Early endogenous growth & IO literature: competition is
detrimental to innovation, rents are major source of
innovation
Opposite view: competition fosters innovation , forces
firms to innovate to survive, firms escape competition
from rivals
Aghion et al (2001): inverted U-shaped relationship
between competition & innovation
Empirical studies: mixed results with more recent studies
pointing to a positive relationship between competition &
innovation
Creusen et al(2006), Hopman & Rojas-Romagosa (2010):
positive relationship, no evidence of inverted U
Gorodnichenco et al (2009): negative relationship
especially for firms far from frontier, no evidence of
inverted U
(2). Trade & competition
• Trade has a pro-competitive effect, open trade regime is a
powerful instrument to discipline firms that have market
power
• Import discipline hypothesis: competition from imports
constrains ability of firms to engage on anti-competitive
activities
• Empirical work: strong evidence supporting IDH
• Erdem & Tybout (2003), Tybout (2001):mark-ups decline with
import competition
• Harrison (1994), Krishna & Mitra (1998), De Melo & Urata
(1986), Levinsohn (1993), Warzynski (2002), Warzynski et al
(2002)
• Trade & productivity: industries facing greatest tariff reduction
& import competition have faster productivity growth
• Pavcnik (2002), Topalova (2003), Muendler (2002), Amite &
Konings(2007), Schor (2003), Fernandes (2007), Aldaba (2010)
(3). Trade & innovation
• International trade affects innovation through
competition
• Aghion & Burgess (2003): liberalization
encourages innovation in industries close to frontier
• Griffith, Harrison & Simpson (2006): EU SMP
product market reforms increased competition
which led to an increase in R&D
• Fernandes (2009): import competition has a
positive effect on product quality upgrading
• Bloom, Draca & V. Reenen (2010):Chinese import
competition increases innovation & TFP within
surviving European firms, it reduces employment &
survival probabilities in low-tech firms & they exit
much more rapidly than high-tech firms in response
to Chinese competition
Trade, competition, innovation
• Trade increases competition, through competition
channel, it has positive effect on innovation & leads
to selection of most productive firms
• Trade liberalization induces least productive firms to
exit & most productive non-exporters to become
exporters (Pavcnik, Topalova, Tybout)
• Impulliti & Licandro (2010):links these 3 effects,
trade affects both selection & innovation thru
competition, tradelibfirms, competition,
mark-upprofit, productivity threshold
above which firms can profitably produceless
productive firms exit, resources reallocated from
exiting firms to higher productivity surviving firms
which innovate at faster rate
Part III: Analytical Framework
Trade liberalization affects innovation through competition
• where i indexes firms, j industries and t years
• Z is a vector of control variables that may affect the firm’s
innovation efforts: TFP gap, age, total workers, entry and exit
indicators
• model is estimated using a two-stage instrumental variables (IV)
technique & Tobit regression
• 2 trade indicators: EPRs & output tariff rates
• Firms are grouped based on trade orientation: non-traded, purely
importable, purely exportable, mixed sector
Specific model
• Competition function
PCMijt = l0 Tariffjt +l1TGapijt +l2 Ageijt +l3Sizeijt +l4Exit ijt +l5 Entry ijt +l6 Time+l7 Ind +e
• Innovation function
RDijt = d 0 PCMjt +d 1TGapijt +d 2 Ageijt +d 3 Sizeijt +d 4 Exit ijt +d 5 Entry ijt +d 6 Time +d 7 Ind +r
PCM: price cost margin
Tariff and EPR: trade reform indicator
TGap: technology gap, distance to the technological frontier
RD: research and development expenditures
Age, Size, Exit and Entry : firm characteristics
+ relationship between competition & trade,  tariff PCM or
profitability, with competition, competition is main channel through which
trade affects innovation
- relationship between competition & innovation, inefficient firms will be
forced out of the market, resources reallocated to more productive surviving
firms’ who innovate at a faster pace
Part IV. Data & Analysis of Results
Summary Statistics: All Mfg
Variable
Obs
Mean
Std. Dev.
Min
Max
Total revenue (P million)
8296
736
5200
0.065
233000
Compensation (in P million)
8296
43
141
0
2640
Total costs (in million pesos)
Book value of fixed assets
Capital cost
Financial cost of capital
Price cost margin
8296
8296
8296
8296
8296
594
180
0.07
15
0.053
4510
1000
0.059
102
0.259
0.026
0
0.03
0
-6.086
203000
47600
0.219
5750
0.96
R&D (as % of value added)
Age of firm (in years)
Total number of workers
TFP Gap
Tariff (in percent)
Net entry
8296
8263
8296
8296
8296
8296
0.005
17
264
0.371
9.087
-3
0.068
14
703
0.146
6.309
6.9
0
0
10
0
1.073
-52
5.373
100
14647
1.054
60
6
• Panel data covering 8 years from 1996 to 2006
Summary Statistics
by trade orientation
Variable
Non-traded
Purely
Importable
Purely
exportable
Mixed sector
Obs
Obs
Obs
Obs
Mean
Mean
Mean
Mean
R&D (%)
377
0.0018
775
0.0045
628
0.0026
6516
0.0055
PCM
377
0.0372
775
0.0920
628
0.0548
6516
0.0495
No. workers
377
174
775
210
628
109
6516
291
Age
373
15.4
771
18.6887
624
18.5016
6495
16.3150
TFP gap
377
0.3859
775
0.3551
628
0.3508
6516
0.3740
Tariff
377
9.2912
775
13.3604
628
8.9374
6516
8.5812
EPR
377
12.0489
775
10.0601
628
13.6641
6516
13.7386
•
Non-traded: exports & imports are 0 or <1% (custom tailoring, slaughtering); purely
importable: minimal exports & significant imports (atleast 10%, meat products, butter,
cheese, auto assembly); purely exportable: minimal imports & significant exports
(tobacco leaf); mixed: substantial imports & exports (auto parts & components, semiconductor, chemicals, soap)
All Manufacturing: IV Regression
STAGE 1
PCM
TARIFF
Age
0.00031
0.0026855
-0.00001
Workers
0.0000128
-2.54176***
TFP Gap
0.1052527
0.0069049***
Trade
0.0022272
Constant 1.096718***
Year
Industry
Obs
R2
0.1022577
Y
Y
8263
0.0672
STAGE 2
EPR
RD
-0.0007018*
PCM
0.0004111
-0.0000282***
0.00000648
-1.864594***
0.0532788
-0.000508
0.0004102
Y
Y
8263
0.0723
TARIFF
-0.114983*
-0.0704618
Age
-0.00044
-0.0005744
Workers -0.00000538*
-0.00000285
TFP Gap
-0.11871
-0.1816651
Constant 0.09242
-0.0904484
Year
Y
Industry
Y
Obs
8263
R2
0.0044
EPR
-0.1189551
0.1272509
0.0000955
0.000136
-0.00000422
0.00000396
-0.1017999
0.2370014
0.0000826
0.0001225
Y
Y
8263
All Manufacturing: Tobit Regression
PCM
Trade
Workers
STAGE 1
TARIFF
EPR
0.0012992***
0.0000996
-0.000547
-0.0001304
-0.0000211*** -0.000021*** Workers
-0.00000405
Age
TFP Gap
-10.05107
-5.906214
-17.95807
-0.0005009***
-0.0004926
-0.0001365
-0.0003815
-0.0003545* Age
-0.0064991*
-0.0063593
-0.0002017
-0.0002018
-0.0035068
-0.0068841
-5.04204
-4.551069
-7.30149
-22.14417
-0.5995352
-0.7849602
-2.761603
Y
-8.364468
Y
Y
Y
8263
8263
0.1207
0.12
-1.242917*** -1.234866*** TFP Gap
Constant 0.4478913***
-0.0196814
R2
-4.05E-06
-10.44935*
-0.0003406*
-0.0393622
Year
Industry
Obs
LNRD
PCM
STAGE 2
TARIFF
EPR
-0.039239
0.4647943
Constant
Y
-0.0182534
Y
Y
Y
8263
8263
Year
Industry
Obs
0.1207
0.12
R2
IV Regression: Mixed Sector
PCM
Age
Workers
TFP Gap
TRADE
STAGE 1
EPR
TARIFF
-0.0006029
-0.0004183
RD
-0.0007068 PCM
OBS
R2
-0.0906546
-0.0678799
0.0001018
-0.0001255
0.0001219
-0.0001337
-3.80E-06
-2.70E-06
-3.09E-06
-2.58E-06
-0.1114657
-0.126285
-0.0453125
-0.1348436
CONSTANT 0.0527683
0.0256419
-0.0546182
Y
Y
6495
Age
-1.855282*** -1.983007*** Workers
-0.0592093
-0.061406
.006108*** .0017411*** TFP Gap
-0.0014744
-0.000455
Constant
YEAR
INDUSTRY
-.1295984*
-0.0682428
-0.0004806
-.0000288*** -.0000277***
-6.37E-06
-6.69E-06
Y
Y
6495
0.0736
Y
Y
6495
0.0723
STAGE 2
EPR
TARIFF
-0.0512104
Y
YEAR
Y
INDUSTRY
6495
OBS
R2
0.0045
0.0043
Mixed Sector: Tobit Regression
PCM
Age
Workers
STAGE 1
EPR
TARIFF
-.0003994 *
-0.0002435
LnRD
-.0003936* PCM
-0.0002436
-.0000216*** -.0000219***
-4.33E-06
-4.34E-06
Workers
TFP Gap
-1.332122*** -1.322314*** Age
-0.0474155 -0.0472372
TRADE
.0030229***
-0.001026
Constant
YEAR
INDUSTRY
OBS
R2
.0005372* TFP Gap
-0.0002858
.5039854***
STAGE 2
EPR
TARIFF
-5.733137
-3.639965
-8.414397
-6.594807
-.0003721*** -.000431***
-0.0000925
(.0001546)*
-.0060584**
-0.0029606
-0.0070863
-0.003938
0.9419193
-4.813166
-2.583998
-8.691929
-4.12588
CONSTANT -5.503807***
.4655379***
-0.0301794
Y
Y
6495
-0.0258772
Y
Y
6495
0.1189
0.1182
YEAR
INDUSTRY
OBS
-1.890225
Y
Y
6495
-3.403656
Y
Y
6495
Mixed Sector: IV Regression (net entry)
PCM
Age
STAGE 1
TARIFF
EPR
-0.0005626
-0.0006576
STAGE 2
LNRD
TARIFF
EPR
PCM
-0.1336937*
-0.0956812
0.0724602
0.0727616
0.0001007
0.0001196
0.0001213
0.0001289
-0.00000371
-0.00000302
0.00000281
0.00000274
-0.1139012
-0.0523605
0.1294799
0.139814
0.0001094
0.0001017
0.0001416
0.0001321
0.0519422
0.0286122
0.0506673
6495
0.05666
6495
0.0014297
Workers
0.00045
-0.0000292*** 0.0000285*** Age
0.0003939
0.00000654
TFP Gap -1.793328*** -1.919879***
Net Entry
Trade
0.00000622
0.0603512
-0.0005875
-0.000747*
0.0581184
0.000448
TFP Gap
0.0057119*** 0.0016159*** Net Entry
0.0004647
Constant
OBS
R2
Workers
0.0004418
0.734464*** Constant
6495
0.0323591
6495
0.0723
0.0723
OBS
Mixed Sector: Tobit Regression (net entry)
PCM
Age
STAGE 1
TARIFF
EPR
-0.0004035* -0.000397*
0.0002437
STAGE 2
LNRD
TARIFF
EPR
PCM
-6.083573*
-8.772339
3.682705
6.686467
-0.0059966**
-0.0070351*
0.0030161
0.0040205
0.0002438
Workers -0.0000216*** -0.0000218***
Age
0.00000434 0.00000434
TFP Gap -1.331775*** -1.321962***
0.0474237
0.047248
Trade Ind 0.0030443*** 0.0005407*
Net Entry
Workers
0.001027
0.000286
0.0002632
0.0002235
0.0005458
0.0005457
TFP Gap
Net Entry
Constant 0.4598655*** 0.4916265*** Constant
OBS
R2
0.0267683
6495
0.1188
0.0235211
6495
0.1181
OBS
-0.0003815*** -0.0004406***
0.0000937
0.0001567
0.4578945
-3.076967
4.868762
8.810686
-0.013027**
-0.0125073*
0.0059947
0.0070161
-2.754255
-1.409861
1.85854
6495
3.355992
6495
Part V. Conclusions & policy
Implications
• Trade liberalization affects firm innovation through competition
 An increase in tariffs will increase profitability & reduce competition
likely result in reduced innovation, holding all else equal
• For overall manufacturing, both IV & Tobit results show that with
tariff as trade indicator, trade reform has a strong positive effect
on competition which leads to a significant positive impact on
innovation activity
• Mixed sector, where intense trade takes place, confirms the
importance of market competition as channel through which trade
liberalization affects innovation
• IV results with tariffs show that tariff & PCM have a highly
significant positive relationship while R&D & PCM have a
significant negative relationship
Policy Implications
• Considering the low level of R&D spending, overall
innovation activity in the country, and role of competition
in the relationship between international trade &
innovation, maintaining effective competition is essential,
market contestability important
– Increasing globalization & regional economic integration
• Government should design strategy that would ensure
competition, innovation, & productivity growth of firms
• Motivations for new industrial policy
– Inclusive growth, ASEAN Economic Community
• Transform & upgrade manufacturing – AEC opportunities
& create more & better jobs
• Strengthen human capital, infrastructure, institutions
• Innovation Ecosystem to link business & academe
“ Innovations do not fall like manna from
heaven. Instead, they are created by human
beings……. to profit from opening up new
markets….”
Aghion and Howitt
(1999)