Competitiveness and Growth in Latin America: The Chilean Case Matías Braun Universidad Adolfo...
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Transcript of Competitiveness and Growth in Latin America: The Chilean Case Matías Braun Universidad Adolfo...
Competitiveness and Growth
in Latin America: The Chilean Case
Matías BraunUniversidad Adolfo Ibáñez & IM Trust
Ignacio BrionesUniversidad Adolfo Ibáñez
Christian JohnsonUniversidad Adolfo Ibáñez
September 2007
Non-Binding Constraints
We dismiss the following as being material constraints • Property rights• Macroeconomic unstability• Tax scheme• Infrastructure• Public institutions
Selected scores at the WEF-Global Competitiveness Report 2006-2007
Global Competitiveness
index
Tax Efficiency (a)
Property rights
Macroeconomic stability
Public Institutions
Corruption Infrastructure
Chile 4,9 4,3 5,5 5,6 5,7 6,4 5,11st Quartile Raw per capita GDP Growth 4,2 3,2 4,4 4,8 (*) 4,2 4,6 3,31st Quartile pc GDP Growth controlling for Initial pc GDP 4,3 3,3 4,5 4,8 (*) 4,4 4,8 (*) 3,51st Quartile Raw per worker GDP Growth controlling for Initial pw GDP 4,2 3,2 4,5 4,8 4,4 4,8 3,4High Growth Countries (union of the three above) 4,2 3,2 4,5 4,8 4,3 4,7 3,4Latin America & Caribbean 4,0 (**) 2,9 (*) 4,2 (*) 4,4 (**) 4,3 (**) 5,2 (**) 3,3Rich OECD Countries 5,0 2,8 6,1 4,6 5,8 6,2 5,4All Countries 4,1 3,0 4,4 4,6 (*) 4,3 4,7 3,4
Source: WEF-Global Competitiveness Report 2006-2007. (a) Data from WEF-GCR 2005-2006.* 10%, **5%, *1%. Significance levels of the test of whether Chile is different than the one of each group of countries
Selected binding “suspects”
1. Poor quality of Education
2. Bad Income Distribution
3. Micro Constraints on Growth: a) labor, b) energy constraints
4. External sector and self-discovery
5. Financial Constraints
Methodology• We consider a factor to be a considerable constraint if three conditions
apply:1. If, compared to a relevant group of countries, a measure of the relevant
issue is shown to be significantly smaller in Chile. 2. If there is an economic and statistically significant association between the
measure of the particular concept and the rate of growth and/or the level of income.
3. If we can show either shadow prices or behavior that is consistent with the hypothesis that there is a significant constraint steaming from supply rather than demand factors.
• For each candidate, we compute and rank dXX
YY
per capita GDP
Growth 1995-
2004
pc GDP Growth
controlling for Inicial pc GDP
1995-2004
per worker
GDP Growth
1995-2004
per worker GDP Growth controlling for Inicial pw GDP
1995-2005
per capita GDP
2000 USD 1995-
2004 Chile 3.3% 1.2% 2.5% 0.9% 4,2951st Quartile Raw per capita GDP Growth 5.7% 3.3% 5.3% 3.3% 3,3201st Quartile pc GDP Growth controlling for Initial pc GDP 5.7% 3.3% 5.2% 3.3% 3,8191st Quartile Raw per worker GDP Growth controlling for Initial pw GDP 5.6% 3.3% 5.3% 3.4% 5,092High Growth Countries (union of the three above) 5.3% 3.0% 5.0% 3.0% 4,629Latin America & Caribbean 1.2% -0.9% 0.3% -1.4% 3,831Rich OECD Countries 2.4% 0.7% 2.3% 1.0% 21,631All Countries 2.4% 0.1% 1.9% 0.0% 5,352
* The sample consists of up to 166 countries. Data are from World Development Indicators.
Benchmark Groups
Our own implementation of GDM
y=f(X)
dy=δy/δX·dX1) dX lower than benchmark (expected, desired, rich or
fast-growing countries)
2) δy/δX relatively large and in the right direction3) δy/δX X=>y and not the other way around
(behavior or prices consistent with lack of supply instead of lack of demand)
• For X to be binding we need all 1, 2, and 3 to be true.
• Also, dy=δy/δX·dX allows us to rank them
1- Lack of resources: human capital
• Quantitative educational indicators
• Qualitative educational indicators
• Behavior: Industry panel regression
CHL
05
1015
tyr2
5+
0 10000 20000 30000 40000GDP pc (2000, ppp)
62 data predicted data62
CHL
010
2030
4050
lh25
+
0 10000 20000 30000 40000GDP pc (2000, ppp)
8 data Fitted values
Average years of Education (pop, 25+), 2000 Percentage of Higher school attained (pop, 25+),2000
•Both attainment and years of school in Chile are in line or over the country’s economic development.
Education: Quantity
•Gross tertiary enrolment is higher than LA and than the fast growing economies•In line in 1990, over the expected value in 2004 •Quantity is NOT a problem
Quantitative educational indicators
Wage premia and % of labor force with tertiary education completed
•At first sight Chile’s wage premia looks high…
•However, it is in line with its quantity of skilled workers (and also level of development and capital per worker)
•Quantity rather than quality?
Quantity. Indirect measures wage premium
Wage premia skilled/unskilled workers in the World
0
2
4
6
8
10
12
14
16
ITA
GR
C
PO
L
HU
N IND
DE
U
CH
N
CA
N
AU
S
OA
N
HK
G
TS
R
JPN
SW
E
GB
R
LKA
BO
L
NLD
CH
E
PH
L
TU
N
PE
R
VE
N
GH
A
DO
M
MY
S
SLV NIC
PA
K
UR
Y
US
A
FR
A
PR
T
AR
G
TH
A
KO
R
CR
1
CY
P
PR
Y
EC
U
CH
L
SG
P
PA
N
CO
L
ME
X
BR
A
GT
M
KE
N
IDN
HN
D
BW
A
Secondary equivalentstertitiary equivalents CHL
05
10
15
Wag
e pr
em
ia te
rtia
ry
0 10 20 30% pop higher edu. compl.
rw_t Fitted values
Quantity. Indirect measures wage premium0
24
68
Pre
mia
(#
tim
es)
1970 1980 1990 2000year
higher over primary higher over secondarysecondary over primary
• Skilled wage premia roughly constant during the 1990s
• Ceateris paribus, supply of high skilled workers has compensated the demand expansion.
• Supply was not a mayor constraint
• Wage premia secondary vs primary are converging. Quality?
Wage premia in Chile 1970-2003
Quality: indirect measures
•Mincer> ex-post => negative quality effect at school level
•Mixed Results:
•No difference from national data
•Mincer > ex-post, Santiago’s data
Table 1.2. Mincer estimates vs effective returns Returns to education 1 (Mincer specification) 1990 1992 1994 1996 1998Primary (8 yrs) 2.9 3.6 4.2 3.2 3.6Secondary (4 yrs) 9.1 9.9 9.1 11.3 9.3Higher (4 yrs) 20.6 22.1 22 21.4 21
Returns to education 2 (Mincer specification) 1990 1992 1994 1996 1998
(Sapelli 2003)(Arellano and Braun 1999)
(Beyer 2000) (Sapelli 2003)
Primary (8 yrs) 5.8 5.2 3.8 7.1Secondary (4 yrs) 13.2 12.3 10.2 13.9Higher (4 yrs) 18.9 20.9 20.5 22.8
Implicit Ex-post (effective) returns (1) 1990 1992 1994 1996 1998Primary (8 yrs)Secondary (4 yrs) 9.5 11.1 11.3 12.1 12.1Higher (4 yrs) 26.2 29.9 26.8 26.3 27.8
Implicit Ex-post (effective) returns (2) 1990 1992 1994 1996 1998Primary (8 yrs)Secondary (4 yrs) 10.3 7.6 9.1 8.9 6.9Higher (4 yrs) 39.4 35.4 36.0 34.6 34.2
* (1) data from Mideplan (2000), (2) from Gallego (2006).
Quality: direct measures
Prueba TIMSS 2003 Prueba Pisa 2000
CHL400
450
500
550
600
Tim
ss 2
003
0 10000 20000 30000 40000GDP pc (2000,ppp)
timss_all03 Fitted values
CHL
300
350
400
450
500
550
TP
isa
2000
0 10000 20000 30000 40000GDP pc (2000,ppp)
pisa_all Fitted values
•Chile’s results in TIMSS and PISA test should be 15% higher (=1 standard deviation)
•In principle, economic effect could be large: 1% in in per capita GDP growth per year. (Hanushek and Kimko, 2000)
•However, quantity x quality= ok. Combined economic effect 0.4% in per capita GDP growth per year.
•Quality could be binding
CHL
50
100
150
200
250
300
Pis
a200
0xls
25
0 10000 20000 30000 40000GDP pc (2000,ppp)
pisa_ls Fitted values
Quality. Further tests: Industry panel approach
• 2 specifications:• A- Dependent variable is value added growth at
isic3 level, over interaction of human capital intensity x availability + other control variables
• B- Dependent variable is the share of isic3 value added (to GDP), over interaction of human capital intensity x availability + other control variables
• Idea is to test behavior: given Chile´s endowment of human capital, do its HK intensive industries are growing slowly than in other countries?
Quality. Further tests: Industry panel approach
• 1985 - 2002 Chile was not different from other countries (value added growth an share)
• 85-95 binding= 0.4% GDP growth.
• 95-02 the opposite• All in all, industrial
behavior not consistent with the quality binding hypothesis. Latent restriction?
Panel A: Industry Growth Variable 1985-2002 1985-95 1995-2002
Ln(Adult Total Years of Schooling) x Industry Human Capital Intensity
0.0963273 *** 0.0722401 *** 0.0914181 **
(0.0253915) (0.0195681) (0.0350952)Ln(Natural ressources per capita) x Industry Natural ressources Intensity
0.0000546 -0.0022444 0.0260225 **
(0.00682) (0.0059767) (0.0120633)Ln(physical capital per worker) x Industry Physical Capital Intensity
-0.0488542 -0.0077716 0.0945287
(0.0919342) (0.0809609) (0.1318218)Initial Share of Indutry of Total Manufacturing Value Added
-0.0656481 -0.2296529 *** -0.0686246
(0.0478216) (0.0474045) (0.1110064)
Dummy_Chile Ln(Adult Total Years of Schooling) x Industry Human Capital Intensity
0.0035107 -0.0219832 *** 0.0178446 *
(0.0052558) (0.0046378) (0.0103143)
R-squared 0.3666 0.4032 0.2558Obs. 1392 1351 1128*** 1% ; ** 5% ; * 10%
Panel B: Industry Composition Variable 1985-2002 1985-95 1995-2002
Ln(Adult Total Years of Schooling) x Industry Human Capital Intensity
0.5414796 * 0.381451 1.22883 **
(0.2832166) (0.2777096) (0.5044525)Ln(Natural ressources per capita) x Industry Natural ressources Intensity
0.1938891 * 0.159585 0.2528286 **
(0.1028954 ) (0.1006135) (0.0971905)Ln(physical capital per worker) x Industry Physical Capital Intensity
0.1991707 0.0735766 -1.777133
(1.015046) (1.039054) (1.361254)Dummy_Chile Ln(Adult Total Years of Schooling) x Industry Human Capital Intensity
-0.0620676 -0.0664267 -0.2497667 ***
(0.092631) (0.0988869) (0.0969371)
R-squared 0.4899 0.487 0.424Obs. 1564 1479 1181*** 1% ; ** 5% ; * 10%
2. Inequality
• High inequality in Chile• Empirical (weak) link (income inequality)= 0.5-
0.8 % GDP gth.• Asset inequality: 0.6 % GDP gth.
Income Gini index (2000)
Land Gini Index (Frankema)
Chile 57,1 84,11st Quartile Raw per capita GDP Growth 35,7 ** 49,8 **1st Quartile pc GDP Growth controlling for Initial pc GDP 36,0 ** 55,3 **1st Quartile Raw per worker GDP Growth controlling for Initial pw GDP 35,4 ** 53,5 **High Growth Countries (union of the three above) 36,1 ** 54,7 **Latin America & Caribbean 51,5 77,8Rich OECD Countries 32,1 * 62,7 *All Countries 40,4 59,5 *
Sources: Frankema (2007), WDI (2005) and Deininger and Squire (1996)* 10%, **5%, *1%. Significance levels of the test of whether Chile is different than the one of each group of countries
2. Inequality
• High growth coupled with high but stable inequality. Binding? Not clear.
• Channels:– Political making
process? No– Social unstability? No– Capital market? No
• Conclusion: NOT binding
CHILE: Gini (income) index
30
35
40
45
50
55
60
1958-63 1964-69 1970-73 1974-81 1982-86 1987-90 1991-98 1999-01 2002-06
CHL
20
40
60
80
Gin
i
-.05 0 .05 .1 .15 .2GDP pc growth
gini predicted gini
3- Micro Distortions on Growth
• A) Labor Market Regulations– Policy-induced price distortions and regulations in some
sectors – World Economic Forum Competitiveness Reports indicate
that by far labor regulation is a problem
• B) Energy– Experiences such as the oil shock of the recent years, the
shortage of gas from Argentina during the last few years, and the low levels energy investment in the economy were circumstances that might be constraining Chilean’s future growth prospects.
A) Labor Market Rigidities
• Labor market would be binding constraint to Chilean growth?– Evidence supporting the view that labor regulation and
labor market rigidity (Job security Indexes) does not affect• Employment growth• Investment • Industrial production growth • Substitution of Labor and Capital
– And what about Investment Climate Survey?• Labor regulations does not affect employment growth• Labor regulations does not affect production
B) Energy Constraints
Dependent Variable: Per worker GDP Growth controlling for initial pw GDP 1995-2005---------------------------------------------------------------------------------------------------------------------------------------------------------------Constant -0.0057419 ** -0.015554 *** -0.0074231 ** -0.0079032 *** -0.003021
0.0027338 0.0022397 0.003316 0.0030425 0.002877
Energy Growth 0.2711198 ** 0.1361062 0.2747035 ** 0.2818019 * 0.2823193 ***0.1067166 0.0943757 0.1069168 0.1074592 0.1080365
grupogthun~n 0.0412029 ***0.0045801
pcgdp2000us 3.00E-071.99E-07
Rich OECD 0.0139734 ***0.0033288
Latin American Country -0.0181801 ***0.0041249
---------------------------------------------------------------------------------------------------------------------------------------------------------------# Obs 166 166 166 166 166R2 0.0914 0.4298 0.0974 0.1145 0.1362F Test 6.45 40.63 4.75 11.77 10.28P-value 0.0120 0.0000 0.0099 0.0000 0.0001Root MSE 0.03034 0.02410 0.03033 0.03004 0.02967---------------------------------------------------------------------------------------------------------------------------------------------------------------*10%, **5%, ***1%. Robust standard errors below the coeff.Cross Section Sample of 166 countries, average of indicators for 1995-2005.
Robust Elasticity
Dependent Variable: Gross Output (Log) Group All Firms
All SampleFirms with HighUse of Energy
Firms with LowUse of Energy
ln(electc) 0.24597 *** 0.51799 *** 0.34754 ***0.00342 0.00576 0.00479
Fixed Assets 5.42E-10 *** 1.60E-10 *** 7.78E-09 ***7.94E-11 6.80E-11 4.51E-10
Investments 1.31E-09 9.18E-10 9.96E-09 ***9.92E-10 9.18E-10 2.39E-09
Gross Output Growth 18.90312 15.23884 22.43303Electricity Consumption Growth 29.44707 47.71685 11.84724# Obs 53126 26999 26127# Groups 8834 6153 6314R2 Overall 0.6225 0.8478 0.7876F Test 1754.72 2710.33 1925.5P-value 0.0000 0.0000 0.0000*10%, **5%, ***1%. Robust standard errors below the coeff.Panel Data (ENIA): 1990-2000, 6153 firms Industrial SectorConstant estimated but not reported in tableHigh Use of energy defined as firms with electc/Gross Output higher than the median: 0.0002069 (dummy=1)
• Worldscope• Data ENIA
– Energy is consistently a relevant factor in the productive process
B) Energy• BUT: Is Energy really a Problem? No
– WB Inv. Climate Survey– Not binding for
• Sales• Employment• production
(1) (2) (3)
Dependent VariableEmployment
GrowthSales Growth
Market Value of Production
GrowthElectricity (c218b) 0.1169947 0.6314801 0.4900666
0.2281866 0.4994278 0.9084524
Firm Size (Total Employment) 0.9429716 *** 2.562169 *** 0.72949750.242563 0.5292068 0.9612507
Cost of Financing (c218L) -0.1865434 -0.0703586 0.66084040.2144453 0.4710471 0.8981119
Macroeconomic Instability (c218n) -0.4875233 ** -0.3124173 -0.68290680.2336334 0.5115749 1.006361
Legal System/Conflict Resolution (c218r) -0.4247077 * -0.7668764 -0.5533730.2391423 0.526087 0.9455888
# Obs 11759 10388 4985R2 0.0025 0.0026 0.0003F Test 5.96 5.51 0.35P-value 0.0000 0.0000 0.8853*10%, **5%, ***1%. Robust standard errors below the coeff.Constant not Reported. Similar resukts with HP Index instead of Djankov et al.Codes from WB Inv. Climate Survey: Employment: c262a1y-c262a2y; Sales: c274a1y-c274a2y;Market Value of Production: c274c1y-c274c2y
B) Chile: Is Power Supply a Problem? No
• Based on official projections, the Chilean economy will require additional energy in an amount close to 400-450 Mega Watts– Planned infrastructure will satisfy demand (see annex.)
• Many actions taken by the Energy Minister to decrease our energy dependence in short and long run:– Efficient use of energy from households, firms and
government agencies (Programa Pais Eficiencia Energetica: PPEE)– Promoting a tripartite agreement between Chile,
Argentina and Brazil to make energy swaps in case of shortage
– To control the use of hydro resources, to avoid leakages, etc.
B) Energy: Conclusion
• Energy supply is important for
• …However from World Bank’s Investment Climate Survey– energy has not been an obstacle for the
operation and growth of businesses
• And supply planned power infrastructure is in line
• Energy will not be a binding constraint for growth in Chile
4-External sector and self-discovery
• Despite its outstanding growth rate and its relevant size, the export sector is still very concentrated in a few primary products.
• This lack of diversification could be hampering Haussmann’s Self-Discovery process and thus constraining Chile’s future growth.
4- External sector and self-discovery
• Chile shows a level of open forest that is lower than expected from the growth equation
ECU
NIC
TTO
NICECUGUY
TTO
GUYSLV
TTO
GUYGUYGUYGUYECU
TTO
ECUJAM
TTO
TTO
JAM
SLV
SLVNICGTMNIC
JAMCHLJAMECUJAM
SLVPAN
GTMJAMGTM
NICCHLCHLPAN
NIC
PANPAN
ECU
GTM
COLSLVCOL
GTM
COL
SLV
PANCHL
CHL
COL
BRA
GTM
ARG
PAN
CHL
ARG
ARG
COL COL
ARG
ARG
BRABRABRA
ARG
BRABRA
-20
00
02
000
400
06
000
800
0e
( g
dpp
cpp
p |
X )
-500000 0 500000 1000000 1500000e( open_forest | X )
coef = .00330884, (robust) se = .00066759, t = 4.96
4-External sector and self-discovery
• Chile’s current export basket is very peripherical– export sophistication is low– specialized in activities with few new
applications– however, output and export growth has been
high• The ability of the economy to transit to a new
development stage is not for granted• Chile’s nearby efficient frontier favors:
– agricultural-based manufactures, shipbuilding, industrial chemicals, non-electric machinery, and forestry-based manufactures
4-External sector and self-discovery
• It is Chile’s ability to move to these sectors where future growth probably lies
– education quality, and energy, and financial constraints, can play an important role
• Given the low density of its open forest, Chile will likely require the other determinants of growth to be much more enhanced than in other countries without this condition
5. Financial Constraints
Chile’s Financial System is Large
• And is not perceived as a constraint for growth
Bank Credit to
the Private
Sector to GDP
1995-2004
Stock Market
Capitalization to
GDP 1995-
2004
Private Bond Market
Capitalization to GDP 1995-
2004 Chile 55.4% 85.2% 19.0%1st Quartile Raw per capita GDP Growth 25.3% 24.6% 11.5%1st Quartile pc GDP Growth controlling for Initial pc GDP 27.7% 30.5% 11.1%1st Quartile Raw per worker GDP Growth controlling for Initial pw GDP 33.0% 43.9% 14.9%High Growth Countries (union of the three above) 31.8% 42.6% 15.3%Latin America & Caribbean 27.8% 19.3% 6.9%Rich OECD Countries 89.5% 72.8% 37.7%All Countries 36.3% 39.9% 22.6%
* The sample consists of up to 166 countries. Data are from World Development Indicators and Beck et al (2006).
Ranking of Contraints for Doing Business: Chilean Firms
All Firms
Financing 4Infrastructure 7
Political Instability 1Inflation 6
Exchange Rate 2Street Crime 3Organized Crime 9Taxes and Regulations 5Corruption 8
Ranking of Financial Contraints for Doing Business: Chilean vs. Other Countries' Firms
All Firms
Chile 41st Quartile Raw per capita GDP Growth 2
1st Quartile pc GDP Growth controlling for Initial pc GDP 21st Quartile Raw per worker GDP Growth controlling for Initial pw GDP2
High Growth Countries (union of the three above) 2Latin America & Caribbean 5Rich OECD Countries 2All Countries 3
Financial Development has a large effect of Growth
• Across countries [King and Levine (1993)
• Across countries and time [Levine, Loayza, and Beck (1998)]
• Across industries [Rajan and Zingales (1998)]
• Across firms [Demirguc-Kunt and Maksimovic (1998)]
COG
TZA
AGO
CMR
CAF
KHM
UGA
LAO
DZA
GEO
VEN
GHA
ROM
ARMALB
BEN
LSO
BTN
RWA
BWA
LTU
GTM
TUR
MLI
SEN
COL
BGR
IRN
NIC
LVA
IDNETH
PAK
PER
DOM
BGDNPL
SLV
BRA
MRT
LKA
POL
EST
IND
HND
PHLOMN
SVK
HUNWSM
NAM
TON
SVNCZE
VNM
BOL
HRV
EGYUSA
TUN
MUS
FINGRC
CHL
CAN
JORZAF
NOR
BEL
ITATHAFRA
SWE
KOR
ISR
AUS
MYS
AUTESP
JPN
SGPIRL
NZL
DEU
CHN
DNK
GBR
PRTNLD
HKG
-.6
-.4
-.2
0.2
e( p
cgdp
gth5
| X
)
-.5 0 .5 1e( privatec5 | X )
coef = .09184159, se = .04229492, t = 2.17
A one standard deviation increase in financial development is associated with around 1% faster growth per year.
There is behavior consistent with financing being a constraint in Chile
• Firms are more sensitive to internal cash and less to investment opportunities than elsewhere, particularly the young, small and intangible.
• More tangible industries grow disproportionaly faster in Chile
• Young and small firms were more severely affected during the post-Asian Crisis growth deceleration period.
• However, large, listed firms appear not to be particularly constrained in Chile.
0.661*** 0.559*** 0.609*** 0.529*** 0.636*** 0.518*** 0.465*** 0.473***0.07 0.034 0.046 0.02 0.079 0.0381 0.0847 0.037
-0.0091 0.060** -0.024 0.020 -0.051 0.070* 0.038 0.0330.071 0.026 0.041 0.020 0.083 0.035 0.079 0.028
-0.020 -0.027 -0.009 -0.018 -0.042*** -0.039** -0.017 -0.0150.02 0.0188 0.013 0.0127 0.016 0.016 0.018 0.0188
-0.036* -0.027* -0.039 0.0020.021 0.014 0.027 0.024
0.023 0.014 0.040 -0.0010.022 0.012 0.027 0.0253
-0.287*** 0.065** -0.720*** -0.0600.0358 0.025 0.047 0.037
-0.035 -0.037* 0.885*** 0.162***0.027 0.02 0.038 0.029
# Obs 2091 2102 4539 4560 1536 1547 2128 2135R2 0.325 0.320 0.290 0.289 0.320 0.327 0.176 0.177
* 10%, **5%, ***1%. Constant and Country Fixed Effects included but not reported. Errors clustered at the country level. The sample consists of firm-level observations in 58 countries.
IntangLocal Young
Past Sales Growth X General Financing Constraint
Expected Increase on Sales X CHILE
Past Sales Growth X CHILE
Small
Expected Increase on Sales
Past Sales Growth
Average Importance of non-financial constraints
Expected Increase on Sales X General Financing Constraint
Internal Cash/ Inv. Opp. Sensitivity
Investment Employment
-0.260*** -0.327*** -0.287*** -0.192*** -0.263*** -0.356*** -0.300*** 0.087 -0.073***0.015 0.018 0.015 0.015 0.015 0.0189 0.0222 0.058 0.004
0.036** 0.039** 0.035** -0.009 0.0110.015 0.016 0.015 0.083 0.008
0.268*** 0.270*** 0.269*** 0.025 0.097***0.021 0.021 0.019 0.093 0.014
-0.111***0.0188
0.064**0.021
0.043* 0.044* 0.044* -0.001 0.030***0.020 0.021 0.023 0.088 0.005
0.051** 0.048** 0.045** 0.051 -0.0160.019 0.0198 0.0167 0.107 0.01
-0.0150.0128
0.000.205
# Obs 43767 43767 43767 43767 43767 43767 43768 20400 43768R2 0.229 0.229 0.236 0.232 0.229 0.237 0.247 0.166 0.266Firm FE Yes Yes Yes Yes Yes Yes Yes Yes YesYear FE Yes Yes Yes Yes Yes Yes Yes Yes YesIndustry X Year FE No No No No No No Yes Yes Yes
* 10%, **5%, ***1%. Constant included but not reported. Robust errors clustered at the year level. The sample corresponds to 7346 different firms observed during the 1990-200 period.
Firm Value Added Growth
Foreign
Post98 X Tangible
Post98 X Foreign
Post98 X Old
Post98 X Large
Post98
Old
Large
Tangible
Small, Young Firms and growth decelaration
6. Conclusion
Bad Local Finance and Poor Quality of Human Capital make the Self-
Discovery constraint much more critical
ΔX δGrowth / δX
Behavior /
Shadow
Prices
Overall Ranking
Low Economic ReturnLow Social ReturnsLow Human Capital Quantity None Large No No - Quality Large Large Mixed Maybe 3High Income Inequality Large Medium No No -Energy Constraints Future-Small Large No Maybe 4Low AppropriabilityLabor Market Distortions Medium Small No No -Self-Discovery Large Large ? Maybe 1High Costs of FinanceBad Local Finance Maybe Large Yes Maybe 2
ΔX: difference between Chiles’s and benchmark indicator. δGrowth/δX effect of indicator on growth. Behavior/Shadow Prices consistent with the hypothesis that there is a significant constraint steaming from supply rather than demand factors. See methodological issues section.
Constraints on Growth: Summary
6. Conclusions • Not binding
– Quantity of Education– General Institutions– Finance for large, old, and collateral-rich
firms
• Binding– Self-Discovery– Finance for small, young, and collateral-poor
firms – Quality of Education– Energy (future)