Firm Heterogeneity and Export Pricing in
India
Michael A. Anderson
Washington and Lee University
Martin H. Davies
Washington and Lee University
Center for Applied Macroeconomic Analysis, Australia National University
Jose E. Signoret
U.S. International Trade Commission
Stephen L. S. Smith
Gordon College
The views in this presentation are strictly those of the authors and do not represent
the opinions of the U.S. International Trade Commission or any of its individual
Commissioners.
Plan
•
•
•
•
•
•
motivation and contribution
literature review: theory and empirics
data
results
discussion
conclusion
Motivation and Contribution
• New dataset (Prowess + TIPS) that allows us to examine pricing
behavior of Indian exporters
• Motivation: Indian firms: the same or different?
• Previous studies, for a number of countries, find:
• more productive firms charge higher prices,
• prices rise with distance and fall with remoteness.
• By contrast we find Indian firms are different:
• more productive firms charge lower prices,
• prices fall with distance and rise with remoteness.
• What are Indian firms doing differently?
Theory
• Melitz (2003) and Melitz & Ottaviano (2008)
• competition depends on price
• more productive firms (lower MC) set lower prices
• M 2003: mark-ups constant; M&O 2008: mark-ups higher
• prices fall with distance
• prices rise with remoteness
• Baldwin & Harrigan (2011)
• Modify Melitz (2003) to include quality
• competition depends on price and quality (quality adjusted price)
• more productive firms produce higher quality goods (with high
MC—quality is costly)
• lower quality adjusted prices—but higher money prices
• only high price (high quality) goods are sold in distant markets
• prices rise with distance
• prices fall with remoteness
Literature
• heterogeneous goods, heterogeneous markets
• China:
Manova and Zhang (2012)
• Colombia: Kugler and Verhoogen (2012)
• US:
Harrigan, Ma, and Shlykov (2015)
• Portugal: Bastos and Silva (2010)
• Hungary: Gorg, Halpern, and Murakozy (2010)
• France:
Martin (2009)
• Findings:
• Firms price discriminate across destinations
• Higher productivity firms charge higher prices
• linked to product quality upgrades.
• prices increase with distance: all papers
• prices fall with remoteness: MZ, HMS
• above are consistent with Baldwin & Harrigan quality-adjusted Melitz
(2003)
Theory: Antoniades (2015)
• heterogeneous markets: quality ladders long
• correlation between prices and productivity positive
• homogeneous market: quality ladders short
• correlation between prices and productivity negative
• Sign of relationship depends on scope for quality differentiations (cost of quality
upgrading): 𝜆 determined by
• market size (L),
• the degree of differentiation between varieties (1/γ)
• cost of innovation (θ)
• appreciation of quality (β)
𝑑𝑝(𝑐) 1
= (1 − 𝛽 + 𝛿 𝜆)
𝑑𝑐
2
𝑑𝑝(𝑐)
𝜆 < 1/ 𝛽 + 𝛿 then
> 0 scope for quality differentiation is low
𝑑𝑐
𝜆 > 1/ 𝛽 + 𝛿 then
𝑑𝑝(𝑐)
𝑑𝑐
< 0 scope for quality differentiation is high
where 1/c is productivity and δ measures the cost of quality upgrading
𝐿 𝛽−𝛿
λ=
4θγ − 𝐿 𝛽 − 𝛿 2
• homogeneous goods: γ → ∞, and λ → 0 .
Diagram: Scope for quality differentiation
Scope for quality differentiation: low
Scope for quality differentiation: high
CORRELATION BETWEEN PRICES AND PRODUCTIVITY
Simple example
• two firms: high productivity (H) and low productivity (L)
• marginal cost firm i: ci
mark-up firm i: μi
cL > cH → μL < μH
• price = mc + mark-up
pi = ci + μi
Two Cases:
• scope for quality differentiation: high
pH = cH + μH > pL = cL + μL
HIGH PRODUCTIVITY FIRM HAS HIGHER PRICE
• scope for quality differentiation: low
pH = cH + μH < pL = cL + μL
LOW PRODUCTIVITY FIRM HAS HIGHER PRICE
Literature
• heterogeneous goods, heterogeneous markets
• China:
Manova and Zhang (2012)
• Columbia: Kugler and Verhoogen (2012)
• US:
Harrigan, Ma, and Shlykov (2015)
• Portugal: Bastos and Silva (2010)
• Hungary: Gorg, Halpern, and Murakozy (2010)
• France:
Martin (2009)
• Findings:
• Firms price discriminate across destinations
• Higher productivity firms charge higher prices
• linked to product quality upgrades.
• prices increase with distance: all papers
• prices fall with remoteness: MZ, HMS
• above are consistent with Baldwin & Harrigan quality-adjusted Melitz
(2003)
Literature
• homogeneous goods, homogeneous markets
• Roberts and Supina: (1996, 2000): white pan bread, coffee, tin cans,
corrugated boxes, gasoline, concrete
• Syverson (2007): ready-mix concrete
• Foster, Haltiwanger, Syversion (2008): ice, concrete, sugar, boxes,
oak flooring
• Findings
• prices fall with productivity
• heterogeneous goods, homogeneous markets
• this paper
III.
Data
A. Sources
• TIPS data on Indian Exporters
• Firm-level product, quantity, unit-value, destination.
• Coverage:
• 11 major sea/airports
• 20,000+ firms--10,000+ goods--200+ destinations
• Fiscal year data 2000-2003, HS 8-digit
• Prowess data on firm characteristics
• Coverage:
• 23,000+ large and medium-sized firms
• State-owned and private enterprises
• CEPII data on destination market characteristics
III. Data
B. Construction
• Aggregation issues
•
•
•
•
…over time
…over firm IDs
…over product IDs
…over units
C. Result
• 20,850 observations of unique firm-product-unit valuedestination-year data
• All matched with firm and destination characteristics
• 1,018 unique manufacturing firms
IV.
A.
Results
Descriptive findings
• Overall export revenue rises: $143 million (2000) to $520
million (2003)
• Exports dominated by a few firms: top 10 percent export 80
percent of value
• Sources of revenue growth:
• Pure extensive growth—new revenue from new products, new
destinations—accounts for 40-50 percent of revenue increases.
• At least half is from intensive growth—ongoing sales of established
goods to established destinations.
A. Descriptives (cont.)
• Intensive revenue growth can be decomposed into
contributions of price and quantity changes
• Unconditioned finding: revenue growth occurs through
quantity increases rather than price increases.
• n = 2,545 continuing firm-product-destination combinations
for which rates of change can be calculated:
• Median revenue change: 38.7%
• Median price change: -1.0%
• Median quantity change: 50.0%
Cross-tabulation of price, quantity changes
Table 5. B. Continuing Firm-Product Observations With
Positive Revenue Growth (n = 1,532)
Percent (number)
%quantity
%price
(-)
(+)
Total
(-)
0 (0)
4.7 (73)
4.9 (73)
(+)
50.2 (770)
44.9 (689)
95.1 (1,459)
Total
50.3 (770)
49.7 (762)
100.0 (1,532)
IV.
B.
Results (cont.)
Conditioned results
• Dependent variable: export unit value
• Independent variables:
• Country variables:
•
•
•
•
GDP per capita (loggdppc)
GDP (loggdp)
Distance (logdist)
Remoteness (logremote)
• Product fixed effects
• Firm variables:
• TFP (logtfp)—Levinsohn-Petrin on gross value added, indexed
• K/L (logklabor)
• Size, proxied by wagebill (loglabor)
Selection correction
• Bias because firms’ prices only observed if firms choose to
export to particular destinations.
• HMS’s 3-stage estimator
• Extension of Wooldridge (1995).
• 1st stage: Probit of entry (firm in a destination) estimated over
all possible firm-destination-year combinations.
• 2nd stage: OLS regression of (positive) firm-product-destination
revenue on inverse Mills ratio, export-market and firm
characteristics.
• 3rd stage: OLS regression of firm unit values on partial residuals
from 2nd stage (actual residuals plus estimated term
for the inverse Mills ratio), export-market and firm
characteristics.
Table 5. Firm-Product Pricing by Destination and Firm
Characteristics—With and Without Sample Selection
Correction
All Goods
(1)
logprice
0.0892***
(0.0209)
0.0366***
(0.0133)
-0.0242
(0.0473)
0.00446
(0.0432)
-0.171**
(0.0827)
0.0823
(0.0554)
0.0645*
(0.0345)
(2)
VARIABLES
logprice
loggdppc
0.177***
(0.0277)
loggdp
0.271***
(0.0540)
logdist
-0.373***
(0.0661)
logremote
0.361***
(0.0779)
logtfp
-0.162**
(0.0816)
logklabor
0.0933*
(0.0560)
loglabor
0.181***
(0.0334)
selection
0.211***
(0.0464)
Observations
20,850
20,850
R-squared
0.862
0.871
Fixed effects
Prod
Prod
SE clusters
Country
Country
Robust standard errors in parentheses
*** p<0.01, ** p<0.05, * p<0.1
Table 5.B. Firm-Product Pricing by Destination and Firm
Characteristics—With Sample Selection Correction
All goods
VARIABLES
loggdppc
loggdp
logdist
logremote
logtfp
logklabor
loglabor
selection
Observations
R-squared
Fixed effects
SE clusters
(2)
logprice
0.177***
(0.0277)
0.271***
(0.0540)
-0.373***
(0.0661)
0.361***
(0.0779)
-0.162**
(0.0816)
0.0933*
(0.0560)
0.181***
(0.0334)
0.211***
(0.0464)
20,850
0.871
Prod
Country
Textile and
textile
articles
(4)
logprice
0.127***
(0.0249)
0.189***
(0.0387)
-0.162**
(0.0678)
0.240***
(0.0510)
-0.137**
(0.0688)
0.0102
(0.0308)
0.162***
(0.0269)
0.0355***
(0.00698)
2,915
0.919
Prod
Country
Machinery,
appliances,
elect.
equipment
(6)
logprice
0.0136
(0.0472)
0.194***
(0.0555)
-0.330***
(0.112)
0.347***
(0.126)
-0.565***
(0.173)
0.0258
(0.183)
0.388***
(0.105)
0.269***
(0.0386)
4,233
0.913
Prod
Country
All other
HS chapters
(8)
logprice
0.163***
(0.0274)
0.230***
(0.0449)
-0.300***
(0.0586)
0.244***
(0.0701)
-0.208**
(0.0881)
0.158**
(0.0754)
0.0973**
(0.0394)
0.242***
(0.0567)
13,657
0.842
Prod
Country
Results: Main Findings…
VARIABLES
loggdppc
loggdp
logdist
logremote
logtfp
logklabor
loglabor
Observations
R-squared
(2)
logprice
0.177***
(0.0277)
0.271***
(0.0540)
-0.373***
(0.0661)
0.361***
(0.0779)
-0.162**
(0.0816)
0.0933*
(0.0560)
0.181***
(0.0334)
20,850
0.871
• 1. Pricing-to-market
• 2. Prices…
• fall with firm productivity
• fall with distance
• rise with remoteness
• 3. Results unchanged with
differentiated goods
defined by Rauch
categories.
• 4. Prices rise with firm size
and K/L
Discussion:Three Zones: I, II, III
Discussion: three zones
• Zone III: heterogeneous goods, heterogeneous markets
• US, China, Portugal, Hungary, France, Columbia
• Zone I: homogeneous goods, homogeneous markets
• white pan bread, coffee, tin cans, corrugated boxes, gasoline,
concrete
• Zone II: heterogeneous goods, homogeneous markets
• this paper
Discussion: China v India: scope of q.d. 2000-2005
• market size: China larger relative to India
•
•
•
•
Chinese domestic markets bigger (richer, more people, less segmented)
Chinese firms more export oriented:
India less export oriented: exports/GDP 14% vs 30% (2003)
impediments to exporting: 258 signatures and 130 copies (2003)
• cost of innovation: higher in India relative to China
• India: impediments to firm adjustments
• firm size: regulations limits scale of k-int and l-int firms, labor allocation
• increases cost of innovation
• difficult for firm to release or reassign resources
• labor laws, difficulty of bankruptcy: firms more cautious about new activities
(innovations)
• China: more funding for innovation (true now, early 2000s?)
• Evidence: expenditure on R&D as a share of manufacturing output is
7.5 times higher in China relative to India (2008-2010)
Discussion: what is driving result
• Divide observations along two lines:
1.
by ternary Rauch Categories: homogeneous; reference-priced;
differentiated
2.
main groups in
• Machinery (20%) –
• Textiles (14%) –
• All other goods (66%) –
all differentiated
62% differentiated
57% differentiated
• Correlation (conditioned) strongest in machinery (all
differentiated) (-0.53)
• where expect correlation might positive it is most negative.
Remoteness, Distance
• heterogeneous markets (rest of literature)
• prices and quality positively correlated
• highest priced goods are highest quality and lowest price per unit of
quality => most competitive
• distance: only highest priced goods make it to most distant markets
• price rises with distance
• remoteness: only most competitive goods compete in areas with high
mass of economic activity
• prices fall with remote
• homogeneous markets (this paper)
• prices and quality negatively correlated
• lowest prices goods has the lowest price per unknit of quality => most
competitive
• distance: prices fall with distance
• remoteness: prices rise with remoteness.
Conclusions
• Indian firms are different
• New empirical findings:
• Indian firms with higher productivity charge lower prices in
destination markets
• Negative association between distance and prices
• prices increase with remoteness
• results: heterogeneous goods, homogeneous markets: Zone II
• firms quality upgrading
• but mark-ups rise too slowly to offset falling MC
• in contrast to:
• heterogeneous goods, heterogeneous markets: Zone III
• homogeneous goods, homogeneous markets: Zone I