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Report on Indicators of quality adjusted price competitiveness.
By
Maria Bas, Philippe Martin and Thierry Mayer
Work Package 5 / Deliverable 5.2
Sciences Po was the partner responsible for the preparation of this
report.
24 November 2013
1 This project is funded by the European Union Mapcompete is a project designed to provide an assessment of data
opportunities and requirements for the comparative analysis of
competitiveness in European countries
The project leader is László Halpern for CERS-HAS. The leaders of the six teams are: Carlo
Altomonte (Bocconi University) for Bruegel; Giorgio Barba Navaretti (University of Milan)
for Ld’A; Gábor Békés for CERS-HAS; Katja Neugebauer for IAW; Lionel Fontagné for
Paris School of Economics and Philippe Martin for Science Po.
Supporting Institutions are National Bank of Belgium, Banque de France, Banco de España,
Deutsche Bundesbank, Banca d’Italia, Magyar Nemzeti Bank and the Italian National
Institute of Statistics (ISTAT)
LEGAL NOTICE: This project has received funding from the European Union’s Seventh
Framework Programme for research, technological development and demonstration under
grant agreement no 320197. The views expressed in this publication are the authors’ alone,
and do not necessarily reflect the views of the European Commission.
2 Executive summary
This report reviews the state of the art of the literature on measures of quality
adjusted competitiveness. The report starts by an analysis of how the recent
theoretical literature on heterogeneous firms' trade models has introduced product
quality on both the demand and the supply side. The first family of models relies on
the idea that consumers value quality. The valuation of quality is reflected on their
willing to pay a higher price for high quality goods. On the supply side, firms' quality
choice depends on the quality of inputs (skill labor or intermediate goods) used in the
production of final goods. Also, producing high-quality goods is costly with marginal
costs increasing in the level of quality of the final good but also involves a sunk
investment cost in quality upgrading. The paper presents the recent empirical
methodologies developed in the literature to estimate product quality using microdata. The early literature relied on unit values to capture differences in quality at the
product level. The more recent literature disentangles price and quality using trade
values and quantities to obtain a quality-adjusted measure of unit values. The
identification strategy of these works infers quality from a demand function. Quality
differentiation across products is then associated to product characteristics that are
valued by consumers. The paper then describes alternative measures of non-price
competitiveness at the firm level in particular related to R&D and other technological
investments. Finally, it analyzes the recent findings of works that focused on how
macroeconomic shocks affect firms' competitiveness.
3 1. Introduction
This report, which is one of the three deliverables of WP51, aims at summarizing the
state of the art of the literature on indicators of quality adjusted price competitiveness
at the micro-level. The recent micro-level empirical research has emphasized the role
of firm heterogeneity in terms of differences in firm productivity and competitiveness
of firms producing within the same industry. Firm heterogeneity has been introduced
in theoretical models as differences in technological factors across firms within the
same industry. Heterogeneity in initial firm productivity levels captures differences in
input requirements to produce one unit of output. The industrial organization literature
and recently the international trade literature have emphasized that in this setting
more productive firms are more profitable, have larger revenues, lower marginal
costs and set lower prices (Hopenhayn, 1992, Ericson and Pakes, 1995, Melitz, 2003,
Melitz and Ottaviano, 2008).
The literature has highlighted different channels through which firms might improve
their efficiency. One mechanism that allows firms to upgrade their competitiveness is
related to production cost reductions.
This price (cost) competitiveness channel
implies that the lower the unit cost of production the higher the efficiency and the
more competitive the firm/ industry. An alternative mechanism to cost reductions
through which firms are able to improve their efficiency is by investing in research
and development (R&D), other technological investments related to foreign
technology transfers or by improving the quality of their products.
1
It corresponds to the deliverable D.5.2. The others deliverables are D5.1, which is a “Theoretical and
policy aspects of competitiveness at different aggregation levels” which will be delivered by PSE and
D.5.3 which is a report on “The main directions of research towards better assessment of
competitiveness” carried out by Sciences Po.
4 One of the main differences between both channels concerns the relationship
between firms’ efficiency and output price. On the one hand, the “price/cost
competitiveness” channel implies that firms with lower production costs are more
efficient and set lower prices. On the other hand, the “non-price competitiveness”
channel highlights a positive relationship between firm competitiveness and prices of
final goods charged by firms. The reason of this positive correlation between output
prices and non-price competitiveness measures like R&D, foreign technology and
product quality is that in the short run those technology/quality investments translate
into an increase in the fixed and /or variable costs that firms have to make to upgrade
their competitiveness. This survey focuses on these alternative channels that allow
firms to upgrade their efficiency through non-price competitiveness mechanisms and
aims at reviewing the main indicators of quality adjusted price competitiveness.
Recent firm level studies on the determinants of price differences across firms have
shown that exporters are more productive and larger but also charge higher prices
(Bastos and Silva, 2010; Martin, 2012; Manova and Zhang, 2012; Harrigan, Ma and
Shlychkov, 2012 and Hallak and Sivadasan -forthcoming-).
One possible
explanation for this empirical feature is related to product quality differentiation across
firms. Introducing consumers' preferences that vary with product quality on the
demand side and differences across firms in the scope for quality differentiation on
the supply side allows explaining the empirical fact that firm productivity, prices and
export status are positively correlated. On the demand side, consumers value quality
and they are willing to pay a higher price for high-quality goods. On the supply side,
quality differentiation on final goods depends on the quality of inputs. Output quality
varies with the quality of different skilled labor in Verhoogen (2008) or the quality of
5 intermediate goods in Kugler and Verhoogen (2012) or in Hallak and Sivadasan forthcoming-. Producing high-quality goods requires high-quality inputs with highwage or high-cost. Marginal costs are then increasing in the level of product quality.
In a framework of heterogeneous firms and endogenous product quality, these
models predict a product-quality sorting along the initial productivity level of firms.
More productive firms choose to produce high-quality products that involve higher
marginal costs and they charge then higher prices than less productive firms.2 In this
framework, quality and prices are positively correlated with firm size and profits since
they are all increasing in firm productivity.
In the empirical analysis, variations in prices across products and firms might reflect
changes in markups or in production costs rather than quality differentiation across
products. Disentangling product-quality from output prices in the data requires
detailed information on output values and quantities at the product or product-firm
level. Recent studies have developed methodologies based on demand functions
estimations to infer quality at the product level (Khandelwal, 2010) or at the firmproduct level (Khandelwal, Schott and Wei (2013)). These methodologies are based
on different assumptions on the demand structure, but both assume demand
systems where consumer preferences for quality are introduced as a demand shifter.
Quality is then represented as any product attribute that imply a shift in the demand
curve reflecting Sutton's (1991) pioneering idea. Inferring product quality from
demand functions implies that conditional on prices a product with a higher market
share or a higher demand (quantity) is assigned a higher quality.
2
In Kugler and Verhoogen (2012) the relationship between firm productivity and output prices
depends on the scope for quality differentiation.
6 The remainder of this review of literature is structured as follows. Section 2 reviews
how the theoretical literature on heterogeneous firms' trade models has introduced
product quality on demand and supply side. Section 3 presents the recent empirical
methodologies developed in the literature to estimate product quality using microdata. Section 4 describes alternative measures of non-price competitiveness. Section
5 presents the recent findings of works that focused on how macroeconomic shocks
affect firms' competitiveness. The last section concludes.
2. Theoretical mechanisms
2.1. Introducing quality on the demand side
The demand for a specific variety depends on its quality attribute. These models rely
on the idea that consumers value quality. The valuation of quality is reflected on their
willing to pay a higher price for high quality goods. This representation of quality
corresponds to the views of the European Commision that highlights “Upgrading the
products may also make customers willing to pay a premium for them if the products
are perceived to be of high enough quality" (European Competitiveness Report
2013).”
The main idea behind these models is very simple and intuitive: given that quality is
expensive to produce, a rise in price may be associated with an increase in demand.
Consumers are ready to pay a premium for higher quality goods. Linder's (1961)
early work already noted the role of quality as a determinant of the direction of trade
arguing that richer countries spend a larger share of their income on high-quality
goods. Recent empirical work corroborates this idea. On the consumption side, Bils
and Klenow (2005) show that the demand for quality is positively correlated with
7 income per capita at the country level. Hallak (2006) also identifies how product
quality affects the demand for the product using international trade data. He finds that
demand for quality is related to importers' income per capita: richer countries import
relatively more from countries that produce high-quality goods.
Including preferences that vary with product quality helps to understand several trade
patterns revealed by the empirical literature. Most models assume a representative
consumer who maximizes a Constant Elasticity of Substitution (CES) utility function
where quality can be understood as any product attribute that is valued by
consumers and that enhances consumers' willingness-to-pay for a variety. This
representation of preferences reflects the idea that consumers are willing to pay a
higher price for high-quality varieties. Hence, instead of making decisions based only
the observed price, consumers take their decisions based on quality-adjusted prices.
The demand for any variety is increasing in its quality and decreasing on its price.
Quality acts as a demand shifter: quality can be interpreted as a shift parameter in
the variety's demand schedule. This interpretation of quality reflects Sutton's (1991)
idea that an improvement of quality implies a shift in the demand curve. Holding the
price fixed, high-quality products have a larger demand. Several recent models have
adopted this demand structure to introduce product quality in consumers' preferences.
See among others, Hallak (2006), Baldwin and Harrigan (2011), Kugler and
Verhoogen (2012), Hallak and Sivadasan -forthcoming-, Crozet, Head and Mayer
(2012), Johnson (2012) and Khandelwal, Schott and Wei (2013).
8 One exception is the work of Di Comite, Thisse and Vandenbussche (2013) 3, that
extend the quadratic utility function presented by Ottaviano, Tabuchi and Thisse
(2002) to incorporate vertical and horizontal differentiation. The extension of this
demand function made by Di Comite, Thisse and Vandenbussche (2013) implies that
the differentiation among varieties varies now across countries and between varieties
in a country. The difference with the standard quadratic utility function where all
varieties share the same quality is that in this framework the quality of a product is
variety specific.
In equilibrium, this model shows that the price of variety is an
increasing function of the quality.
Finally, other models introduce product-quality on the consumption side using indirect
utility functions such as the nested-logit demand structure. This demand function
links the marginal value of quality and the income level of consumers: households or
countries that have greater income are willing to pay more for high-quality goods.
This utility function represents then the idea of Linder (1961) that countries with a
higher income per capita spend more on high-quality goods. Verhoogen (2008)
assumes that quality varies with the level of development of countries: consumers in
Northern countries with a high income per capita are willing to pay more for highquality goods than consumers in the southern ones. This nested-logit demand
structure has been used in international trade by Goldberg (1995), Verboven (1996),
3
Antoniades (2012) also develops a model that introduces product-quality in the Melitz and Ottaviano
(2008) framework of heterogeneous firms and endogenous markups. A key feature of this model
when including endogenous supply of product quality is that competition affects the scope for quality
differentiation and markups heterogeneously depending on firms' initial productivity level or marginal
costs.
9 Verhoogen (2008), Khandelwal (2010) and Fajgelbaum, Grossman, and Helpman
(2011), among others. 4
2.2. Production
On the production side, the recent models differ in the way they introduce
endogenous product quality choice but they all share several common features.
Firstly, in most of these models firms' quality choice depends on the quality of inputs
(skill labor or intermediate goods) used in the production of final goods. Secondly,
producing high-quality goods is costly with marginal costs increasing in the level of
quality of the final good 5 . Thirdly, some of these models follow the framework
developed by
Shaked and Sutton (1982 and 1983) and Sutton (1991, 1998)
assuming an endogenous sunk investment cost in quality upgrading. Finally, there is
a mapping between the firm's initial exogenous level of performance and the supply
of product-quality. In these models, the endogenous supply of quality is determined
by the exogenous firm performance parameter: Khandelwal (2010) calls it ability,
Verhoogen (2008) and Feenstra and Romalis (2012) productivity, Kugler and
Verhoogen (2012) capability and Hallak and Sivadasan -forthcoming- process
productivity.
4
Other indirect utility function that has been used to represent preferences for quality that depend on
consumers' income is the non-homothetic demand function. Feenstra and Romalis (2012) rely on a
non-homothetic CES demand for quality function where the demand for quality increases with the
income of the country. This utility function also implies that richer countries will import high-quality
goods.
5
Baldwin and Harrigan (2011) assume that higher quality implies higher marginal costs in a model
where product quality is exogenous. Other models represent the endogenous input choice to produce
product quality of final goods as Verhoogen (2008), Kugler and Verhoogen (2012), Feenstra and
Romalis (2012) and Hallak and Sivadasan -forthcoming-.
10 Verhoogen (2008) introduces endogenous quality in a model of monopolistic
competition and heterogeneous firms in terms of productivity a la Melitz. He assumes
that product quality of the final good produced by each firm depends on the ability of
the firm (or productivity), the quality of white and blue collar workers and the technical
sophistication of capital equipment combined by a Cobb-Douglas production function.
The qualities of different workers are assumed to be complementary. Firms decide
the input demand that maximizes profits and then input decisions determine quality of
the final goods produced. The model predicts that firms with a high-initial productivity
draw produce high-quality products for the export market, pay higher wages to both
types of labor, are more capital intensive and charge higher prices than those firms
with a low-productivity draw. In this framework, quality and prices are increasing
functions of firm productivity and thereby, they are positively correlated with firm
size.6
Kugler and Verhoogen (2012) assume differences in the production function of
physical units of output and the production of endogenous quality in a monopolistic
competition
setting
with
heterogeneous
firms.
Consumer
preferences
are
represented by a CES utility function including quality as a demand shifter. The
production of physical units of output depends on the number of units of inputs used
and firm capability draw (the equivalent to the ability parameter in Verhoogen, 2008,
or the productivity parameter in Melitz, 2003). They derive two functional forms for
the production of quality of final goods in a model where output quality is endogenous
and firms optimize their quality choice. In the first case, they assume that plant
6
Other model that adopts a similar Cobb-Douglas production function of output quality is the one
developed by Feenstra and Romalis (2012). They assume a similar production function that combines
an aggregate labor input and firm productivity to produce the quality of final goods. Optimal output
quality is an increasing function of firm productivity.
11 capability and input quality are complements in the production of final good output
quality. The production of endogenous quality is given by a CES function combining
plant capability and input quality.
Output prices are then a constant markup over marginal costs. In this setting, firm
capability has two opposite effects on marginal costs: (i) a direct effect through which
firm productivity reduces marginal costs as in the baseline Melitz model and (ii) an
indirect effect via input prices where firm capability increases input quality and input
price and then raises marginal costs. In equilibrium, higher capability firms rely on
high-quality inputs to produce high-quality outputs. This result is driven by the
complementarity between firm capability draw and input quality. In the intermediate
input sector, producing higher quality inputs is more costly in terms of labor.
Therefore, for the final goods producers, the quality of intermediate inputs and the
price of that input are positively correlated. Hence, higher-quality inputs have a
higher price, which raises marginal costs.
In the second case, producing high-quality output requires both high-quality inputs
and investing in a fixed cost of quality upgrading in the esprit of Sutton (1991, 1998).
They assume that producing high-quality final goods requires high-quality inputs. The
fixed costs of quality upgrading and input quality are combined by a Leontief
production function of endogenous quality. This fixed investment cost in quality is
endogenously determined by profit maximization as a function of plant capability and
other parameters of the model. As in the previous variant of the model the optimal
input quality, output quality and output price are ultimately determined by plant
capability. Higher capability firms also produce high-quality final goods with highquality inputs. In this variant of the model, this result is derived from the fact that firms
12 with a higher capability draw have economies of scales and are able to spread the
fixed cost of quality upgrading over more units of output. Quality is costly to produce
since requires high-quality inputs (high-priced).
In both variants of the model, output price is a markup over marginal costs and firm
productivity has opposite effects on marginal costs as described above. The
relationship between firm productivity and output prices depends then on the
magnitud of the parameters of scope for quality differentiation. More productive firms
produce high-quality goods with high-quality (high-cost) inputs. But for a given level
of product quality, more productive firms have lower costs. 7
Hallak and Sivadasan -forthcoming- propose a model including heterogeneous
product quality where firms differ in their productivity (called process productivity) as
well as in their ability to develop high-quality goods spending small fixed outlays
(product productivity). Both sources of productivity are randomly drawn from a bivariate distribution. The demand function for each variety is derived from a CES utility
function. Producing high-quality final goods is costly and involves marginal costs that
depend on quality and firm productivity and on a fixed cost that is an increasing
function of quality and decreasing on product productivity.
Firms with a high-value of process productivity draw have lower marginal cost and
firms with a high-value of product productivity draw have lower fixed costs of quality
upgrading. Hence, the optimal quality is an increasing function of both process
productivity and product productivity. Moreover, they assume that iceberg trade costs
7
In a North-South framework, Demir (2012) extends the model of Kugler and Verhoogen (2012) to
show the mechanisms through which input-trade liberalization leads to export quality-upgrading of
firms located in the South. Other related model of endogenous supply of quality is presented in
Jonhson (2012), where the firm's quality is a monotone, constant elasticity function of firm's
capability, reflecting a positive correlation between these two variables.
13 decrease with quality. These assumptions imply that conditional on size, exporters
produce high-quality goods, charge higher output prices, buy more expensive inputs,
pay higher wages and are more capital intensive.
Although the profit maximizing output price increases with the level of product quality,
high-price, high-quality, high-capability (high-productivity) firms generate higher
revenues and profits than their lower capability (productivity) counterparts. This
occurs because the increase in utility resulting from the consumption of higher quality
products more than compensates for the higher production costs. Product-quality,
output and input prices are then positively correlated with firm-size since all variables
are increasing functions of firm productivity.
As exporting firms incur a fixed cost, these models provide a convincing framework to
explain why exporters produce higher quality goods and charge higher output prices
producing with high-quality inputs as well as why export prices are higher in more
distant (Baldwin and Harrigan, 2011, Feenstra and Romalis, 2012) and more difficult
to enter (Jonhson, 2012) destination markets.
Box 1 – Main Theoretical predictions of heterogeneous firms models with
product quality
The models described in the previous section yield a set of theoretical predictions on
the relationship between firm productivity, output and input prices, product quality
and export status:
14 (1) High-quality goods have a larger demand since the consumer values quality;
(2) Product quality acts as a demand shifter that captures all attributes of a product
other than price that consumers value.
(3)Producing high-quality goods is costly since it involves the use of high-quality
intermediate goods (skilled labor or inputs) that increase marginal costs.
(4) Product quality is positively correlated with firm competitiveness (or productivity).
(5) Firm productivity increases product quality of final goods due to a
complementarity channel between firm capability and input quality as in Verhoogen
(2008), Feenstra and Romalis (2012) and the first variant of the model of Kugler and
Verhoogen (2012);
(6) Or by enhancing quality upgrading investments as in the second variant of the
model of Kugler and Verhoogen (2012) and Hallak and Sivadasan (forthcoming).
(7) These models predict a quality sorting of firms depending on their initial
productivity level. High-productivity firms have a larger demand and produce highquality goods with high-quality inputs (high-cost).
15 3. Measuring quality adjusted price competitiveness
3.1. Unit values as proxy for quality
The first empirical works in international trade studying the determinants of product
quality across products and countries rely on unit values to capture differences in
quality at the product level. This literature argues that prices (unit values) can be
used as a proxy of product quality since higher prices act as a signal for higher
product quality in imperfect market conditions following the idea of Akerlof's (1970)
market for lemons.
On the supply side, export prices are correlated with exporters' income per capita
and relative physical and human capital endowments (Schott, 2004). Cross-country
comparisons reveal that capital and skill abundant countries export goods at higher
unit values. Countries that increase their skill and capital deepening over time
experienced greater growth of unit values. Hummels and Klenow (2005) rely on the
quantity exported and proxies for the number of varieties to explain that differences in
quality are necessary to describe the observed differences in unit values.
On the demand side, Hallak (2006) combines unit values at the product-country of
origin level with information on countries income per capita. He also interprets the
results in terms of product-quality: richer countries import relatively more from
countries producing high-quality goods. 8
8
Other works relying on cross-country and product international trade data that use unit values to
measure quality are Schott (2008), Fontagne et al (2008) and Berthou and Emlinger (2010) among
others. They construct a relative price that compares for each market, the unit value of each individual
trade flow to the average trade price of the product category.
16 Box 2 – Unit values as a proxy for quality at the firm level study cases for
different countries
The first works aiming at measuring product quality at the firm level rely on prices
(unit values) to capture differences across firms-products in terms of quality. The
main idea is that higher prices are a good proxy of product quality since they act as a
signal for higher quality in imperfect market conditions.
Based on the theoretical framework presented in Box 1, the firm level empirical
literature argues that prices are a good proxy for quality (Baldwin and Harrigan,
2011). The firm-level empirical literature investigates the determinants of export price
variation in cross-section analyses, i.e., within-product across firms or within productfirm across markets for different countries:
- Bastos and Silva 2010 and Bastos, Silva and Verhoogen 2013 for Portugal;
- Gorg, Halpern and Murakovy 2010 for Hungary;
- Kugler and Verhoogen 2012 for Colombia;
- Martin 2012 for France;
- Manova and Zhang 2012 for China;
- Harrigan, Ma and Shlychkov 2012 for U.S.;
- Hallak and Sivadasan -forthcoming- for India, the US, Chile and Colombia
These studies are based on customs datasets that report detailed information on
firms’ products at the 8 or 6 digit product level disaggregation by export destination
country.
17 Box 3 – Main empirical findings of firm level studies:
(1) Exporting firms charge higher prices in more distant markets and to highincome countries (Bastos and Silva 2010, Gorg, Halpern and Murakovy 2010,
Manova and Zhang, 2012; Martin, 2012).
(2) Bigger, more productive and skilled intensive firms charge higher prices and
pay higher input prices (Harrigan, Ma and Shlychkov, 2012, Kugler and
Verhoogen, 2012, Hallak and Sivadasan -forthcoming-).
(3) Firms exporting to high-income countries buy more expensive inputs (Bastos,
Silva and Verhoogen, 2013).
This firm level evidence supports the predictions of the trade models of
heterogeneous firms that incorporate product quality.
3.2. Going beyond unit values to infer quality at the product level
Prices (unit values) are however imperfect measures of product quality. Variations in
prices across markets may indeed reflect differences on market structure or supply
shocks. Changes in unit values across firms-products might be associated to
variations in markups (pricing-to-market) or marginal costs rather than quality. The
18 first alternative explanation suggests that firms with market power charge higher
prices across markets. 9 In particular, firms might charge higher markups in richer
markets where consumers are less sensitive to price variations. Other possible
explanation for different price strategies across firms within the same market is
related to their cost structure: higher-cost firms charge higher prices.
Alternative empirical methodologies disentangle price and quality using trade values
and quantities to obtain a quality-adjusted measure of unit values. The identification
strategy of these works infers quality from a demand function. Quality differentiation
across products is associated to product characteristics that are valued by
consumers.
Hallak and Schott (2011) develop a methodology that decomposes countries
observed export prices into quality and quality-adjusted components using
information of their trade balances from the demand side. For constant observed
export prices, they infer that countries with trade surpluses produce high-quality
products relative to countries with trade deficits.
This methodology takes into account changes in trade balances generated by both
horizontal and vertical differentiation. Relying on this method, they estimate the
evolution of manufacturing quality for the world's top exporters from 1989 to 2003.
Their findings suggest that unit value ratios might be a poor proxy for relative quality
differences and that the product quality supply by a country is correlated with the
income level.
9
De Loecker and Warzynski (2012) develop a method to estimate markups at firm level based on costminimizing function and the existence of one variable input of production. They show that exporters
have higher markups than firms selling only in the domestic market.
19 Khandelwal (2010) proposes a measure of quality that accounts for both product
prices and market shares. The methodology to estimate product quality relies on a
nested logit demand system based on Berry (1994). This demand system features
preferences for horizontal and vertical attributes. He uses unit value and quantity
information for the US at the detailed level HS6 level to infer quality from the
estimation a nested logit demand system. A quality measure at the product level, is
then inferred from the estimation of the nested-logit demand function using the
estimated parameters: This methodology provides quality estimates at the product
level in which imported products with higher market shares are assigned higher
quality after controlling for price differences and country size. Khandelwal (2010)
shows that the estimated quality for products exported to the US expose significant
heterogeneity in the scope for quality differentiation across product markets (quality
ladder). He finds that for products with a larger scope for quality differentiation (i.e., a
long quality ladder), unit values are more correlated with the estimated quality than
for products with a short quality ladder. Hence, for differentiated products with a long
quality ladder, prices are appropriate proxies for product quality.
Other attempt that aims at disentangling quality from unit values at the productcountry level is the work of Feenstra and Romalis (2012). Differently from the
previous works, their methodology incorporates supply-side information. They
estimate a gravity model that incorporates endogenous quality to obtain measures of
quality-adjusted prices for traded goods at the 4-digit level for 200 countries for the
period 1984-2008. Their gravity estimation is theoretically grounded on a model of
endogenous quality, heterogeneous firms and transport cost, where countries have
non-homothetic preferences for quality that depend on their income. On the supply
20 side, endogenous optimal quality is a function of firm productivity, the production cost
of quality (wages) as well as transport costs. Under these assumptions, richer
countries (more productive) demand and produce high-quality goods and these
goods are exported to more distant countries. This identification of endogenous
quality relies on the idea of Washignton apples described by Hummels and Skiba
(2004): high-quality goods are shipped longer distances.
In this framework, product quality is a function of exporter's f.o.b. price divided by the
productivity-adjusted wages. Feenstra and Romalis (2012) rely on the equilibrium
conditions of the model to solve for productivity-adjusted wages and quality. They
obtain then a measure of product quality that can be constructed by the parameters
of the model that are estimated using a gravity equation. Their gravity estimates
show that the elasticity of substitution between varieties of the same 4-digit industries
is higher than in previous estimations that do not incorporate endogenous quality
such as Broda and Weinstein (2006). This finding implies that the observed
differences in export unit-values are attributed to quality differences. Their findings
also show that richer countries export and import high-quality goods. 10
3.3. Measuring quality at the firm level
At the firm level one of the few works that estimate product quality is Khandelwal,
Schott and Wei (2013). They develop a methodology to estimate quality and qualityadjusted prices at the firm-product-country of destination relying on demand function
estimation. They show that assuming a CES utility function which accounts for
10
Benkovskis and Woerz (2012) extend the Broda and Weinstein (2006) methodology to include
changes in the quality of traded varieties. They propose an export price index adjusted for non-price
factors using data at the 8-digit product level for 10 countries in central, eastern and south-eastern
Europe for the period 1999-2010.
21 product quality, the quality for each firm-product-country-year observation can be
estimated using information on quantities and unit values. They estimate quality as a
demand shifter that correspond to the residual of an OLS estimation of the quantity
and price (unit value) on country-time fixed effect that controls for price index and
income at destination, and product fixed effect that controls for variation across
products since prices and quantities are not necessarily comparable across products.
The estimated quality depends on the residual of such estimation and the elasticity of
substitution between products.
They estimate product quality at the firm level using Chinese firm-product
disaggregated at the HS6 level and country of destination level customs data for the
textile sector. This methodology requires an assumption on the elasticity of
substitution across products. Since Khandelwal, Schott and Wei (2013) are interested
in quality estimates for one specific sector (textile), they rely on the median elasticity
across textile products of Broda, Greenfield and Weinstein (2006).
The indicator of quality adjusted price competitiveness derived from this estimation
implies that conditional on price, a variety with a higher quantity (demand) is
assigned higher quality. In this framework, quality is any unobserved product
characteristic that increases demand other than price so it acts as a demand shifter.
Other related recent work that develops a methodology to estimate firm level product
quality is the work of Piveteau and Smagghue (2013). Their methodology does not
require any assumption on the elasticity of substitution between varieties. Using firmproduct and country of destination level customs data for France, they estimate
export product quality as a residual from demand function estimation where export
22 prices are instrumented using variations on exchange rate on imports as an
exogenous supply shock.
Box 4 – Data requirements to disentangle price and quality at the firm level
Alternative methodologies have been developed aiming at disentangling price from
quality indicators. The idea behind these methodologies is very simple and intuitive: a
higher quality is measured as all characteristics of a good that increase demand for a
given price.
The indicator of quality adjusted price competitiveness derived from this methodology
is closely related to the views of the European Commission on quality that defines it
in the following manner "Upgrading the products may also make customers willing to
pay a premium for them if the products are perceived to be of high enough quality"
(European Competitiveness Report 2013).
The data requirements to apply this methodology at the firm level are:
(1) Firm-product level information on values;
(2) Firm-product level information on quantities;
(3) Information on the elasticity of substitution among varieties.
While it is very difficult to have access to this information for domestic production,
most of the studies rely on Customs data that provide information on values and
quantities at the firm-product level for exports and imports. Khandelwal, Schott and
Wei (2013) rely on Chinese firm-product and destination country customs datasets to
estimate quality.
23 3.4. Other direct measures of quality
Studies relying on direct measures of quality are scarce due to data limitation since
quality attributes are very difficult to observe. There are, however, some exceptions
that rely on product attributes or explicit quality ratings that need to be highlighted.
Goldberg and Verboven (2001) look at price dispersion and quality adjusted prices
across European car constructors where the product-quality is inferred from product
attributes.
Crozet, Head and Mayer (2012) rely on expert assessments of the quality of
Champagne producers to estimate the key parameters of the quality interpretation of
the Melitz (2003) model. In the same line, a recent work of Chen and Juvenal (2013)
rely on experts wine ratings as a measure of quality to investigate the relationship
between real exchange rate pass-through and quality.
Other works use the ISO-9000 norms adoption (international production standard) as
a proxy for product quality such as Verhoogen 2008 and Hallak and Sivadasan forthcoming-.
Finally, Martin and Mayneris (2013) have recently developed a methodology to
identify high-end variety exporters (high-quality) for French exporters using
information on the list of members of the Comite Colbert, an organization composed
of the main brands of the French luxury Industry. They use the list of firms in this
Colbert committee as a benchmark. A firm exporting a high-quality variety (a highend variety) is defined as a firm that export the same product categories and charge
a price at least as high as the one charged by the members of the Comite Colbert.
They then examine how these high-end variety exporting firms react to gravity
24 measures relative to the low-end variety exporters. Their findings show that firms
selling high-quality products are less sensitive to distance and more sensitive to GDP
per capita.
4. Alternative measures of non-price competitiveness
This subsection presents alternative measures of non-price competitiveness at the
firm level related to R&D and other technological investments. The aim of this
subsection is to review the literature on the theoretical determinants of firms’
technological investments within the framework of heterogeneous firms as well as the
empirical measures used to capture technological differences across firms within
industries.
Several extensions of the baseline heterogeneous firms models à la Hopenhayn
(1992) -Melitz (2003) have been developed to incorporate binary technology choice
(Yeaple, 2005, Bustos, 2011, Lileeva and Trefler 2010, Bas, 2012, Bas and Berthou,
2013) or R&D investments that increase firm efficiency (Atkeson and Burstein, 2010).
These models show that the initial firm heterogeneity determines firms’ decision to
upgrade technology or invest in R&D that in turns enhance within-firm productivity
differently depending on the initial heterogeneity.
The binary technology choice models study the determinants of firms’ decision to
upgrade technology by paying a fixed technological cost (Yeaple, 2005, Bustos, 2011,
Lileeva and Trefler 2010, Navas Ruiz and Sala, 2007, Bas, 2012, Bas and Berthou,
2013). They rely on two key assumptions: (i) heterogeneity in terms of productivity;
and (ii) the existence of fixed costs of innovation / technology adoption to improve
firm efficiency. Firms faced the following trade-off between fixed technology cost and
25 marginal costs: firms must pay a fixed cost of technology that reduces their marginal
cost. All firms that upgrade their technology will improve their efficiency by reducing
marginal costs in the same proportion. These two assumptions explain why only a
subset of most efficient firms (bigger, more profitable and more productive) is able to
invest on R&D or rely on high-modern technologies to produce. These models
explain the heterogeneous determinants of firms’ technology choice what can be
called the “extensive margin of technological investments”.
Atkeson and Burstein (2010) develop a model where heterogeneous firms make in
each period risky investments in an R&D good in order to improve their productivity
(process innovation). The sunk entry investment is also made in units of this research
good, so that entry decisions can be interpreted as product innovation.
The empirical literature has highlighted a productivity premium for firms that invest in
technology / R&D (Bustos, 2011, Bas, 2012, Bas and Berthou, 2013, Lileeva and
Trefler 2010). This evidence points out that firms that invest in technology improve
their competitiveness. These empirical facts imply that within the same industry firms
that engage in technological investments have a greater productivity relative to firms
that do not upgrade their technology.
However, the direction of causality between firms’ R&D and productivity is very
difficult to establish. The literature has highlighted two-direction of causality between
firms’ R&D and productivity gains. Most productive firms have enough revenues to
afford the fixed technological costs (self-selection effect into innovation) and ex-post,
R&D and technological investments enhance firm productivity. Aw, Roberts and Xu
(2008) emphasize the two-directions of the causality between R&D and productivity:
while R&D investments are an important determinant of firm’ productivity, there is
26 also a selection effect of initially most efficient firms into innovation activities due to
the existence of the sunk fixed R&D cost. Relying on detailed data of Taiwanese
electronics exporters, they find that most productive firms self-select into export
markets and that the decision to export is accompanied by the decision to invest in
R&D that further raises exporter’s productivity gains.
In the same line, Doraszelski and Jaumandreu (2009) develop a model in which firm
productivity is determined by R&D investments with uncertain outcomes. Using firm
level data from Spain they estimate their model and find that investing in R& doubles
the degree of uncertainty in the evolution of a producers’ productivity level.
Balasubramanian and Sivadasan (2011) use data on firms’ patenting and production
activities to explore what happens when a firm patents. They find clear evidence that
new patent grants are associated with increases in firm size (by any one of a number
of measures), scope (the number of products it makes), and TFP. Bernard, Redding,
and Schott (2010) show that a firm’s TFP is positively correlated with the number of
products it produces. This holds both in the cross section and within firms over time.
Other branch of the literature on the micro determinants of firms’ R&D has focused
on technological spillovers. The existence of knowledge spillovers enhances firm
productivity and R&D investments of other firms that operate in similar technology
areas. The concentration of firms that sign new patents in an area has positive
effects on other firms’ decision to invest in innovation. The technological knowledge
is spread across firms in their environment. Bloom et al (2013) find that positive
technology spillovers for US firms and they show that the social returns to R&D are at
least twice as high as the private returns. Their findings also suggest that the effect of
technology spillovers is heterogeneous across firms of different sizes. For smaller
27 firms technology spillovers are more limited because few other firms operate in their
technology fields.
Box 5 – Different measures of non-price competitiveness
(1) Proxy of quality adjusted competitiveness based on demand function estimations:
-
Information on unit values
-
A higher quality is measured as all characteristics of a good that increase
demand for a given price (Khandelwal, 2010 and Khandelwal, Schott and
Wei, 2013, Piveteau and Smagghue 2013)
(2) Direct measures of quality for specific products and markets:
- Product-quality is inferred from product attributes for the Automobile market
(Goldberg and Verboven, 2001)
- Quality rankings and expert assessments of the quality of Champagne and
wine Crozet, Head and Mayer, 2012 and Chen and Juvenal 2013)
- ISO-9000 norms adoption (international production standard) (Verhoogen
2008 and Hallak and Sivadasan -forthcoming-).
- List of members of the Comite Colbert, an organization composed of the
main brands of the French luxury Industry. (Martin and Mayneris, 2013)
(3) R&D and other technological investments
-Firm level measures of expenditure on R&D and patents (Aw, Roberts and Xu
2008 and Bustos, 2011, Bloom et al, 2013)
28 -Product scope at the firm level measuring the number of new varieties of
domestic products introduced in the market (Bernard et al, 2010; Goldberg et
al, 2012)
-Firm level data on foreign technology proxies by imported inputs and capital
equipment goods (Bas and Berthou, 2012).
5. Macroeconomic shocks affecting firm competitiveness
This section revisits the literature that explores how firms adjust their price decisions,
product-quality choices and R&D investments to different macroeconomic shocks. A
first set of works investigates the role of competition on quality upgrading. A growing
recent literature focuses on the relationship between output- and input-trade
liberalization, firms' prices, markups and quality upgrading.
Other set of papers
explore the heterogeneous reaction of firms' prices to real exchange movements and
the pass-through effects. Finally, a last set of papers looks at the effects of industrial
cluster policies on firm TFP and innovation.
Box 6 – Main macroeconomic determinants of firms’ quality upgrading
(1) Competition
- Increasing competitive pressures creates incentives for incumbents firms to engage
in quality upgrading investments in order face competition;
(2) Trade liberalization
o Foreign competition channel: reductions on tariff affecting final
consumption goods;
29 o Imported inputs channel: access to high quality/more efficient
inputs from abroad allows firms to upgrade the quality of their final
products.
(3) Real exchange rate pass-through
-
The pass-through effect is greater for low-quality producers than for highquality ones.
(4) Industrial policies
-Mixed results of the effects of cluster industrial policies on firm performance.
5.1. Competition and quality upgrading
The effect of competition on product quality might be heterogeneous across firms
and products. Fiercer competition might increase the incentives for some firms to
engage in quality upgrading investments. Some firms might find it profitable then to
raise the quality of their products in order to face competition. Other firms, least
efficient, might be discouraged from investing in quality since they will not be able to
survive fiercer competition.
At the product level, Amiti and Khandelwal (2013) have explored the relationship
between import competition and product quality. They study how import competition
affects product quality upgrading using highly disaggregated export data to the U.S.,
import tariffs and a product level quality measure developed by Khandelwal (2010)
presented in the previous section. Their findings show that import tariff cuts across
30 countries affect the degree of product quality upgrading. The effect of foreign
competition on quality is non-linear as it depends on the distance of products to the
world quality frontier. Import competition foster quality upgrading for products close to
the frontier, while it has a negative impact on quality for products that are far away
from the world quality frontier.
At the firm level, competition might affect quality upgrading within-firm over time and
across firms producing in the same sector. Fernandes and Paunov (2011) look at the
effects of import competition on firm quality upgrading relying on Chilean firm-product
level data. Quality is measured with unit values and import competition is captured by
industry-level transport costs. They focus on a within-firm channel through which
competition affects firm-product quality over time. Their findings show that import
competition mainly from less developed economies is a key factor explaining firmproduct quality upgrading. Martin and Mejean (2011) investigate the effect of lowwage country competition in export markets on the growth of unit values in highincome economies. They emphasize a between-firms channel studying the
adjustments across French firms producing heterogeneous qualities of the same
product to fiercer competition of low-wage countries.
5.2. Trade liberalization, prices and quality
Trade liberalization affects firms' prices both through a reduction in final goods
(output tariffs) and intermediate goods tariffs (input tariffs). The impact of both tariff
cuts on firms' output prices is ambiguous since it affects markups as well as the
incentives to revise product-quality.
31 Output tariff reductions raise firms' competitive pressures (i.e., the pro-competitive
effect) forcing them to lower markups (e.g. Levinsohn, 1993, Harrison, 1994). In a
recent paper, De Loecker et al., (2013) investigate the effect of trade liberalization in
India on firms' output prices, markups and marginal costs. They rely on the
methodology developed by De Loecker and Warzynski (2012) to estimate markups at
firm level based on the estimation of a translog production function in order to
retrieve measures of output elasticity of variable input. De Loecker et al. (2013) find
that conditional on marginal costs, output tariffs cuts have a pro-competitive effect on
markups. Output tariff reductions might also create incentives to spend in quality
upgrading investments in order to revise product quality to face foreign competition
(Amiti and Khandelwal, 2013; Fernandes and Paunov, 2011).
Trade liberalization also affects both the cost and the access to imported varieties of
intermediate goods. Firms may take advantage of less expensive imported inputs to
reduce their marginal costs and then to reduce their output prices or increase their
markups. De Loecker et al., (2013) find larger declines in marginal costs associated
to input tariff liberalization relative to the observed reductions on output prices. This
imperfect pass-through effect from declines in marginal cost to output prices
reductions suggests that firms offset the cost reductions by raising their markups as
input-tariff fall. Input-trade liberalization might also allow firms to access to highquality imported inputs (high-priced). In this latter case, firms buy higher quality inputs
in order to upgrade the quality of their exported products thanks to input-tariff cuts
(Bas and Strauss-Kahn -2013-).
32 5.3. Real exchange rate pass-through, prices, markups and quality
A recent literature investigates the exchange rate pass-through to prices. Berman,
Martin and Mayer (2012) study the heterogeneous effect of real exchange rate
variations on export prices and volumes. Their findings suggest heterogeneous
reactions in pricing-to-market: more productive firms react to depreciation by raising
more their markups and by increasing less their export volume. This finding may
explain the weak effect of exchange rate movements on aggregate exports since
more productive firms explain most of aggregate export patterns. Chen and Juvenal
(2013) extends the analysis of Berman, Martin and Mayer (2012) to explore the
relationship between real exchange rate pass-through and quality with similar
findings in terms of quality instead of productivity: high-quality firms react to
depreciation by raising more their markups and by increasing less their export
volume.
Amiti, Itskhoki and Konings (2012) show that import intensity of inputs and market
shares of exporters are determinants of exchange rate pass-through in a crosssection analysis of firms. Smaller exporters that do not import intermediate inputs
have a complete pass-through relative to exporting firms with the highest import
intensity and market shares that display a low aggregate pass-through.
Auer, Chaney and Saure (2012) look at the relationship between the exchange-rate
pass-through in the European car industry and product quality. Their findings suggest
that this pass-through is greater for low-quality cars than for high-quality ones. They
develop a model that rationalizes this feature where firms produce products of
heterogeneous quality to consumers that have a preference for quality and are willing
to pay more for high-quality goods. Firms compete on prices and quality and so firms'
33 market power depends on both the prices and qualities of its direct competitors. In
this model markups are increasing in quality, exporting firms tend to produce highquality goods and the degree of exchange rate pass-through is decreasing in quality.
5.4. Firm competitiveness and industrial policy
Micro-level empirical studies investigate the effects of industrial policy through
clusters on firm-level performance (see Nathan and Overman, 2013, for a complete
survey). These studies find mixed results. The main econometric issue that these
studies face is to find a rigorous identification strategy that allows a microeconometric evaluation of the causal effects of industrial policy on firm
competitiveness. This section described this mixed findings in the literature on the
role of industrial policies in firm performance/competitiveness.
Criscuolo et al (2012) rely on a quasi-natural experiment methodology by exploiting
the exogenous changes in the area-specific eligibility criteria for a major program to
support manufacturing jobs in the UK (Regional Selective Assistance) and firm panel
data for the UK. They have an exogenous shock since the area eligibility is decided
by pan-European state aid rules which change every seven years. They rely on these
rule changes to construct instrumental variables for program participation. Their
results under instrumental variables show a positive impact of the industrial policy on
firms employment, investment and net entry. Their findings suggest that a 10\%
investment subsidy is associated with an increase of 7\% in employment and almost
half of this (3.6\%) arises from the growth of incumbent firms and the other half is
caused by a greater net entry. They also show that the positive effect of industrial
policy is explained by smaller firms producing with less than 150 workers. They
provide two possible explanations for this result: on the one hand, larger firms are
34 able to game the system and take the subsidy without changing their investment and
employment levels and on the other hand, smaller firms might suffer from financial
constraints. In terms of the channels through which the industrial policy raises
manufacturing employment is mainly through reducing unemployment. However,
they find not significant effect of the industrial policy on firm total factor productivity
gains after controlling for investment effect. Given that less productive plants get a
higher amount of subsidies, this implies that the industrial policy reduces aggregate
productivity in the industry due to reallocation effects since it increases the
employment share of low productivity firms. Devereux, Griffith and Simpson (2007)
also study the impact of this program to support manufacturing jobs in the UK on the
new investments by foreign-owned multinationals and UK owned multi-plant groups.
Their findings suggest that this industrial policy has positive but quantitatively low
effects on multinational location decisions.
Evaluations of industrial policies on firm performance also yield to mixed results.
Martin et al. (2011a) rely on firm and plant panel data in order to measure the
strength of agglomeration externalities in France. Based on GMM estimations, they
find that the only significant agglomeration externalities in the French economy in the
short-run are localization economies. These findings suggest that cluster policies
might improve firm productivity and competitiveness. Nevertheless, the elasticity of
firm-level TFP to the size of its own sector at the local level is rather low, equal to 5\%.
This result is also in line with measures obtained in the literature in other contexts by
Rosenthal and Strange (2004). This low elasticity of firm-level TFP to the size of its
own sector is not due to weak agglomeration economies, but because those gains
seem to be already well internalized by firms in their location decisions. They find that
35 localization economies are bell-shaped and when comparing the estimated
geographical distribution of plants that would maximize productivity and the one that
is actually observed suggests that the gap is not large at least in the French case. In
the same line, several works that focus on firm location decisions have demonstrated
that the presence of other firms in a region increases significantly the probability that
a plant chooses to locate in this region (see, e.g., Head et al., 1999; Crozet et al.,
2004; Devereux et al., 2007). Therefore, the gains arising from cluster policy are, at
least in the short-run, relatively small. Note that this finding is only about firm
productivity gains and it should not be confounded with welfare gains, which
agglomeration could also shape through other mechanisms than productivity.
However, this suggests that even though the starting point of cluster policy advocates
is right, their conclusion advocating costly public intervention to favor agglomeration
is dubious, at least in France. Martin et al. (2011b) rely on the same dataset to
evaluate the first cluster policy implemented in France, the Systemes Productifs
Locaux policy. They show that the policy helped declining firms producing in
declining sectors and areas, and had no measurable effect on firm-level productivity,
employment or exports.
Another strand of the literature focuses on other type of industrial policy related to
direct research subsidies to industrial R\&D. The evidence on the effects of these
direct subsidies on firm performance is also mixed. The surveys of David et al, (2000),
Klette et al, (2000), or Takalo et al, (2008) describe these mixed results. Bronzini and
Iachini (2010) use a proposal's score by an independent committee to investigate the
impact of receiving a R\&D subsidy on the performance of Italian firms. Their findings
suggest a positive causal effect on investment that is only significant for small firms.
36 Nevertheless, Jacob and Lefgren (2010) rely on a similar methodology for US
National Institute of Health grants and in that case, they identify a zero effect.
6. Conclusions
This survey presents a review of literature on firms' determinants of quality adjusted
competitiveness. The recent empirical literature has highlighted that prices (unit
values) are imperfect measures of product quality. Prices might represent higher
markups and costs not related to product quality. Recent empirical methodologies
have been developed in the literature to disentangle prices and quality. These
methodologies rely on demand function estimations to measure product quality using
micro-data. The main intuitive idea of these quality indicators is that firms / products
with larger demand (selling higher quantity) or market shares have a higher quality
conditional on prices.
Further research is required on measures of quality beyond unit values and prices.
Direct measures of quality derived from consumers’ behavior and tastes for specific
products could help to shed light on the determinants of firms’ quality upgrading and
the macroeconomic mechanisms that are at play.
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