Research Proposal
Understanding Productivity Levels, Dispersion and Growth in Latin American
and Caribbean Industries –
I - Differences in productivity level and growth within and across industries and firm
size: the case of Brazil.
II – Industry Case Studies
Eduardo Pontual Ribeiro
João Alberto DeNegri
Carlos Henrique Corseuil
Danilo Santa Cruz Coelho
Victor Prochnik
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Proposed by
Universidade Federal do Rio de Janeiro - UFRJ
Instituto de Pesquisa Econômica Aplicada – IPEA
Instituto de Pesquisa Econômica Aplicada – IPEA
Instituto de Pesquisa Econômica Aplicada – IPEA
Universidade Federal do Rio de Janeiro - UFRJ
Summary
We propose to measure productivity levels, heterogeneity and growth in manufacturing and
trade (retail) in Brazil using sector wide annual surveys and matched administrative data
with detailed worker information, for 1996-2005. This allows us to consider entry and exit
in detail. We shall use recent TFP measurement techniques that deal with the endogeneity
problem, suited for developing country data.
In addition, we propose to study in detail the case of the informatics industry (SIC 3.1
divisions 30, 32, 33). This is a high R&D, skilled labor and technology intensive sector,
and subject to significant external competition and target of government policy. We focus
on the innovation and productivity growth link for this sector.
1
1. Description of the data to be used in the study
1.1. Primary Sources
1.1.a. Pesquisa Industrial Anual (PIA)
Pesquisa Industrial Anual is an annual survey sampling formally established Brazilian
mining and manufacturing firms and plants, conducted by the census bureau IBGE
(InstitutoBrasileiro de Geografia e Estatística). The database's inception dates back to
1966.
In 1996 and 2005, the methodology has changed in ways that affects the temporal
comparability of productivity estimations. In 1996 it experienced major transformations
both in the sampling scheme and the information collected from the sampled firms. The
change in 2005 can be considered a minor one since it is limited to include firms that
employ less than five workers in the sampling scheme. To avoid any source of
comparability problems we will use the nine surveys relative to the period 1996 to 2004.
During this time the sample of firms in PIA is drawn from two strata: a non-random sample
of all Brazilian mining and manufacturing firms with a labor force of 30 or more workers
and employees (Estrato Final Certo, receiving a complete questionnaire called modelo
completo), and a random sample of small to medium-sized firms with a labor force of five
to 29 workers and employees (Estrato Final Amostrado, receiving a simplified
questionnaire called modelo simplificado).
2
A firm is eligible to be sampled in PIA only if at least half of its revenues stem from
manufacturing and if it is formally registered as a tax payer with the Brazilian tax
authorities. In 2004, PIA sample covers 42,371 firms among 155,656 eligible ones.
PIA contains three main groups of variables: (a) Information about longitudinal relations
across firms, (b) balance sheet and income statement information, and (c) economic
information beyond the balance sheet and income statement.
The main longitudinal information in group (a) is the register number as a tax payer firm
(CNPJ code). This allows us to link observations longitudinally, as well as combining it
with other sources such as RAIS. Among other variables in group (a) are the ones that
indicate the state of activity of a firm in a given year (such as whether it operates all year,
only part of the year, or exits) and its structural changes (such as whether it emerges from a
pre-existing firm or whether it creates a spin-off firm itself, and the like). Variables in
group (b) include cost, revenue, and profit information, detailed in a manner similar to a
typical Brazilian income statement. In the revenue side, for example, we are able to rip-off
non operational revenues, while on the cost side it is possible to identify intermediate
inputs, among other details. Variables in group (c) go beyond the income statement and
include data such as investment flows by type of asset, numbers of workers and employees.
Employment is broken down in production and non-production workers.
1.1.b. Pesquisa Anual de Comércio (PAC)
This is also an annual survey conducted by IBGE to collect the same kind of information as
in PIA. The only major difference is the fact that it deals with the trade segment, instead of
3
manufacturing. It covers, broadly speaking, three groups within the trade segments: retail
trade, wholesale trade, and repair services on vehicles and personal appliances.
Not only most of the variables in both surveys coincide but also the sampling scheme of
one mimics the other. Even the methodological disruptions of 1996 and 2005 are common
to both surveys. The only difference regarding the sampling procedure is the threshold to
distinguish census from sample coverage, which in the case of PAC is 20 workers or
employees, instead of 30 in PIA. The sample size of PAC in 2004 is 54,951 firms.
1.1.b. Pesquisa de Inovação Tecnológica (PINTEC)
This is a regular survey by IBGE on manufacturing firms, aiming to measure and
understand the innovation process. Sampling weights are used to compensate the deliberate
oversampling of firms that engaged in some form of innovation or acquisition of
machinery. Detailed quantitative and qualitative information on R&D expenditures and
innovation is provided. The design of the survey is based on CIS-4 surveys of the European
Community. There is data for 2003 and 2005, as well as 2000, with a slightly different
questionnaire. The sampling scheme includes all firms with 500 workers or more or firms
that have engaged in at least one type of innovation information and a sample of firms with
at least one innovation proxy information from other sources. The sample sizes of PINTEC
surveys are 10,000.
1.1.c Relação Anual de Informação Sociais (RAIS)
Relação Anual de Informações Sociais is an administrative file maintained by the Brazilian
Ministry of Employment and Labour (Ministério do Trabalho e Emprego - MTE). All
registered tax paying establishments must send every year to the Ministry information
4
about every single worker who had been employed by the establishment anytime during the
reference year.
The RAIS information provides a matched employer-employee longitudinal data set,
similar to those available in developed countries. The novelty differential of these data is to
combine the matched employer-employee structure with detailed information available on
workers' occupation. This characteristic of the data allows us to build a precise
categorization of workers in “blue” and “white” collar from the information on both
education and occupation. So the main use of RAIS will be to provide the labor inputs
variables.
In addition, the use of administrative data on labor (RAIS) allows us to have a direct
measurement of input quantities (number of workers) and an independent measurement of
factor prices. The administrative data have the regularly paid wages of each individual
worker, in a given year, in the firm or plant. So the main use of RAIS will be to provide the
labor inputs variables.
The census nature of RAIS is important to overcome the limitations of the sampling frame
of the firm surveys of IBGE. In principle it is not known whether the firm does not appear
in the IBGE data due to sampling or exit. Similarly, if a firm appears for the first time in the
IBGE data it is not clear whether it has just entered the market, or has entered the sample.
Such entry and exit information will be obtained from the RAIS administrative data.
In addition, we can also use RAIS data to either refine or complement the IBGE
information on structural changes. The issue again is that this information is available at
IBGE data only to those firms that continue in the sample. Broadly speaking, RAIS data
allow us to follow workers so to identify suspicious spurious entry and exit, when all
workers in a given establishment code switch to another one between two consecutive
years.
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1.2 Database
We plan to work with either two or three distinct database. Each one of these database will
combine two different sources: one establishment survey and RAIS. For sure one of these
combinations will be a RAIS-PIA database, which will cover the manufacturing segment.
The other combination will be a RAIS-PAC database for trade.
2. A summary of data availability
Since the year 2000 IPEA has got access to the RAIS micro-data. At that time it was
limited to the execution of a research project on job creation and job destruction for the
ministry of Labor (MTE), which also had a version adapted to an IADB research project on
the same topic. Nowadays IPEA and MTE have an institutional agreement where any IPEA
researcher may conduct studies using RAIS, as long as (s)he declares to be responsible for
not revealing any confidential information.
By the same time IBGE has adopted a procedure similar to the one adopted in the US
Census Bureau and in other developed countries concerning the access to confidential
information collected through establishment surveys. The procedure consists in providing a
room where the computers lack any means of data extraction (ie no internet connection, no
usb entries, no cd/dvd recorder, etc…).
IPEA researchers have been using intensely this facility. In fact as a consequence of an
agreement between IPEA and IBGE, the former institution was allowed to equip the
“confidential data” room of IBGE with four computers, in which it is stored not only the
PIA data but also some other firm level data provided by other institutions to IPEA, such as
RAIS. As a consequence of this arrangement between the two institutions IPEA has a fast6
track in getting permission to use the “confidential data” room of IBGE, avoiding a
burocratic process that may take 6 months for a standard (non-IPEA) request. Works
generated by this set up include DeNegri and Araújo (2007), DeNegri and Turchi (2007),
DeNegri, DeNegri e Coelho (2006), DeNegri and Kubota (2006) and DeNegri and Salerno
(2005), Corseuil (2007)
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3. Questionnaire(s) of the data
Please see attached files
PIA 2004 QUESTIONNAIRE.PDF
PAC 2004 QUESTIONNAIRE. PDF
PINTEC 2005 QUESTIONAIRE.PDF
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4. Detailed description of the study and methodology
PART I – Documenting differences in productivity level and growth within and across
industries, firm size and formality status.
The goal of the paper will be to document the productivity level, growth and heterogeneity
for Brazilian manufacturing and retail, with particular detail on the contribution of entry
and exit.
Manufacturing productivity (TFP) in Brazil has been growing from 1990 to 2000, as
estimated by Ferreira and Rossi (2003) using sector data, Muendler, Sevérn and Sepúlveda
(2002) and Schor (2004) using firm data1. . Pinheiro et al. (2000) using aggregate data
indicate that the productivity growth is observed using aggregates. Only Muendler, Servén
and Sepúlveda have considered the role of entry and exit, but the contribution of entry and
exit is small and highly correlated with the productivity evolution of continuing firms.
Many suggest that the trade liberalization of the early 1990s have contributed to much of
this growth, although Schor (2004) suggests that the effect is quite heterogeneous. It
remains to be seen if the period without significant policy changes2 has the same trend and
heterogeneity.
As mentioned above, we shall use data from three data sources: for manufacturing, the
Annual Manufacturing Survey (Pesquisa Industrial Annual - PIA) and for retail, the Annual
Retail Survey (Pesquisa Annual do Comércio - PAC). These surveys provide sales,
investment and intermediate input expenditure data, as well as sector information.
1
They use the Olley and Pakes (1996) method, to be discussed below.
2
In the 1996-2005 period, apart from a significant exchange devaluation in 1999, there were no significant
macroeconomic shocks (Plano Real is from 1994). Tariff changes were small compared to the previous 19881995 experience.
9
We will not be able to overcome the known sector price heterogeneity issues (Katayama,
Lu and Tybout, 2006, Foster, Haltiwanger and Syverson, 2008, Griliches and Klette, 1996,
and others). Except for labor inputs, our survey variables are firm revenues (from final
goods sales) and materials, energy and investment expenditure, deflated by appropriate
sector output price indices and input price indices. The known implications are that changes
in our productivity measure may be due to true productivity changes or due to demand,
mark-up and input price shocks.
On the other hand, using the matched administrative record data we shall consider two
issues in detail:
(i)
The role of entry and exit;
(ii)
The contribution of different labor types (measured by skill level)
The use of administrative data on labor (RAIS) allows us to have a direct measurement of
input quantities (number of workers) and quality (skill level), as well as independent
measurement of factor prices. The administrative data records regular wages for each
individual worker, in a given year, in the firm or plant.
We can present two types of productivity measurements. A simple average labor
productivity measure (deflated value added over workforce size, adjusted for quality) and a
total factor productivity (TFP) measure to be detailed below. Both measures will be used to
estimate
(i) Firm and sector productivity levels
(ii) Sector productivity growth; and
(iii) Productivity heterogeneity
Firm total factor productivity (TFP) is specified under a Cobb-Douglas production
function, as usual in the literature3
3
Alternative functional forms could be used, although more flexible forms, such as Translog do not lend
themselves to direct estimation due to potential multicolinearity. Indirect estimation of technology parameters
by use of dual factor demand functions is not possible for the Translog, as the cost function does not map into
10
yit = α + βl lit + βk kit +βm mit +βe eit + εit
εit = ωit + uit
where low case variables indicate log variables, y measures real revenue, l labor units used,
k deflated capital stock4, m deflated materials expenditure, e deflated energy expenditure
and εit is decomposed in a firm observed productivity shock and uit an unobserved, decision
making irrelevant, mean zero, revenue shock.
As discussed in the literature, e.g., Ackenberg et al (2008), under profit maximization input
use will be correlated with current productivity shocks ωit, generating inconsistent estimates
under OLS estimates. Alternative methods have been proposed in the literature to overcome
the least squares inconsistency. First, simple fixed effects panel data methods, under the
assumption that ωit is time invariant. This has been identified as too restrictive.
Second, Blundell and Bond (2000) assume a first order autoregressive (Markov) process for
productivity and allow for unobserved time invariant fixed effects
εit =µi + ωit + uit
ωit = ρωit-1 + vit
where vit is white noise. This specification allows the use of lagged variables as
instruments. See also Bond and Soderbom (2005).
A third method available in the literature is that of Olley and Pakes (1996) that also suppose
a Markov process for productivity shocks, but instead of instrumental variables, they use of
proxies. These proxies are obtained by the inversion of a quasi-fixed input demand function
that depends itself on current and past productivity shocks. There is an additional
assumption that there are flexible inputs that depend only on current productivity shocks.
production function parameters. The Translog cost function and associated factor demands are useful for
measuring returns to scale, that are not of direct interest here. (Chambers, 1988). In addition, the lack of
appropriate input and output quantity information hinder production functional form inverstigation.
4
The capital stock will be estimated suing a perpetual inventory method. For PIA, there is an alternative,
based on aggregate investment, as seen in Alves and Messa (2008).
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Levinsohn and Petrin (2003) note that for developing countries in particular there is a
significant share of firms that do not invest every year. The Olley and Pakes (1996) method
require non-zero investment in every year the firm appears in the sample. This is a serious
problem in our data, as at least a third of the manufacturing firm with 30 employees or
more report zero investment in a given year, as can be seen from the table below.
Table 1 – Firms declaring positive investment expenditure – Brazil –
PIA Manufacturing survey.
Zero Positive investment investment Year Total expenditure expenditure (%) (%) 1996 22,904 36.30 63.70 1997 21,935 35.44 64.56 1998 23,207 39.66 60.34 1999 23,933 40.72 59.28 2000 24,263 37.79 62.21 2001 26,151 39.99 60.01 2002 27,409 40.98 59.02 2003 28,790 43.90 56.10 2004 29,547 43.85 56.15 2005 31,666 45.82 54.18 Note: authors tabulations from PIA; firms
with 30 employees or more
In addition, only 6.51% of the firms in the census extract of the PIA data set reported
positive investment every year. As an alternative, Levinsohn and Petrin (2003) propose
using intermediate input use as a productivity shock proxy, adapting the Olley and Pakes
(1996) method. It is interesting to note that the empirical example of Levinsohn and Petrin
(2003) use deflated revenue and expenditures for estimation, although it is suited for
output/input quantities.
Two methods for estimation of total factor productivity shall be used. First, simple factor
shares as elasticities (βj) for inputs, as in Foster, Haltiwanger and Syverson (2008) and
Katayama, Lu and Tybout (2005):
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TFPit=ωit= yit – (βl lit + βk kit +βm mit +βe eit)
where βj=Cj/C, and Cj represent expenditures on input j (j=L,K,M,E) and C=ΣjCj. Note that
eit=ln(Ce). As mentioned above, y is measured as sector deflated firm revenue, and inputs
are measured as deflated expenditures but for labor.
The second method we shall use is the Levinsohn and Petrin method. It is a method that
attracted a lot of attention recently (e.g., Bergoing and Repetto, 2006) and has been
implemented in Stata. Other methods, as seen above, could be used for comparison, but we
do not think that more sophisticated methods could overcome the lack of appropriate data
for production function estimates.
The estimates will be based on unbalanced panels, with careful measurement of entry and
exit. As mentioned before, there are two ways to identify a true entry and exit for firms that
appear in the sample: PIA and PAC questions on entry (see 1st page of questionnaires
above) and RAIS records.5 The estimates will be used to decompose productivity growth
using the well known Foster, Haltiwanger, Krizan (2001) decomposition, with market share
(revenues) as aggregation weights. Namely, we use
∆TFPit = Σ θit ωit – Σ θit-1 ωit-1
=
ΣC θit-1 ∆ωit + ΣC (ωit-1 – TFPit-1) ∆θit + ΣC ∆θit-1 ∆ωit
+ ΣE θit (ωit – TFPit-1) + ΣX θit-1 (ωit-1 – TFPit-1)
where C identifies the continuing firms, E the entering firms and X exiting firms, θit
represent the revenue share of each firm and ωit is the firm TFP as seen above.
5
For example, if a firm does not appear in the PIA sample at year t, it may be due to sampling or a true exit.
In the former case, the firm will appear in the RAIS database at year t, while in the latter case, the firm will
not appear in the RAIS database either.
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Finally, firm TFP level and growth variance can be calculated as a measure of
heterogeneity for each year. This has an interesting decomposition in between and within
heterogeneity by firm size or sector.
Alternative heterogeneity measures, such as the interquantile range, do not lend themselves
to decompositions, due to the non-linear nature of order statistics. A non-decomposition
way to understand the sector and time evolution of firm productivity heterogeneity would
be to estimate quantile regressions for productivity using time and sector (or firm size)
dummies6. As seen in Koenker (2006), a quantile regression coefficient for a dummy has
the interesting interpretation of (conditional) sample quantile differences between the
selected and omitted dummy groups. As such, interquantile ranges for time dummies (say
the .25 and .75 quantile regression coefficients) may be compared between regressions with
and without sector dummies. This provides indirect evidence of the within and between
heterogeneity evolution, at the benefit of using robust statistics.
6
The sectors cannot be finely defined, as a larger number of sectors increase the number of estimated
parameters, rendering the estimates inconsistent, much like the linear fixed effects least squares panel data
model, where the estimates the fixed effect estimates are inconsistent (yet unbiased) due to the curse of
dimensionality problem.
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PART II – Case study: OBSTACLES FOR PRODUCTIVITY GROWTH INTHE
BRAZILIAN INFORMATION AND COMMUNICATION TECHNOLOGY (ICT)
SECTOR
The aim of this case study is to analyze the productivity distribution and productivity
growth in the Brazilian ICT sector identifying factors that can be considered obstacles to
the expansion of the more productive firms.
The ICT sector comprises the firms belonging to the divisions 30 (Manufacture of office,
accounting and computing machinery), 32 (Manufacture of radio, television and
communication equipment and apparatus) and 33 (Manufacture of medical, precision and
optical instruments, watches and clocks) of ISIC 3.1. A more refined classification may be
adopted at the beginning of the project. These are differentiated products, but they have a
common technological base and, in Brazil, they are subjected to the same policy measures.
Also, many of them are general purpose products (computers, for instance) and are thus
sold across several market segments. Other similar characteristics of the industry that are
relevant to the present study are the following: their expenses in R&D are higher than the
industrial average; they employ more skilled labor and they are subjected to a set of
specifics laws and regulations - Igliori, D. C and Diegues Jr. (2008), Gutierrez and
Alexandre (2003) and Prochnik and Dias (2005)
The ICT industry is particularly relevant to a productivity study, as the significant impact of
this sector on the productivity of the other sectors has been document. For instance, an
OECD report concludes that “… ICT is having substantial impacts on economic
performance and the success of individual firms, in particular when it is combined with
investment in skills, organizational change and innovation. These impacts can be observed
in firm-level studies for all OECD countries, but have not yet translated in better economic
performance at the industry or economy-wide level in many OECD countries”(OECD,
2004, 5).. More recently, a UNCTAD report states that “Studies reviewed confirm that
15
developing countries can gain as much as developed countries from ICTs in terms of
productivity. In recent years developing countries have received a significant positive
contribution to GDP growth from investment in ICTs.” - UNCTAD (2008, 180)
The Brazilian ICT sector is highly prioritized by the economic policy and has received
benefits that are not available to other economic sectors, through Law n. 8.248/1991,
known as "ICT Law" and Law n. 10.176/2001 (the "new ICT Law", or “Lei de
Informática” in Portuguese). These laws compel ICT hardware companies to invest 5% of
their revenue in R&D so that they can enjoy the exemption and subsequently reduction of
the tax on manufactured products (IPI, Imposto sobre Produtos Industrializados).
The ICT sector is thus particularly suitable for study because several relevant factors
explaining productivity growth and productivity distribution in different other sectors are
very evident in this sector, namely R&D expenses, skilled human resources and
government support, inter allia, as noted in a previous study on the Brazilian lower labor
productivity firms (Prochnik and Dias, 2005).
We propose to further the analysis using more data and better productivity measures, to be
estimated in Part I of the proposal. For example, the PINTEC survey allows us to study
specific barriers to innovation (see question 174 of the survey) and their impact on
productivity. This information may be used to segregate firms in the productivity
decomposition of the first part of the study, or in a regression model to evaluate teh effect
on productivity levels.
The tax benefits from the ITC Law depend on a firm applying for the benefits. Question
157 of the PINTEC survey indicates whether the firm has benefited from the ITC law tax
breaks. While aware of the potential endogeneity issues associated with a causal
16
interpretation of the effect of such information of productivity, nevertheless, such
information may be helpful to provide a first view of the potential benefits (or not) of such
law on productivity. In short, we expect that the study may possibly highlight questions and
problems that are of general occurrence but are harder to spot in other sectors.
One issue that is important for this sector is their ownership structure (foreign X local
firms). In general, foreign firms have access to broader resources and they also might
follow strategies that are different from the ones pursued by local firms. For instance, in
2007, large international industrial automation firms informed that they have postponed
productive investments in Brazil because their global strategy had lead them to prioritize to
invest in China (Prochnik, 2007).
The use of the data set local firms will be segmented into three classes: Brazilian firms that
engage in foreign direct investment (‘INV firms’), firms that only export (‘EXP firms’) and
firms that neither export nor invest abroad, i.e., that sell only to the domestic market
(‘DOM firms’), as in Helpman et al.(2004), Castellani & Zanfei (2006) and Prochnik et al.
(2007). This classification is broadly correlated with productivity, size and other firm
characteristics, as shown in table 1, restricted to local firms. Table 1 shows the results of
the application of the Kolmogorov-Smirnov non-parametric test to three distribution pairs:
INV firms vs. EXP firms; INV firms vs. DOM firms; and EXP firms vs. DOM firms.
Table 2 – Firm characteristics and the degree of internationalisation, measured by the
Kolmogorov-Smirnov stochastic dominance test - 2003.
(2) EXP firms
(3) INV firms
(3) INV firms
vs.
vs.
vs.
(1) DOM firms
(2) EXP firms
(1) DOM firms
Productivity
0.4457 xxx
0.4506xxx
0.7073xxx
Size (employees)
Added value/employee
Mean years schooling
0.4931xxx
0.4073xxx
0.1440xxx
0.5521xxx
0.8242xxx
0.4511xxx
0.6760xxx
0.3339xxx
0.4368xxx
17
Mean employment time
0.1879xxx
0.3184xxx
0.4675xxx
Average sales/employee
0.2875xxx
0.4419xxx
0.6506xxx
R&D expenditure/ sales
0.1723xxx
0.1753xxx
0.2892xxx
Total innovation expenditure
0.3700xxx
0.4753xxx
0.7611xxx
Masters and Ph.D.s in R&D
0.0600xxx
0.3528xxx
0.4132xxx
% Employees in R&D
0.1909xxx
0.4235xxx
0.6140xxx
Notes: (xxx) – variable significant at least at the 1% level;
Sources: Prochnik et all (2005), IBGE (2005) and Central Bank
IT should be noted that the size variable has as lower bound 10 employees, instead of the
usual 15 employee cut-off point of PIA. While the ITC sector may have very large
(international) firms, the survey covers firms of quite different firm sizes, as seen here.
The case study proposed here will benefit from the access to the large database that will be
used by the first study. The data from the 1998-2001 and 2001-2003 innovation surveys are
part of this database and will be extensively used as they contain relevant data not available
elsewhere in Brazil and, sometimes, even in international innovation surveys. As the ICT
sector is highly innovative, the innovation survey is a very useful database to study this
industry.
18
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Tecnológicas do Estado de São Paulo, São Paulo, mimeo, 2008
Katayama, H., Lu S. and Tybout. J. (2006). Firm-level Productivity Studies: Illusions and a
Solution.” Penn State Mimeo.
Koenker, R. (2006) Quantile Regression. Cambridge: University Press.
Levinsohn, J. and Petrin, A. (2003). “Estimating Production Functions usingInputs to
Control for Unobservables”, Review of Economic Studies 70, 317-341
Levinsohn, J., Petrin, A. and Poi, B. P. (2003). Production Function Estimation in Stata
using Inputs to Control for Unobservables. Stata Journal 4(2): pp. 113-123
Muendler, M., Servén, L. and Sepulveda, C. Productivity growth in the Brazilian industry.
In Brazil:new growth agenda (vol.II). report 22950-BR, The WorldBank.
OECD (2004) The Economic Impact of ICT Measurement, Evidence and Implications
OECD. OECD Publishing, 2004
Pinheiro, A.C., et al. (2004) Brazilian Economic Growth 1900-2000: lessons and policy
implications. IADB Region 1 Report.
Prochnik, V., Freitas, F. And Esteves, L. A. (2007) Firm Level Heterogeneity and
Internationalisation in Brazilian Industry, Eds: in deNegri and Araújo (op cit).; IPEA, .
Prochnik, V. And Araújo, R. D., "Analyzing the Low Degree of Innovation in Brazilian
Industry by Studying the Least Innovative Firms" (2005). Available at SSRN:
http://ssrn.com/abstract=1094305
Prochnik, V. Instrumentation and Control Industry, Research report to Programa de
Mobilização da Indústria Nacional de Petróleo e Gás Natural PROMINP, mimeo, 2007
Ribeiro, E. et al. (2004) Trade liberalization, the exchange rate and job flows in Brazil.
Journal of Policy Reform, 7(4), 209-223
Schor, A. (2004) Heterogeneous Productivity response to tariff reduction: evidence from
Brazilian manufacturing firms. Journal of Development Economics 75 373-396.
20
6 – Previous studies
Eduardo Ribeiro: This author have worked with micro firm level data from Mexico
(Maloney and Ribeiro, 1999, WorldBank PRWP 2131), Colombia and Chile (Maloney,
Fajnzylber and Ribeiro, 2001 WorldBank PRWP 2659) and Brazil (Ribeiro, 2007, and
Ribeiro and Jacinto 2008 cited below). Recently two papers for IPEA were written for a
forthcoming book organized by Coelho and DeNegri, using PIA and RAIS, on skilled labor
demand and skilled job flows. He also have extensive work with micro household data (see
CV below).
Jointly with Carlos Corseuil he worked together in a major research project on job creation
and job destruction using RAIS database from 1992 to 2000. The results were used to
publish a book in Portuguese following Haltiwanger, Davis and Schu 1996 (Corseuil and
Servo 2008 http://www.ipea.gov.br/082/08201004.jsp?ttCD_CHAVE=2784 ), as well as a
report
and
paper
on
job
and
worker
flows
for
the
IADB
(http://www.iadb.org/res/network_study.cfm?st_id=73) paying attention to entry and exits.
Apart from these publications, the research project provided the authors an opportunity to
develop know-how on compiling the RAIS-data to build variables at the establishment
level.
Carlos Corseuil: In addition to joint work with Eduardo Ribeiro, in the last three years this
author has been working intensively with RAIS data for the purpose of his PhD
dissertation, which is practically concluded by now (just waiting for a final reading of the
supervisor). In this work the author has used the information about the occupation of the
employees, which can be used to propose a refined classification of blue and white collar
workers. Finally, in the last chapter of the dissertation the author combine RAIS with PIA
to study changes in the occupational structure within the establishments and it’s relation
with performance.
João DeNegri: This author has arranged the agreements with IBGE, organized and
managed the joint database and ´secure room´ used in this study (RAIS/PIA/PAC), as well
21
as data from other sources, such as the IBGE´s PINTEC (technology industrial survey),
while Director of Industry Policies and Studies at IPEA. He has supervised the data
development, organized and coordinated research teams that elaborated papers for the
books listed in the CVs and cited above, as well as written extensively using the data on
innovation, export activity, productivity growth and investment.
Danilo Coelho: This author has been working and has helped organize the joint database
used in this study, as Coordinator of Labor and Industrial Policies and Studies at IPEA,
since 2006. His own work has dealt with innovation public financing in Brazilian
manufacturing, gender biases in promotion for domestic and multinational firms (linking
RAIS worker information and history and PIA and the Central Bank Census of Foreign
Capital), as well as organizing and coordinating teams of researchers that elaborated papers
for the books listed in the CVs and cited above.
Victor Prochnik: In the last three years, this author has written four papers for the research
projects directed by João De Negri, using the same database described in this proposal, in
the field of economics of technological change. Since 1984, he has also undertaken many
research projects based on interviews in firms, visiting factories and debating engineering,
management and economic questions with its owners, managers, consumers and suppliers.
For instance, in 1988, he published two papers on Industry/University relations in the
informatics sector and in 2007 he wrote a study on the supply of process automation and
control systems and hardware to the Brazilian petroleum industry.
22
7 – CVs
João Alberto De Negri
Institute for Applied Economic Research (IPEA)
Edifício BNDES, SBS, Quadra 1, Brasília DF 70076-900 Brazil
Fax: +55 61 315 5321, Phone: +55 61 315 5340
Email: [email protected]
1.
Education
Engineer, Federal University of Paraná, Brazil, 1992
Master in Economics, University of Minas Gerais, Brazil, 1994
PhD in Economics, University of Brasília, Brazil, 2003
2.
-
-
3.
3.1
Professional activities
Researcher of the Institute for Applied Economic Research (Brazil), 1997Vice-President of IPEA - 2005
Former Director of Sectorial Policies and Studies of IPEA – 2004-2007
Deputy-Director of Sectorial Policies and Studies of IPEA – 2003-2004
Represent the Institute in the “Fóruns de Competitividade” (Sectoral Chamber that
congregates Government, Entrepreneurs and Workers for making decisions on
implementation of industrial policy in Brazil)
General coordinator in the Secretariat of Foreign Commerce of the Ministry of
Development and International Trade, 1999-1999
Consultant for Inter-American Development Bank, United Nations Development
Programme, Ministry of Labor, Ministry of International Affairs, Ministry of
Development and International Trade, Ministry of Finance, among other
organizations.
Selection of the publications (2000-2007)
Books
DE NEGRI, João Alberto (Org.) ; TURCHI, Lenita (Org.) . Technological Innovation in
Brazilian and Argentinean Firms. Brasília: IPEA, 2006.
DE NEGRI, João Alberto (Org.) ; ARAUJO, Bruno (Org.) . As Empresas Brasileiras E O
Comércio Internacional. Brasília: IPEA, 2007.
DE NEGRI, João Alberto (Org.) ; DE NEGRI, Fernanda; COELHO, Danilo (Org.) .
Tecnologia Exportação e Emprego. Brasília: IPEA, 2006.
DE NEGRI, João Alberto (Org.) ; KUBOTA, Luis (Org.) . ESTRUTURA E DINÂMICA
DO SETOR DE SERVIÇOS NO BRASIL. Brasília: IPEA, 2006.
DE NEGRI, João Alberto (Org.) ; SALERNO, Mario Sergio (Org.) . Inovações, padrões
tecnológicos e desempenho das firmas industriais brasileiras. Brasília: IPEA, 2005. v. 1.
713 p.
23
3.2
Articles and Working Papers
2002
DE NEGRI, João Alberto ; FREITAS, Fernando . Inovação tecnológica,
eficiência de escala e exportações brasileiras. Brasília: IPEA, 2004 (Textos para
Discussão).
2003
DE NEGRI, João Alberto . Desempenho exportador das firmas industriais
no Brasil: a influência da eficiência de escala e dos rendimentos crescentes de escala.
Brasília: IPEA, 2003 (Textos para Discussão).
2003
DE NEGRI, João Alberto ; ARBACHE, Jorge Saba . O impacto de um
acordo entre o Mercosul e a União Européia sobre o potencial exportador brasileiro
para o mercado europeu. Brasília: IPEA, 2003 (Textos para Discussão).
2003
DE NEGRI, João Alberto ; ARBACHE, Jorge Saba ; SILVA, Maria Luiza
Falcão . A formação da ALCA e seu impacto no potencial exportador brasileiro para os
mercados dos Estados Unidos e Canadá. Brasília: IPEA, 2003 (Textos para Discussão).
2002
“Determinantes das exportações brasileiras: novas evidências”. XXX
Encontro Nacional de Economia – ANPEC. Dezembro de 2002 (with Arbache, J. S.)
English version “The Determinants of Brazilians Exports” was presented in Oxford
University.
2001
Mercado Formal de Trabalho: Comparação entre os Microdados da RAIS e
da PNAD. Texto Para Discussão do IPEA. N.º 840
3.3
Chapters
Rendimentos Crescentes de Escala e as Firmas Exportadoras Brasileiras, in R. Markwald
(edt.), Obstáculos ao Crescimento das Exportações Brasileiras: Diagnóstico e Sugestão para
uma Política Comercial, Funcex/IPRI, 2002;
DE NEGRI, João Alberto . Inovações, padrões tecnológicos e desempenho das firmas
industriais brasileiras. In: João Alberto De Negri; Mario Sergio Salerno. (Org.). Inovações,
padrões tecnológicos e desempenho das firmas industriais brasileiras. Brasília, 2005, v. , p.
5-46.
ARBIX, Glauco Antonio Truzzi ; SALERNO, Mario ; DE NEGRI, João Alberto .
Internacionalização gera emprego de qualidade e melhora a competitividade das firmas
brasileiras. In: João Alberto De Negri; Mario Sergio Salerno. (Org.).
DE NEGRI, João Alberto ; FREITAS, Fernando ; COSTA, Gustavo ; SILVA, Alan ;
ALVES, Patrick . Tipologia das firmas integrantes da indústria brasileira. In: João Alberto
De Negri; Mario Sergio Salerno. (Org.).
ARBIX, Glauco Antonio Truzzi ; SALERNO, Mario Sergio ; DE NEGRI, João Alberto .
Inovação, via internacionalização, faz bem para as exportações brasilerias. In: João Paulo
dos Reis Veloso. (Org.). Economia do conhecimento crescimento e inclusão social. Rio de
Janeiro, 2004, v. 1, p. 185-224.
ARBACHE, Jorge Saba ; DE NEGRI, João Alberto . Abertura econômica e
competitividade industrial: uma análise preliminar. In: Dieter W. Benecke; Renata
24
Nacimento. (Org.). Opções de política econômica para o Brasil. Rio de Janeiro, 2003, v. 1,
p. 161-184.
4
Other activities
Referee for Revista Brasileira de Economia, Pesquisa e Planejamento Econômico, Revista
de Econometria, Revista de Economia e Sociologia Rural, Economia Aplicada, Economia
Member of the Publishing Advice of the Boletim de Política Industrial do IPEA.
5
Research Interests
Technological innovation International Economics, Development Economics, Growth
Economics, Industrial Policy and Brazilian Economy.
25
CARLOS HENRIQUE CORSEUIL
May, 2008
HOME ADDRESS
BUSINESS ADDRESS
Av. Lineu de Paula Machado, 1006/903
Rio de Janeiro, RJ 22470-040
Phone: (5521) 3204-5844
IPEA – Rio de Janeiro
Av. Pres. Antonio Carlos 51/1406
E-mail: [email protected]
EDUCATION
University of College London
London School of Economics
Universidade Federal do Rio de Janeiro
Degree
Ph.D.
M. Sc.
B.S.
Year
in progress
1997
1994
Field
Economics
Economics
Economics
Ph.D. Dissertation : Labor Market Dynamics Under Imperfect Information, Advisor: Prof.
Pedro Carneiro
PROFESSIONAL EXPERIENCE
2008 ; Lecturer of Microeconometrics for the graduate program in Economics at EPGEFGV
1998/ - : Research Economist at IPEA (major fields: Labor Economics, and Income
Distribution)
Languages: Portuguese (fluent), English (fluent), Spanish (reading)
SELECTED CONFERENCES/MEETINGS
1999 – IADB/LACEA Inequality Network: Desigualdade e Pobreza no Brasil, Rio de
Janeiro. BARROS, Ricardo P., CORSEUIL Carlos H., LEITE, Phillippe G. Labor
Market and Poverty in Brasil
IV Meeting of Latin America and Caribe Economic Association (LACEA),
Santiago (Chile). BARROS, Ricardo P., CORSEUIL Carlos H. and BAHIA, Mônica.
Labor Market regulation and the duration of employment in Brazil
2001 - VI Meeting of Latin America and Caribe Economic Association (LACEA),
Montevideu. BARROS, Ricardo P., CORSEUIL Carlos H.; CURY, Samir and LEITE,
Phillippe. Liberalization and Income Distribution in Brazil.
2007 - Labour Market Dynamic Growth (LMDG), Sandbjerg.
CORSEUIL, Carlos H. Hiring Under Uncertainty And Firm Dynamics
European Association of Labour Economics (EALE), Oslo.
CORSEUIL, Carlos H. Hiring Under Uncertainty And Firm Dynamics
MAIN PUBLISHED WORK
(a) Books
- Criação, Destruição e Realocação de Empregos no Brasil (Job Creation, Job
Destruction and Job Reallocation in Brazil). IPEA, Rio de Janeiro, 2007.
26
-
Abertura Comercial Brasileira nos Anos 1990: Impactos Sobre Emprego e Salário
(The Trade Opening Process in Brazil during the 1990s: Impacts on Employment
and Wages). IPEA, Rio de Janeiro, 2003.
- Estrutura Salarial: Aspectos Conceituais e Novos Resultados Para o Brasil (Wages
Structure: Conceptual Issues and Novel Results to Brazil). IPEA, Rio de Janeiro,
2002.
(b) Papers in Brazilian Journals
- Determinantes da Evolução da Estrutura do Desemprego no Brasil; 1986-1995
(Determinants of Employment Structure in Brazil), in Revista de Economia Aplicada,
vol.1, n o 3, Jul/Set 1997. (with André Urani and Carla Reis)
- Desemprego Regional no Brasil: Uma Abordagem Empirica (Regional Unemployment in
Brazil: An Empirical Approach). Revista Economia Aplicada, vol.3, n o 3, Jul/Set 1999
(with Gustavo Gonzaga and João Issler)
- Labor Market regulation and the duration of employment in Brazil, Pesquisa e
Planejamento Econômico, v.29, n.3, 1999. (with Ricardo Paes de Barros and Mônica
Bahia)
- Labor Market and Poverty in Brasil Revista de Econometria, v.19, n.2, 1999. (with
Ricardo Paes de Barros and Phillippe Leite)
- Salário Mínimo e Pobreza no Brasil: uma abordagem de equilíbrio geral (Minimum Wage
and Poverty in Brazil: a General Equilibrium Approach) Pesquisa e Planejamento
Econômico, v.30, n.2, 2000. (with Ricardo Paes de Barros and Samir Cury)
- Poverty, Inequality and Macroeconomic Instability. Revista Economia Aplicada, vol.4, n o
4, 2001. (with Ricardo Paes de Barros and Rosane Mendonça and Maurício Reis)
- Uma Avaliação dos Impactos do Salário Mínimo sobre o Nível de Pobreza Metropolitana
no Brasil (An Evaluation of Minimum Wage Effects on the Poverty Level of Brazilian
Metropolitan Areas). Economia, v.2, n.1, 2001. (with Ricardo Barros and Miguel Foguel
and Phillippe Leite)
- Emprego Industrial no Brasil: Uma Análise de Curto e Longo Prazo (Manufacturing
Employment in Brazil: Short-run and Long-run Analysis). Revista Brasileira de
Economia, v.55, n.4, 2001. (with Gustavo Gonzaga)
- Decisões Críticas em Idades Críticas: A Escolha dos Jovens entre o Estudo e o Trabalho
no Brasil e outros Países da América Latina (Crucial Decisions at Crucial Age: The
Choice for the Youngs Between School and Work in Brazil). Revista Economia Aplicada,
vol.5, n o 4, 2001. (with Ricardo Barros and Miguel Foguel)
- A Evolução da Demanda por Trabalho na Indústria Brasileira: Evidências de Dados por
Estabelecimentos – 1985/97 (Labor Demand Evolution in Brazilian Manufacturing:
Evidences Using Plant Level Data – 1985/97), Pesquisa e Planejamento Econômico v.31,
n.2, 2001 (with Gustavo Gonzaga and Ricardo Paes de Barros)
- Gender Differences and Consequences on Welfare, Brazilian Review of Econometrics,
v.21, n.2, 2001 (with Ricardo Paes de Barros, Sérgio Firpo and Daniel Santos)
- Liberalização comercial e estruturas de emprego e salário (Trade Liberalization,
Eployment Structure and Wages). Revista. Brasileira de Economia., vol.58, no.4, 2004.
(with Jorge Arbache)
- Trade liberalization, the exchange rate, and job flows in Brazil. Journal of Policy Reform,
Londres, v. 7, n. 4, 2004. (with Eduardo Ribeiro, Daniel Santos, Luciana Servo, Brunu
Amorim and Paulo Furtado)
27
May, 2008
Curriculum Vitae Danilo Santa Cruz Coelho Professional Address
SBS QUADRA 1 – BLOCO J
ED. BNDES – Sala 1108
70076-900
Brasília, Brasil.
Phone: +55 61 33155187
E-mail: [email protected]
Education •
•
•
•
Ph.D. in Economics (with honors), Universitat Autònoma de Barcelona, 2004.
M.A. in Economics, Universitat Pompeu Fabra, 2000.
M.A. in Economics, Universidade Federal Fluminense, 1999.
B.A. in Civil Engineering, Universidade do Estado do Rio de Janeiro, 1996.
Main Fields of Interest Labor Economics, Applied Econometrics and Social Choice
Work Experience •
•
•
Coordinator of Labor and Technology Studies at Instituto de Pesquisa Econômica
Aplicada (IPEA), Brasília, Brazil. 2006-Present
Researcher at Instituto de Pesquisa Econômica Aplicada (IPEA), Brasília, Brazil. 1998Present
Internship at Instituto de Pesquisa Econômica Aplicada (IPEA), Rio de Janeiro, Brazil.
1997-1998
Articles in Scientific Journals •
•
How to Choose a Non-controversial List with k Names, with Salvador Barberà.
Forthcoming in Social Choice and Welfare (available online).
Maximin Choice of Voting Rules for Committees. Economics of Governance, 2005,
5:159-175.
28
•
Aspectos Dinâmicos do Desemprego e da Posição na Ocupação, with Marcelo Neri,
Milene Ancora and Alexandre Pinto, Revista de Estudos Econômicos, Brasil, 1997,
v.27, p. 137-159.
Books •
De Negri (Org.), De Negri, F. (Org.), Coelho, D. (Org.) . Tecnologia, Exportação e
Emprego. 1. ed. Brasília: Instituto de Pesquisa Econômica Aplicada, 2006. v. 1. 600 p.
Chapters in Books
•
•
Coelho, D. Ascensão Profissional de Homens e Mulheres nas Grandes Empresas
Brasileiras. In: João Alberto De Negri, Fernanda De Negri e Danilo Coelho. (Org.).
Tecnologia, Exportação e Emprego. 1 ed. Brasília: Instituto de Pesquisa Econômica
Aplicada, 2006, v. 1, p. 143-159.
Coelho, D., De Negri ; De Negri, F. . Tecnologia, Exportação e Emprego. In: João
Alberto De Negri; Fernanda De Negri; Danilo Coelho. (Org.). Tecnologia Exportação e
Emprego. 1 ed. Brasília: Instituto de Pesquisa Econômica Aplicada, 2006, v. 1, p. 17-
Working Papers
•
•
•
•
•
On the Rule of k Names, with Salvador Barberà. Second revision to Games and
Economic Behavior.
Foreign Capital and Gender Differences in Promotions: Evidence from the Brazilian
Transformation Industry, with Marcelo Fernandes and Miguel Foguel.
R&D Cooperation Between Firms and Universities: Some Quantitative and Qualitative
Evidences from Brazilian Manufacturing, with Lenita Turchi and Adriano Baessa.
Quantile Regression with Sample Selection: Estimating Married Women’s Return of
Education and Racial Wage Differential in Brazil, with Fabio Veras and Robert
Veszteg. Submitted to Pesquisa e Planejamento Econômico.
A Comment on “The Parametric and Semi-parametric Estimation of Sample Selection
Models: An Empirical Application to the Female Labor Force in Portugal “, [by M.F.O.
Martins, Journal of Applied Econometrics, 16(1) 23-39, 2001], with M. Helena Veiga
and Robert Veszteg.
Referee Activities Games and Economic Behavior, Social Choice and Welfare, Journal of Public Economic
Theory, Brazilian Review of Econometrics and Revista Economia.
Congresses •
Conference on Micro Evidence on Innovation in Developing Economies - UNUMERIT, United Nations University and University of Maastricht, Maastricht,
Netherland, 2007 – Speaker.
29
•
•
•
•
•
•
Annual Meeting of Associação Nacional dos Centros de Pós-graduação em Economia
(ANPEC), Recife, Brazil, December 2007 – Speaker and Discussant
Annual Meeting of Brazilian Econometrics Society (SBE), Natal, Brazil, December
2005, 2004 – Speaker and Discussant
19th Annual Congress of the European Economic Association (EEA-ESEM), Madrid,
Spain, August, 2004.
Seventh International Meeting of the Society for Social Choice and Welfare, Osaka,
Japan, July 2004 - Speaker.
Second World Congress of the Game Theory Society, Marseille, France, June 2004 Speaker.
Annual Meeting of Public Choice Society, Baltimore-Maryland, USA, March 2004 and
March 2003 – Speaker and Discussant.
Workshops (by invitation) GREQAM, Université de la Méditerranée, Aix-en-Provence, France, June 2004 , January
2003; Microeconomics Workshop, Universitat Autònoma de Barcelona 2004, 2002; 11th
ENTER Jamboree, Universitat Autònoma de Barcelona, Barcelona 2004
Languages Portuguese (Native), English (Fluent) and Spanish (Fluent).
30
May, 2008
EDUARDO PONTUAL RIBEIRO
Office Address:
Instituto de Economia
Universidade Federal do Rio de Janeiro
Av. Pasteur, 250, Térreo, Urca, Rio de Janeiro, RJ,
22290-240, Brazil
Phone(+55) 21 3873-5246
e-mail: [email protected]
http://www.ie.ufrj.br/
Education
Graduate:
Undergraduate:
Ph.D., University of Illinois at Urbana-Champaign, 1996.
M.A., University of Illinois at Urbana-Champaign, 1993.
B.A., Economics, Universidade Federal de Pernambuco (UFPE),
Brazil, 1991.
Areas of Expertise
Labor Economics and Poverty, Microeconometrics, Local Public Finance.
Professional Experience
-
-
Associate Professor of Economics, Universidade Federal do Rio de Janeiro (UFRJ),
Brazil, 2006-present.
Consultant, Inter-American Development Bank, Regional Development, 2006-2007.
Academic external consultant for the research project Economics of Aging and Public
Policy in Latin America and the Caribbean (Social Programs Division) .
Associate Professor of Economics, Universidade Federal do Rio Grande do Sul
(UFRGS), Brazil, 1997-2005.
Coordinator and Researcher, Southern Brazil Regional Lab – Millennium Development
Goals, UNDP, 2004-2007.
Consultant, Inter-American Development Bank, Red de Investigaciones Económicas,
2001-2003. Research on trade liberalization and job flows in Brazil.
Short time consultant, The WorldBank, PREM/LAC 1998 and 1999. Research on trade
liberalization, and labor markets in Chile and Colombia and Mexico.
Publications
Articles in Refereed Journals
-
The dynamics of firm size distribution. Revista de Econometria/Brazilian Review of
Econometrics, v. 27, p. 250-272, 2007.
31
-
Earnings and chronic renal disease. Transplantation Proceedings, v. 39, p. 378-380
(with Balbonotto, G. and Godoy, M.), 2007
Economic Effects of Regional Tax Incentives: A General Equilibrium Approach, (joint
with A. Porsse and E. Haddad) Latin American Business Review. 7, p. 195-216, 2006
Trade Liberalization, the Exchange Rate and Job Flows in Brazil (with co-authors),
Journal of Policy Reform, Vol. 7(4), pp. 219–233, 2004.
Asymmetric Labor Supply Empirical Economics, 26(1) 183 - 197, 2001.
Preference Structures and the Excess Burden of Income Taxes in Brazil. (with Jane H.
Leuthold). Public Finance Review, 27(3), 243-261, May, 1999.
Criação e Destruição de Emprego na Indústria e os Efeitos do Câmbio e da Abertura
Comercial: o caso da Indústria Gaúcha nos anos 90 [Job creation and job destruction
and the effect of trade liberalization and the exchange rate in Rio Grande do Sul
manufacturing] Revista Economia Aplicada. www.scielo.br/ecoa], 2006
Books and Reports
-
Criação e Destruição de Emprego no Brasil [Job Creation and Job Destruction in
Brazil] (with co-authors) IPEA, 2007
Objetivo de Desenvolvimento do Milênio 1 – Pobreza e Fome [MDG1 – Poverty and
Hunger] Millennium Development Goals Reports (with co-authors)– UNDP/PNUDBrazil and IDHS, 2005 (http://www.pnud.org.br/estudos/index.php).
Selected Working papers
-
Selection Bias, Returns to Schooling and Migration in Brazil (with V. Bastos). In:
SOLE 2008, New York.
Microeconomic Adjustment Cost Structure And The Dynamics Of Regional Industrial
Employment (with. P. Jacinto). Reg. Sci. Ass. World Congress 2008
Fluxos de Empregos, Fluxos de Trabalhadores e Fluxos de Postos de Trabalhos no
Brasil [job flows, worker flows and occupation flows in Brazil].XXXV Encontro
Nacional de Economia - ANPEC, 2007
Languages
Portuguese (native), English (fluent), Spanish (speaking and reading good), French (basic).
Complete CV in Portuguese: http://lattes.cnpq.br/8025102145074887
32
VICTOR PROCHNIK
HOME ADDRESS
Address: Rua Desembargador Alfredo Russel, n. 67, apt. l02
Leblon - 2243l-030 - Rio de Janeiro - RJ - BRAZIL
Phone (5521) 2512-4783
Cel phone (5521) 9914-9242
PROFESSIONAL ADDRESS
Institute of Economics
Federal University of Rio de Janeiro
Av. Pasteur 250 room 108
Phone (5521) 3873-5248
E-mail: [email protected]
EDUCATION
B. A. In Statistics - National School of Statistical Sciences of the Brazilian Institute of
Geography and Statistics, l977
Master of Sciences (Economics) - Institute of Industrial Economics, Federal
University of Rio de Janeiro, l983; title of thesis: "Cement industry in Brazil"
(awarded a prize by the National Bank for Economic and Social Development, l984).
PhD Degree (Production Engineering) - Coordination of Graduate Programs in
Engineering, Federal University of Rio de Janeiro, l996;
Ph.D. Dissertation: "Perspectives for Industrial Networks in Technology Intensive
Sectors in Brazil"
3 PROFESSIONAL EXPERIENCE
Associated Professor of the Institute of Economics/ Federal University of Rio de Janeiro since
l979. Courses taught in the last two years:
Microeconomics
Economics of the Multinational Firm
Competitive Strategy
4. SELECTED PUBLISHED PAPERS
WHY IS BRAZILIAN FDI SO LOW? Accepted to be published in Revista de Economia
Mackenzie;
ISSN:1678-5002;
São
Paulo,
(also
available
at
the
URL
www.ie.ufrj.br/cadeiasprodutivas) 2008
CADEIAS PRODUTIVAS E OPORTUNIDADES DE INVESTIMENTOS NO
NORDESTE BRASILEIRO, 2002 (with LIA HAGUENAUER): Revista de Análise
Econômica; (also available at the URL www.ie.ufrj.br/cadeiasprodutivas) 2002
33
ORGANIZATIONAL ROUTINES TRANSFERENCE IN TRANSNATIONAL
ENTERPRISES: TWO CASE STUDIES (with Tiago de Fernandes); Economia &
Tecnologia; ISSN:1415-451; (also available at the URL www.ie.ufrj.br/cadeiasprodutivas) 2001
5. SELECTED CONFERENCES/MEETINGS
THE IMPACT OF REVERSE KNOWLEDGE TRANSFER ON THE INNOVATION
PROCESS OF BRAZILIAN MULTINATIONALS; accepted to the Joseph A. Schumpeter
Society Conference, Rio de Janeiro, Brazil, July, 2008
ANALYZING THE LOW DEGREE OF INNOVATION IN BRAZILIAN INDUSTRY
BY STUDYING THE LEAST INNOVATIVE FIRMS (with Rogério Dias Araújo) - 3rd
Annual Conference Of The Global Network For The Economics Of Learning, Innovation
And Competence; Pretoria; South Africa, 2005 - (Available at SSRN:
http://ssrn.com/abstract=1094305)
SYSTEMIC INNOVATION, STRATEGIC ALLIANCES AND INTERNATIONAL
TECHNOLOGY TRANSFER TO BRAZIL, 20th Annual McMaster Business Conference
The 3rd World Congress on the Management of Intellectual Capital Michael G. DeGroote
School of BusinessMcMaster University Hamilton. Ont Canadá (also available at the URL
www.ie.ufrj.br/cadeiasprodutivas), 1999
6 SELECTED CHAPTERS IN BOOKS
A COMPARISON OF THE TECHNOLOGICAL STRATEGIES OF THE LESS
PRODUCTIVE ARGENTINE AND BRAZILIAN FIRMS (with Rogério Dias de Araújo) –
(Eds): João de Negri and Lenita Maria Turchi; IPEA, Instituto de Pesquisas Econômicas
Aplicadas
do
Ministério
do
Planejamento;
Brasília;
Brazil.
(URL:
http://www.ipea.gov.br/082/08201004.jsp?ttCD_CHAVE=2862), 2007
O GRAU DE INTERNACIONALIZAÇÃO DAS FIRMAS INDUSTRIAIS BRASILEIRAS
E SUAS CARACTERÍSTICAS MICROECONÔMICAS (with Fernando Freitas and Luiz
Alberto Esteves) Eds: João de Negri and Bruno César de Araújo; IPEA, Instituto de Pesquisas
Econômicas Aplicadas do Ministério do Planejamento; Brasília; Brazil, ISBN:13:
978858617093-5; 2007
EMPREGO E SALÁRIOS NA EVOLUÇÃO RECENTE DO SETOR DE SERVIÇOS E
TELECOMUNICAÇÕES BRASILEIRO (with Fernando Freitas and Luiz Alberto Esteves)
in ESTRUTURA E DINÂMICA DO SETOR DE SERVIÇOS NO BRASIL; Eds: João de
Negri and Luis Cláudio Kubota.; IPEA, Instituto de Pesquisas Econômicas Aplicadas do
Ministério do Planejamento; Brasília; Brazil, ISBN:8586170828; (also available at the URL
www.ie.ufrj.br/cadeiasprodutivas) 2006
SUCESSO E FRACASSO EM TRANSFERÊNCIA INTERNACIONAL DE ROTINAS
PARA O BRASIL (with Tiago Fernandes) in ESTUDOS EM NEGÓCIOS IV; Eds.
Margarida Gutierrez; Hélène Bertrand; Mauad Editora; Rio de Janeiro, Brazil; (also available at
the URL www.ie.ufrj.br/cadeiasprodutivas), 2005
34
UMA ANÁLISE DO BAIXO GRAU DE INOVAÇÃO NA INDÚSTRIA BRASILEIRA A
PARTIR DO ESTUDO DAS FIRMAS MENOS INOVADORAS (with Rogério Dias de
Araújo) Eds. João Alberto De Negri and Mario Sergio Salerno; IPEA, Instituto de Pesquisas
Econômicas Aplicadas do Ministério do Planejamento; Brasília; Brazil, (also available at the
URL www.ie.ufrj.br/cadeiasprodutivas), 2005
FOREIGN DIRECT INVESTMENT AND THE INDUSTRIAL STRUCTURE OF THE
BRAZILIAN FOREST SECTOR (with Carlos E. F. Young in The Brazilian Tropical Timber
Industry and International Markets; (Ed) MACQUEEN, Duncan; Earthprint Limited;
Stevenage; ISBN:1 84369 437 9; (also available at the URL www.ie.ufrj.br/cadeiasprodutivas),
2003
THE COMPUTER SCIENCES ACADEMIC COMMUNITY AND THE DIFFUSION OF
THE INTERNET IN BRAZIL (with Mauricio Yoshinori Une); in INFORMATION
SYSTEMS AND THE ECONOMICS OF INNOVATION; Eds: Chrisanthi Avgerou and
Renata Lèbre La Rovere; Edward Elgar Publishing; Great Britain, (URL:
www.ie.ufrj.br/cadeiasprodutivas), 2003
7 OTHER ACTIVITIES
Member of the Academic Committee of the 17th International Telecommunications Society
(ITS) Biennial Conference, 2008
Referee for:
Revista Brasileira de Inovação RBI/FINEP
Revista de Gestão da Tecnologia e Sistemas de Informação (University of São Paulo)
Latin American Business Review (COPPEAD/UFRJ)
Revista Economia (ANPEC -Associação Nacional de Centros de Pós-Graduação em
Economia)
Revista Economia Aplicada (University of São Paulo)
Revista Economia e Sociedade (Institute of Economics, UNICAMP
Revista de Economia Contemporânea (Institute of Economics, UFRJ
Revista Econômica do Nordeste
35
8. Budget
Please see separate file
36