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Adoption des technologies et Bien-Être

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Bukavu Journal of Economics and Social Sciences est la nouvelle revue de la Faculté de sciences économiques et de gestion de l'Université catholique de Bukavu (Province du Sud-Kivu, RDCongo). L'objectif de la revue est de collecter des données, d'organiser des connaissances sur différents aspects de la vie socioéconomique de la région du Kivu.
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Bukavu Journal of Economics and Social Bukavu Journal
Sciences est la nouvelle revue de la Faculté
de sciences économiques et de gestion de of Economics and Social Sciences
l'Université catholique de Bukavu (Province
du Sud-Kivu, RDCongo). L’objectif de la revue
est de collecter des données, d’organiser des 3 Revue de la faculté de sciences économiques et de gestion
connaissances sur différents aspects de la vie
UNIVERSITÉ CATHOLIQUE DE BUKAVUsocioéconomique de la région du Kivu.
AU SOMMAIRE ADOPTION
DE CE TROISI ME NUMÉRO
DES TECHNOLOGIES
technological progress and investment: déterminants des inégalités de revenu ET BIEN-ÊTREa non-technical survey à Burhale au sud-Kivu
Raouf Boucekkine et Bruno de Oliveira Cruz Godelive Batano Kusimwa,
Célestin Bucekuderhwa Bashige
et Jean-Baptiste Ntagoma Kushinganine
technology adoption in south Kivu
province subsistence farming
of democratic republic of the congo capital humain et croissance
Bucekuderhwa Bashige Célestin du bien-être à Kagera, en tanzanie
Christian Kamala Kaghoma
relation entre la satisfaction des
employés et leur intention de départ smuggling at the congolese-rwandan
des institutions de microinance au border: drivers, context and welfare
Kivu en rdc : effets modérateurs des impact
variables sociodémographiques Nene Morisho Mwana Biningo et Martin
Eddy Balemba Kanyurhi Doevenspeck
et Deogratias Bugandwa Munguakonkwa
22,50 €
ISBN : 978-2-343-11226-8
En collaboration avec la collection "Comptes rendus"
Fondée et dirigée par Eddie Tambwe
è
Maquette de couverture : Serge Lauret / Illustration : © mitay20 - Fotolia.com
Bukavu Journal
Adoption des technologies et Bien-être
of Economics and Social SciencesBukavu Journal
of Economics
and Social Sciences
Revue de la faculté de sciences économiques et de gestion
1
Revue d’économie et de sciences socialesRevue de la faculté
de sciences économiques
et de gestion
Publiée par l’Université catholique de Bukavu
Revue semestrielle
Comité de rédaction
Rédacteur en chef
Célestin BUCEKUDERHWA Bashige
Assistants de rédaction
Guillaume BIDUBULA Juwa
Christian KAMALA Kaghoma
éditeur Responsable
Université Catholique de Bukavu
recteurucb@ucbukavu.ac.cd, vraucb@ucbukavu.ac.cd
Comité Scientifque
Deogratias BUGAn DWA Munguakonkwa, Marc LABIE, Fréderic
KALALA Tshimpaka, Augustin MUTABAZI ngaboy’eka, Paul
KADUn DU Karhamikire, Paul GERADIn , Dieudonné MUHIn
DUKAdi-Kuruba, Paul-Robain nAMEGABE Rugarabura, Rita SUKADI,
Raouf BOUCEKKInE, Stephan MARYSSE, Jean-Baptiste nT AGOMA
Kushinganine, Eddy BALEMBA Kanyurhi, Ketty-Albert LUKUITSHI
Malaika, nene MORISHO Mwana Biningo, Paul Dontsop n ., Adamon
n DUn GU MUKASA, Janvier KILOSHO Buraye, Douglas AMULI Ibale,
John QUATTROCHI, Alice MUFnUGIZI n abintu.
Conception graphique : Serge Lauret.
© L’Harmattan, 2017
5-7 rue de l’école-Polytechnique
75005 Paris
ISBN : 978-2-343-11226-8
EAN : 97823431122682
Bukavu Journal of Economics and Social Sciences (BJESS) numéro 3, 2016UNIv ERSIt é cAt hol IqUE dE BUkAv U
Adoption
des technologies
et bien-être

En collaboration avec la collection « comptes rendus »
l’hARmAtt AN
3
Revue d’économie et de sciences socialesPrésentation
des auteurs
Raouf Boucekkine, PhD – est professeur des universités (classe exceptionnelle)
à l’Université d’Aix-Marseille, et membre senior de l’Institut Universitaire de
France. Il est actuellement directeur général de l’Institut d’Etudes Avancées
d’Aix-Marseille. Ses thèmes de recherche sont principalement la théorie de la
croissance et du développement et la macroéconomie dynamique. Il est
éditeur associé de nombreuses revues internationales de premier plan comme
Journal of Mathematical Economics, Journal of Economic Dynamics and
Control ou Macroeconomic Dynamics.
Bruno de Oliveira Cruz, PhD – holds a B. A. and a Master in economics from
the University of Brasilia, and a Master of Arts and PhD from Université
Catholique de Louvain. He has worked on. He has been researcher at IPEA
since 1996, working in themes on investment and technological adoption,
innovation and growth, regional and urban economics. In 2007, he was
awarded the best paper in the 4th Urban Research Seminar at the World Bank,
in the same year; he was nominated Deputy-director of Regional and Urban
Studies at IPEA. n ow, he is a Director for Economic and Social Research at
CODEPLAn (Brasília, Federal District, Brazil).
Célestin Bucekuderhwa Bashige, PhD – est professeur associé à la faculté des
Sciences Economiques et de Gestion et chercheur au Laboratoire d’Economie
4 Appliquée au Développement (LEAD) de l’Université Catholique de Bukavu.
Bukavu Journal of Economics and Social Sciences (BJESS) numéro 3, 2016Ses thèmes de recherche embrassent l’économie rurale, la sécurité
alimentaire, l’entrepreneuriat, la microéconomie du développement, l’accès aux
services publics, l’intégration régionale et le commerce transfrontalier. Il est
consultant dans plusieurs institutions et organismes internationaux comme la
Banque Mondiale, le Pn UD, l’EDF-RD, etc.
Eddy Balemba Kanyurhi, PhD – est professeur associé à la faculté des Sciences
Economiques et de gestion de l’Université Catholique de Bukavu (UCB) et
chercheur au Laboratoire d’Economie Appliquée au Développement (LEAD).
Il détient un doctorat en Sciences Economiques et Gestion de la Warocqué
School of Business and Economics de l’Université de Mons (Belgique). Ses
recherches portent sur la microfnance, le marketing bancaire et
l’entrepreneuriat. Il a récemment publié des articles dans les revues International Journal
of Bank Marketing, African Journal of Marketing Management et Bukavu
Journal of Economics and Social Sciences. Il mène aussi des consultances pour
le compte du Programme des n ations Unies pour le Développement (Pn UD),
Adam Smith International, EDF-RD, etc.
Deogratias Bugandwa Mungu Akonkwa, PhD – Docteur en Sciences
Economiques et de Gestion (Université Libre de Bruxelles) et détenteur
d’un Diplôme d’Etudes Approfondies en Gestion (Université Catholique de
5Louvain), Deogratias Bugandwa Mungu Akonkwa est professeur des cours
Revue d’économie et de sciences socialesde Méthodologies quantitatives en Economie et en Sciences Sociales à
l’Université Catholique de Bukavu, à l’Université de Goma et à l’Institut Supérieur
d’Informatique et de Gestion (Goma). Actuellement, il assure en même temps
les fonctions de Directeur Général Adjoint chargé des Opérations & Finances
de la Centrale des Mutuelles d’Epargne et de Crédit du Congo (MECRECO/
COOCEC). Ses principaux domaines de recherche sont la Gouvernance des
Institutions d’enseignement supérieur, la Gestion de la Qualité, le Marketing
Stratégique et la recherche marketing.
Godelive Batano Kusimwa – est assistante à la faculté des Sciences
économiques et de gestion de l’Université Catholique de Bukavu (UCB). Elle détient
une licence en Economie rurale. Elle participe aux études du Laboratoire
d’Economie Appliquée au Développement (LEAD) et du Centre d’Expertise
et de Gestion Minière (CEGEMI). Ses recherches portent sur la pauvreté et les
inégalités.
Jean-Baptiste Ntagoma Kushinganine, PhD – est professeur à la Faculté des
Sciences Economiques et de Gestion de l’Université Catholique de Bukavu
(UCB) et chercheur au Laboratoire d’Economie Appliquée au Développement
(LEAD). Il est titulaire d’un doctorat en Sciences économiques de
l’Université Catholique de Louvain. Ses travaux de recherche embrassent les thèmes
suivants : l’intégration régionale, la décentralisation, les fnances publiques,
la macroéconomie de l’environnement, la politique économique. II a conduit
plusieurs projets de recherche dans divers domaines, notamment en
économie de l’environnement, économie de développement et sur le commerce
transfrontalier. Il a été vice-recteur aux Afaires académiques de l’Université
Catholique de Bukavu et consultant dans plusieurs institutions des n
ationsUnies, notamment la Banque mondiale et la Commission Economique pour
l’Afrique. Il est actuellement membre du Comité n ational de la Recherche
Scientifque, du Comité national LMD en RDC et Conseiller Principal en 6
Bukavu Journal of Economics and Social Sciences (BJESS) numéro 3, 2016charge des Stratégies et Prospectives Economiques au Cabinet du Premier
Ministre de la RDC.
Christian Kamala Kaghoma, PhD – Kamala Kaghoma has a Ph.D in Economics
from Université de Yaoundé II-Soa with majors in Econometrics and
Environmental economics. He is currently a Professeur Associé and the Dean
of the faculty of Economics and Management of the Université Catholique de
Bukavu (UCB) where he has been teaching for more than a decade. Kamala’s
main areas of research include Public Economics, Environmental
Economics, Human resources Economics, Applied Macroeconomics,
Welfare Economics, Applied econometrics, Development microeconomics
and research methodology. His work focuses on child welfare related to w-a
ter and sanitation access, poverty dynamics, social mobility and
intergenerational (multidimensional) welfare transmission with emphasis on African
countries. He is currently working on youth employment, entrepreneurship
and internal migration in the Democra/c Republic of the Congo (DRC), his
country. Mr. Kamala Kaghoma has conducted several feld researches and
surveys in DRC and has a broad consultancy experience in Africa.
Nene Morisho Mwana Biningo, PhD – holds a PhD in Institutional Economics
from the University of Bayreuth in Germany. He also holds two masters
degrees in Macroeconomics and Management of Development Projects
(Development Studies). He is an Associate Professor at the Catholic University
of Bukavu (UCB) where he teaches Macroeconomics and Public Finances. His
felds of interest are Cross border trade, Regional Economic Integration and
Institutions and growth.
Martin Doevenspeck, PhD – Professor of Geographical Confict Research at the
University of Bayreuth, Germany. His research focuses on violent confict and
the political geography of climate change and risk in West and Central Africa. 7
Revue d’économie et de sciences socialestable
des matières
Technological progress and investment: a non-technical survey ......... 10
Raouf Boucekkine et Bruno de Oliveira Cruz
Technology adoption in South Kivu province subsistence
farming of Democratic Republic of the Cong .........................................o 32
Bucekuderhwa Bashige Célestin
Relation entre la satisfaction des employés et leur intention
de départ des institutions de microfnance au Kivu en RDC :
Efets modérateurs des variables sociodémographiques .........................77
Eddy Balemba Kanyurhi et Deogratias Bugandwa Munguakonkwa
Déterminants des inégalités de revenu à Burhale au Sud-Kivu ............124
Godelive Batano Kusimwa, Célestin Bucekuderhwa Bashige
et Jean-Baptiste Ntagoma Kushinganine
8
Bukavu Journal of Economics and Social Sciences (BJESS) numéro 3, 2016Capital humain et croissance du bien-être à Kagera,
en Tanzani e.................................................................................................. 162
Christian Kamala Kaghoma
Smuggling at the Congolese-Rwandan border: drivers, context
and welfare impact ......................................................................................190
Nene Morisho Mwana Biningo et Martin Doevenspeck
• • •
9
Revue d’économie et de sciences socialesTechnological progress
and investment
A non-technical survey
Raouf BOUCEKKINE et Bruno de Oliveira CRUZ*
RéSUMé/ABSTRACT
t his paper presents a non-technical overview of the recent investment literature with a special
emphasis on the connection between technological progress and the investment decision.
First of all, we acknowledge that some dramatic advances have been made in the 1990s in
understanding and modelling non-convex capital adjustment schemes and irreversibility.
Nonetheless, this new literature has not always satisfactorily accounted for the
investmentspecifc (or embodied) nature of technical progress. We argue that the recent technological
trends towards more embodiment have had a heavy impact on the way the investment
decision is taken and is to be taken. t his is turn should imply the reconsideration of many
empirical results, and a more careful modelling strategy taking into account the price variables and
scrupulously choosing the most appropriate level of (dis)aggregation.
Keywords: Investment, technological progress, Non-convex adjustment, irreversibility,
Embodiment.
Journal of Economic Literature: E22, E32, o40.
efective demand and employ-1. Introduction
ment. If only we knew more about
“Economic Teory can give rea- the determinants of investment!
sonably good account of how the But unfortunately, our knowledge
in this direction is still very mea-level of investment infuences
ger. One might well ask, what is
* Bruno Cruz acknowledges the fnancial wrong with the theory of
investsupport of CAPES Foudation (Brazil) for this 10 ment? Or perhaps, what is wrong research.
Bukavu Journal of Economics and Social Sciences (BJESS) numéro 3, 2016with the subject matter itself! For quite unsuccessful in empirically
one thing, this variable - the pivot forecasting this component of a-g
of modern macroeconomics- has gregate demand. One can observe
apparently lived a somewhat noma- that heuristic models, such as
accedic life among the various chap - lerator models, have shown to be
ters of economic theory. Perhaps empirically better adjusted than
it has not stayed long enough in models based on
micro-foundaany one place. Perhaps it has been tions. Te apparent superiority of
ill-treated” (Haavelmo, T. (1960) A heuristic models should not lead
Study in the Teory of Investment, us to forget about price variables
pp.3) and Tobin’s “q” when talking about
With this astonishing paragraph, investment. First of all, the superio -
Haavelmo (1960) begins his famous rity of estimated accelerator mo -
book A Study in the Teory est- dels, for example, does not mean
ment Teory in the early 1960s. that decision is made and how this
Many surveys on the subject have decision is oriented by economic
appeared since then (for instance, policy; there is not a theory behind
Jorgenson, 1963; Chirinko, 1993); the accelerator, it’s just a technique
theory has made an incredible step that apparently works in some
cirtowards a more comprehensible cumstances and that has its own
understanding of this important problems (see Oliner, Rudebusch
variable. Yet in 2000, Caballero, and Sichel, 1995, for example).
one of the most important resear- Second, the bad empirical
perforchers in the feld, opened his talk mances of optimal control-based
“Aggregate Investment: Lessons investment models can be also
parfrom the Previous Millennium” tially attributed to the way they are
with the following statement: tested in practice. For example, the
“But while we all may agree on the way the rate of capital depreciation
importance of investment for a n-a is traditionally treated in
econometion’s economic health, our unders- tric applications is highly
questiotanding of its determinants, both at nable, especially during the 1990s,
the microeconomic as well as the as it does not accurately capture the
macroeconomic level, has remained pace at which capital goods actually
limited. Te empirical investment become obsolete.
literature has been nearly merciless It seems therefore overwhelmin -
in evaluating investment theo- gly clear that the traditional user
ries.” (Caballero, R. 2000 American cost and Tobin’s q models are too
Economic Association Session. In much “stylized” to serve as
univerMemoriam: Robert Eisner, pp 1-2). sal and unquestionable models of
Tis pessimistic view about the both microeconomic and aggregate
evolution of our knowledge about investment. Tere is an urgent need
investment might be infuenced by to profoundly study and docu -
11the fact that researchers have been ment how the investment decision
Revue d’économie et de sciences socialesis efectively taken in real life over (summing up the investments done
a wide variety of microeconomic by all the establishments of their
cases. In particular, a much clo- sample) and an index of microeco -
ser inspection into how the capi- nomic investments and showed that
tal adjustment processes actually it is actually very high.
take place is required, especially in b. Recent empirical studies
connection with the pace of tech - confrm that the Information and
nological progress. Tis calls for Communication Technologies (ICT
two major focuses: hereafer) burst in the 1990s has
a. In the traditional optimal control considerably distorted the
investtheory developed (see for instance ment behavior at all levels: Te
assoChirinko (1993)), the capital adjust- ciated dramatic decrease in the
relament issue is settled by setting a tive price of capital during the 1990s
convex adjustment function, usually has rehabilitated price variables as
a quadratic function for tractability. a major determinant of investment
But is adjustment gradual in real decisions (see for instance Tevlin
life? Te answer is defnitely no. It is and Whelan, 2003). Tis has led
now known that investment at the some authors like Whelan (2002)
frm level is lumpy and infrequent to advocate another empirical
ap(Doms and Dunne, 1998), and that praisal of the investment decision,
these two characteristics are unli- based on a two-sector accounting
kely to completely disappear in the benchmark model in order to refect
aggregate (Cooper, Haltiwanger the pace of the relative price of cap -i
and Power, 1999). Doms and Dunne tal and the very fast depreciation of
worked on the investment patterns an increasingly large fraction of the
of 12 000 plants in US manufa-c capital stock. At the same time,
anoturing over the interval 1972-1989. ther complementary view of
investFor each frm, they constructed a ment emerged, resurgence of the
series of the proportion of the total vintage capital theory of the sixties:
equipment investment of the frm. It investment and technological
innoturns out that the largest investment vations are not “separated”,
investperiod accounts on average for more ment is the unique vehicle of inno -
than 25 percent of the 17 year of in- vations decisions, as Greenwood
vestment. Moreover, more than half and Jovanovic (2001) observe:
of the frms exhibit a capital growth ”In reality, advances in
technoof about 50 percent in a single year. logy tend to be embodied in the
laAlso, the second largest investment test vintages of capital. Tis means
spike ofen comes next to the largest that new capital is better than old
investment, which suggest that the capital, not just because machines
two biggest spikes correspond to a sufer wear and tear as they age, but
single investment episode. Finally, also because new capital is better
Doms and Dunne studied the corre- than the old capital was when the
12 lation between aggregate investment latter was new. It also means that
Bukavu Journal of Economics and Social Sciences (BJESS) numéro 3, 2016there can be no technological pro- 2. Characterization
gress without investment” (pp. 179- of microeconomic adjustment
180, Italics ours).
In this paper, we carefully review As we have mentioned in the
the state of art of the literature introduction, there is a compelling
investment regarding these two evidence that investment patterns
fundamental aspects. We start by at least at the plant level are far from
a non-technical discussion of the gradual, which goes at odds with
“new” investment theories which the optimal control investment
have recently introduced non- model with convex adjustment
convex adjustment costs and irre- costs. How could the economic
versibility in the heart of invest- theory deal with this clear
inconment theory (Section II). We frst sistency problem? We shall briefy
notice that these theories have review the recent stream of econo -
considerably improved our unders- mic literature devoted to this fun -
tanding of how the investment damental issue. We start with the
decision is taken both at the plant basic non-convex adjustment costs
and the aggregate levels. However, story, more sophisticated concepts
we also observe that, with some will be treated along the way.
very few exceptions, the modelling
of technological progress in such 2.1. Non-convex capital
adjusttheories is not markedly diferent ment costs
from traditional “exogenous” mo - Tis issue is very
comprehensideling in the neoclassical model; vely treated by Caballero (1999),
the whole action inherent in these among others. Following this
autheories come from non-convex thor, assume that a given frm has
*adjustment and other ingredients an optimal capital stock, K , which
like irreversibility. nonetheless as depends on the interest rate and
outlined just above, there are plenty on any proftability (exogenous)
of microeconomic and macroeco - variable (possibly technological
nomic studies pointing at a signi- innovations). Te crucial thing
fcant change in the composition is the specifcation of the
adjustof technological progress afer the ment costs. If one aims at
genera60s, and showing that embodiment ting infrequent and lumpy
investshould be seriously accounted for, ment patterns at the optimum, he
especially in the computer era. We should care about the functional
therefore end the survey with a de- form to assign to these costs. Te
tailed non-technical exposition on traditional simple convex form is
modelling embodiment both at the inadequate. In order to generate
micro and macro level, and on the infrequent investment, the
adjustmethodological consequences of ment costs function should be cho -
the information technologies boom sen such that it increases sharply
13in the 1990s (Section III). around the point of no adjustment.
Revue d’économie et de sciences socialesK1As mentioned by Caballero, a cost the following. Call K * , a measure K
proportional to the size of the nee- of capital imbalance. Assume that
ded adjustment is enough. now, the actual capital imbalance is near
this specifcation gives infrequen - the point which maximizes the
vacy, but not lumpiness. To get the lue of the frm (roughly speaking the
latter characteristic, there must be discounted sum of the present and
an advantage in bunching invest- (expected) future profts of the frm).
ment, and this can be achieved if Ten, the frm may not have any
for example adjustment requires incentive to pursue the adjustment
a fxed cost. For a positive invest- because of the incurred adjustment
ment I, the associated adjustment costs. Tis is specially true for small
cost is consequently: c +c I where adjustments because of the fxed f v
c and c are two positive constants. costs. Hence, the frm may perfectly f v
A similar adjustment costs func- choose to be inactive in such a case.
tion has to be set in case of disin - Indeed, it is possible to prove
rigovestment (when I < 0), including a rously that there exists a non-empty
positive fxed cost of disinvestment. range of inaction in the space of Z.
We are in a typical situation where More concretely, there exists a target
the adjustment technology exhibits point L such that there is no
investincreasing returns. For the relative ment for Z > L, and a target point U
importance of adjustment costs to such that there is no disinvestment
be constant over time, the latter for Z < U. Which ultimately means
*term is usually multiplied by K . that there exists a range of inaction
How does the optimization mo- (L, U). Infrequency and lumpiness
del perform with this modifed can therefore be generated within
adjustment costs function? And this alternative framework.
how does the obtained demand for 2. Is the q-theory robust to such
capital goods look like, in particu- a "realistic" specifcation of
adjustlar in relation with technical inno- ment costs? Recall that in the basic
vations? Te main properties of the optimization setting, we get the fo-l
optimization problems are stated in lowing relationship between
investCaballero (1999), section 3. Te fo-l ment and (marginal) q : q=1+C’(I),
lowing points can be highlighted: when the unit price of capital is equal
1. In such a model, there is room to 1 (s = 1). In the quadratic case, ie.
2for inaction. Tis a crucial departure when C(I)=bI , where b > 0 , we get
from the standard models with qua- a linear relationship between q and
dratic adjustment costs. In such mo- I. In the general convex case, we get
dels, capital accumulation and in- an implicit monotonic functional
vestment paths are smooth in time,
so there is no infrequent or lumpy 1. Te reader interested in the exact
mathematical solution can _nd all the technicalities in investment episode. In the
alternaCaballero (1999). Te technique makes use of
tive model, things are very diferent.
dynamic programming in continuous time 14 Te intuitive reasoning behind is with the associated optimality principle.
Bukavu Journal of Economics and Social Sciences (BJESS) numéro 3, 2016relation between q and I : I = φ(q). simply due to the use of linear
reTo each value of q corresponds a gressions, as the “true” relationship
single investment amount. Is this between q and capital is probably
functional relationship preserved highly nonlinear.
in the case of adjustment costs with 3. How do technological
innoincreasing returns? Te answer is vations enter this new investment
no as demonstrated by Caballero set-up? Actually, these new
microand Leahy (1996). In efect, the rela- economically founded adjustment
tionship between marginal q and Z, theories enrich in a considerable
the capital imbalance, is not func- way the discussion on the efects
tional over the Z space in that the of technological innovations (or
same value of q is associated with any other external shock) on the
diferent investment values. And in demand for equipment. In the stan -
the region of the Z space where this dard optimal control theory, there
relationship is functional, it is highly is no range for inaction. In the case
nonlinear. So in the very best case, of a technological improvement
the q-theory only holds "locally" but (raising the productivity of
capithe induced functional relationship tal goods for example), q increases
between q and I is by no way linear. since it is a measure of the value
Tis suggests two main points. to the frm of an additional unit
First of all, the q-theory is typically of (new) equipment. As q goes up,
a non-robust theory. Indeed, there investment is systematically
stimuexists a huge literature on this par- lated, because q is monotonically
ticular point. Many authors have related to I via the investment
equastudied the implications of diferent tion, q = 1 + C’(I), under the strict
specifcations of the adjustment convexity of the adjustment costs
costs departing from the initial function. When a range of inaction
quadratic formulation. Some have (optimally) arises, a technical
innoremoved the fxed costs; others vation does not necessarily trigger
1have added a strictly convex term to an investment boom .
the adjustment functions. In some Let us have a closer look at this
contributions, the monotonic rela- specifc point. A careful reading
tionship between q and investment of Caballero and Engel (1999)
is recovered but at the cost of less allows to notice that
technologirealistic generated investment pat- cal progress, purely disembodied
terns, notably in terms of lumpiness in this theory, exclusively
ope(as in the very well-known Abel rates through the optimal capital
*and Eberly’s 1994 paper). Because of stock, K , thus through the
imbathese robustness problems, the fai- lance ratio Z. Indeed, neither the
lures registered in its econometric threshold, L nor the threshold U
implementation are not surprising
at all. Second, a more favorable to
1. Tis may be true even in the absence of 15the q-theory, these failures may be fxed costs. See Abel and Eberly (1994).
Revue d’économie et de sciences socialesdepends on technological progress: 2. 2. Irreversibility and
In Caballero and Engel (1999), both uncertainty
are function of the fraction of p-ro Te literature relating
investfts foregone due to capital stock ment and uncertainty has
geneadjustment, which is ultimately rated two diferent conclusions.
assumed to be randomly distribu- In the one hand, the presence of
1ted . Tus, a technological impro- constant returns to scale and
symvement has essentially the virtue metric adjustment costs have led
of raising the optimal capital stock, to the conclusion that uncertainty
*K , which for given K, lowers the increases the value of investment
Kcapital imbalance Z since Z = . (see for instance Hartman, 1972, *K  
Suppose that initially Z is in the and Abel, 1983 and 1985)). In this
range of inaction (L,U). A small set-up, the marginal value of capital
technological shock is unlikely to is a convex function of the stocha-s
lower Z at a value below the thres- tic process: Jensen’s inequality thus
hold L. For investment to occur, ie. implies a higher demand for
investfor Z to be shifed below L, the ma- ment. On the order hand, the
intrognitude of the technological impro - duction of irreversibility gives rise to
vement should be big enough. Tis another diferent mechanism (Dixit
is one the reasons why technologi- and Pindyck, 1994, and Pindyck,
cal difusion is not instantaneous. 1988). Irreversibility of investment
Investment involves some non- amounts to saying that undertaking
negligible adjustment costs which investment projects results in some
makes it optimal sometimes to not unrecoverable initial costs, the
soact, to not invest. In such a case, the called sunk costs. Uncertainty on
institutions have a role to play, and future benefts and costs of inves-t
economic policy crucially matters. ment projects makes the resulting
For example, when the technologi- investment problem trickier. If we
cal improvement is not enough big assume with Dixit and Pindyck
to encourage investment, a further that if the investment project is not
decrease in the interest rate (or any undertaken today, the frms retain
other component of the user cost of the option of undertaking the pro -
capital) may help the difusion (by ject tomorrow, there is a clear value
☐increasing K and then by lowering of waiting: the frms have always the
even more the capital imbalance Z). possibility to postpone investment
Uncertainty and irreversibility tomorrow in order to learn more
are other factors that call for ina-c about present and future project
tion and delayed adoption of inno - payofs. Tis value of waiting, this
vative tools, as it is explained in the option of waiting, is the main cha -
next sub-section. racteristic of the above mentioned
theories, and it has some crucial
implications in terms of investment
1. See page 8 of the article by Caballero and 16 patterns (lumpiness, infrequency, as Engel (1999).
Bukavu Journal of Economics and Social Sciences (BJESS) numéro 3, 2016observed in micro data) and econo- to the innovation by investing, that
mic policy. We shall summarize the is the threshold value of expected
related stream of literature in the MPK above which the frm invests,
few following points. is a priori signifcantly bigger than
1. As argued in Chirinko (1996), the typical user cost or discounting
\...In the traditional optimal control rate threshold values encountered
model àla Jorgenson, investment is in the traditional theory. To these
reversible because well-functioning typical terms, one has to add the
secondary markets exist or the rate value of waiting, which is in general
at which frms wish to reduce the a function of a measure of unce-r
capital stock is less than the rate tainty, typically the variance of a
of depreciation, ie. gross invest- stochastic price or technological
ment is always positive. Moreover, variables, and of the actual levels
in the traditional approach, there of the latter variables, including the
1is no room for fexible timing in capital depreciation rate .
investment: Either the frms invest It follows that investment
pat(I>0) or they don’t, and in the lat- terns are potentially less smooth
ter case, it is implicitly assumed when one has to account for
irrethat the investment opportunity versibility under uncertainty. As
lost will never be recovered. Te in the models with non-convex
optimal investment rule giving adjustment costs seen above, there
the optimal capital stock is basi- is room for inaction: provided the
cally: Investment is undertaken if fexibility of the investment
deciand only if the (expected) margi- sion timing, the frms can decide
nal proftability of capital, MPK, is to not act for a while since there is
bigger than a user cost of capital, a value of waiting, which generates
which includes the interest rate (the the infrequency characteristic.
discounting rate), the depreciation What are the theoretical
implicarate of capital, and the (expected) tions of this approach as to
investrate of change of the acquisition ment patterns? As we have just said,
price of capital. Tis is exactly irreversibility plus uncertainty and
what may happen if the frm, ini- time fexibility implies that
equiptially at equilibrium, is afected by ment purchases occur only in
a positive technical innovation; the spurts. To be precise, investment
curve is likely to be shifed upward, occurs if the (expected) proftability
so that investment takes place. In of marginal investment is enough
Dixit-Pyndick’s models, the rule high to compensate the cost of
capiis not that simple. Tere is an op- tal and the value of waiting. Tis is
tion of waiting. Even if a technical likely to happen in very good times
innovation unambiguously shifs (for example, when the demand for
upward MPK, uncertainty,
irrever1. Te reader interested in the exact formula
sibility plus time fexibility may
inof the value of waiting can fnd the necessary 17duce the frm to wait, and not react material in Pindyck (1988).
Revue d’économie et de sciences socialesthe goods produced by the frms (demand and/or technological)
is very high using historical stan- shock should be of a very large
dards, as in Pindyck, 1988). But this magnitude. For moderate
negais unlikely to happen for any good tive shocks, full utilization (and
draw in the distribution of the zero investment) is optimal. Te
stochastic environment. Typically rate of capacity utilization plays
the frms increase their productive therefore a central role in shaping
capacity only periodically. Tese investment patterns when
irrevermodels usually have marginal in- sibility and uncertainty matters,
crement, and are unable to generate and this should be of interest for
lumpiness. practitioners seeking for the best
Tere is a much more important investment decision in such a
new direction in the irreversibility context. Typical wisdom from this
literature with respect to the tra- approach is that frms must reuse
ditional non-convex adjustment all the units, that’s increase their
costs models: Te role of the rate rate of capacity utilization if po-s
of utilization of capital. Allow the sible, before investing. Certainly,
frms to choose this rate in pre- this behavior is not always
corrosence of uncertainty, irreversibi- borated by the empirical evidence.
lity and time fexibility, and forget In certain cases, frms do invest
about capital depreciation. Te even if they have not reached full
typical outcome is the following. capacity, which goes at odds with
In good times, there is little doubt one of the main implications of the
that the optimal decision should 1988 Pindyck’s seminal work. Tis
be to fully utilize the productive kind of behavior is highlighted in
capacity. In very good times, as several micro-econometric
stuwe have just mentioned above, the dies (see for example Licandro et
frms additionally increase their al. (2005) on Spanish data among
capital stock. What happens in many other frm level studies).
bad times? Tis crucial question Cruz and Pommeret (2010) show
is addressed in Dixit and Pindyck that accounting for
investment(1994), and before by Pindyck specifc technological progress
(1988) in a basic formal setting. (via vintage capital modelling) is
In bad times, since investment enough to explain this striking
is irreversible and capital depre- fnding. Indeed, if investment is
ciation is assumed to be zero, the the exclusive vehicle of
technolocapital stock held does not move. gical innovations and if a decisive
Tis inertia in the capital stock technological upgrading is taking
is coupled with a non-constant place, the decision to invest (ofen
optimal utilization rate. An ad- coupled with replacement of old
verse shock need not reduce this and less productive equipment) is
rate systematically. For the rate likely to be less intimately related
18 of utilization to fall, the adverse to the rate of utilization control.
Bukavu Journal of Economics and Social Sciences (BJESS) numéro 3, 2016We shall insist on the necessity to the empirical failures of this
theoaccount for this feature of techn-o ry. Tat is the usual tests do not
logical progress (that’s embodi- consider the possible existence of a
ment) in Section III, especially in multiple regime (q,I) relationship.
connection with the ICT burst. Teir failure may come from this
Te q-theory is generally non- omission. While this claim is so
robust to extensions of the basic far unproven, as correctly pointed
model incorporating non-convex out by Chirinko (1996), it gives an
adjustment costs. When the early idea about the complexity
benchmark model is extended to of the empirical debate surroun -
include uncertainty, irreversibi- ding the concepts of
irreversibility and fexibility in timing, then lity, uncertainty and non-convex
this non-robustness is much less adjustment costs. Te next
subclear, as it is brilliantly explai- section addresses very briefy this
ned by Dixit and Pindyck in their issue, among others.
1book . True, there is no monotonic
relationship between q and invest- 2.3. Some remarks on the “new”
ment over the whole space of capi- investment theories
tal imbalance Z. But, in contrast Some crucial issues remain to be
to the model with non-convex ad- addressed. First of all, if it is widely
justment costs where non-mono- admitted that non-convex
adjusttonicity may show up locally in the ment costs and/or irreversibility
-space, the picture is simpler here: are much more consistent with
Te Z space is divided in three re- observed investment behavior at
gions where investment is respec- the plant level that the Jorgenson
tively rising, falling or constant neoclassical model, it is crucial to
with increases in q. In other terms, study whether aggregation will
there exist three distinct regimes not “kill” them. In other terms, it
but none shows up a non-mo- is important to assert neatly that
notonic relationship between q non-convex adjustment costs and/
and investment. Tis leads many or irreversibility have a frst-order
theorists, following Dixit and impact in explaining aggregate
Pindyck, to argue that accounting investment patterns. Second, it is
for irreversibility and uncertainty important to examine if these new
does not only preserve the basic q- theories are not leaving in the dark,
theory but it also allows to remedy some crucial aspects of the
investment decision; we shall argue in
1. The reader can find a complete proof of this respect that embodied
techthese claims in the quoted book. These
pronical progress, and more generally perties are mathematically quite intuitive:
The presence of a fixed cost has a much the vintage composition of the
camore damaging effect on the concavity of pital stock, are important but still
the value functions of the firms, arising
insufciently dealt with in these
in the considered dynamic programming 19new theories.problems.
Revue d’économie et de sciences sociales1. With either non-convex ad- of frms exist in the sample (which
justment costs or irreversibility, is the case in the empirical
studthe investment patterns seem to ies conducted on US micro data),
be consistent with the empirical so that the law of large numbers
characteristics of micro adjust- prevails, one can frst take average
ment as documented by Doms and investment over the establishments
Dunne (1998), namely infrequency of the sample having
approximateand lumpiness. But as mentioned ly the same capital imbalance Z,
by Caballero (1999), the empiri- as an estimate of expected
investcal corroboration of these simple ment (conditional to the level of
adjustment rules is far from easy, imbalance). Ten, using the above
as”...frms respond diferently to mentioned simple expression of
exsimilar imbalances over time and pected investment in terms of the
across frms”. Tis leads Caballero hazard function, one can precisely
and Engel (1999) to construct a estimate the latter function. Te
stochastic version of the model second step simply requires
averawith non-convex adjustment costs, ging across all Z.
where the regions of inaction and 3. Te results obtained by
adjustment are not deterministi- Caballero, Engel and Haltiwanger
cally set, the basic idea being that (1995) (corroborated by further
large imbalances are more likely to empirical studies) seem to confrm
induce investment. A simple way to the importance of non-convexities
randomize the latter model is to as- and, incidentally of
irreversibisume that the fxed cost variable is lity, both at the micro and
aggrestochastic. Ten, the analysis relies gate levels. Te main result is that
on the so-called hazard functions, the hazard functions are clearly
H(Z), which describe the probabili- increasing consistently with the
ty to adjust when capital imbalance «new» investment theories
em(or any other convenient function phasizing the role of
non-conveof it) is equal to Z. xities and irreversibility. In
par2. In their celebrated 1999 pa- ticular, expected investment rises
per, Caballero and Engel provide more that proportionally with
the necessary material to estimate capital imbalance. Te linear
spethese hazard functions and more cifcations, consistent with the
traimportantly, to aggregate them. ditional formulations of the user
For a given imbalance Z, it is dem- cost and Tobin’s q-theories, rather
onstrated that the expected invest- predict constant hazard functions,
ment by any frm can be written as ie. the probability to adjust is the
basically the product of the adjust- same whatever is the level of
capiment to be done and the probability tal imbalance. Te same
conclufor the frm to undertake it (namely sion is made at the aggregate level.
H(Z)). Ten aggregation follows in Moreover, the estimated hazard
20 two steps. Provided a large number functions are shown to be very low
Bukavu Journal of Economics and Social Sciences (BJESS) numéro 3, 2016