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- Boucekkine
Boucekkine
Raouf Boucekkine
Faculty
,
Aix-Marseille Université
,
Faculté d'économie et de gestion (FEG)
Status
Professor
Research fields
Development economics
Macroeconomics
Thesis
1993
,
Université Paris I Panthéon-Sorbonne
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Contact
raouf.boucekkine[at]univ-amu.fr
Address
Îlot Bernard du Bois
Publications
We investigate the link between resource revenues volatility and institutions. We build a stochastic differential game with two players (conservatives vs. liberals) lobbying for changing the institutions in their preferred directions. First, uncertainty surrounds the dynamics of institutions and the resource revenues. Second, the lobbying power is asymmetric, the conservatives’ power being increasing with resource revenues. We show the existence of a unique equilibrium in the set of affine strategies. We then examine to which extent uncertainty leads to more liberal institutions in the long run, compared to the deterministic case. We finally explore the institutional impact of volatility using a database covering 91 countries over the period 1973–2005. Focusing on financial liberalization, we find that as oil revenue volatility increases, liberalization goes down. This result is robust to different specifications and sample distinctions.
In this paper, we tackle a generic optimal regime switching problem where the decision-making process is not the same from one regime to another. Precisely, we consider a simple model of optimal switching from competition to cooperation. To this end, we solve a two-stage optimal control problem. In the first stage, two players engage in a dynamic game with a common state variable and one control for each player. We solve for open-loop strategies with a linear state equation and linear-quadratic payoffs. More importantly, the players may also consider the possibility to switch at finite time to a cooperative regime with the associated joint optimization of the sum of the individual payoffs. Using theoretical analysis and numerical exercises, we study the optimal switching strategy from competition to cooperation. We also discuss reverse switching.
Does drawing economic benefit from nature impinge on conservation? This has been a subject of controversy in the literature. The article presents a management method to overcome this possible dilemma, and reconcile conservation biology with economics. It is based on recent advances in the mathematical theory of dynamic systems under viability constraints. In the case of a one-locus two-allele plant coexisting with a one-locus two-allele parasite, the method provides a rule for deciding when and to what extent the resistant or the susceptible strain should be cultivated, in the uncertain time-varying presence of the parasite. This is useful for preventing the fixation of the susceptible allele - and thereby limiting the plant's vulnerability in the medium term, should the parasite reappear. The method thus provides an aid to decision for economic and ecology-friendly profitability.
We consider an autocracy where the ruling elite control both the resource wealth and education policies. Education prompts economic growth and enriches the budget of the elite. However, education also increases the “awareness of citizens” – capturing their reluctance to accept a dictatorship and their labor market aspirations – and forces the elite to expand redistribution or handover the power. A power handover leads to a more democratic regime, where the elite retains (at least partially) its economic power. This trade-off is the backbone of our Lipsetian theory of voluntary power handover. This theory provides new insights on the positive relationship between economic development, education, and democratization, and on the negative relationship between inequality and democratization. Finally, we revisit the resources-curse hypothesis within our setting.
We provide an optimal growth spatio-temporal setting with capital accumulation and diffusion across space to study the link between economic growth triggered by capital spatio-temporal dynamics and agglomeration across space. The technology is AK, K being broad capital. The social welfare function is Benthamite. In sharp contrast to the related literature, which considers homogeneous space, we derive optimal location outcomes for any given space distributions for technology and population. Both the transitional spatio-temporal dynamics and the asymptotic spatial distributions are computed in closed form. Concerning the latter, we find, among other results, that: (i) due to inequality aversion, the consumption per capital distribution is much flatter than the distribution of capital per capita; (ii) endogenous spillovers inherent in capital spatio-temporal dynamics occur as capital distribution is much less concentrated than the (pre-specified) technological distribution; (iii) the distance to the center (or to the core) is an essential determinant of the shapes of the asymptotic distributions, that is relative location matters.
The pure risk sharing mechanism implies that financial liberalization is growth enhancing for all countries as the world portfolio shifts from safe low-yield capital to riskier high-yield capital. This result is typically obtained under the assumption that the volatilities for risky assets prevailing under autarky are not altered after liberalization. We relax this assumption within a simple two-country model of intertemporal portfolio choices. By doing so, we put together the risk sharing effect and a well-defined instability effect. We identify the conditions under which liberalization may cause a drop in growth. These conditions combine the typical threshold conditions outlined in the literature, which concern the deep characteristics of the economies, and size conditions on the instability effect induced by liberalization.
We solve a linear-quadratic model of a spatio-temporal economy using a polluting one-input technology. Space is continuous and heterogenous: locations differ in productivity, nature self-cleaning technology and environmental awareness. The unique link between locations is transboundary pollution which is modelled as a PDE diffusion equation. The spatio-temporal functional is quadratic in local consumption and linear in pollution. Using a dynamic programming method adapted to our infinite dimensional setting, we solve the associated optimal control problem in closed-form and identify the asymptotic (optimal) spatial distribution of pollution. We show that optimal emissions will decrease at given location if and only if local productivity is larger than a threshold which depends both on the local pollution absorption capacity and environmental awareness. Furthermore, we numerically explore the relationship between the spatial optimal distributions of production and (asymptotic) pollution in order to uncover possible (geographic) environmental Kuznets curve cases.
