On the dynamic effects of fiscal policy

Dans le sillage de la récession mondiale de 2008-09, plusieurs questions ont été soulevées dans la littérature économique sur les effets à court et à long terme de la politique budgétaire sur l’activité économique par rapport à son signe, sa taille et sa durée. Ceux-ci ont des implications importantes pour mieux comprendre les canaux de transmission et l’efficacité des politiques budgétaires, avec la politique monétaire étant poursuivi, ainsi que pour leurs retombées économiques. Cette thèse fait partie de ce regain d’intérêt de la littérature d’examiner comment les changements dans la politique budgétaire affectent l’activité économique. Elle repose alors sur trois essais: les effets macroéconomiques des chocs de dépenses publiques et des recettes fiscales, les résultats macroéconomiques de l’interaction entre les politiques budgétaire et monétaire et le lien entre la politique budgétaire et la répartition des revenus. Le premier chapitre examine les effets des chocs de politique budgétaire (chocs de dépenses publiques et chocs de recettes fiscales) sur l’économie canadienne au cours de la période 1970-2010, en s’appuyant sur la méthode d’identification des restrictions de signe développée par Mountford et Uhlig [2009]. En réponse à la récession mondiale, les autorités fiscales dans les économies avancées, dont le Canada ont généralement mis en oeuvre une approche en deux phases pour la politique budgétaire. Tout d’abord, ils ont introduit des plans de relance sans précédent pour relancer leurs économies. Par exemple, les mesures de relance au Canada, introduites à travers le Plan d’action économique du Canada, ont été projetées à 3.2 pour cent du PIB dans le budget fédéral de 2009 tandis que l’ "American Recovery and Reinvestment Act"(ARRA) a été estimé à 7 pour cent du PIB. Par la suite, ils ont mis en place des plans d’ajustement en vue de réduire la dette publique et en assurer la soutenabilité à long terme. Dans ce contexte, évaluer les effets multiplicateurs de la politique budgétaire est important en vue d’informer sur l'efficacité de telles mesures dans la relance ou non de l'activité économique. Les résultats montrent que les multiplicateurs d'impôt varient entre 0.2 et 0.5, tandis que les multiplicateurs de dépenses varient entre 0.2 et 1.1. Les multiplicateurs des dépenses ont tendance à être plus grand que les multiplicateurs des recettes fiscales au cours des deux dernières décennies. Comme implications de politique économique, ces résultats tendent à suggérer que les ajustements budgétaires par le biais de grandes réductions de dépenses publiques pourraient être plus dommageable pour l'économie que des ajustements budgétaires par la hausse des impôts. Le deuxième chapitre, co-écrit avec Constant Lonkeng Ngouana, estime les effets multiplicateurs des dépenses publiques aux Etats-Unis en fonction du cycle de la politique monétaire. Les chocs de dépenses publiques sont identifiés comme étant des erreurs de prévision du taux de croissance des dépenses publiques à partir des données d'Enquêtes des prévisionnistes professionnels et des informations contenues dans le "Greenbook". L'état de la politique monétaire est déduite à partir de la déviation du taux des fonds fédéraux du taux cible de la Réserve Fédérale, en faisant recours à une fonction lisse de transition. L'application de la méthode des «projections locales» aux données trimestrielles américaines au cours de la période 1965-2012 suggère que les effets multiplicateurs des dépenses fédérales sont sensiblement plus élevées quand la politique monétaire est accommodante que lorsqu'elle ne l'est pas. Les résultats suggèrent aussi que les dépenses fédérales peuvent stimuler ou non la consommation privée, dépendamment du degré d’accommodation de la politique monétaire. Ce dernier résultat réconcilie ainsi, sur la base d’un cadre unifié des résultats autrement contradictoires à première vue dans la littérature. Ces résultats ont d'importantes implications de politique économique. Ils suggèrent globalement que la politique budgétaire est plus efficace lorsqu'on en a le plus besoin (par exemple, lorsque le taux de chômage est élevé), si elle est soutenue par la politique monétaire. Ils ont également des implications pour la normalisation des conditions monétaires dans les pays avancés: la sortie des politiques monétaires non-conventionnelles conduirait à des multiplicateurs de dépenses fédérales beaucoup plus faibles qu'autrement, même si le niveau de chômage restait élevé. Ceci renforce la nécessité d'une calibration prudente du calendrier de sortie des politiques monétaires non-conventionnelles. Le troisième chapitre examine l'impact des mesures d'expansion et de contraction budgétaire sur la distribution des revenus dans un panel de 18 pays d'Amérique latine au cours de la période 1990-2010, avec un accent sur les deniers 40 pour cent. Il explore alors comment ces mesures fiscales ainsi que leur composition affectent la croissance des revenus des dernier 40 pour cent, la croissance de leur part de revenu ainsi que la croissance économique. Les mesures d'expansion et de contraction budgétaire sont identifiées par des périodes au cours desquels il existe une variation significative du déficit primaire corrigé des variations conjoncturelles en pourcentage du PIB. Les résultats montrent qu'en moyenne l'expansion budgétaire par la hausse des dépenses publiques est plus favorable à la croissance des revenus des moins bien-nantis que celle par la baisse des impôts. Ce résultat est principalement soutenu par la hausse des dépenses gouvernementales de consommation courante, les transferts et subventions. En outre ces mesures d’expansion budgétaire sont favorables à la réduction des inégalités car elles permettent d'améliorer la part des revenus des moins bien-nantis tout en réduisant la part des revenus des mieux-nantis de la distribution des revenus. En outre ces mesures d’expansion budgétaire sont favorables à la réduction des inégalités car elles permettent d'améliorer la part des revenus des moins bien-nantis tout en réduisant la part des revenus des mieux-nantis de la distribution des revenus. Cependant, l'expansion budgétaire pourrait soit n'avoir aucun effet sur la croissance économique ou entraver cette dernière à travers la hausse des dépenses en capital. Les résultats relatifs à la contraction budgétaire sont quelque peu mitigés. Parfois, les mesures de contraction budgétaire sont associées à une baisse de la croissance des revenus des moins bien nantis et à une hausse des inégalités, parfois l'impact de ces mesures est non significatif. Par ailleurs, aucune des mesures n’affecte de manière significative la croissance du PIB. Comme implications de politique économique, les pays avec une certaine marge de manœuvre budgétaire pourraient entamer ou continuer à mettre en œuvre des programmes de "filets de sauvetage"--par exemple les programmes de transfert monétaire conditionnel--permettant aux segments vulnérables de la population de faire face à des chocs négatifs et aussi d'améliorer leur conditions de vie. Avec un potentiel de stimuler l'emploi peu qualifié, une relance budgétaire sage par les dépenses publique courantes pourrait également jouer un rôle important pour la réduction des inégalités. Aussi, pour éviter que les dépenses en capital freinent la croissance économique, les projets d'investissements publics efficients devraient être prioritaires dans le processus d'élaboration des politiques. Ce qui passe par la mise en œuvre des projets d'investissement avec une productivité plus élevée capable de générer la croissance économique nécessaire pour réduire les inégalités.

Dynamic cumulative residual Renyi’s entropy

Recently, cumulative residual entropy (CRE) has been found to be a new measure of information that parallels Shannon’s entropy (see Rao et al. [Cumulative residual entropy: A new measure of information, IEEE Trans. Inform. Theory. 50(6) (2004), pp. 1220–1228] and Asadi and Zohrevand [On the dynamic cumulative residual entropy, J. Stat. Plann. Inference 137 (2007), pp. 1931–1941]). Motivated by this finding, in this paper, we introduce a generalized measure of it, namely cumulative residual Renyi’s entropy, and study its properties.We also examine it in relation to some applied problems such as weighted and equilibrium models. Finally, we extend this measure into the bivariate set-up and prove certain characterizing relationships to identify different bivariate lifetime models

Information Exchange and Fusion in Dynamic and Heterogeneous Distributed Environments

Context awareness, dynamic reconfiguration at runtime and heterogeneity are key characteristics of future distributed systems, particularly in ubiquitous and mobile computing scenarios. The main contributions of this dissertation are theoretical as well as architectural concepts facilitating information exchange and fusion in heterogeneous and dynamic distributed environments. Our main focus is on bridging the heterogeneity issues and, at the same time, considering uncertain, imprecise and unreliable sensor information in information fusion and reasoning approaches. A domain ontology is used to establish a common vocabulary for the exchanged information. We thereby explicitly support different representations for the same kind of information and provide Inter-Representation Operations that convert between them. Special account is taken of the conversion of associated meta-data that express uncertainty and impreciseness. The Unscented Transformation, for example, is applied to propagate Gaussian normal distributions across highly non-linear Inter-Representation Operations. Uncertain sensor information is fused using the Dempster-Shafer Theory of Evidence as it allows explicit modelling of partial and complete ignorance. We also show how to incorporate the Dempster-Shafer Theory of Evidence into probabilistic reasoning schemes such as Hidden Markov Models in order to be able to consider the uncertainty of sensor information when deriving high-level information from low-level data. For all these concepts we provide architectural support as a guideline for developers of innovative information exchange and fusion infrastructures that are particularly targeted at heterogeneous dynamic environments. Two case studies serve as proof of concept. The first case study focuses on heterogeneous autonomous robots that have to spontaneously form a cooperative team in order to achieve a common goal. The second case study is concerned with an approach for user activity recognition which serves as baseline for a context-aware adaptive application. Both case studies demonstrate the viability and strengths of the proposed solution and emphasize that the Dempster-Shafer Theory of Evidence should be preferred to pure probability theory in applications involving non-linear Inter-Representation Operations.

Decision‐Making in Public Good Dilemmas: Theory and Agent‐Based Simulation

In many real world contexts individuals find themselves in situations where they have to decide between options of behaviour that serve a collective purpose or behaviours which satisfy one’s private interests, ignoring the collective. In some cases the underlying social dilemma (Dawes, 1980) is solved and we observe collective action (Olson, 1965). In others social mobilisation is unsuccessful. The central topic of social dilemma research is the identification and understanding of mechanisms which yield to the observed cooperation and therefore resolve the social dilemma. It is the purpose of this thesis to contribute this research field for the case of public good dilemmas. To do so, existing work that is relevant to this problem domain is reviewed and a set of mandatory requirements is derived which guide theory and method development of the thesis. In particular, the thesis focusses on dynamic processes of social mobilisation which can foster or inhibit collective action. The basic understanding is that success or failure of the required process of social mobilisation is determined by heterogeneous individual preferences of the members of a providing group, the social structure in which the acting individuals are contained, and the embedding of the individuals in economic, political, biophysical, or other external contexts. To account for these aspects and for the involved dynamics the methodical approach of the thesis is computer simulation, in particular agent-based modelling and simulation of social systems. Particularly conductive are agent models which ground the simulation of human behaviour in suitable psychological theories of action. The thesis develops the action theory HAPPenInGS (Heterogeneous Agents Providing Public Goods) and demonstrates its embedding into different agent-based simulations. The thesis substantiates the particular added value of the methodical approach: Starting out from a theory of individual behaviour, in simulations the emergence of collective patterns of behaviour becomes observable. In addition, the underlying collective dynamics may be scrutinised and assessed by scenario analysis. The results of such experiments reveal insights on processes of social mobilisation which go beyond classical empirical approaches and yield policy recommendations on promising intervention measures in particular.

On the Convergence of Stochastic Iterative Dynamic Programming Algorithms

Recent developments in the area of reinforcement learning have yielded a number of new algorithms for the prediction and control of Markovian environments. These algorithms, including the TD(lambda) algorithm of Sutton (1988) and the Q-learning algorithm of Watkins (1989), can be motivated heuristically as approximations to dynamic programming (DP). In this paper we provide a rigorous proof of convergence of these DP-based learning algorithms by relating them to the powerful techniques of stochastic approximation theory via a new convergence theorem. The theorem establishes a general class of convergent algorithms to which both TD(lambda) and Q-learning belong.

Soft budget constraints in a dynamic general equilibrium model

This paper considers an overlapping generations model in which capital investment is financed in a credit market with adverse selection. Lenders’ inability to commit ex-ante not to bailout ex-post, together with a wealthy position of entrepreneurs gives rise to the soft budget constraint syndrome, i.e. the absence of liquidation of poor performing firms on a regular basis. This problem arises endogenously as a result of the interaction between the economic behavior of agents, without relying on political economy explanations. We found the problem more binding along the business cycle, providing an explanation to creditors leniency during booms in some LatinAmerican countries in the late seventies and early nineties.

Variational calculation of static and dynamic vibrational nonlinear optical properties

The vibrational configuration interaction method used to obtain static vibrational (hyper)polarizabilities is extended to dynamic nonlinear optical properties in the infinite optical frequency approximation. Illustrative calculations are carried out on H2 O and N H3. The former molecule is weakly anharmonic while the latter contains a strongly anharmonic umbrella mode. The effect on vibrational (hyper)polarizabilities due to various truncations of the potential energy and property surfaces involved in the calculation are examined

Electronic couplings and on-site energies for hole transfer in DNA: systematic quantum mechanical/molecular dynamic study

The electron hole transfer (HT) properties of DNA are substantially affected by thermal fluctuations of the π stack structure. Depending on the mutual position of neighboring nucleobases, electronic coupling V may change by several orders of magnitude. In the present paper, we report the results of systematic QM/molecular dynamic (MD) calculations of the electronic couplings and on-site energies for the hole transfer. Based on 15 ns MD trajectories for several DNA oligomers, we calculate the average coupling squares 〈 V2 〉 and the energies of basepair triplets X G+ Y and X A+ Y, where X, Y=G, A, T, and C. For each of the 32 systems, 15 000 conformations separated by 1 ps are considered. The three-state generalized Mulliken-Hush method is used to derive electronic couplings for HT between neighboring basepairs. The adiabatic energies and dipole moment matrix elements are computed within the INDO/S method. We compare the rms values of V with the couplings estimated for the idealized B -DNA structure and show that in several important cases the couplings calculated for the idealized B -DNA structure are considerably underestimated. The rms values for intrastrand couplings G-G, A-A, G-A, and A-G are found to be similar, ∼0.07 eV, while the interstrand couplings are quite different. The energies of hole states G+ and A+ in the stack depend on the nature of the neighboring pairs. The X G+ Y are by 0.5 eV more stable than X A+ Y. The thermal fluctuations of the DNA structure facilitate the HT process from guanine to adenine. The tabulated couplings and on-site energies can be used as reference parameters in theoretical and computational studies of HT processes in DNA

The effect of flow field & geometry on the dynamic contact angle

A number of recent experiments suggest that, at a given wetting speed, the dynamic contact angle formed by an advancing liquid-gas interface with a solid substrate depends on the flow field and geometry near the moving contact line. In the present work, this effect is investigated in the framework of an earlier developed theory that was based on the fact that dynamic wetting is, by its very name, a process of formation of a new liquid-solid interface (newly “wetted” solid surface) and hence should be considered not as a singular problem but as a particular case from a general class of flows with forming or/and disappearing interfaces. The results demonstrate that, in the flow configuration of curtain coating, where a liquid sheet (“curtain”) impinges onto a moving solid substrate, the actual dynamic contact angle indeed depends not only on the wetting speed and material constants of the contacting media, as in the so-called slip models, but also on the inlet velocity of the curtain, its height, and the angle between the falling curtain and the solid surface. In other words, for the same wetting speed the dynamic contact angle can be varied by manipulating the flow field and geometry near the moving contact line. The obtained results have important experimental implications: given that the dynamic contact angle is determined by the values of the surface tensions at the contact line and hence depends on the distributions of the surface parameters along the interfaces, which can be influenced by the flow field, one can use the overall flow conditions and the contact angle as a macroscopic multiparametric signal-response pair that probes the dynamics of the liquid-solid interface. This approach would allow one to investigate experimentally such properties of the interface as, for example, its equation of state and the rheological properties involved in the interface’s response to an external torque, and would help to measure its parameters, such as the coefficient of sliding friction, the surface-tension relaxation time, and so on.

Dynamic scaling of bred vectors in spatially extended chaotic systems

We unfold a profound relationship between the dynamics of finite-size perturbations in spatially extended chaotic systems and the universality class of Kardar-Parisi-Zhang (KPZ). We show how this relationship can be exploited to obtain a complete theoretical description of the bred vectors dynamics. The existence of characteristic length/time scales, the spatial extent of spatial correlations and how to time it, and the role of the breeding amplitude are all analyzed in the light of our theory. Implications to weather forecasting based on ensembles of initial conditions are also discussed.

A perspective on chaos theory: Potential applications to intelligent buildings

Mathematical models have been vitally important in the development of technologies in building engineering. A literature review identifies that linear models are the most widely used building simulation models. The advent of intelligent buildings has added new challenges in the application of the existing models as an intelligent building requires learning and self-adjusting capabilities based on environmental and occupants' factors. It is therefore argued that the linearity is an impropriate basis for any model of either complex building systems or occupant behaviours for control or whatever purpose. Chaos and complexity theory reflects nonlinear dynamic properties of the intelligent systems excised by occupants and environment and has been used widely in modelling various engineering, natural and social systems. It is proposed that chaos and complexity theory be applied to study intelligent buildings. This paper gives a brief description of chaos and complexity theory and presents its current positioning, recent developments in building engineering research and future potential applications to intelligent building studies, which provides a bridge between chaos and complexity theory and intelligent building research.

Inverse problems in dynamic cognitive modeling

Inverse problems for dynamical system models of cognitive processes comprise the determination of synaptic weight matrices or kernel functions for neural networks or neural/dynamic field models, respectively. We introduce dynamic cognitive modeling as a three tier top-down approach where cognitive processes are first described as algorithms that operate on complex symbolic data structures. Second, symbolic expressions and operations are represented by states and transformations in abstract vector spaces. Third, prescribed trajectories through representation space are implemented in neurodynamical systems. We discuss the Amari equation for a neural/dynamic field theory as a special case and show that the kernel construction problem is particularly ill-posed. We suggest a Tikhonov-Hebbian learning method as regularization technique and demonstrate its validity and robustness for basic examples of cognitive computations.

An Efficient Parameterization of Dynamic Neural Networks for Nonlinear System Identification

Dynamic neural networks (DNNs), which are also known as recurrent neural networks, are often used for nonlinear system identification. The main contribution of this letter is the introduction of an efficient parameterization of a class of DNNs. Having to adjust less parameters simplifies the training problem and leads to more parsimonious models. The parameterization is based on approximation theory dealing with the ability of a class of DNNs to approximate finite trajectories of nonautonomous systems. The use of the proposed parameterization is illustrated through a numerical example, using data from a nonlinear model of a magnetic levitation system.

Flow-induced dynamic surface tension effects at nanoscale

The aim of this study is to investigate flow-induced dynamic surface tension effects, similar to the well-known Marangoni phenomena, but solely generated by the nanoscale topography of the substrates. The flow-induced surface tension effects are examined on the basis of a sharp interface theory. It is demonstrated how nanoscale objects placed at the boundary of the flow domain result in the generation of substantial surface forces acting on the bulk flow.

Dynamic recurrent neural network for system identification and control

A dynamic recurrent neural network (DRNN) that can be viewed as a generalisation of the Hopfield neural network is proposed to identify and control a class of control affine systems. In this approach, the identified network is used in the context of the differential geometric control to synthesise a state feedback that cancels the nonlinear terms of the plant yielding a linear plant which can then be controlled using a standard PID controller.