Religion and Economic Growth: Was Weber Right?

Evidence of falling wages in Catholic cities and rising wages in Protestant cities between 1500 and 1750, during the spread of literacy in the vernacular, is inconsistent with most theoretical models of economic growth. In The Protestant Ethic, Weber suggested an alternative explanation based on culture. Here, a theoretical model confirms that a small change in the subjective cost of cooperating with strangers can generate a profound transformation in trading networks. In explaining urban growth in early-modern Europe, specifications compatible with human-capital versions of the neoclassical model and endogenous-growth theory are rejected in favor of a “small-world” formulation based on the Weber thesis.

La finance islamique: fondements, theorie et realite.

L’Islam interdit le riba , mot arabe signifiant à la fois usure et intérêt. L’interdiction du rib figure dans la loi islamique, née dans l’Arabie du Moyen Âge. Elle est à la base de la finance islamique qui connut une expansion remarquable durant la deuxième moitié du XX e siècle. Nous nous interrogeons sur les origines de cette interdiction, sur les problèmes que connaît actuellement la finance islamique et sur ses perspectives d’avenir.

Semi-Parametric Weak Instrument Regressions with an Application to the Risk-Return Trade-off

Recent work shows that a low correlation between the instruments and the included variables leads to serious inference problems. We extend the local-to-zero analysis of models with weak instruments to models with estimated instruments and regressors and with higher-order dependence between instruments and disturbances. This makes this framework applicable to linear models with expectation variables that are estimated non-parametrically. Two examples of such models are the risk-return trade-off in finance and the impact of inflation uncertainty on real economic activity. Results show that inference based on Lagrange Multiplier (LM) tests is more robust to weak instruments than Wald-based inference. Using LM confidence intervals leads us to conclude that no statistically significant risk premium is present in returns on the S&P 500 index, excess holding yields between 6-month and 3-month Treasury bills, or in yen-dollar spot returns.

Simulation-Based Finite and Large Sample Tests in Multivariate Regressions.

In the context of multivariate linear regression (MLR) models, it is well known that commonly employed asymptotic test criteria are seriously biased towards overrejection. In this paper, we propose a general method for constructing exact tests of possibly nonlinear hypotheses on the coefficients of MLR systems. For the case of uniform linear hypotheses, we present exact distributional invariance results concerning several standard test criteria. These include Wilks' likelihood ratio (LR) criterion as well as trace and maximum root criteria. The normality assumption is not necessary for most of the results to hold. Implications for inference are two-fold. First, invariance to nuisance parameters entails that the technique of Monte Carlo tests can be applied on all these statistics to obtain exact tests of uniform linear hypotheses. Second, the invariance property of the latter statistic is exploited to derive general nuisance-parameter-free bounds on the distribution of the LR statistic for arbitrary hypotheses. Even though it may be difficult to compute these bounds analytically, they can easily be simulated, hence yielding exact bounds Monte Carlo tests. Illustrative simulation experiments show that the bounds are sufficiently tight to provide conclusive results with a high probability. Our findings illustrate the value of the bounds as a tool to be used in conjunction with more traditional simulation-based test methods (e.g., the parametric bootstrap) which may be applied when the bounds are not conclusive.

Exact Tests for Contemporaneous Correlation of Disturbances in Seemingly Unrelated Regressions.

This paper proposes finite-sample procedures for testing the SURE specification in multi-equation regression models, i.e. whether the disturbances in different equations are contemporaneously uncorrelated or not. We apply the technique of Monte Carlo (MC) tests [Dwass (1957), Barnard (1963)] to obtain exact tests based on standard LR and LM zero correlation tests. We also suggest a MC quasi-LR (QLR) test based on feasible generalized least squares (FGLS). We show that the latter statistics are pivotal under the null, which provides the justification for applying MC tests. Furthermore, we extend the exact independence test proposed by Harvey and Phillips (1982) to the multi-equation framework. Specifically, we introduce several induced tests based on a set of simultaneous Harvey/Phillips-type tests and suggest a simulation-based solution to the associated combination problem. The properties of the proposed tests are studied in a Monte Carlo experiment which shows that standard asymptotic tests exhibit important size distortions, while MC tests achieve complete size control and display good power. Moreover, MC-QLR tests performed best in terms of power, a result of interest from the point of view of simulation-based tests. The power of the MC induced tests improves appreciably in comparison to standard Bonferroni tests and, in certain cases, outperforms the likelihood-based MC tests. The tests are applied to data used by Fischer (1993) to analyze the macroeconomic determinants of growth.

Markovian Processes, Two-Sided Autoregressions and Finite-Sample Inference for Stationary and Nonstationary Autoregressive Processes.

In this paper, we develop finite-sample inference procedures for stationary and nonstationary autoregressive (AR) models. The method is based on special properties of Markov processes and a split-sample technique. The results on Markovian processes (intercalary independence and truncation) only require the existence of conditional densities. They are proved for possibly nonstationary and/or non-Gaussian multivariate Markov processes. In the context of a linear regression model with AR(1) errors, we show how these results can be used to simplify the distributional properties of the model by conditioning a subset of the data on the remaining observations. This transformation leads to a new model which has the form of a two-sided autoregression to which standard classical linear regression inference techniques can be applied. We show how to derive tests and confidence sets for the mean and/or autoregressive parameters of the model. We also develop a test on the order of an autoregression. We show that a combination of subsample-based inferences can improve the performance of the procedure. An application to U.S. domestic investment data illustrates the method.

The Bootstrap of Mean for Dependent Heterogeneous Arrays.

Presently, conditions ensuring the validity of bootstrap methods for the sample mean of (possibly heterogeneous) near epoch dependent (NED) functions of mixing processes are unknown. Here we establish the validity of the bootstrap in this context, extending the applicability of bootstrap methods to a class of processes broadly relevant for applications in economics and finance. Our results apply to two block bootstrap methods: the moving blocks bootstrap of Künsch ( 989) and Liu and Singh ( 992), and the stationary bootstrap of Politis and Romano ( 994). In particular, the consistency of the bootstrap variance estimator for the sample mean is shown to be robust against heteroskedasticity and dependence of unknown form. The first order asymptotic validity of the bootstrap approximation to the actual distribution of the sample mean is also established in this heterogeneous NED context.

Simulation-Based Finite-and Large-sample Inference Methods in Multivariate Regressions and Seemingly Unrelated Regressions

In the context of multivariate regression (MLR) and seemingly unrelated regressions (SURE) models, it is well known that commonly employed asymptotic test criteria are seriously biased towards overrejection. in this paper, we propose finite-and large-sample likelihood-based test procedures for possibly non-linear hypotheses on the coefficients of MLR and SURE systems.

What’s so Special About Cyberspace ? Reflections on Elkin-Koren And Salzberger

Un résumé en français est également disponible.

La composition au moyen des quarts de ton

La version intégrale de cette thèse est disponible uniquement pour consultation individuelle à la Bibliothèque de musique de l’Université de Montréal.

What’s so Special About Cyberspace Reflections on Elkin-Koren And Salzberger

Dans cet article, l’auteur Ejan Mackaay présente les caractéristiques fondamentales du cyberespace et analyse les relations économiques et juridiques entre les acteurs du marché virtuel de l’Internet. Cette analyse s'inscrit en marge des travaux de Niva Elkin-Koren et Eli Salzberger, dont elle suit le plan. D'une part, il y est précisé que le marché virtuel de l’Internet remet en question l’analyse classique des interactions entre les acteurs économiques. La nouvelle analyse néo-institutionnel présente un cadre analytique qui relève plus adéquatement les relations complexes entre les acteurs économiques du marché virtuel que les théories économiques classiques. Cette nouvelle approche se fonde sur le concept que les acteurs économiques utilisent les ressources afin d’être intégrés au sein des institutions les plus actives et efficaces. D'autre part, il est fait mention que le cyberespace présente plusieurs caractéristiques d’un marché économique. Toutefois, étant virtuel, le cyberespace ne présente pas les mêmes limites qu’un marché physique. En effet, dans ce dernier, certaines limites physiques imposent diverses règles de comportement. Le législateur doit donc prendre conscience de l’absence de telles limites et des normes qu’elles imposaient afin de légiférer adéquatement sur les échanges dans le cyberespace. Ensuite, afin d’illustrer les divergences entre les marchés physiques et virtuels, une analyse est faite au regard des principaux échecs de marchés, soit l’établissement d’un monopole, l’accès aux biens publics, les informations imparfaites et les externalités négatives. Un monopole est un échec de marché qui restreint considérablement la compétition, peut être accrut par l’effet boule de neige et, s’il n’est pas contrôlé, peut mener à un effet de blocage ou d’exclusion de certains acteurs. Le second échec analysé est l’accès aux biens publics. Dans le cyberespace, le principal bien public est l’information qui peut être échangée entre les utilisateurs. Toutefois, certaines règles de droits d’auteur et de propriété intellectuelle peuvent considérablement limiter l’accès à ce bien. L’information incomplète des acteurs économiques constitue un autre échec de marché, mais le cyberespace offre plusieurs moyens d’accéder à l’information pertinente aux transactions éclairées. Enfin, les externalités négatives peuvent généralement être considérées comme des effets secondaires des échanges commerciaux. Toutefois il est souligné que ces dernières ont un effet très limité dans le cyberespace, étant donné le plus grand nombre d’options de retrait et la facilité accrue de l’exercer. Enfin, il est rappelé que le commerce électronique et le cyberespace remettent en questions toutes les théories économiques et politiques traditionnelles et offrent une perspective nouvelle sur le phénomène de la formation des normes.