Equilibrium in a reinsurance market: Introducing taxes

We introduce profit taxation in Borch's [1962] model of a competitive insurance market. We analyze the impact of taxation on equilibrium prices and characterize the cases where optimal risk sharing is preserved. In the case of Constant Relative Risk Aversion (CRRA) utility functions, this abstract characterization is translated into simple conditions involving the solvency ratios of the companies. The case of Constant Absolute Risk Aversion (CARA) utility functions is also studied.     

The decentralization of credit: A selected summary of the Mayoux report

The Mayoux Report is the official report of a Committee of Inquiry headed by Jacques Mayoux that examined problems of the local and regional financial opportunities of small and medium-sized firms. This note, written by two of the aides to Mr. Mayoux in the preparation of the report, provides a summary of the major findings and suggestions of the Committee regarding banking reform. The principal recommendations include the simplification and decentralization of the granting of credit in France and continued steps toward the balancing of the rules and conditions governing lending and deposit collection among the various French financial institutions. It appeared to the Committee that the compartmentalization of French financial institutions due to the special rules under which specific institutions are permitted to operate was the major obstacle preventing better distributions of credit in France.     

Outcomes of voting and planning: Condorcet,Weber and Rawls locations

The paper is concerned with the comparison of the locations of a facility resulting from voting and planning procedures. It is shown that a voting location exists and coincides with that minimizing the total distance covered by the users to go to the facility when the transportation network contains no cycles. For a general network, least upper bounds on the ratio of the social values of the voting and planning locations are given in the cases where the total or the maximal travelled distance is minimized.     

关于现代地学研究方法的几点思考

现代地学研究方法在继承了古代和近代地学研究方法的精华并结合了当代科学和哲学的成果后发展起来。然而，受地球科学研究客体的特殊性、地球科学家认识的历史局限性以及社会整体发展的要求等方面的制约和影响，现代地学研究方法需要更新。尤其是在把地学对象的认识向其过程转变方面，在处理地学一手与二手资料所采用的辩证态度方面以及在经验和理论的关系、摆正或处理好现代新型人──地关系等方面需要新的观点和做法。     

Wage and competition channels of foreign direct investment and new firm entry

Using a rich data set of the Dutch manufacturing sector between 1995 and 2010, we investigate the effect of foreign direct investment (FDI) on domestic new firm entry. The emerging empirical literature has focused on the direct relationship between FDI and entry, but has not explored the mechanisms behind the observed effect. Drawing on a simultaneous equations model, our analysis features both the direct effect of FDI as well as indirect effects through two channels: industry competition and wages. We estimate the parameters through 3SLS and take into account the endogeneity of competition and wages with respect to entry. Our results show that there is a significant negative direct effect of FDI on entry. At the same time, FDI decreases competition and increases wage levels, which then impact entry positively and negatively, respectively. The total effect of FDI is negative, but small and virtually disappears after one year. Policy implications are discussed.

     

Bayesian Inference in Spatial Sample Selection Models

In this study, we consider Bayesian methods for the estimation of a sample selection model with spatially correlated disturbance terms. We design a set of Markov chain Monte Carlo algorithms based on the method of data augmentation. The natural parameterization for the covariance structure of our model involves an unidentified parameter that complicates posterior analysis. The unidentified parameter – the variance of the disturbance term in the selection equation – is handled in different ways in these algorithms to achieve identification for other parameters. The Bayesian estimator based on these algorithms can account for the selection bias and the full covariance structure implied by the spatial correlation. We illustrate the implementation of these algorithms through a simulation study and an empirical application.     

Heteroskedasticity-consistent covariance matrix estimators for spatial autoregressive models

In the presence of heteroskedasticity, conventional test statistics based on the ordinary least squares (OLS) estimator lead to incorrect inference results for the linear regression model. Given that heteroskedasticity is common in cross-sectional data, the test statistics based on various forms of heteroskedasticity-consistent covariance matrices (HCCMs) have been developed in the literature. In contrast to the standard linear regression model, heteroskedasticity is a more serious problem for spatial econometric models, generally causing inconsistent extremum estimators of model coefficients. This paper investigates the finite sample properties of the heteroskedasticity-robust generalized method of moments estimator (RGMME) for a spatial econometric model with an unknown form of heteroskedasticity. In particular, it develops various HCCM-type corrections to improve the finite sample properties of the RGMME and the conventional Wald test. The Monte Carlo results indicate that the HCCM-type corrections can produce more accurate results for inference on model parameters and the impact effects estimates in small samples.