Geography,demography, and economic growth in Africa

This paper presents the effects of climate, topography, and natural ecology on public health, nutrition, demographics, technological diffusion, international trade and other determinants of economic development in Africa. The goal of this paper is to emphasize the need for intensified research on the issues at the intersection of ecology and human society. Geography was given emphasis because of three reasons: the minimal gain from another recitation of the damage caused by statism, protectionism and corruption to African economic performance; negligence of the role of natural forces in shaping economic performance; and tailoring of policies to geographical realities. The paper also discusses the general problems of tropical development and the focus of Africa's problems in worldwide tropical perspectives; demographic trends in Africa; use of standard cross-country growth equations with demographic and geographic variables, to account for the relative roles of geography; and the future growth strategies and the need for urban-based export growth in manufacturing and services. Lastly, the authors provide a summary of conclusions and discuss the agenda for future research.     

Adjoint-based Monte Carlo calibration of financial market models

Adjoint methods have recently gained considerable importance in the finance sector, because they allow to quickly compute option sensitivities with respect to a large number of model parameters. In this paper we investigate how the efficiency of adjoint methods can be exploited to speed up the Monte Carlo-based calibration of financial market models. After analyzing the calibration problem both theoretically and numerically, we derive the associated adjoint equation and propose its application in combination with a multi-layer method, for which we prove convergence to a stationary point of the underlying optimization problem. Detailed numerical examples illustrate the performance of the method. In particular, the proposed algorithm reduces the calibration time for a typical equity market model with time-dependent model parameters from over three hours to less than ten minutes on a usual desktop PC.      

Twentieth-century political economy: a brief history of global capitalism

Modern capitalism emerged in the early nineteenth century inwestern Europe and the European offshoots of the Americas andOceania. Recognizing the unparalleled dynamism of the new socio-economicsystem, Marx and Engels predicted in 1848 that capitalism wouldspread to the entire world. By the end of the twentieth century,that prediction was confirmed: capitalism had indeed becomeglobal, but only after a tortuous and violent course of institutionalchange in many parts of the world. This paper provides a briefaccount of the emergence of global capitalism, and discussessome of the reasons why the diffusion of capitalism has beenso conflictual and violently contested.     

An Inframarginal Analysis of the Ricardian Model

This paper shows that a 2 × 2 Ricardian model has a unique general equilibrium, and the comparative statics of the equilibrium involve discontinuous jumps. If partial division of labor occurs in equilibrium, the country producing both goods would impose a tariff, whereas the country producing a single good would prefer unilateral free trade. If complete division of labor occurs in equilibrium, both countries would negotiate to achieve free trade. In a model with three countries, the country which does not have a comparative advantage relative to the other two countries, and/or which has low transaction efficiency, may be excluded from trade.     

Fitting dynamic factor models to non-stationary time series

Factor modelling of a large time series panel has widely proven useful to reduce its cross-sectional dimensionality. This is done by explaining common co-movements in the panel through the existence of a small number of common components, up to some idiosyncratic behaviour of each individual series. To capture serial correlation in the common components, a dynamic structure is used as in traditional (uni- or multivariate) time series analysis of second order structure, i.e. allowing for infinite-length filtering of the factors via dynamic loadings. In this paper, motivated from economic data observed over long time periods which show smooth transitions over time in their covariance structure, we allow the dynamic structure of the factor model to be non-stationary over time by proposing a deterministic time variation of its loadings. In this respect we generalize the existing recent work on static factor models with time-varying loadings as well as the classical, i.e. stationary, dynamic approximate factor model. Motivated from the stationary case, we estimate the common components of our dynamic factor model by the eigenvectors of a consistent estimator of the now time-varying spectral density matrix of the underlying data-generating process. This can be seen as a time-varying principal components approach in the frequency domain. We derive consistency of this estimator in a “double-asymptotic” framework of both cross-section and time dimension tending to infinity. The performance of the estimators is illustrated by a simulation study and an application to a macroeconomic data set.     

趋同的时代

对于任何一个经济学家来说,想对今后5年的状况做一个准确预测往往是非常困难的,所以今天我只想对50年后的世界经济状况谈些自己的想法.     

Measures of risk associated to regulations compliance: a laboratory experiment on the use of common-pool resources

The present research examined the influence of different risk perspectives by the use of four different target persons (who could be affected: abstract person, self, specific person, and specific others) and of four different questionnaire answer formats (rating, open percentage, open, and closed frequency) on risk assessments. It was assumed that subjects use two different systems in terms of probabilistic reasoning: a distributional approach for abstract targets leading to higher risk estimates and a singular approach for specific targets leading to lower risk assessments. According to unrealistic optimism (UO) research (showing higher risk assessments for an abstract person than for self), the assumption was that risk assessments for a specific (named) target lead to lower risk assessments compared to an abstract target. Further, common quantitative answer formats for assessing risk were compared to explore differences in risk estimates. The hypotheses were tested using data of a sample of 512 students from a Bavarian university. The frequently confirmed finding of UO could be replicated with both rating scale and open frequency scale, which appeared to be more sensitive compared to the other used scales. However, UO disappeared when the comparison target was specific. Further, risk assessments for an abstract target were highest within every answer format and lowest for specific targets. Furthermore, results revealed that the type of answer format has a moderating effect on the extent of the influence of risk perspective on risk assessments. Overall, this study gives evidence that both the chosen scale and the risk perspective strongly influence risk assessments. Results aim to contribute to the research fields of quantitative assessment of perceived risk. They suggest that probabilistic reasoning in regard to risk not only underlies motivational or cognitive ego-defensive mechanisms but is rather presumably caused by the use of different systems of inferential strategies.