The fertility transition around the world

In this paper, we study the evolution of the distribution of fertility rates across the world from 1950 to 2005 using parametric mixture models. We demonstrate the existence of twin peaks and the division of the world’s countries in two distinct components: a high-fertility regime and a low-fertility regime. Whereas the significance of twin peaks vanishes over time, the two fertility regimes continue to exists over the whole observation period. In 1950, about two thirds of the world’s countries belonged to the high-fertility regime and the rest constituted the low-fertility regime. By the year 2005, this picture has reversed. Within both the low- and the high-fertility regime, the average fertility rate declined, with a larger absolute decline within the high-fertility regime. Visually, the two peaks moved closer together. For the low-fertility regime, we find both β- and σ -convergence but we cannot establish any convergence pattern for the high-fertility regime. Our results support the idea of conditional convergence where the condition is the successful initiation of the fertility transition. The results are less supportive of the existence of a unique high-fertility equilibrium.     

Making sense of conflicting empirical findings: A meta-analytic review of the relationship between corporate environmental and financial performance

Despite the tremendous number of publications concerned with the relationship between corporate environmental performance (CEP) and corporate financial performance (CFP), inconsistent empirical findings persist and the overall picture remains vague. Drawing on a hybrid theoretical framework (combining the theoretical reasoning of the natural-resource-based view (NRBV) with instrumental stakeholder and slack resources arguments), we address the apparent lack of consensus by meta-analytically integrating the findings of 149 studies. We pay particular attention to two highly material issues: the direction of causality and the multidimensionality of the focal constructs. Meta-analytic results indicate that there is a positive and partially bidirectional relationship between CEP and CFP. In addition, our findings suggest that the relationship is stronger when the strategic approach underlying CEP is proactive rather than reactive. Furthermore, we reveal moderation effects of methodological artifacts, which may provide explanations for the inconsistency of the results of previous studies. Based on our findings, we discuss the implications and outline avenues for further research.     

Abstracts

Ohne Zusammenfassung

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Abstracts

     

On Smooth Statistical Tail Functionals

Many estimators of the extreme value index of a distribution function F that are based on a certain number k _n of largest order statistics can be represented as a statistical tail function al, that is a functional T applied to the empirical tail quantile function Q _n. We study the asymptotic behaviour of such estimators with a scale and location invariant functional T under weak second order conditions on F . For that purpose first a new approximation of the empirical tail quantile function is established. As a consequence we obtain weak consistency and asymptotic normality of T ( Q _n) if T is continuous and Hadamard differentiable, respectively, at the upper quantile function of a generalized Pareto distribution and k _pn tends to infinity sufficiently slowly. Then we investigate the asymptotic variance and bias. In particular, those functionals T re characterized that lead to an estimator with minimal asymptotic variance. Finally, we introduce a method to construct estimators of the extreme value index with a made-to-order asymptotic behaviour     

Optimal designs for estimating the slope of a regression

In the common linear model with quantitative predictors we consider the problem of designing experiments for estimating the slope of the expected response in a regression. We discuss locally optimal designs, where the experimenter is only interested in the slope at a particular point, and standardized minimax optimal designs, which could be used if precise estimation of the slope over a given region is required. General results on the number of support points of locally optimal designs are derived if the regression functions form a Chebyshev system. For polynomial regression and Fourier regression models of arbitrary degree the optimal designs for estimating the slope of the regression are determined explicitly for many cases of practical interest.     

Success Factors of New Product Development: A Review of the Empirical Literature

The continuous development and market introduction of new products can be an important determinant of sustained company performance. For approximately 30 years, conceptual and empirical research has been undertaken to identify the critical success factors of new products. This paper reviews the findings of empirical work into the success factors of new product development (NPD). It is the prime objective of this work to summarize the most important findings in a compact and structured way. In addition, shortcomings of previous empirical work on NPD success factors will be discussed and suggestions for improvement in future empirical NPD studies will be made.     

Adaptive grid semidefinite programming for finding optimal designs

We find optimal designs for linear models using a novel algorithm that iteratively combines a semidefinite programming (SDP) approach with adaptive grid techniques. The proposed algorithm is also adapted to find locally optimal designs for nonlinear models. The search space is first discretized, and SDP is applied to find the optimal design based on the initial grid. The points in the next grid set are points that maximize the dispersion function of the SDP-generated optimal design using nonlinear programming. The procedure is repeated until a user-specified stopping rule is reached. The proposed algorithm is broadly applicable, and we demonstrate its flexibility using (i) models with one or more variables and (ii) differentiable design criteria, such as A-, D-optimality, and non-differentiable criterion like E-optimality, including the mathematically more challenging case when the minimum eigenvalue of the information matrix of the optimal design has geometric multiplicity larger than 1. Our algorithm is computationally efficient because it is based on mathematical programming tools and so optimality is assured at each stage; it also exploits the convexity of the problems whenever possible. Using several linear and nonlinear models with one or more factors, we show the proposed algorithm can efficiently find optimal designs.     

Interjurisdictional Sorting and Majority Rule: An Empirical Analysis

The goal of this paper is to provide a comprehensive empirical analysis of majority rule and Tiebout sorting within a system of local jurisdictions. The idea behind the estimation procedure is to investigate whether observed levels of public expenditures satisfy necessary conditions implied by majority rule in a general equilibrium model of residential choice. The estimator controls for observed and unobserved heterogeneity among households, observed and unobserved characteristics of communities, and the potential endogeneity of prices and expenditures, as well as the self‐selection of households into communities of their choice. We estimate the structural parameters of the model using data from the Boston Metropolitan Area. The empirical findings reject myopic voting models. More sophisticated voting models based on utility‐taking provide a potential explanation of the main empirical regularities.     

Admission,Tuition, and Financial Aid Policies in the Market for Higher Education

We present an equilibrium model of the market for higher education. Our model simultaneously predicts student selection into institutions of higher education, financial aid, educational expenditures, and educational outcomes. We show that the model gives rise to a strict hierarchy of colleges that differ by the educational quality provided to the students. We also develop a new estimation procedure that exploits the observed variation in prices within colleges. Identification is based on variation in endowments and technology. It does not rely on observed variation in potentially endogenous characteristics of colleges such as peer quality measures and expenditures. We estimate the structural parameters using data collected by the National Center for Education Statistics and aggregate data from Peterson's and the National Science Foundation.