WHICH AGGLOMERATION EXTERNALITIES MATTER MOST AND WHY?

This paper revisits the ongoing discussion on the importance of agglomeration externalities – specifically specialization, diversity and competition effects – that may contribute to innovation, productivity and urban employment growth. Previous meta‐analyses suggested that the evidence on agglomeration externalities is strongly context‐specific. Expanding an earlier analysis of 31 articles, we seek to draw in this paper more robust conclusions by means of the statistical evidence for agglomeration externalities presented in 73 scientific articles, all building on the seminal work of Glaeser et al. (1992). Our results confirm that the heterogeneity among studies is huge and can only be partially accounted for by means of an ordered probit analysis. Additionally, some evidence of publication bias is found. We conclude that the conventional lines of inquiry in this literature may now have reached strongly diminishing returns. New lines of inquiry, using rich micro‐level data on firms and workers, dynamic general equilibrium models at the macro level, more attention for spatial and temporal variation in the impacts of agglomeration, and further investigations into the spatial scope of externalities are promising avenues for further research that can enhance our understanding of how agglomeration externalities continue to fuel our increasingly urbanized world.     

AGGLOMERATION ECONOMIES IN JAPAN: TECHNICAL EFFICIENCY, GROWTH AND UNEMPLOYMENT

This paper examines if the effects of agglomeration economies are manifested in technical efficiency and generate faster economic growth and higher (lower) levels of employment (unemployment). Using the prefecture level data for each of the two-digit groups of industries in Japan, it estimates a region-specific technical efficiency index based on the stochastic frontier production function framework. The factor analysis shows that in most of the industry-groups, efficiency has a positive association with external scale variable(s). Though the relationship is not very strong, it would be erroneous to ignore the effect of agglomeration economies on efficiency. For some light goods industries, the agglomeration effect is relatively stronger. Economic growth varies positively with external scale variable(s) and the unemployment rate tends to fall with respect to growth and concentration. This suggests that measures against industrial concentration may be counter-productive, particularly in the context of globalization when countries greatly need to raise productivity.     

AGGLOMERATION AND SUB‐REGIONAL DISPARITIES UNDER DECENTRALIZATION: EVIDENCE OF SPATIAL CLUSTERING OF LAND VALUES IN THE PHILIPPINES

Like other developing countries, the Philippines aims for balanced spatial development. This paper investigates the pattern of sub‐regional disparities by applying the global Moran I and local Moran I_i test statistics on land values data for 1986–2000. Overall, both provincial and city land values diverge spatially. Local clustering of land values is found only within and around Metro Manila. While the results suggest persistent agglomeration economies during the decentralization period, partly because of bias in the fiscal transfer system, they also indicate that other government policies were effective in promoting land values immediately outside Metro Manila.     

Optimality results on orthogonal arrays plus <Emphasis Type="Italic">p</Emphasis> runs for <Emphasis Type="Italic">s</Emphasis><Superscript><Emphasis Type="Italic">m</Emphasis></Superscript> factorial experiments

The optimality of designs obtained by adding p runs to an orthogonal array is studied for experiments involving m factors each at s levels. The optimality criterion used here, is the Type 1 criterion due to Cheng (1978) which is an extension of Kiefer (1975) universal optimality criterion. Unlike what happens with orthogonal array plus one run designs, the behavior of designs obtained via augmentation of an orthogonal array by p runs depends on the particular runs added.     

Measuring process capability index <Emphasis Type="Italic">C</Emphasis><Subscript><Emphasis Type="Italic">pm</Emphasis></Subscript> with fuzzy data

The process capability index C _pm , which considers the process variance and departure of the process mean from the target value, is important in the manufacturing industry to measure process potential and performance. This paper extends its applications to calculate the process capability index [(C)\tilde]_pm{\tilde {C}_{pm} } of fuzzy numbers. In this paper, the α-cuts of fuzzy observations are first derived based on various values of α. The membership function of fuzzy process capability index [(C)\tilde]_pm{\tilde {C}_{pm} } is then constructed based on the α-cuts of fuzzy observations. An example is presented to demonstrate how the fuzzy process capability index [(C)\tilde]_pm{\tilde {C}_{pm} } is interpreted. When the quality characteristic cannot be precisely determined, the proposed method provides the most possible value and spread of fuzzy process capability index [(C)\tilde]_pm{\tilde {C}_{pm} }. With crisp data, the proposed method reduces to the classical method of process capability index C _pm .     

Maximal Rank Minimum Aberration Foldover Plans for 2<Superscript><Emphasis Type="Italic">m</Emphasis>-<Emphasis Type="Italic">k</Emphasis></Superscript> Fractional Factorial Designs

Two level regular fractional factorial designs are often used in industry as screening designs to help identify early on in an experimental process those experimental or system variables which have significant effects on the process being studied. In a recent paper, Li and Lin (2003) suggested a strategy for constructing optimal follow up designs using the well known foldover technique and the minimum aberration criterion. In this paper, we extend the results of Li and Lin (2003) by giving an alternate technique for constructing optimal follow up designs using the foldover technique in conjunction with the maximal rank–minimum aberration criterion suggested in Jacroux (2003).     

Top-<Emphasis Type="Italic">k</Emphasis>-lists

Top-k-lists are introduced as sequences of k-dimensional random vectors with ordered components being k largest observations from a sequence of independent identically distributed random variables. Such lists changing in time are natural stochastic models of ranking tables which appear in many situations in real life, when one wants to keep a track of several best results in a given field. Here we study basic properties of top-k-lists as joint distributions, conditional structures, representations, driving examples of top-k-lists from exponential and uniform distributions, asymptotics and a relation to generalized order statistics.     

¿Está adoptando Asia la «flexiseguridad»?

Incitados por la competencia mundial, muchos países están adaptando la reglamentación laboral al principio de la «flexiseguridad>>, que da a las empresas más flexibilidad para contratar y despedir a los trabajadores, al tiempo que ampara a éstos cuando deben pasar de un empleo a otro. El presente estudio de seis países asiáticos indica que China y República de Corea han promulgado reformas de este género; Singapur y Malasia han implantado algunos elementos de «flexiseguridad>>, pero no un seguro de desempleo, y la India y Sri Lanka han hecho pocas reformas y mantienen un modelo anticuado en el que la protección depende de la empresa. Para prestar apoyo a los trabajadores del sector informal, China, India y Sri Lanka se valen de obras públicas y de programas de fomento del trabajo por cuenta propia y de formación profesional.     

Inference by the <Emphasis Type="Italic">m</Emphasis> out of <Emphasis Type="Italic">n</Emphasis> bootstrap in nonparametric frontier models

It is well-known that the naive bootstrap yields inconsistent inference in the context of data envelopment analysis (DEA) or free disposal hull (FDH) estimators in nonparametric frontier models. For inference about efficiency of a single, fixed point, drawing bootstrap pseudo-samples of size m < n provides consistent inference, although coverages are quite sensitive to the choice of subsample size m. We provide a probabilistic framework in which these methods are shown to valid for statistics comprised of functions of DEA or FDH estimators. We examine a simple, data-based rule for selecting m suggested by Politis et al. (Stat Sin 11:1105–1124, 2001), and provide Monte Carlo evidence on the size and power of our tests. Our methods (i) allow for heterogeneity in the inefficiency process, and unlike previous methods, (ii) do not require multivariate kernel smoothing, and (iii) avoid the need for solutions of intermediate linear programs.     

Two-stage DEA: <Emphasis Type="Italic">caveat emptor</Emphasis>

This paper examines the wide-spread practice where data envelopment analysis (DEA) efficiency estimates are regressed on some environmental variables in a second-stage analysis. In the literature, only two statistical models have been proposed in which second-stage regressions are well-defined and meaningful. In the model considered by Simar and Wilson (J Prod Anal 13:49–78, 2007), truncated regression provides consistent estimation in the second stage, where as in the model proposed by Banker and Natarajan (Oper Res 56: 48–58, 2008a), ordinary least squares (OLS) provides consistent estimation. This paper examines, compares, and contrasts the very different assumptions underlying these two models, and makes clear that second-stage OLS estimation is consistent only under very peculiar and unusual assumptions on the data-generating process that limit its applicability. In addition, we show that in either case, bootstrap methods provide the only feasible means for inference in the second stage. We also comment on ad hoc specifications of second-stage regression equations that ignore the part of the data-generating process that yields data used to obtain the initial DEA estimates.     

Heteroscedasticity diagnostics for <Emphasis Type="Italic">t</Emphasis> linear regression models

The t regression models provide a useful extension of the normal regression models for datasets involving errors with longer-than-normal tails. Homogeneity of variances (if they exist) is a standard assumption in t regression models. However, this assumption is not necessarily appropriate. This paper is devoted to tests for heteroscedasticity in general t linear regression models. The asymptotic properties, including asymptotic Chi-square and approximate powers under local alternatives of the score tests, are studied. Based on the modified profile likelihood (Cox and Reid in J R Stat Soc Ser B 49(1):1–39, 1987), an adjusted score test for heteroscedasticity is developed. The properties of the score test and its adjustment are investigated through Monte Carlo simulations. The test methods are illustrated with land rent data (Weisberg in Applied linear regression. Wiley, New York, 1985). The project supported by NSFC 10671032, China, and a grant (HKBU2030/07P) from the Grant Council of Hong Kong, Hong Kong, China.     

浅谈“三背回填”质量控制

"三背回填"是公路工程的重要组成部分,出现错台、沉降、结构物位移等现象,直接影响到公路路基的稳定性,影响车辆行驶的安全度和舒适度,对此,在公路设计、施工和质量检测方面也提出更高的要求。本文从地基处理、填料选择、施工工艺及加筋土运用四方面对施工进行了改进,达到了质量控制要求。     

Bayesian estimation of log odds ratios from R × C and 2 × 2 × K contingency tables

In this paper, Bayesian estimation of log odds ratios over R × C and 2 × 2 × K contingency tables is considered, which is practically reasonable in the presence of prior information. Likelihood functions for log odds ratios are derived for each table structure. A prior specification strategy is proposed. Posterior inferences are drawn using Gibbs sampling and Metropolis–Hastings algorithm. Two numerical examples are given to illustrate the matters argued.     

Multi-level and mixed-level <Emphasis Type="Italic">k</Emphasis>-circulant supersaturated designs

Supersaturated designs (SSDs) constitute an important class of fractional factorial designs that could be extremely useful in factor screening experiments. Most of the existing studies have focused on balanced designs. This paper provides a new lower bound for the \(E(f_{NOD})\)-optimality measure of SSDs with general run sizes. This bound is a generalization of existing bounds since it is applicable to both balanced and unbalanced designs. Optimal multi and mixed-level, balanced and nearly balanced SSDs are constructed by applying a k-circulant type methodology. Necessary and sufficient conditions are introduced for the generator vectors, in order to pre-ensure the optimality of the constructed k-circulant SSDs. The provided lower bounds were used to measure the efficiency of the generated designs. The presented methodology leads to a number of new families of improved SSDs, providing tools for directly constructing optimal or nearly-optimal k-circulant designs by just checking the corresponding generator vector.