Raising the bar (6)

Raising the bar (6). Spatial Economic Analysis. This editorial summarizes and comments on the papers published in issue 12(4) so as to raise the bar in applied spatial economic research and highlight new trends. The first paper addresses the question of whether ‘jobs follow people’ or ‘people follow jobs’. The second paper develops a new methodology to determine functional regions. The third paper is a major contribution to the growing literature on new modelling approaches and applications of disaster impact models. The fourth paper focuses on the costs and benefits of higher education. The fifth paper develops a two-step procedure to identify endogenously spatial regimes in the first step using geographically weighted regression, and to account for spatial dependence in the second step. Finally, the sixth paper estimates a dynamic spatial panel data model to explain house prices and to show that restricted housing supply in the city of Cambridge, UK, has some undesirable labour market effects.     

From a System of National Accounts to a Process of National Wellbeing Accounting

There are repeated calls to go ‘Beyond GDP’, for measures of wellbeing and progress in addition to those that the System of National Accounts (SNA) is designed to provide. We identify key issues that can help build on the rigour of SNA whilst fitting the measurement of economic performance within a broader assessment of national wellbeing and progress. Such drivers are already leading to a proliferation of indicators and accounts, for example in the development of non‐monetary measures of natural resources, but there are significant measurement challenges, not least the question of whether a single, overall measure or index of wellbeing is valid. But the challenge of measurement, per se, is one thing: in our view, a more critical issue is whether the measures will actually be used. We propose a dynamic and multi‐staged approach for developing SNA, embracing the production and use of measures. This would start by identifying user requirements for wider measures, to provide the basis for national and cross‐national developments in well‐being accounting. We envisage greater branding and marketing of national well‐being concepts to promote measures and support their use. We call for outreach by producers, so that there is dialogue about the development and use of measures.     

Manufacturer collusion: Strategic implications of the channel structure

We investigate how the structure of the distribution channel affects tacit collusion between manufacturers. When selling through a common retailer, we find—in contrast to the conventional understanding of tacit collusion that firms act to maximize industry profits—that colluding manufacturers strategically induce double marginalization so that retail prices are above the monopoly level. This lowers industry profits but increases the profit share that manufacturers appropriate from the retailer. Comparing common distribution with independent (exclusive) distribution, we show that the latter facilitates collusion. Despite this result, common retailing leads to lower welfare because a common retailer monopolizes the downstream market. For the case of independent retailing, we also demonstrate that contract offers that are observable to the rival retailer are not necessarily beneficial for collusive purposes.     

Conditional assessment of the impact of a Hausman pretest on confidence intervals

In the analysis of clustered and longitudinal data, which includes a covariate that varies both between and within clusters, a Hausman pretest is commonly used to decide whether subsequent inference is made using the linear random intercept model or the fixed effects model. We assess the effect of this pretest on the coverage probability and expected length of a confidence interval for the slope, conditional on the observed values of the covariate. This assessment has the advantages that it (i) relates to the values of this covariate at hand, (ii) is valid irrespective of how this covariate is generated, (iii) uses exact finite sample results, and (iv) results in an assessment that is determined by the values of this covariate and only two unknown parameters. For two real data sets, our conditional analysis shows that the confidence interval constructed after a Hausman pretest should not be used.     

Labour market recruiting with intermediaries

We consider a Rothschild–Stiglitz–Spence labour market model and employ a centralised mechanism to coordinate the efficient matching of workers to firms. This mechanism can be thought of as operated by a recruitment agency, an employment office or head hunter. In a centralised descending-bid, multi-item procurement auction, workers submit wage-bids for each job and are assigned stable jobs as equilibrium outcome. We compare this outcome to independent, sequential hiring by firms and conclude that, in general, a stable assignment can only be implemented if firms coordinate to some extent.      

Instrumental variable estimation based on grouped data

The paper considers the estimation of the coefficients of a single equation in the presence of dummy intruments. We derive pseudo ML and GMM estimators based on moment restrictions induced either by the structural form or by the reduced form of the model. The performance of the estimators is evaluated for the non-Gaussian case. We allow for heteroscedasticity. The asymptotic distributions are based on parameter sequences where the number of instruments increases at the same rate as the sample size. Relaxing the usual Gaussian assumption is shown to affect the normal asymptotic distributions. As a result also recently suggested new specification tests for the validity of instruments depend on Gaussianity. Monte Carlo simulations confirm the accuracy of the asymptotic approach.     

An Integrative Framework for Measuring the Extent to which Organizational Variables Influence the Success of Process Improvement Programmes

abstract    Studies on the three types of process improvement programmes (Continuous Improvement, Reengineering and Benchmarking) have appeared many times in the literature. These studies suggest that certain organizational variables act as enablers and their presence or absence can significantly influence success rates. Such studies have tended to examine companies where a single programme has been implemented. In contrast, this paper examines a sample of companies who have experienced all three programmes. Our aim is to compare and contrast each programme's impact on firm performance and identify which organizational variables are common and which are programme-specific enablers of success. We build and test an integrative framework to support our analysis. Our study found that: (1) Reengineering delivered the greatest impact on performance; (2) executive commitment was needed to make this happen; (3) strategic alignment was the major influence on the success rate of Reengineering and Continuous Improvement programmes; and (4) employee empowerment was necessary for each programme to work effectively.     

Transportation cost changes with statewide school district consolidation

This article studies the relationship between school district size and bus transportation costs, and estimates the change in such costs when a statewide policy of consolidation is pursued. To explore this relationship, we develop a multiple-objective model and solution procedure that combines a geographic aggregation and bus routing heuristic to generate consolidation scenarios. The heuristic was developed to explicitly consider efficiency, effectiveness, and equity objectives, and can be applied in both urban and rural states. The scenarios will generate average statewide bus transportation costs. As applied to the State of Iowa, within the legislature's proposed range of consolidation of 500-1000 students, it was found that transportation operational and capital cost increases range from 0.6 to 10.6 percent and 0.7 to 7.7 percent, respectively.     

Historical resources, uncertainty and preservation values: An application of option and optimal stopping models

State agencies and private historical organizations frequently acquire historical sites with unknown characteristics. In this paper, we provide two approaches to evaluating the preservation decision. In the first approach, we show that a historical site which is not permanently preserved provides citizens with a certain flexibility whose value can be measured as an option on the maximum between the current real estate value and the preservation value. In the second approach, we assume that the organization has an infinite planning horizon and chooses the optimal sale date. Using a contingent valuation estimate of the public's willingness to pay for preservation of a specific historical site and the real estate price, we provide simulation values of the preservation option value and the optimal stopping rule.