Detecting Dependence Between Spatial Processes

Abstract

Testing the assumption of independence between variables is a crucial aspect of spatial data analysis. However, the literature is limited and somewhat confusing. To our knowledge, we can mention only the bivariate generalization of Moran's statistic. This test suffers from several restrictions: it is applicable only to pairs of variables, a weighting matrix and the assumption of linearity are needed; the null hypothesis of the test is not totally clear. Given these limitations, we develop a new non-parametric test, Υ(m), based on symbolic dynamics with better properties. We show that the Υ(m) test can be extended to a multivariate framework, it is robust to departures from linearity, it does not need a weighting matrix and can be adapted to different specifications of the null. The test is consistent, computationally simple and with good size and power, as shown by a Monte Carlo experiment. An application to the case of the productivity of the manufacturing sector in the Ebro Valley illustrates our approach.     

Employment Growth in Italian Local Labour Systems: Issues of Model Specification and Sectoral Aggregation

Abstract

In this paper we construct a model to estimate local employment growth in Italian local labour markets for the period 1991–2001. The model is constructed in a similar manner to the original models of Glaeser et al. (1992), Henderson et al. (1995) and Combes (2000). Our objective is to identify the extent to which the results estimated by these types of models are themselves sensitive to the model specification. In order to do this we extend the basic models by successively incorporating new explanatory variables into the model framework. In addition, and for the first time, we also estimate these same models at two different levels of sectoral aggregation, for the same spatial structure. Our results indicate that these models are highly sensitive to sectoral aggregation and classification and our results therefore strongly support the use of highly disaggregated data.     

An Extension of the J‐Test to a Spatial Panel Data Framework

Kelejian (Letters in Spatial and Resources Sciences; 1 : 3–11) extended the J‐test procedure to a spatial framework. Although his suggested test was computationally simple and intuitive, it did not use the available information in an efficient manner. Kelejian and Piras (Regional Science and Urban Economics; 41 : 281–292) generalized and modified Kelejian's test to account for all the available information. However, neither Kelejian ( 2008 ) nor Kelejian & Piras ( 2011 ) considered a panel data framework. In this paper we generalize these earlier works to a panel data framework with fixed effects and additional endogenous variables. We give theoretical as well as Monte Carlo results relating to our suggested tests. An empirical application on a crime model for North Carolina is also estimated. Copyright © 2015 John Wiley & Sons, Ltd.     

A framework for the identification of reusable processes

A significant challenge that faces IT management is that of aligning the IT infrastructure of an enterprise with its business goals and practices, also called business-IT alignment. A particular business-IT alignment approach, the foundation for execution approach, was well-accepted by practitioners due to a novel construct, called the operating model (OM). The OM supports business-IT alignment by directing the coherent and consistent design of business and IT components. Even though the OM is a popular construct, our previous research detected the need to enhance the OM, since the OM does not specify methods to identify opportunities for data sharing and process reuse in an enterprise. In this article, we address one of the identified deficiencies in the OM. We present a process reuse identification framework (PRIF) that could be used to enhance the OM in identifying process reuse opportunities in an enterprise. We applied design research to develop PRIF as an artefact, where the development process of PRIF was facilitated by means of the business-IT alignment model (BIAM). We demonstrate the use of the PRIF as well as report on the results of evaluating PRIF in terms of its usefulness and ease-of-use, using experimentation and a questionnaire.     

Technology Transfer to China: A Theoretical Approach

SUMMARY

Various economic theories can be used to shed some light on the complex phenomenon of technology transfer between two firms belonging to two distinct economies. Vernon's PLC model, Dunning's eclectic theory, and Coase's and Williamson's transaction cost theory highlight various aspects of the firm's transnational economic and business relations. Moreover, the new international trade theories and the more modern concept of National Innovation System emphasize technology as a crucial variable in the determination of commercial flows and of economic growth. Our theoretical approach goes beyond these various approaches in that it is designed to reflect the complexities of the economic, socio-cultural and political conditions prevailing in the recipient country. In particular, the ability of recipient countries to use their bargaining power is highlighted. The case of technology transfer in the Chinese telecommunications equipment industry will illustrate our general framework.     

New Employee Orientation Programs

The conceptual domain of new employee orientation programs is defined. Following this, orientation programs are distinguished from socialization, psychological contracts, training, and realistic job previews (RJPs). Three somewhat diverse areas of academic research are used to develop a framework for the design and study of new employee orientation programs: (a) stress theory/coping methods, (b) attitude theory/change methods, (c) RJP theory/methods. The framework for designing new employee orientation is called “ROPES,” an acronym for Realistic Orientation Programs for new Employee Stress. Five field experiments that best represent ROPES are reviewed. Future research on newcomer orientation should be guided by a clear definition of the conceptual domain, borrow liberally from related areas of inquiry, be conducted in field settings, and use experimental designs.     

Do not say a word! Conceptualizing employee silence in a long-term crisis context

Abstract

Although research has emphasized the organizational and individual factors that influence employee voice and silence at work, it is less known how employee voice/silence is affected by the economic context, particularly when this context is one of intensive and long-term economic crisis in a country with weak institutional bases. In this study, we explore how employee silence is formulated in long-term turbulent economic environments and in more vulnerable organizational settings like those of small enterprises. The study draws on qualitative data gathered from 63 interviews with employees in a total of 48 small enterprises in Greece in two periods of time (2009 and 2015). This study suggests a new type of employee silence, social empathy silence, and offers a conceptual framework for understanding the development of silence over time in particular contexts of long-term turbulence and crisis.     

Restoring Credible Economic Governance to the Eurozone

This paper discusses new institutional rules for a stable and lasting European Monetary Union (EMU). We propose a return to a strict and sustainable economic governance framework, which is mainly driven by market forces within a smart rule‐based environment. Our recommendations are: (a) ex ante conditionalities with a tough monitoring process to avoid moral hazard in the future; (b) further enhancement of the Stability and Growth Pact; and (c) ultimo ratio punishment to be able to respond to the unique constellation of fiscal–monetary interaction and new rescue facilities. Countries violating fiscal rules for more than four years in a row will thus lose their fiscal sovereignty or will have to resign from the Eurozone. After fulfilling the ex ante conditionalities as well as all required criteria, the country either will recover its fiscal sovereignty, or, in case of exclusion, will be given the option to rejoin EMU under certain conditions.     

An inflated multivariate integer count hurdle model: an application to bid and ask quote dynamics

In this paper we develop a model for the conditional inflated multivariate density of integer count variables with domain ?ⁿ, n ∈ ?. Our modelling framework is based on a copula approach and can be used for a broad set of applications where the primary characteristics of the data are: (i) discrete domain; (ii) the tendency to cluster at certain outcome values; and (iii) contemporaneous dependence. These kinds of properties can be found for high‐ or ultra‐high‐frequency data describing the trading process on financial markets. We present a straightforward sampling method for such an inflated multivariate density through the application of an independence Metropolis–Hastings sampling algorithm. We demonstrate the power of our approach by modelling the conditional bivariate density of bid and ask quote changes in a high‐frequency setup. We show how to derive the implied conditional discrete density of the bid–ask spread, taking quote clusterings (at multiples of 5 ticks) into account. Copyright © 2009 John Wiley & Sons, Ltd.     

Testing for Multicointegration in Panel Data with Common Factors*

This paper addresses the concept of multicointegration in a panel data framework and builds upon the panel data cointegration procedures developed in Pedroni [Econometric Theory (2004), Vol. 20, pp. 597–625]. When individuals are either cross‐section independent, or cross‐section dependence can be removed by cross‐section demeaning, our approach can be applied to the wider framework of mixed I(2) and I(1) stochastic processes. The paper also deals with the issue of cross‐section dependence using approximate common‐factor models. Finite sample performance is investigated through Monte Carlo simulations. Finally, we illustrate the use of the procedure investigating an inventories, sales and production relationship for a panel of US industries.     

Fast Fashion: Calculative Technologies and the Governance of Everyday Dress

Abstract

The speed at which contemporary fashion changes is such that the life of a garment can now be measured in a matter of weeks rather than months. The organisational consequences of operating in this environment are that fashion retailers have been prompted to adopt a range of quick response (QR) initiatives. QR involves responding promptly to the information contained within emerging sales trends while simultaneously accelerating the movement of product from factory to shop shelf. Drawing on the case of a UK fashion chain, this paper explores accounting's role in enacting QR. In addition, by deploying the theoretical framework of governmentality [Miller, P., & Rose, N. (1990). Governing economic life. Economy and Society, 19(1), 1–31; Rose, N., & Miller, P. (1992). Political power beyond the state: Problematics of government. British Journal of Sociology, 43(2), 173–205], the paper highlights the role of calculative technologies in the creation and sustenance of fast fashion and hence the governance of everyday dress.     

Toward a non-organizational theory of human resource management? A complex adaptive systems perspective on the human resource management ecosystem in (con)temporary organizing

The emergence of the temporary organization has ushered in a new logic of organizing accompanied by paradigm-shifting challenges with respect to how the evolving nature of work, workers, and collective effort are to be understood. To capture the complexity inherent in this new order, and to broaden our focus from the organization to the enfolding ecosystem within which temporary organizing must be situated and understood, we engage in problematization to develop a multi-level framework for theorizing the contemporary human resource management ecosystem. Curating insights from complexity science, we conceptualize this ecosystem as a complex adaptive one and we propose a framework that integrates key structural (open boundaries and relational constitution), emergent (contextual and complex causality), and temporal (dynamic and adaptive) properties. To deepen lines of inquiry around these defining elements, we advance a series of propositions for testing, and we outline a range of theoretical, methodological, and practical implications that arise from our work.     

Multivariate L1 mean

The center of a univariate data set {x ₁,…,x _n} can be defined as the point μ that minimizes the norm of the vector of distances y′=(|x ₁−μ|,…,|x _n−μ|). As the median and the mean are the minimizers of respectively the L ₁- and the L ₂-norm of y, they are two alternatives to describe the center of a univariate data set. The center μ of a multivariate data set {x ₁,…,x _n} can also be defined as minimizer of the norm of a vector of distances. In multivariate situations however, there are several kinds of distances. In this note, we consider the vector of L ₁-distances y′₁=(∥x ₁- μ∥₁,…,∥x _n- μ∥₁) and the vector of L ₂-distances y′₂=(∥x ₁- μ∥₂,…,∥x _n-μ∥₂). We define the L ₁-median and the L ₁-mean as the minimizers of respectively the L ₁- and the L ₂-norm of y ₁; and then the L ₂-median and the L ₂-mean as the minimizers of respectively the L ₁- and the L ₂-norm of y ₂. In doing so, we obtain four alternatives to describe the center of a multivariate data set. While three of them have been already investigated in the statistical literature, the L ₁-mean appears to be a new concept. Received January 1999     

Time to decision: the drivers of innovation adoption decisions

Organisations desire timeliness. Timeliness facilitates a better responsiveness to changes in an organisation's external environment to either attain or maintain competitiveness. Despite its importance, decision timeliness has not been explicitly examined. Decision timeliness is measured in this study as the time taken to commit to a decision. The research objective is to identify the drivers of decision timeliness in the context of adopting service-oriented architecture (SOA), an innovation for enterprise computing. A research model rooted in the technology–organisation–environment (TOE) framework is proposed and tested with data collected in a large-scale study. The research variables have been examined before in the context of adoption, but their applicability to the timeliness of innovation decision-making has not received much attention and their salience is unclear. The results support multiple hypothesised relationships, including the finding that a risk-oriented organisational culture as well as normative and coercive pressures accelerates decision timeliness. Top management support as well as the traditional innovation attributes (compatibility, relative advantage and complexity/ease-of-use) were not found to be significant when examining their influence on decision timeliness, which appears inconsistent with generally accepted knowledge and deserves further examination.     

Notes and Comments: Sup-convolutions of HARA utilities in the affine term structure

Abstract In the financial literature, the problem of maximizing the expected utility of the terminal wealth has been investigated extensively (for a survey, see, e.g., Karatzas and Shreve (1998), p. 153, and references therein) by using different approaches. In this paper, we extend the existing literature in two directions. First, we let the utility function U(.) of the financial agent (who is a price taker) be implicitly defined through I(.)=(U ^′ (.))^–1, which is assumed to be additively separable, i.e., I(.)=∑ _k=1 ^N I _k (.). Second, we solve the investment problem in the general affine term structure model proposed by Duffie and Kan (1996) in which the functions I _k (.), k=1,...,N are associated to HARA utility functions (with possibly different risk aversion parameters), and we show that the utility maximization problem leads to a Riccati ODE. Moreover, we extend to the multi-factor framework the stability result proved in Grasselli (2003), namely, the almost-sure convergence of the solution with respect to the parameters of the utility function. Mathematics Subject Classification (2000): 91B28 Journal of Economic Literature Classification: G11     

Debt Service Capacity Revisited

Abstract

Debt Service Capacity (DSC) is revisited within a new framework, i.e., Neural Networks (NN), an established method in the field of artificial intelligence (AI). A select group of traditional models that have been used to predict DSC is also reviewed and the logit approach is chosen for comparison with NN.

Ten measures (indices) are constructed as determinants of DSC. To keep the comparison simple, empirical applications of the two models are controlled by employing the same data sample and the same holdout and estimation groups in both models. A few drawbacks of the traditional approaches, especially the presence of multicollinearity, are pointed out. It is shown that when multicollinearity is present, the exponential of the coefficients cannot be explained as the odds ratio.

A number of tests and sensitivity analyses are performed to exhibit the attributes and the performance of the two models.     

Measuring global flow of funds: focus on China,Japan, and the United States

ABSTRACT

This paper aims to establish a new statistical framework for measuring global flow of funds (GFF) based on its inherent mechanisms. It advances a previous theoretical discussion and develops a practical operational statistical matrix. Based on theoretical and practical possibilities the paper gets existing data from the International Investment Position, the Coordinated Direct Investment Survey, the Coordinated Portfolio Investment Survey, and International Banking Statistics are integrated for measuring GFF. The main outcome is a prototype GFF matrix that includes stock data geographically disaggregated by country/region and selected financial instruments. The paper presents a GFF Matrix compiled with the pattern of ‘Country vis-à-vis Country’ matrix, and through using the GFF matrix to analyze the basic status, mutual relationship and existing problems between China, Japan, and the United States in the external financial positions.     

China's Approach to Social Market Economics: The Chinese variant of Market Socialism Seeks to Escape from the Difficulties of Central Command Planning

Abstract . The paradigm of a social market economy provides a rational basis for resolving structural socioeconomic changes, as presently evidenced in the People's Republic of China. China's approach to socioeconomic change, labeled as “Socialism with Chinese Characteristics,” resembles a modified version of Eucken's paradigm of a social market economy.¹ The Chinese paradigm, leaning on that of Walter Eucken, provides for a “limited”free market, which not only accommodates economic growth and change, but which also makes allowance for some degree of human, especially economic freedom, and dignity. Eucken's model is based on a sound institutional and legal framework which he considered to be essential for a viable modern market economy. China's new socioeconomic program is moving the country in this direction. It takes into account people's desire for a useful and Just socioeconomic order (however defined), characterized by stable socioeconomic and political policies and by a flexible price mechanism, to enable them to live a life in dignity, free of economic deprivation.     

Selection correction and sensitivity analysis for ordered treatment effect on count response

In estimating the effect of an ordered treatment τ on a count response y with an observational data where τ is self‐selected (not randomized), observed variables x and unobserved variables ε can be unbalanced across the control group (τ = 0) and the treatment groups (τ = 1, …, J). While the imbalance in x causes ‘overt bias’ which can be removed by controlling for x, the imbalance in ε causes ‘covert (hidden or selection) bias’ which cannot be easily removed. This paper makes three contributions. First, a proper counter‐factual causal framework for ordered treatment effect on count response is set up. Second, with no plausible instrument available for τ, a selection correction approach is proposed for the hidden bias. Third, a nonparametric sensitivity analysis is proposed where the treatment effect is nonparametrically estimated under no hidden bias first, and then a sensitivity analysis is conducted to see how sensitive the nonparametric estimate is to the assumption of no hidden bias. The analytic framework is applied to data from the Health and Retirement Study: the treatment is ordered exercise levels in five categories and the response is doctor office visits per year. The selection correction approach yields very large effects, which are however ruled out by the nonparametric sensitivity analysis. This finding suggests a good deal of caution in using selection correction approaches. Copyright © 2004 John Wiley & Sons, Ltd.