Conducting Mode 2 research in HRM: A phase‐based framework

Recent studies in the field of human resource management (HRM) have highlighted that current research is mostly performed and consumed by academics, and is driven by theoretical and disciplinary concerns rather than practical ones. This debate has invoked the need to produce more Mode 2 research in the HRM field, that is, research driven by practical problems that integrate collaborative efforts by academics and practitioners. Yet, guidelines on how academics and practitioners may implement Mode 2 research remain disjointed and incomplete. Our study provides a phase‐based collaborative‐based framework for the implementation of Mode 2 research in the HRM field, in ways that both academic rigor and practical relevance are achieved. Our framework is informed by a comprehensive review of previous Mode 2 research, within and outside the HRM field. The proposed framework details four macro‐phases: the codevelopment of research questions with practitioners; the design of collaborative spaces and mechanisms; the design and management of double‐loop iterative research processes; and finally the academic and practice legitimization of Mode 2 outcomes. Our framework has the objective to support HRM researchers and practitioners, as well as relevant institutions and gatekeepers in the design, implementation, education, and assessment of Mode 2 research.     

Narrow Replication of ‘A Spatio‐Temporal Model of House Prices in the Usa’ Using R

I narrowly replicate Holly et al.'s (Journal of Econometrics 2010; 158 (1): 160–173) analysis of the housing market in the USA, using the open source R software instead of the original ad hoc GAUSS routines. Their main findings are confirmed and most results are matched exactly. Attention is given to providing a self‐contained and fully reproducible analysis, exclusively using user‐level features available in the public domain. Copyright © 2014 John Wiley & Sons, Ltd.     

Integrating Environmental,Social and Governance (ESG) Disclosure for a Sustainable Development: An Australian Study

Addressing environmental, social and governance (ESG) issues has become a critical part of business strategy. This article explores the extent of ESG reporting of metal and mining sector companies listed in the Australian Securities Exchange to determine the nature of ESG indicators in use in the sector. The current study argues that stakeholder engagement is the key to enhance company environmental policy and sustainable development. According to the results of this study, ESG reporting motives are highly influenced by reporting regulations. Given the diversity in reporting of ESG, comparability of ESG strategic performance is problematic. This study contributes towards developing an ESG disclosure index, which companies could use as a legitimacy tool that external stakeholders could use to reliably measure and compare the ESG performance of companies. It also reveals there is an increased demand for more empirical research on integration of sustainability into strategic planning process. Copyright © 2016 John Wiley & Sons, Ltd and ERP Environment     

Unveiling Urban Sprawl in the Mediterranean Region: Towards a Latent Urban Transformation?

The relationship between form and function in European Mediterranean cities has been widely addressed from various perspectives. A number of studies indicate that, until the 1980s, compactness was a key trait of several cities of the Northern Mediterranean. However, after the ‘compact growth’ period, these cities experienced patterns of urbanization that differed from their traditional trends. Since the 1990s, sprawl, coupled with population decline in the inner cities, has become the main pattern of urban development. This article explores the key features of exurban development in the Mediterranean region in order to provide material for a discussion based on the differences and similarities in the characteristics of sprawl processes originating in the US and Northern Europe. It concludes that any debate on policy responses to sprawl must be specifically formulated according to the scope, administrative level, housing and planning system, territorial and socioeconomic characteristics of the urban system under examination. It is our belief that sprawl requires site‐specific analyses and policy strategies for the region being studied if the process is to be effectively controlled.     

SALES,INVENTORIES AND REAL INTEREST RATES: A CENTURY OF STYLIZED FACTS

We use Bayesian time‐varying parameter structural vector autoregressions with stochastic volatility to investigate changes in reduced‐form and structural correlations between inventories and either sales growth or the real interest rate in the USA during both the inter‐war and post‐World War II periods. We identify four structural shocks by combining a single long‐run restriction to identify a permanent output shock with three sign restrictions to identify demand‐ and supply‐side transitory shocks. We show that during both the inter‐war and post‐war periods the structural correlation between inventories and real interest rate conditional on identified interest rate shocks is systematically positive; the reduced‐form correlation between the two series is positive during the post‐war period, but in line with the predictions of theory it is robustly negative during the inter‐war era; during that era the correlations between inventories and either of the two other series exhibit a remarkably strong co‐movement with output at business cycle frequencies. Copyright © 2014 John Wiley & Sons, Ltd.     

Simulation‐based tests of forward‐looking models under VAR learning dynamics

In this paper we propose a simulation‐based technique to investigate the finite sample performance of likelihood ratio (LR) tests for the nonlinear restrictions that arise when a class of forward‐looking (FL) models typically used in monetary policy analysis is evaluated with vector autoregressive (VAR) models. We consider ‘one‐shot’ tests to evaluate the FL model under the rational expectations hypothesis and sequences of tests obtained under the adaptive learning hypothesis. The analysis is based on a comparison between the unrestricted and restricted VAR likelihoods, and the p‐values associated with the LR test statistics are computed by Monte Carlo simulation. We also address the case where the variables of the FL model can be approximated as non‐stationary cointegrated processes. Application to the ‘hybrid’ New Keynesian Phillips Curve (NKPC) in the euro area shows that (i) the forward‐looking component of inflation dynamics is much larger than the backward‐looking component and (ii) the sequence of restrictions implied by the cointegrated NKPC under learning dynamics is not rejected over the monitoring period 1984–2005. Copyright © 2010 John Wiley & Sons, Ltd.     

An alternative procedure for imputing missing data based on principal components analysis

This work entailed tackling the significant problem of missing data which was solved by identifying a new substitution procedure, following an empirical approach based on the analysis of the information contained in the entire set of data collected. This procedures offers a number of advantages compared to other techniques commonly mentioned in the statistical–methodological literature.     

Testing the Influence of Substitute Sites in Nature Valuation by Using Spatial Discounting Factors

This paper investigates the effect of nearby nature substitute sites on preferences for nature restoration. Contrary to prior studies, we use a respondent-centric approach to control for substitute sites. We assess each respondent-specific spatial context by computing densities of nature substitute sites within various ranges from each respondent’s home. This approach considers the use and non-use values of nature together. Data from three similar discrete choice experiments carried out in Flanders (Belgium) are compared. Different spatial discounting factors are tested to explore how the substitution effect behaves with regard to distance. Latent class analyses are performed to account for preference heterogeneity among respondents. We observe divergent behaviours across groups of respondents. The “distance-to-substitutes” affects how respondents gauge substitute sites. We find a significant influence of the squared average buffer distance but this effect varies in sign across case studies and classes of respondents. Our results demonstrate that individual-specific GIS data can significantly improve the representation of the spatial context and the transferability of value functions. However, the roles played by preference heterogeneity and nature perception on respondents’ capacity to value nature still deserves further attention in future research.     

HOW DO FISCAL CONSOLIDATION AND FISCAL STIMULI IMPACT ON THE SYNCHRONIZATION OF BUSINESS CYCLES?

Using quarterly data for a panel of advanced economies, we show that synchronized fiscal consolidation (stimulus) programmes in different countries make their business cycles more closely linked. We also find: (i) some evidence of decoupling when an inflation targeting regime is unilaterally adopted; (ii) an increase in business cycle synchronization when countries fix their exchange rates and become members of a monetary union; (iii) a positive effect of bilateral trade on the synchronization of business cycles. Global factors, such as a rise in global risk aversion and uncertainty and a reversal of nonstandard expansionary monetary policy, can also reduce the degree of co‐movement of business cycles across countries. From a policy perspective, our work shows that an inflation targeting regime coupled with simultaneous fiscal consolidations can lead to more business cycle synchronization.     

Sharp IV Bounds on Average Treatment Effects on the Treated and Other Populations Under Endogeneity and Noncompliance

In the presence of an endogenous binary treatment and a valid binary instrument, causal effects are point identified only for the subpopulation of compliers, given that the treatment is monotone in the instrument. With the exception of the entire population, causal inference for further subpopulations has been widely ignored in econometrics. We invoke treatment monotonicity and/or dominance assumptions to derive sharp bounds on the average treatment effects on the treated, as well as on other groups. Furthermore, we use our methods to assess the educational impact of a school voucher program in Colombia and discuss testable implications of our assumptions. Copyright © 2015 John Wiley & Sons, Ltd.