Panicca: Panic on Cross‐Section Averages

The cross‐section average (CA) augmentation approach of Pesaran (A simple panel unit root test in presence of cross‐section dependence. Journal of Applied Econometrics 2007; 22 : 265–312) and Pesaran et al. (Panel unit root test in the presence of a multifactor error structure. Journal of Econometrics 2013; 175 : 94–115), and the principal components‐based panel analysis of non‐stationarity in idiosyncratic and common components (PANIC) of Bai and Ng (A PANIC attack on unit roots and cointegration. Econometrica 2004; 72 : 1127–1177; Panel unit root tests with cross‐section dependence: a further investigation. Econometric Theory 2010; 26 : 1088–1114) are among the most popular ‘second‐generation’ approaches for cross‐section correlated panels. One feature of these approaches is that they have different strengths and weaknesses. The purpose of the current paper is to develop PANICCA, a combined approach that exploits the strengths of both CA and PANIC. Copyright © 2015 John Wiley & Sons, Ltd.     

Financial Distress Prediction in an International Context: A Review and Empirical Analysis of Altman's Z‐Score Model

This paper assesses the classification performance of the Z‐Score model in predicting bankruptcy and other types of firm distress, with the goal of examining the model's usefulness for all parties, especially banks that operate internationally and need to assess the failure risk of firms. We analyze the performance of the Z‐Score model for firms from 31 European and three non‐European countries using different modifications of the original model. This study is the first to offer such a comprehensive international analysis. Except for the United States and China, the firms in the sample are primarily private, and include non‐financial companies across all industrial sectors. We use the original Z′′‐Score model developed by Altman, Corporate Financial Distress: A Complete Guide to Predicting, Avoiding, and Dealing with Bankruptcy (1983) for private and public manufacturing and non‐manufacturing firms. While there is some evidence that Z‐Score models of bankruptcy prediction have been outperformed by competing market‐based or hazard models, in other studies, Z‐Score models perform very well. Without a comprehensive international comparison, however, the results of competing models are difficult to generalize. This study offers evidence that the general Z‐Score model works reasonably well for most countries (the prediction accuracy is approximately 0.75) and classification accuracy can be improved further (above 0.90) by using country‐specific estimation that incorporates additional variables.     

Responsiveness of industry to eco‐efficiency improvements in the product chain: the case of Akzo Nobel11

Increasingly, arguments are being made concerning the benefits of a marriage between ecology and economy in life cycle management. This article provides insights into the business conditions under which market opportunities and eco‐efficiency improvements in the product chain can indeed go hand in hand. The study focuses on the differences in responsiveness of six different sub‐business units within the chemical company of Akzo Nobel to eco‐efficiency improvements in the product chain and how these differences can be explained. The comparative analysis shows the importance of the following three criteria: (i) the level of environmental pressure; (ii) the room for manoeuvre and (iii) the degree to which the environment can be used to obtain a competitive advantage. These criteria may also be valid for other companies. However, research needs to investigate whether additional factors (e.g. the culture of the company, its technological capabilities and market strength) also influence corporate environmental response. Copyright © 2000 John Wiley & Sons, Ltd and ERP Environment     

Greenwashing Revisited: In Search of a Typology and Accusation‐Based Definition Incorporating Legitimacy Strategies

Is greenwashing a concept describing companies using misleading communication or is it co‐constructed in the eye of the beholder? By discussing the literature, we find that existing definitions of greenwashing overemphasize the strategic intention to mislead and do not incorporate unjust allegations. Then, by combining signaling theory with legitimacy theory, we frame the communication process of the greenwashing accusation and the emergence of a negative narrative caused by the accusation and its effect on legitimacy. Hence, in this paper we argue that greenwashing epistemologically is constituted in the eye of the beholder , depending on an external accusation. Following this view, the greenwashing accusation is understood as a distortion factor altering the signal reliability of green messages. Based on our conceptual analysis, we provide a conceptual framework introducing a new typology of case‐based greenwashing (greenwashing , false greenwashing , potential greenwashing and no greenwashing ) and the effects of these types on corporate legitimacy. Finally, we propose a revised definition of greenwashing as co‐creation of an external accusation toward an organization with regard to presenting a misleading green message. Copyright © 2015 John Wiley & Sons, Ltd and ERP Environment     

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.     

Through Thick and Thin? How Self‐determination Drives the Corporate Sustainability Initiatives of Multinational Subsidiaries

Multinational corporation (MNC) subsidiaries implement corporate sustainability initiatives (CSIs) if they are self‐determined to do so (based on intrinsic motivation) or when urged on by circumstances and pressures (based on extrinsic motivation). Such differences in self‐determination are derived from underlying corporate psychological needs for competence, autonomy and relatedness, and are manifested in the governance choices of making, allying or buying CSIs. In this study of oil and gas MNC subsidiaries in the developing country context of Trinidad and Tobago, four distinct types of firm are identified based on their levels of self‐determination and corporate governance tendencies. These groups are identified as trail blazers, marching soldiers, sharp shooters and fire fighters, and their distinctive characteristics are described. These findings are useful to corporate sustainability strategists seeking to select, design and implement CSIs that satisfy MNC headquarter directives but balance subsidiary objectives of maintaining good relations and access to operate in developing countries. Copyright © 2014 John Wiley & Sons, Ltd and ERP Environment     

Factor‐Based Identification‐Robust Interference in IV Regressions

Robust methods for instrumental variable inference have received considerable attention recently. Their analysis has raised a variety of problematic issues such as size/power trade‐offs resulting from weak or many instruments. We show that information reduction methods provide a useful and practical solution to this and related problems. Formally, we propose factor‐based modifications to three popular weak‐instrument‐robust statistics, and illustrate their validity asymptotically and in finite samples. Results are derived using asymptotic settings that are commonly used in both the factor and weak‐instrument literature. For the Anderson–Rubin statistic, we also provide analytical finite‐sample results that do not require any underlying factor structure. An illustrative Monte Carlo study reveals the following. Factor‐based tests control size regardless of instruments and factor quality. All factor‐based tests are systematically more powerful than standard counterparts. With informative instruments and in contrast to standard tests: (i) power of factor‐based tests is not affected by k even when large; and (ii) weak factor structure does not cost power. An empirical study on a New Keynesian macroeconomic model suggests that our factor‐based methods can bridge a number of gaps between structural and statistical modeling. Copyright © 2015 John Wiley & Sons, Ltd.     

Sustainability‐oriented capabilities for eco‐innovation: Meeting the regulatory,technology, and market demands

Despite consensus in the literature that regulation, technology push, and market pull drive eco‐innovation (EI), evidence remains limited on the diverse firm capabilities needed to boost EI. Building on the natural‐resource‐based view of the firm and the EI literature, this paper posits that firms need to renew and realign their capabilities, and ultimately develop distinctive sustainability‐oriented capabilities, in order to meet the rapidly changing regulatory, technology, and market demands. Results of the analysis, based on a survey of U.K. firms, reveal that EIs are more likely to arise when firms (a) build capabilities on voluntary self‐regulation (i.e., executive driven environmental management system and corporate social responsibility) because such organizational capabilities allow them to address increasing regulatory pressures; (b) invest in environmental research and development (i.e., eco‐R&D)—instead of generic research and development—because it provides them with the relevant and specific technological capabilities to tackle technology shifts towards sustainability; and (c) develop capabilities in green market sensing as such capabilities allow them to address green consumption needs.     

Stratified studies about risk ratios in 2 × 2 tables with structural zero

Incomplete correlated 2 × 2 tables are common in some infectious disease studies and two‐step treatment studies in which one of the comparative measures of interest is the risk ratio (RR). This paper investigates the two‐stage tests of whether K RRs are homogeneous and whether the common RR equals a freewill constant. On the assumption that K RRs are equal, this paper proposes four asymptotic test statistics: the Wald‐type, the logarithmic‐transformation‐based, the score‐type and the likelihood ratio statistics to test whether the common RR equals a prespecified value. Sample size formulae based on hypothesis testing method and confidence interval method are proposed in the second stage of test. Simulation results show that sample sizes based on the score‐type test and the logarithmic‐transformation‐based test are more accurate to achieve the predesigned power than those based on the Wald‐type test. The score‐type test performs best of the four tests in terms of type I error rate. A real example is used to illustrate the proposed methods.     

A note on two‐part pricing under uncertainty

In his classic article, Walter Oi (Oi, Q. J. Econ. 2005; 85 : 77–96) analyzed the optimal structure of a two‐part tariff. He showed that identical consumer demands result in user fees equal to marginal cost and a lump‐sum entry fee equal to the consumer surplus that marginal cost pricing generates. This result appears in managerial economics texts (Managerial Economics (6th edn). W. W. Norton: New York; 472–475; Managerial Economics and Business Strategy (5th edn). McGraw Hill/Irwin: New York; 410–412) and intermediate microeconomics texts (Intermediate Microeconomics (6th edn). W. W. Norton: New York; 451–453). In this note, we extend Oi's analysis to the case of uncertainty. We show that attitudes toward risk influence the optimal two‐part tariff. The results from our model describe the two‐part tariff that emerges from expected utility maximization. Copyright © 2010 John Wiley & Sons, Ltd.     

Limit theorems for reflected Ornstein–Uhlenbeck processes

This paper studies one‐dimensional Ornstein–Uhlenbeck (OU) processes, with the distinguishing feature that they are reflected on a single boundary (put at level 0) or two boundaries (put at levels 0 and d > 0). In the literature, they are referred to as reflected OU (ROU) and doubly reflected OU (DROU), respectively. For both cases, we explicitly determine the decay rates of the (transient) probability to reach a given extreme level. The methodology relies on sample‐path large deviations, so that we also identify the associated most likely paths. For DROU, we also consider the ‘idleness process’ L_t and the ‘loss process’ U_t, which are the minimal non‐decreasing processes, which make the OU process remain ≥ 0 and ≤ d, respectively. We derive central limit theorems (CLTs) for U_t and L_t, using techniques from stochastic integration and the martingale CLT.     

Exploring the Complementarities Within High‐Performance Work Systems: A Set‐Theoretic Analysis of UK Firms

High‐performance work systems (HPWS) are important conceptual instruments in the human resource management literature. Yet our current understanding of the complementarities within HPWS remains limited for two reasons: First, the dominant theoretical perspectives on HPWS provide a landscape of theoretical possibilities rather than an understanding of different possibilities through which HPWS generate positive effects on performance; and second, the literature on HPWS merely proposes several seemingly equally important HR practices. This article explores the internal nature of HPWS by integrating a configurational perspective of core, peripheral, and nonessential HR practices with a typology of complementarities. Analyzing 530 UK‐based firms using fuzzy set qualitative comparative analysis (fsQCA), I identify four frequently implemented HPWS consistently associated with high labor productivity. The complementarities within all HPWS combine pairs of core HR practices with sets of peripheral HR practices. Moreover, the complementarities within three of the four HPWS rely on firms’ avoidance of implementing certain HR practices. The results suggest that the synergies of HPWS arise from efficient complementarities and virtuous overlaps, and reveal the significance of achieving high performance by not implementing HR practices. This article thus advances a new perspective on HPWSs, highlighting the challenges involved in successfully designing HPWS. © 2016 Wiley Periodicals, Inc.     

Segmenting university alumni using a person‐centered methodology

Higher education leaders in the United States increasingly rely on relationships with alumni to advance multiple institutional goals. Scholars have traditionally relied on variable‐centered approaches to understand associations among alumni experiences, personal attributes, and support behaviors. Departing from this tradition, this study draws on a person‐centered approach, latent class analysis, to segment groups of alumni by their non‐monetary support behaviors. We define non‐monetary support as engaging in actions outside of charitable giving that advance institutional objectives. Drawing on past literature, we conceptualize alumni non‐monetary support behaviors as falling into 4 categories: (a) volunteerism: charitable preferences, (b) political advocacy: social change preferences, (c) multimode engagement: charity and social change, and (d) disengagement: nonsupport. Relying on an alumni survey from a research‐intensive university in the United States, our analysis found support for a 4‐class model of alumni supporters and nonsupporters. These groupings include the classes of Political Advocates, Apolitical Recruiters, Super Engaged Alumni, and Disengaged Alumni. Using cross‐tabulation analysis, we explore attributes of each class by age, gender, and involvement in religious, political, and volunteer organizations in college. We find that groups of alumni exhibit the same patterns of engagement while they were students. For example, students who were engaged in political action in college are those who are likely to become Political Engagers as alumni. Students who volunteered in college and stayed clear of politics emerge as Apolitical Recruiters after college. Super Engaged Alumni are those who were engaged in multiple domains in college. Implications for advancement practice are discussed.     

ESTIMATION OF TIME‐VARYING ADJUSTED PROBABILITY OF INFORMED TRADING AND PROBABILITY OF SYMMETRIC ORDER‐FLOW SHOCK

Recently, Duarte and Young (2009) studied the probability of informed trading (PIN) proposed by Easley et al. (2002) and decomposed it into two parts: the adjusted PIN (APIN) as a measure of asymmetric information and the probability of symmetric order‐flow shock (PSOS) as a measure of illiquidity. They provide some cross‐section estimates of these measures using daily data over annual periods. In this paper we propose a method to estimate daily APIN and PSOS by extending the method in Tay et al. (2009) using high‐frequency transaction data. Our empirical results show that while PIN is positively contemporaneously correlated with variance, APIN is not. On the other hand, PSOS is positively correlated with daily average effective spread and variance, which is consistent with the interpretation of PSOS as a measure of illiquidity. Compared to APIN, PSOS exhibits clustering and sporadic bursts over time. Copyright © 2012 John Wiley & Sons, Ltd.     

Do stakeholder groups influence environmental management system development in the Dutch agri‐food sector?

This paper presents the results of a survey that included 492 companies in the Dutch agri‐food sector with respect to the influence of stakeholder groups on the companies' level of environmental management system (EMS) implementation. It is concluded that primary stakeholders (government, clients) are more relevant for EMS development than secondary stakeholders (such as environmental organizations). The results suggest that small and medium‐sized companies are able to accommodate to demands with respect to the implementation of internally oriented care systems (I‐EMSs). I‐EMSs focus at the single firm or location. In general, they are predominantly influenced by governmental and other ‘non‐commercial’ stakeholder groups. For the implementation of externally oriented EMSs (E‐EMSs), which focus on the supply chain and network, qualitative rather than quantitative relationship characteristics between companies and the government are important. Moreover, commercial stakeholder groups (such as suppliers, clients and competitors) influence E‐EMS levels significantly. Copyright © 2006 John Wiley & Sons, Ltd and ERP Environment.     

Adjusting for Non‐Response in Population‐Based Case‐Control Studies

In this paper we discuss the analysis of data from population‐based case‐control studies when there is appreciable non‐response. We develop a class of estimating equations that are relatively easy to implement. For some important special cases, we also provide efficient semi‐parametric maximum‐likelihood methods. We compare the methods in a simulation study based on data from the Women's Cardiovascular Health Study discussed in Arbogast et al. (Estimating incidence rates from population‐based case‐control studies in the presence of non‐respondents, Biometrical Journal 44, 227–239, 2002).     

General‐to‐Specific Model Selection Procedures for Structural Vector Autoregressions*

Structural vector autoregressive (SVAR) models have emerged as a dominant research strategy in empirical macroeconomics, but suffer from the large number of parameters employed and the resulting estimation uncertainty associated with their impulse responses. In this paper, we propose general‐to‐specific (Gets) model selection procedures to overcome these limitations. It is shown that single‐equation procedures are generally efficient for the reduction of recursive SVAR models. The small‐sample properties of the proposed reduction procedure (as implemented using PcGets) are evaluated in a realistic Monte Carlo experiment. The impulse responses generated by the selected SVAR are found to be more precise and accurate than those of the unrestricted VAR. The proposed reduction strategy is then applied to the US monetary system considered by Christiano, Eichenbaum and Evans (Review of Economics and Statistics, Vol. 78, pp. 16–34, 1996) . The results are consistent with the Monte Carlo and question the validity of the impulse responses generated by the full system.     

Real‐time detection of regimes of predictability in the US equity premium

We propose new real‐time monitoring procedures for the emergence of end‐of‐sample predictive regimes using sequential implementations of standard (heteroskedasticity‐robust) regression t‐statistics for predictability applied over relatively short time periods. The procedures we develop can also be used for detecting historical regimes of temporary predictability. Our proposed methods are robust to both the degree of persistence and endogeneity of the regressors in the predictive regression and to certain forms of heteroskedasticity in the shocks. We discuss how the monitoring procedures can be designed such that their false positive rate can be set by the practitioner at the start of the monitoring period using detection rules based on information obtained from the data in a training period. We use these new monitoring procedures to investigate the presence of regime changes in the predictability of the US equity premium at the 1‐month horizon by traditional macroeconomic and financial variables, and by binary technical analysis indicators. Our results suggest that the 1‐month‐ahead equity premium has temporarily been predictable, displaying so‐called “pockets of predictability,” and that these episodes of predictability could have been detected in real time by practitioners using our proposed methodology.     

Half‐panel jackknife fixed‐effects estimation of linear panels with weakly exogenous regressors

This paper considers estimation and inference in linear panel regression models with lagged dependent variables and/or other weakly exogenous regressors when N (the cross‐section dimension) is large relative to T (the time series dimension). It allows for fixed and time effects (FE‐TE) and derives a general formula for the bias of the FE‐TE estimator which generalizes the well‐known Nickell bias formula derived for the pure autoregressive dynamic panel data models. It shows that in the presence of weakly exogenous regressors inference based on the FE‐TE estimator will result in size distortions unless N/T is sufficiently small. To deal with the bias and size distortion of the FE‐TE estimator the use of a half‐panel jackknife FE‐TE estimator is considered and its asymptotic distribution is derived. It is shown that the bias of the half‐panel jackknife FE‐TE estimator is of order T^?2, and for valid inference it is only required that N/T³→0, as N,T→∞ jointly. Extension to unbalanced panel data models is also provided. The theoretical results are illustrated with Monte Carlo evidence. It is shown that the FE‐TE estimator can suffer from large size distortions when N>T, with the half‐panel jackknife FE‐TE estimator showing little size distortions. The use of half‐panel jackknife FE‐TE estimator is illustrated with two empirical applications from the literature.