Escape dynamics and equilibria selection by iterative cycle decomposition

This paper explores the medium-run behaviour of bounded rational players in repeatedly played games when they occasionally experiment or make mistakes. The formal analysis introduces a hierarchical structure of limit sets to characterize the most possible medium-run behaviour over gradually increased time intervals. The paper refines the notion of stochastic stability and offers a precise measure of the speed at which stochastically stable equilibria occur. Finally, the paper applies the results to a 3×3 symmetric game of Young (1993).     

E-stability and stability of adaptive learning in models with private information

The paper demonstrates how the E-stability principle introduced by Evans and Honkapohja [2001. Learning and Expectations in Macroeconomics. Princeton University Press, Princeton, NJ] can be applied to models with heterogeneous and private information in order to assess the stability of rational expectations equilibria under learning. The paper extends already known stability results for the Grossman and Stiglitz [1980. On the impossibility of informationally efficient markets. American Economic Review 70, 393–408] model to a more general case with many differentially informed agents and to the case where information is endogenously acquired by optimizing agents. In both cases it turns out that the rational expectations equilibrium of the model is inherently E-stable and thus locally stable under recursive least squares learning.     

Learning and time-varying macroeconomic volatility

This paper presents a DSGE model in which agents׳ learning about the economy can endogenously generate time-varying macroeconomic volatility. Economic agents use simple models to form expectations and need to learn the relevant parameters. Their gain coefficient is endogenous and is adjusted according to past forecast errors.The model is estimated using likelihood-based Bayesian methods. The endogenous gain is jointly estimated with the structural parameters of the system.The estimation results show that private agents appear to have often switched to constant-gain learning, with a high constant gain, during most of the 1970s and until the early 1980s, while reverting to a decreasing gain later on. As a result, the model can generate a pattern of volatility, which is increasing in the 1970s and falling in the second half of the sample, with a decline that can roughly match the magnitude of the so-called “Great Moderation” in the 1984–2007 period. The paper also documents how a failure to incorporate learning into the estimation may lead econometricians to spuriously find time-varying volatility in the exogenous shocks, even when these have constant variance by construction.     

Evolving macroeconomic perceptions and the term structure of interest rates

We explore the role of evolving beliefs regarding the structure of the macroeconomy in improving our understanding of the term structure of interest rates within the context of a simple macro-finance model. Using quarterly vintages of real-time data and survey forecasts for the United States over the past 40 years, we show that a recursively estimated VAR on real GDP growth, inflation and the nominal short-term interest rate generates predictions that are more consistent with survey forecasts than a benchmark fixed-coefficient counterpart. We then estimate a simple term structure model under the assumption that investor risk attitude is driven by near-term expectations of the three state variables. When we allow for evolving beliefs about the macroeconomy, the resulting term structure model provides a better fit to the cross section of yields than the benchmark model, especially at longer maturities, and exhibits better performance in out-of-sample predictions of future yield movements.     

Routine dynamics and paradox: A revised research agenda

This comment reflects on the paper by Rosales et al. (2022) and discusses the role and contribution of paradox theory for our understanding of routine dynamics. Whilst the authors claim that routines serve as rubber bands that enable practitioners to manage the paradoxical relationship between stability and change, in this commentary I want to challenge some of the core assumptions around stability and change in this paper and propose a revised understanding. It is a central tenant of routine dynamics studies that stability and change are mutually enabling – a duality – and hence not contradictory categories. As I outline in this comment this has significant consequences for the way routine dynamics are studied. Furthermore, I propose some areas in which paradox theory and routine dynamics studies may fruitfully be combined to address novel research questions.     

农村最低生活保障标准调整实证研究——以山东省泰安市为例

本文利用计量经济模型分析了泰安市1997年-2009年农村最低生活保障标准的面板数据,对影响农村最低生活保障标准调整的因素做出了定量及定性分析。分析表明:人均预算内财政收入是农村最低生活保障标准调整的主要影响因素。但由于考虑因素欠妥,农村低保标准调整中存在依据不够合理,人为因素影响较大等问题,产生了农村低保标准偏低、覆盖面窄、未实现应保尽保等负面效应。由此提出合理调整农村低保标准的建议,为客观合理制定适合当地经济发展水平的农村低保标准提供科学依据。     

Network dynamics and new ventures in China: A longitudinal study

This study examines the effects of networking skills of entrepreneurs on network dynamics and venture legitimacy. The article is based on the longitudinal survey data of 94 Internet entrepreneurs in Beijing, China. The findings suggest that networking skills of entrepreneurs have positive effects on the structural changes of entrepreneurial networks over time. Further, improvements in networking skills of entrepreneurs are conducive to greater venture legitimacy measured as the number of institutional investors in the new venture. The research and practical implications are discussed.     

Booking horizon forecasting with dynamic updating: A case study of hotel reservation data

A highly accurate demand forecast is fundamental to the success of every revenue management model. As is often required in both practice and theory, we aim to forecast the accumulated booking curve, as well as the number of reservations expected for each day in the booking horizon. To reduce the dimensionality of this problem, we apply singular value decomposition to the historical booking profiles. The forecast of the remaining part of the booking horizon is dynamically adjusted to the earlier observations using the penalized least squares and historical proportion methods. Our proposed updating procedure considers the correlation and dynamics of bookings both within the booking horizon and between successive product instances. The approach is tested on real hotel reservation data and shows a significant improvement in forecast accuracy.     

Using partial least squares in operations management research: A practical guideline and summary of past research

The partial least squares (PLS) approach to structural equation modeling (SEM) has been widely adopted in business research fields such as information systems, consumer behavior, and marketing. The use of PLS in the field of operations management is also growing. However, questions still exist among some operations management researchers regarding whether and how PLS should be used. To address these questions, our study provides a practical guideline for using PLS and uses examples from the operations management literature to demonstrate how the specific points in this guideline can be applied. In addition, our study reviews and summarizes the use of PLS in the recent operations management literature according to our guideline. The main contribution of this study is to present a practical guideline for evaluating and using PLS that is tailored to the operations management field.     

The links between active cooperation and eco-innovation orientation of firms: A multi-analysis study

The environmental orientation of companies is key for firms to gain a competitive advantage against peers. However, the high level of novelty and uncertainty involved with eco-innovations requires additional knowledge and capabilities that go beyond the firm and that can be achieved through cooperation. Thus, it is crucial to analyse how cooperation affects the elements that drive eco-innovation. This study tests the impact of cooperation on the environmental orientation of companies while innovating using structural equation modelling with partial least squares and multigroup analysis and a fuzzy-set qualitative comparative analysis for a sample of Spanish companies. Results suggest that companies that do not cooperate are less eco-innovation-oriented and show lower dependence on external information sources, although their impact on the orientation to product and process innovation is higher. This work leads to some theoretical conclusions and implications for researchers and practitioners.     

Heterogeneous expectations,boom-bust housing cycles,and supply conditions: A nonlinear economic dynamics approach

We combine a standard stock-flow housing market model, incorporating explicit relationships between house prices, the housing stock, and the rent level, with a parsimonious expectation formation scheme of housing market investors, reflecting an evolving mix of extrapolative and regressive expectation rules. The model results in a two-dimensional discrete-time nonlinear dynamical system. Based on realistic parameters, the model is able to generate endogenous boom-bust housing market dynamics with lasting periods of overvaluation and overbuilding. We thus exploit our model to investigate how real forces, in particular supply conditions, interact with expectations-driven housing market fluctuations.     

Explaining vaccination decisions: A system dynamics model of the interaction between epidemiological and behavioural factors

The WHO goal of eradicating measles is delayed by widespread scepticism of parents against the recommended MMR vaccination. In this context, a model of the prevalence of measles that incorporates behavioural aspects is desirable. Parental decisions can be influenced by epidemiological and behavioural factors. The former include vaccination coverage and its impact on the prevalence of the disease. The latter include perceptions of the risk to be infected, which affects vaccination decisions, as well as government campaigns to affect vaccination behaviour, vaccination scares or changes in disease control policies. We develop a model that incorporates both kinds of effects. In particular, we illustrate how incorporating parental response to a change in the prevalence of the disease impacts the outcome of governmental policies aiming to increase the vaccination coverage. While calibrated to measles, this model is also applicable to other childhood diseases, such as pertussis or diphtheria. Different scenarios illustrate the long-term consequences of the interaction between health policies (in particular, vaccination campaigns) or the agenda of social institutions (e.g., drawing attention to specific events to create vaccination scares) and parental reactions. Periodic ups and downs of the disease's prevalence, characteristic of epidemiological feedback, are the consequence of the interaction between parental behaviour and events such as vaccination campaigns or vaccination scares. International and national health authorities, pursuing the fight against measles, may be helped by the potential of the model to provide understanding in the way different predictors of vaccination behaviour interact.     

调适性结构化视角下的信息系统实施——辽河油田通信公司视频会议系统实施案例分析

如今信息化成为企业发展的动力之一,企业信息化是为了提高企业的竞争力而将先进的信息技术应用于企业的管理过程之中,从而降低企业的成本、提高企业的利润,然而企业信息化不仅是信息技术工具的应用,也是一个组织变革的过程。本文以调适性结构化理论（AST）作为理论基础,通过案例研究分析了辽河油田通信公司视频会议系统的应用过程。研究结...     

TACKLING FALSE POSITIVES IN BUSINESS RESEARCH: A STATISTICAL TOOLBOX WITH APPLICATIONS

Serious concerns have been raised that false positive findings are widespread in empirical research in business disciplines. This is largely because researchers almost exclusively adopt the ‘p‐value less than 0.05’ criterion for statistical significance; and they are often not fully aware of large‐sample biases which can potentially mislead their research outcomes. This paper proposes that a statistical toolbox (rather than a single hammer) be used in empirical research, which offers researchers a range of statistical instruments, including a range of alternatives to the p‐value criterion such as the Bayesian methods, optimal significance level, sample size selection, equivalence testing and exploratory data analyses. It is found that the positive results obtained under the p‐value criterion cannot stand, when the toolbox is applied to three notable studies in finance.