Evidence on nonlinear error correction in money demand: the case of Taiwan

This paper proposes a nonlinear error-correction model based upon smooth transition regression methodology. The model is specified such that the short-run adjustment toward long-run equilibrium is nonlinear and that the error correction is a smooth function of long-run deviation. Empirical results obtained from estimating M2 money demand in Taiwan support the hypothesis of a nonlinear error-correction process and provide better interpretation of change in the demand for money.     

Bold Policies for Economic Justice

The U.S. is characterized by a longstanding pattern of large structural racial inequality that deepens further as a result of economic downturn. Although there have been some improvements in the income gap up until around the mid 1970s, the employment gap, and the racial wealth gap - two dramatic indicators of economic security - remains exorbitant and stubbornly persistent. We offer two race-neutral programs that could go a long way towards eliminating racial inequality, while at the same time providing economic security, mobility and sustainability for all Americans. The first program, a federal job guarantee, would provide the economic security of a job and the removal of the threat of unemployment for all Americans. The second program, a substantial child development account that rises progressively based on the familial asset positioning of the child??s parents, would provide a pathways towards asset security for all Americans regardless of their economic position at birth.     

Entrepreneurial learning from observing role models

Abstract

This study examines entrepreneurial learning through the observation of role models. Adopting an interpretive and inductive approach, and using biographical interviews and life course techniques, the article examines how sixteen entrepreneurs articulate their entrepreneurial learning from role models. The overarching research question ‘How do entrepreneurs learn from observing role models?’ enables illustrating who the role models are (parents, teachers, colleagues, other entrepreneurs), the relevant social contexts (home, education, workplace) and what is learned in relation to entrepreneurial learning tasks (learning about oneself, managing relationships, the business and small business management). The study contributes to developing the social perspectives of entrepreneurial learning by demonstrating the significance of learning from role models in different social contexts and at distinct entrepreneurial stages pre- and post-start-up.     

The discourse of entrepreneurial masculinities (and femininities)

The overarching concern of this paper is the dominant discourse of entrepreneurship portrayed as a form of masculinity. It argues that this discourse is perpetuated by academic research and by media representations of the entrepreneur. The entrepreneur is represented in the media by a narrow range of male stereotypes, whilst women are under-represented and often that representation is linked to domestic concerns. At the same time, academic studies persistently rely on male experience to theorize entrepreneurship, and women are studied in terms of their difference. This enduring discourse results in entrepreneurial femininities being rendered invisible. This paper argues that studies in entrepreneurship should remain alert to the denial and masking of gender. It calls for entrepreneurship researchers to engage with contemporary debates in gender, culture and media studies and proposes a research agenda to challenge the dominant discourses.     

A simple closed-form approximation for the cumulative distribution function of the composite error of stochastic frontier models

This paper derives an analytic closed-form formula for the cumulative distribution function (cdf) of the composite error of the stochastic frontier analysis (SFA) model. Since the presence of a cdf is frequently encountered in the likelihood-based analysis with limited-dependent and qualitative variables as elegantly shown in the classic book of Maddala (Limited-dependent and qualitative variables in econometrics. Cambridge University Press, Cambridge, 1983), the proposed methodology is useful in the framework of the stochastic frontier analysis. We apply the formula to the maximum likelihood estimation of the SFA models with a censored dependent variable. The simulations show that the finite sample performance of the maximum likelihood estimator of the censored SFA model is very promising. A simple empirical example on the modeling of reservation wage in Taiwan is illustrated as a potential application of the censored SFA.     

Understanding How Goal‐striving,Goal Orientation,and Shame Influence Self‐perceptions after Exposure to Models in Advertising

Marketers frequently use advertisements featuring thin models to promote the goal of self‐improvement to consumers. However, many of these appeals lead to detrimental effects on the self‐perceptions of the females who view them. This paper integrates components of goal‐striving theory and social comparison theory to explain consumer response to these advertisements and investigates how goal attainability may mitigate the negative effects of these ads. Additionally, this work investigates how a promotion‐focus goal orientation moderates the effects of the goal‐striving process and provides evidence of the mediating effects of shame. Finally, this work addresses a gap in the literature by examining how the interplay of model size and goal attainability impacts male consumers’ self‐perceptions. Study 1 reveals that high levels of perceived goal attainability mitigate the negative effects of exposure to thin models on self‐perceptions for females. Study 2 demonstrates that a high promotion‐focus goal orientation can lead to more favorable self‐perceptions for female participants exposed to a thin model with attainable goals, but it does not isolate participants from feelings of shame, which mediates the effects of goal attainability on self‐perceptions. Study 3 reveals similar findings for male consumers, but notably finds that shame does not play a significant role in understanding the comparison process for male consumers, suggesting key differences in the comparison processes between sexes.     

Using Aggregate Time Series Variables to Forecast Notices of Default

This paper emphasizes the economic variables and data used to model notices of default in California. Forecast models are notoriously complicated and require sophisticated software to run. Few businesses, particularly small enterprises, have the necessary resources to engage in large-scale model building. Datasets can be difficult and expensive to obtain and usually require significant analysis. The paper focuses on methodology to give the model a general appeal.     

A new approach to estimating the metafrontier production function based on a stochastic frontier framework

This paper proposes a new two-step stochastic frontier approach to estimate technical efficiency (TE) scores for firms in different groups adopting distinct technologies. Analogous to Battese et al. (J Prod Anal 21:91–103, 2004), the metafrontier production function allows for calculating comparable TE measures, which can be decomposed into group specific TE measures and technology gap ratios. The proposed approach differs from Battese et al. (J Prod Anal 21:91–103, 2004) and O’Donnell et al. (Empir Econ 34:231–255, 2008) mainly in the second step, where a stochastic frontier analysis model is formulated and applied to obtain the estimates of the metafrontier, instead of relying on programming techniques. The so-derived estimators have the desirable statistical properties and enable the statistical inferences to be drawn. While the within-group variation in firms’ technical efficiencies is frequently assumed to be associated with firm-specific exogenous variables, the between-group variation in technology gaps can be specified as a function of some exogenous variables to take account of group-specific environmental differences. Two empirical applications are illustrated and the results appear to support the use of our model.     

Calling recessions in real time

This paper surveys efforts to automate the dating of business cycle turning points. Doing this on a real time, out-of-sample basis is a bigger challenge than many academics might assume, due to factors such as data revisions and changes in economic relationships over time. The paper stresses the value of both simulated real-time analysis — looking at what the inference of a proposed model would have been using data as they were actually released at the time — and actual real-time analysis, in which a researcher stakes his or her reputation on publicly using the model to generate out-of-sample, real-time predictions. The immediate publication capabilities of the internet make the latter a realistic option for researchers today, and many are taking advantage of it. The paper reviews a number of approaches to dating business cycle turning points and emphasizes the fundamental trade-off between parsimony — trying to keep the model as simple and robust as possible — and making full use of the available information. Different approaches have different advantages, and the paper concludes that there may be gains from combining the best features of several different approaches.