Estimating Transition Probabilities from a Time Series of Independent Cross Sections

This paper considers the implementation of a nonstationary, heterogeneous Markov model for the analysis of a binary dependent variable in a time series of independent cross sections. The model, previously considered by M offitt (1993), offers the opportunity to estimate entry and exit transition probabilities and to examine the effects of time-constant and time-varying covariates on the hazards. We show how ML estimates of the parameters can be obtained by Fisher's method-of-scoring and how to estimate both fixed and time-varying covariate effects. The model is exemplified with an analysis of the labor force participation decision of Dutch women using data from the Socio-economic Panel (SEP) study conducted in the Netherlands between 1986 and 1995. We treat the panel data as independent cross sections and compare the employment status sequences predicted by the model with the observed sequences in the panel. Some open problems concerning the application of the model are also discussed.     

On forecasting cointegrated seasonal time series

We analyze periodic and seasonal cointegration models for bivariate quarterly observed time series in an empirical forecasting study. We include both single equation and multiple equation methods for those two classes of models. A VAR model in first differences, with and without cointegration restrictions, and a VAR model in annual differences are also included in the analysis, where they serve as benchmark models. Our empirical results indicate that the VAR model in first differences without cointegration is best if one-step ahead forecasts are considered. For longer forecast horizons however, the VAR model in annual differences is better. When comparing periodic versus seasonal cointegration models, we find that the seasonal cointegration models tend to yield better forecasts. Finally, there is no clear indication that multiple equations methods improve on single equation methods.     

Life cycle assessment in the food supply chain: a case study

This research aims at assessing the environmental impact of the poultry supply chain from cradle to grave using case study research and also life cycle assessment (LCA). While a limited number of generic poultry production LCA studies have been published, fewer yet assess the whole process of a specific organisation, none comparing the increased impact of further processing. Our results show that irrespectively of the impact assessment method utilised, the process of producing portions is considerably higher in total environmental impact due to the extra raw material required to produce the same mass into retail. Our research contributes to the growing number of LCA studies and could be used by practitioners for comparison against national and international averages. From a theoretical point of view, this research provides new insights into the relationship between vertically integrated supply chains and environmental performance which has not been examined in the past.     

Can we reject linearity in an HAR-RV model for the S&P 500? Insights from a nonparametric HAR-RV

This article tests the linearity assumption underlying the popular heterogeneous autoregressive model for realized volatility (HAR-RV). We implement a consistent model specification test that is robust to both distributional and model misspecification. We find that, using a nonparametric HAR-RV (NPHAR-RV), we are unable to reject the null of linearity.     

Power,Intergroup Conflicts and Social Stratification in the United States: What has the Global Crisis Taught us?

Abstract

Drawing on early sociological analyses of how power and intergroup conflicts can affect the development of modern economies, this paper investigates how the recent Global Crisis (GC) has affected the stratification of the US society. The paper argues that the consumerist society has reinforced the historical stratification of social identities with white men in high-paid, high-social status managerial and financial occupations at the top, and black women in low-paid, low-status service occupations at the bottom. This paper calls for a deconstruction of the neoliberal individual into a unique combination of identities in a stratified capitalist society in order to reveal how social stratification has evolved during the GC. The paper finally concludes on the importance of heterogeneous identities in reflecting the diversity of societal and economic interests in order to address the issues of financial stability and sustainability at the corporate and societal levels.     

Carbon efficiency of US colleges and universities: a nonparametric assessment

Under the American College and University Presidents’ Climate Commitment (ACUPCC), institutes of higher education have pledged to pursue a goal of carbon neutrality. We utilize emissions reported under the ACUPCC agreement and a nonparametric data envelopment analysis approach in order to evaluate the relative performance of signatories to the agreement in terms of producing teaching and research with the least greenhouse gas emissions. We find that while many signatory institutions are now producing their desirable outputs relatively efficiently in terms of carbon emissions, there still exists considerable variation in efficiency and potential for improvement. Results of a second stage efficiency change analysis shows evidence of both movement towards the efficiency frontier since signing, and some movement of the frontier itself, though this evidence comes primarily from teaching-focused institutions.