USING THE RANDOM PARAMETERS LOGIT MODEL TO COMBINE REVEALED AND STATED PREFERENCE DATA

Recent literature has combined Revealed (RP) and Stated Preference (SP) data in the Multinomial Logit Model (MNL) to estimate the value of environmental goods. However, emerging research has identified that a limitation of the MNL is the assumption of Independently and Identically Distributed (IID) errors, resulting in inaccurate model predictions and inconsistent utility parameters. Our analysis applies an alternative method to combine RP and SP data that takes into account the heterogeneity in both the observable and unobservable components of utility. This allows us to test whether such heterogeneity has an important effect on predicting behavioral choices.Revealed and Stated Preference Data, Scale Factor, Environmental Economics and Policy,

Uncertainty and Human Capital Decisions: Traditional Valuation Methods and Real Options Logic

As the importance of human capital increases in organizations, so does the need to develop more sophisticated financial valuation models. This paper reviews some of the major traditional financial decision making models used in costing employment mode choices. It then introduces the real options valuation approach for costing such choices. The advantage of the real options model is demonstrated to build flexibility into employment decisions