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This paper studies the empirical application of an asset pricing model derived from the irrational individual behavior of loss aversion. Previous research using loss aversion asset pricing finds conclusive evidence that estimations match market equity premium and volatility using simulation data. We find that within its empirical application, the estimated errors are comparable to errors estimated from the capital asset pricing model. This study of the correlations between rational and irrational asset pricing model from the empirical results finds validity for both estimated values. Finally, we see the importance of cultures, economic development and financial development on asset pricing through an empirical examination of five pacific-basin countries in the estimation of asset pricing models.

The purpose of this project was to compare the cost of transportation engineering design services provided by private contractors versus services provided by state transportation agency staff for the Louisiana Department of Transportation and Development (LaDOTD). Due to shrinking budgets, staff cuts, and a trend toward privatization, state transportation agencies now outsource the majority of the services they provide. The merits of doing so, however, have been difficult to discern for lack of “apples-to-apples” comparisons. For engineering design services, this problem is particularly acute due to the uniqueness of many projects (e.g., a bridge over the Mississippi river). A simulation approach was used in this study to make “apples-to-apples” comparisons for 39 design projects, 22 in-house projects and 17 consultant projects. For each in-house design project, the cost was estimated had the work been done by a consulting firm. Similarly, for each consultant design project, the cost was estimated had the work been done by in-house staff. The result of the study was that in-house design costs were cheaper by an average of 17 to 19 percent.

We take Cumulative Prospect Theory (CPT) seriously by rigorously estimating structural models using the full set of CPT parameters. Much of the literature only estimates a subset of CPT parameters, or more simply assumes CPT parameter values from prior studies. Our data are from laboratory experiments with undergraduate students and MBA students facing substantial real incentives and losses. We also estimate structural models from Expected Utility Theory (EUT), Dual Theory (DT), Rank-Dependent Utility (RDU), and Disappointment Aversion (DA) for comparison. Our major finding is that a majority of individuals in our sample locally asset integrate. That is, they see a loss frame for what it is, a frame, and behave as if they evaluate the net payment rather than the gross loss when one is presented to them. This finding is devastating to the direct application of CPT to these data for those subjects. Support for CPT is greater when losses are covered out of an earned endowment rather than house money, but RDU is still the best single characterization of individual and pooled choices. Defenders of the CPT model claim, correctly, that the CPT model exists “because the data says it should.” In other words, the CPT model was borne from a wide range of stylized facts culled from parts of the cognitive psychology literature. If one is to take the CPT model seriously and rigorously then it needs to do a much better job of explaining the data than we see here.

The issue of export instability exerts an enduring fascination for economists with an interest in the area of economic development. Over several decades a voluminous literature has emerged embracing debates on the domestic consequences and on the causes of export instability. The purpose here is to examine these debates and an attempt is made to set out different theoretical stances, to classify and examine empirical findings, and to indicate the directions in which the debates have moved. Such a statement of a review article's purpose is, of course, incomplete without more specific delineation of the boundaries within which the general objectives are pursued. Here that delineation has three facets.

Purpose – Partial least squares (PLS) path modeling has become a pivotal empirical research method in international marketing. Owing to group comparisons' important role in research on international marketing, we provide researchers with recommendations on how to conduct multigroup analyses in PLS path modeling.

Methodology/approach – We review available multigroup analysis methods in PLS path modeling and introduce a novel confidence set approach. A characterization of each method's strengths and limitations and a comparison of their outcomes by means of an empirical example extend the existing knowledge of multigroup analysis methods. Moreover, we provide an omnibus test of group differences (OTG), which allows testing the differences across more than two groups.

Findings – The empirical comparison results suggest that Keil et al.'s (2000) parametric approach can generally be considered more liberal in terms of rendering a certain difference significant. Conversely, the novel confidence set approach and Henseler's (2007) approach are more conservative.

Originality/value of paper – This study is the first to deliver an in-depth analysis and a comparison of the available procedures with which to statistically assess differences between group-specific parameters in PLS path modeling. Moreover, we offer two important methodological extensions of existing research (i.e., the confidence set approach and OTG). This contribution is particularly valuable for international marketing researchers, as it offers recommendations regarding empirical applications and paves the way for future research studies aimed at comparing the approaches' properties on the basis of simulated data.

In this chapter, I detail a procedure for incorporating status characteristics with more than two ordered states, or graded status characteristics, into status characteristics theory. I revise theoretical definitions and assumptions accordingly. The new procedure adds a weighting function to the existing mathematical structure of the theory. I show that estimates using the new procedure are consistent with findings drawn from four experiments that were run in the standard setting for status characteristics theory. I also show that the procedure explains more variation and improves global model fit when predicting expectations using newly collected vignette data. I conclude with a general discussion of the procedures and implications for other expectation states theories and for research conducted outside the laboratory.

The purpose of this article, starting from linear regression, was to estimate a switching regression model, nonparametric model and generalized additive model as a semi-parametric model, perform function estimation with multiple nonlinear estimation methods and conduct comparative analysis of their predictive accuracy. The theoretical importance of estimating hedonic functions using a nonlinear function form has been pointed out in ample previous research (e.g. Heckman et al. (2010).

The distinctive features of this study include not only our estimation of multiple nonlinear model function forms but also the method of verifying predictive accuracy. Using out-of-sample testing, we predicted and verified predictive accuracy by performing random sampling 500 times without replacement for 9,682 data items (the same number used in model estimation), based on data for the years before and after the year used for model estimation.

As a result of estimating multiple models, we believe that when it comes to hedonic function estimation, nonlinear models are superior based on the strength of predictive accuracy viewed in statistical terms and on graphic comparisons. However, when we examined predictive accuracy using out-of-sample testing, we found that the predictive accuracy was inferior to linear models for all nonlinear models.

In terms of the reason why the predictive accuracy was inferior, it is possible that there was an overfitting in the function estimation. Because this research was conducted for a specific period of time, it needs to be developed by expanding it to multiple periods over which the market fluctuates dynamically and conducting further analysis.

Many studies compare predictive accuracy by separating the estimation model and verification model using data at the same point in time. However, when attempting practical application for auto-appraisal systems and the like, it is necessary to estimate a model using past data and make predictions with respect to current transactions. It is possible to apply this study to auto-appraisal systems.

It is recognized that housing price fluctuations caused by the subprime crisis had a massive impact on the financial system. The findings of this study are expected to serve as a tool for measuring housing price fluctuation risks in the financial system.

While the importance of nonlinear estimation when estimating hedonic functions has been pointed out in theoretical terms, there is a noticeable lag when it comes to testing based on actual data. Given this, we believe that our verification of nonlinear estimation’s validity using multiple nonlinear models is significant not just from an academic perspective – it may also have practical applications.

The chapter estimates the cost of maintaining a child, at different ages, the cost of being single, and the cost of additional adults present in a family, with the aim of making comparable the income levels of different households. The study investigates the issue of econometric identification of equivalence scales within a demand system modified to include demographic characteristics consistently with economic theory. It shows that a robust estimation of equivalence scales must take into formal consideration the problem of econometric identification. The estimate also puts forward all-encompassing demographic specifications to identify costs due to differences in needs, household lifestyles, and economies of scale.

A simulation methodology is applied to the loan loss reserve process of an agricultural lender. Weaknesses of the point‐estimate approach to estimating loan loss reserves are addressed with a “bottom‐up” model. Modeling includes consideration of the producer’s and the lender’s diversification efforts. Implementation of this model will provide the lender a better understanding of the institution’s portfolio risk, as well as the credit risk associated with each loan. This study compares the lender’s loan loss estimates to a distribution of losses with associated probabilities. The comparative results could provide the lender a basis for setting probability levels for determining the regulatory required level of loan loss reserve.

In the land reform literature an important issue has been the effect land redistribution has on the allocation of resources and agricultural productivity. Generally, monopolistic behaviour of plantation owners with respect to land has prevailed since control of the land has generated monopsonistic power with respect to labour. This behaviour would result in a lesser degree of land utilization by large land owners and a lower value of marginal product for labour on small farms than on large farms. The rural labour force is effectively left with no options for employment other than the plantation sector. The monopolization of land causes a higher land/labour ratio for large operations than for small farmers. In a competitive market with tillable land held constant, the value of marginal product for labour for the two farm classes would be equal. Further, monopsony theory reveals that output and employment would be lower than in a competitive market.