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Choice under risk has a large stochastic (unpredictable) component. This chapter examines five stochastic models for binary discrete choice under risk and how they combine with “structural” theories of choice under risk. Stochastic models are substantive theoretical hypotheses that are frequently testable in and of themselves, and also identifying restrictions for hypothesis tests, estimation and prediction. Econometric comparisons suggest that for the purpose of prediction (as opposed to explanation), choices of stochastic models may be far more consequential than choices of structures such as expected utility or rank-dependent utility.

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.

This paper investigates how well regulator examinations predict bank failures and how best to incorporate examination information into an econometric model of time‐to‐failure. We estimate proportional hazard models with time‐varying covariates and find that examiner ratings help explain the failure hazard. Both the overall rating of a bank's condition and management, i.e., the composite CAMELS rating, and ratings of specific components contain information. In addition, we find that the marginal “effect” of ratings is non‐linear, in that the impact of a rating downgrade on the hazard is larger, the weaker a bank's initial rating.

This study investigates the impact of the enhanced continuous disclosure regime introduced in December 2002 on several measures of information risk in NZX‐listed stocks. We employ two microstructure models and an intraday data set to measure information risk in a sample of 71 stocks. Our empirical results show that the reforms enacted in December 2002 had no significant effect on either the level of information‐based trading or the adverse selection component of market spreads in our sample of NZX‐listed stocks.

The purpose of this paper is to show that multivariate t-distribution assumption provides a better description of stock return data than multivariate normality assumption.

The EM algorithm is applied to solve the statistical estimation problem almost analytically, and the asymptotic theory is provided for inference.

The authors find that the multivariate normality assumption is almost always rejected by real stock return data, while the multivariate t-distribution assumption can often be adequate. Conclusions under normality vs under t can be drastically different for estimating expected returns and Jensen’s αs, and for testing asset pricing models.

The results provide improved estimates of cost of capital and asset moment parameters that are useful for corporate project evaluation and portfolio management.

The authors proposed new procedures that makes it easy to use a multivariate t-distribution, which models well the data, as a simple and viable alternative in practice to examine the robustness of many existing results.

An understanding of the determination of real wages is crucial in analysing the determination of the natural rate of unemployment or NAIRU. Uses cointegration techniques to examine a core theoretical model of the long‐run determinants of real wages involving unit labour costs, unemployment, union power and the replacement ratio. Considers the different measures of union power and the duration of unemployment and alternative specifications involving the “wedge” but a robust cointegrating relationship is not found. These results can be interpreted in several ways: concepts such as union power or the “generosity” of benefits may be measured inadequately; the theoretical understanding of the long‐run determinants of real earnings may remain seriously incomplete; alternatively the short spans of data examined may be insufficient for the application of cointegration techniques, although the sample sizes examined here are fairly typical of most macroeconomic time series.

This paper aims to develop a corporate financial distress model for Indian listed companies using financial and non-financial parameters by using a conditional logit regression technique.

This study used a sample of 96 companies, of which 48 were declared sick between 2014 and 2016. The sample was divided into a training sample and a testing sample. The variables for the study included nine financial variables and four non-financial variables. The models were developed using financial variables alone as well as combining financial and non-financial variables. The performance of the test sample was measured with confusion matrix, sensitivity, specificity, precision, F-measure, Types 1 and 2 error.

The results show that models with financial variables had a prediction accuracy of 85.19 and 86.11 per cent, whereas models with a combination of financial and non-financial variables predict with comparatively better accuracy of 89.81 and 91.67 per cent. Net asset value, long-term debt–equity ratio, return on investment, retention ratio, age, promoters holdings pledged and institutional holdings are the critical financial and non-financial predictors of financial distress.

This study contributes to the financial distress prediction literature in different ways. First, there have been, until now, few studies in the area of financial distress prediction in the Indian context. Second, business failure studies in the past have used only financial variables. The authors have combined financial and non-financial variables in their model to increase predictive ability. Thirdly, in most earlier studies, variable institutional holdings were found to affect financial distress negatively. In contrast, the authors found this parameter to be positively significant to the financial distress of the company. Finally, there have hitherto been few studies that have used promoter holdings pledged (PHP) or pledge ratio. The authors found this variable to influence business failure positively.

The role of energy efficiency and particularly energy performance certificates (EPCs) has emerged as a topical and important aspect of real estate markets. Various studies have been carried out investigating the perceived capitalisation effects of energy efficiency on property prices. There, however, remains divergence of opinion whether the capitalisation effect is truly in existence with extant research showing differing magnitudes of effects, if any. To date, no study (that the authors are aware of) has investigated the nature of the transition between EPC bands and price effects. The purpose of this study is to add to the research of the energy efficiency of housing to examine the nature of the likelihood of property characteristics being associated with higher EPC scores and value.

This research undertakes a suite of methodological tests to investigate the more latent relationships between EPC bands and pricing behaviour using 3,797 achieved sales prices within the Belfast housing market. Binary logit regression models are specified in conjunction with a Polytomous Universal Model to examine the likelihood of EPC bands falling within a particular property type and the likelihood of any pricing effects.

The findings show the differing property types to comprise very distinct and complex relationships in terms of price and EPC banding. The binary logit model estimations for both terrace properties and apartments reveal an increased likelihood to obtain higher EPC scores, with the semi-detached sector displaying a “mixed effect” with detached property revealing decreased probability of having superior energy performance and decreased likelihood of having poorer energy performance. The ordinal model estimations indicate that sales price comprises no relationship with energy performance, inferring that there is no increased probability of an increase in sales price with higher EPC rating.

This research offers new insights and focus on achieving a better understanding of the nexus between energy performance and property characteristics using alternative modelling approaches. This provides more exploratory insights into the complex relationships and offers awareness for policy discourse in terms of targeting properties which will tend to be poorer in energy efficiency.

The main objective of this study is to examine whether firms follow the financing hierarchy as suggested by the Pecking Order Theory (POT). The External Funds Needed (EFN) model offers a financing hierarchy that can be used for examining the POT. As far as the EFN considers growth of sales as a driver for changing capital structure, it follows that shall firms plan for a sustainable growth of sales, a sustainable financing can be reached and maintained. This study uses data about the firms listed in two indexes: Dow Jones Industrial Average (DJIA30) and NASDAQ100. The data cover quarterly periods from June 30, 1999, to March 31, 2012. The methodology includes (a) cointegration analysis in order to test for model specification and (b) causality analysis in order to show the generic and mutual associations between the components of EFN. The results conclude that (a) in the majority of the cases, firms plan for an increase in growth sales but not necessarily to approach sustainable rate; (b) in cases of observed and sustainable growth of sales, firms reduce debt financing persistently; (c) firms use equity financing to finance sustainable growth of sales in the long run only, while in the short run, firms use internal financing, that is, retained earnings as a flexible source of financing; and (d) the EFN model is quite useful for examining the hierarchy of financing. This study contributes to the related literature in terms of utilizing the properties of the EFN model in order to examine the practical aspects of the POT. These practical considerations are extended to examine the use of the POT in cases of observed and sustainable growth rates. The findings contribute to the current literature that there is a need to offer an adjustment to the financing order suggested by the POT. Equity financing is the first source of financing current and sustainable growth of sales, followed by retained earnings, and debt financing is the last resort.

Research on strategic choices available to the firm are often modeled as a limited number of possible decision outcomes and leads to a discrete limited dependent variable. A limited dependent variable can also arise when values of a continuous dependent variable are partially or wholly unobserved. This chapter discusses the methodological issues associated with such phenomena and the appropriate statistical methods developed to allow for consistent and efficient estimation of models that involve a limited dependent variable. The chapter also provides a road map for selecting the appropriate statistical technique and it offers guidelines for consistent interpretation and reporting of the statistical results.