Problems with extending conclusions between Bowman's paradox and Beta's death

This issue of Omega contains a commentary by P.L. Brockett, W.W. Cooper, K.H. Kwon, and T.W. Ruefli on the review of Bowman's paradox by Nickel and Rodríguez, published in the February 2002 issue of Omega. In their commentary, the authors describe an article, published in the 1992 issue of Decision Sciences but not covered by the review, and claim that they had previously overcome three of the outstanding problems noted in Nickel and Rodríguez's review. This reply to the commentary proves that the conclusions drawn in the review by Nickel and Rodríguez are relevant in spite of the Brockett et al. arguments against them. In this reply, we show that the paper by Brockett et al. neither explains Bowman's paradox nor resolves its underlying problems. First, the definitions of risk and return measures are mathematically linked, and second, a cross-sectional methodology is used. We also provide our opinion on what would be necessary to bear in mind in order to extend any conclusion from Bowman's paradox to beta's death and vice versa

Survival as a success in the face of a scarcity of resources

From institutional, resource dependence and organizational ecology perspectives, there are two initial requirements for organizational survival: 1) there are sufficient resources in the niche, and 2) the organization can obtain these resources. A new concept, saturation, is created to measure the scarcity of resources by analyzing its influence on survival. However, organizational success also depends on organizational characteristics, which can hinder the securing of the resources necessary for survival. This article researches ownership structure as an organizational characteristic. These influences are tested utilizing data from a population of 1298 Spanish olive oil mills

New size measurements in population ecology

In organizational ecology, we find the analysis of the impact exerted by competition between populations on vital ratios to be relatively under-developed. This paper intends to address this issue by developing new competition measurements whose common denominator is to give importance to organizational size. The application of these measurements in the case of competition between organizational forms in a population and their impact on mortality rates, demonstrates the usefulness of modelling competition on them. More specifically, results show how competition levels between firms in a population can be more adequately estimated when rival population mass is used (that is, the aggregate size of the organizations of which it is made up)

Is the risk-return paradox still alive?

To date, the validity of empirical Bowman's paradox papers that employ mean-variance approach for testing the risk/return relationship are inherently unverifiable and their results cannot be generalized. However, this problem can be overcome by developing an econometric model with two fundamental characteristics. The first one is the use of a time series model for each firm, avoiding the traditional cross-sectional analysis. The other one is to estimate a model with a single variable (the firm rate of return), but whose expectation and variance are mathematically related according to behavioral theories hypotheses, forming a heterocedastic model similar to "GARCH". Our results agree with behavioral theories and show that these theories can also be carry out with market measures

IS THE RISK-RETURN PARADOX STILL ALIVE?

To date, the validity of empirical Bowman’s paradox papers that employ mean-variance approach for testing the risk/return relationship are inherently unverifiable and their results cannot be generalized. However, this problem can be overcome by developing an econometric model with two fundamental characteristics. The first one is the use of a time series model for each firm, avoiding the traditional cross-sectional analysis. The other one is to estimate a model with a single variable (the firm rate of return), but whose expectation and variance are mathematically related according to behavioral theories hypotheses, forming a heterocedastic model similar to “GARCH”. Our results agree with behavioral theories and show that these theories can also be carry out with market measures.

Consistent estimation of conditional conservatism

In this paper, we propose an econometric model that presents three advantages in relation to the Basu model: (1) it is robust to the aggregation problem; that is, we prove that the Basu model produces inconsistent estimations of conditional conservatism and that this problem is solved with our proposal; (2) it can produce firm-specific measures of conservatism by using time-series; and (3) it completes the understanding of the intercept in the Basu model by breaking it down between unconditional conservatism and the reversion of the differences between market and book values of equity. In other words, we can provide firm-specific measures of both conditional and unconditional conservatism with the same model. We demonstrate all these theoretical assertions using simulated dataAccounting conservatism, Conditional conservatism, Unconditional conservatism, The Basu model, Aggregation effect

Author's Reply: Problems With Extending Conclusions Between Bowman's Paradox and Beta's Death.

This issue of Omega contains a commentary by P.L. Brockett, W.W. Cooper, K.H. Kwon, and T.W. Ruefli on the review of Bowman's paradox by Nickel and Rodríguez, published in the February 2002 issue of Omega. In their commentary, the authors describe an article, published in the 1992 issue of Decision Sciences but not covered by the review, and claim that they had previously overcome three of the outstanding problems noted in Nickel and Rodríguez's review. This reply to the commentary proves that the conclusions drawn in the review by Nickel and Rodríguez are relevant in spite of the Brockett et al. arguments against them. In this reply, we show that the paper by Brockett et al. neither explains Bowman's paradox nor resolves its underlying problems. First, the definitions of risk and return measures are mathematically linked, and second, a cross-sectional methodology is used. We also provide our opinion on what would be necessary to bear in mind in order to extend any conclusion from Bowman's paradox to beta's death and vice versa.Risk and return measures; Kinds of risk; Risk adverse; Risk prone;

PROBLEMS WITH EXTENDING CONCLUSIONS BETWEEN BOWMAN’S PARADOX AND BETA’S DEATHK

This issue of Omega contains a commentary by P.L. Brockett, W.W. Cooper, K.H. Kwon, and T.W. Ruefli on the review of Bowman’s paradox by Nickel and Rodríguez, published in the February 2002 issue of Omega. In their commentary, the authors describe an article, published in the 1992 issue of Decision Sciences but not covered by the review, and claim that they had previously overcome three of the outstanding problems noted in Nickel and Rodríguez’s review. This reply to the commentary proves that the conclusions drawn in the review by Nickel and Rodríguez are relevant in spite of the Brockett et al. arguments against them. In this reply, we show that the paper by Brockett et al. neither explains Bowman’s paradox nor resolves its underlying problems. First, the definitions of risk and return measures are mathematically linked, and second, a cross-sectional methodology is used. We also provide our opinion on what would be necessary to bear in mind in order to extend any conclusion from Bowman’s paradox to beta’s death and vice versa.

A review of research on the negative accounting relationship between risk and return: Bowman's paradox.

A cornerstone in finance theory continues to be the positive relationship between risk and return in spite of Fama and French (The Journal of Finance 47(2) (1992) 427–65) and several later papers finding no relationship between the two variables. Twelve years earlier, Bowman (Sloan Management Review 1980, pp. 17–31) studied the same relationship from organization theory, achieving similar results with accounting data, and developing a whole research stream known as “Bowman's paradox”. This stream has contributed to some curious and interesting ideas that could also be applied to other different streams: new risk measures, managerial goal selection, response to the decline in the organization, diversification strategy on risk and return, among others. Similar to the financial stream, a number of researchers have tried to study this issue from the strategic management perspective. Their inconclusive results have generated a considerable controversy, keeping this research stream alive. In this work, we describe and explore this phenomenon from “Bowman's paradox”, theoretical explanations, criticisms and future orientations.Risk–return relationship; Bowman's paradox; Accounting risk;

Overcoming the lack of identification in Bowman's Paradox tests : Heteroskedaski behavior of returns.

To date, the validity of the empirical tests that employ the mean–variance approach for testing the risk– return relationship in the research stream named Bowman’s paradox is inherently unverifiable, and the results cannot be generalized. However, this problem can be solved by developing an econometric model with two fundamental characteristics: first, the use of a time-series model for each firm, avoiding the traditional cross-sectional analysis; and, second, the estimation of a model with a single variable (firm’s rate of return), whose expectation and variance are mathematically related according to behavioral theories, forming a heteroskedastic model similar to GARCH (generalized autoregressive conditional heteroskedasticity). The application of this methodology for Bowman’s paradox is new, and its main advantage is that it solves the previous criticism of the lack of identification. With this model, we achieve results that agree with behavioral theories and show that these theories can also be carried out with market measures.---------------------------------------------------------------------------------Los contrastes empíricos sobre la relación entre la rentabilidad y riesgo dentro de la corriente de investigación conocida como la Paradoja de Bowman realizados hasta la fecha, que están basados en el binomio media-varianza, presentan el problema de su no verificabilidad y la imposibilidad de generalizar sus resultados. Este problema puede resolverse usando un modelo econométrico definido por dos características principales: primero, se usará un modelo de series temporales específico para cada empresa, evitando los problemas del tradicional análisis de corte transversal; y, segundo, en el modelo se estimará una única variable (la rentabilidad de la empresa) cuyos momentos esperanza y varianza estarán relacionados matemáticamente de acuerdo con lo previsto en las Teorías del Comportamiento, conformando un modelo similar a los modelos GARCH (modelos autorregresivos de heterocedasticidad condicional generalizados). La aplicación de esta metodología en la investigación sobre la Paradoja de Bowman es nueva y su principal ventaja es que resuelve los problemas de falta de identificación señalados en la literatura previa. Los resultados obtenidos con este modelo apoyan lo previsto por las Teorías del Comportamiento y muestran que los postulados de estas teorías pueden extenderse al ámbito de los mercados de capitales.Bowman's paradox; Econometric modelling; Risk-return relationship; Time-series model;