Assumption Of Heteroscedasticity Research Articles

Pengaruh Gender, Kompleksitas Tugas, Tekanan Ketaatan, Pengalaman Auditor Terhadap Audit Judgement

The purpose of this research was to examine the impact of gender, task complexity, obedience pressure, experience of auditors towards Audit Judgement. The object the auditors who works in the Public Accountant firms in Jakarta and Tangerang which have at least 3 years experience or have position as senior auditor. Data that had been analyzed were 110 questionnaires and the data were primer data. The type in this research is causal study and the sampling techniques that used is convenience sampling. The method that used is multiple regression analysis. The data that had been used from the entire questionnaires were valid. Reliability test results show questionnaires in this study is reliable. Normality test results showed all variables were normally distributed. Data used indicate the absence of the classical assumption of heteroscedasticity and non-occurrence of symptoms multicoloniarity between variables. Hypothesis test results indicate a strong correlation between variables and adjusted R-square value of 34.6%. In partial test only complexity of tasks that affect theentire audit judgment and all variables influential simultaneously.
 Keywords: Audit Experience, Audit Judgement, Gender, Obedience Pressure, Task Complexity

Importance of modelling heteroscedasticity of survey index data in fishery stock assessments

AbstractMany fish stock assessments use a survey index and assume a stochastic error in the index on which a likelihood function of associated parameters is built and optimized for the parameter estimation. The purpose of this paper is to evaluate the assumption that the standard deviation for the difference in the log-transformed index is approximately equal to the coefficient of variation of the index, and also to examine the homo- and heteroscedasticity of the errors. The traditional practice is to assume a common variance of the index errors over time for estimation convenience. However, if additional information is available about year-to-year variability in the errors, such as year-to-year coefficient of variation, then we suggest that the heteroscedasticity assumption should be considered. We examined five methods with the assumption of a multiplicative error in the survey index and two methods with that of an additive error in the index: M1, homoscedasticity in the multiplicative error model; M2, heteroscedasticity in the multiplicative error model; M3, M2 with approximate weighting and an additional parameter for scaling variance; M4–M5, pragmatic practices; M6, homoscedasticity in the additive error model; M7, heteroscedasticity in the additive error model. M1–M2 and M6–M7 are strictly based on statistical theories, whereas M3–M5 are not. Heteroscedasticity methods M2, M3, and M7 consistently outperformed the other methods. However, we select M2 as the best method. M3 requires one more parameter than M2. M7 has problems arising from the use of the raw scale as opposed to the logarithm transformation. Furthermore, the fitted survey index in M7 can be negative although its domain is positive.

Are GCC stock markets predictable?

Weak-form efficiency in the stock markets of the Gulf Cooperation Council is examined using daily, weekly, and monthly index data for the 10-year period 2000–2009. Various variance ratio test specifications with specific homo- and heteroscedasticity assumptions found evidence of nonlinear dependence for the daily data, supporting the evidence in favor of a rejection of the random walk. A correction procedure for thin and nonsynchronous trading was applied but failed to produce significantly different results. Following an ARCH based model building procedure, conditional heteroscedasticity models are applied to the log return series. Significant differences in forecasting performance cannot be detected. The random walk hypothesis is generally rejected for daily but differences appear across markets using weekly and monthly data. The increased involvement of foreign institutional investors may play a role in the increased serial correlation in stock returns in the most recent period.

Relaxing Heteroscedasticity Assumptions in Area‐Yield Crop Insurance Rating

This article focuses on the effect of differing heteroscedasticity assumptions on derived premium rates of area‐yield crop insurance. Tests of the proportional and absolute heteroscedasticity assumptions are conducted using both in‐sample and out‐of‐sample measures. Our results suggest that arbitrarily imposing a specific form of heteroscedasticity or homoscedasticity in insurance rate calculations limits actuarial soundness. Our results have practical implications for the federal crop insurance programs, as we reject the traditional rating assumptions for many cotton regions and lower‐yielding/higher‐risk corn and soybean counties but not in the heart of the Cornbelt.

Introduction of a new measure for detecting poor fit due to omitted nonlinear terms in SEM

The model chi-square that is used in linear structural equation modeling compares the fitted covariance matrix of a target model to an unstructured covariance matrix to assess global fit. For models with nonlinear terms, i.e., interaction or quadratic terms, this comparison is very problematic because these models are not nested within the saturated model that is represented by the unstructured covariance matrix. We propose a novel measure that quantifies the heteroscedasticity of residuals in structural equation models. It is based on a comparison of the likelihood for the residuals under the assumption of heteroscedasticity with the likelihood under the assumption of homoscedasticity. The measure is designed to respond to omitted nonlinear terms in the structural part of the model that result in heteroscedastic residual scores. In a small Monte Carlo study, we demonstrate that the measure appears to detect omitted nonlinear terms reliably when falsely a linear model is analyzed and the omitted nonlinear terms account for substantial nonlinear effects. The results also indicate that the measure did not respond when the correct model or an overparameterized model were used.

Tranquil and crisis windows, heteroscedasticity, and contagion measurement: MS-VAR application of the DCC procedure

The key objective of this study is to show that two potential shortcomings of the Determinant of Change in Covariance (DCC) matrix procedure of Rigobon (2003 Rigobon, R. 2003. On the measurement of the international propagation of shocks: is the transmission stable?. Journal of International Economics, 61: 261–83. [Crossref], [Web of Science ®] , [Google Scholar]), namely with the arbitrary determination of the windows, i.e. tranquil and crisis periods and the violation of its heteroscedasticity assumption under the null, can be simultaneously addressed via a simple incorporation of a Markov-switching vector autoregressive approach into the overall DCC procedure. To demonstrate this, we revisit the period around the time of the East Asian crises using daily stock exchange of Indonesia, Malaysia, Philippines, Thailand, Singapore, Korea, Hong Kong and Taiwan, and test whether there is a significant break or discontinuity in the stock exchange returns of the eight East Asian markets during crisis periods, especially around the time of the 1997 financial crises. In contrast to that of Rigobon (2003 Rigobon, R. 2003. On the measurement of the international propagation of shocks: is the transmission stable?. Journal of International Economics, 61: 261–83. [Crossref], [Web of Science ®] , [Google Scholar]), our results show that the propagation of shocks shifted significantly starting with the onset of the sharp decline in the Hong Kong stock market.

A further investigation of the link between trade and income

The link between openness and income has received increasing attention as countries try to justify their trade-promoting policies. Recent work of Frankel & Romer (1999) examines the effect of trade on income. We explore how the estimates of the trade effect change when we relax their assumption of heteroscedasticity in the bilateral trade equation they use to construct the instrument for the IV regression. Because the instrument is constructed through a nonlinear transformation, unequal disturbance variances imply inconsistency and not just inefficiency of the Frankel–Romer estimates. We find a smaller positive effect of trade than that found by Frankel & Romer.

Estimation of a Doubly Heteroscedastic Stochastic Frontier Cost Function

This article extends the results obtained by Caudill, Ford, and Cropper in estimating and testing stochastic frontier cost functions in the presence of heteroscedastic inefficiency using cross-section data. It suggests the estimation of the model under the assumption of heteroscedasticity in both random terms. This avoids any possible misspecification bias and the use of incorrect tests. The same data as used by Caudill et al. supports the new specification. Moreover, we find that firm-specific inefficiency measures are extremely sensitive to the proposed correction for heteroscedasticity.

A study of several new and existing tests for heteroscedasticity in the general linear model

Several optimum non-parametric tests for heteroscedasticity are proposed and studied along with the tests introduced in the literature in terms of power and robustness properties. It is found that all tests are reasonably robust to the Ordinary Least Squares (OLS) residual estimates, number and character of the regressors. Only a few are robust to both the distributional and independence assumptions about the errors. The power of tests can be improved with the OLS residual estimates, the increased sample size and the variability of the regressors. It can be substantially reduced if the observations are not normally distributed, and may increase or decrease if the errors are dependent. Each test is optimum to detect a specific form of heteroscedasticity and a serious power loss may occur if the underlying heteroscedasticity assumption in the data generation deviates from it.

Tractors in Spain: A Logistic Analysis

This paper presents an attempt to make reliable projections of the stock of agricultural tractors in Spain. The approach to be followed is that of fitting a logistic trend to the historical data for the period 1951-1976. A set of possible trend curves is presented and their properties discussed; reasons for choosing the logistic trend are given. Preliminary estimates for the parameters of the logistic are obtained by means of the relatively unsophisticated three point method. Alternative heteroscedasticity assumptions in the data are explored with the help of a non-linear regression. Final estimates are obtained by means of a non-linear optimization algorithm. The influence of economic variables and government policies is traced in the residuals.