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Journal articles on the topic 'Durbin-Watson test'

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Published: 4 June 2021

Last updated: 25 April 2022

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1

Inder, Brett. "An Approximation to the Null Distribution of the Durbin-Watson Statistic in Models Containing Lagged Dependent Variables." Econometric Theory 2, no. 3 (December 1986): 413–28. http://dx.doi.org/10.1017/s0266466600011683.

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We consider testing for autoregressive disturbances in the linear regression model with a lagged dependent variable. An approximation to the null distribution of the Durbin—Watson statistic is developed using small-disturbance asymptotics, and is used to obtain test critical values. We also obtain nonsimilar critical values for the Durbin—Watson and Durbin's h and t tests. Monte Carlo results are reported comparing the performances of the tests under the null and alternative hypotheses. The Durbin–Watson test is found to be more powerful and to perform more consistently than either of Durbin's tests under Ho.

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2

King, Maxwell L., and Merran A. Evans. "Locally Optimal Properties of the Durbin-Watson Test." Econometric Theory 4, no. 3 (December 1988): 509–16. http://dx.doi.org/10.1017/s0266466600013426.

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Although originally designed to detect AR(1) disturbances in the linear-regression model, the Durbin-Watson test is known to have good power against other forms of disturbance behavior. In this paper, we identify disturbance processes involving any number of parameters against which the Durbin–Watson test is approximately locally best invariant uniformly in a range of directions from the null hypothesis. Examples include the sum of q independent ARMA(1,1) processes, certain spatial autocorrelation processes involving up to four parameters, and a stochastic cycle model.

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3

Löbus, Jörg-Uwe, and Lutz Ritter. "The limiting power of the durbin-watson test." Communications in Statistics - Theory and Methods 29, no. 12 (January 2000): 2665–76. http://dx.doi.org/10.1080/03610920008832630.

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4

King, Maxwell L., and Merran A. Evans. "The Durbin-Watson test and cross-sectional data." Economics Letters 18, no. 1 (January 1985): 31–34. http://dx.doi.org/10.1016/0165-1765(85)90073-4.

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5

Grose, Simone D., and Maxwell L. King. "The locally unbiased two-sided Durbin—Watson test." Economics Letters 35, no. 4 (April 1991): 401–7. http://dx.doi.org/10.1016/0165-1765(91)90010-i.

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6

Benkovitz, Carmen M., and Neal L. Oden. "Probability calculation for the Durbin-Watson correlation test." Environmental Software 2, no. 2 (June 1987): 85–88. http://dx.doi.org/10.1016/0266-9838(87)90005-0.

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7

White, Kenneth J. "The Durbin-Watson Test for Autocorrelation in Nonlinear Models." Review of Economics and Statistics 74, no. 2 (May 1992): 370. http://dx.doi.org/10.2307/2109675.

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8

Akter, Jesmin. "Bootstrapped Durbin– Watson Test of Autocorrelation for Small Samples." ABC Journal of Advanced Research 3, no. 2 (2014): 137–42. http://dx.doi.org/10.18034/abcjar.v3i2.39.

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9

Akter, Jesmin. "Bootstrapped Durbin- Watson Test of Autocorrelation for Small Samples." ABC Journal of Advanced Research 3, no. 2 (June 7, 2014): 68. http://dx.doi.org/10.15590/abcjar/2014/v3i2/54980.

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10

Evans, Merran A. "The twelfth order analogue of the durbin-watson test." Communications in Statistics - Simulation and Computation 16, no. 3 (January 1987): 679–88. http://dx.doi.org/10.1080/03610918708812612.

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11

MUNSON, PETER J., and ROBERT W. JERNIGAN. "A cubic spline extension of the Durbin-Watson test." Biometrika 76, no. 1 (1989): 39–47. http://dx.doi.org/10.1093/biomet/76.1.39.

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12

Bartels, Robert. "On the power function of the Durbin-Watson test." Journal of Econometrics 51, no. 1-2 (January 1992): 101–12. http://dx.doi.org/10.1016/0304-4076(92)90031-l.

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13

Billah, Mu'tasim, and Mohammad Syaiful Pradana. "Pengaruh Jumlah Industri dan Tenaga Kerja Terhadap Nilai Produksi Industri Formal Kecil." Unisda Journal of Mathematics and Computer Science (UJMC) 6, no. 01 (June 30, 2020): 19–24. http://dx.doi.org/10.52166/ujmc.v6i01.2383.

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The purpose of this study to analyze the effect of the number of industries and labor on the value of production in small industries in Lamongan Regency using the Durbin-Watson test. The Durbin-Watson test is an autocorrelation test that assesses the presence of autocorrelation in residuals. Data taken from the Central Bureau of Statistics of Lamongan Regency. Furthermore, it was analyzed using SPSS assistance. Based on the results of the analysis, it is known that there is no autocorrelation between the number of industries and workers on the value of production in small industries in Lamongan Regency.

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14

Giles, David, and Offer Lieberman. "Some properties of the durbin-watson test after a preliminaryt-test." Journal of Statistical Computation and Simulation 41, no. 3-4 (July 1992): 219–27. http://dx.doi.org/10.1080/00949659208811402.

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15

Turner, Paul. "Critical values for the Durbin-Watson test in large samples." Applied Economics Letters 27, no. 18 (November 12, 2019): 1495–99. http://dx.doi.org/10.1080/13504851.2019.1691711.

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16

Ali, Mukhtar M., and Subhash C. Sharma. "Robustness to nonnormality of the Durbin-Watson test for autocorrelation." Journal of Econometrics 57, no. 1-3 (May 1993): 117–36. http://dx.doi.org/10.1016/0304-4076(93)90061-9.

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17

Zeisel, Helmut. "On the power of the durbin-watson test under high autocorrelation." Communications in Statistics - Theory and Methods 18, no. 10 (January 1989): 3907–16. http://dx.doi.org/10.1080/03610928908830130.

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18

Kleiber, Christian, and Walter Krämer. "Finite‐sample power of the Durbin–Watson test against fractionally integrated disturbances." Econometrics Journal 8, no. 3 (November 25, 2005): 406–17. http://dx.doi.org/10.1111/j.1368-423x.2005.00171.x.

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19

Giles, David E. A., and John P. Small. "The power of the Durbin-Watson test when the errors are heteroscedastic." Economics Letters 36, no. 1 (May 1991): 37–41. http://dx.doi.org/10.1016/0165-1765(91)90052-m.

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20

Krämer, W. "The power of the Durbin-Watson test for regressions without an intercept." Journal of Econometrics 28, no. 3 (June 1985): 363–70. http://dx.doi.org/10.1016/0304-4076(85)90005-3.

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21

Aisami, A., Umar Abubakar, Motharasan Manogaran, and M. Y. Shukor. "Test for the Presence of Autocorrelation in the Morgan-Mercer-Flodin (MMF) Model used for Modelling the Total Number of COVID-19 Cases for Brazil." Bulletin of Environmental Science and Sustainable Management (e-ISSN 2716-5353) 5, no. 1 (July 31, 2021): 32–36. http://dx.doi.org/10.54987/bessm.v5i1.589.

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Mathematical models can be used to conduct COVID-19 pandemic analyses, including theoretical, quantitative, and simulation analyses. COVID-19 pandemic models such as the modified Gompertz, von Bertalanffy, modified logistics including the recent MMF model which was the best model in fitting the total number of COVID-19 cases for Brazil. We were the first to note the high suitability of the MMF model to fit total death and infection cases for COVID-19. The least-squares approach, which is employed in conventional nonlinear regression, including the MMF model, must be subjected to the idea that data points do not rely on one another and that the value of a data point is not impacted by the value of data points that came before or after it. This is known as autocorrelation and the Durbin-Watson test can be utilized to check the conformity of this model to non-autocorrelation. The value of the Durbin-Watson statistics was d =0.648. The statistic is approximately equal to 2(1âˆ’ p). We then test the hypothesis H0: Ï= 0 versus the alternative hypothesis of H1: Ï > 0. From the Durbin-Watson table [1,2] for n=50 and 4 parameters, the lower critical value for dL was 1.206, while the upper critical value dU was 1.537. According to this, the d value was lower than the lower critical value or dL, resulting in the null hypothesis being rejected or indicating that there is evidence of autocorrelation. This demonstrates that the MMF model used in the nonlinear regression model for modelling the total number of COVID-19 cases for Brazil needs remedial action, perhaps identifying potential outliers

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22

Kariya, Takeaki. "The Class of Models for Which the Durbin-Watson Test is Locally Optimal." International Economic Review 29, no. 1 (February 1988): 167. http://dx.doi.org/10.2307/2526816.

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23

Lee, Mei Yu. "On the Durbin-Watson statistic based on a Z-test in large samples." International Journal of Computational Economics and Econometrics 6, no. 1 (2016): 114. http://dx.doi.org/10.1504/ijcee.2016.073370.

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24

Albertson, K., J. Aylen*, and K. B. Lim†. "The power of the durbin watson test when the errors are par(1)." Journal of Statistical Computation and Simulation 72, no. 6 (January 2002): 507–16. http://dx.doi.org/10.1080/00949650213700.

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25

Bercu, Bernard, Bruno Portier, and Victor Vazquez. "A Durbin–Watson serial correlation test for ARX processes via excited adaptive tracking." International Journal of Control 88, no. 12 (June 14, 2015): 2611–18. http://dx.doi.org/10.1080/00207179.2015.1052017.

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26

Ansley, Craig F., Robert Kohn, and Thomas S. Shively. "Computing p-values for the generalized Durbin-Watson and other invariant test statistics." Journal of Econometrics 54, no. 1-3 (October 1992): 277–300. http://dx.doi.org/10.1016/0304-4076(92)90109-5.

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27

Preinerstorfer, David, and Benedikt M. Pötscher. "ON THE POWER OF INVARIANT TESTS FOR HYPOTHESES ON A COVARIANCE MATRIX." Econometric Theory 33, no. 1 (December 14, 2015): 1–68. http://dx.doi.org/10.1017/s026646661500033x.

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The behavior of the power function of autocorrelation tests such as the Durbin–Watson test in time series regressions or the Cliff-Ord test in spatial regression models has been intensively studied in the literature. When the correlation becomes strong, Krämer (1985, Journal of Econometrics 28, 363–370.) (for the Durbin–Watson test) and Krämer (2005, Journal of Statistical Planning and Inference, 128, 489–496) (for the Cliff-Ord test) have shown that power can be very low, in fact can converge to zero, under certain circumstances. Motivated by these results, Martellosio (2010, Econometric Theory, 26, 152–186) set out to build a general theory that would explain these findings. Unfortunately, Martellosio (2010) does not achieve this goal, as a substantial portion of his results and proofs suffer from nontrivial flaws. The present paper now builds a theory as envisioned in Martellosio (2010) in an even more general framework, covering general invariant tests of a hypothesis on the disturbance covariance matrix in a linear regression model. The general results are then specialized to testing for spatial correlation and to autocorrelation testing in time series regression models. We also characterize the situation where the null and the alternative hypothesis are indistinguishable by invariant tests.

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28

Shukor, M. Y. "Autocorrelation Test for the Residual Data from the Pseudo-1st Order Kinetic Model of the Brominated Flame Retardant 4-Bromodiphenyl Ether Adsorption onto Biochar-immobilized Sphingomonas sp." Journal of Environmental Bioremediation and Toxicology 4, no. 1 (July 30, 2021): 35–39. http://dx.doi.org/10.54987/jebat.v4i1.583.

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Because of their fire-retardant properties, polybrominated diphenyl ethers (PBDEs) are frequently used in the manufacturing industry. PBDEs are mixed with polymers as additives and employed in a range of sectors, including plastics and textiles. They are, nevertheless, capable of leaking from the surfaces of these items and into the environment since they are not chemically connected to plastics or textile materials. The adsorption of PBDEs onto biochar-immobilized bacteria is a useful method to remediate PBDEs from the environment. Understanding the kinetics of adsorption can be done by using models such as pseudo-1st or pseudo-2nd. The pseudo-1st order kinetic model was previously found to best fit the data via a nonlinear regression exercise for brominated flame retardant 4-bromodiphenyl ether adsorption onto biochar-immobilized Sphingomonas sp. However, the use of nonlinear regression requires the residual of the fitted curve to be non-autocorrelated. The Durbinâ€“Watson statistic, which is derived from the Durbinâ€“Watson distribution, is one of the most commonly used ways for determining whether or not there is autocorrelation. In this study, the calculated value of the Durbin-Watson statistics was d = 2.260. The Durbin-Watsonâ€™s lower critical value for dL was 0.700, while the upper critical value dU was 1.252. Since the d value was greater than the upper critical value or dU, this resulted in the null hypothesis not being rejected or indicating that there is no evidence of autocorrelation. This demonstrates that the pseudo-1st model used in the nonlinear regression model is adequate

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29

Javan, Rahman Sadeghi. "The relationship between personality traits and entrepreneurial intentions." Social and Management Research Journal 11, no. 2 (December 1, 2014): 46. http://dx.doi.org/10.24191/smrj.v11i2.5239.

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This study investigates the impact of personality traits on intention to start an entrepreneurship. In order to examine personality traits, the big five model was used. The big five model consists of five dimensions: extroversion, agreeableness, conscientiousness, emotional stability, and openness to experience. Entrepreneurship consists of six dimensions: hardworking, risk-taking, self-confidence, creativity, flexibility, and tolerance of ambiguity. In order to collect data, a 47 items questionnaire was designed. Statistical population was university of Isfahan’s personnel, and sample size was 160 personnel and were selected based on the available sampling method. In order to analyse data,descriptive statistic, inferential statistics, ENTER method, and Durbin-Watson test has been used. To measure stability of questionnaires’ items, Cronbach's alpha was calculated for each variable separately. The results of this article indicate that personality traits have an impact on the tendency to entrepreneurship. Based on these results, between all personality traits, agreeableness, conscientiousness, neuroticism, and openness to experience have impacts on the tendency to entrepreneurship and these factors could explain 0/533 of entrepreneurship regression. Durbin- Watson test results also indicate that there is no selfcorrelation between independent variables. Finally, empirical suggestions have been offered for human resources managers and related professionals.

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30

Jeong, Ki-Jun. "A New Approximation of the Critical Point of the Durbin-Watson Test for Serial Correlation." Econometrica 53, no. 2 (March 1985): 477. http://dx.doi.org/10.2307/1911249.

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31

Lieberman, Offer. "On the Approximation of Saddlepoint Expansions in Statistics." Econometric Theory 10, no. 5 (December 1994): 900–916. http://dx.doi.org/10.1017/s0266466600008914.

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The saddlepoint approximation as developed by Daniels [3] is an extremely accurate method for approximating probability distributions. Econometric and statistical applications of the technique to densities of statistics of interest are often hindered by the requirements of explicit knowledge of the c.g.f. and the need to obtain an analytical solution to the saddlepoint defining equation. In this paper, we show the conditions under which any approximation to the saddlepoint is justified and suggest a convenient solution. We illustrate with an approximate saddlepoint expansion of the Durbin-Watson test statistic.

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32

Gourieroux, C., A. Monfort, and A. Trognon. "A General Approach to Serial Correlation." Econometric Theory 1, no. 3 (December 1985): 315–40. http://dx.doi.org/10.1017/s0266466600011245.

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In this paper the testing and estimation problems are discussed in the case of serial correlation. Various models are particular cases of the general framework considered: the nonlinear simultaneous equations models, the probit models, the tobit models, the disequilibrium models, the frontier models, etc. In this context, it is shown that the score test can be written explicitly and that the statistic obtained is a generalization of that of Durbin and Watson; moreover, the maximum likelihood estimation procedure is shown to be robust with respect to serial correlation.

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33

De Beer, C. F., and J. W. H. Swanepoel. "A modified durbin—watson test for serial correlation in multiple regression under nonnormality using the bootstrap." Journal of Statistical Computation and Simulation 33, no. 2 (October 15, 1989): 75–81. http://dx.doi.org/10.1080/00949658908811188.

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34

Střelec, Luboš, and Václav Adamec. "Exploration into power of homogeneity and serial correlation tests." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 61, no. 4 (2013): 1129–36. http://dx.doi.org/10.11118/actaun201361041129.

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Verification of regression models is primarily based on analysis of error terms and constitutes one of the most important steps in applied regression analysis. In cross-sectional models, the error terms are typically heteroskedastic, while in time series regressions the errors are often affected by serial correlation. Consequently, in this paper, we focus on Monte Carlo simulations applied to explore the power of several tests of homogeneity and tests for presence of autocorrelation. In the past decades, the computational power has increased significantly to allow the benefit of simulation from exact distributions, which are not defined explicitly. We will discuss 1) testing of homogeneity for a given number of components in the exponential mixture approximated by subpopulations and 2) simulation of power in several commonly used tests of autocorrelation. For the first case, we consider exact likelihood ratio test (ELR) and exact likelihood ratio test against the alternative with two-component subpopulation (ELR2). In the second case, we consider the Durbin-Watson, Durbin h, Breusch-Godfrey, Box-Pierce and Ljung-Box tests of 1st order serial correlation and the runs test of randomness in two different types of linear regression models.

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35

Ghorbanian, Sohrabali, Mostafa Davoudinejad, Amir Khakpay, and Saeidreza Radpour. "Modeling Breakthrough Curves of Citric Acid Adsorption onto Anionic Resins in an Aqueous Solution." Journal of Engineering 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/139041.

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Breakthrough curves for citric acid adsorption from aqueous solution onto ion-exchange resin at 20, 35, and 55°C have been investigated. To predict breakthrough curves, three mathematical models have been analyzed based on the values of the least square method parameters, Durbin-Watson test, and mean relative percent error and, finally, appropriate models have been achieved. Models are in good agreement with experimental data based on the results. To examine models reliabilities and accuracy, models have been compared by various breakthrough curve data obtained by other investigators. The results show appropriate agreement and in some cases regression errors have been reduced to less than 1.0 percent.

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36

Shukor, Mohd Yunus. "Test for the presence of autocorrelation in the modified Gompertz model used in fitting of Burkholderia sp. strain Neni-11 growth on acrylamide." Bioremediation Science and Technology Research 4, no. 2 (December 31, 2016): 25–27. http://dx.doi.org/10.54987/bstr.v4i2.372.

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The growth of microorganism on substrates, whether toxic or not usually exhibits sigmoidal pattern. This sigmoidal growth pattern can be modelled using primary models such as Logistic, modified Gompertz, Richards, Schnute, Baranyi-Roberts, Von Bertalanffy, Buchanan three-phase and Huang. Previously, the modified Gompertz model was chosen to model the growth of Burkholderia sp. strain Neni-11 on acrylamide, which shows a sigmoidal curve. The modified Gompertz model relies on the ordinary least squares method, which in turn relies heavily on several important assumptions, which include that the data does not show autocorrelation. In this work we perform statistical diagnosis test to test for the presence of autocorrelation using the Durbin-Watson test and found that the model was adequate and robust as no autocorrelation of the data was found.

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37

Huitema, Bradley E., and Joseph W. McKean. "A Simple and Powerful Test for Autocorrelated Errors in OLS Intervention Models." Psychological Reports 87, no. 1 (August 2000): 3–20. http://dx.doi.org/10.2466/pr0.2000.87.1.3.

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The important assumption of independent errors should be evaluated routinely in the application of interrupted time-series regression models. The two most frequently recommended tests of this assumption [Mood's runs test and the Durbin-Watson ( D-W) bounds test] have several weaknesses. The former has poor small sample Type I error performance and the latter has the bothersome property that results are often declared to be “inconclusive.” The test proposed in this article is simple to compute (special software is not required), there is no inconclusive region, an exact p-value is provided, and it has good Type I error and power properties relative to competing procedures. It is shown that these desirable properties hold when design matrices of a specified form are used to model the response variable. A Monte Carlo evaluation of the method, including comparisons with other tests ( viz., runs, D-W bounds, and D-W beta), and examples of application are provided.

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38

Marshall, P., T. Szikszai, V. LeMay, and A. Kozak. "Testing the distributional assumptions of least squares linear regression." Forestry Chronicle 71, no. 2 (April 1, 1995): 213–18. http://dx.doi.org/10.5558/tfc71213-2.

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The error terms in least squares linear regression are assumed to be normally distributed with equal variance (homoskedastic), and independent of one another. If any of these distributional assumptions are violated, several of the desirable properties of a least squares fit may not hold. A variety of statistical tests of the assumptions is available. The following are recommended for reasons of ease of use and discriminating power: the K2 test for testing for non-normality, either the Durbin-Watson test or the Q-test for testing for autocorrelation, and either Szroeter's or White's test for testing for heteroskedasticity. The assumptions should be tested in this order; violating one of the assumptions may invalidate the results of subsequent tests. A microcomputer-based software package for least squares linear regression that incorporates the above tests is introduced. Key words: normality, homoskedasticity, independence

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39

Khasharmeh, Hussein. "Does Liquidity Influence Profitability in Islamic Banks of Bahrain: An Empirical Study?" International Journal of Financial Research 9, no. 2 (February 5, 2018): 236. http://dx.doi.org/10.5430/ijfr.v9n2p236.

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This study examines the impact of liquidity on Islamic banks’ profitability during the years from 2010 to 2015. The study extracted its data from the annual reports of six Islamic banks in Bahrain that have been in operations on or before 2010 to 2015. The liquidity model is built from four liquidity variables namely cash & due from banks to total assets (CDTA), cash & due from banks to total deposits (CDTD), investment to total assets (INVSTA) and investment to total deposits (INVSTD). According to adjusted R squares profitability variables return on assets (ROA), return on equity (ROE) and return on deposits (ROD) are respectively 16.2%, 3.1% and 21.3% dependent on liquidity variables.The results of the study show that CDTD and INVESTD are correlated positively with ROE. In addition, CDTD, INVSTA indicate a negative correlation with ROE. Thus, only INVSTA and INVSTD found to be significant with ROE at 0.05 significant level. Durbin-Watson test shows that the residuals are uncorrelated since its value is approximately very close to 2. However, according to the P-value, the overall liquidity model (Model 2) is not significantly related with ROE. Thus, the null hypothesis (H0) is accepted and the alternative hypothesis is rejected for the ROE. Furthermore, the results in the table show that CDTA and INVESTD are positively correlated with ROD, and negatively with CDTA and INVSTA, and CDTA is the only insignificant variable. CDTD is significantly related with ROD at 10%. Durbin-Watson test shows that the residuals are positive auto - correlated since its value is approximately very close to 1. However, according to the P-value, the overall liquidity model (Model 3), is significantly related with ROD at 1% level.The researcher recommended for further studies to add more liquidity variables to the model so as to enhance and enrich Islamic banks outlook.

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40

Shively, Thomas S., Craig F. Ansley, and Robert Kohn. "Fast Evaluation of the Distribution of the Durbin-Watson and other Invariant Test Statistics in Time Series Regression." Journal of the American Statistical Association 85, no. 411 (September 1990): 676–85. http://dx.doi.org/10.1080/01621459.1990.10474927.

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41

Maxwell, L. King, and C. Harris David. "The application of the durbin-watson test to the dynamic regression model under normal and non-normal errors." Econometric Reviews 14, no. 4 (January 1995): 487–510. http://dx.doi.org/10.1080/07474939508800333.

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42

Farebrother, R. W. "A critique of recent methods for computing the distribution of the Durbin-Watson and other invariant test statistics." Statistical Papers 35, no. 1 (December 1994): 365–69. http://dx.doi.org/10.1007/bf02926430.

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43

Eladly, Salah Mohamed. "The Financial Performance on Asset Quality of Insurance Industry in Egypt (Panel Data Analysis)." International Business Research 14, no. 6 (May 12, 2021): 24. http://dx.doi.org/10.5539/ibr.v14n6p24.

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This study is an attempt to analyze the  impact of the financial performance on asset quality of insurance industry in Egypt as  applied on a sample of 19 insurance companies over the period 1999-2019.The financial performance measured by profitability (return on equity-return on investment) and liquidity results show that there is a significant negative linear relationship between the independent variable in terms ofX3, and the dependent variable; y, at a significant level less than (0.01), while there is no significant linear relationship between the independent variable of X1,X2, and dependent variable; y at a significant level greater than (0.05) . The study methodology used panel data analysis according to ARDL model and OLS, beside the robustness check supports these results using the Jarque-Bera test and the Durbin-Watson test statistic

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44

Osesoga, Maria Stefani, and Jimmy Ardianto. "Pengaruh Opini Audit Terhadap Earnings Response Coefficient." Jurnal ULTIMA Accounting 3, no. 2 (December 1, 2011): 64–83. http://dx.doi.org/10.31937/akuntansi.v3i2.435.

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The users of financial statements require quality and relevant earnings information to be used in decision-making process. The purpose of this study is to determine the significant effect of audit opinion information that contained in the companies' annual report against the quality and relevance earnings information, which measured by Earning Response Coefficient or ERC. This research used control variables, which are beta, leverage, and PBV. The tests conducted in this study were normality test using normal probability plot, the autocorrelation test using Durbin-Watson, multicollinearity test using the value of tolerance and VIF, and heteroscedasticity test using the scatter plot graphic. The hypotheses were tested by using multiple regressions. The results of the study showed that PBV had significant impact on ERC, and indicated that investors had not appreciated the audit opinion information disclosed by the companies in their annual reports for their investment decision. Keywords: Audit Opinion, Beta, Earnings Response Coefficient, Leverage, Price to Book Value.

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Rahmawati, Erma. "The Influence Of The Role Of The Homeroom Teacher In Learning From Home(BDR) On The Activeness Of Class XI Students In MAN 1 Jombang Academic Year: 2020/2021." Inovasi-Jurnal Diklat Keagamaan 14, no. 3 (December 21, 2020): 180–86. http://dx.doi.org/10.52048/inovasi.v14i3.167.

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The implementation of teaching and learning activities in madrasas since March 2020 has changed due tothe Covid-19 pandemic, the government has established the concept of BDR (Learning from Home) at alllevels of education. This study aims to determine the extent of the influence of the role of the homeroomteacher in BdR activities on the activeness of class XI students in MAN 1 Jombang. The method used in thisresearch is quantitative research methods. Data collection techniques that researchers use are observation,interviews, documentation, and questionnaires. For data analysis using the Durbin-Watson autocorrelationtest, and the Simultaneous F test. The results showed that there was an influence on the role of homeroomteacher on the activeness of class XI students in MAN 1 Jombang, amounting to 69.2 %.

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Dash, Mihir. "Beta Estimation in Indian Stock Markets - Some Issues." Asian Journal of Finance & Accounting 7, no. 2 (August 1, 2015): 23. http://dx.doi.org/10.5296/ajfa.v7i2.6751.

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<p>This study examines the reliability of the OLS beta estimates in Indian stock markets by considering the residual characteristics of the market model regressions. The statistics used include the coefficient of determination (R<sup>2</sup>), the F-test for significance of the regression coefficient, the Durbin-Watson test for serial autocorrelation, the residual autocorrelation function, the Kolmogorov-Smirnov and Shapiro-Wilk tests for normality of the residuals, the presence of outliers, and White’s test for heteroskedasticity.</p><p>The results of the study indicate some serious issues afflicting beta estimation in Indian stock markets, including: non-normality of stock returns and of residuals, extreme standardized residual values, heteroskedasticity, residual autocorrelation, and low R<sup>2</sup>. Thus, the simple market model is likely to result in biased estimates for beta in Indian stock markets.</p>

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Abbasnezhad, Parisa, and Hossein Miladiyan. "The effect of investment diversification on return and risk of private banks in the implementation on monetary policy." Journal of Management and Accounting Studies 2, no. 02 (July 3, 2019): 7–13. http://dx.doi.org/10.24200/jmas.vol2iss02pp7-13.

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The present study evaluates the effect of investment diversification on the return on investment and risk as long as the central bank's monetary policy factors will affect how banks investment. Methodology: This study has a descriptive-correlation nature that has analyzed the financial information of 10 active banks in Tehran stock exchange in the period of 1388 to 1392 using the SPSS version 21. In this study Hirschman-Herfindahl index (HHI) was used to evaluate the investment diversification level of banks in various economic parts. The normality of research data, the holograph – Esmirnoph test has been used and the Durbin Watson test was used for investigating the independence among errors. Results: The (ANOVA) variance analysis test has been used for investigating the meaningfulness of regression. Results showed that investment diversification has a negative and inverse effect on investment return and risk. Conclusion: Also any of control variable and interfere has no effect on investment return and bank risk.

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Kalina, J. "Three contributions to robust regression diagnostics." Journal of Applied Mathematics, Statistics and Informatics 11, no. 2 (December 1, 2015): 69–78. http://dx.doi.org/10.1515/jamsi-2015-0013.

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Abstract Robust regression methods have been developed not only as a diagnostic tool for standard least squares estimation in statistical and econometric applications, but can be also used as self-standing regression estimation procedures. Therefore, they need to be equipped by their own diagnostic tools. This paper is devoted to robust regression and presents three contributions to its diagnostic tools or estimating regression parameters under non-standard conditions. Firstly, we derive the Durbin-Watson test of independence of random regression errors for the regression median. The approach is based on the approximation to the exact null distribution of the test statistic. Secondly, we accompany the least trimmed squares estimator by a subjective criterion for selecting a suitable value of the trimming constant. Thirdly, we propose a robust version of the instrumental variables estimator. The new methods are illustrated on examples with real data and their advantages and limitations are discussed.

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Hada, Teodor, Nicoleta Bărbuţă-Mişu, and Radu Mărginean. "Forecasting Firm Performance: Evidence From Romanian Furniture Firms." Ekonomika 97, no. 1 (July 3, 2018): 87–104. http://dx.doi.org/10.15388/ekon.2018.1.11781.

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The aim at this paper is to propose an econometric model for analyzing economic performance in the furniture industry in Romania, conducted on a sample of 293 firms. The net profit was considered as a dependent variable and the turnover, expenses with employees, value added, current liabilities and inventories as independent variables. Five hypotheses were proposed, tested and validated by using multiple linear regression. The most significant results show that there is a positive significant relationship between net profit and value added and a negative significant relationship between net profit and expenses with employees. Since the model has been validated statistically, we consider that it can provide useful predictions in terms of economic performance analysis in the furniture industry.Keywords: multiple linear regression, ANOVA, Durbin-Watson test, net profit estimation, value added

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Ahmad, S. A., M. S. Shukor, N. A. Masdor, N. A. Shamaan, M. A. H. Roslan, and M. Y. Shukor. "Test for the Presence of Autocorrelation in the Buchanan-three-phase Model used in the Growth of Paracoccus sp. SKG on Acetonitrile." Journal of Environmental Bioremediation and Toxicology 3, no. 1 (July 30, 2015): 6–8. http://dx.doi.org/10.54987/jebat.v3i1.252.

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Millions of tonnes of organonitriles are produced annually for use in industry. They are carcinogenic and mutagenic. Bioremediation of acetonitrile, an organonitrile, has been touted as a more economical and feasible method compared to physical and chemical approaches. In this work, we model the growth of growth of Paracoccus sp. SKG on acetonitrile from publishedliterature to obtain vital growth constants. We discovered that the Buchanan-three-phase model via nonlinear regression utilizing the least square method was the very best model to explain the growth curve. Nonlinear regression utilizing the least square method typically utilizes the idea that data points usually do not depend upon each other or the value of a data point is notdetermined by the value of previous or proceeding data points or usually do not display autocorrelation. In this work, the Durbin-Watson statistic to check for the presence of autocorrelation in the growth model was carried out.

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