We apply the **Hausman** **test** to each dataset, as well. The **Hausman** **test** is the traditional tool used to assist researchers in choosing between the traditional RE and FE estimators. This paper begins with an explanation of the underlying clustered data model and the traditionally specified RE and FE estimators. We also outline and explain the WB.

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Search: Endogeneity **Test** Stata Panel. Both **test** the null hypothesis that the variance of the residuals is homogenous So, watch straight-to-the-point, short-clipped hands-on tutorial videos on multicollinearity, one-way ANOVA, two-way ANOVA, how to convert excel file into Stata file, how to reshape wide-format to long-format data (Stata), optimal lags selection (EViews, Stata), interpret output.

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Berdasarkan hasil Uji t, maka pengambilan keputusannya adalah sebagai berikut: 1. Pengujian terhadap variabel X1. Hipotesis pertama menyebutkan bahwa X1 tidak berpengaruh signifikan terhadap Y. Berdasarkan hasil perhitungan data menggunakan program Eview 8. diperoleh hasil bahwa nilai signifikansi sebesar 0,5184.

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Just use fixed effects. No one knows the power of the **Hausman** **test**, and failing to reject the null tells you little about whether the null is true (see also, classical hypothesis testing). And random effects is a stupid assumption to begin with; the only reason it would be true would be if God were trying to be nice to econometricians..

However, the data has problem of endogeneity when i use **Hausman** **test** BACKGROUND In the Breusch-Pagan **Test** the null hypothesis is that of homoscedasticity i Data type: Panel data 2 Use a random-effects estimator to regress your covariates and the panel-level means generated in (1) against your outcome Use a random-effects estimator to regress.

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The **test** statistic is proportionally adjusted for the distribution by the number of constraints in the hypothesis. df_constraints int, optional. The number of constraints. If not provided the number of constraints is determined from r_matrix. scalar bool, optional. Flag indicating whether the Wald **test** statistic should be returned as a sclar float.

With simple models, taking the derivative still helps with **interpretation** With a dummy variable, we calculated incremental e ects (di erences or contrasts from 1 vs 0, holding other covariates constant): E[yjage;male] male = 2 + 3age Centering also helps with parameter **interpretation**: y = 0 + 1(age m) + 2male + 3male (age m) If m is average age.

“In the case of time-series cro ss-sectional data the **interpretation** of the beta coefficients would be “for a given country, as X varies across time by one unit, Y increases or decreases by βunits” (Bartels, Brandom, “Beyond “Fixed Versus Random Effects”: A framework for improving substantive and.

The **Hausman Test** Is a **test** for the independence of the λ i and the x kit. The covariance of an efficient estimator with its difference from an inefficient estimator should be zero. Under the null hypothesis we **test**: 10 W=( )'ˆ ( )~ 2() RE 1 β RE −βFE Σ β −βFE χ k − If Wis significant, we should not use the random effects estimator.

The **test** statistic for the Durbin-Watson **test**, typically denoted d, is calculated as follows: where: T: The total number of observations. et: The tth residual from the regression model. The **test** statistic always ranges from 0 to 4 where: d = 2 indicates no autocorrelation. d < 2 indicates positive serial correlation.

“In the case of time-series cro ss-sectional data the **interpretation** of the beta coefficients would be “for a given country, as X varies across time by one unit, Y increases or decreases by βunits” (Bartels, Brandom, “Beyond “Fixed Versus Random Effects”: A framework for improving substantive and.

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2sls postestimation endogeneity check, weak instrument **test**,estat overid, in STATA pperron performs a PP **test** in Stata and has a similar syntax as dfuller stata expand, Jul 25, 2014 · The expand weightCRround command replicated each dataset case n-1 times, in which n is the number in the weightCRround variable: for example, each case with a weightCRround value of.

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Re: st: St: **interpret** the result of **Hausman test**. Although not a universal rule but more conventional to compare the p-value to 0.05. If p<0.05, reject the null and the other way arround. SO what p-value in your case (0.0687) is greater than 0.05, so you can reject the NULL but I am not sure how much straightforward that rejection would be.

1 Answer. When you reject with a Hausmann **test** you are effectively comparing the OLS estimate of your parameter on VariableOne to the 2SLS estimate of the same. If these two estimates differ, then you should believe that the variable is endogenous. If they are the same (in a statistical sense), then you should usually use OLS.

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Likewise **Hausman** (1992), though motivated by different methodological considerations to that of Boitani and Salanti, also invokes the D-Q thesis in the context of his analysis of neoclassical microeconomics. **Hausman** also adopts and extremely pessimistic **interpretation** of the D-Q thesis.

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Likelihood Ratio **Test**; by Tommy Anderson; Last updated over 3 years ago; Hide Comments (-) Share Hide Toolbars.

your **interpretation** and understanding. So sometimes it is a personal choice. This should become more clear with some examples. ... same 40-mile **test** course (n = 2) 34-35 . 34-36 . 34-37 SAS Coding proc glm data =a1; class driver car; model mpg=driver car driver*car; random driver car driver*car/ **test** ;.

Dec 2004. Viera Chmelarova. R. Carter Hill. The **Hausman** (1978) **test** is widely used in applied research to **test** the endogeneity of explanatory variables in a regression. Asymptotically the **test** ....

Duplicate RT Controls (RTC) to **test** the efficiency of the miRNA RT reaction, with a primer set that detects the template synthesized from the built in miRNA External RNA Control (ERC). ... **interpretation** of data, or in preparing this manuscript for publication. References. ... Dodson MV, **Hausman** GJ, Moore SS, et al. (2011) MicroRNA regulation.

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The **Hausman** **test** is regularly used to **test** whether RE can be used, or whether FE estimation should be used instead (for example Greene Reference Greene 2012, 421). However, it is problematic when the **test** is viewed in terms of fixed and random effects, and not in terms of what is actually going on in the data.

Search: Endogeneity **Test** Stata Panel. com) Tim Essam ([email protected] **Testing** Endogeneity in Panel Data Regression using Eviews * Robust Durbin-Wu-**Hausman test** of endogeneity implemented by estat endogenous Because the **test** did not reject the null, CT emphasize their FE estimates The syntax and outputs are closely patterned after Stata’s built.

A chi-square **test** for independence was computed to determine whether education (primary school, secondary school, BA, Master, Ph.D.) is independent of gender (male, female). The results are not significant, χ2(4) = 1.111, p = .892, Cramer's V/phi = .892. We fail to reject the null hypothesis that education is the same across gender (male.

Apr 20, 2022 · Code: **hausman** iv ols Note: the rank of the differenced variance matrix (22) does not equal the number of coefficients being tested (23); be sure this is what you expect, or there may be problems computing the **test**. Examine the output of your estimators for anything unexpected and possibly consider scaling your variables so that the coefficients ....

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The outcome of a **Hausman** **test** is simple to interpret: if the p-value is modest (less than 0.05), the null hypothesis should be rejected. The issue stems from the fact that there are multiple variants of the **test**, each with a distinct hypothesis and possible outcomes.

A panel data set (Source: World Development Indicators data under CC BY 4.0 license) (Image by Author) In the above data set, the unit is a country, the time frame is 1992 through 2014 (23 time periods), and the panel data is fixed and balanced.. The set of data points pertaining to one unit (one country) is called a group.In the above data panel, there are seven groups.

The Durwin-Wu-**Hausman** **test** 1 First step: regress y 2 z 1 predict ^v, res 2 Second step regress y 1 z 1 y 2 ^v If cov (y 2;u )6=0, plimcov N (v^;y 1)6=0 and the coe cient for ^v in second step would be signi cant (in this case, the second step is like adding to the original regression the missing. **Interpretation Hausman Test** Posted 07-30-2010 08:33 AM (919 views) Hi, I use the panel procedure, and I want to check if I should use a fixed- or random effects model. The **Hausman test** output (when checking for random effects) is: **Hausman Test** for Random Effects.

Need to use IV methods (**Hausman**-Taylor). A. Colin Cameron Univ. of California - Davis (Based on A. Colin Cameron and Pravin K. Trivedi,Panel methods for Stata Microeconometrics using Stata, Stata Press, forthcoming.April 8, 2008 5 / 55 ) 2.2 Reading in panel data Data organization may be.

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Search: Endogeneity **Test** Stata Panel. 2019 · Endogeneity **Test** Panel Data 29 Jun 2016, 07:48 **Test** for Clustering Some Speciﬁc Examples with Simulations References Clustering of Errors Cluster-Robust Standard Errors More Dimensions A Seemingly Unrelated Topic Types of Clustering—Serial Corr reg y x1 x2 estimates store ols ivregress 2sls y x1 (x2 = z1 z2) estimates store iv **hausman** iv ols ....

May 2, 2013. #2. You haven't directly shown us the random effects model, but the general principle is that you're **testing** to see whether the effect of v & k within groups (fe model) is different from the effect of v & k between groups. The re model averages out the within & between estimates by assuming that they're equal; this **Hausman test**.

From results of the **Hausman** **test**, estimates by OLS are efficient but not consistent: indicating the absence of endogeneity and vailidity of a GLS with Random effect. I can't really be of help untill I understand the essence of integrating a dummy variable in your research objective. ... October 30, 2011 4:01 PM Subject: [Gretl-users] panel.

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To **test** whether the IV or OLS regression technique is best, one can use the **Hausman** endogeneity **test** Econometrics Stata Commands and Cluster Sampling The notation above naturally brings to mind a paradigmatic case of clustering: a panel model with group-level shocks (u i I have a panel dataset of treatment group and control Stata implementation of modern panel unit root tests for ....

The **Hausman** **test** for 2sls is not significant, so it means that 2sls is not preferable to OLS. But when I look at the specific parameter estimates from OLS and 2SLS, the parameters for the endogenous variables are different: in OLS they are significant, but in 2SLS they are not significant. This seems to contradict with an insignificant **Hausman**.

Durbin–Wu–**Hausman** **test**. The Durbin–Wu–**Hausman** **test** (also called **Hausman** specification **test**) is a statistical hypothesis **test** in econometrics named after James Durbin, De-Min Wu, and Jerry A. **Hausman**. The **test** evaluates the consistency of an estimator when compared to an alternative, less efficient estimator which is already known to be ....

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Search: Endogeneity **Test** Stata Panel. Partially Linear Functional-Coefficient Dynamic Panel Data Models: Sieve Estimation and Specification **Testing** (with Yonghui Zhang), Accepted for publication at Econometric Reviews General econometric questions and advice should go in the Econometric Discussions forum Dynamic panel-data estimation, two-step system Generalized.

The **Hausman** **test** The **Hausman** **test** statistic The **Hausman** **test** statistic is defined as m = q′(var ^FE var ^RE) 1q; with q = ^FE ^RE. Under RE, the matrix difference in brackets is positive, as the RE estimator is efficient and any other estimator has a larger variance. The statistic m is distributed ˜2 under the null of RE, with degrees.

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Search: Endogeneity **Test** Stata Panel. 107 Chi-sq(1 Null hypothesis : Homoskedasticity One can **test** heterskedasticity in STATA either using the "rvfplot" (graphical) or the through Breusch - Pagan **Test** (numerically) 107 Chi-sq(1 Endogeneity in Econometrics I In a multiple linear regression, if at least one of the regressors is correlated with the residual, then the exogeneity assumption.

**Testing** for IIA with the **Hausman**-McFadden **Test*** The Independence of Irrelevant Alternatives assumption inherent in multinomial logit models is most frequently tested with a **Hausman**-McFadden **test**. As is confirmed by many findings in the literature, this **test** sometimes produces negative outcomes, in contradiction of its asymptotic χ2 distribution.

We then show how the **Hausman** form of the **test** can beappliedintheGMM context, how it can be interpreted as a GMM **test**, when it Stata implementation Specification **tests** Panel data models with strictly exogenous instruments The module is made available under terms of the GPL v3 (https://www Because are unobserved, you can replace them with the OLS.

3 **Interpretation** . 3 **Interpretation**. by Cristian Angelo Guevara-Cue AnEc Center for Econometrics Research 19 Diallo Ibrahima Amadou, 2020 For a more conceptual understanding, including an explanation of the score **test**,.

Search: Endogeneity **Test** Stata Panel" Economics Letters, Volume 95, Issue 2, May 2007, Pages 272-277 This archive includes the complete list of user-written Stata packages till January 1st 2015 and includes a brief description and HTML help file To **test** whether the IV or OLS regression technique is best, one can use the **Hausman** endogeneity Wooldridge, Jeffrey;.

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An introduction to **Hausman**-Taylor model Xiang Ao January 27, 2009 1 **Hausman**-Taylor model Random eﬀects and ﬁxed eﬀects models are used widely in econometrics for panel data. Many economists tend to like ﬁxed-eﬀect model better since it eliminates all the commonality within an individual (or a ﬁrm, etc), therefore the.

by the information available, people's **interpretation** of such information and how they form expectations based on such **interpretation** for decisions influencing demand of securities as per (Yadav, 2017).

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Assemble a panel dataset of U Title : Stata 5: Durbin–Wu–**Hausman test** (augmented regression **test**) for endogeneity: Author: Ronna Cong, StataCorp: Date: November 1999 **Testing** for endogeneity; Instrumental Variables in Stata/R: Topics This paper addresses an important issue of modeling nonlinear asymmetric dynamics and unobserved individual heterogeneity in the.

F-test **interpretation** 22 Aug 2019, 09:55 I am running restricted F **tests** on diff-in-diff regressions to evaluate the effect of a government health initiative. ... F value is a value on the F distribution. alleqs speciﬁes that all the equations in the models be used to perform the **hausman** **test**; by default, only the ﬁrst equation is used. The.

Specification **Test** -**Hausman** 8 The fixed effects estimator is more accurate than the random effects estimator, but less efficient (larger variance). In turn, the random effects estimator is more efficient than the fixed effects estimator, but may be biased. The **Hausman** specification **test** basically compares the parameters for the models with fixed.

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performs a **Hausman** **test** and is unable to reject the null hypothesis that the criminal justice variables are exogenous. The **Hausman** **test** is inapplicable within the ARDL framework. However, Pesaran and Shin (1999, p. 16) contend that "appropriate modification of the orders of the ARDL model is sufficient to simultaneously correct.

Key Results: P-Value for Pearson Chi-Square, P-Value for Likelihood Ratio Chi-Square. In these results, the Pearson chi-square statistic is 11.788 and the p-value = 0.019. The likelihood chi-square statistic is 11.816 and the p-value = 0.019. Therefore, at a significance level of 0.05, you can conclude that the association between the variables. The covariance matrix for the **Hausman** **test** is only positive semi-definite under the null. It also does not necessarily have the obvious degrees of freedom. Take a simple example. Consider adding an.

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multinomial response models. Use choice of insurance type as the outcome variable, based on their income ethnicity, , maximum likelihood estimates require large sample size. Multiple equations also require large sample size. Iteration 0: log likelihood = -210.58254 Iteration 1: log likelihood = -201.60669 Iteration 2: log likelihood = -201..

Assemble a panel dataset of U Title : Stata 5: Durbin-Wu-**Hausman** **test** (augmented regression **test**) for endogeneity: Author: Ronna Cong, StataCorp: Date: November 1999 Testing for endogeneity; Instrumental Variables in Stata/R: Topics This paper addresses an important issue of modeling nonlinear asymmetric dynamics and unobserved individual heterogeneity in the threshold panel data framework. Edited by Daniel M. **Hausman**. Cambridge: Cambridge University Press, pp. 17-21. Original pagination shown in square brackets. ... Third (as Erkki Koskela reminded me), it is easier to interpret a road **test** than an econometric study. The difficulties of testing in economics make it all the more mandatory to look under the hood.

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download **test** for serial correlation in panel data stata 1) and datasets are available for easy download an incremental F **test**) How Do You Activate A Verizon Phone By Yourself To verify whether one should use FE or RE on a particular dataset, **Hausman** **test** should be used (xthausman) 3 **Interpretation** 3 **Interpretation**. There, for the 2SLS.

Robust **Hausman Test** Stata This can occur under a variety of conditions Earnings management analysis and STATA helper 2sls postestimation endogeneity check, weak instrument **test**,estat overid, in STATA Public policy researchers have relied on Stata for over 30 years because of its breadth, accuracy, extensibility, and reproducibility Public policy.

With a hypothesis **test** with the null hypothesis that the two variables are linearly independent or uncorrelated. This is rejected at a very low level of significance (check out the p-value: it is much lower than any traditional level of significance, like 0.05 (0.01) or 5% (1%)). 1.3 transforming variables.

A Wu-**Hausman** **Interpretation** of a t-Test for the Presence of a Trend in the Cointegration Relationship. 2004. María-Isabel Ayuda. Antonio Aznar Grasa. M. Salvador. Download Download PDF. Full PDF Package Download Full PDF Package. This Paper. A short summary of this paper. 37 Full PDFs related to this paper.

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Search: Endogeneity **Test** Stata Panel. Partially Linear Functional-Coefficient Dynamic Panel Data Models: Sieve Estimation and Specification **Testing** (with Yonghui Zhang), Accepted for publication at Econometric Reviews General econometric questions and advice should go in the Econometric Discussions forum Dynamic panel-data estimation, two-step system Generalized.

With a hypothesis **test** with the null hypothesis that the two variables are linearly independent or uncorrelated. This is rejected at a very low level of significance (check out the p-value: it is much lower than any traditional level of significance, like 0.05 (0.01) or 5% (1%)). 1.3 transforming variables.

The **interpretation** of coefficients is the same in the RE model as it is in the FE model. ... My justification for using a FE model even though within the **hausman** **test** I failed to reject the null was that the RE assumption that individual effects are uncorrelated with the independent variable of interest was unrealistic in my model. 1.

Principles of Econometrics, Fifth Edition, is an introductory book for undergraduate students in economics and finance, as well as first-year graduate students in a variety of fields that include economics, finance, accounting, marketing, public policy, sociology, law, and political science. Students will gain a working knowledge of basic econometrics so they can apply modeling, estimation.

The drawbacks of the Andersen's likelihood ratio **test** both for the Rasch model (see Traub & Wolfe, 1981 for details) and the multilevel Rasch led to the introduction of the **Hausman** specification **test** (**Hausman**, 1978) in this paper. The **Hausman** **test** is easy to implement and potentially useful because the **test** requires only the estimated covariance.

VECM Estimation and **Interpretation**; Impulse Response Functions after VAR and VECM; Simultaneous Equation Models. Two-Stage Least Squares (2SLS) Estimation; **Test** of Endogeneity: Durbin-Wu-**Hausman** **Test**; **Test** of Overidentifying Restrictions: Sargan **Test**; Microeconomics. Consumer Behaviour. Cardinal Utility Analysis and Law of Diminishing Returns.

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multinomial response models. Use choice of insurance type as the outcome variable, based on their income ethnicity, , maximum likelihood estimates require large sample size. Multiple equations also require large sample size. Iteration 0: log likelihood = -210.58254 Iteration 1: log likelihood = -201.60669 Iteration 2: log likelihood = -201..

Durbin–Wu–**Hausman** **test**. The Durbin–Wu–**Hausman** **test** (also called **Hausman** specification **test**) is a statistical hypothesis **test** in econometrics named after James Durbin, De-Min Wu, and Jerry A. **Hausman**. The **test** evaluates the consistency of an estimator when compared to an alternative, less efficient estimator which is already known to be ....

the new **test** with invalid instruments and high dimensional covariates. 1 Introduction Many empirical studies using instrumental variables (IV) regression are accompanied by the Durbin-Wu-**Hausman** **test** [Durbin, 1954, Wu, 1973, **Hausman**, 1978], hereafter called the DWH **test**. The primary purpose of the DWH **test** is to **test** the presence of endogeneity.

**Tests** for endogeneity Other sources of endogeneity Problems with weak instruments. Idea of Instrumental Variables attributed to Philip Wright 1861-1934 interested in working out whether price of butter was demand or supply driven. More formally, an instrument Z.

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Search: Endogeneity **Test** Stata Panel, weight, anxiety level, salary, reaction time, etc Type Article de périodique (Anglais) Stata Journal Volume Abstract I introduce xtsfkk, a new Stata command for fitting panel stochastic frontier models with endogeneity xtivreg2 y x2 x3 (x1=z1), fe endog(x1) cluster(id year) >> >> My questions are the Type Article de périodique (Anglais). Duplicate RT Controls (RTC) to **test** the efficiency of the miRNA RT reaction, with a primer set that detects the template synthesized from the built in miRNA External RNA Control (ERC). ... **interpretation** of data, or in preparing this manuscript for publication. References. ... Dodson MV, **Hausman** GJ, Moore SS, et al. (2011) MicroRNA regulation.

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Search: Endogeneity **Test** Stata Panel. Shapiro Wilk **test**-is the sample normally distributed 5 Step 2: V = B+BX + BZ + Vov+ H Step 3: Now we **test** the significance of coefficient V using t-test We then present readily implementable econometric methods to correct for endogeneity and, when feasible, provide STATA code to ease implementation Entry data secara cut paste ke Stata Assemble a panel.

Table 1. Microsoft Excel® Wu-**Hausman** (Wooldridge) and Sargan **tests** auxiliary regressions F and chi-square **tests** from original multiple linear regression of house price explained by its lot size and number of bedrooms using whether house has a driveway and number of garage places as instrumental variables.

The Durbin-Watson **test** has the null hypothesis that the autocorrelation of the disturbances is 0. It is possible to **test** against the alternative that it is greater than, not equal to, or less than 0, respectively. This can be specified by the alternative argument. Under the assumption of normally distributed disturbances, the null distribution.

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The Durwin-Wu-**Hausman** **test** 1 First step: regress y 2 z 1 predict ^v, res 2 Second step regress y 1 z 1 y 2 ^v If cov (y 2;u )6=0, plimcov N (v^;y 1)6=0 and the coe cient for ^v in second step would be signi cant (in this case, the second step is like adding to the original regression the missing.

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Jan 06, 2021 · But this question can also be answered perfoming the **Hausman**-**Test**. **Hausman**-**Test**: In simple termns, the **Hausman**-**Test** is a **test** of endogeneity. By running the **Hausman**-**Test**, the null hypothesis is that the covariance between IV(s) and alpha is zero. If this is the case, then RE is preferred over FE..

The Durbin-Wu-**Hausman Test** of Endogeneity is used to determine whether the endogenous regressors in a simultaneous equation model are truly endogenous. Simultaneous equation models include both endogenous and exogenous variables. The decision to take certain variables as endogenous generally depends on theoretical considerations or a priori.

by the information available, people's **interpretation** of such information and how they form expectations based on such **interpretation** for decisions influencing demand of securities as per (Yadav, 2017).

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