sugyaan july jan 14

SuGyaan1

Volume VI / VII, Issue II / I

ISSN - 0975-4032 Volume VI/VII Issue II / I July - Dec. 2013 / Jan. - June 2014

RESEARCH ARTICLES

Shivani Nischal & Exploring the Predictive Power of OSCM Model of ConflictG.S. Bhalla Management towards Work Productivity- A Comparative

Approach between Public and Private Sector Banks

Suyam Praba. R & Determinants of Households decisions and influence ofMalarmathi. B Cultural and Demographic factors on Investment Decision

Making - An Empirical study among Salaried Investors

Parag Rijwani Investigating Mutual Fund Performance Persistence

Pardhasaradhi Madasu Preliminary Performance Analysis of S&P BSE 500Shariah Index

Meenakshi Tyagi & Impact of Inflation on Economic Factors in Indian EconomyRenu Sharma

BOOK REVIEW

Pavan Patel & The Challenges of Indian ManagementK.V.S. Krihna Mohan

Global Impact Factor (GIF) for 2012 - 0.421 & 2013 - 0.493

Chief Patron: Mrs. S. Aarathy

President and CEO

Siva Sivani Group of Institutions, Secunderabad.

Patron: Mr. Sailesh Sampathy

Vice President and Deputy CEO

Siva Sivani Group of Institutions, Secunderabad.

Editor: Dr. V. G. Chari

Assistant Vice President

Siva Sivani Institute of Management.

Assistant Editor: Dr.Kompalli Sasi Kumar

Associate Professor, Finance Area

Siva Sivani Institute of Management.

Editorial Advisory and Review Panel

Dr. Ashish Sadh, Professor, Marketing area, IIM Indore

Dr. Cullen Habel, Lecturer in Marketing, The University of Adelaide Business School, South Australia

Prof. Anantha S Babbili, Professor in Media and Communication, Texas A&M Univeristy, Corpus Christi.

Dr. C. Gopalkrishnan, Director & Professor of Strategic Management, Institute of Management, Nirma

University, Ahmedabad

Dr. H.K. Jayavelu, Professor- HR, IIM K

Dr. Prashanth N Bharadwaj, Dean’s Associate and Professor, Indiana University of Pennsylvania, USA

Dr. B. Rajashekar, Reader, School of Management Studies, University of Hyderabad,

Dr. RajendraNargundkar, Director, MDI , Gurgaon

Dr.A.Sudhakar, Professor & Registarar, Department of Commerce, Dr.B.R.A.O.U, Hyderabad.

Dr. G.B. Reddy, Associate Professor, Department of law, Osmania University, Hyderabad

Dr. S.M. Vijaykumar, Professor - OB & HRM,Chairperson - Research & Ph.D. IMT Nagpur

Dr. Yerram Raju. B, Regional Director, PRMIA, Hyderabad

Dr. Shahaida .P, Associate Professor –Marketing, ASCI, Hyderabad

Prof. V. Venkaiah, Professor and Head, Department of Business Management, Dr. B. R. Ambedkar

Open University

Dr. M. Kamalakar, Professor - Operations and IT & EVP, SSIM

Dr. V. G. Chari, Professor – Finance & AVP, SSIM

Dr. P.V. S. Sai, Director, Training and Consultancy, SSIM

Dr. S. F. Chandrashekar, Professor - HR, SSIM

Dr. S.V.Ramana Rao, Professor –Finance & Director -Academic, SSIM

Prof. Muralidhar Rao, Professor – Marketing, SSIM.

Dr. K. S. Harish, Associate Professor - QT, SSIM.

Contents

Title Page #

RESEARCH ARTICLES

Exploring the Predictive Power of OSCM Model of Conflict

Management towards Work Productivity- A Comparative

Approach between Public and Private Sector Banks

– Shivani Nischal & G.S. Bhalla 5

Determinants of Households decisions and influence of

Cultural and Demographic factors on Investment Decision

Making - An Empirical study among Salaried Investors

– Suyam Praba. R & Malarmathi. B 19

Investigating Mutual Fund Performance Persistence

– Parag Rijwani 28

Preliminary Performance Analysis of S&P BSE 500 Shariah Index

– Pardhasaradhi Madasu 42

Impact of Inflation on Economic Factors in Indian Economy

– Meenakshi Tyagi & Renu Sharma 50

BOOK REVIEW

The Challenges of Indian Management 59

– Pavan Patel & K.V.S. Krihna Mohan

Copyright: Siva Sivani Institute of Management, Secunderabad, India.

SuGyaan is a bi-annual publication of the Siva Sivani Institute of Management,

NH-7, Kompally, Secunderabad- 500 100.

All efforts are made to ensure correctness of the published information. However, Siva Sivani Institute

of management is not responsible for any errors caused due to oversight or otherwise. The views

expressed in this publication are purely personal judgments of the authors and do not reflect the

views of Siva Sivani Institute of Management. All efforts are made to ensure that published information

is free from copyright violations. However, authors are personally responsible for any copyright

violation.

SuGyaan


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Editorial...

It gives me immense pleasure in presenting before you the combined issues of Volume VI/ Volume-VII, Issue II/ Issue-I- July-Dec,2013/ Jan-June, 2014 of Sugyaan Management Journal of SivaSivani Institute of Management. In its fifth year of existence Sugyaan has received a tremendousresponse from its readers and contributors. Our sincere gratitude to the readers, authors and reviewersfor their support.

In our continuous effort to contribute to the cause of nation building by promoting quality researchthrough thought provoking ideas in the form of research papers, articles, case studies and bookreviews we, in the current issue of Sugyaan, have included six papers from different disciplines viz.,Marketing, Accounts, Finance, Economics, Insurance, Human Resource, followed by a book review.

The first paper titled "Exploring the Predictive Power of OSCM Model of Conflict Management towardsWork Productivity - A Comparative Approach between Public and Private Sector Banks", byShivaniNischal&G.S.Bhalla, used the pre-tested structured questionnaire based upon UdaiPareek'smodel i.e. OSCM (Opinion Survey on Conflict Management) and 9-item work performance instrumentbased upon Minnesota Satisfactoriness Scale (MSS Scale) has been utilized under the study. Theyconcluded that significant impact of conflict management strategies upon the work performance ofthe employees in these selected public and private sector banks under study.

The second paper titled, "Determinants of Households decisions and influence of Cultural andDemographic factors on Investment decision making - An empirical study among Salaried Investors",by SuyamPraba&Malarmathi.K, examined the relationship between the cultural factors like religion,mother tongue, the demographical factors like age, gender, education, life stage, marital status,occupation, work experience, the reference group and investment decision making in households.They concluded that there is a significant associations between these cultural and demographicalfactors on household investment decision maker.

The third paper titled "Investigating Mutual Fund Performance Persistence" by ParagRijwani analyzedthe short run persistence performance of equity diversified growth mutual funds based on threemajor empirical tests: contingency table analysis of winners and losers, chi-squared independencetesting on these tables and Ordinary Least Square (OLS) regression analysis of returns. The studyindicated that there is significant performance persistence in mutual fund returns. This outcome istrue for both the lowest performing and highest performing mutual funds.

The fourth paper titled "Preliminary Performance Analysis of S&P BSE 500 Shariah Index byPardhasaradhimadasu", addressed the Islamic Finance Industry trends and practices with the help ofa proxy by name Shariah Index. Performance of Shariah Index was analyzed against S&P BSE-Sensex, S&P BSE-100, S&P BSE-500 and concluded that there is a strong correlation presents betweenvarious indices.

The fifth research paper titled "Impact of Inflation on Economic Factors in Indian Economy", byMeenaskhi andRenu Sharma examined the impact of inflation on various economic factors viz.,economic growth, investment and household saving rate. They concluded that Inflation has a negativeeffect on growth but positive effect on investment and household savings.

Lastly, we have a book review, "The Challenges of Indian Management" by Pavan Patel and K.V.S.Krishnamohan.

We hope you find this issue interesting and look forward to your feedback.

SuGyaan 5


1. Introduction

“Although conflict management is complex and

sometimes hard to achieve, a greater

understanding of the behavioural skills associated

with it can have a bottom line impact on

organisational productivity.”

-Vincent L. Ferraro and Sheila A. Adams

Conflict is defined as disagreement betweenindividuals. It can vary from mild disagreementsto a win-or-lose, emotion-packed, confrontation(Kirchoff and Adams, 1982). Conflict can be aserious problem in an organisation. It can createchaotic conditions that make it nearly impossiblefor employees to work together. Thomas andScmidt have reported that managers spend 20%of their time in dealing with conflict situations.Hence it is very much important that managersshould understand the serious consequences of

Exploring the Predictive Power of OSCM Model of Conflict Managementtowards Work Productivity -A Comparative Approach between Public and

Private Sector Banks

*ShivaniNischal and ** Dr. G.S. Bhalla

ABSTRACT

Conflict exists throughout environments of all kinds. Although conflict management is complex andsometimes hard to achieve, a greater understanding of the behavioural skills associated with it canhave a bottom line impact on work performance as well as organisational productivity. This researchpaper actually attempts to explore the significant predictors of OSCM model of conflict managementupon work performance or productivity in comparative form among the public and private sectorbanks selected under the scope of the study. For the purpose of study, the sample includes 365 bankmanagers from twenty commercial banks situated in Amritsar, Jalandhar and Ludhiana cities ofPunjab. Ten banks each from public sector and private sector has been selected on the basis ofhighest number of employees (Prowess Software and annual reports of these banks March, 2013).

The pre-tested structured questionnaire based upon UdaiPareek’s model i.e. OSCM (Opinion Surveyon Conflict Management) and 9-item work performance instrument based upon MSS Scale has beenutilized under the study. Various statistical techniques have been employed such as reliability andvalidity analysis, descriptive statistics, weighted average scores, Bi-variate correlation analysis, simpleregression and multiple regression analysis. Overall the findings revealed the significant influenceof two main modes of OSCM model of conflict management upon the work performance of theemployees in both public sector and private sector banks and it shakes the employees’ performanceat significance level.

Keywords: Conflict Management Strategies: Resignation, Withdrawal, Negotiation, Confrontation,Compromise, Arbitration, Appeasement and Defusion; Work Performance and Public& Private SectorCommercial Banks.

JEL Classification Code : D74

*Senior Research Fellow, Department of Commerce & Business Management, Guru Nanak Dev University, Amritsar (143001),Punjab, India, Ct: 8427009718, [email protected].; ** Professor, Department of Commerce & Business Management,Guru Nanak Dev University, Amritsar (143001), Punjab, India.

conflict in organisation so that they can find outtechniques to deal with the relative dysfunctionalimpacts of conflicts. Conflict resolvingapproaches have been suggested by variousacademicians and experts such as Blake &Mouton’s Managerial Grid (1964), Thomas&Killman’s MODE (1976), Rahim’s ConflictResolving Mechanism (1982), Pareek (1982),Knudson, Sommers& Golding, (1980);Billingham& Sack, (1987), Sillars, (1980); Putnam& Wilson, (1982), four Smyth, (1977); Phillips&Cheston, (1979), (Sternberg & Soriano, (1984);Morrill & Thomas, (1992), Nicotera, (1993);Pareek, (1982) and Kindler, (1996) to handle ormanage conflict. Pareek (1982) proposed acontingency model of managing conflict in theorganisations. This model consists of avoidance-approach mode to handle or manageconflict.Rahim’s (1983) model ROCI-II had beendeveloped for the measurement of five styles of

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inter-personal conflicts such as Accommodating,Collaborating, Compromising, Avoiding&Competing and further research should beneeded in the diagnosis of styles of handlinginterpersonal conflict between the employees oforganisation. Further, Rahim et al. (2001) exploredthe relationship between conflict handling stylesand job performance of employees. The findingsrevealed the positive significant influence ofconflict handling modes upon job performanceof employees. Rahim and Psenicka (2004) furtherinvestigated the moderating or mediating effectsof various strategies of the conflict managementupon job performance with significant andpositive relationships in outcomes. Rahim (2010)in his research article “Functional andDysfunctional strategies for managing conflict”revealed that employees who used functionalconflict management strategy attained high levelof job performance than employees who useddysfunctional style of conflict management. Thestudy stressed upon the usage of only functionalstrategy of conflict management because of itssignificant association with better jobperformance and organisational citizenshipbehaviour. Obasan (2011) reviewedconsequentialeffects of conflict and its management uponcorporate productivity with the motive ofsuggesting a valid conclusion to banking industry.Results revealed the significant positiverelationships of work performance and conflict

resolving mechanism adopted in selected banksunder study. Rashid et al. (2012) developedregression model of conflict handling approachesand investigated the impact of conflictmanagement upon team performance. The studyanalysed that how team members adjust withconflict through appropriate conflict managementapproach and how the particular conflict handlingmode impact the effectiveness of team. Data hasbeen gathered from 240 employees of public andprivate sector higher organisations. The resultsamazed that the conflict handling methods had asignificant positive influence upon the teamperformance. This research paper has beendivided into several sections. Firstly; the analysissection deals with studying the overall impact ofconflict management strategies upon the workperformance of the employees; thereby furthersections deal with analysing significantly theimpact of avoidance and approach modes ofhandling conflict upon the work performance ofprivate sector and public sector bank employees.Concluding observations has been discussed inthe final section. Approach mode of conflictmanagement model includes confrontation,negotiation, arbitration and compromise strategieswhereas Avoidance mode includes resignation,withdrawal, appeasement and defusion strategiesto handle conflict in the organisation.

2. Objectives and Research Methodology:

Fig. 1 Approach-Avoidance Styles of Conflict Management (Pareek’s OSCM Model, 1982)

(Source: Training Instruments in HRD & OD by Pareek 2012)

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The main objectives of research paper are toexplore the significant predictors of OSCM modelof conflict management upon work performanceor productivity in comparative form among thepublic and private sector banks selected underthe scope of the study. Further, the sample of thestudy includes 365 bank managers from twentycommercial banks selected each from Amritsar,Jalandhar and Ludhiana economical well off citiesof Punjab. Ten banks each from public sector andprivate sector has been selected on the basis ofhighest number of employees (Prowess Softwareand annual reports of these banks March, 2013).Convenience cum Judgement samplingtechnique had been chosen for the purpose ofstudy. The pre-tested structured questionnairebased upon UdaiPareek’s model i.e. OSCM(Opinion Survey on Conflict Management) hasbeen utilized under the study and workperformance of employees has been measuredwith the help of 9-item Minnesota satisfactorinessscale (MSS Scale) (Dewis, Gibson, Lofquist&Weiss 1970).Hypothesis has been testedempirically through various statistical techniquessuch as descriptive statistics, weighted averagescores, Bi-variate correlation analysis, simple

regression and multiple regression analysis. Thefindings revealed the significant influence of twomain modes i.e. approach and avoidance modeof OSCM model of conflict management upon thework performance of the employees in both publicsector and private sector banks selected understudy.

3. Conflict Resolution Mechanism Adopted inSelected Public and Private Sector Banks

For the purpose under study, the measurementOSCM scale was first put to reliability test andcronbach’s alpha was calculated. It came out tobe 0.71, which was considered satisfactory(Nunnally& Bernstein, 1994). As shown in tableno.1, the mean scores of all the constructs of thestatements concerning conflict managementstrategies has been specified and constructvalidity has been computed with the help ofcronbach’s alpha for each construct or conflictmanagement strategy; that comes out to be greaterthan 0.60 for each construct. This satisfies theconstruct validity of the OSCM scale undertakenfor the research purpose. Table no.1 depicted thedescriptive statistics of various conflictmanagement strategies across public sector banksand private sector banks in comparative form.

Table -1 Weighted Average Scores and Rank Orderings based on WAS of Opinion Survey on Conflict

Management I (OSCM Model)in Public & Private Sector Banks

Coding Variables Public Sector Private Sector Combine Results

(N=181) (N=184) (N=365)

WAS Rank WAS Rank WAS Rank

RR_1 Resignation Strategy (α=0.649) 2.84 8 3.62 4 3.22 5

WW_2 Withdrawal Strategy (α=0.706) 2.93 7 2.40 8 2.66 8

NN_3 Negotiation Strategy (α=0.61) 4.00 1 4.09 1 4.04 1

CC_4 Confrontation Strategy 3.71 3 3.76 3 3.73 4

(α=0.675)

MM_5 Compromise (α=0.696) 3.97 2 3.61 5 3.79 2

TT_6 Arbitration Strategy (α=0.703) 3.69 4 3.84 2 3.76 3

AA_7 Appeasement Strategy 3.23 6 2.77 6 3.00 6

(α=0.65)

DD_8 Defusion Strategy (α=0.692) 3.31 5 2.43 7 2.87 7

Overall Cronbach’s alpha (á) =0.71; [Public Sector Banks under sample: State Bank of India, Punjab NationalBank, Canara Bank, Bank of Baroda, Bank of India, Central Bank of India, Union Bank of India, Syndicate Bankand Indian Overseas Bank; Private Sector Banks under sample: ICICI Bank, HDFC Bank, AXIS Bank, KotakMahindra Bank, Jammu & Kashmir Bank, ING Vysya Bank, Indusind Bank, Karnataka Bank, South Indian Bankand KarurVysya Bank]

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The results (table no.1) indicated that public

sector bank managers used to follow Negotiation

style or strategy mostly to handle conflict with

(WAS=4.00); which is further followed by

Compromise style (WAS=3.97); Confrontation

style (WAS=3.71); Arbitration style (WAS=3.69);

Defusion style (WAS=3.31); Appeasement style

(WAS=3.23); Withdrawal style (WAS=2.93) and

Resignation style (WAS=2.84) of handling conflict

with their respective weightage average scores.

Where in private sector, bank managers mostly

follow Negotiation strategy to handle conflict with

WAS=4.09; followed by Arbitration style

(WAS=3.84); Confrontation style (WAS=3.76);

Resignation style (WAS=3.62); Compromise style

(WAS=3.61); Appeasement style (WAS=2.77);

Defusion style (WAS=2.43) and Withdrawal style

(WAS=2.40) of handling conflict with their

respective weightage average scores. Results

indicated that managers of public and private

sector banks both prefer to negotiate first to

resolve conflict in their relative concerns.

Managers of both public and private sector banks

are least concerned to follow withdrawal strategy

and defusion strategy to handle conflict. Ranks

based on weighted average scores have been

specifically made a clear cut demarcation of the

various strategies or styles preferred by the

managers of selected public, private sector banks

and overall banks. The indicated results (table

no.1) revealed that Negotiation style ranks first

followed by Compromise style; Confrontation

style; Arbitration; Appeasement style; Defusion

style; Withdrawal style and Resignation style of

handling conflict in public sector banks whereas

in private sector banks, Negotiation ranks first

followed by Arbitration style; Confrontation style;

Resignation style; Compromise style;

Appeasement style; Defusion style and

Withdrawal style of handling conflict.

4. Work Performance Instrument (MSS Scale)

Adopted in Public and Private Sector Banks

The mean score and standard deviation for all

statements of work performance scale has been

depicted in table no.2 showing the results of

public sector, private sector and combined areas

in comparative form. The measurement scale was

put to reliability test and cronbach’s alpha was

calculated. The calculated value came out to be

0.628, which was considered satisfactory scale.

The results indicated that the private sector

employees are good performers (WAS=3.56) but

the public sector bank employees are average or

intermediate performers (WAS=3). The overall

combined results depicted the average

performance (overall WAS=3.20) of the

employees working in these selected banks under

study. (Table 2)

5. Relationship between OSCM Model of Conflict

Management and Work Performance Instrument

Further moving towards main objective of the

study i.e., to analyse the significant impact of

conflict management upon work performance of

employees in the selected public and private

sector banks. First of all, Bi-variate correlation

analysis has been applied to check the strength

of association between conflict management and

work performance variables; then regression

analysis has been applied to predict the

significance of the predictor variable i.e. conflict

management towards dependent variable i.e.

work performance. Correlations analysis

demonstrated the significant results in private

sector banks and public sector banks. From the

table no.3, the sign of coefficient of correlation

shows the direction of relationship i.e. positive

relationship which denotes that there is positive

correlation exists between conflict management

strategies and work performance of the employees

working in these public and private sector banks.

(Table 3)

5.1 Simple Regression Analysis

With the help of correlation analysis one can only

comment upon the association of relationship

between the variables but the degree of

dependence can only be calculated with the help

of regression analysis i.e. change in dependent

variable (work performance) with the help of

change in independent variable (conflict

management). Table no.4 displays the results of

simple regression model for work performance

with single predictor variable i.e., conflict

Management.

In table no.4, R square statistic is measure of

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Table 2 :

Descriptive Statistics of Statements of Work Performance Scale (MSS Scale)

Variables Combined Results Private sector Public Sector

Mean S.D. Mean S.D. Mean S.D.

WP1 3.54 1.434 4.17 .974 2.91 1.545

WP2 3.51 1.457 4.10 1.097 2.91 1.536

WP3 3.29 1.472 3.72 1.296 2.86 1.517

WP4 3.27 1.444 3.47 1.414 3.08 1.451

WP5 3.15 1.520 3.69 1.386 2.61 1.459

WP6 3.55 1.420 3.73 1.323 3.38 1.495

WP7 2.15 1.235 2.21 1.184 2.08 1.284

WP8 2.29 1.300 2.85 1.444 1.73 .816

WP9 4.05 1.022 4.13 .924 3.97 1.110

WAS 3.20 3.56 2.83

Valid N (Listwise) 365 184 181

Overall Cronbach’s alpha (α) = 0.628, n=365

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extent to which the total variation of the

dependent variable (work performance) is

explained by the independent variable (conflict

management). A high value of R square in

regression model explain the variation in the

dependent variable i.e. work performance, very

well. A large unexplained variation in the

regression model will increase the standard errors

Model Development

Dependent Variable Work Performance

Independent Variable Conflict Management

The Regression equation for the study would be:

Y= e

Where, Y=Dependent Variable (Work Performance Score);

X= Independent Variable (Conflict Management Score);

α=Intercept/Constant; β= Slope & e=error term.

of the coefficient. The adjusted R2 tells how well

the regression model generalizes. The value of

adjusted R2 came out to be 0.426 which indicates

that 42.60 percent of the total variation in the

dependent variable (work performance) has been

explained by independent variable (conflict

management). Hence the model is a good fit. An

assumption of normal distribution has also been

tested with the help of normal probability curve

and histograms. F-statistics is mean square

(regression) divided by the mean square

(residual). ANOVA, i.e. Analysis of variance has

been performed to test the overall significance of

model. Hence the hypothesis has been tested: H0:

β=0. The table no.4 depicted the value of f-

statistic=271.652** (p<0.01) i.e. highly

significant. Higher the value of F statistic signifies

that it is a good regression model predicting

outcomes. The higher value of f-statistic

(f=271.652**) denotes its significance and

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rejection of null hypothesis stated above. Further,

table no.5 displays the regression coefficients for

regression equation of work performance with

single predictor variable i.e. conflict management.

The value of intercept came out to be 0.878 and

the Column B depicted the value of regression

coefficient for predicting the dependent variable

that is 0.753. The value of regression coefficient

indicates that work performance variable change

by 0.753 units for every unit change in conflict

management variable. So, the conflict

management is very much important to be focused

upon in order to increase the work performance

of the employees working in these selected banks

under study and the sign of regression coefficient

is positive that means conflict management and

work performance variables are positively related.

The regression equation would be framed as:

Y= 0.878+0.753X+e

Where, Y=Dependent Variable (Work

Performance Score) and; X= Independent

Variable (Conflict Management Score)

Simple regression analysis displayed the

significance of overall regression model

(f=271.652**) and value of adjusted R2 is 0.426

that indicates total 42.60% of variation in the work

performance of the employees has been explained

by the independent variable i.e. conflict

management. Overall the regression model is good

fit. At last, Null Hypothesis (H01) that there is

insignificant impact of conflict management upon

the work performance of the overall bank

employees has been rejected and alternate

hypothesis has been accepted which clearly

demonstrated the positive significant impact of

conflict management upon the work performance

of the overall bank employees.

5.2 Impact of Approach Mode and Avoidance

Mode of Handling Conflict upon Work

Performance

Before formulating the model of regression,

Pearson Correlations have been computed to

study the association of relationship between the

various modes of handling conflict i.e. approach

mode (includes negotiation, compromise,

confrontation and arbitration); avoidance mode

(includes resignation, withdrawal, defusion and

appeasement) and work performance variable. Bi-

variate correlation has been applied and variables

have been found statistically significant at 0.01

level of significance. From the table no.6, the sign

of coefficient of correlation shows the direction

of relationship i.e. positive relationship which

denotes that there is positive correlation between

approach mode (includes negotiation,

compromise, confrontation and arbitration);

avoidance mode (includes resignation,

withdrawal, defusion and appeasement) strategies

of handling conflict in the banks and work

performance of the employees working in these

public and private sector banks. (Table 6)

5.2.1 Multiple Regression Analysis- Private

Sector Scenario

Multiple regression has been applied to predict

the significance of the several predictor variables

towards dependent variable. Multiple regression

has been applied in order to ascertain the

significant predictors of OSCM model of conflict

management towards work performance. So in

this section, multiple regression analysis has been

performed in order to study the impact of

avoidance and approach mode of handling

conflict upon work performance of private sector

bank employees.

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The summary of multiple regression model has

been depicted in table no.7. The value of R i.e.

correlation between approach mode, avoidance

mode and work performance come out to be 0.671.

The value of adjusted R2 came out to be 0.444

which indicates that 44.40 percent of the total

variation in the dependent variable (work

performance) has been explained by independent

variables i.e. avoidance mode of handling conflict

and approach mode of handling conflict. The

difference between the values of R2 and adjusted

R2 (0.450-0.444=0.006) is very less that means the

model will give very less variations in the outcome

if it is to be taken from universe rather than from

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sample. Hence the model is a good fit. Before the

application of regression analysis, the problem of

multicollinearity has to be checked otherwise

results of regression analysis will be damaged.

Multicollinearity is a serious problem in

regression analysis and occurs when two or more

independent variables are highly correlated.

(Table 7)

a. Predictors: (Constant), Avoidance Mode of

Conflict Management, Approach Mode of Conflict

Management; b. Dependent Variable: Work

Performance Score (Table 8)

In the current research, correlation matrix has

been generated and no serious problem of

multicollinearity has been found. This correlation

matrix is a powerful tool to judge about the

relationship between variables under study. The

suggested rule by Gujrati, 2008 is that if

correlation coefficient between two regressors is

greater than 0.80, then the problem of

multicollinearity is found very serious. Another

way to check the problem of multicollinearity is

VIF i.e. Variance Inflation Factor, its value should

be below 10 as per rule of thumb but if the value

exceeds (>10) which mean correlation coefficient

is greater than 0.80 and multicollinearity is there.

But in our present analysis, no variable has been

found whose variance inflation factor exceeds 10

(Table no.8). Toleration value is a measure of

correlation between dependent variable and

predictor variables and it can vary between 0 to 1

toleration value closer to 0 signify stronger

relationship between the regressors and

dependent variable. But the variables should not

have low tolerance level otherwise this will pose

the problem of multicollinearity if the value goes

less than 0.20. Hence no problem of

multicollinearity has been found in the present

analysis. The table no.7 depicted the value of f-

statistic=73.946** (p<0.01) i.e. highly

significant. Higher the value of F statistic signifies

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14

that it is a good regression model predicting

outcomes. The higher value of f-statistic

(f=73.946**) denotes its significance and

rejection of null hypothesis stated above and

concludes that one or more partial regression

coefficients have a value ‘“0. The value of á=1.060

and the Column B depicted the regression

coefficients for predicting the dependent variable

that are 0.564 in case of avoidance mode of

conflict management and 0.192 in case of

approach mode of conflict management. The

partial regression coefficients ‘B’ depicted that

work performance variable changed by 0.564 unit

and 0.192 unit for every unit change in avoidance

mode variable and approach mode variable

respectively. This indicates that avoidance mode

and approach modes of handling conflict are very

important to be focused upon in order to increase

the work performance of the employees working

in these selected private sector banks under study

and the sign of regression coefficient is positive

that means these avoidance and approach modes

are positively related with work performance as

dependent variable. Further moving towards the

framing of regression equation, i.e.:

Y= 1.060+0.564X1+0.192X

2+e


Performance Score)

X1= Independent Variable 1(Avoidance Mode of

handling Conflict)

X2= Independent Variable 2(Approach Mode of

handling Conflict)

Multiple regression analysis displayed the


(f=73.946**) and adjusted R2 is 0.444 that

indicated 44.40% variation in the work


by the independent variables i.e. i.e. avoidance

mode of handling conflict and approach mode of

handling conflict. Overall the regression model

is good fit. At last, both null hypothesis [H02 &

H03] that there is insignificant impact of avoidance


handling conflict upon the work performance of

the private sector bank employees has been

rejected and alternate hypothesis has been

accepted.

5.2.2. Multiple Regression Analysis- Public

Sector Scenario

In this section, multiple regression analysis has

been performed in order to study the impact of

avoidance and approach mode of handling

conflict upon work performance of public sector

bank employees.

SuGyaan 15


a. Predictors: (Constant), Avoidance Mode of

Conflict Management, Approach Mode of Conflict

Management; b. Dependent Variable: Work

Performance Score

The summary of multiple regression model has

been given in table no.9. The value of adjusted R2

came out to be 0.405 indicates that 40.50 percent

of the total variation in the in the dependent

variable (work performance) explained by

independent variables i.e. avoidance mode of

handling conflict and approach mode of handling

conflict. The difference between the values of R2

and adjusted R2 (0.411-0.405=0.006) is very less

that means the model will give very less variations

in the outcome if it is to be taken from universe

rather than from sample. Hence the model is a

good fit. Before the application of regression

analysis, the problem of multicollinearity has

been checked and no serious problem of

multicollinearity has been found (table no.10).

Higher the value of F statistic signifies that it is a

good regression model predicting outcomes. The

higher value of f-statistic (f=62.194**) denotes

its significance and rejection of null hypothesis

stated above and concludes that one or more

partial regression coefficients have a value # 0.

(Table 10)

Further, table no.10 displays the regression

coefficients for regression equation of work

performance with two predictor variables i.e.

approach mode and avoidance mode of handling

conflict. The value of α=1.031 and the Column

B depicted the regression coefficients for

predicting the dependent variable that are 0.544

in case of avoidance mode of conflict management

and 0.203 in case of approach mode of conflict

management. The partial regression coefficients

‘B’ depicted that work performance variable

changed by 0.544 unit and 0.203 unit for every

unit change in avoidance mode variable and

approach mode variable respectively. This

indicated that avoidance mode and approach

modes of handling conflict are very important to

be focused upon in order to increase the work

performance of the employees working in these

selected public sector banks under study and the

sign of regression coefficient is positive that

means these avoidance and approach modes are

positively related with work performance as

dependent variable. Further moving towards the

framing of regression equation, i.e.:

Y= 1.031+0.544X1+0.203X

2+e


Performance Score)

SuGyaan


16

X1= Independent Variable 1(Avoidance Mode of

handling Conflict);

X2= Independent Variable 2(Approach Mode of

handling Conflict)

Hence, the overall regression model is good.

Multiple regression analysis displayed the


(f=62.194**) and adjusted R2 is 0.405 that

indicated 40.50% of the total variation in the work


by the independent variables i.e. i.e. avoidance


handling conflict. Overall the regression model

is good fit. At last, both null hypothesis [H04 &

H05] that there is insignificant impact of avoidance


handling conflict upon the work performance of

the public sector bank employees has been

rejected and alternate hypothesis has been

accepted which clearly demonstrated the positive

significant impact of avoidance mode and

approach mode of handling conflict upon the

work performance of the public sector bank

employees. So, concluding observations states the

significant positive relationships of conflict

management in public and private sector banks

towards work performance. If workplace conflict

has been managed properly, it will automatically

improve the work performance of the employees

as well as enhance organisational productivity.

6. Concluding Observations

This research paper mainly deals with

comparative data analysis related to exploration

of the significant impact of OSCM Model of

conflict management upon work performance in

selected public and private sector banks under

study. Hypothesis (H01 to H

05) has been tested

empirically through various statistical techniques

such as descriptive statistics, weighted average

scores, Bi-variate correlation analysis, simple

regression and multiple regression analysis.

Overall results indicated significant impact of

conflict management strategies upon the work

performance of the employees in these selected

public and private sector banks under study.

Avoidance and Approach; both modes of handling

conflict are found significant and valid predictors

of work performance of in selected public and

private sector banks. Further, summary has been

given below concentrating towards major

description of accepted hypothesis and results

obtained (table no.11).

7. Limitations, Suggestions and Managerial

Implications

The present research work is incapable to plug

all the possible sources of errors and

contaminations just because of shortage of time

and resources, also very likely to produce the

genuine results. In the light of above findings,

Effective conflict management is necessary both

in public as well as in private sector banking

organisations. Healthy approaches should be

followed up by identifying particularly the nature,

types, level and extent of conflict in these banks

along with its sources and dysfunctional impacts.

Management should have open communication

policy so that human resources can come closer,

collaborate and make compromises where

possible with the authorities concerned.

Organisational functionaries should make efforts

to conduct seminars and workshops on

organisational conflict from time to time for the

bank employees. It will help employees’ learning

about conflict and its management which in turns

helpful in enhancing individual and

organisational productivity.

If the workplace conflict is managed properly then

it helps the management to achieve its strategic

objectives with the better work performance of

banking staff; positive working environment that

will automatically leads towards high

organisational productivity.

REFERENCES

1. Adebile, O. and Ojo, T. (2012), “Management

of organizational conflict in Nigeria

Polytechnics, an empirical study of the

Federal Polytechnic, Ede Osun State”,

International Journal of Asian Social Science,

Vol.2, No.3, pp. 229-243.

2. Bezrukova, K., Ramarajan, L., Jehn, K.A. and

Euwema, M. (2003), “The Role of Conflict

Management Styles and Content-Specific

Training across Organisational Boundaries”,

SuGyaan 17


retrieved from, http://webpages.scu.edu/ftp/

bezrukova/bezrukov/14249c.doc%20-

%20bes t%20paper%20proceedings .

doc%20KATE.doc.

3. Bose, K. and Pareek, U. (1986) “The dynamics

of conflict management styles of the

bankers”, Indian Journal of Industrial

Relations, July, Vol.22, No.1, pp. 59-78.

4. Islamoglu, G., Boru, D. and Birsel, M, (2008),

“Conflict management styles in relation to

demographics”, Bogazici Journal, Vol. 22, No.

2, pp. 107-140.

5. Nunnally, J. and Bernstein, I. (1994),

Psychometric Theory, McGraw Hill

Humanities/Social Sciences/Languages, 3rd

edition, pp. 251-261.

6. Obasan, K. A. (2011), “Impact of Conflict

Management on Corporate productivity: An

evaluative study”, Australian Journal of

Business and Management Research, August,

Vol. 1 No. 5, pp. 44-49.

7. Pareek, U. (1982), Preventing & Resolving

Conflicts, San Diego: University Associates,

pp. 164-169.

SuGyaan


18

8. Pareek, U. (2012), Training Instruments in

HRD and OD, Tata McGraw-Hill Publishing

Company Limited, New Delhi.

9. Rahim et al. (2001), “A Structural Equations

Model of Leader Power, Subordinates’ Styles

of Handling Conflict, and Job Performance”,

International Journal of Conflict

Management, Vol.12, No. 3, pp. 191-211.

10. Rahim, A. and Psenicka, C., (2004), “Conflict

Management strategies as moderators or

mediators of the relationship between intra-

group conflict and job performance”,

Presented at annual conference of the

International Association for Conflict

Management, Pittsburgh, PA, June, pp. 15-

18.

11. Rahim, A. (1983), “A Measure of Styles of

handling Interpersonal Conflict”, The

Academy of Management Journal, Vol. 26, No.

2, pp. 368-376.

12. Rahim, A. (2010), “Functional and

Dysfunctional Strategies for Managing

Conflict”, paper retrieved from http://

p a p e r s . s s r n . c o m / s o l 3 / p a p e r s . c f m ?

abstract_id=1612886, accessed on Febuary

10th, 2014.

13. Rashid, S, Habib, A. and Toheed, H. (2012),

“Effect of Conflict Handling Approaches on

team performance: A study on Higher

Education”, European Journal of Business and

Management, Vol. 4, No. 12, pp. 96-100.

14. Riaz, M. K., Jamal, W. (2012), “Ethnic

Background and Conflict Management Styles

Preferences”, paper presented at 4th South

Asian International Conferences (SAICON)

retrieved from http://papers.ssrn.com/sol3/

papers.cfm?abstract_id=2187185, accessed

on Febuary 10th, 2014.

15. Thomas K. W. and Schmidt W. H. (1976), “A

survey of managerial interests with respect

to conflict”, The Academy of management

Journal, Vol. 19, No.2, pp. 315-318.

# MJ SSIM VI(II) & VII (I) 1, 2014

SuGyaan 19


1. INTRODUCTION

Household Investment decision maker could be

an individual, the individuals’ spouse, the

individual’s parents or any other members of the

family. There are various studies conducted to

understand the impact of marriage on investment

decisions, gender difference on investment

decisions, occupation on investment decisions

and investment decisions during different life

stage. Investment behaviour is a complex study

is dependent on various variables and degree of

impact of these variables would change from time

to time. Hence this study is aimed to understand

who makes the investment decisions in a family

and the impact of decision making on the

individual’s investment pattern.

2. REVIEW OF LITERATURE

There is an expanding body of literature that

documents evidence of decisions that influence

investment decision-making. Barber and Odean

(2001) specifically document that overconfidence

affects male trading and investment behaviour.

Correspondingly, they show that marriage

ameliorates some of the behavioural biases males

express with respect to investment decisions.

Most any person with a sibling of a different

gender can attest to the fact that occasionally

specific parental decisions seem to be influenced

by the gender of the child affected by the decision.

Determinants of Households Decisions and Influence of Cultural andDemographic Factors on Investment Decision Making – An Empirical Study

among Salaried Investors

*Suyam Praba.R and **Malarmathi .B.

ABSTRACT

This study provides us with an insight on investment decision making in Households. There arevarious factors influencing the investment decisions like cultural, demographical, social, economicalfactors. This study attempts to identify the relationship between the cultural factors like religion,mother tongue, the demographical factors like age, gender, education, life stage, marital status,occupation, work experience, the reference group and investment decision making in households.405 samples from salaried class respondents were considered for the study. The Chi square testresult shows that there are significant associations between these cultural and demographical factorson household investment decision maker.

JEL Classification Code : D14

* Research Scholar, Bharathiar School of Management and Entrepreneur Development, Bharathiar University, Coimbatore,Tamil Nadu, India.;**Professor, School of Management and Entrepreneur Development, Bharathiar University, Coimbatore, Tamil Nadu, India.

Many elements of family structure have been

linked to aspects of financial decision making

behaviour (see, for example, Smith and Ward,

1980; Browning, 1992; Hao, 1996; Keister, 2003).

Smith and Ward (1980) find that young children

depress savings for young families but increase

savings for marriages of duration greater than 5

years. The principal channel through which

children act to reduce savings is the decline in

female earnings associated with the child-induced

withdrawal of wives from the labour force. In

another research study by Nava Ashraf “Spousal

Control and Intra-Household Decision Making:

An Experimental Study in the Philippines

Harvard Business School” found that household

savings and investments typically depend on how

decision making power distributed between men

and women. It also analyzed the fact that,

financial decisions of the household are greatly

affected by the fact that the income is known to

spouses or not. Dev Raj Acharya, Jacqueline S Bell,

PadamSimkhada, Edwin R van Teijlingen and

Pramod Raj Regmi in the study of ‘ Determinants

of Women’s Autonomy in Decision Making’(2010)

aimed to explore the links between women’s

household position and their autonomy in

decision making. M. Hemanta Meitei in the study

titled ‘Education or Earning and Access to

Resources Determining Women’s Autonomy: An

Experience among Women of Manipur’

SuGyaan


20

investigated how far education or earning and

access to resources have a significant impact on

women’s decision making power. He concluded

that, most of the decisions are taken jointly (both

husband and wife) while working women take

more of independent decisions than the non-

working women. Controlling effect of the other

background variables work status of women turn

out a significant explanatory variable rather

education.

3. NEED FOR THE STUDY

This research is done to study the influence of

investment decision making on the pattern of

investment. The preference and selection of

appropriate investment avenues the best suits

their investment objective is determined by

various influencing factors. One such factors aims

for the study is the investment decision maker in

a family. The investment decision making could

be influenced religion, mother tongue, age,

marriage, education, occupation, life stage etc.

The research seeks information to find out

specifically what influences the investment

decisions and their investment process.

4. OBJECTIVE OF THE STUDY

� To analyse the impact of culture of individual

investors on their Investment decision

making.

� To analyze the influence of Individual’s

demographic factors on Investment decision

making

5. HYPOTHESES

H10: There is no significant relationship between

age and household investment decisions H20:

there is no significant relationship between

gender and household investment decisions

H30: there is no significant relationship between

education and household investment decisions


marital status and household investment

decisions


life stage and household investment decisions


occupation and household investment decisions


work experience and household investment

decisions

6. RESEARCH METHODOLOGY

This study presents the impact of individual’s

cultural and demographic factors on investment

behaviour. Keeping this in mind, a schedule was

created among the salaried class individual who

work either for a Bank, NBFC, Insurance

Company, Mutual Fund, IT, ITES, or for Education

institutions. In this study, 405 samples were

considered based on the Krejcie& Morgan

sampling table. It is a Multistage random sampling

method is used for the study. The investment

details were obtained using a structure

questionnaire. The study was conducted in

Coimbatore city and the data collection process

took place during November 2012 to May 2013.

7. ANALYSIS AND INTERPRETATION

It is inferred from the table no: 7.1 that Chi Square

test results shows there is significant association

between Household Investment decisions and the

investors’ age, gender, education, marital status,

life stage, occupation, work experience and most

influential person for investment. It is also

inferred that there is no association between

Household Investment decisions and the

Investors’ religion, mother tongue, SEC

classification and the most preferred Investment

Avenue.


age and household investment decision making

From the Table No. 7.1, it is inferred that the p

value is 0.000 which is lesser than 0.05 (5% level

of significance) hence the null hypothesis is

rejected. Therefore there is significant

relationship between age and Household

investment decisions.It is evident from the Table

No.7.2 that 47.2% of respondents whose age

which is lesser than 25 group state that their

parents take all investment related decisions.

45.3% of respondents of 26-30 age group and 60%

of the respondents of 35 years state they make

self decision on Investment. 29.2% of 31-35 age

group respondents state their spouse make

Investment decisions.

SuGyaan 21


SuGyaan


22


Gender and Household investment decisions

From the Table No. 7.1, it is inferredthat the p




relationship between gender and Household

investment decisions. It is evident from the Table

No 7.3 that 53.8% of male respondents make self

decision on all investment decisions, whereas

33.7% of female respondents have mentioned that

their parents take all investment related decisions.


Education and Household investment decisions





SuGyaan 23


relationship between education and Household

investment decisions.Table No. 7.4 shows that

55.6% of respondents whose diploma holders

have responded that their spouse decide on

investment. 45.3% of respondents who have

completed bachelor degree of education and 50%

of respondents who are professionals state that

they make self decisions on investments. 36.7%

of the respondents who have completed master

degree state their parents make Investment

decisions.


Marital Status and Household investment

decisions.





relationship between Marital Status and

Household investment decisions. From the Table

No. 7.5, it is evident that 48.4% of respondents

who are single and 100% of those who are

widowed have mentioned that their parents make

investment related decisions in their family.

51.6% of respondents who are married and 66.7%

of divorced, take self decisions on investments.


Life stage and Household investment decisions

From the Table No. 7.1, it is inferredthat the p




relationship between Life stage and Household

investment decisions. It is inferred from the Table

No.7.6, that 48.1% of respondents who are single

and 26.8% of respondents who are young couple

without children have mentioned that their

parents make investment related decisions in their

family. 36.0% of respondents who are in the life

stage – young family with mortgage/childcare cost

their spouse make investment related decisions

in their family. 60.0% of those who in the stage

mature family and 64.7% of those preparing for

their retirement take self decisions on

investments.

SuGyaan


24


Occupation and Household investment decisions





relationship between Occupation and Household

investment decisions. It is inferred from the Table

No. 7.7 that 63.5% of respondents who work in

bank and 50.6% of respondents who work in

NBFC take self decisions on investments. 30.0%

who work in Insurance Company state their

spouse make investment decisions in their family.

36.9% of respondents, who work in IT/ITES

Company, and 34.8% of respondents who work

in Educational institution and 29.4% of

respondents who work in Mutual Fund Company,

state their parents take investment decisions in

their family.


Work Experience and Household investment

decisions





relationship between Work experience and

Household investment decisions. It is inferred

from the Table No.7.8 that 43.1% of respondents

whose work experience is below 5 years state their

parents take investment decisions in their family.

21.2% of respondents whose work experience is

SuGyaan 25


between 5 years to 10 years and 27.3% of the

respondents whose work experience is between

15 to 20 years state their spouse make all

investment decisions in their family. 62.5% of

respondents whose work experience is between

10 to 15 years and 75% of those with 20-25 years

of work experience take self decisions on

investments.

8. FINDINGS

• There is significant association between

Household Investment decisions and the

investors’ age, gender, education, marital

status, life stage, occupation, work

experience, most influential person for

investment,

• Youngster (age < 25 years) state their parents

make investment decisions in their family,

middle aged respondents state self decisions

are done on Investments, while elder

respondents claim their spouse as investment

decision makers in family.

• Men mostly make self decisions on

Investments, while women state their parents

make investment decisions in their family.

• Diploma holders state their spouse while post

graduates state their parents about the

Investment decisions in their family.

Undergraduates and professionals claim to

make self decisions on investment.

• Respondents who are unmarried and those

widowed state their parents make investment

related decisions in their family. Married

SuGyaan


26

respondents and also those divorced

respondents state take self decisions on

investments.

• Respondents who are single and respondents

in the Life stage - young couple without

children have mentioned that their parents

make investment related decisions in their

family. Respondents who are in the life stage

– young family with mortgage/childcare cost

their spouse make investment related

decisions in their family. Respondents who

in the life stage - mature family and also those

preparing for their retirement take self

decisions on investments.

• Respondents who work in bank or NBFC take

self decisions on investments. Respondents

who work in Insurance Company state their

spouse make investment decisions in their

family. Respondents, who work in IT/ITES

Company, Educational institution or Mutual

Fund Company, state their parents take

investment decisions in their family.

• Respondents whose work experience is

below 5 years state their parents and those

between 5 years to 10 years state their spouse

make all investment decisions in their family.

Respondents whose work experience is

between 10 to 15 years and 20-25 years take

self decisions on investments.

SuGyaan 27


9. CONCLUSION

In modern era, families getting scattered to nuclear

from the traditional extended family type but still

we find family values are imbibed in the Indian

household culture. It is vital to know the factors

influencing the investment decision making

within households. It is evident from the study

that the investment decision making in a family

is dependent and is associated with the investors’

age, gender, marital status, education, occupation,

work experience and life stage on investment

decisions. Hence it would be interesting for

behavioural study researchers and marketers to

know about the investment decisions making in

household. Such study helps to design and market

financial products and services accordingly for

effective segmenting, targeting and positioning

(STP). It is concluded that decision making in

household is sensitive especially in money

matters. In depth study can be done in future since

such investment decision making in household

may be variable from time to time.

10. REFERENCE

1. Dinesh Gabhane (2013), “Preferences and

significance of demographics on the factors

influencing InvestmentDecisions: A Study of

Investors in Thane City, Maharashtra”, India,

Volume No. 3 (2013), Issue No. 07 (July)

2. Dr. M. Muniraju, Joychen Manuel, (2013), “A

Study on Investor’s Perception towards

Various Avenues of Investment”,

Intercontinental Journal of Finance Resource

Research Review, Volume 1, Issue 9, Pp 14-

22

3. Lalit Mohan Kathuria and KanikaSinghania

(2012), “Investment Decision Making: A

Gender-Based Study of Private Sector Bank

Employees”, The IUP Journal of Behavioral

Finance, Vol. IX, No. 56 1, 2012.

4. Mandeep Kaur and Tina Vohra, (2012),

“Understanding Individual Investor’s

Behavior: A Review of Empirical Evidences”

Pacific Business Review International, Vol.2,

Issue 6.

5. Mittal M and Vyas R K (2007), “Demographics

and Investment Choice among Indian

Investors”, The IUP Journal of Behavioral

Finance, Vol. 4, No. 4, pp. 51-65.

6. Nava Ashraf, (2009), “Spousal Control and

Intra-Household Decision Making: An

Experimental Study in the Philippines”,

American Economic Review 2009, 99:4,

1245–1277

7. NizamettinBayyurt, VildanKarýsýk, Ali

Coskun (2013), “Gender Differences in

Investment Preferences”, European Journal

of Economic and Political Studies - 6 (1)

8. Ravichandran. K (2008), “A study on

Investors Preferences towards various

investment avenues in Capital Market with

special reference to Derivatives”, Journal of

Contemporary Research in Management

9. Singh J and Chander S (2006), “Investors’

Preference for Investment in Mutual Funds:

An Empirical Evidence”, The IUP Journal of

Behavioral Finance, Vol. 3, No. 1, pp. 55-70.


SuGyaan


28

Investigating Mutual Fund Performance Persistence

*Parag Rijwani

ABSTRACT

The performance of the mutual funds depends on the successive effort fund manager to time themarket. The objective of this study is to examine whether the past performance of the mutual fundreflects the present and future performance of the fund in equity diversified growth funds in India fortime 2010-2012. For this study, 188 mutual funds have been observed that exist in the market for thesame time period. The assessment of the persistence in performance in the short-run is done basedon three major empirical tests: contingency table analysis of winners and losers, chi-squaredindependence testing on these tables and Ordinary Least Square (OLS) regression analysis of returns.If past performance is a predictor of future performance, first half ‘superior’ funds in the first periodwould remain as ‘superior’ funds in the next period, second half ‘inferior’ funds in the second halfand so on. It is found that returns exhibit strong evidence of persistence in the selected time period.Funds that performed poorly during a prior year are likely to continue their poor performance duringthe next year and likewise a superior performing fund is likely to continue to perform well during thenext year.

Key Words: Mutual Funds Performance, Persistence of Returns, Diversified Equity Funds

JEL Classification Code : G24

* Assistant Professor, Institute of Management, Nirma University, Sarkhej-Gandhinagar Highway, Ahmedabad – 382 481,Email: [email protected], [email protected], M +91 9898002772

1. Introduction

Mutual funds industry has shown a consistent

growth over a time period in Indian financial

market. The performance of the mutual funds

depends on the market timing ability of the fund

manager and many of the AMCs boast of their

superior performance to attract new investors. All

mutual funds advertisements in media contains

a disclaimer that the performance data featured

represents the past performance which does not

assure the future performance of the fund. And

still all mutual funds boast of their past

performance in the advertisements. Many

economists and investors believe that the funds

are expected to repeat their performance in the

next years. Fund performance is said to be

persistent if, for the consecutive time periods, the

fund return is above or below the median of all

funds after being above or below the median in

the previous period. The performance persistence

is very important for the individual investors

while selecting the mutual funds. As if the

persistence exists, then the funds which

performed poorly during the past year are likely

to perform poorly in the next year also. Similarly,

well performing funds are likely to perform better

again. It is being one of the most popular topics

in mutual funds literature in previous decades

because of the huge market of mutual funds in

US. The persistence studies has focused on the

issue of predicting future performance by using

past performance records. The persistence studies

is central from the viewpoint of the entire

performance measurement as if the past

performance has no prediction power over the

future performance, the data collecting and ex-

post performance evaluation will be useless

procedure from the investor’s view. Investors rely

on managers past risk adjusted performance in

order to assess their ability to generate excess

returns. It is then important to evaluate whether

or not past performance has predictive value for

future performance. From the market efficiency

perspective, the existence of persistent

performance conflicts with the efficient market

hypothesis. This study is an effort to analyse the

performance persistence of the mutual funds in

India.

2. Literature Review

The earliest work on persistence of mutual funds’

performance is paper by(Sharpe, 1966). The

issues raised in this paper include the

SuGyaan 29


performance measure that has to be; considered

while measuring the performance of the funds.

The previous measure that had been used was

Treynor’s ratio which is the ratio of return in

excess of risk-free rate to CAPM (Capital Asset

Pricing Model) beta of the portfolio. But Sharpe

proposed that this approach do not carry firm-

specific risk and best only for well-diversified

portfolio. So, he recommends his own measure

known as Sharpe Ratio (or, reward to variability

ratio), which is the ratio of expected excess return

of a portfolio to its total risk. Using this measure

for 34 mutual funds for previous 20 years period,

Sharpe finds positive though not statistically

significant correlation. The results from the

Treynor’s ratio were also the same.

This study was followed by (Jensen, 1968) who

used the same length of holding period and

selection as Sharpe, but the difference was in the

measurement of the performance. In his study,

he used Jenson’s alpha for mutual fund

performance. He found positive correlation in

performance between selection period and

holding period indicating the funds can be

consistently superior and inferior in the

performance. But Jenson also mentioned that this

persistence is more sound in case of the funds

which had performed inferior in the past. So, the

funds which had performed superior not

necessarily perform superior again in the next

period.

The study of Carlson (1970) based on 57 mutual

funds with sample data for 20 years (1948-1967)

finds that the inter decade rankings based on

Sharpe ratio show no persistence but the rankings

based on volatility does. So, he came out with

the conclusion that the objective of the investment

can influence the performance persistence. He

again tested 33 common stock funds on the same

criteria and found no differences in the results.

Carlson again divided each decade into five year

period and based on the Sharpe ratio, he found

that the funds had the tendency to remain either

in the top or the bottom quartiles (groupings).

Sarnat(1972) examined the performance of 56

mutual funds with the data for 12 years for both

the holding period and selection period. The

performance was based on the General efficiency,

Risk aversion, Mean-Variance and two stage

criterion and efficient sets were formed for

examination. The findings said that the

composition of efficient sets over time was not

stable enough to benefit an investor, or can be

said that the performance persistence was found

to be weak in the study.

Lehmann and Modest (1987) examined the

persistence of fund rankings based on the various

performance measures (Treynor& Black appraisal

ratios, alpha based on the CAPM model, APT

model and total returns) for the 15 year period

sub-divided into three 5-year periods. The study

is considered as a milestone for the performance

persistence measurement as it for the first time

used multifactor models for the performance

measurement. Though the performance

persistence was found but the authors also found

that this also depend upon the performance

measure used. The results showed significant

difference between rankings based on CAPM

model and APT model. So, Lehman and Modest

also stressed on the need of finding the benchmark

performance measure to represent the factors

determining fund returns.

Levy & Lerman(1988) also conducted the study

to work out the predictive power of the

investments decisions also using information

about the riskless assets. The study used the data

for the period of 11 years and the result indicated

that the results are persistent when selection of

efficient sets is based on mean-variance criterion

with riskless asset, or the second degree or third

degree stochastic dominance criterion with

riskless asset. The persistence studies conducted

in 1990s showed a shift of research design in

terms of the shortening of the selection period

and holding period of the data as compared to

the earlier studies that used the data generally

for the longer period.

(Grinblatt & Titman, 1992) examined the

performance persistence of mutual funds over the

time period of 9 years using methodology based

on the eight-portfolio benchmark (P8). The study

showed the positive performance persistence and

this persistence cannot be explained by the

inefficiencies in the benchmark that are related

to firm size, dividend yield, past returns,

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30

skewness, interest rates sensitivity and CAPM

beta. The findings were consistent with the

differences in fees and transaction costs across

funds also remain persistent.

In another study, (Grinblatt & Titman, 1993)

developed a new performance measure named

Portfolio Change Measure that was used to

evaluate the performance on the basis of changes

in quarterly portfolio holdings of 155 funds for

10 year time period. The result showed the strong

evidence of persistence for the entire sample and

weaker evidence for the subsamples of the growth,

aggressive growth and growth-income funds.

In a US based study, (Hendricks, Patel, &

Zeckhauser, 1993) found that in the period 1974–

1988 relative performance of no-load, growth-

oriented mutual funds persisted in the near term,

with the strongest evidence for a one-year

evaluation horizon. A study (Coggin, Fabozzi, &

Rahman, 1993) examined the investment

performance of US equity pension fund managers.

They found that pension fund managers were

good at picking stocks, but poor at timing the

market. The best managers produced substantial

risk-adjusted excess returns. The relative risk-

adjusted performance persistence was found in a

study; however, the persistence was mostly due

to funds that lag the S&P 500, depends upon the

time period observed and is correlated across

managers (Brown & Goetzmann, 1995).

Bond funds underperformed the returns predicted

by a relative pricing model that they developed

by the amount of expenses, on average (Elton,

Gruber, & Blake, 1995). They note that there is no

evidence that managers, on average, can provide

superior returns on the portfolios they manage,

even if they provide their services free of cost.

Grinblatt, Titman and Wermers(1995) found that

mutual funds which bought past winners

(followed a momentum strategy) realized

significantly better performance than other funds.

Brown, Harlow and Starks (1996) looked at

growth-oriented mutual funds and demonstrated

that mid-year losers tend to increase fund

volatility in the latter part of an annual assessment

period to a greater extent than mid-year winners.

Elton, Gruber and Blake (1996a) provide estimates

of survivorship bias that can be used as

benchmarks to determine the amount of bias in

studies that do not take survivorship bias into

account. Elton, Gruber and Blake (1996b) found

persistence in risk-adjusted stock mutual fund

returns. Ferson and Schadt(1996) advocate

conditional mutual fund performance evaluation

in which the relevant expectations are

conditioned on public information variables. This

method made the average performance of the

mutual funds in their sample look better.

Gruber (1996) seeks to solve the puzzle as to why

investors buy actively managed open end mutual

funds when their performance on average has

been inferior to that of index funds. He suggests

that the solution to the puzzle is that if managers

have skill, future performance is in part

predictable from past performance, and this

management ability may not be included in the

price. Ferson and Warther(1996) modified

classical performance measures to take account

of well-known market indicators (interest rates,

dividend yields and other commonly available

variables). This conditional performance

evaluation makes mutual funds’ performance look

better.

Goetzmann and Peles(1997) presented evidence

that cognitive dissonance explains mutual fund

investor inertia. That is, investor aversion to

switching from poor performers may be explained

by overly optimistic perceptions of past mutual

fund performance. Carhart(1997) considered the

persistence in equity mutual funds’ mean and

risk-adjusted returns. He concluded that the

results do not support the existence of skilled or

informed mutual fund portfolio managers. Daniel,

et al. (1997) looked at the performance of equity

mutual funds. Their results showed that mutual

funds, particularly aggressive-growth funds,

exhibit some selectivity ability, but that funds

exhibit no characteristic timing ability.

Indro, et al. (1999) reported that fund size (net

assets under management) affects mutual fund

performance and found that, in effect, 20% of non-

indexed US equity funds were too small and 10%

too large. Ackermann, McEnally and

Ravenscraft(1999) examined hedge fund data

SuGyaan 31


from 1988–1995 and found that hedge funds

consistently outperform mutual funds, but not

standard market indices. However, hedge funds

are more volatile than both mutual funds and

market indices. Incentive fees explained some of

the higher performance, but were not correlated

with total risk.

Chevalier and Ellison (1999) found that mutual

fund managers who attended higher-SAT

undergraduate institutions have systematically

higher risk-adjusted excess returns. Liang (1999)

looked at hedge fund performance. “Funds with

“high watermarks” (under which managers are

required to make up previous losses before

receiving any incentive fees) significantly

outperform those without. Hedge funds provide

higher Sharpe ratios than mutual funds, and their

performance in the period of January 1992

through December 1996 reflects better manager

skills, although hedge fund returns are more

volatile. Average hedge fund returns are related

positively to incentive fees, fund assets, and the

lockup period.”

Edelen(1999) show that the common finding of

negative return performance at open-end mutual

funds is attributable to the costs of liquidity

motivated trading: open-end equity funds provide

diversified equity positions with little direct cost

to investors for liquidity. Blake, Lehmann and

Timmermann(1999)analysed a data set on UK

pension funds. Their main finding was that

strategic asset allocation accounts for most of the

ex post variation of UK pension funds’ returns.

Moreover, the vast majority of funds had negative

market-timing estimates.

Wermers(2000) examined mutual fund databases

and concluded that their evidence supported the

value of active mutual fund management. Liang

(1999) studied hedge fund performance and risk

from 1990 to mid- 1999. Hedge funds had an

annual return of 14.2 percent in this period,

compared with 18.8 percent for the S&P 500

Index, although the S&P 500 was much more

volatile. Kothari and Warner (2001) argue that

standard mutual fund performance measures are

inadequate for detecting abnormal fund

performance. They suggest using event-study

procedures that analyse a fund’s stock trades.

Berk and Green (2004) derived a parsimonious

rational model of active portfolio management.

They state that “the lack of persistence in returns

does not imply that differential ability across

managers is non-existent or unrewarded or that

gathering information about performance is

socially wasteful.” Bollen and Busse(2005)

examine daily mutual fund data, consider

quarterly returns and conclude that superior

performance is a short-lived phenomenon that is

observable only when funds are evaluated several

times a year.

Droms and Walker (2006)analysed fixed income

mutual fund performance persistence for

government and corporate bond funds. According

to this study, the government and corporate bond

funds exhibit remarkable performance persistence

as z-statistics for these are statistically significant.

It showed that if intermediate-term (long-term)

bond returns are higher than long-term

(intermediate-term) bond returns for successive

years, then the z-statistics is positive (or, say that

persistence is positive). By contrast, if higher

returns on intermediate (long) bonds are followed

by a year of higher returns on long (intermediate)

binds, then persistence is negative. Also, they

suggest that the nature of persistence (i.e. normal

vs. perverse persistence) is driven by changes in

interest rates. As the changes in the interest rates

cause market leadership to change from on bond

to another (i.e. higher returns to intermediate or

long term bonds), the nature of persistence

changes. So, the stability of market leadership is

associated with the positive persistence.

Similarly a study (Fortin & Michelson, 2010)

examines the performance persistence of a large

sample of equity and bond fund categories over

the time period of ten years and found significant

performance persistence in mutual fund returns

for all categories except government bond and

corporate bond funds. The outcome tends to be

true for both highest performing as well as lowest

performing funds but do not applies to the funds

in the middle performance categories.

3. Research Problem

The literature appears to support performancepersistence in the past, but the results are mixed.

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32

Also, the studies done in this area are majority inthe developed countries like US, UK etc. Thisstudy is intended to extend the previous researchin the Indian Mutual Fund industry. Thus, thequestion that it addresses is; does the performancepersistence exist in mutual funds in India?

4. Research Objectives

To study the presence of performance persistenceof equity diversified- growth mutual funds inIndia.

5. Methodology

Research Hypothesis: The research will test thehypothesis that diversified mutual funds showsignificant performance persistence over the studyperiod.

H0: The performance persistence does not exist

in the equity diversified- growth mutual funds inIndia.

H1: The performance persistence exists in the

equity diversified- growth mutual funds in India.

Data Source: Secondary data that is collected fromACE Equity database of Accord Fintech Pvt. Ltd.and websites like Value research online, AMFI.

Scope: Equity diversified open ended regularfunds in India that are the survivor for the studiedtime period.

Sampling

Population:The mutual fund industry in India isconsisting of more than forty four Assetmanagement Companies (AMC). There are 202mutual funds scheme in Equity-diversifiedgrowth option as on December 2012 (as per SEBIdata).

Unit:The unit is being the one equity diversified-growth mutual fund scheme.

Size:The sample size is 188 mutual funds withdata for the previous 3 years which is dividedinto sub-period of 3 months each.

Technique:The judgmental sampling is used toselect the sample where the criterion for selectionis the schemes with at least 3 years in operation.

Data:Quarterly mutual fund data are collected fora total of 188 equity diversified mutual fundsthose are in operation during the 3-year period

from December 2009 through June 2014. Thoughthere were total 202 mutual funds were operatingfor the same time period but the data for fewmutual funds was not available, so numberdecreased to 188. The data set consists of quarterlyNAVs data for these funds from the ACE MFdatabase. Returns are calculated as the percentagetotal rate of return for the fund. Table 1 providesthe general characteristics of the dataset for thedifferent time periods.

Data Analysis: First contingency tables are usedto analyse performance persistence. Forcontingency analysis, the funds are categorizedas a “winner” or “loser” in each time period.Winner/Loser (W/L) is determined by comparingeach fund’s return to the median return for thatfunds category (In this case equity diversifiedfunds). If a fund’s return is greater than or equalto the median, it is classified as a Winner. Fundslower than the median are classified as a Loser.On a time period and overall basis the funds aretabulated as Winner/Winner, Winner/Loser, Loser/Winner, and Loser/Loser. The fund return arecalculated using the raw Net Asset Value (NAV)as follows:

Returnt= ∆NAV

t/ NAV

t-1

Cross-Product Ratio reports the odds ratio of thenumber of repeat performers to the number ofthose that do not repeat; that is, {WW*LL)/(WL*LW). The null hypothesis that performancein the first period is unrelated to performance inthe second period corresponds to an odds ratio ofone. In large samples with independentobservations, the standard error of the natural logof the odds ratio is well approximated.

Using the Odds-Ratio the Z-statistic andaccompanying P-value is computed. Additionallythe nonparametric Chi-Square statistic iscalculated to determine the P-value as well.

The odds ratio (OR), its standard error and 95%confidence interval are calculated as under(Altman, 1991)

The odds ratio is given by

SuGyaan 33


with the standard error of the log odds ratio being

and 95% confidence interval

Where zeros cause problems with computation

of the odds ratio or its standard error, 0.5 is added

to all cells (a, b, c, d)

To analyse statistical significance, following

statistics are used:

And,

χ2 = Σ(Oi – E

i)2/E

i

Where O, is the observed number in each bin and

Ei is the expected number in each bin. Π2 follows

a chi-square distribution with 1 degree of freedom

in the case of a two-by-two table and (R -l)*(C- 1)

degrees of freedom in an R by C contingency

matrix.

Another methodology that is used for first

investigation of persistence is OLS regression

analysis, regressing Period 2 performance against

Period 1 performance.

Performance (2) = a + b*Performance (1) + e

Where, “performance” can be cumulative total

returns, cumulative selection returns,

orinformation ratios. Positive estimates of the

coefficient b with significant t-statistics are

evidence of persistence or Period 1 performance

contains useful information for predicting Period

2 performance. In this case the raw returns have

been taken as the measurement of the

performance. Henriksson(1984) and Merton

(1981) suggest the managed portfolio’s return will

exhibit conditional heteroscedasticity because of

the fund manager’s attempt to time the market,

even when stock returns are independently and

identically distributed through time. Breen,

Jagannathan, and Ofer(1986) show the importance

of correcting for heteroscedasticity in return

studies and document the adequacy of White’s

(1980) correction. We use White’s

heteroscedasticity-consistent variance-covariance

matrix. The adjusted i-statistic is calculated as

follows:

t-statistic = Coefficient/ HSCE

whereHSCE is the heteroscedastic-consistent

standard errors.

This regression technique is being used as the

verification technique for the first used

contingency table and odd-ratio results.

6. Empirical Results

Contingency Table and Odd-ratio Results

In table 2, the two-way contingency table shows

the numbers of funds that were winners in both

periods, losers in periods, winners then losers,

and losers then winners. The combined results

of all eleven periods can be seen in the table 3.

From Table 2, it can be seen that the numbers of

funds in the diagonal bins (top left and bottom

right) are relatively higher, providing evidence of

persistence in each quarter interval period.

However, this evidence of persistence is not very

strong for the Q2 2010-Q3 2010 period, Q3 2010-

Q4 2010, Q3 2012-Q4 2012 and Q1 2013- Q2 2014

period which is confirmed by the chi-squared test

with insignificant statistics of 1.36, 0.34, 1.36 and

0.34 respectively. This implies that the

performances in these quarters are independent

of the previous quarter performances. And the

statistics of the remaining time periods are

statistically significant exhibiting the strong

evidence of the performance persistence in

sample.

In table 4, the significance of persistence of returns

is tested by calculation of a z-statistic, which is

distributed normally with a zero mean and a

standard deviation of 1.0. A large positive z-

statistic is obtained when a high percentage of

the “winners” in one period remain “winners” in

the next period tested. When a high percentage

of “winners” in one period become “losers” in the

next period, a large negative z-statistic is found.

Small z-statistics are determined when there is

no clear pattern in the returns. If exactly the same

winners remain winners and the same losers

remain losers between two periods, the z-statistic

would be zero. Statistics are judged at the five-

SuGyaan


34

percent level of significance. Same as chi-square

test, the z-statistic is not statistically significant

for the four time periods, time period 2, 7, 11 and

13. Also, it can be seen that the z-statistic come

to be negative when the number of winners ought

to become the losers in the next time period. The

combined z-statistic is statistically significant

indicating that the one time period performance

affects the next time period performance of the

mutual fund. So, the significant values of the z-

statistics states that the hypothesis of no

performance persistence can be rejected in most

of the cases (13 out of 17 time periods).

Based on the results of the above two tests it can

be concluded that the performance persistence

exists among the equity diversified-growth mutual

funds.

Regression Results

Table 5 consists of the results of the regression

done on the returns as the time period 1

performance as an independent variable and time

period 2 performance as a dependent variable. All

values of t-statistics have been adjusted with

White’s correction to remove the

heteroscedasticity in returns.

The slope for the most of the time periods comes

to be positive and the t-statistics are also

significant for the most of the time periods

exhibiting strong evidence of the performance

persistence. Also, the results are consistent with

both of the parametric tests (Chi-square and odd-

ratio) as the t-statistics for the same time periods

are not significant enough to show the

performance persistence. Only, in one case (time

period 9) there is a contradictory result when the

regression shows no performance persistence and

non-parametric tests show the performance

persistence. So, out of the 17 time periods, the

regression results show that in 12 such periods,

there is the existence of the performance

persistence.

7. Findings

The evidence for persistence of equity diversified

growth fund performance is found. What are the

investment implications of these results? For

equity funds, the implications are simple. With

persistence of selection returns, unless one have

another basis for choosing future winners (i.e.,

one’s selection criteria include information other

than historical performance), the solution is to

rank the performance to match ones investment

objectives. Since there is evidence of persistence

in our study, this may suggest that there are two

types of investors in the market. The first type

being the ‘superior’ investors (that is, investors

with superior information) while the latter type

being known as the ‘momentum’ investors (one

who buys past ‘winners’ and sells past ‘losers’) as

suggested by Grinblatt and Titman (1989) and

(1993)andGrinblatt, Titman and

Wermers(1995)respectively. It is said that both

types of investors contribute to the positive

performance of mutual funds.

8. Conclusions

This study presents the results of an analysis of

equity diversified-growth mutual fund

performance. The study applies the “winner-

winner, winner-loser” methodology as well as

OLS regression methodology to test for short-term

performance persistence in mutual funds from

January 2010 to June 2014 with analysis done on

the quarterly basis. We use the non-parametric

Odds-Ratio and Chi-Square tests to examine

significance in performance persistence for the

first methodology. Similarly, the regression results

are adjusted for the heteroscedasticity because of

the time-series data using White

heteroscedasticity variance matrix. We found that

there is significant performance persistence in

mutual fund returns. This outcome is true for both

the lowest performing and highest performing

mutual funds.

Investors of mutual funds face two important

decisions viz. selecting and mutual fund scheme

for investments and reviewing the performance

of the existing mutual funds schemes. Both these

decisions involve a careful dissection of attributes

of the mutual fund scheme. Past return is one of

the important variable used in fund selection and

evaluating the performance of the fund as a part

of review. The question is, do past returns matter?

Does it make any sense to choose a mutual fund

that has performed consistently in the past? After

all, there is no guarantee that it would continue

to perform well in future. The disclaimer of ‘past

SuGyaan 35


performance is not indicative of future’ is valid.

However, the empirical results here suggest that

past performance persist in future.

The results of this study are important to

individual investors when selecting mutual funds.

Investors should be cognizant of previous returns

for any funds under consideration. If a fund

performed poorly during the past year, it is likely

the fund will continue to perform poorly in the

next year. Likewise if a fund performed well

during the past year, it is likely the fund will

perform well during the next year. Note that

persistence appears to exist for the best and worst

performing fund categories. Therefore, an investor

selecting funds in the middle performance

categories is not likely to see the same persistence

in returns.

As a caveat we understand that there is

survivorship bias when performing mutual fund

research. A fund must have survived across the

study period are included, so funds that under-

performed and were subsequently closed to

investors are not included in this study. Some past

researchers have considered this dropping of

samples as bias against finding significant

performance persistence for the worst performing

quintile of funds.

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42

PRELIMINARY PERFORMANCE ANALYSIS OF S&P BSE 500 SHARIAHINDEX

Pardhasaradhi Madasu*

ABSTRACT

This study is motivated by the impressive growth of Islamic Finance Industry. Islamic investmentsfollow the Shariah guidelines. Shariah is the Muslim law which regulates many aspects of a Muslim’slife including the type of investments allowed. The concept of Shariah has brought in major changesin the finance and investment world. In one way a new sub-segment named ‘Islamic Finance Industry’has taken shape. Islamic finance industry has undergone a transformation in the last few years.Today it has started asserting itself as an alternate system of finance. Diverse Shariah compliantfinancial products, which include banking products like savings and current accounts (based onWadia and Qard), (Mudarabah based) investment accounts, financing products such as Homefinancing and Ijarah, insurance products and capital market products like Mutual Funds, PortfolioManagement Services and Stock broking, are being offered in both Muslim and secular countries.Shariah prohibits investments in companies which indulge in business activities prohibited by Shariah.So, Shariah compliant stocks are those stocks whose income is not derived from prohibited activities.Stocks are screened for Shariah compliance by using certain Shariah screening norms. “TaqwaaAdvisory and Shariah Investment Solutions (TASIS) Pvt. Ltd” is the leading Shariah advisory institutionin India; it has formulated norms for Shariah screening of Indian stocks, which are widelyacknowledged and accepted in the country. Following the popularity of Shariah investments theinvestors were looking for a benchmark index that could be used for comparing the returns on theShariah compliant stocks. In 2006, S & P Dow Jones Indices introduced the S & P Shariah Indices.On Feb 19, 2013, S & P Dow Jones Indices and the Bombay Stock Exchange have created S & P BSE500 Shariah Index. This index was designed to represent all Shariah compliant stocks of the broadbased S & P BSE 500 Index. The present paper is an attempt to analyze the performance of theIndian Shariah Index.

Key Words: Islamic Finance, Shariah Compliant Stocks, and Shariah Index.

JEL Classification Code : G10

*Associate Professor, Siva Sivani Institute of Management, Kompalli, Secunderabad, Mobile – 07799207014; e-mail :[email protected]

1.0 Introduction

Islamic finance industry has undergone a

transformation in the last few years. Today it has

started asserting itself as an alternate system of

finance. This industry has made a mark by its

rapid growth not only in Muslim countries but

also in other secular and developed nations as

well. As per the Report of PriceWaterCoopers in

2009 Muslims represent 25% of the World’s

Population, but less than 1% of global financial

assets are Shariah compliant1. It is believed that

a growing Muslim population base, with wealth

geographically concentrated in the Middle East,

is underserved by the current Islamic Financial

Service providers. Further, the E & Y Report in

2010 states that the market for Islamic products

is growing 15 – 20% per year. The reason for low

participation by Muslim investors can be traced

to strict dictates of The Shariah. As per the

ShariahMuslim investors should ensure the

income they earn adheres to the guidelines of The

Shariah2. Their earnings should be pure and

choice. The Shariah guidelines prohibit financial

involvement with companies such as

conventional banks, casinos and alcohol

producers. Another key element of Islamic

investing is the avoidance of interest, or Riba. All

these strict guidelines make it difficult to Investors

who have faith in Islam to invest in companies

because they cannot screen these companies on

individual basis. Initially, to choose Shariah

compliant investments the investors used to

approach investment advisors and these advisors

used to suggest the investment avenues. In short,

the investors who had strong faith Islam were

investing based on the Shariah Investment

Solution provided by the advisors. However, over

a period of time there was a change in the

perception of the regulators and leaders of

SuGyaan 43


financial markets and a need was felt for tapping

these untapped markets by introducing the

Shariah compliant financial products3 that

adheres to Shariah guidelines.

Shariah prohibits investments in companies

which indulge in business activities prohibited

by Shariah. So, Shariah compliant stocks are those

stocks whose income is not derived from

prohibited activities. Stocks are screened for

Shariah compliance by using certain Shariah

screening norms. There are two steps involved in

Shariah screening of stocks, Firstly, screening on

the basis of activity and secondly, financial

screening. Stocks or companies which pass both

the criteria are known as Shariah compliant stocks

or companies.

There are several Shariah screening institutions

which have formulated their own Shariah

screening norms under the guidance of their

respective Shariah Boards. The better known

screening norms in use around the world are those

of AAOIFI, Dow Jones, MSCI, S&P and TASIS. In

the first step of the screening process, companies

which are involved in prohibited business

activities are screened out4. The companies which

pass the business screening test are termed as

“Business compliant” and they are put through

financial screening by further applying the

financial norms5. The business compliant

companies or stocks which qualify on the three

financial screening criteria are termed as Shariah

compliant companies. Investment in such Shariah

compliant stocks is called Shariah compliant

investment. Financial institutions like Mutual

Funds, Insurance, Portfolio management services,

etc. are using these Shariah compliant stocks to

build profitable Shariah compliant investment

portfolios and offer Shariah compliant investment

products to Shariah conscious investors.

Out of the available investment vehicles the

preferred Islamic investment format is ‘Equity’6.

The reason for the ‘Equity’ to be preferred for

Shariah investment is that ownership comes along

with equity and equities do not confer any assured

benefits on the holder7. In fact the shareholder

could even stand to lose his entire capital in the

event the company in which he has invested

suffers massive losses. Nor does equity investment

necessarily involve the element of randomness

and uncertainty associated with gambling and

games of chance. The rights and obligations of

the parties too are clearly defined and do not

involve exploitation or injustice. Because of the

importance of ‘Equities’ in the Shariah investment

many stock exchanges have started constructing

and publishing ‘Equity Indices’ based on Shariah

compliant companies. Shariah-compliant indices

were introduced by globally reliable indices’

providers including Dow Jones, FTSE, Standard

& Poor’s and Morgan Stanley. All Islamic indices

follow a common stock selection process which

is termed as stock screening. While basic

prohibitions and Shariah rules are strictly

maintained in the screening process, different

indices may differ in some screening criteria. The

benchmarks from which Islamic indices are

selected are well-recognized conventional

indices. In this background, the present paper has

the following objectives of study:

1. To understand the conceptual framework of

Shariah Compliant Indices

2. To conduct wide review of literature relating

to the performance analysis of Islamic Equity

Indices

3. To study the performance of S & P BSE

SHARIAH INDEX

4. To conduct a comparative analysis of BSE

Sensex and BSE Shariah Index

2.0 Literature Review

Many of the studies that have dealt with Islamic

investment or Shariah investment had brought

in the dimension of ethical investment. The

literature related to social responsible investing

and also ethical investing are both relevant to the

present study. The present study being dedicated

on the performance analysis of Shariah Index or

Islamic Index has focused on the literature relating

to the performance analysis of Islamic Index or

ethical funds. Majority of these studies followed

the same methodologies of comparing the

performance of DJIMI to other benchmarks but

the choices are quite different from one research

to another in terms of performance measures and

benchmarks. Some of the studies have analyzed

the performance of the FTSE Islamic indices.

SuGyaan


44

The initial studies relating to comparative

performance of ethical and non-ethical funds in

the UK were conducted in 1995 by Mallin,

Saadouni, and Briston. They have stated that

ethical and non-ethical funds were not able

outperform the overall market but they have

found that ethical funds performed better than

non-ethical funds. The measurements used for the

analysis were traditional risk-adjusted

measurements such as the Jensen alpha, the

Sharpe ratio, and the Treynor ratio.

Among the studies that are focused on the Islamic

Equity Indices the study conducted by Atta (2000)

may be referred as the earlier study. The study

used the Dow Jones Market Index (DJIMI) for

understanding the performance of Islamic equity

indices.

The present study being performance analysis of

BSE Shariah Index draw much of its motivation

form study conducted by Ahmad and Ibrahim

(2002) which compared the performance of

Malaysia Stock Indices such as KLSI with that of

KLCI over the period from 1999 to 2002. They

used various methodologies to investigate the

performance, measured by the risk and return of

both indexes. Among the techniques used were

the adjusted Sharpe ratio (SR), the Treynor Index

(TI), the adjusted Jensen Alpha, and the t-test for

comparing the means. They divided the sample

into three periods: the overall sample, the period

of growth from April 1999 to February 2000 and

the period of decline from March 2000 to January

2002. In comparing the raw returns and risks

during 1999–2002, they concluded that for the

overall and the declining periods, the return was

low for KLSI, while for the growing period the

KLSI slightly outperformed the KLCI. In terms of

risk, the KLCI was riskier than the KLSI over

1999–2002. When comparing the means, the

results were statistically insignificant. In addition,

the KLSI reported lower risk-adjusted returns than

the KLCI, except during the growing period 1999–

2000.

Study conducted by Hakim and Rashidian (2002)

has examined the risk and returns of Islamic stock

market index in US by using cointegration

analysis and causality analysis to investigate the

relationships among the Dow Jones Islamic

Market Index (DJIMI), the broad stock market

represented by the Wilshire 5000 Index, and the

risk-free rate proxies by 3-m T-bill, but found no

visible link among them. The results showed that

the Islamic index was influenced by factors

independent from the broad market or interest

rate. In one way the study has differed from the

claim of Dow Jones Inc. that the index exhibits

significant high correlation with the broad market.

The new evidence suggested that such correlation

was merely temporary and spurious. However,

their findings suggested that the Islamic index

presents unique risk-return characteristics, which

are known as company or unsystematic risk and

returns, an observation reflected in a risk profile

significantly different from the Wilshire 5000

Index. This result is even more important given

the fact that the Wilshire 5000 Index is

considerably more diversified than the Islamic

index.

Hussein and Omran (2005) studied the

performance of the Islamic index in the Dow Jones

against the Dow Jones index from 1995 until 2003

based on monthly data. The sample was divided

into three sub-periods: the entire period, the bull

period and the bear period. Their results

suggested that the Islamic index outperformed the

non-Islamic index both in the entire and bull

periods, while the opposite is true for the bear

period; however, it was not statistically significant

in the bear period. Similr study by Elfakhani,

Hasan, and Sidani (2005) investigated the

performance of the Islamic mutual funds in

several emerging countries (including Malaysia).

They concluded that there was no statistically

significant difference between Islamic and

conventional funds. Therefore, the screening

mechanism does not affect the performance of

Islamic investments.

Review of literature indicates that there is no

definite proof that the ethically screened or

socially responsible or Shariah compliant stocks

or funds are outperforming the conventional or

traditional stocks or funds. Further, the studies

relating to Islamic Equity Indices have also

revealed diverse results.

SuGyaan 45


3.0 Data and Methodology

The data for the study has been collected from

the BSE and S & P Dow Jones Websites. The study

being descriptive and exploratory in nature has

used fundamental statistical tools such as

averages, standard deviation and correlation to

analyze the performance of the Index under study.

The period of data collection is from 1st Aug, 2009

to 31st July, 2014. In total the closing index values

of five indices BSE has been collected – SENSEX,

BSE 100, BSE 500, BSE 500 Shariah Index.

4.0 Data Analysis

For analyzing the Index the following

methodology has been adopted. Table 1 and

Figure 1 indicate the sector8 wise composition of

the indices. The Shariah Index is composed

mostly of companies from Information

Technology and Health Care Sector. The

combined contribution of both Information Tech.

and Health Care Sector in the Shariah Index is

48.3% which is nearly 50 % of the Index weight.

On the other hand Sensex, BSE 100 and BSE 500

has given more weightage to Financial Sector and

Information Technology. The combined weight of

Financial andInformation Tech. Sector in the

Sensex, BSE 100 and BSE 500 is equal to 43%

approx. The main reason for low weightage for

financial services firms in the BSE Shariah Index

is that these firms are non-shariah compliant as

per the Islamic Law.

Table 2 depicts the Market Capitalization across

all the premium indices of BSE in comparison

with Shariah Index. Table 3 illustrates the

comparative risk and return analysis. The ‘Total

Return’9 of Shariah Index for all the time periods

(viz. 1 yr, 3 yr. and 5 yr) is higher than the

benchmark index Sensex. The total return of

Shariah index when compared to BSE 100, BSE

200 and BSE 500 for 1 yr period is lower but when

the total return for the said indices are compared

for 3 and 5 years periods the Shariah index is

showing superior performance. The Shariah index

is shown superior performance (in all the three

periods) over other indices based on basic risk

measure ‘Standard Deviation’.

Table 4 depicts the correlation between the

Shariah index and other BSE Indices. The

correlation between these indices is very high (>

0.50)10.

6.0 CONCLUSION

The need for creating a conducive environment

for socially responsible and ethical investing has

been felt from long time. However, in the recent

past both emerging economies and the developed

economies have started to put regulations in place

such that financial products which are attractive

to ethical investors are freely available in the

financial markets. In this background Shariah-

compliant investing has grown considerably in

recent decades. The investors who believe in

Islamic Law wanted a transparent market

mechanism for trading equity and other Shariah

Compliant equity products. In this background

the stock exchanges have started to partner with

popular index service providers to construct and

publish indices that are Shariah-Compliant.

Analyzing the performance of these variant of

indices will be useful for proper portfolio

management.

References

1. Ahmad, Z., & Ibrahim, H. (2002). A study of

the performance of the KLSE Syari’ah index.

Malaysian Management Journal, 6(1), 25–34.

2. Elfakhani, S., Hasan, M. K., &Sidani, Y.

(2005). Comparative performance of Islamic

versus secular mutual funds. Paper presented

at the 12th Economic Research Forum,

University of New Orleans, US.

3. Hakim, S., &Rashidian, M. (2002). Risk and

return of Islamic stock market. Paper

presented at the Presentation to Economic

Research Forum Annual Meetings, Sharjah,

UAE, October 2005

4. Hussein, K. (2005). Islamic investment:

Evidence from Dow Jones and FTSE indices.

Paper presented at the International

Conferences on Islamic Economics and

Finance, Indonesia.

5. Hussein, K., &Omran, M. (2005). Ethical

investment revisited: Evidence from Dow

Jones Islamic Indexes. Journal of Investing,

14(3), 105–124.

SuGyaan


46

6. Iqbal, M. 2002. Islamic Banking and Finance:

Current Developments in Theory and

Practice. Islamic Foundation, Leicester, UK.

(Footnotes)

1In India, several prominent studies in recent

years have found that Muslim participation in the

country’s financial system is minimal. The Sachar

Committee Report (2006) found that nearly half

of India’s Muslim population was excluded from

the formal financial sector. The committee among

other things observed that the creation of the

index will help promote financial inclusion of the

Muslims in India and attract investment flows

from international funds that must adhere to

Shariah norms.

2Investment in Shariah compliant stocks is not

meant only for Muslims; socially responsible

investors of any faith could invest in these stocks

as, in effect, the process of Shariah screening

removes companies deemed to be socially

harmful.

3Diverse Shariah compliant financial products,

which include banking products like savings and

current accounts (based on Wadia and Qard),

(Mudarabah based) investment accounts,

financing products such as Home financing and

Ijarah, insurance

products and capital market products like Mutual

Funds, Portfolio Management Services and Stock

broking, are being offered in both Muslim and

secular countries.

4The prohibited sectors include interest based

financial institutions such as banking, insurance,

brokerage financial products and provision of

fund based financial services, manufacture,

distribution and sale of potable alcoholic

beverages and narcotics, processing, distribution

and sale of pork and pork related products, meat

and products of other animals killed in a non-

halal manner, gambling and tobacco.

5Norm 1 - Their total interest-bearing debt

(including from banks, financial institutions,

public deposits and inter-corporate deposits) and

issued preference capital should not be greater

than 25% of their total assets,

Norm 2 - Their interest income from all sources

and 8% of interest-based investments should not

exceed 3% of their total income,

Norm 3 - Their receivables and cash & bank

balance should not be greater than 90% of their

total assets

6 Preferred Stock and Convertible Stocks are not

compliant with the Shariah Investment. On the

other hand ETF or ETNSs and REITS are Shariah

Compliant.

7 Due to the prohibition of interest, the need for

equity markets is higher in Islamic finance (Iqbal

2002).

8 Based on GICS Sectors

9 The Total Return Index is different from the Price

Return Index. A Price Index considers only the

capital gains viz. changes in prices over a period

of time. The Total Return Index (TR) measures

the performance by assuming that all cash

dividends are reinvested.

10 Islamic indices are subsets of conventional

benchmarks that include only those companies

passing rules-based screens for Shariah-

compliance. The resulting Shariah indices tend

to be highly correlated to their conventional

counterparts and provide Islamic investors with

Shariah-compliant versions of a wide variety of

popular benchmarks.


SuGyaan 47


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48

SuGyaan 49


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50

Impact of Inflation on Economic Factors in Indian Economy

*Dr.Meenakshi Tyagi and **Renu Sharma

Abstract

When economic development process starts it brings the quantitative and qualitative changes in themultiple areas of an economy like development of human capital, critical infrastructure, savingand investment, regional competitiveness, environmental sustainability, socialinclusion, health, safety, literacy, and other initiatives. But on the other hand, economy has tobear the inflationary pressures during the process of development. Indian economy also finds itsname in the list of developing economies that is why for a fairly longer period of time Indian economyhas been fighting with the problem of inflation because of increasing demand put forward byuncontrolled population, low growth rate in agro products, investment in long gestation projects,hoardings and black money. From time to time Indian government has been using various monetaryand fiscal measures to control the inflation but all went in vein and still inflation is hamperingIndian economy. The present study shows the impact of inflation on economic factor and examinesthe interrelationship between economic growth, investment and household saving rate throughvarious statistical tools like correlation, regression and t-test. To accomplish the purpose past 12years data have been taken. The result shows that Inflation has a negative effect on growth butpositive effect on investment and household savings. Due to the unavailability of required secondarydata the research is limited to few economic factors. Still these findings for Indian economy withwidely divergent values of aggregates are very relevant for development policies and strategies.

Keywords: Economic development, Inflation, Investment, Household Savings, GDP

JEL Classification Code : E60

*Assistant Professor, MBA Deptt, KIET, Ghaziabad, [email protected], [email protected], Address- 3/1228, vasundhara, Ghaziabad, (U.P.), PIN-201012, Mobile- 9540806623.; **Assistant Professor, MBA Deptt, KIET, Ghaziabad,[email protected], Address- B-9,Krishanpura, Modinagar (U.P.), Pin- 201204, Mobile- 7500149806.

Introduction

In developing nations Economic development

brings the quantitative and qualitative changes

in the economy which includes multiple areas,

like development of human capital, critical

infrastructure, saving and investment, regional

competitiveness, environmental sustainability,

social inclusion, health, safety, literacy, and other

initiatives. During the development process, huge

investment is made to develop social overhead

capital (SOC) which generates a smooth path for

direct productive activities (DPA). Because of long

gestation period of SOC, an economy has to bear

the inflationary pressures during the process of

development. The impact of inflation can be seen

in each and every area of an economy when

development process starts. But if inflation

continues to rise in long run, it has negative

impact on growth rate.

Inflation is a rise in the general level of prices of

goods and services in an economy over a period

of time. When the general price level rises, each

unit of currency buys fewer goods and services.

Consequently, inflation also reflects erosion in the

purchasing power of money – a loss of real value

in the internal medium of exchange and unit of

account in the economy.Inflation impacts every

citizen of a country. It also leads to reduction in

investors’ confidence in the economy due to price

uncertainty. So, RBI strives to maintain a moderate

level of inflation that is good for the economy. A

chief measure of price inflation is the inflation

rate, the annualized percentage change in a

general price index (normally the consumer

price index over time). Many developing countries

use changes in the Consumer Price Index (CPI)

as their central measure of inflation. Consumer

Price Index or CPI measures the average prices of

goods and services that we, the consumers, have

paid for. There are 8 groups in which CPI is used.

They are: education, apparel, foods and beverages,

communication, transportation, recreation,

housing, and medical care. Other services like

school and government registration fees and

electricity and water bills are sometimes counted

aswell.

SuGyaan 51


However, this method is unsuitable for use in

India, for structural and demographic reasons.

CPI numbers are typically measured monthly, and

with a significant lag, making them unsuitable

for policy use. This is why the Wholesale Price

Index, is used to measure inflation rate in India.

Now since September 2010 with the introduction

of new base year 2004-05, each week the

wholesale price of a set of 676 goods is calculated

by the Indian government.

The WPI measures the price of a representative

basket of wholesale goods. In India, this basket is

composed of three groups: Primary Articles

(20.1% of total weight), Fuel and Power (14.9%)

and Manufactured Products (65%). Food Articles

from the Primary Articles Group account for

14.3% of the total weight. The most important

components of the Manufactured Products Group

are Chemicals and Chemical products (12%);

Basic Metals, Alloys and Metal Products (10.8%);

Machinery and Machine Tools (8.9%); Textiles

(7.3%) and Transport, Equipment and Parts

(5.2%).

The inflation rate in India was recorded at 8.79

percent in January of 2014. Inflation Rate in India

averaged 9.83 Percent from 2012 until 2014,

reaching an all time high of 11.16 Percent in

November of 2013 and a record low of 7.55

Percent in January of 2012. These days economies

of all countries whether underdeveloped,

developing as well developed suffers from

inflation. Inflation or persistent rising prices are

major problem today in world. Because of many

reasons, first, the rate of inflation these years are

much high than experienced earlier periods.

Second, Inflation in these years coexists with high

rate of unemployment, which is a new

phenomenon and made it difficult to control

inflation.

The Indian economy has been registering

stupendous growth after the liberalization of

Indian economy. In fact, till the early nineties

Indians were used to ignore inflation. But, since

the mid-nineties controlling inflation has become

a priority. The natural fallout of this has been that

we, as a nation, have become virtually intolerant

to inflation. The opening up of the Indian

economy in the early 1990s had increased India’s

industrial output and consequently has raised the

India Inflation Rate. While inflation was primarily

caused by domestic factors (supply usually was

unable to meet demand, resulting in the classical

definition of inflation of too much money chasing

too few goods), today the situation has changed

significantly.

Inflation today is caused more by global rather

than by domestic factors. Naturally, as the Indian

economy undergoes structural changes, the causes

of domestic inflation too have undergone tectonic

changes. The main cause of rise in the rate of

inflation rate in India is the pricing disparity of

agricultural products between the producer and

consumers in the Indian market. Moreover, the

sky-rocketing of prices of food products,

manufacturing products, and essential

commodities have also catapulted the inflation

rate in India. Furthermore, the unstable

international crude oil prices have worsened the

situation. High prices of day-to-day goods make

it difficult for consumers to afford even the basic

commodities in life. This leaves them with no

choice but to ask for higher incomes. Hence the

government tries to keep inflation under control.

Literature Review

In the literature of inflation, the most attention

has been paid to maintain an appropriate rate of

inflation which could have a favourable impact

on macro economic factors, required for a smooth

growth rate in an economy. Inflation affects

numerous macroeconomic factors economic

growth rate, savings, investment, employment,

foreign exchange rate, etc. The rate of these factors

is widely varying across the nations and so also

their economic growth. The effect of inflation on

savings, however, is ambiguous both in theory and

practice (Heer and Suessmuth, 2006; and Deaton

and Paxson, 1993). This is why the relationship

between inflation and growth remains a

controversial. Originating in the Latin American

context in the 1950s, the issue has generated an

enduring debate between structuralistsand

monetarists. The structuralists believe that

inflation is essential for economic growth,

whereas the monetarists see inflation as

detrimental to economic progress. Empirical

SuGyaan


52

evidence about the relationship of inflation and

growth also differs with some studies finding a

negligible effect of inflation on growth (e.g. Chari

et al., 1996), some finding a negative effect

(Chopra, 1988; Fischer, 1993; Gylfason and

Herbertsson, 2001) and some studies providing

an evidence of positive effect (Dholakia, 1995;

Mallik and Chowdhury, 2001). The effect of

inflation on economic growth in theory is largely

through the sub-optimal use of resources and

distorted investment decisions due to inflation

(Miller and Benjamin, 2008; Paul et. al., 1997).

However, it is also found in practice that economic

growth is also led by inflation. On the other hand,

higher growth can lead to reduced inflation.

(Dholakia R. H., 1990). Thus, the relationship

between growth and inflation may also be bi-

directional. This ambiguous relationship between

inflation and growth implies that though rising

inflation may have associated growth costs, policy

efforts to contain inflation could negatively affect

growth. On the other hand, allowing inflation at

higher rates could lead to higher growth although

it may cause some distorted choices. Relationship

between inflation and savings is critical in

understanding this complex trade-off between

growth and inflation particularly for the policy

makers.

There are broadly two types of theoretical

expectations concerning the effect of change in

average inflation level on output growth (Chari

et al., 1996). One expectation, based on exogenous

growth models, is that inflation rate will have no

effect on the growth rate as well as the level of

output. As opposed to this, the endogenous

growth models emphasize that money and

inflation do affect the growth rate of output itself.

There are two channels for such an effect. One

argument is known as the Mundell-Tobin effect

in which a more inflationary policy enhances

growth as investors move out of money and into

growth enhancing capital investment. This is

because inflation reduces the wealth of people,

and for accumulating the desired wealth, people

save more, decreasing real interest rate and

driving up capital accumulation (Haslag, 1997).

It is possible, however, to argue that inflation in

such a case would affect savings and investment

decisions essentially by increasing the

uncertainties with regard to the real rates of

return. This can actually reduce the productive

capital and hurt the output growth (Motley, 1994;

and Miller and Benjamin, 2008).

Growth, savings, investment, employment and

inflation are interrelated variables and should,

therefore, be endogenously determined

simultaneously in the system. However, most of

the studies on these variables do not analyze them

in a simultaneous equation framework. It is

important for a policy maker to understand the

dynamics among economic growth, savings and

inflation in the system. If inflation increases, it

also raises the consumption expenditure which

results in low household savings. The effect of

inflation on savings depends on the way

households react to increase in inflation (Chopra,

1988). If households direct their savings from

financial to physical assets and consumer

durables, then due to increase in consumption of

consumer durables, present savings will decline.

Most of the studies examining the relationship

between inflation and growth end up focusing on

the effect of inflation on savings and investments

and thereby on the growth of the economy,

assuming independence of the incremental

capital output ratio (ICOR) from inflation. Except

Chopra (1988), the ICOR channel of the effect of

inflation on growth is not seriously examined in

the literature. Thus, if inflation leads saving rate

to increase and ICOR to decrease, inflation will

definitely promote growth, but the reverse would

be true if saving ratio decreases and ICOR

increases with inflation. If both these variables

increase or decrease simultaneously as a result of

inflation, the magnitude of the statistical impact

of inflation on these two variables would

determine the sign of the relationship between

inflation and growth. Chopra (1988) argued that

inflation would affect the ICOR by changes in the

composition of output produced as a result of

households shifting from financial savings to

physical savings or consumer durables in an

economy. This would lead to shifts of investment

from low capital intensive industries to high

capital intensive industries, increasing the capital

output ratio in the economy. Thus, inflation is

likely to increase the ICOR.

SuGyaan 53


Also, due to increased uncertainty, the utility from

holding wealth declines leading to increased

consumption and decreased savings. On the other

hand, wealth owners interested in maintaining

the real value of their wealth would increase their

savings in an inflationary scenario to maintain

the desired amount (Chopra, 1988).

Most of the models analyzing the effect of inflation

on savings find a considerably negative effect

(Heer and Suessmuth, 2006). If the incomes are

not indexed, unanticipated inflation will cause

unanticipated cuts in the real income and hence

decreased the saving rates (Deaton, 1977). Also,

high inflation can increase the opportunity cost

of holding money and increase the rewards for

the search activities in shopping wasting real

resources and thereby reducing savings (Miller

and Benjamin, 2008). As against this, another

theory proposes that if the real income is correctly

anticipated either by indexation or wage inflation,

unanticipated inflation will increase the saving

rate. Inflation is a good proxy for macroeconomic

uncertainty. Higher uncertainty induces people

to save a larger portion of their money for

precautionary motives. Thus rise in inflation

should have a positive coefficient. Savings will

also increase if there are lifecycle factors

promoting savings (Deaton and Paxson, 1993).

(Heer and Suessmuth, 2006) have stated that if

one believes in the super-neutrality of money in

the ultimate sense, inflation cannot have any

effect on savings in the long run

The impact of inflation on growth, output,

investment, employment and productivity has

been one of the main issues examined in

macroeconomics. Theoretical models in the

money and growth literature analyze the impact

of inflation on growth focusing on the effects of

inflation on the steady state equilibrium of capital

per capita and output (e.g., Orphanides and

Solow, 1990). There are three possible results

regarding the impact of inflation on output and

growth: i) none; ii) positive; and iii) negative.

Sidrauski (1967) established the first result,

showing that money is neutral and superneutral1

in an optimal control framework considering real

money balances (M/P) in the utility function.

Tobin (1965), who assumed money as substitute

to capital, established the positive impact of

inflation on growth, his result being known as

the Tobin effect. The negative impact of inflation

on growth, also known as the anti-Tobin effect, is

associated mainly with cash in advance models

(e.g., Stockman, 1981) which consider money as

complementary to capital. Based on cross-country

and panel regression, several studies have

demonstrated in recent years, that there is

negative correlation between inflation and growth

in the long run due to the influence of the former

on reducing investment and productivity growth.

Earlier works (for example, TunWai, 1959) failed

to establish any meaningful relationship between

inflation and economic growth. A work by Paul,

Kearney and Chowdhury (1997) involving 70

countries (of which 48 are developing economies)

for the period 1960-1989 found no causal

relationship between inflation and economic

growth in 40 % of the countries; they reported

bidirectional causality in about 20 % of countries

and a unidirectional (either inflation to growth

or vice versa) relationship in the rest. More

interestingly, the relationship was found to be

positive in some cases, but negative in others.

Recent cross-country studies, found that inflation

affecting economic growth negatively, includes

Fischer (1993), Barro (1996) and Bruno and

Easterly (1998). Fischer (1993) and Barro (1996)

found a very small negative impact of inflation

on growth. Yet Fischer (1993: 281) concluded

¯however weak the evidence, one strong

conclusion can be drawn: inflation is not good

for longer-term growth . Barro (1996) also

preferred price stability because he believed it to

be good for economic growth.

The effect of macroeconomic instability on growthcomes largely from the effect of uncertainty onprivate investment. Multi-country panel datastudies on investment report that measures ofmacroeconomic instability, like the variability inthe real exchange rate or the rate of inflation, havean adverse impact on investment (Serven andSolimano 1992). Fischer (1993) examines the roleof macroeconomic factors in growth. He foundevidence that growth is negatively associated withinflation and positively associated with goodfiscal performance and undistorted foreignexchange markets. Growth may be linked to

SuGyaan


54

uncertainty and macroeconomic instability wheretemporary uncertainty about the macro economycauses potential investors to wait for itsresolution, thereby reducing the investment rate(Pindyck and Solimano 1993). The ChakravartyCommittee (RBI, 1985) referred to an inflation rateof 4 % as an acceptable rise in prices. This can beregarded as the first influential fix on thethreshold rate of inflation in India. More recentstudies have made estimates of threshold inflationusing Sarel methodology and these estimatesplace threshold inflation for India in the range of4-7 % (Kannan and Joshi, 2002; Rangarajan, 1997;RBI, 2003a; Samantaraya and Prasad, 2001;Vasudevan, Bhoi and Dhal, 1998). The estimateof threshold inflation has, however, a shiftingperspective (RBI, 2003b). With structural changesin the economy, prolonged price stability at theglobal level as well as in India and the credibleanchoring of inflationary expectations at a lowerlevel, the threshold inflation could also movedownwards.

Objective of the Study

Inflation influences each and every area of aneconomy. The main objective of this paper is toexamine the impact of Inflation on variouseconomic factors i.e. Growth rate, Saving,Investment, Employment, Import and Export. Tomake the study more precise, it attempts to showthe interrelationship between inflation, GDP,Investment and Household savings. Thisrelationship can provide a better way to policy

makers to make appropriate economic policies toset a smooth path for swift growth of Indianeconomy.

Hypotheses

The following three Alternative Hypotheses havebeen framed:

1. Hα: High inflation slows down growth rate.

2. Hα: Inflation accelerates investment rate inDPA.

3. Hα: Inflation curtails household savings.

Research Design

To examine the impact of inflation on GDP,Employment, Saving, Investment, Import andExport, Secondary data of past ten years have beencomprised from various sources. In order toanalyze the data tabulation, correlation andregression have been used.

Interrelationship between Inflation andEconomic Factors

Economists also advocate a moderate rate ofinflation for economic growth of a nation and 5-6% rate is considered good for an economy. But ifthis rate goes up, it becomes obstacle in theeconomic growth of the nation. The present studytries to seek the relationship between inflation,GDP and the related factors, as it is said a moderaterate of inflation has positive impact on growth,investment and direct productive activities. (Table1)

Table 1

Macro Economic Indicators

Time GDP Inflation WPI Inflation CPI Industry GDP growth

2002-03 3.88 3.4 4.1 7.21

2003-04 7.97 5.5 3.8 7.32

2004-05 7.05 6.5 3.9 9.81

2005-06 9.48 4.4 4.2 9.72

2006-07 9.57 6.5 6.8 12.17

2007-08 9.32 4.82 6.2 9.67

2008-09 6.72 8 9.1 4.44

2009-10 8.59 3.6 12.3 9.16

2010-11 8.91 9.6 10.5 7.55

2011-12 6.69 8.8 8.4 7.81

2012-13 4.47 7.4 10.2 0.96

2013-14 4.86 6.5 9.6 0.65

Source: CMIE

SuGyaan 55


Data Analysis

The above mentioned Data have been analyzed

by using Karl Pearson correlation and regression

techniques. It gives following results :

As we all know that a certain rate of inflation is

required for the smooth growth rate of an economy

but if it continues increasing beyond that rate then

it starts impeding the growth rate. The regression

equation is

Table 2Savings & Investiments

Time Savings Investment Household savings

2002-03 25.93 25.02 21.2

2003-04 29.03 26.17 22

2004-05 32.41 32.45 23.1

2005-06 33.44 34.28 23.5

2006-07 34.6 35.87 23.15

2007-08 36.82 38.11 22.42

2008-09 32.02 35.53 23.64

2009-10 33.69 36.3 25.18

2010-11 34.02 36.53 23.51

2011-12 31.81 36.39 22.33

2012-13 31.8 34.7 22.8

2013-14 30.5 35.3 24

Source: CMIE

Table 3Unemployment, Export & Import Growth

Time Unemployment Export Growth Import Growth

2002-03 - 20.36 14.56

2003-04 - 23.23 24.03

2004-05 5.5 28.51 48.63

2005-06 5.1 23.47 32.13

2006-07 4.6 20.36 21.39

2007-08 4.6 23.23 35.08

2008-09 5.8 28.51 19.76

2009-10 9.3 23.47 -2.56

2010-11 9.6 20.36 26.78

2011-12 8.9 23.23 31.07

2012-13 8.1 28.51 0.54

2013-14 7.4 23.47 -6

Source: CMIEGDP = 7.53 - 0.038 WPI

Predictor Coef SE Coef T p-value

Constant 7.527 2.104 3.58 0.005

WPI -0.0375 0.3219 -0.12 0.909

Pearson correlation and regression analysis alsosupport the same but p value (0.909) is muchhigher than 0.05 (.909 > 0.05) which shows thatrelationship between two variables is not

SuGyaan


56

pace of economy growth slower and somehow itaffects it negatively. Second, household savingsfall but overall savings not. Inflation has positiveimpact on investments. These findings can haveimportant policy implications. The importantconclusion is that any increase in inflation fromthe previous period negatively affects growth thisis why the policymakers should note that anyincrease in inflation from the previous period at

significant and that is why first Há is rejected.

On the other hand, when rate of inflation goes upit increases the induced investment. Inducedinvestment is that investment which changes withthe change in income of the rate of profit. Itincreases with as income increases and decreasesas income decreases. Thus-induced investmentis income elastic. The induced investment curveslopes upward to might showing increase ininvestment as a result of increase in income.Autonomous investment, on the other hand, isindependent of income and is not guided by profitmotive. This investment is generally undertakesby the Government, who is not guided by theprofit consideration. The autonomous investmentcurve is a horizontal straight line parallel to theOX-axis. It indicates that the investment remainsthe same at all levels of income. In equation forminvestment can be defined as: I= a+ bY

Where, I= Aggregate investment, a is constantmeans autonomous investment and b is inducedinvestment which depends on income (Y).Inpresent study we find the regression equation ofinvestment on inflation is:

Investment = 28.5 + 0.861 WPI


Constant 28.504 3.894 7.32 0.000

WPI 0.8611 0.5959 1.45 0.179

Pearson correlation is 0.416; it shows a moderatedegree positive correlation between investmentand inflation WPI. But p value (0.179) is higher

than 0.05 (0.179 > 0.05) which shows thatrelationship between two variables is notsignificant and that is why second Há is alsorejected.

As it is said that during inflation because of higherprices consumers are left with less savings thisin turn decreases the share of household savingsin total savings. By analyzing the data we find:

The regression equation is

Household savings = 22.9 + 0.028 WPI


Constant 22.895 1.071 21.38 0.000

WPI 0.0278 0.1639 0.17 0.869

Here, Pearson correlation shows low degreepositive relationship between inflation andhousehold savings. It does not support third H1;the reason is because inflation affects differentsegments of society differently. In this case p value(0.869) is higher than 0.05 (0.869 > 0.05) whichshows that relationship between two variables isnot significant and that is why third Há is alsorejected.

To see the impact of growth, investment andsavings on inflation multivariate regression hasbeen used and the summary is as follows:

Conclusion

As economics states that inflation affects differentsections of economy differently, some sections arebenefited while some are affected adversely. Thepositive impact of inflation is, it is beneficial forproducers who play crucial role in an economy.If this section has large gains, results in higherinvestment, higher production, higheremployment and higher growth rate. As the mainobjective of this paper was to examine theinterrelationship between inflation and economicgrowth, investment, employment, savings,imports and exports. The interesting results foundin this exercise are that the inflation makes the

Model Summary

Model R R Square Adjusted R Std. Error of the

Square Estimate

1 .522a .273 .000 1.98796

a. Predictors: (Constant), investment, growth, savings

SuGyaan 57


ANOVAb

Model Sum of Squares Df Mean Square F Sig.

Regression 11.856 3 3.952 1.000 .441a

Residual 31.616 8 3.952

Total 43.472 11

a. Predictors: (Constant), investment, growth, savingsb. Dependent Variable: WPI

Coefficientsa

Model Unstandardized Standardized t Sig.Coefficients Coefficients

B Std. Error Beta

(Constant) 6.131 10.557 .581 .577

growth .108 .604 .110 .179 .862

savings -.541 .764 -.765 -.709 .499

investment .494 .377 1.024 1.312 .226

a. Dependent Variable: WPI

The regression equation is

WPI = 6.1 + 0.108 Growth - 0.541 Savings + 0.494 Investment

Regression Analysis: CPI versus Growth, Savings, Investment, Household savings and Exports

The regression equation is CPI = - 27.4 - 0.667 Growth - 0.213 Savings + 0.510 Investment + 1.50Household Savings - 0.227 Exports

Predictor Coef SE Coef T P

Constant -27.36 22.16 -1.23 0.263

Growth -0.6669 0.8422 -0.79 0.459

Savings -0.2133 0.9785 -0.22 0.835

Investment 0.5097 0.5078 1.00 0.354

Household Savings 1.5028 0.8853 1.70 0.141

Exports -0.2274 0.2635 -0.86 0.421

S = 2.07446 R-Sq = 73.7% R-Sq(adj) = 51.9%

Analysis of Variance

Source DF SS MS F P

Regression 5 72.502 14.500 3.37 0.086

Residual Error 6 25.820 4.303

Total 11 98.322

Source DF Seq SS

Growth 1 0.466

Savings 1 28.450

Investment 1 30.920

Household Savings 1 9.462

Exports 1 3.204

SuGyaan


58

any level has negative effect on economic growth.However, the fact that the common people andthe decision makers do not like inflation hasenormous effects on the consumption pattern,which in turn affects the output demanded.Macroeconomic stability and the necessaryinfrastructure are among the preconditions forsustained growth. Among the ways inflation canaffect growth, an important avenue is the effectof inflation on investment. Low or moderateinflation is an indicator of macroeconomicstability and creates a favourable environment forinvestment. Countries with moderate rates ofinflation have higher growth rates over the long-term compared with countries with high inflationrates. The Indian experience appears to supportthe above view. In India, government also needsto make the effective monetary policy so thatinflation could be kept under control. To promotegrowth and keep inflation at moderate level, thegovernment needs to control budget deficits. Thiscan be achieved by switching public expenditurefrom consumption to investment, this may bedifficult to pursue, especially in a developingcountry where parallel economy is existing witha multiparty democracy but this is the urgent needof Indian economy. Indian government shouldcurtail unproductive expenditure, which is acause of high inflation rate and low growth rate.To maintain sustainable growth,government alsoneeds to make induced investments to promotenew technologies and innovations to increaselevel of production that can help Indian economyto restart the engine of growth.

References

1. Andres J. and I. Hernando (1997). Doesinflation harm Economic Growth? Evidencefor the OECD, Banco de Espana WorkingPaper 9706.

2. Athukorala, P. C. and Sen, K. (2004) TheDeterminants of Private Saving in India.World Development, Vol. 32, No. 3, pp. 491–503

3. Balakrishnan P (2005): ¯Macroeconomicpolicy and economic growth in the 1990s”,Economic and Political Weekly, XXXX, 3969-3977.

4. Barro ,R. and Sala-i-Martin, X. 1995.Economic Growth. McGraw Hill

5. Barro, R. J. (1995). Inflation and economicgrowth. NBER Working Paper 5326.Cambridge,

6. Bruno, M.,&Easterly,W. (1998). Inflationcrises and long-run growth. Journal ofMonetary Economics, 41, 3–26.

7. Chakravarty Committee (RBI report 1985)

8. Charan D Wadhava [ed.] (1978), Someproblems of India’s Economic Policy, TataMcGraw-Hill, New Delhi.

9. Chopra, S. 1988. Inflation, HouseholdSavings and Economic Growth. Ph. D. thesis,M. S. University of Baroda, India.

10. Dholakia, Archana. 1990. Benefits fromGovernment Expenditures in India- AWelfare Indicator Approach. Bombay:Himalaya Publishing House, India.

11. Dholakia, R. H. 1990. Extended PhillipsCurve for the Indian Economy. IndianEconomic Journal, Vol. 38, No. 1, pp. 69-78.

12. Dholakia, R. H. 1995. Expected Inflation andShort-Term Forecast of Growth Rate in India.IASSI Quarterly, Vol. 13, No. 4, pp. 44-67.

13. Fischer, S (1993): ‘The Role of Macro-economic Factors in Growth’, Journal ofMonetary Economics, Vol 32(3).

14. Khan, M. S. and Senhadji, A. S. 2001.Threshold Effects in the RelationshipBetween Inflation and Growth. IMF StaffPapers 2001, Vol. 48, No. 1.

15. Krishnamurty K (2002): “Macroeconomicmodels for India: past, present andprospects”,Economic and Political Weekly,XXXVII, No 42 (October 19).

16. K Krishnamurty, ‘Inflation and Growth: AModel for India’ in Krishnamurty and Pandit,Macro Econometric Modeling of the IndianEconomy, (Hindustan PublishingCorporation, 1985) pp 39-42.

17. Mallik, G. and Chowdhury, A. 2001. Inflationand Economic Growth: Evidence from fourSouth Asian Countries. Asia-PacificDevelopment Journal Vol. 8, no. 1, June 2001.

18. Smyth, D. J. (1994), “Inflation and Growth”,Journal of Macroeconomics 16: 261-270.

#MJ SSIM VI(II) & VII (I) 5, 2014

SuGyaan 59


Author: Professor B.R Virmani is the founder

Chairman, Centre for Organisational Research

&Development in Management (CORD-M)

Hyderabad, India. Professor BR Virmani has been

the Dean and IPCL Chair Professor of Strategic

Management at Administrative Staff College of

India (ASCI). He is Academic Advisory Board

Member of Siva Sivani Institute of Management.

Secunderabad, Andhra Pradesh.

Professor Virmani has published over 50 articles

and 14 books, including Managing People in

Organization’s: Challenges of Change; Indian

Management; Evaluating Management and

Development; Participative Management vs.

Collective Bargaining; Workers Education;

Economic Development Alternatives: Andaman

and Nicobar Island; Economic Restructuring,

Technology Transfer and Human Resource

Development etc.

His latest book on The Challenges of Indian

Management address the burning issues in Indian

Organizational Management Practices and

divided the contents into five parts, the first part

consist Indian Management: An Overview, the

chapter focus on the universality of management

versus culture specificity further this chapter

elaborated on practice of Indian Management

from historical perspective. Second part consists:

Indian management through the ages, brief about

Vedic period administrative structure, Kautilya

model of administrative setup and management

practices, Aryan period, and British period and

discussed further up to the period of post-

Independence period. This part also includes

Management outside India, focusing more on

development of Management practices in Western

Book Review

THE CHALLENGES OF INDIAN MANAGEMENT

Author: Prof.B.R.Virmani

Publisher: Response Books; A division of Sage Publication Indian Private Limited, First published in

2007,

ISBN: 9780761935513.

Reviewers: Dr.Pavan Patel, Professor and Mr.K.V.S.Krishnamohan, Associate Professor, SSIM, Kompally,

Secunderabad. 500014.

world discussing from Scientific Management to

Business Process Re-engineering, Total Quality

Management and 360degrees feedback etc. At the

same time the author highlighted Japanese

Management also. Third Part consists the working

of Indian Management typical cases for the study

purpose the author has taken five different types

of organizations which includes a government

department, a public sector, a traditional family-

owned Indian Organization, a traditional British

multinational and American information

technology based organization. This study

focused on the similarities of management

practices and similarity in differences. Part four

discussed on Indian Management Practices:

Employees Perspective, study conducted through

a structured questionnaire employee perspective

on Indian Management practices this concludes

very interesting facts about the Indian

management practices. Part fifth chapter number

seven explaining what is Indian Management and

comparative management practices in the west,

japan and India, mentioned very clearly to

understand gap between execution management

in India and claimed the management practice.

This will enhance readers to understand that the

importance of execution management in the

organization to accomplish the objectives of the

organization. In the last chapter the author

concluded that the Indian organizations can

fallow the foreign systems of management

provided that those have adaptive and modified

to the Indian climate to be effective in

accomplishing the organizational objectives.

This book recommended highly for business

leaders, HR and OD consultants, Management

experts, and as an additional reading for

SuGyaan


60

management students in the subjects like Human

Resource Management, Organizational

Development, and Strategic Human Resource

Management. Interesting aspect here would be the

irrespective of nature of business leader can

understand the pulse of employees perception

towards management, further this book will help

business leaders bring a all-inclusive change in

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Specifically for Academicians each chapter in

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respective topics in the area of almost major

functional areas of management, how Indian

management challenges can be understood, it

can be solved adopting, modified, improvised

western management practices and concepts

applied in Indian scenario to address the

challenges.

#MJ SSIM VI(II) & VII (I) 6, 2014

SuGyaan 61


Siva Sivani Institute of Management

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