Can a Force Savng Polcy Enhance the Future Happness of the Socety? A Survey study of the Mandatory Provdent Fund (MPF) polcy n Hong Kong Dr. Wa-kee Yuen Department of Economcs Hong Kong Shue Yan Unversty Braemar Hll Hong Kong, CHINA Tel: (852) 2806-5171 Fax: (852) 2806-8044 Emal: wkyuen@hksyu.edu, wkyuenhksyu@yahoo.com.hk Mss Wan-Lng Chu Department of Economcs Hong Kong Shue Yan Unversty Braemar Hll Hong Kong, CHINA Tel: (852) 2570-7110 Fax: (852) 2806-8044 Emal: wlchu@hksyu.edu Abstract Populaton gettng agng s a problem or gong to be a problem for many Asan countres. Hong Kong s expectng a rapd populaton agng, by 2033, t s predcted by the government that 27 percent of populaton wll be over the usual retrement age 65. The Mandatory Provdent Fund (MPF) polcy was mplemented n year 2000 as a retrement protecton system. The core of the MPF polcy s a force savng polcy ams at enhancng future well-beng or happness. Indeed the smlar force savng polcy can be mplemented for dfferent purpose of enhancng happness, for example reducng future poverty, fnancng future educaton or fnancng future health-care system. Ths paper employs an ordered probt model to revew MPF polcy from the pont of vew of self-reported happness expectaton after retrement. The data were collected by means of a survey conducted by Economcs and Well-beng Research n February 2007 usng randomly selected telephone numbers from resdental telephone drectores. A total of 543 respondents were successfully ntervewed. Ths paper ntends to answer the followng questons: 1) Can MPF make the people n Hong Kong havng a happer retrement expectaton? 2) What are some of the determnants of happness expectaton after retrement? 3) What can other countres learn from the experence of mplementng the MPF n Hong Kong? Keywords: Force Savng Polcy, Agng, Happness, Retrement, Mandatory Provdent Fund ( MPF) Date: 14 June 2007 1
Can a Force Savng Schemes Enhance the Future Happness of the Socety? A Survey study of the Mandatory Provdent Fund (MPF) polcy n Hong Kong 1. Introducton Populaton gettng agng s a problem or gong to be a problem for many Asan countres. Hong Kong s expectng a rapd populaton agng, by 2033, t s predcted by the government that 27 percent of populaton wll be over the usual retrement age 65. Ruut (2005) suggests that one of the measurements for the qualty of lfe s Happy lfetme (.e. how long and happy people lve). As the populaton s expected to get agng, the happness expectaton after retrement wll drectly affect current happness. In Hong Kong a retrement protecton scheme, the Mandatory Provdent Fund (MPF), that can generally be descrbed as a force savng scheme to enhance future happness, s ntroduced n year 2000. MPF s an employment-based retrement protecton system that requres both employees and employers to make regular contrbutons, 5% of the employee nto a MPF scheme (subject to the maxmum HKD$20,000 and mnmum HKD$5,000 monthly ncome). By September 2006 around 68% of the total employed populaton are now covered under the MPF schemes. Indeed there s growng lterature relatng lfe satsfacton to retrement. For example, Mchalos and Orlando (2006) fnd that lfe satsfacton of young people s sgnfcantly lower than that of retrement groups. Chen (2001) examnes how major lfe events - such as retrement experenced n the agng process may affect the lfe satsfacton. Gall and Evans (2000) studes the pre-retrement expectatons and the qualty of lfe of male retrees n later retrement. One of the major problems facng by retred people s that ncome drops dramatcally, lterature have shown that mprovng the fnancal status of retred people can mprove ther happness (Dorfman, 1992; Rchardson & Klty,1991). Ths paper ntends to revew the success of MPF (a force savng polcy), from the pont of vew of happness retrement expectaton. The focus of ths paper s to answer the followng questons: 1) Can MPF make the people n Hong Kong havng a happer retrement expectaton? 2) What are some of the determnants of happness expectaton after retrement? 3) What can other countres learn from the experence of mplementng the MPF n Hong Kong? The rest of ths paper s organzed as follows: Secton 2 descrbes the survey that was employed to collect the emprcal data and exhbt the statstcal facts of the 2
survey; Secton 3 dscusses the constructon of the emprcal models; Secton 4 descrbes and evaluates the emprcal results; and Secton 5 contans the concluson and polcy mplcatons. 2. Survey and Statstcal Summary Data was collected by means of a survey conducted by Shue Yan Economcs and Well-beng Research durng the frst two weeks of February 2007 usng randomly selected telephone numbers from resdental telephone drectores. A total of 543 respondents were successfully ntervewed. The margns of samplng error were estmated to be ±4.29% at a 95% confdence level. Snce the majorty of the populaton of Hong Kong s Cantonese speakng, the orgnal questonnares were wrtten n Chnese. 2.1 The questonnare desgn The questonnare conssted of two man parts. The frst part collects the personal nformaton about the respondents, such as ther gender, martal status, educaton, age and monthly ncome. The second part focuses on questons relatng to MPF and happness ssues. The responses to the questons are rated usng ordnal scale. Table 1 reports the dstrbuton of the respondents. Table 1: Dstrbuton of the respondents Gender Age Educaton Monthly Personal Income Prmary school or Male 55.1% 18-24 32.4% 4.6% Below $5000 10.1% below Female 44.9% 25-34 28.9% Secondary school 28.7% $5000 to $7999 21.9% Form 6, 7 or $8000 to Martal Status 35-44 22.3% 25.2% 38.3% equvalent $14999 College or 45 or $15000 to Marred 57.6% 16.4% Unversty and 41.4% 21.7% above $29999 above $30000 or Unmarred 42.4% 7.9% above Questons 1 and 2 of part two revew the self-reported expected happness after retrement. Table 2 shows that over 50% of the respondents expect to have a happy retrement lfe. Moreover, table 2 shows that less than 10% of the respondents thnk that they maybe not or certanly not havng a happy retrement lfe. However around 67% of the respondents thnk that MPF cannot or may not be able to gve them happy retrement lfe. 3
Table 2: Self-reported expected happness after retrement 1) Do you expect your retrement lfe to be happy? 1=Certanly not happy 2=Maybe not happy 3=The same 4=Maybe happy 5=Certanly happy 1.84% 7.18% 39.04% 45.49% 6.45% 2) Do you thnk that MPF can gve you a happy retrement lfe? 1=Certanly cannot 2=Maybe not 3=May be 4=Certanly can 16.39% 50.64% 30.76% 2.21% Questons 3 to 7 of part two ntend to explore whether respondents care about ther force nvestment n MPF. The summary statstc of Queston 3 n table 3 shows that around 60% of the respondents clam that they care about the yeld of ther MPF account. In addton queston 4 also shows that around 65% respondents know the yeld of ther MPF account n the last year. However the statstcal result from questons 5 to 7 show that respondents know lttle about MPF. Around 79% of the respondents do not know the admnstraton fee of MPF, around 71% of the respondents do not know the estmated accumulatve amount of MPF by the tme of retrement and around 66% of the respondents do not know how to calculate the yeld of MPF. The statstcal result mples that although the people of Hong Kong care about ther MPF account, they have lmted knowledge about how MPF works. Table 3: Care about MPF 3) Do you care about the yeld of your MPF account? 1=Certanly not care 2=Maybe not care 3=May be care 4=Certanly care 7.92% 30.57% 51.57% 9.94% 4) Do you know the yeld of your MPF nvestment n the last year? 1= Know 2= Do not Know 65.7% 34.3% 5) Do you know the admnstraton fee of your MPF account n the last year? 1= Know 2= Do not Know 20.63% 79.37% 6) Do you know the estmated accumulatve amount of MPF account by the tme you retred? 1= Know 2= Do not Know 28.73% 71.27% 7) Do you know how to calculate the yeld of your MPF nvestment? 1= Know 2= Do not Know 33.33% 66.67% The fnal queston, queston 8, of part two asked the respondents to estmate when they wll retre. Table 4 shows that most of the respondents (around 75%) are expected to get retred before the usual retrement age 65. Table 4: Retrement Age 8) When would you expected to retre? 30-39 40-49 50-59 60-69 70 or above 3.68% 20.26% 52.30% 20.99% 2.76% 4
3. The Emprcal Ordered Probt model Ths paper uses the commonly used ordered probt model 1 as the workhorse to handle the ordnal scale dependent and ndependent varables (see: Myata 2003, Greene 2000). Wnkelmann (2005) used an ordered probt model to dentfy the ntra-famly correlaton of happness. In addton, Tsou and Lu (2001) nvestgated the determnants of happness n Tawan usng an ordered probt model. Ths paper models self-reported expected happness after retrement wth the followng functon n lnear form: HAPP= f (MARTIAL, AGE, EDU, GENDER, INCOME, MPF_HAPP, RETIRE_AGE, ADMIN_FEE, MPF_YIELD, CARE_MPF, ACCUM_MPF, CAL_MPF) (1) Table 5: Notaton of Varables Dependent Varable HAPP Self-reported expected happness after retrement (1=Certanly not happy, 2=Maybe not happy, 3=The same, 4=Maybe happy, 5=Certanly happy) Independent Varables MARTIAL Martal status (1=Marred, 2= Unmarred) GENDER Gender (1=Male, 2=Female) AGE Age (1=18-24, 2=25-34, 3=35-44, 4=45 or above) EDU Educaton (1=Prmary school or below, 2=Secondary school,3=post- Secondary or equvalent, 4=College or Unversty and above) INCOME Monthly personal ncome n HK$ (1=Below $5000, 2=$5000 to $7999, 3=$8000 to $15000, 4=$14999 to $29999, 5=$30000 or above) MPF_HAPP Data collected from queston 2; Do you thnk that MPF can gve you a happy retrement lfe? (1=Certanly cannot, 2=Maybe not, 3=May be, 4=Certanly can) RETIRE_AGE Data collected from queston 8; When would you expected to retre? (1=30 to 39, 2=40 to 49, 3=50 to 59, 4=60 to 69, 5=70 or above) ADMIN_FEE Data collected from queston 5; Do you know the admnstraton fee of your MPF account n the last year? (1= Know, 2= Do not Know) MPF_YIELD Data collected from queston 4; Do you know the yeld of your MPF nvestment n the last year? (1= Know, 2= Do not Know) CARE_MPF Data collected from queston 3; Do you care about the yeld of your MPF account? (1=Certanly not care, 2=Maybe not care, 3=May be care, 4=Certanly care) ACCUM_MPF Data collected from queston 6; Do you know the estmated accumulatve amount n your MPF account by the tme your retred? (1= Know, 2= Do not Know) CAL_MPF Data collected from queston 7; Do you know how to calculate the yeld of your MPF nvestment? (1= Know, 2= Do not Know) It s worth mentonng that the estmated coeffcents only nfluence the condtonal probablty that a certan value of the dependent varable wll appear. A 5
postve estmated coeffcent ndcates that an ncrease n the ordnal scale of the ndependent varable nfluences the dependent varable n such a way that the condtonal probablty of the dependent varable fallng nto a hgher ordnal scale ncreases whle the opposte happens n the case of a negatve estmated coeffcent. (See: Boccalett and Moro, 2000). In the cases where the ndependent varables are dscrete, the dscrete change n the condtonal probablty can be evaluated at the average of the ndependent varables. (See: Rvera, 2001) 4. Emprcal Results Table 6, model 1.1, presents the emprcal results of equaton (1). Table 6, model 1.2 amends model 1.1 by droppng the ndependent varables that are nsgnfcantly dfferent from zero at conventonal levels of sgnfcance. Table 6: Determnants of Self-reported expected happness after retrement Dependent Varable: Self-reported expected happness after retrement (HAPP) Model 1.1 Model 1.2 Determnants Coeffcent Std. Error Coeffcent Std. Error ACCUM_MPF -0.034894 0.115851 - - ADMIN_FEE 0.193017 0.133510 - - AGE -0.048921 0.065070 - - CAL_MPF -0.139573 0.114490 - - CARE_MPF 0.284446** 0.071173 0.245684** 0.065714 EDU 0.113479* 0.059157 0.148717** 0.050613 GENDER 0.158124 0.097187 - - INCOME 0.096666* 0.054595 - - MARTIAL -0.056094 0.112649 - - MPF_HAPP 0.390417** 0.069191 0.395989** 0.068066 MPF_YIELD 0.181314 0.114550 0.203423* 0.104219 RETIRE_AGE -0.119913* 0.067738-0.156161** 0.064382 Note: 1)** means sgnfcantly dfferent from zero at a 5% sgnfcance level 2) * means sgnfcantly dfferent from zero at a 10% sgnfcance level Model 1.2 shows that the condtonal probablty of respondents to report a happy self-reported expected happness after retrement ncreases as: 1) Respondents havng hgher educaton. 2) Respondents know about the yeld of ther MPF n the last year. 3) Respondents clam that they care about ther MPF nvestment. 4) Respondents thnk that MPF can gve them a happer retrement lfe. 5) Respondents expected to retre earler. 1 Detal descrpton of ordered probt model could be found n the techncal appendx. 6
5. Concluson and Polcy mplcatons 5.1 Can MPF make the people n Hong Kong havng a happer retrement expectaton? The survey result n table 2 shows that around 67% respondents thnk that MPF cannot or may not be able to gve them a happy retrement lfe. From the pont of vew of statstcal facts, t seems that MPF polcy cannot enhance expected happness after retrement. Table 3 revews that around 60% of the respondents clam that they care about the yeld of ther MPF account, but respondents actually know lttle about MPF. The survey results from queston 5 to 7 show that around 79% of the respondents do not know the admnstraton fee of MPF, around 71% of the respondents do not know the estmated accumulatve amount of MPF by the tme of retrement and around 66% of the respondents do not know how to calculate the yeld of MPF. Wth lttle knowledge about the MPF polcy, t s reasonable for respondents to clam that MPF cannot gve them happy retrement lfe. The polcy mplcaton s that the government needs to provde more nformaton to help the general publc to understand the mechansm of MPF polcy. 5.2 What are the determnants of happness expectaton after retrement? The emprcal result n table 6 shows that happness expectaton after retrement s postvely related to the level of educaton, respondents know about the yeld of MPF, respondents care about ther MPF and respondents beleve that MPF can brng them happy retrement lfe. In addton table 6 also shows that happness expectaton after retrement s negatvely related to the age of retrement. The emprcal results n table 6 mply that hgher educaton people tend to have more confdence n havng a happer retrement lfe. However, extendng the retrement age does not appear to be a good polcy to enhance happness expectaton after retrement. One nterestng pont to note s that, among the fve determnants dentfed n table 6, three of them related to MPF. Although, the survey result n table 2 revews the statstcal fact that a large porton, around 67% do not beleve that MPF can gve them happy retrement lfe, the emprcal result n table 6 provdes another story. The story n the emprcal results n table 6 s that MPF polcy can enhance happy retrement lfe, as long as three condtons are beng fulflled. 1) Respondents need to care about ther MPF; 2) Respondents need to know the yeld of ther MPF and 3) Respondents need to beleve n the MPF as a retrement protecton polcy. 7
5.3 What can other countres learn from the experence of mplementng the MPF n Hong Kong? The core of the MPF polcy s a force savng polcy ams at enhancng future wellbeng or happness. Indeed the smlar force savng polcy can be mplemented for dfferent purpose of enhancng happness, for example reducng future poverty, fnancng future educaton or fnancng future health system. Recently the government of Hong Kong s callng for a publc consultaton on another force savng polcy ams at fnancng future health-care system. From the experence of Hong Kong, any country that would lke to mplement a force savng polcy to enhance future happness need to ensure the transparency of the polcy. The general publc needs to understand the beneft of the polcy and care about how to nvest ther savng so that the polcy can fulfll ts am to enhance the future happness of the socety. That s the government needs to lead the general publc see-through the future beneft of the force savng polcy. A happness expectaton about the future wll mprove current happness of the socety. 8
Reference: Boccalett S. and Moro D. (2000) Consumer Wllngness-To-Pay for GM Food Products n Italy, AgBoForum, Volume 3, Number 4, pg. 259-267 Chen C. (2001).Agng and lfe satsfacton, Socal Indcators Research. Apr, Vol.54, Iss. 1; pg. 57 Dorfman L.T. (1992), Academcs and the transton to retrement, Educatonal Gerontology, 18, pg. 343-363 Gall T. L. and Evans. D.R. (2000), Pre-retrement expectatons and the qualty of lfe of male retrees n later retrement, Canadan Journal of Behavoral Scence, Jul Vol.32, Iss. 3; pg.187 Greene, W. H. (2000) Econometrc Analyss, 4th edton, Prentce-Hall Internatonal Mchalos A.C. and Orlando J.A. (2006) Qualty of Lfe of Some Under-Represented Survey Respondents: Youth, Aborgnals and Unemployed, Socal Indcators Research. : Nov, Vol.79, Iss. 2; pg. 191 Myata S. (2003) Households rsk atttudes n Indonesan vllages, Appled Economcs, 35, pg.573 583 Rchardson V. and Klty K.M. (1991), Adjustment to retrement: Contnuty vs. dscontnuty, Internatonal Journal of Agng and Human Development, 33, pg. 151-169 Rvera B. (2001) The effects of publc health spendng on self-assessed health status: an ordered probt Model, Appled Economcs, 33, pg.1313 1319 Ruut V. (2005), Apparent Qualty-of-lfe n Natons: How Long and Happy people lve, Socal Indcators Research 71: pg.61 86 Tsou M. W. and Lu J.T. (2001) Happness and Doman Satsfacton n Tawan, Journal of Happness Studes, v. 2, ss. 3, pg. 269-88 Wnkelmann R. (2005) Subjectve Well-Beng and the Famly: Results from an Ordered Probt Model wth Multple Random Effects, Emprcal Economcs, October, v. 30, ss. 3, pg. 749-61 9
Techncal Appendx The happness ordered probt model used n ths paper s: HAPP = X β ' + ε (A1) where HAPP s the self reported happness after retrement, X s the vector of the ndependent varables also n the ordnal scale, β s a vector of the coeffcents to be estmated, and ε are ndependent and dentcally dstrbuted random varables. The subscrpt ndcates an ndvdual. 0 f HAPP γ 1 1 f γ 1 < HAPP γ 2 HAPP = (A2) k f γ < k HAPPk where γ represents the lmts of HAPP. The emprcal model to be estmated becomes an ordered probt model. The log lkelhood functon to be maxmzed s: n log(pr( HAPP = j X, β, )) l( HAPP = l ( β, γ ) = γ j) k j (A3) The condtonal probabltes of observng each ordnal level of HAPP are gven by Pr( HAPP Pr( HAPP Pr( HAPP ' = 0 X, β, γ ) = F( γ 1 X β ) (A4) ' ' = 1 X, β, γ ) = F( γ X β ) F( γ X ) (A5) 2 1 β = k X, β, γ ) = 1 F( γ X ' β ) (A6) k where F s the cumulatve dstrbuton functon of ε. It s worth mentonng that the magntude of the coeffcent ( β ) does not reveal the effect of the ndependent varables (X ) on the dependent varable (HAPP). 10