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0pfom^nLpjmfo i|>|iiiiuiiuiul|iuii 4РШ wqqn^
qii|iftniiiih|i|i фп^шщш^д^шб^эдшЬ qЬшhшmnLtfp
^m^npjmh Uprfhh U.
«ЩршршЩ» PPP ц^ш^щ hш2^шщшh SйmhuшqfimnLpJшй цпЦтпр, щрпфЬищ (Ьркшй, <<)
armen_hakobyan@hotmail.com Qpfiqnpjmh Ер^Ц W. «ЦрЬйр» U^P фщтдшршй щЪшшЦшй тЬтЬишд^тш^шЬ hшйшluшp,шй ¿Ь^йшйийЪр,^, шйр^пй^, шищ^ршЬт (Ъркшй, ^) erik_grigoryan@hotmail.com
336.7
^^йЬшршпЪр. ф^ЬшЬиш^шЬ ф^ЬшЬиш^шЬ upphu, ф^ЬшЬиш^шЬ
qpmq^rnnLpjnLb, ф^ЬшЬиш^шЬ рш^шршр^ш&^рщШ, ^шп^д^ш&рщфЬ tfnqh (SEM):
Оценка взаимосвязанности факторов, влияющих на финансовое поведение населения РА
Акопян Армен А.
Доктор экономических наук, профессор (Ереван, РА)
armen_hakobyan@hotmail.com Григорян Эрик М.
Армянский государственный экономический университет Аспирант кафедры финансов (Ереван, РА) erik_grigoryan@hotmail.com
Абстракт. В настоящее время финансовое поведение населения является популярной темой в финансовой литературе. В эмпирических исследованиях в основном обсуждаются детерминанты финансового поведения, взаимосвязь между ними. Для сбора данных анализа в Армении был проведен опрос, объем выборки N = 511 (после очистки). Хотя в литературе упоминается множество детерминант финансового поведения, в данной статье в качестве независимых переменных были выбраны финансовый стресс, финансовая грамотность и финансовая удовлетворенность, а в качестве зависимой переменной — финансовое поведение. С одной стороны, анализ показал, что финансовый стресс не оказал существенного прямого влияния на финансовое поведение, с другой стороны, он оказал существенное влияние на финансовое поведение, опосредованное финансовой удовлетворенностью. Финансовый стресс оказал значительное влияние на финансовую удовлетворенность, взаимосвязь была отрицательной. И финансовая грамотность, и финансовая удовлетворенность оказали значительное влияние на финансовое поведение, и взаимосвязь была положительной. Полученные результаты могут быть полезны населению, финансовым учреждениям, финансовым консультантам, частному сектору, разработчикам экономической политики.
Ключевые слова: финансовое поведение, финансовый стресс, финансовая грамотность, финансовое удовлетворенность, структурная модель (SEM).
The Relationship Assessment of the Factors Affecting Financial Behavior
of Population in the RA
Hakobyan Armen A.
Doctor of Economics, professor (Yerevan, RA) armen_hakobyan@hotmail.com Grigoryan Erik M. Armenian State University of Economics PhD student at finance department (Yerevan, RA) erik_grigoryan@hotmail.com
Abstract. Currently, financial behavior of population is popular topic in finance literature. Empiric studies mostly discuss the determinants of the financial behavior, the relationship between them. To compile analysis data, a survey was conducted in Armenia, sample size N=511 (after cleaning). Although there are many determinants of financial behavior mentioned in literature, in this article, financial stress, financial literacy and financial satisfaction were chosen as independent variables and financial behavior as a dependent variable. On the one hand, the analysis proved that
Регион u Mup, 2022, № 2
financial stress had no significant direct impact on financial behavior, on the other hand it had significant impact on financial behavior mediated by financial satisfaction. Financial stress had significant impact on financial satisfaction, the relationship was negative. Both financial literacy and financial satisfaction had significant impact on financial behavior, and the relationship was positive. The obtained results may be of use to people, financial institutions, financial advisors, private sector and economic policymakers.
Keywords: financial behavior, financial stress, financial literacy, financial satisfaction, structural model (SEM).
PbmU^nLpjmb ^bmbumUmb ^mppmq^&p ^bmbubhp^ ^hpmphpjmi tfmubmq^mmUmb qpmUmbmpjmb mtfhbmpbbmpU^nq h^tfbm-fabq^pbhp^g t: fofrbmbumUmb ^mppmqft^ pmph-jm^nLtfp Umpnq t b^mumh^ tfmpqUmbg pmph-Uhgmpjmbp: Pbm^nLpjmb Umtf mbmj^b mbmh-umpjnLbbhp^ ^mppmq&mj^b ^bmbubhp^ ttf^frpfrU hhmmqnmnLpjnLbbhpnLtf mnm^h 2ms q^mmpU^nLtf hb qpmbg ^pm mqqnq qnp&nbbhpp nL mqqhgmpjmb ^m^p: Pmgm-hmjmhp^ ^bmbumUmb ^mppmqft^ ^pm mqqnq qnp&nbbhpb nL qpmbg mqqhgmpjmb nLqqnL-pjnLbbhpp" hbmpm^np t qpmbg tfh&nLpjnLbbhp^ ^n^nfampjmb tf^ngn^ mqqhgnLpjnLb nLbhbmi pbmU^nLpjmb ^bmbumUmb ^mppmqft^ ^pm, ^bmbumUmb ^mppmq^&p mnbhp^
^pmUmbmgbhi m^hj^ ^pmmhumUmb $^bmb-umUmb ^mbm^npnLtf" tf^UpntfmUmpqmUnLtf (mjq p^nLtf' ^bmbumUmb ^bum^mnLmbhpnLtf), mbmhumUmb pmqmpmUmbnLpjmb tf2mUnLtf" tfm^pntfmUmpqmUnLtf: Pbm^mpjmb $^bmbum-Umb ^mppmqft^ ^pm mqqnq qnp&nbbhpp Umtf qpm npn2^bhpp (qhmhptf^bmbmbhpp) Umphi^ t mmpmb^mmhi tfm^pnmbmhumUmb^ k tf^Upn-mbmhumUmb^: -^-nLtf pbmU^nLpjmb $^bmbum-Umb ^mppmqft^ tfm^pnmbmhumUmb npn2^bhp^ 4hpmphpjm]_ ^hppL&nLpjnLbbhpp mnm^h tfmbpmtfmub Umphj^ t qmbh]_ b2^m& hnq^m&bh-pnLtf [1; 5], ^uU unLjb hhmmqnmmpjnLbp Uhbmpnbmgmft t tf^UpnmbmhumUmb qnp&nbbhpp ^hpinL&nLpjmb, qpmbg" ^pbmbumUmb ^mppmq&p ^pm mqqhgmpjmb qbmhmmtfmb ^pm: Pmqtfmpp4 hb mjb tf^UpnmbmhumUmb qnp&nbbhpp, npnbp mqqnLtf hb tfmpqUmbg ^^bmbumUmb ^mppmq&p ^pm, qpmbg^g Umphjp t mnmb&bmgbh]_ ^pbmbumUmb qpmqpmnL-pjnLbp, ^^bmbumUmb pm^mpmp^m&nLpjnLbp, ^^bmbumUmb ^hpmphptfnLbpp, ^pbmbumUmb ^hpmhuUnqnLpjnLbp, ^pbmbumUmb upphup k mj]b [2; 10; 13; 14; 16]: ^.hppL&nLpjmb b^m-mmUn^ pbmU^nLpjmb ^pbmbumUmb ^mppmq&p ^pm mqqnq qnp&nbbhp^g pbmp^h hb $pbmb-umUmb upphup, ^pbmbumUmb qpmq^mnLpjnLbp k ^^bmbumUmb pm^mpmp^m&mpjnLbp: Q-np&nbbhpp pbmpnLpjnLbp Ummmp^h t qpmUmbmpjnLbnLtf mnUm hhmmqnmmpjnLb-bhpp hptfmb ^pm, npmhq hmfim^ pbq&^nLtf t b2^m6 qnp&nbbhpp k ^pbmbumUmb ^mppmq&p tfp^k b2mbmUm|^ Um^p mnUmjnLpjnLbp [4; 7; 8; 10; 13; 14; 16]: UnLjb hhmmqnmnLpjmb b^m-mmUb t pmgmhmjmh]_ k gnLjg mm]_ umnpk 4
^mpUm&bhpnLtf b2^m& Um^hpp nLqqmpjnLb-bhpp, qpmbg b2mbmUmipnLpjnLbp k mqqhgnLpjmb ^m^p:
Hj. ^pbmbumUmb upphup k ^pbmbumUmb ^mppmq&p tfp^k pmgmumUmb k b2mbmUm|p Um^ qnjnLpjnLb nLbp:
H2. ^pbmbumUmb qpmqpmmpjmb k $pbmb-umUmb ^mppmq&p tf^^k qpmUmb k b2mbmUm]^ Um^ qnjnLpjnLb nLb^:
H3. ^^bmbumUmb pm^mpmp^mftnLpjmb k ^^bmbumUmb ^mppmqft^ tf^^k qpmUmb k b2mbmUm]^ Um^ qnjnLpjnLb nLb^:
H4. ^^bmbumUmb upphup k ^^bmbumUmb ^mppmqft^ tf^^k Um^p $^bmbumUmb pm^m-pmp^mftnLpjmb tf^^bnpqnLpjmtfp t:
Um^hpp pmgmhmjmh^nL b^mmmUn^ ^n^n^mUmbbhp^ 4hpmphpjm]_ m4]m]_bhp hb hm^mpmqp^hi hmpgtfmb tf^^ngn^, npb ^pm-Umbmg^hi t 2021 p.-^ qhUmhtfphp^g 2022 p.-^ ^hmp^mp dmtfmbmUmhmm^mftnLtf: ^mpgm-phpp^Up pmqUmgmft t 5 pmd^bbhp^g («^nqn-^pqmqpmUmb, ung^m]_-mbmhumUmb m4]m]_bhp», «^^bmbumUmb ^mppmq^ft», «^^bmbumUmb qpmq^mnLpjnLb», «^^bmbumUmb pm^mpmp^m-6nLpjnLb», «^^bmbumUmb upphu»), pbqhmbnLp 25 hmpghp^g: ^mpgmphpp^ btfmb UmnnLg^mftpb pbmp^hi t ^pmrnj^b phum ^pmUmbmgbh^nLg hhmn: ^mpgtfmbp tfmubmUgh^nL ^mpmmq^p ^mjtfmbbhp hb hqhp i^bhi ^^ nhq^qhbm, 16 k pmp&p mmp^p nLbhbm]_: ^mpgtfmbp tfmubmUgh]_ hb ^^ pninp tfmpqhp^g k tfmjpmpmqmp bpkmb^g mmpphp uhnmmmp^pmj^b fatfphpnLtf pbqqpU^mft, mmpphp tfmubmq^mnLpjnLb, Uppm-Umb tfmUmpqmU, qpmq^mftnLpjnLb nLbhgnq mb&^bp: hmpgtfmb mpqjnLbpbhpn^" pbmpmbpp Umqtfhi t N=517, np^g 2-p gb^^hl hb ufami Umtf UpUbmU^ ipmgtfmb ^mmfimnn^, pmgmUmjnq ^mmmufambbhpn^, Uhq&, mhfab^UmUmb ^p^-^mUbhpn^ Umtf bnLjb mpdhpn^ ipmg^mft hmpgm-phpp^Ubhp ^hb hmjmbmphp^hi: S^jmibhp^ ^hpinL&nLpjmb hmtfmp U^pmn^hi hb Microsoft Excel 2019, IBM SPSS Statistics 26, IBM SPSS AMOS 26 hmtfmUmpq^mj^b ftpmqphpp: IBM SPSS AMOS 26 4^fimUmqpmUmb ftpmqp^ tf^gngn^ ^pmUmbmg^hi t N=515 pbmpmbpn^ m^jm^bhp^ qbmhmmtfmb tfnqhj^ Umtf ufahtfmj^ (measurement model) UmnnLgnLtf, npmhq jnLpm-pmb^jnLp pmnmbU]nLb (item / observed variable) bhpmnnLtf t hmpgmphpp^g tfhU hmpg, ^uU o^mpLtf (latent variable) b2^m6 jnLpmpmb^jnLp qnp&nb pbnLpmqp^nLtf t ^p hhm Um^ nLbhgnq
pmnm&hjnL&hhpn^ fruh 2p?mhhhpnLtf &24m& el, e2,..., e19-p tfnphjfr hm^rnqmrnrnu^fflb qmmm-hm^mh ufamjfr tfh&nLpjnL&hhph hh [6, t? 631; 11, t? 623]: &frhmhumhm& ^mppmqfr&p, $frhmh-um^mh qpmqfrmnLpjnL&p, ^frhmhum^mh upphup k ^frhmhum^mh pm^mpmp^m&nLpjnL&p phnL-pmqp^mtf hh hmJmqmmmu^m&mpmp 4, 6, 3 k 3 hmpghpn^: &frhmhumhm& ^mppmq&frh, ^frhmhum^mh qpmqfrrnnLpjmhp ^hpmphpnp hmpghpp qhmhmm^hi hh 0-frg 1 umhppm^n^ (0-h" pmgmum^mh, 1-p" ppm^mh), ^frhmhum^mh upphufrh ^hpmphpnp 2 hmpghpp qhmhmm^hi hh 0-frg 1 umfrppm^n^, 1-p" Lmjphppfr 1-frg 7 umfrppm^n^, fruh ^frhmhum^mh pm^mpmp^m-&nLpjnL&p qhmhmm^hi t Lmjphppfr (Likert) 1-frg 5 k 1-frg 7 umhppmh&hpn^, hmk 1-frg 10 umhp-pm^n^, umhmjh pn]np q&mhmmmhmhhhpp
php^hi hh 0-frg 1 umhppmhfr: bphhnptf rnpp^m-&m.pjmtfp ujmp&hpp gnijg hh mmjfru ^n^n^m-hmhhhpfr tffr?k hn^mpfrmgfrmh: ^&mhmmJmb tfnphjfr hmnrngrntffrg hhmn frpm^mfrmg^h t hmummmnp qnp&nhmjfrh ^hpinL&nLpjnLh (Confirmatory Factor Analysis hmtf CFA), npfr mppjnLh-
prntf npn2 hmpghp pnLpu hh tfp^h tfnphjfrg, pmhfr np ppmhg ummhpmpmmg^mft qnp&nhmjfrh phnhnLtfhhpp (standardized factor loading) ^npp hh umMmh^mft &4mqmqmj& 0.5-frg, frhp &2m&m^nL^ t, np hhnmg^mft ^n^n^mhmhhhpfr (hmpghpfr) k ppmhg hfrriprntf ph^mft qnp&nhfr tffr?k hm^p hmtf hnnhmgfrmh hmdhJmmmpmp pnijL t, n pm^mpmp [12, t? 9]: Q-hmhmmtfm& tfnphinLtf mpmmgn^mft ^n^n^mhmhhhpp (hmpghpp) hm^mqmmmu^mb &2m&mhnLtfhhpn4 hh
UpjnLumh 7-rntf mjh^hu, frh^hu k &km^hp^^m& hh hph hmpgmphppfrh&hpnLtf: On^n^mhmhhhpp phnLpmqpnp hmpghpp ^hpg^mft hh mmpphp hhmmqnmnLpjnL&hhpnLtf hfrpmn^mft hmpgmphppfrhhhpfrg, npfrg hhmn hhpfrhmhhhpfr ^np^frg pmpqtfmh^hl hh hmjhphh [3, t? 58; 2, t?hp 3463-3464; 9, t?hp 7-8]: Unphp hmpnp t q&mhmm^hi mnm^himqnLjh hm^mhm-hmhnLpjmh (maximum likelihood) tfhpnpn^" qhmhmmhp^ jnipmprnfrynip qnp&nhp (&2^m& t o^mpLtf) phnLpmqpnp ^n^n^m^mhp (&24m& t pmnm&hjmh hhpumtf) [6, t? 636]:
On^n^w^wb (Construct) ^pwhw^nLd (Measure items)
&frhmhumhm& ^mppmqfrft 1 bu ^fimpmtfhhpp hmmmpmtf htf mtfpnp?mpjmtfp k dmtfmhmhfrh:
&frhmhumhm& ^mppmqfrft 2 fohmjnqmpjnLh mhhg &2Um& mmpphpmhhhpfrg npkfrgh &kn^" pmh^hprntf, phhhphhpfr, phmmhfrgfr k mjing hhm, ^mh^fr^, nu^frn^:
&frhmhumhm& ^mppmqfrft 3 ^nLg hhpppmtfhhp hmmmpn°L^ hp. mji mhSmhg pfrqhhumtf (op." hmpkmhfr, ph^hpn?, pmph^m^fr) hmtf op." mh2mpd qnLjgfr, hnpfr, pmh^mpdhg Jhmmphhpfr k gmphpfr 2nLhmhhpnL^, mp^hummtf k mj^h:
&frhmhumhm& ^mppmqfrft 4* ^m^npp 12 mtffruhhpfr phpmggnL^ gmhfr" mhqm^ hp ^mpmgn^ qnL^mp ^hpgphi (pmgfr smh mhpmtfhhpfrg, op." ^mp^):
&frhmhumhm& qpmqfrmnLpjnLh 1 bhpmpphhg, np mhhg 10,000 ppm^ k ^hmg t pmdmhhg 5 hnqnL Jfr?k: Apgm"h qnL^mp hummhm hpmhgfrg jnLpmpmh»nLpp, hph pmdmhhp hm^mumpm>m^:
&frhmhumhm& qpmqfrmnLpjnLh 2 bhpmpphhg, np hmpfrg nLhhg ^mpmgn^ ^hpghhi 10,000 ppmtf: Cum 9hq" 4hpmpmp5hh]fru h2Um6hhpfrg n"ph t m^h]fr hm^phmph]fr (^ngp qmtfmp). 10,500 ppm°^p, ph° 10,000 ppmtf qnL^mpmft 3 mn^nup:
&frhmhumhm& qpmqfrmnLpjnLh 3 bhpmpphhg, np hm?npp 10 mmpfrhhpfr phpmggnL^ mjh m^pmhghhpfr qhhpp, npnhg qhnL^ hp, hphhm^mmMhim hh: bph 9hp hhmtfmmh tl t hphhm^mmhUhinL, m^m. T-mg fr ^frfimhfr hlfrhhg qhhi m^h]fr gfr^, gmh mjuop, hnLjhgmh, nppmh mjuop, m^hjfrh, pmh mjuop:
&frhmhumhm& qpmqfrmnLpjnLh 4 n"ph t m^h]fr m^mhn^ hm^ gfr^ nfruhmjfrh. hhpphhi 9hp qnL^mpp tfhh pfrqhhunL^ mhmfr^nL^, hhpphhi 9hp qnL^mpp Jhhfrg m^hifr pfrqhhuhhpnL^ hmtf mhmfr^hhpnL^:
^pbmbumUmb qpmqpmnLpjnLb 5 bbpmqphbg, np pub^nLtf bhpqph hp qrntfup, pubUp hutfu&ujbhi t 5hp fabmjnqmhmh hu2^pb muphUub m^himgbhi 15 mn^nu: Cum 9hq" pmbUp hpUpnpq muprntf m^h]p 2m°m qnLtfup t Uhiugbhim. 9hp fabmjnqmhmh hm2dpb, pub mnugpb mupnLtf, ph" bnL]b>m^:
^pbmbumUmb qpmqpmnLpjnLb 6 bbpmqphbp, np T-mp mbhp 10,000 qputf 9hp fabujnquhub hu2^pb, k pubUb ujq hu2^pb muphUub Uhugbrntf t 10 mnUnu: nppu"b qrntfup T-mp UnLbhbup hu2^pb 5 mmpnLg, hph hu2^pb tfnLmp Umtf hu2^pg hp >Uumuphp:
^pbmbumUmb pm^mpmp^mftnLpjnLb 1* M ub&buhub ^ptmbuthph tfmupb tfmmfthip Umpnq t mbbmbqumnLpinLb ^mmfimnh]:
^pbmbumUmb pm^mpmp^mftnLpjnLb 2 bpp UmqtfnLtf hp 9hp h^mtfnLmp 6mfauhinL 6pmqpp, nppm"b hmfimfa hp hhmknLtf qpmb:
^pbmbumUmb pm^mpmp^mftnLpjnLb &P 3 CbqhmbnLp mntfmtfp, nppmbn"^ hp pm^mpmp^mft 9hp pbpmgpU mbSbmUmb ^ptmbumUmb ^pfimhn^" hm2^p mnbhin^ 9hp mhmp^bhpp, ^mpmphpp k fahulJnqnLpJnLhhhpp:
^pbmbumUmb upphu &U 1 bu >u^uquhg 2mm ^mpmphp mbhtf m]u ^mhpb:
^pbmbumUmb upphu &U 2 ^hpgpb 12 m^puthph pbpmgpnLtf ^upmumhphppg Umtf ^mpmpp hu4upuqptfuh pudphhhppg 9hq hhm uu^ hmummmt"] hb:
^pbmbumUmb upphu &U 3 ^tf $phuhuhhpp pbtuphhip Uupnq t ump^hi, np uppmu upuq pupufap, Uutf' upphu qqutf:
* -upghpp updhpbhpp 2pgUh hb (op." 0-b qup&l
Unqhjp Umqtftfmb qnp&pbpmgnLtf m^jmi-bhpp ^m^hpmUmbnLpjmb (validity), hnLumjpnL-pjmb (reliability), m4jm]bhpp hmtfm^mmmufam-bnLpjmb (goodness of fit), bnptfmi pm2fatfmb k hqpmjpb mpdhpbhpp (outlier) umnLqtfmb mpqjnLbpnLtf tfnqhjp npmUp pmphjm^tfmb b^mmmUn^ mbhpmdh2mnLpjnLb t mnmgmgh ummg^mft Umhmimbnppup hhnm^npnLpjmb mpdhpbhpp hptfmb ^pm pbmpmbppg hhnmgbh 4 hqpmjpb mpdhpbhp (^mmmufambbhp 84, 247, 284 k 429), nppg hhmn bnppg ppmUmbmgbhi hmummmnq qnp&nbujpb ^hpinL&nLpjnLb (CFA), umUmjb N=511 pbmpmbpn^ [6, tg 631; 11, tg 622]: pbmpmbpp ftm^m^p bhpUujmgnLg-
^mUmb t (tfh& t 385-pg), ummg^mft mpqjnLbpbhpp hbmpm^np t mmpm&hi -- pbmU^nLpjmb ^pm: ^pmUmbmg^mft qnp&nqnLpjnLbbhppg hhmn ummg^hi t Q-ftm^mmUhp 1-nLtf bhpUmjmg^mft mhupp:
Q-np&nbujpb 4hpinL&nLpjmb pbpmgpnLtf, pmgp qnp&nbmjpb phnbnLtfbhppg k hqpujpb
1): UqjnLumUp Uuqtf^hl t hhqpbmhhhph Unqtfpg:
mpdhpbhppg, nL2mqpnLpjnLb t ^hmp qmp&bhi tfp 2mpp mji mfamnpn2p^ umnLqnLtfbhpp (diagnostic test), pb^pupf hb ^m^hpmUmhnLpjmb, hnLum-IpnLpjmb 4hpinL&nLpjnLbp, m^jmjbhpp hmtfm^m-mmufambnLpjmb, bnptfm^nLpjmb umnLqnLtfbhpp:
Unmb&bmg^nLtf hb ^m^hpmUmbnLpjmb hpUnL mhumU hmtfmtfhm ^m^hpmUmbnLpjnLb (convergent validity) k mmpphpu^ ^m^hpmUm-bnLpjnLb (discriminant validity) [15, tg 6]: -mtfmtfhm ^m^hpmUmbnLpjnLbp mhqp nLbp, pmbp np ummbqmpmmg^mft qnp&nbmjpb phn-bnLtfbhpp 0.5-pg tfh& hb (gnLjg hb mp^mft Q-ftm^mmUhp 1-nLtf o^mjpg qh^p pmnmbUjnLb nLqq^mft ujmpbhppb Upg), qnp&nbbhpp ^pfim-Umqpnphb b2mbmUm|p hb 5% b2mbmUm|pnLpjmb tfmUmpqmUnLtf, ^n^nfamUmbbhpp hmtfmUg^mft hnLumjpnLpjnLbp (composite reliability) tfh& t 0.6-pg, tfh& t bmk ummbqmpm 2hqtfmb (average variance extracted) gnLgmbp2pg [15, tg 6]:
^йшщшт^Ьр 1. <шитштщ qnpдnüшJfiü ^Ьщтдтршй (CFA) шр^тйрйЬрр ^рд^йЬрр umшйцшpmшgrf_шд Ш)1
SшpphpшЦp 4ш4hpшhшünLpJшü qüшhшmúшü hшúшp ppшЦшüшg4hL t hhmhpnrnpfrrn-únünrnpfrrn ^nnh^g^ühpp hшpшphpшЦgnLpJшü (heterotrait-monotrait ratio of correletions Цшй HTMT) ^hpinLÖnLpjnLÜ, npü ШÚфnф4шÖ t
Ц^тишЦ 2-m.ú: U^bhmjrn t, np Ü2^ö шpdhgühpp фп^ hü 0.85-pg, püp Ü2шüшЦnLÚ t, np mшpphpш4p 4ш4hpшЦшЬnLpJnLÜp ünijü^hu rnhpp nLÜp:
Цп.|пшш^ 2. ^hmhpnmpftm-ününmpftm fymh^g^ühpft hшpшphpшfygnщJшй (HTMT) qnpдшfyftgйhpp
фирринфй %|iiiiiiiiiiuil|iiiii (Пшкфиниррий upphu RjnLb
1 Uju к йЬшдшй qöшщшm^hpЬhpp к шц)nLuш^Ьhpp ^qú^hj hb hhqpta^bhpp ^n^úpg, m^^jbhpb шpmшhшЬ4h]_ hb IBM SPSS AMOS 2б tato^pq^mjpb öpшqppg:
ilui|ipui((lH> - 0.488 0.266 0.445
%liiiuiiiiiuilpiiii (HiuiqliinnLpjiiLii 0.488 - 0.104 0.202
%liiiuiiiiiuilpiiii iipphu 0.266 0.104 - 0.701
%liiiuiiiiiuilpiiii pu^upup^u^nLpjnLh 0.445 0.202 0.701 -
S4jm]bhpp hmtfm^mmmufambnLpjmb qpmUmbnLpjnLbnLtf pbqnLb^mft bnptfmbhpp hhm,
umnLqtfmb hmtfmp hm2^p hb mnb^nLtf tfp 2mpp hbmpm^np t hqpmUmgnLpjnLb Ummmphp gnLgmbp2bhpp mpdhpbhp, npnbp, hmtfhtfmmhp^
UqjnLumU 3-pg Umphjp t hmuUmbm]_, np ummg^mft mpqjnLbpbhpp pm^mpmp hb [6, tghp 639-647; 11, tg 646]:
Uqjniuw^ 3. Stf/wihhpfi huriu^umuufauhnLpjuh hnpduhhpp k hu2tfupfyujfih wpqjnihphhpp.. huumumnq
S^juibhpl hudu^umuu^ubnLpjnLb ■udhdumnLpjnLh ^npdu updhg UpqjnLbg
CMIN/df < 5.00 3.711 Pm^mpmp t
CFI > 0.90 0.909 Pm^mpmp t
IFI > 0.90 0.911 Pm^mpmp t
PNFI > 0.50 0.568 Pm^mpmp t
PCFI > 0.50 0.586 Pm^mpmp t
RMSEA < 0.08 0.073 Pm^mpmp t
SRMR < 0.08 0.049 Pm^mpmp t
№qhpubhpp k qpubg hu^u^nLtfbhpp ^hpuphpju]_ tfubputfuub" [6, tghp 639-647; 11, tg 646]:
"Unptfmi pm2fatfmb ^hpmphpjmi Umpnq hbp b2hi, np tfpmqnp&nb muptfhmppm (skewness) k tpughu (kurtosis) ^hb hmjmbmphp^hi, puU pmqtfm-qnp&nb tpughup mpdhpb t 1.833 (^npp t 5-pg), puU pmqtfmqnp&nb bnptfmpLpjmb UppmpUmUmb hmpmphpmUgnLpjnLbp (c. r.)' 1.338 (^npp t 1.96-pg): Pnjnp gnLgmbp2bhpp hm^mumnLtf hb bnptfmi pm2fatfmb mnUmjnLpjnLbp: ^.hpp b24m& hqpujpb mpdhpbhpp hhnmgnLtfpg hhmn (Umhmimbnppup hhnm^npnLpjnLbp tfh& tp 26-pg) mji hqpujpb mpdhpbhp ^hb hmjmbmphp^h];
UqjnLumU 4-pg hpkntf t, np m^jmjbhpp hutfuqummufambmtf hb UmnnLg^m&pujpb tfnqhjpb, mqjnLumUnLtf bhpmn^mft pninp
^.hpp b24m6 mfamnpn2p^ umnLqnLtfbhppg k hmummmnq qnp&nbmjpb ^hppL&nLpjmb ppmUm-bmgnLtfpg hhmn Umphjp t ppmUmbmgbhi UmnnLg-4m6pujpb hm^mumptfmb tfnqhjm^npnLtf (structural equation modeling Umtf SEM) [6, tg 649]:
"Umfa, pb^hu hmummmnq qnp&nbujpb ^hp-inL&nLpjmb qh^pnLtf, ujb^hu tl UmnnLg^mft-pmjpb tfnqhjp Umqtftfmb dmtfmbmU m&hpmdh2m t umnLqh]_ m^jmibhpp hmtfm^mmmufam&nLpjnLbp UmnnLg^mft tfnqhjpb:
gnLgmbp2bhpp hm24mpUujpb mpdhpbhpp pm^mpmpnLtf hb &nptfmjpb bUmmtfmtfp b24m& ^mjtfmbbhppb:
Ui]jiiliiiiiIi 4. Stf/uihhpfi huriu^umuufauhnLpjuh hnjttiuhhpp k hu2tfupfyujfih upqjnihphhpp. tyunnigtfudpujfrh
S^juibhpl hudu^umuu^ubnLpjnLb1 ■^udhdumnLpjnLh ^npdu updhg UpqjnLbg
CMIN/df < 5.00 3.570 Pm^mpmp t
GFI > 0.90 0.955 Pm^mpmp t
AGFI > 0.80 0.921 Pm^mpmp t
CFI > 0.90 0.908 Pm^mpmp t
IFI > 0.90 0.910 Pm^mpmp t
1 №qhpubhpp k qpubg hu^u^nLtfbhpp ^hpuphpju]_ tfubputfuub" [6, tghp 639-647; 11, tg 646]:
155
PNFI > G.5G G.6G5 Pш^шpшp t
PCFI > G.5G G.626 Pш^шpшp t
RMSEA < G.G8 G.G71 Pш4шpшp t
SRMR < G.G8 G.G5G Pш4шpшp t
Qöшщшm^hp 2-rnú bhp^m^g^ö hb (щшр-bhpp mhupn^) unijb hhmшqпmпLpJПLbпLÚ mnm^
рш2^ш0 4 4шpUшöЬhpp к ^шnпLg4шöpшJpb únph]^ hшJhgш^шpqшJpb mшpphpш^p:
(eîT)-^.
(eîj)-^
Эф1ли1шш1|ш1| pLui|ujpujpi|ujönLpjnLlj 1
Эф1ли1шш1|шЪ i|iupEiuqfiö 2 Э>fillшЪиш1|mil i|iup{>ujqtiö 3
^дшщшш^Ьр 2. ЧшnnlgtfшдpшJfcй ünqhjß hщ|hgшЦшрqщ|fcй тшррЬршЦ
^шnпLg4шöpшJpb únph]^ hшJhgш^шpqшJpb mшpphpш^пLÚ щшm^hp4шö hb qnpönbbhpp, qpшbp pbпLpшqpпp фпфп^ш^шbbhpp, qnpönbbhpp úp^k фп^шqшpй ^^hpb nL qpшbg nLppnLpjnLbbhpp" 4шpUшöЬhpp hшúшщшшшu-^шЬ b2шbш^пLÚbhpпф
5-nLÚ, npmhq шпшЬ^РЬ bhp^m^g^ö hb nLppp, шЬ^ррш^р к pЬphшЬпLp t$h^mbhpp b2шbш^шфпLpJПLbp, ^шщр шп^ш]^р]шЬ ph^pnLÚ Ьшк ppш
Qnpönbbhpp фп^шщш^g4шöпLpJшb
pbnLjpb nL nLppnLpjnLbbhpp úhpdhpL ^шй pbpnLbhpL hшúшp ppш^шbшg4hl t qpшЬg 4pfiш^шqpш^шb umnLqnLÚ, npnbg шpp]ПLbp-bhpb ш^ФпФ4ш0 hb
nLppnLpjnLbp: ЦПШ^Ь ^p^öp ph^pnLÚ ^ШЩЬ шЬ^ррш^ t, pшgшuш^шb, úpb^phn úbшgшö pnpp 4шpUшöЬhpp ph^pnLÚ nLppp ^шщ t ШП^Ш:
5. йюшршдр^шд ^шрЦшдййр^ ummqmtíp к дрш^ шрщтйрйЬрр
Cbqhmbrnp
Чшр-^шй фпфп^ш^шЬ фпфп^ш^шЬ P-шрдйр кшщ P-шрдйр P-шрдйр кшщ UpqjnL&p
Hl ^ЬШЬИШ^ШЬ upphu &pbшbuшl[шb 4шpgшqpö G.GGG (-), b2шbш^ш|p G.GGG (-), b2шbш^ш|p G.735 Ь2ШЬШ^Ш^ ЫЬ^РРШФ ^шй úpgbnp-qш4np4шö
H2 &pbшbuш^шb qpшqpmnLpJnLb &pbшbuшl[шb 4шpgшqpö G.GGl b2шbш^ш|p - - G.GGl (+), Ь2ШЬШ^Ш^ nLppp ^шщ
Регион и мир, 2022, № 2
H3 Ь^ЬшЬиш^шЬ pш4шpшp4ш-önLpjnLb Ь^ЬшЬиш^шЬ 4шpgшqpö 0.001 ^шЬш^шф - - 0.001 ^шЬш^шф HLqpq ^шщ
H4 Ь^ЬшЬиш^шЬ upphu Ь^ЬшЬиш^шЬ pш4шpшp4ш-önLpjnLb 0.001 ^шЬш^шф - - 0.001 ^шЬш^шф HLqpq ^шщ
UqjnLum^ 6-nLÚ mpmmgni^ö qnpöm^pg-ühppg ки rnhumühip t, np фpüшüишhшü upphup к фpüшüишhшü pш4шpшp4шönLp)шü йр?к ^m^p pmgmum^mü t, mjupügü" фpüшüишhшü upphup ш4hlшgúшüp qnLqpüpшg ü^qnLÚ t фpüшüишhшü pш4шpшp4шÖnLp)nLÜp, pU^ фpüшüишhшü pш4шpшp4шönLp)шü, фpüшüиш-^ü qpшqpmnLp)шü pшpйpшgúшüp qnLqpüprng qpшhшü фpüшüишhшü 4шp2шqpö t qpu^p-
^nLÚ: Güq npnLÜ, фpüшüишhшü upphup úpш4np шfip цЬщрп1.й, фpüшüишhшü prn^rnprnp^rnftnL-pjnLÜp ü^qnLÚ t 0.591 ^hrnn^, фpüшüишhшü pш4шpшp4шönLp)шü к фpüшüишhшü qprnqp-mnLp)шü úpш4np pшpйpшgúшü цЬщрпьй фpüшüишhшü 4шpgшqpöp qpшhшü mhqш2шpd t nLÜhünLÚ hшúшщшmши^шЬшpшp 0.4б4 к 0.295 ^hrnn^: Ъ2^ш0 фnфn^nLp)nLÜühpp ^pfiшhшqpnphü ü2шüшhшlp hü rnüqrnú 0.1% Ü2шüшhш|pnLp)шü úшhшpqшhnLÚ:
üqqbgnLpjnLb итш^шрт ^р^т^ш^шЬ 1iiii|iiiiph|iiiilig nL-RjnLb Чшр^шй
^ЬшЬиш^шЬ pш4шpшp4шÖnLp]nLÜ <- ^ЬшЬиш^шЬ upphu -0.59i 0.078 -7.б2б H4 (-)
^ЬшЬиш^шЬ 4шppшqpö <- ^ЬшЬиш^шЬ pш4шpшp4шÖnLpJnLÜ 0.4б4 0.ii3 4.113 H3 (+)
^ЬшЬиш^шЬ 4шppшqpö <- ^ЬшЬиш^шЬ qprnqprnnLpjnLÜ 0.295 0.0б 4.887 H2 (+)
.40
(ein* älflTjLUllUUjljUjll uppbu 1 п
Í)hllLUllULljL|Ujll Ufäpbü 2
(еШ-* Л5Ь1|Ш1|иш1|Ш1| uppbu 3
.34
(е6> ÍlfllJLLlllUUjljUjll qpUJQtlLririLpjnLll 2
(е9> älflTjLUllUUjljUjll qpiliqtlLririLpjnLll 5 Jr)
(еН))-*- ;Ь[Л1ш1шш1|ш1| qpLuq.|iinnLpjnLli 6
e2 ) ( e3
^йшщшт^Ьр 3. кшютд^шдрш^й tínqh¡fi (SEM) шрщтйрйЬрр (fcfinühpp итшйцшртшд^шд hü)
frt^hu thp^mjmg^mft t Q-ftm^mm^hp 3-mtf, ptm^mpjmt ^ptmtum^mt ^mppmq&p ^mppmgpmt 34%-n^ pmgmmp^mtf t tfnqhimtf thpmn^mft qnp&ntthpn^, pu^ ^ptmtum^mt pm^mpmp^m&mpjmt ^mppmgpmk 55%-n^ $p-tmtum^mt upphun^: ^mnmg^m&pmjpt tfnqhjp gnLjg t mmjpu, np t2^m& qnpftntthpt mnmtg-pmjpt ht ^-mri ptm^mpjmt ^ptmtum^mt ^mppmqp&t nLunLtftmupphinL mhumt^jmtpg, pmtp np ^ptmtum^mt upphup ^ptmtum^mt pm^mpmp^m&mpjmt tfp^ngn^, pu^ ^ptmtum-^mt qpmqpmmpjnLtt nL ^ptmtum^mt pm^m-pmp^m&mpjnLtt mppm^pnpht t2mtm^m|p mqqhgmpjnLt mtht ptm^mpjmt ^ptmtum-^mt ^mppmqftp ^pm:
^mmmp^mft nLunL^&muppnLpj mtthppg, 4hpinL&nLpjnL&pg k mp&mtmqp^mft mpqmtp-thppg ^mphjp t ^mmmphi rip 2mpp hqpm^m-gmpjnLtthp:
• H2, H3, H4 ^mp^m&thpp hmummmnL^p gnLjg t mmjpu, np tfnqhimtf thpmn^mft qnpftnt-thpp ^ptmtum^mt ^mppmq&p tm^mt npn2p^-thp ht (pmgmmpmtf ht ^ptmtum^mt ^mppmq&p ^mppmgpmjp 34%-p):
• £mtp np ^ptmtum^mt upphup mnm^h ptnpn2 t ptm^mpjmt gmftp h^mtfmm mthgnp hmm^m&pt k ^ptmtum^mt pm^mpmp^m&m-pjmt tfp^ngn^ t2mtm^m]p mqqhgmpjnLt t nL&h&nL^ ^ptmtum^mt ^mppmq&p ^pm (n nLppm^pnpht), 4hp?p&p pmphjm^tfmt mhumt-^jmtpg ptm^mpjmt 2p2mtmtf ^ptmtum^mt upphup mn^mjnLpjnLtp hptftmfatqpp t qnpftm-qp^mpjmt k mppmmnLpjmt pmp&p tfm^mpqm^p ^mj tfmtthpmtf:
• Upmdmtfmtm^ ^ptmtum^mt pm^mpmp-^m&mpjnLtp, &2m&m^m|p mqqhgmpjnLt mth-tmp^ ^ptmtum^mt ^mppmq&p ^pm (1% ^n^n^mpjnLtp hmtqhg&mtf t ^ptmtum^mt ^mppmq&p 0.464% ^n^n^mpjmt), htmpm^np t pmp&pmgthi hmm^m^hu ptm^mpjmt h^mtfmmthpp mfip hm2^pt:
• &ptmtum^mt qpmqpmnLpjmtp bmjt-^hu tm^mt t qmrnmu^ffltmrnni ^ptmtum^mt ^mppmq&p fapmMmt hmtfmp (1% ^n^n^m-pjmtp hmtqhgtmtf t ^ptmtum^mt ^mppmq&p 0.295% ^n^n^mpjmt): ^m htmpm^np t ppm-^mtmgthi mt&tm^mt ^ptmtum^mt tfp^ngthpp ^mnm^mptfmt MmmpjnLtthpp pmphjm^mt, ^ptmtum^mt qpmhjpgthpp m^hmgtfmt tfp^n-gn^, mji_ ^hp^ mumft ^ptmtum^mt ^ppmpjmt tfp^ngn^, npmhp ^mpknp^mtf t n tfpmjt q^png-thpp, hmtfmjumpmtthpp, mj^k ^ptmtum^mt ptumpmmmthpp qhpp:
• &ptmtum^mt qpmqpmmpjnLtt mnm^h tm^mt mqqhgmpjnLt mtp ^ptmtum^mt ^mppmqftp ^pm, pmt pttmp^^mft ^jnLu qnpftntthpp, pt^p ku ^h^ mtqm^ ptqq&mtf t
^ppm^mt hm^m^mpqm^ pmph^n^m^thpp ^mpknpmpjnLtp, ^mutm^npm^hu ^mppm-qftmjpt ^ptmtuthpp tfmutmqhmthpp qmmpmu-mm^p k munL^tm^mt ftprnqphprntf ^mppm-qftmjpt ^ptmtuthpp 4hpmphpjm]_ qmuptpmg-thpp thpqpm^p qmpnp ht ^ptmtum^mt qpmqpmmpjmt pmp&pmg^mt k ^ptmtum^mt ^mppmqftp pmph^m^^mt qpm^mt u^pqp k mqqm^ ipth]_:
Uju^pun^, hhmmqnmnLpjmt mpqjnLtpnL^ pmgmhmjm^hgpt, np ^ptmtum^mt upphup ^ptmtum^mt pm^mpmp^mftnLpjmt ^p^ngn^ pmgmum^mt, pu^ ^ptmtum^mt qpmqpmmpjnLtt nL ^ptmtum^mt pm^mpmp^mftnLpinLtt mppm^p k qpm^mt ^pfim^mqpnpht t2mtm^m|p (0.1% t2mtm^m|pnLpjmt ^m^mpqm^m^) mqqhgmpjnLt ht rnthtrn^ ptm^^rnpjmt $ptmt-um^mt ^mppmq&p ^pm: Ummg^mft mpqjrntp-thpp ^mpnp ht oqmm^mp ipth]_ ptm^^rnpjmtp, ^ppm^mt k ^ptmtum^mt ptumpmnLmthppt, mtmhum^mt pmpmpm^mtnLpirnt ^2m^npth-ppt:
Oqmmqnpd^wd qpm^mbnLpjmb gwb^
1. ^ppqnpjmh, t. (2021). ^^ nhqpqhtm mtmjpt mtmhunLpjnLtthpp ^mppmq&p ^pm mqqnq ungpmi-mtmhumhmt qnpftntthpp qtmhmmnL^. ^mmdnipjm^ k pm^mfm^mhnipjmh qfrmMfymh hwhqhu, 15(4), 153-161.
2. Chauhan, S., & Indapurkar, K. (2020). Interplay of Financial Knowledge and Psychological Factors on Financial Behavior: Evidence from Urban India. International Journal of Scientific & Technology Research, 9(4), 3461-3468.
3. Dew, J., & Xiao, J. J. (2011). The Financial Management Behavior Scale: Development and Validation. Journal of Financial Counseling and Planning, 22(1), 43-59.
4. Dew, J., & Xiao, J. J. (2013). Financial Declines, Financial Behaviors, and Relationship Satisfaction during the Recession. Journal of Financial Therapy, 4(1), 1-20. doi:10.4148/jft.v4i1.1723
5. Grigoryan, E. M. (2021). Impact of Socioeconomic Factors on the Saving Behavior of the RA Resident Households. Messenger of ASUE, 2021(5), 22-34. doi:10.52174/1829-0280_2021_5_22
6. Hair JR., J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis (7 fatfp.). Pearson Prentice Hall.
7. Hasibuan, B. K., HR, W. A., & Lubis, Y. M. (2018). Financial Literacy and Financial Behavior as a Measure of Financial Satisfaction. Advances in Economics, Business and Management Research (AEBMR), 46, 503-507.
8. Henager, R., & Cude, B. J. (2016). Financial Literacy and Long- and Short-Term Financial Behavior in Different Age Groups. Journal of Financial Counseling and Planning, 27(1), 3-19. doi:10.1891/1052-3073.27.1.3
Регион u Mup, 2022, № 2
9. Lee, Y. G., & Dustin, L. (2021). Explaining Financial Satisfaction in Marriage: The Role of Financial Stress, Financial Knowledge and Financial Behavior. Marriage & Family Review, 1-25. doi:10.1080/01494929.2020.1865229
10. Mandell, L., & Klein, L. S. (2009). The Impact of Financial Literacy Education on Subsequent Financial Behavior. Journal of Financial Counseling and Planning, 20(1), 15-24.
11. Meyers, L. S., Gamst, G., & Guarino, A. J. (2017). Applied Multivariate Research: Design and Interpretation (3 faüp.). SAGE Publications, Inc.
12. Mien, N. T., & Thao, T. P. (2015). Factors Affecting Personal Financial Management Behaviors: Evidence from Vietnam. Second Asia-Pacific Conference on Global Business, Economics, Finance and Social Sciences (AP15Vietnam Conference). DanangVietnam.
13. Owusu, G. M. (2021). Predictors of Financial Satisfaction and Its Impact on Psychological Wellbeing of Individuals. Journal of Humanities and Applied Social Sciences, 1-18. doi:10.1108/JHASS-05-2021-0101
14. Robb, C. A., & Woodyard, A. S. (2011). Financial Knowledge and Best Practice Behavior. Journal of Financial Counseling and Planning, 22(1), 60-70.
15. Sharif, S. P., & Nia, H. S. (2018). Structural Equation Modeling with AMOS. Tehran: Artin Teb.
16. Stolper, O. A., & Walter, A. (2017). Financial Literacy, Financial Advice, and Financial Behavior. Journal of Business Economics, 581-643. doi:10.1007/s11573-017-0853-9.
Cdana/^wü&ütfhi f 10.03.2022 Pe^H3upoeaHa/0-pwfanutfhi f 24.03.2022 npuHxma/^üqniütfhi f 28.03.2022
