Научная статья на тему 'ОЦЕНКА МАКРОЭКОНОМИЧЕСКОГО  ВЛИЯНИЯ ВНЕШНИХ ЛИЧНЫХ  ТРАНСФЕРТОВ РА'

ОЦЕНКА МАКРОЭКОНОМИЧЕСКОГО ВЛИЯНИЯ ВНЕШНИХ ЛИЧНЫХ ТРАНСФЕРТОВ РА Текст научной статьи по специальности «Экономика и бизнес»

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Ключевые слова
ЛИЧНЫЕ ТРАНСФЕРТЫ / ВВП / СОВОКУПНЫЙ СПРОС / КОРРЕЛЯЦИОННАЯ МАТРИЦА / ЭКОНОМЕТРИЧЕСКАЯ МОДЕЛЬ / PERSONAL REMITTANCES / GDP / AGGREGATE DEMAND / CORRELATION MATRIX / ECONOMETRIC MODEL

Аннотация научной статьи по экономике и бизнесу, автор научной работы — Харатян Алвард, Тигранян Варсик, Аветян Заруи

В статье анализируется поток личных трансфертов из-за границы в Армению. Макроэкономическое влияние внешних личных трансфертов оценивалось с помощью эконометрических моделей, построенных для экономики Армении. Было установлено, что поступающие из-за границы личные трансферты в краткосрочной перспективе оказывают значительное положительное влияние на ВВП и расходную составляющую ВВП, а также на ВВП на душу населения. 10-процентное увеличение личных трансфертов из-за границы в текущем квартале положительно влияет на рост конечного потребления на 0,55 процентных пункта, в следующем квартале положительно повлияет на рост ВВП на 1,2 процентных пункта и на рост ВВП на душу населения на 0,78 процентных пункта, а через год положительно повлияет на рост валовых инвестиций на 1,78 процентных пункта. Полученные оценки могут быть использованы в качестве основы для разработки эффективной макроэкономической политики, направленной на регулирование шоков, вызванных потоками внешних личных трансфертов

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ASSESSMENT OF MACROECONOMIC IMPACT OF RA EXTERNAL PERSONAL REMITTANCES .

The flow of personal remittances from abroad to Armenia is analyzed in the paper. The macroeconomic impact of external personal remittances was assessed using econometric models built for the RA economy. Personal remittances from abroad were found to have a significant positive impact on GDP and GDP expenditure components, as well as per capita GDP, in the short run. A 10 percent increase in personal remittances from abroad in the current quarter has a positive impact on the growth of final consumption by 0.55 percentage points, in the next quarter it has a positive impact on GDP growth by 1.2 percentage points and on per capita GDP growth by 0.78 percentage points, in the next year it has a positive impact on gross investment growth by 1.78 percentage points. The assessments obtained can be a basis for developing an effective macroeconomic policy aimed at regulating shocks caused by external personal remittance flows.

Текст научной работы на тему «ОЦЕНКА МАКРОЭКОНОМИЧЕСКОГО ВЛИЯНИЯ ВНЕШНИХ ЛИЧНЫХ ТРАНСФЕРТОВ РА»

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2 Sb'u Abdelhadi S., Bashayreh A., Remittances and Economic Growth Nexus: Evidence from Jordan. International Journal of Business and Social Scienc, Volume 8, Number 12, December 2017, t2 98-102:

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3 Sb'u Kumar R. R., Stauvermann P. J., Patel A., Prasad S., The Effect of Remittances on Economic Growth in Kyrgyzstan and Macedonia: Accounting for Financial Development. International Migration Vol. 56 (1) 2018, tg 95-126:

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5 Sb'u Olofsdotter K., Abdullaev R., Impact of remittances on economic growth in selected Asian and Former Soviet Union countries. Lund University, School of Economics and Management, 2011:

6 Sb'u Comes C.-A., Bunduchi E., Vasile V., Stefan D., The Impact of Foreign Direct Investments and Remittances on Economic Growth: A Case Study in Central and Eastern Europe. MDPI. Sustainability, 2018,10, 238, tg 1-16:

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^lunnLgijbL bti inliinbuiu^iui|iiul|iuli il|i 2UJPP Jnqb[libp, npntignui pn[np i|ini|infuiul|iulilibpQ q|iiniupl|i|b[ bti uiniug|inliiup qiupâpiuô, ubqnliiujtinLpjnLti mtibgnq i|ini|infuiul|iulilibpQ hiuppbgi|b[ bti Census X-12-|i l||ipiuniiiuijp: lipiuj-l|b|i (AlC-Akaike information criterion) m Gi[iupg|i inbqbl|iuini|iul|iutj jiuijiiu-li|i2libp|i (SIC-Schwarz information criterion) h|iiliulj i[piu pliinpi[b[ bti |iui|iu-qmjli Jnqb[tibpp: lTnqb|tjbpnLd piugiuinpnq i|ini(infuiul|iutilibp|i ptnqhiutinLp iuqqbgnL|3-jnLtjQ l|iufujiuL i|ini(infLiiuL|iuti|i i[piu i|ji6iul|iuqpnpbtj li2wtiiul|iu|]i t (Prob(F-statistic)<0.05): ^tjiuhiuini[iuô qnpôiul||igtjbpQ i|Ji6iul|iuqpnpbtj ti2iu-ti lu L) lu [h bti li2wtiiul|iu|]'inL[3jiuli 1-10 innl|nu Jiul|iupqiul|tjbpnLJ: 9-tiiuhiuiniu-L|iutitibpQ hnLuiu[|i bti, npntij) uinni.qi|b[ bti iniuppbp pbuinbpni|: U"iuuliiui|npiu-ii|bu, iltiiugnpqlibp|i hniinul|bqiuuin|il|nLpjnLtiQ uinnLqb|nL hiuiiiup L||ipiuni|b[ t PnbnL2-'Tliuqiuti-cl-nq^pbj|i hbinbpnul|bqiuuin|il|nLpjiuti (Breusch-Pagan-Godfrey Heteroskedasticity) pbuinQ, uiti L| lu |xi n Lfaj n Lti q uinnLqb|nL hiuLÎiup' PnbnL2-cl-nq^pbj|i Lui|LnnL|nnbijiug|iLuj|i LM (Breusch-Godfrey Serial Correlation LM) pbuinp, tinpJiu[ pLU2fumJ mlibtiiuLO uinnLqb[nL hiudiup' SiupnL-Pbnujj|i

8 Sb'u 11. Chnluuitijuiti, T-piuLiLuLiujli i|in[uujlignLJlibp[i Luqrj.bgnLfsjnLtiQ « mliujjfili mtimbunL-fajrutitibph LU2|xiLULnnLdh LuniugLuplih i|fiw> «lljLDliuipujbp» q.fimujL|Ujb hiulin-bu, 2016/12, tg 11-19:

9 Sb'u Karapetyan L., Harutyunyan L., The Development and the Side Effects of Remittances in CIS Countries: the Case of Armenia», 2013,

https://cadmus.eui.eu/bitstream/hand le/1814/27881/CARIM-East_RR-2013-24. pdf?seq uence=2:

linpiiiu|nLpjiuti (Jarque-Bera Normality) pbuuiQ: U"nr|.b|libp|i npuil||i qliiuhuiLn-Jixiti huiiiiup oqmuiq.np&i|bL t 62cl-PLnLl.LU& qbiribpii|itiLug|iLuj|i qi^oil^g!]'

l|iuq.|iptibpQ:

4bpinL6ni|ajnLb: ClujiuultiiuIiq pwfui|nLd t lihq-pwghwjlitj wntj^i|nrL miu-piuLnbuiuL| dujpLnujhpuji|bpLibp|i L htiiupLui|npnLpjnLtilibp|i hiuilLur|.pnLiilibp|"i: bpl|p|ili plinpn2 t ubqntiiuj|ili LupinwqliLU w2fuLULnLuti£>Luj|ili d|iqpLug|iiuj|i wi[wliquipwp piupSp grugiuli|i2 b LU2fuwph|i iniuppbp hwLni|LU&tibpnLiI pliuil|-

qiugduitj i[pui twl|uitj wqqbgnLpjriLtj l|iupnq bb rubbliLUL iupinbpl|p|ig urniug-i[nq ^>|iIiluIjuluL|luIi nburuputjbpQ, npnlig|ig bb LupiriLup|ili luIj51iluL|luIj mpiuliu-

2007-2013 pp. dwdwbwI^whwmi^w&riLij qba||i <iujiuuLniuli Luti5tiiul|iuli inpiutiui})bpintibpQ qpuUnpbL bli iu6|i ii|iLnnLir 755,8 d|ti L1LTL qn[iup|ig haiu-lib|ni[ 963,9 d[li LLLTL iqn[lup|n: 2014-2019 pp. diu dwtjLul|iuhLULni|LU&nLd qbiq|i <LujLuuinwli luIi51iluL|luIi Lnpuitju!|>bpintjbpQ 909,7 J[b LLLTL qn|wp|ig bijiuqbL bli d|il^lL 682,0 J[b LLLTL qniuip, Lupmaip|ilj luIj51jluL|luIi mpiuliu^bpin-libp/<LUL griLgujli|i2Q 8,7%-fig l|p6iuLni|bL t d|ili£b 5%, dfiti^qbri, <LujiuuLniuti|ig qrupu qliaignq luIi51iiuI|luIi Lnpiuliui}>bpLnlibp|i 6lul|lulq Lilnugb[ t hiupwpbpiu-LjLutinpbti L|lujnlIj (iuqjnLuujL| 1, q&wll|LULnl|bp 1):

llrynluiul) 1

« lupipuigfib LuhdhLul/Luh qmip ippiubufybpiptibpfi li <l>U-/i 2wpd[itipuigi] 2007-2019 pp. (Jib MIL rinpup)"

9206,311662,0 8648,0 9260,3 10142,1 10619,4 11121,3 11609,510553,310546,111527,412457,913672,7

616,9 707,6 498,8 532,7 642,3 685,1 785,9 712,6 466,0 427,1 488,4 490,0 489,9

755,8 837,3 602,2 661,1 790,0 843,8 963,9 909,7 649,1 608,7 680,5 665,7 682,0

138,9 129,7 103,4 128,5 147,7 158,6 178,0 197,1 183,2 181,6 192,1 175,7 192,1

^Lbp^hli miup|ilibp|ilj iupinbpl|p|ig umiugL[nq iuli(5liwl|iuli inpiuliu^bpinlib-p|i l|p6iuinnLdQ II « CLU-rud qpiulig duiutjLupiucHi|i Lutil)Jujti d|iinnLd[i, pliai-LjLutjlupujp, hpbbg LuqqbgrupjnLljli bb pnqlinLd bpl|p|i inliLnbuiul|Lutj qiupqiug-duiti l|pai, nLuui|i L|lupbnpi[nllI bli £luIiluI|luI|iuIi qliLuhiuLnrudtibpQ:

10 Sb'u U"hq.nwghntJ ini|jw|tibpQ Opiul|iupq 2030-fi hwdwinbpuinnLd. J|nq.pujg|nluj|n U qwpqiugdwtj qliiuhiuinnLilQ <wjiuuinwtinLiI, qbl|nLjg, LT|nq.pujg|iujj|n illngwqqwjfiti l|iuqJwl|bpii|nL[ajnili, ULPh CwjiuuLnwbfi LunLupb[nL|ajnLli, <wjwuLnwbfi <wbpwu|binnL[ajnLtj, 2019:

" LJLry n lu lu Lj q l|iuqi5i|b[ f https://www.cba.am/am/SitePages/statexternalsector.aspx, « qfiuipujj |n"U hLU2i|bL|2hnp b http://www.minfin.am/hy/page/_hy_chartJ, CC intiinbunL|ajnLtip ptinL|aiuqpnri h|nJ biul|iuli iIiuLjpnintiinbuiuljiub grng wtif^bbpQ (bniuilujwl|wjfitj) ini|jw|libp|n h|iJwtj l[piu:

9-0шщш1п1|Ьр 1. « lupipiujjfiti lubâbuiljiub h lubâbuiljuib qmip

ippuibu$bpipbbp/<bU 2uipd[ibpuig[} 2007-2019 pp. (%f

ULpmbpL|p|ng uiniugi|nrL шЬ0Ьш1|шЬ mpiuliu$bpintjhp|i h|idtjiul|iuli iup-iniuô|ili (tl|qnqhli) aiqqhgnLpjnLliQ u|ujùuitiiui|npi|iuô t i|hp2tiiul|ujli uu|iuruiiuli ijpiu lihpqnpôrupjiudp, npli iudpnr]2iul|iutj ii|iuhiutj2Lupl||i óiufuunijlnli piur|iur}-p|i^libp|ig t: <huiuiqninnLpjriLlinLij qliiuhiuini|tïL t iupinhpl|p|ig uiniugi|nrL uitiö-lnul|iuti inpiutiuí}>hpintihp|i uqqbgnLfajnLliQ i|hp2liLul|Ujti uu|iuruíiuti, lihpiinLÔ-diub, <Lli-|i, dbl| hui2L|nL[ <LLL-|i b. hiudiufuiunli libpqpnLJlibp|i ijpiu:

»-LbpLnL&nLfajnLtitibpnLiJ oqmiuqnpôi|b[. ^ ^ hbinlijuiL diulipninliinhuiuliiiili grugiutj|i2tibpp. ш1и[шЬш1|шЬ СЫТ J[b « qpiud (GDP), L|hp2tiLul|iuli uu|iun-diub óiufuubp' d[li « ppiud (CONS), hiudiufuiunli libpqpnLJlibp' d[li « qpiud (INV), lupiniuhiutinLiT lïlÏJ « qpiuij (EX), libpiinLÖnuT iî[li « qpiuii (IM), uitiö-lnul|iuti шршЬифЬршЬЬр шртЬр^р^д' ií|ti ILIXL q.n|iup (REM), iunLinpiuj|iti piutil|t¡p|i ш^шЬг^ЬЬр' lîlIj « qpiuií (DEP), iíhl| 2^h hiu2i|nil СЫТ « qpiuii (GDP_P_C)13:

М.ЬрпЬ2|Ш[ фпфп^ш1|ш1|ЬЬр|1 hiudiup hiu2i[iupl|L|hi bli h|idtjiul|iutj ptinl-ри^р^ЬЬрр1 LÎh^h^D' iîbq|imLiQ, uiniutir|xupin 2bqnLiÎQ, шпшф^Ф11.)^ ^ Мш~ qiuqrujli iwpdtplihpQ, Ьпрйш[ рш2[ипи1 гиЬЫници Иш4шЬш1|шЬп1.р|ги1|[]: ULju-u|bu, 1996-2020 pp. qIiI|iuô ^шйшЬш1^шИши11|ш0П1.й iupinhpl|p|ig iutiÖtiiul|iuli 1лрш1|ифЬр1л1|Ьр|1 iî|i2|iLi bnLULÎujLul|Luj|nli iupd"hpQ L|mqiJb[ 1125,8051 d|ti LiLTb гучшр, шаш^ш^^О1316,4 ií|li lilTL грпцир (2013 p. 4-pq hrauiíujiul|), ln|iu-quqinjlip1 15,2 J[b LLLTL фпцир (1996 p. 1-|ili t¡niudujiul|):

П-|пL|nL[bp|n d|iiui|np lupdiuin (ADF Unit Root) pbum|i iupq|rutjplihp|i hшJшÖШJlJ, гф1пшр1|1|пг[ pn[np с1"шJmljLuL|Luj|nlj 2шррЬрр п^ ишшд|лпЬшр hti, qpiulip ^0--' qnpÖQlipiuglihp bli14: UhqnliiujtiriLpjnLli rnlibgnq <Lli, iíhl| 2^h hiu2i|ni( СЫ1, ш1|0Ьш1|ш1| шршЬифЬршЬЬр iupinhpl|p|ig, i|t¡p2liiul|ujti иьцшп-

12 <iu2i|ujpL|tjhp[i l|iuiniupi|h[ bli шгупшш1| 1-|п ini|jiu|lihp|n h|nliuli i[pw:

13 Sb'u 1лфш[1|Ьр|п piuquitihp, llqqiuj|ilj Ии^И^Ьр, tmiuiSujujliujjfitj gnLgujbf^tihp https://www.armstat.am/am/?nid=202. CC 4P, CC i|6ujpujj|itJ hu^ilbl^hi, https://www.cba.am/am/SitePages/statexternalsector.aspx:

14 Uiniugfintiiup hti rj-mnlinu] uiniughti LniupphpnL[ajnLtitihpQ r|.|nniupl|h|nLg hhinn

diuti Siufuubp, hiuiiiufuiunli libpqpnLiitibp, wpinwhwlmuj, libpiImdnLiI 2wppbpQ hiuppbgi|bL bli:

Mnnbijwglinti i|bp|nLdnLpjiuti luprjjnLtiplibpq l[L|lujnllJ bli, np iupinbpl|p|ig iuti5tiiul|iiili inpiutiui}>bpintibpQ md~bq q.piul|iuti l|nnb[jiiig|"intj l|iuii|bp rulibli wli-i|iutiiiil|iuli CLli-fi, dbl| hiu2i|ni{ <Lli-|i, i|bp2tiiiil|iuli uu|iunijiiili diufuub-p|i U hiudiufuiunli bbpr|.pnLJlibp|i hbirT rrl|npun'tj|n L|nnb|jiug|iiuj|i qnp&iul||igQ hiuJiuiqiuiniuufLiiuljiupiup 0,73, 0,72, 0,71 L 0,77 t: UjnLU grugiuli^bbpli hbin iunL|iu t hiupiupbpiuL|iulinpbli mdtiq qpiiil|iutj Liiuiq' L|nnbyiug|iiuj|i qnp&iul||igQ iniuiniulii[nLJ t 0,45-0,65 J|i2iul|iujpnLJ: Uiu li2iutiiul|nLd t, np iupinbpl|p|ig « i|infLiiuljgi[nrL LubStiLuLjiuti inpiubu^bpinlibp|i iu6p tiii|iiiuinnLd t L[tfnLnL^nLfaJLU^1 dbg libpiuni[iu6 gnLgiuli|i2libp|i iu6|iIj:

^-pbtigbpfi ii|iuin6iuniuL|lullmpjiub pbuin|i wprunLliptibpni^ ti2wtiiul|iii|]"inL-pjiuli 1% iIluL|ujpr(_ujL)nLii iibpdi|b[ bti |ili^ii|bu «iupinbpL|p|ig iuti5tiiul|iuti inpiuliu^bpinlibpQ Cbli i|ini|infunLpjiuli ii|iuin6iun ^bti», iujliii|bu t[ «CbU.-li iupinbpl|p|ig iuli6Liiul|iuLi inpiuliu^bpinLibp|i i|ini|infijnLpjiuti ii|iuin6iun ^t» qpn-jiuL|iuli i|iupl|iu6libpQ (Prob(F-statistic)<0.01) (iurijnLuiul| 2): Uiu li2uilnul|nLd t, np iupinbpl|p|ig iuti6tiiul|iuti inpiuliu^bpinlibp|i U <Lli-|i dfigU iunl|iu t bpl|-l|nr]diutj|i iqiuin6iuniul|iulinLpjnLli. iupinbpL|p|ig iuti(5tiiul|iutj inpiubu^>bpinlibp|i iu6p (iubl|nLJp), iudpnr]2iiil|iutj iqiuhiuli2iupL||i i[piu tibpqnp&b|ni[, piuqdiupl|j|i t$bl|inni[ JbSiugbrnJ t (ijinppiuglinLJ t) CLll-li: UjnLU L|nqJ|ig, gui&p inbinb-uiul|iutj iu6p bpLipmJ hiubqbgbnLJ t J|nq-pLutiLnljbp|n iui|b[iugdwtiQ, wprynLti-pmd tiiulT iupinbpl|p|ig iub5biuL|iuli inpnitiu$bpintibp|i iu6|iti: PiupSp inbinb-uujL|Lutj iu6p hbiupiui[npnLpjnLli t uinbq&nLd piup(5piugtib|nL L|bliuiuJiuL|iupqiu-L|q" iu2fuiuinb[ni| hiujpbti|i£>nLd, np|i lup^jmlipnul, iujl hiuijiuuiup u|iujdiutilib-prrnJ, L|p6iuini[nliI t iupinbpl|p|ig iuli6liiul|iiili inpiuliu^bpinLibp|i hnupp:

Liryniuuil| 2

Q-pbhgbpli uiuiipfiiuniulfuitinipjiuh p-buipfi u/pqjnitij)bbpin

Pairwise Granger Causality Tests Sample: 1996Q1 2020Q2

Null Hypothesis: Obs F-Statistic Prob.

DREM does not Granger Cause DGDP DGDP does not Granger Cause DREM 95 29.1754 24.4155 2.E-10 3.E-09

lipinbpl|p|ig uiniugijnq iuti0tiuil|iutj inpiubu^>bpinljbp|i luqqbgnLpjnLbp i[bp2biul|iuli uiL|iunJiub i[piu bbpl|iujiugi[nLJ t hbinlijiu[ dnqbinil15.

ln(C0NSSA)t = 2,595 + 0.0551«(Jlfftf^), + 0,lMiii(CDPSjj)r + + 0, 37D[n(C0JV5Sjl)t_i + 0,13Z(nCOF^jf + 0, 069[n(/MSjj jt_i +et ;

15 U~nr|.b|tibpnLii In q tibpl|iujiugtinLii t" ptiiuLjiuti h|nJpni[ [nq.wpfi|aiiq, ifinifinfuiul|iubfi ijbpgnLii q.pi|wö SA-b' hujp[abgi[uj&2Luppp:

U.r|jnLUUll| 3

LTnr|.b[ 1. Ijiufujuii ifinifinfviulpub' ilbpgbiulpub uupunJiub diujvubp

Dependent Variable: LNCONS_SA

Method: Least Squares

Sample (adjusted): 2000Q2 2020Q2

Included observations: 81 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

2.594710

0.604763

4.290455

0.0001

LNREM SA

0.019063

LNGDP SA

0.192030

0.054013

3.555277

0.0007

LNCONS_SA(-1)

0.369950

0.099833

3.705702

LNDEP

0.132056

0.032552

4.056782

0.0001

LNIM_SA(-1)

0.089423

0.047951

R-squared

0.996485

Mean dependent var

13.51790

Adjusted R-squared

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0.896250

S.D. dependent var

0.525375

S.E. of regression

Akaike info criterion

-3.964351

Sum squared resid

0.077620

Schwarz criterion

-3.786984

Log likelihood

166.5562

Hannan-Quinn criter.

F-statistic

4252.219

Durbin-Watson stat

1.600047

Prob(F-statistic)

0.000000

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p|i Luöfi inbiiu|Q t-pq brnuiîujLul|nuJ, -ti' wnLinpwj|iti piulil|bp|i w-

i|ailjr|.libp|i lu6|i inbJaip t-prj. bniudujiul|nLd, -p' tibpdnLÔduitj iu6|i

UlblJa|Q (t-1)-pr|. briLULÎUJLuL|nLLÎ, et -it LÎnr|.b|Jn Li|LULnLuhujL|Lulj u[ulul|i q.llLuhuJ-uiluL|ujIiq t-prj. bQiuiîujiuL|nLiî: U"nr|.biJn aipr|.jnLliplibp|i hwiiiuâwjlT aipuibpL|p|ig uinwgi|nq wtiâtiiul|wli inpwtiui}>bpinlibp|i 10% lu6q, lujl han|iuuujp iqwjdwti-libprud, plipaig|iL| briiudujuil|nLd, qpuil|iulinpbtj t wqqrud L|bp2tiiul|Lutj uu|iun-Jaib iu6|i l[piu' 0,55 innl|nuLuj|ili l|bmni[: OjUL-|i 10% iu6p, lujl hiuijiuuiup ll|luj-diulilibprud, pbpiug|iL| bnujJujLuLjnuJ, r|.piul|Lutjnpbtj t wqqrud i|bp2tiwl|iuti uu|iundwtj lu6|i l|jW 1,92 innl|nuiuj|itj L|binnL[, |iul| uiL|Lutjqlibp|i 10% iu6p qpiuL|Luljnpblj t wqqrud 1,32 mnl|nuLuj|ilj L|bmnL[: LbpdnLÔdwli 10% iu6p, lujl h lu i[iu u lu p ll|luj JLutitibpnuI, huignprj. bnuidujiul|nLd, qpwl|iulinpbli t wqqrud i|bp2liLul|LuLi ull|luqiJluIj iu6|i i|]W 0,89 innl|nu iuj|ili L|bmni| (iurunLuwl| 3):

LLrynLuiul| 4

LTni}b[ 1-fi libiugnpritibp/i hbipbpnuljbi}uiuipfiliniiajuib U uiilipnlfnnb[jiuglmijli pbuipbpfi uipqjnib^bbpp

Heteroskedasticity Test: Breusch-Paean-Godfre

F-statistic Obs*R-squared Scaled explained SS

1.057850 Prob. F(5,75) 5.336072 Prob. Chi-Square(5) 7.444817 Prob. Chi-Square(5)

Breusch-Godfrey Serial Correlation LM Test:

F-statistic Obs*R-squared

1.613537 3.429136

Prob. F(2,73) Prob. Chi-Square(2)

0.3906 0.3763 0.1896

0.2062 0.1800

U"nri_bL 1-|i iitiiugnpr|libpQ hniinul|br|xuuin|"il| bli (Prob(F-statistic)=0,391), oiL[LnnL|nribLLugL|Luö ¿bti (Prob(F-statistic)=0,206), nilibli LinpJlu[ pu^nu! (Prob(Jarque-Bera)=0,154) (wqjnLuwli 4, q.ôwu|iuinl|bp 2)16:

Series: Residuals

Sample 2000Q2 2020Q2

Observations 81

Mean -1.67e-15

Median -0.002803

Maximum 0.061386

Minimum -0.102563

Std. Dev. 0.028794

Skewness -0.365155

Kurtosis 3.757548

Jarque-Bera 3.736908

Probability 0.154362

-0.10

-0.08

-0.06 -0.04 -0.02 0.00

0.02

0.04

0.06

^duiujuimljbp 2. U~ni}b[ 1-fi iHiiugnpq.libpfi hnpiliu[ pui2[uiSuiti pbuip/i Lupqjnibf)libpi1

« bbptfrnMiuli i[piu iupinbpl|p|ig uiniugi|nrL luIj51jluL|luIj inpiuliu^bpin-libp|i Luqr}bgnL|ajnLliQ libpl|iujiuglinrL dnr}b[tj t.

I«(jjfjjg) = —0,004 + 0,759iii(GDJPSj9)t + 0.1331 n(REMSA) + 0.13 51 «(/ifAfJj4)t + et:

LLqjnLuuilj 5

lTni}b[ 2. Qiu/vjuj[ iftniftn/vuiliuiti' bbpJnidniJ

Dependent Variable: LNIMSA Method: Least Squares Sample (adjusted): 2000Q2 2020Q2 Included observations: 81 after adjustments

Variable

Coefficient

Std. Error

t-Statistic

LNGDPJSA LNREM_SA(-1) LNREM SA

-0.004128 0.758849 0.133268 0.134760

0.009446 0.183947 0.078390 0.074954

-0.437044 4.125366 1.700059 1.797895

0.6633 0.0001 0.0932 0.0761

R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic)

0.274828 0.246574 0.076584 0.451618 95.23540 9.727228 0.000016

Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter. Durbin-Watson stat

0.017853 0.088231 -2.252726 -2.134482 -2.205285 2.130258

16 Cbinwqwjnuj ùbpl|iujwgi|nrL pn[np Jnr|.b[übpnLij dtiiugnpiYübpp hni5nulibr|.wuuifil| bti, wijinn l|nnb[iugi|wô ¿bti, nLlibti tinpJiu[ piu2funLiJ:

UnqbinLd -li libpdnLÔdiutj iu6|i uibJiqli t t-pq bnaiJujail|nLJ: U"n-

qb|]i iupqjnLtjplibp|i hLudiuäiujlf wpinbpL|p|ig uinLugL|nq LubÔtiLuLjLulj rnpwliu-$bpinlibp|i 10% iu6p, luj[ hanjaiuaip ii|iujdiutjlibpni.d, plipwg|iL| bniudujLuL|nLd, qpwL|Lulinpbtj t wqqmd bbpJnLÔJiuli iu6|i l|jilu 1,35 innl|nuiuj|itj L|bmnL[, huL| hwgnpq bniudujiul|nLif 1,33 mnl|nuLuj|ilj L|binnL[: CblL-|i 10% iu6p, luj[ hiuL[iu-uiup u|wjiiiulitibpnLii, Qlipiug|iL| biuuLiujiuL|nLii, qpiuL|wlinpbti t wqqnuj libp-lînLÔiîujli lu6|i l[puu' 7,59 innl|nuwj|iti l|bmni| (iurijnLULuL| 5):

lipmbpl|p|ig uiniugi|nq LutiâtiwL|wti inpLuliu^bpintibpli wqqbgnLpjnLliQ « <Lli-|i i[piu libpl|LujLugi|nLiJ t hbuiUjaiL ünqb[nL|.

ln{GDPSA)t = 0.025 + 0,1211 jf_j - 0,198/îi(GDÎ,Jj1]î_1 + et

ULrynLUUll] 6

ITnrçbi 3. butfiijui[ ifinifinfuuiljuib' <LU

Dependent Variable: LNGDP_SA

Method: Least Squares

Sample (adjusted): 1996Q4 2020Q2

Included observations: 95 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

0.024630

0.005672

4.342547

LNGDP_SA(-2)

-0.198319

0.106431

-1.863358

LNREM_SA(-1)

0.120684

0.037281

R-squared

0.120105

Mean dependent var

Adjusted R-squared

0.100977

S.D. dependent var

iНе можете найти то, что вам нужно? Попробуйте сервис подбора литературы.

S.E. of regression

0.048698

Akaike info criterion

Sum squared resid

Schwarz criterion

Log likelihood

153.8257

Hannan-Quinn criter.

F-statistic

6.278990

Durbin-Watson stat

Prob(F-statistic)

0.002778

lTnqb|ji iupqjni.tjf)tjbp|i hiudiuäiujlf iupinbpl|p|ig uiniugi|nq luIjÖIjluL|luIi inpiuliu!|>bpinlibp|i 10% iu6p, wjL h lu l[lu u lu p ii|LujdiutjtjbpnLd, hwgnpq bnwd-ujoil|nLJ, qpoil|Luljnpbli t LuqqmJ CblL-|i lu6|i l|jW 1,2 mnl|nuLuj|ili L|bmni[ (LuqjriLuujl| 6): UpinbpL|p|ig ULnLugijnq luLiÖLiujL|ujIi inpiutiui}>bpLnlibp|i wqqbgnL-pjnLliQ tfbl| 2tiih hLU2L|ni| « <Lli-|i L[pai libpl|UJjLugLinq ijnqb|li t.

ln(GDPpc ^ = 0,013 + 0,078in(^FM3j3)t_1 + 0. 241ln(EXSA)t + et

lulîujluLjnllî, lnC^'^it -Li LupuiLuhailiJaib iu6|i LnbJa|p t-pq bnai JujluL|iilJ: Un-qb|ji luprynLtiptibphaiJluÖlujIi' wpinbpL|p|ig umiugL|nq luIiÖIiluL|luIi inpwliu-$bpinlibp|i 10% lu6q, luj[ h lu l[lu u lu p ll|luj JLulilibprnJ, hwgnpq briLU JujaiL|nLJ, qpLuL|Lulinpbb t wqqmd JbL| hiu2i|nil CLlL-|i lu6|i i|]W 0,78 mnL|nuaij|ilj L|buini|: Upinwhiutidiuti 10% lu6q, luj[ hwijujuLup ll|wjdwtitibpnLd, Qlipwg|iL| biuuLÏujwL|nLii, qpiuL|Lutinpbli t wqqmd dbL| 2^h hw2L|ni{ <Lli-|i w6|i ijpw' 2,4 uinL|nuLuj|ili Ljbuini| (LurumuaiLi 7):

uu^nnsLSbuiiq-hsnKra-anKb LLrynLuuil) 7

LTni}b[ 4 W/u/iu/ ifinifinfuwliwti' tiblf hu'2llnil

Dependent Variable: LNGDP_P_C_SA

Method: Least Squares

Sample (adjusted): 2000Q2 2020Q2

Included observations: 81 after adjustments

Variable

Coefficient Std. Error

0.013354

0.005076

t-Statistic

2.630935

0.0103

LNREM SA(-1)

0.077844

0.043259

1.799495

0.0758

LNEX SA

0.241078

0.053791

4.481740

0.0000

R-squared

0.250179

Mean dependent var

0.021274

Adjusted R-squared

S.D. dependent var

S.E. of regression

0.043427

Akaike info criterion

Sum squared resid

0.147097

Schwarz criterion

Log likelihood

140.6659

Hannan-Quinn criter.

F-statistic

Durbin-Watson stat

2.145822

Prob(F-statistic)

0.000013

lipinbpl|p|ig wtiötiwl|wti inpiutiui}>bpintibp|i luqq.bgnlfajruliq hwiiiufuiunti libpqpruijtibp|i i[piu tibpl|iujwgi|nLii t hbinlijiuL tfnq.b|ni|.

In(/JV|fJj5}r = -0,037+ 1744/n(GWM) + D^SBlnfGDPjj) + + 0.178in(REMsjiJ - 0.26/-n.(/A,rM)f_1 + et :

LLrynLuuilj 8

LTnr|.b[ 5. Liwfiijuii ifinifin|uuil|uitP huiiîuifuuirili tibpripmiltibp

Dependent Variable: LNINV_SA

Method: Least Squares

Sample (adjusted): 2000Q3 2020Q2

Included observations: 80 after adjustments

Variable Coefficient Std. Error t-Statistic Prob.

0.013351

LNREM_SA(-4)

0.178453

0.094932

1.879812

0.0640

LNGDP SA

0.223868

7.789285

LNINV_SA(-1)

-0.260023

0.109154

-2.382175

0.0197

LNGDP_SA(-1)

0.757786

0.313947

R-squared

0.484114

Mean dependent var

0.016289

Adjusted R-squared

S.D. dependent var

0.128886

S.E. of regression

0.095009

Akaike info criterion

-1.809231

Sum squared resid

Schwarz criterion

-1.660355

Log likelihood

iНе можете найти то, что вам нужно? Попробуйте сервис подбора литературы.

77.36926

Hannan-Quinn criter.

-1.749543

F-statistic

Durbin-Watson stat

Prob(F-statistic)

0.000000

U"nq.b|nLii ln(JArySd)f -tj h wiïiufuwnli tibpq.pnLiilibp|i w6|i inbiiu|ti t t-pq, InCi^n^aDt-i-Q' (t-1)-pq bnaiJujailirnJ, -p" iupinbpl|p|ig wtiâ-

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luqqnuj hiuiiiufuiunli lihpqpruiitihp|i iu6|i i|piu' 1,78 innl|nuiuj|iti l|hinni|; <LUL-|i 10% шбр, iujl hiui|iiiuiup u|iujiíiulilihpnLií, qpiul|iulinphli t luqqruií hiuiíiufuiunti lihpqpruiïtihp|i iu6|i i[piu' ptipiug|il| hniuiíujiul|nLij 17,44 innl|nuiuj|"ili l|hinni{, hmgnpq Ьпшйц|ш1|пиГ 7,58 innl|nuiuj|iti l|hinni{ (iururuuiul| 8):

bqpuil|uigrH|ajrutjtibp « inliinhurufajiulip plinpn2 t uhqntiiuj|"ili lupiniu-qbiu n^fuuiiniulipiujl'itj J|iqpmg|imj|i piupöp дгидш1ф2, npni[ u|iujdiutjiiii|np-i[iuô' bpL|p|i inliinhuiul|iiili qiupqiugdiuli 1[РШ twl|iuli niqqbgnL|ajruli bli rulib-lirud iupinbpl|p|ig uiniugi|nq iuliÖliiul|iiili илршЬифЬртЬЬрр, npnlig diuuliiupiu-d"|ntjQ « CLLL-rud 2007-2019 pp. ^^^l|iuhiuini|iiiônLd l|iuqdh[ t 5,08,7%: 2007-2013 pp. ^^l^l|iuhiuini|iuônLd qhu||i <iujiuuiniiili шЬ0Ьш1|ш1| ипршЬифЬртЬЬрр qpuUnpb[ bli iu6|i, |iul| 2014-2019 pp.' iutil|iíiuti ií|iinnLií: n-fiiniupliilnq сТшйш1|ш1|шИш1Л1|ш0П1й iupinhpl|p|ig iuliÖtiiul|iuti тршЬифЬрт-lihp, iutiÖtiiul|iuti тршЬифЬртЬЬр/СЬи. U iuliâliiul|iiili qnixn тршЬифЬрт-lihp/CLLi grnguli|i2Libp|i luiihtiiuiihö lupdtiplihpp qpmligi|b[ bli 2013 fa.' hiu-diuu|iuiniuufbiiutiiiipiup l|iuqdh|ni( 963,9 d[li UUL qn|iup, 8,7% U 7,1%: 2019 p. шртЬр1|р|пд iuliäliiul|iiili тршЬифЬрипЬЬрр l|iuqdb[ bli 682 d[li U.UL qn|iup, шЬ0Ьш1|ш1| ипршЬифЬрипЬЬр/СЫ! ЬшршрЬрш^дп^тЬр' 5,0%, |iul| шЬ0Ьш-1|шЬ qriLin тршЬифЬртЬЬр/СЬИ-Ь' 3,6%: ЧшЬ^иштЬиЬф t, пр, 2020 р. linpnliiuilhpnLuiujI'itj hiudiui|iiipiul|ni[ ii|iujdiuliiui|npi|iuô, diupql|iiilig luqiuin inhqiu2nipdfi uiuhdiutjiiiLl'iiulinLdlibpli iui|b|Ji l|l|p6iuinbli iuliÖtjiul|iutj inpiulju-фЬр1п1|Ьр|п tibphnupp' ршдшишршр iutjqpiuqiuntjiu|nil ludpnq^iuliiiili u|iu-Иш1|2шр1||1 ijpiii:

1996-2020|Э|Э. ^шйш1|ш1^шИшт1|ш0гий iupinhpl|p|ig iuliâtiiul|iiiti inpiutiu-фЬрт1|Ьр|1 ú^b briujiïujiuL|iuj|ili lupdhpp 1|шс^йЬ[ 1125,8051 ií|li LiUL qn|iup, шпшi|b[шqnljIiq1 316,4 ií|ti liLTb qn|iup (2013 p. 4-pq hrouiíujiul|), lii|iuqiii-qnijlip115,2 ú[li UUL qn|iup (1996 p. 1-|ili hiuuiiujiuli):

Sbinhuiu£iui|iiul|iiili iínqh|tihp|i l||ipiuriijiiiiíp líhp qliiuhiuinriLiítihpp i|l|iu-jrud bb, np « intiinbunLpjiiili i[pw iuliÖliiiil|iutj ьпршЬифЬрьпЬЬрЬ rubbli li2iu-liiul|iu|]i niqqbgnLpjruli: Я-рЬЬ^Ьр^ phuin|i hiudiuóiujlf iupinbpl|p|ig шЬ0Ьш-1|шЬ 1лршЬифЬртЬЬр|п U <Lli-|i d^gli шп1|ш t bpL|L)niqJLuti|n u|iuin6iiiniul|iii-tiпLfajпLti: lipinbpl|p|ig шЬ01ии1|шЬ 1прш1шфЬртЬЬр|1 шбр (iuliL|nLdp), ludpnq-2ш1|шЬ ii|iuhiuli2iupl||i i[piu tihpqnpôh|ni[, pmqJmpL)^|n tфЫ|lлnL[ Jb&mgtiriLJ t (ifinppiuglinLd t) CLU-b: Ujruu l|nqd|ig, дшбр (ршр0р) inliinhuiul|iuli шбр bpL|-pnllî huitiqhgtiruií t Ы|шйпил1|Ьр|1 1|рбштйш1|р (uii|h|iugiJiuliQ), mi|b[mlinLiJ t (liL[mqnLiJ t) ui2fuiuiniulipiuj|iti iJ|iqpuliLnlibp|i p|iLlD ^ luóiiliJ (l|póuiini|nlií) ш1|0Ьш1|ш1| трш1|ифЬр1л1|Ьр|1 libphnupp:

« inliiuj|"ili LnliLnbunLpjnLlilibp|i iJbô lîuuQ шр1лЬр1|р|1д uiniugi|nq uipmliu-фЬртЬЬрЬ oquimqnpöriLiJ t Qtipiug|il| uu|mQnqul|uli 0ш[ииЬр|1 4рш' 1т|ши-inh|ni( шйрп^ш1|ш1| и|шИш1|2шр1||1 ш6|п1|, Li i|hp2tiiul|iuti uii|iuniîiuli ijpiu qpiulig luqqbgnLpjrulip qpulinpi|nLd t h|iJliiuL|iulinLJ plipiug|iL| bniuJujujLjrnJ: LLpinbpL|p|ig uiniugi[nq iuliÖliiuL|iulj 1пршЬифЬртЬЬр|1 10% шбр i|t¡p2tJiul|iuli иа|ш^ш1| шб|л i[piu шqqnLJ t qpшL|шljnpblj, рЬршд|л1| ЬпшJujujlinnJ' 0,55 тп1|пиш]|пЬ L|binni[:

М.Ьр2Ьш1|ш1| иа|ш^шЬ Jnqb[rnJ, npiqbu ш1|1|ш[и фпфп[иш1|шЬ1|Ьр, q|i-тшр1|1[Ь[ bli ЬшЬ. CLLL-|i, шп1илрш]|п1| рш1|1|Ьр|л шl[шllqlJЬp|^ Ii lihpdnLÔdiutj ujqqbgnLfajruljtjbpQ: Ч-ЬшИшттйЬЬр^ ИшйшЙш^' р1|ршд|п1| hiuuiíujiul|nuj

CLli-fi 10% шбр 1|Ьр2Ьш1|ш1| uu|iumíiuti iuó|i i(puj qpiuL|iulinphti t luqqnLií 1,92 innL|nuujj|iti L|hinni{, |iul| iunlanpiuj|nli piutiL|hp|i iui|iuliqtihp|i 10% шбр qpiuL|iutinphti t luqqruií 1,32 mnL|numj|ili L|hinni|; LhpiiniMiuli 10% шбр 1|Ьр£-lnul|iuti uu|iuruíiuti iu6|i 1[рш qpiuL|iulinphti t LuqqnLií hiu^ripq Ьгиийщш^пиГ 0,89 innl|nuiuj|iti L|hinni|;

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14. http://www.minfin.am/hy/page/_hy_chartJ

АЛВАРД ХАРАТЯН

Доцент кафедры математического моделирования в экономике ЕГУ,

кандидат экономических наук

ВАРСИК ТИГРАНЯН

Ассистент кафедры макроэкономики АГЭУ,

кандидат экономических наук

ЗАРУИ АВЕТЯН

Кредитный специалист Армэкономбанка

Оценка макроэкономического влияния внешних личных трансфертов РА.- В статье анализируется поток личных трансфертов из-за границы в Армению. Макроэкономическое влияние внешних личных трансфертов оценивалось с помощью эконометрических моделей, построенных для экономики Армении. Было установлено, что поступающие из-за границы личные трансферты в краткосрочной перспективе оказывают значительное положительное влияние на ВВП и расходную составляющую ВВП, а также на ВВП на душу населения. 10-процентное увеличение личных трансфертов из-за границы в текущем квартале положительно влияет на рост конечного потребления на 0,55 процентных пункта, в следующем квартале положительно влияет на рост ВВП на 1,2 процентных пункта и на рост ВВП на душу населения на 0,78 процентных пункта, а через год положительно влияет на рост валовых инвестиций на 1,78 процентных пункта.

Полученные оценки могут быть использованы в качестве основы для разработки эффективной макроэкономической политики, направленной на регулирование шоков, вызванных потоками внешних личных трансфертов.

Ключевые слова личные трансферты, ВВП, совокупный спрос, корреляционная матрица, эконометрическая модель. \Е1: С50, Е01

42 PllTjPbP cnsc 2020.3

ALVARD KHARATYAN

Associate Professor at the Chair of Mathematical Modeling at YSU,

PhD in Economics

VARSIK TIGRANYAN

Assistant Professor at the Chair of Macroeconomics,

PhD in Economics

ZARUHI AVETYAN

Credit Specialist at Armeconombank

Assessment of Macroeconomic Impact of RA External Personal Remittances.-The flow of personal remittances from abroad to Armenia is analyzed in the paper. The macroeconomic impact of external personal remittances was assessed using econometric models built for the RA economy. Personal remittances from abroad were found to have a significant positive impact on GDP and GDP expenditure components, as well as per capita GDP in the short run. A 10 percent increase in personal remittances from abroad in the current quarter has a positive impact on the growth of final consumption by 0.55 percentage points, in the next quarter it has a positive impact on GDP growth by 1.2 percentage points and on per capita GDP growth by 0.78 percentage points, in the next year it has a positive impact on gross investment growth by 1.78 percentage points.

The assessments obtained can be a basis for developing an effective macroeconomic policy aimed at regulating shocks caused by external personal remittance flows.

words: personal remittances, GDP, aggregate demand, correlation matrix, econometric model. JEL: C50, E01

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